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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

    2018-05-01

    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 the 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 the

  2. Proteomic and metabolomic approaches to biomarker discovery

    CERN Document Server

    Issaq, Haleem J

    2013-01-01

    Proteomic and Metabolomic Approaches to Biomarker Discovery demonstrates how to leverage biomarkers to improve accuracy and reduce errors in research. Disease biomarker discovery is one of the most vibrant and important areas of research today, as the identification of reliable biomarkers has an enormous impact on disease diagnosis, selection of treatment regimens, and therapeutic monitoring. Various techniques are used in the biomarker discovery process, including techniques used in proteomics, the study of the proteins that make up an organism, and metabolomics, the study of chemical fingerprints created from cellular processes. Proteomic and Metabolomic Approaches to Biomarker Discovery is the only publication that covers techniques from both proteomics and metabolomics and includes all steps involved in biomarker discovery, from study design to study execution.  The book describes methods, and presents a standard operating procedure for sample selection, preparation, and storage, as well as data analysis...

  3. Biomarker Discovery in Human Prostate Cancer: an Update in Metabolomics Studies

    Directory of Open Access Journals (Sweden)

    Ana Rita Lima

    2016-08-01

    Full Text Available Prostate cancer (PCa is the most frequently diagnosed cancer and the second leading cause of cancer death among men in Western countries. Current screening techniques are based on the measurement of serum prostate specific antigen (PSA levels and digital rectal examination. A decisive diagnosis of PCa is based on prostate biopsies; however, this approach can lead to false-positive and false-negative results. Therefore, it is important to discover new biomarkers for the diagnosis of PCa, preferably noninvasive ones. Metabolomics is an approach that allows the analysis of the entire metabolic profile of a biological system. As neoplastic cells have a unique metabolic phenotype related to cancer development and progression, the identification of dysfunctional metabolic pathways using metabolomics can be used to discover cancer biomarkers and therapeutic targets. In this study, we review several metabolomics studies performed in prostatic fluid, blood plasma/serum, urine, tissues and immortalized cultured cell lines with the objective of discovering alterations in the metabolic phenotype of PCa and thus discovering new biomarkers for the diagnosis of PCa. Encouraging results using metabolomics have been reported for PCa, with sarcosine being one of the most promising biomarkers identified to date. However, the use of sarcosine as a PCa biomarker in the clinic remains a controversial issue within the scientific community. Beyond sarcosine, other metabolites are considered to be biomarkers for PCa, but they still need clinical validation. Despite the lack of metabolomics biomarkers reaching clinical practice, metabolomics proved to be a powerful tool in the discovery of new biomarkers for PCa detection.

  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.

    Science.gov (United States)

    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. Shotgun Proteomics and Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  13. Urinary metabonomics study on toxicity biomarker discovery in rats treated with Xanthii Fructus.

    Science.gov (United States)

    Lu, Fang; Cao, Min; Wu, Bin; Li, Xu-zhao; Liu, Hong-yu; Chen, Da-zhong; Liu, Shu-min

    2013-08-26

    Xanthii Fructus (XF) is commonly called "Cang-Erzi" in traditional Chinese medicine (TCM) and widely used for the treatment of sinusitis, headache, rheumatism, and skin itching. However, the clinical utilization of XF is relatively restricted owing to its toxicity. To discover the characteristic potential biomarkers in rats treated with XF by urinary metabonomics. Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) was applied in the study. The total ion chromatograms obtained from control and different dosage groups were distinguishable by a multivariate statistical analysis method. The greatest difference in metabolic profile was observed between high dosage group and control group, and the metabolic characters in rats treated with XF were perturbed in a dose-dependent manner. The metabolic changes in response for XF treatment were observed in urinary samples, which were revealed by orthogonal projection to latent structures discriminate analysis (OPLS-DA), and 10 metabolites could be served as the potential toxicity biomarkers. In addition, the mechanism associated with the damages of lipid per-oxidation and the metabolic disturbances of fatty acid oxidation were investigated. These results indicate that metabonomics analysis in urinary samples may be useful for predicting the toxicity induced by XF. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  14. Mass Spectrometry-Based Biomarker Discovery.

    Science.gov (United States)

    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.

  15. Using Aptamers for Cancer Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    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.

  16. 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.

  17. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  19. 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.

  20. Novel ageing-biomarker discovery using data-intensive technologies.

    Science.gov (United States)

    Griffiths, H R; Augustyniak, E M; Bennett, S J; Debacq-Chainiaux, F; Dunston, C R; Kristensen, P; Melchjorsen, C J; Navarrete, Santos A; Simm, A; Toussaint, O

    2015-11-01

    Ageing is accompanied by many visible characteristics. Other biological and physiological markers are also well-described e.g. loss of circulating sex hormones and increased inflammatory cytokines. Biomarkers for healthy ageing studies are presently predicated on existing knowledge of ageing traits. The increasing availability of data-intensive methods enables deep-analysis of biological samples for novel biomarkers. We have adopted two discrete approaches in MARK-AGE Work Package 7 for biomarker discovery; (1) microarray analyses and/or proteomics in cell systems e.g. endothelial progenitor cells or T cell ageing including a stress model; and (2) investigation of cellular material and plasma directly from tightly-defined proband subsets of different ages using proteomic, transcriptomic and miR array. The first approach provided longitudinal insight into endothelial progenitor and T cell ageing. This review describes the strategy and use of hypothesis-free, data-intensive approaches to explore cellular proteins, miR, mRNA and plasma proteins as healthy ageing biomarkers, using ageing models and directly within samples from adults of different ages. It considers the challenges associated with integrating multiple models and pilot studies as rational biomarkers for a large cohort study. From this approach, a number of high-throughput methods were developed to evaluate novel, putative biomarkers of ageing in the MARK-AGE cohort. Crown Copyright © 2015. Published by Elsevier Ireland Ltd. All rights reserved.

  1. 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

  2. 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.

  3. Aptamer-based multiplexed proteomic technology for biomarker discovery.

    Science.gov (United States)

    Gold, Larry; Ayers, Deborah; Bertino, Jennifer; Bock, Christopher; Bock, Ashley; Brody, Edward N; Carter, Jeff; Dalby, Andrew B; Eaton, Bruce E; Fitzwater, Tim; Flather, Dylan; Forbes, Ashley; Foreman, Trudi; Fowler, Cate; Gawande, Bharat; Goss, Meredith; Gunn, Magda; Gupta, Shashi; Halladay, Dennis; Heil, Jim; Heilig, Joe; Hicke, Brian; Husar, Gregory; Janjic, Nebojsa; Jarvis, Thale; Jennings, Susan; Katilius, Evaldas; Keeney, Tracy R; Kim, Nancy; Koch, Tad H; Kraemer, Stephan; Kroiss, Luke; Le, Ngan; Levine, Daniel; Lindsey, Wes; Lollo, Bridget; Mayfield, Wes; Mehan, Mike; Mehler, Robert; Nelson, Sally K; Nelson, Michele; Nieuwlandt, Dan; Nikrad, Malti; Ochsner, Urs; Ostroff, Rachel M; Otis, Matt; Parker, Thomas; Pietrasiewicz, Steve; Resnicow, Daniel I; Rohloff, John; Sanders, Glenn; Sattin, Sarah; Schneider, Daniel; Singer, Britta; Stanton, Martin; Sterkel, Alana; Stewart, Alex; Stratford, Suzanne; Vaught, Jonathan D; Vrkljan, Mike; Walker, Jeffrey J; Watrobka, Mike; Waugh, Sheela; Weiss, Allison; Wilcox, Sheri K; Wolfson, Alexey; Wolk, Steven K; Zhang, Chi; Zichi, Dom

    2010-12-07

    The interrogation of proteomes ("proteomics") in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (~100 fM-1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states. We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.

  4. Aptamer-based multiplexed proteomic technology for biomarker discovery.

    Directory of Open Access Journals (Sweden)

    Larry Gold

    2010-12-01

    Full Text Available The interrogation of proteomes ("proteomics" in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine.We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma. Our current assay measures 813 proteins with low limits of detection (1 pM median, 7 logs of overall dynamic range (~100 fM-1 µM, and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD. We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states.We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.

  5. 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.

  6. 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

  7. 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.

  8. Improving the quality of biomarker discovery research: the right samples and enough of them.

    Science.gov (United States)

    Pepe, Margaret S; Li, Christopher I; Feng, Ziding

    2015-06-01

    Biomarker discovery research has yielded few biomarkers that validate for clinical use. A contributing factor may be poor study designs. The goal in discovery research is to identify a subset of potentially useful markers from a large set of candidates assayed on case and control samples. We recommend the PRoBE design for selecting samples. We propose sample size calculations that require specifying: (i) a definition for biomarker performance; (ii) the proportion of useful markers the study should identify (Discovery Power); and (iii) the tolerable number of useless markers amongst those identified (False Leads Expected, FLE). We apply the methodology to a study of 9,000 candidate biomarkers for risk of colon cancer recurrence where a useful biomarker has positive predictive value ≥ 30%. We find that 40 patients with recurrence and 160 without recurrence suffice to filter out 98% of useless markers (2% FLE) while identifying 95% of useful biomarkers (95% Discovery Power). Alternative methods for sample size calculation required more assumptions. Biomarker discovery research should utilize quality biospecimen repositories and include sample sizes that enable markers meeting prespecified performance characteristics for well-defined clinical applications to be identified. The scientific rigor of discovery research should be improved. ©2015 American Association for Cancer Research.

  9. 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.

  10. The path from biomarker discovery to regulatory qualification

    CERN Document Server

    Goodsaid, Federico

    2013-01-01

    The Path from Biomarker Discovery to Regulatory Qualification is a unique guide that focuses on biomarker qualification, its history and current regulatory settings in both the US and abroad. This multi-contributed book provides a detailed look at the next step to developing biomarkers for clinical use and covers overall concepts, challenges, strategies and solutions based on the experiences of regulatory authorities and scientists. Members of the regulatory, pharmaceutical and biomarker development communities will benefit the most from using this book-it is a complete and practical guide to biomarker qualification, providing valuable insight to an ever-evolving and important area of regulatory science. For complimentary access to chapter 13, 'Classic' Biomarkers of Liver Injury, by John R. Senior, Associate Director for Science, Food and Drug Administration, Silver Spring, Maryland, USA, please visit the following site:  http://tinyurl.com/ClassicBiomarkers Contains a collection of experiences of different...

  11. 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.

  12. Cellular Models for Environmental Toxicant Biomarker Discovery

    National Research Council Canada - National Science Library

    Halverson, Kelly M; Lewsis, John A; Jackson, David A; Dennis, William; Brennan, Linda; Krakaner, Teresa

    2006-01-01

    ...) is the development of biomarkers of exposure, effect, and susceptibility. As exposure monitoring using environmental sampling equipment can be impractical and doesn't account for differences in individual responses, new methodologies must be sought...

  13. PROFILEing idiopathic pulmonary fibrosis: rethinking biomarker discovery

    Directory of Open Access Journals (Sweden)

    Toby M. Maher

    2013-06-01

    Full Text Available Despite major advances in the understanding of the pathogenesis of idiopathic pulmonary fibrosis (IPF, diagnosis and management of the condition continue to pose significant challenges. Clinical management of IPF remains unsatisfactory due to limited availability of effective drug therapies, a lack of accurate indicators of disease progression, and an absence of simple short-term measures of therapeutic response. The identification of more accurate predictors of prognosis and survival in IPF would facilitate counseling of patients and their families, aid communication among clinicians, and would guide optimal timing of referral for transplantation. Improvements in molecular techniques have led to the identification of new disease pathways and a more targeted approach to the development of novel anti-fibrotic agents. However, despite an increased interest in biomarkers of IPF disease progression there are a lack of measures that can be used in early phase clinical trials. Careful longitudinal phenotyping of individuals with IPF together with the application of novel omics-based technology should provide important insights into disease pathogenesis and should address some of the major issues holding back drug development in IPF. The PROFILE (Prospective Observation of Fibrosis in the Lung Clinical Endpoints study is a currently enrolling, prospective cohort study designed to tackle these issues.

  14. Metabolomics in cancer biomarker discovery: current trends and future perspectives.

    Science.gov (United States)

    Armitage, Emily G; Barbas, Coral

    2014-01-01

    Cancer is one of the most devastating human diseases that causes a vast number of mortalities worldwide each year. Cancer research is one of the largest fields in the life sciences and despite many astounding breakthroughs and contributions over the past few decades, there is still a considerable amount to unveil on the function of cancer. It is well known that cancer metabolism differs from that of normal tissue and an important hypothesis published in the 1950s by Otto Warburg proposed that cancer cells rely on anaerobic metabolism as the source for energy, even under physiological oxygen levels. Following this, cancer central carbon metabolism has been researched extensively and beyond respiration, cancer has been found to involve a wide range of metabolic processes, and many more are still to be unveiled. Studying cancer through metabolomics could reveal new biomarkers for cancer that could be useful for its future prognosis, diagnosis and therapy. Metabolomics is becoming an increasingly popular tool in the life sciences since it is a relatively fast and accurate technique that can be applied with either a particular focus or in a global manner to reveal new knowledge about biological systems. There have been many examples of its application to reveal potential biomarkers in different cancers that have employed a range of different analytical platforms. In this review, approaches in metabolomics that have been employed in cancer biomarker discovery are discussed and some of the most noteworthy research in the field is highlighted. Copyright © 2013 Elsevier B.V. All rights reserved.

  15. 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.

  16. Bioinformatics and biomarker discovery "Omic" data analysis for personalized medicine

    CERN Document Server

    Azuaje, Francisco

    2010-01-01

    This book is designed to introduce biologists, clinicians and computational researchers to fundamental data analysis principles, techniques and tools for supporting the discovery of biomarkers and the implementation of diagnostic/prognostic systems. The focus of the book is on how fundamental statistical and data mining approaches can support biomarker discovery and evaluation, emphasising applications based on different types of "omic" data. The book also discusses design factors, requirements and techniques for disease screening, diagnostic and prognostic applications. Readers are provided w

  17. 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.

  18. 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

  19. 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

  20. Proteomic Approaches in Biomarker Discovery: New Perspectives in Cancer Diagnostics

    Science.gov (United States)

    Kocevar, Nina; Komel, Radovan

    2014-01-01

    Despite remarkable progress in proteomic methods, including improved detection limits and sensitivity, these methods have not yet been established in routine clinical practice. The main limitations, which prevent their integration into clinics, are high cost of equipment, the need for highly trained personnel, and last, but not least, the establishment of reliable and accurate protein biomarkers or panels of protein biomarkers for detection of neoplasms. Furthermore, the complexity and heterogeneity of most solid tumours present obstacles in the discovery of specific protein signatures, which could be used for early detection of cancers, for prediction of disease outcome, and for determining the response to specific therapies. However, cancer proteome, as the end-point of pathological processes that underlie cancer development and progression, could represent an important source for the discovery of new biomarkers and molecular targets for tailored therapies. PMID:24550697

  1. Exhaled Breath Condensate for Proteomic Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    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.

  2. Cancer biomarker discovery: the entropic hallmark.

    Science.gov (United States)

    Berretta, Regina; Moscato, Pablo

    2010-08-18

    It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles

  3. Approach to cerebrospinal fluid (CSF) biomarker discovery and evaluation in HIV infection.

    Science.gov (United States)

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

    2013-12-01

    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. Previously-defined 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.

  4. 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

  5. Computational and Experimental Approaches to Cancer Biomarker Discovery

    DEFF Research Database (Denmark)

    Krzystanek, Marcin

    of a patient’s response to a particular treatment, thus helping to avoid unnecessary treatment and unwanted side effects in non-responding individuals.Currently biomarker discovery is facilitated by recent advances in high-throughput technologies when association between a given biological phenotype...... and the state or level of a large number of molecular entities is investigated. Such associative analysis could be confounded by several factors, leading to false discoveries. For example, it is assumed that with the exception of the true biomarkers most molecular entities such as gene expression levels show...... random distribution in a given cohort. However, gene expression levels may also be affected by technical bias when the actual measurement technology or sample handling may introduce a systematic error. If the distribution of systematic errors correlates with the biological phenotype then the risk...

  6. 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

    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...

  7. Metabolomics for Biomarker Discovery: Moving to the Clinic

    Science.gov (United States)

    Zhang, Aihua; Sun, Hui; Yan, Guangli; Wang, Ping; Wang, Xijun

    2015-01-01

    To improve the clinical course of diseases, more accurate diagnostic and assessment methods are required as early as possible. In order to achieve this, metabolomics offers new opportunities for biomarker discovery in complex diseases and may provide pathological understanding of diseases beyond traditional technologies. It is the systematic analysis of low-molecular-weight metabolites in biological samples and has become an important tool in clinical research and the diagnosis of human disease and has been applied to discovery and identification of the perturbed pathways. It provides a powerful approach to discover biomarkers in biological systems and offers a holistic approach with the promise to clinically enhance diagnostics. When carried out properly, it could provide insight into the understanding of the underlying mechanisms of diseases, help to identify patients at risk of disease, and predict the response to specific treatments. Currently, metabolomics has become an important tool in clinical research and the diagnosis of human disease and becomes a hot topic. This review will highlight the importance and benefit of metabolomics for identifying biomarkers that accurately screen potential biomarkers of diseases. PMID:26090402

  8. Mass spectrometric based approaches in urine metabolomics and biomarker discovery.

    Science.gov (United States)

    Khamis, Mona M; Adamko, Darryl J; El-Aneed, Anas

    2017-03-01

    Urine metabolomics has recently emerged as a prominent field for the discovery of non-invasive biomarkers that can detect subtle metabolic discrepancies in response to a specific disease or therapeutic intervention. Urine, compared to other biofluids, is characterized by its ease of collection, richness in metabolites and its ability to reflect imbalances of all biochemical pathways within the body. Following urine collection for metabolomic analysis, samples must be immediately frozen to quench any biogenic and/or non-biogenic chemical reactions. According to the aim of the experiment; sample preparation can vary from simple procedures such as filtration to more specific extraction protocols such as liquid-liquid extraction. Due to the lack of comprehensive studies on urine metabolome stability, higher storage temperatures (i.e. 4°C) and repetitive freeze-thaw cycles should be avoided. To date, among all analytical techniques, mass spectrometry (MS) provides the best sensitivity, selectivity and identification capabilities to analyze the majority of the metabolite composition in the urine. Combined with the qualitative and quantitative capabilities of MS, and due to the continuous improvements in its related technologies (i.e. ultra high-performance liquid chromatography [UPLC] and hydrophilic interaction liquid chromatography [HILIC]), liquid chromatography (LC)-MS is unequivocally the most utilized and the most informative analytical tool employed in urine metabolomics. Furthermore, differential isotope tagging techniques has provided a solution to ion suppression from urine matrix thus allowing for quantitative analysis. In addition to LC-MS, other MS-based technologies have been utilized in urine metabolomics. These include direct injection (infusion)-MS, capillary electrophoresis-MS and gas chromatography-MS. In this article, the current progresses of different MS-based techniques in exploring the urine metabolome as well as the recent findings in providing

  9. Biomarkers as drug development tools: discovery, validation, qualification and use.

    Science.gov (United States)

    Kraus, Virginia B

    2018-06-01

    The 21st Century Cures Act, approved in the USA in December 2016, has encouraged the establishment of the national Precision Medicine Initiative and the augmentation of efforts to address disease prevention, diagnosis and treatment on the basis of a molecular understanding of disease. The Act adopts into law the formal process, developed by the FDA, of qualification of drug development tools, including biomarkers and clinical outcome assessments, to increase the efficiency of clinical trials and encourage an era of molecular medicine. The FDA and European Medicines Agency (EMA) have developed similar processes for the qualification of biomarkers intended for use as companion diagnostics or for development and regulatory approval of a drug or therapeutic. Biomarkers that are used exclusively for the diagnosis, monitoring or stratification of patients in clinical trials are not subject to regulatory approval, although their qualification can facilitate the conduct of a trial. In this Review, the salient features of biomarker discovery, analytical validation, clinical qualification and utilization are described in order to provide an understanding of the process of biomarker development and, through this understanding, convey an appreciation of their potential advantages and limitations.

  10. Urine protein concentration estimation for biomarker discovery

    OpenAIRE

    Mistry, Hiten D.; Bramham, Kate; Weston, Andrew; Ward, Malcolm; Thompson, Andrew; Chappell, Lucy C.

    2013-01-01

    Recent advances have been made in the study of urinary proteomics as a diagnostic tool for renal disease and pre-eclampsia which requires accurate measurement of urinary protein. We compared different protein assays (Bicinchoninic acid (BCA), Lowry and Bradford) against the ‘gold standard’ amino-acid assay in urine from 43 women (8 non-pregnant, 34 pregnant, including 8 with pre-eclampsia. BCA assay was superior to both Lowry and Bradford assays (Bland Altman bias: 0.08) compared to amino-aci...

  11. Role of proteomics in the discovery of autism biomarkers

    Energy Technology Data Exchange (ETDEWEB)

    Ayadhi, L. A.; Halepoto, D. M. [King Saud Univ., Riyadh (Saudi Arabia). Dept. of Physiology

    2013-02-15

    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)

  12. 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)

  13. Proteome analysis of body fluids for amyotrophic lateral sclerosis biomarker discovery.

    Science.gov (United States)

    Krüger, Thomas; Lautenschläger, Janin; Grosskreutz, Julian; Rhode, Heidrun

    2013-01-01

    Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder of motor neurons leading to death of the patients, mostly within 2-5 years after disease onset. The pathomechanism of motor neuron degeneration is only partially understood and therapeutic strategies based on mechanistic insights are largely ineffective. The discovery of reliable biomarkers of disease diagnosis and progression is the sine qua non of both the revelation of insights into the ALS pathomechanism and the assessment of treatment efficacies. Proteomic approaches are an important pillar in ALS biomarker discovery. Cerebrospinal fluid is the most promising body fluid for differential proteome analyses, followed by blood (serum, plasma), and even urine and saliva. The present study provides an overview about reported peptide/protein biomarker candidates that showed significantly altered levels in certain body fluids of ALS patients. These findings have to be discussed according to proposed pathomechanisms to identify modifiers of disease progression and to pave the way for the development of potential therapeutic strategies. Furthermore, limitations and advantages of proteomic approaches for ALS biomarker discovery in different body fluids and reliable validation of biomarker candidates have been addressed. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Random glycopeptide bead libraries for seromic biomarker discovery

    DEFF Research Database (Denmark)

    Kracun, Stjepan Kresimir; Cló, Emiliano; Clausen, Henrik

    2010-01-01

    have developed a random glycopeptide bead library screening platform for detection of autoantibodies and other binding proteins. Libraries were build on biocompatible PEGA beads including a safety-catch C-terminal amide linker (SCAL) that allowed mild cleavage conditions (I(2)/NaBH(4) and TFA...... to other tumor glycoforms by on-bead enzymatic glycosylation reactions with recombinant glycosyltransferases. Hence, we have developed a high-throughput flexible platform for rapid discovery of O-glycopeptide biomarkers and the method has applicability in other types of assays such as lectin...

  15. Novel ageing-biomarker discovery using data-intensive technologies

    OpenAIRE

    Griffiths, H.R.; Augustyniak, E.M.; Bennett, S.J.; Debacq-Chainiaux, F.; Dunston, C.R.; Kristensen, P.; Melchjorsen, C.J.; Navarrete, Santos A.; Simm, A.; Toussaint, O.

    2015-01-01

    Ageing is accompanied by many visible characteristics. Other biological and physiological markers are also well-described e.g. loss of circulating sex hormones and increased inflammatory cytokines. Biomarkers for healthy ageing studies are presently predicated on existing knowledge of ageing traits. The increasing availability of data-intensive methods enables deep-analysis of biological samples for novel biomarkers. We have adopted two discrete approaches in MARK-AGE Work Package 7 for bioma...

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

    Science.gov (United States)

    Tahara, Hideaki; Sato, Marimo; Thurin, Magdalena; Wang, Ena; Butterfield, Lisa H; Disis, Mary L; Fox, Bernard A; Lee, Peter P; Khleif, Samir N; Wigginton, Jon M; Ambs, Stefan; Akutsu, Yasunori; Chaussabel, Damien; Doki, Yuichiro; Eremin, Oleg; Fridman, Wolf Hervé; Hirohashi, Yoshihiko; Imai, Kohzoh; Jacobson, James; Jinushi, Masahisa; Kanamoto, Akira; Kashani-Sabet, Mohammed; Kato, Kazunori; Kawakami, Yutaka; Kirkwood, John M; Kleen, Thomas O; Lehmann, Paul V; Liotta, Lance; Lotze, Michael T; Maio, Michele; Malyguine, Anatoli; Masucci, Giuseppe; Matsubara, Hisahiro; Mayrand-Chung, Shawmarie; Nakamura, Kiminori; Nishikawa, Hiroyoshi; Palucka, A Karolina; Petricoin, Emanuel F; Pos, Zoltan; Ribas, Antoni; Rivoltini, Licia; Sato, Noriyuki; Shiku, Hiroshi; Slingluff, Craig L; Streicher, Howard; Stroncek, David F; Takeuchi, Hiroya; Toyota, Minoru; Wada, Hisashi; Wu, Xifeng; Wulfkuhle, Julia; Yaguchi, Tomonori; Zeskind, Benjamin; Zhao, Yingdong; Zocca, Mai-Britt; Marincola, Francesco M

    2009-01-01

    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. PMID:19534815

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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

  2. 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.

  3. Disease Classification and Biomarker Discovery Using ECG Data

    Directory of Open Access Journals (Sweden)

    Rong Huang

    2015-01-01

    Full Text Available In the recent decade, disease classification and biomarker discovery have become increasingly important in modern biological and medical research. ECGs are comparatively low-cost and noninvasive in screening and diagnosing heart diseases. With the development of personal ECG monitors, large amounts of ECGs are recorded and stored; therefore, fast and efficient algorithms are called for to analyze the data and make diagnosis. In this paper, an efficient and easy-to-interpret procedure of cardiac disease classification is developed through novel feature extraction methods and comparison of classifiers. Motivated by the observation that the distributions of various measures on ECGs of the diseased group are often skewed, heavy-tailed, or multimodal, we characterize the distributions by sample quantiles which outperform sample means. Three classifiers are compared in application both to all features and to dimension-reduced features by PCA: stepwise discriminant analysis (SDA, SVM, and LASSO logistic regression. It is found that SDA applied to dimension-reduced features by PCA is the most stable and effective procedure, with sensitivity, specificity, and accuracy being 89.68%, 84.62%, and 88.52%, respectively.

  4. 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

  5. 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.

  6. 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.

  7. Biomarker Discovery in Gulf War Veterans: Development of a War Illness Diagnostic Panel

    Science.gov (United States)

    2016-12-01

    Award Number: W81XWH-12-1-0382 TITLE: Biomarker Discovery in Gulf War Veterans: Development of a War Illness Diagnostic Panel PRINCIPAL...SUBTITLE Biomarker Discovery in Gulf War Veterans: Development of a War Illness Diagnostic Panel 5a. CONTRACT NUMBER W81XWH-12-1-0382 5b. GRANT...of the 1990-1991 Gulf War are affected by Gulf War illness (GWI), the chronic condition currently defined only by veterans’ self-reported symptoms

  8. 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

  9. 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.

  10. 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

  11. Application of mass spectrometry-based proteomics for biomarker discovery in neurological disorders

    Directory of Open Access Journals (Sweden)

    Venugopal Abhilash

    2009-01-01

    Full Text Available Mass spectrometry-based quantitative proteomics has emerged as a powerful approach that has the potential to accelerate biomarker discovery, both for diagnostic as well as therapeutic purposes. Proteomics has traditionally been synonymous with 2D gels but is increasingly shifting to the use of gel-free systems and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS. Quantitative proteomic approaches have already been applied to investigate various neurological disorders, especially in the context of identifying biomarkers from cerebrospinal fluid and serum. This review highlights the scope of different applications of quantitative proteomics in understanding neurological disorders with special emphasis on biomarker discovery.

  12. The MURDOCK Study: a long-term initiative for disease reclassification through advanced biomarker discovery and integration with electronic health records

    Science.gov (United States)

    Tenenbaum, Jessica D; Christian, Victoria; Cornish, Melissa A; Dolor, Rowena J; Dunham, Ashley A; Ginsburg, Geoffrey S; Kraus, Virginia B; McHutchison, John G; Nahm, Meredith L; Newby, L Kristin; Svetkey, Laura P; Udayakumar, Krishna; Califf, Robert M

    2012-01-01

    Background Facing critically low return per dollar invested on clinical research and clinical care, the American biomedical enterprise is in need of a significant transformation. A confluence of high-throughput “omic” technologies and increasing adoption of the electronic health record has fueled excitement for a new paradigm for biomedical research and practice. The ability to simultaneously measure thousands of molecular variables and assess their relationships with clinical data collected during the course of care could enable reclassification of disease not only by gross phenotypic observation but according to underlying molecular mechanism and influence of social determinants.In turn, this reclassification could enable development of targeted therapeutic interventions as well as disease prevention strategies at the individual and population levels. Methods/Design The MURDOCK Study consists of distinct project “horizons” or stages. Horizon 1 entailed the generation and analysis of molecular data for existing large,clinically well-annotated cohorts in four disease areas. Horizon 1.5 involves creating and maintaining a 50,000-person,community volunteer registry for biomarker signature validation and prospective studies, including integration of environmental and social data. Horizon 2 leverages and prospectively recruits Horizon 1.5 volunteers, and extends the study to additional disease areas of interest. Horizon 3 will expand the study through regional, national,and international partnerships. Discussion The MURDOCK Study embodies a new model of team science investigation and represents a significant resource for translational research. The study team invites inquiries to form new collaborations to exploit the rich resources provided by these biospecimens and associated study data. PMID:22937207

  13. 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.

