Finding gene-environment interactions for Phobias

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Gregory, Alice M.; Lau, Jennifer Y. F.; Eley, Thalia C.

2008-01-01

Phobias are common disorders causing a great deal of suffering. Studies of gene-environment interaction (G × E) have revealed much about the complex processes underlying the development of various psychiatric disorders but have told us little about phobias. This article describes what is already known about genetic and environmental influences upon phobias and suggests how this information can be used to optimise the chances of discovering G × Es for phobias. In addition to the careful concep...

Gene × Environment Interactions in Schizophrenia: Evidence from Genetic Mouse Models.

Science.gov (United States)

Moran, Paula; Stokes, Jennifer; Marr, Julia; Bock, Gavin; Desbonnet, Lieve; Waddington, John; O'Tuathaigh, Colm

2016-01-01

The study of gene × environment, as well as epistatic interactions in schizophrenia, has provided important insight into the complex etiopathologic basis of schizophrenia. It has also increased our understanding of the role of susceptibility genes in the disorder and is an important consideration as we seek to translate genetic advances into novel antipsychotic treatment targets. This review summarises data arising from research involving the modelling of gene × environment interactions in schizophrenia using preclinical genetic models. Evidence for synergistic effects on the expression of schizophrenia-relevant endophenotypes will be discussed. It is proposed that valid and multifactorial preclinical models are important tools for identifying critical areas, as well as underlying mechanisms, of convergence of genetic and environmental risk factors, and their interaction in schizophrenia.

Gene × Environment Interactions in Schizophrenia: Evidence from Genetic Mouse Models

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Marr, Julia; Bock, Gavin; Desbonnet, Lieve; Waddington, John

2016-01-01

The study of gene × environment, as well as epistatic interactions in schizophrenia, has provided important insight into the complex etiopathologic basis of schizophrenia. It has also increased our understanding of the role of susceptibility genes in the disorder and is an important consideration as we seek to translate genetic advances into novel antipsychotic treatment targets. This review summarises data arising from research involving the modelling of gene × environment interactions in schizophrenia using preclinical genetic models. Evidence for synergistic effects on the expression of schizophrenia-relevant endophenotypes will be discussed. It is proposed that valid and multifactorial preclinical models are important tools for identifying critical areas, as well as underlying mechanisms, of convergence of genetic and environmental risk factors, and their interaction in schizophrenia. PMID:27725886

Gene × Environment Interactions in Schizophrenia: Evidence from Genetic Mouse Models

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Paula Moran

2016-01-01

Full Text Available The study of gene × environment, as well as epistatic interactions in schizophrenia, has provided important insight into the complex etiopathologic basis of schizophrenia. It has also increased our understanding of the role of susceptibility genes in the disorder and is an important consideration as we seek to translate genetic advances into novel antipsychotic treatment targets. This review summarises data arising from research involving the modelling of gene × environment interactions in schizophrenia using preclinical genetic models. Evidence for synergistic effects on the expression of schizophrenia-relevant endophenotypes will be discussed. It is proposed that valid and multifactorial preclinical models are important tools for identifying critical areas, as well as underlying mechanisms, of convergence of genetic and environmental risk factors, and their interaction in schizophrenia.

Antisocial peer affiliation and externalizing disorders: Evidence for Gene × Environment × Development interaction.

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Samek, Diana R; Hicks, Brian M; Keyes, Margaret A; Iacono, William G; McGue, Matt

2017-02-01

Gene × Environment interaction contributes to externalizing disorders in childhood and adolescence, but little is known about whether such effects are long lasting or present in adulthood. We examined gene-environment interplay in the concurrent and prospective associations between antisocial peer affiliation and externalizing disorders (antisocial behavior and substance use disorders) at ages 17, 20, 24, and 29. The sample included 1,382 same-sex twin pairs participating in the Minnesota Twin Family Study. We detected a Gene × Environment interaction at age 17, such that additive genetic influences on antisocial behavior and substance use disorders were greater in the context of greater antisocial peer affiliation. This Gene × Environment interaction was not present for antisocial behavior symptoms after age 17, but it was for substance use disorder symptoms through age 29 (though effect sizes were largest at age 17). The results suggest adolescence is a critical period for the development of externalizing disorders wherein exposure to greater environmental adversity is associated with a greater expression of genetic risk. This form of Gene × Environment interaction may persist through young adulthood for substance use disorders, but it appears to be limited to adolescence for antisocial behavior.

Antisocial Peer Affiliation and Externalizing Disorders: Evidence for Gene × Environment × Development Interaction

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Samek, Diana R.; Hicks, Brian M.; Keyes, Margaret A.; Iacono, William G.; McGue, Matt

2016-01-01

Gene × environment interaction contributes to externalizing disorders in adolescence, but little is known about whether such effects are long-lasting or present in adulthood. We examined gene-environment interplay in the concurrent and prospective associations between antisocial peer affiliation and externalizing disorders (antisocial behavior and substance use disorders) at ages 17, 20, 24, and 29. The sample included 1,382 same-sex twin pairs participating in the Minnesota Twin Family Study. We detected a gene × environment interaction at age 17, such that additive genetic influences on antisocial behavior and substance use disorders were greater in the context of greater antisocial peer affiliation. This gene × environment interaction was not present for antisocial behavior symptoms after age 17, but was for substance use disorder symptoms through age 29 (though effect sizes were largest at age 17). Results suggest adolescence is a critical period for the development of externalizing disorders wherein exposure to greater environmental adversity is associated with a greater expression of genetic risk. This form of gene × environment interaction may persist through young adulthood for substance use disorders, but is limited to adolescence for antisocial behavior. PMID:27580681

Finding gene-environment interactions for phobias.

Science.gov (United States)

Gregory, Alice M; Lau, Jennifer Y F; Eley, Thalia C

2008-03-01

Phobias are common disorders causing a great deal of suffering. Studies of gene-environment interaction (G x E) have revealed much about the complex processes underlying the development of various psychiatric disorders but have told us little about phobias. This article describes what is already known about genetic and environmental influences upon phobias and suggests how this information can be used to optimise the chances of discovering G x Es for phobias. In addition to the careful conceptualisation of new studies, it is suggested that data already collected should be re-analysed in light of increased understanding of processes influencing phobias.

Shame and Guilt-Proneness in Adolescents: Gene-Environment Interactions.

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Szentágotai-Tătar, Aurora; Chiș, Adina; Vulturar, Romana; Dobrean, Anca; Cândea, Diana Mirela; Miu, Andrei C

2015-01-01

Rooted in people's preoccupation with how they are perceived and evaluated, shame and guilt are self-conscious emotions that play adaptive roles in social behavior, but can also contribute to psychopathology when dysregulated. Shame and guilt-proneness develop during childhood and adolescence, and are influenced by genetic and environmental factors that are little known to date. This study investigated the effects of early traumatic events and functional polymorphisms in the brain-derived neurotrophic factor (BDNF) gene and the serotonin transporter gene promoter (5-HTTLPR) on shame and guilt in adolescents. A sample of N = 271 healthy adolescents between 14 and 17 years of age filled in measures of early traumatic events and proneness to shame and guilt, and were genotyped for the BDNF Val66Met and 5-HTTLPR polymorphisms. Results of moderator analyses indicated that trauma intensity was positively associated with guilt-proneness only in carriers of the low-expressing Met allele of BDNF Val66Met. This is the first study that identifies a gene-environment interaction that significantly contributes to guilt proneness in adolescents, with potential implications for developmental psychopathology.

Gene-environment interaction and male reproductive function

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Axelsson, Jonatan; Bonde, Jens Peter; Giwercman, Yvonne L.; Rylander, Lars; Giwercman, Aleksander

2010-01-01

As genetic factors can hardly explain the changes taking place during short time spans, environmental and lifestyle-related factors have been suggested as the causes of time-related deterioration of male reproductive function. However, considering the strong heterogeneity of male fecundity between and within populations, genetic variants might be important determinants of the individual susceptibility to the adverse effects of environment or lifestyle. Although the possible mechanisms of such interplay in relation to the reproductive system are largely unknown, some recent studies have indicated that specific genotypes may confer a larger risk of male reproductive disorders following certain exposures. This paper presents a critical review of animal and human evidence on how genes may modify environmental effects on male reproductive function. Some examples have been found that support this mechanism, but the number of studies is still limited. This type of interaction studies may improve our understanding of normal physiology and help us to identify the risk factors to male reproductive malfunction. We also shortly discuss other aspects of gene-environment interaction specifically associated with the issue of reproduction, namely environmental and lifestyle factors as the cause of sperm DNA damage. It remains to be investigated to what extent such genetic changes, by natural conception or through the use of assisted reproductive techniques, are transmitted to the next generation, thereby causing increased morbidity in the offspring. PMID:20348940

A simulation study of gene-by-environment interactions in GWAS implies ample hidden effects

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Marigorta, Urko M.; Gibson, Greg

2014-01-01

The switch to a modern lifestyle in recent decades has coincided with a rapid increase in prevalence of obesity and other diseases. These shifts in prevalence could be explained by the release of genetic susceptibility for disease in the form of gene-by-environment (GxE) interactions. Yet, the detection of interaction effects requires large sample sizes, little replication has been reported, and a few studies have demonstrated environmental effects only after summing the risk of GWAS alleles into genetic risk scores (GRSxE). We performed extensive simulations of a quantitative trait controlled by 2500 causal variants to inspect the feasibility to detect gene-by-environment interactions in the context of GWAS. The simulated individuals were assigned either to an ancestral or a modern setting that alters the phenotype by increasing the effect size by 1.05–2-fold at a varying fraction of perturbed SNPs (from 1 to 20%). We report two main results. First, for a wide range of realistic scenarios, highly significant GRSxE is detected despite the absence of individual genotype GxE evidence at the contributing loci. Second, an increase in phenotypic variance after environmental perturbation reduces the power to discover susceptibility variants by GWAS in mixed cohorts with individuals from both ancestral and modern environments. We conclude that a pervasive presence of gene-by-environment effects can remain hidden even though it contributes to the genetic architecture of complex traits. PMID:25101110

Animal model for schizophrenia that reflects gene-environment interactions.

