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Sample records for biomarker discovery studies

  1. Crowdsourcing Disease Biomarker Discovery Research: The IP4IC Study.

    Science.gov (United States)

    Chancellor, Michael B; Bartolone, Sarah N; Veerecke, Andrew; Lamb, Laura E

    2017-12-07

    Biomarker discovery is limited by readily assessable, cost efficient human samples available in large numbers that represent the entire heterogeneity of the disease. We developed a novel, active participation crowdsourcing method to determine BP-RS (Bladder Permeability Defect Risk Score). It is based on noninvasive urinary cytokines to discriminate patients with interstitial cystitis/bladder pain syndrome who had Hunner lesions from controls and patients with interstitial cystitis/bladder pain syndrome but without Hunner lesions. We performed a national crowdsourcing study in cooperation with ICA (Interstitial Cystitis Association). Patients answered demographic, symptom severity and urinary frequency questionnaires on a HIPAA (Health Insurance Portability and Accountability Act) compliant website. Urine samples were collected at home, stabilized with a preservative and sent to Beaumont Hospital for analysis. The expression of 3 urinary cytokines was used in a machine learning algorithm to develop BP-RS. The IP4IC study collected a total of 448 urine samples, representing 153 patients (147 females and 6 males) with interstitial cystitis/bladder pain syndrome, of whom 54 (50 females and 4 males) had Hunner lesions. A total of 159 female and 136 male controls also participated, who were age matched. A defined BP-RS was calculated to predict interstitial cystitis/bladder pain syndrome with Hunner lesions or a bladder permeability defect etiology with 89% validity. In this novel participation crowdsourcing study we obtained a large number of urine samples from 46 states, which were collected at home, shipped and stored at room temperature. Using a machine learning algorithm we developed BP-RS to quantify the risk of interstitial cystitis/bladder pain syndrome with Hunner lesions, which is indicative of a bladder permeability defect etiology. To our knowledge BP-RS is the first validated urine biomarker assay for interstitial cystitis/bladder pain syndrome and one of

  2. Exosomes in urine biomarker discovery.

    Science.gov (United States)

    Huebner, Alyssa R; Somparn, Poorichaya; Benjachat, Thitima; Leelahavanichkul, Asada; Avihingsanon, Yingyos; Fenton, Robert A; Pisitkun, Trairak

    2015-01-01

    Nanovesicles present in urine the so-called urinary exosomes have been found to be secreted by every epithelial cell type lining the urinary tract system in human. Urinary exosomes are an appealing source for biomarker discovery as they contain molecular constituents of their cell of origin, including proteins and genetic materials, and they can be isolated in a non-invasive manner. Following the discovery of urinary exosomes in 2004, many studies have been performed using urinary exosomes as a starting material to identify biomarkers in various renal, urogenital, and systemic diseases. Here, we describe the discovery of urinary exosomes and address the issues on the collection, isolation, and normalization of urinary exosomes as well as delineate the systems biology approach to biomarker discovery using urinary exosomes.

  3. Statistical design for biospecimen cohort size in proteomics-based biomarker discovery and verification studies.

    Science.gov (United States)

    Skates, Steven J; Gillette, Michael A; LaBaer, Joshua; Carr, Steven A; Anderson, Leigh; Liebler, Daniel C; Ransohoff, David; Rifai, Nader; Kondratovich, Marina; Težak, Živana; Mansfield, Elizabeth; Oberg, Ann L; Wright, Ian; Barnes, Grady; Gail, Mitchell; Mesri, Mehdi; Kinsinger, Christopher R; Rodriguez, Henry; Boja, Emily S

    2013-12-06

    Protein biomarkers are needed to deepen our understanding of cancer biology and to improve our ability to diagnose, monitor, and treat cancers. Important analytical and clinical hurdles must be overcome to allow the most promising protein biomarker candidates to advance into clinical validation studies. Although contemporary proteomics technologies support the measurement of large numbers of proteins in individual clinical specimens, sample throughput remains comparatively low. This problem is amplified in typical clinical proteomics research studies, which routinely suffer from a lack of proper experimental design, resulting in analysis of too few biospecimens to achieve adequate statistical power at each stage of a biomarker pipeline. To address this critical shortcoming, a joint workshop was held by the National Cancer Institute (NCI), National Heart, Lung, and Blood Institute (NHLBI), and American Association for Clinical Chemistry (AACC) with participation from the U.S. Food and Drug Administration (FDA). An important output from the workshop was a statistical framework for the design of biomarker discovery and verification studies. Herein, we describe the use of quantitative clinical judgments to set statistical criteria for clinical relevance and the development of an approach to calculate biospecimen sample size for proteomic studies in discovery and verification stages prior to clinical validation stage. This represents a first step toward building a consensus on quantitative criteria for statistical design of proteomics biomarker discovery and verification research.

  4. Glycoscience aids in biomarker discovery

    Directory of Open Access Journals (Sweden)

    Serenus Hua1,2 & Hyun Joo An1,2,*

    2012-06-01

    Full Text Available The glycome consists of all glycans (or carbohydrates within abiological system, and modulates a wide range of important biologicalactivities, from protein folding to cellular communications.The mining of the glycome for disease markers representsa new paradigm for biomarker discovery; however, this effortis severely complicated by the vast complexity and structuraldiversity of glycans. This review summarizes recent developmentsin analytical technology and methodology as applied tothe fields of glycomics and glycoproteomics. Mass spectrometricstrategies for glycan compositional profiling are described, as arepotential refinements which allow structure-specific profiling.Analytical methods that can discern protein glycosylation at aspecific site of modification are also discussed in detail.Biomarker discovery applications are shown at each level ofanalysis, highlighting the key role that glycoscience can play inhelping scientists understand disease biology.

  5. Association of SNCA with Parkinson: replication in the Harvard NeuroDiscovery Center Biomarker Study

    Science.gov (United States)

    Ding, Hongliu; Sarokhan, Alison K.; Roderick, Sarah S.; Bakshi, Rachit; Maher, Nancy E.; Ashourian, Paymon; Kan, Caroline G.; Chang, Sunny; Santarlasci, Andrea; Swords, Kyleen E.; Ravina, Bernard M.; Hayes, Michael T.; Sohur, U. Shivraj; Wills, Anne-Marie; Flaherty, Alice W.; Unni, Vivek K.; Hung, Albert Y.; Selkoe, Dennis J.; Schwarzschild, Michael A.; Schlossmacher, Michael G.; Sudarsky, Lewis R.; Growdon, John H.; Ivinson, Adrian J.; Hyman, Bradley T.; Scherzer, Clemens R.

    2011-01-01

    Background Mutations in the α-synuclein gene (SNCA) cause autosomal dominant forms of Parkinson’s disease, but the substantial risk conferred by this locus to the common sporadic disease has only recently emerged from genome-wide association studies. Methods Here we genotyped a prioritized non-coding variant in SNCA intron-4 in 344 patients with Parkinson’s and 275 controls from the longitudinal Harvard NeuroDiscovery Center Biomarker Study. Results The common minor allele of rs2736990 was associated with elevated disease susceptibility (odds ratio = 1.40, P value = 0.0032). Conclusions This result increases confidence in the notion that in many clinically well-characterized patients genetic variation in SNCA contributes to “sporadic” disease. PMID:21953863

  6. Urinary Proteomics Pilot Study for Biomarker Discovery and Diagnosis in Heart Failure with Reduced Ejection Fraction

    DEFF Research Database (Denmark)

    Rossing, Kasper; Bosselmann, Helle Skovmand; Gustafsson, Finn

    2016-01-01

    and Results Urine samples were analyzed by on-line capillary electrophoresis coupled to electrospray ionization micro time-of-flight mass spectrometry (CE-MS) to generate individual urinary proteome profiles. In an initial biomarker discovery cohort, analysis of urinary proteome profiles from 33 HFr......Background Biomarker discovery and new insights into the pathophysiology of heart failure with reduced ejection fraction (HFrEF) may emerge from recent advances in high-throughput urinary proteomics. This could lead to improved diagnosis, risk stratification and management of HFrEF. Methods.......6%) in individuals with diastolic left ventricular dysfunction (N = 176). The HFrEF-related peptide biomarkers mainly included fragments of fibrillar type I and III collagen but also, e.g., of fibrinogen beta and alpha-1-antitrypsin. Conclusion CE-MS based urine proteome analysis served as a sensitive tool...

  7. Topic model-based mass spectrometric data analysis in cancer biomarker discovery studies.

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    Wang, Minkun; Tsai, Tsung-Heng; Di Poto, Cristina; Ferrarini, Alessia; Yu, Guoqiang; Ressom, Habtom W

    2016-08-18

    A fundamental challenge in quantitation of biomolecules for cancer biomarker discovery is owing to the heterogeneous nature of human biospecimens. Although this issue has been a subject of discussion in cancer genomic studies, it has not yet been rigorously investigated in mass spectrometry based proteomic and metabolomic studies. Purification of mass spectometric data is highly desired prior to subsequent analysis, e.g., quantitative comparison of the abundance of biomolecules in biological samples. We investigated topic models to computationally analyze mass spectrometric data considering both integrated peak intensities and scan-level features, i.e., extracted ion chromatograms (EICs). Probabilistic generative models enable flexible representation in data structure and infer sample-specific pure resources. Scan-level modeling helps alleviate information loss during data preprocessing. We evaluated the capability of the proposed models in capturing mixture proportions of contaminants and cancer profiles on LC-MS based serum proteomic and GC-MS based tissue metabolomic datasets acquired from patients with hepatocellular carcinoma (HCC) and liver cirrhosis as well as synthetic data we generated based on the serum proteomic data. The results we obtained by analysis of the synthetic data demonstrated that both intensity-level and scan-level purification models can accurately infer the mixture proportions and the underlying true cancerous sources with small average error ratios (data, we found more proteins and metabolites with significant changes between HCC cases and cirrhotic controls. Candidate biomarkers selected after purification yielded biologically meaningful pathway analysis results and improved disease discrimination power in terms of the area under ROC curve compared to the results found prior to purification. We investigated topic model-based inference methods to computationally address the heterogeneity issue in samples analyzed by LC/GC-MS. We observed

  8. Systems biology and biomarker discovery

    Energy Technology Data Exchange (ETDEWEB)

    Rodland, Karin D.

    2010-12-01

    Medical practitioners have always relied on surrogate markers of inaccessible biological processes to make their diagnosis, whether it was the pallor of shock, the flush of inflammation, or the jaundice of liver failure. Obviously, the current implementation of biomarkers for disease is far more sophisticated, relying on highly reproducible, quantitative measurements of molecules that are often mechanistically associated with the disease in question, as in glycated hemoglobin for the diagnosis of diabetes [1] or the presence of cardiac troponins in the blood for confirmation of myocardial infarcts [2]. In cancer, where the initial symptoms are often subtle and the consequences of delayed diagnosis often drastic for disease management, the impetus to discover readily accessible, reliable, and accurate biomarkers for early detection is compelling. Yet despite years of intense activity, the stable of clinically validated, cost-effective biomarkers for early detection of cancer is pathetically small and still dominated by a handful of markers (CA-125, CEA, PSA) first discovered decades ago. It is time, one could argue, for a fresh approach to the discovery and validation of disease biomarkers, one that takes full advantage of the revolution in genomic technologies and in the development of computational tools for the analysis of large complex datasets. This issue of Disease Markers is dedicated to one such new approach, loosely termed the 'Systems Biology of Biomarkers'. What sets the Systems Biology approach apart from other, more traditional approaches, is both the types of data used, and the tools used for data analysis - and both reflect the revolution in high throughput analytical methods and high throughput computing that has characterized the start of the twenty first century.

  9. Urinary Proteomics Pilot Study for Biomarker Discovery and Diagnosis in Heart Failure with Reduced Ejection Fraction.

    Directory of Open Access Journals (Sweden)

    Kasper Rossing

    Full Text Available Biomarker discovery and new insights into the pathophysiology of heart failure with reduced ejection fraction (HFrEF may emerge from recent advances in high-throughput urinary proteomics. This could lead to improved diagnosis, risk stratification and management of HFrEF.Urine samples were analyzed by on-line capillary electrophoresis coupled to electrospray ionization micro time-of-flight mass spectrometry (CE-MS to generate individual urinary proteome profiles. In an initial biomarker discovery cohort, analysis of urinary proteome profiles from 33 HFrEF patients and 29 age- and sex-matched individuals without HFrEF resulted in identification of 103 peptides that were significantly differentially excreted in HFrEF. These 103 peptides were used to establish the support vector machine-based HFrEF classifier HFrEF103. In a subsequent validation cohort, HFrEF103 very accurately (area under the curve, AUC = 0.972 discriminated between HFrEF patients (N = 94, sensitivity = 93.6% and control individuals with and without impaired renal function and hypertension (N = 552, specificity = 92.9%. Interestingly, HFrEF103 showed low sensitivity (12.6% in individuals with diastolic left ventricular dysfunction (N = 176. The HFrEF-related peptide biomarkers mainly included fragments of fibrillar type I and III collagen but also, e.g., of fibrinogen beta and alpha-1-antitrypsin.CE-MS based urine proteome analysis served as a sensitive tool to determine a vast array of HFrEF-related urinary peptide biomarkers which might help improving our understanding and diagnosis of heart failure.

  10. Biomarkers: in medicine, drug discovery, and environmental health

    National Research Council Canada - National Science Library

    Vaidya, Vishal S; Bonventre, Joseph V

    2010-01-01

    ... Identification Using Mass Spectrometry Sample Preparation Protein Quantitation Examples of Biomarker Discovery and Evaluation Challenges in Proteomic Biomarker Discovery The Road Forward: Targeted ...

  11. The Process Chain for Peptidomic Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Michael Schrader

    2006-01-01

    Full Text Available Over the last few years the interest in diagnostic markers for specific diseases has increased continuously. It is expected that they not only improve a patient's medical treatment but also contribute to accelerating the process of drug development. This demand for new biomarkers is caused by a lack of specific and sensitive diagnosis in many diseases. Moreover, diseases usually occur in different types or stages which may need different diagnostic and therapeutic measures. Their differentiation has to be considered in clinical studies as well. Therefore, it is important to translate a macroscopic pathological or physiological finding into a microscopic view of molecular processes and vice versa, though it is a difficult and tedious task. Peptides play a central role in many physiological processes and are of importance in several areas of drug research. Exploration of endogenous peptides in biologically relevant sources may directly lead to new drug substances, serve as key information on a new target and can as well result in relevant biomarker candidates. A comprehensive analysis of peptides and small proteins of a biological system corresponding to the respective genomic information (peptidomics®methods was a missing link in proteomics. A new peptidomic technology platform addressing peptides was recently presented, developed by adaptation of the striving proteomic technologies. Here, concepts of using peptidomics technologies for biomarker discovery are presented and illustrated with examples. It is discussed how the biological hypothesis and sample quality determine the result of the study. A detailed study design, appropriate choice and application of technology as well as thorough data interpretation can lead to significant results which have to be interpreted in the context of the underlying disease. The identified biomarker candidates will be characterised in validation studies before use. This approach for discovery of peptide

  12. Shotgun Proteomics and Biomarker Discovery

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    W. Hayes McDonald

    2002-01-01

    Full Text Available Coupling large-scale sequencing projects with the amino acid sequence information that can be gleaned from tandem mass spectrometry (MS/MS has made it much easier to analyze complex mixtures of proteins. The limits of this “shotgun” approach, in which the protein mixture is proteolytically digested before separation, can be further expanded by separating the resulting mixture of peptides prior to MS/MS analysis. Both single dimensional high pressure liquid chromatography (LC and multidimensional LC (LC/LC can be directly interfaced with the mass spectrometer to allow for automated collection of tremendous quantities of data. While there is no single technique that addresses all proteomic challenges, the shotgun approaches, especially LC/LC-MS/MS-based techniques such as MudPIT (multidimensional protein identification technology, show advantages over gel-based techniques in speed, sensitivity, scope of analysis, and dynamic range. Advances in the ability to quantitate differences between samples and to detect for an array of post-translational modifications allow for the discovery of classes of protein biomarkers that were previously unassailable.

  13. Discovery of novel biomarker candidates for liver fibrosis in hepatitis C patients: a preliminary study.

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    Bevin Gangadharan

    Full Text Available Liver biopsy is the reference standard for assessing liver fibrosis and no reliable non-invasive diagnostic approach is available to discriminate between the intermediate stages of fibrosis. Therefore suitable serological biomarkers of liver fibrosis are urgently needed. We used proteomics to identify novel fibrosis biomarkers in hepatitis C patients with different degrees of liver fibrosis.Proteins in plasma samples from healthy control individuals and patients with hepatitis C virus (HCV induced cirrhosis were analysed using a proteomics technique: two dimensional gel electrophoresis (2-DE. This technique separated the proteins in plasma samples of control and cirrhotic patients and by visualizing the separated proteins we were able to identify proteins which were increasing or decreasing in hepatic cirrhosis. Identified markers were validated across all Ishak fibrosis stages and compared to the markers used in FibroTest, Enhanced Liver Fibrosis (ELF test, Hepascore and FIBROSpect by Western blotting. Forty four candidate biomarkers for hepatic fibrosis were identified of which 20 were novel biomarkers of liver fibrosis. Western blot validation of all candidate markers using plasma samples from patients across all Ishak fibrosis scores showed that the markers which changed with increasing fibrosis most consistently included lipid transfer inhibitor protein, complement C3d, corticosteroid-binding globulin, apolipoprotein J and apolipoprotein L1. These five novel fibrosis markers which are secreted in blood showed a promising consistent change with increasing fibrosis stage when compared to the markers used for the FibroTest, ELF test, Hepascore and FIBROSpect. These markers will be further validated using a large clinical cohort.This study identifies 20 novel fibrosis biomarker candidates. The proteins identified may help to assess hepatic fibrosis and eliminate the need for invasive liver biopsies.

  14. Discovery of Metabolic Biomarkers for Duchenne Muscular Dystrophy within a Natural History Study.

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    Simina M Boca

    Full Text Available Serum metabolite profiling in Duchenne muscular dystrophy (DMD may enable discovery of valuable molecular markers for disease progression and treatment response. Serum samples from 51 DMD patients from a natural history study and 22 age-matched healthy volunteers were profiled using liquid chromatography coupled to mass spectrometry (LC-MS for discovery of novel circulating serum metabolites associated with DMD. Fourteen metabolites were found significantly altered (1% false discovery rate in their levels between DMD patients and healthy controls while adjusting for age and study site and allowing for an interaction between disease status and age. Increased metabolites included arginine, creatine and unknown compounds at m/z of 357 and 312 while decreased metabolites included creatinine, androgen derivatives and other unknown yet to be identified compounds. Furthermore, the creatine to creatinine ratio is significantly associated with disease progression in DMD patients. This ratio sharply increased with age in DMD patients while it decreased with age in healthy controls. Overall, this study yielded promising metabolic signatures that could prove useful to monitor DMD disease progression and response to therapies in the future.

  15. Metabolic phenotyping for discovery of urinary biomarkers of diet, xenobiotics and blood pressure in the INTERMAP Study: an overview.

    Science.gov (United States)

    Chan, Queenie; Loo, Ruey Leng; Ebbels, Timothy M D; Van Horn, Linda; Daviglus, Martha L; Stamler, Jeremiah; Nicholson, Jeremy K; Holmes, Elaine; Elliott, Paul

    2017-04-01

    The etiopathogenesis of cardiovascular diseases (CVDs) is multifactorial. Adverse blood pressure (BP) is a major independent risk factor for epidemic CVD affecting ~40% of the adult population worldwide and resulting in significant morbidity and mortality. Metabolic phenotyping of biological fluids has proven its application in characterizing low-molecular-weight metabolites providing novel insights into gene-environmental-gut microbiome interaction in relation to a disease state. In this review, we synthesize key results from the INTERnational study of MAcro/micronutrients and blood Pressure (INTERMAP) Study, a cross-sectional epidemiologic study of 4680 men and women aged 40-59 years from Japan, the People's Republic of China, the United Kingdom and the United States. We describe the advancements we have made regarding the following: (1) analytical techniques for high-throughput metabolic phenotyping; (2) statistical analyses for biomarker identification; (3) discovery of unique food-specific biomarkers; and (4) application of metabolome-wide association studies to gain a better understanding into the molecular mechanisms of cross-cultural and regional BP differences.

  16. Mass Spectrometry-Based Biomarker Discovery.

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    Zhou, Weidong; Petricoin, Emanuel F; Longo, Caterina

    2017-01-01

    The discovery of candidate biomarkers within the entire proteome is one of the most important and challenging goals in proteomic research. Mass spectrometry-based proteomics is a modern and promising technology for semiquantitative and qualitative assessment of proteins, enabling protein sequencing and identification with exquisite accuracy and sensitivity. For mass spectrometry analysis, protein extractions from tissues or body fluids and subsequent protein fractionation represent an important and unavoidable step in the workflow for biomarker discovery. Following extraction of proteins, the protein mixture must be digested, reduced, alkylated, and cleaned up prior to mass spectrometry. The aim of our chapter is to provide comprehensible and practical lab procedures for sample digestion, protein fractionation, and subsequent mass spectrometry analysis.

  17. Using Aptamers for Cancer Biomarker Discovery

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    Yun Min Chang

    2013-01-01

    Full Text Available Aptamers are single-stranded synthetic DNA- or RNA-based oligonucleotides that fold into various shapes to bind to a specific target, which includes proteins, metals, and molecules. Aptamers have high affinity and high specificity that are comparable to that of antibodies. They are obtained using iterative method, called (Systematic Evolution of Ligands by Exponential Enrichment SELEX and cell-based SELEX (cell-SELEX. Aptamers can be paired with recent advances in nanotechnology, microarray, microfluidics, and other technologies for applications in clinical medicine. One particular area that aptamers can shed a light on is biomarker discovery. Biomarkers are important in diagnosis and treatment of cancer. In this paper, we will describe ways in which aptamers can be used to discover biomarkers for cancer diagnosis and therapeutics.

  18. Computational Analyses for Transplant Biomarker Discovery

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    Anyou eWang

    2015-09-01

    Full Text Available Translational medicine offers a rich promise for improved diagnostics and drug discovery for biomedical research in the field of transplantation, where continued unmet diagnostic and therapeutic needs persist. Current advent of genomics and proteomics profiling called omics provides new resources to develop novel biomarkers for clinical routine. Establishing such a marker system heavily depends on appropriate applications of computational algorithms and software, which are basically based on mathematical theories and models. Understanding these theories would help to apply appropriate algorithms to ensure biomarker systems successful. Here, we review the key advances in theories and mathematical models relevant to transplant biomarker developments. Advantages and limitations inherent inside these models are discussed. The principles of key computational approaches for selecting efficiently the best subset of biomarkers from high dimensional omics data are highlighted. Prediction models are also introduced and the integration of multi-microarray data is also discussed. Appreciating these key advances would help to accelerate the development of clinically reliable biomarker systems.

  19. 2D-DIGE as a proteomic biomarker discovery tool in environmental studies with Procambarus clarkii.

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    Fernández-Cisnal, Ricardo; García-Sevillano, Miguel A; Gómez-Ariza, José L; Pueyo, Carmen; López-Barea, Juan; Abril, Nieves

    2017-04-15

    A 2D-DIGE/MS approach was used to assess protein abundance differences in the red swamp crayfish Procambarus clarkii from polluted aquatic ecosystems of Doñana National Park and surrounding areas with different pollution loads. Procambarus clarkii accumulated metals in the digestive glands and gills reflecting sediment concentrations. We first stated that, probably related to elements accumulation, pollution increased oxidative damage in P. clarkii tissues, as shown by the thiol oxidation status of proteins and MDA levels. In these animals, the altered redox status might be responsible for the deregulated abundance of proteins involved in cellular responses to oxidative stress including protein folding, mitochondrial imbalance and inflammatory processes. Interestingly, polluted P. clarkii crayfish also displayed a metabolic shift to enhanced aerobic glycolysis, most likely aimed at generating ATP and reduction equivalents in an oxidative stress situation that alters mitochondrial integrity. The deregulated proteins define the physiological processes affected by pollutants in DNP and its surrounding areas and may help us to unravel the molecular mechanisms underlying the toxicity of environmental pollutants. In addition, these proteins might be used as exposure biomarkers in environmental risk assessment. The results obtained might be extrapolated to many other locations all over the world and have the added value of providing information about the molecular responses of this environmentally and economically interesting animal. Metal content in digestive gland and gills of P. clarkii crayfish reflects their contents in sediments at sites of Doñana National Park and its surroundings. Accumulation of essential and toxic transition metals is paralleled by clear signs of oxidative stress to lipids and proteins and by significant deregulation of many proteins involved in protein folding, mitochondrial respiratory imbalance and inflammatory response. These results

  20. Top-down proteomics with mass spectrometry imaging: a pilot study towards discovery of biomarkers for neurodevelopmental disorders.

    Directory of Open Access Journals (Sweden)

    Hui Ye

    Full Text Available In the developing mammalian brain, inhibition of NMDA receptor can induce widespread neuroapoptosis, inhibit neurogenesis and cause impairment of learning and memory. Although some mechanistic insights into adverse neurological actions of these NMDA receptor antagonists exist, our understanding of the full spectrum of developmental events affected by early exposure to these chemical agents in the brain is still limited. Here we attempt to gain insights into the impact of pharmacologically induced excitatory/inhibitory imbalance in infancy on the brain proteome using mass spectrometric imaging (MSI. Our goal was to study changes in protein expression in postnatal day 10 (P10 rat brains following neonatal exposure to the NMDA receptor antagonist dizocilpine (MK801. Analysis of rat brains exposed to vehicle or MK801 and comparison of their MALDI MS images revealed differential relative abundances of several proteins. We then identified these markers such as ubiquitin, purkinje cell protein 4 (PEP-19, cytochrome c oxidase subunits and calmodulin, by a combination of reversed-phase (RP HPLC fractionation and top-down tandem MS platform. More in-depth large scale study along with validation experiments will be carried out in the future. Overall, our findings indicate that a brief neonatal exposure to a compound that alters excitatory/inhibitory balance in the brain has a long term effect on protein expression patterns during subsequent development, highlighting the utility of MALDI-MSI as a discovery tool for potential biomarkers.

  1. Biomarker Discovery and Mechanistic Studies of Prostate Cancer using Targeted Proteomic Approaches

    Science.gov (United States)

    2012-07-01

    density: a means of distinguishing benign prostatic hypertrophy and prostate cancer. J Urol 147: 815-816, 1992. 11. Catalona WJ, Richie JP, deKernion...Mechanistic Studies of Prostate Cancer using Targeted Proteomic Approaches PRINCIPAL INVESTIGATOR: Haining Zhu, Ph.D...Mechanistic Studies of Prostate Cancer using Targeted Proteomic Approaches 5b. GRANT NUMBER W81XWH-08-1-0430 5c. PROGRAM ELEMENT NUMBER 6

  2. Biomarker discovery in mass spectrometry-based urinary proteomics.

    Science.gov (United States)

    Thomas, Samuel; Hao, Ling; Ricke, William A; Li, Lingjun

    2016-04-01

    Urinary proteomics has become one of the most attractive topics in disease biomarker discovery. MS-based proteomic analysis has advanced continuously and emerged as a prominent tool in the field of clinical bioanalysis. However, only few protein biomarkers have made their way to validation and clinical practice. Biomarker discovery is challenged by many clinical and analytical factors including, but not limited to, the complexity of urine and the wide dynamic range of endogenous proteins in the sample. This article highlights promising technologies and strategies in the MS-based biomarker discovery process, including study design, sample preparation, protein quantification, instrumental platforms, and bioinformatics. Different proteomics approaches are discussed, and progresses in maximizing urinary proteome coverage and standardization are emphasized in this review. MS-based urinary proteomics has great potential in the development of noninvasive diagnostic assays in the future, which will require collaborative efforts between analytical scientists, systems biologists, and clinicians. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. Cancer Biomarker Discovery: Lectin-Based Strategies Targeting Glycoproteins

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    David Clark

    2012-01-01

    Full Text Available Biomarker discovery can identify molecular markers in various cancers that can be used for detection, screening, diagnosis, and monitoring of disease progression. Lectin-affinity is a technique that can be used for the enrichment of glycoproteins from a complex sample, facilitating the discovery of novel cancer biomarkers associated with a disease state.

  4. Biomarker Gene Signature Discovery Integrating Network Knowledge

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    Holger Fröhlich

    2012-02-01

    Full Text Available Discovery of prognostic and diagnostic biomarker gene signatures for diseases, such as cancer, is seen as a major step towards a better personalized medicine. During the last decade various methods, mainly coming from the machine learning or statistical domain, have been proposed for that purpose. However, one important obstacle for making gene signatures a standard tool in clinical diagnosis is the typical low reproducibility of these signatures combined with the difficulty to achieve a clear biological interpretation. For that purpose in the last years there has been a growing interest in approaches that try to integrate information from molecular interaction networks. Here we review the current state of research in this field by giving an overview about so-far proposed approaches.

  5. Mass Spectrometry–Based Biomarker Discovery: Toward a Global Proteome Index of Individuality

    Science.gov (United States)

    Hawkridge, Adam M.; Muddiman, David C.

    2011-01-01

    Biomarker discovery and proteomics have become synonymous with mass spectrometry in recent years. Although this conflation is an injustice to the many essential biomolecular techniques widely used in biomarker-discovery platforms, it underscores the power and potential of contemporary mass spectrometry. Numerous novel and powerful technologies have been developed around mass spectrometry, proteomics, and biomarker discovery over the past 20 years to globally study complex proteomes (e.g., plasma). However, very few large-scale longitudinal studies have been carried out using these platforms to establish the analytical variability relative to true biological variability. The purpose of this review is not to cover exhaustively the applications of mass spectrometry to biomarker discovery, but rather to discuss the analytical methods and strategies that have been developed for mass spectrometry–based biomarker-discovery platforms and to place them in the context of the many challenges and opportunities yet to be addressed. PMID:20636062

  6. The application of mass-spectrometry-based protein biomarker discovery to theragnostics

    OpenAIRE

    Street, Jonathan M; Dear, James W

    2010-01-01

    Over the last decade rapid developments in mass spectrometry have allowed the identification of multiple proteins in complex biological samples. This proteomic approach has been applied to biomarker discovery in the context of clinical pharmacology (the combination of biomarker and drug now being termed ‘theragnostics’). In this review we provide a roadmap for early protein biomarker discovery studies, focusing on some key questions that regularly confront researchers.

  7. Sparse Mbplsr for Metabolomics Data and Biomarker Discovery

    DEFF Research Database (Denmark)

    Karaman, İbrahim

    2014-01-01

    Metabolomics is part of systems biology and a rapidly evolving field. It is a tool to analyze multiple metabolic changes in biofluids and tissues and aims at determining biomarkers in the metabolism. LC-MS (liquid chromatography – mass spectrometry), GC-MS (gas chromatography – mass spectrometry...... the link between high throughput metabolomics data generated on different analytical platforms, discover important metabolites deriving from the digestion processes in the gut, and automate metabolic pathway discovery from mass spectrometry. PLS (partial least squares) based chemometric methods were......, potential biomarkers from LC-MS and NMR data could be detected and the relationships among the measurement variables of both analytical methods could be studied. Detection of potential biomarkers is followed up by an identification process through online metabolite and pathway databases. This process...

  8. Emerging Concepts and Methodologies in Cancer Biomarker Discovery.

    Science.gov (United States)

    Lu, Meixia; Zhang, Jinxiang; Zhang, Lanjing

    2017-01-01

    Cancer biomarker discovery is a critical part of cancer prevention and treatment. Despite the decades of effort, only a small number of cancer biomarkers have been identified for and validated in clinical settings. Conceptual and methodological breakthroughs may help accelerate the discovery of additional cancer biomarkers, particularly their use for diagnostics. In this review, we have attempted to review the emerging concepts in cancer biomarker discovery, including real-world evidence, open access data, and data paucity in rare or uncommon cancers. We have also summarized the recent methodological progress in cancer biomarker discovery, such as high-throughput sequencing, liquid biopsy, big data, artificial intelligence (AI), and deep learning and neural networks. Much attention has been given to the methodological details and comparison of the methodologies. Notably, these concepts and methodologies interact with each other and will likely lead to synergistic effects when carefully combined. Newer, more innovative concepts and methodologies are emerging as the current emerging ones became mainstream and widely applied to the field. Some future challenges are also discussed. This review contributes to the development of future theoretical frameworks and technologies in cancer biomarker discovery and will contribute to the discovery of more useful cancer biomarkers.

  9. Proteomics for discovery of candidate colorectal cancer biomarkers

    Science.gov (United States)

    Álvarez-Chaver, Paula; Otero-Estévez, Olalla; Páez de la Cadena, María; Rodríguez-Berrocal, Francisco J; Martínez-Zorzano, Vicenta S

    2014-01-01

    Colorectal cancer (CRC) is the second most common cause of cancer-related deaths in Europe and other Western countries, mainly due to the lack of well-validated clinically useful biomarkers with enough sensitivity and specificity to detect this disease at early stages. Although it is well known that the pathogenesis of CRC is a progressive accumulation of mutations in multiple genes, much less is known at the proteome level. Therefore, in the last years many proteomic studies have been conducted to find new candidate protein biomarkers for diagnosis, prognosis and as therapeutic targets for this malignancy, as well as to elucidate the molecular mechanisms of colorectal carcinogenesis. An important advantage of the proteomic approaches is the capacity to look for multiple differentially expressed proteins in a single study. This review provides an overview of the recent reports describing the different proteomic tools used for the discovery of new protein markers for CRC such as two-dimensional electrophoresis methods, quantitative mass spectrometry-based techniques or protein microarrays. Additionally, we will also focus on the diverse biological samples used for CRC biomarker discovery such as tissue, serum and faeces, besides cell lines and murine models, discussing their advantages and disadvantages, and summarize the most frequently identified candidate CRC markers. PMID:24744574

  10. Biomarker discovery in high grade sarcomas by mass spectrometry imaging

    OpenAIRE

    Lou, S.

    2017-01-01

    This thesis demonstrates a detailed biomarker discovery Mass Spectrometry Imaging workflow for histologically heterogeneous high grade sarcomas. Panels of protein and metabolite signatures were discovered either distinguishing different histological subtypes or stratifying high risk patients with poor survival.

  11. Approach to Cerebrospinal Fluid (CSF) Biomarker Discovery and Evaluation in HIV Infection

    Energy Technology Data Exchange (ETDEWEB)

    Price, Richard W.; Peterson, Julia; Fuchs, Dietmar; Angel, Thomas E.; Zetterberg, Henrik; Hagberg, Lars; Spudich, Serena S.; Smith, Richard D.; Jacobs, Jon M.; Brown, Joseph N.; Gisslen, Magnus

    2013-12-13

    Central nervous system (CNS) infection is a nearly universal facet of systemic HIV infection that varies in character and neurological consequences. While clinical staging and neuropsychological test performance have been helpful in evaluating patients, cerebrospinal fluid (CSF) biomarkers present a valuable and objective approach to more accurate diagnosis, assessment of treatment effects and understanding of evolving pathobiology. We review some lessons from our recent experience with CSF biomarker studies. We have used two approaches to biomarker analysis: targeted, hypothesis-driven and non-targeted exploratory discovery methods. We illustrate the first with data from a cross-sectional study of defined subject groups across the spectrum of systemic and CNS disease progression and the second with a longitudinal study of the CSF proteome in subjects initiating antiretroviral treatment. Both approaches can be useful and, indeed, complementary. The first is helpful in assessing known or hypothesized biomarkers while the second can identify novel biomarkers and point to broad interactions in pathogenesis. Common to both is the need for well-defined samples and subjects that span a spectrum of biological activity and biomarker concentrations. Previouslydefined guide biomarkers of CNS infection, inflammation and neural injury are useful in categorizing samples for analysis and providing critical biological context for biomarker discovery studies. CSF biomarkers represent an underutilized but valuable approach to understanding the interactions of HIV and the CNS and to more objective diagnosis and assessment of disease activity. Both hypothesis-based and discovery methods can be useful in advancing the definition and use of these biomarkers.

  12. Metabolomic study of lipids in serum for biomarker discovery in Alzheimer's disease using direct infusion mass spectrometry.

    Science.gov (United States)

    González-Domínguez, R; García-Barrera, T; Gómez-Ariza, J L

    2014-09-01

    In this study, we demonstrated the potential of direct infusion mass spectrometry for the lipidomic characterization of Alzheimer's disease. Serum samples were extracted for lipids recovery, and directly analyzed using an electrospray source. Metabolomic fingerprints were subjected to multivariate analysis in order to discriminate between groups of patients and healthy controls, and then some key-compounds were identified as possible markers of Alzheimer's disease. Major differences were found in lipids, although some low molecular weight metabolites also showed significant changes. Thus, important metabolic pathways involved in neurodegeneration could be studied on the basis of these perturbations, such as membrane breakdown (phospholipids and diacylglycerols), oxidative stress (prostaglandins, imidazole and histidine), alterations in neurotransmission systems (oleamide and putrescine) and hyperammonaemia (guanidine and arginine). Moreover, it is noteworthy that some of these potential biomarkers have not been previously described for Alzheimer's disease. Copyright © 2014 Elsevier B.V. All rights reserved.

  13. The Use of Proteomics in Biomarker Discovery in Neurodegenerative Diseases

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    Pia Davidsson

    2005-01-01

    Full Text Available Biomarkers for neurodegenerative diseases should reflect the central pathogenic processes of the diseases. The field of clinical proteomics is especially well suited for discovery of biomarkers in cerebrospinal fluid (CSF, which reflects the proteins in the brain under healthy conditions as well as in several neurodegenerative diseases. Known proteins involved in the pathology of neurodegenerative diseases are, respectively, normal tau protein, β-amyloid (1-42, synaptic proteins, amyloid precursor protein (APP, apolipoprotein E (apoE, which previously have been studied by protein immunoassays. The objective of this paper was to summarize results from proteomic studies of differential protein patterns in neurodegenerative diseases with focus on Alzheimer's disease (AD. Today, discrimination of AD from controls and from other neurological diseases has been improved by simultaneous analysis of both β-amyloid (1-42, total-tau, and phosphorylated tau, where a combination of low levels of CSF-β-amyloid 1-42 and high levels of CSF-tau and CSF-phospho-tau is associated with an AD diagnosis. Detection of new biomarkers will further strengthen diagnosis and provide useful information in drug trials. The combination of immunoassays and proteomic methods show that the CSF proteins express differential protein patterns in AD, FTD, and PD patients, which reflect divergent underlying pathophysiological mechanisms and neuropathological changes in these diseases.

  14. Mass spectrometry for protein quantification in biomarker discovery.

    Science.gov (United States)

    Wang, Mu; You, Jinsam

    2012-01-01

    Major technological advances have made proteomics an extremely active field for biomarker discovery in recent years due primarily to the development of newer mass spectrometric technologies and the explosion in genomic and protein bioinformatics. This leads to an increased emphasis on larger scale, faster, and more efficient methods for detecting protein biomarkers in human tissues, cells, and biofluids. Most current proteomic methodologies for biomarker discovery, however, are not highly automated and are generally labor-intensive and expensive. More automation and improved software programs capable of handling a large amount of data are essential to reduce the cost of discovery and to increase throughput. In this chapter, we discuss and describe mass spectrometry-based proteomic methods for quantitative protein analysis.

  15. Mass spectrometry imaging enriches biomarker discovery approaches with candidate mapping.

    Science.gov (United States)

    Scott, Alison J; Jones, Jace W; Orschell, Christie M; MacVittie, Thomas J; Kane, Maureen A; Ernst, Robert K

    2014-01-01

    Integral to the characterization of radiation-induced tissue damage is the identification of unique biomarkers. Biomarker discovery is a challenging and complex endeavor requiring both sophisticated experimental design and accessible technology. The resources within the National Institute of Allergy and Infectious Diseases (NIAID)-sponsored Consortium, Medical Countermeasures Against Radiological Threats (MCART), allow for leveraging robust animal models with novel molecular imaging techniques. One such imaging technique, MALDI (matrix-assisted laser desorption ionization) mass spectrometry imaging (MSI), allows for the direct spatial visualization of lipids, proteins, small molecules, and drugs/drug metabolites-or biomarkers-in an unbiased manner. MALDI-MSI acquires mass spectra directly from an intact tissue slice in discrete locations across an x, y grid that are then rendered into a spatial distribution map composed of ion mass and intensity. The unique mass signals can be plotted to generate a spatial map of biomarkers that reflects pathology and molecular events. The crucial unanswered questions that can be addressed with MALDI-MSI include identification of biomarkers for radiation damage that reflect the response to radiation dose over time and the efficacy of therapeutic interventions. Techniques in MALDI-MSI also enable integration of biomarker identification among diverse animal models. Analysis of early, sublethally irradiated tissue injury samples from diverse mouse tissues (lung and ileum) shows membrane phospholipid signatures correlated with histological features of these unique tissues. This paper will discuss the application of MALDI-MSI for use in a larger biomarker discovery pipeline.

  16. Maximizing biomarker discovery by minimizing gene signatures

    Directory of Open Access Journals (Sweden)

    Chang Chang

    2011-12-01

    Full Text Available Abstract Background The use of gene signatures can potentially be of considerable value in the field of clinical diagnosis. However, gene signatures defined with different methods can be quite various even when applied the same disease and the same endpoint. Previous studies have shown that the correct selection of subsets of genes from microarray data is key for the accurate classification of disease phenotypes, and a number of methods have been proposed for the purpose. However, these methods refine the subsets by only considering each single feature, and they do not confirm the association between the genes identified in each gene signature and the phenotype of the disease. We proposed an innovative new method termed Minimize Feature's Size (MFS based on multiple level similarity analyses and association between the genes and disease for breast cancer endpoints by comparing classifier models generated from the second phase of MicroArray Quality Control (MAQC-II, trying to develop effective meta-analysis strategies to transform the MAQC-II signatures into a robust and reliable set of biomarker for clinical applications. Results We analyzed the similarity of the multiple gene signatures in an endpoint and between the two endpoints of breast cancer at probe and gene levels, the results indicate that disease-related genes can be preferably selected as the components of gene signature, and that the gene signatures for the two endpoints could be interchangeable. The minimized signatures were built at probe level by using MFS for each endpoint. By applying the approach, we generated a much smaller set of gene signature with the similar predictive power compared with those gene signatures from MAQC-II. Conclusions Our results indicate that gene signatures of both large and small sizes could perform equally well in clinical applications. Besides, consistency and biological significances can be detected among different gene signatures, reflecting the

  17. Secreted proteins as a fundamental source for biomarker discovery

    Czech Academy of Sciences Publication Activity Database

    Šťastná, Miroslava; Van Eyk, J.E.

    2012-01-01

    Roč. 12, 4-5 (2012), s. 722-735 ISSN 1615-9853 Institutional research plan: CEZ:AV0Z40310501 Keywords : conditioned media * secreted proteins * proteomics * biomarker discovery Subject RIV: CB - Analytical Chemistry, Separation Impact factor: 4.132, year: 2012

  18. Exhaled Breath Condensate for Proteomic Biomarker Discovery

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    Sean W. Harshman

    2014-07-01

    Full Text Available Exhaled breath condensate (EBC has been established as a potential source of respiratory biomarkers. Compared to the numerous small molecules identified, the protein content of EBC has remained relatively unstudied due to the methodological and technical difficulties surrounding EBC analysis. In this review, we discuss the proteins identified in EBC, by mass spectrometry, focusing on the significance of those proteins identified. We will also review the limitations surrounding mass spectral EBC protein analysis emphasizing recommendations to enhance EBC protein identifications by mass spectrometry. Finally, we will provide insight into the future directions of the EBC proteomics field.

  19. Application of “omics” to Prion Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Rhiannon L. C. H. Huzarewich

    2010-01-01

    Full Text Available The advent of genomics and proteomics has been a catalyst for the discovery of biomarkers able to discriminate biological processes such as the pathogenesis of complex diseases. Prompt detection of prion diseases is particularly desirable given their transmissibility, which is responsible for a number of human health risks stemming from exogenous sources of prion protein. Diagnosis relies on the ability to detect the biomarker PrPSc, a pathological isoform of the host protein PrPC, which is an essential component of the infectious prion. Immunochemical detection of PrPSc is specific and sensitive enough for antemortem testing of brain tissue, however, this is not the case in accessible biological fluids or for the detection of recently identified novel prions with unique biochemical properties. A complementary approach to the detection of PrPSc itself is to identify alternative, “surrogate” gene or protein biomarkers indicative of disease. Biomarkers are also useful to track the progress of disease, especially important in the assessment of therapies, or to identify individuals “at risk”. In this review we provide perspective on current progress and pitfalls in the use of “omics” technologies to screen body fluids and tissues for biomarker discovery in prion diseases.

  20. Study design and data analysis considerations for the discovery of prognostic molecular biomarkers: a case study of progression free survival in advanced serous ovarian cancer.

    Science.gov (United States)

    Qin, Li-Xuan; Levine, Douglas A

    2016-06-10

    Accurate discovery of molecular biomarkers that are prognostic of a clinical outcome is an important yet challenging task, partly due to the combination of the typically weak genomic signal for a clinical outcome and the frequently strong noise due to microarray handling effects. Effective strategies to resolve this challenge are in dire need. We set out to assess the use of careful study design and data normalization for the discovery of prognostic molecular biomarkers. Taking progression free survival in advanced serous ovarian cancer as an example, we conducted empirical analysis on two sets of microRNA arrays for the same set of tumor samples: arrays in one set were collected using careful study design (that is, uniform handling and randomized array-to-sample assignment) and arrays in the other set were not. We found that (1) handling effects can confound the clinical outcome under study as a result of chance even with randomization, (2) the level of confounding handling effects can be reduced by data normalization, and (3) good study design cannot be replaced by post-hoc normalization. In addition, we provided a practical approach to define positive and negative control markers for detecting handling effects and assessing the performance of a normalization method. Our work showcased the difficulty of finding prognostic biomarkers for a clinical outcome of weak genomic signals, illustrated the benefits of careful study design and data normalization, and provided a practical approach to identify handling effects and select a beneficial normalization method. Our work calls for careful study design and data analysis for the discovery of robust and translatable molecular biomarkers.

  1. State of the Art in Tumor Antigen and Biomarker Discovery

    International Nuclear Information System (INIS)

    Even-Desrumeaux, Klervi; Baty, Daniel; Chames, Patrick

    2011-01-01

    Our knowledge of tumor immunology has resulted in multiple approaches for the treatment of cancer. However, a gap between research of new tumors markers and development of immunotherapy has been established and very few markers exist that can be used for treatment. The challenge is now to discover new targets for active and passive immunotherapy. This review aims at describing recent advances in biomarkers and tumor antigen discovery in terms of antigen nature and localization, and is highlighting the most recent approaches used for their discovery including “omics” technology

  2. State of the Art in Tumor Antigen and Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Patrick Chames

    2011-06-01

    Full Text Available Our knowledge of tumor immunology has resulted in multiple approaches for the treatment of cancer. However, a gap between research of new tumors markers and development of immunotherapy has been established and very few markers exist that can be used for treatment. The challenge is now to discover new targets for active and passive immunotherapy. This review aims at describing recent advances in biomarkers and tumor antigen discovery in terms of antigen nature and localization, and is highlighting the most recent approaches used for their discovery including “omics” technology.

  3. Discovery of novel biomarkers and phenotypes by semantic technologies.

    Science.gov (United States)

    Trugenberger, Carlo A; Wälti, Christoph; Peregrim, David; Sharp, Mark E; Bureeva, Svetlana

    2013-02-13

    Biomarkers and target-specific phenotypes are important to targeted drug design and individualized medicine, thus constituting an important aspect of modern pharmaceutical research and development. More and more, the discovery of relevant biomarkers is aided by in silico techniques based on applying data mining and computational chemistry on large molecular databases. However, there is an even larger source of valuable information available that can potentially be tapped for such discoveries: repositories constituted by research documents. This paper reports on a pilot experiment to discover potential novel biomarkers and phenotypes for diabetes and obesity by self-organized text mining of about 120,000 PubMed abstracts, public clinical trial summaries, and internal Merck research documents. These documents were directly analyzed by the InfoCodex semantic engine, without prior human manipulations such as parsing. Recall and precision against established, but different benchmarks lie in ranges up to 30% and 50% respectively. Retrieval of known entities missed by other traditional approaches could be demonstrated. Finally, the InfoCodex semantic engine was shown to discover new diabetes and obesity biomarkers and phenotypes. Amongst these were many interesting candidates with a high potential, although noticeable noise (uninteresting or obvious terms) was generated. The reported approach of employing autonomous self-organising semantic engines to aid biomarker discovery, supplemented by appropriate manual curation processes, shows promise and has potential to impact, conservatively, a faster alternative to vocabulary processes dependent on humans having to read and analyze all the texts. More optimistically, it could impact pharmaceutical research, for example to shorten time-to-market of novel drugs, or speed up early recognition of dead ends and adverse reactions.

  4. Proteomics and Mass Spectrometry for Cancer Biomarker Discovery

    Science.gov (United States)

    Lu, Ming; Faull, Kym F.; Whitelegge, Julian P.; He, Jianbo; Shen, Dejun; Saxton, Romaine E.; Chang, Helena R.

    2007-01-01

    Proteomics is a rapidly advancing field not only in the field of biology but also in translational cancer research. In recent years, mass spectrometry and associated technologies have been explored to identify proteins or a set of proteins specific to a given disease, for the purpose of disease detection and diagnosis. Such biomarkers are being investigated in samples including cells, tissues, serum/plasma, and other types of body fluids. When sufficiently refined, proteomic technologies may pave the way for early detection of cancer or individualized therapy for cancer. Mass spectrometry approaches coupled with bioinformatic tools are being developed for biomarker discovery and validation. Understanding basic concepts and application of such technology by investigators in the field may accelerate the clinical application of protein biomarkers in disease management. PMID:19662217

  5. Biomarker discovery in asthma and COPD: Application of proteomics techniques in human and mice

    Directory of Open Access Journals (Sweden)

    Steven Haenen

    2014-09-01

    Full Text Available The use of advanced proteomics approaches in the search for biomarkers in chronic lung diseases, such as asthma and COPD, is rather limited. Asthma and COPD are complex disorders, which can be subdivided into several phenotypes. This results in a heterogeneity of differential expressed biological molecules. Furthermore, genetic differences between animals and humans make ‘translation’ of possible biomarkers challenging. Yet, the improved sensitivity and high throughput of proteomic techniques could be an important asset for (new protein biomarker discovery in either human or animal models. We have reviewed the literature that reported the use of different proteomics approaches performed on samples obtained from humans and murine models in asthma and COPD research for the discovery of new biomarkers of diseases, biomarkers of sensitization or for the refinement of treatment. There is an increasing trend in the use of proteomics to explore new biomarkers of asthma or COPD. Although several murine models have been developed to study these lung diseases, and proteomics studies have been performed, ‘translation’ of identified candidate biomarkers into clinical studies is often lacking.

  6. Role of proteomics in the discovery of autism biomarkers

    International Nuclear Information System (INIS)

    Ayadhi, L.A.; Halepoto, D.M.

    2013-01-01

    The epidemiology of autism is continuously increasing all over the world with social, behavioural and economical burdens. Autism is considered as a multi-factorial disorder, influenced by genetic, neurological, environmental and immunological aspects. Autism is still believed to be incurable disorder with little information about the role of proteins patterns in the diagnosis of the disease. Knowing the applications of proteomic tools, it is possible to identify quantitative and qualitative protein patterns in a wide variety of tissues and body fluids such as blood, urine, saliva and cerebrospinal fluid in order to establish specific diagnostic and prognostic biomarkers. The aim of this review is to provide an overview of the various protocols available for proteomics by using mass spectrometry analysis, discuss reports in which these techniques have been previously applied in biomarker discovery for the diagnosis of autism, and consider the future development of this area of research. (author)

  7. Application of nano-LC-based glycomics towards biomarker discovery.

    Science.gov (United States)

    Hua, Serenus; Lebrilla, Carlito; An, Hyun Joo

    2011-11-01

    The glycome, that is, the glycan components of a biological source, has been widely reported to change with disease states. However, mining the glycome for biomarkers is complicated by glycan structural heterogeneity. Nanoflow LC, or nano-LC, significantly addresses the problem by providing a highly sensitive and quantitative method of separating and profiling glycans. This review summarizes recent advances in analytical technology and methodology that enhance and augment the advantages offered by nano-LC. (e.g., reversed phase, hydrophilic interaction and porous graphitized carbon chromatography, as well as associated derivatization strategies), detectors (e.g., fluorescence and MS), and technology platforms (particularly chip-based nano-LC) are examined in detail, along with their application to biomarker discovery. Particular emphasis is placed on methods and technologies that allow structure-specific glycan profiling.

  8. Discovery of nutritional biomarkers: future directions based on omics technologies.

    Science.gov (United States)

    Odriozola, Leticia; Corrales, Fernado J

    2015-07-01

    Understanding the interactions between food and human biology is of utmost importance to facilitate the development of more efficient nutritional interventions that might improve our wellness status and future health outcomes by reducing risk factors for non-transmittable chronic diseases, such as cardiovascular diseases, cancer, obesity and metabolic syndrome. Dissection of the molecular mechanisms that mediate the physiological effects of diets and bioactive compounds is one of the main goals of current nutritional investigation and the food industry as might lead to the discovery of novel biomarkers. It is widely recognized that the availability of robust nutritional biomarkers represents a bottleneck that delays the innovation process of the food industry. In this regard, omics sciences have opened up new avenues of research and opportunities in nutrition. Advances in mass spectrometry, nuclear magnetic resonance, next generation sequencing and microarray technologies allow massive genome, gene expression, proteomic and metabolomic profiling, obtaining a global and in-depth analysis of physiological/pathological scenarios. For this reason, omics platforms are most suitable for the discovery and characterization of novel nutritional markers that will define the nutritional status of both individuals and populations in the near future, and to identify the nutritional bioactive compounds responsible for the health outcomes.

  9. Proteomics and Mass Spectrometry for Cancer Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Ming Lu

    2007-01-01

    Full Text Available Proteomics is a rapidly advancing field not only in the field of biology but also in translational cancer research. In recent years, mass spectrometry and associated technologies have been explored to identify proteins or a set of proteins specific to a given disease, for the purpose of disease detection and diagnosis. Such biomarkers are being investigated in samples including cells, tissues, serum/plasma, and other types of body fluids. When sufficiently refined, proteomic technologies may pave the way for early detection of cancer or individualized therapy for cancer. Mass spectrometry approaches coupled with bioinformatic tools are being developed for biomarker discovery and validation. Understanding basic concepts and application of such technology by investigators in the field may accelerate the clinical application of protein biomarkers in disease management.Abbreviations: 2DE: two-dimensional gel electrophoresis; ABPP: activity-based protein profiling; CEA: carcinoembryonic antigen; CI: confidence interval; ESI: electrospray ionization; FP: fluorophosphonate; HPLC: high performance liquid chromatography; ICAT: isotope coded affi nitytags; IEF: isoelectric focusing; iTRAQ: isobaric tags for relative and absolute quantification; LCMS: combined liquid chromatography-mass spectrometry; LCMSMS: liquid chromatography tandem mass spectrometry; LOD: limit of detection; m/z: mass to charge ratio; MALDI: matrix-assisted laser desorption ionization; MS: mass spectrometry; MUDPIT: multidimensional protein identification technology; NAF: nipple aspirate fluid; PMF: peptide mass fingerprinting; PSA: prostate specifi c antigen; PTMs: post-translational modifications; RPMA: reverse phase protein microarray; SELDI: surface enhanced laser desorption ionization; TOF: time-of-flight.

  10. Biomarker discovery in subclinical mycobacterial infections of cattle.

    Directory of Open Access Journals (Sweden)

    Meetu Seth

    Full Text Available BACKGROUND: Bovine tuberculosis is a highly prevalent infectious disease of cattle worldwide; however, infection in the United States is limited to 0.01% of dairy herds. Thus detection of bovine TB is confounded by high background infection with M. avium subsp. paratuberculosis. The present study addresses variations in the circulating peptidome based on the pathogenesis of two biologically similar mycobacterial diseases of cattle. METHODOLOGY/PRINCIPAL FINDINGS: We hypothesized that serum proteomes of animals in response to either M. bovis or M. paratuberculosis infection will display several commonalities and differences. Sera prospectively collected from animals experimentally infected with either M. bovis or M. paratuberculosis were analyzed using high-resolution proteomics approaches. iTRAQ, a liquid chromatography and tandem mass spectrometry approach, was used to simultaneously identify and quantify peptides from multiple infections and contemporaneous uninfected control groups. Four comparisons were performed: 1 M. bovis infection versus uninfected controls, 2 M. bovis versus M. paratuberculosis infection, 3 early, and 4 advanced M. paratuberculosis infection versus uninfected controls. One hundred and ten differentially elevated proteins (P < or = 0.05 were identified. Vitamin D binding protein precursor (DBP, alpha-1 acid glycoprotein, alpha-1B glycoprotein, fetuin, and serine proteinase inhibitor were identified in both infections. Transthyretin, retinol binding proteins, and cathelicidin were identified exclusively in M. paratuberculosis infection, while the serum levels of alpha-1-microglobulin/bikunin precursor (AMBP protein, alpha-1 acid glycoprotein, fetuin, and alpha-1B glycoprotein were elevated exclusively in M. bovis infected animals. CONCLUSIONS/SIGNIFICANCE: The discovery of these biomarkers has significant impact on the elucidation of pathogenesis of two mycobacterial diseases at the cellular and the molecular level and

  11. At the cross-roads of participatory research and biomarker discovery in autism: the need for empirical data.

    Science.gov (United States)

    Yusuf, Afiqah; Elsabbagh, Mayada

    2015-12-15

    Identifying biomarkers for autism can improve outcomes for those affected by autism. Engaging the diverse stakeholders in the research process using community-based participatory research (CBPR) can accelerate biomarker discovery into clinical applications. However, there are limited examples of stakeholder involvement in autism research, possibly due to conceptual and practical concerns. We evaluate the applicability of CBPR principles to biomarker discovery in autism and critically review empirical studies adopting these principles. Using a scoping review methodology, we identified and evaluated seven studies using CBPR principles in biomarker discovery. The limited number of studies in biomarker discovery adopting CBPR principles coupled with their methodological limitations suggests that such applications are feasible but challenging. These studies illustrate three CBPR themes: community assessment, setting global priorities, and collaboration in research design. We propose that further research using participatory principles would be useful in accelerating the pace of discovery and the development of clinically meaningful biomarkers. For this goal to be successful we advocate for increased attention to previously identified conceptual and methodological challenges to participatory approaches in health research, including improving scientific rigor and developing long-term partnerships among stakeholders.

  12. Emerging concepts in biomarker discovery; The US-Japan workshop on immunological molecular markers in oncology

    Directory of Open Access Journals (Sweden)

    Rivoltini Licia

    2009-06-01

    were recognized that might be added to the list of known entities applicable in immunotherapy trials. The need for a systematic approach to biomarker discovery that takes advantage of powerful high-throughput technologies was recognized; it was clear from the current state of the science that immunotherapy is still in a discovery phase and only a few of the current biomarkers warrant extensive validation. It was, finally, clear that, while current technologies have almost limitless potential, inadequate study design, limited standardization and cross-validation among laboratories and suboptimal comparability of data remain major road blocks. The institution of an interactive consortium for high throughput molecular monitoring of clinical trials with voluntary participation might provide cost-effective solutions.

  13. Discovery of biomarkers for oxidative stress based on cellular metabolomics.

    Science.gov (United States)

    Wang, Ningli; Wei, Jianteng; Liu, Yewei; Pei, Dong; Hu, Qingping; Wang, Yu; Di, Duolong

    2016-07-01

    Oxidative stress has a close relationship with various pathologic physiology phenomena and the potential biomarkers of oxidative stress may provide evidence for clinical diagnosis or disease prevention. Metabolomics was employed to identify the potential biomarkers of oxidative stress. High-performance liquid chromatography-diode array detector, mass spectrometry and partial least squares discriminate analysis were used in this study. The 10, 15 and 13 metabolites were considered to discriminate the model group, vitamin E-treated group and l-glutathione-treated group, respectively. Some of them have been identified, namely, malic acid, vitamin C, reduced glutathione and tryptophan. Identification of other potential biomarkers should be conducted and their physiological significance also needs to be elaborated.

  14. BioPlat: a software for human cancer biomarker discovery.

    Science.gov (United States)

    Butti, Matias D; Chanfreau, Hernan; Martinez, Diego; García, Diego; Lacunza, Ezequiel; Abba, Martin C

    2014-06-15

    Development of effective tools such as oligo-microarrays and next-generation sequencing methods for monitoring gene expression on a large scale has resulted in the discovery of gene signatures with prognostic/predictive value in various malignant neoplastic diseases. However, with the exponential growth of gene expression databases, biologists are faced with the challenge of extracting useful information from these repositories. Here, we present a software package, BioPlat (Biomarkers Platform), which allows biologists to identify novel prognostic and predictive cancer biomarkers based on the data mining of gene expression signatures and gene expression profiling databases. BioPlat has been designed as an easy-to-use and flexible desktop software application, which provides a set of analytical tools related to data extraction, preprocessing, filtering, gene expression signature calculation, in silico validation, feature selection and annotation that leverage the integration and reuse of gene expression signatures in the context of follow-up data. BioPlat is a platform-independent software implemented in Java and supported on GNU/Linux and MS Windows, which is freely available for download at http://www.cancergenomics.net. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  15. Multi-dimensional discovery of biomarker and phenotype complexes

    Directory of Open Access Journals (Sweden)

    Huang Kun

    2010-10-01

    Full Text Available Abstract Background Given the rapid growth of translational research and personalized healthcare paradigms, the ability to relate and reason upon networks of bio-molecular and phenotypic variables at various levels of granularity in order to diagnose, stage and plan treatments for disease states is highly desirable. Numerous techniques exist that can be used to develop networks of co-expressed or otherwise related genes and clinical features. Such techniques can also be used to create formalized knowledge collections based upon the information incumbent to ontologies and domain literature. However, reports of integrative approaches that bridge such networks to create systems-level models of disease or wellness are notably lacking in the contemporary literature. Results In response to the preceding gap in knowledge and practice, we report upon a prototypical series of experiments that utilize multi-modal approaches to network induction. These experiments are intended to elicit meaningful and significant biomarker-phenotype complexes spanning multiple levels of granularity. This work has been performed in the experimental context of a large-scale clinical and basic science data repository maintained by the National Cancer Institute (NCI funded Chronic Lymphocytic Leukemia Research Consortium. Conclusions Our results indicate that it is computationally tractable to link orthogonal networks of genes, clinical features, and conceptual knowledge to create multi-dimensional models of interrelated biomarkers and phenotypes. Further, our results indicate that such systems-level models contain interrelated bio-molecular and clinical markers capable of supporting hypothesis discovery and testing. Based on such findings, we propose a conceptual model intended to inform the cross-linkage of the results of such methods. This model has as its aim the identification of novel and knowledge-anchored biomarker-phenotype complexes.

  16. Mass spectrometry based biomarker discovery, verification, and validation--quality assurance and control of protein biomarker assays.

    Science.gov (United States)

    Parker, Carol E; Borchers, Christoph H

    2014-06-01

    In its early years, mass spectrometry (MS)-based proteomics focused on the cataloging of proteins found in different species or different tissues. By 2005, proteomics was being used for protein quantitation, typically based on "proteotypic" peptides which act as surrogates for the parent proteins. Biomarker discovery is usually done by non-targeted "shotgun" proteomics, using relative quantitation methods to determine protein expression changes that correlate with disease (output given as "up-or-down regulation" or "fold-increases"). MS-based techniques can also perform "absolute" quantitation which is required for clinical applications (output given as protein concentrations). Here we describe the differences between these methods, factors that affect the precision and accuracy of the results, and some examples of recent studies using MS-based proteomics to verify cancer-related biomarkers. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

  17. Analysis of Serum Metabolic Profile by Ultra-performance Liquid Chromatography-mass Spectrometry for Biomarkers Discovery: Application in a Pilot Study to Discriminate Patients with Tuberculosis

    Directory of Open Access Journals (Sweden)

    Shuang Feng

    2015-01-01

    Full Text Available Background: Tuberculosis (TB is a chronic wasting inflammatory disease characterized by multisystem involvement, which can cause metabolic derangements in afflicted patients. Metabolic signatures have been exploited in the study of several diseases. However, the serum that is successfully used in TB diagnosis on the basis of metabolic profiling is not by much. Methods: Orthogonal partial least-squares discriminant analysis was capable of distinguishing TB patients from both healthy subjects and patients with conditions other than TB. Therefore, TB-specific metabolic profiling was established. Clusters of potential biomarkers for differentiating TB active from non-TB diseases were identified using Mann-Whitney U-test. Multiple logistic regression analysis of metabolites was calculated to determine the suitable biomarker group that allows the efficient differentiation of patients with TB active from the control subjects. Results: From among 271 participants, 12 metabolites were found to contribute to the distinction between the TB active group and the control groups. These metabolites were mainly involved in the metabolic pathways of the following three biomolecules: Fatty acids, amino acids, and lipids. The receiver operating characteristic curves of 3D, 7D, and 11D-phytanic acid, behenic acid, and threoninyl-γ-glutamate exhibited excellent efficiency with area under the curve (AUC values of 0.904 (95% confidence interval [CI]: 0863-0.944, 0.93 (95% CI: 0.893-0.966, and 0.964 (95% CI: 00.941-0.988, respectively. The largest and smallest resulting AUCs were 0.964 and 0.720, indicating that these biomarkers may be involved in the disease mechanisms. The combination of lysophosphatidylcholine (18:0, behenic acid, threoninyl-γ-glutamate, and presqualene diphosphate was used to represent the most suitable biomarker group for the differentiation of patients with TB active from the control subjects, with an AUC value of 0.991. Conclusion: The

  18. Biomarker discovery for colon cancer using a 761 gene RT-PCR assay

    Directory of Open Access Journals (Sweden)

    Hackett James R

    2007-08-01

    Full Text Available Abstract Background Reverse transcription PCR (RT-PCR is widely recognized to be the gold standard method for quantifying gene expression. Studies using RT-PCR technology as a discovery tool have historically been limited to relatively small gene sets compared to other gene expression platforms such as microarrays. We have recently shown that TaqMan® RT-PCR can be scaled up to profile expression for 192 genes in fixed paraffin-embedded (FPE clinical study tumor specimens. This technology has also been used to develop and commercialize a widely used clinical test for breast cancer prognosis and prediction, the Onco typeDX™ assay. A similar need exists in colon cancer for a test that provides information on the likelihood of disease recurrence in colon cancer (prognosis and the likelihood of tumor response to standard chemotherapy regimens (prediction. We have now scaled our RT-PCR assay to efficiently screen 761 biomarkers across hundreds of patient samples and applied this process to biomarker discovery in colon cancer. This screening strategy remains attractive due to the inherent advantages of maintaining platform consistency from discovery through clinical application. Results RNA was extracted from formalin fixed paraffin embedded (FPE tissue, as old as 28 years, from 354 patients enrolled in NSABP C-01 and C-02 colon cancer studies. Multiplexed reverse transcription reactions were performed using a gene specific primer pool containing 761 unique primers. PCR was performed as independent TaqMan® reactions for each candidate gene. Hierarchal clustering demonstrates that genes expected to co-express form obvious, distinct and in certain cases very tightly correlated clusters, validating the reliability of this technical approach to biomarker discovery. Conclusion We have developed a high throughput, quantitatively precise multi-analyte gene expression platform for biomarker discovery that approaches low density DNA arrays in numbers of

  19. INDEED: Integrated differential expression and differential network analysis of omic data for biomarker discovery.

    Science.gov (United States)

    Zuo, Yiming; Cui, Yi; Di Poto, Cristina; Varghese, Rency S; Yu, Guoqiang; Li, Ruijiang; Ressom, Habtom W

    2016-12-01

    Differential expression (DE) analysis is commonly used to identify biomarker candidates that have significant changes in their expression levels between distinct biological groups. One drawback of DE analysis is that it only considers the changes on single biomolecule level. Recently, differential network (DN) analysis has become popular due to its capability to measure the changes on biomolecular pair level. In DN analysis, network is typically built based on correlation and biomarker candidates are selected by investigating the network topology. However, correlation tends to generate over-complicated networks and the selection of biomarker candidates purely based on network topology ignores the changes on single biomolecule level. In this paper, we propose a novel approach, INDEED, that builds sparse differential network based on partial correlation and integrates DE and DN analyses for biomarker discovery. We applied this approach on real proteomic and glycomic data generated by liquid chromatography coupled with mass spectrometry for hepatocellular carcinoma (HCC) biomarker discovery study. For each omic data, we used one dataset to select biomarker candidates, built a disease classifier and evaluated the performance of the classifier on an independent dataset. The biomarker candidates, selected by INDEED, were more reproducible across independent datasets, and led to a higher classification accuracy in predicting HCC cases and cirrhotic controls compared with those selected by separate DE and DN analyses. INDEED also identified some candidates previously reported to be relevant to HCC, such as intercellular adhesion molecule 2 (ICAM2) and c4b-binding protein alpha chain (C4BPA), which were missed by both DE and DN analyses. In addition, we applied INDEED for survival time prediction based on transcriptomic data acquired by analysis of samples from breast cancer patients. We selected biomarker candidates and built a regression model for survival time prediction

  20. Variable importance analysis based on rank aggregation with applications in metabolomics for biomarker discovery.

    Science.gov (United States)

    Yun, Yong-Huan; Deng, Bai-Chuan; Cao, Dong-Sheng; Wang, Wei-Ting; Liang, Yi-Zeng

    2016-03-10

    Biomarker discovery is one important goal in metabolomics, which is typically modeled as selecting the most discriminating metabolites for classification and often referred to as variable importance analysis or variable selection. Until now, a number of variable importance analysis methods to discover biomarkers in the metabolomics studies have been proposed. However, different methods are mostly likely to generate different variable ranking results due to their different principles. Each method generates a variable ranking list just as an expert presents an opinion. The problem of inconsistency between different variable ranking methods is often ignored. To address this problem, a simple and ideal solution is that every ranking should be taken into account. In this study, a strategy, called rank aggregation, was employed. It is an indispensable tool for merging individual ranking lists into a single "super"-list reflective of the overall preference or importance within the population. This "super"-list is regarded as the final ranking for biomarker discovery. Finally, it was used for biomarkers discovery and selecting the best variable subset with the highest predictive classification accuracy. Nine methods were used, including three univariate filtering and six multivariate methods. When applied to two metabolic datasets (Childhood overweight dataset and Tubulointerstitial lesions dataset), the results show that the performance of rank aggregation has improved greatly with higher prediction accuracy compared with using all variables. Moreover, it is also better than penalized method, least absolute shrinkage and selectionator operator (LASSO), with higher prediction accuracy or less number of selected variables which are more interpretable. Copyright © 2016 Elsevier B.V. All rights reserved.

  1. Integration of Proteomics, Bioinformatics, and Systems Biology in Traumatic Brain Injury Biomarker Discovery

    Science.gov (United States)

    Guingab-Cagmat, J.D.; Cagmat, E.B.; Hayes, R.L.; Anagli, J.

    2013-01-01

    Traumatic brain injury (TBI) is a major medical crisis without any FDA-approved pharmacological therapies that have been demonstrated to improve functional outcomes. It has been argued that discovery of disease-relevant biomarkers might help to guide successful clinical trials for TBI. Major advances in mass spectrometry (MS) have revolutionized the field of proteomic biomarker discovery and facilitated the identification of several candidate markers that are being further evaluated for their efficacy as TBI biomarkers. However, several hurdles have to be overcome even during the discovery phase which is only the first step in the long process of biomarker development. The high-throughput nature of MS-based proteomic experiments generates a massive amount of mass spectral data presenting great challenges in downstream interpretation. Currently, different bioinformatics platforms are available for functional analysis and data mining of MS-generated proteomic data. These tools provide a way to convert data sets to biologically interpretable results and functional outcomes. A strategy that has promise in advancing biomarker development involves the triad of proteomics, bioinformatics, and systems biology. In this review, a brief overview of how bioinformatics and systems biology tools analyze, transform, and interpret complex MS datasets into biologically relevant results is discussed. In addition, challenges and limitations of proteomics, bioinformatics, and systems biology in TBI biomarker discovery are presented. A brief survey of researches that utilized these three overlapping disciplines in TBI biomarker discovery is also presented. Finally, examples of TBI biomarkers and their applications are discussed. PMID:23750150

  2. Proteomic Biomarker Discovery in 1000 Human Plasma Samples with Mass Spectrometry.

    Science.gov (United States)

    Cominetti, Ornella; Núñez Galindo, Antonio; Corthésy, John; Oller Moreno, Sergio; Irincheeva, Irina; Valsesia, Armand; Astrup, Arne; Saris, Wim H M; Hager, Jörg; Kussmann, Martin; Dayon, Loïc

    2016-02-05

    The overall impact of proteomics on clinical research and its translation has lagged behind expectations. One recognized caveat is the limited size (subject numbers) of (pre)clinical studies performed at the discovery stage, the findings of which fail to be replicated in larger verification/validation trials. Compromised study designs and insufficient statistical power are consequences of the to-date still limited capacity of mass spectrometry (MS)-based workflows to handle large numbers of samples in a realistic time frame, while delivering comprehensive proteome coverages. We developed a highly automated proteomic biomarker discovery workflow. Herein, we have applied this approach to analyze 1000 plasma samples from the multicentered human dietary intervention study "DiOGenes". Study design, sample randomization, tracking, and logistics were the foundations of our large-scale study. We checked the quality of the MS data and provided descriptive statistics. The data set was interrogated for proteins with most stable expression levels in that set of plasma samples. We evaluated standard clinical variables that typically impact forthcoming results and assessed body mass index-associated and gender-specific proteins at two time points. We demonstrate that analyzing a large number of human plasma samples for biomarker discovery with MS using isobaric tagging is feasible, providing robust and consistent biological results.

  3. Plasma biomarker discovery in preeclampsia using a novel differential isolation technology for circulating extracellular vesicles.