  14. Comprehensive Analysis of MILE Gene Expression Data Set Advances Discovery of Leukaemia Type and Subtype Biomarkers.

    Science.gov (United States)

    Labaj, Wojciech; Papiez, Anna; Polanski, Andrzej; Polanska, Joanna

    2017-03-01

    Large collections of data in studies on cancer such as leukaemia provoke the necessity of applying tailored analysis algorithms to ensure supreme information extraction. In this work, a custom-fit pipeline is demonstrated for thorough investigation of the voluminous MILE gene expression data set. Three analyses are accomplished, each for gaining a deeper understanding of the processes underlying leukaemia types and subtypes. First, the main disease groups are tested for differential expression against the healthy control as in a standard case-control study. Here, the basic knowledge on molecular mechanisms is confirmed quantitatively and by literature references. Second, pairwise comparison testing is performed for juxtaposing the main leukaemia types among each other. In this case by means of the Dice coefficient similarity measure the general relations are pointed out. Moreover, lists of candidate main leukaemia group biomarkers are proposed. Finally, with this approach being successful, the third analysis provides insight into all of the studied subtypes, followed by the emergence of four leukaemia subtype biomarkers. In addition, the class enhanced DEG signature obtained on the basis of novel pipeline processing leads to significantly better classification power of multi-class data classifiers. The developed methodology consisting of batch effect adjustment, adaptive noise and feature filtration coupled with adequate statistical testing and biomarker definition proves to be an effective approach towards knowledge discovery in high-throughput molecular biology experiments.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2018-05-01

    Abstract. 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-TIMSCID- 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

  1. Sparse Mbplsr for Metabolomics Data and Biomarker Discovery

    DEFF Research Database (Denmark)

    Karaman, İbrahim

    2014-01-01

    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...

  2. 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.

  3. 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...

  4. 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.

  5. 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

  6. A semiparametric modeling framework for potential biomarker discovery and the development of metabonomic profiles

    Directory of Open Access Journals (Sweden)

    Dey Dipak K

    2008-01-01

    Full Text Available Abstract Background The discovery of biomarkers is an important step towards the development of criteria for early diagnosis of disease status. Recently electrospray ionization (ESI and matrix assisted laser desorption (MALDI time-of-flight (TOF mass spectrometry have been used to identify biomarkers both in proteomics and metabonomics studies. Data sets generated from such studies are generally very large in size and thus require the use of sophisticated statistical techniques to glean useful information. Most recent attempts to process these types of data model each compound's intensity either discretely by positional (mass to charge ratio clustering or through each compounds' own intensity distribution. Traditionally data processing steps such as noise removal, background elimination and m/z alignment, are generally carried out separately resulting in unsatisfactory propagation of signals in the final model. Results In the present study a novel semi-parametric approach has been developed to distinguish urinary metabolic profiles in a group of traumatic patients from those of a control group consisting of normal individuals. Data sets obtained from the replicates of a single subject were used to develop a functional profile through Dirichlet mixture of beta distribution. This functional profile is flexible enough to accommodate variability of the instrument and the inherent variability of each individual, thus simultaneously addressing different sources of systematic error. To address instrument variability, all data sets were analyzed in replicate, an important issue ignored by most studies in the past. Different model comparisons were performed to select the best model for each subject. The m/z values in the window of the irregular pattern are then further recommended for possible biomarker discovery. Conclusion To the best of our knowledge this is the very first attempt to model the physical process behind the time-of flight mass

  7. 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

  8. 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.

  9. Gaucher disease: a model disorder for biomarker discovery

    DEFF Research Database (Denmark)

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

    2009-01-01

    Gaucher disease is an inherited lysosomal storage disorder, characterized by massive accumulation of glucosylceramide-laden macrophages in the spleen, liver and bone marrow as a consequence of deficient activity of glucocerebrosidase. Gaucher disease has been the playground to develop new therape...... in clinical management of Gaucher patients are discussed. Moreover, the use of several modern proteomic technologies for the identification of Gaucher biomarkers is reviewed....

  10. 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.

  11. 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

    biomarker assays. However, the current knowledge of secreted and circulating O-glycoproteins is limited. Here, we used the COSMC KO "SimpleCell" (SC) strategy to characterize the O-glycoproteome of two gastric cancer SC lines (AGS, MKN45) as well as a gastric cell line (KATO III) which naturally expresses...... at least partially truncated O-glycans. Overall we identified 499 O-glycoproteins and 1,236 O-glycosites in gastric cancer SCs, and a total 47 O-glycoproteins and 73 O-glycosites in the KATO III cell line. We next modified the glycoproteomic strategy to apply it to pools of sera from gastric cancer...... with the STn glycoform were further validated as being expressed in gastric cancer tissue. A proximity ligation assay was used to demonstrate that CD44 was expressed with the STn glycoform in gastric cancer tissues. The study provides a discovery strategy for aberrantly glycosylated O-glycoproteins and a set...

  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. Clinical proteomics: Applications for prostate cancer biomarker discovery and detection.

    Science.gov (United States)

    Petricoin, Emanuel F; Ornstein, David K; Liotta, Lance A

    2004-01-01

    The science of proteomics comprises much more than simply generating lists of proteins that change in expression as a cause of or consequence of pathophysiology. The goal of proteomics should be to characterize the information flow through the intercellular protein circuitry that communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. Serum proteomic pattern diagnostics is a new type of proteomic concept in which patterns of ion signatures generated from high dimensional mass spectrometry data are used as diagnostic classifiers. This recent approach has exciting potential for clinical utility of diagnostic patterns because low molecular weight metabolites, peptides, and protein fragments may have higher accuracy than traditional biomarkers of cancer detection. Intriguingly, we now have discovered that this diagnostic information exists in a bound state, complexed with circulating highly abundant carrier proteins. These diagnostic fragments may one day be harvested by circulating nanoparticles, designed to absorb, enrich, and amplify the repertoire of diagnostic biomarkers generated-even at the critical, initial stages of carcinogenesis. Copyright 2004 Elsevier Inc.

  15. atBioNet– an integrated network analysis tool for genomics and biomarker discovery

    Directory of Open Access Journals (Sweden)

    Ding Yijun

    2012-07-01

    Full Text Available Abstract Background Large amounts of mammalian protein-protein interaction (PPI data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. Results atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks. The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. Conclusion atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http

  16. atBioNet--an integrated network analysis tool for genomics and biomarker discovery.

    Science.gov (United States)

    Ding, Yijun; Chen, Minjun; Liu, Zhichao; Ding, Don; Ye, Yanbin; Zhang, Min; Kelly, Reagan; Guo, Li; Su, Zhenqiang; Harris, Stephen C; Qian, Feng; Ge, Weigong; Fang, Hong; Xu, Xiaowei; Tong, Weida

    2012-07-20

    Large amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks). The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.

  17. Analytical Pipeline for Discovery and Verification of Glycoproteins from Plasma-Derived Extracellular Vesicles as Breast Cancer Biomarkers.

    Science.gov (United States)

    Chen, I-Hsuan; Aguilar, Hillary Andaluz; Paez Paez, J Sebastian; Wu, Xiaofeng; Pan, Li; Wendt, Michael K; Iliuk, Anton B; Zhang, Ying; Tao, W Andy

    2018-05-15

    Glycoproteins comprise more than half of current FDA-approved protein cancer markers, but the development of new glycoproteins as disease biomarkers has been stagnant. Here we present a pipeline to develop glycoproteins from extracellular vesicles (EVs) through integrating quantitative glycoproteomics with a novel reverse phase glycoprotein array and then apply it to identify novel biomarkers for breast cancer. EV glycoproteomics show promise in circumventing the problems plaguing current serum/plasma glycoproteomics and allowed us to identify hundreds of glycoproteins that have not been identified in blood. We identified 1,453 unique glycopeptides representing 556 glycoproteins in EVs, among which 20 were verified significantly higher in individual breast cancer patients. We further applied a novel glyco-specific reverse phase protein array to quantify a subset of the candidates. Together, this study demonstrates the great potential of this integrated pipeline for biomarker discovery.

  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. Metabolic profiling of an Echinostoma caproni infection in the mouse for biomarker discovery.

    Directory of Open Access Journals (Sweden)

    Jasmina Saric

    Full Text Available BACKGROUND: Metabolic profiling holds promise with regard to deepening our understanding of infection biology and disease states. The objectives of our study were to assess the global metabolic responses to an Echinostoma caproni infection in the mouse, and to compare the biomarkers extracted from different biofluids (plasma, stool, and urine in terms of characterizing acute and chronic stages of this intestinal fluke infection. METHODOLOGY/PRINCIPAL FINDINGS: Twelve female NMRI mice were infected with 30 E. caproni metacercariae each. Plasma, stool, and urine samples were collected at 7 time points up to day 33 post-infection. Samples were also obtained from non-infected control mice at the same time points and measured using (1H nuclear magnetic resonance (NMR spectroscopy. Spectral data were subjected to multivariate statistical analyses. In plasma and urine, an altered metabolic profile was already evident 1 day post-infection, characterized by reduced levels of plasma choline, acetate, formate, and lactate, coupled with increased levels of plasma glucose, and relatively lower concentrations of urinary creatine. The main changes in the urine metabolic profile started at day 8 post-infection, characterized by increased relative concentrations of trimethylamine and phenylacetylglycine and lower levels of 2-ketoisocaproate and showed differentiation over the course of the infection. CONCLUSION/SIGNIFICANCE: The current investigation is part of a broader NMR-based metabonomics profiling strategy and confirms the utility of this approach for biomarker discovery. In the case of E. caproni, a diagnosis based on all three biofluids would deliver the most comprehensive fingerprint of an infection. For practical purposes, however, future diagnosis might aim at a single biofluid, in which case urine would be chosen for further investigation, based on quantity of biomarkers, ease of sampling, and the degree of differentiation from the non

  20. 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.

  1. Molecular correlates of trait anxiety: expanding biomarker discovery from protein expression to turnover

    OpenAIRE

    Zhang, Yaoyang

    2010-01-01

    Depression and anxiety disorders affect a great number of people in the world. Although remarkable efforts have been devoted to understanding the clinical and biological basis of these disorders, progress has been relatively slow. Furthermore, no laboratory test currently is available for diagnosis of anxiety and depression. These disorders are mainly diagnosed empirically on the basis of a doctor’s personal observations and experiences. Hence, discovery of biomarkers for these psychiatric di...

  2. From the endometrium physiology to a comprehensive strategy for the discovery of ovarian cancer biomarkers

    OpenAIRE

    Janos L. Tanyi; Nathalie Scholler

    2011-01-01

    The development of comprehensive strategies for biomarker discovery of gynecological cancers is needed. The unique physiology of the female genital track revolves around ovulatory cycles ending by the proteolysis of the endometrium triggered by progesterone decline during the last part of the luteal phase. Building on the known link between incessant ovulation and ovarian cancer, we hypothesize that life-long menstruations could damage neighboring organs such as fallopian tubes, ovaries and p...

  3. Integration of lyoplate based flow cytometry and computational analysis for standardized immunological biomarker discovery.

    Directory of Open Access Journals (Sweden)

    Federica Villanova

    Full Text Available Discovery of novel immune biomarkers for monitoring of disease prognosis and response to therapy in immune-mediated inflammatory diseases is an important unmet clinical need. Here, we establish a novel framework for immunological biomarker discovery, comparing a conventional (liquid flow cytometry platform (CFP and a unique lyoplate-based flow cytometry platform (LFP in combination with advanced computational data analysis. We demonstrate that LFP had higher sensitivity compared to CFP, with increased detection of cytokines (IFN-γ and IL-10 and activation markers (Foxp3 and CD25. Fluorescent intensity of cells stained with lyophilized antibodies was increased compared to cells stained with liquid antibodies. LFP, using a plate loader, allowed medium-throughput processing of samples with comparable intra- and inter-assay variability between platforms. Automated computational analysis identified novel immunophenotypes that were not detected with manual analysis. Our results establish a new flow cytometry platform for standardized and rapid immunological biomarker discovery with wide application to immune-mediated diseases.

  4. Integration of lyoplate based flow cytometry and computational analysis for standardized immunological biomarker discovery.

    Science.gov (United States)

    Villanova, Federica; Di Meglio, Paola; Inokuma, Margaret; Aghaeepour, Nima; Perucha, Esperanza; Mollon, Jennifer; Nomura, Laurel; Hernandez-Fuentes, Maria; Cope, Andrew; Prevost, A Toby; Heck, Susanne; Maino, Vernon; Lord, Graham; Brinkman, Ryan R; Nestle, Frank O

    2013-01-01

    Discovery of novel immune biomarkers for monitoring of disease prognosis and response to therapy in immune-mediated inflammatory diseases is an important unmet clinical need. Here, we establish a novel framework for immunological biomarker discovery, comparing a conventional (liquid) flow cytometry platform (CFP) and a unique lyoplate-based flow cytometry platform (LFP) in combination with advanced computational data analysis. We demonstrate that LFP had higher sensitivity compared to CFP, with increased detection of cytokines (IFN-γ and IL-10) and activation markers (Foxp3 and CD25). Fluorescent intensity of cells stained with lyophilized antibodies was increased compared to cells stained with liquid antibodies. LFP, using a plate loader, allowed medium-throughput processing of samples with comparable intra- and inter-assay variability between platforms. Automated computational analysis identified novel immunophenotypes that were not detected with manual analysis. Our results establish a new flow cytometry platform for standardized and rapid immunological biomarker discovery with wide application to immune-mediated diseases.

  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. 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.

  7. 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

  8. Predictive Power Estimation Algorithm (PPEA--a new algorithm to reduce overfitting for genomic biomarker discovery.

    Directory of Open Access Journals (Sweden)

    Jiangang Liu

    Full Text Available Toxicogenomics promises to aid in predicting adverse effects, understanding the mechanisms of drug action or toxicity, and uncovering unexpected or secondary pharmacology. However, modeling adverse effects using high dimensional and high noise genomic data is prone to over-fitting. Models constructed from such data sets often consist of a large number of genes with no obvious functional relevance to the biological effect the model intends to predict that can make it challenging to interpret the modeling results. To address these issues, we developed a novel algorithm, Predictive Power Estimation Algorithm (PPEA, which estimates the predictive power of each individual transcript through an iterative two-way bootstrapping procedure. By repeatedly enforcing that the sample number is larger than the transcript number, in each iteration of modeling and testing, PPEA reduces the potential risk of overfitting. We show with three different cases studies that: (1 PPEA can quickly derive a reliable rank order of predictive power of individual transcripts in a relatively small number of iterations, (2 the top ranked transcripts tend to be functionally related to the phenotype they are intended to predict, (3 using only the most predictive top ranked transcripts greatly facilitates development of multiplex assay such as qRT-PCR as a biomarker, and (4 more importantly, we were able to demonstrate that a small number of genes identified from the top-ranked transcripts are highly predictive of phenotype as their expression changes distinguished adverse from nonadverse effects of compounds in completely independent tests. Thus, we believe that the PPEA model effectively addresses the over-fitting problem and can be used to facilitate genomic biomarker discovery for predictive toxicology and drug responses.

  9. Candidate biomarker discovery and selection for ‘Granny Smith' superficial scald risk management and diagnosis, poster board

    Science.gov (United States)

    Discovery of candidate biomarkers for superficial scald, a peel disorder that develops during storage of susceptible apple cultivars, is part of a larger project aimed at developing biomarker-based risk-management and diagnostic tools for multiple apple postharvest disorders (http://www.tfrec.wsu.ed...

  10. 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.

  11. 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

  12. Scalable Biomarker Discovery for Diverse High-Dimensional Phenotypes

    Science.gov (United States)

    2015-11-23

    William D. Shannon, Richard R. Sharp, Thomas J. Sharpton, Narmada Shenoy, Nihar U. Sheth, Gina A. Simone, Indresh Singh, Chris S. Smillie, Jack D... William D. Shannon, Richard R. Sharp, Thomas J. Sharpton, Narmada Shenoy, Nihar U. Sheth, Gina A. Simone, Indresh Singh, Christopher S. Smillie, Jack D...Susanne J. Szabo, Jeff Porter, Harri Lähdesmäki, Curtis Huttenhower, Dirk Gevers, Thomas W. Cullen , Mikael Knip, on behalf of the DIABIMMUNE Study Group

  13. 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.

  14. 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).

  15. The Emerging Field of Quantitative Blood Metabolomics for Biomarker Discovery in Critical Illnesses

    Science.gov (United States)

    Serkova, Natalie J.; Standiford, Theodore J.

    2011-01-01

    Metabolomics, a science of systems biology, is the global assessment of endogenous metabolites within a biologic system and represents a “snapshot” reading of gene function, enzyme activity, and the physiological landscape. Metabolite detection, either individual or grouped as a metabolomic profile, is usually performed in cells, tissues, or biofluids by either nuclear magnetic resonance spectroscopy or mass spectrometry followed by sophisticated multivariate data analysis. Because loss of metabolic homeostasis is common in critical illness, the metabolome could have many applications, including biomarker and drug target identification. Metabolomics could also significantly advance our understanding of the complex pathophysiology of acute illnesses, such as sepsis and acute lung injury/acute respiratory distress syndrome. Despite this potential, the clinical community is largely unfamiliar with the field of metabolomics, including the methodologies involved, technical challenges, and, most importantly, clinical uses. Although there is evidence of successful preclinical applications, the clinical usefulness and application of metabolomics in critical illness is just beginning to emerge, the advancement of which hinges on linking metabolite data to known and validated clinically relevant indices. In addition, other important aspects, such as patient selection, sample collection, and processing, as well as the needed multivariate data analysis, have to be taken into consideration before this innovative approach to biomarker discovery can become a reliable tool in the intensive care unit. The purpose of this review is to begin to familiarize clinicians with the field of metabolomics and its application for biomarker discovery in critical illnesses such as sepsis. PMID:21680948

  16. 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.

  17. 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.

  18. 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.

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

    KAUST Repository

    Kaur, Mandeep; MacPherson, Cameron R; Schmeier, Sebastian; Narasimhan, Kothandaraman; Choolani, Mahesh; Bajic, Vladimir B.

    2011-01-01

    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.

  20. Discovery of dachshund 2 protein as a novel biomarker of poor prognosis in epithelial ovarian cancer

    Directory of Open Access Journals (Sweden)

    Nodin Björn

    2012-01-01

    Full Text Available Abstract Background The Dachshund homolog 2 (DACH2 gene has been implicated in development of the female genital tract in mouse models and premature ovarian failure syndrome, but to date, its expression in human normal and cancerous tissue remains unexplored. Using the Human Protein Atlas as a tool for cancer biomarker discovery, DACH2 protein was found to be differentially expressed in epithelial ovarian cancer (EOC. Here, the expression and prognostic significance of DACH2 was further evaluated in ovarian cancer cell lines and human EOC samples. Methods Immunohistochemical expression of DACH2 was examined in tissue microarrays with 143 incident EOC cases from two prospective, population-based cohorts, including a subset of benign-appearing fallopian tubes (n = 32. A nuclear score (NS, i.e. multiplier of staining fraction and intensity, was calculated. For survival analyses, cases were dichotomized into low (NS 3 using classification and regression tree analysis. Kaplan Meier analysis and Cox proportional hazards modelling were used to assess the impact of DACH2 expression on survival. DACH2 expression was analysed in the cisplatin sensitive ovarian cancer cell line A2780 and its cisplatin resistant derivative A2780-Cp70. The specificity of the DACH2 antibody was tested using siRNA-mediated silencing of DACH2 in A2780-Cp70 cells. Results DACH2 expression was considerably higher in the cisplatin resistant A2780-Cp70 cells compared to the cisplatin-sensitive A2780 cells. While present in all sampled fallopian tubes, DACH2 expression ranged from negative to strong in EOC. In EOC, DACH2 expression correlated with several proteins involved in DNA integrity and repair, and proliferation. DACH2 expression was significantly higher in carcinoma of the serous subtype compared to non-serous carcinoma. In the full cohort, high DACH2 expression was significantly associated with poor prognosis in univariable analysis, and in carcinoma of the serous subtype

  1. Discovery of Novel Biomarkers for Alzheimer’s Disease from Blood

    Directory of Open Access Journals (Sweden)

    Jintao Long

    2016-01-01

    Full Text Available Blood-based biomarkers for Alzheimer’s disease would be very valuable because blood is a more accessible biofluid and is suitable for repeated sampling. However, currently there are no robust and reliable blood-based biomarkers for practical diagnosis. In this study we used a knowledge-based protein feature pool and two novel support vector machine embedded feature selection methods to find panels consisting of two and three biomarkers. We validated these biomarker sets using another serum cohort and an RNA profile cohort from the brain. Our panels included the proteins ECH1, NHLRC2, HOXB7, FN1, ERBB2, and SLC6A13 and demonstrated promising sensitivity (>87%, specificity (>91%, and accuracy (>89%.

  2. 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.

  3. 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.

  4. 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.

  5. Biomarker discovery and applications for foods and beverages: proteomics to nanoproteomics.

    Science.gov (United States)

    Agrawal, Ganesh Kumar; Timperio, Anna Maria; Zolla, Lello; Bansal, Vipul; Shukla, Ravi; Rakwal, Randeep

    2013-11-20

    Foods and beverages have been at the heart of our society for centuries, sustaining humankind - health, life, and the pleasures that go with it. The more we grow and develop as a civilization, the more we feel the need to know about the food we eat and beverages we drink. Moreover, with an ever increasing demand for food due to the growing human population food security remains a major concern. Food safety is another growing concern as the consumers prefer varied foods and beverages that are not only traded nationally but also globally. The 21st century science and technology is at a new high, especially in the field of biological sciences. The availability of genome sequences and associated high-throughput sensitive technologies means that foods are being analyzed at various levels. For example and in particular, high-throughput omics approaches are being applied to develop suitable biomarkers for foods and beverages and their applications in addressing quality, technology, authenticity, and safety issues. Proteomics are one of those technologies that are increasingly being utilized to profile expressed proteins in different foods and beverages. Acquired knowledge and protein information have now been translated to address safety of foods and beverages. Very recently, the power of proteomic technology has been integrated with another highly sensitive and miniaturized technology called nanotechnology, yielding a new term nanoproteomics. Nanoproteomics offer a real-time multiplexed analysis performed in a miniaturized assay, with low-sample consumption and high sensitivity. To name a few, nanomaterials - quantum dots, gold nanoparticles, carbon nanotubes, and nanowires - have demonstrated potential to overcome the challenges of sensitivity faced by proteomics for biomarker detection, discovery, and application. In this review, we will discuss the importance of biomarker discovery and applications for foods and beverages, the contribution of proteomic technology in

  6. 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).

  7. 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

  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. Accounting for control mislabeling in case-control biomarker studies.

    Science.gov (United States)

    Rantalainen, Mattias; Holmes, Chris C

    2011-12-02

    In biomarker discovery studies, uncertainty associated with case and control labels is often overlooked. By omitting to take into account label uncertainty, model parameters and the predictive risk can become biased, sometimes severely. The most common situation is when the control set contains an unknown number of undiagnosed, or future, cases. This has a marked impact in situations where the model needs to be well-calibrated, e.g., when the prediction performance of a biomarker panel is evaluated. Failing to account for class label uncertainty may lead to underestimation of classification performance and bias in parameter estimates. This can further impact on meta-analysis for combining evidence from multiple studies. Using a simulation study, we outline how conventional statistical models can be modified to address class label uncertainty leading to well-calibrated prediction performance estimates and reduced bias in meta-analysis. We focus on the problem of mislabeled control subjects in case-control studies, i.e., when some of the control subjects are undiagnosed cases, although the procedures we report are generic. The uncertainty in control status is a particular situation common in biomarker discovery studies in the context of genomic and molecular epidemiology, where control subjects are commonly sampled from the general population with an established expected disease incidence rate.

  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. From the endometrium physiology to a comprehensive strategy for the discovery of ovarian cancer biomarkers

    Directory of Open Access Journals (Sweden)

    Janos L. Tanyi

    2011-12-01

    Full Text Available The development of comprehensive strategies for biomarker discovery of gynecological cancers is needed. The unique physiology of the female genital track revolves around ovulatory cycles ending by the proteolysis of the endometrium triggered by progesterone decline during the last part of the luteal phase. Building on the known link between incessant ovulation and ovarian cancer, we hypothesize that life-long menstruations could damage neighboring organs such as fallopian tubes, ovaries and peritoneum via endometrial secretions, and thus endometrium neighboring structures may have developed highly efficient protective strategies that could, in turn, be hijacked by cancer cells for survival and invasion. After literature review, we could classify the molecules involved in ovulation and menstruation pathways in three main categories: proteases, proteases inhibitors and cell-surface protectors. Strikingly, all validated biomarkers for ovarian cancers belong to at least one of these categories. We thus propose the development of comprehensive methods for identification of early diagnostic markers for gynecological cancers using systematical mapping and characterization of surface or soluble molecules belonging to physiological pathways linked to menstruation and differently expressed during luteal cycles.

  12. Analysis of Reverse Phase Protein Array Data: From Experimental Design towards Targeted Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Astrid Wachter

    2015-11-01

    Full Text Available Mastering the systematic analysis of tumor tissues on a large scale has long been a technical challenge for proteomics. In 2001, reverse phase protein arrays (RPPA were added to the repertoire of existing immunoassays, which, for the first time, allowed a profiling of minute amounts of tumor lysates even after microdissection. A characteristic feature of RPPA is its outstanding sample capacity permitting the analysis of thousands of samples in parallel as a routine task. Until today, the RPPA approach has matured to a robust and highly sensitive high-throughput platform, which is ideally suited for biomarker discovery. Concomitant with technical advancements, new bioinformatic tools were developed for data normalization and data analysis as outlined in detail in this review. Furthermore, biomarker signatures obtained by different RPPA screens were compared with another or with that obtained by other proteomic formats, if possible. Options for overcoming the downside of RPPA, which is the need to steadily validate new antibody batches, will be discussed. Finally, a debate on using RPPA to advance personalized medicine will conclude this article.

  13. Biomarkers Discovery for Colorectal Cancer: A Review on Tumor Endothelial Markers as Perspective Candidates

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    Łukasz Pietrzyk

    2016-01-01

    Full Text Available Colorectal cancer (CRC is the third most common cancer in the world. The early detection of CRC, during the promotion/progression stages, is an enormous challenge for a successful outcome and remains a fundamental problem in clinical approach. Despite the continuous advancement in diagnostic and therapeutic methods, there is a need for discovery of sensitive and specific, noninvasive biomarkers. Tumor endothelial markers (TEMs are associated with tumor-specific angiogenesis and are potentially useful to discriminate between tumor and normal endothelium. The most promising TEMs for oncogenic signaling in CRC appeared to be the TEM1, TEM5, TEM7, and TEM8. Overexpression of TEMs especially TEM1, TEM7, and TEM8 in colorectal tumor tissue compared to healthy tissue suggests their role in tumor blood vessels formation. Thus TEMs appear to be perspective candidates for early detection, monitoring, and treatment of CRC patients. This review provides an update on recent data on tumor endothelial markers and their possible use as biomarkers for screening, diagnosis, and therapy of colorectal cancer patients.

  14. Biomarkers Discovery for Colorectal Cancer: A Review on Tumor Endothelial Markers as Perspective Candidates.

    Science.gov (United States)

    Pietrzyk, Łukasz

    2016-01-01

    Colorectal cancer (CRC) is the third most common cancer in the world. The early detection of CRC, during the promotion/progression stages, is an enormous challenge for a successful outcome and remains a fundamental problem in clinical approach. Despite the continuous advancement in diagnostic and therapeutic methods, there is a need for discovery of sensitive and specific, noninvasive biomarkers. Tumor endothelial markers (TEMs) are associated with tumor-specific angiogenesis and are potentially useful to discriminate between tumor and normal endothelium. The most promising TEMs for oncogenic signaling in CRC appeared to be the TEM1, TEM5, TEM7, and TEM8. Overexpression of TEMs especially TEM1, TEM7, and TEM8 in colorectal tumor tissue compared to healthy tissue suggests their role in tumor blood vessels formation. Thus TEMs appear to be perspective candidates for early detection, monitoring, and treatment of CRC patients. This review provides an update on recent data on tumor endothelial markers and their possible use as biomarkers for screening, diagnosis, and therapy of colorectal cancer patients.

  15. 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...

  16. Discovery of Biochemical Biomarkers for Aggression: A Role for Metabolomics in Psychiatry

    NARCIS (Netherlands)

    Hagenbeek, F.A.; Kluft, C.; Hankemeier, T.; Bartels, M.; Draisma, H.H.M.; Middeldorp, C.M.; Berger, R.; Noto, A.; Lussu, M.; Pool, R.; Fanos, V.; Boomsma, D.I.