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Nagai, Taku; Ibi, Daisuke; Yamada, Kiyofumi

2011-01-01

Schizophrenia is a devastating psychiatric disorder that impairs mental and social functioning and affects approximately 1% of the population worldwide. Genetic susceptibility factors for schizophrenia have recently been reported, some of which are known to play a role in neurodevelopment; these include neuregulin-1, dysbindin, and disrupted-in-schizophrenia 1 (DISC1). Moreover, epidemiologic studies suggest that environmental insults, such as prenatal infection and perinatal complication, are involved in the development of schizophrenia. The possible interaction between environment and genetic susceptibility factors, especially during neurodevelopment, is proposed as a promising disease etiology of schizophrenia. Polyriboinosinic-polyribocytidilic acid (polyI : C) is a synthetic analogue of double-stranded RNA that leads to the pronounced but time-limited production of pro-inflammatory cytokines. Maternal immune activation by polyI : C exposure in rodents is known to precipitate a wide spectrum of behavioral, cognitive, and pharmacological abnormalities in adult offspring. Recently, we have reported that neonatal injection of polyI : C in mice results in schizophrenia-like behavioral alterations in adulthood. In this review, we show how gene-environment interactions during neurodevelopment result in phenotypic changes in adulthood by injecting polyI : C into transgenic mice that express a dominant-negative form of human DISC1 (DN-DISC1). Our findings suggest that polyI : C-treated DN-DISC1 mice are a well-validated animal model for schizophrenia that reflects gene-environment interactions.

Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions

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Shungin, Dmitry; Deng, Wei Q; Varga, Tibor V

2017-01-01

Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (G×E) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between...... variance effects (Pv), G×E interaction effects (with smoking and physical activity), and marginal genetic effects (Pm). Correlations between Pv and Pm were stronger for SNPs with established marginal effects (Spearman's ρ = 0.401 for triglycerides, and ρ = 0.236 for BMI) compared to all SNPs. When Pv...... and Pm were compared for all pruned SNPs, only BMI was statistically significant (Spearman's ρ = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the Pv distribution (Pbinomial BMI had...

Environment-Gene interaction in common complex diseases: New approaches

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William A. Toscano, Jr.

2014-10-01

Full Text Available Approximately 100,000 different environmental chemicals that are in use as high production volume chemicals confront us in our daily lives. Many of the chemicals we encounter are persistent and have long half-lives in the environment and our bodies. These compounds are referred to as Persistent Organic Pollutants, or POPS. The total environment however is broader than just toxic pollutants. It includes social capital, social economic status, and other factors that are not commonly considered in traditional approaches to studying environment-human interactions. The mechanism of action of environmental agents in altering the human phenotype from health to disease is more complex than once thought. The focus in public health has shifted away from the study of single-gene rare diseases and has given way to the study of multifactorial complex diseases that are common in the population. To understand common complex diseases, we need teams of scientists from different fields working together with common aims. We review some approaches for studying the action of the environment by discussing use-inspired research, and transdisciplinary research approaches. The Genomic era has yielded new tools for study of gene-environment interactions, including genomics, epigenomics, and systems biology. We use environmentally-driven diabetes mellitus type two as an example of environmental epigenomics and disease. The aim of this review is to start the conversation of how the application of advances in biomedical science can be used to advance public health.

Childhood quality influences genetic sensitivity to environmental influences across adulthood: A life-course Gene × Environment interaction study.

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Keers, Robert; Pluess, Michael

2017-12-01

While environmental adversity has been shown to increase risk for psychopathology, individuals differ in their sensitivity to these effects. Both genes and childhood experiences are thought to influence sensitivity to the environment, and these factors may operate synergistically such that the effects of childhood experiences on later sensitivity are greater in individuals who are more genetically sensitive. In line with this hypothesis, several recent studies have reported a significant three-way interaction (Gene × Environment × Environment) between two candidate genes and childhood and adult environment on adult psychopathology. We aimed to replicate and extend these findings in a large, prospective multiwave longitudinal study using a polygenic score of environmental sensitivity and objectively measured childhood and adult material environmental quality. We found evidence for both Environment × Environment and Gene × Environment × Environment effects on psychological distress. Children with a poor-quality material environment were more sensitive to the negative effects of a poor environment as adults, reporting significantly higher psychological distress scores. These effects were further moderated by a polygenic score of environmental sensitivity. Genetically sensitive children were more vulnerable to adversity as adults, if they had experienced a poor childhood environment but were significantly less vulnerable if their childhood environment was positive. These findings are in line with the differential susceptibility hypothesis and suggest that a life course approach is necessary to elucidate the role of Gene × Environment in the development of mental illnesses.

Study of oral clefts: Indication of gene-environment interaction

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Hwang, S.J.; Beaty, T.H.; Panny, S. [Johns Hopkins Univ., Baltimore, MD (United States)] [and others

1994-09-01

In this study of infants with isolated birth defects, 69 cleft palate-only (CPO) cases, 114 cleft lip with or without palate (CL/P), and 284 controls with non-cleft birth defects (all born in Maryland during 1984-1992) were examined to test for associations among genetic markers and different oral clefts. Modest associations were found between transforming growth factor {alpha} (TGF{alpha}) marker and CPO, as well as that between D17S579 (Mfd188) and CL/P in this study. The association between TGF{alpha} marker and CPO reflects a statistical interaction between mother`s smoking and child`s TGF{alpha} genotype. A significantly higher risk of CPO was found among those reporting maternal smoking during pregnancy and carrying less common TGF{alpha} TaqI allele (odds ratio=7.02 with 95% confidence interval 1.8-27.6). This gene-environment interaction was also found among those who reported no family history of any type of birth defect (odds ratio=5.60 with 95% confidence interval 1.4-22.9). Similar associations were seen for CL/P, but these were not statistically significant.

Random regression models for detection of gene by environment interaction

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Meuwissen Theo HE

2007-02-01

Full Text Available Abstract Two random regression models, where the effect of a putative QTL was regressed on an environmental gradient, are described. The first model estimates the correlation between intercept and slope of the random regression, while the other model restricts this correlation to 1 or -1, which is expected under a bi-allelic QTL model. The random regression models were compared to a model assuming no gene by environment interactions. The comparison was done with regards to the models ability to detect QTL, to position them accurately and to detect possible QTL by environment interactions. A simulation study based on a granddaughter design was conducted, and QTL were assumed, either by assigning an effect independent of the environment or as a linear function of a simulated environmental gradient. It was concluded that the random regression models were suitable for detection of QTL effects, in the presence and absence of interactions with environmental gradients. Fixing the correlation between intercept and slope of the random regression had a positive effect on power when the QTL effects re-ranked between environments.

Multiple Gene-Environment Interactions on the Angiogenesis Gene-Pathway Impact Rectal Cancer Risk and Survival

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Noha Sharafeldin

2017-09-01

Full Text Available Characterization of gene-environment interactions (GEIs in cancer is limited. We aimed at identifying GEIs in rectal cancer focusing on a relevant biologic process involving the angiogenesis pathway and relevant environmental exposures: cigarette smoking, alcohol consumption, and animal protein intake. We analyzed data from 747 rectal cancer cases and 956 controls from the Diet, Activity and Lifestyle as a Risk Factor for Rectal Cancer study. We applied a 3-step analysis approach: first, we searched for interactions among single nucleotide polymorphisms on the pathway genes; second, we searched for interactions among the genes, both steps using Logic regression; third, we examined the GEIs significant at the 5% level using logistic regression for cancer risk and Cox proportional hazards models for survival. Permutation-based test was used for multiple testing adjustment. We identified 8 significant GEIs associated with risk among 6 genes adjusting for multiple testing: TNF (OR = 1.85, 95% CI: 1.10, 3.11, TLR4 (OR = 2.34, 95% CI: 1.38, 3.98, and EGR2 (OR = 2.23, 95% CI: 1.04, 4.78 with smoking; IGF1R (OR = 1.69, 95% CI: 1.04, 2.72, TLR4 (OR = 2.10, 95% CI: 1.22, 3.60 and EGR2 (OR = 2.12, 95% CI: 1.01, 4.46 with alcohol; and PDGFB (OR = 1.75, 95% CI: 1.04, 2.92 and MMP1 (OR = 2.44, 95% CI: 1.24, 4.81 with protein. Five GEIs were associated with survival at the 5% significance level but not after multiple testing adjustment: CXCR1 (HR = 2.06, 95% CI: 1.13, 3.75 with smoking; and KDR (HR = 4.36, 95% CI: 1.62, 11.73, TLR2 (HR = 9.06, 95% CI: 1.14, 72.11, EGR2 (HR = 2.45, 95% CI: 1.42, 4.22, and EGFR (HR = 6.33, 95% CI: 1.95, 20.54 with protein. GEIs between angiogenesis genes and smoking, alcohol, and animal protein impact rectal cancer risk. Our results support the importance of considering the biologic hypothesis to characterize GEIs associated with cancer outcomes.

Microsatellite polymorphisms associated with human behavioural and psychological phenotypes including a gene-environment interaction.

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Bagshaw, Andrew T M; Horwood, L John; Fergusson, David M; Gemmell, Neil J; Kennedy, Martin A

2017-02-03

The genetic and environmental influences on human personality and behaviour are a complex matter of ongoing debate. Accumulating evidence indicates that short tandem repeats (STRs) in regulatory regions are good candidates to explain heritability not accessed by genome-wide association studies. We tested for associations between the genotypes of four selected repeats and 18 traits relating to personality, behaviour, cognitive ability and mental health in a well-studied longitudinal birth cohort (n = 458-589) using one way analysis of variance. The repeats were a highly conserved poly-AC microsatellite in the upstream promoter region of the T-box brain 1 (TBR1) gene and three previously studied STRs in the activating enhancer-binding protein 2-beta (AP2-β) and androgen receptor (AR) genes. Where significance was found we used multiple regression to assess the influence of confounding factors. Carriers of the shorter, most common, allele of the AR gene's GGN microsatellite polymorphism had fewer anxiety-related symptoms, which was consistent with previous studies, but in our study this was not significant following Bonferroni correction. No associations with two repeats in the AP2-β gene withstood this correction. A novel finding was that carriers of the minor allele of the TBR1 AC microsatellite were at higher risk of conduct problems in childhood at age 7-9 (p = 0.0007, which did pass Bonferroni correction). Including maternal smoking during pregnancy (MSDP) in models controlling for potentially confounding influences showed that an interaction between TBR1 genotype and MSDP was a significant predictor of conduct problems in childhood and adolescence (p behaviour up to age 25 years (p ≤ 0.02). This interaction remained significant after controlling for possible confounders including maternal age at birth, socio-economic status and education, and offspring birth weight. The potential functional importance of the TBR1 gene's promoter microsatellite

Gene-environment interactions linking air pollution and inflammation in Parkinson's disease.