    Science.gov (United States)

    Tan, Kok Hian; Tan, Soon Sim; Sze, Siu Kwan; Lee, Wai Kheong Ryan; Ng, Mor Jack; Lim, Sai Kiang

    2014-10-01

    To circumvent the complex protein milieu of plasma and discover robust predictive biomarkers for preeclampsia (PE), we investigate if phospholipid-binding ligands can reduce the milieu complexity by extracting plasma extracellular vesicles for biomarker discovery. Cholera toxin B chain (CTB) and annexin V (AV) which respectively binds GM1 ganglioside and phosphatidylserine were used to isolate extracellular vesicles from plasma of PE patients and healthy pregnant women. The proteins in the vesicles were identified using enzyme-linked immunosorbent assay, antibody array, and mass spectrometry. CTB and AV were found to bind 2 distinct groups of extracellular vesicles. Antibody array and enzyme-linked immunosorbent assay revealed that PE patients had elevated levels of CD105, interleukin-6, placental growth factor, tissue inhibitor of metallopeptidase 1, and atrial natriuretic peptide in cholera toxin B- but not AV-vesicles, and elevated levels of plasminogen activator inhibitor-1, pro-calcitonin, S100b, tumor growth factor β, vascular endothelial growth factor receptor 1, brain natriuretic peptide, and placental growth factor in both cholera toxin B- and AV-vesicles. CD9 level was elevated in cholera toxin B-vesicles but reduced in AV vesicles of PE patients. Proteome analysis revealed that in cholera toxin B-vesicles, 87 and 222 proteins were present only in PE patients and healthy pregnant women respectively while in AV-vesicles, 104 and 157 proteins were present only in PE and healthy pregnant women, respectively. This study demonstrated for the first time that CTB and AV bind unique extracellular vesicles, and their protein cargo reflects the disease state of the patient. The successful use of these 2 ligands to isolate circulating plasma extracellular vesicles for biomarker discovery in PE represents a novel technology for biomarker discovery that can be applied to other specialties. Copyright © 2014 Elsevier Inc. All rights reserved.

  4. The discovery and development of proteomic safety biomarkers for the detection of drug-induced liver toxicity

    International Nuclear Information System (INIS)

    Amacher, David E.

    2010-01-01

    Biomarkers are biometric measurements that provide critical quantitative information about the biological condition of the animal or individual being tested. In drug safety studies, established toxicity biomarkers are used along with other conventional study data to determine dose-limiting organ toxicity, and to define species sensitivity for new chemical entities intended for possible use as human medicines. A continuing goal of drug safety scientists in the pharmaceutical industry is to discover and develop better trans-species biomarkers that can be used to determine target organ toxicities for preclinical species in short-term studies at dose levels that are some multiple of the intended human dose and again later in full development for monitoring clinical trials at lower therapeutic doses. Of particular value are early, predictive, noninvasive biomarkers that have in vitro, in vivo, and clinical transferability. Such translational biomarkers bridge animal testing used in preclinical science and human studies that are part of subsequent clinical testing. Although suitable for in vivo preclinical regulatory studies, conventional hepatic safety biomarkers are basically confirmatory markers because they signal organ toxicity after some pathological damage has occurred, and are therefore not well-suited for short-term, predictive screening assays early in the discovery-to-development progression of new chemical entities (NCEs) available in limited quantities. Efforts between regulatory agencies and the pharmaceutical industry are underway for the coordinated discovery, qualification, verification and validation of early predictive toxicity biomarkers. Early predictive safety biomarkers are those that are detectable and quantifiable prior to the onset of irreversible tissue injury and which are associated with a mechanism of action relevant to a specific type of potential hepatic injury. Potential drug toxicity biomarkers are typically endogenous macromolecules in

  5. Discovery of Predictive Biomarkers for Litter Size in Boar Spermatozoa*

    Science.gov (United States)

    Kwon, Woo-Sung; Rahman, Md Saidur; Lee, June-Sub; Yoon, Sung-Jae; Park, Yoo-Jin; Pang, Myung-Geol

    2015-01-01

    Conventional semen analysis has been used for prognosis and diagnosis of male fertility. Although this tool is essential for providing initial quantitative information about semen, it remains a subject of debate. Therefore, development of new methods for the prognosis and diagnosis of male fertility should be seriously considered for animal species of economic importance as well as for humans. In the present study, we applied a comprehensive proteomic approach to identify global protein biomarkers in boar spermatozoa in order to increase the precision of male fertility prognoses and diagnoses. We determined that l-amino acid oxidase, mitochondrial malate dehydrogenase 2, NAD (MDH2), cytosolic 5′-nucleotidase 1B, lysozyme-like protein 4, and calmodulin (CALM) were significantly and abundantly expressed in high-litter size spermatozoa. We also found that equatorin, spermadhesin AWN, triosephosphate isomerase (TPI), Ras-related protein Rab-2A (RAB2A), spermadhesin AQN-3, and NADH dehydrogenase [ubiquinone] iron-sulfur protein 2 (NDUFS2) were significantly and abundantly expressed in low-litter size spermatozoa (>3-fold). Moreover, RAB2A, TPI, and NDUFS2 were negatively correlated with litter size, whereas CALM and MDH2 were positively correlated. This study provides novel biomarkers for the prediction of male fertility. To the best of our knowledge, this is the first work that shows significantly increased litter size using male fertility biomarkers in a field trial. Moreover, these protein markers may provide new developmental tools for the selection of superior sires as well as for the prognosis and diagnosis of male fertility. PMID:25693803

  6. Application of proteomics in biomarker discovery: a primer for the clinician.

    Science.gov (United States)

    Tambor, V; Fucíková, A; Lenco, J; Kacerovský, M; Rehácek, V; Stulík, J; Pudil, R

    2010-01-01

    Ever since proteomics was proven to be capable of characterizing a large number of differences in both protein quality and quantity, it has been applied in various areas of biomedicine, ranging from the deciphering molecular pathogenesis of diseases to the characterization of novel drug targets and the discovery of potential diagnostic biomarkers. Indeed, the biomarker discovery in human plasma is clearly one of the areas with enormous potential. However, without proper planning and implementation of specific techniques, the efforts and expectations may very easily be hampered. Numerous earlier projects aimed at clinical proteomics, characterized by exaggerated enthusiasm, often underestimated some principal obstacles of plasma biomarker discovery. Consequently, ambiguous and insignificant results soon led to a more critical view in this field. In this article, we critically review the current state of proteomic approaches for biomarker discovery and validation, in order to provide basic information and guidelines for both clinicians and researchers. These need to be closely considered prior to initiation of a project aimed at plasma biomarker discovery. We also present a short overview of recent applications of clinical proteomics in biomarker discovery.

  7. Malignant Mesothelioma Biomarkers: From Discovery to Use in Clinical Practice for Diagnosis, Monitoring, Screening, and Treatment.

    Science.gov (United States)

    Creaney, Jenette; Robinson, Bruce W S

    2017-07-01

    Malignant pleural mesothelioma is a highly aggressive tumor associated with asbestos exposure. There are few effective treatment options for mesothelioma, and patients have a very poor prognosis with a median survival of mesothelioma biomarker has been ongoing for the last 30 years. Many traditional soluble (glyco)protein biomarkers have been evaluated over this time, and an ever-increasing list of new biomarkers, including messenger RNA, DNA, microRNA, and antibodies, is being reported from biomarker discovery projects. To date, soluble mesothelin is the only tumor biomarker to receive US Food and Drug Administration approval for clinical use in mesothelioma. Mesothelin is a glycoprotein normally expressed on the surface of mesothelial cells, and in the cancerous state it can be present in circulation. Mesothelin has a limited expression on normal, nonmalignant tissue and is thus an attractive therapeutic target for mesothelin-positive tumors. In this review we will focus on the discovery and clinical usages of mesothelin and provide an update on other mesothelioma biomarkers and show how such biomarker studies might impact on the management of this deadly tumor in the future. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  8. Progress and Potential of Imaging Mass Spectrometry Applied to Biomarker Discovery.

    Science.gov (United States)

    Quanico, Jusal; Franck, Julien; Wisztorski, Maxence; Salzet, Michel; Fournier, Isabelle

    2017-01-01

    Mapping provides a direct means to assess the impact of protein biomarkers and puts into context their relevance in the type of cancer being examined. To this end, mass spectrometry imaging (MSI) was developed to provide the needed spatial information which is missing in traditional liquid-based mass spectrometric proteomics approaches. Aptly described as a "molecular histology" technique, MSI gives an additional dimension in characterizing tumor biopsies, allowing for mapping of hundreds of molecules in a single analysis. A decade of developments focused on improving and standardizing MSI so that the technique can be translated into the clinical setting. This review describes the progress made in addressing the technological development that allows to bridge local protein detection by MSI to its identification and to illustrate its potential in studying various aspects of cancer biomarker discovery.

  9. Biomarker discovery in neurological diseases: a metabolomic approach

    Directory of Open Access Journals (Sweden)

    Afaf El-Ansary

    2009-12-01

    Full Text Available Afaf El-Ansary, Nouf Al-Afaleg, Yousra Al-YafaeeBiochemistry Department, Science College, King Saud University, Riyadh, Saudi ArabiaAbstract: Biomarkers are pharmacological and physiological measurements or specific biochemicals in the body that have a particular molecular feature that makes them useful for measuring the progress of disease or the effects of treatment. Due to the complexity of neurological disorders, it is very difficult to have perfect markers. Brain diseases require plenty of markers to reflect the metabolic impairment of different brain cells. The recent introduction of the metabolomic approach helps the study of neurological diseases based on profiling a multitude of biochemical components related to brain metabolism. This review is a trial to elucidate the possibility to use this approach to identify plasma metabolic markers related to neurological disorders. Previous trials using different metabolomic analyses including nuclear magnetic resonance spectroscopy, gas chromatography combined with mass spectrometry, liquid chromatography combined with mass spectrometry, and capillary electrophoresis will be traced.Keywords: metabolic biomarkers, neurological disorders. metabolome, nuclear magnetic resonance, mass spectrometry, chromatography

  10. Gaucher disease: a model disorder for biomarker discovery

    DEFF Research Database (Denmark)

    Boot, Rolf G; van Breemen, Mariëlle J; Wegdam, Wouter

    2009-01-01

    role of storage cells in the pathology, various attempts have been made to identify proteins in plasma or serum reflecting the body burden of these pathological cells. In this review, the existing data regarding biomarkers for Gaucher disease, as well as the current application of biomarkers...

  11. OMICS-driven biomarker discovery in nutrition and health.

    Science.gov (United States)

    Kussmann, Martin; Raymond, Frédéric; Affolter, Michael

    2006-08-05

    While traditional nutrition research has dealt with providing nutrients to nourish populations, it nowadays focuses on improving health of individuals through diet. Modern nutritional research is aiming at health promotion and disease prevention and on performance improvement. As a consequence of these ambitious objectives, the disciplines "nutrigenetics" and "nutrigenomics" have evolved. Nutrigenetics asks the question how individual genetic disposition, manifesting as single nucleotide polymorphisms, copy-number polymorphisms and epigenetic phenomena, affects susceptibility to diet. Nutrigenomics addresses the inverse relationship, that is how diet influences gene transcription, protein expression and metabolism. A major methodological challenge and first pre-requisite of nutrigenomics is integrating genomics (gene analysis), transcriptomics (gene expression analysis), proteomics (protein expression analysis) and metabonomics (metabolite profiling) to define a "healthy" phenotype. The long-term deliverable of nutrigenomics is personalised nutrition for maintenance of individual health and prevention of disease. Transcriptomics serves to put proteomic and metabolomic markers into a larger biological perspective and is suitable for a first "round of discovery" in regulatory networks. Metabonomics is a diagnostic tool for metabolic classification of individuals. The great asset of this platform is the quantitative, non-invasive analysis of easily accessible human body fluids like urine, blood and saliva. This feature also holds true to some extent for proteomics, with the constraint that proteomics is more complex in terms of absolute number, chemical properties and dynamic range of compounds present. Apart from addressing the most complex "-ome", proteomics represents the only platform that delivers not only markers for disposition and efficacy but also targets of intervention. The Omics disciplines applied in the context of nutrition and health have the potential

  12. Revisiting biomarker discovery by plasma proteomics

    DEFF Research Database (Denmark)

    Geyer, Philipp E; Holdt, Lesca M; Teupser, Daniel

    2017-01-01

    slow rate. As described in this review, mass spectrometry (MS)-based proteomics has become a powerful technology in biological research and it is now poised to allow the characterization of the plasma proteome in great depth. Previous "triangular strategies" aimed at discovering single biomarker......Clinical analysis of blood is the most widespread diagnostic procedure in medicine, and blood biomarkers are used to categorize patients and to support treatment decisions. However, existing biomarkers are far from comprehensive and often lack specificity and new ones are being developed at a very...

  13. Computer-aided biomarker discovery for precision medicine: data resources, models and applications.

    Science.gov (United States)

    Lin, Yuxin; Qian, Fuliang; Shen, Li; Chen, Feifei; Chen, Jiajia; Shen, Bairong

    2017-11-29

    Biomarkers are a class of measurable and evaluable indicators with the potential to predict disease initiation and progression. In contrast to disease-associated factors, biomarkers hold the promise to capture the changeable signatures of biological states. With methodological advances, computer-aided biomarker discovery has now become a burgeoning paradigm in the field of biomedical science. In recent years, the 'big data' term has accumulated for the systematical investigation of complex biological phenomena and promoted the flourishing of computational methods for systems-level biomarker screening. Compared with routine wet-lab experiments, bioinformatics approaches are more efficient to decode disease pathogenesis under a holistic framework, which is propitious to identify biomarkers ranging from single molecules to molecular networks for disease diagnosis, prognosis and therapy. In this review, the concept and characteristics of typical biomarker types, e.g. single molecular biomarkers, module/network biomarkers, cross-level biomarkers, etc., are explicated on the guidance of systems biology. Then, publicly available data resources together with some well-constructed biomarker databases and knowledge bases are introduced. Biomarker identification models using mathematical, network and machine learning theories are sequentially discussed. Based on network substructural and functional evidences, a novel bioinformatics model is particularly highlighted for microRNA biomarker discovery. This article aims to give deep insights into the advantages and challenges of current computational approaches for biomarker detection, and to light up the future wisdom toward precision medicine and nation-wide healthcare. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  14. Reproducible cancer biomarker discovery in SELDI-TOF MS using different pre-processing algorithms.

    Directory of Open Access Journals (Sweden)

    Jinfeng Zou

    Full Text Available BACKGROUND: There has been much interest in differentiating diseased and normal samples using biomarkers derived from mass spectrometry (MS studies. However, biomarker identification for specific diseases has been hindered by irreproducibility. Specifically, a peak profile extracted from a dataset for biomarker identification depends on a data pre-processing algorithm. Until now, no widely accepted agreement has been reached. RESULTS: In this paper, we investigated the consistency of biomarker identification using differentially expressed (DE peaks from peak profiles produced by three widely used average spectrum-dependent pre-processing algorithms based on SELDI-TOF MS data for prostate and breast cancers. Our results revealed two important factors that affect the consistency of DE peak identification using different algorithms. One factor is that some DE peaks selected from one peak profile were not detected as peaks in other profiles, and the second factor is that the statistical power of identifying DE peaks in large peak profiles with many peaks may be low due to the large scale of the tests and small number of samples. Furthermore, we demonstrated that the DE peak detection power in large profiles could be improved by the stratified false discovery rate (FDR control approach and that the reproducibility of DE peak detection could thereby be increased. CONCLUSIONS: Comparing and evaluating pre-processing algorithms in terms of reproducibility can elucidate the relationship among different algorithms and also help in selecting a pre-processing algorithm. The DE peaks selected from small peak profiles with few peaks for a dataset tend to be reproducibly detected in large peak profiles, which suggests that a suitable pre-processing algorithm should be able to produce peaks sufficient for identifying useful and reproducible biomarkers.

  15. Mass Spectrometry-Based Proteomics in Molecular Diagnostics: Discovery of Cancer Biomarkers Using Tissue Culture

    Science.gov (United States)

    Paul, Debasish; Kumar, Avinash; Gajbhiye, Akshada; Santra, Manas K.; Srikanth, Rapole

    2013-01-01

    Accurate diagnosis and proper monitoring of cancer patients remain a key obstacle for successful cancer treatment and prevention. Therein comes the need for biomarker discovery, which is crucial to the current oncological and other clinical practices having the potential to impact the diagnosis and prognosis. In fact, most of the biomarkers have been discovered utilizing the proteomics-based approaches. Although high-throughput mass spectrometry-based proteomic approaches like SILAC, 2D-DIGE, and iTRAQ are filling up the pitfalls of the conventional techniques, still serum proteomics importunately poses hurdle in overcoming a wide range of protein concentrations, and also the availability of patient tissue samples is a limitation for the biomarker discovery. Thus, researchers have looked for alternatives, and profiling of candidate biomarkers through tissue culture of tumor cell lines comes up as a promising option. It is a rich source of tumor cell-derived proteins, thereby, representing a wide array of potential biomarkers. Interestingly, most of the clinical biomarkers in use today (CA 125, CA 15.3, CA 19.9, and PSA) were discovered through tissue culture-based system and tissue extracts. This paper tries to emphasize the tissue culture-based discovery of candidate biomarkers through various mass spectrometry-based proteomic approaches. PMID:23586059

  16. Mass Spectrometry-Based Proteomics in Molecular Diagnostics: Discovery of Cancer Biomarkers Using Tissue Culture

    Directory of Open Access Journals (Sweden)

    Debasish Paul

    2013-01-01

    Full Text Available Accurate diagnosis and proper monitoring of cancer patients remain a key obstacle for successful cancer treatment and prevention. Therein comes the need for biomarker discovery, which is crucial to the current oncological and other clinical practices having the potential to impact the diagnosis and prognosis. In fact, most of the biomarkers have been discovered utilizing the proteomics-based approaches. Although high-throughput mass spectrometry-based proteomic approaches like SILAC, 2D-DIGE, and iTRAQ are filling up the pitfalls of the conventional techniques, still serum proteomics importunately poses hurdle in overcoming a wide range of protein concentrations, and also the availability of patient tissue samples is a limitation for the biomarker discovery. Thus, researchers have looked for alternatives, and profiling of candidate biomarkers through tissue culture of tumor cell lines comes up as a promising option. It is a rich source of tumor cell-derived proteins, thereby, representing a wide array of potential biomarkers. Interestingly, most of the clinical biomarkers in use today (CA 125, CA 15.3, CA 19.9, and PSA were discovered through tissue culture-based system and tissue extracts. This paper tries to emphasize the tissue culture-based discovery of candidate biomarkers through various mass spectrometry-based proteomic approaches.

  17. Schizophrenia genomics and proteomics: are we any closer to biomarker discovery?

    Directory of Open Access Journals (Sweden)

    Kramer Alon

    2009-01-01

    Full Text Available Abstract The field of proteomics has made leaps and bounds in the last 10 years particularly in the fields of oncology and cardiovascular medicine. In comparison, neuroproteomics is still playing catch up mainly due to the relative complexity of neurological disorders. Schizophrenia is one such disorder, believed to be the results of multiple factors both genetic and environmental. Affecting over 2 million people in the US alone, it has become a major clinical and public health concern worldwide. This paper gives an update of schizophrenia biomarker research as reviewed by Lakhan in 2006 and gives us a rundown of the progress made during the last two years. Several studies demonstrate the potential of cerebrospinal fluid as a source of neuro-specific biomarkers. Genetic association studies are making headway in identifying candidate genes for schizophrenia. In addition, metabonomics, bioinformatics, and neuroimaging techniques are aiming to complete the picture by filling in knowledge gaps. International cooperation in the form of genomics and protein databases and brain banks is facilitating research efforts. While none of the recent developments described here in qualifies as biomarker discovery, many are likely to be stepping stones towards that goal.

  18. Lung Cancer Serum Biomarker Discovery Using Label Free LC-MS/MS

    Science.gov (United States)

    Zeng, Xuemei; Hood, Brian L.; Zhao, Ting; Conrads, Thomas P.; Sun, Mai; Gopalakrishnan, Vanathi; Grover, Himanshu; Day, Roger S.; Weissfeld, Joel L.; Wilson, David O.; Siegfried, Jill M.; Bigbee, William L.

    2011-01-01

    Introduction Lung cancer remains the leading cause of cancer-related death with poor survival due to the late stage at which lung cancer is typically diagnosed. Given the clinical burden from lung cancer, and the relatively favorable survival associated with early stage lung cancer, biomarkers for early detection of lung cancer are of important potential clinical benefit. Methods We performed a global lung cancer serum biomarker discovery study using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in a set of pooled non-small cell lung cancer (NSCLC) case sera and matched controls. Immunoaffinity subtraction was used to deplete the top most abundant serum proteins; the remaining serum proteins were subjected to trypsin digestion and analyzed in triplicate by LC-MS/MS. The tandem mass spectrum data were searched against the human proteome database and the resultant spectral counting data were used to estimate the relative abundance of proteins across the case/control serum pools. The spectral counting derived abundances of some candidate biomarker proteins were confirmed with multiple reaction monitoring MS assays. Results A list of 49 differentially abundant candidate proteins was compiled by applying a negative binomial regression model to the spectral counting data (pbiomarkers with statistically significant differential abundance across the lung cancer case/control pools which, when validated, could improve lung cancer early detection. PMID:21304412

  19. The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Hui; Shi, Tujin; Qian, Wei-Jun; Liu, Tao; Kagan, Jacob; Srivastava, Sudhir; Smith, Richard D.; Rodland, Karin D.; Camp, David G.

    2015-12-04

    Mass spectrometry-based proteomics has become an indispensable tool in biomedical research with broad applications ranging from fundamental biology, systems biology, and biomarker discovery. Recent advances in LC-MS have made it become a major technology in clinical applications, especially in cancer biomarker discovery and verification. To overcome the challenges associated with the analysis of clinical samples, such as extremely wide dynamic range of protein concentrations in biofluids and the need to perform high throughput and accurate quantification, significant efforts have been devoted to improve the overall performance of LC-MS bases clinical proteomics. In this review, we summarize the recent advances in LC-MS in the aspect of cancer biomarker discovery and quantification, and discuss its potentials, limitations, and future perspectives.

  20. Metabolic profiling study on potential toxicity and immunotoxicity-biomarker discovery in rats treated with cyclophosphamide using HPLC-ESI-IT-TOF-MS.

    Science.gov (United States)

    Li, Jing; Lin, Wensi; Lin, Weiwei; Xu, Peng; Zhang, Jianmei; Yang, Haisong; Ling, Xiaomei

    2015-05-01

    Despite the recent advances in understanding toxicity mechanism of cyclophosphamide (CTX), the development of biomarkers is still essential. CTX-induced immunotoxicity in rats by a metabonomics approach was investigated using high-performance liquid chromatography coupled with ion trap time-of-flight mass spectrometry (HPLC-ESI-IT-TOF-MS). The rats were orally administered CTX (30 mg/kg/day) for five consecutive days, and on the fifth day samples of urine, thymus and spleen were collected and analyzed. A significant difference in metabolic profiling was observed between the CTX-treated group and the control group by partial least squares-discriminant analysis (PLS-DA), which indicated that metabolic disturbances of immunotoxicity in CTX-treated rats had occurred. One potential biomarker in spleen, three in urine and three in thymus were identified. It is suggested that the CTX-toxicity mechanism may involve the modulation of tryptophan metabolism, phospholipid metabolism and energy metabolism. This research can help to elucidate the CTX-influenced pathways at a low dose and can further help to indicate the patients' pathological status at earlier stages of toxicological progression after drug administration. Copyright © 2014 John Wiley & Sons, Ltd.

  1. Discovery of sexual dimorphisms in metabolic and genetic biomarkers.

    Directory of Open Access Journals (Sweden)

    Kirstin Mittelstrass

    2011-08-01

    Full Text Available Metabolomic profiling and the integration of whole-genome genetic association data has proven to be a powerful tool to comprehensively explore gene regulatory networks and to investigate the effects of genetic variation at the molecular level. Serum metabolite concentrations allow a direct readout of biological processes, and association of specific metabolomic signatures with complex diseases such as Alzheimer's disease and cardiovascular and metabolic disorders has been shown. There are well-known correlations between sex and the incidence, prevalence, age of onset, symptoms, and severity of a disease, as well as the reaction to drugs. However, most of the studies published so far did not consider the role of sexual dimorphism and did not analyse their data stratified by gender. This study investigated sex-specific differences of serum metabolite concentrations and their underlying genetic determination. For discovery and replication we used more than 3,300 independent individuals from KORA F3 and F4 with metabolite measurements of 131 metabolites, including amino acids, phosphatidylcholines, sphingomyelins, acylcarnitines, and C6-sugars. A linear regression approach revealed significant concentration differences between males and females for 102 out of 131 metabolites (p-values<3.8×10(-4; Bonferroni-corrected threshold. Sex-specific genome-wide association studies (GWAS showed genome-wide significant differences in beta-estimates for SNPs in the CPS1 locus (carbamoyl-phosphate synthase 1, significance level: p<3.8×10(-10; Bonferroni-corrected threshold for glycine. We showed that the metabolite profiles of males and females are significantly different and, furthermore, that specific genetic variants in metabolism-related genes depict sexual dimorphism. Our study provides new important insights into sex-specific differences of cell regulatory processes and underscores that studies should consider sex-specific effects in design and

  2. Proteomic biomarker discovery in 1000 human plasma samples with mass spectrometry

    DEFF Research Database (Denmark)

    Cominetti, Ornella; Núñez Galindo, Antonio; Corthésy, John

    2016-01-01

    /validation trials. Compromised study designs and insufficient statistical power are consequences of the to-date still limited capacity of mass spectrometry (MS)-based workflows to handle large numbers of samples in a realistic time frame, while delivering comprehensive proteome coverages. We developed a highly...... automated proteomic biomarker discovery workflow. Herein, we have applied this approach to analyze 1000 plasma samples from the multicentered human dietary intervention study "DiOGenes". Study design, sample randomization, tracking, and logistics were the foundations of our large-scale study. We checked...... the quality of the MS data and provided descriptive statistics. The data set was interrogated for proteins with most stable expression levels in that set of plasma samples. We evaluated standard clinical variables that typically impact forthcoming results and assessed body mass index-associated and gender...

  3. Discovery of serum biomarkers predicting development of a subsequent depressive episode in social anxiety disorder.

    Science.gov (United States)

    Gottschalk, M G; Cooper, J D; Chan, M K; Bot, M; Penninx, B W J H; Bahn, S

    2015-08-01

    Although social anxiety disorder (SAD) is strongly associated with the subsequent development of a depressive disorder (major depressive disorder or dysthymia), no underlying biological risk factors are known. We aimed to identify biomarkers which predict depressive episodes in SAD patients over a 2-year follow-up period. One hundred sixty-five multiplexed immunoassay analytes were investigated in blood serum of 143 SAD patients without co-morbid depressive disorders, recruited within the Netherlands Study of Depression and Anxiety (NESDA). Predictive performance of identified biomarkers, clinical variables and self-report inventories was assessed using receiver operating characteristics curves (ROC) and represented by the area under the ROC curve (AUC). Stepwise logistic regression resulted in the selection of four serum analytes (AXL receptor tyrosine kinase, vascular cell adhesion molecule 1, vitronectin, collagen IV) and four additional variables (Inventory of Depressive Symptomatology, Beck Anxiety Inventory somatic subscale, depressive disorder lifetime diagnosis, BMI) as optimal set of patient parameters. When combined, an AUC of 0.86 was achieved for the identification of SAD individuals who later developed a depressive disorder. Throughout our analyses, biomarkers yielded superior discriminative performance compared to clinical variables and self-report inventories alone. We report the discovery of a serum marker panel with good predictive performance to identify SAD individuals prone to develop subsequent depressive episodes in a naturalistic cohort design. Furthermore, we emphasise the importance to combine biological markers, clinical variables and self-report inventories for disease course predictions in psychiatry. Following replication in independent cohorts, validated biomarkers could help to identify SAD patients at risk of developing a depressive disorder, thus facilitating early intervention. Copyright © 2015 Elsevier Inc. All rights reserved.

  4. Comprehensive mass spectrometry based biomarker discovery and validation platform as applied to diabetic kidney disease

    Directory of Open Access Journals (Sweden)

    Scott D. Bringans

    2017-03-01

    Full Text Available A protein biomarker discovery workflow was applied to plasma samples from patients at different stages of diabetic kidney disease. The proteomics platform produced a panel of significant plasma biomarkers that were statistically scrutinised against the current gold standard tests on an analysis of 572 patients. Five proteins were significantly associated with diabetic kidney disease defined by albuminuria, renal impairment (eGFR and chronic kidney disease staging (CKD Stage ≥1, ROC curve of 0.77. The results prove the suitability and efficacy of the process used, and introduce a biomarker panel with the potential to improve diagnosis of diabetic kidney disease.

  5. The Knowledge-Integrated Network Biomarkers Discovery for Major Adverse Cardiac Events

    Science.gov (United States)

    Jin, Guangxu; Zhou, Xiaobo; Wang, Honghui; Zhao, Hong; Cui, Kemi; Zhang, Xiang-Sun; Chen, Luonan; Hazen, Stanley L.; Li, King; Wong, Stephen T. C.

    2010-01-01

    The mass spectrometry (MS) technology in clinical proteomics is very promising for discovery of new biomarkers for diseases management. To overcome the obstacles of data noises in MS analysis, we proposed a new approach of knowledge-integrated biomarker discovery using data from Major Adverse Cardiac Events (MACE) patients. We first built up a cardiovascular-related network based on protein information coming from protein annotations in Uniprot, protein–protein interaction (PPI), and signal transduction database. Distinct from the previous machine learning methods in MS data processing, we then used statistical methods to discover biomarkers in cardiovascular-related network. Through the tradeoff between known protein information and data noises in mass spectrometry data, we finally could firmly identify those high-confident biomarkers. Most importantly, aided by protein–protein interaction network, that is, cardiovascular-related network, we proposed a new type of biomarkers, that is, network biomarkers, composed of a set of proteins and the interactions among them. The candidate network biomarkers can classify the two groups of patients more accurately than current single ones without consideration of biological molecular interaction. PMID:18665624

  6. A Standardized and Reproducible Urine Preparation Protocol for Cancer Biomarkers Discovery

    Directory of Open Access Journals (Sweden)

    Julia Beretov

    2014-01-01

    Full Text Available A suitable and standardized protein purification technique is essential to maintain consistency and to allow data comparison between proteomic studies for urine biomarker discovery. Ultimately, efforts should be made to standardize urine preparation protocols. The aim of this study was to develop an optimal analytical protocol to achieve maximal protein yield and to ensure that this method was applicable to examine urine protein patterns that distinguish disease and disease-free states. In this pilot study, we compared seven different urine sample preparation methods to remove salts, and to precipitate and isolate urinary proteins. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE profiles showed that the sequential preparation of urinary proteins by combining acetone and trichloroacetic acid (TCA alongside high speed centrifugation (HSC provided the best separation, and retained the most urinary proteins. Therefore, this approach is the preferred method for all further urine protein analysis.

  7. Common Subcluster Mining in Microarray Data for Molecular Biomarker Discovery.

    Science.gov (United States)

    Sadhu, Arnab; Bhattacharyya, Balaram

    2017-10-11

    Molecular biomarkers can be potential facilitators for detection of cancer at early stage which is otherwise difficult through conventional biomarkers. Gene expression data from microarray experiments on both normal and diseased cell samples provide enormous scope to explore genetic relations of disease using computational techniques. Varied patterns of expressions of thousands of genes at different cell conditions along with inherent experimental error make the task of isolating disease related genes challenging. In this paper, we present a data mining method, common subcluster mining (CSM), to discover highly perturbed genes under diseased condition from differential expression patterns. The method builds heap through superposing near centroid clusters from gene expression data of normal samples and extracts its core part. It, thus, isolates genes exhibiting the most stable state across normal samples and constitute a reference set for each centroid. It performs the same operation on datasets from corresponding diseased samples and isolates the genes showing drastic changes in their expression patterns. The method thus finds the disease-sensitive genesets when applied to datasets of lung cancer, prostrate cancer, pancreatic cancer, breast cancer, leukemia and pulmonary arterial hypertension. In majority of the cases, few new genes are found over and above some previously reported ones. Genes with distinct deviations in diseased samples are prospective candidates for molecular biomarkers of the respective disease.

  8. Compact cancer biomarkers discovery using a swarm intelligence feature selection algorithm.

    Science.gov (United States)

    Martinez, Emmanuel; Alvarez, Mario Moises; Trevino, Victor

    2010-08-01

    Biomarker discovery is a typical application from functional genomics. Due to the large number of genes studied simultaneously in microarray data, feature selection is a key step. Swarm intelligence has emerged as a solution for the feature selection problem. However, swarm intelligence settings for feature selection fail to select small features subsets. We have proposed a swarm intelligence feature selection algorithm based on the initialization and update of only a subset of particles in the swarm. In this study, we tested our algorithm in 11 microarray datasets for brain, leukemia, lung, prostate, and others. We show that the proposed swarm intelligence algorithm successfully increase the classification accuracy and decrease the number of selected features compared to other swarm intelligence methods. Copyright © 2010 Elsevier Ltd. All rights reserved.

  9. A Critical Assessment of Feature Selection Methods for Biomarker Discovery in Clinical Proteomics

    NARCIS (Netherlands)

    Christin, Christin; Hoefsloot, Huub C. J.; Smilde, Age K.; Hoekman, B.; Suits, Frank; Bischoff, Rainer; Horvatovich, Peter

    In this paper, we compare the performance of six different feature selection methods for LC-MS-based proteomics and metabolomics biomarker discovery-t test, the Mann-Whitney-Wilcoxon test (mww test), nearest shrunken centroid (NSC), linear support vector machine-recursive features elimination

  10. Biomarker discovery by proteomics : challenges not only for the analytical chemist

    NARCIS (Netherlands)

    Horvatovich, Peter; Govorukhina, Natalia; Bischoff, Rainer

    2006-01-01

    This forum article outlines some of the major challenges in present day biomarker discovery research. Notably the dilemma of reaching sufficient concentration sensitivity versus the required analysis time per sample is highlighted using a model calculation. A number of possible developments and

  11. DIGE and iTRAQ as biomarker discovery tools in aquatic toxicology.

    Science.gov (United States)

    Martyniuk, Christopher J; Alvarez, Sophie; Denslow, Nancy D

    2012-02-01

    Molecular approaches in ecotoxicology have greatly enhanced mechanistic understanding of the impact of aquatic pollutants in organisms. These methods have included high throughput Omics technologies, including quantitative proteomics methods such as 2D differential in-gel electrophoresis (DIGE) and isobaric tagging for relative and absolute quantitation (iTRAQ). These methods are becoming more widely used in ecotoxicology studies to identify and characterize protein bioindicators of adverse effect. In teleost fish, iTRAQ has been used successfully in different fish species (e.g. fathead minnow, goldfish, largemouth bass) and tissues (e.g. hypothalamus and liver) to quantify relative protein abundance. Of interest for ecotoxicology is that many proteins commonly utilized as bioindicators of toxicity or stress are quantifiable using iTRAQ on a larger scale, providing a global baseline of biological effect from which to assess changes in the proteome. This review highlights the successes to date for high throughput quantitative proteomics using DIGE and iTRAQ in aquatic toxicology. Current challenges for the iTRAQ method for biomarker discovery in fish are the high cost and the lack of complete annotated genomes for teleosts. However, the use of protein homology from teleost fishes in protein databases and the introduction of hybrid LTQ-FT (Linear ion trap-Fourier transform) mass spectrometers with high resolution, increased sensitivity, and high mass accuracy are able to improve significantly the protein identification rates. Despite these challenges, initial studies utilizing iTRAQ for ecotoxicoproteomics have exceeded expectations and it is anticipated that the use of non-gel based quantitative proteomics will increase for protein biomarker discovery and for characterization of chemical mode of action. Copyright © 2011 Elsevier Inc. All rights reserved.

  12. Recent mass spectrometry-based proteomics for biomarker discovery in lung cancer, COPD, and asthma.

    Science.gov (United States)

    Fujii, Kiyonaga; Nakamura, Haruhiko; Nishimura, Toshihide

    2017-04-01

    Lung cancer and related diseases have been one of the most common causes of deaths worldwide. Genomic-based biomarkers may hardly reflect the underlying dynamic molecular mechanism of functional protein interactions, which is the center of a disease. Recent developments in mass spectrometry (MS) have made it possible to analyze disease-relevant proteins expressed in clinical specimens by proteomic challenges. Areas covered: To understand the molecular mechanisms of lung cancer and its subtypes, chronic obstructive pulmonary disease (COPD), asthma and others, great efforts have been taken to identify numerous relevant proteins by MS-based clinical proteomic approaches. Since lung cancer is a multifactorial disease that is biologically associated with asthma and COPD among various lung diseases, this study focused on proteomic studies on biomarker discovery using various clinical specimens for lung cancer, COPD, and asthma. Expert commentary: MS-based exploratory proteomics utilizing clinical specimens, which can incorporate both experimental and bioinformatic analysis of protein-protein interaction and also can adopt proteogenomic approaches, makes it possible to reveal molecular networks that are relevant to a disease subgroup and that could differentiate between drug responders and non-responders, good and poor prognoses, drug resistance, and so on.

  13. Enhancement of MS Signal Processing For Improved Cancer Biomarker Discovery

    Science.gov (United States)

    Si, Qian

    Technological advances in proteomics have shown great potential in detecting cancer at the earliest stages. One way is to use the time of flight mass spectroscopy to identify biomarkers, or early disease indicators related to the cancer. Pattern analysis of time of flight mass spectra data from blood and tissue samples gives great hope for the identification of potential biomarkers among the complex mixture of biological and chemical samples for the early cancer detection. One of the keys issues is the pre-processing of raw mass spectra data. A lot of challenges need to be addressed: unknown noise character associated with the large volume of data, high variability in the mass spectroscopy measurements, and poorly understood signal background and so on. This dissertation focuses on developing statistical algorithms and creating data mining tools for computationally improved signal processing for mass spectrometry data. I have introduced an advanced accurate estimate of the noise model and a half-supervised method of mass spectrum data processing which requires little knowledge about the data.

  14. Establishment of Protocols for Global Metabolomics by LC-MS for Biomarker Discovery.

    Directory of Open Access Journals (Sweden)

    Daisuke Saigusa

    Full Text Available Metabolomics is a promising avenue for biomarker discovery. Although the quality of metabolomic analyses, especially global metabolomics (G-Met using mass spectrometry (MS, largely depends on the instrumentation, potential bottlenecks still exist at several basic levels in the metabolomics workflow. Therefore, we established a precise protocol initially for the G-Met analyses of human blood plasma to overcome some these difficulties. In our protocol, samples are deproteinized in a 96-well plate using an automated liquid-handling system, and conducted either using a UHPLC-QTOF/MS system equipped with a reverse phase column or a LC-FTMS system equipped with a normal phase column. A normalization protocol of G-Met data was also developed to compensate for intra- and inter-batch differences, and the variations were significantly reduced along with our normalization, especially for the UHPLC-QTOF/MS data with a C18 reverse-phase column for positive ions. Secondly, we examined the changes in metabolomic profiles caused by the storage of EDTA-blood specimens to identify quality markers for the evaluation of the specimens' pre-analytical conditions. Forty quality markers, including lysophospholipids, dipeptides, fatty acids, succinic acid, amino acids, glucose, and uric acid were identified by G-Met for the evaluation of plasma sample quality and established the equation of calculating the quality score. We applied our quality markers to a small-scale study to evaluate the quality of clinical samples. The G-Met protocols and quality markers established here should prove useful for the discovery and development of biomarkers for a wider range of diseases.

  15. Discovery and Longitudinal Evaluation of Candidate Protein Biomarkers for Disease Recurrence in Prostate Cancer.

    Science.gov (United States)

    Tonry, Claire L; Doherty, Darren; O'Shea, Carmel; Morrissey, Brian; Staunton, Lisa; Flatley, Brian; Shannon, Aoife; Armstrong, John; Pennington, Stephen R

    2015-07-02

    When compared with hormonal therapy alone, treatment with combined hormone and radiation therapy (CHRT) gives improved disease-specific survival outcomes for patients with prostate cancer; however, a significant number of CHRT patients still succumb to recurrent disease. The purpose of this study was to use longitudinal patient samples obtained as part of an ongoing noninterventional clinical trial (ICORG06-15) to identify and evaluate a potential serum protein signature of disease recurrence. Label-free LC-MS/MS based protein discovery was undertaken on depleted serum samples from CHRT patients who showed evidence of disease recurrence (n = 3) and time-matched patient controls (n = 3). A total of 104 proteins showed a significant change between these two groups. Multiple reaction monitoring (MRM) assays were designed for a subset of these proteins as part of a panel of putative prostate cancer biomarkers (41 proteins) for evaluation in longitudinal serum samples. These data revealed significant interpatient variability in individual protein expression between time of diagnosis, disease recurrence, and beyond and serve to highlight the importance of longitudinal patient samples for evaluating the use of candidate protein biomarkers in disease monitoring.

  16. Comprehensive Phenotyping in Multiple Sclerosis: Discovery Based Proteomics and the Current Understanding of Putative Biomarkers

    Directory of Open Access Journals (Sweden)

    Kevin C. O’Connor

    2006-01-01

    Full Text Available Currently, there is no single test for multiple sclerosis (MS. Diagnosis is confirmed through clinical evaluation, abnormalities revealed by magnetic resonance imaging (MRI, and analysis of cerebrospinal fluid (CSF chemistry. The early and accurate diagnosis of the disease, monitoring of progression, and gauging of therapeutic intervention are important but elusive elements of patient care. Moreover, a deeper understanding of the disease pathology is needed, including discovery of accurate biomarkers for MS. Herein we review putative biomarkers of MS relating to neurodegeneration and contributions to neuropathology, with particular focus on autoimmunity. In addition, novel assessments of biomarkers not driven by hypotheses are discussed, featuring our application of advanced proteomics and metabolomics for comprehensive phenotyping of CSF and blood. This strategy allows comparison of component expression levels in CSF and serum between MS and control groups. Examination of these preliminary data suggests that several CSF proteins in MS are differentially expressed, and thus, represent putative biomarkers deserving of further evaluation.

  17. Novel automated biomarker discovery work flow for urinary peptidomics

    DEFF Research Database (Denmark)

    Balog, Crina I.; Hensbergen, Paul J.; Derks, Rico

    2009-01-01

    eluted peptides using MALDI-TOF, Fourier transform ion cyclotron resonance, and liquid chromatography-iontrap mass spectrometry. We determined qualitative and quantitative reproducibility of the system and robustness of the method using BSA digests and urine samples, and we used a selected set of urine......Urine is potentially a rich source of peptide biomarkers, but reproducible, high-throughput peptidomic analysis is often hampered by the inherent variability in factors such as pH and salt concentration. Our goal was to develop a generally applicable, rapid, and robust method for screening large...... samples from Schistosoma haematobium-infected individuals to evaluate clinical applicability. RESULTS: The automated RP-SCX sample cleanup and fractionation system exhibits a high qualitative and quantitative reproducibility, with both BSA standards and urine samples. Because of the relatively high...

  18. Averaged differential expression for the discovery of biomarkers in the blood of patients with prostate cancer.

    Directory of Open Access Journals (Sweden)

    V Uma Bai

    Full Text Available The identification of a blood-based diagnostic marker is a goal in many areas of medicine, including the early diagnosis of prostate cancer. We describe the use of averaged differential display as an efficient mechanism for biomarker discovery in whole blood RNA. The process of averaging reduces the problem of clinical heterogeneity while simultaneously minimizing sample handling.RNA was isolated from the blood of prostate cancer patients and healthy controls. Samples were pooled and subjected to the averaged differential display process. Transcripts present at different levels between patients and controls were purified and sequenced for identification. Transcript levels in the blood of prostate cancer patients and controls were verified by quantitative RT-PCR. Means were compared using a t-test and a receiver-operating curve was generated. The Ring finger protein 19A (RNF19A transcript was identified as having higher levels in prostate cancer patients compared to healthy men through the averaged differential display process. Quantitative RT-PCR analysis confirmed a more than 2-fold higher level of RNF19A mRNA levels in the blood of patients with prostate cancer than in healthy controls (p = 0.0066. The accuracy of distinguishing cancer patients from healthy men using RNF19A mRNA levels in blood as determined by the area under the receiving operator curve was 0.727.Averaged differential display offers a simplified approach for the comprehensive screening of body fluids, such as blood, to identify biomarkers in patients with prostate cancer. Furthermore, this proof-of-concept study warrants further analysis of RNF19A as a clinically relevant biomarker for prostate cancer detection.

  19. Feature Selection Methods for Early Predictive Biomarker Discovery Using Untargeted Metabolomic Data.

    Science.gov (United States)

    Grissa, Dhouha; Pétéra, Mélanie; Brandolini, Marion; Napoli, Amedeo; Comte, Blandine; Pujos-Guillot, Estelle

    2016-01-01

    Untargeted metabolomics is a powerful phenotyping tool for better understanding biological mechanisms involved in human pathology development and identifying early predictive biomarkers. This approach, based on multiple analytical platforms, such as mass spectrometry (MS), chemometrics and bioinformatics, generates massive and complex data that need appropriate analyses to extract the biologically meaningful information. Despite various tools available, it is still a challenge to handle such large and noisy datasets with limited number of individuals without risking overfitting. Moreover, when the objective is focused on the identification of early predictive markers of clinical outcome, few years before occurrence, it becomes essential to use the appropriate algorithms and workflow to be able to discover subtle effects among this large amount of data. In this context, this work consists in studying a workflow describing the general feature selection process, using knowledge discovery and data mining methodologies to propose advanced solutions for predictive biomarker discovery. The strategy was focused on evaluating a combination of numeric-symbolic approaches for feature selection with the objective of obtaining the best combination of metabolites producing an effective and accurate predictive model. Relying first on numerical approaches, and especially on machine learning methods (SVM-RFE, RF, RF-RFE) and on univariate statistical analyses (ANOVA), a comparative study was performed on an original metabolomic dataset and reduced subsets. As resampling method, LOOCV was applied to minimize the risk of overfitting. The best k-features obtained with different scores of importance from the combination of these different approaches were compared and allowed determining the variable stabilities using Formal Concept Analysis. The results revealed the interest of RF-Gini combined with ANOVA for feature selection as these two complementary methods allowed selecting the 48

  20. Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: rationale and design of the epidemiological studies within the IMI DIRECT Consortium

    DEFF Research Database (Denmark)

    Koivula, Robert W.; Heggie, Alison; Barnett, Anna

    2014-01-01

    Aims/hypothesis The DIRECT (Diabetes Research on Patient Stratification) Study is part of a European Union Framework 7 Innovative Medicines Initiative project, a joint undertaking between four industry and 21 academic partners throughout Europe. The Consortium aims to discover and validate biomar...

  1. Nutrition and biomarkers in psychiatry: research on micronutrient deficiencies in schizophrenia, the role of the intestine in the hyperserotonemia of autism, and a method for non-hypothesis driven discovery of biomarkers in urine

    OpenAIRE

    Kemperman, Ramses Franciscus Jacobus

    2007-01-01

    This thesis describes the study of markers of nutrition and intestinal motility in mental disorders with a focus on schizophrenia and autism, and the development, evaluation and application of a biomarker discovery method for urine. The aim of the thesis is to investigate the role of long-chain polyunsaturated fatty acids (LCPUFA), B-vitamins and platelet (PLT) serotonin (5-HT) in schizophrenia and autism. The thesis proposes also that biomarker research in psychiatric disease is of great rel...

  2. Informatics-guided procurement of patient samples for biomarker discovery projects in cancer research.

    Science.gov (United States)

    Suh, K Stephen; Remache, Yvonne K; Patel, Jalpa S; Chen, Steve H; Haystrand, Russell; Ford, Peggy; Shaikh, Anadil M; Wang, Jian; Goy, Andre H

    2009-02-01

    Modern cancer research for biomarker discovery program requires solving several tasks that are directly involved with patient sample procurement. One requirement is to construct a highly efficient workflow on the clinical side for the procurement to generate a consistent supply of high quality samples for research. This undertaking needs a network of interdepartmental collaborations and participations at various levels, including physical human interactions, information technology implementations and a bioinformatics tool that is highly effective and user-friendly to busy clinicians and researchers associated with the sample procurement. Collegial participation that is sequential but continual from one department to another demands dedicated bioinformatics software coordinating between the institutional clinic and the tissue repository facility. Participants in the process include admissions, consenting process, phlebotomy, surgery center and pathology. During this multiple step procedures, clinical data are collected for detailed analytical endpoints to supplement logistics of defining and validating the discovery of biomarkers.

  3. Biomarker discovery by proteomics: challenges not only for the analytical chemist.

    Science.gov (United States)

    Horvatovich, Peter; Govorukhina, Natalia; Bischoff, Rainer

    2006-11-01

    This forum article outlines some of the major challenges in present day biomarker discovery research. Notably the dilemma of reaching sufficient concentration sensitivity versus the required analysis time per sample is highlighted using a model calculation. A number of possible developments and recent research findings are considered to show possible ways out of this dilemma. Finally, the challenge of processing large, megavariate datasets prior to statistical analysis is presented.

  4. Improving feature ranking for biomarker discovery in proteomics mass spectrometry data using genetic programming

    Science.gov (United States)

    Ahmed, Soha; Zhang, Mengjie; Peng, Lifeng

    2014-07-01

    Feature selection on mass spectrometry (MS) data is essential for improving classification performance and biomarker discovery. The number of MS samples is typically very small compared with the high dimensionality of the samples, which makes the problem of biomarker discovery very hard. In this paper, we propose the use of genetic programming for biomarker detection and classification of MS data. The proposed approach is composed of two phases: in the first phase, feature selection and ranking are performed. In the second phase, classification is performed. The results show that the proposed method can achieve better classification performance and biomarker detection rate than the information gain- (IG) based and the RELIEF feature selection methods. Meanwhile, four classifiers, Naive Bayes, J48 decision tree, random forest and support vector machines, are also used to further test the performance of the top ranked features. The results show that the four classifiers using the top ranked features from the proposed method achieve better performance than the IG and the RELIEF methods. Furthermore, GP also outperforms a genetic algorithm approach on most of the used data sets.

  5. Towards Discovery and Targeted Peptide Biomarker Detection Using nanoESI-TIMS-TOF MS

    Science.gov (United States)

    Garabedian, Alyssa; Benigni, Paolo; Ramirez, Cesar E.; Baker, Erin S.; Liu, Tao; Smith, Richard D.; Fernandez-Lima, Francisco

    2017-09-01

    In the present work, the potential of trapped ion mobility spectrometry coupled to TOF mass spectrometry (TIMS-TOF MS) for discovery and targeted monitoring of peptide biomarkers from human-in-mouse xenograft tumor tissue was evaluated. In particular, a TIMS-MS workflow was developed for the detection and quantification of peptide biomarkers using internal heavy analogs, taking advantage of the high mobility resolution (R = 150-250) prior to mass analysis. Five peptide biomarkers were separated, identified, and quantified using offline nanoESI-TIMS-CID-TOF MS; the results were in good agreement with measurements using a traditional LC-ESI-MS/MS proteomics workflow. The TIMS-TOF MS analysis permitted peptide biomarker detection based on accurate mobility, mass measurements, and high sequence coverage for concentrations in the 10-200 nM range, while simultaneously achieving discovery measurements of not initially targeted peptides as markers from the same proteins and, eventually, other proteins. [Figure not available: see fulltext.

  6. The Proteomics Big Challenge for Biomarkers and New Drug-Targets Discovery

    Science.gov (United States)

    Savino, Rocco; Paduano, Sergio; Preianò, Mariaimmacolata; Terracciano, Rosa

    2012-01-01

    In the modern process of drug discovery, clinical, functional and chemical proteomics can converge and integrate synergies. Functional proteomics explores and elucidates the components of pathways and their interactions which, when deregulated, lead to a disease condition. This knowledge allows the design of strategies to target multiple pathways with combinations of pathway-specific drugs, which might increase chances of success and reduce the occurrence of drug resistance. Chemical proteomics, by analyzing the drug interactome, strongly contributes to accelerate the process of new druggable targets discovery. In the research area of clinical proteomics, proteome and peptidome mass spectrometry-profiling of human bodily fluid (plasma, serum, urine and so on), as well as of tissue and of cells, represents a promising tool for novel biomarker and eventually new druggable targets discovery. In the present review we provide a survey of current strategies of functional, chemical and clinical proteomics. Major issues will be presented for proteomic technologies used for the discovery of biomarkers for early disease diagnosis and identification of new drug targets. PMID:23203042

  7. Advancing Urinary Protein Biomarker Discovery by Data-Independent Acquisition on a Quadrupole-Orbitrap Mass Spectrometer.

    Science.gov (United States)

    Muntel, Jan; Xuan, Yue; Berger, Sebastian T; Reiter, Lukas; Bachur, Richard; Kentsis, Alex; Steen, Hanno

    2015-11-06

    The promises of data-independent acquisition (DIA) strategies are a comprehensive and reproducible digital qualitative and quantitative record of the proteins present in a sample. We developed a fast and robust DIA method for comprehensive mapping of the urinary proteome that enables large scale urine proteomics studies. Compared to a data-dependent acquisition (DDA) experiments, our DIA assay doubled the number of identified peptides and proteins per sample at half the coefficients of variation observed for DDA data (DIA = ∼8%; DDA = ∼16%). We also tested different spectral libraries and their effects on overall protein and peptide identifications and their reproducibilities, which provided clear evidence that sample type-specific spectral libraries are preferred for reliable data analysis. To show applicability for biomarker discovery experiments, we analyzed a sample set of 87 urine samples from children seen in the emergency department with abdominal pain. The whole set was analyzed with high proteome coverage (∼1300 proteins/sample) in less than 4 days. The data set revealed excellent biomarker candidates for ovarian cyst and urinary tract infection. The improved throughput and quantitative performance of our optimized DIA workflow allow for the efficient simultaneous discovery and verification of biomarker candidates without the requirement for an early bias toward selected proteins.

  8. Systems Biology Modeling of the Radiation Sensitivity Network: A Biomarker Discovery Platform

    International Nuclear Information System (INIS)

    Eschrich, Steven; Zhang Hongling; Zhao Haiyan; Boulware, David; Lee, Ji-Hyun; Bloom, Gregory; Torres-Roca, Javier F.

    2009-01-01

    Purpose: The discovery of effective biomarkers is a fundamental goal of molecular medicine. Developing a systems-biology understanding of radiosensitivity can enhance our ability of identifying radiation-specific biomarkers. Methods and Materials: Radiosensitivity, as represented by the survival fraction at 2 Gy was modeled in 48 human cancer cell lines. We applied a linear regression algorithm that integrates gene expression with biological variables, including ras status (mut/wt), tissue of origin and p53 status (mut/wt). Results: The biomarker discovery platform is a network representation of the top 500 genes identified by linear regression analysis. This network was reduced to a 10-hub network that includes c-Jun, HDAC1, RELA (p65 subunit of NFKB), PKC-beta, SUMO-1, c-Abl, STAT1, AR, CDK1, and IRF1. Nine targets associated with radiosensitization drugs are linked to the network, demonstrating clinical relevance. Furthermore, the model identified four significant radiosensitivity clusters of terms and genes. Ras was a dominant variable in the analysis, as was the tissue of origin, and their interaction with gene expression but not p53. Overrepresented biological pathways differed between clusters but included DNA repair, cell cycle, apoptosis, and metabolism. The c-Jun network hub was validated using a knockdown approach in 8 human cell lines representing lung, colon, and breast cancers. Conclusion: We have developed a novel radiation-biomarker discovery platform using a systems biology modeling approach. We believe this platform will play a central role in the integration of biology into clinical radiation oncology practice.

  9. Nutrition and biomarkers in psychiatry : research on micronutrient deficiencies in schizophrenia, the role of the intestine in the hyperserotonemia of autism, and a method for non-hypothesis driven discovery of biomarkers in urine

    NARCIS (Netherlands)

    Kemperman, Ramses Franciscus Jacobus

    2007-01-01

    This thesis describes the study of markers of nutrition and intestinal motility in mental disorders with a focus on schizophrenia and autism, and the development, evaluation and application of a biomarker discovery method for urine. The aim of the thesis is to investigate the role of long-chain

  10. Quantitative, multiplexed workflow for deep analysis of human blood plasma and biomarker discovery by mass spectrometry.

    Science.gov (United States)

    Keshishian, Hasmik; Burgess, Michael W; Specht, Harrison; Wallace, Luke; Clauser, Karl R; Gillette, Michael A; Carr, Steven A

    2017-08-01

    Proteomic characterization of blood plasma is of central importance to clinical proteomics and particularly to biomarker discovery studies. The vast dynamic range and high complexity of the plasma proteome have, however, proven to be serious challenges and have often led to unacceptable tradeoffs between depth of coverage and sample throughput. We present an optimized sample-processing pipeline for analysis of the human plasma proteome that provides greatly increased depth of detection, improved quantitative precision and much higher sample analysis throughput as compared with prior methods. The process includes abundant protein depletion, isobaric labeling at the peptide level for multiplexed relative quantification and ultra-high-performance liquid chromatography coupled to accurate-mass, high-resolution tandem mass spectrometry analysis of peptides fractionated off-line by basic pH reversed-phase (bRP) chromatography. The overall reproducibility of the process, including immunoaffinity depletion, is high, with a process replicate coefficient of variation (CV) of 4,500 proteins are detected and quantified per patient sample on average, with two or more peptides per protein and starting from as little as 200 μl of plasma. The approach can be multiplexed up to 10-plex using tandem mass tags (TMT) reagents, further increasing throughput, albeit with some decrease in the number of proteins quantified. In addition, we provide a rapid protocol for analysis of nonfractionated depleted plasma samples analyzed in 10-plex. This provides ∼600 quantified proteins for each of the ten samples in ∼5 h of instrument time.

  11. NMR and pattern recognition methods in metabolomics: From data acquisition to biomarker discovery: A review

    International Nuclear Information System (INIS)

    Smolinska, Agnieszka; Blanchet, Lionel; Buydens, Lutgarde M.C.; Wijmenga, Sybren S.

    2012-01-01

    Highlights: ► Procedures for acquisition of different biofluids by NMR. ► Recent developments in metabolic profiling of different biofluids by NMR are presented. ► The crucial steps involved in data preprocessing and multivariate chemometric analysis are reviewed. ► Emphasis is given on recent findings on Multiple Sclerosis via NMR and pattern recognition methods. - Abstract: Metabolomics is the discipline where endogenous and exogenous metabolites are assessed, identified and quantified in different biological samples. Metabolites are crucial components of biological system and highly informative about its functional state, due to their closeness to functional endpoints and to the organism's phenotypes. Nuclear Magnetic Resonance (NMR) spectroscopy, next to Mass Spectrometry (MS), is one of the main metabolomics analytical platforms. The technological developments in the field of NMR spectroscopy have enabled the identification and quantitative measurement of the many metabolites in a single sample of biofluids in a non-targeted and non-destructive manner. Combination of NMR spectra of biofluids and pattern recognition methods has driven forward the application of metabolomics in the field of biomarker discovery. The importance of metabolomics in diagnostics, e.g. in identifying biomarkers or defining pathological status, has been growing exponentially as evidenced by the number of published papers. In this review, we describe the developments in data acquisition and multivariate analysis of NMR-based metabolomics data, with particular emphasis on the metabolomics of Cerebrospinal Fluid (CSF) and biomarker discovery in Multiple Sclerosis (MScl).

  12. Discovery of potential protein biomarkers of lung adenocarcinoma in bronchoalveolar lavage fluid by SWATH MS data-independent acquisition and targeted data extraction.

    Science.gov (United States)

    Ortea, I; Rodríguez-Ariza, A; Chicano-Gálvez, E; Arenas Vacas, M S; Jurado Gámez, B

    2016-04-14

    Lung cancer currently ranks as the neoplasia with the highest global mortality rate. Although some improvements have been introduced in recent years, new advances in diagnosis are required in order to increase survival rates. New mildly invasive endoscopy-based diagnostic techniques include the collection of bronchoalveolar lavage fluid (BALF), which is discarded after using a portion of the fluid for standard pathological procedures. BALF proteomic analysis can contribute to clinical practice with more sensitive biomarkers, and can complement cytohistological studies by aiding in the diagnosis, prognosis, and subtyping of lung cancer, as well as the monitoring of treatment response. The range of quantitative proteomics methodologies used for biomarker discovery is currently being broadened with the introduction of data-independent acquisition (DIA) analysis-related approaches that address the massive quantitation of the components of a proteome. Here we report for the first time a DIA-based quantitative proteomics study using BALF as the source for the discovery of potential lung cancer biomarkers. The results have been encouraging in terms of the number of identified and quantified proteins. A panel of candidate protein biomarkers for adenocarcinoma in BALF is reported; this points to the activation of the complement network as being strongly over-represented and suggests this pathway as a potential target for lung cancer research. In addition, the results reported for haptoglobin, complement C4-A, and glutathione S-transferase pi are consistent with previous studies, which indicates that these proteins deserve further consideration as potential lung cancer biomarkers in BALF. Our study demonstrates that the analysis of BALF proteins by liquid chromatography-tandem mass spectrometry (LC-MS/MS), combining a simple sample pre-treatment and SWATH DIA MS, is a useful method for the discovery of potential lung cancer biomarkers. Bronchoalveolar lavage fluid (BALF

  13. Banking on the future: biobanking for "omics" approaches to biomarker discovery for Opisthorchis-induced cholangiocarcinoma in Thailand.

    Science.gov (United States)

    Mulvenna, Jason; Yonglitthipagon, Ponlapat; Sripa, Banchob; Brindley, Paul J; Loukas, Alex; Bethony, Jeffrey M

    2012-03-01

    Cholangiocarcinoma (CCA)--bile duct cancer--is associated with late presentation, poses challenges for diagnosis, and has high mortality. These features t highlight the desperate need for biomarkers than can be measured early and in accessible body fluids such as plasma of people at risk for developing this lethal cancer. In this manuscript, we address previous limitations in the discovery stage of biomarker(s) for CCA and indicate how new generation of "omics" technologies could be used for biomarker discovery in Thailand. A key factor in the success of this biomarker program for CCA is the combination of cutting edge technology with strategic sample acquisition by a biorepositories. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  14. Discovery of safety biomarkers for atorvastatin in rat urine using mass spectrometry based metabolomics combined with global and targeted approach

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Bhowmik Salil [Bioanalysis and Biotransformation Research Center, Korea Institute of Science and Technology, P.O. Box 131, Cheongryang, Seoul 130-650 (Korea, Republic of); University of Science and Technology, (305-333) 113 Gwahangno, Yuseong-gu, Daejeon (Korea, Republic of); Lee, Young-Joo; Yi, Hong Jae [College of Pharmacy, Kyung Hee University, Hoegi-dong, Dongdaemun-gu, Seoul 130-791 (Korea, Republic of); Chung, Bong Chul [Bioanalysis and Biotransformation Research Center, Korea Institute of Science and Technology, P.O. Box 131, Cheongryang, Seoul 130-650 (Korea, Republic of); Jung, Byung Hwa, E-mail: jbhluck@kist.re.kr [Bioanalysis and Biotransformation Research Center, Korea Institute of Science and Technology, P.O. Box 131, Cheongryang, Seoul 130-650 (Korea, Republic of); University of Science and Technology, (305-333) 113 Gwahangno, Yuseong-gu, Daejeon (Korea, Republic of)

    2010-02-19

    In order to develop a safety biomarker for atorvastatin, this drug was orally administrated to hyperlipidemic rats, and a metabolomic study was performed. Atorvastatin was given in doses of either 70 mg kg{sup -1} day{sup -1} or 250 mg kg{sup -1} day{sup -1} for a period of 7 days (n = 4 for each group). To evaluate any abnormal effects of the drug, physiological and plasma biochemical parameters were measured and histopathological tests were carried out. Safety biomarkers were derived by comparing these parameters and using both global and targeted metabolic profiling. Global metabolic profiling was performed using liquid chromatography/time of flight/mass spectrometry (LC/TOF/MS) with multivariate data analysis. Several safety biomarker candidates that included various steroids and amino acids were discovered as a result of global metabolic profiling, and they were also confirmed by targeted metabolic profiling using gas chromatography/mass spectrometry (GC/MS) and capillary electrophoresis/mass spectrometry (CE/MS). Serum biochemical and histopathological tests were used to detect abnormal drug reactions in the liver after repeating oral administration of atorvastatin. The metabolic differences between control and the drug-treated groups were compared using PLS-DA score plots. These results were compared with the physiological and plasma biochemical parameters and the results of a histopathological test. Estrone, cortisone, proline, cystine, 3-ureidopropionic acid and histidine were proposed as potential safety biomarkers related with the liver toxicity of atorvastatin. These results indicate that the combined application of global and targeted metabolic profiling could be a useful tool for the discovery of drug safety biomarkers.

  15. Discovery of safety biomarkers for atorvastatin in rat urine using mass spectrometry based metabolomics combined with global and targeted approach

    International Nuclear Information System (INIS)

    Kumar, Bhowmik Salil; Lee, Young-Joo; Yi, Hong Jae; Chung, Bong Chul; Jung, Byung Hwa

    2010-01-01

    In order to develop a safety biomarker for atorvastatin, this drug was orally administrated to hyperlipidemic rats, and a metabolomic study was performed. Atorvastatin was given in doses of either 70 mg kg -1 day -1 or 250 mg kg -1 day -1 for a period of 7 days (n = 4 for each group). To evaluate any abnormal effects of the drug, physiological and plasma biochemical parameters were measured and histopathological tests were carried out. Safety biomarkers were derived by comparing these parameters and using both global and targeted metabolic profiling. Global metabolic profiling was performed using liquid chromatography/time of flight/mass spectrometry (LC/TOF/MS) with multivariate data analysis. Several safety biomarker candidates that included various steroids and amino acids were discovered as a result of global metabolic profiling, and they were also confirmed by targeted metabolic profiling using gas chromatography/mass spectrometry (GC/MS) and capillary electrophoresis/mass spectrometry (CE/MS). Serum biochemical and histopathological tests were used to detect abnormal drug reactions in the liver after repeating oral administration of atorvastatin. The metabolic differences between control and the drug-treated groups were compared using PLS-DA score plots. These results were compared with the physiological and plasma biochemical parameters and the results of a histopathological test. Estrone, cortisone, proline, cystine, 3-ureidopropionic acid and histidine were proposed as potential safety biomarkers related with the liver toxicity of atorvastatin. These results indicate that the combined application of global and targeted metabolic profiling could be a useful tool for the discovery of drug safety biomarkers.

  16. In Silico discovery of transcription factors as potential diagnostic biomarkers of ovarian cancer

    KAUST Repository

    Kaur, Mandeep

    2011-09-19

    Background: Our study focuses on identifying potential biomarkers for diagnosis and early detection of ovarian cancer (OC) through the study of transcription regulation of genes affected by estrogen hormone.Results: The results are based on a set of 323 experimentally validated OC-associated genes compiled from several databases, and their subset controlled by estrogen. For these two gene sets we computationally determined transcription factors (TFs) that putatively regulate transcription initiation. We ranked these TFs based on the number of genes they are likely to control. In this way, we selected 17 top-ranked TFs as potential key regulators and thus possible biomarkers for a set of 323 OC-associated genes. For 77 estrogen controlled genes from this set we identified three unique TFs as potential biomarkers.Conclusions: We introduced a new methodology to identify potential diagnostic biomarkers for OC. This report is the first bioinformatics study that explores multiple transcriptional regulators of OC-associated genes as potential diagnostic biomarkers in connection with estrogen responsiveness. We show that 64% of TF biomarkers identified in our study are validated based on real-time data from microarray expression studies. As an illustration, our method could identify CP2 that in combination with CA125 has been reported to be sensitive in diagnosing ovarian tumors. 2011 Kaur et al; licensee BioMed Central Ltd.

  17. Sample preparation and fractionation for proteome analysis and cancer biomarker discovery by mass spectrometry.

    Science.gov (United States)

    Ahmed, Farid E

    2009-03-01

    Sample preparation and fractionation technologies are one of the most crucial processes in proteomic analysis and biomarker discovery in solubilized samples. Chromatographic or electrophoretic proteomic technologies are also available for separation of cellular protein components. There are, however, considerable limitations in currently available proteomic technologies as none of them allows for the analysis of the entire proteome in a simple step because of the large number of peptides, and because of the wide concentration dynamic range of the proteome in clinical blood samples. The results of any undertaken experiment depend on the condition of the starting material. Therefore, proper experimental design and pertinent sample preparation is essential to obtain meaningful results, particularly in comparative clinical proteomics in which one is looking for minor differences between experimental (diseased) and control (nondiseased) samples. This review discusses problems associated with general and specialized strategies of sample preparation and fractionation, dealing with samples that are solution or suspension, in a frozen tissue state, or formalin-preserved tissue archival samples, and illustrates how sample processing might influence detection with mass spectrometric techniques. Strategies that dramatically improve the potential for cancer biomarker discovery in minimally invasive, blood-collected human samples are also presented.

  18. Automated Sample Preparation Platform for Mass Spectrometry-Based Plasma Proteomics and Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Vilém Guryča

    2014-03-01

    Full Text Available The identification of novel biomarkers from human plasma remains a critical need in order to develop and monitor drug therapies for nearly all disease areas. The discovery of novel plasma biomarkers is, however, significantly hampered by the complexity and dynamic range of proteins within plasma, as well as the inherent variability in composition from patient to patient. In addition, it is widely accepted that most soluble plasma biomarkers for diseases such as cancer will be represented by tissue leakage products, circulating in plasma at low levels. It is therefore necessary to find approaches with the prerequisite level of sensitivity in such a complex biological matrix. Strategies for fractionating the plasma proteome have been suggested, but improvements in sensitivity are often negated by the resultant process variability. Here we describe an approach using multidimensional chromatography and on-line protein derivatization, which allows for higher sensitivity, whilst minimizing the process variability. In order to evaluate this automated process fully, we demonstrate three levels of processing and compare sensitivity, throughput and reproducibility. We demonstrate that high sensitivity analysis of the human plasma proteome is possible down to the low ng/mL or even high pg/mL level with a high degree of technical reproducibility.

  19. Clinical proteomics for liver disease: a promising approach for discovery of novel biomarkers

    Directory of Open Access Journals (Sweden)

    Tsubouchi Hirohito

    2010-12-01

    Full Text Available Abstract Hepatocellular carcinoma (HCC is the fifth most common cancer and advanced hepatic fibrosis is a major risk factor for HCC. Hepatic fibrosis including liver cirrhosis and HCC are mainly induced by persistent hepatitis B or C virus infection, with approximately 500 million people infected with hepatitis B or C virus worldwide. Furthermore, the number of patients with non-alcoholic fatty liver disease (NAFLD has recently increased and NAFLD can progress to cirrhosis and HCC. These chronic liver diseases are major causes of morbidity and mortality, and the identification of non-invasive biomarkers is important for early diagnosis. Recent advancements in quantitative and large-scale proteomic methods could be used to optimize the clinical application of biomarkers. Early diagnosis of HCC and assessment of the stage of hepatic fibrosis or NAFLD can also contribute to more effective therapeutic interventions and an improve prognosis. Furthermore, advancements of proteomic techniques contribute not only to the discovery of clinically useful biomarkers, but also in clarifying the molecular mechanisms of disease pathogenesis by using body fluids, such as serum, and tissue samples and cultured cells. In this review, we report recent advances in quantitative proteomics and several findings focused on liver diseases, including HCC, NAFLD, hepatic fibrosis and hepatitis B or C virus infections.

  20. A Comprehensive Workflow of Mass Spectrometry-Based Untargeted Metabolomics in Cancer Metabolic Biomarker Discovery Using Human Plasma and Urine

    Directory of Open Access Journals (Sweden)

    Jianwen She

    2013-09-01

    Full Text Available Current available biomarkers lack sensitivity and/or specificity for early detection of cancer. To address this challenge, a robust and complete workflow for metabolic profiling and data mining is described in details. Three independent and complementary analytical techniques for metabolic profiling are applied: hydrophilic interaction liquid chromatography (HILIC–LC, reversed-phase liquid chromatography (RP–LC, and gas chromatography (GC. All three techniques are coupled to a mass spectrometer (MS in the full scan acquisition mode, and both unsupervised and supervised methods are used for data mining. The univariate and multivariate feature selection are used to determine subsets of potentially discriminative predictors. These predictors are further identified by obtaining accurate masses and isotopic ratios using selected ion monitoring (SIM and data-dependent MS/MS and/or accurate mass MSn ion tree scans utilizing high resolution MS. A list combining all of the identified potential biomarkers generated from different platforms and algorithms is used for pathway analysis. Such a workflow combining comprehensive metabolic profiling and advanced data mining techniques may provide a powerful approach for metabolic pathway analysis and biomarker discovery in cancer research. Two case studies with previous published data are adapted and included in the context to elucidate the application of the workflow.

  1. NMR and pattern recognition methods in metabolomics: From data acquisition to biomarker discovery: A review

    Energy Technology Data Exchange (ETDEWEB)

    Smolinska, Agnieszka, E-mail: A.Smolinska@science.ru.nl [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands); Blanchet, Lionel [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands); Department of Biochemistry, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen Medical Centre, Nijmegen (Netherlands); Buydens, Lutgarde M.C.; Wijmenga, Sybren S. [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands)

    2012-10-31

    Highlights: Black-Right-Pointing-Pointer Procedures for acquisition of different biofluids by NMR. Black-Right-Pointing-Pointer Recent developments in metabolic profiling of different biofluids by NMR are presented. Black-Right-Pointing-Pointer The crucial steps involved in data preprocessing and multivariate chemometric analysis are reviewed. Black-Right-Pointing-Pointer Emphasis is given on recent findings on Multiple Sclerosis via NMR and pattern recognition methods. - Abstract: Metabolomics is the discipline where endogenous and exogenous metabolites are assessed, identified and quantified in different biological samples. Metabolites are crucial components of biological system and highly informative about its functional state, due to their closeness to functional endpoints and to the organism's phenotypes. Nuclear Magnetic Resonance (NMR) spectroscopy, next to Mass Spectrometry (MS), is one of the main metabolomics analytical platforms. The technological developments in the field of NMR spectroscopy have enabled the identification and quantitative measurement of the many metabolites in a single sample of biofluids in a non-targeted and non-destructive manner. Combination of NMR spectra of biofluids and pattern recognition methods has driven forward the application of metabolomics in the field of biomarker discovery. The importance of metabolomics in diagnostics, e.g. in identifying biomarkers or defining pathological status, has been growing exponentially as evidenced by the number of published papers. In this review, we describe the developments in data acquisition and multivariate analysis of NMR-based metabolomics data, with particular emphasis on the metabolomics of Cerebrospinal Fluid (CSF) and biomarker discovery in Multiple Sclerosis (MScl).

  2. Statistical interpretation of machine learning-based feature importance scores for biomarker discovery.

    Science.gov (United States)

    Huynh-Thu, Vân Anh; Saeys, Yvan; Wehenkel, Louis; Geurts, Pierre

    2012-07-01

    Univariate statistical tests are widely used for biomarker discovery in bioinformatics. These procedures are simple, fast and their output is easily interpretable by biologists but they can only identify variables that provide a significant amount of information in isolation from the other variables. As biological processes are expected to involve complex interactions between variables, univariate methods thus potentially miss some informative biomarkers. Variable relevance scores provided by machine learning techniques, however, are potentially able to highlight multivariate interacting effects, but unlike the p-values returned by univariate tests, these relevance scores are usually not statistically interpretable. This lack of interpretability hampers the determination of a relevance threshold for extracting a feature subset from the rankings and also prevents the wide adoption of these methods by practicians. We evaluated several, existing and novel, procedures that extract relevant features from rankings derived from machine learning approaches. These procedures replace the relevance scores with measures that can be interpreted in a statistical way, such as p-values, false discovery rates, or family wise error rates, for which it is easier to determine a significance level. Experiments were performed on several artificial problems as well as on real microarray datasets. Although the methods differ in terms of computing times and the tradeoff, they achieve in terms of false positives and false negatives, some of them greatly help in the extraction of truly relevant biomarkers and should thus be of great practical interest for biologists and physicians. As a side conclusion, our experiments also clearly highlight that using model performance as a criterion for feature selection is often counter-productive. Python source codes of all tested methods, as well as the MATLAB scripts used for data simulation, can be found in the Supplementary Material.