    2016-01-01

    Human aggression encompasses a wide range of behaviors and is related to many psychiatric disorders. We introduce the different classification systems of aggression and related disorders as a basis for discussing biochemical biomarkers and then present an overview of studies in humans (published

  17. 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

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

    Science.gov (United States)

    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.

  19. Quantitative proteomic analysis of microdissected oral epithelium for cancer biomarker discovery.

    Science.gov (United States)

    Xiao, Hua; Langerman, Alexander; Zhang, Yan; Khalid, Omar; Hu, Shen; Cao, Cheng-Xi; Lingen, Mark W; Wong, David T W

    2015-11-01

    Specific biomarkers are urgently needed for the detection and progression of oral cancer. The objective of this study was to discover cancer biomarkers from oral epithelium through utilizing high throughput quantitative proteomics approaches. Morphologically malignant, epithelial dysplasia, and adjacent normal epithelial tissues were laser capture microdissected (LCM) from 19 patients and used for proteomics analysis. Total proteins from each group were extracted, digested and then labelled with corresponding isobaric tags for relative and absolute quantitation (iTRAQ). Labelled peptides from each sample were combined and analyzed by liquid chromatography-mass spectrometry (LC-MS/MS) for protein identification and quantification. In total, 500 proteins were identified and 425 of them were quantified. When compared with adjacent normal oral epithelium, 17 and 15 proteins were consistently up-regulated or down-regulated in malignant and epithelial dysplasia, respectively. Half of these candidate biomarkers were discovered for oral cancer for the first time. Cornulin was initially confirmed in tissue protein extracts and was further validated in tissue microarray. Its presence in the saliva of oral cancer patients was also explored. Myoglobin and S100A8 were pre-validated by tissue microarray. These data demonstrated that the proteomic biomarkers discovered through this strategy are potential targets for oral cancer detection and salivary diagnostics. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. Discovery of prognostic biomarker candidates of lacunar infarction by quantitative proteomics of microvesicles enriched plasma.

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    Arnab Datta

    Full Text Available Lacunar infarction (LACI is a subtype of acute ischemic stroke affecting around 25% of all ischemic stroke cases. Despite having an excellent recovery during acute phase, certain LACI patients have poor mid- to long-term prognosis due to the recurrence of vascular events or a decline in cognitive functions. Hence, blood-based biomarkers could be complementary prognostic and research tools.Plasma was collected from forty five patients following a non-disabling LACI along with seventeen matched control subjects. The LACI patients were monitored prospectively for up to five years for the occurrence of adverse outcomes and grouped accordingly (i.e., LACI-no adverse outcome, LACI-recurrent vascular event, and LACI-cognitive decline without any recurrence of vascular events. Microvesicles-enriched fractions isolated from the pooled plasma of four groups were profiled by an iTRAQ-guided discovery approach to quantify the differential proteome. The data have been deposited to the ProteomeXchange with identifier PXD000748. Bioinformatics analysis and data mining revealed up-regulation of brain-specific proteins including myelin basic protein, proteins of coagulation cascade (e.g., fibrinogen alpha chain, fibrinogen beta chain and focal adhesion (e.g., integrin alpha-IIb, talin-1, and filamin-A while albumin was down-regulated in both groups of patients with adverse outcome.This data set may offer important insight into the mechanisms of poor prognosis and provide candidate prognostic biomarkers for validation on larger cohort of individual LACI patients.

  1. 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

  2. Discovery and validation of DNA hypomethylation biomarkers for liver cancer using HRM-specific probes.

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    Barbara Stefanska

    Full Text Available Poor prognosis of hepatocellular carcinoma (HCC associated with late diagnosis necessitates the development of early diagnostic biomarkers. We have previously delineated the landscape of DNA methylation in HCC patients unraveling the importance of promoter hypomethylation in activation of cancer- and metastasis-driving genes. The purpose of the present study was to test the feasibility that genes that are hypomethylated in HCC could serve as candidate diagnostic markers. We use high resolution melting analysis (HRM as a simple translatable PCR-based method to define methylation states in clinical samples. We tested seven regions selected from the shortlist of genes hypomethylated in HCC and showed that HRM analysis of several of them distinguishes methylation states in liver cancer specimens from normal adjacent liver and chronic hepatitis in the Shanghai area. Such regions were identified within promoters of neuronal membrane glycoprotein M6-B (GPM6B and melanoma antigen family A12 (MAGEA12 genes. Differences in HRM in the immunoglobulin superfamily Fc receptor (FCRL1 separated invasive tumors from less invasive HCC. The identified biomarkers differentiated HCC from chronic hepatitis in another set of samples from Dhaka. Although the main thrust in DNA methylation diagnostics in cancer is on hypermethylated genes, our study for the first time illustrates the potential use of hypomethylated genes as markers for solid tumors. After further validation in a larger cohort, the identified DNA hypomethylated regions can become important candidate biomarkers for liver cancer diagnosis and prognosis, especially in populations with high risk for HCC development.

  3. 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.

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

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    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

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

    Science.gov (United States)

    Shi, Linan; Zhang, Jun; Wu, Peng; Feng, Kai; Li, Jing; Xie, Zhensheng; Xue, Peng; Cai, Tanxi; Cui, Ziyou; Chen, Xiulan; Hou, Junjie; Zhang, Jianzhong; Yang, Fuquan

    2009-01-01

    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 additional

  6. Unlocking biomarker discovery: large scale application of aptamer proteomic technology for early detection of lung cancer.

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    Rachel M Ostroff

    Full Text Available BACKGROUND: Lung cancer is the leading cause of cancer deaths worldwide. New diagnostics are needed to detect early stage lung cancer because it may be cured with surgery. However, most cases are diagnosed too late for curative surgery. Here we present a comprehensive clinical biomarker study of lung cancer and the first large-scale clinical application of a new aptamer-based proteomic technology to discover blood protein biomarkers in disease. METHODOLOGY/PRINCIPAL FINDINGS: We conducted a multi-center case-control study in archived serum samples from 1,326 subjects from four independent studies of non-small cell lung cancer (NSCLC in long-term tobacco-exposed populations. Sera were collected and processed under uniform protocols. Case sera were collected from 291 patients within 8 weeks of the first biopsy-proven lung cancer and prior to tumor removal by surgery. Control sera were collected from 1,035 asymptomatic study participants with ≥ 10 pack-years of cigarette smoking. We measured 813 proteins in each sample with a new aptamer-based proteomic technology, identified 44 candidate biomarkers, and developed a 12-protein panel (cadherin-1, CD30 ligand, endostatin, HSP90α, LRIG3, MIP-4, pleiotrophin, PRKCI, RGM-C, SCF-sR, sL-selectin, and YES that discriminates NSCLC from controls with 91% sensitivity and 84% specificity in cross-validated training and 89% sensitivity and 83% specificity in a separate verification set, with similar performance for early and late stage NSCLC. CONCLUSIONS/SIGNIFICANCE: This study is a significant advance in clinical proteomics in an area of high unmet clinical need. Our analysis exceeds the breadth and dynamic range of proteome interrogated of previously published clinical studies of broad serum proteome profiling platforms including mass spectrometry, antibody arrays, and autoantibody arrays. The sensitivity and specificity of our 12-biomarker panel improves upon published protein and gene expression panels

  7. Biomarker Discovery Using New Metabolomics Software for Automated Processing of High Resolution LC-MS Data

    Science.gov (United States)

    Hnatyshyn, S.; Reily, M.; Shipkova, P.; McClure, T.; Sanders, M.; Peake, D.

    2011-01-01

    Robust biomarkers of target engagement and efficacy are required in different stages of drug discovery. Liquid chromatography coupled to high resolution mass spectrometry provides sensitivity, accuracy and wide dynamic range required for identification of endogenous metabolites in biological matrices. LCMS is widely-used tool for biomarker identification and validation. Typical high resolution LCMS profiles from biological samples may contain greater than a million mass spectral peaks corresponding to several thousand endogenous metabolites. Reduction of the total number of peaks, component identification and statistical comparison across sample groups remains to be a difficult and time consuming challenge. Blood samples from four groups of rats (male vs. female, fully satiated and food deprived) were analyzed using high resolution accurate mass (HRAM) LCMS. All samples were separated using a 15 minute reversed-phase C18 LC gradient and analyzed in both positive and negative ion modes. Data was acquired using 15K resolution and 5ppm mass measurement accuracy. The entire data set was analyzed using software developed in collaboration between Bristol Meyers Squibb and Thermo Fisher Scientific to determine the metabolic effects of food deprivation on rats. Metabolomic LC-MS data files are extraordinarily complex and appropriate reduction of the number of spectral peaks via identification of related peaks and background removal is essential. A single component such as hippuric acid generates more than 20 related peaks including isotopic clusters, adducts and dimers. Plasma and urine may contain 500-1500 unique quantifiable metabolites. Noise filtering approaches including blank subtraction were used to reduce the number of irrelevant peaks. By grouping related signals such as isotopic peaks and alkali adducts, data processing was greatly simplified by reducing the total number of components by 10-fold. The software processes 48 samples in under 60minutes. Principle

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

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    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

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. The BioFIND study: Characteristics of a clinically typical Parkinson's disease biomarker cohort

    Science.gov (United States)

    Goldman, Jennifer G.; Alcalay, Roy N.; Xie, Tao; Tuite, Paul; Henchcliffe, Claire; Hogarth, Penelope; Amara, Amy W.; Frank, Samuel; Rudolph, Alice; Casaceli, Cynthia; Andrews, Howard; Gwinn, Katrina; Sutherland, Margaret; Kopil, Catherine; Vincent, Lona; Frasier, Mark

    2016-01-01

    ABSTRACT Background Identifying PD‐specific biomarkers in biofluids will greatly aid in diagnosis, monitoring progression, and therapeutic interventions. PD biomarkers have been limited by poor discriminatory power, partly driven by heterogeneity of the disease, variability of collection protocols, and focus on de novo, unmedicated patients. Thus, a platform for biomarker discovery and validation in well‐characterized, clinically typical, moderate to advanced PD cohorts is critically needed. Methods BioFIND (Fox Investigation for New Discovery of Biomarkers in Parkinson's Disease) is a cross‐sectional, multicenter biomarker study that established a repository of clinical data, blood, DNA, RNA, CSF, saliva, and urine samples from 118 moderate to advanced PD and 88 healthy control subjects. Inclusion criteria were designed to maximize diagnostic specificity by selecting participants with clinically typical PD symptoms, and clinical data and biospecimen collection utilized standardized procedures to minimize variability across sites. Results We present the study methodology and data on the cohort's clinical characteristics. Motor scores and biospecimen samples including plasma are available for practically defined off and on states and thus enable testing the effects of PD medications on biomarkers. Other biospecimens are available from off state PD assessments and from controls. Conclusion Our cohort provides a valuable resource for biomarker discovery and validation in PD. Clinical data and biospecimens, available through The Michael J. Fox Foundation for Parkinson's Research and the National Institute of Neurological Disorders and Stroke, can serve as a platform for discovering biomarkers in clinically typical PD and comparisons across PD's broad and heterogeneous spectrum. © 2016 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society PMID:27113479

  15. 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.

  16. 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

    2018-03-20

    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 ).

  17. 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.

  18. 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.

  19. 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.

  20. 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...

  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. Metabolomics as a tool for discovery of biomarkers of autism spectrum disorder in the blood plasma of children.

    Directory of Open Access Journals (Sweden)

    Paul R West

    Full Text Available 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.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.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.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.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 recommendations.

  3. Metabolomic Discovery of Novel Urinary Galabiosylceramide Analogs as Fabry Disease Biomarkers

    Science.gov (United States)

    Boutin, Michel; Auray-Blais, Christiane

    2015-03-01

    Fabry disease is an X-linked, complex, multisystemic lysosomal storage disorder presenting marked phenotypic and genotypic variability among affected male and female patients. Glycosphingolipids, mainly globotriaosylceramide (Gb3) isoforms/analogs, globotriaosylsphingosine (lyso-Gb3) and analogs, as well as galabiosylceramide (Ga2) isoforms/analogs accumulate in the vascular endothelium, nerves, cardiomyocytes, renal glomerular and tubular epithelial cells, and biological fluids. The search for biomarkers reflecting disease severity and progression is still on-going. A metabolomic study using quadrupole time-of-flight mass spectrometry has revealed 22 galabiosylceramide isoforms/analogs in urine of untreated Fabry patients classified in seven groups according to their chemical structure: (1) Saturated fatty acid; (2) one extra double bond; (3) two extra double bonds; (4) hydroxylated saturated fatty acid; (5) hydroxylated fatty acid and one extra double bond; (6) hydrated sphingosine and hydroxylated fatty acid; (7) methylated amide linkage. Relative quantification of both Ga2 and Gb3 isoforms/analogs was performed. All these biomarkers are significantly more abundant in urine samples from untreated Fabry males compared with healthy male controls. A significant amount of Ga2 isoforms/analogs, accounting for 18% of all glycosphingolipids analyzed (Ga2 + Gb3 and respective isoforms/analogs), were present in urine of Fabry patients. Gb3 isoforms containing saturated fatty acids are the most abundant (60.9%) compared with 26.3% for Ga2. A comparison between Ga2 isoforms/analogs and their Gb3 counterparts also showed that the proportion of analogs with hydroxylated fatty acids is significantly greater for Ga2 (35.8%) compared with Gb3 (1.9%). These results suggest different biological pathways involved in the synthesis and/or degradation of Gb3 and Ga2 metabolites.

  4. Early-Phase Studies of Biomarkers

    DEFF Research Database (Denmark)

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

    2016-01-01

    of a positive biomarker test in cases (true positive) to cost associated with a positive biomarker test in controls (false positive). Guidance is offered on soliciting the cost/benefit ratio. The calculations are based on the longstanding decision theory concept of providing a net benefit on average...... impact on patient outcomes of using the biomarker to make clinical decisions....

  5. Discovery of putative salivary biomarkers for Sjögren's syndrome using high resolution mass spectrometry and bioinformatics.

    Science.gov (United States)

    Zoukhri, Driss; Rawe, Ian; Singh, Mabi; Brown, Ashley; Kublin, Claire L; Dawson, Kevin; Haddon, William F; White, Earl L; Hanley, Kathleen M; Tusé, Daniel; Malyj, Wasyl; Papas, Athena

    2012-03-01

    The purpose of the current study was to determine if saliva contains biomarkers that can be used as diagnostic tools for Sjögren's syndrome (SjS). Twenty seven SjS patients and 27 age-matched healthy controls were recruited for these studies. Unstimulated glandular saliva was collected from the Wharton's duct using a suction device. Two µl of salvia were processed for mass spectrometry analyses on a prOTOF 2000 matrix-assisted laser desorption/ionization orthogonal time of flight (MALDI O-TOF) mass spectrometer. Raw data were analyzed using bioinformatic tools to identify biomarkers. MALDI O-TOF MS analyses of saliva samples were highly reproducible and the mass spectra generated were very rich in peptides and peptide fragments in the 750-7,500 Da range. Data analysis using bioinformatic tools resulted in several classification models being built and several biomarkers identified. One model based on 7 putative biomarkers yielded a sensitivity of 97.5%, specificity of 97.8% and an accuracy of 97.6%. One biomarker was present only in SjS samples and was identified as a proteolytic peptide originating from human basic salivary proline-rich protein 3 precursor. We conclude that salivary biomarkers detected by high-resolution mass spectrometry coupled with powerful bioinformatic tools offer the potential to serve as diagnostic/prognostic tools for SjS.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Mining PubMed for Biomarker-Disease Associations to Guide Discovery

    OpenAIRE

    Jessen, Walter; Landschulz, Katherine; Turi, Thomas; Reams, Rachel

    2012-01-01

    Biomedical knowledge is growing exponentially; however, meta-knowledge around the data is often lacking. PubMed is a database comprising more than 21 million citations for biomedical literature from MEDLINE and additional life science journals dating back to the 1950s. To explore the use and frequency of biomarkers across human disease, we mined PubMed for biomarker-disease associations. We then ranked the top 100 linked diseases by relevance and mapped them to medical subject headings (MeSH)...

  11. 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/.

  12. 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/.

  13. Proteomics pipeline for biomarker discovery of laser capture microdissected breast cancer tissue

    NARCIS (Netherlands)

    N.Q. Liu (Ning Qing); R.B.H. Braakman (René); C. Stingl (Christoph); T.M. Luider (Theo); J.W.M. Martens (John); J.A. Foekens (John); A. Umar (Arzu)

    2012-01-01

    textabstractMass spectrometry (MS)-based label-free proteomics offers an unbiased approach to screen biomarkers related to disease progression and therapy-resistance of breast cancer on the global scale. However, multi-step sample preparation can introduce large variation in generated data, while

  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. Candidate Biomarkers in Children with Autism Spectrum Disorder: A Review of MRI Studies

    Institute of Scientific and Technical Information of China (English)

    Dongyun Li; Hans-Otto Karnath; Xiu Xu

    2017-01-01

    Searching for effective biomarkers is one of the most challenging tasks in the research field of Autism Spectrum Disorder (ASD).Magnetic resonance imaging (MRI) provides a non-invasive and powerful tool for investigating changes in the structure,function,maturation,connectivity,and metabolism of the brain of children with ASD.Here,we review the more recent MRI studies in young children with ASD,aiming to provide candidate biomarkers for the diagnosis of childhood ASD.The review covers structural imaging methods,diffusion tensor imaging,resting-state functional MRI,and magnetic reso nance spectroscopy.Future advances in neuroimaging techniques,as well as cross-disciplinary studies and largescale collaborations will be needed for an integrated approach linking neuroimaging,genetics,and phenotypic data to allow the discovery of new,effective biomarkers.

  16. Three-Dimensionally Functionalized Reverse Phase Glycoprotein Array for Cancer Biomarker Discovery and Validation.

    Science.gov (United States)

    Pan, Li; Aguilar, Hillary Andaluz; Wang, Linna; Iliuk, Anton; Tao, W Andy

    2016-11-30

    Glycoproteins have vast structural diversity that plays an important role in many biological processes and have great potential as disease biomarkers. Here, we report a novel functionalized reverse phase protein array (RPPA), termed polymer-based reverse phase glycoprotein array (polyGPA), to capture and profile glycoproteomes specifically, and validate glycoproteins. Nitrocellulose membrane functionalized with globular hydroxyaminodendrimers was used to covalently capture preoxidized glycans on glycoproteins from complex protein samples such as biofluids. The captured glycoproteins were subsequently detected using the same validated antibodies as in RPPA. We demonstrated the outstanding specificity, sensitivity, and quantitative capabilities of polyGPA by capturing and detecting purified as well as endogenous α-1-acid glycoprotein (AGP) in human plasma. We further applied quantitative N-glycoproteomics and the strategy to validate a panel of glycoproteins identified as potential biomarkers for bladder cancer by analyzing urine glycoproteins from bladder cancer patients or matched healthy individuals.

  17. Development of a universal metabolome-standard method for long-term LC-MS metabolome profiling and its application for bladder cancer urine-metabolite-biomarker discovery.

    Science.gov (United States)

    Peng, Jun; Chen, Yi-Ting; Chen, Chien-Lun; Li, Liang

    2014-07-01

    Large-scale metabolomics study requires a quantitative method to generate metabolome data over an extended period with high technical reproducibility. We report a universal metabolome-standard (UMS) method, in conjunction with chemical isotope labeling liquid chromatography-mass spectrometry (LC-MS), to provide long-term analytical reproducibility and facilitate metabolome comparison among different data sets. In this method, UMS of a specific type of sample labeled by an isotope reagent is prepared a priori. The UMS is spiked into any individual samples labeled by another form of the isotope reagent in a metabolomics study. The resultant mixture is analyzed by LC-MS to provide relative quantification of the individual sample metabolome to UMS. UMS is independent of a study undertaking as well as the time of analysis and useful for profiling the same type of samples in multiple studies. In this work, the UMS method was developed and applied for a urine metabolomics study of bladder cancer. UMS of human urine was prepared by (13)C2-dansyl labeling of a pooled sample from 20 healthy individuals. This method was first used to profile the discovery samples to generate a list of putative biomarkers potentially useful for bladder cancer detection and then used to analyze the verification samples about one year later. Within the discovery sample set, three-month technical reproducibility was examined using a quality control sample and found a mean CV of 13.9% and median CV of 9.4% for all the quantified metabolites. Statistical analysis of the urine metabolome data showed a clear separation between the bladder cancer group and the control group from the discovery samples, which was confirmed by the verification samples. Receiver operating characteristic (ROC) test showed that the area under the curve (AUC) was 0.956 in the discovery data set and 0.935 in the verification data set. These results demonstrated the utility of the UMS method for long-term metabolomics and

  18. 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

  19. Three-dimensionally Functionalized Reverse Phase Glycoprotein Array for Cancer Biomarker Discovery and Validation

    OpenAIRE

    Pan, Li; Aguilar, Hillary Andaluz; Wang, Linna; Iliuk, Anton; Tao, W. Andy

    2016-01-01

    Glycoproteins have vast structural diversity which plays an important role in many biological processes and have great potential as disease biomarkers. Here we report a novel functionalized reverse phase protein array (RPPA), termed polymer-based reverse phase GlycoProtein Array (polyGPA), to specifically capture and profile glycoproteomes, and validate glycoproteins. Nitrocellulose membrane functionalized with globular hydroxyaminodendrimers was used to covalently capture pre-oxidized glycan...

  20. 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...

  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. Use of the local false discovery rate for identification of metabolic biomarkers in rat urine following Genkwa Flos-induced hepatotoxicity.

    Directory of Open Access Journals (Sweden)

    Zuojing Li

    Full Text Available Metabolomics is concerned with characterizing the large number of metabolites present in a biological system using nuclear magnetic resonance (NMR and HPLC/MS (high-performance liquid chromatography with mass spectrometry. Multivariate analysis is one of the most important tools for metabolic biomarker identification in metabolomic studies. However, analyzing the large-scale data sets acquired during metabolic fingerprinting is a major challenge. As a posterior probability that the features of interest are not affected, the local false discovery rate (LFDR is a good interpretable measure. However, it is rarely used to when interrogating metabolic data to identify biomarkers. In this study, we employed the LFDR method to analyze HPLC/MS data acquired from a metabolomic study of metabolic changes in rat urine during hepatotoxicity induced by Genkwa flos (GF treatment. The LFDR approach was successfully used to identify important rat urine metabolites altered by GF-stimulated hepatotoxicity. Compared with principle component analysis (PCA, LFDR is an interpretable measure and discovers more important metabolites in an HPLC/MS-based metabolomic study.

  3. 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.

  4. 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). To ac...

  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. 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.

  7. Towards Precision Medicine in the Clinic: From Biomarker Discovery to Novel Therapeutics.

    Science.gov (United States)

    Collins, Dearbhaile C; Sundar, Raghav; Lim, Joline S J; Yap, Timothy A

    2017-01-01

    Precision medicine continues to be the benchmark to which we strive in cancer research. Seeking out actionable aberrations that can be selectively targeted by drug compounds promises to optimize treatment efficacy and minimize toxicity. Utilizing these different targeted agents in combination or in sequence may further delay resistance to treatments and prolong antitumor responses. Remarkable progress in the field of immunotherapy adds another layer of complexity to the management of cancer patients. Corresponding advances in companion biomarker development, novel methods of serial tumor assessments, and innovative trial designs act synergistically to further precision medicine. Ongoing hurdles such as clonal evolution, intra- and intertumor heterogeneity, and varied mechanisms of drug resistance continue to be challenges to overcome. Large-scale data-sharing and collaborative networks using next-generation sequencing (NGS) platforms promise to take us further into the cancer 'ome' than ever before, with the goal of achieving successful precision medicine. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. 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.

  9. 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

  10. Studying Scientific Discovery by Computer Simulation.

    Science.gov (United States)

    1983-03-30

    Mendel’s laws of inheritance, the law of Gay- Lussac for gaseous reactions, tile law of Dulong and Petit, the derivation of atomic weights by Avogadro...neceseary mid identify by block number) scientific discovery -ittri sic properties physical laws extensive terms data-driven heuristics intensive...terms theory-driven heuristics conservation laws 20. ABSTRACT (Continue on revere. side It necessary and identify by block number) Scientific discovery

  11. 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...... well-documented candidate miRNA markers for PC. Moreover, we identified several new potential serum miRNA markers for PC and developed three novel and highly specific (100 %) miRNA candidate marker panels able to identify 84 % of all PC patients (miR-562/miR-210/miR-501-3p/miR-375/miR-551b), 80...

  12. 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...

  13. Metabolomic and Genome-wide Association Studies Reveal Potential Endogenous Biomarkers for OATP1B1.

    Science.gov (United States)

    Yee, S W; Giacomini, M M; Hsueh, C-H; Weitz, D; Liang, X; Goswami, S; Kinchen, J M; Coelho, A; Zur, A A; Mertsch, K; Brian, W; Kroetz, D L; Giacomini, K M

    2016-11-01

    Transporter-mediated drug-drug interactions (DDIs) are a major cause of drug toxicities. Using published genome-wide association studies (GWAS) of the human metabolome, we identified 20 metabolites associated with genetic variants in organic anion transporter, OATP1B1 (P acids and fatty acid dicarboxylates were among the metabolites discovered using both GWAS and CSA administration. In vitro studies confirmed tetradecanedioate (TDA) and hexadecanedioate (HDA) were novel substrates of OATP1B1 as well as OAT1 and OAT3. This study highlights the use of multiple datasets for the discovery of endogenous metabolites that represent potential in vivo biomarkers for transporter-mediated DDIs. Future studies are needed to determine whether these metabolites can serve as qualified biomarkers for organic anion transporters. Quantitative relationships between metabolite levels and modulation of transporters should be established. © 2016 American Society for Clinical Pharmacology and Therapeutics.

  14. 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.

  15. 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…

  16. 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.

  17. 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.

  18. Combined serum and EPS-urine proteomic analysis using iTRAQ technology for discovery of potential prostate cancer biomarkers.

    Science.gov (United States)

    Zhang, Mo; Chen, Lizhu; Yuan, Zhengwei; Yang, Zeyu; Li, Yue; Shan, Liping; Yin, Bo; Fei, Xiang; Miao, Jianing; Song, Yongsheng

    2016-11-01

    Prostate cancer (PCa) is one of the most common malignant tumors and a major cause of cancer-related death for men worldwide. The aim of our study was to identify potential non-invasive serum and expressed prostatic secretion (EPS)-urine biomarkers for accurate diagnosis of PCa. Here, we performed a combined isobaric tags for relative and absolute quantification (iTRAQ) proteomic analysis to compare protein profiles using pooled serum and EPS-urine samples from 4 groups of patients: benign prostate hyperplasia (BPH), high grade prostatic intraepithelial neoplasia (HGPIN), localized PCa and metastatic PCa. The differentially expressed proteins were rigorously selected and further validated in a large and independent cohort using classical ELISA and Western blot assays. Finally, we established a multiplex biomarker panel consisting of 3 proteins (serum PF4V1, PSA, and urinary CRISP3) with an excellent diagnostic capacity to differentiate PCa from BPH [area under the receiver operating characteristic curve (AUC) of 0.941], which showed an evidently greater discriminatory ability than PSA alone (AUC, 0.757) (P<0.001). Importantly, even when PSA level was in the gray zone (4-10 ng/mL), a combination of PF4V1 and CRISP3 could achieve a relatively high diagnostic efficacy (AUC, 0.895). Furthermore, their combination also had the potential to distinguish PCa from HGPIN (AUC, 0.934). Our results demonstrated that the combined application of serum and EPS-urine biomarkers can improve the diagnosis of PCa and provide a new prospect for non-invasive PCa detection.

  19. Discovery of salivary gland tumors’ biomarkers via co-regularized sparse-group lasso

    NARCIS (Netherlands)

    Imangaliyev, S.; Matse, J.H.; Bolscher, J.G.M.; Brakenhoff, R.H.; Wong, D.T.W.; Bloemena, E.; Veerman, E.C.I.; Levin, E.; Yamamoto, A.; Kida, T.; Uno, T.; Kuboyama, T.

    2017-01-01

    In this study, we discovered a panel of discriminative microRNAs in salivary gland tumors by application of statistical machine learning methods. We modelled multi-component interactions of salivary microRNAs to detect group-based associations among the features, enabling the distinction of

  20. 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

  1. Radiation Biomarker Research Using Mass Spectrometry

    National Research Council Canada - National Science Library

    Bach, Stephan B; Hubert, Walter

    2007-01-01

    .... This review is intended to give an overview of mass spectrometry and its application to biological systems and biomarker discovery and how that might relate to relevant radiation dosimetry studies...

  2. Plasma membrane proteomics and its application in clinical cancer biomarker discovery

    DEFF Research Database (Denmark)

    Leth-Larsen, Rikke; Lund, Rikke; Ditzel, Henrik J

    2010-01-01

    Plasma membrane proteins that are exposed on the cell surface have important biological functions, such as signaling into and out of the cells, ion transport, and cell-cell and cell-matrix interactions. The expression level of many of the plasma membrane proteins involved in these key functions...... targeted by protein drugs, such as human antibodies, that have enhanced survival of several groups of cancer patients. The combination of novel analytical approaches and subcellular fractionation procedures has made it possible to study the plasma membrane proteome in more detail, which will elucidate...... cancer biology, particularly metastasis, and guide future development of novel drug targets. The technical advances in plasma membrane proteomics and the consequent biological revelations will be discussed herein. Many of the advances have been made using cancer cell lines, but because the main goal...