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Lee, Pei-Chen; Raaschou-Nielsen, Ole; Lill, Christina M; Bertram, Lars; Sinsheimer, Janet S; Hansen, Johnni; Ritz, Beate

2016-11-01

Both air pollution exposure and systemic inflammation have been linked to Parkinson's disease (PD). In the PASIDA study, 408 incident cases of PD diagnosed in 2006-2009 and their 495 population controls were interviewed and provided DNA samples. Markers of long term traffic related air pollution measures were derived from geographic information systems (GIS)-based modeling. Furthermore, we genotyped functional polymorphisms in genes encoding proinflammatory cytokines, namely rs1800629 in TNFα (tumor necrosis factor alpha) and rs16944 in IL1B (interleukin-1β). In logistic regression models, long-term exposure to NO 2 increased PD risk overall (odds ratio (OR)=1.06 per 2.94μg/m 3 increase, 95% CI=1.00-1.13). The OR for PD in individuals with high NO 2 exposure (≧75th percentile) and the AA genotype of IL1B rs16944 was 3.10 (95% CI=1.14-8.38) compared with individuals with lower NO 2 exposure (<75th percentile) and the GG genotype. The interaction term was nominally significant on the multiplicative scale (p=0.01). We did not find significant gene-environment interactions with TNF rs1800629. Our finds may provide suggestive evidence that a combination of traffic-related air pollution and genetic variation in the proinflammatory cytokine gene IL1B contribute to risk of developing PD. However, as statistical evidence was only modest in this large sample we cannot rule out that these results represent a chance finding, and additional replication efforts are warranted. Copyright © 2016 Elsevier Inc. All rights reserved.

Gene-Environment Interactions in Genome-Wide Association Studies: Current Approaches and New Directions

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Winham, Stacey J.; Biernacka, Joanna M.

2013-01-01

Background: Complex psychiatric traits have long been thought to be the result of a combination of genetic and environmental factors, and gene-environment interactions are thought to play a crucial role in behavioral phenotypes and the susceptibility and progression of psychiatric disorders. Candidate gene studies to investigate hypothesized…

Epistasis × environment interactions among Arabidopsis thaliana glucosinolate genes impact complex traits and fitness in the field.

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Kerwin, Rachel E; Feusier, Julie; Muok, Alise; Lin, Catherine; Larson, Brandon; Copeland, Daniel; Corwin, Jason A; Rubin, Matthew J; Francisco, Marta; Li, Baohua; Joseph, Bindu; Weinig, Cynthia; Kliebenstein, Daniel J

2017-08-01

Despite the growing number of studies showing that genotype × environment and epistatic interactions control fitness, the influences of epistasis × environment interactions on adaptive trait evolution remain largely uncharacterized. Across three field trials, we quantified aliphatic glucosinolate (GSL) defense chemistry, leaf damage, and relative fitness using mutant lines of Arabidopsis thaliana varying at pairs of causal aliphatic GSL defense genes to test the impact of epistatic and epistasis × environment interactions on adaptive trait variation. We found that aliphatic GSL accumulation was primarily influenced by additive and epistatic genetic variation, leaf damage was primarily influenced by environmental variation and relative fitness was primarily influenced by epistasis and epistasis × environment interactions. Epistasis × environment interactions accounted for up to 48% of the relative fitness variation in the field. At a single field site, the impact of epistasis on relative fitness varied significantly over 2 yr, showing that epistasis × environment interactions within a location can be temporally dynamic. These results suggest that the environmental dependency of epistasis can profoundly influence the response to selection, shaping the adaptive trajectories of natural populations in complex ways, and deserves further consideration in future evolutionary studies. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Gene environment interaction studies in depression and suicidal behavior: An update.

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Mandelli, Laura; Serretti, Alessandro

2013-12-01

Increasing evidence supports the involvement of both heritable and environmental risk factors in major depression (MD) and suicidal behavior (SB). Studies investigating gene-environment interaction (G × E) may be useful for elucidating the role of biological mechanisms in the risk for mental disorders. In the present paper, we review the literature regarding the interaction between genes modulating brain functions and stressful life events in the etiology of MD and SB and discuss their potential added benefit compared to genetic studies only. Within the context of G × E investigation, thus far, only a few reliable results have been obtained, although some genes have consistently shown interactive effects with environmental risk in MD and, to a lesser extent, in SB. Further investigation is required to disentangle the direct and mediated effects that are common or specific to MD and SB. Since traditional G × E studies overall suffer from important methodological limitations, further effort is required to develop novel methodological strategies with an interdisciplinary approach. Copyright © 2013 Elsevier Ltd. All rights reserved.

Gene Environment Interactions and Predictors of Colorectal Cancer in Family-Based, Multi-Ethnic Groups.

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Shiao, S Pamela K; Grayson, James; Yu, Chong Ho; Wasek, Brandi; Bottiglieri, Teodoro

2018-02-16

For the personalization of polygenic/omics-based health care, the purpose of this study was to examine the gene-environment interactions and predictors of colorectal cancer (CRC) by including five key genes in the one-carbon metabolism pathways. In this proof-of-concept study, we included a total of 54 families and 108 participants, 54 CRC cases and 54 matched family friends representing four major racial ethnic groups in southern California (White, Asian, Hispanics, and Black). We used three phases of data analytics, including exploratory, family-based analyses adjusting for the dependence within the family for sharing genetic heritage, the ensemble method, and generalized regression models for predictive modeling with a machine learning validation procedure to validate the results for enhanced prediction and reproducibility. The results revealed that despite the family members sharing genetic heritage, the CRC group had greater combined gene polymorphism rates than the family controls ( p relation to gene-environment interactions in the prevention of CRC.

Evidence for gene-environment interaction in a genome wide study of isolated, non-syndromic cleft palate

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Beaty, Terri H.; Ruczinski, Ingo; Murray, Jeffrey C.; Marazita, Mary L.; Munger, Ronald G.; Hetmanski, Jacqueline B.; Murray, Tanda; Redett, Richard J.; Fallin, M. Daniele; Liang, Kung Yee; Wu, Tao; Patel, Poorav J.; Jin, Sheng C.; Zhang, Tian Xiao; Schwender, Holger; Wu-Chou, Yah Huei; Chen, Philip K; Chong, Samuel S; Cheah, Felicia; Yeow, Vincent; Ye, Xiaoqian; Wang, Hong; Huang, Shangzhi; Jabs, Ethylin W.; Shi, Bing; Wilcox, Allen J.; Lie, Rolv T.; Jee, Sun Ha; Christensen, Kaare; Doheny, Kimberley F.; Pugh, Elizabeth W.; Ling, Hua; Scott, Alan F.

2011-01-01

Non-syndromic cleft palate (CP) is a common birth defect with a complex and heterogeneous etiology involving both genetic and environmental risk factors. We conducted a genome wide association study (GWAS) using 550 case-parent trios, ascertained through a CP case collected in an international consortium. Family based association tests of single nucleotide polymorphisms (SNP) and three common maternal exposures (maternal smoking, alcohol consumption and multivitamin supplementation) were used in a combined 2 df test for gene (G) and gene-environment (G×E) interaction simultaneously, plus a separate 1 df test for G×E interaction alone. Conditional logistic regression models were used to estimate effects on risk to exposed and unexposed children. While no SNP achieved genome wide significance when considered alone, markers in several genes attained or approached genome wide significance when G×E interaction was included. Among these, MLLT3 and SMC2 on chromosome 9 showed multiple SNPs resulting in increased risk if the mother consumed alcohol during the peri-conceptual period (3 months prior to conception through the first trimester). TBK1 on chr. 12 and ZNF236 on chr. 18 showed multiple SNPs associated with higher risk of CP in the presence of maternal smoking. Additional evidence of reduced risk due to G×E interaction in the presence of multivitamin supplementation was observed for SNPs in BAALC on chr. 8. These results emphasize the need to consider G×E interaction when searching for genes influencing risk to complex and heterogeneous disorders, such as non-syndromic CP. PMID:21618603

Gene-environment interaction and covariation in schizophrenia: the role of obstetric complications.

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Mittal, Vijay A; Ellman, Lauren M; Cannon, Tyrone D

2008-11-01

While genetic factors account for a significant proportion of liability to schizophrenia, a body of evidence attests to a significant environmental contribution. Understanding the mechanisms through which genetic and environmental factors coalesce in influencing schizophrenia is critical for elucidating the pathways underlying psychotic illness and for developing primary prevention strategies. Although obstetric complications (OCs) remain among the most well-documented environmental indicators of risk for schizophrenia, the pathogenic role they play in the etiology of schizophrenia continues to remain poorly understood. A question of major importance is do these factors result from a genetic diathesis to schizophrenia (as in gene-environment covariation), act additively or interactively with predisposing genes for the disorder in influencing disease risk, or independently cause disease onset? In this review, we evaluate 3 classes of OCs commonly related to schizophrenia including hypoxia-associated OCs, maternal infection during pregnancy, and maternal stress during pregnancy. In addition, we discuss several mechanisms by which OCs impact on genetically susceptible brain regions, increasing constitutional vulnerability to neuromaturational events and stressors later in life (ie, adolescence), which may in turn contribute to triggering psychosis.