  3. Quantitative label-free proteomics for discovery of biomarkers in cerebrospinal fluid: assessment of technical and inter-individual variation.

    Directory of Open Access Journals (Sweden)

    Richard J Perrin

    Full Text Available Biomarkers are required for pre-symptomatic diagnosis, treatment, and monitoring of neurodegenerative diseases such as Alzheimer's disease. Cerebrospinal fluid (CSF is a favored source because its proteome reflects the composition of the brain. Ideal biomarkers have low technical and inter-individual variability (subject variance among control subjects to minimize overlaps between clinical groups. This study evaluates a process of multi-affinity fractionation (MAF and quantitative label-free liquid chromatography tandem mass spectrometry (LC-MS/MS for CSF biomarker discovery by (1 identifying reparable sources of technical variability, (2 assessing subject variance and residual technical variability for numerous CSF proteins, and (3 testing its ability to segregate samples on the basis of desired biomarker characteristics.Fourteen aliquots of pooled CSF and two aliquots from six cognitively normal individuals were randomized, enriched for low-abundance proteins by MAF, digested endoproteolytically, randomized again, and analyzed by nano-LC-MS. Nano-LC-MS data were time and m/z aligned across samples for relative peptide quantification. Among 11,433 aligned charge groups, 1360 relatively abundant ones were annotated by MS2, yielding 823 unique peptides. Analyses, including Pearson correlations of annotated LC-MS ion chromatograms, performed for all pairwise sample comparisons, identified several sources of technical variability: i incomplete MAF and keratins; ii globally- or segmentally-decreased ion current in isolated LC-MS analyses; and iii oxidized methionine-containing peptides. Exclusion of these sources yielded 609 peptides representing 81 proteins. Most of these proteins showed very low coefficients of variation (CV<5% whether they were quantified from the mean of all or only the 2 most-abundant peptides. Unsupervised clustering, using only 24 proteins selected for high subject variance, yielded perfect segregation of pooled and

  4. SITC/iSBTc Cancer Immunotherapy Biomarkers Resource Document: Online resources and useful tools - a compass in the land of biomarker discovery

    Directory of Open Access Journals (Sweden)

    Disis Mary L

    2011-09-01

    Full Text Available Abstract Recent positive clinical results in cancer immunotherapy point to the potential of immune-based strategies to provide effective treatment of a variety of cancers. In some patients, the responses to cancer immunotherapy are durable, dramatically extending survival. Extensive research efforts are being made to identify and validate biomarkers that can help identify subsets of cancer patients that will benefit most from these novel immunotherapies. In addition to the clear advantage of such predictive biomarkers, immune biomarkers are playing an important role in the development, clinical evaluation and monitoring of cancer immunotherapies. This Cancer Immunotherapy Resource Document, prepared by the Society for Immunotherapy of Cancer (SITC, formerly the International Society for Biological Therapy of Cancer, iSBTc, provides key references and online resources relevant to the discovery, evaluation and clinical application of immune biomarkers. These key resources were identified by experts in the field who are actively pursuing research in biomarker identification and validation. This organized collection of the most useful references, online resources and tools serves as a compass to guide discovery of biomarkers essential to advancing novel cancer immunotherapies.

  5. Antibody validation of immunohistochemistry for biomarker discovery: Recommendations of a consortium of academic and pharmaceutical based histopathology researchers

    OpenAIRE

    Howat, W.J.; Lewis, A.; Jones, P.; Kampf, C.; Pontén, F.; C.M., van der Loos; Gray, N.; Womack, C.; Warford, A.

    2014-01-01

    As biomarker discovery takes centre-stage, the role of immunohistochemistry within that process is increasing. At the same time, the number of antibodies being produced for ‘‘research use’’ continues to rise and it is important that antibodies to be used as biomarkers are validated for specificity and sensitivity before use. This guideline seeks to provide a stepwise approach for the validation of an antibody for immunohistochemical assays, reflecting the views of a consortium of academic and...

  6. LOBSTAHS: An Adduct-Based Lipidomics Strategy for Discovery and Identification of Oxidative Stress Biomarkers.

    Science.gov (United States)

    Collins, James R; Edwards, Bethanie R; Fredricks, Helen F; Van Mooy, Benjamin A S

    2016-07-19

    Discovery and identification of molecular biomarkers in large LC/MS data sets requires significant automation without loss of accuracy in the compound screening and annotation process. Here, we describe a lipidomics workflow and open-source software package for high-throughput annotation and putative identification of lipid, oxidized lipid, and oxylipin biomarkers in high-mass-accuracy HPLC-MS data. Lipid and oxylipin biomarker screening through adduct hierarchy sequences, or LOBSTAHS, uses orthogonal screening criteria based on adduct ion formation patterns and other properties to identify thousands of compounds while providing the user with a confidence score for each assignment. Assignments are made from one of two customizable databases; the default databases contain 14 068 unique entries. To demonstrate the software's functionality, we screened more than 340 000 mass spectral features from an experiment in which hydrogen peroxide was used to induce oxidative stress in the marine diatom Phaeodactylum tricornutum. LOBSTAHS putatively identified 1969 unique parent compounds in 21 869 features that survived the multistage screening process. While P. tricornutum maintained more than 92% of its core lipidome under oxidative stress, patterns in biomarker distribution and abundance indicated remodeling was both subtle and pervasive. Treatment with 150 μM H2O2 promoted statistically significant carbon-chain elongation across lipid classes, with the strongest elongation accompanying oxidation in moieties of monogalactosyldiacylglycerol, a lipid typically localized to the chloroplast. Oxidative stress also induced a pronounced reallocation of lipidome peak area to triacylglycerols. LOBSTAHS can be used with environmental or experimental data from a variety of systems and is freely available at https://github.com/vanmooylipidomics/LOBSTAHS .

  7. Early-Phase Studies of Biomarkers

    DEFF Research Database (Denmark)

    Pepe, Margaret S.; Janes, Holly; Li, Christopher I.

    2016-01-01

    BACKGROUND: Many cancer biomarker research studies seek to develop markers that can accurately detect or predict future onset of disease. To design and evaluate these studies, one must specify the levels of accuracy sought. However, justified target levels are rarely available. METHODS: We describe...... a way to calculate target levels of sensitivity and specificity for a biomarker intended to be applied in a defined clinical context. The calculation requires knowledge of the prevalence or incidence of cases in the clinical population and the ratio of benefit associated with the clinical consequences...... for ovarian cancer. CONCLUSIONS: It is feasible to specify target levels of biomarker performance that enable evaluation of the potential clinical impact of biomarkers in early-phase studies. Nevertheless, biomarkers meeting the criteria should still be tested rigorously in studies that measure the actual...

  8. Comprehensive serum profiling for the discovery of epithelial ovarian cancer biomarkers.

    Directory of Open Access Journals (Sweden)

    Ping Yip

    Full Text Available FDA-cleared ovarian cancer biomarkers are limited to CA-125 and HE4 for monitoring and recurrence and OVA1, a multivariate panel consisting of CA-125 and four additional biomarkers, for referring patients to a specialist. Due to relatively poor performance of these tests, more accurate and broadly applicable biomarkers are needed. We evaluated the dysregulation of 259 candidate cancer markers in serum samples from 499 patients. Sera were collected prospectively at 11 monitored sites under a single well-defined protocol. All stages of ovarian cancer and common benign gynecological conditions were represented. To ensure consistency and comparability of biomarker comparisons, all measurements were performed on a single platform, at a single site, using a panel of rigorously calibrated, qualified, high-throughput, multiplexed immunoassays and all analyses were conducted using the same software. Each marker was evaluated independently for its ability to differentiate ovarian cancer from benign conditions. A total of 175 markers were dysregulated in the cancer samples. HE4 (AUC=0.933 and CA-125 (AUC=0.907 were the most informative biomarkers, followed by IL-2 receptor α, α1-antitrypsin, C-reactive protein, YKL-40, cellular fibronectin, CA-72-4 and prostasin (AUC>0.800. To improve the discrimination between cancer and benign conditions, a simple multivariate combination of markers was explored using logistic regression. When combined into a single panel, the nine most informative individual biomarkers yielded an AUC value of 0.950, significantly higher than obtained when combining the markers in the OVA1 panel (AUC 0.912. Additionally, at a threshold sensitivity of 90%, the combination of the top 9 markers gave 88.9% specificity compared to 63.4% specificity for the OVA1 markers. Although a blinded validation study has not yet been performed, these results indicate that alternative biomarker combinations might lead to significant improvements in the

  9. Discovery of serum protein biomarkers in drug-free patients with major depressive disorder.

    Science.gov (United States)

    Lee, Min Young; Kim, Eun Young; Kim, Se Hyun; Cho, Kyung-Cho; Ha, Kyooseob; Kim, Kwang Pyo; Ahn, Yong Min

    2016-08-01

    Major depressive disorder (MDD) is a systemic and multifactorial disorder involving complex interactions between genetic predisposition and disturbances of various molecular pathways. Its underlying molecular pathophysiology remains unclear, and no valid and objective diagnostic tools for the condition are available. We performed large-scale proteomic profiling to identify novel peripheral biomarkers implicated in the pathophysiology of MDD in 25 drug-free female MDD patients and 25 healthy controls. First, quantitative serum proteome profiles were obtained and analyzed by liquid chromatography-tandem mass spectrometry using serum samples from 10 MDD patients and 10 healthy controls. Next, candidate biomarker sets, including differentially expressed proteins from the profiling experiment and those identified in the literature, were verified using multiple-reaction monitoring in 25 patients and 25 healthy controls. The final panel of potential biomarkers was selected using multiparametric statistical analysis. We identified a serum biomarker panel consisting of six proteins: apolipoprotein D, apolipoprotein B, vitamin D-binding protein, ceruloplasmin, hornerin, and profilin 1, which could be used to distinguish MDD patients from controls with 68% diagnostic accuracy. Our results suggest that modulation of the immune and inflammatory systems and lipid metabolism are involved in the pathophysiology of MDD. Our findings of functional proteomic changes in the peripheral blood of patients with MDD further clarify the molecular biological pathway underlying depression. Further studies using larger, independent cohorts are needed to verify the role of these candidate biomarkers for the diagnosis of MDD. Copyright © 2016 Elsevier Inc. All rights reserved.

  10. MRM screening/biomarker discovery with linear ion trap MS: a library of human cancer-specific peptides

    International Nuclear Information System (INIS)

    Yang, Xu; Lazar, Iulia M

    2009-01-01

    The discovery of novel protein biomarkers is essential in the clinical setting to enable early disease diagnosis and increase survivability rates. To facilitate differential expression analysis and biomarker discovery, a variety of tandem mass spectrometry (MS/MS)-based protein profiling techniques have been developed. For achieving sensitive detection and accurate quantitation, targeted MS screening approaches, such as multiple reaction monitoring (MRM), have been implemented. MCF-7 breast cancer protein cellular extracts were analyzed by 2D-strong cation exchange (SCX)/reversed phase liquid chromatography (RPLC) separations interfaced to linear ion trap MS detection. MS data were interpreted with the Sequest-based Bioworks software (Thermo Electron). In-house developed Perl-scripts were used to calculate the spectral counts and the representative fragment ions for each peptide. In this work, we report on the generation of a library of 9,677 peptides (p < 0.001), representing ~1,572 proteins from human breast cancer cells, that can be used for MRM/MS-based biomarker screening studies. For each protein, the library provides the number and sequence of detectable peptides, the charge state, the spectral count, the molecular weight, the parameters that characterize the quality of the tandem mass spectrum (p-value, DeltaM, Xcorr, DeltaCn, Sp, no. of matching a, b, y ions in the spectrum), the retention time, and the top 10 most intense product ions that correspond to a given peptide. Only proteins identified by at least two spectral counts are listed. The experimental distribution of protein frequencies, as a function of molecular weight, closely matched the theoretical distribution of proteins in the human proteome, as provided in the SwissProt database. The amino acid sequence coverage of the identified proteins ranged from 0.04% to 98.3%. The highest-abundance proteins in the cellular extract had a molecular weight (MW)<50,000. Preliminary experiments have

  11. Discovery and validation of molecular biomarkers for colorectal adenomas and cancer with application to blood testing.

    Directory of Open Access Journals (Sweden)

    Lawrence C LaPointe

    Full Text Available BACKGROUND & AIMS: Colorectal cancer incidence and deaths are reduced by the detection and removal of early-stage, treatable neoplasia but we lack proven biomarkers sensitive for both cancer and pre-invasive adenomas. The aims of this study were to determine if adenomas and cancers exhibit characteristic patterns of biomarker expression and to explore whether a tissue-discovered (and validated biomarker is differentially expressed in the plasma of patients with colorectal adenomas or cancer. METHODS: Candidate RNA biomarkers were identified by oligonucleotide microarray analysis of colorectal specimens (222 normal, 29 adenoma, 161 adenocarcinoma and 50 colitis and validated in a previously untested cohort of 68 colorectal specimens using a custom-designed oligonucleotide microarray. One validated biomarker, KIAA1199, was assayed using qRT-PCR on plasma extracted RNA from 20 colonoscopy-confirmed healthy controls, 20 patients with adenoma, and 20 with cancer. RESULTS: Genome-wide analysis uncovered reproducible gene expression signatures for both adenomas and cancers compared to controls. 386/489 (79% of the adenoma and 439/529 (83% of the adenocarcinoma biomarkers were validated in independent tissues. We also identified genes differentially expressed in adenomas compared to cancer. KIAA1199 was selected for further analysis based on consistent up-regulation in neoplasia, previous studies and its interest as an uncharacterized gene. Plasma KIAA1199 RNA levels were significantly higher in patients with either cancer or adenoma (31/40 compared to neoplasia-free controls (6/20. CONCLUSIONS: Colorectal neoplasia exhibits characteristic patterns of gene expression. KIAA1199 is differentially expressed in neoplastic tissues and KIAA1199 transcripts are more abundant in the plasma of patients with either cancer or adenoma compared to controls.

  12. Data processing pipelines for comprehensive profiling of proteomics samples by label-free LC MS for biomarker discovery

    NARCIS (Netherlands)

    Christin, Christin; Bischoff, Rainer; Horvatovich, Peter

    2011-01-01

    Label-free quantitative LC-MS profiling of complex body fluids has become an important analytical tool for biomarker and biological knowledge discovery in the past decade. Accurate processing, statistical analysis and validation of acquired data diversified by the different types of mass

  13. Application in pesticide analysis: Liquid chromatography - A review of the state of science for biomarker discovery and identification

    Science.gov (United States)

    Book Chapter 18, titled Application in pesticide analysis: Liquid chromatography - A review of the state of science for biomarker discovery and identification, will be published in the book titled High Performance Liquid Chromatography in Pesticide Residue Analysis (Part of the C...

  14. Translational bioinformatics in mental health: open access data sources and computational biomarker discovery.

    Science.gov (United States)

    Tenenbaum, Jessica D; Bhuvaneshwar, Krithika; Gagliardi, Jane P; Fultz Hollis, Kate; Jia, Peilin; Ma, Liang; Nagarajan, Radhakrishnan; Rakesh, Gopalkumar; Subbian, Vignesh; Visweswaran, Shyam; Zhao, Zhongming; Rozenblit, Leon

    2017-11-27

    Mental illness is increasingly recognized as both a significant cost to society and a significant area of opportunity for biological breakthrough. As -omics and imaging technologies enable researchers to probe molecular and physiological underpinnings of multiple diseases, opportunities arise to explore the biological basis for behavioral health and disease. From individual investigators to large international consortia, researchers have generated rich data sets in the area of mental health, including genomic, transcriptomic, metabolomic, proteomic, clinical and imaging resources. General data repositories such as the Gene Expression Omnibus (GEO) and Database of Genotypes and Phenotypes (dbGaP) and mental health (MH)-specific initiatives, such as the Psychiatric Genomics Consortium, MH Research Network and PsychENCODE represent a wealth of information yet to be gleaned. At the same time, novel approaches to integrate and analyze data sets are enabling important discoveries in the area of mental and behavioral health. This review will discuss and catalog into an organizing framework the increasingly diverse set of MH data resources available, using schizophrenia as a focus area, and will describe novel and integrative approaches to molecular biomarker discovery that make use of mental health data. © The Author 2017. Published by Oxford University Press.

  15. Pairwise protein expression classifier for candidate biomarker discovery for early detection of human disease prognosis

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    Kaur Parminder

    2012-08-01

    Full Text Available Abstract Background An approach to molecular classification based on the comparative expression of protein pairs is presented. The method overcomes some of the present limitations in using peptide intensity data for class prediction for problems such as the detection of a disease, disease prognosis, or for predicting treatment response. Data analysis is particularly challenging in these situations due to sample size (typically tens being much smaller than the large number of peptides (typically thousands. Methods based upon high dimensional statistical models, machine learning or other complex classifiers generate decisions which may be very accurate but can be complex and difficult to interpret in simple or biologically meaningful terms. A classification scheme, called ProtPair, is presented that generates simple decision rules leading to accurate classification which is based on measurement of very few proteins and requires only relative expression values, providing specific targeted hypotheses suitable for straightforward validation. Results ProtPair has been tested against clinical data from 21 patients following a bone marrow transplant, 13 of which progress to idiopathic pneumonia syndrome (IPS. The approach combines multiple peptide pairs originating from the same set of proteins, with each unique peptide pair providing an independent measure of discriminatory power. The prediction rate of the ProtPair for IPS study as measured by leave-one-out CV is 69.1%, which can be very beneficial for clinical diagnosis as it may flag patients in need of closer monitoring. The “top ranked” proteins provided by ProtPair are known to be associated with the biological processes and pathways intimately associated with known IPS biology based on mouse models. Conclusions An approach to biomarker discovery, called ProtPair, is presented. ProtPair is based on the differential expression of pairs of peptides and the associated proteins. Using mass

  16. Systematic biomarker discovery and coordinative validation for different primary nephrotic syndromes using gas chromatography-mass spectrometry.

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    Lee, Jung-Eun; Lee, Yu Ho; Kim, Se-Yun; Kim, Yang Gyun; Moon, Ju-Young; Jeong, Kyung-Hwan; Lee, Tae Won; Ihm, Chun-Gyoo; Kim, Sooah; Kim, Kyoung Heon; Kim, Dong Ki; Kim, Yon Su; Kim, Chan-Duck; Park, Cheol Whee; Lee, Do Yup; Lee, Sang-Ho

    2016-07-01

    The goal of this study is to identify systematic biomarker panel for primary nephrotic syndromes from urine samples by applying a non-target metabolite profiling, and to validate their utility in independent sampling and analysis by multiplex statistical approaches. Nephrotic syndrome (NS) is a nonspecific kidney disorder, which is mostly represented by minimal change disease (MCD), focal segmental glomerulosclerosis (FSGS), and membranous glomerulonephritis (MGN). Since urine metabolites may mirror disease-specific functional perturbations in kidney injury, we examined urine samples for distinctive metabolic changes to identify biomarkers for clinical applications. We developed unbiased multi-component covarianced models from a discovery set with 48 samples (12 healthy controls, 12 MCD, 12 FSGS, and 12 MGN). To extensively validate their diagnostic potential, new batch from 54 patients with primary NS were independently examined a year after. In the independent validation set, the model including citric acid, pyruvic acid, fructose, ethanolamine, and cysteine effectively discriminated each NS using receiver operating characteristic (ROC) analysis except MCD-MGN comparison; nonetheless an additional metabolite multi-composite greatly improved the discrimination power between MCD and MGN. Finally, we proposed the re-constructed metabolic network distinctively dysregulated by the different NSs that may deepen comprehensive understanding of the disease mechanistic, and help the enhanced identification of NS and therapeutic plans for future. Copyright © 2016 Elsevier B.V. All rights reserved.

  17. Approaches to dimensionality reduction in proteomic biomarker studies.

    Science.gov (United States)

    Hilario, Melanie; Kalousis, Alexandros

    2008-03-01

    Mass-spectra based proteomic profiles have received widespread attention as potential tools for biomarker discovery and early disease diagnosis. A major data-analytical problem involved is the extremely high dimensionality (i.e. number of features or variables) of proteomic data, in particular when the sample size is small. This article reviews dimensionality reduction methods that have been used in proteomic biomarker studies. It then focuses on the problem of selecting the most appropriate method for a specific task or dataset, and proposes method combination as a potential alternative to single-method selection. Finally, it points out the potential of novel dimension reduction techniques, in particular those that incorporate domain knowledge through the use of informative priors or causal inference.

  18. Solid-state nanopores: A new platform for DNA biomarker discovery

    Science.gov (United States)

    Marshall, Michael M.

    Solid-state (SS) nanopores emerged as a molecular detection platform in 2001, offering many advantages over their biological counterparts, α-hemolysin nanopores (α-HL). These advantages include better chemical, electrical, mechanical, and thermal stability, as well as size tunability and device integration. In addition, the size of α-HL restricts its application to translocations of single-stranded polynucleotides (ssDNA and ssRNA). This research project focused on developing a SS-nanopore platform for biomarker detection, based on differentiating ssDNA and double-stranded DNA (dsDNA) at the single-molecule scale. Reported dsDNA translocation measurements result in an average residence time of ~ 30 ns/bp, so the temporal resolution required for detection of small DNA duplexes can exceed available bandwidth limitations. To address this issue, several system parameters were explored in order to slow down translocation speed, thereby increasing temporal resolution and signal-to-noise ratio. These parameters included: applied voltage, pH, pore geometry, DNA binding agents, salt composition and concentration, and temperature. Experimental findings showed that SS-nanopores can be precisely fabricated using a controlled helium ion milling technique, acidic conditions cause DNA depurination that results in slower translocation durations, and single-stranded binding proteins (SSBs) bind preferentially to ssDNA, forming complexes with distinct translocation characteristics that permit large (> 7 kb) ds- and ssDNA to be effectively distinguished. Together, these data show that SS-nanopores can serve as a tool to electronically detect the presence and relative concentration of target DNA molecules with ultrahigh sensitivity, thus demonstrating their potential utility as a biomarker discovery platform in both biomedical and environmental applications.

  19. Mass spectrometry in biomarker applications: from untargeted discovery to targeted verification, and implications for platform convergence and clinical application

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Richard D.

    2012-03-01

    It is really only in the last ten years that mass spectrometry (MS) has had a truly significant (but still small) impact on biomedical research. Much of this impact can be attributed to proteomics and its more basic applications. Early biomedical applications have included a number of efforts aimed at developing new biomarkers; however, the success of these endeavors to date have been quite modest - essentially confined to preclinical applications - and have often suffered from combinations of immature technology and hubris. Now that MS-based proteomics is reaching adolescence, it is appropriate to ask if and when biomarker-related applications will extend to the clinical realm, and what developments will be essential for this transition. Biomarker development can be described as a multistage process consisting of discovery, qualification, verification, research assay optimization, validation, and commercialization (1). From a MS perspective, it is possible to 'bin' measurements into 1 of 2 categories - those aimed at discovering potential protein biomarkers and those seeking to verify and validate biomarkers. Approaches in both categories generally involve digesting proteins (e.g., with trypsin) as a first step to yield peptides that can be effectively detected and identified with MS. Discovery-based approaches use broad 'unbiased' or 'undirected' measurements that attempt to cover as many proteins as possible in the hope of revealing promising biomarker candidates. A key challenge with this approach stems from the extremely large dynamic range (i.e., relative stoichiometry) of proteins of potential interest in biofluids such as plasma and the expectation that biomarker proteins of the greatest clinical value for many diseases may very well be present at low relative abundances (2). Protein concentrations in plasma extend from approximately 10{sup 10} pg/mL for albumin to approximately 10 pg/mL and below for interleukins and other

  20. The use of time-resolved fluorescence in gel-based proteomics for improved biomarker discovery

    Science.gov (United States)

    Sandberg, AnnSofi; Buschmann, Volker; Kapusta, Peter; Erdmann, Rainer; Wheelock, Åsa M.

    2010-02-01

    This paper describes a new platform for quantitative intact proteomics, entitled Cumulative Time-resolved Emission 2-Dimensional Gel Electrophoresis (CuTEDGE). The CuTEDGE technology utilizes differences in fluorescent lifetimes to subtract the confounding background fluorescence during in-gel detection and quantification of proteins, resulting in a drastic improvement in both sensitivity and dynamic range compared to existing technology. The platform is primarily designed for image acquisition in 2-dimensional gel electrophoresis (2-DE), but is also applicable to 1-dimensional gel electrophoresis (1-DE), and proteins electroblotted to membranes. In a set of proof-of-principle measurements, we have evaluated the performance of the novel technology using the MicroTime 100 instrument (PicoQuant GmbH) in conjunction with the CyDye minimal labeling fluorochromes (GE Healthcare, Uppsala, Sweden) to perform differential gel electrophoresis (DIGE) analyses. The results indicate that the CuTEDGE technology provides an improvement in the dynamic range and sensitivity of detection of 3 orders of magnitude as compared to current state-of-the-art image acquisition instrumentation available for 2-DE (Typhoon 9410, GE Healthcare). Given the potential dynamic range of 7-8 orders of magnitude and sensitivities in the attomol range, the described invention represents a technological leap in detection of low abundance cellular proteins, which is desperately needed in the field of biomarker discovery.

  1. Urinary candidate biomarker discovery in a rat unilateral ureteral obstruction model.

    Science.gov (United States)

    Yuan, Yuan; Zhang, Fanshuang; Wu, Jianqiang; Shao, Chen; Gao, Youhe

    2015-03-20

    Urine has the potential to become a better source of biomarkers. Urinary proteins are affected by many factors; therefore, differentiating between the variables associated with any particular pathophysiological condition in clinical samples is challenging. To circumvent these problems, simpler systems, such as animal models, should be used to establish a direct relationship between disease progression and urine changes. In this study, a unilateral ureteral obstruction (UUO) model was used to observe tubular injury and the eventual development of renal fibrosis, as well as to identify differential urinary proteins in this process. Urine samples were collected from the residuary ureter linked to the kidney at 1 and 3 weeks after UUO. Five hundred proteins were identified and quantified by LC-MS/MS, out of which 7 and 19 significantly changed in the UUO 1- and 3-week groups, respectively, compared with the sham-operation group. Validation by western blot showed increased levels of Alpha-actinin-1 and Moesin in the UUO 1-week group, indicating that they may serve as candidate biomarkers of renal tubular injury, and significantly increased levels of Vimentin, Annexin A1 and Clusterin in the UUO 3-week group, indicating that they may serve as candidate biomarkers of interstitial fibrosis.

  2. Discovery and identification of potential biomarkers of pediatric Acute Lymphoblastic Leukemia

    Directory of Open Access Journals (Sweden)

    Cui Ziyou

    2009-03-01

    Full Text Available Abstract Background Acute lymphoblastic leukemia (ALL is a common form of cancer in children. Currently, bone marrow biopsy is used for diagnosis. Noninvasive biomarkers for the early diagnosis of pediatric ALL are urgently needed. The aim of this study was to discover potential protein biomarkers for pediatric ALL. Methods Ninety-four pediatric ALL patients and 84 controls were randomly divided into a "training" set (45 ALL patients, 34 healthy controls and a test set (49 ALL patients, 30 healthy controls and 30 pediatric acute myeloid leukemia (AML patients. Serum proteomic profiles were measured using surface-enhanced laser desorption/ionization-time-of-flight mass spectroscopy (SELDI-TOF-MS. A classification model was established by Biomarker Pattern Software (BPS. Candidate protein biomarkers were purified by HPLC, identified by LC-MS/MS and validated using ProteinChip immunoassays. Results A total of 7 protein peaks (9290 m/z, 7769 m/z, 15110 m/z, 7564 m/z, 4469 m/z, 8937 m/z, 8137 m/z were found with differential expression levels in the sera of pediatric ALL patients and controls using SELDI-TOF-MS and then analyzed by BPS to construct a classification model in the "training" set. The sensitivity and specificity of the model were found to be 91.8%, and 90.0%, respectively, in the test set. Two candidate protein peaks (7769 and 9290 m/z were found to be down-regulated in ALL patients, where these were identified as platelet factor 4 (PF4 and pro-platelet basic protein precursor (PBP. Two other candidate protein peaks (8137 and 8937 m/z were found up-regulated in the sera of ALL patients, and these were identified as fragments of the complement component 3a (C3a. Conclusion Platelet factor (PF4, connective tissue activating peptide III (CTAP-III and two fragments of C3a may be potential protein biomarkers of pediatric ALL and used to distinguish pediatric ALL patients from healthy controls and pediatric AML patients. Further studies with

  3. A systematic approach to biomarker discovery; Preamble to "the iSBTc-FDA taskforce on immunotherapy biomarkers"

    Directory of Open Access Journals (Sweden)

    Schendel Dolores

    2008-12-01

    Full Text Available Abstract The International Society for the Biological Therapy of Cancer (iSBTc has initiated in collaboration with the United States Food and Drug Administration (FDA a programmatic look at innovative avenues for the identification of relevant parameters to assist clinical and basic scientists who study the natural course of host/tumor interactions or their response to immune manipulation. The task force has two primary goals: 1 identify best practices of standardized and validated immune monitoring procedures and assays to promote inter-trial comparisons and 2 develop strategies for the identification of novel biomarkers that may enhance our understating of principles governing human cancer immune biology and, consequently, implement their clinical application. Two working groups were created that will report the developed best practices at an NCI/FDA/iSBTc sponsored workshop tied to the annual meeting of the iSBTc to be held in Washington DC in the Fall of 2009. This foreword provides an overview of the task force and invites feedback from readers that might be incorporated in the discussions and in the final document.

  4. microRNA Biomarker Discovery and High-Throughput DNA Sequencing Are Possible Using Long-term Archived Serum Samples.

    Science.gov (United States)

    Rounge, Trine B; Lauritzen, Marianne; Langseth, Hilde; Enerly, Espen; Lyle, Robert; Gislefoss, Randi E

    2015-09-01

    The impacts of long-term storage and varying preanalytical factors on the quality and quantity of DNA and miRNA from archived serum have not been fully assessed. Preanalytical and analytical variations and degradation may introduce bias in representation of DNA and miRNA and may result in loss or corruption of quantitative data. We have evaluated DNA and miRNA quantity, quality, and variability in samples stored up to 40 years using one of the oldest prospective serum collections in the world, the Janus Serumbank, a biorepository dedicated to cancer research. miRNAs are present and stable in archived serum samples frozen at -25°C for at least 40 years. Long-time storage did not reduce miRNA yields; however, varying preanalytical conditions had a significant effect and should be taken into consideration during project design. Of note, 500 μL serum yielded sufficient miRNA for qPCR and small RNA sequencing and on average 650 unique miRNAs were detected in samples from presumably healthy donors. Of note, 500 μL serum yielded sufficient DNA for whole-genome sequencing and subsequent SNP calling, giving a uniform representation of the genomes. DNA and miRNA are stable during long-term storage, making large prospectively collected serum repositories an invaluable source for miRNA and DNA biomarker discovery. Large-scale biomarker studies with long follow-up time are possible utilizing biorepositories with archived serum and state-of-the-art technology. ©2015 American Association for Cancer Research.

  5. Cell surface profiling using high-throughput flow cytometry: a platform for biomarker discovery and analysis of cellular heterogeneity.

    Directory of Open Access Journals (Sweden)

    Craig A Gedye

    Full Text Available Cell surface proteins have a wide range of biological functions, and are often used as lineage-specific markers. Antibodies that recognize cell surface antigens are widely used as research tools, diagnostic markers, and even therapeutic agents. The ability to obtain broad cell surface protein profiles would thus be of great value in a wide range of fields. There are however currently few available methods for high-throughput analysis of large numbers of cell surface proteins. We describe here a high-throughput flow cytometry (HT-FC platform for rapid analysis of 363 cell surface antigens. Here we demonstrate that HT-FC provides reproducible results, and use the platform to identify cell surface antigens that are influenced by common cell preparation methods. We show that multiple populations within complex samples such as primary tumors can be simultaneously analyzed by co-staining of cells with lineage-specific antibodies, allowing unprecedented depth of analysis of heterogeneous cell populations. Furthermore, standard informatics methods can be used to visualize, cluster and downsample HT-FC data to reveal novel signatures and biomarkers. We show that the cell surface profile provides sufficient molecular information to classify samples from different cancers and tissue types into biologically relevant clusters using unsupervised hierarchical clustering. Finally, we describe the identification of a candidate lineage marker and its subsequent validation. In summary, HT-FC combines the advantages of a high-throughput screen with a detection method that is sensitive, quantitative, highly reproducible, and allows in-depth analysis of heterogeneous samples. The use of commercially available antibodies means that high quality reagents are immediately available for follow-up studies. HT-FC has a wide range of applications, including biomarker discovery, molecular classification of cancers, or identification of novel lineage specific or stem cell

  6. Cell surface profiling using high-throughput flow cytometry: a platform for biomarker discovery and analysis of cellular heterogeneity.

    Science.gov (United States)

    Gedye, Craig A; Hussain, Ali; Paterson, Joshua; Smrke, Alannah; Saini, Harleen; Sirskyj, Danylo; Pereira, Keira; Lobo, Nazleen; Stewart, Jocelyn; Go, Christopher; Ho, Jenny; Medrano, Mauricio; Hyatt, Elzbieta; Yuan, Julie; Lauriault, Stevan; Meyer, Mona; Kondratyev, Maria; van den Beucken, Twan; Jewett, Michael; Dirks, Peter; Guidos, Cynthia J; Danska, Jayne; Wang, Jean; Wouters, Bradly; Neel, Benjamin; Rottapel, Robert; Ailles, Laurie E

    2014-01-01

    Cell surface proteins have a wide range of biological functions, and are often used as lineage-specific markers. Antibodies that recognize cell surface antigens are widely used as research tools, diagnostic markers, and even therapeutic agents. The ability to obtain broad cell surface protein profiles would thus be of great value in a wide range of fields. There are however currently few available methods for high-throughput analysis of large numbers of cell surface proteins. We describe here a high-throughput flow cytometry (HT-FC) platform for rapid analysis of 363 cell surface antigens. Here we demonstrate that HT-FC provides reproducible results, and use the platform to identify cell surface antigens that are influenced by common cell preparation methods. We show that multiple populations within complex samples such as primary tumors can be simultaneously analyzed by co-staining of cells with lineage-specific antibodies, allowing unprecedented depth of analysis of heterogeneous cell populations. Furthermore, standard informatics methods can be used to visualize, cluster and downsample HT-FC data to reveal novel signatures and biomarkers. We show that the cell surface profile provides sufficient molecular information to classify samples from different cancers and tissue types into biologically relevant clusters using unsupervised hierarchical clustering. Finally, we describe the identification of a candidate lineage marker and its subsequent validation. In summary, HT-FC combines the advantages of a high-throughput screen with a detection method that is sensitive, quantitative, highly reproducible, and allows in-depth analysis of heterogeneous samples. The use of commercially available antibodies means that high quality reagents are immediately available for follow-up studies. HT-FC has a wide range of applications, including biomarker discovery, molecular classification of cancers, or identification of novel lineage specific or stem cell markers.

  7. In vitro biomarker discovery in the parasitic flatworm Fasciola hepatica for monitoring chemotherapeutic treatment

    Directory of Open Access Journals (Sweden)

    Russell M. Morphew

    2014-06-01

    Full Text Available The parasitic flatworm Fasciola hepatica is a global food security risk. With no vaccines, the sustainability of triclabendazole (TCBZ is threatened by emerging resistance. F. hepatica excretory/secretory (ES products can be detected in host faeces and used to estimate TCBZ success and failure. However, there are no faecal based molecular diagnostics dedicated to assessing drug failure or resistance to TCBZ in the field. Utilising in vitro maintenance and sub-proteomic approaches two TCBZ stress ES protein response fingerprints were identified: markers of non-killing and lethal doses. This study provides candidate protein/peptide biomarkers to validate for detection of TCBZ failure and resistance.

  8. Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach

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    Parida Shreemanta K

    2010-01-01

    Full Text Available Abstract Background For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on estimation of gene expression signals for homogeneous cell populations, e.g. by applying micro-dissection, fluorescence activated cell sorting, or in-silico deconfounding. We studied feasibility and validity of a non-negative matrix decomposition algorithm using experimental gene expression data for blood and sorted cells from the same donor samples. Our objective was to optimize the algorithm regarding detection of differentially expressed genes and to enable its use for classification in the difficult scenario of reversely regulated genes. This would be of importance for the identification of candidate biomarkers in heterogeneous tissues. Results Experimental data and simulation studies involving noise parameters estimated from these data revealed that for valid detection of differential gene expression, quantile normalization and use of non-log data are optimal. We demonstrate the feasibility of predicting proportions of constituting cell types from gene expression data of single samples, as a prerequisite for a deconfounding-based classification approach. Classification cross-validation errors with and without using deconfounding results are reported as well as sample-size dependencies. Implementation of the algorithm, simulation and analysis scripts are available. Conclusions The deconfounding algorithm without decorrelation using quantile normalization on non-log data is proposed for biomarkers that are difficult to detect, and for cases where confounding by varying proportions of cell types is the suspected reason. In this case, a deconfounding ranking approach can be used as a powerful alternative to, or complement of, other statistical learning approaches to define candidate biomarkers for molecular diagnosis and prediction in biomedicine, in

  9. Using MALDI-IMS and MRM to stablish a pipeline for discovery and validation of tumor neovasculature biomarker candidates. — EDRN Public Portal

    Science.gov (United States)

    In an effort to circumvent the limitations associated with biomarker discovery workflows involving cell lines and cell cultures, histology-directed MALDI protein profiling and imaging mass spectrometry will be used for identification of vascular endothelial biomarkers suitable for early prostate cancer detection by CEUS targeted molecular imaging

  10. Biomarker discovery for early detection of hepatocellular carcinoma in hepatitis C-infected patients.

    Science.gov (United States)

    Mustafa, Mehnaz G; Petersen, John R; Ju, Hyunsu; Cicalese, Luca; Snyder, Ned; Haidacher, Sigmund J; Denner, Larry; Elferink, Cornelis

    2013-12-01

    monitoring of HCC. Future multiplexing of SRM assays for other candidate biomarkers is envisioned to develop a biomarker panel for subsequent verification and validation studies.

  11. Automated Morphological and Morphometric Analysis of Mass Spectrometry Imaging Data: Application to Biomarker Discovery

    Science.gov (United States)

    Picard de Muller, Gaël; Ait-Belkacem, Rima; Bonnel, David; Longuespée, Rémi; Stauber, Jonathan

    2017-12-01

    Mass spectrometry imaging datasets are mostly analyzed in terms of average intensity in regions of interest. However, biological tissues have different morphologies with several sizes, shapes, and structures. The important biological information, contained in this highly heterogeneous cellular organization, could be hidden by analyzing the average intensities. Finding an analytical process of morphology would help to find such information, describe tissue model, and support identification of biomarkers. This study describes an informatics approach for the extraction and identification of mass spectrometry image features and its application to sample analysis and modeling. For the proof of concept, two different tissue types (healthy kidney and CT-26 xenograft tumor tissues) were imaged and analyzed. A mouse kidney model and tumor model were generated using morphometric - number of objects and total surface - information. The morphometric information was used to identify m/z that have a heterogeneous distribution. It seems to be a worthwhile pursuit as clonal heterogeneity in a tumor is of clinical relevance. This study provides a new approach to find biomarker or support tissue classification with more information. [Figure not available: see fulltext.

  12. SWATHtoMRM: Development of High-Coverage Targeted Metabolomics Method Using SWATH Technology for Biomarker Discovery.

    Science.gov (United States)

    Zha, Haihong; Cai, Yuping; Yin, Yandong; Wang, Zhuozhong; Li, Kang; Zhu, Zheng-Jiang

    2018-03-02

    The complexity of metabolome presents a great analytical challenge for quantitative metabolite profiling, and restricts the application of metabolomics in biomarker discovery. Targeted metabolomics using multiple-reaction monitoring (MRM) technique has excellent capability for quantitative analysis, but suffers from the limited metabolite coverage. To address this challenge, we developed a new strategy, namely, SWATHtoMRM, which utilizes the broad coverage of SWATH-MS technology to develop high-coverage targeted metabolomics method. Specifically, SWATH-MS technique was first utilized to untargeted profile one pooled biological sample and to acquire the MS 2 spectra for all metabolites. Then, SWATHtoMRM was used to extract the large-scale MRM transitions for targeted analysis with coverage as high as 1000-2000 metabolites. Then, we demonstrated the advantages of SWATHtoMRM method in quantitative analysis such as coverage, reproducibility, sensitivity, and dynamic range. Finally, we applied our SWATHtoMRM approach to discover potential metabolite biomarkers for colorectal cancer (CRC) diagnosis. A high-coverage targeted metabolomics method with 1303 metabolites in one injection was developed to profile colorectal cancer tissues from CRC patients. A total of 20 potential metabolite biomarkers were discovered and validated for CRC diagnosis. In plasma samples from CRC patients, 17 out of 20 potential biomarkers were further validated to be associated with tumor resection, which may have a great potential in assessing the prognosis of CRC patients after tumor resection. Together, the SWATHtoMRM strategy provides a new way to develop high-coverage targeted metabolomics method, and facilitates the application of targeted metabolomics in disease biomarker discovery. The SWATHtoMRM program is freely available on the Internet ( http://www.zhulab.cn/software.php ).

  13. Blood diagnostic biomarkers for major depressive disorder using multiplex DNA methylation profiles: discovery and validation.

    Science.gov (United States)

    Numata, Shusuke; Ishii, Kazuo; Tajima, Atsushi; Iga, Jun-ichi; Kinoshita, Makoto; Watanabe, Shinya; Umehara, Hidehiro; Fuchikami, Manabu; Okada, Satoshi; Boku, Shuken; Hishimoto, Akitoyo; Shimodera, Shinji; Imoto, Issei; Morinobu, Shigeru; Ohmori, Tetsuro

    2015-01-01

    Aberrant DNA methylation in the blood of patients with major depressive disorder (MDD) has been reported in several previous studies. However, no comprehensive studies using medication-free subjects with MDD have been conducted. Furthermore, the majority of these previous studies has been limited to the analysis of the CpG sites in CpG islands (CGIs) in the gene promoter regions. The main aim of the present study is to identify DNA methylation markers that distinguish patients with MDD from non-psychiatric controls. Genome-wide DNA methylation profiling of peripheral leukocytes was conducted in two set of samples, a discovery set (20 medication-free patients with MDD and 19 controls) and a replication set (12 medication-free patients with MDD and 12 controls), using Infinium HumanMethylation450 BeadChips. Significant diagnostic differences in DNA methylation were observed at 363 CpG sites in the discovery set. All of these loci demonstrated lower DNA methylation in patients with MDD than in the controls, and most of them (85.7%) were located in the CGIs in the gene promoter regions. We were able to distinguish patients with MDD from the control subjects with high accuracy in the discriminant analysis using the top DNA methylation markers. We also validated these selected DNA methylation markers in the replication set. Our results indicate that multiplex DNA methylation markers may be useful for distinguishing patients with MDD from non-psychiatric controls.

  14. Proteomics and metabolomics for mechanistic insights and biomarker discovery in cardiovascular disease.

    Science.gov (United States)

    Barallobre-Barreiro, Javier; Chung, Yuen-Li; Mayr, Manuel

    2013-08-01

    In the last decade, proteomics and metabolomics have contributed substantially to our understanding of cardiovascular diseases. The unbiased assessment of pathophysiological processes without a priori assumptions complements other molecular biology techniques that are currently used in a reductionist approach. In this review, we highlight some of the "omics" methods used to assess protein and metabolite changes in cardiovascular disease. A discrete biological function is very rarely attributed to a single molecule; more often it is the combined input of many proteins. In contrast to the reductionist approach, in which molecules are studied individually, "omics" platforms allow the study of more complex interactions in biological systems. Combining proteomics and metabolomics to quantify changes in metabolites and their corresponding enzymes will advance our understanding of pathophysiological mechanisms and aid the identification of novel biomarkers for cardiovascular disease. Copyright © 2013 Sociedad Española de Cardiología. Published by Elsevier Espana. All rights reserved.

  15. Guidelines for Biomarker of Food Intake Reviews (BFIRev): how to conduct an extensive literature search for biomarker of food intake discovery.

    Science.gov (United States)

    Praticò, Giulia; Gao, Qian; Scalbert, Augustin; Vergères, Guy; Kolehmainen, Marjukka; Manach, Claudine; Brennan, Lorraine; Pedapati, Sri Harsha; Afman, Lydia A; Wishart, David S; Vázquez-Fresno, Rosa; Lacueva, Cristina Andres; Garcia-Aloy, Mar; Verhagen, Hans; Feskens, Edith J M; Dragsted, Lars O

    2018-01-01

    Identification of new biomarkers of food and nutrient intake has developed fast over the past two decades and could potentially provide important new tools for compliance monitoring and dietary intake assessment in nutrition and health science. In recent years, metabolomics has played an important role in identifying a large number of putative biomarkers of food intake (BFIs). However, the large body of scientific literature on potential BFIs outside the metabolomics area should also be taken into account. In particular, we believe that extensive literature reviews should be conducted and that the quality of all suggested biomarkers should be systematically evaluated. In order to cover the literature on BFIs in the most appropriate and consistent manner, there is a need for appropriate guidelines on this topic. These guidelines should build upon guidelines in related areas of science while targeting the special needs of biomarker methodology. This document provides a guideline for conducting an extensive literature search on BFIs, which will provide the basis to systematically validate BFIs. This procedure will help to prioritize future work on the identification of new potential biomarkers and on validating these as well as other biomarker candidates, thereby providing better tools for future studies in nutrition and health.

  16. Guidelines for Biomarker of Food Intake Reviews (BFIRev: how to conduct an extensive literature search for biomarker of food intake discovery

    Directory of Open Access Journals (Sweden)

    Giulia Praticò

    2018-02-01

    Full Text Available Abstract Identification of new biomarkers of food and nutrient intake has developed fast over the past two decades and could potentially provide important new tools for compliance monitoring and dietary intake assessment in nutrition and health science. In recent years, metabolomics has played an important role in identifying a large number of putative biomarkers of food intake (BFIs. However, the large body of scientific literature on potential BFIs outside the metabolomics area should also be taken into account. In particular, we believe that extensive literature reviews should be conducted and that the quality of all suggested biomarkers should be systematically evaluated. In order to cover the literature on BFIs in the most appropriate and consistent manner, there is a need for appropriate guidelines on this topic. These guidelines should build upon guidelines in related areas of science while targeting the special needs of biomarker methodology. This document provides a guideline for conducting an extensive literature search on BFIs, which will provide the basis to systematically validate BFIs. This procedure will help to prioritize future work on the identification of new potential biomarkers and on validating these as well as other biomarker candidates, thereby providing better tools for future studies in nutrition and health.

  17. Probing the O-glycoproteome of Gastric Cancer Cell Lines for Biomarker Discovery

    DEFF Research Database (Denmark)

    Vieira Campos, Diana Alexandra; Freitas, Daniela; Gomes, Joana

    2015-01-01

    Circulating O-glycoproteins shed from cancer cells represent important serum biomarkers for diagnostic and prognostic purposes. We have recently shown that selective detection of cancer-associated aberrant glycoforms of circulating O-glycoprotein biomarkers can increase specificity of cancer biom...

  18. Predictive biomarker discovery through the parallel integration of clinical trial and functional genomics datasets

    DEFF Research Database (Denmark)

    Swanton, C.; Larkin, J.M.; Gerlinger, M.

    2010-01-01

    -cancer agents. The consortium focuses on the identification of reliable predictive biomarkers to approved agents with anti-angiogenic activity for which no reliable predictive biomarkers exist: sunitinib, a multi-targeted tyrosine kinase inhibitor and everolimus, a mammalian target of rapamycin (mTOR) pathway...

  19. Antibody validation of immunohistochemistry for biomarker discovery: recommendations of a consortium of academic and pharmaceutical based histopathology researchers.

    Science.gov (United States)

    Howat, William J; Lewis, Arthur; Jones, Phillipa; Kampf, Caroline; Pontén, Fredrik; van der Loos, Chris M; Gray, Neil; Womack, Chris; Warford, Anthony

    2014-11-01

    As biomarker discovery takes centre-stage, the role of immunohistochemistry within that process is increasing. At the same time, the number of antibodies being produced for "research use" continues to rise and it is important that antibodies to be used as biomarkers are validated for specificity and sensitivity before use. This guideline seeks to provide a stepwise approach for the validation of an antibody for immunohistochemical assays, reflecting the views of a consortium of academic and pharmaceutical based histopathology researchers. We propose that antibodies are placed into a tier system, level 1-3, based on evidence of their usage in immunohistochemistry, and that the degree of validation required is proportionate to their place on that tier. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  20. From SOMAmer-based biomarker discovery to diagnostic and clinical applications: a SOMAmer-based, streamlined multiplex proteomic assay.

    Directory of Open Access Journals (Sweden)

    Stephan Kraemer

    Full Text Available Recently, we reported a SOMAmer-based, highly multiplexed assay for the purpose of biomarker identification. To enable seamless transition from highly multiplexed biomarker discovery assays to a format suitable and convenient for diagnostic and life-science applications, we developed a streamlined, plate-based version of the assay. The plate-based version of the assay is robust, sensitive (sub-picomolar, rapid, can be highly multiplexed (upwards of 60 analytes, and fully automated. We demonstrate that quantification by microarray-based hybridization, Luminex bead-based methods, and qPCR are each compatible with our platform, further expanding the breadth of proteomic applications for a wide user community.

  1. Metabolomics as a Tool for Discovery of Biomarkers of Autism Spectrum Disorder in the Blood Plasma of Children

    Science.gov (United States)

    West, Paul R.; Amaral, David G.; Bais, Preeti; Smith, Alan M.; Egnash, Laura A.; Ross, Mark E.; Palmer, Jessica A.; Fontaine, Burr R.; Conard, Kevin R.; Corbett, Blythe A.; Cezar, Gabriela G.; Donley, Elizabeth L. R.; Burrier, Robert E.

    2014-01-01

    Background The diagnosis of autism spectrum disorder (ASD) at the earliest age possible is important for initiating optimally effective intervention. In the United States the average age of diagnosis is 4 years. Identifying metabolic biomarker signatures of ASD from blood samples offers an opportunity for development of diagnostic tests for detection of ASD at an early age. Objectives To discover metabolic features present in plasma samples that can discriminate children with ASD from typically developing (TD) children. The ultimate goal is to identify and develop blood-based ASD biomarkers that can be validated in larger clinical trials and deployed to guide individualized therapy and treatment. Methods Blood plasma was obtained from children aged 4 to 6, 52 with ASD and 30 age-matched TD children. Samples were analyzed using 5 mass spectrometry-based methods designed to orthogonally measure a broad range of metabolites. Univariate, multivariate and machine learning methods were used to develop models to rank the importance of features that could distinguish ASD from TD. Results A set of 179 statistically significant features resulting from univariate analysis were used for multivariate modeling. Subsets of these features properly classified the ASD and TD samples in the 61-sample training set with average accuracies of 84% and 86%, and with a maximum accuracy of 81% in an independent 21-sample validation set. Conclusions This analysis of blood plasma metabolites resulted in the discovery of biomarkers that may be valuable in the diagnosis of young children with ASD. The results will form the basis for additional discovery and validation research for 1) determining biomarkers to develop diagnostic tests to detect ASD earlier and improve patient outcomes, 2) gaining new insight into the biochemical mechanisms of various subtypes of ASD 3) identifying biomolecular targets for new modes of therapy, and 4) providing the basis for individualized treatment

  2. Discovery and identification of potential biomarkers for alcohol-induced oxidative stress based on cellular metabolomics.

    Science.gov (United States)

    Hu, Qingping; Wei, Jianteng; Liu, Yewei; Fei, Xiulan; Hao, Yuwei; Pei, Dong; Di, Duolong

    2017-07-01

    Biomarkers involved in alcohol-induced oxidative stress play an important role in alcoholic liver disease prevention and diagnosis. Alcohol-induced oxidative stress in human liver L-02 cells was used to discover the potential biomarkers. Metabolites from L-02 cells induced by alcohol were measured by high-performance liquid chromatography and mass spectrometry. Fourteen metabolites that allowed discrimination between control and model groups were discovered by multivariate statistical data analysis (i.e. principal components analysis, orthogonal partial least-squares discriminate analysis). Based on the retention time, UV spectrum and LC-MS findings of the samples and compared with the authentic standards, eight biomarkers involved in alcohol-induced oxidative stress, namely, malic acid, oxidized glutathione, γ-glutamyl-cysteinyl-glycine, adenosine triphosphate, phenylalanine, adenosine monophosphate, nitrotyrosine and tryptophan, were identified. These biomarkers offered important targets for disease diagnosis and other researches. Copyright © 2016 John Wiley & Sons, Ltd.

  3. Emerging field of metabolomics: big promise for cancer biomarker identification and drug discovery.

    Science.gov (United States)

    Patel, Seema; Ahmed, Shadab

    2015-03-25

    Most cancers are lethal and metabolic alterations are considered a hallmark of this deadly disease. Genomics and proteomics have contributed vastly to understand cancer biology. Still there are missing links as downstream to them molecular divergence occurs. Metabolomics, the omic science that furnishes a dynamic portrait of metabolic profile is expected to bridge these gaps and boost cancer research. Metabolites being the end products are more stable than mRNAs or proteins. Previous studies have shown the efficacy of metabolomics in identifying biomarkers associated with diagnosis, prognosis and treatment of cancer. Metabolites are highly informative about the functional status of the biological system, owing to their proximity to organismal phenotypes. Scores of publications have reported about high-throughput data generation by cutting-edge analytic platforms (mass spectrometry and nuclear magnetic resonance). Further sophisticated statistical softwares (chemometrics) have enabled meaningful information extraction from the metabolomic data. Metabolomics studies have demonstrated the perturbation in glycolysis, tricarboxylic acid cycle, choline and fatty acid metabolism as traits of cancer cells. This review discusses the latest progress in this field, the future trends and the deficiencies to be surmounted for optimally implementation in oncology. The authors scoured through the most recent, high-impact papers archived in Pubmed, ScienceDirect, Wiley and Springer databases to compile this review to pique the interest of researchers towards cancer metabolomics. Copyright © 2014 Elsevier B.V. All rights reserved.

  4. Application of a high throughput method of biomarker discovery to improvement of the EarlyCDT(®-Lung Test.

    Directory of Open Access Journals (Sweden)

    Isabel K Macdonald

    Full Text Available BACKGROUND: The National Lung Screening Trial showed that CT screening for lung cancer led to a 20% reduction in mortality. However, CT screening has a number of disadvantages including low specificity. A validated autoantibody assay is available commercially (EarlyCDT®-Lung to aid in the early detection of lung cancer and risk stratification in patients with pulmonary nodules detected by CT. Recent advances in high throughput (HTP cloning and expression methods have been developed into a discovery pipeline to identify biomarkers that detect autoantibodies. The aim of this study was to demonstrate the successful clinical application of this strategy to add to the EarlyCDT-Lung panel in order to improve its sensitivity and specificity (and hence positive predictive value, (PPV. METHODS AND FINDINGS: Serum from two matched independent cohorts of lung cancer patients were used (n = 100 and n = 165. Sixty nine proteins were initially screened on an abridged HTP version of the autoantibody ELISA using protein prepared on small scale by a HTP expression and purification screen. Promising leads were produced in shake flask culture and tested on the full assay. These results were analyzed in combination with those from the EarlyCDT-Lung panel in order to provide a set of re-optimized cut-offs. Five proteins that still displayed cancer/normal differentiation were tested for reproducibility and validation on a second batch of protein and a separate patient cohort. Addition of these proteins resulted in an improvement in the sensitivity and specificity of the test from 38% and 86% to 49% and 93% respectively (PPV improvement from 1 in 16 to 1 in 7. CONCLUSION: This is a practical example of the value of investing resources to develop a HTP technology. Such technology may lead to improvement in the clinical utility of the EarlyCDT--Lung test, and so further aid the early detection of lung cancer.

  5. Isolation and characterization of urinary extracellular vesicles: implications for biomarker discovery.

    Science.gov (United States)

    Merchant, Michael L; Rood, Ilse M; Deegens, Jeroen K J; Klein, Jon B

    2017-12-01

    Urine is a valuable diagnostic medium and, with the discovery of urinary extracellular vesicles, is viewed as a dynamic bioactive fluid. Extracellular vesicles are lipid-enclosed structures that can be classified into three categories: exosomes, microvesicles (or ectosomes) and apoptotic bodies. This classification is based on the mechanisms by which membrane vesicles are formed: fusion of multivesicular bodies with the plasma membranes (exosomes), budding of vesicles directly from the plasma membrane (microvesicles) or those shed from dying cells (apoptotic bodies). During their formation, urinary extracellular vesicles incorporate various cell-specific components (proteins, lipids and nucleic acids) that can be transferred to target cells. The rigour needed for comparative studies has fueled the search for optimal approaches for their isolation, purification, and characterization. RNA, the newest extracellular vesicle component to be discovered, has received substantial attention as an extracellular vesicle therapeutic, and compelling evidence suggests that ex vivo manipulation of microRNA composition may have uses in the treatment of kidney disorders. The results of these studies are building the case that urinary extracellular vesicles act as mediators of renal pathophysiology. As the field of extracellular vesicle studies is burgeoning, this Review focuses on primary data obtained from studies of human urine rather than on data from studies of laboratory animals or cultured immortalized cells.

  6. Discovery and characterization of potential prognostic biomarkers for dengue hemorrhagic fever.

    Science.gov (United States)

    Poole-Smith, B Katherine; Gilbert, Alexa; Gonzalez, Andrea L; Beltran, Manuela; Tomashek, Kay M; Ward, Brian J; Hunsperger, Elizabeth A; Ndao, Momar

    2014-12-01

    Half a million patients are hospitalized with severe dengue every year, many of whom would die without timely, appropriate clinical intervention. The majority of dengue cases are uncomplicated; however, 2-5% progress to severe dengue. Severe dengue cases have been reported with increasing frequency over the last 30 years. To discover biomarkers for severe dengue, we used surface-enhanced laser desorption/ionization time-of-flight mass spectrometry to analyze dengue virus positive serum samples from the acute phase of infection. Using this method, 16 proteins were identified as candidate biomarkers for severe dengue. From these 16 biomarkers, three candidates were selected for confirmation by enzyme-linked immunosorbent assay and Western blot: vitronectin (Vtn, 55.1 kDa), hemopexin (Hx, 52.4 kDa), and serotransferrin (Tf, 79.2 kDa). Vitronectin, Hx, and Tf best differentiated between dengue and severe dengue. © The American Society of Tropical Medicine and Hygiene.

  7. Use of biomarkers in the discovery of novel anti-schizophrenia drugs

    DEFF Research Database (Denmark)

    Mikkelsen, Jens D.; Thomsen, Morten S.; Hansen, Henrik

    2010-01-01

    Schizophrenia is characterized by a diverse symptomatology that often includes positive, cognitive and negative symptoms. Current anti-schizophrenic drugs act at multiple receptors, but little is known about how each of these receptors contributes to their mechanisms of action. Screening of novel...... anti-schizophrenic drug candidates targeting single receptors will be based on biomarker assays that measure signalling pathways, transcriptional factors, epigenetic mechanisms and synaptic function and translate these effects to behavioural effects in animals and humans. This review discusses current...... states of the validity of biomarkers in the identification of novel anti-schizophrenic drug candidates....

  8. Mass Spectrometry-Based Serum Proteomics for Biomarker Discovery and Validation.

    Science.gov (United States)

    Bhosale, Santosh D; Moulder, Robert; Kouvonen, Petri; Lahesmaa, Riitta; Goodlett, David R

    2017-01-01

    Blood protein measurements are used frequently in the clinic in the assessment of patient health. Nevertheless, there remains the need for new biomarkers with better diagnostic specificities. With the advent of improved technology for bioanalysis and the growth of biobanks including collections from specific disease risk cohorts, the plasma proteome has remained a target of proteomics research toward the characterization of disease-related biomarkers. The following protocol presents a workflow for serum/plasma proteomics including details of sample preparation both with and without immunoaffinity depletion of the most abundant plasma proteins and methodology for selected reaction monitoring mass spectrometry validation.

  9. Searching for new biomarkers in ovarian cancer patients: Rationale and design of a retrospective study under the Mermaid III project

    Directory of Open Access Journals (Sweden)

    Julie L. Hentze

    2017-12-01

    A thorough investigation of biomarkers in ovarian cancer, including large numbers of different markers, has never been done before. Besides from improving diagnosis and treatment, other outcomes could be markers for screening, knowledge of the molecular aspects of cancer and the discovery of new drugs. Moreover, biomarkers are a prerequisite for the development of precision medicine. This study will attack the ovarian cancer problem from several angles, thereby increasing the chance of successfully contributing to saving lives.

  10. voomDDA: discovery of diagnostic biomarkers and classification of RNA-seq data

    Directory of Open Access Journals (Sweden)

    Gokmen Zararsiz

    2017-10-01

    Full Text Available RNA-Seq is a recent and efficient technique that uses the capabilities of next-generation sequencing technology for characterizing and quantifying transcriptomes. One important task using gene-expression data is to identify a small subset of genes that can be used to build diagnostic classifiers particularly for cancer diseases. Microarray based classifiers are not directly applicable to RNA-Seq data due to its discrete nature. Overdispersion is another problem that requires careful modeling of mean and variance relationship of the RNA-Seq data. In this study, we present voomDDA classifiers: variance modeling at the observational level (voom extensions of the nearest shrunken centroids (NSC and the diagonal discriminant classifiers. VoomNSC is one of these classifiers and brings voom and NSC approaches together for the purpose of gene-expression based classification. For this purpose, we propose weighted statistics and put these weighted statistics into the NSC algorithm. The VoomNSC is a sparse classifier that models the mean-variance relationship using the voom method and incorporates voom’s precision weights into the NSC classifier via weighted statistics. A comprehensive simulation study was designed and four real datasets are used for performance assessment. The overall results indicate that voomNSC performs as the sparsest classifier. It also provides the most accurate results together with power-transformed Poisson linear discriminant analysis, rlog transformed support vector machines and random forests algorithms. In addition to prediction purposes, the voomNSC classifier can be used to identify the potential diagnostic biomarkers for a condition of interest. Through this work, statistical learning methods proposed for microarrays can be reused for RNA-Seq data. An interactive web application is freely available at http://www.biosoft.hacettepe.edu.tr/voomDDA/.

  11. voomDDA: discovery of diagnostic biomarkers and classification of RNA-seq data.

    Science.gov (United States)

    Zararsiz, Gokmen; Goksuluk, Dincer; Klaus, Bernd; Korkmaz, Selcuk; Eldem, Vahap; Karabulut, Erdem; Ozturk, Ahmet

    2017-01-01

    RNA-Seq is a recent and efficient technique that uses the capabilities of next-generation sequencing technology for characterizing and quantifying transcriptomes. One important task using gene-expression data is to identify a small subset of genes that can be used to build diagnostic classifiers particularly for cancer diseases. Microarray based classifiers are not directly applicable to RNA-Seq data due to its discrete nature. Overdispersion is another problem that requires careful modeling of mean and variance relationship of the RNA-Seq data. In this study, we present voomDDA classifiers: variance modeling at the observational level (voom) extensions of the nearest shrunken centroids (NSC) and the diagonal discriminant classifiers. VoomNSC is one of these classifiers and brings voom and NSC approaches together for the purpose of gene-expression based classification. For this purpose, we propose weighted statistics and put these weighted statistics into the NSC algorithm. The VoomNSC is a sparse classifier that models the mean-variance relationship using the voom method and incorporates voom's precision weights into the NSC classifier via weighted statistics. A comprehensive simulation study was designed and four real datasets are used for performance assessment. The overall results indicate that voomNSC performs as the sparsest classifier. It also provides the most accurate results together with power-transformed Poisson linear discriminant analysis, rlog transformed support vector machines and random forests algorithms. In addition to prediction purposes, the voomNSC classifier can be used to identify the potential diagnostic biomarkers for a condition of interest. Through this work, statistical learning methods proposed for microarrays can be reused for RNA-Seq data. An interactive web application is freely available at http://www.biosoft.hacettepe.edu.tr/voomDDA/.

  12. Discovery of serum biomarkers predicting development of a subsequent depressive episode in social anxiety disorder

    NARCIS (Netherlands)

    Gottschalk, M.G.; Cooper, J.D.; Chan, M.K.; Bot, M.; Penninx, B.W.J.H.; Bann, S.

    2015-01-01

    Although social anxiety disorder (SAD) is strongly associated with the subsequent development of a depressive disorder (major depressive disorder or dysthymia), no underlying biological risk factors are known. We aimed to identify biomarkers which predict depressive episodes in SAD patients over a

  13. Cardiovascular biomarkers in clinical studies of type 2 diabetes

    DEFF Research Database (Denmark)

    Baldassarre, M P A; Andersen, A; Consoli, A

    2018-01-01

    When planning cardiovascular studies in type 2 diabetes, selection of cardiovascular biomarkers is a complex issue. Since the pathophysiology of cardiovascular disease in type 2 diabetes is multifactorial, ideally, the selected cardiovascular biomarkers should cover all aspects of the known...... biomarkers and 3) novel biomarkers (oxidative stress and endothelial dysfunction biomarkers). Within each category we present the currently best validated biomarkers with special focus on the population of interest (type 2 diabetes). For each individual biomarker, the physiological role, the validation...... in the general population and in type 2 diabetes, analytical methodology, the modifying factors, the effects of glucose-lowering drugs, and the interpretation are discussed. This approach will provide clinical researchers with all information necessary for planning, conducting and interpreting results from...

  14. Strategies to design clinical studies to identify predictive biomarkers in cancer research.

    Science.gov (United States)

    Perez-Gracia, Jose Luis; Sanmamed, Miguel F; Bosch, Ana; Patiño-Garcia, Ana; Schalper, Kurt A; Segura, Victor; Bellmunt, Joaquim; Tabernero, Josep; Sweeney, Christopher J; Choueiri, Toni K; Martín, Miguel; Fusco, Juan Pablo; Rodriguez-Ruiz, Maria Esperanza; Calvo, Alfonso; Prior, Celia; Paz-Ares, Luis; Pio, Ruben; Gonzalez-Billalabeitia, Enrique; Gonzalez Hernandez, Alvaro; Páez, David; Piulats, Jose María; Gurpide, Alfonso; Andueza, Mapi; de Velasco, Guillermo; Pazo, Roberto; Grande, Enrique; Nicolas, Pilar; Abad-Santos, Francisco; Garcia-Donas, Jesus; Castellano, Daniel; Pajares, María J; Suarez, Cristina; Colomer, Ramon; Montuenga, Luis M; Melero, Ignacio

    2017-02-01

    The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework-the DESIGN guidelines-to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  15. Sparse multi-block PLSR for biomarker discovery when integrating data from LC-MS and NMR metabolomics

    DEFF Research Database (Denmark)

    Karaman, Ibrahim; Nørskov, Natalja; Yde, Christian Clement

    2015-01-01

    The objective of this study was to implement a multivariate method which analyzes multi-block metabolomics data and performs variable selection in order to discover potential biomarkers, simultaneously. We call this method sparse multi-block partial least squares regression (Sparse MBPLSR...... and stability of the selected variables. The performance of the method was evaluated using a simulated data set and a multi-block data set from a dietary intervention study with pigs used as model for humans. The objective of the study was to investigate the biochemical effects in plasma after dietary...... intervention with breads varying in types of dietary fiber and to identify potential biomarkers. By introducing Sparse MBPLSR, we aimed at identifying the biomarkers where data from LC–MS and NMR instruments were analyzed simultaneously and therefore in addition we intended to explore the relationships among...

  16. The use of multiplexed MRM for the discovery of biomarkers to differentiate iron-deficiency anemia from anemia of inflammation.

    Science.gov (United States)

    Domanski, Dominik; Cohen Freue, Gabriela V; Sojo, Luis; Kuzyk, Michael A; Ratkay, Leslie; Parker, Carol E; Goldberg, Y Paul; Borchers, Christoph H

    2012-06-27

    In this study we demonstrate the use of a multiplexed MRM-based assay to distinguish among normal (NL) and iron-metabolism disorder mouse models, particularly, iron-deficiency anemia (IDA), inflammation (INFL), and inflammation and anemia (INFL+IDA). Our initial panel of potential biomarkers was based on the analysis of 14 proteins expressed by candidate genes involved in iron transport and metabolism. Based on this study, we were able to identify a panel of 8 biomarker proteins: apolipoprotein A4 (APO4), transferrin, transferrin receptor 1, ceruloplasmin, haptoglobin, lactoferrin, hemopexin, and matrix metalloproteinase-8 (MMP8) that clearly distinguish among the normal and disease models. Within this set of proteins, transferrin showed the best individual classification accuracy over all samples (72%) and within the NL group (94%). Compared to the best single-protein biomarker, transferrin, the use of the composite 8-protein biomarker panel improved the classification accuracy from 94% to 100% in the NL group, from 50% to 72% in the INFL group, from 66% to 96% in the IDA group, and from 79% to 83% in the INFL+IDA group. Based on these findings, validation of the utility of this potentially important biomarker panel in human samples in an effort to differentiate IDA, inflammation, and combinations thereof, is now warranted. This article is part of a Special Section entitled: Understanding genome regulation and genetic diversity by mass spectrometry. Copyright © 2011 Elsevier B.V. All rights reserved.

  17. TOFwave: reproducibility in biomarker discovery from time-of-flight mass spectrometry data.

    Science.gov (United States)

    Chierici, Marco; Albanese, Davide; Franceschi, Pietro; Furlanello, Cesare

    2012-11-01

    Many are the sources of variability that can affect reproducibility of disease biomarkers from time-of-flight (TOF) Mass Spectrometry (MS) data. Here we present TOFwave, a complete software pipeline for TOF-MS biomarker identification, that limits the impact of parameter tuning along the whole chain of preprocessing and model selection modules. Peak profiles are obtained by a preprocessing based on Continuous Wavelet Transform (CWT), coupled with a machine learning protocol aimed at avoiding selection bias effects. Only two parameters (minimum peak width and a signal to noise cutoff) have to be explicitly set. The TOFwave pipeline is built on top of the mlpy Python package. Examples on Matrix-Assisted Laser Desorption and Ionization (MALDI) TOF datasets are presented. Software prototype, datasets and details to replicate results in this paper can be found at http://mlpy.sf.net/tofwave/.

  18. Use of biomarkers in the discovery of novel anti-schizophrenia drugs

    DEFF Research Database (Denmark)

    Mikkelsen, Jens D; Thomsen, Morten S; Hansen, Henrik H

    2010-01-01

    Schizophrenia is characterized by a diverse symptomatology that often includes positive, cognitive and negative symptoms. Current anti-schizophrenic drugs act at multiple receptors, but little is known about how each of these receptors contributes to their mechanisms of action. Screening of novel...... anti-schizophrenic drug candidates targeting single receptors will be based on biomarker assays that measure signalling pathways, transcriptional factors, epigenetic mechanisms and synaptic function and translate these effects to behavioural effects in animals and humans. This review discusses current...

  19. Efficient high-throughput discovery of large peptidic hormones and biomarkers.

    Science.gov (United States)

    Taylor, Steven W; Andon, Nancy L; Bilakovics, James M; Lowe, Carolyn; Hanley, Michael R; Pittner, Richard; Ghosh, Soumitra S

    2006-07-01

    A novel approach is presented for the simultaneous identification and relative quantification of secreted peptides, particularly those that have been historically difficult to analyze in a concerted manner. Peptides exceeding 60 residues with various degrees of post-translational modification were identified on a liquid chromatographic time scale. The approach demonstrates high efficiency pattern-based recognition analysis of complex neuroendocrine peptide sets and enables rapid identification of biomarkers from biological material.

  20. A Comprehensive Tool and Analytical Pathway for Differential Molecular Profiling and Biomarker Discovery

    Science.gov (United States)

    2014-10-20

    Approved for public release; distribution unlimited. 88ABW-2015-1753; Cleared 07 April 2015 coupled to a Waters QToF ® hybrid tandem quadrupole/time of...profiling low level kidney biomarkers in the F344 rat model. Importation of the raw QToF MS data files and subsequent analysis of the aligned and...background level previously established by our group for the QToF Micro). 27 Distribution A. Approved for public release; distribution unlimited. 88ABW

  1. Isolation and characterization of urinary extracellular vesicles: implications for biomarker discovery

    NARCIS (Netherlands)

    Merchant, M.L.; Rood, I.M.; Deegens, J.K.J.; Klein, J.B.

    2017-01-01

    Urine is a valuable diagnostic medium and, with the discovery of urinary extracellular vesicles, is viewed as a dynamic bioactive fluid. Extracellular vesicles are lipid-enclosed structures that can be classified into three categories: exosomes, microvesicles (or ectosomes) and apoptotic bodies.

  2. The Discovery of Novel Genomic, Transcriptomic, and Proteomic Biomarkers in Cardiovascular and Peripheral Vascular Disease: The State of the Art

    Directory of Open Access Journals (Sweden)

    Stefano de Franciscis

    2016-01-01

    Full Text Available Cardiovascular disease (CD and peripheral vascular disease (PVD are leading causes of mortality and morbidity in western countries and also responsible of a huge burden in terms of disability, functional decline, and healthcare costs. Biomarkers are measurable biological elements that reflect particular physiological or pathological states or predisposition towards diseases and they are currently widely studied in medicine and especially in CD. In this context, biomarkers can also be used to assess the severity or the evolution of several diseases, as well as the effectiveness of particular therapies. Genomics, transcriptomics, and proteomics have opened new windows on disease phenomena and may permit in the next future an effective development of novel diagnostic and prognostic medicine in order to better prevent or treat CD. This review will consider the current evidence of novel biomarkers with clear implications in the improvement of risk assessment, prevention strategies, and medical decision making in the field of CD.