  3. 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.

  4. Proteomic discovery of biomarkers of metal contamination in Sydney Rock oysters (Saccostrea glomerata)

    Energy Technology Data Exchange (ETDEWEB)

    Thompson, Emma L., E-mail: emma.thompson@mq.edu.au [Department of Biological Sciences, Macquarie University, NSW 2109 (Australia); Sydney Institute of Marine Science, Chowder Bay, NSW 2088 (Australia); Taylor, Daisy A. [Department of Biological Sciences, Macquarie University, NSW 2109 (Australia); Sydney Institute of Marine Science, Chowder Bay, NSW 2088 (Australia); Nair, Sham V. [Department of Biological Sciences, Macquarie University, NSW 2109 (Australia); Birch, Gavin [Department of Geochemistry, University of Sydney, NSW 2006 (Australia); Haynes, Paul A. [Department of Chemistry and Biomolecular Sciences, Macquarie University, NSW 2109 (Australia); Raftos, David A. [Department of Biological Sciences, Macquarie University, NSW 2109 (Australia); Sydney Institute of Marine Science, Chowder Bay, NSW 2088 (Australia)

    2012-03-15

    In the current study we examined the effects of metal contamination on the protein complement of Sydney Rock oysters. Saccostrea glomerata were exposed for 4 days to three environmentally relevant concentrations (100 {mu}g/l, 50 {mu}g/l and 5 {mu}g/l) of cadmium, copper, lead and zinc. Protein abundances in oyster haemolymph from metal-exposed oysters were compared to those from non-exposed controls using two-dimensional electrophoresis to display differentially expressed proteins. Differentially expressed proteins were subsequently identified using tandem mass spectrometry (LC-MS/MS), to assign their putative biological functions. Unique sets of differentially expressed proteins were affected by each metal, in addition to proteins that were affected by more than one metal. The proteins identified included some that are commonly associated with environmental monitoring, such as HSP 70, and other novel proteins not previously considered as candidates for molecular biomonitoring. The most common biological functions of proteins were associated with stress response, cytoskeletal activity and protein synthesis.

  5. 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.

  6. 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.

  7. 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.

  8. Biomarkers in differentiating clinical dengue cases: A prospective cohort study

    Directory of Open Access Journals (Sweden)

    Gary Kim Kuan Low

    2015-12-01

    Full Text Available Objective: To evaluate five biomarkers (neopterin, vascular endothelial growth factor-A, thrombomodulin, soluble vascular cell adhesion molecule 1 and pentraxin 3 in differentiating clinical dengue cases. Methods: A prospective cohort study was conducted whereby the blood samples were obtained at day of presentation and the final diagnosis were obtained at the end of patients’ follow-up. All patients included in the study were 15 years old or older, not pregnant, not infected by dengue previously and did not have cancer, autoimmune or haematological disorder. Median test was performed to compare the biomarker levels. A subgroup Mann-Whitney U test was analysed between severe dengue and non-severe dengue cases. Monte Carlo method was used to estimate the 2-tailed probability (P value for independent variables with unequal number of patients. Results: All biomarkers except thrombomodulin has P value < 0.001 in differentiating among the healthy subjects, non-dengue fever, dengue without warning signs and dengue with warning signs/severe dengue. Subgroup analysis for all the biomarkers between severe dengue and non-severe dengue cases was not statistically significant except vascular endothelial growth factor-A (P < 0.05. Conclusions: Certain biomarkers were able to differentiate the clinical dengue cases. This could be potentially useful in classifying and determining the severity of dengue infected patients in the hospital.

  9. 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.

  10. 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.

  11. Cardiovascular biomarkers in clinical studies of type 2 diabetes

    DEFF Research Database (Denmark)

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

    2018-01-01

    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...

  12. 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

  13. 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

  14. Urine stability studies for novel biomarkers of acute kidney injury.

    Science.gov (United States)

    Parikh, Chirag R; Butrymowicz, Isabel; Yu, Angela; Chinchilli, Vernon M; Park, Meyeon; Hsu, Chi-Yuan; Reeves, W Brian; Devarajan, Prasad; Kimmel, Paul L; Siew, Edward D; Liu, Kathleen D

    2014-04-01

    The study of novel urinary biomarkers of acute kidney injury has expanded exponentially. Effective interpretation of data and meaningful comparisons between studies require awareness of factors that can adversely affect measurement. We examined how variations in short-term storage and processing might affect the measurement of urine biomarkers. Cross-sectional prospective. Hospitalized patients from 2 sites: Yale New Haven Hospital (n=50) and University of California, San Francisco Medical Center (n=36). We tested the impact of 3 urine processing conditions on these biomarkers: (1) centrifugation and storage at 4°C for 48 hours before freezing at -80°C, (2) centrifugation and storage at 25°C for 48 hours before freezing at -80°C, and (3) uncentrifuged samples immediately frozen at -80°C. Urine concentrations of 5 biomarkers: neutrophil gelatinase-associated lipocalin (NGAL), interleukin 18 (IL-18), kidney injury molecule 1 (KIM-1), liver-type fatty acid-binding protein (L-FABP), and cystatin C. We measured urine biomarkers by established enzyme-linked immunosorbent assay methods. Biomarker values were log-transformed, and agreement with a reference standard of immediate centrifugation and storage at -80°C was compared using concordance correlation coefficients (CCCs). Neither storing samples at 4°C for 48 hours nor centrifugation had a significant effect on measured levels, with CCCs higher than 0.9 for all biomarkers tested. For samples stored at 25°C for 48 hours, excellent CCC values (>0.9) also were noted between the test sample and the reference standard for NGAL, cystatin C, L-FABP and KIM-1. However, the CCC for IL-18 between samples stored at 25°C for 48 hours and the reference standard was 0.81 (95% CI, 0.66-0.96). No comparisons to fresh, unfrozen samples; no evaluation of the effect of protease inhibitors. All candidate markers tested using the specified assays showed high stability with both short-term storage at 4°C and without centrifugation

  15. 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

  16. Clinical studies of biomarkers in suicide prediction

    OpenAIRE

    Jokinen, Jussi

    2007-01-01

    Suicide is a major clinical problem in psychiatry and suicidal behaviours can be seen as a nosological entity per se. Predicting suicide is difficult due to its low base-rate and the limited specificity of clinical predictors. Prospective biological studies suggest that dysfunctions in the hypothalamo pituitary adrenal (HPA) axis and the serotonergic system have predictive power for suicide in mood disorders. Suicide attempt is the most robust clinical predictor making suici...

  17. 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

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

    Energy Technology Data Exchange (ETDEWEB)

    Lobdell, Danelle T [US Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Human Studies Division, Epidemiology and Biomarkers Branch, MD 58A, Research Triangle Park, NC 27711 (United States); Mendola, Pauline [US Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Human Studies Division, Epidemiology and Biomarkers Branch, MD 58A, Research Triangle Park, NC 27711 (United States)

    2005-08-07

    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.

  19. 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

  20. Glycoblotting method allows for rapid and efficient glycome profiling of human Alzheimer's disease brain, serum and cerebrospinal fluid towards potential biomarker discovery.

    Science.gov (United States)

    Gizaw, Solomon T; Ohashi, Tetsu; Tanaka, Masakazu; Hinou, Hiroshi; Nishimura, Shin-Ichiro

    2016-08-01

    Understanding of the significance of posttranslational glycosylation in Alzheimer's disease (AD) is of growing importance for the investigation of the pathogenesis of AD as well as discovery research of the disease-specific serum biomarkers. We designed a standard protocol for the glycoblotting combined with MALDI-TOFMS to perform rapid and quantitative profiling of the glycan parts of glycoproteins (N-glycans) and glycosphingolipids (GSLs) using human AD's post-mortem samples such as brain tissues (dissected cerebral cortices such as frontal, parietal, occipital, and temporal domains), serum and cerebrospinal fluid (CSF). The structural profiles of the major N-glycans released from glycoproteins and the total expression levels of the glycans were found to be mostly similar between the brain tissues of the AD patients and those of the normal control group. In contrast, the expression levels of the serum and CSF protein N-glycans such as bisect-type and multiply branched glycoforms were increased significantly in AD patient group. In addition, the levels of some gangliosides such as GM1, GM2 and GM3 appeared to alter in the AD patient brain and serum samples when compared with the normal control groups. Alteration of the expression levels of major N- and GSL-glycans in human brain tissues, serum and CSF of AD patients can be monitored quantitatively by means of the glycoblotting-based standard protocols. The changes in the expression levels of the glycans derived from the human post-mortem samples uncovered by the standardized glycoblotting method provides potential serum biomarkers in central nervous system disorders and can contribute to the insight into the molecular mechanisms in the pathogenesis of neurodegenerative diseases and future drug discovery. Most importantly, the present preliminary trials using human post-mortem samples of AD patients suggest that large-scale serum glycomics cohort by means of various-types of human AD patients as well as the normal

  1. 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.

  2. 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.

  3. Early LHC physics studies What can be obtained before discoveries?

    CERN Document Server

    AUTHOR|(CDS)2068230

    2006-01-01

    The Large Hadron Collider will provide an unprecedented quantity of collision data right from the start-up. The challenge for the LHC experiments is the quick use of these data for the final commissioning of the detectors, including calibration, alignment, measuring of detector and trigger efficiencies. A new energy frontier will open up, and measurement of basic Standard Model processes will build a solid basement for any discovery studies.

  4. Discovery and Use of Online Learning Resources: Case Study Findings

    OpenAIRE

    Laurie Miller Nelson; James Dorward; Mimi M. Recker

    2004-01-01

    Much recent research and funding have focused on building Internet-based repositories that contain collections of high-quality learning resources, often called learning objects. Yet little is known about how non-specialist users, in particular teachers, find, access, and use digital learning resources. To address this gap, this article describes a case study of mathematics and science teachers practices and desires surrounding the discovery, selection, and use of digital library resources for...

  5. Hemostasis biomarkers and incident cognitive impairment: the REGARDS study.

    Science.gov (United States)

    Gillett, S R; McClure, L A; Callas, P W; Thacker, E L; Unverzagt, F W; Wadley, V G; Letter, A J; Cushman, M

    2018-05-07

    Vascular risk factors are associated with cognitive impairment, a condition with substantial public health burden. We hypothesized that hemostasis biomarkers related to vascular disease would be associated with risk of incident cognitive impairment. We performed a nested case control study including 1,082 participants with 3.5 years of follow-up in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, a longitudinal cohort study of 30,239 black and white Americans ≥45 years old. Participants were free of stroke or cognitive impairment at baseline. Baseline D-dimer, fibrinogen, factor VIII, and protein C were measured in 495 cases who developed cognitive impairment during follow-up (based on abnormal scores on ≥2 of 3 cognitive tests) and 587 controls. Unadjusted ORs for incident cognitive impairment were 1.32 (95% CI 1.02, 1.70) for D-dimer >0.50 μg/mL, 1.83 (CI 1.24, 2.71) for fibrinogen >90 th percentile, 1.63 (CI 1.11, 2.38) for factor VIII >90 th percentile and 1.10 (CI 0.73, 1.65) for protein C impairment, with an adjusted OR 1.73 (CI 1.10, 2.69). Elevated D-dimer, fibrinogen, and factor VIII were not associated with occurrence of cognitive impairment after multivariable adjustment; however, having at least 2 abnormal biomarkers was associated, suggesting the burden of these biomarkers is relevant. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  6. 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.

  7. 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.

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

    DEFF Research Database (Denmark)

    Ahluwalia, Tarun Veer Singh; Allin, Kristine Højgaard; Sandholt, Camilla Helene

    2015-01-01

    CONTEXT: 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. OBJECTIVE: We aimed to discover underlying coding genetic variants influencing fasting serum levels of nine......-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. RESULTS: We discovered 11 associations between single-nucleotide polymorphisms and five distinct......, of which the association with the CELSR2 locus has not been shown previously. CONCLUSION: 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...

  9. 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

  10. Consensus definitions and application guidelines for control groups in cerebrospinal fluid biomarker studies in multiple sclerosis

    DEFF Research Database (Denmark)

    Teunissen, Charlotte; Menge, Til; Altintas, Ayse

    2013-01-01

    The choice of appropriate control group(s) is critical in cerebrospinal fluid (CSF) biomarker research in multiple sclerosis (MS). There is a lack of definitions and nomenclature of different control groups and a rationalized application of different control groups. We here propose consensus......). Furthermore, we discuss the application of these control groups in specific study designs, such as for diagnostic biomarker studies, prognostic biomarker studies and therapeutic response studies. Application of these uniform definitions will lead to better comparability of biomarker studies and optimal use...

  11. [Collaborative projects with academia for regulatory science studies on biomarkers].

    Science.gov (United States)

    Saito, Yoshiro; Nakamura, Ryosuke; Maekawa, Keiko

    2014-01-01

    Biomarkers are useful tools to be utilized as indicators/predictors of disease severity and drug responsiveness/safety, and thus are expected to promote efficient drug development and to accelerate proper use of approved drugs. Many academic achievements have been reported, but only a small number of biomarkers are used in clinical trials and drug treatments. Regulatory sciences on biomarkers for their secure development and proper qualification are necessary to facilitate their practical application. We started to collaborate with Tohoku University and Nagoya City University for sample quality, biomarker identification, evaluation of their usage, and making guidances. In this short review, scheme and progress of these projects are introduced.

  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...... a reduction in cigarettes per day of 50% or more without quitting were compared with continuing medium, heavy and light smokers (1-14 g/day) using linear regression. Sex (CCHS only), age, self-reported inhalation of smoke, duration of smoking, type of tobacco and amount smoked were included as covariates...

  13. 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

  14. 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

  15. 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...... increased with increasing discordance in perceived age within the twin pair-that is, the bigger the difference in perceived age within the pair, the more likely that the older looking twin died first. Twin analyses suggested that common genetic factors influence both perceived age and survival. Perceived...

  16. 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.

  17. 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

  18. Ambient temperature and cardiovascular biomarkers in a repeated-measure study in healthy adults: A novel biomarker index approach.

    Science.gov (United States)

    Wu, Shaowei; Yang, Di; Pan, Lu; Shan, Jiao; Li, Hongyu; Wei, Hongying; Wang, Bin; Huang, Jing; Baccarelli, Andrea A; Shima, Masayuki; Deng, Furong; Guo, Xinbiao

    2017-07-01

    Associations of ambient temperature with cardiovascular morbidity and mortality have been well documented in numerous epidemiological studies, but the underlying pathways remain unclear. We investigated whether systemic inflammation, coagulation, systemic oxidative stress, antioxidant activity and endothelial function may be the mechanistic pathways associated with ambient temperature. Forty study participants underwent repeated blood collections for 12 times in Beijing, China in 2010-2011. Ambient temperature and air pollution data were measured in central monitors close to student residences. We created five indices as the sum of weighted biomarker percentiles to represent the overall levels of 15 cardiovascular biomarkers in five pathways (systemic inflammation: hs-CRP, TNF-α and fibrinogen; coagulation: fibrinogen, PAI-1, tPA, vWF and sP-selectin; systemic oxidative stress: Ox-LDL and sCD36: antioxidant activity: EC-SOD and GPX1; and endothelial function: ET-1, E-selectin, ICAM-1 and VCAM-1). We used generalized mixed-effects models to estimate temperature effects controlling for air pollution and other covariates. There were significant decreasing trends in the adjusted means of biomarker indices over the lowest to the highest quartiles of daily temperatures before blood collection. A 10°C decrease at 2-d average daily temperature were associated with increases of 2.5% [95% confidence interval (CI): 0.7, 4.2], 1.6% (95% CI: 0.1, 3.1), 2.7% (95% CI: 0.5, 4.8), 5.5% (95% CI: 3.8, 7.3) and 2.0% (95% CI: 0.3, 3.8) in the indices for systemic inflammation, coagulation, systemic oxidative stress, antioxidant activity and endothelial function, respectively. In contrast, the associations between ambient temperature and individual biomarkers had substantial variation in magnitude and strength. The altered cardiovascular biomarker profiles in healthy adults associated with ambient temperature changes may help explain the temperature-related cardiovascular morbidity

  19. 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 ...

  20. 76 FR 82306 - Draft Guidance for Industry on Use of Histology in Biomarker Qualification Studies; Availability

    Science.gov (United States)

    2011-12-30

    ...] Draft Guidance for Industry on Use of Histology in Biomarker Qualification Studies; Availability AGENCY... announcing the availability of a draft guidance for industry entitled ``Use of Histology in Biomarker... studies for which histology is a reference standard. This guidance discusses the processes that should be...

  1. 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…

  2. Discovery and Use of Online Learning Resources: Case Study Findings

    Directory of Open Access Journals (Sweden)

    Laurie Miller Nelson

    2004-04-01

    Full Text Available Much recent research and funding have focused on building Internet-based repositories that contain collections of high-quality learning resources, often called ‘learning objects.’ Yet little is known about how non-specialist users, in particular teachers, find, access, and use digital learning resources. To address this gap, this article describes a case study of mathematics and science teachers’ practices and desires surrounding the discovery, selection, and use of digital library resources for instructional purposes. Findings suggest that the teacher participants used a broad range of search strategies in order to find resources that they deemed were age-appropriate, current, and accurate. They intended to include these resources with little modifications into planned instructional activities. The article concludes with a discussion of the implications of the findings for improving the design of educational digital library systems, including tools supporting resource reuse.

  3. 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; Dalmeijer, Gerdien W; Evelein, Annemieke M V; Fauser, Bart C J M; de Jager, Wilco

    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

  4. 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

  5. Biomarker kinetics in the prediction of VAP diagnosis: results from the BioVAP study

    NARCIS (Netherlands)

    Póvoa, Pedro; Martin-Loeches, Ignacio; Ramirez, Paula; Bos, Lieuwe D.; Esperatti, Mariano; Silvestre, Joana; Gili, Gisela; Goma, Gema; Berlanga, Eugenio; Espasa, Mateu; Gonçalves, Elsa; Torres, Antoni; Artigas, Antonio

    2016-01-01

    Prediction of diagnosis of ventilator-associated pneumonia (VAP) remains difficult. Our aim was to assess the value of biomarker kinetics in VAP prediction. We performed a prospective, multicenter, observational study to evaluate predictive accuracy of biomarker kinetics, namely C-reactive protein

  6. 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

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. Heritability of Biomarkers of Oxidized Lipoproteins: Twin Pair Study.

    Science.gov (United States)

    Rao, Fangwen; Schork, Andrew J; Maihofer, Adam X; Nievergelt, Caroline M; Marcovina, Santica M; Miller, Elizabeth R; Witztum, Joseph L; O'Connor, Daniel T; Tsimikas, Sotirios

    2015-07-01

    To determine whether biomarkers of oxidized lipoproteins are genetically determined. Lipoprotein(a) (Lp[a]) is a heritable risk factor and carrier of oxidized phospholipids (OxPL). We measured oxidized phospholipids on apolipoprotein B-containing lipoproteins (OxPL-apoB), Lp(a), IgG, and IgM autoantibodies to malondialdehyde-modified low-density lipoprotein, copper oxidized low-density lipoprotein, and apoB-immune complexes in 386 monozygotic and dizygotic twins to estimate trait heritability (h(2)) and determine specific genetic effects among traits. A genome-wide linkage study followed by genetic association was performed. The h(2) (scale: 0-1) for Lp(a) was 0.91±0.01 and for OxPL-apoB 0.87±0.02, which were higher than physiological, inflammatory, or lipid traits. h(2) of IgM malondialdehyde-modified low-density lipoprotein, copper oxidized low-density lipoprotein, and apoB-immune complexes were 0.69±0.04, 0.67±0.05, and 0.80±0.03, respectively, and for IgG malondialdehyde-modified low-density lipoprotein, copper oxidized low-density lipoprotein, and apoB-immune complexes 0.62±0.05, 0.52±0.06, and 0.53±0.06, respectively. There was an inverse correlation between the major apo(a) isoform and OxPL-apoB (R=-0.49; Plipoprotein and copper oxidized low-density lipoprotein, and apoB-immune complexes. Sib-pair genetic linkage of the Lp(a) trait revealed that single nucleotide polymorphism rs10455872 was significantly associated with OxPL-apoB after adjusting for Lp(a). OxPL-apoB and other biomarkers of oxidized lipoproteins are highly heritable cardiovascular risk factors that suggest novel genetic origins of atherothrombosis. © 2015 American Heart Association, Inc.

  12. Biomarkers study in rainbow trout exposed to industrially contaminated groundwater

    Directory of Open Access Journals (Sweden)

    Nadjet Benchalgo

    2014-03-01

    Full Text Available The spill of liquid industrial waste from chemical and petrochemical industries in Mercier lagoons located 20 km south of Montreal, Quebec, caused a major groundwater contamination by industrial contaminants. The aim of this study was to investigate the toxic effects of Mercier groundwater, following 4 and 14 days of exposure to graded concentrations from three wells at increasing distances 1.2, 2.7 and 5.4 km from the source of contamination. Rainbow trout were examined for several biomarkers of defense [ethoxyresorufin O-deethylase (EROD and gluthatione S-transferase (GST activities] and those of tissue damage [lipid peroxidation (LPO and DNA strand breaks]. The results showed that EROD activity was significantly enhanced in hepatic tissue at 1.2 and 5.4 km, whereas inhibition in activity was observed in group at 2.7 km. Therefore, GST activity was significantly increased at 3.1% concentration for the 2.7 km well. No change in LPO was observed. However, a significant induction of DNA strand breaks in liver was obtained at each distance. In conclusion, the data suggest that the release of these contaminants in groundwater leads to increased biotransformation for coplanar aromatic hydrocarbons and DNA damage in groundwater.

  13. Discovery and Validation of Pyridoxic Acid and Homovanillic Acid as Novel Endogenous Plasma Biomarkers of Organic Anion Transporter (OAT) 1 and OAT3 in Cynomolgus Monkeys.

    Science.gov (United States)

    Shen, Hong; Nelson, David M; Oliveira, Regina V; Zhang, Yueping; Mcnaney, Colleen A; Gu, Xiaomei; Chen, Weiqi; Su, Ching; Reily, Michael D; Shipkova, Petia A; Gan, Jinping; Lai, Yurong; Marathe, Punit; Humphreys, W Griffith

    2018-02-01

    Perturbation of organic anion transporter (OAT) 1- and OAT3-mediated transport can alter the exposure, efficacy, and safety of drugs. Although there have been reports of the endogenous biomarkers for OAT1/3, none of these have all of the characteristics required for a clinical useful biomarker. Cynomolgus monkeys were treated with intravenous probenecid (PROB) at a dose of 40 mg/kg in this study. As expected, PROB increased the area under the plasma concentration-time curve (AUC) of coadministered furosemide, a known substrate of OAT1 and OAT3, by 4.1-fold, consistent with the values reported in humans (3.1- to 3.7-fold). Of the 233 plasma metabolites analyzed using a liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolomics method, 29 metabolites, including pyridoxic acid (PDA) and homovanillic acid (HVA), were significantly increased after either 1 or 3 hours in plasma from the monkeys pretreated with PROB compared with the treated animals. The plasma of animals was then subjected to targeted LC-MS/MS analysis, which confirmed that the PDA and HVA AUCs increased by approximately 2- to 3-fold by PROB pretreatments. PROB also increased the plasma concentrations of hexadecanedioic acid (HDA) and tetradecanedioic acid (TDA), although the increases were not statistically significant. Moreover, transporter profiling assessed using stable cell lines constitutively expressing transporters demonstrated that PDA and HVA are substrates for human OAT1, OAT3, OAT2 (HVA), and OAT4 (PDA), but not OCT2, MATE1, MATE2K, OATP1B1, OATP1B3, and sodium taurocholate cotransporting polypeptide. Collectively, these findings suggest that PDA and HVA might serve as blood-based endogenous probes of cynomolgus monkey OAT1 and OAT3, and investigation of PDA and HVA as circulating endogenous biomarkers of human OAT1 and OAT3 function is warranted. Copyright © 2018 by The American Society for Pharmacology and Experimental Therapeutics.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. CHURCHILL COUNTY, NEVADA ARSENIC STUDY: WATER CONSUMPTION AND EXPOSURE BIOMARKERS

    Science.gov (United States)

    The US Environmental Protection Agency is required to reevaluate the Maximum Contaminant Level (MCL) for arsenic in 2006. To provide data for reducing uncertainties in assessing health risks associated with exposure to low levels (<200 g/l) of arsenic, a large scale biomarker st...

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. Prognostic utility of novel biomarkers of cardiovascular stress: the Framingham Heart Study.

    Science.gov (United States)

    Wang, Thomas J; Wollert, Kai C; Larson, Martin G; Coglianese, Erin; McCabe, Elizabeth L; Cheng, Susan; Ho, Jennifer E; Fradley, Michael G; Ghorbani, Anahita; Xanthakis, Vanessa; Kempf, Tibor; Benjamin, Emelia J; Levy, Daniel; Vasan, Ramachandran S; Januzzi, James L

    2012-09-25

    Biomarkers for predicting cardiovascular events in community-based populations have not consistently added information to standard risk factors. A limitation of many previously studied biomarkers is their lack of cardiovascular specificity. To determine the prognostic value of 3 novel biomarkers induced by cardiovascular stress, we measured soluble ST2, growth differentiation factor-15, and high-sensitivity troponin I in 3428 participants (mean age, 59 years; 53% women) in the Framingham Heart Study. We performed multivariable-adjusted proportional hazards models to assess the individual and combined ability of the biomarkers to predict adverse outcomes. We also constructed a "multimarker" score composed of the 3 biomarkers in addition to B-type natriuretic peptide and high-sensitivity C-reactive protein. During a mean follow-up of 11.3 years, there were 488 deaths, 336 major cardiovascular events, 162 heart failure events, and 142 coronary events. In multivariable-adjusted models, the 3 new biomarkers were associated with each end point (Pstatistic (P=0.005 or lower) and net reclassification improvement (P=0.001 or lower). Multiple biomarkers of cardiovascular stress are detectable in ambulatory individuals and add prognostic value to standard risk factors for predicting death, overall cardiovascular events, and heart failure.

  4. Biomarker discovery for cervical cancer

    NARCIS (Netherlands)

    Govorukhina, Natalia I.

    2007-01-01

    Proteomics of human boy fluids is still in its early stage of development with major methodological challenges ahead. This implies that much attention is given to improving the methods and strategies. One major challenge is that many samples that have been acquired in the past may not fulfill the

  5. 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...

  6. "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)

  7. Discovery of urinary biomarkers to discriminate between exogenous and semi-endogenous thiouracil in cattle: A parallel-like randomized design.

    Science.gov (United States)

    Van Meulebroek, Lieven; Wauters, Jella; Pomian, Beata; Vanden Bussche, Julie; Delahaut, Philippe; Fichant, Eric; Vanhaecke, Lynn

    2018-01-01

    In the European Union, the use of thyreostats for animal fattening purposes has been banned and monitoring plans have been established to detect potential abuse. However, this is not always straightforward as thyreostats such as thiouracil may also have a semi-endogenous origin. Therefore, this study aimed at defining urinary metabolites, which may aid in defining the origin of detected thiouracil. Hereto, a parallel-like randomized in vivo study was conducted in which calves (n = 8) and cows (n = 8) were subjected to either a control treatment, rapeseed-enriched diet to induce semi-endogenous formation, or thiouracil treatment. Urine samples (n = 330) were assessed through metabolic fingerprinting, employing liquid-chromatography and Q-ExactiveTM Orbitrap mass spectrometry. Urinary fingerprints comprised up to 40,000 features whereby multivariate discriminant analysis was able to point out significant metabolome differences between treatments (Q2(Y) ≥ 0.873). Using the validated models, a total of twelve metabolites (including thiouracil) were assigned marker potential. Combining these markers into age-dependent biomarker panels rendered a tool by which sample classification could be improved in comparison with thiouracil-based thresholds, and this during on-going thiouracil treatment (specificities ≥ 95.2% and sensitivities ≥ 85.7%), post-treatment (sensitivities ≥ 80% for ≥ 24 h after last administration), and simulated low-dose thiouracil treatment (exogenous thiouracil below 30 ng μL-1). Moreover, the metabolic relevance of revealed markers was supported by the suggested identities, for which a structural link with thiouracil could be determined in most cases. The proposed biomarker panels may contribute to a more justified decision-making in monitoring thiouracil abuse.

  8. 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.

  9. Pharmacogenomic Biomarkers

    Directory of Open Access Journals (Sweden)

    Sandra C. Kirkwood

    2002-01-01

    Full Text Available Pharmacogenomic biomarkers hold great promise for the future of medicine and have been touted as a means to personalize prescriptions. Genetic biomarkers for disease susceptibility including both Mendelian and complex disease promise to result in improved understanding of the pathophysiology of disease, identification of new potential therapeutic targets, and improved molecular classification of disease. However essential to fulfilling the promise of individualized therapeutic intervention is the identification of drug activity biomarkers that stratify individuals based on likely response to a particular therapeutic, both positive response, efficacy, and negative response, development of side effect or toxicity. Prior to the widespread clinical application of a genetic biomarker multiple scientific studies must be completed to identify the genetic variants and delineate their functional significance in the pathophysiology of a carefully defined phenotype. The applicability of the genetic biomarker in the human population must then be verified through both retrospective studies utilizing stored or clinical trial samples, and through clinical trials prospectively stratifying patients based on the biomarker. The risk conferred by the polymorphism and the applicability in the general population must be clearly understood. Thus, the development and widespread application of a pharmacogenomic biomarker is an involved process and for most disease states we are just at the beginning of the journey towards individualized therapy and improved clinical outcome.