A genetic ensemble approach for gene-gene interaction identification

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Ho Joshua WK

2010-10-01

Full Text Available Abstract Background It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases. Though a considerable effort has been put into developing statistical models and algorithmic strategies for identifying such interactions, the accurate identification of those genetic interactions has been proven to be very challenging. Methods In this paper, we propose a new approach for identifying such gene-gene and gene-environment interactions underlying complex diseases. This is a hybrid algorithm and it combines genetic algorithm (GA and an ensemble of classifiers (called genetic ensemble. Using this approach, the original problem of SNP interaction identification is converted into a data mining problem of combinatorial feature selection. By collecting various single nucleotide polymorphisms (SNP subsets as well as environmental factors generated in multiple GA runs, patterns of gene-gene and gene-environment interactions can be extracted using a simple combinatorial ranking method. Also considered in this study is the idea of combining identification results obtained from multiple algorithms. A novel formula based on pairwise double fault is designed to quantify the degree of complementarity. Conclusions Our simulation study demonstrates that the proposed genetic ensemble algorithm has comparable identification power to Multifactor Dimensionality Reduction (MDR and is slightly better than Polymorphism Interaction Analysis (PIA, which are the two most popular methods for gene-gene interaction identification. More importantly, the identification results generated by using our genetic ensemble algorithm are highly complementary to those obtained by PIA and MDR. Experimental results from our simulation studies and real world data application also confirm the effectiveness of the proposed genetic ensemble algorithm, as well as the potential benefits of

Gene by Environment Interaction and Resilience: Effects of Child Maltreatment and Serotonin, Corticotropin Releasing Hormone, Dopamine, and Oxytocin Genes

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Cicchetti, Dante; Rogosch, Fred A.

2013-01-01

In this investigation, gene-environment interaction effects in predicting resilience in adaptive functioning among maltreated and nonmaltreated low-income children (N = 595) were examined. A multi-component index of resilient functioning was derived and levels of resilient functioning were identified. Variants in four genes, 5-HTTLPR, CRHR1, DRD4 -521C/T, and OXTR, were investigated. In a series of ANCOVAs, child maltreatment demonstrated a strong negative main effect on children’s resilient functioning, whereas no main effects for any of the genotypes of the respective genes were found. However, gene-environment interactions involving genotypes of each of the respective genes and maltreatment status were obtained. For each respective gene, among children with a specific genotype, the relative advantage in resilient functioning of nonmaltreated compared to maltreated children was stronger than was the case for nonmaltreated and maltreated children with other genotypes of the respective gene. Across the four genes, a composite of the genotypes that more strongly differentiated resilient functioning between nonmaltreated and maltreated children provided further evidence of genetic variations influencing resilient functioning in nonmaltreated children, whereas genetic variation had a negligible effect on promoting resilience among maltreated children. Additional effects were observed for children based on the number of subtypes of maltreatment children experienced, as well as for abuse and neglect subgroups. Finally, maltreated and nonmaltreated children with high levels of resilience differed in their average number of differentiating genotypes. These results suggest that differential resilient outcomes are based on the interaction between genes and developmental experiences. PMID:22559122

A methodology to establish a database to study gene environment interactions for childhood asthma

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McCormick Jonathan

2010-12-01

Full Text Available Abstract Background Gene-environment interactions are likely to explain some of the heterogeneity in childhood asthma. Here, we describe the methodology and experiences in establishing a database for childhood asthma designed to study gene-environment interactions (PAGES - Paediatric Asthma Gene Environment Study. Methods Children with asthma and under the care of a respiratory paediatrician are being recruited from 15 hospitals between 2008 and 2011. An asthma questionnaire is completed and returned by post. At a routine clinic visit saliva is collected for DNA extraction. Detailed phenotyping in a proportion of children includes spirometry, bronchodilator response (BDR, skin prick reactivity, exhaled nitric oxide and salivary cotinine. Dietary and quality of life questionnaires are completed. Data are entered onto a purpose-built database. Results To date 1045 children have been invited to participate and data collected in 501 (48%. The mean age (SD of participants is 8.6 (3.9 years, 57% male. DNA has been collected in 436 children. Spirometry has been obtained in 172 children, mean % predicted (SD FEV1 97% (15 and median (IQR BDR is 5% (2, 9. There were differences in age, socioeconomic status, severity and %FEV1 between the different centres (p≤0.024. Reasons for non-participation included parents not having time to take part, children not attending clinics and, in a small proportion, refusal to take part. Conclusions It is feasible to establish a national database to study gene-environment interactions within an asthmatic paediatric population; there are barriers to participation and some different characteristics in individuals recruited from different centres. Recruitment to our study continues and is anticipated to extend current understanding of asthma heterogeneity.

Measuring the genetic influence on human life span: gene-environment interaction and sex-specific genetic effects

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Tan, Qihua; De Benedictis, G; Yashin, Annatoli

2001-01-01

New approaches are needed to explore the different ways in which genes affect the human life span. One needs to assess the genetic effects themselves, as well as gene–environment interactions and sex dependency. In this paper, we present a new model that combines both genotypic and demographicinf......New approaches are needed to explore the different ways in which genes affect the human life span. One needs to assess the genetic effects themselves, as well as gene–environment interactions and sex dependency. In this paper, we present a new model that combines both genotypic...

Gene-environment interaction in Major Depression: focus on experience-dependent biological systems

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Nicola eLopizzo

2015-05-01

Full Text Available Major Depressive Disorder (MDD is a multifactorial and polygenic disorder, where multiple and partially overlapping sets of susceptibility genes interact each other and with the environment, predisposing individuals to the development of the illness. Thus, MDD results from a complex interplay of vulnerability genes and environmental factors that act cumulatively throughout individual's lifetime. Among these environmental factors, stressful life experiences, especially those occurring early in life, have been suggested to exert a crucial impact on brain development, leading to permanent functional changes that may contribute to life long risk for mental health outcomes. In this review we will discuss how genetic variants (polymorphisms, SNPs within genes operating in neurobiological systems that mediate stress response and synaptic plasticity, can impact, by themselves, the vulnerability risk for MDD; we will also consider how this MDD risk can be further modulated when gene X environment interaction is taken into account. Finally, we will discuss the role of epigenetic mechanisms, and in particular of DNA methylation and miRNAs expression changes, in mediating the effect of the stress on the vulnerability risk to develop MDD. Taken together, in this review we aim to underlie the role of genetic and epigenetic processes involved in stress and neuroplasticity related biological systems on development of MDD after exposure to early life stress, thereby building the basis for future research and clinical interventions.

Music training and speech perception: a gene-environment interaction.

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Schellenberg, E Glenn

2015-03-01

Claims of beneficial side effects of music training are made for many different abilities, including verbal and visuospatial abilities, executive functions, working memory, IQ, and speech perception in particular. Such claims assume that music training causes the associations even though children who take music lessons are likely to differ from other children in music aptitude, which is associated with many aspects of speech perception. Music training in childhood is also associated with cognitive, personality, and demographic variables, and it is well established that IQ and personality are determined largely by genetics. Recent evidence also indicates that the role of genetics in music aptitude and music achievement is much larger than previously thought. In short, music training is an ideal model for the study of gene-environment interactions but far less appropriate as a model for the study of plasticity. Children seek out environments, including those with music lessons, that are consistent with their predispositions; such environments exaggerate preexisting individual differences. © 2015 New York Academy of Sciences.

A Fast Multiple-Kernel Method With Applications to Detect Gene-Environment Interaction.

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Marceau, Rachel; Lu, Wenbin; Holloway, Shannon; Sale, Michèle M; Worrall, Bradford B; Williams, Stephen R; Hsu, Fang-Chi; Tzeng, Jung-Ying

2015-09-01

Kernel machine (KM) models are a powerful tool for exploring associations between sets of genetic variants and complex traits. Although most KM methods use a single kernel function to assess the marginal effect of a variable set, KM analyses involving multiple kernels have become increasingly popular. Multikernel analysis allows researchers to study more complex problems, such as assessing gene-gene or gene-environment interactions, incorporating variance-component based methods for population substructure into rare-variant association testing, and assessing the conditional effects of a variable set adjusting for other variable sets. The KM framework is robust, powerful, and provides efficient dimension reduction for multifactor analyses, but requires the estimation of high dimensional nuisance parameters. Traditional estimation techniques, including regularization and the "expectation-maximization (EM)" algorithm, have a large computational cost and are not scalable to large sample sizes needed for rare variant analysis. Therefore, under the context of gene-environment interaction, we propose a computationally efficient and statistically rigorous "fastKM" algorithm for multikernel analysis that is based on a low-rank approximation to the nuisance effect kernel matrices. Our algorithm is applicable to various trait types (e.g., continuous, binary, and survival traits) and can be implemented using any existing single-kernel analysis software. Through extensive simulation studies, we show that our algorithm has similar performance to an EM-based KM approach for quantitative traits while running much faster. We also apply our method to the Vitamin Intervention for Stroke Prevention (VISP) clinical trial, examining gene-by-vitamin effects on recurrent stroke risk and gene-by-age effects on change in homocysteine level. © 2015 WILEY PERIODICALS, INC.

Does parental divorce moderate the heritability of body dissatisfaction? An extension of previous gene-environment interaction effects.

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O'Connor, Shannon M; Klump, Kelly L; VanHuysse, Jessica L; McGue, Matt; Iacono, William

2016-02-01

Previous research suggests that parental divorce moderates genetic influences on body dissatisfaction. Specifically, the heritability of body dissatisfaction is higher in children of divorced versus intact families, suggesting possible gene-environment interaction effects. However, prior research is limited to a single, self-reported measure of body dissatisfaction. The primary aim of this study was to examine whether these findings extend to a different dimension of body dissatisfaction: body image perceptions. Participants were 1,534 female twins from the Minnesota Twin Family Study, aged 16-20 years. The Body Rating Scale (BRS) was used to assess body image perceptions. Although BRS scores were heritable in twins from divorced and intact families, the heritability estimates in the divorced group were not significantly greater than estimates in the intact group. However, there were differences in nonshared environmental effects, where the magnitude of these environmental influences was larger in the divorced as compared with the intact families. Different dimensions of body dissatisfaction (i.e., negative self-evaluation versus body image perceptions) may interact with environmental risk, such as parental divorce, in discrete ways. Future research should examine this possibility and explore differential gene-environment interactions using diverse measures. © 2015 Wiley Periodicals, Inc.