  3. Imaging biomarker roadmap for cancer studies

    NARCIS (Netherlands)

    O'Connor, James P. B.; Aboagye, Eric O.; Adams, Judith E.; Aerts, Hugo J. W. L.; Barrington, Sally F.; Beer, Ambros J.; Boellaard, Ronald; Bohndiek, Sarah E.; Brady, Michael; Brown, Gina; Buckley, David L.; Chenevert, Thomas L.; Clarke, Laurence P.; Collette, Sandra; Cook, Gary J.; Desouza, Nandita M.; Dickson, John C.; Dive, Caroline; Evelhoch, Jeffrey L.; Faivre-Finn, Corinne; Gallagher, Ferdia A.; Gilbert, Fiona J.; Gillies, Robert J.; Goh, Vicky; Griffiths, J. R.; Groves, Ashley M.; Halligan, Steve; Harris, Adrian L.; Hawkes, David J.; Hoekstra, Otto S.; Huang, Erich P.; Hutton, Brian F.; Jackson, Edward F.; Jayson, Gordon C.; Jones, Andrew; Koh, Dow-Mu; Lacombe, Denis; Lambin, Philippe; Lassau, Nathalie; Leach, Martin O.; Lee, Ting-Yim; Leen, Edward L.; Lewis, Jason S.; Liu, Yan; Lythgoe, Mark F.; Manoharan, Prakash; Maxwell, Ross J.; Miles, Kenneth A.; Morgan, Bruno; Morris, Steve; Ng, Tony; Padhani, Anwar R.; Parker, Geoff J. M.; Partridge, Mike; Pathak, Arvind P.; Peet, Andrew C.; Punwani, Shonit; Reynolds, Andrew R.; Robinson, Simon P.; Shankar, Lalitha K.; Sharma, Ricky A.; Soloviev, Dmitry; Stroobants, Sigrid G.; Sullivan, Daniel C.; Taylor, Stuart A.; Tofts, Paul S.; Tozer, Gillian M.; van Herk, Marcel B.; Walker-Samuel, Simon; Wason, James; Williams, Kaye J.; Workman, Paul; Yankeelov, Thomas E.; Brindle, Kevin M.; McShane, Lisa M.; Jackson, Alan; Waterton, John C.

    Imaging biomarkers (IBs) are integral to the routine management of patients with cancer. IBs used daily in oncology include clinical TNM stage, objective response and left ventricular ejection fraction. Other CT, MRI, PET and ultrasonography biomarkers are used extensively in cancer research and

  4. Protein biomarker discovery and fast monitoring for the identification and detection of Anisakids by parallel reaction monitoring (PRM) mass spectrometry.

    Science.gov (United States)

    Carrera, Mónica; Gallardo, José M; Pascual, Santiago; González, Ángel F; Medina, Isabel

    2016-06-16

    Anisakids are fish-borne parasites that are responsible for a large number of human infections and allergic reactions around the world. World health organizations and food safety authorities aim to control and prevent this emerging health problem. In the present work, a new method for the fast monitoring of these parasites is described. The strategy is divided in three steps: (i) purification of thermostable proteins from fish-borne parasites (Anisakids), (ii) in-solution HIFU trypsin digestion and (iii) monitoring of several peptide markers by parallel reaction monitoring (PRM) mass spectrometry. This methodology allows the fast detection of Anisakids in Biomarker Discovery and the Fast Monitoring for the identification and detection of Anisakids in fishery products. The strategy is based on the purification of thermostable proteins, the use of accelerated in-solution trypsin digestions under an ultrasonic field provided by High-Intensity Focused Ultrasound (HIFU) and the monitoring of several peptide biomarkers by Parallel Reaction Monitoring (PRM) Mass Spectrometry in a linear ion trap mass spectrometer. The workflow allows the unequivocal detection of Anisakids, in <2h. The present strategy constitutes the fastest method for Anisakids detection, whose application in the food quality control area, could provide to the authorities an effective and rapid method to guarantee the safety to the consumers. Copyright © 2016 Elsevier B.V. All rights reserved.

  5. Multiple reaction monitoring (MRM)-profiling for biomarker discovery applied to human polycystic ovarian syndrome.

    Science.gov (United States)

    Cordeiro, Fernanda B; Ferreira, Christina R; Sobreira, Tiago Jose P; Yannell, Karen E; Jarmusch, Alan K; Cedenho, Agnaldo P; Lo Turco, Edson G; Cooks, R Graham

    2017-09-15

    We describe multiple reaction monitoring (MRM)-profiling, which provides accelerated discovery of discriminating molecular features, and its application to human polycystic ovary syndrome (PCOS) diagnosis. The discovery phase of the MRM-profiling seeks molecular features based on some prior knowledge of the chemical functional groups likely to be present in the sample. It does this through use of a limited number of pre-chosen and chemically specific neutral loss and/or precursor ion MS/MS scans. The output of the discovery phase is a set of precursor/product transitions. In the screening phase these MRM transitions are used to interrogate multiple samples (hence the name MRM-profiling). MRM-profiling was applied to follicular fluid samples of 22 controls and 29 clinically diagnosed PCOS patients. Representative samples were delivered by flow injection to a triple quadrupole mass spectrometer set to perform a number of pre-chosen and chemically specific neutral loss and/or precursor ion MS/MS scans. The output of this discovery phase was a set of 1012 precursor/product transitions. In the screening phase each individual sample was interrogated for these MRM transitions. Principal component analysis (PCA) and receiver operating characteristic (ROC) curves were used for statistical analysis. To evaluate the method's performance, half the samples were used to build a classification model (testing set) and half were blinded (validation set). Twenty transitions were used for the classification of the blind samples, most of them (N = 19) showed lower abundances in the PCOS group and corresponded to phosphatidylethanolamine (PE) and phosphatidylserine (PS) lipids. Agreement of 73% with clinical diagnosis was found when classifying the 26 blind samples. MRM-profiling is a supervised method characterized by its simplicity, speed and the absence of chromatographic separation. It can be used to rapidly isolate discriminating molecules in healthy/disease conditions by

  6. Profiling of circulating microRNAs for prostate cancer biomarker discovery

    DEFF Research Database (Denmark)

    Haldrup, Christa; Kosaka, Nobuyoshi; Ochiya, Takahiro

    2014-01-01

    Prostate cancer (PC) is the most frequent cancer in men in the Western world. Currently, serum prostate-specific antigen levels and digital rectal examinations are used to indicate the need for diagnostic prostate biopsy, but lack in specificity and sensitivity. Thus, many men undergo unnecessary...... performed genome-wide miRNA profiling of serum samples from 13 benign prostatic hyperplasia (BPH) control patients and 31 PC patients. Furthermore, we carefully reviewed the literature on circulating miRNA biomarkers for PC. Our results confirmed the de-regulation of miR-141 and miR-375, two of the most...

  7. Biomarker discovery with SELDI-TOF MS in human urine associated with early renal injury: evaluation with computational analytical tools.

    NARCIS (Netherlands)

    Vanhoutte, K.J.A.; Laarakkers, C.M.; Marchiori, E.; Pickkers, P.; Wetzels, J.F.M.; Willems, J.L.; Heuvel, L.P.W.J. van den; Russel, F.G.M.; Masereeuw, R.

    2007-01-01

    BACKGROUND: Urine proteomics is one of the key emerging technologies to discover new biomarkers for renal disease, which may be used in the early diagnosis, prognosis and treatment of patients. In the present study, we validated surface-enhanced laser desorption/ionization time-of-flight mass

  8. “Omics”-Informed Drug and Biomarker Discovery: Opportunities, Challenges and Future Perspectives

    Directory of Open Access Journals (Sweden)

    Holly Matthews

    2016-09-01

    Full Text Available The pharmaceutical industry faces unsustainable program failure despite significant increases in investment. Dwindling discovery pipelines, rapidly expanding R&D budgets and increasing regulatory control, predict significant gaps in the future drug markets. The cumulative duration of discovery from concept to commercialisation is unacceptably lengthy, and adds to the deepening crisis. Existing animal models predicting clinical translations are simplistic, highly reductionist and, therefore, not fit for purpose. The catastrophic consequences of ever-increasing attrition rates are most likely to be felt in the developing world, where resistance acquisition by killer diseases like malaria, tuberculosis and HIV have paced far ahead of new drug discovery. The coming of age of Omics-based applications makes available a formidable technological resource to further expand our knowledge of the complexities of human disease. The standardisation, analysis and comprehensive collation of the “data-heavy” outputs of these sciences are indeed challenging. A renewed focus on increasing reproducibility by understanding inherent biological, methodological, technical and analytical variables is crucial if reliable and useful inferences with potential for translation are to be achieved. The individual Omics sciences—genomics, transcriptomics, proteomics and metabolomics—have the singular advantage of being complimentary for cross validation, and together could potentially enable a much-needed systems biology perspective of the perturbations underlying disease processes. If current adverse trends are to be reversed, it is imperative that a shift in the R&D focus from speed to quality is achieved. In this review, we discuss the potential implications of recent Omics-based advances for the drug development process.

  9. Metabolic profiling of yeast culture using gas chromatography coupled with orthogonal acceleration accurate mass time-of-flight mass spectrometry: application to biomarker discovery.

    Science.gov (United States)

    Kondo, Elsuida; Marriott, Philip J; Parker, Rhiannon M; Kouremenos, Konstantinos A; Morrison, Paul; Adams, Mike

    2014-01-07

    Yeast and yeast cultures are frequently used as additives in diets of dairy cows. Beneficial effects from the inclusion of yeast culture in diets for dairy mammals have been reported, and the aim of this study was to develop a comprehensive analytical method for the accurate mass identification of the 'global' metabolites in order to differentiate a variety of yeasts at varying growth stages (Diamond V XP, Yea-Sacc and Levucell). Microwave-assisted derivatization for metabolic profiling is demonstrated through the analysis of differing yeast samples developed for cattle feed, which include a wide range of metabolites of interest covering a large range of compound classes. Accurate identification of the components was undertaken using GC-oa-ToFMS (gas chromatography-orthogonal acceleration-time-of-flight mass spectrometry), followed by principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) for data reduction and biomarker discovery. Semi-quantification (fold changes in relative peak areas) was reported for metabolites identified as possible discriminative biomarkers (p-value 2), including D-ribose (four fold decrease), myo-inositol (five fold increase), L-phenylalanine (three fold increase), glucopyranoside (two fold increase), fructose (three fold increase) and threitol (three fold increase) respectively. Copyright © 2013 Elsevier B.V. All rights reserved.

  10. Metabolomics in critical care medicine: a new approach to biomarker discovery.

    Science.gov (United States)

    Banoei, Mohammad M; Donnelly, Sarah J; Mickiewicz, Beata; Weljie, Aalim; Vogel, Hans J; Winston, Brent W

    2014-12-01

    To present an overview and comparison of the main metabolomics techniques (1H NMR, GC-MS, and LC-MS) and their current and potential use in critical care medicine. This is a focused review, not a systematic review, using the PubMed database as the predominant source of references to compare metabolomics techniques. 1H NMR, GC-MS, and LC-MS are complementary techniques that can be used on a variety of biofluids for metabolomics analysis of patients in the Intensive Care Unit (ICU). These techniques have been successfully used for diagnosis and prognosis in the ICU and other clinical settings; for example, in patients with septic shock and community-acquired pneumonia. Metabolomics is a powerful tool that has strong potential to impact diagnosis and prognosis and to examine responses to treatment in critical care medicine through diagnostic and prognostic biomarker and biopattern identification.

  11. Adipokines: a treasure trove for the discovery of biomarkers for metabolic disorders.

    Science.gov (United States)

    Lehr, Stefan; Hartwig, Sonja; Sell, Henrike

    2012-01-01

    Adipose tissue is a major endocrine organ, releasing signaling and mediator proteins, termed adipokines, via which adipose tissue communicates with other organs. Expansion of adipose tissue in obesity alters adipokine secretion which may contribute to the development of metabolic diseases. Consequently, this correlation has emphasized the importance to further characterize the adipocyte secretion profile, and several attempts have been made to characterize the complex nature of the adipose tissue secretome by utilizing diverse proteomic profiling approaches. Although the entirety of human adipokines is still incompletely characterized, to date more than 600 potentially secretory proteins were identified providing a rich source to identify putative novel biomarkers associated with metabolic diseases. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Mendelian randomization studies of biomarkers and type 2 diabetes

    NARCIS (Netherlands)

    Abbasi, Ali

    2015-01-01

    Many biomarkers are associated with type 2 diabetes (T2D) risk in epidemiological observations. The aim of this study was to identify and summarize current evidence for causal effects of biomarkers on T2D. A systematic literature search in PubMed and EMBASE (until April 2015) was done to identify

  13. An epithelial biomarker signature for idiopathic pulmonary fibrosis: an analysis from the multicentre PROFILE cohort study.

    Science.gov (United States)

    Maher, Toby M; Oballa, Eunice; Simpson, Juliet K; Porte, Joanne; Habgood, Anthony; Fahy, William A; Flynn, Aiden; Molyneaux, Philip L; Braybrooke, Rebecca; Divyateja, Hrushikesh; Parfrey, Helen; Rassl, Doris; Russell, Anne-Marie; Saini, Gauri; Renzoni, Elisabetta A; Duggan, Anne-Marie; Hubbard, Richard; Wells, Athol U; Lukey, Pauline T; Marshall, Richard P; Jenkins, R Gisli

    2017-12-01

    Idiopathic pulmonary fibrosis (IPF) is a progressive, fatal disorder with a variable disease trajectory. The aim of this study was to assess potential biomarkers to predict outcomes for people with IPF. PROFILE is a large prospective longitudinal cohort of treatment-naive patients with IPF. We adopted a two-stage discovery and validation design using patients from the PROFILE cohort. For the discovery analysis, we examined 106 patients and 50 age and sex matched healthy controls from Nottingham University Hospitals NHS Trust and the Royal Brompton Hospital. We did an unbiased, multiplex immunoassay assessment of 123 biomarkers. We further investigated promising novel markers by immunohistochemical assessment of IPF lung tissue. In the validation analysis, we examined samples from 206 people with IPF from among the remaining 212 patients recruited to PROFILE Central England. We used the samples to attempt to replicate the biomarkers identified from the discovery analysis by use of independent immunoassays for each biomarker. We investigated the predictive power of the selected biomarkers to identify individuals with IPF who were at risk of progression or death. The PROFILE studies are registered on ClinicalTrials.gov, numbers NCT01134822 (PROFILE Central England) and NCT01110694 (PROFILE Royal Brompton Hospital). In the discovery analysis, we identified four serum biomarkers (surfactant protein D, matrix metalloproteinase 7, CA19-9, and CA-125) that were suitable for replication. Histological assessment of CA19-9 and CA-125 suggested that these proteins were markers of epithelial damage. Replication analysis showed that baseline values of surfactant protein D (46·6 ng/mL vs 34·6 ng/mL, p=0·0018) and CA19-9 (53·7 U/mL vs 22·2 U/mL; p<0·0001) were significantly higher in patients with progressive disease than in patients with stable disease, and rising concentrations of CA-125 over 3 months were associated with increased risk of mortality (HR 2·542, 95% CI 1

  14. Low molecular weight protein enrichment on mesoporous silica thin films for biomarker discovery.

    Science.gov (United States)

    Fan, Jia; Gallagher, James W; Wu, Hung-Jen; Landry, Matthew G; Sakamoto, Jason; Ferrari, Mauro; Hu, Ye

    2012-04-17

    The identification of circulating biomarkers holds great potential for non invasive approaches in early diagnosis and prognosis, as well as for the monitoring of therapeutic efficiency.(1-3) The circulating low molecular weight proteome (LMWP) composed of small proteins shed from tissues and cells or peptide fragments derived from the proteolytic degradation of larger proteins, has been associated with the pathological condition in patients and likely reflects the state of disease.(4,5) Despite these potential clinical applications, the use of Mass Spectrometry (MS) to profile the LMWP from biological fluids has proven to be very challenging due to the large dynamic range of protein and peptide concentrations in serum.(6) Without sample pre-treatment, some of the more highly abundant proteins obscure the detection of low-abundance species in serum/plasma. Current proteomic-based approaches, such as two-dimensional polyacrylamide gel-electrophoresis (2D-PAGE) and shotgun proteomics methods are labor-intensive, low throughput and offer limited suitability for clinical applications.(7-9) Therefore, a more effective strategy is needed to isolate LMWP from blood and allow the high throughput screening of clinical samples. Here, we present a fast, efficient and reliable multi-fractionation system based on mesoporous silica chips to specifically target and enrich LMWP.(10,11) Mesoporous silica (MPS) thin films with tunable features at the nanoscale were fabricated using the triblock copolymer template pathway. Using different polymer templates and polymer concentrations in the precursor solution, various pore size distributions, pore structures, connectivity and surface properties were determined and applied for selective recovery of low mass proteins. The selective parsing of the enriched peptides into different subclasses according to their physicochemical properties will enhance the efficiency of recovery and detection of low abundance species. In combination with mass

  15. Multivariate models from RNA-Seq SNVs yield candidate molecular targets for biomarker discovery: SNV-DA.

    Science.gov (United States)

    Paul, Matt R; Levitt, Nicholas P; Moore, David E; Watson, Patricia M; Wilson, Robert C; Denlinger, Chadrick E; Watson, Dennis K; Anderson, Paul E

    2016-03-31

    It has recently been shown that significant and accurate single nucleotide variants (SNVs) can be reliably called from RNA-Seq data. These may provide another source of features for multivariate predictive modeling of disease phenotype for the prioritization of candidate biomarkers. The continuous nature of SNV allele fraction features allows the concurrent investigation of several genomic phenomena, including allele specific expression, clonal expansion and/or deletion, and copy number variation. The proposed software pipeline and package, SNV Discriminant Analysis (SNV-DA), was applied on two RNA-Seq datasets with varying sample sizes sequenced at different depths: a dataset containing primary tumors from twenty patients with different disease outcomes in lung adenocarcinoma and a larger dataset of primary tumors representing two major breast cancer subtypes, estrogen receptor positive and triple negative. Predictive models were generated using the machine learning algorithm, sparse projections to latent structures discriminant analysis. Training sets composed of RNA-Seq SNV features limited to genomic regions of origin (e.g. exonic or intronic) and/or RNA-editing sites were shown to produce models with accurate predictive performances, were discriminant towards true label groupings, and were able to produce SNV rankings significantly different from than univariate tests. Furthermore, the utility of the proposed methodology is supported by its comparable performance to traditional models as well as the enrichment of selected SNVs located in genes previously associated with cancer and genes showing allele-specific expression. As proof of concept, we highlight the discovery of a previously unannotated intergenic locus that is associated with epigenetic regulatory marks in cancer and whose significant allele-specific expression is correlated with ER+ status; hereafter named ER+ associated hotspot (ERPAHS). The use of models from RNA-Seq SNVs to identify and

  16. Promise Fulfilled? An EBSCO Discovery Service Usability Study

    Science.gov (United States)

    Williams, Sarah C.; Foster, Anita K.

    2011-01-01

    Discovery tools are the next phase of library search systems. Illinois State University's Milner Library implemented EBSCO Discovery Service in August 2010. The authors conducted usability studies on the system in the fall of 2010. The aims of the study were twofold: first, to determine how Milner users set about using the system in order to…

  17. Discovery-based strategies for studying platelet function.

    Science.gov (United States)

    Flaumenhaft, R; Dilks, J R

    2008-04-01

    The platelet is an anucleate cell, complicating efforts to study platelet function by traditional genetic means. Discovery-based strategies have lead to the identification of pharmacological agents capable of targeting specific proteins critical for platelet activation. This review will address the evolution of discovery-based strategies to identify probes that are at once useful reagents for studying platelet activation and effective therapeutics.

  18. Mendelian randomization studies of biomarkers and type 2 diabetes.

    Science.gov (United States)

    Abbasi, Ali

    2015-12-01

    Many biomarkers are associated with type 2 diabetes (T2D) risk in epidemiological observations. The aim of this study was to identify and summarize current evidence for causal effects of biomarkers on T2D. A systematic literature search in PubMed and EMBASE (until April 2015) was done to identify Mendelian randomization studies that examined potential causal effects of biomarkers on T2D. To replicate the findings of identified studies, data from two large-scale, genome-wide association studies (GWAS) were used: DIAbetes Genetics Replication And Meta-analysis (DIAGRAMv3) for T2D and the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) for glycaemic traits. GWAS summary statistics were extracted for the same genetic variants (or proxy variants), which were used in the original Mendelian randomization studies. Of the 21 biomarkers (from 28 studies), ten have been reported to be causally associated with T2D in Mendelian randomization. Most biomarkers were investigated in a single cohort study or population. Of the ten biomarkers that were identified, nominally significant associations with T2D or glycaemic traits were reached for those genetic variants related to bilirubin, pro-B-type natriuretic peptide, delta-6 desaturase and dimethylglycine based on the summary data from DIAGRAMv3 or MAGIC. Several Mendelian randomization studies investigated the nature of associations of biomarkers with T2D. However, there were only a few biomarkers that may have causal effects on T2D. Further research is needed to broadly evaluate the causal effects of multiple biomarkers on T2D and glycaemic traits using data from large-scale cohorts or GWAS including many different genetic variants. © 2015 The authors.

  19. Biomarker candidate discovery in Atlantic cod (Gadus morhua) continuously exposed to North Sea produced water from egg to fry

    DEFF Research Database (Denmark)

    Bohne-Kjersem, Anneli; Bache, Nicolai; Meier, Sonnich

    2010-01-01

    were able to compare the induced changes by PW to the mode of action of oestrogens. Changes in the proteome in response to exposure in whole cod fry (approximately 80 days post-hatching, dph) were detected by two-dimensional gel electrophoresis and image analysis and identified by MALDI-ToF-ToF mass...... spectrometry, using a newly developed cod EST database and the NCBI database. Many of the protein changes occurred at low levels (0.01% and 0.1% PW) of exposure, indicating putative biological responses at lower levels than previously detected. Using discriminant analysis, we identified a set of protein...... changes that may be useful as biomarker candidates of produced water (PW) and oestradiol exposure in Atlantic cod fry. The biomarker candidates discovered in this study may, following validation, prove effective as diagnostic tools in monitoring exposure and effects of discharges from the petroleum...

  20. Nonylphenol Toxicity Evaluation and Discovery of Biomarkers in Rat Urine by a Metabolomics Strategy through HPLC-QTOF-MS

    Directory of Open Access Journals (Sweden)

    Yan-Xin Zhang

    2016-05-01

    Full Text Available Nonylphenol (NP was quantified using liquid chromatography tandem mass spectrometry (LC-MS/MS in the urine and plasma of rats treated with 0, 50, and 250 mg/kg/day of NP for four consecutive days. A urinary metabolomic strategy was originally implemented by high performance liquid chromatography time of flight mass spectrometry (HPLC-QTOF-MS to explore the toxicological effects of NP and determine the overall alterations in the metabolite profiles so as to find potential biomarkers. It is essential to point out that from the observation, the metabolic data were clearly clustered and separated for the three groups. To further identify differentiated metabolites, multivariate analysis, including principal component analysis (PCA, orthogonal partial least-squares discriminant analysis (OPLS-DA, high-resolution MS/MS analysis, as well as searches of Metlin and Massbank databases, were conducted on a series of metabolites between the control and dose groups. Finally, five metabolites, including glycine, glycerophosphocholine, 5-hydroxytryptamine, malonaldehyde (showing an upward trend, and tryptophan (showing a downward trend, were identified as the potential urinary biomarkers of NP-induced toxicity. In order to validate the reliability of these potential biomarkers, an independent validation was performed by using the multiple reaction monitoring (MRM-based targeted approach. The oxidative stress reflected by urinary 8-oxo-deoxyguanosine (8-oxodG levels was elevated in individuals highly exposed to NP, supporting the hypothesis that mitochondrial dysfunction was a result of xenoestrogen accumulation. This study reveals a promising approach to find biomarkers to assist researchers in monitoring NP.

  1. Nonylphenol Toxicity Evaluation and Discovery of Biomarkers in Rat Urine by a Metabolomics Strategy through HPLC-QTOF-MS

    Science.gov (United States)

    Zhang, Yan-Xin; Yang, Xin; Zou, Pan; Du, Peng-Fei; Wang, Jing; Jin, Fen; Jin, Mao-Jun; She, Yong-Xin

    2016-01-01

    Nonylphenol (NP) was quantified using liquid chromatography tandem mass spectrometry (LC-MS/MS) in the urine and plasma of rats treated with 0, 50, and 250 mg/kg/day of NP for four consecutive days. A urinary metabolomic strategy was originally implemented by high performance liquid chromatography time of flight mass spectrometry (HPLC-QTOF-MS) to explore the toxicological effects of NP and determine the overall alterations in the metabolite profiles so as to find potential biomarkers. It is essential to point out that from the observation, the metabolic data were clearly clustered and separated for the three groups. To further identify differentiated metabolites, multivariate analysis, including principal component analysis (PCA), orthogonal partial least-squares discriminant analysis (OPLS-DA), high-resolution MS/MS analysis, as well as searches of Metlin and Massbank databases, were conducted on a series of metabolites between the control and dose groups. Finally, five metabolites, including glycine, glycerophosphocholine, 5-hydroxytryptamine, malonaldehyde (showing an upward trend), and tryptophan (showing a downward trend), were identified as the potential urinary biomarkers of NP-induced toxicity. In order to validate the reliability of these potential biomarkers, an independent validation was performed by using the multiple reaction monitoring (MRM)-based targeted approach. The oxidative stress reflected by urinary 8-oxo-deoxyguanosine (8-oxodG) levels was elevated in individuals highly exposed to NP, supporting the hypothesis that mitochondrial dysfunction was a result of xenoestrogen accumulation. This study reveals a promising approach to find biomarkers to assist researchers in monitoring NP. PMID:27187439

  2. Custom database development and biomarker discovery methods for MALDI-TOF mass spectrometry-based identification of high-consequence bacterial pathogens.

    Science.gov (United States)

    Tracz, Dobryan M; Tyler, Andrea D; Cunningham, Ian; Antonation, Kym S; Corbett, Cindi R

    2017-03-01

    A high-quality custom database of MALDI-TOF mass spectral profiles was developed with the goal of improving clinical diagnostic identification of high-consequence bacterial pathogens. A biomarker discovery method is presented for identifying and evaluating MALDI-TOF MS spectra to potentially differentiate biothreat bacteria from less-pathogenic near-neighbour species. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

  3. Biomarker discovery in low-grade breast cancer using isobaric stable isotope tags and two-dimensional liquid chromatography-tandem mass spectrometry (iTRAQ-2DLC-MS/MS) based quantitative proteomic analysis.

    Science.gov (United States)

    Bouchal, Pavel; Roumeliotis, Theodoros; Hrstka, Roman; Nenutil, Rudolf; Vojtesek, Borivoj; Garbis, Spiros D

    2009-01-01

    The present pilot study constitutes a proof-of-principle in the use of a quantitative LC-MS/MS based proteomic method for the comparative analysis of representative low-grade breast primary tumor tissues with and without metastases and metastasis in lymph node relative to the nonmetastatic tumor type. The study method incorporated iTRAQ stable isotope labeling, two-dimensional liquid chromatography, nanoelectrospray ionization and high resolution tandem mass spectrometry using the hybrid QqTOF platform (iTRAQ-2DLC-MS/MS). The principal aims of this study were (1) to define the protein spectrum obtainable using this approach, and (2) to highlight potential candidates for verification and validation studies focused on biomarkers involved in metastatic processes in breast cancer. The study resulted in the reproducible identification of 605 nonredundant proteins (p biomarker discovery program.

  4. Studying Scientific Discovery by Computer Simulation.

    Science.gov (United States)

    1983-03-30

    MAR 83 UNCLASSIFIED CMU-CIP-WP-444 NOOOI4-82-K-0168 F/G 9/2 NL 4lU iQ 111125 . 1 MICROCOPY RESOLUIION TESI CHART NAL URLAD Of SIANDARDS %4 A Isp...About 1760 - the exact date is not known - Joseph Black, a Scottish chemistry professor, made the first of the several important discoveries that have...preserved his name.5 Using data reported in a standard chemistry textbook of his time (Boerhaave’s) and obtained from an experiment performed at

  5. Discovery of coding genetic variants influencing diabetes-related serum biomarkers and their impact on risk of type 2 diabetes.

    Science.gov (United States)

    Ahluwalia, Tarunveer Singh; Allin, Kristine Højgaard; Sandholt, Camilla Helene; Sparsø, Thomas Hempel; Jørgensen, Marit Eika; Rowe, Michael; Christensen, Cramer; Brandslund, Ivan; Lauritzen, Torsten; Linneberg, Allan; Husemoen, Lise Lotte; Jørgensen, Torben; Hansen, Torben; Grarup, Niels; Pedersen, Oluf

    2015-04-01

    Type 2 diabetes (T2D) prevalence is spiraling globally, and knowledge of its pathophysiological signatures is crucial for a better understanding and treatment of the disease. We aimed to discover underlying coding genetic variants influencing fasting serum levels of nine biomarkers associated with T2D: adiponectin, C-reactive protein, ferritin, heat shock 70-kDa protein 1B, IGF binding protein 1 and IGF binding protein 2, IL-18, IL-2 receptor-α, and leptin. A population-based sample of 6215 adult Danes was genotyped for 16 340 coding single-nucleotide polymorphisms and were tested for association with each biomarker. Identified loci were tested for association with T2D through a large-scale meta-analysis involving up to 17 024 T2D cases and up to 64 186 controls. We discovered 11 associations between single-nucleotide polymorphisms and five distinct biomarkers at a study-wide P < 3.4 × 10(-7). Nine associations were novel: IL18: BIRC6, RAD17, MARVELD2; ferritin: F5; IGF binding protein 1: SERPING1, KLKB, GCKR, CELSR2, and heat shock 70-kDa protein 1B: CFH. Three of the identified loci (CELSR2, HNF1A, and GCKR) were significantly associated with T2D, of which the association with the CELSR2 locus has not been shown previously. The identified loci influence processes related to insulin signaling, cell communication, immune function, apoptosis, DNA repair, and oxidative stress, all of which could provide a rationale for novel diabetes therapeutic strategies.

  6. Pathway and biomarker discovery in a posttraumatic stress disorder mouse model

    OpenAIRE

    Kao, Chi-Ya

    2015-01-01

    Posttraumatic stress disorder (PTSD), a prevalent psychiatric disorder, is caused by exposure to a traumatic event. Individuals diagnosed for PTSD not only experience significant functional impairments but also have higher rates of physical morbidity and mortality. Despite intense research efforts, the neurobiological pathways affecting fear circuit brain regions in PTSD remain obscure and most of the previous studies were limited to characterization of specific markers in periphery or define...

  7. Application of Fluorescence Two-Dimensional Difference In-Gel Electrophoresis as a Proteomic Biomarker Discovery Tool in Muscular Dystrophy Research

    Directory of Open Access Journals (Sweden)

    Steven Carberry

    2013-12-01

    Full Text Available In this article, we illustrate the application of difference in-gel electrophoresis for the proteomic analysis of dystrophic skeletal muscle. The mdx diaphragm was used as a tissue model of dystrophinopathy. Two-dimensional gel electrophoresis is a widely employed protein separation method in proteomic investigations. Although two-dimensional gels usually underestimate the cellular presence of very high molecular mass proteins, integral membrane proteins and low copy number proteins, this method is extremely powerful in the comprehensive analysis of contractile proteins, metabolic enzymes, structural proteins and molecular chaperones. This gives rise to two-dimensional gel electrophoretic separation as the method of choice for studying contractile tissues in health and disease. For comparative studies, fluorescence difference in-gel electrophoresis has been shown to provide an excellent biomarker discovery tool. Since aged diaphragm fibres from the mdx mouse model of Duchenne muscular dystrophy closely resemble the human pathology, we have carried out a mass spectrometry-based comparison of the naturally aged diaphragm versus the senescent dystrophic diaphragm. The proteomic comparison of wild type versus mdx diaphragm resulted in the identification of 84 altered protein species. Novel molecular insights into dystrophic changes suggest increased cellular stress, impaired calcium buffering, cytostructural alterations and disturbances of mitochondrial metabolism in dystrophin-deficient muscle tissue.

  8. Application of Fluorescence Two-Dimensional Difference In-Gel Electrophoresis as a Proteomic Biomarker Discovery Tool in Muscular Dystrophy Research

    Science.gov (United States)

    Carberry, Steven; Zweyer, Margit; Swandulla, Dieter; Ohlendieck, Kay

    2013-01-01

    In this article, we illustrate the application of difference in-gel electrophoresis for the proteomic analysis of dystrophic skeletal muscle. The mdx diaphragm was used as a tissue model of dystrophinopathy. Two-dimensional gel electrophoresis is a widely employed protein separation method in proteomic investigations. Although two-dimensional gels usually underestimate the cellular presence of very high molecular mass proteins, integral membrane proteins and low copy number proteins, this method is extremely powerful in the comprehensive analysis of contractile proteins, metabolic enzymes, structural proteins and molecular chaperones. This gives rise to two-dimensional gel electrophoretic separation as the method of choice for studying contractile tissues in health and disease. For comparative studies, fluorescence difference in-gel electrophoresis has been shown to provide an excellent biomarker discovery tool. Since aged diaphragm fibres from the mdx mouse model of Duchenne muscular dystrophy closely resemble the human pathology, we have carried out a mass spectrometry-based comparison of the naturally aged diaphragm versus the senescent dystrophic diaphragm. The proteomic comparison of wild type versus mdx diaphragm resulted in the identification of 84 altered protein species. Novel molecular insights into dystrophic changes suggest increased cellular stress, impaired calcium buffering, cytostructural alterations and disturbances of mitochondrial metabolism in dystrophin-deficient muscle tissue. PMID:24833232

  9. Robust statistical methods for significance evaluation and applications in cancer driver detection and biomarker discovery

    DEFF Research Database (Denmark)

    Madsen, Tobias

    2017-01-01

    . These challenges include model selection and multiple testing problems. On the other hand, in large datasets we can often exploit hierarchical structures to improve inference: E.g. in differential expression studies with multiple genes, it is natural to define a distribution of the variability of each gene......-point approximation and an importance sampling scheme that are fast to evaluate yet accurate. We demonstrate the methods on multiple models including the Poisson-binomial model, a high-order Markov chain motif model and phylogenetic trees of sequence evolution The methods are implemented in a publicly available R...

  10. Extracellular Vesicles: A New Frontier in Biomarker Discovery for Non-Alcoholic Fatty Liver Disease

    Science.gov (United States)

    Ban, Linda A.; Shackel, Nicholas A.; McLennan, Susan V.

    2016-01-01

    In recent years, the global burden of obesity and diabetes has seen a parallel rise in other metabolic complications, such as non-alcoholic fatty liver disease (NAFLD). This condition, once thought to be a benign accumulation of hepatic fat, is now recognized as a serious and prevalent disorder that is conducive to inflammation and fibrosis. Despite the rising incidence of NAFLD, there is currently no reliable method for its diagnosis or staging besides the highly invasive tissue biopsy. This limitation has resulted in the study of novel circulating markers as potential candidates, one of the most popular being extracellular vesicles (EVs). These submicron membrane-bound structures are secreted from stressed and activated cells, or are formed during apoptosis, and are known to be involved in intercellular communication. The cargo of EVs depends upon the parent cell and has been shown to be changed in disease, as is their abundance in the circulation. The role of EVs in immunity and epigenetic regulation is widely attested, and studies showing a correlation with disease severity have made these structures a favorable target for diagnostic as well as therapeutic purposes. This review will highlight the research that is available on EVs in the context of NAFLD, the current limitations, and projections for their future utility in a clinical setting. PMID:26985892

  11. Extracellular Vesicles: A New Frontier in Biomarker Discovery for Non-Alcoholic Fatty Liver Disease

    Directory of Open Access Journals (Sweden)

    Linda A. Ban

    2016-03-01

    Full Text Available In recent years, the global burden of obesity and diabetes has seen a parallel rise in other metabolic complications, such as non-alcoholic fatty liver disease (NAFLD. This condition, once thought to be a benign accumulation of hepatic fat, is now recognized as a serious and prevalent disorder that is conducive to inflammation and fibrosis. Despite the rising incidence of NAFLD, there is currently no reliable method for its diagnosis or staging besides the highly invasive tissue biopsy. This limitation has resulted in the study of novel circulating markers as potential candidates, one of the most popular being extracellular vesicles (EVs. These submicron membrane-bound structures are secreted from stressed and activated cells, or are formed during apoptosis, and are known to be involved in intercellular communication. The cargo of EVs depends upon the parent cell and has been shown to be changed in disease, as is their abundance in the circulation. The role of EVs in immunity and epigenetic regulation is widely attested, and studies showing a correlation with disease severity have made these structures a favorable target for diagnostic as well as therapeutic purposes. This review will highlight the research that is available on EVs in the context of NAFLD, the current limitations, and projections for their future utility in a clinical setting.

  12. Alterations of the Subgingival Microbiota in Pediatric Crohn's Disease Studied Longitudinally in Discovery and Validation Cohorts.

    Science.gov (United States)

    Kelsen, Judith; Bittinger, Kyle; Pauly-Hubbard, Helen; Posivak, Leah; Grunberg, Stephanie; Baldassano, Robert; Lewis, James D; Wu, Gary D; Bushman, Frederic D

    2015-12-01

    Oral manifestations are common in Crohn's disease (CD). Here we characterized the subgingival microbiota in pediatric patients with CD initiating therapy and after 8 weeks to identify microbial community features associated with CD and therapy. Pediatric patients with CD were recruited from The Children's Hospital of Pennsylvania. Healthy control subjects were recruited from primary care or orthopedics clinic. Subgingival plaque samples were collected at initiation of therapy and after 8 weeks. Treatment exposures included 5-ASAs, immunomodulators, steroids, and infliximab. The microbiota was characterized by 16S rRNA gene sequencing. The study was repeated in separate discovery (35 CD, 43 healthy) and validation cohorts (43 CD, 31 healthy). Most subjects in both cohorts demonstrated clinical response after 8 weeks of therapy (discovery cohort 88%, validation cohort 79%). At week 0, both antibiotic exposure and disease state were associated with differences in bacterial community composition. Seventeen genera were identified in the discovery cohort as candidate biomarkers, of which 11 were confirmed in the validation cohort. Capnocytophaga, Rothia, and TM7 were more abundant in CD relative to healthy controls. Other bacteria were reduced in abundance with antibiotic exposure among CD subjects. CD-associated genera were not enriched compared with healthy controls after 8 weeks of therapy. Subgingival microbial community structure differed with CD and antibiotic use. Results in the discovery cohort were replicated in a separate validation cohort. Several potentially pathogenic bacterial lineages were associated with CD but were not diminished in abundance by antibiotic treatment, suggesting targets for additional surveillance.

  13. A Proteomic Approach for Plasma Biomarker Discovery with iTRAQ Labelling and OFFGEL Fractionation

    Directory of Open Access Journals (Sweden)

    Emilie Ernoult

    2010-01-01

    Full Text Available Human blood plasma contains a plethora of proteins, encompassing not only proteins that have plasma-based functionalities, but also possibly every other form of low concentrated human proteins. As it circulates through the tissues, the plasma picks up proteins that are released from their origin due to physiological events such as tissue remodeling and cell death. Specific disease processes or tumors are often characterized by plasma “signatures,” which may become obvious via changes in the plasma proteome profile, for example, through over expression of proteins. However, the wide dynamic range of proteins present in plasma makes their analysis very challenging, because high-abundance proteins tend to mask those of lower abundance. In the present study, we used a strategy combining iTRAQ as a reagent which improved the peptide ionization and peptide OFFGEL fractionation that has already been shown, in our previous research, to improve the proteome coverage of cellular extracts. Two prefractioning methods were compared: immunodepletion and a bead-based library of combinatorial hexapeptide technology. Our data suggested that both methods were complementary, with regard to the number of identified proteins. iTRAQ labelling, in association with OFFGEL fractionation, allowed more than 300 different proteins to be characterized from 400 μg of plasma proteins.

  14. A proteomic approach for plasma biomarker discovery with iTRAQ labelling and OFFGEL fractionation.

    Science.gov (United States)

    Ernoult, Emilie; Bourreau, Anthony; Gamelin, Erick; Guette, Catherine

    2010-01-01

    Human blood plasma contains a plethora of proteins, encompassing not only proteins that have plasma-based functionalities, but also possibly every other form of low concentrated human proteins. As it circulates through the tissues, the plasma picks up proteins that are released from their origin due to physiological events such as tissue remodeling and cell death. Specific disease processes or tumors are often characterized by plasma "signatures," which may become obvious via changes in the plasma proteome profile, for example, through over expression of proteins. However, the wide dynamic range of proteins present in plasma makes their analysis very challenging, because high-abundance proteins tend to mask those of lower abundance. In the present study, we used a strategy combining iTRAQ as a reagent which improved the peptide ionization and peptide OFFGEL fractionation that has already been shown, in our previous research, to improve the proteome coverage of cellular extracts. Two prefractioning methods were compared: immunodepletion and a bead-based library of combinatorial hexapeptide technology. Our data suggested that both methods were complementary, with regard to the number of identified proteins. iTRAQ labelling, in association with OFFGEL fractionation, allowed more than 300 different proteins to be characterized from 400 microg of plasma proteins.

  15. RNA Profiling for Biomarker Discovery: Practical Considerations for Limiting Sample Sizes

    Directory of Open Access Journals (Sweden)

    Danny J. Kelly

    2005-01-01

    Full Text Available We have compared microarray data generated on Affymetrix™ chips from standard (8 micrograms or low (100 nanograms amounts of total RNA. We evaluated the gene signals and gene fold-change estimates obtained from the two methods and validated a subset of the results by real time, polymerase chain reaction assays. The correlation of low RNA derived gene signals to gene signals obtained from standard RNA was poor for less to moderately abundant genes. Genes with high abundance showed better correlation in signals between the two methods. The signal correlation between the low RNA and standard RNA methods was improved by including a reference sample in the microarray analysis. In contrast, the fold-change estimates for genes were better correlated between the two methods regardless of the magnitude of gene signals. A reference sample based method is suggested for studies that would end up comparing gene signal data from a combination of low and standard RNA templates; no such referencing appears to be necessary when comparing fold-changes of gene expression between standard and low template reactions.

  16. Discovery and validation of plasma biomarkers for major depressive disorder classification based on liquid chromatography-mass spectrometry.

    Science.gov (United States)

    Liu, Xinyu; Zheng, Peng; Zhao, Xinjie; Zhang, Yuqing; Hu, Chunxiu; Li, Jia; Zhao, Jieyu; Zhou, Jingjing; Xie, Peng; Xu, Guowang

    2015-05-01

    Major depressive disorder (MDD) is a debilitating mental disease with a pronounced impact on the quality of life of many people; however, it is still difficult to diagnose MDD accurately. In this study, a nontargeted metabolomics approach based on ultra-high-performance liquid chromatography equipped with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) was used to find the differential metabolites in plasma samples from patients with MDD and healthy controls. Furthermore, a validation analysis focusing on the differential metabolites was performed in another batch of samples using a targeted approach based on the dynamic multiple reactions monitoring method. Levels of acyl carnitines, ether lipids, and tryptophan pronouncedly decreased, whereas LPCs, LPEs, and PEs markedly increased in MDD subjects as compared with the healthy controls. Disturbed pathways, mainly located in acyl carnitine metabolism, lipid metabolism, and tryptophan metabolism, were clearly brought to light in MDD subjects. The binary logistic regression result showed that carnitine C10:1, PE-O 36:5, LPE 18:1 sn-2, and tryptophan can be used as a combinational biomarker to distinguish not only moderate but also severe MDD from healthy control with good sensitivity and specificity. Our findings, on one hand, provide critical insight into the pathological mechanism of MDD and, on the other hand, supply a combinational biomarker to aid the diagnosis of MDD in clinical usage.

  17. Metabolomic profiling of ascending thoracic aortic aneurysms and dissections - Implications for pathophysiology and biomarker discovery.

    Directory of Open Access Journals (Sweden)

    Christian Doppler

    Full Text Available Our basic understanding of ascending thoracic aortic aneurysm (ATAA pathogenesis is still very limited, hampering early diagnosis, risk prediction, and development of treatment options. "Omics"-technologies, ideal to reveal tissue alterations from the normal physiological state due to disease have hardly been applied in the field. Using a metabolomic approach, with this study the authors seek to define tissue differences between controls and various forms of ATAAs.Using a targeted FIA-MS/MS metabolomics approach, we analysed and compared the metabolic profiles of ascending thoracic aortic wall tissue of age-matched controls (n = 8, bicuspid aortic valve-associated aneurysms (BAV-A; n = 9, tricuspid aortic valve-associated aneurysms (TAV-A; n = 14, and tricuspid aortic valve-associated aortic dissections (TAV-Diss; n = 6.With sphingomyelin (SM (OH C22:2, SM C18:1, SM C22:1, and SM C24:1 only 4 out of 92 detectable metabolites differed significantly between controls and BAV-A samples. Between controls and TAV-Diss samples only phosphatidylcholine (PC ae C32:1 differed. Importantly, our analyses revealed a general increase in the amount of total sphingomyelin levels in BAV-A and TAV-Diss samples compared to controls.Significantly increased levels of sphingomyelins in BAV-A and TAV-Diss samples compared to controls may argue for a repression of sphingomyelinase activity and the sphingomyelinase-ceramide pathway, which may result in an inhibition of tissue regeneration; a potential basis for disease initiation and progression.

  18. Blood Biomarkers for the Early Diagnosis of Stroke: The Stroke-Chip Study.

    Science.gov (United States)

    Bustamante, Alejandro; López-Cancio, Elena; Pich, Sara; Penalba, Anna; Giralt, Dolors; García-Berrocoso, Teresa; Ferrer-Costa, Carles; Gasull, Teresa; Hernández-Pérez, María; Millan, Mónica; Rubiera, Marta; Cardona, Pedro; Cano, Luis; Quesada, Helena; Terceño, Mikel; Silva, Yolanda; Castellanos, Mar; Garces, Moisés; Reverté, Silvia; Ustrell, Xavier; Marés, Rafael; Baiges, Joan Josep; Serena, Joaquín; Rubio, Francisco; Salas, Eduardo; Dávalos, Antoni; Montaner, Joan

    2017-09-01

    Stroke diagnosis could be challenging in the acute phase. We aimed to develop a blood-based diagnostic tool to differentiate between real strokes and stroke mimics and between ischemic and hemorrhagic strokes in the hyperacute phase. The Stroke-Chip was a prospective, observational, multicenter study, conducted at 6 Stroke Centers in Catalonia. Consecutive patients with suspected stroke were enrolled within the first 6 hours after symptom onset, and blood samples were drawn immediately after admission. A 21-biomarker panel selected among previous results and from the literature was measured by immunoassays. Outcomes were differentiation between real strokes and stroke mimics and between ischemic and hemorrhagic strokes. Predictive models were developed by combining biomarkers and clinical variables in logistic regression models. Accuracy was evaluated with receiver operating characteristic curves. From August 2012 to December 2013, 1308 patients were included (71.9% ischemic, 14.8% stroke mimics, and 13.3% hemorrhagic). For stroke versus stroke mimics comparison, no biomarker resulted included in the logistic regression model, but it was only integrated by clinical variables, with a predictive accuracy of 80.8%. For ischemic versus hemorrhagic strokes comparison, NT-proBNP (N-Terminal Pro-B-Type Natriuretic Peptide) >4.9 (odds ratio, 2.40; 95% confidence interval, 1.55-3.71; P 4.7 (odds ratio, 2.02; 95% confidence interval, 1.19-3.45; P =0.010), together with age, sex, blood pressure, stroke severity, atrial fibrillation, and hypertension, were included in the model. Predictive accuracy was 80.6%. The studied biomarkers were not sufficient for an accurate differential diagnosis of stroke in the hyperacute setting. Additional discovery of new biomarkers and improvement on laboratory techniques seem necessary for achieving a molecular diagnosis of stroke. © 2017 American Heart Association, Inc.

  19. Multiple inflammatory biomarker detection in a prospective cohort study: a cross-validation between well-established single-biomarker techniques and an electrochemiluminescense-based multi-array platform.

    Directory of Open Access Journals (Sweden)

    Bas C T van Bussel

    Full Text Available BACKGROUND: In terms of time, effort and quality, multiplex technology is an attractive alternative for well-established single-biomarker measurements in clinical studies. However, limited data comparing these methods are available. METHODS: We measured, in a large ongoing cohort study (n = 574, by means of both a 4-plex multi-array biomarker assay developed by MesoScaleDiscovery (MSD and single-biomarker techniques (ELISA or immunoturbidimetric assay, the following biomarkers of low-grade inflammation: C-reactive protein (CRP, serum amyloid A (SAA, soluble intercellular adhesion molecule 1 (sICAM-1 and soluble vascular cell adhesion molecule 1 (sVCAM-1. These measures were realigned by weighted Deming regression and compared across a wide spectrum of subjects' cardiovascular risk factors by ANOVA. RESULTS: Despite that both methods ranked individuals' levels of biomarkers very similarly (Pearson's r all≥0.755 absolute concentrations of all biomarkers differed significantly between methods. Equations retrieved by the Deming regression enabled proper realignment of the data to overcome these differences, such that intra-class correlation coefficients were then 0.996 (CRP, 0.711 (SAA, 0.895 (sICAM-1 and 0.858 (sVCAM-1. Additionally, individual biomarkers differed across categories of glucose metabolism, weight, metabolic syndrome and smoking status to a similar extent by either method. CONCLUSIONS: Multiple low-grade inflammatory biomarker data obtained by the 4-plex multi-array platform of MSD or by well-established single-biomarker methods are comparable after proper realignment of differences in absolute concentrations, and are equally associated with cardiovascular risk factors, regardless of such differences. Given its greater efficiency, the MSD platform is a potential tool for the quantification of multiple biomarkers of low-grade inflammation in large ongoing and future clinical studies.

  20. Release of Tissue-specific Proteins into Coronary Perfusate as a Model for Biomarker Discovery in Myocardial Ischemia/Reperfusion Injury

    DEFF Research Database (Denmark)

    Cordwell, Stuart; Edwards, Alistair; Liddy, Kiersten

    2012-01-01

    of 60 min reperfusion following brief, reversible ischemia (15 min; 15I/60R) for comparison with irreversible I/R (60I/60R). Perfusate proteins were separated using two-dimensional gel electrophoresis (2-DE) and identified by mass spectrometry (MS), revealing 26 tissue-specific proteins released during...... reperfusion post-15I. Proteins released during irreversible I/R (60I/60R) were profiled using gel-based (2-DE and one-dimensional gel electrophoresis coupled to liquid chromatography and tandem mass spectrometry; geLC–MS) and gel-free (LC–MS/MS) methods. A total of 192 tissue-specific proteins were identified......Diagnosis of acute coronary syndromes is based on protein biomarkers, such as the cardiac troponins (cTnI/cTnT) and creatine kinase (CK-MB) that are released into the circulation. Biomarker discovery is focused on identifying very low abundance tissue-derived analytes from within albumin...

  1. The Discovery of Novel Biomarkers Improves Breast Cancer Intrinsic Subtype Prediction and Reconciles the Labels in the METABRIC Data Set

    Science.gov (United States)

    Milioli, Heloisa Helena; Vimieiro, Renato; Riveros, Carlos; Tishchenko, Inna; Berretta, Regina; Moscato, Pablo

    2015-01-01

    Background The prediction of breast cancer intrinsic subtypes has been introduced as a valuable strategy to determine patient diagnosis and prognosis, and therapy response. The PAM50 method, based on the expression levels of 50 genes, uses a single sample predictor model to assign subtype labels to samples. Intrinsic errors reported within this assay demonstrate the challenge of identifying and understanding the breast cancer groups. In this study, we aim to: a) identify novel biomarkers for subtype individuation by exploring the competence of a newly proposed method named CM1 score, and b) apply an ensemble learning, as opposed to the use of a single classifier, for sample subtype assignment. The overarching objective is to improve class prediction. Methods and Findings The microarray transcriptome data sets used in this study are: the METABRIC breast cancer data recorded for over 2000 patients, and the public integrated source from ROCK database with 1570 samples. We first computed the CM1 score to identify the probes with highly discriminative patterns of expression across samples of each intrinsic subtype. We further assessed the ability of 42 selected probes on assigning correct subtype labels using 24 different classifiers from the Weka software suite. For comparison, the same method was applied on the list of 50 genes from the PAM50 method. Conclusions The CM1 score portrayed 30 novel biomarkers for predicting breast cancer subtypes, with the confirmation of the role of 12 well-established genes. Intrinsic subtypes assigned using the CM1 list and the ensemble of classifiers are more consistent and homogeneous than the original PAM50 labels. The new subtypes show accurate distributions of current clinical markers ER, PR and HER2, and survival curves in the METABRIC and ROCK data sets. Remarkably, the paradoxical attribution of the original labels reinforces the limitations of employing a single sample classifiers to predict breast cancer intrinsic subtypes

  2. SELDI-TOF MS-based discovery of a biomarker in Cucumis sativus seeds exposed to CuO nanoparticles.

    Science.gov (United States)

    Moon, Young-Sun; Park, Eun-Sil; Kim, Tae-Oh; Lee, Hoi-Seon; Lee, Sung-Eun

    2014-11-01

    Metal oxide nanoparticles (NPs) can inhibit plant seed germination and root elongation via the release of metal ions. In the present study, two acute phytotoxicity tests, seed germination and root elongation tests, were conducted on cucumber seeds (Cucumis sativus) treated with bulk copper oxide (CuO) and CuO NPs. Two concentrations of bulk CuO and CuO NPs, 200 and 600ppm, were used to test the inhibition rate of root germination; both concentrations of bulk CuO weakly inhibited seed germination, whereas CuO NPs significantly inhibited germination, showing a low germination rate of 23.3% at 600ppm. Root elongation tests demonstrated that CuO NPs were much stronger inhibitors than bulk CuO. SELDI-TOF MS analysis showed that 34 proteins were differentially expressed in cucumber seeds after exposure to CuO NPs, with the expression patterns of at least 9 proteins highly differing from those in seeds treated with bulk CuO and in control plants. Therefore, these 9 proteins were used to identify CuO NP-specific biomarkers in cucumber plants exposed to CuO NPs. A 5977-m/z protein was the most distinguishable biomarker for determining phytotoxicity by CuO NPs. Principal component analysis (PCA) of the SELDI-TOF MS results showed variability in the modes of inhibitory action on cucumber seeds and roots. To our knowledge, this is the first study to demonstrate that the phytotoxic effect of metal oxide NPs on plants is not caused by the same mode of action as other toxins. Copyright © 2014 Elsevier B.V. All rights reserved.

  3. Biomarkers in Veterinary Medicine.

    Science.gov (United States)

    Myers, Michael J; Smith, Emily R; Turfle, Phillip G

    2017-02-08

    This article summarizes the relevant definitions related to biomarkers; reviews the general processes related to biomarker discovery and ultimate acceptance and use; and finally summarizes and reviews, to the extent possible, examples of the types of biomarkers used in animal species within veterinary clinical practice and human and veterinary drug development. We highlight opportunities for collaboration and coordination of research within the veterinary community and leveraging of resources from human medicine to support biomarker discovery and validation efforts for veterinary medicine.

  4. Biomarkers of safety and immune protection for genetically modified live attenuated leishmania vaccines against visceral leishmaniasis - discovery and implications.

    Science.gov (United States)

    Gannavaram, Sreenivas; Dey, Ranadhir; Avishek, Kumar; Selvapandiyan, Angamuthu; Salotra, Poonam; Nakhasi, Hira L

    2014-01-01

    Despite intense efforts there is no safe and efficacious vaccine against visceral leishmaniasis, which is fatal and endemic in many tropical countries. A major shortcoming in the vaccine development against blood-borne parasitic agents such as Leishmania is the inadequate predictive power of the early immune responses mounted in the host against the experimental vaccines. Often immune correlates derived from in-bred animal models do not yield immune markers of protection that can be readily extrapolated to humans. The limited efficacy of vaccines based on DNA, subunit, heat killed parasites has led to the realization that acquisition of durable immunity against the protozoan parasites requires a controlled infection with a live attenuated organism. Recent success of irradiated malaria parasites as a vaccine candidate further strengthens this approach to vaccination. We developed several gene deletion mutants in Leishmania donovani as potential live attenuated vaccines and reported extensively on the immunogenicity of LdCentrin1 deleted mutant in mice, hamsters, and dogs. Additional limited studies using genetically modified live attenuated Leishmania parasites as vaccine candidates have been reported. However, for the live attenuated parasite vaccines, the primary barrier against widespread use remains the absence of clear biomarkers associated with protection and safety. Recent studies in evaluation of vaccines, e.g., influenza and yellow fever vaccines, using systems biology tools demonstrated the power of such strategies in understanding the immunological mechanisms that underpin a protective phenotype. Applying similar tools in isolated human tissues such as PBMCs from healthy individuals infected with live attenuated parasites such as LdCen(-/-) in vitro followed by human microarray hybridization experiments will enable us to understand how early vaccine-induced gene expression profiles and the associated immune responses are coordinately regulated in normal

  5. Biomarkers of Safety and Immune Protection for Genetically Modified Live Attenuated Leishmania Vaccines Against Visceral Leishmaniasis – Discovery and Implications

    Science.gov (United States)

    Gannavaram, Sreenivas; Dey, Ranadhir; Avishek, Kumar; Selvapandiyan, Angamuthu; Salotra, Poonam; Nakhasi, Hira L.

    2014-01-01

    Despite intense efforts there is no safe and efficacious vaccine against visceral leishmaniasis, which is fatal and endemic in many tropical countries. A major shortcoming in the vaccine development against blood-borne parasitic agents such as Leishmania is the inadequate predictive power of the early immune responses mounted in the host against the experimental vaccines. Often immune correlates derived from in-bred animal models do not yield immune markers of protection that can be readily extrapolated to humans. The limited efficacy of vaccines based on DNA, subunit, heat killed parasites has led to the realization that acquisition of durable immunity against the protozoan parasites requires a controlled infection with a live attenuated organism. Recent success of irradiated malaria parasites as a vaccine candidate further strengthens this approach to vaccination. We developed several gene deletion mutants in Leishmania donovani as potential live attenuated vaccines and reported extensively on the immunogenicity of LdCentrin1 deleted mutant in mice, hamsters, and dogs. Additional limited studies using genetically modified live attenuated Leishmania parasites as vaccine candidates have been reported. However, for the live attenuated parasite vaccines, the primary barrier against widespread use remains the absence of clear biomarkers associated with protection and safety. Recent studies in evaluation of vaccines, e.g., influenza and yellow fever vaccines, using systems biology tools demonstrated the power of such strategies in understanding the immunological mechanisms that underpin a protective phenotype. Applying similar tools in isolated human tissues such as PBMCs from healthy individuals infected with live attenuated parasites such as LdCen−/− in vitro followed by human microarray hybridization experiments will enable us to understand how early vaccine-induced gene expression profiles and the associated immune responses are coordinately regulated in normal

  6. Ovarian carcinoma subtypes are different diseases: implications for biomarker studies.

    Directory of Open Access Journals (Sweden)

    Martin Köbel

    2008-12-01

    Full Text Available BACKGROUND: Although it has long been appreciated that ovarian carcinoma subtypes (serous, clear cell, endometrioid, and mucinous are associated with different natural histories, most ovarian carcinoma biomarker studies and current treatment protocols for women with this disease are not subtype specific. With the emergence of high-throughput molecular techniques, distinct pathogenetic pathways have been identified in these subtypes. We examined variation in biomarker expression rates between subtypes, and how this influences correlations between biomarker expression and stage at diagnosis or prognosis. METHODS AND FINDINGS: In this retrospective study we assessed the protein expression of 21 candidate tissue-based biomarkers (CA125, CRABP-II, EpCam, ER, F-Spondin, HE4, IGF2, K-Cadherin, Ki-67, KISS1, Matriptase, Mesothelin, MIF, MMP7, p21, p53, PAX8, PR, SLPI, TROP2, WT1 in a population-based cohort of 500 ovarian carcinomas that was collected over the period from 1984 to 2000. The expression of 20 of the 21 biomarkers differs significantly between subtypes, but does not vary across stage within each subtype. Survival analyses show that nine of the 21 biomarkers are prognostic indicators in the entire cohort but when analyzed by subtype only three remain prognostic indicators in the high-grade serous and none in the clear cell subtype. For example, tumor proliferation, as assessed by Ki-67 staining, varies markedly between different subtypes and is an unfavourable prognostic marker in the entire cohort (risk ratio [RR] 1.7, 95% confidence interval [CI] 1.2%-2.4% but is not of prognostic significance within any subtype. Prognostic associations can even show an inverse correlation within the entire cohort, when compared to a specific subtype. For example, WT1 is more frequently expressed in high-grade serous carcinomas, an aggressive subtype, and is an unfavourable prognostic marker within the entire cohort of ovarian carcinomas (RR 1.7, 95% CI 1

  7. Discovery, screening and evaluation of a plasma biomarker panel for subjects with psychological suboptimal health state using (1)H-NMR-based metabolomics profiles.

    Science.gov (United States)

    Tian, Jun-Sheng; Xia, Xiao-Tao; Wu, Yan-Fei; Zhao, Lei; Xiang, Huan; Du, Guan-Hua; Zhang, Xiang; Qin, Xue-Mei

    2016-09-21

    Individuals in the state of psychological suboptimal health keep increasing, only scales and questionnaires were used to diagnose in clinic under current conditions, and symptoms of high reliability and accuracy are destitute. Therefore, the noninvasive and precise laboratory diagnostic methods are needed. This study aimed to develop an objective method through screen potential biomarkers or a biomarker panel to facilitate the diagnosis in clinic using plasma metabolomics. Profiles were based on H-nuclear magnetic resonance ((1)H-NMR) metabolomics techniques combing with multivariate statistical analysis. Furthermore, methods of correlation analysis with Metaboanalyst 3.0 for selecting a biomarker panel, traditional Chinese medicine (TCM) drug intervention for validating the close relations between the biomarker panel and the state and the receiver operating characteristic curves (ROC curves) analysis for evaluation of clinical diagnosis ability were carried out. 9 endogenous metabolites containing trimethylamine oxide (TMAO), glutamine, N-acetyl-glycoproteins, citrate, tyrosine, phenylalanine, isoleucine, valine and glucose were identified and considered as potential biomarkers. Then a biomarker panel consisting of phenylalanine, glutamine, tyrosine, citrate, N-acetyl-glycoproteins and TMAO was selected, which exhibited the highest area under the curve (AUC = 0.971). This study provided critical insight into the pathological mechanism of psychological suboptimal health and would supply a novel and valuable diagnostic method.

  8. Discovery proteomics and nonparametric modeling pipeline in the development of a candidate biomarker panel for dengue hemorrhagic fever.

    Science.gov (United States)

    Brasier, Allan R; Garcia, Josefina; Wiktorowicz, John E; Spratt, Heidi M; Comach, Guillermo; Ju, Hyunsu; Recinos, Adrian; Soman, Kizhake; Forshey, Brett M; Halsey, Eric S; Blair, Patrick J; Rocha, Claudio; Bazan, Isabel; Victor, Sundar S; Wu, Zheng; Stafford, Susan; Watts, Douglas; Morrison, Amy C; Scott, Thomas W; Kochel, Tadeusz J

    2012-02-01

    Secondary dengue viral infection can produce capillary leakage associated with increased mortality known as dengue hemorrhagic fever (DHF). Because the mortality of DHF can be reduced by early detection and intensive support, improved methods for its detection are needed. We applied multidimensional protein profiling to predict outcomes in a prospective dengue surveillance study in South America. Plasma samples taken from initial clinical presentation of acute dengue infection were subjected to proteomics analyses using ELISA and a recently developed biofluid analysis platform. Demographics, clinical laboratory measurements, nine cytokines, and 419 plasma proteins collected at the time of initial presentation were compared between the DF and DHF outcomes. Here, the subject's gender, clinical parameters, two cytokines, and 42 proteins discriminated between the outcomes. These factors were reduced by multivariate adaptive regression splines (MARS) that a highly accurate classification model based on eight discriminant features with an area under the receiver operator curve (AUC) of 0.999. Model analysis indicated that the feature-outcome relationship were nonlinear. Although this DHF risk model will need validation in a larger cohort, we conclude that approaches to develop predictive biomarker models for disease outcome will need to incorporate nonparametric modeling approaches. © 2012 Wiley Periodicals, Inc.

  9. Optimized Phenotypic Biomarker Discovery and Confounder Elimination via Covariate-Adjusted Projection to Latent Structures from Metabolic Spectroscopy Data.

    Science.gov (United States)

    Posma, Joram M; Garcia-Perez, Isabel; Ebbels, Timothy M D; Lindon, John C; Stamler, Jeremiah; Elliott, Paul; Holmes, Elaine; Nicholson, Jeremy K

    2018-02-27

    Metabolism is altered by genetics, diet, disease status, environment, and many other factors. Modeling either one of these is often done without considering the effects of the other covariates. Attributing differences in metabolic profile to one of these factors needs to be done while controlling for the metabolic influence of the rest. We describe here a data analysis framework and novel confounder-adjustment algorithm for multivariate analysis of metabolic profiling data. Using simulated data, we show that similar numbers of true associations and significantly less false positives are found compared to other commonly used methods. Covariate-adjusted projections to latent structures (CA-PLS) are exemplified here using a large-scale metabolic phenotyping study of two Chinese populations at different risks for cardiovascular disease. Using CA-PLS, we find that some previously reported differences are actually associated with external factors and discover a number of previously unreported biomarkers linked to different metabolic pathways. CA-PLS can be applied to any multivariate data where confounding may be an issue and the confounder-adjustment procedure is translatable to other multivariate regression techniques.

  10. Biomarkers of safety and immune protection for genetically modified live attenuated Leishmania vaccines against visceral leishmaniasis-Discovery and implications

    Directory of Open Access Journals (Sweden)

    Sreenivas eGannavaram

    2014-05-01

    Full Text Available Despite intense efforts there is no safe and efficacious vaccine against visceral leishmaniasis, which is fatal and endemic in many tropical countries. A major shortcoming in the vaccine development against blood borne parasitic agents such as Leishmania is the inadequate predictive power of the early immune responses mounted in the host against the experimental vaccines. Often immune correlates derived from in-bred animal models do not yield immune markers of protection that can be readily extrapolated to humans. The limited efficacy of vaccines based on DNA, sub-unit, heat killed parasites has led to the realization that acquisition of durable immunity against the protozoan parasites requires a controlled infection with a live attenuated organism. Recent success of irradiated malaria parasites as a vaccine candidate further strengthens this approach to vaccination. We developed several gene deletion mutants in L. donovani as potential live attenuated vaccines and reported extensively on the immunogenicity of LdCentrin1 deleted mutant in mice, hamsters and dogs. Additional limited studies using genetically modified live attenuated Leishmania parasites as vaccine candidates have been reported. However, for the live attenuated parasite vaccines, the primary barrier against widespread use remains the absence of clear biomarkers associated with protection and safety. Recent studies in evaluation of vaccines e.g., influenza and yellow fever vaccines, using systems biology tools demonstrated the power of such strategies in understanding the immunological mechanisms that underpin a protective phenotype. Applying similar tools in isolated human tissues such as PBMCs from healthy individuals infected with live attenuated parasites such as LdCen1-/- in vitro followed by human microarray hybridization experiments will enable us to understand how early vaccine-induced gene expression profiles and the associated immune responses are coordinately regulated

  11. Ionizing radiation biomarkers for potential use in epidemiological studies

    International Nuclear Information System (INIS)

    Pernot, Eileen; Cardis, Elisabeth; Hall, Janet; Baatout, Sarah; El Saghire, Houssein; Mohammed Abderrafi Benotmane; Roel Quintens; Blanchardon, Eric; Bouffler, Simon; Gomolka, Maria; Guertler, Anne; Kreuzer, Michaela; Harms-Ringdahl, Mats; Jeggo, Penny; Laurier, Dominique; Lindholm, Carita; Mkacher, Radhia; Sabatier, Laure; Tapio, Soile; De Vathaire, Florent

    2012-01-01

    Ionizing radiation is a known human carcinogen that can induce a variety of biological effects depending on the physical nature, duration, doses and dose-rates of exposure. However, the magnitude of health risks at low doses and dose-rates (below 100 mSv and/or 0.1 mSv min -1 ) remains controversial due to a lack of direct human evidence. It is anticipated that significant insights will emerge from the integration of epidemiological and biological research, made possible by molecular epidemiology studies incorporating biomarkers and bioassays. A number of these have been used to investigate exposure, effects and susceptibility to ionizing radiation, albeit often at higher doses and dose rates, with each reflecting time-limited cellular or physiological alterations. This review summarises the multidisciplinary work undertaken in the framework of the European project DoReMi (Low Dose Research towards Multidisciplinary Integration) to identify the most appropriate biomarkers for use in population studies. In addition to logistical and ethical considerations for conducting large-scale epidemiological studies, we discuss the relevance of their use for assessing the effects of low dose ionizing radiation exposure at the cellular and physiological level. We also propose a temporal classification of biomarkers that may be relevant for molecular epidemiology studies which need to take into account the time elapsed since exposure. Finally, the integration of biology with epidemiology requires careful planning and enhanced discussions between the epidemiology, biology and dosimetry communities in order to determine the most important questions to be addressed in light of pragmatic considerations including the appropriate population to be investigated (occupationally, environmentally or medically exposed), and study design. The consideration of the logistics of biological sample collection, processing and storing and the choice of biomarker or bioassay, as well as awareness of

  12. Smoking reduction and biomarkers in two longitudinal studies

    DEFF Research Database (Denmark)

    Godtfredsen, Nina; Prescott, Eva; Vestbo, Jørgen

    2006-01-01

    AIMS: To measure reduction in exposure to smoke in two population-based studies of self-reported smoking reduction not using nicotine replacement. DESIGN: Cross-sectional analyses of biomarkers and smoking. SETTING: Data from two time-points in the Copenhagen City Heart Study (CCHS), 1981....../83 and 1991/94, and the Copenhagen Male Study (CMS) in 1976 and 1985/86, respectively. PARTICIPANTS: There were 3026 adults who were smokers at both time-points in the CCHS and 1319 men smoking at both time-points in the CMS. MEASUREMENTS: Smoking status and tobacco consumption were assessed by self......-completion questionnaire. Measurements of biomarkers of smoke intake were taken at the second time-point in the two studies: expired-air carbon monoxide (CO) in the CCHS and serum cotinine in the CMS. Biomarker levels in medium (15-29 g tobacco/day) and heavy (> 30 g/day) smokers at the first time-point who later reported...

  13. Development of a biomarkers database for the National Children's Study

    International Nuclear Information System (INIS)

    Lobdell, Danelle T.; Mendola, Pauline

    2005-01-01

    The National Children's Study (NCS) is a federally-sponsored, longitudinal study of environmental influences on the health and development of children across the United States (www.nationalchildrensstudy.gov). Current plans are to study approximately 100,000 children and their families beginning before birth up to age 21 years. To explore potential biomarkers that could be important measurements in the NCS, we compiled the relevant scientific literature to identify both routine or standardized biological markers as well as new and emerging biological markers. Although the search criteria encouraged examination of factors that influence the breadth of child health and development, attention was primarily focused on exposure, susceptibility, and outcome biomarkers associated with four important child health outcomes: autism and neurobehavioral disorders, injury, cancer, and asthma. The Biomarkers Database was designed to allow users to: (1) search the biomarker records compiled by type of marker (susceptibility, exposure or effect), sampling media (e.g., blood, urine, etc.), and specific marker name; (2) search the citations file; and (3) read the abstract evaluations relative to our search criteria. A searchable, user-friendly database of over 2000 articles was created and is publicly available at: http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=85844. PubMed was the primary source of references with some additional searches of Toxline, NTIS, and other reference databases. Our initial focus was on review articles, beginning as early as 1996, supplemented with searches of the recent primary research literature from 2001 to 2003. We anticipate this database will have applicability for the NCS as well as other studies of children's environmental health

  14. Computational protein biomarker prediction: a case study for prostate cancer

    Directory of Open Access Journals (Sweden)

    Adam Bao-Ling

    2004-03-01

    Full Text Available Abstract Background Recent technological advances in mass spectrometry pose challenges in computational mathematics and statistics to process the mass spectral data into predictive models with clinical and biological significance. We discuss several classification-based approaches to finding protein biomarker candidates using protein profiles obtained via mass spectrometry, and we assess their statistical significance. Our overall goal is to implicate peaks that have a high likelihood of being biologically linked to a given disease state, and thus to narrow the search for biomarker candidates. Results Thorough cross-validation studies and randomization tests are performed on a prostate cancer dataset with over 300 patients, obtained at the Eastern Virginia Medical School using SELDI-TOF mass spectrometry. We obtain average classification accuracies of 87% on a four-group classification problem using a two-stage linear SVM-based procedure and just 13 peaks, with other methods performing comparably. Conclusions Modern feature selection and classification methods are powerful techniques for both the identification of biomarker candidates and the related problem of building predictive models from protein mass spectrometric profiles. Cross-validation and randomization are essential tools that must be performed carefully in order not to bias the results unfairly. However, only a biological validation and identification of the underlying proteins will ultimately confirm the actual value and power of any computational predictions.

  15. Protein biomarkers on tissue as imaged via MALDI mass spectrometry: A systematic approach to study the limits of detection.

    Science.gov (United States)

    van de Ven, Stephanie M W Y; Bemis, Kyle D; Lau, Kenneth; Adusumilli, Ravali; Kota, Uma; Stolowitz, Mark; Vitek, Olga; Mallick, Parag; Gambhir, Sanjiv S

    2016-06-01

    MALDI mass spectrometry imaging (MSI) is emerging as a tool for protein and peptide imaging across tissue sections. Despite extensive study, there does not yet exist a baseline study evaluating the potential capabilities for this technique to detect diverse proteins in tissue sections. In this study, we developed a systematic approach for characterizing MALDI-MSI workflows in terms of limits of detection, coefficients of variation, spatial resolution, and the identification of endogenous tissue proteins. Our goal was to quantify these figures of merit for a number of different proteins and peptides, in order to gain more insight in the feasibility of protein biomarker discovery efforts using this technique. Control proteins and peptides were deposited in serial dilutions on thinly sectioned mouse xenograft tissue. Using our experimental setup, coefficients of variation were biomarkers and a new benchmarking strategy that can be used for comparing diverse MALDI-MSI workflows. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Major depressive disorder: insight into candidate cerebrospinal fluid protein biomarkers from proteomics studies.

    Science.gov (United States)

    Al Shweiki, Mhd Rami; Oeckl, Patrick; Steinacker, Petra; Hengerer, Bastian; Schönfeldt-Lecuona, Carlos; Otto, Markus

    2017-06-01

    Major Depressive Disorder (MDD) is the leading cause of global disability, and an increasing body of literature suggests different cerebrospinal fluid (CSF) proteins as biomarkers of MDD. The aim of this review is to summarize the suggested CSF biomarkers and to analyze the MDD proteomics studies of CSF and brain tissues for promising biomarker candidates. Areas covered: The review includes the human studies found by a PubMed search using the following terms: 'depression cerebrospinal fluid biomarker', 'major depression biomarker CSF', 'depression CSF biomarker', 'proteomics depression', 'proteomics biomarkers in depression', 'proteomics CSF biomarker in depression', and 'major depressive disorder CSF'. The literature analysis highlights promising biomarker candidates and demonstrates conflicting results on others. It reveals 42 differentially regulated proteins in MDD that were identified in more than one proteomics study. It discusses the diagnostic potential of the biomarker candidates and their association with the suggested pathologies. Expert commentary: One ultimate goal of finding biomarkers for MDD is to improve the diagnostic accuracy to achieve better treatment outcomes; due to the heterogeneous nature of MDD, using bio-signatures could be a good strategy to differentiate MDD from other neuropsychiatric disorders. Notably, further validation studies of the suggested biomarkers are still needed.