  10. Validation study of genetic biomarkers of response to TNF inhibitors in rheumatoid arthritis.

    Directory of Open Access Journals (Sweden)

    Rosario Lopez-Rodriguez

    Full Text Available Genetic biomarkers are sought to personalize treatment of patients with rheumatoid arthritis (RA, given their variable response to TNF inhibitors (TNFi. However, no genetic biomaker is yet sufficiently validated. Here, we report a validation study of 18 previously reported genetic biomarkers, including 11 from GWAS of response to TNFi. The validation was attempted in 581 patients with RA that had not been treated with biologic antirheumatic drugs previously. Their response to TNFi was evaluated at 3, 6 and 12 months in two ways: change in the DAS28 measure of disease activity, and according to the EULAR criteria for response to antirheumatic drugs. Association of these parameters with the genotypes, obtained by PCR amplification followed by single-base extension, was tested with regression analysis. These analyses were adjusted for baseline DAS28, sex, and the specific TNFi. However, none of the proposed biomarkers was validated, as none showed association with response to TNFi in our study, even at the time of assessment and with the outcome that showed the most significant result in previous studies. These negative results are notable because this was the first independent validation study for 12 of the biomarkers, and because they indicate that prudence is needed in the interpretation of the proposed biomarkers of response to TNFi even when they are supported by very low p values. The results also emphasize the requirement of independent replication for validation, and the need to search protocols that could increase reproducibility of the biomarkers of response to TNFi.

  11. 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 sha...... bulky DNA adducts determined by 32P-postlabelling, or in DNA damage. The study indicated that smoking, diet and residential indoor air pollution are important non-occupational factors to consider when interpreting biomonitoring results....

  12. 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.

  13. Study of Tools for Network Discovery and Network Mapping

    Science.gov (United States)

    2003-11-01

    connected to the switch. iv. Accessibility of historical data and event data In general, network discovery tools keep a history of the collected...has the following software dependencies: - Java Virtual machine 76 - Perl modules - RRD Tool - TomCat - PostgreSQL STRENGTHS AND...systems - provide a simple view of the current network status - generate alarms on status change - generate history of status change VISUAL MAP

  14. The "BIOmarkers associated with Sarcopenia and PHysical frailty in EldeRly pErsons" (BIOSPHERE) study: Rationale, design and methods.

    Science.gov (United States)

    Calvani, Riccardo; Picca, Anna; Marini, Federico; Biancolillo, Alessandra; Cesari, Matteo; Pesce, Vito; Lezza, Angela Maria Serena; Bossola, Maurizio; Leeuwenburgh, Christiaan; Bernabei, Roberto; Landi, Francesco; Marzetti, Emanuele

    2018-05-10

    Sarcopenia, the progressive and generalised loss of muscle mass and strength/function, is a major health issue in older adults given its high prevalence and burdensome clinical implications. Over the years, this condition has been endorsed as a marker for discriminating biological from chronological age. However, the absence of a unified operational definition has hampered its full appreciation by healthcare providers, researchers and policy-makers. In addition to this unsolved debate, the complexity of musculoskeletal ageing represents a major challenge to the identification of clinically meaningful biomarkers. Here, we illustrate the advantages of biomarker discovery procedures in muscle ageing based on multivariate methodologies as an alternative approach to traditional single-marker strategies. The rationale, design and methods of the "BIOmarkers associated with Sarcopenia and PHysical frailty in EldeRly pErsons" (BIOSPHERE) study are described as an application of a multi-marker strategy for the development of biomarkers for the newly operationalised Physical Frailty & Sarcopenia condition. Copyright © 2018 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

  15. Alarmins as biomarkers of gastrointestinal surgical injury - a pilot study.

    Science.gov (United States)

    Maca, Jan; Holub, Michal; Bursa, Filip; Ihnat, Peter; Reimer, Petr; Svagera, Zdenek; Burda, Michal; Sevcik, Pavel

    2018-02-01

    The dysregulation of inflammatory response to surgical injury affects outcomes. Alarmins, the earliest bioactive substances from damaged cells, play a crucial role in initiating the inflammation. We analyzed serum levels of alarmins (S100A8, S100A12, high mobility group box, and heat shock protein 70) after major abdominal surgery (MAS) in surgical (S) (n = 82) and nonsurgical (NS) groups (n = 35). The main objective was determining a role of selected alarmins in host response to MAS. The secondary objectives were (i) evaluation of the relationship among alarmins and selected biomarkers (C-reactive protein, interleukin-6), (ii) influence of the place of gastrointestinal resection, and (iii) role of alarmins in MAS for cancer. Except for HMGB1, the levels of all alarmins were higher in the S group compared with the NS group. In the S group, positive correlations were found between S100A8 and both IL-6 and CRP. Additionally, the S100A8 level was higher (p < 0.01) in patients who underwent upper gastrointestinal tract (GIT) surgery compared to middle and lower GIT resections. Alarmins levels did not differ between cancer and noncancer patients. MAS is able to elicit increase in alarmin levels. S100A8 can be considered a potential biomarker of surgical injury, especially in the upper part of the GIT. © 2018 APMIS. Published by John Wiley & Sons Ltd.

  16. Cohort profile of BIOMArCS: the BIOMarker study to identify the Acute risk of a Coronary Syndrome-a prospective multicentre biomarker study conducted in the Netherlands.

    Science.gov (United States)

    Oemrawsingh, Rohit M; Akkerhuis, K Martijn; Umans, Victor A; Kietselaer, Bas; Schotborgh, Carl; Ronner, Eelko; Lenderink, Timo; Liem, Anho; Haitsma, David; van der Harst, Pim; Asselbergs, Folkert W; Maas, Arthur; Oude Ophuis, Anton J; Ilmer, Ben; Dijkgraaf, Rene; de Winter, Robbert-Jan; The, S Hong Kie; Wardeh, Alexander J; Hermans, Walter; Cramer, Etienne; van Schaik, Ron H; Hoefer, Imo E; Doevendans, Pieter A; Simoons, Maarten L; Boersma, Eric

    2016-12-23

    Progression of stable coronary artery disease (CAD) towards acute coronary syndrome (ACS) is a dynamic and heterogeneous process with many intertwined constituents, in which a plaque destabilising sequence could lead to ACS within short time frames. Current CAD risk assessment models, however, are not designed to identify increased vulnerability for the occurrence of coronary events within a precise, short time frame at the individual patient level. The BIOMarker study to identify the Acute risk of a Coronary Syndrome (BIOMArCS) was designed to evaluate whether repeated measurements of multiple biomarkers can predict such 'vulnerable periods'. BIOMArCS is a multicentre, prospective, observational study of 844 patients presenting with ACS, either with or without ST-elevation and at least one additional cardiovascular risk factor. We hypothesised that patterns of circulating biomarkers that reflect the various pathophysiological components of CAD, such as distorted lipid metabolism, vascular inflammation, endothelial dysfunction, increased thrombogenicity and ischaemia, diverge in the days to weeks before a coronary event. Divergent biomarker patterns, identified by serial biomarker measurements during 1-year follow-up might then indicate 'vulnerable periods' during which patients with CAD are at high short-term risk of developing an ACS. Venepuncture was performed every fortnight during the first half-year and monthly thereafter. As prespecified, patient enrolment was terminated after the primary end point of cardiovascular death or hospital admission for non-fatal ACS had occurred in 50 patients. A case-cohort design will explore differences in temporal patterns of circulating biomarkers prior to the repeat ACS. Follow-up and event adjudication have been completed. Prespecified biomarker analyses are currently being performed and dissemination through peer-reviewed publications and conference presentations is expected from the third quarter of 2016. Should

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

    Science.gov (United States)

    2010-07-01

    EMMPRIN is implicated in metastasis via its ability to confer resistance of breast cancer cells to anoikis by inhibiting BIM [21], and its association with...of Bim . J Biol Chem 2006;281:9719–9727. 22. Gupta N, Wollscheid B, Watts JD, Scheer B, Aebersold R, DeFranco AL. Quantitative proteomic analysis of B...disseminated in electronic form, nor  deployed in part or in whole in any  marketing , promotional or educational  contexts without authorization from

  18. 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.

  19. 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

  20. Biomarkers of tolerance: searching for the hidden phenotype.

    Science.gov (United States)

    Perucha, Esperanza; Rebollo-Mesa, Irene; Sagoo, Pervinder; Hernandez-Fuentes, Maria P

    2011-08-01

    Induction of transplantation tolerance remains the ideal long-term clinical and logistic solution to the current challenges facing the management of renal allograft recipients. In this review, we describe the recent studies and advances made in identifying biomarkers of renal transplant tolerance, from study inceptions, to the lessons learned and their implications for current and future studies with the same goal. With the age of biomarker discovery entering a new dimension of high-throughput technologies, here we also review the current approaches, developments, and pitfalls faced in the subsequent statistical analysis required to identify valid biomarker candidates.

  1. 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.

  2. Metabolomics as a tool in the identification of dietary biomarkers.

    Science.gov (United States)

    Gibbons, Helena; Brennan, Lorraine

    2017-02-01

    Current dietary assessment methods including FFQ, 24-h recalls and weighed food diaries are associated with many measurement errors. In an attempt to overcome some of these errors, dietary biomarkers have emerged as a complementary approach to these traditional methods. Metabolomics has developed as a key technology for the identification of new dietary biomarkers and to date, metabolomic-based approaches have led to the identification of a number of putative biomarkers. The three approaches generally employed when using metabolomics in dietary biomarker discovery are: (i) acute interventions where participants consume specific amounts of a test food, (ii) cohort studies where metabolic profiles are compared between consumers and non-consumers of a specific food and (iii) the analysis of dietary patterns and metabolic profiles to identify nutritypes and biomarkers. The present review critiques the current literature in terms of the approaches used for dietary biomarker discovery and gives a detailed overview of the currently proposed biomarkers, highlighting steps needed for their full validation. Furthermore, the present review also evaluates areas such as current databases and software tools, which are needed to advance the interpretation of results and therefore enhance the utility of dietary biomarkers in nutrition research.

  3. 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.

  4. Mycotoxin exposure in rural residents in northern Nigeria: a pilot study using multi-urinary biomarkers.

    Science.gov (United States)

    Ezekiel, Chibundu N; Warth, Benedikt; Ogara, Isaac M; Abia, Wilfred A; Ezekiel, Victoria C; Atehnkeng, Joseph; Sulyok, Michael; Turner, Paul C; Tayo, Grace O; Krska, Rudolf; Bandyopadhyay, Ranajit

    2014-05-01

    A pilot, cross-sectional, correlational study was conducted in eight rural communities in northern Nigeria to investigate mycotoxin exposures in 120 volunteers (19 children, 20 adolescents and 81 adults) using a modern LC-MS/MS based multi-biomarker approach. First morning urine samples were analyzed and urinary biomarker levels correlated with mycotoxin levels in foods consumed the day before urine collection. A total of eight analytes were detected in 61/120 (50.8%) of studied urine samples, with ochratoxin A, aflatoxin M1 and fumonisin B1 being the most frequently occurring biomarkers of exposure. These mycotoxin biomarkers were present in samples from all age categories, suggestive of chronic (lifetime) exposures. Rough estimates of mycotoxin intake suggested some exposures were higher than the tolerable daily intake. Overall, rural consumer populations from Nasarawa were more exposed to several mixtures of mycotoxins in their diets relative to those from Kaduna as shown by food and urine biomarker data. This study has shown that mycotoxin co-exposure may be a major public health challenge in rural Nigeria; this calls for urgent intervention. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. 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.

  6. Monitoring Progression of Amyotrophic Lateral Sclerosis Using Ultrasound Morpho-Textural Muscle Biomarkers: A Pilot Study.

    Science.gov (United States)

    Martínez-Payá, Jacinto J; Ríos-Díaz, José; Medina-Mirapeix, Francesc; Vázquez-Costa, Juan F; Del Baño-Aledo, María Elena

    2018-01-01

    The need is increasing for progression biomarkers that allow the loss of motor neurons in amyotrophic lateral sclerosis (ALS) to be monitored in clinical trials. In this prospective longitudinal study, muscle thickness, echointensity, echovariation and gray level co-occurrence matrix textural features are examined as possible progression ultrasound biomarkers in ALS patients during a 5-mo follow-up period. We subjected 13 patients to 3 measurements for 20 wk. They showed a significant loss of muscle, an evident tendency to loss of thickness and increased echointensity and echovariation. In regard to textural parameters, muscle heterogeneity tended to increase as a result of the neoformation of non-contractile tissue through denervation. Considering some limitations of the study, the quantitative muscle ultrasound biomarkers evaluated showed a promising ability to monitor patients affected by ALS. Copyright © 2018 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.

  7. Urine biomarkers in the early stages of diseases: current status and perspective.

    Science.gov (United States)

    Jing, Jian; Gao, Youhe

    2018-02-01

    As a noninvasive and easily available biological fluid, the urine is becoming an important source for disease biomarker study. Change is essential for the usefulness of a biomarker. Without homeostasis mechanisms, urine can accommodate more changes, especially in the early stages of diseases. In this review, we summarize current status and discuss perspectives on the discovery of urine biomarkers in the early stages of diseases. We emphasize the advantages of urine biomarkers compared to plasma biomarkers for the diagnosis of diseases at early stages, propose a urine biomarker research roadmap, and highlight a novel membrane storage technique that enables large-scale urine sample collection and storage efficiently and economically. It is anticipated that urine biomarker studies will greatly promote early diagnosis, prevention, treatment, and prognosis of a variety of diseases, and provide strong support for translational and precision medicine.

  8. 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

  9. 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.

  10. Biomarkers in Czech workers exposed to 1,3-butadiene: a transitional epidemiologic study

    NARCIS (Netherlands)

    Albertini, Richard J.; Srám, Radim J.; Vacek, Pamela M.; Lynch, Jeremiah; Nicklas, Janice A.; van Sittert, Nico J.; Boogaard, Peter J.; Henderson, Rogene F.; Swenberg, James A.; Tates, Ad D.; Ward, Jonathan B.; Wright, Michael; Ammenheuser, Marinel M.; Binkova, Blanka; Blackwell, Walter; de Zwart, Franz A.; Krako, Dean; Krone, Jennifer; Megens, Hendricus; Musilová, Petra; Rajská, Gabriela; Ranasinghe, Asoka; Rosenblatt, Judah I.; Rössner, Pavel; Rubes, Jiri; Sullivan, Linda; Upton, Patricia; Zwinderman, Ailko H.

    2003-01-01

    A multiinstitutional, transitional epidemiologic study was conducted with a worker population in the Czech Republic to evaluate the utility of a continuum of non-disease biological responses as biomarkers of exposure to 1,3-butadiene (BD)* in an industrial setting. The study site included two BD

  11. Multicollinearity may lead to artificial interaction: an example from a cross sectional study of biomarkers.

    Science.gov (United States)

    Sithisarankul, P; Weaver, V M; Diener-West, M; Strickland, P T

    1997-06-01

    Collinearity is the situation which arises in multiple regression when some or all of the explanatory variables are so highly correlated with one another that it becomes very difficult, if not impossible, to disentangle their influences and obtain a reasonably precise estimate of their effects. Suppressor variable is one of the extreme situations of collinearity that one variable can substantially increase the multiple correlation when combined with a variable that is only modestly correlated with the response variable. In this study, we describe the process by which we disentangled and discovered multicollinearity and its consequences, namely artificial interaction, using the data from cross-sectional quantification of several biomarkers. We showed how the collinearity between one biomarker (blood lead level) and another (urinary trans, trans-muconic acid) and their interaction (blood lead level* urinary trans, trans-muconic acid) can lead to the observed artificial interaction on the third biomarker (urinary 5-aminolevulinic acid).

  12. Evidence that iron accelerates Alzheimer's pathology: a CSF biomarker study.

    Science.gov (United States)

    Ayton, Scott; Diouf, Ibrahima; Bush, Ashley Ian

    2018-05-01

    To investigate whether cerebrospinal fluid (CSF) ferritin (reporting brain iron) is associated with longitudinal changes in CSF β-amyloid (Aβ) and tau. Mixed-effects models of CSF Aβ 1-42 and tau were constructed using data from 296 participants who had baseline measurement of CSF ferritin and annual measurement of CSF tau and Aβ 1-42 for up to 5 years. In subjects with biomarker-confirmed Alzheimer's pathology, high CSF ferritin (>6.2 ng/mL) was associated with accelerated depreciation of CSF Aβ 1-42 (reporting increased plaque formation; p=0.0001). CSF ferritin was neither associated with changes in CSF tau in the same subjects, nor longitudinal changes in CSF tau or Aβ 1-42 in subjects with low baseline pathology. In simulation modelling of the natural history of Aβ deposition, which we estimated to occur over 31.4 years, we predicted that it would take 12.6 years to reach the pathology threshold value of CSF Aβ from healthy normal levels, and this interval is not affected by CSF ferritin. CSF ferritin influences the fall in CSF Aβ over the next phase, where high CSF ferritin accelerated the transition from threshold preclinical Aβ levels to the average level of Alzheimer's subjects from 18.8 to 10.8 years. Iron might facilitate Aβ deposition in Alzheimer's and accelerate the disease process. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  13. 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-...

  14. 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.

  15. A new approach towards biomarker selection in estimation of human exposure to chiral chemicals: a case study of mephedrone.

    Science.gov (United States)

    Castrignanò, Erika; Mardal, Marie; Rydevik, Axel; Miserez, Bram; Ramsey, John; Shine, Trevor; Pantoș, G Dan; Meyer, Markus R; Kasprzyk-Hordern, Barbara

    2017-11-02

    Wastewater-based epidemiology is an innovative approach to estimate public health status using biomarker analysis in wastewater. A new compound detected in wastewater can be a potential biomarker of an emerging trend in public health. However, it is currently difficult to select new biomarkers mainly due to limited human metabolism data. This manuscript presents a new framework, which enables the identification and selection of new biomarkers of human exposure to drugs with scarce or unknown human metabolism data. Mephedrone was targeted to elucidate the assessment of biomarkers for emerging drugs of abuse using a four-step analytical procedure. This framework consists of: (i) identification of possible metabolic biomarkers present in wastewater using an in-vivo study; (ii) verification of chiral signature of the target compound; (iii) confirmation of human metabolic residues in in-vivo/vitro studies and (iv) verification of stability of biomarkers in wastewater. Mephedrone was selected as a suitable biomarker due to its high stability profile in wastewater. Its enantiomeric profiling was studied for the first time in biological and environmental matrices, showing stereoselective metabolism of mephedrone in humans. Further biomarker candidates were also proposed for future investigation: 4'-carboxy-mephedrone, 4'-carboxy-normephedrone, 1-dihydro-mephedrone, 1-dihydro-normephedrone and 4'-hydroxy-normephedrone.

  16. Metabolite Profiling in the Pursuit of Biomarkers for IVF Outcome: The Case for Metabolomics Studies

    Directory of Open Access Journals (Sweden)

    C. McRae

    2013-01-01

    Full Text Available Background. This paper presents the literature on biomarkers of in vitro fertilisation (IVF outcome, demonstrating the progression of these studies towards metabolite profiling, specifically metabolomics. The need for more, and improved, metabolomics studies in the field of assisted conception is discussed. Methods. Searches were performed on ISI Web of Knowledge SM for literature associated with biomarkers of oocyte and embryo quality, and biomarkers of IVF outcome in embryo culture medium, follicular fluid (FF, and blood plasma in female mammals. Results. Metabolomics in the field of female reproduction is still in its infancy. Metabolomics investigations of embryo culture medium for embryo selection have been the most common, but only within the last five years. Only in 2012 has the first metabolomics investigation of FF for biomarkers of oocyte quality been reported. The only metabolomics studies of human blood plasma in this context have been aimed at identifying women with polycystic ovary syndrome (PCOS. Conclusions. Metabolomics is becoming more established in the field of assisted conception, but the studies performed so far have been preliminary and not all potential applications have yet been explored. With further improved metabolomics studies, the possibility of identifying a method for predicting IVF outcome may become a reality.

  17. 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

  18. 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

  19. 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

  20. Biomarkers in Alzheimer’s Disease Analysis by Mass Spectrometry-Based Proteomics

    Directory of Open Access Journals (Sweden)

    Yahui Liu

    2014-05-01

    Full Text Available Alzheimer’s disease (AD is a common chronic and destructive disease. The early diagnosis of AD is difficult, thus the need for clinically applicable biomarkers development is growing rapidly. There are many methods to biomarker discovery and identification. In this review, we aim to summarize Mass spectrometry (MS-based proteomics studies on AD and discuss thoroughly the methods to identify candidate biomarkers in cerebrospinal fluid (CSF and blood. This review will also discuss the potential research areas on biomarkers.

  1. 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

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

    Science.gov (United States)

    Pham, Nam; Akonasu, Hungbo; Shishkin, Rhonda; Taghibiglou, Changiz

    2015-01-01

    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.

  3. 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.

  4. 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.

  5. 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).

  6. 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.

  7. 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.

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

    Science.gov (United States)

    Sehgal, Vasudha; Seviour, Elena G; Moss, Tyler J; Mills, Gordon B; Azencott, Robert; Ram, Prahlad T

    2015-01-01

    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.

  9. Influences of Normalization Method on Biomarker Discovery in Gas Chromatography-Mass Spectrometry-Based Untargeted Metabolomics: What Should Be Considered?

    Science.gov (United States)

    Chen, Jiaqing; Zhang, Pei; Lv, Mengying; Guo, Huimin; Huang, Yin; Zhang, Zunjian; Xu, Fengguo

    2017-05-16

    Data reduction techniques in gas chromatography-mass spectrometry-based untargeted metabolomics has made the following workflow of data analysis more lucid. However, the normalization process still perplexes researchers, and its effects are always ignored. In order to reveal the influences of normalization method, five representative normalization methods (mass spectrometry total useful signal, median, probabilistic quotient normalization, remove unwanted variation-random, and systematic ratio normalization) were compared in three real data sets with different types. First, data reduction techniques were used to refine the original data. Then, quality control samples and relative log abundance plots were utilized to evaluate the unwanted variations and the efficiencies of normalization process. Furthermore, the potential biomarkers which were screened out by the Mann-Whitney U test, receiver operating characteristic curve analysis, random forest, and feature selection algorithm Boruta in different normalized data sets were compared. The results indicated the determination of the normalization method was difficult because the commonly accepted rules were easy to fulfill but different normalization methods had unforeseen influences on both the kind and number of potential biomarkers. Lastly, an integrated strategy for normalization method selection was recommended.

  10. 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

  11. Molecular Elucidation of Disease Biomarkers at the Interface of Chemistry and Biology.

    Science.gov (United States)

    Zhang, Liqin; Wan, Shuo; Jiang, Ying; Wang, Yanyue; Fu, Ting; Liu, Qiaoling; Cao, Zhijuan; Qiu, Liping; Tan, Weihong

    2017-02-22

    Disease-related biomarkers are objectively measurable molecular signatures of physiological status that can serve as disease indicators or drug targets in clinical diagnosis and therapy, thus acting as a tool in support of personalized medicine. For example, the prostate-specific antigen (PSA) biomarker is now widely used to screen patients for prostate cancer. However, few such biomarkers are currently available, and the process of biomarker identification and validation is prolonged and complicated by inefficient methods of discovery and few reliable analytical platforms. Therefore, in this Perspective, we look at the advanced chemistry of aptamer molecules and their significant role as molecular probes in biomarker studies. As a special class of functional nucleic acids evolved from an iterative technology termed Systematic Evolution of Ligands by Exponential Enrichment (SELEX), these single-stranded oligonucleotides can recognize their respective targets with selectivity and affinity comparable to those of protein antibodies. Because of their fast turnaround time and exceptional chemical properties, aptamer probes can serve as novel molecular tools for biomarker investigations, particularly in assisting identification of new disease-related biomarkers. More importantly, aptamers are able to recognize biomarkers from complex biological environments such as blood serum and cell surfaces, which can provide direct evidence for further clinical applications. This Perspective highlights several major advancements of aptamer-based biomarker discovery strategies and their potential contribution to the practice of precision medicine.

  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. 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

  14. Thermal stability of thiophene biomarkers as studied by hydrous pyrolysis

    NARCIS (Netherlands)

    Sinninghe Damsté, J.S.; Koopmans, M.P.; Lewan, M.D.; Leeuw, J.W. de

    1995-01-01

    An immature (Ro = 0.25%) sulphur-rich calcareous shale from the Gessoso-solfifera Formation (Messinian) in the Vena del Gesso Basin (northern Italy) was artificially matured by hydrous pyrolysis at constant temperatures ranging from 160 to 330°C for 72 h to study the applicability of alkylthiophenes

  15. 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.

  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...... non-significant in men (ß = 0.9924, [0.9839; 1.0011]) and women (ß = 0.9932, [0.8605; 1.0014]). Conclusion: SLTB appears to be an independent CVD risk factor, regardless of snacking habits and physical activity....

  17. 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.

  18. Mining biomarker information in biomedical literature

    Directory of Open Access Journals (Sweden)

    Younesi Erfan

    2012-12-01

    Full Text Available Abstract Background For selection and evaluation of potential biomarkers, inclusion of already published information is of utmost importance. In spite of significant advancements in text- and data-mining techniques, the vast knowledge space of biomarkers in biomedical text has remained unexplored. Existing named entity recognition approaches are not sufficiently selective for the retrieval of biomarker information from the literature. The purpose of this study was to identify textual features that enhance the effectiveness of biomarker information retrieval for different indication areas and diverse end user perspectives. Methods A biomarker terminology was created and further organized into six concept classes. Performance of this terminology was optimized towards balanced selectivity and specificity. The information retrieval performance using the biomarker terminology was evaluated based on various combinations of the terminology's six classes. Further validation of these results was performed on two independent corpora representing two different neurodegenerative diseases. Results The current state of the biomarker terminology contains 119 entity classes supported by 1890 different synonyms. The result of information retrieval shows improved retrieval rate of informative abstracts, which is achieved by including clinical management terms and evidence of gene/protein alterations (e.g. gene/protein expression status or certain polymorphisms in combination with disease and gene name recognition. When additional filtering through other classes (e.g. diagnostic or prognostic methods is applied, the typical high number of unspecific search results is significantly reduced. The evaluation results suggest that this approach enables the automated identification of biomarker information in the literature. A demo version of the search engine SCAIView, including the biomarker retrieval, is made available to the public through http

  19. Storage Time and Urine Biomarker Levels in the ASSESS-AKI Study

    Science.gov (United States)

    Liu, Kathleen D.; Siew, Edward D.; Reeves, W. Brian; Himmelfarb, Jonathan; Go, Alan S.; Hsu, Chi-yuan; Bennett, Michael R.; Devarajan, Prasad; Ikizler, T. Alp; Kaufman, James S.; Kimmel, Paul L.; Chinchilli, Vernon M.; Parikh, Chirag R.

    2016-01-01

    Background 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. Methods 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. Results 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. Conclusion 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. PMID:27788160

  20. 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.

  1. Imaging studies and biomarkers to detect clinically meaningful vesicoureteral reflux

    Directory of Open Access Journals (Sweden)

    Michaella Maloney Prasad

    2017-06-01

    Full Text Available The work-up of a febrile urinary tract infection is generally performed to detect vesicoureteral reflux (VUR and its possible complications. The imaging modalities most commonly used for this purpose are renal-bladder ultrasound, voiding cystourethrogram and dimercapto-succinic acid scan. These studies each contribute valuable information, but carry individual benefits and limitations that may impact their efficacy. Biochemical markers are not commonly used in pediatric urology to diagnose or differentiate high-risk disease, but this is the emerging frontier, which will hopefully change our approach to VUR in the future. As it becomes more apparent that there is tremendous clinical variation within grades of VUR, the need to distinguish clinically significant from insignificant disease grows. The unfortunate truth about VUR is that recommendations for treatment may be inconsistent. Nuances in clinical decision-making will always exist, but opinions for medical versus surgical intervention should be more standardized, based on risk of injury to the kidney.

  2. 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...

  3. An exploratory study of inflammatory cytokines as prognostic biomarkers in patients with ductal pancreatic adenocarcinoma.

    Science.gov (United States)

    Dima, Simona O; Tanase, Cristiana; Albulescu, Radu; Herlea, Vlad; Chivu-Economescu, Mihaela; Purnichescu-Purtan, Raluca; Dumitrascu, Traian; Duda, Dan G; Popescu, Irinel

    2012-10-01

    We measured the serum concentration of a panel of inflammatory cytokines and evaluated their association with circulating proangiogenic biomarkers and with outcome in patients with pancreatic ductal adenocarcinoma (PDAC). We collected serum samples from 36 patients with PDAC, 9 patients with chronic pancreatitis, and 22 healthy volunteers as a control. Inflammatory cytokines and proangiogenic biomarkers were measured using the multianalyte xMAP array and carcinoembryonic antigen (CEA) and carbohydrate 19-9 by immunoassay. Patients with PDAC had higher circulating levels of interleukin 6 (IL-6) than those of patients with pancreatitis or healthy individuals and higher levels of IL-10 and tumor necrosis factor α (TNF-α) compared with those of healthy individuals. In patients with PDAC, circulating IL-6, TNF-α, IL-1β, and IL-10 correlated with serum concentrations of vascular endothelial growth factor and basic fibroblast growth factor; circulating IL-6, IL-1β, and TNF-α correlated with carbohydrate 19-9; and IL-8, IL-10, and TNF-α correlated with CEA levels. Circulating IL-8, TNF-α, and CEA; tumor stage; and lymph node metastases were associated with a poor outcome. The results of this exploratory study indicate that inflammatory cytokines should be pursued as potential prognostic biomarkers as well as targets for therapy in larger studies in PDAC.