How Gene-Environment Interaction Affects Children's Anxious and Fearful Behavior. Science Briefs

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National Scientific Council on the Developing Child, 2007

2007-01-01

"Science Briefs" summarize the findings and implications of a recent study in basic science or clinical research. This brief reports on the study "Evidence for a Gene-Environment Interaction in Predicting Behavioral Inhibition in Middle Childhood" (N. A. Fox, K E. Nichols, H. A. Henderson, K. Rubin, L. Schmidt, D. Hamer, M. Ernst, and D. S.…

Gene-Environment Interaction Research and Transgenic Mouse Models of Alzheimer's Disease

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L. Chouliaras

2010-01-01

Full Text Available The etiology of the sporadic form of Alzheimer's disease (AD remains largely unknown. Recent evidence has suggested that gene-environment interactions (GxE may play a crucial role in its development and progression. Whereas various susceptibility loci have been identified, like the apolipoprotein E4 allele, these cannot fully explain the increasing prevalence of AD observed with aging. In addition to such genetic risk factors, various environmental factors have been proposed to alter the risk of developing AD as well as to affect the rate of cognitive decline in AD patients. Nevertheless, aside from the independent effects of genetic and environmental risk factors, their synergistic participation in increasing the risk of developing AD has been sparsely investigated, even though evidence points towards such a direction. Advances in the genetic manipulation of mice, modeling various aspects of the AD pathology, have provided an excellent tool to dissect the effects of genes, environment, and their interactions. In this paper we present several environmental factors implicated in the etiology of AD that have been tested in transgenic animal models of the disease. The focus lies on the concept of GxE and its importance in a multifactorial disease like AD. Additionally, possible mediating mechanisms and future challenges are discussed.

Gene-environment interaction and behavioral disorders: a developmental perspective based on endophenotypes.

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Battaglia, Marco; Marino, Cecilia; Maziade, Michel; Molteni, Massimo; D'Amato, Francesca

2008-01-01

It has been observed that 'No aspect of human behavioral genetics has caused more confusion and generated more obscurantism than the analysis and interpretation of various types of non-additivity and non-independence of gene and environmental action and interaction' (Eaves LJ et al 1977 Br J Math Stat Psychol 30:1-42). On the other hand, a bulk of newly published studies appear to speak in favour of common and frequent interplay--and possibly interaction--between identified genetic polymorphisms and specified environmental variables in shaping behavior and behavioral disorders. Considerable interest has arisen from the introduction of putative functional 'endophenotypes' which would represent a more proximate biological link to genes, as well as an obligatory intermediate of behavior. While explicit criteria to identify valid endophenotypes have been offered, a number of new 'alternative phenotypes' are now being proposed as possible 'endophenotypes' for behavioral and psychiatric genetics research, sometimes with less than optimal stringency. Nonetheless, we suggest that some endophenotypes can be helpful in investigating several instances of gene-environment interactions and be employed as additional tools to reduce the risk for spurious results in this controversial area.

An Efficient Test for Gene-Environment Interaction in Generalized Linear Mixed Models with Family Data.

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Mazo Lopera, Mauricio A; Coombes, Brandon J; de Andrade, Mariza

2017-09-27

Gene-environment (GE) interaction has important implications in the etiology of complex diseases that are caused by a combination of genetic factors and environment variables. Several authors have developed GE analysis in the context of independent subjects or longitudinal data using a gene-set. In this paper, we propose to analyze GE interaction for discrete and continuous phenotypes in family studies by incorporating the relatedness among the relatives for each family into a generalized linear mixed model (GLMM) and by using a gene-based variance component test. In addition, we deal with collinearity problems arising from linkage disequilibrium among single nucleotide polymorphisms (SNPs) by considering their coefficients as random effects under the null model estimation. We show that the best linear unbiased predictor (BLUP) of such random effects in the GLMM is equivalent to the ridge regression estimator. This equivalence provides a simple method to estimate the ridge penalty parameter in comparison to other computationally-demanding estimation approaches based on cross-validation schemes. We evaluated the proposed test using simulation studies and applied it to real data from the Baependi Heart Study consisting of 76 families. Using our approach, we identified an interaction between BMI and the Peroxisome Proliferator Activated Receptor Gamma ( PPARG ) gene associated with diabetes.

BDNF Val66Met polymorphism, life stress and depression: A meta-analysis of gene-environment interaction.

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Zhao, Mingzhe; Chen, Lu; Yang, Jiarun; Han, Dong; Fang, Deyu; Qiu, Xiaohui; Yang, Xiuxian; Qiao, Zhengxue; Ma, Jingsong; Wang, Lin; Jiang, Shixiang; Song, Xuejia; Zhou, Jiawei; Zhang, Jian; Chen, Mingqi; Qi, Dong; Yang, Yanjie; Pan, Hui

2018-02-01

Depression is thought to be multifactorial in etiology, including genetic and environmental components. While a number of gene-environment interaction studies have been carried out, meta-analyses are scarce. The present meta-analysis aimed to quantify evidence on the interaction between brain-derived neurotrophic factor (BDNF) Val66Met polymorphism and stress in depression. Included were 31 peer-reviewed with a pooled total of 21060 participants published before October 2016 and literature searches were conducted using PubMed, Wolters Kluwer, Web of Science, EBSCO, Elsevier Science Direct and Baidu Scholar databases. The results indicated that the Met allele of BDNF Val66Met polymorphism significantly moderated the relationship between stress and depression (Z=2.666, p = 0.003). The results of subgroup analysis concluded that stressful life events and childhood adversity separately interacted with the Met allele of BDNF Val66Met polymorphism in depression (Z = 2.552, p = 0.005; Z = 1.775, p = 0.03). The results could be affected by errors or bias in primary studies which had small sample sizes with relatively lower statistic power. We could not estimate how strong the interaction effect between gene and environment was. We found evidence that supported the hypothesis that BDNF Val66Met polymorphism moderated the relationship between stress and depression, despite the fact that many included individual studies did not show this effect. Copyright © 2017 Elsevier B.V. All rights reserved.

Gene Environment Interactions and Predictors of Colorectal Cancer in Family-Based, Multi-Ethnic Groups

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S. Pamela K. Shiao

2018-02-01

Full Text Available For the personalization of polygenic/omics-based health care, the purpose of this study was to examine the gene–environment interactions and predictors of colorectal cancer (CRC by including five key genes in the one-carbon metabolism pathways. In this proof-of-concept study, we included a total of 54 families and 108 participants, 54 CRC cases and 54 matched family friends representing four major racial ethnic groups in southern California (White, Asian, Hispanics, and Black. We used three phases of data analytics, including exploratory, family-based analyses adjusting for the dependence within the family for sharing genetic heritage, the ensemble method, and generalized regression models for predictive modeling with a machine learning validation procedure to validate the results for enhanced prediction and reproducibility. The results revealed that despite the family members sharing genetic heritage, the CRC group had greater combined gene polymorphism rates than the family controls (p < 0.05, on MTHFR C677T, MTR A2756G, MTRR A66G, and DHFR 19 bp except MTHFR A1298C. Four racial groups presented different polymorphism rates for four genes (all p < 0.05 except MTHFR A1298C. Following the ensemble method, the most influential factors were identified, and the best predictive models were generated by using the generalized regression models, with Akaike’s information criterion and leave-one-out cross validation methods. Body mass index (BMI and gender were consistent predictors of CRC for both models when individual genes versus total polymorphism counts were used, and alcohol use was interactive with BMI status. Body mass index status was also interactive with both gender and MTHFR C677T gene polymorphism, and the exposure to environmental pollutants was an additional predictor. These results point to the important roles of environmental and modifiable factors in relation to gene–environment interactions in the prevention of CRC.

Research progress in machine learning methods for gene-gene interaction detection.

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Peng, Zhe-Ye; Tang, Zi-Jun; Xie, Min-Zhu

2018-03-20

Complex diseases are results of gene-gene and gene-environment interactions. However, the detection of high-dimensional gene-gene interactions is computationally challenging. In the last two decades, machine-learning approaches have been developed to detect gene-gene interactions with some successes. In this review, we summarize the progress in research on machine learning methods, as applied to gene-gene interaction detection. It systematically examines the principles and limitations of the current machine learning methods used in genome wide association studies (GWAS) to detect gene-gene interactions, such as neural networks (NN), random forest (RF), support vector machines (SVM) and multifactor dimensionality reduction (MDR), and provides some insights on the future research directions in the field.

Assessing the joint effect of population stratification and sample selection in studies of gene-gene (environment interactions

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Cheng KF

2012-01-01

Full Text Available Abstract Background It is well known that the presence of population stratification (PS may cause the usual test in case-control studies to produce spurious gene-disease associations. However, the impact of the PS and sample selection (SS is less known. In this paper, we provide a systematic study of the joint effect of PS and SS under a more general risk model containing genetic and environmental factors. We provide simulation results to show the magnitude of the bias and its impact on type I error rate of the usual chi-square test under a wide range of PS level and selection bias. Results The biases to the estimation of main and interaction effect are quantified and then their bounds derived. The estimated bounds can be used to compute conservative p-values for the association test. If the conservative p-value is smaller than the significance level, we can safely claim that the association test is significant regardless of the presence of PS or not, or if there is any selection bias. We also identify conditions for the null bias. The bias depends on the allele frequencies, exposure rates, gene-environment odds ratios and disease risks across subpopulations and the sampling of the cases and controls. Conclusion Our results show that the bias cannot be ignored even the case and control data were matched in ethnicity. A real example is given to illustrate application of the conservative p-value. These results are useful to the genetic association studies of main and interaction effects.

Enhancing the gene-environment interaction framework through a quasi-experimental research design: evidence from differential responses to September 11.