  17. Discovery and Reuse of Open Datasets: An Exploratory Study

    Directory of Open Access Journals (Sweden)

    Sara

    2016-07-01

    Full Text Available Objective: This article analyzes twenty cited or downloaded datasets and the repositories that house them, in order to produce insights that can be used by academic libraries to encourage discovery and reuse of research data in institutional repositories. Methods: Using Thomson Reuters’ Data Citation Index and repository download statistics, we identified twenty cited/downloaded datasets. We documented the characteristics of the cited/downloaded datasets and their corresponding repositories in a self-designed rubric. The rubric includes six major categories: basic information; funding agency and journal information; linking and sharing; factors to encourage reuse; repository characteristics; and data description. Results: Our small-scale study suggests that cited/downloaded datasets generally comply with basic recommendations for facilitating reuse: data are documented well; formatted for use with a variety of software; and shared in established, open access repositories. Three significant factors also appear to contribute to dataset discovery: publishing in discipline-specific repositories; indexing in more than one location on the web; and using persistent identifiers. The cited/downloaded datasets in our analysis came from a few specific disciplines, and tended to be funded by agencies with data publication mandates. Conclusions: The results of this exploratory research provide insights that can inform academic librarians as they work to encourage discovery and reuse of institutional datasets. Our analysis also suggests areas in which academic librarians can target open data advocacy in their communities in order to begin to build open data success stories that will fuel future advocacy efforts.

  18. Phospholipid fatty acid biomarkers in a freshwater periphyton community exposed to uranium: discovery by non-linear statistical learning

    Energy Technology Data Exchange (ETDEWEB)

    Webb-Robertson, Bobbie-Jo M.; Bunn, Amoret L.; Bailey, Vanessa L.

    2011-01-01

    Phospholipid fatty acids (PLFA) have been widely used to characterize environmental microbial communities, generating community profiles that can distinguish phylogenetic or functional groups within the community. The poor specificity of organism groups with fatty acid biomarkers in the classic PLFA-microorganism associations is a confounding factor in many of the statistical classification/clustering approaches traditionally used to interpret PLFA profiles. In this paper we demonstrate that non-linear statistical learning methods, such as a support vector machine (SVM), can more accurately find patterns related to uranyl nitrate exposure in a freshwater periphyton community than linear methods, such as partial least squares discriminant analysis. In addition, probabilistic models of exposure can be derived from the identified lipid biomarkers to demonstrate the potential model-based approach that could be used in remediation. The SVM probability model separates dose groups at accuracies of ~87.0%, ~71.4%, ~87.5%, and 100% for the four groups; Control (non-amended system), low-dose (amended at 10 µg U L-1), medium dose (amended at 100 µg U L-1), and high dose (500 µg U L-1). The SVM model achieved an overall cross-validated classification accuracy of ~87% in contrast to ~59% for the best linear classifier.

  19. Biomarker Discovery Based on Hybrid Optimization Algorithm and Artificial Neural Networks on Microarray Data for Cancer Classification.

    Science.gov (United States)

    Moteghaed, Niloofar Yousefi; Maghooli, Keivan; Pirhadi, Shiva; Garshasbi, Masoud

    2015-01-01

    The improvement of high-through-put gene profiling based microarrays technology has provided monitoring the expression value of thousands of genes simultaneously. Detailed examination of changes in expression levels of genes can help physicians to have efficient diagnosing, classification of tumors and cancer's types as well as effective treatments. Finding genes that can classify the group of cancers correctly based on hybrid optimization algorithms is the main purpose of this paper. In this paper, a hybrid particle swarm optimization and genetic algorithm method are used for gene selection and also artificial neural network (ANN) is adopted as the classifier. In this work, we have improved the ability of the algorithm for the classification problem by finding small group of biomarkers and also best parameters of the classifier. The proposed approach is tested on three benchmark gene expression data sets: Blood (acute myeloid leukemia, acute lymphoblastic leukemia), colon and breast datasets. We used 10-fold cross-validation to achieve accuracy and also decision tree algorithm to find the relation between the biomarkers for biological point of view. To test the ability of the trained ANN models to categorize the cancers, we analyzed additional blinded samples that were not previously used for the training procedure. Experimental results show that the proposed method can reduce the dimension of the data set and confirm the most informative gene subset and improve classification accuracy with best parameters based on datasets.

  20. Analytical strategies for discovery and replication of genetic effects in pharmacogenomic studies

    Directory of Open Access Journals (Sweden)

    Kohler JR

    2014-08-01

    Full Text Available Jared R Kohler, Tobias Guennel, Scott L MarshallBioStat Solutions, Inc., Frederick, MD, USAAbstract: In the past decade, the pharmaceutical industry and biomedical research sector have devoted considerable resources to pharmacogenomics (PGx with the hope that understanding genetic variation in patients would deliver on the promise of personalized medicine. With the advent of new technologies and the improved collection of DNA samples, the roadblock to advancements in PGx discovery is no longer the lack of high-density genetic information captured on patient populations, but rather the development, adaptation, and tailoring of analytical strategies to effectively harness this wealth of information. The current analytical paradigm in PGx considers the single-nucleotide polymorphism (SNP as the genomic feature of interest and performs single SNP association tests to discover PGx effects – ie, genetic effects impacting drug response. While it can be straightforward to process single SNP results and to consider how this information may be extended for use in downstream patient stratification, the rate of replication for single SNP associations has been low and the desired success of producing clinically and commercially viable biomarkers has not been realized. This may be due to the fact that single SNP association testing is suboptimal given the complexities of PGx discovery in the clinical trial setting, including: 1 relatively small sample sizes; 2 diverse clinical cohorts within and across trials due to genetic ancestry (potentially impacting the ability to replicate findings; and 3 the potential polygenic nature of a drug response. Subsequently, a shift in the current paradigm is proposed: to consider the gene as the genomic feature of interest in PGx discovery. The proof-of-concept study presented in this manuscript demonstrates that genomic region-based association testing has the potential to improve the power of detecting single SNP or

  1. Biomarkers of Acute Stroke Etiology (BASE) Study Methodology.

    Science.gov (United States)

    Jauch, Edward C; Barreto, Andrew D; Broderick, Joseph P; Char, Doug M; Cucchiara, Brett L; Devlin, Thomas G; Haddock, Alison J; Hicks, William J; Hiestand, Brian C; Jickling, Glen C; June, Jeff; Liebeskind, David S; Lowenkopf, Ted J; Miller, Joseph B; O'Neill, John; Schoonover, Tim L; Sharp, Frank R; Peacock, W Frank

    2017-05-05

    Acute ischemic stroke affects over 800,000 US adults annually, with hundreds of thousands more experiencing a transient ischemic attack. Emergent evaluation, prompt acute treatment, and identification of stroke or TIA (transient ischemic attack) etiology for specific secondary prevention are critical for decreasing further morbidity and mortality of cerebrovascular disease. The Biomarkers of Acute Stroke Etiology (BASE) study is a multicenter observational study to identify serum markers defining the etiology of acute ischemic stroke. Observational trial of patients presenting to the hospital within 24 h of stroke onset. Blood samples are collected at arrival, 24, and 48 h later, and RNA gene expression is utilized to identify stroke etiology marker candidates. The BASE study began January 2014. At the time of writing, there are 22 recruiting sites. Enrollment is ongoing, expected to hit 1000 patients by March 2017. The BASE study could potentially aid in focusing the initial diagnostic evaluation to determine stroke etiology, with more rapidly initiated targeted evaluations and secondary prevention strategies.Clinical Trial Registration Clinicaltrials.gov NCT02014896 https://clinicaltrials.gov/ct2/show/NCT02014896?term=biomarkers+of+acute+stroke+etiology&rank=1.

  2. Protein Complexes in Urine Interfere with Extracellular Vesicle Biomarker Studies

    Directory of Open Access Journals (Sweden)

    Magda Wachalska

    2016-03-01

    Full Text Available Urine exosomes (extracellular vesicles; EVs contain (microRNA (miRNA and protein biomarkers that are useful for the non-invasive diagnosis of various urological diseases. However, the urinary Tamm-Horsfall protein (THP complex, which forms at reduced temperatures, may affect EV isolation and may also lead to contamination by other molecules including microRNAs (miRNAs. Therefore, we compared the levels of three miRNAs within the purified EV fraction and THP- protein-network. Urine was collected from healthy donors and EVs were isolated by ultracentrifugation (UC, two commercial kits or sepharose size-exclusion chromatography (SEC. SEC enables the separation of EVs from protein-complexes in urine. After UC, the isolation of EV-miRNA was compared with two commercial kits. The EV isolation efficiency was evaluated by measuring the EV protein markers, Alix and TSG101, CD63 by Western blotting, or miR-375, miR-204 and miR-21 by RT-qPCR. By using commercial kits, EV isolation resulted in either low yields or dissimilar miRNA levels. Via SEC, the EVs were separated from the protein-complex fraction. Importantly, a different ratio was observed between the three miRNAs in the protein fraction compared to the EV fraction. Thus, protein-complexes within urine may influence EV-biomarker studies. Therefore, the characterization of the isolated EV fraction is important to obtain reproducible results.

  3. In-depth cDNA library sequencing provides quantitative gene expression profiling in cancer biomarker discovery.

    Science.gov (United States)

    Yang, Wanling; Ying, Dingge; Lau, Yu-Lung

    2009-06-01

    Quantitative gene expression analysis plays an important role in identifying differentially expressed genes in various pathological states, gene expression regulation and co-regulation, shedding light on gene functions. Although microarray is widely used as a powerful tool in this regard, it is suboptimal quantitatively and unable to detect unknown gene variants. Here we demonstrated effective detection of differential expression and co-regulation of certain genes by expressed sequence tag analysis using a selected subset of cDNA libraries. We discussed the issues of sequencing depth and library preparation, and propose that increased sequencing depth and improved preparation procedures may allow detection of many expression features for less abundant gene variants. With the reduction of sequencing cost and the emerging of new generation sequencing technology, in-depth sequencing of cDNA pools or libraries may represent a better and powerful tool in gene expression profiling and cancer biomarker detection. We also propose using sequence-specific subtraction to remove hundreds of the most abundant housekeeping genes to increase sequencing depth without affecting relative expression ratio of other genes, as transcripts from as few as 300 most abundantly expressed genes constitute about 20% of the total transcriptome. In-depth sequencing also represents a unique advantage of detecting unknown forms of transcripts, such as alternative splicing variants, fusion genes, and regulatory RNAs, as well as detecting mutations and polymorphisms that may play important roles in disease pathogenesis.

  4. Candidate proteins, metabolites and transcripts in the Biomarkers for Spinal Muscular Atrophy (BforSMA clinical study.

    Directory of Open Access Journals (Sweden)

    Richard S Finkel

    Full Text Available Spinal Muscular Atrophy (SMA is a neurodegenerative motor neuron disorder resulting from a homozygous mutation of the survival of motor neuron 1 (SMN1 gene. The gene product, SMN protein, functions in RNA biosynthesis in all tissues. In humans, a nearly identical gene, SMN2, rescues an otherwise lethal phenotype by producing a small amount of full-length SMN protein. SMN2 copy number inversely correlates with disease severity. Identifying other novel biomarkers could inform clinical trial design and identify novel therapeutic targets.To identify novel candidate biomarkers associated with disease severity in SMA using unbiased proteomic, metabolomic and transcriptomic approaches.A cross-sectional single evaluation was performed in 108 children with genetically confirmed SMA, aged 2-12 years, manifesting a broad range of disease severity and selected to distinguish factors associated with SMA type and present functional ability independent of age. Blood and urine specimens from these and 22 age-matched healthy controls were interrogated using proteomic, metabolomic and transcriptomic discovery platforms. Analyte associations were evaluated against a primary measure of disease severity, the Modified Hammersmith Functional Motor Scale (MHFMS and to a number of secondary clinical measures.A total of 200 candidate biomarkers correlate with MHFMS scores: 97 plasma proteins, 59 plasma metabolites (9 amino acids, 10 free fatty acids, 12 lipids and 28 GC/MS metabolites and 44 urine metabolites. No transcripts correlated with MHFMS.In this cross-sectional study, "BforSMA" (Biomarkers for SMA, candidate protein and metabolite markers were identified. No transcript biomarker candidates were identified. Additional mining of this rich dataset may yield important insights into relevant SMA-related pathophysiology and biological network associations. Additional prospective studies are needed to confirm these findings, demonstrate sensitivity to change with

  5. Proteomics studies in inner ear disorders: pathophysiology and biomarkers.

    Science.gov (United States)

    Alawieh, Ali; Mondello, Stefania; Kobeissy, Firas; Shibbani, Kamel; Bassim, Marc

    2015-04-01

    Although proteomics has been exploited in a wide range of diseases for identification of biomarkers and pathophysiological mechanisms, there are still biomedical disciplines such as otology where proteomics platforms are underused due to technical challenges and/or complex features of the disease. Thus, in the past few years, healthcare and scientific agencies have advocated the development and adoption of proteomic technologies in otological research. However, few studies have been conducted and limited literature is available in this area. Here, we present the state of the art of proteomics in otology, discussing the substantial evidence from recent experimental models and clinical studies in inner-ear conditions. We also delineate a series of critical issues including minute size of the inner ear, delicacy and poor accessibility of tissue that researchers face while undertaking otology proteomics research. Furthermore, we provide perspective to enhance the impact and lead to the clinical implementation of these proteomics-based strategies.

  6. Autoantibody profiling on human proteome microarray for biomarker discovery in cerebrospinal fluid and sera of neuropsychiatric lupus.

    Directory of Open Access Journals (Sweden)

    Chaojun Hu

    Full Text Available Autoantibodies in cerebrospinal fluid (CSF from patients with neuropsychiatric systemic lupus erythematosus (NPSLE may be potential biomarkers for prediction, diagnosis, or prognosis of NPSLE. We used a human proteome microarray with~17,000 unique full-length human proteins to investigate autoantibodies associated with NPSLE. Twenty-nine CSF specimens from 12 NPSLE, 7 non-NPSLE, and 10 control (non-systemic lupus erythematosuspatients were screened for NPSLE-associated autoantibodies with proteome microarrays. A focused autoantigen microarray of candidate NPSLE autoantigens was applied to profile a larger cohort of CSF with patient-matched sera. We identified 137 autoantigens associated with NPSLE. Ingenuity Pathway Analysis revealed that these autoantigens were enriched for functions involved in neurological diseases (score = 43.Anti-proliferating cell nuclear antigen (PCNA was found in the CSF of NPSLE and non-NPSLE patients. The positive rates of 4 autoantibodies in CSF specimens were significantly different between the SLE (i.e., NPSLE and non-NPSLE and control groups: anti-ribosomal protein RPLP0, anti-RPLP1, anti-RPLP2, and anti-TROVE2 (also known as anti-Ro/SS-A. The positive rate for anti-SS-A associated with NPSLE was higher than that for non-NPSLE (31.11% cf. 10.71%; P = 0.045.Further analysis showed that anti-SS-A in CSF specimens was related to neuropsychiatric syndromes of the central nervous system in SLE (P = 0.009. Analysis with Spearman's rank correlation coefficient indicated that the titers of anti-RPLP2 and anti-SS-A in paired CSF and serum specimens significantly correlated. Human proteome microarrays offer a powerful platform to discover novel autoantibodies in CSF samples. Anti-SS-A autoantibodies may be potential CSF markers for NPSLE.

  7. Application of bio-marker to study on tumor radiosensitivity

    International Nuclear Information System (INIS)

    Guo Wanfeng; Ding Guirong; Han Liangfu

    2001-01-01

    To definite tumor radiosensitivity is important for applying the schedules of individualization of patient radiotherapy. Many laboratories were carrying on the research which predict the tumor radiosensitivity with one bio-marker or/and multi-bio-marker in various levels. At present has not witnessed the specific bio-marker, but it provides an excellent model for predicting tumor radiosensitivity

  8. Archaeological discoveries in Jordan: their impact on biblical studies

    Directory of Open Access Journals (Sweden)

    H. Olivier

    1992-06-01

    Full Text Available The major impact of archaeological exploration in Jordan on the history and development of Biblical studies is not always fully appreciated. It is shown here that several important innovations and developments in the field of Biblical studies are directly to be linked to such archaeological discoveries. Moreover, contrary to the more easily accessible and religiously more significant Cisjordan, certain regions in Transjordan have remained virtually untouched until a few years ago. Consequently, they can presently be explored by means of the most advanced survey and excavation techniques. The current interest in the social, cultural and economical aspects of society in Biblical times has been served significantly by modern socio-anthropolocical based archaeological research in the more isolated regions of Jordan.

  9. Perceived age as clinically useful biomarker of ageing: cohort study

    DEFF Research Database (Denmark)

    Christensen, Kaare; Thinggaard, Mikael; McGue, Matt

    2009-01-01

    OBJECTIVE: To determine whether perceived age correlates with survival and important age related phenotypes. DESIGN: Follow-up study, with survival of twins determined up to January 2008, by which time 675 (37%) had died. SETTING: Population based twin cohort in Denmark. PARTICIPANTS: 20 nurses, 10...... young men, and 11 older women (assessors); 1826 twins aged >or=70. MAIN OUTCOME MEASURES: Assessors: perceived age of twins from photographs. Twins: physical and cognitive tests and molecular biomarker of ageing (leucocyte telomere length). RESULTS: For all three groups of assessors, perceived age...... was significantly associated with survival, even after adjustment for chronological age, sex, and rearing environment. Perceived age was still significantly associated with survival after further adjustment for physical and cognitive functioning. The likelihood that the older looking twin of the pair died first...

  10. The Discovery of Insulin: A Case Study of Scientific Methodology

    Science.gov (United States)

    Stansfield, William D.

    2012-01-01

    The nature of scientific research sometimes involves a trial-and-error procedure. Popular reviews of successful results from this approach often sanitize the story by omitting unsuccessful trials, thus painting the rosy impression that research simply follows a direct route from hypothesis to experiment to scientific discovery. The discovery of…

  11. Open Source Drug Discovery in Practice: A Case Study

    Science.gov (United States)

    Årdal, Christine; Røttingen, John-Arne

    2012-01-01

    Background Open source drug discovery offers potential for developing new and inexpensive drugs to combat diseases that disproportionally affect the poor. The concept borrows two principle aspects from open source computing (i.e., collaboration and open access) and applies them to pharmaceutical innovation. By opening a project to external contributors, its research capacity may increase significantly. To date there are only a handful of open source R&D projects focusing on neglected diseases. We wanted to learn from these first movers, their successes and failures, in order to generate a better understanding of how a much-discussed theoretical concept works in practice and may be implemented. Methodology/Principal Findings A descriptive case study was performed, evaluating two specific R&D projects focused on neglected diseases. CSIR Team India Consortium's Open Source Drug Discovery project (CSIR OSDD) and The Synaptic Leap's Schistosomiasis project (TSLS). Data were gathered from four sources: interviews of participating members (n = 14), a survey of potential members (n = 61), an analysis of the websites and a literature review. Both cases have made significant achievements; however, they have done so in very different ways. CSIR OSDD encourages international collaboration, but its process facilitates contributions from mostly Indian researchers and students. Its processes are formal with each task being reviewed by a mentor (almost always offline) before a result is made public. TSLS, on the other hand, has attracted contributors internationally, albeit significantly fewer than CSIR OSDD. Both have obtained funding used to pay for access to facilities, physical resources and, at times, labor costs. TSLS releases its results into the public domain, whereas CSIR OSDD asserts ownership over its results. Conclusions/Significance Technically TSLS is an open source project, whereas CSIR OSDD is a crowdsourced project. However, both have enabled high quality

  12. Open source drug discovery in practice: a case study.

    Science.gov (United States)

    Årdal, Christine; Røttingen, John-Arne

    2012-01-01

    Open source drug discovery offers potential for developing new and inexpensive drugs to combat diseases that disproportionally affect the poor. The concept borrows two principle aspects from open source computing (i.e., collaboration and open access) and applies them to pharmaceutical innovation. By opening a project to external contributors, its research capacity may increase significantly. To date there are only a handful of open source R&D projects focusing on neglected diseases. We wanted to learn from these first movers, their successes and failures, in order to generate a better understanding of how a much-discussed theoretical concept works in practice and may be implemented. A descriptive case study was performed, evaluating two specific R&D projects focused on neglected diseases. CSIR Team India Consortium's Open Source Drug Discovery project (CSIR OSDD) and The Synaptic Leap's Schistosomiasis project (TSLS). Data were gathered from four sources: interviews of participating members (n = 14), a survey of potential members (n = 61), an analysis of the websites and a literature review. Both cases have made significant achievements; however, they have done so in very different ways. CSIR OSDD encourages international collaboration, but its process facilitates contributions from mostly Indian researchers and students. Its processes are formal with each task being reviewed by a mentor (almost always offline) before a result is made public. TSLS, on the other hand, has attracted contributors internationally, albeit significantly fewer than CSIR OSDD. Both have obtained funding used to pay for access to facilities, physical resources and, at times, labor costs. TSLS releases its results into the public domain, whereas CSIR OSDD asserts ownership over its results. Technically TSLS is an open source project, whereas CSIR OSDD is a crowdsourced project. However, both have enabled high quality research at low cost. The critical success factors appear to be clearly

  13. Open source drug discovery in practice: a case study.

    Directory of Open Access Journals (Sweden)

    Christine Årdal

    Full Text Available BACKGROUND: Open source drug discovery offers potential for developing new and inexpensive drugs to combat diseases that disproportionally affect the poor. The concept borrows two principle aspects from open source computing (i.e., collaboration and open access and applies them to pharmaceutical innovation. By opening a project to external contributors, its research capacity may increase significantly. To date there are only a handful of open source R&D projects focusing on neglected diseases. We wanted to learn from these first movers, their successes and failures, in order to generate a better understanding of how a much-discussed theoretical concept works in practice and may be implemented. METHODOLOGY/PRINCIPAL FINDINGS: A descriptive case study was performed, evaluating two specific R&D projects focused on neglected diseases. CSIR Team India Consortium's Open Source Drug Discovery project (CSIR OSDD and The Synaptic Leap's Schistosomiasis project (TSLS. Data were gathered from four sources: interviews of participating members (n = 14, a survey of potential members (n = 61, an analysis of the websites and a literature review. Both cases have made significant achievements; however, they have done so in very different ways. CSIR OSDD encourages international collaboration, but its process facilitates contributions from mostly Indian researchers and students. Its processes are formal with each task being reviewed by a mentor (almost always offline before a result is made public. TSLS, on the other hand, has attracted contributors internationally, albeit significantly fewer than CSIR OSDD. Both have obtained funding used to pay for access to facilities, physical resources and, at times, labor costs. TSLS releases its results into the public domain, whereas CSIR OSDD asserts ownership over its results. CONCLUSIONS/SIGNIFICANCE: Technically TSLS is an open source project, whereas CSIR OSDD is a crowdsourced project. However, both have enabled high

  14. Resonance Raman Spectroscopic Evaluation of Skin Carotenoids as a Biomarker of Carotenoid Status for Human Studies

    Science.gov (United States)

    Mayne, Susan T.; Cartmel, Brenda; Scarmo, Stephanie; Jahns, Lisa; Ermakov, Igor V.; Gellermann, Werner

    2013-01-01

    Resonance Raman Spectroscopy (RRS) is a non-invasive method that has been developed to assess carotenoid status in human tissues including human skin in vivo. Skin carotenoid status has been suggested as a promising biomarker for human studies. This manuscript describes research done relevant to the development of this biomarker, including its reproducibility, validity, feasibility for use in field settings, and factors that affect the biomarker such as diet, smoking, and adiposity. Recent studies have evaluated the response of the biomarker to controlled carotenoid interventions, both supplement-based and dietary [e.g., provision of a high-carotenoid fruit and vegetable (F/V)-enriched diet], demonstrating consistent response to intervention. The totality of evidence supports the use of skin carotenoid status as an objective biomarker of F/V intake, although in the cross-sectional setting, diet explains only some of the variation in this biomarker. However, this limitation is also a strength in that skin carotenoids may effectively serve as an integrated biomarker of health, with higher status reflecting greater F/V intake, lack of smoking, and lack of adiposity. Thus, this biomarker holds promise as both a health biomarker and an objective indicator of F/V intake, supporting its further development and utilization for medical and public health purposes. PMID:23823930

  15. Omega-3 polyunsaturated fatty acid biomarkers and coronary heart disease: Pooling project of 19 cohort studies

    Science.gov (United States)

    The role of omega-3 polyunsaturated fatty acids for primary prevention of coronary heart disease (CHD) remains controversial. Most prior longitudinal studies evaluated self-reported consumption rather than biomarkers. This study sought to evaluate biomarkers of seafood-derived eicosapentaenoic acid ...

  16. Study of Tools for Network Discovery and Network Mapping

    Science.gov (United States)

    2003-11-01

    DISCOVERY OptiView Console supports central and distributed architectures. OptiView Console consists of the Viewer and the Service Manager that...OptiView console. Service Manager is the engine that performs network discovery, data management, data analysis, and provides notification services...The Service Manager gives you status information and configuration control of the services that are part of the OptiView Console application. These

  17. ACE inhibition with perindopril and biomarkers of atherosclerosis and thrombosis : Results from the PERTINENT study

    NARCIS (Netherlands)

    Ceconi, C.; Fox, K.M.; Remme, W.J.; Simoons, M.L.; Deckers, J.W.; Bertrand, M.; Parrinello, G.; Kluft, C.; Blann, A.; Cokkinos, D.; Ferrari, R.

    2009-01-01

    The PERTINENT study measured biomarkers of atherosclerosis and thrombosis in a stable coronary artery disease population from EUROPA receiving ACE inhibition with perindopril 8 mg/day or placebo. Biomarkers of inflammation, C-reactive protein (CRP), fibrinogen, and tumor necrosis factor-alpha

  18. Biomarker Profiles in Women with PCOS and PCOS Offspring; A Pilot Study

    NARCIS (Netherlands)

    Daan, Nadine M P; Koster, Maria P H; de Wilde, Marlieke A|info:eu-repo/dai/nl/413993809; Dalmeijer, Gerdien W|info:eu-repo/dai/nl/343075881; Evelein, Annemieke M V; Fauser, Bart C J M|info:eu-repo/dai/nl/071281932; de Jager, Wilco|info:eu-repo/dai/nl/304816906

    2016-01-01

    OBJECTIVE: To study metabolic/inflammatory biomarker risk profiles in women with PCOS and PCOS offspring. DESIGN: Cross-sectional comparison of serum biomarkers. SETTING: University Medical Center Utrecht. PATIENTS: Hyperandrogenic PCOS women (HA-PCOS, n = 34), normoandrogenic PCOS women (NA-PCOS, n

  19. Pilot Study on the Investigation of Tear Fluid Biomarkers as an Indicator of Ocular, Neurological, and Immunological Health in Astronauts

    Science.gov (United States)

    Morton, Stephen; Crucian, Brian; Hagan, Suzanne; Satyamitra, Merriline; Daily, Anna

    2018-01-01

    The purpose of this pilot study is to investigate the collection, preparation, and analysis of tear biomarkers as a means of assessing ocular, neurological, and immunological health. At present, no published data exists on the cytokine profiles of tears from astronauts exposed to long periods of microgravity and space irradiations. In addition, no published data exist on cytokine (biomarker) profiles of tears that have been collected from irradiated non-human biological systems (primates and other animal models). A goal for the proposed pilot study is to discover novel tear biomarkers which can help inform researchers, clinicians, epidemiologist and healthcare providers about the health status of a living biological system, as well as informing them when a disease state is triggered. This would be done via analysis of the onset of expression of pro-inflammatory cytokines, leading up to the full progression of a disease (i.e. cancer, loss of vision, radiation-induced oxidative stress, cardiovascular disorders, fibrosis in major organs, bone loss). Another goal of this pilot study is to investigate the state of disease against proposed medical countermeasures, in order to determine whether the countermeasures are efficacious in preventing or mitigating these injuries. An example of an up and coming tear biomarker technology, Ascendant Dx, a clinical stage diagnostic company, is developing a screening test to detect breast cancer using proteins from tears. The team utilized Liquid Chromatography -Mass Spectrometry with Mass analysis (LC MS/MS) as a discovery platform followed by validation with ELISA to come up with a panel of protein biomarkers that can differentiate breast cancer samples from control ("cancer free") samples with results far surpassing the results of imaging techniques in use today. Continued research into additional proteins is underway to increase the sensitivity and specificity of the test and development efforts are on the way to transfer the

  20. A pilot study to evaluate the application of a generic protein standard panel for quality control of biomarker detection technologies

    Directory of Open Access Journals (Sweden)

    Valdivia Hernan J

    2011-08-01

    Full Text Available Abstract Background Protein biomarker studies are currently hampered by a lack of measurement standards to demonstrate quality, reliability and comparability across multiple assay platforms. This is especially pertinent for immunoassays where multiple formats for detecting target analytes are commonly used. Findings In this pilot study a generic panel of six non-human protein standards (50 - 10^7 pg/mL of varying abundance was prepared as a quality control (QC material. Simulated "normal" and "diseased" panels of proteins were prepared in pooled human plasma and incorporated into immunoassays using the Meso Scale Discovery® (MSD® platform to illustrate reliable detection of the component proteins. The protein panel was also evaluated as a spike-in material for a model immunoassay involving detection of ovarian cancer biomarkers within individual human plasma samples. Our selected platform could discriminate between two panels of the proteins exhibiting small differences in abundance. Across distinct experiments, all component proteins exhibited reproducible signal outputs in pooled human plasma. When individual donor samples were used, half the proteins produced signals independent of matrix effects. These proteins may serve as a generic indicator of platform reliability. Each of the remaining proteins exhibit differential signals across the distinct samples, indicative of sample matrix effects, with the three proteins following the same trend. This subset of proteins may be useful for characterising the degree of matrix effects associated with the sample which may impact on the reliability of quantifying target diagnostic biomarkers. Conclusions We have demonstrated the potential utility of this panel of standards to act as a generic QC tool for evaluating the reproducibility of the platform for protein biomarker detection independent of serum matrix effects.

  1. Multimodal lung cancer screening using the ITALUNG biomarker panel and low dose computed tomography. Results of the ITALUNG biomarker study.

    Science.gov (United States)

    Carozzi, Francesca Maria; Bisanzi, Simonetta; Carrozzi, Laura; Falaschi, Fabio; Lopes Pegna, Andrea; Mascalchi, Mario; Picozzi, Giulia; Peluso, Marco; Sani, Cristina; Greco, Luana; Ocello, Cristina; Paci, Eugenio

    2017-07-01

    Asymptomatic high-risk subjects, randomized in the intervention arm of the ITALUNG trial (1,406 screened for lung cancer), were enrolled for the ITALUNG biomarker study (n = 1,356), in which samples of blood and sputum were analyzed for plasma DNA quantification (cut off 5 ng/ml), loss of heterozygosity and microsatellite instability. The ITALUNG biomarker panel (IBP) was considered positive if at least one of the two biomarkers included in the panel was positive. Subjects with and without lung cancer diagnosis at the end of the screening cycle with LDCT (n = 517) were evaluated. Out of 18 baseline screen detected lung cancer cases, 17 were IBP positive (94%). Repeat screen-detected lung cancer cases were 18 and 12 of them positive at baseline IBP test (66%). Interval cancer cases (2-years) and biomarker tests after a suspect Non Calcific Nodule follow-up were investigated. The single test versus multimodal screening measures of accuracy were compared in a simulation within the screened ITALUNG intervention arm, considering screen-detected and interval cancer cases. Sensitivity was 90% at baseline screening. Specificity was 71 and 61% for LDCT and IBP as baseline single test, and improved at 89% with multimodal, combined screening. The positive predictive value was 4.3% for LDCT at baseline and 10.6% for multimodal screening. Multimodal screening could improve the screening efficiency at baseline and strategies for future implementation are discussed. If IBP was used as primary screening test, the LDCT burden might decrease of about 60%. © 2017 UICC.

  2. Genomic Biomarkers for Personalized Medicine: Development and Validation in Clinical Studies

    Directory of Open Access Journals (Sweden)

    Shigeyuki Matsui

    2013-01-01

    Full Text Available The establishment of high-throughput technologies has brought substantial advances to our understanding of the biology of many diseases at the molecular level and increasing expectations on the development of innovative molecularly targeted treatments and molecular biomarkers or diagnostic tests in the context of clinical studies. In this review article, we position the two critical statistical analyses of high-dimensional genomic data, gene screening and prediction, in the framework of development and validation of genomic biomarkers or signatures, through taking into consideration the possible different strategies for developing genomic signatures. A wide variety of biomarker-based clinical trial designs to assess clinical utility of a biomarker or a new treatment with a companion biomarker are also discussed.

  3. Guidelines for uniform reporting of body fluid biomarker studies in neurologic disorders

    DEFF Research Database (Denmark)

    Gnanapavan, Sharmilee; Hegen, Harald; Khalil, Michael

    2014-01-01

    -point uniform reporting format ranging from introduction, materials and methods, through to results and discussion. Each item is discussed in detail in the guidance report. CONCLUSIONS: To enhance the future development of body fluid biomarkers, it will be important to standardize the reporting......OBJECTIVE: The aim of these guidelines is to make the process of reporting body fluid biomarker studies in neurologic disorders more uniform and transparent, in line with existing standards for reporting research in other biomedical areas. Although biomarkers have been around for decades......, there are concerns over the high attrition rate of promising candidate biomarkers at later phases of development. METHODS: BioMS-eu consortium, a collaborative network working toward improving the quality of biomarker research in neurologic disorders, discussed the merits of standardizing the reporting of body fluid...

  4. Single-Nucleotide Variations in Cardiac Arrhythmias: Prospects for Genomics and Proteomics Based Biomarker Discovery and Diagnostics

    Directory of Open Access Journals (Sweden)

    Ayman Abunimer

    2014-03-01

    Full Text Available Cardiovascular diseases are a large contributor to causes of early death in developed countries. Some of these conditions, such as sudden cardiac death and atrial fibrillation, stem from arrhythmias—a spectrum of conditions with abnormal electrical activity in the heart. Genome-wide association studies can identify single nucleotide variations (SNVs that may predispose individuals to developing acquired forms of arrhythmias. Through manual curation of published genome-wide association studies, we have collected a comprehensive list of 75 SNVs associated with cardiac arrhythmias. Ten of the SNVs result in amino acid changes and can be used in proteomic-based detection methods. In an effort to identify additional non-synonymous mutations that affect the proteome, we analyzed the post-translational modification S-nitrosylation, which is known to affect cardiac arrhythmias. We identified loss of seven known S-nitrosylation sites due to non-synonymous single nucleotide variations (nsSNVs. For predicted nitrosylation sites we found 1429 proteins where the sites are modified due to nsSNV. Analysis of the predicted S-nitrosylation dataset for over- or under-representation (compared to the complete human proteome of pathways and functional elements shows significant statistical over-representation of the blood coagulation pathway. Gene Ontology (GO analysis displays statistically over-represented terms related to muscle contraction, receptor activity, motor activity, cystoskeleton components, and microtubule activity. Through the genomic and proteomic context of SNVs and S-nitrosylation sites presented in this study, researchers can look for variation that can predispose individuals to cardiac arrhythmias. Such attempts to elucidate mechanisms of arrhythmia thereby add yet another useful parameter in predicting susceptibility for cardiac diseases.

  5. Big-data-based edge biomarkers: study on dynamical drug sensitivity and resistance in individuals.

    Science.gov (United States)

    Zeng, Tao; Zhang, Wanwei; Yu, Xiangtian; Liu, Xiaoping; Li, Meiyi; Chen, Luonan

    2016-07-01

    Big-data-based edge biomarker is a new concept to characterize disease features based on biomedical big data in a dynamical and network manner, which also provides alternative strategies to indicate disease status in single samples. This article gives a comprehensive review on big-data-based edge biomarkers for complex diseases in an individual patient, which are defined as biomarkers based on network information and high-dimensional data. Specifically, we firstly introduce the sources and structures of biomedical big data accessible in public for edge biomarker and disease study. We show that biomedical big data are typically 'small-sample size in high-dimension space', i.e. small samples but with high dimensions on features (e.g. omics data) for each individual, in contrast to traditional big data in many other fields characterized as 'large-sample size in low-dimension space', i.e. big samples but with low dimensions on features. Then, we demonstrate the concept, model and algorithm for edge biomarkers and further big-data-based edge biomarkers. Dissimilar to conventional biomarkers, edge biomarkers, e.g. module biomarkers in module network rewiring-analysis, are able to predict the disease state by learning differential associations between molecules rather than differential expressions of molecules during disease progression or treatment in individual patients. In particular, in contrast to using the information of the common molecules or edges (i.e.molecule-pairs) across a population in traditional biomarkers including network and edge biomarkers, big-data-based edge biomarkers are specific for each individual and thus can accurately evaluate the disease state by considering the individual heterogeneity. Therefore, the measurement of big data in a high-dimensional space is required not only in the learning process but also in the diagnosing or predicting process of the tested individual. Finally, we provide a case study on analyzing the temporal expression

  6. Proteomics and phosphoproteomics analysis of liver in male rats exposed to bisphenol A: Mechanism of hepatotoxicity and biomarker discovery.

    Science.gov (United States)

    Vahdati Hassani, Faezeh; Abnous, Khalil; Mehri, Soghra; Jafarian, Amirhossein; Birner-Gruenberger, Ruth; Yazdian Robati, Rezvan; Hosseinzadeh, Hossein

    2018-02-01

    Bisphenol A (BPA), discovered to be an artificial estrogen, has been shown to leach from some containers and mediate oxidative damage to cells and tissues and to be involved in reproductive disorders, obesity, diabetes, and liver dysfunction. In the current study, we investigated the effects of oral chronic exposure to low dose of BPA (0.5 mg kg -1 ) on the protein and phosphoprotein expression profiles in male Wistar rat liver using a gel-based proteomics approach based on two-dimensional gel electrophoresis followed by matrix-assisted laser desorption/ionization mass spectrometry identification. Our results showed that BPA exposure affected the levels of proteins and phosphoproteins involved in diverse biological processes associated with hepatotoxicity, fatty liver, and carcinoma. Moreover, we analyzed the effects of BPA on oxidative stress by assessing levels of malondialdehyde (MDA), a marker of lipid peroxidation, and reduced glutathione (GSH), a non-enzymatic antioxidant agent, in the liver. As expected BPA induced oxidative stress indicated by increased levels of MDA and decreased GSH content in the liver. In conclusion, chronic oral exposure of rats to BPA leads to increased oxidative stress in the liver and major alterations in the liver proteome and phosphoproteome, which may contribute to the pathophysiology of liver diseases. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Bioavailability and Toxicity of Copper, Manganese, and Nickel in Paronychiurus kimi (Collembola), and Biomarker Discovery for Their Exposure.

    Science.gov (United States)

    Son, Jino; Lee, Yun-Sik; Lee, Sung-Eun; Shin, Key-Il; Cho, Kijong

    2017-01-01

    Bioavailability and toxicity of Cu, Mn, and Ni in Paronychiurus kimi were investigated after 28 days of exposure to OECD artificial soil spiked with these metals. Uptake and effect of Cu, Mn, and Ni on the reproduction of P. kimi were related to different metal fractions (water-soluble, 0.01 M CaCl 2 -extractable or porewater metal concentrations). Cu and Mn concentrations in P. kimi increased with increasing Cu and Mn concentrations in the soil, while Ni contents in P. kimi reached a plateau at a concentration higher than 200 mg/kg in soil. Both uptake and juvenile production related well to different metal fractions, suggesting that these metal fractions are suitable for assessing bioavailability and toxicity of metals in P. kimi. When toxicity for reproduction was compared, as reflected by EC 50 values, the order of metal toxicity varied depending upon how exposure concentration was expressed. Moreover, the results of proteomic analysis showed that several proteins involved in the immune system, neuronal outgrowth, and metal ion binding were up-regulated in P. kimi following short-term (7 days) exposure to sublethal level (corresponding to 50% of the EC 50 ) of Cu, Mn, or Ni, respectively. This suggests that the ecotoxicoproteomic approach seems to be a promising tool for early exposure warnings below which significant adverse effects are unlikely to occur. This study demonstrated that a combination of chemical and biological measures can provide information about metal bioavailability and toxicity to which P. kimi has been exposed.

  8. Potential Peripheral Biomarkers for the Diagnosis of Alzheimer's Disease

    Directory of Open Access Journals (Sweden)

    Seema Patel

    2011-01-01

    Full Text Available Advances in the discovery of a peripheral biomarker for the diagnosis of Alzheimer's would provide a way to better detect the onset of this debilitating disease in a manner that is both noninvasive and universally available. This paper examines the current approaches that are being used to discover potential biomarker candidates available in the periphery. The search for a peripheral biomarker that could be utilized diagnostically has resulted in an extensive amount of studies that employ several biological approaches, including the assessment of tissues, genomics, proteomics, epigenetics, and metabolomics. Although a definitive biomarker has yet to be confirmed, advances in the understanding of the mechanisms of the disease and major susceptibility factors have been uncovered and reveal promising possibilities for the future discovery of a useful biomarker.

  9. "Structured Discovery": A Modified Inquiry Approach to Teaching Social Studies.

    Science.gov (United States)

    Lordon, John

    1981-01-01

    Describes structured discovery approach to inquiry teaching which encourages the teacher to select instructional objectives, content, and questions to be answered. The focus is on individual and group activities. A brief outline using this approach to analyze Adolf Hitler is presented. (KC)

  10. Possible Biomarkers of Chronic Stress Induced Exhaustion - A Longitudinal Study.

    Science.gov (United States)

    Wallensten, Johanna; Åsberg, Marie; Nygren, Åke; Szulkin, Robert; Wallén, Håkan; Mobarrez, Fariborz; Nager, Anna

    2016-01-01

    Vascular endothelial growth factor (VEGF), epidermal growth factor (EGF) and monocyte chemotactic protein-1 (MCP-1) have previously been suggested to be potential biomarkers for chronic stress induced exhaustion. The knowledge about VEGF has increased during the last decades and supports the contention that VEGF plays an important role in stress and depression. There is scarce knowledge on the possible relationship of EGF and MCP-1 in chronic stress and depression. This study further examines the role of VEGF, EGF and MCP-1 in women with chronic stress induced exhaustion and healthy women during a follow-up period of two years. Blood samples were collected from 105 women with chronic stress induced exhaustion on at least 50% sick leave for at least three months, at inclusion (T0), after 12 months (T12) and after 24 months (T24). Blood samples were collected at inclusion (T0) in 116 physically and psychiatrically healthy women. The plasma levels of VEGF, EGF and MCP-1 were analyzed using Biochip Array Technology. Women with chronic stress induced exhaustion had significantly higher plasma levels of VEGF and EGF compared to healthy women at baseline, T12 and at T24. There was no significant difference in plasma levels of MCP-1. Plasma levels of VEGF and EGF decreased significantly in women with chronic stress induced exhaustion during the two years follow-up. The replicated findings of elevated levels of VEGF and EGF in women with chronic stress induced exhaustion and decreasing plasma levels of VEGF and EGF during the two years follow-up add important knowledge to the pathophysiology of chronic stress induced exhaustion.

  11. Molecular biomarkers for the study of childhood leukemia

    International Nuclear Information System (INIS)

    Smith, Martyn T.; McHale, Cliona M.; Wiemels, Joseph L.; Zhang, Luoping; Wiencke, John K.; Zheng, Shichun; Gunn, Laura; Skibola, Christine F.; Ma, Xiaomei; Buffler, Patricia A.

    2005-01-01

    Various specific chromosome rearrangements, including t(8;21), t(15;17), and inv(16), are found in acute myeloid leukemia (AML) and in childhood acute lymphocytic leukemia (ALL), t(12;21) and t(1;19) are common. We sequenced the translocation breakpoints of 56 patients with childhood ALL or AML harboring t(12;21), t(8;21), t(15;17), inv(16), and t(1;19), and demonstrated, with the notable exception of t(1;19), that these rearrangements are commonly detected in the neonatal blood spots (Guthrie cards) of the cases. These findings show that most childhood leukemias begin before birth and that maternal and perinatal exposures such as chemical and infectious agents are likely to be critical. Indeed, we have reported that exposure to indoor pesticides during pregnancy and the first year of life raises leukemia risk, but that later exposures do not. We have also examined aberrant gene methylation in different cytogenetic subgroups and have found striking differences between them, suggesting that epigenetic events are also important in the development of some forms of childhood leukemia. Further, at least two studies now show that the inactivating NAD(P)H:quinone acceptor oxidoreductase (NQO1) C609T polymorphism is positively associated with leukemias arising in the first 1-2 years of life and polymorphisms in the 5,10-methylenetetrahydrofolate reductase (MTHFR) gene have been associated with adult and childhood ALL. Thus, low folate intake and compounds that are detoxified by NQO1 may be important in elevating leukemia risk in children. Finally, we are exploring the use of proteomics to subclassify leukemia, because cytogenetic analysis is costly and time-consuming. Several proteins have been identified that may serve as useful biomarkers for rapidly identifying different forms of childhood leukemia

  12. Hepcidin- A Burgeoning Biomarker

    Directory of Open Access Journals (Sweden)

    Hemkant Manikrao Deshmukh

    2017-10-01

    Full Text Available The discovery of hepcidin has triggered a virtual ignition of studies on iron metabolism and related disorders. The peptide hormone hepcidin is a key homeostatic regulator of iron metabolism. The synthesis of hepcidin is induced by systemic iron levels and by inflammatory stimuli. Several human diseases are associated with variations in hepcidin concentrations. The evaluation of hepcidin in biological fluids is therefore a promising device in the diagnosis and management of medical situations in which iron metabolism is affected. Thus, it made us to recapitulate role of hepcidin as biomarker.

  13. Epigenome-Wide Association Study Identifies Cardiac Gene Patterning and a Novel Class of Biomarkers for Heart Failure.

    Science.gov (United States)

    Meder, Benjamin; Haas, Jan; Sedaghat-Hamedani, Farbod; Kayvanpour, Elham; Frese, Karen; Lai, Alan; Nietsch, Rouven; Scheiner, Christina; Mester, Stefan; Bordalo, Diana Martins; Amr, Ali; Dietrich, Carsten; Pils, Dietmar; Siede, Dominik; Hund, Hauke; Bauer, Andrea; Holzer, Daniel Benjamin; Ruhparwar, Arjang; Mueller-Hennessen, Matthias; Weichenhan, Dieter; Plass, Christoph; Weis, Tanja; Backs, Johannes; Wuerstle, Maximilian; Keller, Andreas; Katus, Hugo A; Posch, Andreas E

    2017-10-17

    Biochemical DNA modification resembles a crucial regulatory layer among genetic information, environmental factors, and the transcriptome. To identify epigenetic susceptibility regions and novel biomarkers linked to myocardial dysfunction and heart failure, we performed the first multi-omics study in myocardial tissue and blood of patients with dilated cardiomyopathy and controls. Infinium human methylation 450 was used for high-density epigenome-wide mapping of DNA methylation in left-ventricular biopsies and whole peripheral blood of living probands. RNA deep sequencing was performed on the same samples in parallel. Whole-genome sequencing of all patients allowed exclusion of promiscuous genotype-induced methylation calls. In the screening stage, we detected 59 epigenetic loci that are significantly associated with dilated cardiomyopathy (false discovery corrected P ≤0.05), with 3 of them reaching epigenome-wide significance at P ≤5×10 -8 . Twenty-seven (46%) of these loci could be replicated in independent cohorts, underlining the role of epigenetic regulation of key cardiac transcription regulators. Using a staged multi-omics study design, we link a subset of 517 epigenetic loci with dilated cardiomyopathy and cardiac gene expression. Furthermore, we identified distinct epigenetic methylation patterns that are conserved across tissues, rendering these CpGs novel epigenetic biomarkers for heart failure. The present study provides to our knowledge the first epigenome-wide association study in living patients with heart failure using a multi-omics approach. © 2017 American Heart Association, Inc.

  14. Biomarkers of Oxidative Stress Study IV. Are Antioxidants Markers of Ozone Exposure?

    Science.gov (United States)

    To determine whether the oxidative effects of ozone would result in losses of antioxidants from plasma, and possibly bronchoalveolar lavage fluid (BALF). This research is part of a comprehensive, multilaboratory validation study searching for noninvasive biomarkers of oxidative ...

  15. Endoscopic TriModal imaging and biomarkers for neoplasia conjoined: a feasibility study in Barrett's esophagus

    NARCIS (Netherlands)

    Boerwinkel, D. F.; Di Pietro, M.; Liu, X.; Shariff, M. K.; Lao-Sirieix, P.; Walker, C. E.; Visser, M.; O' Donovan, M.; Kaye, P.; Bergman, J. J. G. H. M.; Fitzgerald, R. C.

    2014-01-01

    In Barrett's esophagus (BE), the normal squamous lining of the esophagus is replaced by specialized columnar epithelium. Endoscopic surveillance with autofluorescence imaging (AFI) and molecular biomarkers have been studied separately to detect early neoplasia (EN) in BE. The combination of

  16. Asthma characteristics and biomarkers from the Airways Disease Endotyping for Personalized Therapeutics (ADEPT) longitudinal profiling study

    DEFF Research Database (Denmark)

    Silkoff, P E; Strambu, I; Laviolette, M

    2015-01-01

    BACKGROUND: Asthma is a heterogeneous disease and development of novel therapeutics requires an understanding of pathophysiologic phenotypes. The purpose of the ADEPT study was to correlate clinical features and biomarkers with molecular characteristics, by profiling asthma (NCT01274507). This re...

  17. Qualitative and quantitative characterization of plasma proteins when incorporating traveling wave ion mobility into a liquid chromatography-mass spectrometry workflow for biomarker discovery: use of product ion quantitation as an alternative data analysis tool for label free quantitation.

    Science.gov (United States)

    Daly, Charlotte E; Ng, Leong L; Hakimi, Amirmansoor; Willingale, Richard; Jones, Donald J L

    2014-02-18

    Discovery of protein biomarkers in clinical samples necessitates significant prefractionation prior to liquid chromatography-mass spectrometry (LC-MS) analysis. Integrating traveling wave ion mobility spectrometry (TWIMS) enables in-line gas phase separation which when coupled with nanoflow liquid chromatography and data independent acquisition tandem mass spectrometry, confers significant advantages to the discovery of protein biomarkers by improving separation and inherent sensitivity. Incorporation of TWIMS leads to a packet of concentrated ions which ultimately provides a significant improvement in sensitivity. As a consequence of ion packeting, when present at high concentrations, accurate quantitation of proteins can be affected due to detector saturation effects. Human plasma was analyzed in triplicate using liquid-chromatography data independent acquisition mass spectrometry (LC-DIA-MS) and using liquid-chromatography ion-mobility data independent acquisition mass spectrometry (LC-IM-DIA-MS). The inclusion of TWIMS was assessed for the effect on sample throughput, data integrity, confidence of protein and peptide identification, and dynamic range. The number of identified proteins is significantly increased by an average of 84% while both the precursor and product mass accuracies are maintained between the modalities. Sample dynamic range is also maintained while quantitation is achieved for all but the most abundant proteins by incorporating a novel data interpretation method that allows accurate quantitation to occur. This additional separation is all achieved within a workflow with no discernible deleterious effect on throughput. Consequently, TWIMS greatly enhances proteome coverage and can be reliably used for quantification when using an alternative product ion quantification strategy. Using TWIMS in biomarker discovery in human plasma is thus recommended.

  18. "Omics" of High Altitude Biology: A Urinary Metabolomics Biomarker Study of Rats Under Hypobaric Hypoxia.

    Science.gov (United States)

    Koundal, Sunil; Gandhi, Sonia; Kaur, Tanzeer; Mazumder, Avik; Khushu, Subash

    2015-12-01

    High altitude medicine is an emerging subspecialty that has crosscutting relevance for 21(st) century science and society: from sports medicine and aerospace industry to urban and rural communities living in high altitude. Recreational travel to high altitude has also become increasingly popular. Rarely has the biology of high altitude biology been studied using systems sciences and omics high-throughput technologies. In the present study, 1H-NMR-based metabolomics, along with multivariate analyses, were employed in a preclinical rat model to characterize the urinary metabolome under hypobaric hypoxia stress. Rats were exposed to simulated altitude of 6700 m above the sea level. The urine samples were collected from pre- and post-exposure (1, 3, 7, and 14 days) of hypobaric hypoxia. Metabolomics urinalysis showed alterations in TCA cycle metabolites (citrate, α-ketoglutarate), cell membrane metabolism (choline), gut micro-flora metabolism (hippurate, phenylacetylglycine), and others (N-acetyl glutamate, creatine, taurine) in response to hypobaric hypoxia. Taurine, a potential biomarker of hepatic function, was elevated after 3 days of hypobaric hypoxia, which indicates altered liver functioning. Liver histopathology confirmed the damage to tissue architecture due to hypobaric hypoxia. The metabolic pathway analysis identified taurine metabolism and TCA as important pathways that might have contributed to hypobaric hypoxia-induced pathophysiology. This study demonstrates the use of metabolomics as a promising tool for discovery and understanding of novel biochemical responses to hypobaric hypoxia exposure, providing new insight in the field of high altitude medicine and the attendant health problems that occur in response to high altitude. The findings reported here also have potential relevance for sports medicine and aviation sciences.

  19. Statistical design for a confirmatory trial with a continuous predictive biomarker: A case study.

    Science.gov (United States)

    Joshi, Adarsh; Zhang, Jenny; Fang, Liang

    2017-12-01

    With targeted therapies, it is often hypothesized that their effect may be specific to the subpopulation in which the target pathway is activated. We consider the problem of designing a confirmatory trial when the biological hypothesis of the experimental therapy is strongly supported by the pre-clinical data but limited clinical data is available to pre-define a subpopulation based on a biomarker with continuous values. The study design is further complicated if interim evaluations of the biomarker-based subpopulations are also being considered. We compared several strategies, including a naïve threshold nomination approach, a modification of the "explore and confirm" strategy proposed by Friedlin et al. (2005), and a novel biomarker sequential testing approach, motivated by the "general bivariate normal method" discussed by Wang el al. (2007), and further discussions in Spiessens and Debois (2010) and Holmgren (2017), in a setting where all-comers and biomarker subpopulation evaluations can be performed at interim analyses as well as the end of study. Based on extensive simulations, we concluded that the novel biomarker sequential testing approach out-performed other strategies when there was limited prior information for biomarker threshold determination. This design was implemented in a recently completed clinical trial of simtuzumab (RAINIER study) and provides a useful case study for designing future confirmatory clinical trials of novel targeted therapies. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Managing discovery risks--A Tevatron case study

    International Nuclear Information System (INIS)

    Bakul Banerjee

    2004-01-01

    To meet the increasing need for higher performance, Management of Fermi National Accelerator Laboratory has undertaken various projects to improve systems associated with the Tevatron high-energy particle collider located at Batavia, Illinois. One of the larger projects is the Tevatron Beam Position Monitor (BPM) system. The objective of this project is to replace the existing BPM electronics and software system that was originally installed during early 1980s, along with the original construction of the Tevatron.The original system consists of 236 beam position monitors located around the underground tunnel of the accelerator. Above ground control systems are attached to these monitors using pickup cables. When the Tevatron collider is operational, signals received from the BPMs are used to perform a number of control and diagnostic tasks. The original system can only capture the proton signals from the collider. The new system, when fully operational, will be able to capture combined proton and antiproton signals and will be able to separate the antiproton signal from the combined signal at high resolution. This significant enhancement was beyond the range of technical capabilities when the Tevatron was constructed about two decades ago. To take advantage of exceptional progress made in the hardware and software area in past two decades, Department of Energy approved funding of the BPM electronics and software replacement project. The approximate length of the project is sixteen months with a budget of four million dollars not including overhead, escalation, and contingencies. Apart from cost and schedule risks, there are two major risks associated with this research and development project. The primary risk is the risk of discovery. Since the Tevatron beam path is highly complex, BPMs have to acquire and process a large amount of data. In this environment, analysis of data to separate antiproton signals is even more complex. Finding an optimum algorithm that can

  1. Mass spectrometry for biomarker development

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Chaochao; Liu, Tao; Baker, Erin Shammel; Rodland, Karin D.; Smith, Richard D.

    2015-06-19

    Biomarkers potentially play a crucial role in early disease diagnosis, prognosis and targeted therapy. In the past decade, mass spectrometry based proteomics has become increasingly important in biomarker development due to large advances in technology and associated methods. This chapter mainly focuses on the application of broad (e.g. shotgun) proteomics in biomarker discovery and the utility of targeted proteomics in biomarker verification and validation. A range of mass spectrometry methodologies are discussed emphasizing their efficacy in the different stages in biomarker development, with a particular emphasis on blood biomarker development.

  2. Harmonization of immune biomarker assays for clinical studies.

    Science.gov (United States)

    van der Burg, Sjoerd H; Kalos, Michael; Gouttefangeas, Cécile; Janetzki, Sylvia; Ottensmeier, Christian; Welters, Marij J P; Romero, Pedro; Britten, Cedrik M; Hoos, Axel

    2011-11-09

    Assays that measure a patient's immune response play an increasingly important role in the development of immunotherapies. The inherent complexity of these assays and independent protocol development between laboratories result in high data variability and poor reproducibility. Quality control through harmonization--based on integration of laboratory-specific protocols with standard operating procedures and assay performance benchmarks--is one way to overcome these limitations. Harmonization guidelines can be widely implemented to address assay performance variables. This process enables objective interpretation and comparison of data across clinical trial sites and also facilitates the identification of relevant immune biomarkers, guiding the development of new therapies.

  3. A Case Study on the Path to Resource Discovery

    Directory of Open Access Journals (Sweden)

    Beth Guay

    2017-09-01

    Full Text Available A meeting in April 2015 explored the potential withdrawal of valuable collections of microfilm held by the University of Maryland, College Park Libraries. This resulted in a project to identify OCLC record numbers (OCN for addition to OCLC’s Chadwyck-Healey Early English Books Online (EEBO KBART file.[i] Initially, the project was an attempt to adapt cataloging workflows to a new environment in which the copy cataloging of e-resources takes place within discovery system tools rather than traditional cataloging utilities and MARC record set or individual record downloads into online catalogs. In the course of the project, it was discovered that the microfilm and e-version bibliographic records contained metadata which had not been utilized by OCLC to improve its link resolution and discovery services for digitized versions of the microfilm resources. This metadata may be advantageous to OCLC and to others in their work to transition from MARC to linked data on the Semantic Web. With MARC record field indexing and linked data implementations, this collection and others could better support scholarly research. [i] A KBART file is a file compliant with the NISO recommended practice, Knowledge Bases and Related Tools (KBART. See KBART Phase II Working Group, Knowledge Bases and Related Tools (KBART: Recommended Practice: NISO RP-9-2014 (Baltimore, MD: National Information Standards Organization (NISO, 2014, accessed March 14, 2017, http://www.niso.org/publications/rp/rp-9-2014/.

  4. Retrieval of Legal Information Through Discovery Layers: A Case Study Related to Indian Law Libraries

    Directory of Open Access Journals (Sweden)

    Kushwah, Shivpal Singh

    2016-09-01

    Full Text Available Purpose. The purpose of this paper is to analyze and evaluate discovery layer search tools for retrieval of legal information in Indian law libraries. This paper covers current practices in legal information retrieval with special reference to Indian academic law libraries, and analyses its importance in the domain of law.Design/Methodology/Approach. A web survey and observational study method are used to collect the data. Data related to the discovery tools were collected using email and further discussion held with the discovery layer/ tool /product developers and their representatives.Findings. Results show that most of the Indian law libraries are subscribing to bundles of legal information resources such as Hein Online, JSTOR, LexisNexis Academic, Manupatra, Westlaw India, SCC web, AIR Online (CDROM, and so on. International legal and academic resources are compatible with discovery tools because they support various standards related to online publishing and dissemination such as OAI/PMH, Open URL, MARC21, and Z39.50, but Indian legal resources such as Manupatra, Air, and SCC are not compatible with the discovery layers. The central index is one of the important components in a discovery search interface, and discovery layer services/tools could be useful for Indian law libraries also if they can include multiple legal and academic resources in their central index. But present practices and observations reveal that discovery layers are not providing facility to cover legal information resources. Therefore, in the present form, discovery tools are not very useful; they are an incomplete and half solution for Indian libraries because all available Indian legal resources available in the law libraries are not covered.Originality/Value. Very limited research or published literature is available in the area of discovery layers and their compatibility with legal information resources.

  5. Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic Approaches

    Science.gov (United States)

    2010-07-01

    asso- ciation between the actin microfilaments with cell motility and migration in response to androgens, possibly facilitat- ing interaction with the...may enable cell migration and metastasis of the escaped prostate tumor cells. Changes in actin microfila - ment network organization in androgen-treated...indicates actin microfilaments ; blue indicates nuclei. D) LNCaP-null vector control cells and LNCaP AR sh cells; CW22-null vector control cells and CW22

  6. Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic Approaches

    Science.gov (United States)

    2012-07-01

    epithelium of benign pathology) was generously provided by Dr. Simon W. Hayward (Department of Urological Surgery, Vanderbilt University Medical Center...Western blotting. Stable tansfectants were cloned under Geneticin selection (Invitrogen) (300µg/ml), the generated clones were maintained in RPMI 1640...Kuno N, Muramatsu H, et al. Abnormalities of sensory and memory functions in mice lacking Bsg gene. Biochem Biophys Res Commun 1997; 236:733-7. 9

  7. Influence of PCOS in Obese vs. Non-Obese women from Mesenchymal Progenitors Stem Cells and Other Endometrial Cells: An in silico biomarker discovery.

    Science.gov (United States)

    Desai, Ashvini; Madar, Inamul Hasan; Asangani, Amjad Hussain; Ssadh, Hussain Al; Tayubi, Iftikhar Aslam

    2017-01-01

    Polycystic ovary syndrome (PCOS) is endocrine system disease which affect women ages 18 to 44 where the women's hormones are imbalance. Recently it has been reported to occur in early age. Alteration of normal gene expression in PCOS has shown negative effects on long-term health issues. PCOS has been the responsible factor for the infertility in women of reproductive age group. Early diagnosis and treatment can improve the women's health suffering from PCOS. Earlier Studies shows correlation of PCOS upon insulin resistance with significant outcome, Current study shows the linkage between PCOS with obesity and non-obese patients. Gene expression datasets has been downloaded from GEO (control and PCOS affected patients). Normalization of the datasets were performed using R based on RMA and differentially expressed gene (DEG) were selected on the basis of p-value 0.05 followed by functional annotation of selected gene using Enrich R and DAVID. The DEGs were significantly related to PCOS with obesity and other risk factors involved in disease. The Gene Enrichment Analysis suggests alteration of genes and associated pathway in case of obesity. Current study provides a productive groundwork for specific biomarkers identification for the accurate diagnosis and efficient target for the treatment of PCOS.

  8. Homocysteine as a potential biomarker in bipolar disorders: a critical review and suggestions for improved studies.

    Science.gov (United States)

    Ghanizadeh, Ahmad; Singh, Ajeet B; Berk, Michael; Torabi-Nami, Mohammad

    2015-07-01

    Homocysteine levels have been associated with major depression, but associations with bipolar disorder remain less clear. Some data suggest homocysteine levels have potential as a biomarker of treatment response; however the literature is mixed. Oxidized forms of homocysteine can be potentially neurotoxic leading to glutamate toxicity, apoptotic transformation and neurodegenerative processes. High homocysteine may be a risk biomarker for bipolar disorders, but the empirical base remains too weak for firm conclusions. This review discusses the current literature for homocysteine levels as a biomarker. It is premature to foreclose the utility of homocysteine levels as a biomarker for bipolar disorder due the methodological inadequacies in the existing literature. These methodological design issues include lack of control for the confounding variables of concurrent medication, phase of bipolar disorder, gender, age, nutritional status, thyroid, liver and renal function, smoking or lean body mass. Well-powered association studies with confounder control could help shed more light on the important clinical question of homocysteine's utility as a biomarker in bipolar disorder. Future experiments are needed to examine the outcome of interventions modulating homocysteine for treating bipolar disorder. Only prospective randomized control trials will provide definitive evidence of the utility of homocysteine as a biomarker or therapeutic target.

  9. [Preclinical AD and Biomarker; from J-ADNI to AMED Preclinical Study].

    Science.gov (United States)

    Suzuki, Kazushi

    2017-07-01

    Alzheimer's disease (AD) is most prevalent cause of dementia and no cure has been discovered. Although the framework of AD clinical trials is being established utilizing results of large-scale observational studies such as the AD Neuroimaging Initiative (ADNI) and the Japanese-ADNI (J-ADNI), the development of disease-modifying therapy for Alzheimer's disease (AD) has not yet been achieved. Preclinical AD was recently defined as a new disease stage in which AD is asymptomatic but biomarkers suggest the presence of amyloid pathology. Preclinical AD has been focused as promising therapeutic time window and establishment of reliable biomarkers for preclinical AD is an urgent task. The Japanese Agency for Medical Research and Development (AMED) preclinical study is a nationwide multicenter observational study carried out by public research funding from AMED as a successor to the J-ADNI study. The goal of this study is to establish a biomarker that can quantitatively evaluate the disease progression of preclinical AD and mild cognitive impairment (MCI) or predict the progression to MCI and dementia in the future. To achieve this goal, the following assessments will be conducted over time for three years: clinical evaluations; cognitive tests; genetic testing; body fluid biomarker tests; and imaging biomarker studies such as MRI, FDG-PET, and amyloid PET. The obtained data will eventually be released to the public database.

  10. [Studies on discovery and synthesis of bioactive marine organic molecules].

    Science.gov (United States)

    Yamada, Yasuji

    2002-10-01

    This paper describes the discovery and total synthesis of bioactive marine natural products conducted in our laboratory. Clavulone, chlorovulone, bromovulone, and iodovulone are antitumor marine prostanoids isolated from the Okinawan soft coral Clavularia viridis. The synthesis of clavulone and chlorovulone was achieved from chiral 4-hydroxy-2-cyclopentenone. Marine prostanoid punaglandins 3 and 4 were synthesized via similar methodology. The chemical structures of punaglandins 3 and 4 were revised by these syntheses. Dollaberane-type diterpenoid stolonidiol and claenone were isolated from Okinawan soft coral Clavularia sp. Stolonidiol showed potent choline acetyltransferase-inducible activity in cultured basal forebrain cells. The synthesis of stolondiol and claenone was conducted via sequential Michael reaction and retro-aldol reaction. Aragusterols, isolated from the Okinawan marine sponge Xestospongia sp., are structurally unique steroids possessing a rare 26,27-cyclo structure in the side chain. Aragusterols express potent in vivo antitumor activity against L1210 leukemia in mice. The synthesis of aragusterols was carried out via steroselective construction of the side chain and stereocontrolled coupling reaction with the steroid skeleton. Kalihinane-type diterpenoid kalihinol A, isolated by Scheuer, has remarkable in vitro antimalarial activity. The absolute configuration of kalihinol A was determined by applying the CD exciton chiral method. Synthesis of kalihinene X, a kalihinane-type diterpenoid, was achieved. This synthesis involves the regioselective coupling reaction of carbanion of alkyl sulfone with epoxyalcohol and construction of cis-decalin by an intramolecular Diels-Alder reaction.

  11. Oxidative stress biomarkers and asthma characteristics in adults of the EGEA study.

    Science.gov (United States)

    Andrianjafimasy, Miora; Zerimech, Farid; Akiki, Zeina; Huyvaert, Helene; Le Moual, Nicole; Siroux, Valérie; Matran, Régis; Dumas, Orianne; Nadif, Rachel

    2017-12-01

    Asthma is an oxidative stress related disease, but associations with asthma outcomes are poorly studied in adults. We aimed to study the associations between several biomarkers related to oxidative stress and various asthma outcomes.Cross-sectional analyses were conducted in 1388 adults (mean age 43 years, 44% with asthma) from the Epidemiological Study of the Genetics and Environment of Asthma (EGEA2). Three blood antioxidant enzyme activities (biomarkers of response to oxidative stress) and exhaled breath condensate 8-isoprostanes and plasma fluorescent oxidation products (FlOPs) levels (two biomarkers of damage) were measured. Associations between biomarkers and 1) ever asthma and 2) asthma attacks, asthma control and lung function in participants with asthma were evaluated using regression models adjusted for age, sex and smoking.Biomarkers of response were unrelated to asthma outcomes. Higher 8-isoprostane levels were significantly associated with ever asthma (odds ratio for one interquartile range increase 1.28 (95% CI 1.06-1.67). Among participants with asthma, 8-isoprostane levels were negatively associated with adult-onset asthma (0.63, 0.41-0.97) and FlOPs levels were positively associated with asthma attacks (1.33, 1.07-1.65), poor asthma control (1.30, 1.02-1.66) and poor lung function (1.34, 1.04-1.74).Our results suggest that 8-isoprostanes are involved in childhood-onset asthma and FlOPs are linked to asthma expression. Copyright ©ERS 2017.

  12. Putative salivary protein biomarkers for the diagnosis of oral lichen planus: a case-control study.

    Science.gov (United States)

    Talungchit, Sineepat; Buajeeb, Waranun; Lerdtripop, Chotima; Surarit, Rudee; Chairatvit, Kongthawat; Roytrakul, Sittiruk; Kobayashi, Hiroaki; Izumi, Yuichi; Khovidhunkit, Siribang-On Piboonniyom

    2018-03-13

    Salivary protein biomarkers for screening and diagnosis of oral lichen planus (OLP) are not well-defined. The objective of this study was to identify putative protein biomarkers for OLP using proteomic approaches. Pooled unstimulated whole saliva was collected from five OLP patients and five healthy control participants. Saliva samples were then subjected to two-dimensional gel electrophoresis, followed by mass spectrometry to identify putative protein biomarkers. Subsequently, a subset of these putative biomarkers were validated in 24 OLP patients and 24 age-matched healthy control subjects, using an enzyme-linked immunosorbent assay (ELISA). Immunoblotting analyses were then performed in 3 pairs of age- and sex-matched OLP patients and healthy controls to confirm results from the ELISA study. Thirty-one protein spots were identified, corresponding to 20 unique proteins. Notably, fibrinogen fragment D and complement component C3c exhibited increased expression in OLP patients, while cystatin SA exhibited decreased expression in OLP patients, compared with healthy control subjects. ELISA analyses indicated increased expression of fibrinogen fragment D and complement component C3c, and decreased expression of cystatin SA, in the saliva of OLP patients. Statistical differences in the expression of salivary complement C3c were observed between OLP patients and healthy control subjects. Immunoblotting analyses confirmed the results of our ELISA study. Complement C3c, fibrinogen fragment D and cystatin SA may serve as salivary biomarkers for screening and/or diagnosis of OLP.

  13. Reconstructing exposures from biomarkers using exposure-pharmacokinetic modeling--A case study with carbaryl.

    Science.gov (United States)

    Brown, Kathleen; Phillips, Martin; Grulke, Christopher; Yoon, Miyoung; Young, Bruce; McDougall, Robin; Leonard, Jeremy; Lu, Jingtao; Lefew, William; Tan, Yu-Mei

    2015-12-01

    Sources of uncertainty involved in exposure reconstruction for short half-life chemicals were characterized using computational models that link external exposures to biomarkers. Using carbaryl as an example, an exposure model, the Cumulative and Aggregate Risk Evaluation System (CARES), was used to generate time-concentration profiles for 500 virtual individuals exposed to carbaryl. These exposure profiles were used as inputs into a physiologically based pharmacokinetic (PBPK) model to predict urinary biomarker concentrations. These matching dietary intake levels and biomarker concentrations were used to (1) compare three reverse dosimetry approaches based on their ability to predict the central tendency of the intake dose distribution; and (2) identify parameters necessary for a more accurate exposure reconstruction. This study illustrates the trade-offs between using non-iterative reverse dosimetry methods that are fast, less precise and iterative methods that are slow, more precise. This study also intimates the necessity of including urine flow rate and elapsed time between last dose and urine sampling as part of the biomarker sampling collection for better interpretation of urinary biomarker data of short biological half-life chemicals. Resolution of these critical data gaps can allow exposure reconstruction methods to better predict population-level intake doses from large biomonitoring studies. Published by Elsevier Inc.

  14. Use of biomarkers in ALS drug development and clinical trials.

    Science.gov (United States)

    Bakkar, Nadine; Boehringer, Ashley; Bowser, Robert

    2015-05-14

    The past decade has seen a dramatic increase in the discovery of candidate biomarkers for ALS. These biomarkers typically can either differentiate ALS from control subjects or predict disease course (slow versus fast progression). At the same time, late-stage clinical trials for ALS have failed to generate improved drug treatments for ALS patients. Incorporation of biomarkers into the ALS drug development pipeline and the use of biologic and/or imaging biomarkers in early- and late-stage ALS clinical trials have been absent and only recently pursued in early-phase clinical trials. Further clinical research studies are needed to validate biomarkers for disease progression and develop biomarkers that can help determine that a drug has reached its target within the central nervous system. In this review we summarize recent progress in biomarkers across ALS model systems and patient population, and highlight continued research directions for biomarkers that stratify the patient population to enrich for patients that may best respond to a drug candidate, monitor disease progression and track drug responses in clinical trials. It is crucial that we further develop and validate ALS biomarkers and incorporate these biomarkers into the ALS drug development process. This article is part of a Special Issue entitled ALS complex pathogenesis. Copyright © 2014 Elsevier B.V. All rights reserved.

  15. A statistical framework for genome-wide discovery of biomarker splice variations with GeneChip Human Exon 1.0 ST Arrays.

    Science.gov (United States)

    Yoshida, Ryo; Numata, Kazuyuki; Imoto, Seiya; Nagasaki, Masao; Doi, Atsushi; Ueno, Kazuko; Miyano, Satoru

    2006-01-01

    Alternative splicing is an important regulatory mechanism that generates multiple mRNA transcripts which are transcribed into functionally diverse proteins. According to the current studies, aberrant transcripts due to splicing mutations are known to cause for 15% of genetic diseases. Therefore understanding regulatory mechanism of alternative splicing is essential for identifying potential biomarkers for several types of human diseases. Most recently, advent of GeneChip Human Exon 1.0 ST Array enables us to measure genome-wide expression profiles of over one million exons. With this new microarray platform, analysis of functional gene expressions could be extended to detect not only differentially expressed genes, but also a set of specific-splicing events that are differentially observed between one or more experimental conditions, e.g. tumor or normal control cells. In this study, we address the statistical problems to identify differentially observed splicing variations from exon expression profiles. The proposed method is organized according to the following process: (1) Data preprocessing for removing systematic biases from the probe intensities. (2) Whole transcript analysis with the analysis of variance (ANOVA) to identify a set of loci that cause the alternative splicing-related to a certain disease. We test the proposed statistical approach on exon expression profiles of colorectal carcinoma. The applicability is verified and discussed in relation to the existing biological knowledge. This paper intends to highlight the potential role of statistical analysis of all exon microarray data. Our work is an important first step toward development of more advanced statistical technology. Supplementary information and materials are available from http://bonsai.ims.u-tokyo.ac.jp/~yoshidar/IBSB2006_ExonArray.htm.