  4. Serum biomarkers for the early diagnosis of TIA: The MIND-TIA study protocol.

    Science.gov (United States)

    Dolmans, L Servaas; Rutten, Frans H; El Bartelink, Marie-Louise; Seppenwoolde, Gerdien; van Delft, Sanne; Kappelle, L Jaap; Hoes, Arno W

    2015-07-28

    A Transient Ischaemic Attack (TIA) bears a high risk of a subsequent ischaemic stroke. Adequate diagnosis of a TIA should be followed immediately by the start of appropriate preventive therapy, including antiplatelets. The diagnosis of a TIA based on symptoms and signs only is notoriously difficult and biomarkers of brain ischaemia might improve the recognition, and target management and prognosis of TIA patients. Our aim is to quantify the added diagnostic value of serum biomarkers of brain ischaemia in patients suspected of TIA. a cross-sectional diagnostic accuracy study with an additional six month follow-up period. 350 patients suspected of TIA in the primary care setting. Patients suspected of a TIA will be recruited by at least 200 general practitioners (GPs) in the catchment area of seven TIA outpatient clinics willing to participate in the study. In all patients a blood sample will be drawn as soon as possible after the patient has contacted the GP, but at least within 72 h after onset of symptoms. Participants will be referred by the GP to the regional TIA outpatient clinic for additional investigations, including brain imaging. The 'definite' diagnosis (reference standard) will be made by a panel consisting of three experienced neurologists who will use all available diagnostic information and the clinical information obtained during the outpatient clinic assessment, and a six month follow-up period. The diagnostic accuracy, and value in addition to signs and symptoms of candidate serum biomarkers will be assessed in terms of discrimination with C statistics, and calibration with plots. We aim to include 350 suspected cases, with 250 patients with indeed definite TIA (or minor stroke) according to the panel. We hope to find novel biomarkers that will enable a rapid and accurate diagnosis of TIA. This would largely improve the management and prognosis of such patients. ClinicalTrials.gov Identifier NCT01954329.

  5. Biomarkers for acute kidney injury in decompensated cirrhosis: A Prospective Study.

    Science.gov (United States)

    Jaques, David A; Spahr, Laurent; Berra, Gregory; Poffet, Vincent; Lescuyer, Pierre; Gerstel, Eric; Garin, Nicolas; Martin, Pierre-Yves; Ponte, Belen

    2018-01-25

    Acute kidney injury (AKI) is a frequent complication in cirrhotic patients. As serum creatinine is a poor marker of renal function in this population, we aimed to study the utility of several biomarkers in this context. A prospective study was conducted in hospitalized patients with decompensated cirrhosis. Serum creatinine (SCr), Cystatin C (CystC), NGAL and urinary NGAL, KIM-1, protein, albumin and sodium were measured on three separate occasions. Renal resistive index (RRI) was obtained. We analyzed the value of these biomarkers to determine the presence of AKI, its etiology [prerenal, acute tubular necrosis (ATN), or hepatorenal (HRS)], its severity and a composite clinical outcome at 30 days (death, dialysis and intensive care admission). We included 105 patients, of which 55 had AKI. SCr, CystC, NGAL (plasma and urinary), urinary sodium and RRI at inclusion were independently associated with the presence of AKI. SCr, CystC and plasma NGAL were able to predict the subsequent development of AKI. Pre-renal state showed lower levels of SCr, NGAL (plasma and urinary) and RRI. ATN patients had high levels of NGAL (plasma and urinary) as well as urinary protein and sodium. HRS patients presented an intermediate pattern. All biomarkers paralleled the severity of AKI. SCr, CystC and plasma NGAL predicted the development of the composite clinical outcome with the same performance as the MELD score. In patients with decompensated cirrhosis, early measurement of renal biomarkers provides valuable information on AKI etiology. It could also improve AKI diagnosis and prognosis. This article is protected by copyright. All rights reserved.

  6. 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

  7. Diagnostic and prognostic stratification in the emergency department using urinary biomarkers of nephron damage: a multicenter prospective cohort study.

    Science.gov (United States)

    Nickolas, Thomas L; Schmidt-Ott, Kai M; Canetta, Pietro; Forster, Catherine; Singer, Eugenia; Sise, Meghan; Elger, Antje; Maarouf, Omar; Sola-Del Valle, David Antonio; O'Rourke, Matthew; Sherman, Evan; Lee, Peter; Geara, Abdallah; Imus, Philip; Guddati, Achuta; Polland, Allison; Rahman, Wasiq; Elitok, Saban; Malik, Nasir; Giglio, James; El-Sayegh, Suzanne; Devarajan, Prasad; Hebbar, Sudarshan; Saggi, Subodh J; Hahn, Barry; Kettritz, Ralph; Luft, Friedrich C; Barasch, Jonathan

    2012-01-17

    This study aimed to determine the diagnostic and prognostic value of urinary biomarkers of intrinsic acute kidney injury (AKI) when patients were triaged in the emergency department. Intrinsic AKI is associated with nephron injury and results in poor clinical outcomes. Several urinary biomarkers have been proposed to detect and measure intrinsic AKI. In a multicenter prospective cohort study, 5 urinary biomarkers (urinary neutrophil gelatinase-associated lipocalin, kidney injury molecule-1, urinary liver-type fatty acid binding protein, urinary interleukin-18, and cystatin C) were measured in 1,635 unselected emergency department patients at the time of hospital admission. We determined whether the biomarkers diagnosed intrinsic AKI and predicted adverse outcomes during hospitalization. All biomarkers were elevated in intrinsic AKI, but urinary neutrophil gelatinase-associated lipocalin was most useful (81% specificity, 68% sensitivity at a 104-ng/ml cutoff) and predictive of the severity and duration of AKI. Intrinsic AKI was strongly associated with adverse in-hospital outcomes. Urinary neutrophil gelatinase-associated lipocalin and urinary kidney injury molecule 1 predicted a composite outcome of dialysis initiation or death during hospitalization, and both improved the net risk classification compared with conventional assessments. These biomarkers also identified a substantial subpopulation with low serum creatinine at hospital admission, but who were at risk of adverse events. Urinary biomarkers of nephron damage enable prospective diagnostic and prognostic stratification in the emergency department. Copyright © 2012 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

  8. Validation of New Cancer Biomarkers

    DEFF Research Database (Denmark)

    Duffy, Michael J; Sturgeon, Catherine M; Söletormos, Georg

    2015-01-01

    BACKGROUND: Biomarkers are playing increasingly important roles in the detection and management of patients with cancer. Despite an enormous number of publications on cancer biomarkers, few of these biomarkers are in widespread clinical use. CONTENT: In this review, we discuss the key steps...... in advancing a newly discovered cancer candidate biomarker from pilot studies to clinical application. Four main steps are necessary for a biomarker to reach the clinic: analytical validation of the biomarker assay, clinical validation of the biomarker test, demonstration of clinical value from performance...... of the biomarker test, and regulatory approval. In addition to these 4 steps, all biomarker studies should be reported in a detailed and transparent manner, using previously published checklists and guidelines. Finally, all biomarker studies relating to demonstration of clinical value should be registered before...

  9. 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.

  10. 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 <  0.0001). Exosomal tau discriminated between the groups, with 82% sensitivity, 100% specificity, 100% positive predictive value, and 53% 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.

  11. 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

  12. 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.

  13. 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.

  14. Identification of biomarkers for lung cancer in never smokers — EDRN Public Portal

    Science.gov (United States)

    The overall goal of this project is to identify, verify and apply biomarkers for the early diagnosis or risk assessment of lung cancer in never smokers. The first year will be regarded as a year of discovery. After successful demonstration of the feasibility of the approach for novel marker discovery, funding will be applied for to perform confirmation and preclinical studies on the biomarkers and validation studies (specific aims 2 and 3, to be performed in years two and three). Year two can be regarded as the year of confirmation and year three as the year of validation.

  15. 76 FR 26682 - Study on Protection of Certain Railroad Risk Reduction Data From Discovery or Use in Litigation

    Science.gov (United States)

    2011-05-09

    ...-2011-0025] Study on Protection of Certain Railroad Risk Reduction Data From Discovery or Use in... Act of 2008 (RSIA), FRA is soliciting public comment on the issue of whether it is in the public... withhold from discovery or use in litigation in a Federal or State court proceeding for damages involving...

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. QSAR studies in the discovery of novel type-II diabetic therapies.

    Science.gov (United States)

    Abuhammad, Areej; Taha, Mutasem O

    2016-01-01

    Type-II diabetes mellitus (T2DM) is a complex chronic disease that represents a major therapeutic challenge. Despite extensive efforts in T2DM drug development, therapies remain unsatisfactory. Currently, there are many novel and important antidiabetic drug targets under investigation by many research groups worldwide. One of the main challenges to develop effective orally active hypoglycemic agents is off-target effects. Computational tools have impacted drug discovery at many levels. One of the earliest methods is quantitative structure-activity relationship (QSAR) studies. QSAR strategies help medicinal chemists understand the relationship between hypoglycemic activity and molecular properties. Hence, QSAR may hold promise in guiding the synthesis of specifically designed novel ligands that demonstrate high potency and target selectivity. This review aims to provide an overview of the QSAR strategies used to model antidiabetic agents. In particular, this review focuses on drug targets that raised recent scientific interest and/or led to successful antidiabetic agents in the market. Special emphasis has been made on studies that led to the identification of novel antidiabetic scaffolds. Computer-aided molecular design and discovery techniques like QSAR have a great potential in designing leads against complex diseases such as T2DM. Combined with other in silico techniques, QSAR can provide more useful and rational insights to facilitate the discovery of novel compounds. However, since T2DM is a complex disease that includes several faulty biological targets, multi-target QSAR studies are recommended in the future to achieve efficient antidiabetic therapies.

  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. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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 ...

  7. 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

  8. 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

  9. 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

  10. Dried Blood Spot Collection of Health Biomarkers to Maximize Participation in Population Studies

    Science.gov (United States)

    Ostler, Michael W.; Porter, James H.; Buxton, Orfeu M.

    2014-01-01

    Biomarkers are directly-measured biological indicators of disease, health, exposures, or other biological information. In population and social sciences, biomarkers need to be easy to obtain, transport, and analyze. Dried Blood Spots meet this need, and can be collected in the field with high response rates. These elements are particularly important in longitudinal study designs including interventions where attrition is critical to avoid, and high response rates improve the interpretation of results. Dried Blood Spot sample collection is simple, quick, relatively painless, less invasive then venipuncture, and requires minimal field storage requirements (i.e. samples do not need to be immediately frozen and can be stored for a long period of time in a stable freezer environment before assay). The samples can be analyzed for a variety of different analytes, including cholesterol, C-reactive protein, glycosylated hemoglobin, numerous cytokines, and other analytes, as well as provide genetic material. DBS collection is depicted as employed in several recent studies. PMID:24513728

  11. 'Omics' biomarkers associated with chronic low back pain: protocol of a retrospective longitudinal study.

    Science.gov (United States)

    Allegri, Massimo; De Gregori, Manuela; Minella, Cristina E; Klersy, Catherine; Wang, Wei; Sim, Moira; Gieger, Christian; Manz, Judith; Pemberton, Iain K; MacDougall, Jane; Williams, Frances Mk; Van Zundert, Jan; Buyse, Klaas; Lauc, Gordan; Gudelj, Ivan; Primorac, Dragan; Skelin, Andrea; Aulchenko, Yurii S; Karssen, Lennart C; Kapural, Leonardo; Rauck, Richard; Fanelli, Guido

    2016-10-19

    Chronic low back pain (CLBP) produces considerable direct costs as well as indirect burdens for society, industry and health systems. CLBP is characterised by heterogeneity, inclusion of several pain syndromes, different underlying molecular pathologies and interaction with psychosocial factors that leads to a range of clinical manifestations. There is still much to understand in the underlying pathological processes and the non-psychosocial factors which account for differences in outcomes. Biomarkers that may be objectively used for diagnosis and personalised, targeted and cost-effective treatment are still lacking. Therefore, any data that may be obtained at the '-omics' level (glycomics, Activomics and genome-wide association studies-GWAS) may be helpful to use as dynamic biomarkers for elucidating CLBP pathogenesis and may ultimately provide prognostic information too. By means of a retrospective, observational, case-cohort, multicentre study, we aim to investigate new promising biomarkers potentially able to solve some of the issues related to CLBP. The study follows a two-phase, 1:2 case-control model. A total of 12 000 individuals (4000 cases and 8000 controls) will be enrolled; clinical data will be registered, with particular attention to pain characteristics and outcomes of pain treatments. Blood samples will be collected to perform -omics studies. The primary objective is to recognise genetic variants associated with CLBP; secondary objectives are to study glycomics and Activomics profiles associated with CLBP. The study is part of the PainOMICS project funded by European Community in the Seventh Framework Programme. The study has been approved from competent ethical bodies and copies of approvals were provided to the European Commission before starting the study. Results of the study will be reviewed by the Scientific Board and Ethical Committee of the PainOMICS Consortium. The scientific results will be disseminated through peer-reviewed journals

  12. New biomarkers for sepsis

    Directory of Open Access Journals (Sweden)

    Li-xin XIE

    2013-01-01

    Full Text Available There is a higher sepsis rate in the intensive care unit (ICU patients, which is one of the most important causes for patient death, but the sepsis lacks specific clinical manifestations. Exploring sensitive and specific molecular markers for infection that accurately reflect infection severity and prognosis is very clinically important. In this article, based on our previous study, we introduce some new biomarkers with high sensitivity and specificity for the diagnosis and predicting the prognosis and severity of sepsis. Increase of serum soluble(s triggering receptor expressed on myeloid cells-1 (sTREM-1 suggests a poor prognosis of septic patients, and changes of locus rs2234237 of sTREM-1 may be the one of important mechanisms. Additionally, urine sTREM-1 can provide an early warning of possible secondary acute kidney injury (AKI in sepsis patients. Serum sCD163 level was found to be a more important factor than procalcitonin (PCT and C-reactive protein (CRP in prognosis of sepsis, especially severe sepsis. Moreover, urine sCD163 also shows excellent performance in the diagnosis of sepsis and sepsis-associated AKI. Circulating microRNAs, such as miR-150, miR-297, miR-574-5p, miR -146a , miR-223, miR -15a and miR-16, also play important roles in the evaluation of status of septic patients. In the foreseeable future, newly-emerging technologies, including proteomics, metabonomics and trans-omics, may exert profound effects on the discovery of valuable biomarkers for sepsis.

  13. Biomarker Detection in Association Studies: Modeling SNPs Simultaneously via Logistic ANOVA

    KAUST Repository

    Jung, Yoonsuh; Huang, Jianhua Z.; Hu, Jianhua

    2014-01-01

    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.

  14. 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.

  15. 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.

  16. 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)

  17. 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

  18. Ethics and data protection in human biomarker studies in environmental health.

    Science.gov (United States)

    Casteleyn, Ludwine; Dumez, Birgit; Van Damme, Karel; Anwar, Wagida A

    2013-08-01

    Human biomarker studies in environmental health are essential tools to study the relationship between health and environment. They should ultimately contribute to a better understanding of environmentally induced adverse health effects and to appropriate preventive actions. To ensure the protection of the rights and dignity of study participants a complex legal and ethical framework is applied, consisting of several international directives, conventions, and guidelines, whether or not translated in domestic laws. Main characteristics of ethics and data protection in studies using biomarkers in the field of environmental health are summarized and current discussions on related questions and bottlenecks highlighted. In the current regulatory context, dominated by the protection of the individual study participant, difficulties are reported due to the different interpretation and implementation of the regulations of concern within and across borders. Advancement of consistency and compatibility is recommended and efforts are ongoing. An increasing demand for secondary use of data and samples poses additional challenges in finding a right balance between the individual rights of the study participants on the one hand and the common interest of, and potential benefit for the public or community at large on the other. Ethics committees could play a key role in assessing problems originating from the sometimes competing needs at individual and societal level. Building trust in science amongst (potential) study participants and within the community allows the inclusion of arguments from the societal perspective. This requires increased attention for respectful communication efforts. Striving for public participation in decision making processes may promote policy relevant research and the related translation of study results into action. Copyright © 2013 Elsevier GmbH. All rights reserved.

  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. The study of protein biomarkers to understand the biochemical processes underlying beef color development in young bulls.

    Science.gov (United States)

    Gagaoua, Mohammed; Terlouw, E M Claudia; Picard, Brigitte

    2017-12-01

    This study investigates relationships between 21 biomarkers and meat color traits of Longissimus thoracis muscles of young Aberdeen Angus and Limousin bulls. The relationships found allowed to propose metabolic processes underlying meat color. The color coordinates were related with several biomarkers. The relationships were in some cases breed-dependent and the variability explained in the regression models varied between 31 and 56%. The correlations between biomarkers and color parameters were sometimes opposite between breeds. The PCA using the 21 biomarkers and the instrumental color coordinates showed that these variables discriminated efficiently between the two studied breeds. Results are coherent with earlier studies on other beef breeds showing that several proteins belonging to different but partly related biological pathways involved in muscle contraction, metabolism, heat stress and apoptosis are related to beef color. The results suggest that in future, biomarkers may be used to classify meat cuts sampled early post-mortem according to their forthcoming color. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Mitochondrial Biomarkers Reflect Semen Quality: Results from the MARCHS Study in Chongqing, China.

    Science.gov (United States)

    Zhang, Guowei; Wang, Zhi; Ling, Xi; Zou, Peng; Yang, Huan; Chen, Qing; Zhou, Niya; Sun, Lei; Gao, Jianfang; Zhou, Ziyuan; Cao, Jia; Ao, Lin

    2016-01-01

    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, psemen quality in a general population, and the study provides a baseline for the effects of population characteristics and lifestyles on such mitochondrial markers.

  2. 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

    Introduction: Chronic Obstructive Pulmonary Disease (COPD) is a common chronic disease primarily treated in primary care. It is a complex and heterogeneous disease and the trajectory is difficult to predict. The overall aim of this study is to investigate predictors of the trajectory of COPD...... 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...... 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...

  3. 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.

  4. Implementation of proteomic biomarkers: making it work

    Science.gov (United States)

    Mischak, Harald; Ioannidis, John PA; 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

    2012-01-01

    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. PMID:22519700

  5. Alterations in inflammatory biomarkers and energy intake in cancer cachexia: a prospective study in patients with inoperable pancreatic cancer.

    Science.gov (United States)

    Bye, Asta; Wesseltoft-Rao, Nima; Iversen, Per Ole; Skjegstad, Grete; Holven, Kirsten B; Ulven, Stine; Hjermstad, Marianne J

    2016-06-01

    Chronic systemic inflammatory response is proposed as an underlying mechanism for development of cancer cachexia. We conducted a prospective study to examine changes in inflammatory biomarkers during the disease course and the relationship between inflammatory biomarkers and cachexia in patients with inoperable pancreatic cancer. Twenty patients, median (range) age 67.5 (35-79) years, 5 females, were followed for median 5.5 (1-12) months. Cachexia was diagnosed according to the 2011 consensus-based classification system (weight loss >5 % past six months, BMI 2 %, or sarcopenia) and the modified Glasgow Prognostic score (mGPS) that combines CRP and albumin levels. Inflammatory biomarkers were measured by enzyme immunoassays. The patients had increased levels of most inflammatory biomarkers, albeit not all statistically significant, both at study entry and close to death, indicating ongoing inflammation. According to the consensus-based classification system, eleven (55 %) patients were classified as cachectic upon inclusion. They did not differ from non-cachectic patients with regard to inflammatory biomarkers or energy intake. According to the mGPS, seven (35 %) were defined as cachectic and had a higher IL-6 (p cachexia.

  6. The utility of biomarkers in hepatocellular carcinoma: review of urine-based 1H-NMR studies – what the clinician needs to know

    Directory of Open Access Journals (Sweden)

    Cartlidge CR

    2017-11-01

    Full Text Available Caroline R Cartlidge,1 M R Abellona U,2 Alzhraa M A Alkhatib,2 Simon D Taylor-Robinson1 1Department of Surgery and Cancer, Liver Unit, Division of Digestive Health, 2Department of Surgery and Cancer, Division of Computational and Systems Medicine, Faculty of Medicine, Imperial College London, London, UK Abstract: Hepatocellular carcinoma (HCC is the fifth most common malignancy, the third most common cause of cancer death, and the most common primary liver cancer. Overall, there is a need for more reliable biomarkers for HCC, as those currently available lack sensitivity and specificity. For example, the current gold-standard biomarker, serum alpha-fetoprotein, has a sensitivity of roughly only 70%. Cancer cells have different characteristic metabolic signatures in biofluids, compared to healthy cells; therefore, metabolite analysis in blood or urine should lead to the detection of suitable candidates for the detection of HCC. With the advent of metabonomics, this has increased the potential for new biomarker discovery. In this article, we look at approaches used to identify biomarkers of HCC using proton nuclear magnetic resonance (1H-NMR spectroscopy of urine samples. The various multivariate statistical analysis techniques used are explained, and the process of biomarker identification is discussed, with a view to simplifying the knowledge base for the average clinician. Keywords: hepatocellular carcinoma, biomarkers, metabonomics, urine, proton nuclear magnetic resonance spectroscopy, 1H-NMR 

  7. Serum Sclerostin as a Possible Biomarker in Ankylosing Spondylitis: A Case-Control Study

    Directory of Open Access Journals (Sweden)

    Fabio Massimo Perrotta

    2018-01-01

    Full Text Available Objective. Several molecules are involved in the pathogenesis of a new bone formation in ankylosing spondylitis (AS. The aim of this study was to evaluate the serum levels of sclerostin in patients with AS as a possible biomarker and to investigate any correlations with radiographic damage, disease activity, and function. Methods. AS patients fulfilled the modified New York criteria, and healthy controls were enrolled for this study. BASDAI, ASDAS-CRP, BASMI, BASFI, patient and physician VAS, and C-reactive protein were evaluated at baseline visit. Spinal damage was assessed using the mSASSS on radiographs performed within 3 months from baseline. Serum concentrations of sclerostin were assessed at baseline and after four months of therapy in patients who started an anti-TNF. Results. Twenty healthy subjects and 40 AS patients were enrolled in the study. In our group, serum sclerostin levels (median (25th–75th percentile were significantly higher in healthy controls (18.04 (13.6–24 pg/ml than in AS patients (6.46 (4.5–11.1 pg/ml; P value < 0.01. However, no significant correlations were found between serum sclerostin levels and radiographic damage, assessed by mSASSS, and between serum sclerostin levels and clinical indices of activity and disability or with laboratory parameters. Sclerostin levels did not show significant changes after 4 months of anti-TNF therapy. Conclusions. The results of our study suggest a possible role of sclerostin in the identification of AS patients. Further studies are needed to prove the role of sclerostin as a disease activity biomarker and progression of disease in AS.

  8. 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

    patients on chronic hemodialysis versus controls (Ziegelmeier et al., 2007). This study indicates that RBP4 levels correlate with c- reactive protein in...kidney injury, as well as cancer, rheumatoid arthritis , viral infections, and other chronic inflammatory diseases (Beorchia et al., 1981; Schuster...increase in plasma in dialysis patients , thought to be caused by an inflammatory response stimulated in the kidney due to interactions with hemodialysis

  9. Discovery and prevalidation of salivary extracellular microRNA biomarkers panel for the noninvasive detection of benign and malignant parotid gland tumors

    NARCIS (Netherlands)

    Matse, J.H.; Yoshizawa, J.; Wang, X.; Elashoff, D.; Bolscher, J.G.M.; Veerman, E.C.I.; Bloemena, E.; Wong, D.T.W.

    2013-01-01

    Purpose: This study was conducted to explore the differences in salivary microRNA (miRNA) profiles between patients with malignant or benign parotid gland tumors as a potential preoperative diagnostic tool of tumors in the salivary glands. Experimental Design: Whole saliva samples from patients with

  10. 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.

  11. Blood arsenic as a biomarker of arsenic exposure: Results from a prospective study

    International Nuclear Information System (INIS)

    Hall, Marni; Chen Yu; Ahsan, Habibul; Slavkovich, Vesna; Geen, Alexander van; Parvez, Faruque; Graziano, Joseph

    2006-01-01

    Exposure to arsenic (As)-contaminated drinking water affects millions of people worldwide. Arsenic exposure is associated with skin lesions, skin, lung, kidney and liver cancers, neurologic and cardiovascular effects. Past studies involving biomarkers of As exposure have typically examined urinary As (UAs) (adjusted for urinary creatinine), hair or toenail As, but not blood As (BAs) since blood concentrations are exceedingly low and are not detectable by conventional atomic absorption spectrophotometric techniques. In a case-cohort analysis of 303 newly diagnosed cases of skin lesions, and 849 subcohort members randomly selected from 8092 participants in the health effects of as longitudinal study (HEALS) in Araihazar, Bangladesh, we measured blood, urine and water As concentrations, and examined their associations with each other, and with the risk for skin lesions. BAs concentrations were highly correlated with creatinine-adjusted UAs concentrations (r = 0.85) and with water As (WAs) (r = 0.75). We observed consistent dose-response relationships between the risk of skin lesions and all the measures of As exposure. Rate ratios (RRs) for skin lesions by quintile of As exposure, adjusted for age and gender, revealed that the two highest quintiles were significantly related to an increased risk of skin lesions for each measure of exposure: BAs, UAs, WAs and a time-weighted water As variable. This prospective study confirms the increased risk of skin lesions in relation to As concentrations in blood, urine and water and also establishes that BAs is a useful biomarker of As exposure in this study population

  12. 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.

  13. The implementation of discovery learning model based on lesson study to increase student's achievement in colloid

    Science.gov (United States)

    Suyanti, Retno Dwi; Purba, Deby Monika

    2017-03-01

    The objectives of this research are to get the increase student's achievement on the discovery learning model based on lesson study. Beside of that, this research also conducted to know the cognitive aspect. This research was done in three school that are SMA N 3 Medan. Population is all the students in SMA N 11 Medan which taken by purposive random sampling. The research instruments are achievement test instruments that have been validated. The research data analyzed by statistic using Ms Excell. The result data shows that the student's achievement taught by discovery learning model based on Lesson study higher than the student's achievement taught by direct instructional method. It can be seen from the average of gain and also proved with t-test, the normalized gain in experimental class of SMA N 11 is (0.74±0.12) and control class (0.45±0.12), at significant level α = 0.05, Ha is received and Ho is refused where tcount>ttable in SMA N 11 (9.81>1,66). Then get the improvement cognitive aspect from three of school is C2 where SMA N 11 is 0.84(high). Then the observation sheet result of lesson study from SMA N 11 92 % of student working together while 67% less in active using media.

  14. Risk stratification after paracetamol overdose using mechanistic biomarkers: results from two prospective cohort studies.

    Science.gov (United States)

    Dear, James W; Clarke, Joanna I; Francis, Ben; Allen, Lowri; Wraight, Jonathan; Shen, Jasmine; Dargan, Paul I; Wood, David; Cooper, Jamie; Thomas, Simon H L; Jorgensen, Andrea L; Pirmohamed, Munir; Park, B Kevin; Antoine, Daniel J

    2018-02-01

    Paracetamol overdose is common but patient stratification is suboptimal. We investigated the usefulness of new biomarkers that have either enhanced liver specificity (microRNA-122 [miR-122]) or provide mechanistic insights (keratin-18 [K18], high mobility group box-1 [HMGB1], and glutamate dehydrogenase [GLDH]). The use of these biomarkers could help stratify patients for their risk of liver injury at hospital presentation. Using data from two prospective cohort studies, we assessed the potential for biomarkers to stratify patients who overdose with paracetamol. We completed two independent prospective studies: a derivation study (MAPP) in eight UK hospitals and a validation study (BIOPAR) in ten UK hospitals. Patients in both cohorts were adults (≥18 years in England, ≥16 years in Scotland), were diagnosed with paracetamol overdose, and gave written informed consent. Patients who needed intravenous acetylcysteine treatment for paracetamol overdose had circulating biomarkers measured at hospital presentation. The primary endpoint was acute liver injury indicating need for continued acetylcysteine treatment beyond the standard course (alanine aminotransferase [ALT] activity >100 U/L). Receiver operating characteristic (ROC) curves, category-free net reclassification index (cfNRI), and integrated discrimination index (IDI) were applied to assess endpoint prediction. Between June 2, 2010, and May 29, 2014, 1187 patients who required acetylcysteine treatment for paracetamol overdose were recruited (985 in the MAPP cohort; 202 in the BIOPAR cohort). In the derivation and validation cohorts, acute liver injury was predicted at hospital presentation by miR-122 (derivation cohort ROC-area under the curve [AUC] 0·97 [95% CI 0·95-0·98]), HMGB1 (0·95 [0·93-0·98]), and full-length K18 (0·95 [0·92-0·97]). Results were similar in the validation cohort (miR-122 AUC 0·97 [95% CI 0·95-0·99], HMGB1 0·98 [0·96-0·99], and full-length K18 0·93 [0·86-0·99]). A

  15. 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

    -rich plasma, in which the wide dynamic range of the native protein complement hinders classical proteomic investigations. We employed an ex vivo rabbit model of myocardial ischemia/reperfusion (I/R) injury using Langendorff buffer perfusion. Nonrecirculating perfusate was collected over a temporal profile...... 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...... release using ex vivo buffer perfused tissue to limit the presence of obfuscating plasma proteins may identify candidates for further study in humans....