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Fletcher, Jason M

2014-01-01

This article uses a gene-environment interaction framework to examine the differential responses to an objective external stressor based on genetic variation in the production of depressive symptoms. This article advances the literature by utilizing a quasi-experimental environmental exposure design, as well as a regression discontinuity design, to control for seasonal trends, which limit the potential for gene-environment correlation and allow stronger causal claims. Replications are attempted for two prominent genes (5-HTT and MAOA), and three additional genes are explored (DRD2, DRD4, and DAT1). This article provides evidence of a main effect of 9/11 on reports of feelings of sadness and fails to replicate a common finding of interaction using 5-HTT but does show support for interaction with MAOA in men. It also provides new evidence that variation in the DRD4 gene modifies an individual's response to the exposure, with individuals with no 7-repeats found to have a muted response.

Environmental and gene-environment interactions and risk of rheumatoid arthritis

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Karlson, Elizabeth W.; Deane, Kevin

2012-01-01

Multiple environmental factors including hormones, dietary factors, infections and exposure to tobacco smoke as well as gene-environment interactions have been associated with increased risk for rheumatoid arthritis (RA). Importantly, the growing understanding of the prolonged period prior to the first onset of symptoms of RA suggests that these environmental and genetic factors are likely acting to drive the development of RA-related autoimmunity long before the appearance of the first joint symptoms and clinical findings that are characteristic of RA. Herein we will review these factors and interactions, especially those that have been investigated in a prospective fashion prior to the symptomatic onset of RA. We will also discuss how these factors may be explored in future study to further the understanding of the pathogenesis of RA, and ultimately perhaps develop preventive measures for this disease. PMID:22819092

The genetics of music accomplishment: evidence for gene-environment correlation and interaction.

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Hambrick, David Z; Tucker-Drob, Elliot M

2015-02-01

Theories of skilled performance that emphasize training history, such as K. Anders Ericsson and colleagues' deliberate-practice theory, have received a great deal of recent attention in both the scientific literature and the popular press. Twin studies, however, have demonstrated evidence for moderate-to-strong genetic influences on skilled performance. Focusing on musical accomplishment in a sample of over 800 pairs of twins, we found evidence for gene-environment correlation, in the form of a genetic effect on music practice. However, only about one quarter of the genetic effect on music accomplishment was explained by this genetic effect on music practice, suggesting that genetically influenced factors other than practice contribute to individual differences in music accomplishment. We also found evidence for gene-environment interaction, such that genetic effects on music accomplishment were most pronounced among those engaging in music practice, suggesting that genetic potentials for skilled performance are most fully expressed and fostered by practice.

Evidence for gene-environment interaction in a genome wide study of nonsyndromic cleft palate

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Beaty, Terri H; Ruczinski, Ingo; Murray, Jeffrey C

2011-01-01

Nonsyndromic cleft palate (CP) is a common birth defect with a complex and heterogeneous etiology involving both genetic and environmental risk factors. We conducted a genome-wide association study (GWAS) using 550 case-parent trios, ascertained through a CP case collected in an international...... consortium. Family-based association tests of single nucleotide polymorphisms (SNP) and three common maternal exposures (maternal smoking, alcohol consumption, and multivitamin supplementation) were used in a combined 2 df test for gene (G) and gene-environment (G × E) interaction simultaneously, plus...... multiple SNPs associated with higher risk of CP in the presence of maternal smoking. Additional evidence of reduced risk due to G × E interaction in the presence of multivitamin supplementation was observed for SNPs in BAALC on chr. 8. These results emphasize the need to consider G × E interaction when...

Interaction between Social/Psychosocial Factors and Genetic Variants on Body Mass Index: A Gene-Environment Interaction Analysis in a Longitudinal Setting.

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Zhao, Wei; Ware, Erin B; He, Zihuai; Kardia, Sharon L R; Faul, Jessica D; Smith, Jennifer A

2017-09-29

Obesity, which develops over time, is one of the leading causes of chronic diseases such as cardiovascular disease. However, hundreds of BMI (body mass index)-associated genetic loci identified through large-scale genome-wide association studies (GWAS) only explain about 2.7% of BMI variation. Most common human traits are believed to be influenced by both genetic and environmental factors. Past studies suggest a variety of environmental features that are associated with obesity, including socioeconomic status and psychosocial factors. This study combines both gene/regions and environmental factors to explore whether social/psychosocial factors (childhood and adult socioeconomic status, social support, anger, chronic burden, stressful life events, and depressive symptoms) modify the effect of sets of genetic variants on BMI in European American and African American participants in the Health and Retirement Study (HRS). In order to incorporate longitudinal phenotype data collected in the HRS and investigate entire sets of single nucleotide polymorphisms (SNPs) within gene/region simultaneously, we applied a novel set-based test for gene-environment interaction in longitudinal studies (LGEWIS). Childhood socioeconomic status (parental education) was found to modify the genetic effect in the gene/region around SNP rs9540493 on BMI in European Americans in the HRS. The most significant SNP (rs9540488) by childhood socioeconomic status interaction within the rs9540493 gene/region was suggestively replicated in the Multi-Ethnic Study of Atherosclerosis (MESA) ( p = 0.07).

Interaction between Social/Psychosocial Factors and Genetic Variants on Body Mass Index: A Gene-Environment Interaction Analysis in a Longitudinal Setting

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Wei Zhao

2017-09-01

Full Text Available Obesity, which develops over time, is one of the leading causes of chronic diseases such as cardiovascular disease. However, hundreds of BMI (body mass index-associated genetic loci identified through large-scale genome-wide association studies (GWAS only explain about 2.7% of BMI variation. Most common human traits are believed to be influenced by both genetic and environmental factors. Past studies suggest a variety of environmental features that are associated with obesity, including socioeconomic status and psychosocial factors. This study combines both gene/regions and environmental factors to explore whether social/psychosocial factors (childhood and adult socioeconomic status, social support, anger, chronic burden, stressful life events, and depressive symptoms modify the effect of sets of genetic variants on BMI in European American and African American participants in the Health and Retirement Study (HRS. In order to incorporate longitudinal phenotype data collected in the HRS and investigate entire sets of single nucleotide polymorphisms (SNPs within gene/region simultaneously, we applied a novel set-based test for gene-environment interaction in longitudinal studies (LGEWIS. Childhood socioeconomic status (parental education was found to modify the genetic effect in the gene/region around SNP rs9540493 on BMI in European Americans in the HRS. The most significant SNP (rs9540488 by childhood socioeconomic status interaction within the rs9540493 gene/region was suggestively replicated in the Multi-Ethnic Study of Atherosclerosis (MESA (p = 0.07.

The Ethics of Translational Science: Imagining Public Benefit in Gene-Environment Interaction Research

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Sara L. Ackerman

2017-06-01

Full Text Available Biomedical research is increasingly informed by expectations of “translation,” which call for the production of scientific knowledge that can be used to create services and products that improve health outcomes. In this paper, we ask how translation, in particular the idea of social responsibility, is understood and enacted in the post-genomic life sciences. Drawing on theories examining what constitutes “good science,” and interviews with 35 investigators who study the role of gene-environment interactions in the etiology of cancer, diabetes, and cardiovascular disease, we describe the dynamic and unsettled ethics of translational science through which the expected social value of scientific knowledge about complex disease causation is negotiated. To describe how this ethics is formed, we first discuss the politics of knowledge production in interdisciplinary research collectives. Researchers described a commitment to working across disciplines to examine a wide range of possible causes of disease, but they also pointed to persistent disciplinary and ontological divisions that rest on the dominance of molecular conceptions of disease risk. The privileging of molecular-level causation shapes and constrains the kinds of knowledge that can be created about gene-environment interactions. We then turn to scientists’ ideas about how this knowledge should be used, including personalized prevention strategies, targeted therapeutics, and public policy interventions. Consensus about the relative value of these anticipated translations was elusive, and many scientists agreed that gene-environment interaction research is part of a shift in biomedical research away from considering important social, economic, political and historical causes of disease and disease disparities. We conclude by urging more explicit engagement with questions about the ethics of translational science in the post-genomic life sciences. This would include a consideration

Gene-gene interaction between MSX1 and TP63 in Asian case-parent trios with nonsyndromic cleft lip with or without cleft palate.

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Liu, Dongjing; Schwender, Holger; Wang, Mengying; Wang, Hong; Wang, Ping; Zhu, Hongping; Zhou, Zhibo; Li, Jing; Wu, Tao; Beaty, Terri H

2018-03-01

Small ubiquitin-like modification, also known as sumoylation, is a crucial post-translational regulatory mechanisms involved in development of the lip and palate. Recent studies reported two sumoylation target genes, MSX1 and TP63, to have achieved genome-wide level significance in tests of association with nonsyndromic clefts. Here, we performed a candidate gene analysis considering gene-gene and gene-environment interaction for SUMO1, MSX1, and TP63 to further explore the etiology of nonsyndromic cleft lip with or without cleft palate (NSCL/P). A total of 130 single-nucleotide polymorphisms (SNPs) in or near SUMO1, MSX1, and TP63 was analyzed among 1,038 Asian NSCL/P trios ascertained through an international consortium. Conditional logistic regression models were used to explore gene-gene (G × G) and gene-environment (G × E) interaction involving maternal environmental tobacco smoke and multivitamin supplementation. Bonferroni correction was used for G × E analysis and permutation tests were used for G × G analysis. While transmission disequilibrium tests and gene-environment interaction analysis showed no significant results, we did find signals of gene-gene interaction between SNPs near MSX1 and TP63. Three pairwise interactions yielded significant p values in permutation tests (rs884690 and rs9290890 with p = 9.34 × 10 -5 and empirical p = 1.00 × 10 -4 , rs1022136 and rs4687098 with p = 2.41 × 10 -4 and empirical p = 2.95 × 10 -4 , rs6819546 and rs9681004 with p = 5.15 × 10 -4 and empirical p = 3.02 × 10 -4 ). Gene-gene interaction between MSX1 and TP63 may influence the risk of NSCL/P in Asian populations. Our study provided additional understanding of the genetic etiology of NSCL/P and underlined the importance of considering gene-gene interaction in the etiology of this common craniofacial malformation. © 2018 Wiley Periodicals, Inc.

Genes and environment in neonatal intraventricular hemorrhage.