  16. Sedentary leisure time behavior, snacking habits and cardiovascular biomarkers: the Inter99 Study

    DEFF Research Database (Denmark)

    Frydenlund, Gitte; Jørgensen, Torben; Toft, Ulla

    2011-01-01

    Aim: To explore the association between sedentary leisure time behavior (SLTB) and cardiovascular biomarkers, taking into account snacking habits, alcohol intake and physical activity level. Design: Cross-sectional. Methods: Study participants were recruited from the 5-year follow-up of a populat......Aim: To explore the association between sedentary leisure time behavior (SLTB) and cardiovascular biomarkers, taking into account snacking habits, alcohol intake and physical activity level. Design: Cross-sectional. Methods: Study participants were recruited from the 5-year follow...

  17. Research strategies and the use of nutrient biomarkers in studies of diet and chronic disease.

    Science.gov (United States)

    Prentice, Ross L; Sugar, Elizabeth; Wang, C Y; Neuhouser, Marian; Patterson, Ruth

    2002-12-01

    To provide an account of the state of diet and chronic disease research designs and methods; to discuss the role and potential of aggregate and analytical observational studies and randomised controlled intervention trials; and to propose strategies for strengthening each type of study, with particular emphasis on the use of nutrient biomarkers in cohort study settings. Observations from diet and disease studies conducted over the past 25 years are used to identify the strengths and weaknesses of various study designs that have been used to associate nutrient consumption with chronic disease risk. It is argued that a varied research programme, employing multiple study designs, is needed in response to the widely different biases and constraints that attend aggregate and analytical epidemiological studies and controlled intervention trials. Study design modifications are considered that may be able to enhance the reliability of aggregate and analytical nutritional epidemiological studies. Specifically, the potential of nutrient biomarker measurements that provide an objective assessment of nutrient consumption to enhance analytical study reliability is emphasised. A statistical model for combining nutrient biomarker data with self-report nutrient consumption estimates is described, and related ongoing work on odds ratio parameter estimation is outlined briefly. Finally, a recently completed nutritional biomarker study among 102 postmenopausal women in Seattle is mentioned. The statistical model will be applied to biomarker data on energy expenditure, urinary nitrogen, selected blood fatty acid measurements and various blood micronutrient concentrations, and food frequency self-report data, to identify study subject characteristics, such as body mass, age or socio-economic status, that may be associated with the measurement properties of food frequency nutrient consumption estimates. This information will be crucial for the design of a potential larger nutrient

  18. Consensus Guidelines for CSF and Blood Biobanking for CNS Biomarker Studies

    Directory of Open Access Journals (Sweden)

    Charlotte E. Teunissen

    2011-01-01

    Full Text Available There is a long history of research into body fluid biomarkers in neurodegenerative and neuroinflammatory diseases. However, only a few biomarkers in cerebrospinal fluid (CSF are being used in clinical practice. Anti-aquaporin-4 antibodies in serum are currently useful for the diagnosis of neuromyelitis optica (NMO, but we could expect novel CSF biomarkers that help define prognosis and response to treatment for this disease. One of the most critical factors in biomarker research is the inadequate powering of studies performed by single centers. Collaboration between investigators is needed to establish large biobanks of well-defined samples. A key issue in collaboration is to establish standardized protocols for biobanking to ensure that the statistical power gained by increasing the numbers of CSF samples is not compromised by pre-analytical factors. Here, consensus guidelines for CSF collection and biobanking are presented, based on the guidelines that have been published by the BioMS-eu network for CSF biomarker research. We focussed on CSF collection procedures, pre-analytical factors and high quality clinical and paraclinical information. Importantly, the biobanking protocols are applicable for CSF biobanks for research targeting any neurological disease.

  19. Consensus Guidelines for CSF and Blood Biobanking for CNS Biomarker Studies.

    Science.gov (United States)

    Teunissen, Charlotte E; Tumani, Hayrettin; Bennett, Jeffrey L; Berven, Frode S; Brundin, Lou; Comabella, Manuel; Franciotta, Diego; Federiksen, Jette L; Fleming, John O; Furlan, Roberto; Hintzen, Rogier Q; Hughes, Steve G; Jimenez, Connie R; Johnson, Michael H; Killestein, Joep; Krasulova, Eva; Kuhle, Jens; Magnone, Maria-Chiara; Petzold, Axel; Rajda, Cecilia; Rejdak, Konrad; Schmidt, Hollie K; van Pesch, Vincent; Waubant, Emmanuelle; Wolf, Christian; Deisenhammer, Florian; Giovannoni, Gavin; Hemmer, Bernhard

    2011-01-01

    There is a long history of research into body fluid biomarkers in neurodegenerative and neuroinflammatory diseases. However, only a few biomarkers in cerebrospinal fluid (CSF) are being used in clinical practice. Anti-aquaporin-4 antibodies in serum are currently useful for the diagnosis of neuromyelitis optica (NMO), but we could expect novel CSF biomarkers that help define prognosis and response to treatment for this disease. One of the most critical factors in biomarker research is the inadequate powering of studies performed by single centers. Collaboration between investigators is needed to establish large biobanks of well-defined samples. A key issue in collaboration is to establish standardized protocols for biobanking to ensure that the statistical power gained by increasing the numbers of CSF samples is not compromised by pre-analytical factors. Here, consensus guidelines for CSF collection and biobanking are presented, based on the guidelines that have been published by the BioMS-eu network for CSF biomarker research. We focussed on CSF collection procedures, pre-analytical factors and high quality clinical and paraclinical information. Importantly, the biobanking protocols are applicable for CSF biobanks for research targeting any neurological disease.

  20. The use of mass spectrometry for analysing metabolite biomarkers in epidemiology

    DEFF Research Database (Denmark)

    Lind, Mads Vendelbo; Savolainen, Otto I; Ross, Alastair B

    2016-01-01

    measurement tools. One tool that is increasingly being used for measuring biomarkers in epidemiological cohorts is mass spectrometry (MS), because of the high specificity and sensitivity of MS-based methods and the expanding range of biomarkers that can be measured. Further, the ability of MS to quantify many...... biomarkers simultaneously is advantageously compared to single biomarker methods. However, as with all methods used to measure biomarkers, there are a number of pitfalls to consider which may have an impact on results when used in epidemiology. In this review we discuss the use of MS for biomarker analyses......, focusing on metabolites and their application and potential issues related to large-scale epidemiology studies, the use of MS "omics" approaches for biomarker discovery and how MS-based results can be used for increasing biological knowledge gained from epidemiological studies. Better understanding...

  1. Predicting mortality with biomarkers: a population-based prospective cohort study for elderly Costa Ricans

    Directory of Open Access Journals (Sweden)

    Rosero-Bixby Luis

    2012-06-01

    Full Text Available Abstract Background Little is known about adult health and mortality relationships outside high-income nations, partly because few datasets have contained biomarker data in representative populations. Our objective is to determine the prognostic value of biomarkers with respect to total and cardiovascular mortality in an elderly population of a middle-income country, as well as the extent to which they mediate the effects of age and sex on mortality. Methods This is a prospective population-based study in a nationally representative sample of elderly Costa Ricans. Baseline interviews occurred mostly in 2005 and mortality follow-up went through December 2010. Sample size after excluding observations with missing values: 2,313 individuals and 564 deaths. Main outcome: prospective death rate ratios for 22 baseline biomarkers, which were estimated with hazard regression models. Results Biomarkers significantly predict future death above and beyond demographic and self-reported health conditions. The studied biomarkers account for almost half of the effect of age on mortality. However, the sex gap in mortality became several times wider after controlling for biomarkers. The most powerful predictors were simple physical tests: handgrip strength, pulmonary peak flow, and walking speed. Three blood tests also predicted prospective mortality: C-reactive protein (CRP, glycated hemoglobin (HbA1c, and dehydroepiandrosterone sulfate (DHEAS. Strikingly, high blood pressure (BP and high total cholesterol showed little or no predictive power. Anthropometric measures also failed to show significant mortality effects. Conclusions This study adds to the growing evidence that blood markers for CRP, HbA1c, and DHEAS, along with organ-specific functional reserve indicators (handgrip, walking speed, and pulmonary peak flow, are valuable tools for identifying vulnerable elderly. The results also highlight the need to better understand an anomaly noted previously in

  2. A Japanese cross-sectional multicentre study of biomarkers associated with cardiovascular disease in smokers and non-smokers

    OpenAIRE

    L?dicke, Frank; Magnette, John; Baker, Gizelle; Weitkunat, Rolf

    2015-01-01

    Abstract We performed a cross-sectional, multicentre study in Japan to detect the differences in biomarkers of exposure and cardiovascular biomarkers between smokers and non-smokers. Several clinically relevant cardiovascular biomarkers differed significantly between smokers and non-smokers, including lipid metabolism (high-density lipoprotein cholesterol concentrations ? lower in smokers), inflammation (fibrinogen and white blood cell count ? both higher in smokers), oxidative stress (8-epi-...

  3. Annual Research Review: Discovery science strategies in studies of the pathophysiology of child and adolescent psychiatric disorders: promises and limitations

    Science.gov (United States)

    Zhao, Yihong; Castellanos, F. Xavier

    2015-01-01

    Background and Scope Psychiatric science remains descriptive, with a categorical nosology intended to enhance inter-observer reliability. Increased awareness of the mismatch between categorical classifications and the complexity of biological systems drives the search for novel frameworks including discovery science in Big Data. In this review, we provide an overview of incipient approaches, primarily focused on classically categorical diagnoses such as schizophrenia (SZ), autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), but also reference convincing, if focal, advances in cancer biology, to describe the challenges of Big Data and discovery science, and outline approaches being formulated to overcome existing obstacles. Findings A paradigm shift from categorical diagnoses to a domain/structure-based nosology and from linear causal chains to complex causal network models of brain-behavior relationship is ongoing. This (r)evolution involves appreciating the complexity, dimensionality and heterogeneity of neuropsychiatric data collected from multiple sources (“broad” data) along with data obtained at multiple levels of analysis, ranging from genes to molecules, cells, circuits and behaviors (“deep” data). Both of these types of Big Data landscapes require the use and development of robust and powerful informatics and statistical approaches. Thus, we describe Big Data analysis pipelines and the promise and potential limitations in using Big Data approaches to study psychiatric disorders. Conclusion We highlight key resources available for psychopathological studies and call for the application and development of Big Data approaches to dissect the causes and mechanisms of neuropsychiatric disorders and identify corresponding biomarkers for early diagnosis. PMID:26732133

  4. Application of a repeat-measure biomarker measurement error model to 2 validation studies: examination of the effect of within-person variation in biomarker measurements.

    Science.gov (United States)

    Preis, Sarah Rosner; Spiegelman, Donna; Zhao, Barbara Bojuan; Moshfegh, Alanna; Baer, David J; Willett, Walter C

    2011-03-15

    Repeat-biomarker measurement error models accounting for systematic correlated within-person error can be used to estimate the correlation coefficient (ρ) and deattenuation factor (λ), used in measurement error correction. These models account for correlated errors in the food frequency questionnaire (FFQ) and the 24-hour diet recall and random within-person variation in the biomarkers. Failure to account for within-person variation in biomarkers can exaggerate correlated errors between FFQs and 24-hour diet recalls. For 2 validation studies, ρ and λ were calculated for total energy and protein density. In the Automated Multiple-Pass Method Validation Study (n=471), doubly labeled water (DLW) and urinary nitrogen (UN) were measured twice in 52 adults approximately 16 months apart (2002-2003), yielding intraclass correlation coefficients of 0.43 for energy (DLW) and 0.54 for protein density (UN/DLW). The deattenuated correlation coefficient for protein density was 0.51 for correlation between the FFQ and the 24-hour diet recall and 0.49 for correlation between the FFQ and the biomarker. Use of repeat-biomarker measurement error models resulted in a ρ of 0.42. These models were similarly applied to the Observing Protein and Energy Nutrition Study (1999-2000). In conclusion, within-person variation in biomarkers can be substantial, and to adequately assess the impact of correlated subject-specific error, this variation should be assessed in validation studies of FFQs. © The Author 2011. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved.

  5. A Systematic Review of Technology-Based Dietary Intake Assessment Validation Studies That Include Carotenoid Biomarkers

    Science.gov (United States)

    Burrows, Tracy L.; Rollo, Megan E.; Williams, Rebecca; Wood, Lisa G.; Garg, Manohar L.; Jensen, Megan; Collins, Clare E.

    2017-01-01

    Technological advances have allowed for the evolution of traditional dietary assessment methods. The aim of this review is to evaluate the accuracy of technology-based dietary assessment methods to determine carotenoid and/or fruit and vegetable intake when compared with carotenoid biomarkers. An online search strategy was undertaken to identify studies published in the English language up to July 2016. Inclusion criteria were adults ≥18 years, a measure of dietary intake that used information and communication technologies that specified fruit and/or vegetable intake or dietary carotenoid, a biomarker of carotenoid status and the association between the two. Sixteen articles from 13 studies were included with the majority cross-sectional in design (n = 9). Some studies used multiple dietary assessment methods with the most common: food records (n = 7), 24-h diet recalls (n = 5), food frequency questionnaires (n = 3) and diet quality assessed by dietary screener (n = 1). Two studies were directly web based, with four studies using technology that could be completed offline and data later transferred. Two studies utilised technology in the collection of dietary data, while the majority (n = 11) automated the collection in combination with nutrient analysis of the dietary data. Four studies provided correlation values between dietary carotenoids with biomarkers, ranging from r = 0.13 to 0.62 with the remaining studies comparing a measure of fruit and vegetable intake with biomarkers (r = 0.09 to 0.25). This review provides an overview of technology-based dietary assessment methods that have been used in validation studies with objectively measured carotenoids. Findings were positive with these dietary assessment measures showing mostly moderate associations with carotenoid biomarkers. PMID:28216582

  6. A Systematic Review of Technology-Based Dietary Intake Assessment Validation Studies That Include Carotenoid Biomarkers.

    Science.gov (United States)

    Burrows, Tracy L; Rollo, Megan E; Williams, Rebecca; Wood, Lisa G; Garg, Manohar L; Jensen, Megan; Collins, Clare E

    2017-02-14

    Technological advances have allowed for the evolution of traditional dietary assessment methods. The aim of this review is to evaluate the accuracy of technology-based dietary assessment methods to determine carotenoid and/or fruit and vegetable intake when compared with carotenoid biomarkers. An online search strategy was undertaken to identify studies published in the English language up to July 2016. Inclusion criteria were adults ≥18 years, a measure of dietary intake that used information and communication technologies that specified fruit and/or vegetable intake or dietary carotenoid, a biomarker of carotenoid status and the association between the two. Sixteen articles from 13 studies were included with the majority cross-sectional in design ( n = 9). Some studies used multiple dietary assessment methods with the most common: food records ( n = 7), 24-h diet recalls ( n = 5), food frequency questionnaires ( n = 3) and diet quality assessed by dietary screener ( n = 1). Two studies were directly web based, with four studies using technology that could be completed offline and data later transferred. Two studies utilised technology in the collection of dietary data, while the majority ( n = 11) automated the collection in combination with nutrient analysis of the dietary data. Four studies provided correlation values between dietary carotenoids with biomarkers, ranging from r = 0.13 to 0.62 with the remaining studies comparing a measure of fruit and vegetable intake with biomarkers ( r = 0.09 to 0.25). This review provides an overview of technology-based dietary assessment methods that have been used in validation studies with objectively measured carotenoids. Findings were positive with these dietary assessment measures showing mostly moderate associations with carotenoid biomarkers.

  7. A Systematic Review of Technology-Based Dietary Intake Assessment Validation Studies That Include Carotenoid Biomarkers

    Directory of Open Access Journals (Sweden)

    Tracy L. Burrows

    2017-02-01

    Full Text Available Technological advances have allowed for the evolution of traditional dietary assessment methods. The aim of this review is to evaluate the accuracy of technology-based dietary assessment methods to determine carotenoid and/or fruit and vegetable intake when compared with carotenoid biomarkers. An online search strategy was undertaken to identify studies published in the English language up to July 2016. Inclusion criteria were adults ≥18 years, a measure of dietary intake that used information and communication technologies that specified fruit and/or vegetable intake or dietary carotenoid, a biomarker of carotenoid status and the association between the two. Sixteen articles from 13 studies were included with the majority cross-sectional in design (n = 9. Some studies used multiple dietary assessment methods with the most common: food records (n = 7, 24-h diet recalls (n = 5, food frequency questionnaires (n = 3 and diet quality assessed by dietary screener (n = 1. Two studies were directly web based, with four studies using technology that could be completed offline and data later transferred. Two studies utilised technology in the collection of dietary data, while the majority (n = 11 automated the collection in combination with nutrient analysis of the dietary data. Four studies provided correlation values between dietary carotenoids with biomarkers, ranging from r = 0.13 to 0.62 with the remaining studies comparing a measure of fruit and vegetable intake with biomarkers (r = 0.09 to 0.25. This review provides an overview of technology-based dietary assessment methods that have been used in validation studies with objectively measured carotenoids. Findings were positive with these dietary assessment measures showing mostly moderate associations with carotenoid biomarkers.

  8. Procalcitonin and midregional proatrial natriuretic peptide as biomarkers of subclinical cerebrovascular damage: the northern manhattan study

    OpenAIRE

    Katan, Mira; Moon, Yeseon; von Eckardstein, Arnold; Spanaus, Kathartina; DeRosa, Janet; Gutierrez, Jose; DeCarli, Charles; Wright, Clinton; Sacco, Ralph; Elkind, Mitchell

    2017-01-01

    BACKGROUND AND PURPOSE: Chronic infections and cardiac dysfunction are risk factors for stroke. We hypothesized that blood biomarkers of infection (procalcitonin) and cardiac dysfunction (midregional proatrial natriuretic peptide [MR-proANP]), previously associated with small vessel stroke and cardioembolic stroke are also associated with subclinical cerebrovascular damage, including silent brain infarcts and white matter hyperintensity volume. METHODS: The NOMAS (Northern Manhattan Study)...

  9. Effect of vitamin levels on biomarkers of exposure and oxidative damage – The EXPAH study

    Czech Academy of Sciences Publication Activity Database

    Šrám, Radim; Farmer, P.; Singh, R.; Garte, S.; Kalina, I.; Popov, T. A.; Binková, Blanka; Ragin, C.; Taioli, E.

    2009-01-01

    Roč. 672, č. 2 (2009), s. 129-134 ISSN 1383-5718 Institutional research plan: CEZ:AV0Z50390512 Keywords : molecular epidemiology * cross-sectional study * biomarkers of exposure Subject RIV: DN - Health Impact of the Environment Quality Impact factor: 2.552, year: 2009

  10. Biomarkers of Exposure to Toxic Substances. Volume 5: Biomarker Pre-validation Studies Prevalidation of Urine and Serum Biomarkers Indicative of Subclinical Kidney Damage in a Nephrotoxin Model

    Science.gov (United States)

    2009-05-01

    Hepatitis C virus and alcoholic steatohepatitis (Petta et al., 2008). Since the kidney is involved in the catabolism of RBP4, renal injury such as chronic... hepatic injury (Beckett et al., 1987). Alpha GST also has been shown to be indicative of proximal tubular damage caused by proteinuria, a major cause...nephrotoxic acute kidney injury,” Toxicology., 245, 3, Mar 2008 pp. 182-93. Fernholm A, “FDA soon may support Biomarker Tests,” San Francisco Chronicle

  11. Proteomic response of mussels Mytilus galloprovincialis exposed to CuO NPs and Cu²⁺: an exploratory biomarker discovery.

    Science.gov (United States)

    Gomes, Tânia; Chora, Suze; Pereira, Catarina G; Cardoso, Cátia; Bebianno, Maria João

    2014-10-01

    CuO NPs are one of the most used metal nanomaterials nowadays with several industrial and other commercial applications. Nevertheless, less is known about the mechanisms by which these NPs inflict toxicity in mussels and to what extent it differs from Cu(2+). The aim of this study was to investigate changes in protein expression profiles in mussels Mytilus galloprovincialis exposed for 15 days to CuO NPs and Cu(2+) (10 μg L(-1)) using a proteomic approach. Results demonstrate that CuO NPs and Cu(2+) induced major changes in protein expression in mussels' showing several tissue and metal-dependent responses. CuO NPs showed a higher tendency to up-regulate proteins in the gills and down-regulate in the digestive gland, while Cu(2+) showed the opposite tendency. Distinctive sets of differentially expressed proteins were found, either common or specific to each Cu form and tissue, reflecting different mechanisms involved in their toxicity. Fifteen of the differentially expressed proteins from both tissues were identified by MALDI-TOF-TOF. Identified proteins indicate common response mechanisms induced by CuO NPs and Cu(2+), namely in cytoskeleton and cell structure (actin, α-tubulin, paramyosin), stress response (heat shock cognate 71, putative C1q domain containing protein), transcription regulation (zinc-finger BED domain-containing protein 1, nuclear receptor subfamily 1G) and energy metabolism (ATP synthase F0 subunit 6). CuO NPs alone also had a marked effect on other biological processes, namely oxidative stress (GST), proteolysis (cathepsin L) and apoptosis (caspase 3/7-1). On the other hand, Cu(2+) affected a protein associated with adhesion and mobility, precollagen-D that is associated with the detoxification mechanism of Cu(2+). Protein identification clearly showed that the toxicity of CuO NPs is not solely due to Cu(2+) dissolution and can result in mitochondrial and nucleus stress-induced cell signalling cascades that can lead to apoptosis. While the

  12. Metabolism and Biomarkers of Heterocyclic Aromatic Amines in Molecular Epidemiology Studies: Lessons Learned from Aromatic Amines

    Science.gov (United States)

    2011-01-01

    Aromatic amines and heterocyclic aromatic amines (HAAs) are structurally related classes of carcinogens that are formed during the combustion of tobacco or during the high-temperature cooking of meats. Both classes of procarcinogens undergo metabolic activation by N-hydroxylation of the exocyclic amine group, to produce a common proposed intermediate, the arylnitrenium ion, which is the critical metabolite implicated in toxicity and DNA damage. However, the biochemistry and chemical properties of these compounds are distinct and different biomarkers of aromatic amines and HAAs have been developed for human biomonitoring studies. Hemoglobin adducts have been extensively used as biomarkers to monitor occupational and environmental exposures to a number of aromatic amines; however, HAAs do not form hemoglobin adducts at appreciable levels and other biomarkers have been sought. A number of epidemiologic studies that have investigated dietary consumption of well-done meat in relation to various tumor sites reported a positive association between cancer risk and well-done meat consumption, although some studies have shown no associations between well-done meat and cancer risk. A major limiting factor in most epidemiological studies is the uncertainty in quantitative estimates of chronic exposure to HAAs and, thus, the association of HAAs formed in cooked meat and cancer risk has been difficult to establish. There is a critical need to establish long-term biomarkers of HAAs that can be implemented in molecular epidemioIogy studies. In this review article, we highlight and contrast the biochemistry of several prototypical carcinogenic aromatic amines and HAAs to which humans are chronically exposed. The biochemical properties and the impact of polymorphisms of the major xenobiotic-metabolizing enzymes on the biological effects of these chemicals are examined. Lastly, the analytical approaches that have been successfully employed to biomonitor aromatic amines and HAAs, and

  13. Chasing the effects of Pre-analytical Confounders - a Multicentre Study on CSF-AD biomarkers

    Directory of Open Access Journals (Sweden)

    Maria Joao Leitao

    2015-07-01

    Full Text Available Core cerebrospinal fluid (CSF biomarkers-Aβ42, Tau and pTau–have been recently incorporated in the revised criteria for Alzheimer’s disease (AD. However, their widespread clinical application lacks standardization. Pre-analytical sample handling and storage play an important role in the reliable measurement of these biomarkers across laboratories. In this study, we aim to surpass the efforts from previous studies, by employing a multicentre approach to assess the impact of less studied CSF pre-analytical confounders in AD-biomarkers quantification. Four different centres participated in this study and followed the same established protocol. CSF samples were analysed for three biomarkers (Aβ42, Tau and pTau and tested for different spinning conditions (temperature: Room temperature (RT vs. 4oC; speed: 500g vs. 2000g vs. 3000g, storage volume variations (25%, 50% and 75% of tube total volume as well as freezing-thaw cycles (up to 5 cyles. The influence of sample routine parameters, inter-centre variability and relative value of each biomarker (reported as normal/abnormal, was analysed. Centrifugation conditions did not influence biomarkers levels, except for samples with a high CSF total protein content, where either non centrifugation or centrifugation at RT, compared to 4ºC, led to higher Aβ42 levels. Reducing CSF storage volume from 75% to 50% of total tube capacity, decreased Aβ42 concentration (within analytical CV of the assay, whereas no change in Tau or pTau was observed. Moreover, the concentration of Tau and pTau appears to be stable up to 5 freeze-thaw cycles, whereas Aβ42 levels decrease if CSF is freeze-thawed more than 3 times. This systematic study reinforces the need for CSF centrifugation at 4ºC prior to storage and highlights the influence of storage conditions in Aβ42 levels. This study contributes to the establishment of harmonized standard operating procedures that will help reducing inter-lab variability of CSF

  14. Blood-borne biomarkers of mortality risk: systematic review of cohort studies.

    Directory of Open Access Journals (Sweden)

    Evelyn Barron

    Full Text Available Lifespan and the proportion of older people in the population are increasing, with far reaching consequences for the social, political and economic landscape. Unless accompanied by an increase in health span, increases in age-related diseases will increase the burden on health care resources. Intervention studies to enhance healthy ageing need appropriate outcome measures, such as blood-borne biomarkers, which are easily obtainable, cost-effective, and widely accepted. To date there have been no systematic reviews of blood-borne biomarkers of mortality.To conduct a systematic review to identify available blood-borne biomarkers of mortality that can be used to predict healthy ageing post-retirement.Four databases (Medline, Embase, Scopus, Web of Science were searched. We included prospective cohort studies with a minimum of two years follow up and data available for participants with a mean age of 50 to 75 years at baseline.From a total of 11,555 studies identified in initial searches, 23 fulfilled the inclusion criteria. Fifty-one blood borne biomarkers potentially predictive of mortality risk were identified. In total, 20 biomarkers were associated with mortality risk. Meta-analyses of mortality risk showed significant associations with C-reactive protein (Hazard ratios for all-cause mortality 1.42, p<0.001; Cancer-mortality 1.62, p<0.009; CVD-mortality 1.31, p = 0.033, N Terminal-pro brain natriuretic peptide (Hazard ratios for all-cause mortality 1.43, p<0.001; CHD-mortality 1.58, p<0.001; CVD-mortality 1.67, p<0.001 and white blood cell count (Hazard ratios for all-cause mortality 1.36, p = 0.001. There was also evidence that brain natriuretic peptide, cholesterol fractions, erythrocyte sedimentation rate, fibrinogen, granulocytes, homocysteine, intercellular adhesion molecule-1, neutrophils, osteoprotegerin, procollagen type III aminoterminal peptide, serum uric acid, soluble urokinase plasminogen activator receptor, tissue inhibitor of

  15. Plasma soluble prion protein, a potential biomarker for sport-related concussions: a pilot study.

    Directory of Open Access Journals (Sweden)

    Nam Pham

    Full Text Available Sport-related mild traumatic brain injury (mTBI or concussion is a significant health concern to athletes with potential long-term consequences. The diagnosis of sport concussion and return to sport decision making is one of the greatest challenges facing health care clinicians working in sports. Blood biomarkers have recently demonstrated their potential in assisting the detection of brain injury particularly, in those cases with no obvious physical injury. We have recently discovered plasma soluble cellular prion protein (PrP(C as a potential reliable biomarker for blast induced TBI (bTBI in a rodent animal model. In order to explore the application of this novel TBI biomarker to sport-related concussion, we conducted a pilot study at the University of Saskatchewan (U of S by recruiting athlete and non-athlete 18 to 30 year-old students. Using a modified quantitative ELISA method, we first established normal values for the plasma soluble PrP(C in male and female students. The measured plasma soluble PrP(C in confirmed concussion cases demonstrated a significant elevation of this analyte in post-concussion samples. Data collected from our pilot study indicates that the plasma soluble PrP(C is a potential biomarker for sport-related concussion, which may be further developed into a clinical diagnostic tool to assist clinicians in the assessment of sport concussion and return-to-play decision making.

  16. Inflammatory biomarkers and academic performance in youth. The UP & DOWN Study.

    Science.gov (United States)

    Esteban-Cornejo, Irene; Martinez-Gomez, David; Gómez-Martínez, Sonia; Del Campo-Vecino, Juan; Fernández-Santos, Jorge; Castro-Piñero, Jose; Marcos, Ascensión; Veiga, Oscar L

    2016-05-01

    Inflammation influences cognitive development in infants and older adults, however, how inflammation may affect academic development during childhood and adolescence remains to be elucidated. This study aimed to examine the association between inflammatory biomarkers and academic performance in children and adolescents. A total of 494 youth (238 girls) aged 10.6 ± 3.4 years participated in the study. Four inflammatory biomarkers were selected: C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α) and white blood cell (WBC) count. An inflammatory index was created using the above mentioned biomarkers. Academic performance was assessed through schools records. Results showed that three of the four inflammatory biomarkers (CRP, IL-6 and WBC) and the inflammatory index were negatively associated with all academic indicators (β values ranging from -0.094 to -0.217, all Pacademic indicators compared with youth in the middle tertile (scores ranging from -0.578 to -0.344) and in the lowest tertile (scores ranging from -0.678 to -0.381). In conclusion, inflammation may impair academic performance independently of body fat levels in youth. Our results are of importance because the consequences of childhood and adolescence inflammation tend to continue into adulthood. Lifestyle interventions in youth may be promising in reducing levels of inflammation beyond the reduction in body fat in order to achieve cognitive benefits. Copyright © 2016 Elsevier Inc. All rights reserved.

  17. Urinary collagen IV and πGST: potential biomarkers for detecting localized kidney injury in diabetes--a pilot study.

    LENUS (Irish Health Repository)

    Cawood, T J

    2010-01-01

    Urinary biomarkers can identify damage to specific parts of the nephron. We performed a cross-sectional study to characterise the pattern of diabetic nephropathy using urinary biomarkers of glomerular fibrosis (collagen IV), proximal tubular damage (α-glutathione-S-transferase, GST) and distal tubular damage (πGST).

  18. Circulating Long Noncoding RNAs as Potential Biomarkers of Sepsis: A Preliminary Study.

    Science.gov (United States)

    Dai, Yu; Liang, Zhixin; Li, Yulin; Li, Chunsun; Chen, Liangan

    2017-11-01

    Long noncoding RNAs (lncRNAs) are becoming promising biomarker candidates in various diseases as assessed via sequencing technologies. Sepsis is a life-threatening disease without ideal biomarkers. The aim of this study was to investigate the expression profile of lncRNAs in the peripheral blood of sepsis patients and to find potential biomarkers of sepsis. A lncRNA expression profile was performed using peripheral blood from three sepsis patients and three healthy volunteers using microarray screening. The differentially expressed lncRNAs were validated by real-time quantitative polymerase chain reaction (qRT-PCR) in a further set of 22 sepsis patients and 22 healthy volunteers. Among 1316 differentially expressed lncRNAs, 771 were downregulated and 545 were upregulated. Results of the qRT-PCR were consistent with the microarray data. lncRNA ENST00000452391.1, uc001vji.1, and uc021zxw.1 were significantly differentially expressed between sepsis patients and healthy volunteers. Moreover, lncRNA ENST00000504301.1 and ENST00000452391.1 were significantly differentially expressed between sepsis survivors and nonsurvivors. The lncRNA expression profile in the peripheral blood of sepsis patients significantly differed from that of healthy volunteers. Circulating lncRNAs may be good candidates for sepsis biomarkers.

  19. Empowering Farmers Through Discovery Learning: A Case Study Of ...

    African Journals Online (AJOL)

    The study assessed the effectiveness of Farmer Field School (FFS) training on farmers\\' competence in Integrated Pest Management of cocoa and the transfer of knowledge to others in Ondo State, Nigeria. Using structured questionnaire and interview schedule, data from 60 randomly selected respondents made up of 30 ...

  20. Transforming and enhancing metadata for enduser discovery: a case study

    Directory of Open Access Journals (Sweden)

    Edward M. Corrado

    2014-05-01

    The Libraries’ workflow and portions of code will be shared; issues and challenges involved will be discussed. While this case study is specific to Binghamton University Libraries, examples of strategies used at other institutions will also be introduced. This paper should be useful to anyone interested in describing large quantities of photographs or other materials with preexisting embedded metadata.

  1. A simulation study on estimating biomarker-treatment interaction effects in randomized trials with prognostic variables.

    Science.gov (United States)

    Haller, Bernhard; Ulm, Kurt

    2018-02-20

    To individualize treatment decisions based on patient characteristics, identification of an interaction between a biomarker and treatment is necessary. Often such potential interactions are analysed using data from randomized clinical trials intended for comparison of two treatments. Tests of interactions are often lacking statistical power and we investigated if and how a consideration of further prognostic variables can improve power and decrease the bias of estimated biomarker-treatment interactions in randomized clinical trials with time-to-event outcomes. A simulation study was performed to assess how prognostic factors affect the estimate of the biomarker-treatment interaction for a time-to-event outcome, when different approaches, like ignoring other prognostic factors, including all available covariates or using variable selection strategies, are applied. Different scenarios regarding the proportion of censored observations, the correlation structure between the covariate of interest and further potential prognostic variables, and the strength of the interaction were considered. The simulation study revealed that in a regression model for estimating a biomarker-treatment interaction, the probability of detecting a biomarker-treatment interaction can be increased by including prognostic variables that are associated with the outcome, and that the interaction estimate is biased when relevant prognostic variables are not considered. However, the probability of a false-positive finding increases if too many potential predictors are included or if variable selection is performed inadequately. We recommend undertaking an adequate literature search before data analysis to derive information about potential prognostic variables and to gain power for detecting true interaction effects and pre-specifying analyses to avoid selective reporting and increased false-positive rates.

  2. Aflatoxin biomarkers in hair may facilitate long-term exposure studies.

    Science.gov (United States)

    Mupunga, Innocent; Izaaks, Christo D; Shai, Leshweni J; Katerere, David R

    2017-04-01

    Aflatoxins are highly toxic fungal metabolites produced by some members of the Aspergillus species. They are low molecular weight lipophilic compounds that are easily absorbed from the gastrointestinal tract. They contaminate most staple foods, including maize, peanuts, peanut butter and sorghum mainly in the tropics where hot and humid conditions promote fungal growth. Absorbed aflatoxins are metabolized by the cytochrome P450 enzyme system in the liver into toxic metabolites. Aflatoxin B (AFB) 1 is the most toxic, carcinogenic and mutagenic naturally occurring toxin. Aflatoxin exposure assessment has been traditionally achieved through food use frequency questionnaires and laboratory analysis of food samples. However, estimation of individual exposure to aflatoxins based on these methods may not be accurate. The use of aflatoxin biomarkers in urine and blood for use in exposure studies has emerged in more recent times. However, the current biomarkers (e.g., AFB-N 7 -guanine and AFB 1 -albumin adduct) in use have a short half-life and are only practically useful to indicate levels over 24 h-3 months post-exposure. There is therefore an immediate need to study and evaluate alternative biomarkers in non-conventional matrices such as hair and nails. Hair analysis revealed considerable interest in forensic analysis particularly in the detection of drugs of abuse where it has emerged as a sensitive and specific technique complementary to blood and urinalysis. This article provides an overview of aflatoxins, current aflatoxin biomarkers and proposes the use of hair as a potential matrix for biomarkers of long-term aflatoxin exposure. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  3. CSF biomarkers associated with disease heterogeneity in early Parkinson's disease: the Parkinson's Progression Markers Initiative study.

    Science.gov (United States)

    Kang, Ju-Hee; Mollenhauer, Brit; Coffey, Christopher S; Toledo, Jon B; Weintraub, Daniel; Galasko, Douglas R; Irwin, David J; Van Deerlin, Vivianna; Chen-Plotkin, Alice S; Caspell-Garcia, Chelsea; Waligórska, Teresa; Taylor, Peggy; Shah, Nirali; Pan, Sarah; Zero, Pawel; Frasier, Mark; Marek, Kenneth; Kieburtz, Karl; Jennings, Danna; Tanner, Caroline M; Simuni, Tanya; Singleton, Andrew; Toga, Arthur W; Chowdhury, Sohini; Trojanowski, John Q; Shaw, Leslie M

    2016-06-01

    The development of biomarkers to predict the progression of Parkinson's disease (PD) from its earliest stage through its heterogeneous course is critical for research and therapeutic development. The Parkinson's Progression Markers Initiative (PPMI) study is an ongoing international multicenter, prospective study to validate biomarkers in drug-naïve PD patients and matched healthy controls (HC). We quantified cerebrospinal fluid (CSF) alpha-synuclein (α-syn), amyloid-beta1-42 (Aβ1-42), total tau (t-tau), and tau phosphorylated at Thr181 (p-tau) in 660 PPMI subjects at baseline, and correlated these data with measures of the clinical features of these subjects. We found that CSF α-syn, t-tau and p-tau levels, but not Aβ1-42, were significantly lower in PD compared with HC, while the diagnostic value of the individual CSF biomarkers for PD diagnosis was limited due to large overlap. The level of α-syn, but not other biomarkers, was significantly lower in PD patients with non-tremor-dominant phenotype compared with tremor-dominant phenotype. In addition, in PD patients the lowest Aβ1-42, or highest t-tau/Aβ1-42 and t-tau/α-syn quintile in PD patients were associated with more severe non-motor dysfunction compared with the highest or lowest quintiles, respectively. In a multivariate regression model, lower α-syn was significantly associated with worse cognitive test performance. APOE ε4 genotype was associated with lower levels of Aβ1-42, but neither with PD diagnosis nor cognition. Our data suggest that the measurement of CSF biomarkers in early-stage PD patients may relate to disease heterogeneity seen in PD. Longitudinal observations in PPMI subjects are needed to define their prognostic performance.

  4. Large-Scale Glycomics of Livestock: Discovery of Highly Sensitive Serum Biomarkers Indicating an Environmental Stress Affecting Immune Responses and Productivity of Holstein Dairy Cows.

    Science.gov (United States)

    Rehan, Ibrahim F; Ueda, Koichiro; Mitani, Tomohiro; Amano, Maho; Hinou, Hiroshi; Ohashi, Tetsu; Kondo, Seiji; Nishimura, Shin-Ichiro

    2015-12-09

    Because various stresses strongly influence the food productivity of livestock, biomarkers to indicate unmeasurable environmental stress in domestic animals are of increasing importance. Thermal comfort is one of the basic principles of dairy cow welfare that enhances productivity. To discover sensitive biomarkers that monitor such environmental stresses in dairy cows, we herein performed, for the first time, large-scale glycomics on 336 lactating Holstein cow serum samples over 9 months between February and October. Glycoblotting combined with MALDI-TOF/MS and DMB/HPLC allowed for comprehensive glycomics of whole serum glycoproteins. The results obtained revealed seasonal alterations in serum N-glycan levels and their structural characteristics, such as an increase in high-mannose type N-glycans in spring, the occurrence of di/triantennary complex type N-glycans terminating with two or three Neu5Gc residues in summer and autumn, and N-glycans in winter dominantly displaying Neu5Ac. A multivariate analysis revealed a correlation between the serum expression levels of these season-specific glycoforms and productivity.

  5. Robust Selection Algorithm (RSA for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

    Directory of Open Access Journals (Sweden)

    Vasudha Sehgal

    Full Text Available MicroRNAs (miRNAs play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.

  6. Proteomic response of mussels Mytilus galloprovincialis exposed to CuO NPs and Cu{sup 2+}: An exploratory biomarker discovery

    Energy Technology Data Exchange (ETDEWEB)

    Gomes, Tânia, E-mail: tania.gomes@niva.no; Chora, Suze; Pereira, Catarina G.; Cardoso, Cátia; Bebianno, Maria João

    2014-10-15

    Highlights: • Different protein expression patterns, tissue and Cu form dependent. • Different cellular mechanisms involved in CuO NPs and Cu{sup 2+} toxicity. • CuO NPs toxicity mediated by cell signalling cascades that result in apoptosis. • Caspase 3/7–1, catL, Zn-finger, precol-D as new molecular targets for both Cu forms in mussels. - Abstract: CuO NPs are one of the most used metal nanomaterials nowadays with several industrial and other commercial applications. Nevertheless, less is known about the mechanisms by which these NPs inflict toxicity in mussels and to what extent it differs from Cu{sup 2+}. The aim of this study was to investigate changes in protein expression profiles in mussels Mytilus galloprovincialis exposed for 15 days to CuO NPs and Cu{sup 2+} (10 μg L{sup −1}) using a proteomic approach. Results demonstrate that CuO NPs and Cu{sup 2+} induced major changes in protein expression in mussels’ showing several tissue and metal-dependent responses. CuO NPs showed a higher tendency to up-regulate proteins in the gills and down-regulate in the digestive gland, while Cu{sup 2+} showed the opposite tendency. Distinctive sets of differentially expressed proteins were found, either common or specific to each Cu form and tissue, reflecting different mechanisms involved in their toxicity. Fifteen of the differentially expressed proteins from both tissues were identified by MALDI-TOF-TOF. Identified proteins indicate common response mechanisms induced by CuO NPs and Cu{sup 2+}, namely in cytoskeleton and cell structure (actin, α-tubulin, paramyosin), stress response (heat shock cognate 71, putative C1q domain containing protein), transcription regulation (zinc-finger BED domain-containing protein 1, nuclear receptor subfamily 1G) and energy metabolism (ATP synthase F0 subunit 6). CuO NPs alone also had a marked effect on other biological processes, namely oxidative stress (GST), proteolysis (cathepsin L) and apoptosis (caspase 3/7-1). On

  7. Knowledge Discovery Process: Case Study of RNAV Adherence of Radar Track Data

    Science.gov (United States)

    Matthews, Bryan

    2018-01-01

    This talk is an introduction to the knowledge discovery process, beginning with: identifying the problem, choosing data sources, matching the appropriate machine learning tools, and reviewing the results. The overview will be given in the context of an ongoing study that is assessing RNAV adherence of commercial aircraft in the national airspace.

  8. Biomarker discovery in biological specimens (plasma, hair, liver and kidney) of diabetic mice based upon metabolite profiling using ultra-performance liquid chromatography with electrospray ionization time-of-flight mass spectrometry.

    Science.gov (United States)

    Tsutsui, Haruhito; Maeda, Toshio; Min, Jun Zhe; Inagaki, Shinsuke; Higashi, Tatsuya; Kagawa, Yoshiyuki; Toyo'oka, Toshimasa

    2011-05-12

    The number of diabetic patients has recently been increasing worldwide. Diabetes is a multifactorial disorder based on environmental factors and genetic background. In many cases, diabetes is asymptomatic for a long period and the patient is not aware of the disease. Therefore, the potential biomarker(s), leading to the early detection and/or prevention of diabetes mellitus, are strongly required. However, the diagnosis of the prediabetic state in humans is a very difficult issue, because the lifestyle is variable in each person. Although the development of a diagnosis method in humans is the goal of our research, the extraction and structural identification of biomarker candidates in several biological specimens (i.e., plasma, hair, liver and kidney) of ddY strain mice, which undergo naturally occurring diabetes along with aging, were carried out based upon a metabolite profiling study. The low-molecular-mass compounds including metabolites in the biological specimens of diabetic mice (ddY-H) and normal mice (ddY-L) were globally separated by ultra-performance liquid chromatography (UPLC) using different reversed-phase columns (i.e., T3-C18 and HS-F5) and detected by electrospray ionization time-of-flight mass spectrometry (ESI-TOF-MS). The biomarker candidates related to diabetes mellitus were extracted from a multivariate statistical analysis, such as an orthogonal partial least-squares-discriminant analysis (OPLS-DA), followed by a database search, such as ChemSpider, KEGG and HMDB. Many metabolites and unknown compounds in each biological specimen were detected as the biomarker candidates related to diabetic mellitus. Among them, the elucidation of the chemical structures of several possible metabolites, including more than two biological specimens, was carried out along with the comparison of the tandem MS/MS analyses using authentic compounds. One metabolite was clearly identified as N-acetyl-L-leucine based upon the MS/MS spectra and the retention time on

  9. Advances in biomarkers of major depressive disorder.

    Science.gov (United States)

    Huang, Tiao-Lai; Lin, Chin-Chuen

    2015-01-01

    Major depressive disorder (MDD) is characterized by mood, vegetative, cognitive, and even psychotic symptoms and signs that can cause substantial impairments in quality of life and functioning. Biomarkers are measurable indicators that could help diagnosing MDD or predicting treatment response. In this chapter, lipid profiles, immune/inflammation, and neurotrophic factor pathways that have long been implicated in the pathogenesis of MDD are discussed. Then, pharmacogenetics and epigenetics of serotonin transport and its metabolism pathway, brain-derived neurotrophic factor, and abnormality of hypothalamo-pituitary-adrenocortical axis also revealed new biomarkers. Lastly, new techniques, such as proteomics and metabolomics, which allow researchers to approach the studying of MDD with new directions and make new discoveries are addressed. In the future, more data are needed regarding pathophysiology of MDD, including protein levels, single nucleotide polymorphism, epigenetic regulation, and clinical data in order to better identify reliable and consistent biomarkers for diagnosis, treatment choice, and outcome prediction. © 2015 Elsevier Inc. All rights reserved.

  10. Ultra-high throughput sequencing-based small RNA discovery and discrete statistical biomarker analysis in a collection of cervical tumours and matched controls

    Directory of Open Access Journals (Sweden)

    Gu Sam

    2010-05-01

    Full Text Available Abstract Background Ultra-high throughput sequencing technologies provide opportunities both for discovery of novel molecular species and for detailed comparisons of gene expression patterns. Small RNA populations are particularly well suited to this analysis, as many different small RNAs can be completely sequenced in a single instrument run. Results We prepared small RNA libraries from 29 tumour/normal pairs of human cervical tissue samples. Analysis of the resulting sequences (42 million in total defined 64 new human microRNA (miRNA genes. Both arms of the hairpin precursor were observed in twenty-three of the newly identified miRNA candidates. We tested several computational approaches for the analysis of class differences between high throughput sequencing datasets and describe a novel application of a log linear model that has provided the most effective analysis for this data. This method resulted in the identification of 67 miRNAs that were differentially-expressed between the tumour and normal samples at a false discovery rate less than 0.001. Conclusions This approach can potentially be applied to any kind of RNA sequencing data for analysing differential sequence representation between biological sample sets.

  11. Personality biomarkers of pathological gambling: A machine learning study.

    Science.gov (United States)

    Cerasa, Antonio; Lofaro, Danilo; Cavedini, Paolo; Martino, Iolanda; Bruni, Antonella; Sarica, Alessia; Mauro, Domenico; Merante, Giuseppe; Rossomanno, Ilaria; Rizzuto, Maria; Palmacci, Antonio; Aquino, Benedetta; De Fazio, Pasquale; Perna, Giampaolo R; Vanni, Elena; Olivadese, Giuseppe; Conforti, Domenico; Arabia, Gennarina; Quattrone, Aldo

    2018-01-15

    The application of artificial intelligence to extract predictors of Gambling disorder (GD) is a new field of study. A plethora of studies have suggested that maladaptive personality dispositions may serve as risk factors for GD. Here, we used Classification and Regression Trees algorithm to identify multivariate predictive patterns of personality profiles that could identify GD patients from healthy controls at an individual level. Forty psychiatric patients, recruited from specialized gambling clinics, without any additional comorbidity and 160 matched healthy controls completed the Five-Factor model of personality as measured by the NEO-PI-R, which were used to build the classification model. Classification algorithm was able to discriminate individuals with GD from controls with an AUC of 77.3% (95% CI 0.65-0.88, p<0.0001). A multidimensional construct of traits including sub-facets of openness, neuroticism and conscientiousness was employed by algorithm for classification detection. To the best of our knowledge, this is the first study that combines behavioral data with machine learning approach useful to extract multidimensional features characterizing GD realm. Our study provides a proof-of-concept demonstrating the potential of the proposed approach for GD diagnosis. The multivariate combination of personality facets characterizing individuals with GD can potentially be used to assess subjects' vulnerability in clinical setting. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Integrative analysis to select cancer candidate biomarkers to targeted validation

    Science.gov (United States)

    Heberle, Henry; Domingues, Romênia R.; Granato, Daniela C.; Yokoo, Sami; Canevarolo, Rafael R.; Winck, Flavia V.; Ribeiro, Ana Carolina P.; Brandão, Thaís Bianca; Filgueiras, Paulo R.; Cruz, Karen S. P.; Barbuto, José Alexandre; Poppi, Ronei J.; Minghim, Rosane; Telles, Guilherme P.; Fonseca, Felipe Paiva; Fox, Jay W.; Santos-Silva, Alan R.; Coletta, Ricardo D.; Sherman, Nicholas E.; Paes Leme, Adriana F.

    2015-01-01

    Targeted proteomics has flourished as the method of choice for prospecting for and validating potential candidate biomarkers in many diseases. However, challenges still remain due to the lack of standardized routines that can prioritize a limited number of proteins to be further validated in human samples. To help researchers identify candidate biomarkers that best characterize their samples under study, a well-designed integrative analysis pipeline, comprising MS-based discovery, feature selection methods, clustering techniques, bioinformatic analyses and targeted approaches was performed using discovery-based proteomic data from the secretomes of three classes of human cell lines (carcinoma, melanoma and non-cancerous). Three feature selection algorithms, namely, Beta-binomial, Nearest Shrunken Centroids (NSC), and Support Vector Machine-Recursive Features Elimination (SVM-RFE), indicated a panel of 137 candidate biomarkers for carcinoma and 271 for melanoma, which were differentially abundant between the tumor classes. We further tested the strength of the pipeline in selecting candidate biomarkers by immunoblotting, human tissue microarrays, label-free targeted MS and functional experiments. In conclusion, the proposed integrative analysis was able to pre-qualify and prioritize candidate biomarkers from discovery-based proteomics to targeted MS. PMID:26540631

  13. Banking of biological fluids for studies of disease-associated protein biomarkers

    DEFF Research Database (Denmark)

    Rasmussen, Anne-Sofie Schrohl; Würtz, Sidse Ørnbjerg; Kohn, Elise

    2008-01-01

    With the increasing demand of providing personalized medicine the need for biobanking of biological material from individual patients has increased. Such samples are essential for molecular research aimed at characterizing diseases at several levels ranging from epidemiology and diagnostic...... and as a surrogate response marker. Many types of biological fluids or tissues can be collected and stored in biorepositories. Samples of blood can be further processed into plasma and serum, and tissue pieces can be either frozen or fixed in formalin and then embedded into paraffin. The present review focuses...... on biological fluids, especially serum and plasma, intended for study of protein biomarkers. In biomarker studies the process from the decision to take a sample from an individual to the moment the sample is safely placed in the biobank consists of several phases including collection of samples, transport...

  14. Biomarkers in patients with Chronic Obstructive Pulmonary Disease in general practice: A prospective cohort study

    DEFF Research Database (Denmark)

    Waldorff, Frans Boch; Halling, Anders; Ledderer, Loni

    treated in primary care and to determine the added value of selected biomarkers such as microfibrillar-associated protein 4 (MFAP4) and surfactant protein D (SP-D). Methods: Prospective cohort study comprising COPD patients. A total of 38 Danish practices were included in the study. Criteria for inclusion...... were a diagnosis of COPD (ICPC code R95-), age ≥ 40 years, Danish language speaking, no severe psychiatric or cognitive disease and ability to visit the GP surgery. Prevalent as well as incident patients diagnosed with COPD were eligible. Baseline data included a patient questionnaire and validated...... questionnaires regarding respiration, activity of daily living, depression and fatigue. Further, clinical indicators of the patient’s COPD status were obtained ad well as blood samples for biomarkers. End points will include rates of exacerbations, hospitalizations, deaths and decline in lung function. Results...

  15. Behavioral studies on anxiety and depression in a drug discovery environment: keys to a successful future.

    Science.gov (United States)

    Bouwknecht, J Adriaan

    2015-04-15

    The review describes a personal journey through 25 years of animal research with a focus on the contribution of rodent models for anxiety and depression to the development of new medicines in a drug discovery environment. Several classic acute models for mood disorders are briefly described as well as chronic stress and disease-induction models. The paper highlights a variety of factors that influence the quality and consistency of behavioral data in a laboratory setting. The importance of meta-analysis techniques for study validation (tolerance interval) and assay sensitivity (Monte Carlo modeling) are demonstrated by examples that use historic data. It is essential for successful discovery of new potential drugs to maintain a high level of control in animal research and to bridge knowledge across in silico modeling, and in vitro and in vivo assays. Today, drug discovery is a highly dynamic environment in search of new types of treatments and new animal models which should be guided by enhanced two-way translation between bench and bed. Although productivity has been disappointing in the search of new and better medicines in psychiatry over the past decades, there has been and will always be an important role for in vivo models in-between preclinical discovery and clinical development. The right balance between good science and proper judgment versus a decent level of innovation, assay development and two-way translation will open the doors to a very bright future. Copyright © 2014 Elsevier B.V. All rights reserved.

  16. Open Access Could Transform Drug Discovery: A Case Study of JQ1.

    Science.gov (United States)

    Arshad, Zeeshaan; Smith, James; Roberts, Mackenna; Lee, Wen Hwa; Davies, Ben; Bure, Kim; Hollander, Georg A; Dopson, Sue; Bountra, Chas; Brindley, David

    2016-01-01

    The cost to develop a new drug from target discovery to market is a staggering $1.8 billion, largely due to the very high attrition rate of drug candidates and the lengthy transition times during development. Open access is an emerging model of open innovation that places no restriction on the use of information and has the potential to accelerate the development of new drugs. To date, no quantitative assessment has yet taken place to determine the effects and viability of open access on the process of drug translation. This need is addressed within this study. The literature and intellectual property landscapes of the drug candidate JQ1, which was made available on an open access basis when discovered, and conventionally developed equivalents that were not are compared using the Web of Science and Thomson Innovation software, respectively. Results demonstrate that openly sharing the JQ1 molecule led to a greater uptake by a wider and more multi-disciplinary research community. A comparative analysis of the patent landscapes for each candidate also found that the broader scientific diaspora of the publically released JQ1 data enhanced innovation, evidenced by a greater number of downstream patents filed in relation to JQ1. The authors' findings counter the notion that open access drug discovery would leak commercial intellectual property. On the contrary, JQ1 serves as a test case to evidence that open access drug discovery can be an economic model that potentially improves efficiency and cost of drug discovery and its subsequent commercialization.

  17. Biosignature Discovery for Substance Use Disorders Using Statistical Learning.

    Science.gov (United States)

    Baurley, James W; McMahan, Christopher S; Ervin, Carolyn M; Pardamean, Bens; Bergen, Andrew W

    2018-02-01

    There are limited biomarkers for substance use disorders (SUDs). Traditional statistical approaches are identifying simple biomarkers in large samples, but clinical use cases are still being established. High-throughput clinical, imaging, and 'omic' technologies are generating data from SUD studies and may lead to more sophisticated and clinically useful models. However, analytic strategies suited for high-dimensional data are not regularly used. We review strategies for identifying biomarkers and biosignatures from high-dimensional data types. Focusing on penalized regression and Bayesian approaches, we address how to leverage evidence from existing studies and knowledge bases, using nicotine metabolism as an example. We posit that big data and machine learning approaches will considerably advance SUD biomarker discovery. However, translation to clinical practice, will require integrated scientific efforts. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Biomarkers used in studying air pollution exposure during pregnancy and perinatal outcomes: a review.

    Science.gov (United States)

    Desai, Gauri; Chu, Li; Guo, Yanjun; Myneni, Ajay A; Mu, Lina

    2017-09-01

    This review focuses on studies among pregnant women that used biomarkers to assess air pollution exposure, or to understand the mechanisms by which it affects perinatal outcomes. We searched PubMed and Google scholar databases to find articles. We found 29 articles, mostly consisting of cohort studies. Interpolation models were most frequently used to assess exposure. The most consistent positive association was between polycyclic aromatic hydrocarbon (PAH) exposure during entire pregnancy and cord blood PAH DNA adducts. Exposure to particulate matter (PM) and nitrogen dioxide (NO 2 ) showed consistent inverse associations with mitochondrial DNA (mtDNA) content, particularly in the third trimester of pregnancy. No single pollutant showed strong associations with all the biomarkers included in this review. C-reactive proteins (CRPs) and oxidative stress markers increased, whereas telomere length decreased with increasing air pollution exposure. Placental global DNA methylation and mtDNA methylation showed contrasting results with air pollution exposure, the mechanism behind which is unclear. Most studies except those on PAH DNA adducts and mtDNA content provided insufficient evidence for characterizing a critical exposure window. Further research using biomarkers is warranted to understand the relationship between air pollution and perinatal outcomes.

  19. Storage Time and Urine Biomarker Levels in the ASSESS-AKI Study.

    Directory of Open Access Journals (Sweden)

    Kathleen D Liu

    Full Text Available Although stored urine samples are often used in biomarker studies focused on acute and chronic kidney disease, how storage time impacts biomarker levels is not well understood.866 subjects enrolled in the NIDDK-sponsored ASsessment, Serial Evaluation, and Subsequent Sequelae in Acute Kidney Injury (ASSESS-AKI Study were included. Samples were processed under standard conditions and stored at -70°C until analyzed. Kidney injury molecule-1 (KIM-1, neutrophil gelatinase-associated lipocalin (NGAL, interleukin-18 (IL-18, and liver fatty acid binding protein (L-FABP were measured in urine samples collected during the index hospitalization or an outpatient visit 3 months later. Mixed effects models were used to determine the effect of storage time on biomarker levels and stratified by visit.Median storage was 17.8 months (25-75% IQR 10.6-23.7 for samples from the index hospitalization and 14.6 months (IQR 7.3-20.4 for outpatient samples. In the mixed effects models, the only significant association between storage time and biomarker concentration was for KIM-1 in outpatient samples, where each month of storage was associated with a 1.7% decrease (95% CI -3% to -0.3%. There was no relationship between storage time and KIM-1 levels in samples from the index hospitalization.There was no significant impact of storage time over a median of 18 months on urine KIM-1, NGAL, IL-18 or L-FABP in hospitalized samples; a statistically significant effect towards a decrease over time was noted for KIM-1 in outpatient samples. Additional studies are needed to determine whether longer periods of storage at -70°C systematically impact levels of these analytes.

  20. Cancer therapy trials employing level-of-evidence-1 disease forecast cancer biomarkers uPA and its inhibitor PAI-1

    DEFF Research Database (Denmark)

    Schmitt, Manfred; Harbeck, Nadia; Brünner, Nils

    2011-01-01

    Clinical research on cancer biomarkers is essential in understanding recent discoveries in cancer biology and heterogeneity of the cancer disease. However, there are only a few examples of clinically useful studies that have identified cancer biomarkers with clinical benefit. Urokinase-type plasm...

  1. Inflammatory Biomarkers and Risk of Schizophrenia: A 2-Sample Mendelian Randomization Study.

    Science.gov (United States)

    Hartwig, Fernando Pires; Borges, Maria Carolina; Horta, Bernardo Lessa; Bowden, Jack; Davey Smith, George

    2017-12-01

    Positive associations between inflammatory biomarkers and risk of psychiatric disorders, including schizophrenia, have been reported in observational studies. However, conventional observational studies are prone to bias, such as reverse causation and residual confounding, thus limiting our understanding of the effect (if any) of inflammatory biomarkers on schizophrenia risk. To evaluate whether inflammatory biomarkers have an effect on the risk of developing schizophrenia. Two-sample mendelian randomization study using genetic variants associated with inflammatory biomarkers as instrumental variables to improve inference. Summary association results from large consortia of candidate gene or genome-wide association studies, including several epidemiologic studies with different designs, were used. Gene-inflammatory biomarker associations were estimated in pooled samples ranging from 1645 to more than 80 000 individuals, while gene-schizophrenia associations were estimated in more than 30 000 cases and more than 45 000 ancestry-matched controls. In most studies included in the consortia, participants were of European ancestry, and the prevalence of men was approximately 50%. All studies were conducted in adults, with a wide age range (18 to 80 years). Genetically elevated circulating levels of C-reactive protein (CRP), interleukin-1 receptor antagonist (IL-1Ra), and soluble interleukin-6 receptor (sIL-6R). Risk of developing schizophrenia. Individuals with schizophrenia or schizoaffective disorders were included as cases. Given that many studies contributed to the analyses, different diagnostic procedures were used. The pooled odds ratio estimate using 18 CRP genetic instruments was 0.90 (random effects 95% CI, 0.84-0.97; P = .005) per 2-fold increment in CRP levels; consistent results were obtained using different mendelian randomization methods and a more conservative set of instruments. The odds ratio for sIL-6R was 1.06 (95% CI, 1.01-1.12; P = .02

  2. New sepsis biomarkers

    Directory of Open Access Journals (Sweden)

    Dolores Limongi

    2016-06-01

    Full Text Available Sepsis remains a leading cause of death in the intensive care units and in all age groups worldwide. Early recognition and diagnosis are key to achieving improved outcomes. Therefore, novel biomarkers that might better inform clinicians treating such patients are surely needed. The main attributes of successful biomarkers would be high sensitivity, specificity, possibility of bedside monitoring and financial accessibility. A panel of sepsis biomarkers along with currently used laboratory tests will facilitate earlier diagnosis, timely treatment and improved outcome may be more effective than single biomarkers. In this review, we summarize the most recent advances on sepsis biomarkers evaluated in clinical and experimental studies.

  3. Can unexplained infertility be evaluated by a new immunological four-biomarkers panel? A pilot study.

    Science.gov (United States)

    Maxia, Nicoletta; Uccella, Stefano; Ersettigh, Gabriele; Fantuzzi, Mario; Manganini, Massimiliano; Scozzesi, Alessandro; Colognato, Renato

    2018-04-01

    Inflammation and oxidative stress are known to be triggering factors for a decrease of the pregnancy rate like maternal immunosuppression. Under these circumstances our study was performed to verify four immunological biomarkers (IMMUNOX Panel) in terms of incidence in a sine-causa infertile population and the overall pregnancy rate when the Panel was showing some non-physiologic values. Sera of 86 women affected by unexplained infertility were screened for the IMMUNOX panel of biomarkers composed by: tumor necrosis factor alpha (TNF-α,) glycodelin (GLY), total oxidative status (TOS), and complement activity toxic factor (CATF). When at least one of the biomarkers tested was showing values outside the physiologic range, the woman was considered IMMUNOX-Positive. The first data was indented to verify the incidence of the women with an IMMUNOX-positive panel. Results show that 19.8%, 18.6%, 25.6%, and 47.7% were IMMUNOX-positive for GLY, TNF-α, TOS and CATF respectively. The overall incidence of IMMUNOX-positive patients, with at least one biomarker positive was 70,9%. Subsequently we have analysed the correlation between IMMUNOX Panel positivity and the pregnancy rate. The pregnancy rate in a subgroup (N.=55) of the entire population tested (N.=86) was 2.9% and 36.6% for the IMMUNOX-positive and IMMUNOX-negative patients respectively. Further validation studies are needed to prove that there is a correlation between unexplained infertility and immunological disorders screened by the IMMUNOX Panel, nevertheless our data shows that this diagnostic approach may be helpful to predict and to identify women at higher risk of IVF cycles failure.

  4. Thrombelastography and biomarker profiles in acute coagulopathy of trauma: a prospective study

    Directory of Open Access Journals (Sweden)

    Larsen Claus F

    2011-10-01

    Full Text Available Abstract Background Severe injury induces an acute coagulopathy associated with increased mortality. This study compared the Thrombelastography (TEG and biomarker profiles upon admission in trauma patients. Methods Prospective observational study of 80 trauma patients admitted to a Level I Trauma Centre. Data on demography, biochemistry including standard coagulation tests, hematology, transfusions, Injury Severity Score (ISS and TEG were recorded. Retrospective analysis of thawed plasma/serum for biomarkers reflecting tissue injury (histone-complexed DNA fragments, sympathoadrenal activation (adrenaline, noradrenaline, coagulation activation/inhibition and fibrinolysis (sCD40L, protein C, activated Protein C, tissue-type plasminogen activator, plasminogen activator inhibitor-1, D-dimer, prothrombinfragment 1+2, plasmin/α2-antiplasmin complex, thrombin/antithrombin complex, tissue factor pathway inhibitor, antithrombin, von willebrand factor, factor XIII. Comparison of patients stratified according to ISS/TEG maximum clot strength. Linear regression analysis of variables associated with clot strength. Results Trauma patients had normal (86%, hypercoagulable (11% or hypocoagulable (1% TEG clot strength; one had primary hyperfibrinolysis. Hypercoagulable patients had higher age, fibrinogen and platelet count (all p 10 red blood cells the initial 24 h. Patients with normal or hypercoagulable TEG clot strength had comparable biomarker profiles, but the few patients with hypocoagulable TEG clot strength and/or hyperfibrinolysis had very different biomarker profiles. Increasing ISS was associated with higher levels of catecholamines, histone-complexed DNA fragments, sCD40L, activated protein C and D-dimer and reduced levels of non-activated protein C, antithrombin, fibrinogen and factor XIII (all p 26. In patients with ISS > 26, adrenaline and sCD40L were independently negatively associated with clot strength. Conclusions Trauma patients displayed

  5. Biomarker Profiles in Women with PCOS and PCOS Offspring; A Pilot Study.

    Science.gov (United States)

    Daan, Nadine M P; Koster, Maria P H; de Wilde, Marlieke A; Dalmeijer, Gerdien W; Evelein, Annemieke M V; Fauser, Bart C J M; de Jager, Wilco

    2016-01-01

    To study metabolic/inflammatory biomarker risk profiles in women with PCOS and PCOS offspring. Cross-sectional comparison of serum biomarkers. University Medical Center Utrecht. Hyperandrogenic PCOS women (HA-PCOS, n = 34), normoandrogenic PCOS women (NA-PCOS, n = 34), non-PCOS reference population (n = 32), PCOS offspring (n = 14, age 6-8 years), and a paedriatic reference population (n = 30). Clustering profile of adipocytokines (IL-1b, IL-6, IL-13, IL-17, IL-18, TNF-α, adiponectin, adipsin, leptin, chemerin, resistin, RBP4, DPP-IV/sCD26, CCL2/MCP-1), growth factors (PIGF, VEGF, sVEGF-R1), soluble cell adhesion molecules (sICAM-1/sCD54, sVCAM-1/sCD106), and other inflammatory related proteases (MMP-9, S100A8, Cathepsin S). Differences in median biomarker concentrations between groups, and associations with the free androgen index (FAI; Testosterone/SHBG x100). The cluster analysis identified leptin, RBP-4, DPP-IV and adiponectin as potential discriminative markers for HA-PCOS with a specifically strong correlation in cases with increased BMI. Leptin (R2 = 0.219) and adiponectin (R2 = 0.182) showed the strongest correlation with the FAI. When comparing median protein concentrations adult PCOS women with or without hyperandrogenemia, the most profound differences were observed for leptin (P PCOS offspring, MMP-9 (P = 0.001) and S100A8 (P PCOS and non-PCOS controls, mostly influenced by BMI. Leptin and adiponectin showed the strongest correlation with the FAI in adult women with PCOS. In PCOS offspring other inflammatory biomarkers (MMP-9, S100A8) were increased, suggesting that these children may exhibit increased chronic low-grade inflammation. Additional research is required to confirm results of the current exploratory investigation.

  6. Preliminary Study of Plasma Exosomal Tau as a Potential Biomarker for Chronic Traumatic Encephalopathy.

    Science.gov (United States)

    Stern, Robert A; Tripodis, Yorghos; Baugh, Christine M; Fritts, Nathan G; Martin, Brett M; Chaisson, Christine; Cantu, Robert C; Joyce, James A; Shah, Sahil; Ikezu, Tsuneya; Zhang, Jing; Gercel-Taylor, Cicek; Taylor, Douglas D

    2016-01-01

    Chronic traumatic encephalopathy (CTE) is a tauopathy associated with prior exposure to repetitive head impacts, such as those incurred through American football and other collision sports. Diagnosis is made through neuropathological examination. Many of the clinical features of CTE are common in the general population, with and without a history of head impact exposure, making clinical diagnosis difficult. As is now common in the diagnosis of other neurodegenerative disorders, such as Alzheimer's disease, there is a need for methods to diagnose CTE during life through objective biomarkers. The aim of this study was to examine tau-positive exosomes in plasma as a potential CTE biomarker. Subjects were 78 former National Football League (NFL) players and 16 controls. Extracellular vesicles were isolated from plasma. Fluorescent nanoparticle tracking analysis was used to determine the number of vesicles staining positive for tau. The NFL group had higher exosomal tau than the control group (p negative predictive value. Within the NFL group, higher exosomal tau was associated with worse performance on tests of memory (p = 0.0126) and psychomotor speed (p = 0.0093). These preliminary findings suggest that exosomal tau in plasma may be an accurate, noninvasive CTE biomarker.

  7. Impact of adalimumab treatment on cardiovascular risk biomarkers in psoriasis: Results of a pilot study.

    Science.gov (United States)

    Gkalpakiotis, Spyridon; Arenbergerova, Monika; Gkalpakioti, Petra; Potockova, Jana; Arenberger, Petr; Kraml, Pavel

    2017-04-01

    Psoriasis is a chronic systemic immune-mediated inflammatory dermatosis associated with several comorbidities. Psoriasis patients are at increased risk of developing cardiovascular diseases (CVD), namely, coronary heart disease, stroke or peripheral vascular disease, and psoriasis seems to be an independent cardiovascular risk factor. Antipsoriatic systemic therapy, especially anti-tumor necrosis factor (TNF)-α, seems to exert a beneficial effect on these comorbidities. The purpose of this study was: (i) to measure the level of cardiovascular serum markers in psoriasis patients in comparison with healthy volunteers; and (ii) to compare the serum level of the same markers in patients before and 3 months after adalimumab therapy. We investigated six biomarkers connected to CVD: C-reactive protein (measured high sensitively, hsCRP), oxidized low-density lipoproteins (oxLDL), oxLDL/β-glycoprotein I complex (oxLDL/β2GPI), vascular endothelial adhesion molecule 1 (VCAM-1), E-selectin and interleukin (IL)-22. These biomarkers were measured in 21 patients with moderate/severe psoriasis before and after treatment with adalimumab and in healthy volunteers. hsCRP (P psoriasis patients but the difference did not reach statistical significance. A decrease of E-selectin (P psoriasis but also decreases serum cardiovascular biomarkers. E-selectin and IL-22 could serve for monitoring of the efficacy of antipsoriatic systemic therapy on cardiovascular risk. © 2016 Japanese Dermatological Association.

  8. Utility of CSF biomarkers in psychiatric disorders: a national multicentre prospective study.

    Science.gov (United States)

    Paquet, Claire; Magnin, Eloi; Wallon, David; Troussière, Anne-Cécile; Dumurgier, Julien; Jager, Alain; Bellivier, Frank; Bouaziz-Amar, Elodie; Blanc, Frédéric; Beaufils, Emilie; Miguet-Alfonsi, Carole; Quillard, Muriel; Schraen, Susanna; Pasquier, Florence; Hannequin, Didier; Robert, Philippe; Hugon, Jacques; Mouton-Liger, François

    2016-06-13

    Affective and psychotic disorders are mental or behavioural patterns resulting in an inability to cope with life's ordinary demands and routines. These conditions can be a prodromal event of Alzheimer's disease (AD). The prevalence of underlying AD lesions in psychiatric diseases is unknown, and it would be helpful to determine them in patients. AD cerebrospinal fluid (CSF) biomarkers (amyloid β, tau and phosphorylated tau) have high diagnostic accuracy, both for AD with dementia and to predict incipient AD (mild cognitive impairment due to AD), and they are sometimes used to discriminate psychiatric diseases from AD. Our objective in the present study was to evaluate the clinical utility of CSF biomarkers in a group of patients with psychiatric disease as the main diagnosis. In a multicentre prospective study, clinicians filled out an anonymous questionnaire about all of their patients who had undergone CSF biomarker evaluation. Before and after CSF biomarker results were obtained, clinicians provided a diagnosis with their level of confidence and information about the treatment. We included patients with a psychiatric disorder as the initial diagnosis. In a second part of the study conducted retrospectively in a followed subgroup, clinicians detailed the psychiatric history and we classified patients into three categories: (1) psychiatric symptoms associated with AD, (2) dual diagnosis and (3) cognitive decline not linked to a neurodegenerative disorder. Of 957 patients, 69 had an initial diagnosis of a psychiatric disorder. Among these 69 patients, 14 (20.2 %) had a CSF AD profile, 5 (7.2 %) presented with an intermediate CSF profile and 50 (72.4 %) had a non-AD CSF profile. Ultimately, 13 (18.8 %) patients were diagnosed with AD. We show that in the AD group psychiatric symptoms occurred later and the delay between the first psychiatric symptoms and the cognitive decline was shorter. This study revealed that about 20 % of patients with a primary

  9. Annual Research Review: Discovery science strategies in studies of the pathophysiology of child and adolescent psychiatric disorders--promises and limitations.

    Science.gov (United States)

    Zhao, Yihong; Castellanos, F Xavier

    2016-03-01

    Psychiatric science remains descriptive, with a categorical nosology intended to enhance interobserver reliability. Increased awareness of the mismatch between categorical classifications and the complexity of biological systems drives the search for novel frameworks including discovery science in Big Data. In this review, we provide an overview of incipient approaches, primarily focused on classically categorical diagnoses such as schizophrenia (SZ), autism spectrum disorder (ASD), and attention-deficit/hyperactivity disorder (ADHD), but also reference convincing, if focal, advances in cancer biology, to describe the challenges of Big Data and discovery science, and outline approaches being formulated to overcome existing obstacles. A paradigm shift from categorical diagnoses to a domain/structure-based nosology and from linear causal chains to complex causal network models of brain-behavior relationship is ongoing. This (r)evolution involves appreciating the complexity, dimensionality, and heterogeneity of neuropsychiatric data collected from multiple sources ('broad' data) along with data obtained at multiple levels of analysis, ranging from genes to molecules, cells, circuits, and behaviors ('deep' data). Both of these types of Big Data landscapes require the use and development of robust and powerful informatics and statistical approaches. Thus, we describe Big Data analysis pipelines and the promise and potential limitations in using Big Data approaches to study psychiatric disorders. We highlight key resources available for psychopathological studies and call for the application and development of Big Data approaches to dissect the causes and mechanisms of neuropsychiatric disorders and identify corresponding biomarkers for early diagnosis. © 2016 Association for Child and Adolescent Mental Health.