  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. Identification of biomarkers for intake of protein from meat, dairy products and grains: A controlled dietary intervention study

    NARCIS (Netherlands)

    Altorf-van der Kuil, W.; Brink, E.J.; Boetje, M.; Siebelink, E.; Bijlsma, S.; Engberink, M.F.; Veer, P.V.'.; Tomé, D.; Bakker, S.J.L.; Baak, M.A. van; Geleijnse, J.M.

    2013-01-01

    In the present controlled, randomised, multiple cross-over dietary intervention study, we aimed to identify potential biomarkers for dietary protein from dairy products, meat and grain, which could be useful to estimate intake of these protein types in epidemiological studies. After 9 d run-in,

  19. Identification of biomarkers for intake of protein from meat, dairy products and grains : a controlled dietary intervention study

    NARCIS (Netherlands)

    Altorf-van der Kuil, Wieke; Brink, Elizabeth J.; Boetje, Martine; Siebelink, Els; Bijlsma, Sabina; Engberink, Marielle F.; van 't Veer, Pieter; Tome, Daniel; Bakker, Stephan J. L.; van Baak, Marleen A.; Geleijnse, Johanna M.

    2013-01-01

    In the present controlled, randomised, multiple cross-over dietary intervention study, we aimed to identify potential biomarkers for dietary protein from dairy products, meat and grain, which could be useful to estimate intake of these protein types in epidemiological studies. After 9 d run-in,

  20. 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.

  1. [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.

  2. 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.

  3. Tumor antigens as proteogenomic biomarkers in invasive ductal carcinomas

    DEFF Research Database (Denmark)

    Olsen, Lars Rønn; Campos, Benito; Winther, Ole

    2014-01-01

    directly linked to the hallmarks of cancer. The results found by proteogenomic analysis of the 32 tumor antigens studied here, capture largely the same pathway irregularities as those elucidated from large-scale screening of genomics analyses, where several thousands of genes are often found......Background: The majority of genetic biomarkers for human cancers are defined by statistical screening of high-throughput genomics data. While a large number of genetic biomarkers have been proposed for diagnostic and prognostic applications, only a small number have been applied in the clinic....... Similarly, the use of proteomics methods for the discovery of cancer biomarkers is increasing. The emerging field of proteogenomics seeks to enrich the value of genomics and proteomics approaches by studying the intersection of genomics and proteomics data. This task is challenging due to the complex nature...

  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. Biomarkers in Autism

    Directory of Open Access Journals (Sweden)

    Robert eHendren

    2014-08-01

    Full Text Available Autism spectrum disorders (ASD are complex, heterogeneous disorders caused by an interaction between genetic vulnerability and environmental factors. In an effort to better target the underlying roots of ASD for diagnosis and treatment, efforts to identify reliable biomarkers in genetics, neuroimaging, gene expression and measures of the body’s metabolism are growing. For this article, we review the published studies of potential biomarkers in autism and conclude that while there is increasing promise of finding biomarkers that can help us target treatment, there are none with enough evidence to support routine clinical use unless medical illness is suspected. Promising biomarkers include those for mitochondrial function, oxidative stress, and immune function. Genetic clusters are also suggesting the potential for useful biomarkers.

  7. 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 .

  8. Short-Term Exposure to Air Pollution and Biomarkers of Oxidative Stress: The Framingham Heart Study.

    Science.gov (United States)

    Li, Wenyuan; Wilker, Elissa H; Dorans, Kirsten S; Rice, Mary B; Schwartz, Joel; Coull, Brent A; Koutrakis, Petros; Gold, Diane R; Keaney, John F; Lin, Honghuang; Vasan, Ramachandran S; Benjamin, Emelia J; Mittleman, Murray A

    2016-04-28

    Short-term exposure to elevated air pollution has been associated with higher risk of acute cardiovascular diseases, with systemic oxidative stress induced by air pollution hypothesized as an important underlying mechanism. However, few community-based studies have assessed this association. Two thousand thirty-five Framingham Offspring Cohort participants living within 50 km of the Harvard Boston Supersite who were not current smokers were included. We assessed circulating biomarkers of oxidative stress including blood myeloperoxidase at the seventh examination (1998-2001) and urinary creatinine-indexed 8-epi-prostaglandin F2α (8-epi-PGF2α) at the seventh and eighth (2005-2008) examinations. We measured fine particulate matter (PM2.5), black carbon, sulfate, nitrogen oxides, and ozone at the Supersite and calculated 1-, 2-, 3-, 5-, and 7-day moving averages of each pollutant. Measured myeloperoxidase and 8-epi-PGF2α were loge transformed. We used linear regression models and linear mixed-effects models with random intercepts for myeloperoxidase and indexed 8-epi-PGF2α, respectively. Models were adjusted for demographic variables, individual- and area-level measures of socioeconomic position, clinical and lifestyle factors, weather, and temporal trend. We found positive associations of PM2.5 and black carbon with myeloperoxidase across multiple moving averages. Additionally, 2- to 7-day moving averages of PM2.5 and sulfate were consistently positively associated with 8-epi-PGF2α. Stronger positive associations of black carbon and sulfate with myeloperoxidase were observed among participants with diabetes than in those without. Our community-based investigation supports an association of select markers of ambient air pollution with circulating biomarkers of oxidative stress. © 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

  9. Novel Stool-Based Protein Biomarkers for Improved Colorectal Cancer Screening: A Case-Control Study.

    Science.gov (United States)

    Bosch, Linda J W; de Wit, Meike; Pham, Thang V; Coupé, Veerle M H; Hiemstra, Annemieke C; Piersma, Sander R; Oudgenoeg, Gideon; Scheffer, George L; Mongera, Sandra; Sive Droste, Jochim Terhaar; Oort, Frank A; van Turenhout, Sietze T; Larbi, Ilhame Ben; Louwagie, Joost; van Criekinge, Wim; van der Hulst, Rene W M; Mulder, Chris J J; Carvalho, Beatriz; Fijneman, Remond J A; Jimenez, Connie R; Meijer, Gerrit A

    2017-12-19

    The fecal immunochemical test (FIT) for detecting hemoglobin is used widely for noninvasive colorectal cancer (CRC) screening, but its sensitivity leaves room for improvement. To identify novel protein biomarkers in stool that outperform or complement hemoglobin in detecting CRC and advanced adenomas. Case-control study. Colonoscopy-controlled referral population from several centers. 315 stool samples from one series of 12 patients with CRC and 10 persons without colorectal neoplasia (control samples) and a second series of 81 patients with CRC, 40 with advanced adenomas, and 43 with nonadvanced adenomas, as well as 129 persons without colorectal neoplasia (control samples); 72 FIT samples from a third independent series of 14 patients with CRC, 16 with advanced adenomas, and 18 with nonadvanced adenomas, as well as 24 persons without colorectal neoplasia (control samples). Stool samples were analyzed by mass spectrometry. Classification and regression tree (CART) analysis and logistic regression analyses were performed to identify protein combinations that differentiated CRC or advanced adenoma from control samples. Antibody-based assays for 4 selected proteins were done on FIT samples. In total, 834 human proteins were identified, 29 of which were statistically significantly enriched in CRC versus control stool samples in both series. Combinations of 4 proteins reached sensitivities of 80% and 45% for detecting CRC and advanced adenomas, respectively, at 95% specificity, which was higher than that of hemoglobin alone (P control samples (P control samples. Proof of concept that such proteins can be detected with antibody-based assays in small sample volumes indicates the potential of these biomarkers to be applied in population screening. Center for Translational Molecular Medicine, International Translational Cancer Research Dream Team, Stand Up to Cancer (American Association for Cancer Research and the Dutch Cancer Society), Dutch Digestive Foundation, and VU

  10. Discovery, detection and use of biomarkers

    Science.gov (United States)

    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.

  11. 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

  12. 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

  13. 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....

  14. Biomarker Qualification: Toward a Multiple Stakeholder Framework for Biomarker Development, Regulatory Acceptance, and Utilization.

    Science.gov (United States)

    Amur, S; LaVange, L; Zineh, I; Buckman-Garner, S; Woodcock, J

    2015-07-01

    The discovery, development, and use of biomarkers for a variety of drug development purposes are areas of tremendous interest and need. Biomarkers can become accepted for use through submission of biomarker data during the drug approval process. Another emerging pathway for acceptance of biomarkers is via the biomarker qualification program developed by the Center for Drug Evaluation and Research (CDER, US Food and Drug Administration). Evidentiary standards are needed to develop and evaluate various types of biomarkers for their intended use and multiple stakeholders, including academia, industry, government, and consortia must work together to help develop this evidence. The article describes various types of biomarkers that can be useful in drug development and evidentiary considerations that are important for qualification. A path forward for coordinating efforts to identify and explore needed biomarkers is proposed for consideration. © 2015 American Society for Clinical Pharmacology and Therapeutics.

  15. A study of the discovery process in 802.11 networks

    OpenAIRE

    Castignani , German; Arcia Moret , Andres Emilio; Montavont , Nicolas

    2011-01-01

    International audience; Today wireless communications are a synonym of mobility and resource sharing. These characteristics, proper of both infrastructure and ad-hoc networks, heavily relies on a general resource discovery process. The discovery process, being an unavoidable procedure, has to be fast and reliable to mitigate the effect of network disruptions. In this article, by means of simulations and a real testbed, our contribution is twofold. First we assess the discovery process focusin...

  16. 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

  17. 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

    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...

  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. 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...

  20. Biomarkers kinetics in the assessment of ventilator-associated pneumonia response to antibiotics - results from the BioVAP study

    NARCIS (Netherlands)

    Póvoa, Pedro; Martin-Loeches, Ignacio; Ramirez, Paula; Bos, Lieuwe D.; Esperatti, Mariano; Silvestre, Joana; Gili, Gisela; Goma, Gemma; Berlanga, Eugenio; Espasa, Mateu; Gonçalves, Elsa; Torres, Antoni; Artigas, Antonio

    2017-01-01

    Purpose: Our aim was to evaluate the role of biomarker kinetics in the assessment of ventilator-associated pneumonia (VAP) response to antibiotics. Materials and methods: We performed a prospective, multicenter, observational study to evaluate in 37 microbiologically documented VAP, the kinetics of

  1. 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...

  2. Biomarkers of Dairy Fatty Acids and Risk of Cardiovascular Disease in the Multi-Ethnic Study of Atherosclerosis

    NARCIS (Netherlands)

    Oliveira Otto, de M.C.; Nettleton, J.A.; Lemaitre, R.N.; Steffen, L.M.; Kromhout, D.; Rich, R.L.; Tsai, M.Y.; Jacobs, D.R.; Mozaffarian, D.

    2013-01-01

    Background Evidence regarding the role of dairy fat intake in cardiovascular disease (CVD) has been mixed and inconclusive. Most earlier studies have used self-reported measures of dietary intake and focused on relatively racially homogeneous populations. Circulating biomarkers of dairy fat in a

  3. 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.

  4. Discovery of early-stage biomarkers for diabetic kidney disease using ms-based metabolomics (FinnDiane study)

    NARCIS (Netherlands)

    Kloet, F.M. van der; Tempels, F.W.A.; Ismail, N.; Heijden, R. van der; Kasper, P.T.; Rojas-Cherto, M.; Doorn, R. van; Spijksma, G.; Koek, M.; Greef, J. van der; Mäkinen, V.P.; Forsblom, C.; Holthöfer, H.; Groop, P.H.; Reijmers, T.H.; Hankemeier, T.

    2012-01-01

    Diabetic kidney disease (DKD) is a devastating complication that affects an estimated third of patients with type 1 diabetes mellitus (DM). There is no cure once the disease is diagnosed, but early treatment at a sub-clinical stage can prevent or at least halt the progression. DKD is clinically

  5. 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.

  6. Validation of biomarkers for the study of environmental carcinogens: a review

    DEFF Research Database (Denmark)

    Gallo, Valentina; Khan, Aneire; Gonzales, Carlos

    2008-01-01

    There is a need for validation of biomarkers. Our aim is to review published work on the validation of selected biomarkers: bulky DNA adducts, N-nitroso compounds, 1-hydroxypyrene, and oxidative damage to DNA. A systematic literature search in PubMed was performed. Information on the variability...... and reliability of the laboratory tests used for biomarkers measurements was collected. For the evaluation of the evidence on validation we referred to the ACCE criteria. Little is known about intraindividual variation of DNA adduct measurements, but measurements have a good repeatability irrespective...... of the technique used for their identification; reproducibility improved after the correction for a laboratory factor. A high-sensitivity method is available for the measurement of 1-hydroxypyrene in urine. There is consensus on validation of biomarkers of oxidative damage DNA based on the comet assay...

  7. 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

    , 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...... biomarker research. A checklist of items integrating the results of other published guidances, literature, conferences, regulatory opinion, and personal expertise was created to ultimately form a structured summary guidance incorporating the key features. RESULTS: The summary guidance is comprised of a 10......-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...

  8. Household air pollution: a call for studies into biomarkers of exposure and predictors of respiratory disease.

    Science.gov (United States)

    Rylance, Jamie; Gordon, Stephen B; Naeher, Luke P; Patel, Archana; Balmes, John R; Adetona, Olorunfemi; Rogalsky, Derek K; Martin, William J

    2013-05-01

    Household air pollution (HAP) from indoor burning of biomass or coal is a leading global cause of morbidity and mortality, mostly due to its association with acute respiratory infection in children and chronic respiratory and cardiovascular diseases in adults. Interventions that have significantly reduced exposure to HAP improve health outcomes and may reduce mortality. However, we lack robust, specific, and field-ready biomarkers to identify populations at greatest risk and to monitor the effectiveness of interventions. New scientific approaches are urgently needed to develop biomarkers of human exposure that accurately reflect exposure or effect. In this Perspective, we describe the global need for such biomarkers, the aims of biomarker development, and the state of development of tests that have the potential for rapid transition from laboratory bench to field use.

  9. Traumatic brain injury produced by exposure to blasts, a critical problem in current wars: biomarkers, clinical studies, and animal models

    Science.gov (United States)

    Dixon, C. Edward

    2011-06-01

    Traumatic brain injury (TBI) resulting from exposure to blast energy released by Improvised Explosive Devices (IEDs) has been recognized as the "signature injury" of Operation Iraqi Freedom and Operation Enduring Freedom. Repeated exposure to mild blasts may produce subtle deficits that are difficult to detect and quantify. Several techniques have been used to detect subtle brain dysfunction including neuropsychological assessments, computerized function testing and neuroimaging. Another approach is based on measurement of biologic substances (e.g. proteins) that are released into the body after a TBI. Recent studies measuring biomarkers in CSF and serum from patients with severe TBI have demonstrated the diagnostic, prognostic, and monitoring potential. Advancement of the field will require 1) biochemical mining for new biomarker candidates, 2) clinical validation of utility, 3) technical advances for more sensitive, portable detectors, 4) novel statistical approach to evaluate multiple biomarkers, and 5) commercialization. Animal models have been developed to simulate elements of blast-relevant TBI including gas-driven shock tubes to generate pressure waves similar to those produced by explosives. These models can reproduce hallmark clinical neuropathological responses such as neuronal degeneration and inflammation, as well as behavioral impairments. An important application of these models is to screen novel therapies and conduct proteomic, genomic, and lipodomic studies to mine for new biomarker candidates specific to blast relevant TBI.

  10. 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.

  11. Systems-based biological concordance and predictive reproducibility of gene set discovery methods in cardiovascular disease.

    Science.gov (United States)

    Azuaje, Francisco; Zheng, Huiru; Camargo, Anyela; Wang, Haiying

    2011-08-01

    The discovery of novel disease biomarkers is a crucial challenge for translational bioinformatics. Demonstration of both their classification power and reproducibility across independent datasets are essential requirements to assess their potential clinical relevance. Small datasets and multiplicity of putative biomarker sets may explain lack of predictive reproducibility. Studies based on pathway-driven discovery approaches have suggested that, despite such discrepancies, the resulting putative biomarkers tend to be implicated in common biological processes. Investigations of this problem have been mainly focused on datasets derived from cancer research. We investigated the predictive and functional concordance of five methods for discovering putative biomarkers in four independently-generated datasets from the cardiovascular disease domain. A diversity of biosignatures was identified by the different methods. However, we found strong biological process concordance between them, especially in the case of methods based on gene set analysis. With a few exceptions, we observed lack of classification reproducibility using independent datasets. Partial overlaps between our putative sets of biomarkers and the primary studies exist. Despite the observed limitations, pathway-driven or gene set analysis can predict potentially novel biomarkers and can jointly point to biomedically-relevant underlying molecular mechanisms. Copyright © 2011 Elsevier Inc. All rights reserved.

  12. 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.

  13. Elastin: a possible genetic biomarker for more severe ligament injuries in elite soccer. A pilot study

    Science.gov (United States)

    Artells, Rosa; Pruna, Ricard; Dellal, Alexandre; Maffulli, Nicola

    2016-01-01

    Summary Background The study of new genetic biomarkers in genes related to connective tissue repair and regeneration may help to identify individuals with greater predisposition to injury, who may benefit from targeted preventive measures, and those who require longer recovery time following a muscle, ligament or tendon injury. The present study investigated whether single nucleotide polymorphisms of the Elastin gene could be related to MCL injury. Methods 60 top class football players were studied to identify single nucleotide polymorphisms for the Elastin (ELN) gene using Allelic Discrimination analysis. Each player was followed for 7 seasons, and each MCL injury was noted. Results Ligament injury rate, severity and recovery time are related to specific genotypes observed in the elastin gene, especially the ELN-AA (16 MCL) and the ELN-AG (3 MCL). Players with the ELN-GG genotype sustained no MCL injury during the 7 seasons of the study. Conclusions The identification of polymorphisms in the ELN gene may be used as a novel tool to better define an athlete’s genotype, and help to plan training and rehabilitation programmes to prevent or minimize MCL ligament injuries, and optimize the therapeutic and rehabilitation process after soft tissue injuries, and manage the workloads during trainings and matches. PMID:27900291

  14. Evaluation of miR-122 as a Serum Biomarker for Hepatotoxicity in Investigative Rat Toxicology Studies.

    Science.gov (United States)

    Sharapova, T; Devanarayan, V; LeRoy, B; Liguori, M J; Blomme, E; Buck, W; Maher, J

    2016-01-01

    MicroRNAs are short noncoding RNAs involved in regulation of gene expression. Certain microRNAs, including miR-122, seem to have ideal properties as biomarkers due to good stability, high tissue specificity, and ease of detection across multiple species. Recent reports have indicated that miR-122 is a highly liver-specific marker detectable in serum after liver injury. The purpose of the current study was to assess the performance of miR-122 as a serum biomarker for hepatotoxicity in short-term (5-28 days) repeat-dose rat toxicology studies when benchmarked against routine clinical chemistry and histopathology. A total of 23 studies with multiple dose levels of experimental compounds were examined, and they included animals with or without liver injury and with various hepatic histopathologic changes. Serum miR-122 levels were quantified by reverse transcription quantitative polymerase chain reaction. Increases in circulating miR-122 levels highly correlated with serum elevations of liver enzymes, such as alanine aminotransferase (ALT), aspartate aminotransferase (AST) and glutamate dehydrogenase (GLDH). Statistical analysis showed that miR-122 outperformed ALT as a biomarker for histopathologically confirmed liver toxicity and was equivalent in performance to AST and GLDH. Additionally, an increase of 4% in predictive accuracy was obtained using a multiparameter approach incorporating miR-122 with ALT, AST, and GLDH. In conclusion, serum miR-122 levels can be utilized as a biomarker of hepatotoxicity in acute and subacute rat toxicology studies, and its performance can rival or exceed those of standard enzyme biomarkers such as the liver transaminases. © The Author(s) 2015.

  15. 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.

  16. 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.

  17. A tool to facilitate clinical biomarker studies - a tissue dictionary based on the Human Protein Atlas

    Directory of Open Access Journals (Sweden)

    Kampf Caroline

    2012-09-01

    Full Text Available Abstract The complexity of tissue and the alterations that distinguish normal from cancer remain a challenge for translating results from tumor biological studies into clinical medicine. This has generated an unmet need to exploit the findings from studies based on cell lines and model organisms to develop, validate and clinically apply novel diagnostic, prognostic and treatment predictive markers. As one step to meet this challenge, the Human Protein Atlas project has been set up to produce antibodies towards human protein targets corresponding to all human protein coding genes and to map protein expression in normal human tissues, cancer and cells. Here, we present a dictionary based on microscopy images created as an amendment to the Human Protein Atlas. The aim of the dictionary is to facilitate the interpretation and use of the image-based data available in the Human Protein Atlas, but also to serve as a tool for training and understanding tissue histology, pathology and cell biology. The dictionary contains three main parts, normal tissues, cancer tissues and cells, and is based on high-resolution images at different magnifications of full tissue sections stained with H & E. The cell atlas is centered on immunofluorescence and confocal microscopy images, using different color channels to highlight the organelle structure of a cell. Here, we explain how this dictionary can be used as a tool to aid clinicians and scientists in understanding the use of tissue histology and cancer pathology in diagnostics and biomarker studies.

  18. Biomarkers of Pediatric Brain Tumors

    Directory of Open Access Journals (Sweden)

    Mark D Russell

    2013-03-01

    Full Text Available Background and Need for Novel Biomarkers: Brain tumors are the leading cause of death by solid tumors in children. Although improvements have been made in their radiological detection and treatment, our capacity to promptly diagnose pediatric brain tumors in their early stages remains limited. This contrasts several other cancers where serum biomarkers such as CA 19-9 and CA 125 facilitate early diagnosis and treatment. Aim: The aim of this article is to review the latest literature and highlight biomarkers which may be of clinical use in the common types of primary pediatric brain tumor. Methods: A PubMed search was performed to identify studies reporting biomarkers in the bodily fluids of pediatric patients with brain tumors. Details regarding the sample type (serum, cerebrospinal fluid or urine, biomarkers analyzed, methodology, tumor type and statistical significance were recorded. Results: A total of 12 manuscripts reporting 19 biomarkers in 367 patients vs. 397 controls were identified in the literature. Of the 19 biomarkers identified, 12 were isolated from cerebrospinal fluid, 2 from serum, 3 from urine, and 2 from multiple bodily fluids. All but one study reported statistically significant differences in biomarker expression between patient and control groups.Conclusions: This review identifies a panel of novel biomarkers for pediatric brain tumors. It provides a platform for the further studies necessary to validate these biomarkers and, in addition, highlights several techniques through which new biomarkers can be discovered.

  19. Dynamic of CSF and serum biomarkers in HIV-1 subtype C encephalitis with CNS genetic compartmentalization-case study.

    Science.gov (United States)

    de Almeida, Sergio M; Rotta, Indianara; Ribeiro, Clea E; Oliveira, Michelli F; Chaillon, Antoine; de Pereira, Ana Paula; Cunha, Ana Paula; Zonta, Marise; Bents, Joao França; Raboni, Sonia M; Smith, Davey; Letendre, Scott; Ellis, Ronald J

    2017-06-01

    Despite the effective suppression of viremia with antiretroviral therapy, HIV can still replicate in the central nervous system (CNS). This was a longitudinal study of the cerebrospinal fluid (CSF) and serum dynamics of several biomarkers related to inflammation, the blood-brain barrier, neuronal injury, and IgG intrathecal synthesis in serial samples of CSF and serum from a patient infected with HIV-1 subtype C with CNS compartmentalization.The phylogenetic analyses of plasma and CSF samples in an acute phase using next-generation sequencing and F-statistics analysis of C2-V3 haplotypes revealed distinct compartmentalized CSF viruses in paired CSF and peripheral blood mononuclear cell samples. The CSF biomarker analysis in this patient showed that symptomatic CSF escape is accompanied by CNS inflammation, high levels of cell and humoral immune biomarkers, CNS barrier dysfunction, and an increase in neuronal injury biomarkers with demyelization. Independent and isolated HIV replication can occur in the CNS, even in HIV-1 subtype C, leading to compartmentalization and development of quasispecies distinct from the peripheral plasma. These immunological aspects of the HIV CNS escape have not been described previously. To our knowledge, this is the first report of CNS HIV escape and compartmentalization in HIV-1 subtype C.

  20. Do classic blood biomarkers of JSLE identify active lupus nephritis? Evidence from the UK JSLE Cohort Study.

    Science.gov (United States)

    Smith, E M D; Jorgensen, A L; Beresford, M W

    2017-10-01

    Background Lupus nephritis (LN) affects up to 80% of juvenile-onset systemic lupus erythematosus (JSLE) patients. The value of commonly available biomarkers, such as anti-dsDNA antibodies, complement (C3/C4), ESR and full blood count parameters in the identification of active LN remains uncertain. Methods Participants from the UK JSLE Cohort Study, aged modeling, with stepAIC function applied to select a final model. Receiver-operating curve analysis was used to assess diagnostic accuracy. Results A total of 370 patients were recruited; 191 (52%) had active LN and 179 (48%) had inactive LN. Binary logistic regression modeling demonstrated a combination of ESR, C3, white cell count, neutrophils, lymphocytes and IgG to be best for the identification of active LN (area under the curve 0.724). Conclusions At best, combining common classic blood biomarkers of lupus activity using multivariate analysis provides a 'fair' ability to identify active LN. Urine biomarkers were not included in these analyses. These results add to the concern that classic blood biomarkers are limited in monitoring discrete JSLE manifestations such as LN.

  1. Prognostic biomarkers in osteoarthritis

    Science.gov (United States)

    Attur, Mukundan; Krasnokutsky-Samuels, Svetlana; Samuels, Jonathan; Abramson, Steven B.

    2013-01-01

    Purpose of review Identification of patients at risk for incident disease or disease progression in osteoarthritis remains challenging, as radiography is an insensitive reflection of molecular changes that presage cartilage and bone abnormalities. Thus there is a widely appreciated need for biochemical and imaging biomarkers. We describe recent developments with such biomarkers to identify osteoarthritis patients who are at risk for disease progression. Recent findings The biochemical markers currently under evaluation include anabolic, catabolic, and inflammatory molecules representing diverse biological pathways. A few promising cartilage and bone degradation and synthesis biomarkers are in various stages of development, awaiting further validation in larger populations. A number of studies have shown elevated expression levels of inflammatory biomarkers, both locally (synovial fluid) and systemically (serum and plasma). These chemical biomarkers are under evaluation in combination with imaging biomarkers to predict early onset and the burden of disease. Summary Prognostic biomarkers may be used in clinical knee osteoarthritis to identify subgroups in whom the disease progresses at different rates. This could facilitate our understanding of the pathogenesis and allow us to differentiate phenotypes within a heterogeneous knee osteoarthritis population. Ultimately, such findings may help facilitate the development of disease-modifying osteoarthritis drugs (DMOADs). PMID:23169101

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. The use of genotoxicity biomarkers in molecular epidemiology: applications in environmental, occupational and dietary studies

    Directory of Open Access Journals (Sweden)

    Carina Ladeira

    2017-08-01

    Full Text Available Molecular epidemiology is an approach increasingly used in the establishment of associations between exposure to hazardous substances and development of disease, including the possible modulation by genetic susceptibility factors. Environmental chemicals and contaminants from anthropogenic pollution of air, water and soil, but also originating specifically in occupational contexts, are potential sources of risk of development of disease. Also, diet presents an important role in this process, with some well characterized associations existing between nutrition and some types of cancer. Genotoxicity biomarkers allow the detection of early effects that result from the interaction between the individual and the environment; they are therefore important tools in cancer epidemiology and are extensively used in human biomonitoring studies. This work intends to give an overview of the potential for genotoxic effects assessment, specifically with the cytokinesis blocked micronucleus assay and comet assay in environmental and occupational scenarios, including diet. The plasticity of these techniques allows their inclusion in human biomonitoring studies, adding important information with the ultimate aim of disease prevention, in particular cancer, and so it is important that they be included as genotoxicity assays in molecular epidemiology.

  7. 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.

  8. [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.

  9. A Customized Quantitative PCR MicroRNA Panel Provides a Technically Robust Context for Studying Neurodegenerative Disease Biomarkers and Indicates a High Correlation Between Cerebrospinal Fluid and Choroid Plexus MicroRNA Expression.