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Ment, Laura R; Ådén, Ulrika; Bauer, Charles R; Bada, Henrietta S; Carlo, Waldemar A; Kaiser, Jeffrey R; Lin, Aiping; Cotten, Charles Michael; Murray, Jeffrey; Page, Grier; Hallman, Mikko; Lifton, Richard P; Zhang, Heping

2015-12-01

Emerging data suggest intraventricular hemorrhage (IVH) of the preterm neonate is a complex disorder with contributions from both the environment and the genome. Environmental analyses suggest factors mediating both cerebral blood flow and angiogenesis contribute to IVH, while candidate gene studies report variants in angiogenesis, inflammation, and vascular pathways. Gene-by-environment interactions demonstrate the interaction between the environment and the genome, and a non-replicated genome-wide association study suggests that both environmental and genetic factors contribute to the risk for severe IVH in very low-birth weight preterm neonates. Copyright © 2015 Elsevier Inc. All rights reserved.

Gene-based interaction analysis shows GABAergic genes interacting with parenting in adolescent depressive symptoms

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Van Assche, Evelien; Moons, Tim; Cinar, Ozan; Viechtbauer, Wolfgang; Oldehinkel, Albertine J.; Van Leeuwen, Karla; Verschueren, Karine; Colpin, Hilde; Lambrechts, Diether; Van den Noortgate, Wim; Goossens, Luc; Claes, Stephan; van Winkel, Ruud

2017-01-01

BACKGROUND: Most gene-environment interaction studies (G × E) have focused on single candidate genes. This approach is criticized for its expectations of large effect sizes and occurrence of spurious results. We describe an approach that accounts for the polygenic nature of most psychiatric

Oh, Behave! Behavior as an Interaction between Genes & the Environment

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Weigel, Emily G.; DeNieu, Michael; Gall, Andrew J.

2014-01-01

This lesson is designed to teach students that behavior is a trait shaped by both genes and the environment. Students will read a scientific paper, discuss and generate predictions based on the ideas and data therein, and model the relationships between genes, the environment, and behavior. The lesson is targeted to meet the educational goals of…

A review for detecting gene-gene interactions using machine learning methods in genetic epidemiology.

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Koo, Ching Lee; Liew, Mei Jing; Mohamad, Mohd Saberi; Salleh, Abdul Hakim Mohamed

2013-01-01

Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs), support vector machine (SVM), and random forests (RFs) in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.

A Review for Detecting Gene-Gene Interactions Using Machine Learning Methods in Genetic Epidemiology

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Ching Lee Koo

2013-01-01

Full Text Available Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs, support vector machine (SVM, and random forests (RFs in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.

Parental divorce and disordered eating: an investigation of a gene-environment interaction.

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Suisman, Jessica L; Burt, S Alexandra; McGue, Matt; Iacono, William G; Klump, Kelly L

2011-03-01

We investigated gene-environment interactions (GxE) for associations between parental divorce and disordered eating (DE). Participants were 1,810 female twins from the Michigan State University Twin Registry and the Minnesota Twin Family Study. The Minnesota Eating Behaviors Survey was used to assess DE. We tested for GxE by comparing the heritability of DE in twins from divorced versus intact families. It was hypothesized that divorce would moderate the heritability of DE, in that heritability would be higher in twins from divorced than twins from intact families. As expected, the heritability of body dissatisfaction was significantly higher in twins from divorced than intact families. However, genetic influences were equal in twins from divorced and intact families for all other forms of DE. Although divorce did not moderate heritability of most DE symptoms, future research should replicate GxEs for body dissatisfaction and identify factors underlying this unique relationship. Copyright © 2010 Wiley Periodicals, Inc.

Evidence of gene-environment interactions between common breast cancer susceptibility loci and established environmental risk factors

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Nickels, Stefan; Truong, Thérèse; Hein, Rebecca

2013-01-01

Various common genetic susceptibility loci have been identified for breast cancer; however, it is unclear how they combine with lifestyle/environmental risk factors to influence risk. We undertook an international collaborative study to assess gene-environment interaction for risk of breast cance...

Evidence of gene-environment interactions between common breast cancer susceptibility loci and established environmental risk factors

NARCIS (Netherlands)

Nickels, S.; Truong, T.; Hein, R.; Stevens, K.; Buck, K.; Behrens, S.; Eilber, U.; Schmidt, M.; Haberle, L.; Vrieling, A.; Gaudet, M.; Figueroa, J.; Schoof, N.; Spurdle, A.B.; Rudolph, A.; Fasching, P.A.; Hopper, J.L.; Makalic, E.; Schmidt, D.F.; Southey, M.C.; Beckmann, M.W.; Ekici, A.B.; Fletcher, O.; Gibson, L.; Idos, S. Silva; Peto, J.; Humphreys, M.K.; Wang, J; Cordina-Duverger, E.; Menegaux, F.; Nordestgaard, B.G.; Bojesen, S.E.; Lanng, C.; Anton-Culver, H.; Ziogas, A.; Bernstein, L.; Clarke, C.A.; Brenner, H.; Muller, H.; Arndt, V.; Stegmaier, C.; Brauch, H.; Bruning, T.; Harth, V.; Genica, N.; Mannermaa, A.; Kataja, V.; Kosma, V.M.; Hartikainen, J.M.; Lambrechts, D.; Smeets, D.; Neven, P.; Paridaens, R.; Flesch-Janys, D.; Obi, N.; Wang-Gohrke, S.; Couch, F.J.; Olson, J.E.; Vachon, C.M.; Giles, G.G.; Severi, G.; Baglietto, L.; Offit, K.; John, E.M.; Miron, A.; Andrulis, I.L.; Knight, J.A.; Glendon, G.; Mulligan, A.M.; Chanock, S.J.; Lissowska, J.; Liu, J.; Cox, A; Cramp, H.; Connley, D.; Balasubramanian, S.; Dunning, A.M.; Shah, M.; Trentham-Dietz, A.; Newcomb, P.; Titus, L.; Egan, K.; Cahoon, E.K.; Rajaraman, P.; Sigurdson, A.J.; Doody, M.M.; Guenel, P.; Pharoah, P.D.; Schmidt, M.K.; Hall, P.; Easton, D.F.; Garcia-Closas, M.; Milne, R.L.; Chang-Claude, J.; et al.,

2013-01-01

Various common genetic susceptibility loci have been identified for breast cancer; however, it is unclear how they combine with lifestyle/environmental risk factors to influence risk. We undertook an international collaborative study to assess gene-environment interaction for risk of breast cancer.

Operating Characteristics of Statistical Methods for Detecting Gene-by-Measured Environment Interaction in the Presence of Gene-Environment Correlation under Violations of Distributional Assumptions.

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Van Hulle, Carol A; Rathouz, Paul J

2015-02-01

Accurately identifying interactions between genetic vulnerabilities and environmental factors is of critical importance for genetic research on health and behavior. In the previous work of Van Hulle et al. (Behavior Genetics, Vol. 43, 2013, pp. 71-84), we explored the operating characteristics for a set of biometric (e.g., twin) models of Rathouz et al. (Behavior Genetics, Vol. 38, 2008, pp. 301-315), for testing gene-by-measured environment interaction (GxM) in the presence of gene-by-measured environment correlation (rGM) where data followed the assumed distributional structure. Here we explore the effects that violating distributional assumptions have on the operating characteristics of these same models even when structural model assumptions are correct. We simulated N = 2,000 replicates of n = 1,000 twin pairs under a number of conditions. Non-normality was imposed on either the putative moderator or on the ultimate outcome by ordinalizing or censoring the data. We examined the empirical Type I error rates and compared Bayesian information criterion (BIC) values. In general, non-normality in the putative moderator had little impact on the Type I error rates or BIC comparisons. In contrast, non-normality in the outcome was often mistaken for or masked GxM, especially when the outcome data were censored.

Gene-Lifestyle Interactions in Obesity.

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van Vliet-Ostaptchouk, Jana V; Snieder, Harold; Lagou, Vasiliki

2012-01-01

Obesity is a complex multifaceted disease resulting from interactions between genetics and lifestyle. The proportion of phenotypic variance ascribed to genetic variance is 0.4 to 0.7 for obesity and recent years have seen considerable success in identifying disease-susceptibility variants. Although with the advent of genome-wide association studies the list of genetic variants predisposing to obesity has significantly increased the identified variants only explain a fraction of disease heritability. Studies of gene-environment interactions can provide more insight into the biological mechanisms involved in obesity despite the challenges associated with such designs. Epigenetic changes that affect gene function without DNA sequence modifications may be a key factor explaining interindividual differences in obesity, with both genetic and environmental factors influencing the epigenome. Disentangling the relative contributions of genetic, environmental and epigenetic marks to the establishment of obesity is a major challenge given the complex interplay between these determinants.

Identification of New Genetic Susceptibility Loci for Breast Cancer Through Consideration of Gene-Environment Interactions

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Schoeps, Anja; Rudolph, Anja; Seibold, Petra; Dunning, Alison M.; Milne, Roger L.; Bojesen, Stig E.; Swerdlow, Anthony; Andrulis, Irene; Brenner, Hermann; Behrens, Sabine; Orr, Nicholas; Jones, Michael; Ashworth, Alan; Li, Jingmei; Cramp, Helen; Connley, Dan; Czene, Kamila; Darabi, Hatef; Chanock, Stephen J.; Lissowska, Jolanta; Figueroa, Jonine D.; Knight, Julia; Glendon, Gord; Mulligan, Anna M.; Dumont, Martine; Severi, Gianluca; Baglietto, Laura; Olson, Janet; Vachon, Celine; Purrington, Kristen; Moisse, Matthieu; Neven, Patrick; Wildiers, Hans; Spurdle, Amanda; Kosma, Veli-Matti; Kataja, Vesa; Hartikainen, Jaana M.; Hamann, Ute; Ko, Yon-Dschun; Dieffenbach, Aida K.; Arndt, Volker; Stegmaier, Christa; Malats, Núria; Arias Perez, JoséI.; Benítez, Javier; Flyger, Henrik; Nordestgaard, Børge G.; Truong, Théresè; Cordina-Duverger, Emilie; Menegaux, Florence; Silva, Isabel dos Santos; Fletcher, Olivia; Johnson, Nichola; Häberle, Lothar; Beckmann, Matthias W.; Ekici, Arif B.; Braaf, Linde; Atsma, Femke; van den Broek, Alexandra J.; Makalic, Enes; Schmidt, Daniel F.; Southey, Melissa C.; Cox, Angela; Simard, Jacques; Giles, Graham G.; Lambrechts, Diether; Mannermaa, Arto; Brauch, Hiltrud; Guénel, Pascal; Peto, Julian; Fasching, Peter A.; Hopper, John; Flesch-Janys, Dieter; Couch, Fergus; Chenevix-Trench, Georgia; Pharoah, Paul D. P.; Garcia-Closas, Montserrat; Schmidt, Marjanka K.; Hall, Per; Easton, Douglas F.; Chang-Claude, Jenny

2014-01-01

Genes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene-environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P-values = 3 × 10−07), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m2 (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m2 or higher (OR = 0.89, 95% CI 0.72–1.11, P for interaction = 3.2 × 10−05). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci. PMID:24248812

Culture as a mediator of gene-environment interaction: Cultural consonance, childhood adversity, a 2A serotonin receptor polymorphism, and depression in urban Brazil.