  10. Cancer predictive value of cytogenetic markers used in occupational health surveillance programs: a report from an ongoing study by the European Study Group on Cytogenetic Biomarkers and Health

    DEFF Research Database (Denmark)

    Hagmar, L; Bonassi, S; Strömberg, U

    1998-01-01

    The cytogenetic endpoints in peripheral blood lymphocytes: chromosomal aberrations (CA), sister chromatid exchange (SCE) and micronuclei (MN) are established biomarkers of exposure for mutagens or carcinogens in the work environment. However, it is not clear whether these biomarkers also may serv......, occupational exposures and smoking, will be assessed in a case-referent study within the study base....

  11. Carcinogen derived biomarkers: applications in studies of human exposure to secondhand tobacco smoke

    OpenAIRE

    Hecht, S

    2004-01-01

    Objective: To review the literature on carcinogen derived biomarkers of exposure to secondhand tobacco smoke (SHS). These biomarkers are specifically related to known carcinogens in tobacco smoke and include urinary metabolites, DNA adducts, and blood protein adducts.

  12. The Impact of Child Sexual Abuse Discovery on Caregivers and Families: A Qualitative Study.

    Science.gov (United States)

    Fong, Hiu-Fai; Bennett, Colleen E; Mondestin, Valerie; Scribano, Philip V; Mollen, Cynthia; Wood, Joanne N

    2017-06-01

    In this qualitative study with nonoffending caregivers of suspected child sexual abuse victims, we aimed to explore the perceived impact of sexual abuse discovery on caregivers and their families, and caregivers' attitudes about mental health services for themselves. We conducted semistructured, in-person interviews with 22 nonoffending caregivers of suspected sexual abuse victims <13 years old seen at a child advocacy center in Philadelphia. Interviews were audio-recorded, transcribed, coded, and analyzed using modified grounded theory. Recruitment continued until thematic saturation was reached. We found that caregivers experienced significant emotional and psychological distress, characterized by anger, depressed mood, and guilt, after learning that their child may have been sexually abused. We identified four specific sources of caregiver distress: concerns about their child, negative beliefs about their parenting abilities, family members' actions and behaviors, and memories of their own past maltreatment experiences. Some caregivers described worsening family relationships after discovery of their child's sexual abuse, while others reported increased family cohesion. Finally, we found that most caregivers in this study believed that mental health services for themselves were necessary or beneficial to help them cope with the impact of their child's sexual abuse. These results highlight the need for professionals working with families affected by sexual abuse to assess the emotional and psychological needs of nonoffending caregivers and offer mental health services. Helping caregivers link to mental health services, tailored to their unique needs after sexual abuse discovery, may be an acceptable strategy to improve caregiver and child outcomes after sexual abuse.

  13. Systematic review of clinical studies examining biomarkers of brain injury in athletes after sports-related concussion.

    Science.gov (United States)

    Papa, Linda; Ramia, Michelle M; Edwards, Damyan; Johnson, Brian D; Slobounov, Semyon M

    2015-05-15

    The aim of this study was to systematically review clinical studies examining biofluid biomarkers of brain injury for concussion in athletes. Data sources included PubMed, MEDLINE, and the Cochrane Database from 1966 to October 2013. Studies were included if they recruited athletes participating in organized sports who experienced concussion or head injury during a sports-related activity and had brain injury biomarkers measured. Acceptable research designs included experimental, observational, and case-control studies. Review articles, opinion papers, and editorials were excluded. After title and abstract screening of potential articles, full texts were independently reviewed to identify articles that met inclusion criteria. A composite evidentiary table was then constructed and documented the study title, design, population, methods, sample size, outcome measures, and results. The search identified 52 publications, of which 13 were selected and critically reviewed. All of the included studies were prospective and were published either in or after the year 2000. Sports included boxing (six studies), soccer (five studies), running/jogging (two studies), hockey (one study), basketball (one study), cycling (one study), and swimming (one study). The majority of studies (92%) had fewer than 100 patients. Three studies (23%) evaluated biomarkers in cerebrospinal fluid (CSF), one in both serum and CSF, and 10 (77%) in serum exclusively. There were 11 different biomarkers assessed, including S100β, glial fibrillary acidic protein, neuron-specific enolase, tau, neurofilament light protein, amyloid beta, brain-derived neurotrophic factor, creatine kinase and heart-type fatty acid binding protein, prolactin, cortisol, and albumin. A handful of biomarkers showed a correlation with number of hits to the head (soccer), acceleration/deceleration forces (jumps, collisions, and falls), postconcussive symptoms, trauma to the body versus the head, and dynamics of different sports

  14. Detecting neuroimaging biomarkers for schizophrenia: a meta-analysis of multivariate pattern recognition studies.

    Science.gov (United States)

    Kambeitz, Joseph; Kambeitz-Ilankovic, Lana; Leucht, Stefan; Wood, Stephen; Davatzikos, Christos; Malchow, Berend; Falkai, Peter; Koutsouleris, Nikolaos

    2015-06-01

    Multivariate pattern recognition approaches have recently facilitated the search for reliable neuroimaging-based biomarkers in psychiatric disorders such as schizophrenia. By taking into account the multivariate nature of brain functional and structural changes as well as their distributed localization across the whole brain, they overcome drawbacks of traditional univariate approaches. To evaluate the overall reliability of neuroimaging-based biomarkers, we conducted a comprehensive literature search to identify all studies that used multivariate pattern recognition to identify patterns of brain alterations that differentiate patients with schizophrenia from healthy controls. A bivariate random-effects meta-analytic model was implemented to investigate the sensitivity and specificity across studies as well as to assess the robustness to potentially confounding variables. In the total sample of n=38 studies (1602 patients and 1637 healthy controls), patients were differentiated from controls with a sensitivity of 80.3% (95% CI: 76.7-83.5%) and a specificity of 80.3% (95% CI: 76.9-83.3%). Analysis of neuroimaging modality indicated higher sensitivity (84.46%, 95% CI: 79.9-88.2%) and similar specificity (76.9%, 95% CI: 71.3-81.6%) of rsfMRI studies as compared with structural MRI studies (sensitivity: 76.4%, 95% CI: 71.9-80.4%, specificity of 79.0%, 95% CI: 74.6-82.8%). Moderator analysis identified significant effects of age (p=0.029), imaging modality (p=0.019), and disease stage (p=0.025) on sensitivity as well as of positive-to-negative symptom ratio (p=0.022) and antipsychotic medication (p=0.016) on specificity. Our results underline the utility of multivariate pattern recognition approaches for the identification of reliable neuroimaging-based biomarkers. Despite the clinical heterogeneity of the schizophrenia phenotype, brain functional and structural alterations differentiate schizophrenic patients from healthy controls with 80% sensitivity and specificity.

  15. Extracting replicable associations across multiple studies: Empirical Bayes algorithms for controlling the false discovery rate.

    Directory of Open Access Journals (Sweden)

    David Amar

    2017-08-01

    Full Text Available In almost every field in genomics, large-scale biomedical datasets are used to report associations. Extracting associations that recur across multiple studies while controlling the false discovery rate is a fundamental challenge. Here, we propose a new method to allow joint analysis of multiple studies. Given a set of p-values obtained from each study, the goal is to identify associations that recur in at least k > 1 studies while controlling the false discovery rate. We propose several new algorithms that differ in how the study dependencies are modeled, and compare them and extant methods under various simulated scenarios. The top algorithm, SCREEN (Scalable Cluster-based REplicability ENhancement, is our new algorithm that works in three stages: (1 clustering an estimated correlation network of the studies, (2 learning replicability (e.g., of genes within clusters, and (3 merging the results across the clusters. When we applied SCREEN to two real datasets it greatly outperformed the results obtained via standard meta-analysis. First, on a collection of 29 case-control gene expression cancer studies, we detected a large set of consistently up-regulated genes related to proliferation and cell cycle regulation. These genes are both consistently up-regulated across many cancer studies, and are well connected in known gene networks. Second, on a recent pan-cancer study that examined the expression profiles of patients with and without mutations in the HLA complex, we detected a large active module of up-regulated genes that are both related to immune responses and are well connected in known gene networks. This module covers thrice more genes as compared to the original study at a similar false discovery rate, demonstrating the high power of SCREEN. An implementation of SCREEN is available in the supplement.

  16. Bode’s law and the discovery of Juno historical studies in asteroid research

    CERN Document Server

    Cunningham, Clifford J

    2017-01-01

    Johann Bode developed a so-called law of planetary distances best known as Bode’s Law. The story of the discovery of Juno in 1804 by Karl Harding tells how Juno fit into that scheme and is examined as it relates to the philosopher Georg Hegel’s 1801 thesis that there could be no planets between Mars and Jupiter. By 1804 that gap was not only filled but had three residents: Ceres, Pallas and Juno! When Juno was discovered no one could have imagined its study would call into question Newton’s law of gravity, or be the impetus for developing the mathematics of the fast Fourier transform by Carl Gauss. Clifford Cunningham, a dedicated scholar, opens to scrutiny this critical moment of astronomical discovery, continuing the story of asteroid begun in earlier volumes of this series. The fascinating issues raised by the discovery of Juno take us on an extraordinary journey. The revelation of the existence of this new class of celestial bodies transformed our understanding of the Solar System, the implications ...

  17. Building a gold standard to construct search filters: a case study with biomarkers for oral cancer.

    Science.gov (United States)

    Frazier, John J; Stein, Corey D; Tseytlin, Eugene; Bekhuis, Tanja

    2015-01-01

    To support clinical researchers, librarians and informationists may need search filters for particular tasks. Development of filters typically depends on a "gold standard" dataset. This paper describes generalizable methods for creating a gold standard to support future filter development and evaluation using oral squamous cell carcinoma (OSCC) as a case study. OSCC is the most common malignancy affecting the oral cavity. Investigation of biomarkers with potential prognostic utility is an active area of research in OSCC. The methods discussed here should be useful for designing quality search filters in similar domains. The authors searched MEDLINE for prognostic studies of OSCC, developed annotation guidelines for screeners, ran three calibration trials before annotating the remaining body of citations, and measured inter-annotator agreement (IAA). We retrieved 1,818 citations. After calibration, we screened the remaining citations (n = 1,767; 97.2%); IAA was substantial (kappa = 0.76). The dataset has 497 (27.3%) citations representing OSCC studies of potential prognostic biomarkers. The gold standard dataset is likely to be high quality and useful for future development and evaluation of filters for OSCC studies of potential prognostic biomarkers. The methodology we used is generalizable to other domains requiring a reference standard to evaluate the performance of search filters. A gold standard is essential because the labels regarding relevance enable computation of diagnostic metrics, such as sensitivity and specificity. Librarians and informationists with data analysis skills could contribute to developing gold standard datasets and subsequent filters tuned for their patrons' domains of interest.

  18. Biomarkers in molecular epidemiology study of oral squamous cell carcinoma in the era of precision medicine

    Directory of Open Access Journals (Sweden)

    Qing-Hao Zhu

    2017-01-01

    Full Text Available Oral cancer, which occurs in the mouth, lips, and tongue, is a multifactorial disease whose etiology involves environment, genetic, and epigenetic factors. Tobacco use and alcohol consumption are regarded as the primary risk factors for oral squamous cell carcinoma (OSCC, and betel use, other chemicals, radiation, environmental, and genetics are reported as relevant risk factors for oral carcinogenesis. The human papillomavirus infection is an independent risk factor. Traditional epidemiology studies have revealed that environmental carcinogens are risk factors for OSCC. Molecular epidemiology studies have revealed that the susceptibility to OSCC is influenced by both environmental and genetic risk factors. However, the details and mechanisms of risk factors involved in OSCC are unclear. Advanced methods and techniques used in human genome studies provide great opportunities for researchers to explore and identify (a the details of such risk factors and (b genetic susceptibility involved in OSCC. Human genome epidemiology is a new branch of epidemiology, which leads the epidemiology study from the molecular epidemiology era into the era of genome-wide association study. In the era of precision medicine, molecular epidemiology studies should focus on biomarkers for cancer genomics and their potential utility in clinical practice. Here, we briefly reviewed several molecular epidemiology studies of OSCC, focusing on biomarkers as valuable utility in risk assessment, clinical screening, diagnosis, and prognosis prediction of OSCC in the era of precision medicine.

  19. New biomarkers defining a novel early stage of Fabry nephropathy: A diagnostic test study.

    Science.gov (United States)

    Aguiar, Patrício; Azevedo, Olga; Pinto, Rui; Marino, Jacira; Baker, Robert; Cardoso, Carlos; Ducla Soares, José Luís; Hughes, Derralynn

    2017-06-01

    Renal involvement in Fabry disease is a major determinant of overall disease prognosis and early enzyme replacement therapy seems effective in preventing progression of kidney injury. Gb3 storage, glomerular sclerosis and tubulo-interstitial fibrosis may occur with minimal or no changes on standard renal tests, hence alternative markers of renal dysfunction are crucial. In this study we compared several biomarkers with albuminuria in the identification of incipient Fabry nephropathy and their diagnostic accuracy to identify chronic kidney disease (CKD) stage≥2. In this multicentre, prospective, cross-sectional and diagnostic test study, a cohort of 78 Fabry patients and 25 healthy controls was consecutively recruited. Patients were grouped by severity of nephropathy: 1) albuminuria300mg/g; 4) glomerular filtration rate (GFR)Fabry patients, even in the subgroup of patients without evidence of nephropathy. We also found inverse significant correlations between estimated GFR and collagen type IV (ρ=-0.289; p=0.003) or N-acetyl-β-glucosaminidase (ρ=-0.448; p<0.001), which were stronger than with albumin (ρ=-0.274; p=0.019). There was also better diagnostic accuracy of N-acetyl-β-glucosaminidase to predict CKD stage≥2. These results suggest that studied biomarkers may overcome the limitations of albuminuria as sensitive marker of early renal dysfunction and as marker for CKD progression risk. These biomarkers may also define novel early stages of nephropathy characterized by mesangial expansion and/or tubular damage. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Biomarkers of histone deacetylase inhibitor activity in a phase 1 combined-modality study with radiotherapy.

    Directory of Open Access Journals (Sweden)

    Anne Hansen Ree

    Full Text Available Following the demonstration that histone deacetylase inhibitors enhanced experimental radiation-induced clonogenic suppression, the Pelvic Radiation and Vorinostat (PRAVO phase 1 study, combining fractionated radiotherapy with daily vorinostat for pelvic carcinoma, was designed to evaluate both clinical and novel biomarker endpoints, the latter relating to pharmacodynamic indicators of vorinostat action in clinical radiotherapy.Potential biomarkers of vorinostat radiosensitizing action, not simultaneously manifesting molecular perturbations elicited by the radiation itself, were explored by gene expression array analysis of study patients' peripheral blood mononuclear cells (PBMC, sampled at baseline (T0 and on-treatment two and 24 hours (T2 and T24 after the patients had received vorinostat.This strategy revealed 1,600 array probes that were common for the comparisons T2 versus T0 and T24 versus T2 across all of the patients, and furthermore, that no significantly differential expression was observed between the T0 and T24 groups. Functional annotation analysis of the array data showed that a significant number of identified genes were implicated in gene regulation, the cell cycle, and chromatin biology. Gene expression was validated both in patients' PBMC and in vorinostat-treated human carcinoma xenograft models, and transient repression of MYC was consistently observed.Within the design of the PRAVO study, all of the identified genes showed rapid and transient induction or repression and therefore, in principle, fulfilled the requirement of being pharmacodynamic biomarkers of vorinostat action in fractionated radiotherapy, possibly underscoring the role of MYC in this therapeutic setting.

  1. A Systematic Review of Longitudinal Studies Which Measure Alzheimer's Disease Biomarkers.

    Science.gov (United States)

    Lawrence, Emma; Vegvari, Carolin; Ower, Alison; Hadjichrysanthou, Christoforos; De Wolf, Frank; Anderson, Roy M

    2017-01-01

    Alzheimer's disease (AD) is a progressive and fatal neurodegenerative disease, with no effective treatment or cure. A gold standard therapy would be treatment to slow or halt disease progression; however, knowledge of causation in the early stages of AD is very limited. In order to determine effective endpoints for possible therapies, a number of quantitative surrogate markers of disease progression have been suggested, including biochemical and imaging biomarkers. The dynamics of these various surrogate markers over time, particularly in relation to disease development, are, however, not well characterized. We reviewed the literature for studies that measured cerebrospinal fluid or plasma amyloid-β and tau, or took magnetic resonance image or fluorodeoxyglucose/Pittsburgh compound B-positron electron tomography scans, in longitudinal cohort studies. We summarized the properties of the major cohort studies in various countries, commonly used diagnosis methods and study designs. We have concluded that additional studies with repeat measures over time in a representative population cohort are needed to address the gap in knowledge of AD progression. Based on our analysis, we suggest directions in which research could move in order to advance our understanding of this complex disease, including repeat biomarker measurements, standardization and increased sample sizes.

  2. Periostin - A Novel Systemic Biomarker for Eosinophilic Airway Inflammation: A Case Control Study.

    Science.gov (United States)

    Emprm, Viswanathan; Rajanandh, M G; Nageswari, A D

    2016-02-01

    Chronic airway inflammation and remodelling are fundamental features of asthma. The molecular phenotypes in asthma are Th2 high and Th2 low. Serum periostin is a biomarker which aid in understanding Th2 high eosinophilic asthma. The present study aimed to identify whether or not serum periostin is a systemic biomarker for eosinophilic airway inflammation in asthmatics. The study was designed as a prospective, case control study. Patients who presented with consistent symptoms of asthma and confirmed by spirometry with reversibility were the cases. The controls were healthy subjects who had no history of lung disease with normal lung function. The sputum and blood samples were collected from both the groups. Sputum eosinophils, Absolute Eosinophil Counts (AEC) and serum periostin levels were compared between the groups. The study comprised of 101 participants in which 30 were controls and 71 were cases. In the study group, mean post FEV1 was 64.45. There was a positive correlation of sputum eosinophils with severity of obstruction. The ROC curve analysis showed the cut-off value of 24.556 for serum periostin with the p-value of limitation in asthmatic patients with a Th2 high eosinophilic phenotype when compared to AEC and sputum eosinophils.

  3. Objectively measured physical activity and cardiac biomarkers: A cross sectional population based study in older men.

    Science.gov (United States)

    Parsons, Tessa J; Sartini, Claudio; Welsh, Paul; Sattar, Naveed; Ash, Sarah; Lennon, Lucy T; Wannamethee, S Goya; Lee, I-Min; Whincup, Peter H; Jefferis, Barbara J

    2018-03-01

    N-terminal pro-brain natriuretic peptide (NT-proBNP) and high sensitivity Troponin T (hsTnT) are markers of cardiac injury used in diagnosis of heart failure and myocardial infarction respectively, and associated with increased risk of cardiovascular disease. Since physical activity is protective against cardiovascular disease and heart failure, we investigated whether higher levels of physical activity, and less sedentary behaviour were associated with lower NT-proBNP and hsTnT. Cross sectional study of 1130 men, age 70-91years, from the British Regional Heart Study, measured in 2010-2012. Fasting blood samples were analysed for NT-proBNP and hsTnT. Physical activity and sedentary behaviour were measured using ActiGraph GT3X accelerometers. Relationships between activity and NT-proBNP or hsTnT were non-linear; biomarker levels were lower with higher total activity, steps, moderate/vigorous activity and light activity only at low to moderate levels of activity. For example, for each additional 10min of moderate/vigorous activity, NT-proBNP was lower by 35.7% (95% CI -47.9, -23.6) and hsTnT by 8.4% (95% CI -11.1, -5.6), in men who undertook <25 or 50min of moderate/vigorous activity per day respectively. Biomarker levels increased linearly with increasing sedentary behaviour, but not independently of moderate/vigorous activity. Associations between biomarkers and moderate/vigorous activity (and between hsTnT and light activity) were independent of sedentary behaviour, suggesting activity is driving the relationships. In these older men with concomitantly low levels of physical activity, activity may be more important in protecting against cardiac health deterioration in less active individuals, although reverse causality might be operating. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  4. Associations of pet ownership with biomarkers of ageing: population based cohort study.

    Science.gov (United States)

    Batty, G David; Zaninotto, Paola; Watt, Richard G; Bell, Steven

    2017-12-13

    To examine the prospective relation between animal companionship and biomarkers of ageing in older people. Analyses of data from the English Longitudinal Study of Ageing, an ongoing, open, prospective cohort study initiated in 2002-03. Nationally representative study from England. 8785 adults (55% women) with a mean age of 67 years (SD 9) at pet ownership assessment in 2010-11 (wave 5). Established biomarkers of ageing in the domains of physical, immunological, and psychological function, as assessed in 2012-13 (wave 6). One third of study members reported pet ownership: 1619 (18%) owned a dog, 1077 (12%) a cat, and 274 (3%) another animal. After adjustment for a range of covariates, there was no evidence of a clear association of any type of pet ownership with walking speed, lung function, chair rise time, grip strength, leg raises, balance, three markers of systemic inflammation, memory, or depressive symptoms. In this population of older adults, the companionship of creatures great and small seems to essentially confer no relation with standard ageing phenotypes. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  5. Lichen biomarkers upon heating: a Raman spectroscopic study with implications for extra-terrestrial exploration

    Science.gov (United States)

    Miralles, I.; Capel Ferrón, C.; Hernández, V.; López-Navarrete, J. T.; Jorge-Villar, S. E.

    2017-01-01

    Lithopanspermia Theory has suggested that life was transferred among planets by meteorites and other rocky bodies. If the planet had an atmosphere, this transfer of life had to survive drastic temperature changes in a very short time in its entry or exit. Only organisms able to endure such a temperature range could colonize a planet from outer space. Many experiments are being carried out by NASA and European Space Agency to understand which organisms were able to survive and how. Among the suite of instruments designed for extraplanetary exploration, particularly for Mars surface exploration, a Raman spectrometer was selected with the main objective of looking for life signals. Among all attributes, Raman spectroscopy is able to identify organic and inorganic compounds, either pure or in admixture, without requiring sample manipulation. In this study, we used Raman spectroscopy to examine the lichen Squamarina lentigera biomarkers. We analyse spectral signature changes after sample heating under different experimental situations, such as (a) laser, (b) analysis accumulations over the same spot and (c) environmental temperature increase. Our goal is to evaluate the capability of Raman spectroscopy to identify unambiguously life markers even if heating has induced spectral changes, reflecting biomolecular transformations. Usnic acid, chlorophyll, carotene and calcium oxalates were identified by the Raman spectra. From our experiments, we have seen that usnic acid, carotene and calcium oxalates (the last two have been suggested to be good biomarkers) respond in a different way to environmental heating. Our main conclusion is that despite their abundance in nature or their inorganic composition the resistance to heat makes some molecules more suitable than others as biomarkers.

  6. Biomarkers in Patients with Metastatic Breast Cancer and the PRAEGNANT Study Network

    Science.gov (United States)

    Fasching, P. A.; Brucker, S. Y.; Fehm, T. N.; Overkamp, F.; Janni, W.; Wallwiener, M.; Hadji, P.; Belleville, E.; Häberle, L.; Taran, F.-A.; Lüftner, D.; Lux, M. P.; Ettl, J.; Müller, V.; Tesch, H.; Wallwiener, D.; Schneeweiss, A.

    2015-01-01

    Progress has been made in the treatment of metastatic breast cancer in recent decades, but very few therapies use patient or tumor-specific characteristics to tailor individualized treatment. More than ten years after the publication of the reference human genome sequence, analysis methods have improved enormously, fostering the hope that biomarkers can be used to individualize therapies and offer precise treatment based on tumor and patient characteristics. Biomarkers at every level of the system (genetics, epigenetics, gene expression, micro-RNA, proteomics and others) can be used for this. This has led to changes in clinical study designs, with drug developments often only focusing on small or very small subgroups of patients and tumors. The screening and registration of patients and their molecular tumor data has therefore become very important for the successful completion of clinical studies. This new form of medicine presents particular challenges for patients and physicians. Even in this new age of genome-wide analysis, the focus should still be on the patientsʼ quality of life. This review summarizes recent developments and describes how the PRAEGNANT study network manages the aforementioned medical challenges and changes to create a professional infrastructure for patients and physicians. PMID:25684786

  7. Biomarkers: Delivering on the expectation of molecularly driven, quantitative health.

    Science.gov (United States)

    Wilson, Jennifer L; Altman, Russ B

    2018-02-01

    Biomarkers are the pillars of precision medicine and are delivering on expectations of molecular, quantitative health. These features have made clinical decisions more precise and personalized, but require a high bar for validation. Biomarkers have improved health outcomes in a few areas such as cancer, pharmacogenetics, and safety. Burgeoning big data research infrastructure, the internet of things, and increased patient participation will accelerate discovery in the many areas that have not yet realized the full potential of biomarkers for precision health. Here we review themes of biomarker discovery, current implementations of biomarkers for precision health, and future opportunities and challenges for biomarker discovery. Impact statement Precision medicine evolved because of the understanding that human disease is molecularly driven and is highly variable across patients. This understanding has made biomarkers, a diverse class of biological measurements, more relevant for disease diagnosis, monitoring, and selection of treatment strategy. Biomarkers' impact on precision medicine can be seen in cancer, pharmacogenomics, and safety. The successes in these cases suggest many more applications for biomarkers and a greater impact for precision medicine across the spectrum of human disease. The authors assess the status of biomarker-guided medical practice by analyzing themes for biomarker discovery, reviewing the impact of these markers in the clinic, and highlight future and ongoing challenges for biomarker discovery. This work is timely and relevant, as the molecular, quantitative approach of precision medicine is spreading to many disease indications.

  8. Urine Exosomes: An Emerging Trove of Biomarkers.

    Science.gov (United States)

    Street, J M; Koritzinsky, E H; Glispie, D M; Star, R A; Yuen, P S T

    Exosomes are released by most cells and can be isolated from all biofluids including urine. Exosomes are small vesicles formed as part of the endosomal pathway that contain cellular material surrounded by a lipid bilayer that can be traced to the plasma membrane. Exosomes are potentially a more targeted source of material for biomarker discovery than unfractionated urine, and provide diagnostic and pathophysiological information without an invasive tissue biopsy. Cytoplasmic contents including protein, mRNA, miRNA, and lipids have all been studied within the exosomal fraction. Many prospective urinary exosomal biomarkers have been successfully identified for a variety of kidney or genitourinary tract conditions; detection of systemic conditions may also be possible. Isolation and analysis of exosomes can be achieved by several approaches, although many require specialized equipment or involve lengthy protocols. The need for timely analysis in the clinical setting has driven considerable innovation with several promising options recently emerging. Consensus on exosome isolation, characterization, and normalization procedures would resolve critical clinical translational bottlenecks for existing candidate exosomal biomarkers and provide a template for additional discovery studies. 2017 Published by Elsevier Inc.

  9. Biomarker Profiles in Women with PCOS and PCOS Offspring; A Pilot Study.

    Directory of Open Access Journals (Sweden)

    Nadine M P Daan

    Full Text Available To study metabolic/inflammatory biomarker risk profiles in women with PCOS and PCOS offspring.Cross-sectional comparison of serum biomarkers.University Medical Center Utrecht.Hyperandrogenic PCOS women (HA-PCOS, n = 34, normoandrogenic PCOS women (NA-PCOS, n = 34, non-PCOS reference population (n = 32, PCOS offspring (n = 14, age 6-8 years, and a paedriatic reference population (n = 30.Clustering profile of adipocytokines (IL-1b, IL-6, IL-13, IL-17, IL-18, TNF-α, adiponectin, adipsin, leptin, chemerin, resistin, RBP4, DPP-IV/sCD26, CCL2/MCP-1, growth factors (PIGF, VEGF, sVEGF-R1, soluble cell adhesion molecules (sICAM-1/sCD54, sVCAM-1/sCD106, and other inflammatory related proteases (MMP-9, S100A8, Cathepsin S. Differences in median biomarker concentrations between groups, and associations with the free androgen index (FAI; Testosterone/SHBG x100.The cluster analysis identified leptin, RBP-4, DPP-IV and adiponectin as potential discriminative markers for HA-PCOS with a specifically strong correlation in cases with increased BMI. Leptin (R2 = 0.219 and adiponectin (R2 = 0.182 showed the strongest correlation with the FAI. When comparing median protein concentrations adult PCOS women with or without hyperandrogenemia, the most profound differences were observed for leptin (P < 0.001, DPP-IV (P = 0.005, and adiponectin (P < 0.001. Adjusting for age, BMI and multiple testing attenuated all differences. In PCOS offspring, MMP-9 (P = 0.001 and S100A8 (P < 0.001 concentrations were significantly higher compared to a healthy matched reference population, even after correcting for age and BMI and adjustment for multiple testing.In this preliminary investigation we observed significant differences in adipocytokines between women with or without hyperandrogenic PCOS and non-PCOS controls, mostly influenced by BMI. Leptin and adiponectin showed the strongest correlation with the FAI in adult women with PCOS. In PCOS offspring other inflammatory biomarkers

  10. Biomarkers of oxidative stress and DNA damage in agricultural workers: A pilot study

    International Nuclear Information System (INIS)

    Muniz, Juan F.; McCauley, Linda; Scherer, J.; Lasarev, M.; Koshy, M.; Kow, Y.W.; Nazar-Stewart, Valle; Kisby, G.E.

    2008-01-01

    Oxidative stress and DNA damage have been proposed as mechanisms linking pesticide exposure to health effects such as cancer and neurological diseases. A study of pesticide applicators and farmworkers was conducted to examine the relationship between organophosphate pesticide exposure and biomarkers of oxidative stress and DNA damage. Urine samples were analyzed for OP metabolites and 8-hydroxy-2'-deoxyguanosine (8-OH-dG). Lymphocytes were analyzed for oxidative DNA repair activity and DNA damage (Comet assay), and serum was analyzed for lipid peroxides (i.e., malondialdehyde, MDA). Cellular damage in agricultural workers was validated using lymphocyte cell cultures. Urinary OP metabolites were significantly higher in farmworkers and applicators (p < 0.001) when compared to controls. 8-OH-dG levels were 8.5 times and 2.3 times higher in farmworkers or applicators (respectively) than in controls. Serum MDA levels were 4.9 times and 24 times higher in farmworkers or applicators (respectively) than in controls. DNA damage (Comet assay) and oxidative DNA repair were significantly greater in lymphocytes from applicators and farmworkers when compared with controls. Markers of oxidative stress (i.e., increased reactive oxygen species and reduced glutathione levels) and DNA damage were also observed in lymphocyte cell cultures treated with an OP. The findings from these in vivo and in vitro studies indicate that organophosphate pesticides induce oxidative stress and DNA damage in agricultural workers. These biomarkers may be useful for increasing our understanding of the link between pesticides and a number of health effects

  11. Retinal vascular caliber is associated with cardiovascular biomarkers of oxidative stress and inflammation: the POLA study.

    Directory of Open Access Journals (Sweden)

    Vincent Daien

    Full Text Available PURPOSE: Retinal vascular caliber has been linked with increased cardiovascular risk and is predictive of cardiovascular pathology, including stroke and coronary heart disease. Oxidative stress, as well as inflammatory mechanisms, plays a major role in the pathogenesis and progression of atherosclerosis, plaque rupture and vascular thrombotic propensity. The purpose of this study is to explore the relationship between retinal vascular calibers and biomarkers of oxidative stress and inflammation, in subjects free of cardiovascular pathology. PATIENTS AND METHODS: Cross-sectional analysis from a community-dwelling cohort comprising 1224 individuals aged 60 years and over, without a history of coronary or peripheral artery disease or stroke. Retinal vascular caliber was measured from fundus photographs using semi-automated standardized imaging software. Oxidative stress was evaluated using plasma superoxide dismutase 2 and glutathione peroxidase (GPx-3 activities, and inflammatory state was assessed using plasma high sensitivity C-reactive protein (hsCRP and orosomucoid. RESULTS: In a multivariate model controlling for cardiovascular risk factors, larger retinal arteriolar caliber was independently related to higher level of GPx-3 activity (p = 0.003 whereas larger venular caliber was associated with higher levels of hsCRP (p = 0.0001 and orosomucoid (p = 0.01. CONCLUSION: In the present study, biomarkers of oxidative stress regulation and inflammation were independently associated with retinal vascular calibers. This suggests that an assessment of retinal vessels may offer early and non-invasive detection of subclinical vascular pathology.

  12. Clinical usefulness of a biomarker-based diagnostic test for acute stroke: the Biomarker Rapid Assessment in Ischemic Injury (BRAIN) study.

    Science.gov (United States)

    Laskowitz, Daniel T; Kasner, Scott E; Saver, Jeffrey; Remmel, Kerri S; Jauch, Edward C

    2009-01-01

    One of the significant limitations in the evaluation and management of patients with suspected acute cerebral ischemia is the absence of a widely available, rapid, and sensitive diagnostic test. The objective of the current study was to assess whether a test using a panel of biomarkers might provide useful diagnostic information in the early evaluation of stroke by differentiating patients with cerebral ischemia from other causes of acute neurological deficit. A total of 1146 patients presenting with neurological symptoms consistent with possible stroke were prospectively enrolled at 17 different sites. Timed blood samples were assayed for matrix metalloproteinase 9, brain natriuretic factor, d-dimer, and protein S100beta. A separate cohort of 343 patients was independently enrolled to validate the multiple biomarker model approach. A diagnostic tool incorporating the values of matrix metalloproteinase 9, brain natriuretic factor, d-dimer, and S-100beta into a composite score was sensitive for acute cerebral ischemia. The multivariate model demonstrated modest discriminative capabilities with an area under the receiver operating characteristic curve of 0.76 for hemorrhagic stroke and 0.69 for all stroke (likelihood test P<0.001). When the threshold for the logistic model was set at the first quartile, this resulted in a sensitivity of 86% for detecting all stroke and a sensitivity of 94% for detecting hemorrhagic stroke. Moreover, results were reproducible in a separate cohort tested on a point-of-care platform. These results suggest that a biomarker panel may add valuable and time-sensitive diagnostic information in the early evaluation of stroke. Such an approach is feasible on a point-of-care platform. The rapid identification of patients with suspected stroke would expand the availability of time-limited treatment strategies. Although the diagnostic accuracy of the current panel is clearly imperfect, this study demonstrates the feasibility of incorporating a

  13. Chimeric mice with humanized liver: Application in drug metabolism and pharmacokinetics studies for drug discovery.

    Science.gov (United States)

    Naritomi, Yoichi; Sanoh, Seigo; Ohta, Shigeru

    2018-02-01

    Predicting human drug metabolism and pharmacokinetics (PK) is key to drug discovery. In particular, it is important to predict human PK, metabolite profiles and drug-drug interactions (DDIs). Various methods have been used for such predictions, including in vitro metabolic studies using human biological samples, such as hepatic microsomes and hepatocytes, and in vivo studies using experimental animals. However, prediction studies using these methods are often inconclusive due to discrepancies between in vitro and in vivo results, and interspecies differences in drug metabolism. Further, the prediction methods have changed from qualitative to quantitative to solve these issues. Chimeric mice with humanized liver have been developed, in which mouse liver cells are mostly replaced with human hepatocytes. Since human drug metabolizing enzymes are expressed in the liver of these mice, they are regarded as suitable models for mimicking the drug metabolism and PK observed in humans; therefore, these mice are useful for predicting human drug metabolism and PK. In this review, we discuss the current state, issues, and future directions of predicting human drug metabolism and PK using chimeric mice with humanized liver in drug discovery. Copyright © 2017 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.

  14. Biomarker Detection in Association Studies: Modeling SNPs Simultaneously via Logistic ANOVA

    KAUST Repository

    Jung, Yoonsuh

    2014-10-02

    In genome-wide association studies, the primary task is to detect biomarkers in the form of Single Nucleotide Polymorphisms (SNPs) that have nontrivial associations with a disease phenotype and some other important clinical/environmental factors. However, the extremely large number of SNPs comparing to the sample size inhibits application of classical methods such as the multiple logistic regression. Currently the most commonly used approach is still to analyze one SNP at a time. In this paper, we propose to consider the genotypes of the SNPs simultaneously via a logistic analysis of variance (ANOVA) model, which expresses the logit transformed mean of SNP genotypes as the summation of the SNP effects, effects of the disease phenotype and/or other clinical variables, and the interaction effects. We use a reduced-rank representation of the interaction-effect matrix for dimensionality reduction, and employ the L 1-penalty in a penalized likelihood framework to filter out the SNPs that have no associations. We develop a Majorization-Minimization algorithm for computational implementation. In addition, we propose a modified BIC criterion to select the penalty parameters and determine the rank number. The proposed method is applied to a Multiple Sclerosis data set and simulated data sets and shows promise in biomarker detection.

  15. A study on some enzymes in rice field fish as biomarkers for pesticide exposure

    International Nuclear Information System (INIS)

    Juzu Hayati Arshad; Mazlina Muhammad; Salmijah Surif; Abdul Manan Mat Jais

    2002-01-01

    A study was carried out on three enzymes in rice field fish which can be used as possible biomarkers for pesticide exposure. The results obtained showed that the activity of the enzyme EROD (ethoxyresorufin-o-deethylase) increased between 1.5-2.2 fold in snakehead or haruan (Channa striata) sampled from the pesticide polluted areas, particularly the recycled areas and only a slight increase in EROD activity in climbing perch or puyu (Anabas testudineus). Increase in the activity of carboxylesterase was also noted. The percentage inhibition of acety1cholinesterase ranges from 18.4%-57.4% and 2.5%-34.2% for Channa striata and Anabas testudineus, respectively. Generally, a higher percentage of acety1cholinesterase inhibition was noted for those fish sampled from the recycled areas. The noted changes in the activity of these enzymes suggest exposure of rice field fish to foreign compounds, possibly pesticides, which are known to induce EROD activity and inhibit acety1cholinesterase activity. Therefore it may be possible to use these enzymes as biomarkers for pesticide exposure. (Author)

  16. Saliva levels of Abeta1-42 as potential biomarker of Alzheimer's disease: a pilot study

    Directory of Open Access Journals (Sweden)

    Antequera Desiree

    2010-11-01

    Full Text Available Abstract Background Simple, non-invasive tests for early detection of degenerative dementia by use of biomarkers are urgently required. However, up to the present, no validated extracerebral diagnostic markers for the early diagnosis of Alzheimer disease (AD are available. The clinical diagnosis of probable AD is made with around 90% accuracy using modern clinical, neuropsychological and imaging methods. A biochemical marker that would support the clinical diagnosis and distinguish AD from other causes of dementia would therefore be of great value as a screening test. A total of 126 samples were obtained from subjects with AD, and age-sex-matched controls. Additionally, 51 Parkinson's disease (PD patients were used as an example of another neurodegenerative disorder. We analyzed saliva and plasma levels of β amyloid (Aβ using a highly sensitive ELISA kit. Results We found a small but statistically significant increase in saliva Aβ42 levels in mild AD patients. In addition, there were not differences in saliva concentration of Aβ42 between patients with PD and healthy controls. Saliva Aβ40 expression was unchanged within all the studied sample. The association between saliva Aβ42 levels and AD was independent of established risk factors, including age or Apo E, but was dependent on sex and functional capacity. Conclusions We suggest that saliva Aβ42 levels could be considered a potential peripheral marker of AD and help discrimination from other types of neurodegenerative disorders. We propose a new and promising biomarker for early AD.

  17. Biomarkers: A Challenging Conundrum in Cardiovascular Disease.

    Science.gov (United States)

    Libby, Peter; King, Kevin

    2015-12-01

    The use of biomarkers has proven utility in cardiovascular medicine and holds great promise for future advances, but their application requires considerable rigor in thinking and methodology. Numerous confounding factors can cloud the clinical and investigative uses of biomarkers. Yet, the thoughtful and critical use of biomarkers can doubtless aid discovery of new pathogenic pathways, identify novel therapeutic targets, and provide a bridge between the laboratory and the clinic. Biomarkers can provide diagnostic and prognostic tools to the practitioner. The careful application of biomarkers can also help design and guide clinical trials required to establish the efficacy of novel interventions to improve patient outcomes. Point of care testing, technological advances, such as microfluidic and wearable devices, and the power of omics approaches all promise to elevate the potential contributions of biomarkers to discovery science, translation, clinical trials, and the practice of cardiovascular medicine. © 2015 American Heart Association, Inc.

  18. Simulation of complex data structures for planning of studies with focus on biomarker comparison.

    Science.gov (United States)

    Schulz, Andreas; Zöller, Daniela; Nickels, Stefan; Beutel, Manfred E; Blettner, Maria; Wild, Philipp S; Binder, Harald

    2017-06-13

    There are a growing number of observational studies that do not only focus on single biomarkers for predicting an outcome event, but address questions in a multivariable setting. For example, when quantifying the added value of new biomarkers in addition to established risk factors, the aim might be to rank several new markers with respect to their prediction performance. This makes it important to consider the marker correlation structure for planning such a study. Because of the complexity, a simulation approach may be required to adequately assess sample size or other aspects, such as the choice of a performance measure. In a simulation study based on real data, we investigated how to generate covariates with realistic distributions and what generating model should be used for the outcome, aiming to determine the least amount of information and complexity needed to obtain realistic results. As a basis for the simulation a large epidemiological cohort study, the Gutenberg Health Study was used. The added value of markers was quantified and ranked in subsampling data sets of this population data, and simulation approaches were judged by the quality of the ranking. One of the evaluated approaches, the random forest, requires original data at the individual level. Therefore, also the effect of the size of a pilot study for random forest based simulation was investigated. We found that simple logistic regression models failed to adequately generate realistic data, even with extensions such as interaction terms or non-linear effects. The random forest approach was seen to be more appropriate for simulation of complex data structures. Pilot studies starting at about 250 observations were seen to provide a reasonable level of information for this approach. We advise to avoid oversimplified regression models for simulation, in particular when focusing on multivariable research questions. More generally, a simulation should be based on real data for adequately reflecting

  19. Simulation of complex data structures for planning of studies with focus on biomarker comparison

    Directory of Open Access Journals (Sweden)

    Andreas Schulz

    2017-06-01

    Full Text Available Abstract Background There are a growing number of observational studies that do not only focus on single biomarkers for predicting an outcome event, but address questions in a multivariable setting. For example, when quantifying the added value of new biomarkers in addition to established risk factors, the aim might be to rank several new markers with respect to their prediction performance. This makes it important to consider the marker correlation structure for planning such a study. Because of the complexity, a simulation approach may be required to adequately assess sample size or other aspects, such as the choice of a performance measure. Methods In a simulation study based on real data, we investigated how to generate covariates with realistic distributions and what generating model should be used for the outcome, aiming to determine the least amount of information and complexity needed to obtain realistic results. As a basis for the simulation a large epidemiological cohort study, the Gutenberg Health Study was used. The added value of markers was quantified and ranked in subsampling data sets of this population data, and simulation approaches were judged by the quality of the ranking. One of the evaluated approaches, the random forest, requires original data at the individual level. Therefore, also the effect of the size of a pilot study for random forest based simulation was investigated. Results We found that simple logistic regression models failed to adequately generate realistic data, even with extensions such as interaction terms or non-linear effects. The random forest approach was seen to be more appropriate for simulation of complex data structures. Pilot studies starting at about 250 observations were seen to provide a reasonable level of information for this approach. Conclusions We advise to avoid oversimplified regression models for simulation, in particular when focusing on multivariable research questions. More generally

  20. Biomarkers of unstable angina pectoris and yangxin decoction intervention: An exploratory metabonomics study of blood plasma.

    Science.gov (United States)

    Yu, Xiao-Hong; Sun, Jing; Wang, Yan; Zhou, Ya-Bin

    2017-05-01

    This study aimed to explore the related metabolic biomarkers and to observe the effects of Yangxin Decoction (YXD) on plasma metabolism of patients with unstable angina (UA). In total, 10 patients with UA (intervention group) and 10 healthy participants (control group) were recruited for this study from January 2009 to December 2010. Plasma samples from both groups were analyzed using liquid chromatography mass spectrometry (LC-MS). Principle component analysis (PCA) and partial least squares (PLS) were used to explore the correlations between metabolic markers in patients with UA. The LC-MS results indicated that the serum levels of 5 potential metabolic markers, namely, ceramide, glycocholic acid, allocholic acid, lithocholic acid, and leukotriene (LT) B4, were significantly higher in the intervention group than those in the control group. The results of this study demonstrated potential metabolic markers that can be used to distinguish and diagnose patients with UA.

  1. Merging clinical chemistry biomarker data with a COPD database - building a clinical infrastructure for proteomic studies.

    Science.gov (United States)

    Eriksson, Jonatan; Andersson, Simone; Appelqvist, Roger; Wieslander, Elisabet; Truedsson, Mikael; Bugge, May; Malm, Johan; Dahlbäck, Magnus; Andersson, Bo; Fehniger, Thomas E; Marko-Varga, György

    2016-01-01

    Data from biological samples and medical evaluations plays an essential part in clinical decision making. This data is equally important in clinical studies and it is critical to have an infrastructure that ensures that its quality is preserved throughout its entire lifetime. We are running a 5-year longitudinal clinical study, KOL-Örestad, with the objective to identify new COPD (Chronic Obstructive Pulmonary Disease) biomarkers in blood. In the study, clinical data and blood samples are collected from both private and public health-care institutions and stored at our research center in databases and biobanks, respectively. The blood is analyzed by Mass Spectrometry and the results from this analysis then linked to the clinical data. We built an infrastructure that allows us to efficiently collect and analyze the data. We chose to use REDCap as the EDC (Electronic Data Capture) tool for the study due to its short setup-time, ease of use, and flexibility. REDCap allows users to easily design data collection modules based on existing templates. In addition, it provides two functions that allow users to import batches of data; through a web API (Application Programming Interface) as well as by uploading CSV-files (Comma Separated Values). We created a software, DART (Data Rapid Translation), that translates our biomarker data into a format that fits REDCap's CSV-templates. In addition, DART is configurable to work with many other data formats as well. We use DART to import our clinical chemistry data to the REDCap database. We have shown that a powerful and internationally adopted EDC tool such as REDCap can be extended so that it can be used efficiently in proteomic studies. In our study, we accomplish this by using DART to translate our clinical chemistry data to a format that fits the templates of REDCap.

  2. Implementation of proteomic biomarkers: making it work.

    Science.gov (United States)

    Mischak, Harald; Ioannidis, John P A; Argiles, Angel; Attwood, Teresa K; Bongcam-Rudloff, Erik; Broenstrup, Mark; Charonis, Aristidis; Chrousos, George P; Delles, Christian; Dominiczak, Anna; Dylag, Tomasz; Ehrich, Jochen; Egido, Jesus; Findeisen, Peter; Jankowski, Joachim; Johnson, Robert W; Julien, Bruce A; Lankisch, Tim; Leung, Hing Y; Maahs, David; Magni, Fulvio; Manns, Michael P; Manolis, Efthymios; Mayer, Gert; Navis, Gerjan; Novak, Jan; Ortiz, Alberto; Persson, Frederik; Peter, Karlheinz; Riese, Hans H; Rossing, Peter; Sattar, Naveed; Spasovski, Goce; Thongboonkerd, Visith; Vanholder, Raymond; Schanstra, Joost P; Vlahou, Antonia

    2012-09-01

    While large numbers of proteomic biomarkers have been described, they are generally not implemented in medical practice. We have investigated the reasons for this shortcoming, focusing on hurdles downstream of biomarker verification, and describe major obstacles and possible solutions to ease valid biomarker implementation. Some of the problems lie in suboptimal biomarker discovery and validation, especially lack of validated platforms with well-described performance characteristics to support biomarker qualification. These issues have been acknowledged and are being addressed, raising the hope that valid biomarkers may start accumulating in the foreseeable future. However, successful biomarker discovery and qualification alone does not suffice for successful implementation. Additional challenges include, among others, limited access to appropriate specimens and insufficient funding, the need to validate new biomarker utility in interventional trials, and large communication gaps between the parties involved in implementation. To address this problem, we propose an implementation roadmap. The implementation effort needs to involve a wide variety of stakeholders (clinicians, statisticians, health economists, and representatives of patient groups, health insurance, pharmaceutical companies, biobanks, and regulatory agencies). Knowledgeable panels with adequate representation of all these stakeholders may facilitate biomarker evaluation and guide implementation for the specific context of use. This approach may avoid unwarranted delays or failure to implement potentially useful biomarkers, and may expedite meaningful contributions of the biomarker community to healthcare. © 2012 The Authors. European Journal of Clinical Investigation © 2012 Stichting European Society for Clinical Investigation Journal Foundation.

  3. Biomarkers of inflammation, coagulation and microbial translocation in HIV/HCV co-infected patients in the SMART study

    DEFF Research Database (Denmark)

    Peters, Lars; Neuhaus, Jacqueline; Duprez, Daniel

    2014-01-01

    synthesized coagulation markers were measured and compared according to the liver fibrosis marker hyaluronic acid (HA) at study entry. Percent difference in changes in biomarker levels from study entry to month 6 was compared between randomization groups and according to study entry HA levels. RESULTS...

  4. Communication in superconductivity research: A study of scientific discoveries with particular reference to a developing country

    International Nuclear Information System (INIS)

    Chu, H.

    1991-01-01

    The main objective is to study the communications dimensions of China's contribution to the discovery of high-Tc superconductors. Chinese researchers of the field were compared with non-Chinese superconductivity scientists from developed countries to reveal similarities and differences in the formal as well as the informal domains of scholarly communication. 240 documents highly cited in a manually created Chinese data base and in Science Citation Index for the period of 1987-89 were examined to delineate the formal structure of communication in the area. Noteworthy similarities, e.g., similar cited cores, identical publication sources, and comparable intellectual structures of cocitation data, were found in formal communication between Chinese and non-Chinese scientists. Nevertheless, differences were also located in regard to citedness, timeliness and direction of communication. Findings reflect the role Chinese scientists played in the discovery of high-Tc superconductors. Chinese researchers overall did better in the formal domain than in the informal realm of scientific communication. Informal communication with scientists from advanced nations appears to be a very weak element in China's endeavors of searching for high-Tc superconductors

  5. Mitochondrial Biomarkers Reflect Semen Quality: Results from the MARCHS Study in Chongqing, China.

    Directory of Open Access Journals (Sweden)

    Guowei Zhang

    Full Text Available Unexplained infertility requires that more sensitive and mechanism-based biomarkers should be developed and used independently of or in addition to conventional semen parameters for an infertility diagnosis. In the present study, semen samples were collected from young men participating in the Male Reproductive Health in Chongqing College students (MARCHS cohort study in the follow-up stage in 2014. Conventional semen parameters were measured in all 656 participants, whereas sperm mitochondrial membrane potential (MMP, mitochondrial DNA copy number (mtDNAcn, mtDNA integrity and apoptotic parameters were measured among 627, 386, 362, and 628 participants, respectively. We found that sperm MMP was significantly positively correlated with all of conventional semen parameters including semen volume (r = 0.090, p = 0.025, sperm concentration (r = 0.301, p<0.01, total sperm count (r = 0.324, p<0.01, and progressive motility (r = 0.399, p<0.01; sperm MMP was also negatively correlated with Annexin V+ sperm (r = -0.553, p<0.01; mtDNAcn was significantly negatively correlated with sperm concentration (r = -0.214, p<0.01, total sperm count (r = -0.232, p<0.01, and progressive motility (r = -0.164, p = 0.01; mtDNA integrity was also significantly positively correlated with sperm concentration (r = 0.195, p<0.01, total sperm count (r = 0.185, p<0.01, and progressive motility (r = 0.106, p = 0.043. After adjusting for potential confounders, these relationships remained significant. Furthermore, we explored the potential effects of lifestyles on such mitochondrial biomarkers and found that the current drinkers displayed a higher level of sperm MMP; additionally, mt DNAcn was increased with age. The results indicated that certain mitochondrial biomarkers could serve as predictors of semen quality in a general population, and the study provides a baseline for the effects of population characteristics and lifestyles on such mitochondrial markers.

  6. Urinary Biomarkers for Chronic Kidney Disease with a Focus on Gene Transcript.

    Science.gov (United States)

    Lyu, Lin-Li; Feng, Ye; Liu, Bi-Cheng

    2017-09-20

    In the upcoming era of precision medicine, searching for the early, noninvasive biomarkers has been the cornerstone and major challenge in the management of chronic kidney disease (CKD). Urine contains rich biological information which could be the ideal source for noninvasive biomarkers of CKD. This review will discuss the recent advance in urinary biomarker. This review was based on data in articles published in the PubMed databases up to June 20, 2017, with the following keywords: "Chronic kidney disease", "Biomarker", and "Urine". Original articles and important reviews on urinary biomarker were selected for this review. Urinary biomarker studies of CKD mainly focused on urine sediment, supernatant, and urinary extracellular vesicles. The gene transcript (microRNA [miRNA], messenger RNA [mRNA]) biomarkers have been recently shown with diagnostic potential for CKD reflecting kidney function and histological change. However, challenges regarding technique and data analysis need to be resolved before translation to clinic. Different fractions of urine contain rich information for biomarker discovery, among which urine (extracellular vesicles) mRNA, miRNA, might represent promising biomarker for CKD.

  7. Tissue proteomics in pancreatic cancer study: discovery, emerging technologies and challenges

    Science.gov (United States)

    Pan, Sheng; Brentnall, Teresa A.; Kelly, Kimberly; Chen, Ru

    2013-01-01

    Pancreatic cancer is a highly lethal disease that is difficult to diagnose and treat. The advances of proteomics technology, especially quantitative proteomics, have stimulated a great interest to apply this technology for pancreatic cancer study. A variety of tissue proteomics approaches have been applied to investigate pancreatic cancer and the associated diseases. These studies were carried out with various goals, aiming to better understand the molecular mechanisms underlying pancreatic tumorigenesis, to improve therapeutic treatment and to identify cancer associated protein signatures, signaling events as well as interactions between cancer cells and tumor microenvironment. Here, we provide an overview on the tissue proteomics studies of pancreatic cancer reported in the past few years in light of discovery and technology development. PMID:23125171

  8. Novel Transgenic Mouse Model for Studying Human Serum Albumin as a Biomarker of Carcinogenic Exposure.

    Science.gov (United States)

    Sheng, Jonathan; Wang, Yi; Turesky, Robert J; Kluetzman, Kerri; Zhang, Qing-Yu; Ding, Xinxin

    2016-05-16

    Albumin is a commonly used serum protein for studying human exposure to xenobiotic compounds, including therapeutics and environmental pollutants. Often, the reactivity of albumin with xenobiotic compounds is studied ex vivo with human albumin or plasma/serum samples. Some studies have characterized the reactivity of albumin with chemicals in rodent models; however, differences between the orthologous peptide sequences of human and rodent albumins can result in the formation of different types of chemical-protein adducts with different interaction sites or peptide sequences. Our goal is to generate a human albumin transgenic mouse model that can be used to establish human protein biomarkers of exposure to hazardous xenobiotics for human risk assessment via animal studies. We have developed a human albumin transgenic mouse model and characterized the genotype and phenotype of the transgenic mice. The presence of the human albumin gene in the genome of the model mouse was confirmed by genomic PCR analysis, whereas liver-specific expression of the transgenic human albumin mRNA was validated by RT-PCR analysis. Further immunoblot and mass spectrometry analyses indicated that the transgenic human albumin protein is a full-length, mature protein, which is less abundant than the endogenous mouse albumin that coexists in the serum of the transgenic mouse. The transgenic protein was able to form ex vivo adducts with a genotoxic metabolite of 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine, a procarcinogenic heterocyclic aromatic amine formed in cooked meat. This novel human albumin transgenic mouse model will facilitate the development and validation of albumin-carcinogen adducts as biomarkers of xenobiotic exposure and/or toxicity in humans.

  9. Volatility Discovery

    DEFF Research Database (Denmark)

    Dias, Gustavo Fruet; Scherrer, Cristina; Papailias, Fotis

    The price discovery literature investigates how homogenous securities traded on different markets incorporate information into prices. We take this literature one step further and investigate how these markets contribute to stochastic volatility (volatility discovery). We formally show...... that the realized measures from homogenous securities share a fractional stochastic trend, which is a combination of the price and volatility discovery measures. Furthermore, we show that volatility discovery is associated with the way that market participants process information arrival (market sensitivity......). Finally, we compute volatility discovery for 30 actively traded stocks in the U.S. and report that Nyse and Arca dominate Nasdaq....

  10. Biomarker response of climate change-induced ocean acidification and hypercapnia studies on brachyurian crab Portunus pelagicus

    Directory of Open Access Journals (Sweden)

    R. Jeevapriya

    2017-04-01

    Full Text Available A laboratory level microcosm analysis of the impacts of ocean acidification on the environmental stress biomarkers in Portunus pelagicus (Linneaus 1758exposed to a series of pH regimes expected in the year 2100 (pH 7.5 and 7.0 and leakage from a sub-seabed carbon dioxide storage site (pH 6.5 - 5.5 was carried out. Levels of the antioxidant enzyme catalase, the phase II detoxification enzyme, glutathione S. transferase, the lipid peroxidation biomarker, malondialdehyde, acetylcholinesterase, and reduced glutathione were estimated in the tissues of the exposed animals to validate theses enzymes as biomarkers of Hypercapnia. The integrated biomarkers indicated a stress full environment in all animals except those exposed to the control seawater (pH 8.1. The reducing pH was also observed to be highly lethal to the animals exposed to lower pH levels which were obvious from the rate of mortality in a short term of exposure. The present study substantiates the role of biomarkers as an early warning of ocean acidification at a sub-lethal level.

  11. Atacama Rover Astrobiology Drilling Studies: Roving to Find Subsurface Preserved Biomarkers

    Science.gov (United States)

    Glass, B.; Davila, A.; Parro, V.; Quinn, R.; Willis, P.; Brinckerhoff, W.; DiRuggiero, J.; Williams, M.; Bergman, D.; Stoker, C.

    2016-05-01

    The ARADS project is a NASA PSTAR that will drill into a Mars analog site in search of biomarkers. Leading to a field test of an integrated rover-drill system with four prototype in-situ instruments for biomarker detection and analysis.

  12. Impact of cerebro-spinal fluid biomarkers of Alzheimer's disease in clinical practice: a multicentric study.

    Science.gov (United States)

    Mouton-Liger, François; Wallon, David; Troussière, Anne-Cécile; Yatimi, Rachida; Dumurgier, Julien; Magnin, Eloi; de la Sayette, Vincent; Duron, Emannuelle; Philippi, Nathalie; Beaufils, Emilie; Gabelle, Audrey; Croisile, Bernard; Robert, Philippe; Pasquier, Florence; Hannequin, Didier; Hugon, Jacques; Paquet, Claire

    2014-01-01

    CSF biomarkers of Alzheimer's disease are well validated in clinical research; however, their pragmatic utility in daily practice is still unappreciated. These biomarkers are used in routine practice according to Health Authority Recommendations. In 604 consecutive patients explored for cognitive disorders, questionnaires were prospectively proposed and filled. Before and after CSF biomarker results, clinicians provided a diagnosis and an estimate of their diagnostic confidence. Analysis has compared the frequency of diagnosis before and after CSF biomarker results using the net reclassification improvement (NRI) method. We have evaluated external validity comparing with data of French Bank National of AD (BNA). A total of 561 patients [Alzheimer's disease (AD), n = 253; non-AD, n = 308] were included (mean age, 68.6 years; women, 52 %). Clinically suspected diagnosis and CSF results were concordant in 65.2 % of cases. When clinical hypothesis and biological results were discordant, a reclassification occurred in favour of CSF biomarkers results in 76.9 %. The NRI was 39.5 %. In addition, the results show a statistically significant improvement in clinician confidence for their diagnosis. In comparison with BNA data, patients were younger and more frequently diagnosed with AD. Clinicians tend to heavily rely on the CSF AD biomarkers results and are more confident in their diagnoses using CSF AD biomarkers. Thus, these biomarkers appear as a key tool in clinical practice.

  13. Analysis of Urinary Biomarkers for Smoking Crack Cocaine: Results of a Danish Laboratory Study.

    Science.gov (United States)

    Jeppesen, Hans Henrik; Busch-Nielsen, Malthe; Larsen, Anders Nørgaard; Breindahl, Torben

    2015-01-01

    Crack cocaine (free-base cocaine) smokers belong to a subgroup of marginalized drug users exposed to severe health risks and great social harm. Detection of the urinary, pyrolytic biomarker methylecgonidine (MED) and its metabolite ecgonidine (ED) secures an unambiguous confirmation of crack cocaine smoking. Although prevalence studies of cocaine based upon self-reporting may not be accurate, laboratory analysis is seldom used for neither diagnostic purpose nor early identification of crack cocaine smoking, which is far more severe than snorting cocaine. A new analytical method was validated for MED, ED and other relevant cocaine metabolites using automated liquid handling and column switching coupled to liquid chromatography and tandem mass spectrometry. Limit of quantification was 30 ng/mL for ED and MED. This method was applied in a laboratory study of urine samples (n = 110) from cocaine users in Denmark subjected to routine drugs-of-abuse testing. Crack cocaine smoking was confirmed by the presence of MED and/or ED. Eighty-four samples (76.4%) were found positive for crack cocaine smoking in this group of problematic cocaine users. MED was only detected in 5.9% of the positive samples. The study shows a prevalence 3-fold higher to that recently suggested by European Monitoring Centre for Drugs and Drug Addiction. We therefore advocate that the urinary biomarkers MED and ED are included in routine testing methods for clinical toxicology. This may lead to an earlier identification of crack cocaine smoking and possibly prevent a more severe drug use. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  14. Plasma selenium levels and oxidative stress biomarkers: a gene-environment interaction population-based study.

    Science.gov (United States)

    Galan-Chilet, Inmaculada; Tellez-Plaza, Maria; Guallar, Eliseo; De Marco, Griselda; Lopez-Izquierdo, Raul; Gonzalez-Manzano, Isabel; Carmen Tormos, M; Martin-Nuñez, Gracia M; Rojo-Martinez, Gemma; Saez, Guillermo T; Martín-Escudero, Juan C; Redon, Josep; Javier Chaves, F

    2014-09-01

    The role of selenium exposure in preventing chronic disease is controversial, especially in selenium-repleted populations. At high concentrations, selenium exposure may increase oxidative stress. Studies evaluating the interaction of genetic variation in genes involved in oxidative stress pathways and selenium are scarce. We evaluated the cross-sectional association of plasma selenium concentrations with oxidative stress levels, measured as oxidized to reduced glutathione ratio (GSSG/GSH), malondialdehyde (MDA), and 8-oxo-7,8-dihydroguanine (8-oxo-dG) in urine, and the interacting role of genetic variation in oxidative stress candidate genes, in a representative sample of 1445 men and women aged 18-85 years from Spain. The geometric mean of plasma selenium levels in the study sample was 84.76 µg/L. In fully adjusted models the geometric mean ratios for oxidative stress biomarker levels comparing the highest to the lowest quintiles of plasma selenium levels were 0.61 (0.50-0.76) for GSSG/GSH, 0.89 (0.79-1.00) for MDA, and 1.06 (0.96-1.18) for 8-oxo-dG. We observed nonlinear dose-responses of selenium exposure and oxidative stress biomarkers, with plasma selenium concentrations above ~110 μg/L being positively associated with 8-oxo-dG, but inversely associated with GSSG/GSH and MDA. In addition, we identified potential risk genotypes associated with increased levels of oxidative stress markers with high selenium levels. Our findings support that high selenium levels increase oxidative stress in some biological processes. More studies are needed to disentangle the complexity of selenium biology and the relevance of potential gene-selenium interactions in relation to health outcomes in human populations. Copyright © 2014 Elsevier Inc. All rights reserved.

  15. Discovering Biomarkers within the Genomic Landscape of Renal Cell Carcinoma

    Science.gov (United States)

    A, Sankin

    2016-01-01

    Recent advances in molecular sequencing technology have led to the discovery of numerous biomarkers in renal cell carcinoma (RCC). These biomarkers have the potential to predict clinical outcomes and aid in clinical management decisions. The following commentary is a review of the preliminary data on some of the most promising genetic biomarker candidates. PMID:27104219

  16. Novel biomarkers of mercury-induced autoimmune dysfunction: a Cross-sectional study in Amazonian Brazil

    Science.gov (United States)

    Motts, Jonathan A.; Shirley, Devon L.; Silbergeld, Ellen K.; Nyland, Jennifer F.

    2014-01-01

    Mercury is an ubiquitous environmental contaminant, causing both neurotoxicity and immunotoxicity. Given its ability to amalgamate gold, mercury is frequently used in small-scale artisanal gold mining. We have previously reported that elevated serum titers of antinuclear autoantibodies (ANA) are associated with mercury exposures of miners in gold mining. The goal of this project was to identify novel serum biomarkers of mercury-induced immunotoxicity and autoimmune dysregulation. We conducted an analysis of serum samples from a cross-sectional epidemiological study on miners working in Amazonian Brazil. In proteomic screening analyses, samples were stratified based on mercury concentrations and ANA titer and a subset of serum samples (N=12) were profiled using Immune Response Biomarker Profiling ProtoArray protein microarray for elevated autoantibodies. Of the up-regulated autoantibodies in the mercury-exposed cohort, potential target autoantibodies were selected based on relevance to pro-inflammatory and macrophage activation pathways. ELISAs were developed to test the entire sample cohort (N=371) for serum titers to the highest of these autoantibodies (anti-glutathione S-transferase alpha, GSTA1) identified in the high mercury/high ANA group. We found positive associations between elevated mercury exposure and up-regulated serum titers of 3760 autoantibodies as identified by ProtoArray. Autoantibodies identified as potential novel biomarkers of mercury-induced immunotoxicity include antibodies to the following proteins: GSTA1, tumor necrosis factor ligand superfamily member 13, linker for activation of T cells, signal peptide peptidase like 2B, stimulated by retinoic acid 13, and interferon induced transmembrane protein. ELISA analyses confirmed that mercury-exposed gold miners had significantly higher serum titers of anti-GSTA1 autoantibody [unadjusted odds ratio = 89.6; 95% confidence interval: 27.2, 294.6] compared to emerald miners (referent population

  17. Pooled results from 5 validation studies of dietary self-report instruments using recovery biomarkers for energy and protein intake

    Science.gov (United States)

    We pooled data from 5 large validation studies of dietary self-report instruments that used recovery biomarkers as references to clarify the measurement properties of food frequency questionnaires (FFQs) and 24-hour recalls. The studies were conducted in widely differing U.S. adult populations from...

  18. Discovery, detection and use of biomarkers

    Energy Technology Data Exchange (ETDEWEB)

    Swanson, Basil I.; Mukundan, Harshini; Sakamuri, Rama Murthy

    2017-12-05

    Provided herein are systems for and methods of capturing, detecting, quantifying, and characterizing target moieties that are characterized by having a lipophilic portion of sufficient size and chemical composition whereby the target moiety inserts (or partitions) into a lipid assembly. Examples of such assays employ synthetic lipid constructs such as supported bilayers which are used to capture target moieties; other example assays exploit the natural absorption of compounds into natural lipid constructs such as HDL or LDL particles or cell membranes to capture target moieties. In specific embodiments, the target moieties are bacterial pathogen associated molecular pattern (PAMP) molecules or compounds not yet identified as PAMP molecules. Also provided are methods of determining PAMP molecule fingerprints and profiles that are linked to (indicative of) bacterial infection, disease states or progression, development of antibiotic resistance, and so forth, as well as these fingerprints, profiles and methods of using them.

  19. [Tetra-saccharide glucose as a diagnostic biomarker for Pompe disease: a study with 35 patients].

    Science.gov (United States)

    Bobillo Lobato, Joaquín; Durán Parejo, Pilar; Tejero Díez, Pedro; Jiménez Jiménez, Luis M

    2013-08-04

    Pompe disease is a disorder originating from an acid alpha-glycosidase (AAG) enzyme deficiency. This disease produces an accumulation of lysosomal glycogen in different tissues, whereby the skeletal and heart muscles are especially involved. The established diagnosis is achieved through the identification of the AAG deficiency. There are also other secondary diagnostic biomarkers, such as tetra-saccharide glucose (Glc4), which shows high levels in the urine of these patients. In this study it is highlighted the usefulness of Glc4 as a diagnostic biomarker for Pompe disease in its different forms of presentation, using a high-performance liquid chromatography with ultraviolet detection (HPLC/UV) adapted to the study. A total of 75 individuals have been analyzed: 40 healthy controls and 35 patients diagnosed with Pompe disease. Twenty-four hour samples of urine were collected from all of the patients and their Glc4 levels were determined by means of HPLC/UV. The evaluation of the urinary Glc4 shows a high discrimination ability between healthy/sick individuals. In addition, the results obtained have allowed to establish the most appropriate level of decision or cut-off point for the identification of sick people. Glc4 urinary levels are found to be high in patients suffering from Pompe disease and even though increased levels are also found in other conditions, the existence of a AAG deficiency together with a compatible clinical symptoms, prove very helpful for a correct diagnosis of this serious disease. Copyright © 2012 Elsevier España, S.L. All rights reserved.

  20. Biomarkers and bacterial pneumonia risk in patients with treated HIV infection: a case-control study.

    Directory of Open Access Journals (Sweden)

    Sonja M Bjerk

    Full Text Available Despite advances in HIV treatment, bacterial pneumonia continues to cause considerable morbidity and mortality in patients with HIV infection. Studies of biomarker associations with bacterial pneumonia risk in treated HIV-infected patients do not currently exist.We performed a nested, matched, case-control study among participants randomized to continuous combination antiretroviral therapy (cART in the Strategies for Management of Antiretroviral Therapy trial. Patients who developed bacterial pneumonia (cases and patients without bacterial pneumonia (controls were matched 1∶1 on clinical center, smoking status, age, and baseline cART use. Baseline levels of Club Cell Secretory Protein 16 (CC16, Surfactant Protein D (SP-D, C-reactive protein (hsCRP, interleukin-6 (IL-6, and d-dimer were compared between cases and controls.Cases (n = 72 and controls (n = 72 were 25.7% female, 51.4% black, 65.3% current smokers, 9.7% diabetic, 36.1% co-infected with Hepatitis B/C, and 75.0% were on cART at baseline. Median (IQR age was 45 (41, 51 years with CD4+ count of 553 (436, 690 cells/mm(3. Baseline CC16 and SP-D were similar between cases and controls, but hsCRP was significantly higher in cases than controls (2.94 µg/mL in cases vs. 1.93 µg/mL in controls; p = 0.02. IL-6 and d-dimer levels were also higher in cases compared to controls, though differences were not statistically significant (p-value 0.06 and 0.10, respectively.In patients with cART-treated HIV infection, higher levels of systemic inflammatory markers were associated with increased bacterial pneumonia risk, while two pulmonary-specific inflammatory biomarkers, CC16 and SP-D, were not associated with bacterial pneumonia risk.

  1. Flow Injection/Sequential Injection Analysis Systems: Potential Use as Tools for Rapid Liver Diseases Biomarker Study

    Directory of Open Access Journals (Sweden)

    Supaporn Kradtap Hartwell

    2012-01-01

    Full Text Available Flow injection/sequential injection analysis (FIA/SIA systems are suitable for carrying out automatic wet chemical/biochemical reactions with reduced volume and time consumption. Various parts of the system such as pump, valve, and reactor may be built or adapted from available materials. Therefore the systems can be at lower cost as compared to other instrumentation-based analysis systems. Their applications for determination of biomarkers for liver diseases have been demonstrated in various formats of operation but only a few and limited types of biomarkers have been used as model analytes. This paper summarizes these applications for different types of reactions as a guide for using flow-based systems in more biomarker and/or multibiomarker studies.

  2. Candidate proteomic biomarkers for non-alcoholic fatty liver disease (steatosis and non-alcoholic steatohepatitis) discovered with mass-spectrometry: a systematic review.

    Science.gov (United States)

    Lădaru, Anca; Bălănescu, Paul; Stan, Mihaela; Codreanu, Ioana; Anca, Ioana Alina

    2016-01-01

    Non-alcoholic fatty liver disease (NAFLD) is characterized by lipid accumulation in the liver which is accompanied by a series of metabolic deregulations. There are sustained research efforts focusing upon biomarker discovery for NAFLD diagnosis and its prognosis in order investigate and follow-up patients as minimally invasive as possible. The objective of this study is to critically review proteomic studies that used mass spectrometry techniques and summarize relevant proteomic NAFLD candidate biomarkers. Medline and Embase databases were searched from inception to December 2014. A final number of 22 records were included that identified 251 candidate proteomic biomarkers. Thirty-three biomarkers were confirmed - 14 were found in liver samples, 21 in serum samples, and two from both serum and liver samples. Some of the biomarkers identified have already been extensively studied regarding their diagnostic and prognostic capacity. However, there are also more potential biomarkers that still need to be addressed in future studies.

  3. Biomarkers of Diabetic Retinopathy.

    Science.gov (United States)

    Ting, Daniel Shu Wei; Tan, Kara-Anne; Phua, Val; Tan, Gavin Siew Wei; Wong, Chee Wai; Wong, Tien Yin

    2016-12-01

    Diabetic retinopathy (DR), a leading cause of acquired vision loss, is a microvascular complication of diabetes. While traditional risk factors for diabetic retinopathy including longer duration of diabetes, poor blood glucose control, and dyslipidemia are helpful in stratifying patient's risk for developing retinopathy, many patients without these traditional risk factors develop DR; furthermore, there are persons with long diabetes duration who do not develop DR. Thus, identifying biomarkers to predict DR or to determine therapeutic response is important. A biomarker can be defined as a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. Incorporation of biomarkers into risk stratification of persons with diabetes would likely aid in early diagnosis and guide treatment methods for those with DR or with worsening DR. Systemic biomarkers of DR include serum measures including genomic, proteomic, and metabolomics biomarkers. Ocular biomarkers including tears and vitreous and retinal vascular structural changes have also been studied extensively to prognosticate the risk of DR development. The current studies on biomarkers are limited by the need for larger sample sizes, cross-validation in different populations and ethnic groups, and time-efficient and cost-effective analytical techniques. Future research is important to explore novel DR biomarkers that are non-invasive, rapid, economical, and accurate to help reduce the incidence and progression of DR in people with diabetes.