    Science.gov (United States)

    Wang, Wang-Xia; Fardo, David W; Jicha, Gregory A; Nelson, Peter T

    2017-12-01

    MicroRNA (miRNA) expression varies in association with different tissue types and in diseases. Having been found in body fluids including blood and cerebrospinal fluid (CSF), miRNAs constitute potential biomarkers. CSF miRNAs have been proposed as biomarkers for neurodegenerative diseases; however, there is a lack of consensus about the best candidate miRNA biomarkers and there has been variability in results from different research centers, perhaps due to technical factors. Here, we sought to optimize technical parameters for CSF miRNA studies. We examined different RNA isolation methods and performed miRNA expression profiling with TaqMan® miRNA Arrays. More specifically, we developed a customized CSF-miRNA low-density array (TLDA) panel that contains 47 targets: miRNAs shown previously to be relevant to neurodegenerative disease, miRNAs that are abundant in CSF, data normalizers, and controls for potential blood and tissue contamination. The advantages of using this CSF-miRNA TLDA panel include specificity, sensitivity, fast processing and data analysis, and cost effectiveness. We optimized technical parameters for this assay. Further, the TLDA panel can be tailored to other specific purposes. We tested whether the profile of miRNAs in the CSF resembled miRNAs isolated from brain tissue (hippocampus or cerebellum), blood, or the choroid plexus. We found that the CSF miRNA expression profile most closely resembles that of choroid plexus tissue, underscoring the potential importance of choroid plexus-derived signaling through CSF miRNAs. In summary, the TLDA miRNA array panel will enable evaluation and discovery of CSF miRNA biomarkers and can potentially be utilized in clinical diagnosis and disease stage monitoring.

  10. Diagnostic accuracy for apical and chronic periodontitis biomarkers in gingival crevicular fluid: an exploratory study.

    Science.gov (United States)

    Baeza, Mauricio; Garrido, Mauricio; Hernández-Ríos, Patricia; Dezerega, Andrea; García-Sesnich, Jocelyn; Strauss, Franz; Aitken, Juan Pablo; Lesaffre, Emmanuel; Vanbelle, Sophie; Gamonal, Jorge; Brignardello-Petersen, Romina; Tervahartiala, Taina; Sorsa, Timo; Hernández, Marcela

    2016-01-01

    The aim of this study was to assess the levels and diagnostic accuracy of a set of potential biomarkers of periodontal tissue metabolism in gingival crevicular fluid (GCF) from patients with chronic periodontitis (CP) and asymptomatic apical periodontitis ( AAP). Thirty one GCF samples from 11 CP patients, 44 GCF samples from 38 AAP patients and 31 GCF samples from 13 healthy volunteers were obtained (N = 106). Matrix metalloproteinases (MMPs) -2 and -9 were determined by zymography; levels of MMP-8 by ELISA and IFMA and MPO by ELISA. IL-1, IL-6, TNFα, DKK-1, Osteonectin, Periostin, TRAP-5 and OPG were determined by a multiplex quantitative panel. Statistical analysis was performed using linear mixed-effects models. The MMP-9 and MMP-8 were higher in CP, followed by AAP, versus healthy individuals (p 0.97) in CP, and for the active form of MMP-9 and MMP-8 (AUC > 0.90) in AAP. Gingival crevicular fluid composition is modified by CP and AAP. MMP-9 and MMP-8 show diagnostic potential for CP and AAP, whereas MMP-2 and TRAP-5 are useful only for CP. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  11. 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

    Energy Technology Data Exchange (ETDEWEB)

    Hagmar, Lars; Stroemberg, Ulf; Mikoczy, Zoli; Tinnerberg, Hakan; Skerfving, Staffan [Department of Occupational and Environmental Medicine, Lund University, S-221 85 Lund (Sweden); Bonassi, Stefano; Lando, Cecilia [Department of Environmental Epidemiology, Istituto Nazionale per la Ricerca sul Cancro, Viale Benedetto XV, I-1016132 Genoa (Italy); Hansteen, Inger-Lise [Department of Occupational Medicine, Telemark Central Hospital, N-3710 Skien (Norway); Montagud, Alicia Huici [Centro Nacional de Condiciones de Trabajo, Instituto Nacional de Seguridad e Higiene en el Trabajo, Dulcet 2-10, ES-08034 Barcelona (Spain); Knudsen, Lisbeth [National Institute of Occupational Health, Lersoe Parkalle 105, DK-2100 Copenhagen (Denmark); Norppa, Hannu [Finnish Institute of Occupational Health, Topeliuksekatu 41 aA, FIN-00250 Helsinki (Finland); Reuterwall, Christina [National Institute of Work Life, S-171 84 Solna (Sweden); Broegger, Anton [Norwegian Radium Hospital, Oslo (Norway); Forni, Alessandra [Istituto di Medicina del Lavoro Clinica del Lavoro `L. Devoto`, Milan (Italy); Hoegstedt, Benkt [Department of Occupational Medicine, Central Hospital, Halmstad (Sweden); Lambert, Bo [Department of Environmental Medicine, Centre for Nutrition and Toxicology, Karolinska Institute, Stockholm (Sweden); Mitelman, Felix [Department of Clinical Genetics, Lund University, Lund (Sweden); Nordenson, Ingrid [National Institute of Work Life, Umea (Sweden); Salomaa, Sisko [Finnish Center for Radiation and Nuclear Safety, Helsinki (Finland)

    1998-09-20

    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

  12. 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

  13. Metabolites as Biomarkers of Adverse Reactions Following Vaccination: A Pilot Study using Nuclear Magnetic Resonance Metabolomics

    Science.gov (United States)

    McClenathan, Bruce M.; Stewart, Delisha A.; Spooner, Christina E.; Pathmasiri, Wimal W.; Burgess, Jason P.; McRitchie, Susan L.; Choi, Y. Sammy; Sumner, Susan C.J.

    2017-01-01

    An Adverse Event Following Immunization (AEFI) is an adverse reaction to a vaccination that goes above and beyond the usual side effects associated with vaccinations. One serious AEFI related to the smallpox vaccine is myopericarditis. Metabolomics involves the study of the low molecular weight metabolite profile of cells, tissues, and biological fluids, and provides a functional readout of the phenotype. Metabolomics may help identify a particular metabolic signature in serum of subjects who are predisposed to developing AEFIs. The goal of this study was to identify metabolic markers that may predict the development of adverse events following smallpox vaccination. Serum samples were collected from military personnel prior to and following receipt of smallpox vaccine. The study population included five subjects who were clinically diagnosed with myopericarditis, 30 subjects with asymptomatic elevation of troponins, and 31 subjects with systemic symptoms following immunization, and 34 subjects with no AEFI, serving as controls. Two-hundred pre- and post-smallpox vaccination sera were analyzed by untargeted metabolomics using 1H nuclear magnetic resonance (NMR) spectroscopy. Baseline (pre-) and post-vaccination samples from individuals who experienced clinically verified myocarditis or asymptomatic elevation of troponins were more metabolically distinguishable pre- and post-vaccination compared to individuals who only experienced systemic symptoms, or controls. Metabolomics profiles pre- and post-receipt of vaccine differed substantially when an AEFI resulted. This study is the first to describe pre- and post-vaccination metabolic profiles of subjects who developed an adverse event following immunization. The study demonstrates the promise of metabolites for determining mechanisms associated with subjects who develop AEFI and the potential to develop predictive biomarkers. PMID:28169076

  14. 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...

  15. Chemical Discovery

    Science.gov (United States)

    Brown, Herbert C.

    1974-01-01

    The role of discovery in the advance of the science of chemistry and the factors that are currently operating to handicap that function are considered. Examples are drawn from the author's work with boranes. The thesis that exploratory research and discovery should be encouraged is stressed. (DT)

  16. 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.

  17. 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.

  18. 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...

  19. 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...

  20. 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.

  1. Unrecognized vitamin D3 deficiency is common in Parkinson disease: Harvard Biomarker Study.

    Science.gov (United States)

    Ding, Hongliu; Dhima, Kaltra; Lockhart, Kaitlin C; Locascio, Joseph J; Hoesing, Ashley N; Duong, Karen; Trisini-Lipsanopoulos, Ana; Hayes, Michael T; Sohur, U Shivraj; Wills, Anne-Marie; Mollenhauer, Brit; Flaherty, Alice W; Hung, Albert Y; Mejia, Nicte; Khurana, Vikram; Gomperts, Stephen N; Selkoe, Dennis J; Schwarzschild, Michael A; Schlossmacher, Michael G; Hyman, Bradley T; Sudarsky, Lewis R; Growdon, John H; Scherzer, Clemens R

    2013-10-22

    To conclusively test for a specific association between the biological marker 25-hydroxy-vitamin D3, a transcriptionally active hormone produced in human skin and liver, and the prevalence and severity of Parkinson disease (PD). We used liquid chromatography/tandem mass spectrometry to establish an association specifically between deficiency of 25-hydroxy-vitamin D3 and PD in a cross-sectional and longitudinal case-control study of 388 patients (mean Hoehn and Yahr stage of 2.1 ± 0.6) and 283 control subjects free of neurologic disease nested in the Harvard Biomarker Study. Plasma levels of 25-hydroxy-vitamin D3 were associated with PD in both univariate and multivariate analyses with p values = 0.0034 and 0.047, respectively. Total 25-hydroxy-vitamin D levels, the traditional composite measure of endogenous and exogenous vitamin D, were deficient in 17.6% of patients with PD compared with 9.3% of controls. Low 25-hydroxy-vitamin D3 as well as total 25-hydroxy-vitamin D levels were correlated with higher total Unified Parkinson's Disease Rating Scale scores at baseline and during follow-up. Our study reveals an association between 25-hydroxy-vitamin D3 and PD and suggests that thousands of patients with PD in North America alone may be vitamin D-deficient. This finding has immediate relevance for individual patients at risk of falls as well as public health, and warrants further investigation into the mechanism underlying this association.

  2. The Biomarkers of Exposure and Effect in Agriculture (BEEA) Study: Rationale, Design, Methods, and Participant Characteristics.

    Science.gov (United States)

    Hofmann, Jonathan N; Beane Freeman, Laura E; Lynch, Charles F; Andreotti, Gabriella; Thomas, Kent W; Sandler, Dale P; Savage, Sharon A; Alavanja, Michael C

    2015-01-01

    Agricultural exposures including pesticides, endotoxin, and allergens have been associated with risk of various cancers and other chronic diseases, although the biological mechanisms underlying these associations are generally unclear. To facilitate future molecular epidemiologic investigations, in 2010 the study of Biomarkers of Exposure and Effect in Agriculture (BEEA) was initiated within the Agricultural Health Study, a large prospective cohort in Iowa and North Carolina. Here the design and methodology of BEEA are described and preliminary frequencies for participant characteristics and current agricultural exposures are reported. At least 1,600 male farmers over 50 years of age will be enrolled in the BEEA study. During a home visit, participants are asked to complete a detailed interview about recent agricultural exposures and provide samples of blood, urine, and (since 2013) house dust. As of mid-September 2014, in total, 1,233 participants have enrolled. Most of these participants (83%) were still farming at the time of interview. Among those still farming, the most commonly reported crops were corn (81%) and soybeans (74%), and the most frequently noted animals were beef cattle (35%) and hogs (13%). There were 861 (70%) participants who reported occupational pesticide use in the 12 months prior to interview; among these participants, the most frequently noted herbicides were glyphosate (83%) and 2,4-D (72%), and most commonly reported insecticides were malathion (21%), cyfluthrin (13%), and permethrin (12%). Molecular epidemiologic investigations within BEEA have the potential to yield important new insights into the biological mechanisms through which these or other agricultural exposures influence disease risk.

  3. Evaluation of pathogen-specific biomarkers for the diagnosis of tuberculosis in white-tailed deer (Odocoileus virginianus)

    Science.gov (United States)

    Objective - To develop a noninvasive biomarker based Mycobacterium bovis specific detection system to track infection in domestic and wild animals. Design – Experimental longitudinal study for discovery and cross sectional design for validation Animals - Yearling white-tailed deer fawns (n=8) were ...

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

    NARCIS (Netherlands)

    Bussel, van B.C.T.; Ferreira, I.; Waarenburg, M.P.H.; Greevenbroek, van M.M.J.; Kallen, van der C.J.H.; Henry, R.M.A.; Feskens, E.J.M.; Stehouwer, C.D.A.; Schalkwijk, C.G.

    2013-01-01

    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),

  5. Unraveling the molecular repertoire of tears as a source of biomarkers: beyond ocular diseases.

    Science.gov (United States)

    Pieragostino, Damiana; D'Alessandro, Michele; di Ioia, Maria; Di Ilio, Carmine; Sacchetta, Paolo; Del Boccio, Piero

    2015-02-01

    Proteomics and metabolomics investigations of body fluids present several challenges for biomarker discovery of several diseases. The search for biomarkers is actually conducted in different body fluids, even if the ideal biomarker can be found in an easily accessible biological fluid, because, if validated, the biomarker could be sought in the healthy population. In this regard, tears could be considered an optimum material obtained by noninvasive procedures. In the past years, the scientific community has become more interested in the study of tears for the research of new biomarkers not only for ocular diseases. In this review, we provide a discussion on the current state of biomarkers research in tears and their relevance for clinical practice, and report the main results of clinical proteomics studies on systemic and eye diseases. We summarize the main methods for tear samples analyses and report recent advances in "omics" platforms for tears investigations. Moreover, we want to take stock of the emerging field of metabolomics and lipidomics as a new and integrated approach to study protein-metabolites interplay for biomarkers research, where tears represent a still unexplored and attractive field. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. 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.

  7. Data on serologic inflammatory biomarkers assessed using multiplex assays and host characteristics in the Multicenter AIDS Cohort Study (MACS

    Directory of Open Access Journals (Sweden)

    Heather S. McKay

    2016-12-01

    Full Text Available This article contains data on the associations between fixed and modifiable host characteristics and twenty-three biomarkers of inflammation and immune activation measured longitudinally in a cohort of 250 HIV-uninfected men from the Multicenter AIDS Cohort Study (1984–2009 after adjusting for age, study site, and blood draw time of day using generalized gamma regression. This article also presents associations between each biomarker and each host characteristic in a sample restricted to 2001–2009. These data are supplemental to our original research article entitled “Host factors associated with serologic inflammatory markers assessed using multiplex assays” (McKay, S. Heather, Bream, H. Jay, Margolick, B. Joseph, Martínez-Maza, Otoniel, Phair, P. John, Rinaldo, R. Charles, Abraham, G. Alison, L.P. Jacobson, 2016 [1].

  8. 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

  9. Characterization of neurophysiologic and neurocognitive biomarkers for use in genomic and clinical outcome studies of schizophrenia.

    Science.gov (United States)

    Light, Gregory A; Swerdlow, Neal R; Rissling, Anthony J; Radant, Allen; Sugar, Catherine A; Sprock, Joyce; Pela, Marlena; Geyer, Mark A; Braff, David L

    2012-01-01

    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 patients

  10. False Discovery Rates in PET and CT Studies with Texture Features: A Systematic Review.

    Directory of Open Access Journals (Sweden)

    Anastasia Chalkidou

    image-derived biomarkers should be supported by appropriate biological and statistical evidence before their association with patient outcome is investigated in prospective studies.

  11. False Discovery Rates in PET and CT Studies with Texture Features: A Systematic Review.

    Science.gov (United States)

    Chalkidou, Anastasia; O'Doherty, Michael J; Marsden, Paul K

    2015-01-01

    -derived biomarkers should be supported by appropriate biological and statistical evidence before their association with patient outcome is investigated in prospective studies.

  12. Chasing the Effects of Pre-Analytical Confounders - A Multicenter Study on CSF-AD Biomarkers

    DEFF Research Database (Denmark)

    Leitão, Maria João; Baldeiras, Inês; Herukka, Sanna-Kaisa

    2015-01-01

    INTRODUCTION: Core cerebrospinal fluid (CSF) biomarkers - Aβ42, Tau, and phosphorylated Tau (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...

  13. Long-interval intracortical inhibition as biomarker for epilepsy : a transcranial magnetic stimulation study

    NARCIS (Netherlands)

    Bauer, Prisca R.; de Goede, Annika A.; Stern, William M.; Pawley, Adam D.; Chowdhury, Fahmida A.; Helling, Robert M.; Bouet, Romain; Kalitzin, Stiliyan N.; Visser, Gerhard H.; Sisodiya, Sanjay M.; Rothwell, John C.; Richardson, Mark P.; van Putten, Michel J.A.M.; Sander, Josemir W.

    2018-01-01

    Cortical excitability, as measured by transcranial magnetic stimulation combined with electromyography, is a potential biomarker for the diagnosis and follow-up of epilepsy. We report on long-interval intracortical inhibition data measured in four different centres in healthy controls (n = 95),

  14. 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

  15. Cross-study and cross-omics comparisons of three nephrotoxic compounds reveal mechanistic insights and new candidate biomarkers

    International Nuclear Information System (INIS)

    Matheis, Katja A.; Com, Emmanuelle; Gautier, Jean-Charles; Guerreiro, Nelson; Brandenburg, Arnd; Gmuender, Hans; Sposny, Alexandra; Hewitt, Philip; Amberg, Alexander; Boernsen, Olaf; Riefke, Bjoern; Hoffmann, Dana; Mally, Angela; Kalkuhl, Arno; Suter, Laura; Dieterle, Frank; Staedtler, Frank

    2011-01-01

    The European InnoMed-PredTox project was a collaborative effort between 15 pharmaceutical companies, 2 small and mid-sized enterprises, and 3 universities with the goal of delivering deeper insights into the molecular mechanisms of kidney and liver toxicity and to identify mechanism-linked diagnostic or prognostic safety biomarker candidates by combining conventional toxicological parameters with 'omics' data. Mechanistic toxicity studies with 16 different compounds, 2 dose levels, and 3 time points were performed in male Crl: WI(Han) rats. Three of the 16 investigated compounds, BI-3 (FP007SE), Gentamicin (FP009SF), and IMM125 (FP013NO), induced kidney proximal tubule damage (PTD). In addition to histopathology and clinical chemistry, transcriptomics microarray and proteomics 2D-DIGE analysis were performed. Data from the three PTD studies were combined for a cross-study and cross-omics meta-analysis of the target organ. The mechanistic interpretation of kidney PTD-associated deregulated transcripts revealed, in addition to previously described kidney damage transcript biomarkers such as KIM-1, CLU and TIMP-1, a number of additional deregulated pathways congruent with histopathology observations on a single animal basis, including a specific effect on the complement system. The identification of new, more specific biomarker candidates for PTD was most successful when transcriptomics data were used. Combining transcriptomics data with proteomics data added extra value.

  16. New biomarkers of coffee consumption identified by the non-targeted metabolomic profiling of cohort study subjects.

    Directory of Open Access Journals (Sweden)

    Joseph A Rothwell

    Full Text Available Coffee contains various bioactives implicated with human health and disease risk. To accurately assess the effects of overall consumption upon health and disease, individual intake must be measured in large epidemiological studies. Metabolomics has emerged as a powerful approach to discover biomarkers of intake for a large range of foods. Here we report the profiling of the urinary metabolome of cohort study subjects to search for new biomarkers of coffee intake. Using repeated 24-hour dietary records and a food frequency questionnaire, 20 high coffee consumers (183-540 mL/d and 19 low consumers were selected from the French SU.VI.MAX2 cohort. Morning spot urine samples from each subject were profiled by high-resolution mass spectrometry. Partial least-square discriminant analysis of multidimensional liquid chromatography-mass spectrometry data clearly distinguished high consumers from low via 132 significant (p-value<0.05 discriminating features. Ion clusters whose intensities were most elevated in the high consumers were annotated using online and in-house databases and their identities checked using commercial standards and MS-MS fragmentation. The best discriminants, and thus potential markers of coffee consumption, were the glucuronide of the diterpenoid atractyligenin, the diketopiperazine cyclo(isoleucyl-prolyl, and the alkaloid trigonelline. Some caffeine metabolites, such as 1-methylxanthine, were also among the discriminants, however caffeine may be consumed from other sources and its metabolism is subject to inter-individual variation. Receiver operating characteristics curve analysis showed that the biomarkers identified could be used effectively in combination for increased sensitivity and specificity. Once validated in other cohorts or intervention studies, these specific single or combined biomarkers will become a valuable alternative to assessment of coffee intake by dietary survey and finally lead to a better understanding of

  17. A pilot randomized study of a gratitude journaling intervention on HRV and inflammatory biomarkers in Stage B heart failure patients

    Science.gov (United States)

    Redwine, Laura; Henry, Brook L.; Pung, Meredith A.; Wilson, Kathleen; Chinh, Kelly; Knight, Brian; Jain, Shamini; Rutledge, Thomas; Greenberg, Barry; Maisel, Alan; Mills, Paul J

    2016-01-01

    Objective Stage B, asymptomatic heart failure (HF) presents a therapeutic window for attenuating disease progression and development of HF symptoms, and improving quality of life. Gratitude, the practice of appreciating positive life features, is highly related to quality of life, leading to development of promising clinical interventions. However, few gratitude studies have investigated objective measures of physical health; most relied on self-report measures. We conducted a pilot study in Stage B HF patients to examine whether gratitude journaling improved biomarkers related to HF prognosis. Methods Patients (N = 70; mean age = 66.2 years, SD = 7.6) were randomized to an 8-week gratitude journaling intervention or treatment as usual (TAU). Baseline (T1) assessments included 6-item Gratitude Questionnaire (GQ-6), resting heart rate variability (HRV), and an inflammatory biomarker index. At T2 (mid-intervention) GQ6 was measured. At T3 (post-intervention), T1 measures were repeated but also included a gratitude journaling task. Results The gratitude intervention was associated with improved trait gratitude scores (F = 6.0, p = .017, η2 = .10), reduced inflammatory biomarker index score over time (F = 9.7, p = .004, η2 = .21) and increased parasympathetic HRV responses during the gratitude journaling task (F = 4.2, p = .036, η2 = .15), compared with TAU. However, there were no resting pre- to post-intervention group differences in HRV (p's > .10). Conclusions Gratitude journaling may improve biomarkers related to HF morbidity, such as reduced inflammation; large-scale studies with active control conditions are needed to confirm these findings. PMID:27187845

  18. Pleural effusion biomarkers and computed tomography findings in diagnosing malignant pleural mesothelioma: A retrospective study in a single center

    Science.gov (United States)

    Kataoka, Yuki; Ikegaki, Shunkichi; Saito, Emiko; Matsumoto, Hirotaka; Kaku, Sawako; Shimada, Masatoshi; Hirabayashi, Masataka

    2017-01-01

    In this study, we aimed to examine the clinical value of the pleural effusion (PE) biomarkers, soluble mesothelin-related peptide (SMRP), cytokeratin 19 fragment (CYFRA 21–1) and carcinoembryonic antigen (CEA), and the utility of combining chest computed tomography (CT) findings with these biomarkers, in diagnosing malignant pleural mesothelioma (MPM). We conducted a retrospective cohort study in a single center. Consecutive patients with undiagnosed pleural effusions who underwent PE analysis between September 2014 and August 2016 were reviewed. This study included 240 patients (32 with MPM and 208 non-MPM). SMRP and the CYFRA 21-1/CEA ratio had a sensitivity and specificity for diagnosing MPM of 56.3% and 86.5%, and 87.5% and 74.0%, respectively. Using receiver operating characteristics (ROC) curve analysis of the ability of these markers to distinguish MPM from all other PE causes, the area under the ROC curve (AUC) for SMRP and the CYFRA 21-1/CEA ratio was 0.804 and 0.874, respectively. The sensitivity and specificity of SMRP combined with the CYFRA 21-1/CEA ratio were 93.8% and 64.9%, respectively. The sensitivity of the combination of SMRP, the CYFRA 21-1/CEA ratio, and the presence of Leung’s criteria (a chest CT finding that is suggestive of malignant pleural disease) was 93.8%. In conclusion, the combined PE biomarkers had a high sensitivity for diagnosing MPM, although the addition of chest CT findings did not improve the sensitivity of SMRP combined with the CYFRA 21-1/CEA ratio. Combination of these biomarkers helped to rule out MPM effectively among patients at high risk of suffering MPM and would be valuable especially for old frail patients who have difficulty in undergoing invasive procedures such as thoracoscopy. PMID:28968445

  19. Applications of biological tools or biomarkers in aquatic biota: A case study of the Tamar estuary, South West England.

    Science.gov (United States)

    Dallas, Lorna J; Jha, Awadhesh N

    2015-06-30

    Biological systems are the ultimate recipients of pollutant-induced damage. Consequently, our traditional reliance on analytical tools is not enough to assess ecosystem health. Biological responses or biomarkers are therefore also considered to be important tools for environmental hazard and risk assessments. Due to historical mining, other anthropogenic activities, and its conservational importance (e.g. NATURA sites, SACs), the Tamar estuary in South West England is an ideal environment in which to examine applications of such biological tools. This review presents a thorough and critical evaluation of the different biological tools used in the Tamar estuary thus far, while also discussing future perspectives for biomarker studies from a global perspective. In particular, we focus on the challenges which hinder applications of biological tools from being more readily incorporated into regulatory frameworks, with the aim of enabling both policymakers and primary stakeholders to maximise the environmental relevance and regulatory usefulness of such tools. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. Production of heparanase constructs suitable for nuclear magnetic resonance and drug discovery studies.

    Science.gov (United States)

    Mosulén, Silvia; Ortí, Leticia; Bas, Esperanza; Carbajo, Rodrigo J; Pineda-Lucena, Antonio

    2011-02-01

    Heparanase is an endo-β-D-glucosidase capable of specifically degrading heparan sulphate, one of the main components of the extracellular matrix. This 65 kDa polypeptide is implicated in cancer processes such as tumour formation, angiogenesis and metastasis, making it a very attractive target in antitumour treatments. Structure-based approaches to find inhibitors of heparanase have been historically hampered by the lack of success in crystallizing the protein. With the aim to undertake the NMR structural characterisation of heparanase, we have designed and produced, using recombinant methods, smaller constructs of heparanase containing the catalytically active glutamic acids and the two binding sites for heparan sulphate. An extensive range of expression and purification conditions were evaluated to alleviate the intrinsic low solubility and aggregation propensity of heparanase, allowing the obtention of the enzyme in milligram quantities, both unlabelled and ¹⁵N-labelled for NMR studies. Using the smallest of the designed constructs and applying NMR and SPR methodologies, we have demonstrated that known inhibitors of heparanase bind to this construct specifically and selectively with K(D) values in the range of those reported for human heparanase, validating it for future drug discovery projects focused on the identification of novel inhibitors of this enzyme. © 2010 Wiley Periodicals, Inc.

  1. Discovery learning with hierarchy concept to improve analysis ability and study achievement hydrolysis subject

    Directory of Open Access Journals (Sweden)

    Leny Yuliatun

    2017-10-01

    Full Text Available The aim of this research is to applied Discovery Learning (DL by the support of hierarchy concept to improve analysis ability and chemistry study achievement in the Hydrolysis subject at eleventh-grade students of Science 1 of SMA N Karangpandan at the academic year of 2016/2017. This research is using Classroom Action Research which using two cycles. In each cycle has four steps of action, they are planning, implementing, observing, and reflecting. The research subject is the eleventh-grade students of science one which consists of 40 students. The data source is using teacher and students and the data were taken by interviewing, observing, documenting, testing, and using questionnaire. Data analysis technique is using descriptive qualitative analysis. Based on the research shows that the achievement of analysis cycle I am from 52,5% increase into 65% in the cycle II. Meanwhile, the rise in students’ achievement in cognitive aspect increase from 57,5% in cycle I to 75% in cycle II. Achievement in an affective aspect in cycle I am 90% become 92,5% in cycle II. Therefore, there is the increase meant of students number in this aspect although in cycle I all of the indicator has been reached.

  2. 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.

  3. 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...

  4. Potential diagnostic biomarkers for chronic kidney disease of unknown etiology (CKDu) in Sri Lanka: a pilot study.

    Science.gov (United States)

    Sayanthooran, Saravanabavan; Magana-Arachchi, Dhammika N; Gunerathne, Lishanthe; Abeysekera, Tilak

    2017-01-19

    In Sri Lanka, there exists chronic kidney disease of both known (CKD) and unknown etiologies (CKDu). Identification of novel biomarkers that are customized to the specific causative factors would lead to early diagnosis and clearer prognosis of the diseases. This study aimed to find genetic biomarkers in blood to distinguish and identify CKDu from CKD as well as healthy populations from CKDu endemic and non-endemic areas of Sri Lanka. The expression patterns of a selected panel of 12 potential genetic biomarkers were analyzed in blood using RT-qPCR. Fold changes of gene expressions in early and late stages of CKD and CKDu patients, and an apparently healthy population of a CKDu endemic area, Girandurukotte (GH) were calculated relative to apparently healthy volunteers from a CKDu non-endemic area, Kandy (KH) of Sri Lanka, using the comparative CT method. Significant differences were observed between KH and early stage CKDu for both the insulin-like growth factor binding protein 1 (IGFBP1; p = 0.012) and kidney injury molecule-1 (KIM1; p = 0.003) genes, and KH and late stage CKD and CKDu for the glutathione-S-transferase mu 1 (GSTM1; p CKDu (p CKDu, whereas these genes in addition with FN1, IGFBP3 and KLK1 could be used to monitor progression of CKDu. The regulation of these genes has to be studied on larger populations to validate their efficiency for further clinical use.

  5. High-Throughput Analysis and Automation for Glycomics Studies

    NARCIS (Netherlands)

    Shubhakar, A.; Reiding, K.R.; Gardner, R.A.; Spencer, D.I.R.; Fernandes, D.L.; Wuhrer, M.

    2015-01-01

    This review covers advances in analytical technologies for high-throughput (HTP) glycomics. Our focus is on structural studies of glycoprotein glyco