  4. Diagnostic and economic evaluation of new biomarkers for Alzheimer’s disease: the research protocol of a prospective cohort study

    Directory of Open Access Journals (Sweden)

    Handels Ron LH

    2012-08-01

    Full Text Available Abstract Background New research criteria for the diagnosis of Alzheimer’s disease (AD have recently been developed to enable an early diagnosis of AD pathophysiology by relying on emerging biomarkers. To enable efficient allocation of health care resources, evidence is needed to support decision makers on the adoption of emerging biomarkers in clinical practice. The research goals are to 1 assess the diagnostic test accuracy of current clinical diagnostic work-up and emerging biomarkers in MRI, PET and CSF, 2 perform a cost-consequence analysis and 3 assess long-term cost-effectiveness by an economic model. Methods/design In a cohort design 241 consecutive patients suspected of having a primary neurodegenerative disease are approached in four academic memory clinics and followed for two years. Clinical data and data on quality of life, costs and emerging biomarkers are gathered. Diagnostic test accuracy is determined by relating the clinical practice and new research criteria diagnoses to a reference diagnosis. The clinical practice diagnosis at baseline is reflected by a consensus procedure among experts using clinical information only (no biomarkers. The diagnosis based on the new research criteria is reflected by decision rules that combine clinical and biomarker information. The reference diagnosis is determined by a consensus procedure among experts based on clinical information on the course of symptoms over a two-year time period. A decision analytic model is built combining available evidence from different resources among which (accuracy results from the study, literature and expert opinion to assess long-term cost-effectiveness of the emerging biomarkers. Discussion Several other multi-centre trials study the relative value of new biomarkers for early evaluation of AD and related disorders. The uniqueness of this study is the assessment of resource utilization and quality of life to enable an economic evaluation. The study results

  5. A comparative study of biological and metabolic biomarkers between healthy individuals and patients with acne vulgaris: A cross-sectional study protocol.

    Science.gov (United States)

    Kim, Kyuseok; Ha, Injin; Kim, Eunok; Kim, Kyunglee

    2017-11-01

    Acne is a multifactorial dermatosis, which is influenced not only by hormones but also by the biochemical relationship between them and the pilosebaceous unit. Inflammatory cytokines, chemokines, active oxygen, and zinc are known to be associated with the development of acne. Further, steroid metabolism is known as one of the important factors related to sebum secretion and comedone formation in acne. However, there is a lack of studies comparing these human biomarkers between healthy individuals and patients with acne. In particular, no study has investigated the relationship between human biomarkers and patterns of acne yet.The purpose of this study is to investigate diagnostic human biomarkers in acne by comparing the biological and metabolic biomarkers between healthy individuals and patients with acne and identify the relationship between human biomarkers and patterns of acne.This study is a protocol for a cross-sectional study. Forty healthy participants and 60 patients with acne will be recruited at 1 center. We will collect their blood samples and analyze the molecular biological and metabolic biomarkers (cytokines, chemokines, reactive oxygen species, corticotropin-releasing hormone, zinc, amino acid, 1-carbon metabolite, lipid metabolite, etc.). Further, we will administer questionnaires regarding their diet, sleep, stress, and other factors relating to acne and measure their skin elasticity.The study protocol was approved by the Institutional Review Board of Oriental Medical Hospital at Kyung Hee Medical Center (KOMCIRB-161118-HR-062). Written informed consent will be obtained from all the participants. The trial was registered in the Clinical Research Information Service, Republic of Korea: KCT0002212.This trial will provide evidence regarding diagnostic human biomarkers in acne and the relationship between the human biomarkers and patterns of acne.

  6. Glial biomarkers in human central nervous system disease.

    Science.gov (United States)

    Garden, Gwenn A; Campbell, Brian M

    2016-10-01

    There is a growing understanding that aberrant GLIA function is an underlying factor in psychiatric and neurological disorders. As drug discovery efforts begin to focus on glia-related targets, a key gap in knowledge includes the availability of validated biomarkers to help determine which patients suffer from dysfunction of glial cells or who may best respond by targeting glia-related drug mechanisms. Biomarkers are biological variables with a significant relationship to parameters of disease states and can be used as surrogate markers of disease pathology, progression, and/or responses to drug treatment. For example, imaging studies of the CNS enable localization and characterization of anatomical lesions without the need to isolate tissue for biopsy. Many biomarkers of disease pathology in the CNS involve assays of glial cell function and/or response to injury. Each major glia subtype (oligodendroglia, astroglia and microglia) are connected to a number of important and useful biomarkers. Here, we describe current and emerging glial based biomarker approaches for acute CNS injury and the major categories of chronic nervous system dysfunction including neurodegenerative, neuropsychiatric, neoplastic, and autoimmune disorders of the CNS. These descriptions are highlighted in the context of how biomarkers are employed to better understand the role of glia in human CNS disease and in the development of novel therapeutic treatments. GLIA 2016;64:1755-1771. © 2016 Wiley Periodicals, Inc.

  7. Host biomarkers are associated with progression to dengue haemorrhagic fever: a nested case-control study.

    Science.gov (United States)

    Conroy, Andrea L; Gélvez, Margarita; Hawkes, Michael; Rajwans, Nimerta; Tran, Vanessa; Liles, W Conrad; Villar-Centeno, Luis Angel; Kain, Kevin C

    2015-11-01

    Dengue represents the most important arboviral infection worldwide. Onset of circulatory collapse can be unpredictable. Biomarkers that can identify individuals at risk of plasma leakage may facilitate better triage and clinical management. Using a nested case-control design, we randomly selected subjects from a prospective cohort study of dengue in Colombia (n=1582). Using serum collected within 96 hours of fever onset, we tested 19 biomarkers by ELISA in cases (developed dengue hemorrhagic fever or dengue shock syndrome (DHF/DSS); n=46), and controls (uncomplicated dengue fever (DF); n=65) and healthy controls (HC); n=15. Ang-1 levels were lower and angptl3, sKDR, sEng, sICAM-1, CRP, CXCL10/IP-10, IL-18 binding protein, CHI3L1, C5a and Factor D levels were increased in dengue compared to HC. sICAM-1, sEng and CXCL10/IP-10 were further elevated in subjects who subsequently developed DHF/DSS (p=0.008, p=0.028 and p=0.025, respectively). In a logistic regression model, age (odds ratio (OR) (95% CI): 0.95 (0.92-0.98), p=0.001), hyperesthesia/hyperalgesia (OR; 3.8 (1.4-10.4), p=0.008) and elevated sICAM-1 (>298ng/mL: OR; 6.3 (1.5-25.7), p=0.011) at presentation were independently associated with progression to DHF/DSS. These results suggest that inflammation and endothelial activation are important pathways in the pathogenesis of dengue and sICAM-1 levels may identify individuals at risk of plasma leakage. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  8. Screening for biomarkers of liver injury induced by Polygonum multiflorum: a targeted metabolomic study

    Directory of Open Access Journals (Sweden)

    Qin eDong

    2015-10-01

    Full Text Available Heshouwu (HSW, the dry roots of Polygonum multiflorum, a classical traditional Chinese medicine is used as a tonic for a wide range of conditions,particularly those associated with aging. However, it tends to be taken overdose or long term in these years, which has resulted in liver damage reported in many countries. In this study, the indicative roles of nine bile acids (BAs were evaluated to offer potential biomarkers for HSW induced liver injury. Nine BAs including cholic acid (CA and chenodeoxycholic acid (CDCA, taurocholic acid (TCA, glycocholic acid (GCA, glycochenodeoxycholic acid (GCDCA, deoxycholic acid (DCA, glycodeoxycholic acid (GDCA, ursodeoxycholic acid (UDCA and hyodeoxycholic acid (HDCA in rat bile and serum were detected by a developed LC-MS method after 42 days treatment. Partial least square-discriminate analysis (PLS-DA was applied to evaluate the indicative roles of the nine BAs, and metabolism of the nine BAs was summarized. Significant change was observed for the concentrations of nine BAs in treatment groups compared with normal control; In the PLS-DA plots of nine BAs in bile, normal control and raw HSW groups were separately clustered and could be clearly distinguished, GDCA was selected as the distinguished components for raw HSW overdose treatment group. In the PLS-DA plots of nine BAs in serum, the normal control and raw HSW overdose treatment group were separately clustered and could be clearly distinguished, and HDCA was selected as the distinguished components for raw HSW overdose treatment group. The results indicated the perturbation of nine BAs was associated with HSW induced liver injury; GDCA in bile, as well as HDCA in serum could be selected as potential biomarkers for HSW induced liver injury; it also laid the foundation for the further search on the mechanisms of liver injury induced by HSW .

  9. Screening for biomarkers of liver injury induced by Polygonum multiflorum: a targeted metabolomic study

    Science.gov (United States)

    Dong, Qin; Li, Na; Li, Qi; Zhang, Cong-En; Feng, Wu-Wen; Li, Guang-Quan; Li, Rui-Yu; Tu, Can; Han, Xue; Bai, Zhao-Fang; Zhang, Ya-Ming; Niu, Ming; Ma, Zhi-Jie; Xiao, Xiao-He; Wang, Jia-Bo

    2015-01-01

    Heshouwu (HSW), the dry roots of Polygonum multiflorum, a classical traditional Chinese medicine is used as a tonic for a wide range of conditions, particularly those associated with aging. However, it tends to be taken overdose or long term in these years, which has resulted in liver damage reported in many countries. In this study, the indicative roles of nine bile acids (BAs) were evaluated to offer potential biomarkers for HSW induced liver injury. Nine BAs including cholic acid (CA) and chenodeoxycholic acid (CDCA), taurocholic acid (TCA), glycocholic acid (GCA), glycochenodeoxycholic acid (GCDCA), deoxycholic acid (DCA), glycodeoxycholic acid (GDCA), ursodeoxycholic acid (UDCA), and hyodeoxycholic acid (HDCA) in rat bile and serum were detected by a developed LC-MS method after 42 days treatment. Partial least square-discriminate analysis (PLS-DA) was applied to evaluate the indicative roles of the nine BAs, and metabolism of the nine BAs was summarized. Significant change was observed for the concentrations of nine BAs in treatment groups compared with normal control; In the PLS-DA plots of nine BAs in bile, normal control and raw HSW groups were separately clustered and could be clearly distinguished, GDCA was selected as the distinguished components for raw HSW overdose treatment group. In the PLS-DA plots of nine BAs in serum, the normal control and raw HSW overdose treatment group were separately clustered and could be clearly distinguished, and HDCA was selected as the distinguished components for raw HSW overdose treatment group. The results indicated the perturbation of nine BAs was associated with HSW induced liver injury; GDCA in bile, as well as HDCA in serum could be selected as potential biomarkers for HSW induced liver injury; it also laid the foundation for the further search on the mechanisms of liver injury induced by HSW. PMID:26483689

  10. Discovering discovery: lessons learnt from a usability study at the University of Liverpool

    Directory of Open Access Journals (Sweden)

    Jeff Woods

    2016-11-01

    Full Text Available In 2015 the University of Liverpool’s Library Service embarked upon a three-part usability study to better understand how library users were engaging with our resource discovery platform, to identify any usability issues and assess the extent to which it was currently meeting their needs. Doing so enabled us to make informed, evidence-based changes to the interface, improving its overall usability and providing a more user-friendly and intuitive resource. In this paper we will detail not only the methodologies employed, what we found out about our users, what they liked and disliked and the changes subsequently made, but also the lessons learnt about the platform, the process itself and ourselves.

  11. Discovery of rare variants via sequencing: implications for the design of complex trait association studies.

    Directory of Open Access Journals (Sweden)

    Bingshan Li

    2009-05-01

    Full Text Available There is strong evidence that rare variants are involved in complex disease etiology. The first step in implicating rare variants in disease etiology is their identification through sequencing in both randomly ascertained samples (e.g., the 1,000 Genomes Project and samples ascertained according to disease status. We investigated to what extent rare variants will be observed across the genome and in candidate genes in randomly ascertained samples, the magnitude of variant enrichment in diseased individuals, and biases that can occur due to how variants are discovered. Although sequencing cases can enrich for casual variants, when a gene or genes are not involved in disease etiology, limiting variant discovery to cases can lead to association studies with dramatically inflated false positive rates.

  12. Academic Drug Discovery Centres

    DEFF Research Database (Denmark)

    Kirkegaard, Henriette Schultz; Valentin, Finn

    2014-01-01

    Academic drug discovery centres (ADDCs) are seen as one of the solutions to fill the innovation gap in early drug discovery, which has proven challenging for previous organisational models. Prior studies of ADDCs have identified the need to analyse them from the angle of their economic and organi......Academic drug discovery centres (ADDCs) are seen as one of the solutions to fill the innovation gap in early drug discovery, which has proven challenging for previous organisational models. Prior studies of ADDCs have identified the need to analyse them from the angle of their economic...... their performance....

  13. Opportunities and Challenges of Proteomics in Pediatric Patients: Circulating Biomarkers After Hematopoietic Stem Cell Transplantation As a Successful Example

    Science.gov (United States)

    Paczesny, Sophie; Duncan, Christine; Jacobsohn, David; Krance, Robert; Leung, Kathryn; Carpenter, Paul; Bollard, Catherine; Renbarger, Jamie; Cooke, Kenneth

    2015-01-01

    Biomarkers have the potential to improve diagnosis and prognosis, facilitate targeted treatment, and reduce health care costs. Thus, there is great hope that biomarkers will be integrated in all clinical decisions in the near future. A decade ago, the biomarker field was launched with great enthusiasm because mass spectrometry revealed that blood contains a rich library of candidate biomarkers. However, biomarker research has not yet delivered on its promise due to several limitations: (i) improper sample handling and tracking as well as limited sample availability in the pediatric population, (ii) omission of appropriate controls in original study designs, (iii) lability and low abundance of interesting biomarkers in blood, and (iv) the inability to mechanistically tie biomarker presence to disease biology. These limitations as well as successful strategies to overcome them are discussed in this review. Several advances in biomarker discovery and validation have been made in hematopoietic stem cell transplantation, the current most effective tumor immunotherapy, and these could serve as examples for other conditions. This review provides fresh optimism that biomarkers clinically relevant in pediatrics are closer to being realized based on: (i) a uniform protocol for low-volume blood collection and preservation, (ii) inclusion of well-controlled independent cohorts, (iii) novel technologies and instrumentation with low analytical sensitivity, and (iv) integrated animal models for exploring potential biomarkers and targeted therapies. PMID:25196024

  14. MiRNA-155 and miRNA-132 as potential diagnostic biomarkers for pulmonary tuberculosis: A preliminary study.

    Science.gov (United States)

    Zheng, Meng-Li; Zhou, Nai-Kang; Luo, Cheng-Hua

    2016-11-01

    In our study, we aimed to profile a panel microRNAs (miRNAs) as potential biomarkers for the early diagnosis of pulmonary tuberculosis (PTB) and to illuminate the molecular mechanisms in the development of PTB. Firstly, gene expression profile of E-GEOD-49951 was downloaded from ArrayExpress database, and quantile-adjusted conditional maximum likelihood method was utilized to identify statistical difference between miRNAs of Mycobacterium tuberculosis (MTB)-infected individuals and healthy subjects. Furthermore, in order to assess the performance of our methodology, random forest (RF) classification model was utilized to identify the top 10 miRNAs with better Area Under The Curve (AUC) using 10-fold cross-validation method. Additionally, Monte Carlo Cross-Validation was repeated 50 times to explore the best miRNAs. In order to learn more about the differentially-expressed miRNAs, the target genes of differentially-expressed miRNAs were retrieved from TargetScan database and Ingenuity Pathways Analysis (IPA) was used to screen out biological pathways where target genes were involved. After normalization, a total of 478 miRNAs with higher than 0.25-fold quantile average across all samples were required. Based on the differential expression analysis, 38 differentially expressed miRNAs were identified when the significance was set as false discovery rate (FDR) < 0.01. Among the top 10 differentially expressed miRNAs, miRNA-155 obtained a highest AUC value 0.976, showing a good performance between PTB and control groups. Similarly, miRNA-449a, miRNA-212 and miRNA-132 revealed also a good performance with AUC values 0.947, 0.931 and 0.930, respectively. Moreover, miRNA-155, miRNA-449a, miRNA-29b-1* and miRNA-132 appeared in 50, 49, 49 and 48 bootstraps. Thus, miRNA-155 and miRNA-132 might be important in the progression of PTB and thereby, might present potential signatures for diagnosis of PTB. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. Correlation of serum MMP3 and other biomarkers with clinical outcomes in patients with ankylosing spondylitis: A pilot study

    Science.gov (United States)

    The studies aimed to assess a set of biomarkers for their correlations with disease activity/severity of patients with ankylosing spondylitis (AS). A total of 24 AS patients were treated with etanercept and prospectively followed for 12 weeks. Serum levels of TNF-alpha, IFN-gamma, TGF-beta, IL6, IL1...

  16. Pooled results from five validation studies of dietary self-report instruments using recovery biomarkers for potassium and sodium intake

    Science.gov (United States)

    We have pooled data from five large validation studies of dietary self-report instruments that used recovery biomarkers as referents to assess food frequency questionnaires (FFQs) and 24-hour recalls. We reported on total potassium and sodium intakes, their densities, and their ratio. Results were...

  17. Prediction of fruit and vegetable intake from biomarkers using individual participant data of diet-controlled intervention studies

    NARCIS (Netherlands)

    Souverein, O.W.; Vries, J.H.M. de; Freese, R.; Watzl, B.; Bub, A.; Miller, E.R., III; Castenmiller, J.J.M.; Pasman, W.J.; Hof, K. van het; Chopra, M.; Karlsen, A.; Dragsted, L.O.; Winkels, R.; Itsiopoulos, C.; Brazionis, L.; O'Dea, K.; Loo-Bouwman, C.A. van; Naber, T.H.J.; Voet, H. van der; Boshuizen, H.C.

    2015-01-01

    Fruit and vegetable consumption produces changes in several biomarkers in blood. The present study aimed to examine the dose-response curve between fruit and vegetable consumption and carotenoid (α-carotene, β-carotene, β-cryptoxanthin, lycopene, lutein and zeaxanthin), folate and vitamin C

  18. Evaluation of C-reactive protein as an inflammatory biomarker in rabbits for vaccine nonclinical safety studies

    NARCIS (Netherlands)

    Destexhe, E.; Prinsen, M.K.; Schöll, I. van; Kuper, C.F.; Garçon, N.; Veenstra, S.; Segal, L.

    2013-01-01

    Introduction: Inflammatory reactions are one of the potential safety concerns that are evaluated in the framework of vaccine safety testing. In nonclinical studies, the assessment of the inflammation relies notably on the measurement of biomarkers. C-reactive protein (CRP) is an acute-phase plasma

  19. CD64 on monocytes and granulocytes in severe acute bronchiolitis: Pilot study on its usefulness as a bacterial infection biomarker.

    Science.gov (United States)

    García-Salido, Alberto; Serrano-González, Ana; Casado-Flores, Juan; Sierra-Colomina, Montserrat; de Azagra-Garde, Amelia Martínez; García-Teresa, María Ángeles; Melen, Gustavo J; Ramírez-Orellana, Manuel

    2018-02-27

    The CD64 receptor has been described as a biomarker of bacterial infection. We speculated that CD64 surface expression on monocytes and granulocytes of children with severe acute bronchiolitis (SAB) could be altered in cases of probable bacterial infection (PBI) determined using classical biomarkers (procalcitonin and C-reactive protein, leukocyte count, and radiographic findings). A prospective observational pilot study was conducted from October 2015 to February 2016 in children admitted for pediatric critical care. A blood sample was taken in the first 24 hours of admission, and CD64 was measured by flow cytometry. The values obtained were analyzed and correlated with traditional biomarkers of PBI. Thirty-two children were included; a correlation was found between CD64 expression and the PBI criteria. CD64 surface expression was higher in children with PBI (area under the receiver operating characteristic curve of 0.73; P = 0.042) and the percentage of CD64 + granulocytes was higher in children with PBI. This is the first study to describe CD64 surface expression on monocytes and granulocytes in SAB, finding CD64 values to be higher in children with PBI. Larger clinical studies are needed to elucidate the real accuracy of CD64 as a biomarker of bacterial infection. ©2018 Society for Leukocyte Biology.

  20. Coronary Artery-Bypass-Graft Surgery Increases the Plasma Concentration of Exosomes Carrying a Cargo of Cardiac MicroRNAs: An Example of Exosome Trafficking Out of the Human Heart with Potential for Cardiac Biomarker Discovery.

    Directory of Open Access Journals (Sweden)

    Costanza Emanueli

    Full Text Available Exosome nanoparticles carry a composite cargo, including microRNAs (miRs. Cultured cardiovascular cells release miR-containing exosomes. The exosomal trafficking of miRNAs from the heart is largely unexplored. Working on clinical samples from coronary-artery by-pass graft (CABG surgery, we investigated if: 1 exosomes containing cardiac miRs and hence putatively released by cardiac cells increase in the circulation after surgery; 2 circulating exosomes and exosomal cardiac miRs correlate with cardiac troponin (cTn, the current "gold standard" surrogate biomarker of myocardial damage.The concentration of exosome-sized nanoparticles was determined in serial plasma samples. Cardiac-expressed (miR-1, miR-24, miR-133a/b, miR-208a/b, miR-210, non-cardiovascular (miR-122 and quality control miRs were measured in whole plasma and in plasma exosomes. Linear regression analyses were employed to establish the extent to which the circulating individual miRs, exosomes and exosomal cardiac miR correlated with cTn-I. Cardiac-expressed miRs and the nanoparticle number increased in the plasma on completion of surgery for up to 48 hours. The exosomal concentration of cardiac miRs also increased after CABG. Cardiac miRs in the whole plasma did not correlate significantly with cTn-I. By contrast cTn-I was positively correlated with the plasma exosome level and the exosomal cardiac miRs.The plasma concentrations of exosomes and their cargo of cardiac miRs increased in patients undergoing CABG and were positively correlated with hs-cTnI. These data provide evidence that CABG induces the trafficking of exosomes from the heart to the peripheral circulation. Future studies are necessary to investigate the potential of circulating exosomes as clinical biomarkers in cardiac patients.

  1. Towards a better understanding of biomarker response in field survey: a case study in eight populations of zebra mussels.

    Science.gov (United States)

    Pain-Devin, S; Cossu-Leguille, C; Geffard, A; Giambérini, L; Jouenne, T; Minguez, L; Naudin, B; Parant, M; Rodius, F; Rousselle, P; Tarnowska, K; Daguin-Thiébaut, C; Viard, F; Devin, S

    2014-10-01

    In order to provide reliable information about responsiveness of biomarkers during environmental monitoring, there is a need to improve the understanding of inter-population differences. The present study focused on eight populations of zebra mussels and aimed to describe how variable are biomarkers in different sampling locations. Biomarkers were investigated and summarised through the Integrated Biomarker Response (IBR index). Inter-site differences in IBR index were analysed through comparisons with morphological data, proteomic profiles and genetic background of the studied populations. We found that the IBR index was a good tool to inform about the status of sites. It revealed higher stress in more polluted sites than in cleaner ones. It was neither correlated to proteomic profiles nor to genetic background, suggesting a stronger influence of environment than genes. Meanwhile, morphological traits were related to both environment and genetic background influence. Together these results attest the benefit of using biological tools to better illustrate the status of a population and highlight the need of consider inter-population difference in their baselines. Copyright © 2014 Elsevier B.V. All rights reserved.

  2. The utility of collateral student drinking reports: Evidence from a biomarker study.

    Science.gov (United States)

    Fendrich, Michael; Fuhrmann, Daniel; Berger, Lisa; Plate, Charles; Lewis, Douglas; Jones, Joseph

    2015-11-01

    Researchers have increasingly used collateral informants to validate the reports provided by primary research subjects. We assessed the utility of collateral informants for college students in a study that incorporates biomarkers to validate student reports of recent drinking behavior. Students from a Midwestern university were randomly selected for a study in which they provided 90-day Timeline Followback data, hair and fingernail specimens for ethylglucuronide (EtG) testing, and information about collateral (friends or peers) informants who were familiar with their drinking behavior. We compared summary measures of recent drinking to collateral informant reports for the subset of 72 students who were selected to participate in the collateral validation process who had complete measures. Kappa, weighted kappa, and McNemar tests were performed to evaluate levels of agreement. We compared levels of use indicated by each informant within the context of EtG findings. We also compared respondent and collateral reports with respect to heavy drinking directly to EtG test results. There was considerable overlap between the reports provided by the student participants and their collateral informants. Within the context of EtG-informed analyses, collaterals rarely provided new information about heavy use beyond that provided by the study subjects. Collateral informants have limited utility in non-clinical studies of heavy drinking in randomly selected college students. Copyright © 2015. Published by Elsevier Ltd.

  3. Beyond Discovery

    DEFF Research Database (Denmark)

    Korsgaard, Steffen; Sassmannshausen, Sean Patrick

    2017-01-01

    In this chapter we explore four alternatives to the dominant discovery view of entrepreneurship; the development view, the construction view, the evolutionary view, and the Neo-Austrian view. We outline the main critique points of the discovery presented in these four alternatives, as well as the...

  4. Whole genome association studies of neuropsychiatric disease: An emerging era of collaborative genetic discovery

    OpenAIRE

    Keller, Margaret A; Gwinn, Katrina; Nash, Josefina; Horsford, Jonathan; Zhang, Ran; Rich, Stephen S; Corriveau, Roderick A

    2007-01-01

    Family history, which includes both common environmental and genetic effects, is associated with an increased risk for many neuropsychiatric diseases. Investigators have identified several disease-causing mutations for specific neuropsychiatric disorders that display Mendelian segregation. Such discoveries can lead to more rational drug design and improved intervention from a better understanding of the underlying biological mechanisms. However, a key challenge of genetic discovery in human c...

  5. Discovery of potential cholesterol esterase inhibitors using in silico docking studies

    Directory of Open Access Journals (Sweden)

    Thirumalaisamy Sivashanmugam

    2013-08-01

    Full Text Available New drug discovery is considered broadly in terms of two kinds of investiga-tional activities such as exploration and exploitation. This study deals with the evaluation of the cholesterol esterase inhibitory activity of flavonoids apigenin, biochanin, curcumin, diosmetin, epipervilline, glycitein, okanin, rhamnazin and tangeritin using in silico docking studies. In silico docking studies were carried out using AutoDock 4.2, based on the Lamarckian genetic algorithm principle. The results showed that all the selected flavonoids showed binding energy ranging between -7.08 kcal/mol to -5.64 kcal/mol when compared with that of the standard compound gallic acid (-4.11 kcal/mol. Intermolecular energy (-9.13 kcal/mol to -7.09 kcal/mol and inhibition constant (6.48 µM to 73.18 µM of the ligands also coincide with the binding energy. All the selected flavonoids contributed cholesterol esterase inhibitory activity, these molecular docking analyses could lead to the further develop-ment of potent cholesterol esterase inhibitors for the treatment of obesity.

  6. CSF biomarkers associated with disease heterogeneity in early Parkinson’s disease: the Parkinson’s Progression Markers Initiative study

    Science.gov (United States)

    Kang, Ju-Hee; Mollenhauer, Brit; Coffey, Christopher S.; Toledo, Jon B.; Weintraub, Daniel; Galasko, Douglas R.; Irwin, David J.; Van Deerlin, Vivianna; Chen-Plotkin, Alice S.; Caspell-Garcia, Chelsea; Waligórska, Teresa; Taylor, Peggy; Shah, Nirali; Pan, Sarah; Zero, Pawel; Frasier, Mark; Marek, Kenneth; Kieburtz, Karl; Jennings, Danna; Tanner, Caroline M.; Simuni, Tanya; Singleton, Andrew; Toga, Arthur W.; Chowdhury, Sohini; Trojanowski, John Q.; Shaw, Leslie M.

    2016-01-01

    The development of biomarkers to predict the progression of Parkinson’s disease (PD) from its earliest stage through its heterogeneous course is critical for research and therapeutic development. The Parkinson’s Progression Markers Initiative (PPMI) study is an ongoing international multicenter, prospective study to validate biomarkers in drug-naïve PD patients and matched healthy controls (HC). We quantified cerebrospinal fluid (CSF) alpha-synuclein (α-syn), amyloid-beta1–42 (Aβ1–42), total tau (t-tau), and tau phosphorylated at Thr181 (p-tau) in 660 PPMI subjects at baseline, and correlated these data with measures of the clinical features of these subjects. We found that CSF α-syn, t-tau and p-tau levels, but not Aβ1–42, were significantly lower in PD compared with HC, while the diagnostic value of the individual CSF biomarkers for PD diagnosis was limited due to large overlap. The level of α-syn, but not other biomarkers, was significantly lower in PD patients with non-tremor-dominant phenotype compared with tremor-dominant phenotype. In addition, in PD patients the lowest Aβ1–42, or highest t-tau/Aβ1–42 and t-tau/α-syn quintile in PD patients were associated with more severe non-motor dysfunction compared with the highest or lowest quintiles, respectively. In a multivariate regression model, lower α-syn was significantly associated with worse cognitive test performance. APOE ε4 genotype was associated with lower levels of Aβ1–42, but neither with PD diagnosis nor cognition. Our data suggest that the measurement of CSF biomarkers in early-stage PD patients may relate to disease heterogeneity seen in PD. Longitudinal observations in PPMI subjects are needed to define their prognostic performance. PMID:27021906

  7. Metabolic and inflammatory profiles of biomarkers in obesity, metabolic syndrome, and diabetes in a Mediterranean population. DARIOS Inflammatory study.

    Science.gov (United States)

    Fernández-Bergés, Daniel; Consuegra-Sánchez, Luciano; Peñafiel, Judith; Cabrera de León, Antonio; Vila, Joan; Félix-Redondo, Francisco Javier; Segura-Fragoso, Antonio; Lapetra, José; Guembe, María Jesús; Vega, Tomás; Fitó, Montse; Elosua, Roberto; Díaz, Oscar; Marrugat, Jaume

    2014-08-01

    There is a paucity of data regarding the differences in the biomarker profiles of patients with obesity, metabolic syndrome, and diabetes mellitus as compared to a healthy, normal weight population. We aimed to study the biomarker profile of the metabolic risk continuum defined by the transition from normal weight to obesity, metabolic syndrome, and diabetes mellitus. We performed a pooled analysis of data from 7 cross-sectional Spanish population-based surveys. An extensive panel comprising 20 biomarkers related to carbohydrate metabolism, lipids, inflammation, coagulation, oxidation, hemodynamics, and myocardial damage was analyzed. We employed age- and sex-adjusted multinomial logistic regression models for the identification of those biomarkers associated with the metabolic risk continuum phenotypes: obesity, metabolic syndrome, and diabetes mellitus. A total of 2851 subjects were included for analyses. The mean age was 57.4 (8.8) years, 1269 were men (44.5%), and 464 participants were obese, 443 had metabolic syndrome, 473 had diabetes mellitus, and 1471 had a normal weight (healthy individuals). High-sensitivity C-reactive protein, apolipoprotein B100, leptin, and insulin were positively associated with at least one of the phenotypes of interest. Apolipoprotein A1 and adiponectin were negatively associated. There are differences between the population with normal weight and that having metabolic syndrome or diabetes with respect to certain biomarkers related to the metabolic, inflammatory, and lipid profiles. The results of this study support the relevance of these mechanisms in the metabolic risk continuum. When metabolic syndrome and diabetes mellitus are compared, these differences are less marked. Copyright © 2013 Sociedad Española de Cardiología. Published by Elsevier Espana. All rights reserved.

  8. GENE AND PROTEIN EXPRESSION PROFILING OF PANCREATIC TUMOURS REVEAL DYSREGULATED PATHWAYS AND NOVEL POTENTIAL BIOMARKER.

    Science.gov (United States)

    Nweke, E N; Ntwasa, M N; Brand, M B; Devar, J D; Smith, M D; Candy, G P

    2017-06-01

    Pancreatic cancer (PDAC) is a deadly type of cancer with almost an equal amount of new cases and deaths observed yearly. It accounts for about 7% of cancer-related deaths worldwide. In many multi-racial societies including South Africa, the black population has the highest incidence rate. Less than 5% of PDAC patients live up to 5 years. The lack of specific and sensitive diagnostic PDAC biomarkers is strongly responsible for this poor statistic. The discovery of differentially expressed genes and proteins associated with PDAC is crucial to elucidating this condition and may lead to biomarker finding and further understanding of the disease. Tissue samples were obtained from Black South African PDAC patients during the Whipple procedure. Using focused arrays and RNA Sequencing, we have shown differentially expressed genes and proteins between tumour and normal tissue samples of PDAC patients in the quest for potential biomarker discovery. Furthermore, we utilised multiple bioinformatics tools to identify pathways and biological processes enriched by differentially expressed genes/proteins, and to discover novel variants and novel potential PDAC biomarkers. Real-time PCR and ELISA were also employed to validate our novel potential PDAC biomarker. We have identified novel 1) potential transcriptomic and 2) proteomic biomarkers of pancreatic cancer. Our identified transcriptomic biomarker has a sensitivity and specificity of 100% and 80% respectively. Furthermore, we observed novel genetic variants and dysregulated pathways occurring during pancreatic carcinogenesis. This study has identified novel potential biomarkers which can help in the diagnosis of PDAC. Information obtained from enriched signalling pathways help in further understanding the biology of PDAC. Going forward, the identified novel potential biomarkers need to be further validated in a larger sample number using easily accessible samples like blood.

  9. Lipid biomarkers for bacterial ecosystems: studies of cultured organisms, hydrothermal environments and ancient sediments

    Science.gov (United States)

    Summons, R. E.; Jahnke, L. L.; Simoneit, B. R.

    1996-01-01

    This paper forms part of our long-term goal of using molecular structure and carbon isotopic signals preserved as hydrocarbons in ancient sediments to improve understanding of the early evolution of Earth's surface environment. We are particularly concerned with biomarkers which are informative about aerobiosis. Here, we combine bacterial biochemistry with the organic geochemistry of contemporary and ancient hydrothermal ecosystems to construct models for the nature, behaviour and preservation potential of primitive microbial communities. We use a combined molecular and isotopic approach to characterize lipids produced by cultured bacteria and test a variety of culture conditions which affect their biosynthesis. This information is then compared with lipid mixtures isolated from contemporary hot springs and evaluated for the kinds of chemical change that would accompany burial and incorporation into the sedimentary record. In this study we have shown that growth temperature does not appear to alter isotopic fractionation within the lipid classes produced by a methanotropic bacterium. We also found that cultured cyanobacteria biosynthesize diagnostic methylalkanes and dimethylalkanes with the latter only made when growing under low pCO2. In an examination of a microbial mat sample from Octopus Spring, Yellowstone National Park (USA), we could readily identify chemical structures with 13C contents which were diagnostic for the phototrophic organisms such as cyanobacteria and Chloroflexus. We could not, however, find molecular evidence for operation of a methane cycle in the particular mat samples we studied.

  10. Comparative study of two-photon fluorescent bio-markers at nanosecond and femtosecond pulsed excitation

    Science.gov (United States)

    Peterson, Burl H.; Sarkisov, Sergey S.; Nesterov, V. N.; Curley, Michael J.; Urbas, Augustine; Patel, Darayas N.; Wang, J.-C.

    2007-02-01

    In this study we investigate visible fluorescence of cytotoxic bio-markers (molecular probes) based on the derivatives of piperidone at femtosecond infrared pulsed laser excitation. The subject of this investigation is the origin of the fluorescence. Does it originate from the excited state absorption, which occurs only at slow, nanosecond excitation, or is it due to intrinsic multi-photon absorption? In the past, it has been shown indirectly, through the laser photolysis study, that the contribution of the excited state absorption is minimal for several compounds of such type. The results of direct experiments with an infrared femtosecond fiber laser as an excitation source described here support this hypothesis. The observed dependence of the fluorescence on the pump power indicated the contribution of not only two-photon, but multi-photon routes of excitation. Additionally, it was shown that the spectral features of the fluorescence correlate with the presence of glycine, an amino acid that is one of the building blocks of proteins in a cell. The implication of this result is, in addition to their anticancer action, the compounds can possibly be used for fluorescent diagnostics of cancer and multi-photon fluorescent microscopy of malignant cell cultures using portable infrared fiber lasers as excitation sources.

  11. Sensitivity analysis for publication bias in meta-analysis of diagnostic studies for a continuous biomarker.

    Science.gov (United States)

    Hattori, Satoshi; Zhou, Xiao-Hua

    2018-02-10

    Publication bias is one of the most important issues in meta-analysis. For standard meta-analyses to examine intervention effects, the funnel plot and the trim-and-fill method are simple and widely used techniques for assessing and adjusting for the influence of publication bias, respectively. However, their use may be subjective and can then produce misleading insights. To make a more objective inference for publication bias, various sensitivity analysis methods have been proposed, including the Copas selection model. For meta-analysis of diagnostic studies evaluating a continuous biomarker, the summary receiver operating characteristic (sROC) curve is a very useful method in the presence of heterogeneous cutoff values. To our best knowledge, no methods are available for evaluation of influence of publication bias on estimation of the sROC curve. In this paper, we introduce a Copas-type selection model for meta-analysis of diagnostic studies and propose a sensitivity analysis method for publication bias. Our method enables us to assess the influence of publication bias on the estimation of the sROC curve and then judge whether the result of the meta-analysis is sufficiently confident or should be interpreted with much caution. We illustrate our proposed method with real data. Copyright © 2017 John Wiley & Sons, Ltd.

  12. Zinc Status Biomarkers and Cardiometabolic Risk Factors in Metabolic Syndrome: A Case Control Study

    Science.gov (United States)

    Freitas, Erika P. S.; Cunha, Aline T. O.; Aquino, Sephora L. S.; Pedrosa, Lucia F. C.; Lima, Severina C. V. C.; Lima, Josivan G.; Almeida, Maria G.; Sena-Evangelista, Karine C. M.

    2017-01-01

    Metabolic syndrome (MS) involves pathophysiological alterations that might compromise zinc status. The aim of this study was to evaluate zinc status biomarkers and their associations with cardiometabolic factors in patients with MS. Our case control study included 88 patients with MS and 37 controls. We performed clinical and anthropometric assessments and obtained lipid, glycemic, and inflammatory profiles. We also evaluated zinc intake, plasma zinc, erythrocyte zinc, and 24-h urinary zinc excretion. The average zinc intake was significantly lower in the MS group (p 0.05) between the two groups. We found significantly higher erythrocyte zinc concentration in the MS group (p < 0.001) independent from co-variable adjustments. Twenty-four hour urinary zinc excretion was significantly higher in the MS group (p = 0.008), and adjustments for age and sex explained 21% of the difference (R2 = 0.21, p < 0.001). There were significant associations between zincuria and fasting blood glucose concentration (r = 0.479), waist circumference (r = 0.253), triglyceride concentration (r = 0.360), glycated hemoglobin concentration (r = 0.250), homeostatic model assessment—insulin resistance (r = 0.223), and high-sensitivity C-reactive protein concentration (r = 0.427) (all p < 0.05) in the MS group. Patients with MS had alterations in zinc metabolism mainly characterized by an increase in erythrocyte zinc and higher zincuria. PMID:28241426

  13. Zinc Status Biomarkers and Cardiometabolic Risk Factors in Metabolic Syndrome: A Case Control Study

    Directory of Open Access Journals (Sweden)

    Erika P. S. Freitas

    2017-02-01

    Full Text Available Metabolic syndrome (MS involves pathophysiological alterations that might compromise zinc status. The aim of this study was to evaluate zinc status biomarkers and their associations with cardiometabolic factors in patients with MS. Our case control study included 88 patients with MS and 37 controls. We performed clinical and anthropometric assessments and obtained lipid, glycemic, and inflammatory profiles. We also evaluated zinc intake, plasma zinc, erythrocyte zinc, and 24-h urinary zinc excretion. The average zinc intake was significantly lower in the MS group (p < 0.001. Regression models indicated no significant differences in plasma zinc concentration (all p > 0.05 between the two groups. We found significantly higher erythrocyte zinc concentration in the MS group (p < 0.001 independent from co-variable adjustments. Twenty-four hour urinary zinc excretion was significantly higher in the MS group (p = 0.008, and adjustments for age and sex explained 21% of the difference (R2 = 0.21, p < 0.001. There were significant associations between zincuria and fasting blood glucose concentration (r = 0.479, waist circumference (r = 0.253, triglyceride concentration (r = 0.360, glycated hemoglobin concentration (r = 0.250, homeostatic model assessment—insulin resistance (r = 0.223, and high-sensitivity C-reactive protein concentration (r = 0.427 (all p < 0.05 in the MS group. Patients with MS had alterations in zinc metabolism mainly characterized by an increase in erythrocyte zinc and higher zincuria.

  14. Pooled Results From 5 Validation Studies of Dietary Self-Report Instruments Using Recovery Biomarkers for Energy and Protein Intake

    OpenAIRE

    Freedman, Laurence S.; Commins, John M.; Moler, James E.; Arab, Lenore; Baer, David J.; Kipnis, Victor; Midthune, Douglas; Moshfegh, Alanna J.; Neuhouser, Marian L.; Prentice, Ross L.; Schatzkin, Arthur; Spiegelman, Donna; Subar, Amy F.; Tinker, Lesley F.; Willett, Walter

    2014-01-01

    We pooled data from 5 large validation studies of dietary self-report instruments that used recovery biomarkers as references to clarify the measurement properties of food frequency questionnaires (FFQs) and 24-hour recalls. The studies were conducted in widely differing US adult populations from 1999 to 2009. We report on total energy, protein, and protein density intakes. Results were similar across sexes, but there was heterogeneity across studies. Using a FFQ, the average correlation coef...

  15. [A surveillance study on CRISPR/Cas molecular biomarker in Escherichia coli].

    Science.gov (United States)

    Liang, W J; Zhang, R G; Duan, G C; Hong, L J; Zhang, B; Xi, Y L; Yang, H Y; Chen, S Y; Lou, T Y; Zhao, Y X

    2016-08-10

    A new method related to molecular biomarker with CRISPR/Cas (clustered regularly interspaced short palindromic repeats-cas) in Escherichia (E.) coli was developed and used for surveillance programs. CRISPR/Cas sequence that containing 135 strains with complete sequence and 203 strains with whole genome shotgun sequence of E. coli in GenBank by BLAST and 361 strains of E. coli (including 38 strains of E. coli O157∶H7) in laboratory were identified by PCR and analyzed with the CRISPR Finder. Spacers were compared with DANMAN and the phylogenetic trees of cas gene were constructed under Clustal Ⅹ and Mega 5.1. With new perspective, a descriptive method was developed targeting on the position of CRISPR/cas in E. coli. The CRISPR1 was detected in 77.04%, 100.00% and 75.62% and the CRISPR2 was detected in 74.81%, 100.00% and 92.24% and the CRISPR3 and CRISPR4 were detected in 11.85%, 0 and 1.39% for 135 strains with complete sequence, 203 strains with whole genome shotgun sequence and 361 strains in the laboratory, respectively. One strain downloaded in GenBank with whole genome sequencing and 2 strains in the our laboratory were identified that containing four CRISPR locus. The other E. coli strain was with insertion sequence in downstream of the non-cas CRISPR1. The unique CRISPR was found in 8 strains of O55∶H7, in 180 strains of O157∶H7, in 8 strains of O157∶HNM, in 40 strains of O104∶H4, in 4 strains of O145∶H28, in all the 699 E. coli strains. The phylogenetic tree could be divided into two groups-cas with type I-E or type I-F. CRISPR/Cas might be used as a valuable molecular biomarker in epidemiological surveillance studies to identify the high virulent strains or new strains of E. coli. Phage night be related to the missing or obtaining of spacers.

  16. Discovery of novel phthalimide analogs: Synthesis, antimicrobial and antitubercular screening with molecular docking studies.

    Science.gov (United States)

    Rateb, Heba S; Ahmed, Hany E A; Ahmed, Sahar; Ihmaid, Saleh; Afifi, Tarek H

    2016-01-01

    In continuation of our endeavor towards the design and development of potent and effective antimicrobial agents, three series of phthalimide derivatives ( 4a-i, 5a-f, and 6a-c ) were synthesized, fully characterized and evaluated for their potential antibacterial, antifungal and antimycobacterial activities. These efforts led to the discovery of nine compounds 4c, 4f, 4g, 4h, 4i, 5c, 5d, 5e , and 6c (MIC range from 0.49 to 31.5 μg/mL) with potent antibacterial, antifungal, and antimycobacterial activities. Ampicillin, ciprofloxacin, amphotericin B were used as references for antibacterial and antifungal screening respectively, while isoniazid was used as a reference for antimycobacterial testing. Furthermore, molecular modeling studies were done to explore the binding mode of the most active derivatives to M. tuberculosis enoyl reductase (InhA) and DNA gyrase B. Our study showed the importance of both hydrogen bonding and hydrophobic interactions as a key interaction with the target enzymes.

  17. New tools for the study of Alzheimer's disease: what are biomarkers and morphometric markers teaching us?

    Science.gov (United States)

    Fjell, Anders M; Walhovd, Kristine B

    2011-10-01

    Early detection is vital in the quest to develop a cure for Alzheimer's disease (AD), and CSF biomarkers (Aβ42, t-tau, p-tau) and MRI morphometry distinguish AD from healthy controls. Aβ42 and neurodegenerative biomarkers may precede clinical symptoms, but it is not clear whether AD invariably follows and whether neuropsychological tests are as sensitive. Aβ42 is related to plaque burden, which was assumed to be the main cause of AD. Evidence is now pointing to other forms of Aβ, for example, soluble Aβ oligomers, and it is possible that plaques are secondary rather than causative to neuronal damage. This makes it less obvious that CSF Aβ42 necessarily is the most potent marker. Atrophy has been regarded as a downstream event, but novel MRI analysis techniques detect atrophy at a stage where the cognitive reductions are small and possibly reversible, and MRI is superior to CSF biomarkers in the prediction of cognitive decline. The impact of biomarkers may be dynamic; changed Aβ42 is seen in cognitively normal, while atrophy causes decrements later. In conclusion, CSF and MRI biomarkers are extremely important, but it is not known whether they can distinguish events that will lead to AD from events that will not before cognitive reductions are measurable.

  18. Parental receptivity to child biomarker testing for tobacco smoke exposure: A qualitative study.

    Science.gov (United States)

    Rosen, Laura J; Tillinger, Efrat; Guttman, Nurit; Rosenblat, Shira; Zucker, David M; Stillman, Frances; Myers, Vicki

    2015-11-01

    Widespread tobacco smoke exposure (TSE) of children suggests that parents may be unaware of their children's exposure. Biomarkers demonstrate exposure and may motivate behavior change, but their acceptability is not well understood. Sixty-five in-depth interviews were conducted with parents of young children, in smoking families in central Israel. Data were analyzed using thematic analysis. Consent to testing was associated with desire for information, for reassurance or to motivate change, and with concerns for long-term health, taking responsibility for one's child, and trust in research. Opposition to testing was associated with preference to avoid knowledge, reluctance to cause short-term discomfort, perceived powerlessness, and mistrust of research. Most parents expressed willingness to allow measurement by urine (83%), hair (88%), or saliva (93%), but not blood samples (43%); and believed that test results could motivate behavior change. Parents were receptive to non-invasive child biomarker testing. Biomarker information could help persuade parents who smoke that their children need protection. Biomarker testing of children in smoking families is an acceptable and promising tool for education, counseling, and motivation of parents to protect their children from TSE. Additionally, biomarker testing allows objective assessment of population-level child TSE. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  19. Usability Study Identifies Vocabulary, Facets, and Education as Primary Primo Discovery System Interface Problems

    Directory of Open Access Journals (Sweden)

    Ruby Muriel Lavallee Warren

    2017-09-01

    Full Text Available A Review of: Brett, K. R., Lierman, A., & Turner, C. (2016. Lessons learned: A Primo usability study. Information Technology and Libraries, 35(1, 7-25. https://doi.org/10.6017/ital.v35i1.8965 Abstract Objective – To discover whether users can effectively complete common research tasks in a modified Primo Discovery System interface. Design – Usability testing. Setting – University of Houston Libraries. Subjects – Users of the University of Houston Libraries Ex Libris Primo Discovery System interface. Methods – The researchers used a think aloud usability test methodology, with participants asked to verbalize their thought processes as they completed a set of tasks. Four tasks were developed and divided into two task sets (Test 1 and Test 2, with session facilitators alternating sets for each participant. Tasks were as follows: locating a known article, finding a peer reviewed article on a requested subject, locating a book, and finding a newspaper article on a topic. Tests were conducted in front of the library entrance using a laptop equipped with Morae (screen and audio recording software, and participants were recruited via an assigned “caller” at the table offering library merchandise and food as a research incentive. Users could opt out of having their session recorded, resulting in a total of fifteen sessions completed with fourteen recorded. Thirteen of the fifteen participants were undergraduate students, one was a graduate student, one was a post-baccalaureate student, and there were no faculty participants. Facilitators completed notes on a standard rubric, coding participant responses into successes or failures and noting participant feedback. Main Results – All eight participants assigned Test 1 successfully completed Test 1, Task 1: locating a known article. Participants expressed a need for an author limiter in advanced search, and had difficulty using the citation formatted information to locate materials

  20. Time-to-event data with time-varying biomarkers measured only at study entry, with applications to Alzheimer's disease.

    Science.gov (United States)

    Lee, Catherine; Betensky, Rebecca A

    2018-03-15

    Relating time-varying biomarkers of Alzheimer's disease to time-to-event using a Cox model is complicated by the fact that Alzheimer's disease biomarkers are sparsely collected, typically only at study entry; this is problematic since Cox regression with time-varying covariates requires observation of the covariate process at all failure times. The analysis might be simplified by using study entry as the time origin and treating the time-varying covariate measured at study entry as a fixed baseline covariate. In this paper, we first derive conditions under which using an incorrect time origin of study entry results in consistent estimation of regression parameters when the time-varying covariate is continuous and fully observed. We then derive conditions under which treating the time-varying covariate as fixed at study entry results in consistent estimation. We provide methods for estimating the regression parameter when a functional form can be assumed for the time-varying biomarker, which is measured only at study entry. We demonstrate our analytical results in a simulation study and apply our methods to data from the Rush Religious Orders Study and Memory and Aging Project and data from the Alzheimer's Disease Neuroimaging Initiative. Copyright © 2017 John Wiley & Sons, Ltd.

  1. Biomarkers of brain injury following an American football game: A pilot study.

    Science.gov (United States)

    Rogatzki, Matthew J; Soja, Scott E; McCabe, Colleen A; Breckenridge, Ryanne E; White, Jeffrey L; Baker, Julien S

    2016-09-01

    The goals of this study were to determine if the biomarkers of head injury, NSE and S100B, increased in serum following an American football game. Serum creatine kinase (CK) and cortisol levels were also measured to determine muscle damage and stress caused by the football game. NSE, S100B, CK, and cortisol were measured in the serum of 17 football players before and after a collegiate junior varsity football game. No head injuries were reported by the players, athletic training staff, or coaches yet both NSE (Pre-game: 7.0 μg•L-1 ± 2.2 versus Post-game: 13.1 μg•L-1 ± 7.0, P football game. There was little correlation found between S100B and body mass (R2 = 0.029) or CK (R2 = 0.352) levels. Although serum NSE and S100B increase as a result of playing in an American football game, the values are similar to or lower than levels found following competition in other contact and non-contact sports. Furthermore, the lack of correlation between S100B and body mass or CK indicates that S100B increases independent of body mass or muscle injury. © The Author(s) 2016.

  2. Hepatoprotective potential of Phyllanthus muellarianus leaf extract: studies on hepatic, oxidative stress and inflammatory biomarkers.

    Science.gov (United States)

    Ajiboye, Taofeek O; Ahmad, Fatimah M; Daisi, Airat O; Yahaya, Aminat A; Ibitoye, Oluwayemisi B; Muritala, Hamdalat F; Sunmonu, Taofik O

    2017-12-01

    Leaves of Phyllanthus muellarianus (Kuntze) Exell. (Euphorbiacea) are widely used in the management of liver disorders in Nigeria. However, no there is no scientific validation to support this use. Hepatoprotective effect of Phyllanthus muellarianus aqueous leaf extract was investigated in acetaminophen-induced liver injury mice. Hepatoprotective effect of Phyllanthus muellarianus aqueous leaf extract was evaluated in acetaminophen-induced hepatic damage in Swiss albino mice using biomarkers of hepatocellular indices, oxidative stress, proinflammatory factors and lipid peroxidation. Mice received distilled water, 100, 200, or 400 mg/kg b.w of Phyllanthus muellarianus aqueous leaf extract, respectively, for seven days. Treatment groups were challenged with 300 mg/kg b.w of acetaminophen on the sixth day. Oral administration of Phyllanthus muellarianus aqueous leaf extract significantly (p protein carbonyl, fragmented DNA, tumor necrosis factor-α, interleukin-6 and -8 were significantly lowered by Phyllanthus muellarianus aqueous leaf extract. Overall, results of this study show that Phyllanthus muellarianus halted acetaminophen-mediated hepatotoxicity due to its capability to enhance antioxidant enzymes.

  3. Using biomarkers to predict treatment response in major depressive disorder: evidence from past and present studies.

    Science.gov (United States)

    Thase, Michael E

    2014-12-01

    Major depressive disorder (MDD) is a heterogeneous condition with a variable response to a wide range of treatments. Despite intensive efforts, no biomarker has been identified to date that can reliably predict response or non-response to any form of treatment, nor has one been identified that can be used to identify those at high risk of developing treatment-resistant depression (ie, non-response to a sequence of treatments delivered for adequate duration and intensity). This manuscript reviews some past areas of research that have proved informative, such as studies using indexes of hypercortisolism or sleep disturbance, and more recent research findings using measures of inflammation and different indicators of regional cortical activation to predict treatment response. It is concluded that, although no method has yet been demonstrated to be sufficiently accurate to be applied in clinical practice, progress has been made. It thus seems likely that--at some point in the not-too-distant future--it will be possible to prospectively identify, at least for some MDD patients, the likelihood of response or non-response to cognitive therapy or various antidepressant medications.

  4. Cancer predictive value of cytogenetic markers used in occupational health surveillance programs. A report from an ongoing study by the European Study Group on Cytogenetic Biomarkers and Health

    International Nuclear Information System (INIS)

    Hagmar, Lars; Stroemberg, Ulf; Mikoczy, Zoli; Tinnerberg, Hakan; Skerfving, Staffan; Bonassi, Stefano; Lando, Cecilia; Hansteen, Inger-Lise; Montagud, Alicia Huici; Knudsen, Lisbeth; Norppa, Hannu; Reuterwall, Christina; Broegger, Anton; Forni, Alessandra; Hoegstedt, Benkt; Lambert, Bo; Mitelman, Felix; Nordenson, Ingrid; Salomaa, Sisko

    1998-01-01

    The cytogenetic endpoints in peripheral blood lymphocytes: chromosomal aberrations (CA), sister chromatid exchange (SCE) and micronuclei (MN) are established biomarkers of exposure for mutagens or carcinogens in the work environment. However, it is not clear whether these biomarkers also may serve as biomarkers for genotoxic effects which will result in an enhanced cancer risk. In order to assess this problem, Nordic and Italian cohorts were established, and preliminary results from these two studies indicated a predictive value of CA frequency for cancer risk, whereas no such associations were observed for SCE or MN. A collaborative study between the Nordic and Italian research groups, will enable a more thorough evaluation of the cancer predictivity of the cytogenetic endpoints. We here report on the establishment of a joint data base comprising 5271 subjects, examined 1965-1988 for at least one cytogenetic biomarker. Totally, 3540 subjects had been examined for CA, 2702 for SCE and 1496 for MN. These cohorts have been followed-up with respect to subsequent cancer mortality or cancer incidence, and the expected values have been calculated from rates derived from the general populations in each country. Stratified cohort analyses will be performed with respect to the levels of the cytogenetic biomarkers. The importance of potential effect modifiers such as gender, age at test, and time since test, will be evaluated using Poisson regression models. The remaining two potential effect modifiers, occupational exposures and smoking, will be assessed in a case-referent study within the study base

  5. The potential utility of urinary biomarkers for risk prediction in combat casualties: a prospective observational cohort study

    OpenAIRE

    Stewart, Ian J.; Glass, Kristen R.; Howard, Jeffrey T.; Morrow, Benjamin D.; Sosnov, Jonathan A.; Siew, Edward D.; Wickersham, Nancy; Latack, Wayne; Kwan, Hana K.; Heegard, Kelly D.; Diaz, Christina; Henderson, Aaron T.; Saenz, Kristin K.; Ikizler, T. Alp; Chung, Kevin K.

    2015-01-01

    Introduction Traditional risk scoring prediction models for trauma use either anatomically based estimations of injury or presenting vital signs. Markers of organ dysfunction may provide additional prognostic capability to these models. The objective of this study was to evaluate if urinary biomarkers are associated with poor outcomes, including death and the need for renal replacement therapy. Methods We conducted a prospective, observational study in United States Military personnel with tr...

  6. Discovery and study of novel protein tyrosine phosphatase 1B inhibitors

    Science.gov (United States)

    Zhang, Qian; Chen, Xi; Feng, Changgen

    2017-10-01

    Protein tyrosine phosphatase 1B (PTP1B) is considered to be a target for therapy of type II diabetes and obesity. So it is of great significance to take advantage of a computer aided drug design protocol involving the structured-based virtual screening with docking simulations for fast searching small molecule PTP1B inhibitors. Based on optimized complex structure of PTP1B bound with specific inhibitor of IX1, structured-based virtual screening against a library of natural products containing 35308 molecules, which was constructed based on Traditional Chinese Medicine database@ Taiwan (TCM database@ Taiwan), was conducted to determine the occurrence of PTP1B inhibitors using the Lubbock module and CDOCKER module from Discovery Studio 3.1 software package. The results were further filtered by predictive ADME simulation and predictive toxic simulation. As a result, 2 good drug-like molecules, namely para-benzoquinone compound 1 and Clavepictine analogue 2 were identified ultimately with the dock score of original inhibitor (IX1) and the receptor as a threshold. Binding model analyses revealed that these two candidate compounds have good interactions with PTP1B. The PTP1B inhibitory activity of compound 2 hasn't been reported before. The optimized compound 2 has higher scores and deserves further study.

  7. Early investigations of Ceres and the discovery of Pallas historical studies in asteroid research

    CERN Document Server

    Cunningham, Clifford

    2016-01-01

    An asteroid scholar, Cunningham in this book picks up where his Discovery of the First Asteroid, Ceres left off in telling the story of the impact created by the discovery of this new class of object in the early 1800s. The best and brightest minds of mathematics, science, and philosophy were fascinated by Ceres, and figures as diverse as Gauss, Herschel, Brougham, Kant, and Laplace all contributed something to the conversation. The first few chapters deal with the mathematical and philosophical aspects of the discovery, and the rivalry between Germany and France that so affected science and astronomy of that era. The jockeying for glory over the discovery of Ceres by both Piazzi and Bode is examined in detail, as is the reception given to Herschel’s use of the word 'asteroid.' Archival research that reveals the creator of the word 'asteroid' is presented in this book. Astronomy was a truly cosmopolitan field at the time, spanning across various disciplines, and the discovery of Pallas, a story completely t...

  8. A Selected Reaction Monitoring Mass Spectrometry Protocol for Validation of Proteomic Biomarker Candidates in Studies of Psychiatric Disorders.

    Science.gov (United States)

    Reis-de-Oliveira, Guilherme; Garcia, Sheila; Guest, Paul C; Cassoli, Juliana S; Martins-de-Souza, Daniel

    2017-01-01

    Most biomarker candidates arising from proteomic studies of psychiatric disorders have not progressed for use in clinical studies due to insufficient validation steps. Here we describe a selective reaction monitoring mass spectrometry (SRM-MS) approach that could be used as a follow-up validation tool of proteins identified in blood serum or plasma. This protocol specifically covers the stages of peptide selection and optimization. The increasing application of SRM-MS should enable fast, sensitive, and robust methods with the potential for use in clinical studies involving sampling of serum or plasma. Understanding the molecular mechanisms and identifying potential biomarkers for risk assessment, diagnosis, prognosis, and prediction of drug response goes toward the implementation of translational medicine strategies for improved treatment of patients with psychiatric disorders and other debilitating diseases.

  9. Prediction of fruit and vegetable intake from biomarkers using individual participant data of diet-controlled intervention studies

    DEFF Research Database (Denmark)

    Souverein, Olga W; de Vries, Jeanne H M; Freese, Riitta

    2015-01-01

    Fruit and vegetable consumption produces changes in several biomarkers in blood. The present study aimed to examine the dose-response curve between fruit and vegetable consumption and carotenoid (α-carotene, β-carotene, β-cryptoxanthin, lycopene, lutein and zeaxanthin), folate and vitamin C...... concentrations. Furthermore, a prediction model of fruit and vegetable intake based on these biomarkers and subject characteristics (i.e. age, sex, BMI and smoking status) was established. Data from twelve diet-controlled intervention studies were obtained to develop a prediction model for fruit and vegetable...... intake (including and excluding fruit and vegetable juices). The study population in the present individual participant data meta-analysis consisted of 526 men and women. Carotenoid, folate and vitamin C concentrations showed a positive relationship with fruit and vegetable intake. Measures...

  10. Relationship of Bone Metabolism Biomarkers and Periodontal Disease: The Osteoporotic Fractures in Men (MrOS) Study.

    Science.gov (United States)

    Schulze-Späte, Ulrike; Turner, Ryan; Wang, Ying; Chao, Raylien; Schulze, P Christian; Phipps, Kathy; Orwoll, Eric; Dam, Thuy-Tien

    2015-06-01

    Periodontitis is an inflammatory disease of tooth-supporting tissue leading to bone destruction and tooth loss. Periodontitis affects almost 50% of adults greater than 30 years of age. This study evaluated the association between biomarkers linked to bone formation and resorption with the occurrence and progression of periodontal disease in older men (≥ 65 y). The Osteoporotic Fractures in Men (MrOS) study is a prospective, observational study among men 65 years of age and older. This ancillary study, Oral and Skeletal Bone Loss in Older Men, was conducted at two of the six MrOS study sites (Birmingham, AL and Portland, OR). Patients underwent medical and dental evaluation. Diagnoses of periodontitis were based on clinical attachment loss, pocket depth, calculus, plaque, and bleeding on a random half-mouth. Bone metabolism biomarkers included serum levels of calcium, phosphate (Pi), alkaline phosphatase, albumin, carboxy-terminal collagen crosslinks (CTX), N-terminal propeptides of type I procollagen, isoform 5b of tartrate-resistant acid phosphatase, and urine alpha- carboxy-terminal collagen crosslinks (alpha-CTX) and beta-CTX and serum levels of calciotropic hormones vitamin D (25(OH)D) and PTH. The aim of this study is to correlate bone metabolism biomarkers with prevalence and progression of periodontal disease in older men. Patients with more severe periodontitis had significantly higher levels of PTH (P trend = .0004), whereas 25(OH)D was lower (P trend = .001). In a subset of men reevaluated at a second dental visit, improvement of periodontitis was associated with lower alpha-CTX, beta-CTX, and CTX levels at baseline after adjusting for age, site, and body mass index. This study suggests that a distinct set of biomarkers of bone metabolism are associated with more severe periodontal disease (PTH, 25(OH)D) and periodontal progression (alpha-CTX, beta-CTX, and CTX) over time.

  11. An exploratory pilot study with copeptin as a biomarker for individualizing treatment for nocturnal polyuria.

    Science.gov (United States)

    Bruneel, Elke; Goessaert, An-Sofie; Denys, Marie-Astrid; Juul, Kristian V; Nørgaard, Jens P; Everaert, Karel

    2017-10-23

    The aim of the present study was to investigate the use of random copeptin concentrations as possible biomarkers for the differential diagnosis of nocturnal polyuria (NP). In all, 111 patients with and without nocturia were enrolled in the study. Patients with a neurogenic bladder and/or those who had undergone bladder or urethral surgery were excluded from the study. All patients completed a 72-hour frequency-volume chart and a renal function profile. A random blood sample was obtained during the day for measurement of plasma copeptin concentrations, osmolality, and serum sodium and creatinine concentrations. The effect of the use of different definitions for NP was evaluated. The median age of the study participants was 61 years, and 48% were female. Copeptin was significantly correlated with urinary and plasma osmolality, as well as free water clearance (r=0.43, 0.56 and -0.38 respectively; P NP (n = 41), and those with global polyuria (n = 19). Copeptin concentrations were significantly lower in subjects with global polyuria than in those with NP and the control group (2.96 vs 3.97 and 3.94 pM, respectively; P = .008 and .005). There was no significant difference in random daytime copeptin concentrations between the NP and control groups (P = .972). The results differed when other definitions for NP were used (e.g. NPi33 or NUP10). We could not confirm our hypothesis that patients with NP have lower copeptin concentrations, although random blood sampling is not ideal. Further research is required to determine the use of copeptin in NP, perhaps in the identification of the desmopressin response. © 2017 John Wiley & Sons Australia, Ltd.

  12. The Australian biomarker, imaging and lifestyle study: phase 1 amyloid imaging results

    International Nuclear Information System (INIS)

    Rowe, C. C.; Pike, K.; Villemagne, V. L.; Morandeau, L.; Masters, C. L.; Ames, D.

    2009-01-01

    Full text:Background: Phase 1 of the Australian Imaging, Biomarkers and Lifestyle (AIBL) Flagship Study of Ageing, a three-year prospective longitudinal study recruiting 1,112 volunteers from a cross-section of Australia's elderly population, concluded with more than a quarter of the participants undergoing PiB-PET. Methods: 287 participants received PiB PET scans: 177 Healthy controls (HC); 57 Mild Cognitive Impairment (MCI) subjects; and 53 mild Alzheimer's disease (AD) patients. HC were further classified according to their subjective memory complaints and genetic predisposition. All participants underwent a comprehensive neuropsychological examination, a 3D T1 MP-RAGE and T2 FSE MR, and a PiB-PET scan. Regional and global cortical SUVR were calculated using the cerebellar cortex as reference region. A SUVR cut-off of 1.40 was used to define PiB scans as normal or abnormal. Results: Cortical PIB binding was markedly elevated in all AD patients except one. MCI subjects presented either an AD-like (63%) or normal pattern. Cortical PiB retention was abnormal in 34% of HC and the prevalence increased with age. HC with subjective memory complaints carrying an ApoE4 allele had significantly higher A burdens than non ApoE4 carriers. Conclusions: Phase 1 of the AIBL study has set the foundations for the longitudinal assessment of A burden in HC, MCI and AD. This wil assist the development of techniques for early detection of AD providing a cohort suitable for targeted early intervention studies.

  13. Trace elements in scalp hair and fingernails as biomarkers in clinical studies

    Directory of Open Access Journals (Sweden)

    Awad Abdalla Momen

    2015-01-01

    Full Text Available Context: There are accumulating evidences that the metabolism of several trace elements might have specific roles in clinical disorders and the pathogenesis of many diseases, such as diabetes mellitus (DM and hypertension (HT. Objectives: To validate the analytical procedure and compare the levels of Cd, Cr, Cu, Pb, and Zn in scalp hair (SH and fingernails (FN of patients. Furthermore, to prove that human tissues such as hair and nails are useful in the studies pertaining to chronic body exposure and good biomarkers in clinical studies. Setting and Design: Inductively coupled plasma optical emission spectroscopy operating conditions were carefully selected and well-optimised in order to maximise the sensitivity for the desired elements and to obtain the best precision and accuracy. Factors affecting analytical and biological variability of the concentrations under study were discussed and carefully optimised. Materials and Methods: Totally, 160 samples of SH and 130 FN were collected from occupants of urban population from different districts adjacent to Taif city, Kingdom of Saudi Arabia. Different analytical procedures were investigated, and the most reliable one was developed and validated. Method Validity: The validity of the method was checked by standard addition method. The recoveries were in the range of 96.2-105.7%. Results: Cd, Cr, Cu, and Pb levels in SH were significantly higher in DM and HT compared to control groups, whereas, Zn was significantly lower. Cd and Pb levels in FN were significantly higher in DM and HT, whereas, Cr and Zn were lower, and Cu was in the same levels as compared to the control group. Conclusion: These findings may be consistent with those obtained in other studies, confirming that the deficiency and efficiency of trace elements play a role in clinical disorders and the pathogenesis of many diseases.

  14. Applying Data-driven Imaging Biomarker in Mammography for Breast Cancer Screening: Preliminary Study

    OpenAIRE

    Kim, Eun-Kyung; Kim, Hyo-Eun; Han, Kyunghwa; Kang, Bong Joo; Sohn, Yu-Mee; Woo, Ok Hee; Lee, Chan Wha

    2018-01-01

    We assessed the feasibility of a data-driven imaging biomarker based on weakly supervised learning (DIB; an imaging biomarker derived from large-scale medical image data with deep learning technology) in mammography (DIB-MG). A total of 29,107 digital mammograms from five institutions (4,339 cancer cases and 24,768 normal cases) were included. After matching patients’ age, breast density, and equipment, 1,238 and 1,238 cases were chosen as validation and test sets, respectively, and the remai...

  15. BIOMarkers for occupational diesel exhaust exposure monitoring (BIOMODEM)--a study in underground mining

    DEFF Research Database (Denmark)

    Scheepers, P T J; Coggon, D; Knudsen, Lisbeth E.

    2002-01-01

    Methods for the assessment of exposures to diesel exhaust were evaluated, including various biomarkers of internal exposure and early biological effects. The impact of possible biomarkers of susceptibility was also explored. Underground workers (drivers of diesel-powered excavators) at an oil shale...... mine in Estonia were compared with surface workers. Personal exposures to particle-associated 1-nitropyrene (NP) were some eight times higher underground than on the surface. Underground miners were also occupationally exposed to benzene and polycyclic aromatic hydrocarbons, as indicated by excretion...

  16. Study of the apoptotic effect of urine as a diagnostic biomarker in patients with interstitial cystitis.

    Science.gov (United States)

    Di Capua-Sacoto, C; Sanchez-Llopis, A; O'Connor, E; Martinez, A; Ruiz-Cerdá, J L

    2016-11-01

    The main objective of the study was to assess the apoptotic effect of urine from patients with interstitial cystitis (IC) in cell cultures and to study its value as a diagnostic biomarker for IC. A prospective study was conducted between January 2010 and January 2015 and included 57 patients diagnosed with IC and 50 healthy patients from the Hospital Clinic of Barcelona and the La Paz University Hospital. The urine of these patients was exposed to cell cultures, and its ability to induce apoptosis in the cultures was analysed. Using flow cytometry, we then measured the degree of apoptosis, quantified by the percentage of cells of the cell cycle in phase sub G0. The cell cultures exposed to the urine of patients with IC had a sub G1 peak and a G2 phase, which was significantly greater than that of the control group, and a significantly lower percentage in the S phase than the control group. The mean apoptosis values in the urine cultures from patients with IC were significantly higher than those of the control group. Using a value >10% of the apoptosis test as a positive result, we observed a specificity of 96% and a positive predictive value of 92%. The urine of patients with IC exerts an apoptotic effect on tumour cell cultures that is significantly greater than that exerted by the urine of healthy control patients. A≥10% cutoff for the apoptosis test presented very low sensitivity (40%) but had a very high specificity (96%), thereby able to confirm the diagnosis of IC when positive. Copyright © 2016 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

  17. Plasma proteomics to identify biomarkers - Application to cardiovascular diseases

    DEFF Research Database (Denmark)

    Beck, Hans Christian; Overgaard, Martin; Melholt Rasmussen, Lars

    2015-01-01

    There is an unmet need for new cardiovascular biomarkers. Despite this only few biomarkers for the diagnosis or screening of cardiovascular diseases have been implemented in the clinic. Thousands of proteins can be analysed in plasma by mass spectrometry-based proteomics technologies. Therefore......, this technology may therefore identify new biomarkers that previously have not been associated with cardiovascular diseases. In this review, we summarize the key challenges and considerations, including strategies, recent discoveries and clinical applications in cardiovascular proteomics that may lead...... to the discovery of novel cardiovascular biomarkers....

  18. Brain tissues atrophy is not always the best structural biomarker of physiological aging: A multimodal cross-sectional study.

    Science.gov (United States)

    Cherubini, Andrea; Caligiuri, Maria Eugenia; Péran, Patrice; Sabatini, Umberto; Cosentino, Carlo; Amato, Francesco

    2015-01-01

    This study presents a voxel-based multiple regression analysis of different magnetic resonance image modalities, including anatomical T1-weighted, T2* relaxometry, and diffusion tensor imaging. Quantitative parameters sensitive to complementary brain tissue alterations, including morphometric atrophy, mineralization, microstructural damage, and anisotropy loss, were compared in a linear physiological aging model in 140 healthy subjects (range 20-74 years). The performance of different predictors and the identification of the best biomarker of age-induced structural variation were compared without a priori anatomical knowledge. The best quantitative predictors in several brain regions were iron deposition and microstructural damage, rather than macroscopic tissue atrophy. Age variations were best resolved with a combination of markers, suggesting that multiple predictors better capture age-induced tissue alterations. These findings highlight the importance of a combined evaluation of multimodal biomarkers for the study of aging and point to a number of novel applications for the method described.

  19. Subgroup Discovery for Election Analysis: A Case Study in Descriptive Data Mining

    Science.gov (United States)

    Grosskreutz, Henrik; Boley, Mario; Krause-Traudes, Maike

    In this paper, we investigate the application of descriptive data mining techniques, namely subgroup discovery, for the purpose of the ad-hoc analysis of election results. Our inquiry is based on the 2009 German federal Bundestag election (restricted to the City of Cologne) and additional socio-economic information about Cologne's polling districts. The task is to describe relations between socio-economic variables and the votes in order to summarize interesting aspects of the voting behavior. Motivated by the specific challenges of election data analysis we propose novel quality functions and visualizations for subgroup discovery.

  20. Characterization of neurophysiologic and neurocognitive biomarkers for use in genomic and clinical outcome studies of schizophrenia.

    Directory of Open Access Journals (Sweden)

    Gregory A Light

    Full Text Available Endophenotypes are quantitative, laboratory-based measures representing intermediate links in the pathways between genetic variation and the clinical expression of a disorder. Ideal endophenotypes exhibit deficits in patients, are stable over time and across shifts in psychopathology, and are suitable for repeat testing. Unfortunately, many leading candidate endophenotypes in schizophrenia have not been fully characterized simultaneously in large cohorts of patients and controls across these properties. The objectives of this study were to characterize the extent to which widely-used neurophysiological and neurocognitive endophenotypes are: 1 associated with schizophrenia, 2 stable over time, independent of state-related changes, and 3 free of potential practice/maturation or differential attrition effects in schizophrenia patients (SZ and nonpsychiatric comparison subjects (NCS. Stability of clinical and functional measures was also assessed.Participants (SZ n = 341; NCS n = 205 completed a battery of neurophysiological (MMN, P3a, P50 and N100 indices, PPI, startle habituation, antisaccade, neurocognitive (WRAT-3 Reading, LNS-forward, LNS-reorder, WCST-64, CVLT-II. In addition, patients were rated on clinical symptom severity as well as functional capacity and status measures (GAF, UPSA, SOF. 223 subjects (SZ n = 163; NCS n = 58 returned for retesting after 1 year.Most neurophysiological and neurocognitive measures exhibited medium-to-large deficits in schizophrenia, moderate-to-substantial stability across the retest interval, and were independent of fluctuations in clinical status. Clinical symptoms and functional measures also exhibited substantial stability. A Longitudinal Endophenotype Ranking System (LERS was created to rank neurophysiological and neurocognitive biomarkers according to their effect sizes across endophenotype criteria.The majority of neurophysiological and neurocognitive measures exhibited deficits in