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Dressler, William W; Balieiro, Mauro C; Ferreira de Araújo, Luiza; Silva, Wilson A; Ernesto Dos Santos, José

2016-07-01

Research on gene-environment interaction was facilitated by breakthroughs in molecular biology in the late 20th century, especially in the study of mental health. There is a reliable interaction between candidate genes for depression and childhood adversity in relation to mental health outcomes. The aim of this paper is to explore the role of culture in this process in an urban community in Brazil. The specific cultural factor examined is cultural consonance, or the degree to which individuals are able to successfully incorporate salient cultural models into their own beliefs and behaviors. It was hypothesized that cultural consonance in family life would mediate the interaction of genotype and childhood adversity. In a study of 402 adult Brazilians from diverse socioeconomic backgrounds, conducted from 2011 to 2014, the interaction of reported childhood adversity and a polymorphism in the 2A serotonin receptor was associated with higher depressive symptoms. Further analysis showed that the gene-environment interaction was mediated by cultural consonance in family life, and that these effects were more pronounced in lower social class neighborhoods. The findings reinforce the role of the serotonergic system in the regulation of stress response and learning and memory, and how these processes in turn interact with environmental events and circumstances. Furthermore, these results suggest that gene-environment interaction models should incorporate a wider range of environmental experience and more complex pathways to better understand how genes and the environment combine to influence mental health outcomes. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Association between Gene-Environment Interactions and Diseases Involving the Human GST Superfamily with SNP Variants

Directory of Open Access Journals (Sweden)

Antoinesha L. Hollman

2016-03-01

Full Text Available Exposure to environmental hazards has been associated with diseases in humans. The identification of single nucleotide polymorphisms (SNPs in human populations exposed to different environmental hazards, is vital for detecting the genetic risks of some important human diseases. Several studies in this field have been conducted on glutathione S-transferases (GSTs, a phase II detoxification superfamily, to investigate its role in the occurrence of diseases. Human GSTs consist of cytosolic and microsomal superfamilies that are further divided into subfamilies. Based on scientific search engines and a review of the literature, we have found a large amount of published articles on human GST super- and subfamilies that have greatly assisted in our efforts to examine their role in health and disease. Because of its polymorphic variations in relation to environmental hazards such as air pollutants, cigarette smoke, pesticides, heavy metals, carcinogens, pharmaceutical drugs, and xenobiotics, GST is considered as a significant biomarker. This review examines the studies on gene-environment interactions related to various diseases with respect to single nucleotide polymorphisms (SNPs found in the GST superfamily. Overall, it can be concluded that interactions between GST genes and environmental factors play an important role in human diseases.

Assessment of Multifactor Gene-Environment Interactions and Ovarian Cancer Risk

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Usset, Joseph L; Raghavan, Rama; Tyrer, Jonathan P

2016-01-01

and non-obese women. METHODS: We considered interactions between 11,441 SNPs within 80 candidate genes related to hormone biosynthesis and metabolism and insulin-like growth factors with six hormone-related factors (oral contraceptive use, parity, endometriosis, tubal ligation, hormone replacement therapy...... Future work is needed to develop powerful statistical methods able to detect these complex interactions. IMPACT: Assessment of multifactor interaction is feasible, and, here, suggests that the relationship between genetic variants within candidate genes and hormone-related risk factors may vary EOC...

Gene-Lifestyle Interactions in Complex Diseases: Design and Description of the GLACIER and VIKING Studies.

Science.gov (United States)

Kurbasic, Azra; Poveda, Alaitz; Chen, Yan; Agren, Asa; Engberg, Elisabeth; Hu, Frank B; Johansson, Ingegerd; Barroso, Ines; Brändström, Anders; Hallmans, Göran; Renström, Frida; Franks, Paul W

2014-12-01

Most complex diseases have well-established genetic and non-genetic risk factors. In some instances, these risk factors are likely to interact, whereby their joint effects convey a level of risk that is either significantly more or less than the sum of these risks. Characterizing these gene-environment interactions may help elucidate the biology of complex diseases, as well as to guide strategies for their targeted prevention. In most cases, the detection of gene-environment interactions will require sample sizes in excess of those needed to detect the marginal effects of the genetic and environmental risk factors. Although many consortia have been formed, comprising multiple diverse cohorts to detect gene-environment interactions, few robust examples of such interactions have been discovered. This may be because combining data across studies, usually through meta-analysis of summary data from the contributing cohorts, is often a statistically inefficient approach for the detection of gene-environment interactions. Ideally, single, very large and well-genotyped prospective cohorts, with validated measures of environmental risk factor and disease outcomes should be used to study interactions. The presence of strong founder effects within those cohorts might further strengthen the capacity to detect novel genetic effects and gene-environment interactions. Access to accurate genealogical data would also aid in studying the diploid nature of the human genome, such as genomic imprinting (parent-of-origin effects). Here we describe two studies from northern Sweden (the GLACIER and VIKING studies) that fulfill these characteristics.

Blood lead levels, iron metabolism gene polymorphisms and homocysteine: a gene-environment interaction study.

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Kim, Kyoung-Nam; Lee, Mee-Ri; Lim, Youn-Hee; Hong, Yun-Chul

2017-12-01

Homocysteine has been causally associated with various adverse health outcomes. Evidence supporting the relationship between lead and homocysteine levels has been accumulating, but most prior studies have not focused on the interaction with genetic polymorphisms. From a community-based prospective cohort, we analysed 386 participants (aged 41-71 years) with information regarding blood lead and plasma homocysteine levels. Blood lead levels were measured between 2001 and 2003, and plasma homocysteine levels were measured in 2007. Interactions of lead levels with 42 genotyped single-nucleotide polymorphisms (SNPs) in five genes ( TF , HFE , CBS , BHMT and MTR ) were assessed via a 2-degree of freedom (df) joint test and a 1-df interaction test. In secondary analyses using imputation, we further assessed 58 imputed SNPs in the TF and MTHFR genes. Blood lead concentrations were positively associated with plasma homocysteine levels (p=0.0276). Six SNPs in the TF and MTR genes were screened using the 2-df joint test, and among them, three SNPs in the TF gene showed interactions with lead with respect to homocysteine levels through the 1-df interaction test (plead levels. Blood lead levels were positively associated with plasma homocysteine levels measured 4-6 years later, and three SNPs in the TF gene modified the association. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Beyond the single gene: How epistasis and gene-by-environment effects influence crop domestication.

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Doust, Andrew N; Lukens, Lewis; Olsen, Kenneth M; Mauro-Herrera, Margarita; Meyer, Ann; Rogers, Kimberly

2014-04-29

Domestication is a multifaceted evolutionary process, involving changes in individual genes, genetic interactions, and emergent phenotypes. There has been extensive discussion of the phenotypic characteristics of plant domestication, and recent research has started to identify the specific genes and mutational mechanisms that control domestication traits. However, there is an apparent disconnect between the simple genetic architecture described for many crop domestication traits, which should facilitate rapid phenotypic change under selection, and the slow rate of change reported from the archeobotanical record. A possible explanation involves the middle ground between individual genetic changes and their expression during development, where gene-by-gene (epistatic) and gene-by-environment interactions can modify the expression of phenotypes and opportunities for selection. These aspects of genetic architecture have the potential to significantly slow the speed of phenotypic evolution during crop domestication and improvement. Here we examine whether epistatic and gene-by-environment interactions have shaped how domestication traits have evolved. We review available evidence from the literature, and we analyze two domestication-related traits, shattering and flowering time, in a mapping population derived from a cross between domesticated foxtail millet and its wild progenitor. We find that compared with wild progenitor alleles, those favored during domestication often have large phenotypic effects and are relatively insensitive to genetic background and environmental effects. Consistent selection should thus be able to rapidly change traits during domestication. We conclude that if phenotypic evolution was slow during crop domestication, this is more likely due to cultural or historical factors than epistatic or environmental constraints.

Sleep Duration and Depressive Symptoms: A Gene-Environment Interaction

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Watson, Nathaniel F.; Harden, Kathryn Paige; Buchwald, Dedra; Vitiello, Michael V.; Pack, Allan I.; Strachan, Eric; Goldberg, Jack

2014-01-01

Objective: We used quantitative genetic models to assess whether sleep duration modifies genetic and environmental influences on depressive symptoms. Method: Participants were 1,788 adult twins from 894 same-sex twin pairs (192 male and 412 female monozygotic [MZ] pairs, and 81 male and 209 female dizygotic [DZ] pairs] from the University of Washington Twin Registry. Participants self-reported habitual sleep duration and depressive symptoms. Data were analyzed using quantitative genetic interaction models, which allowed the magnitude of additive genetic, shared environmental, and non-shared environmental influences on depressive symptoms to vary with sleep duration. Results: Within MZ twin pairs, the twin who reported longer sleep duration reported fewer depressive symptoms (ec = -0.17, SE = 0.06, P sleep duration interaction effect on depressive symptoms (a'c = 0.23, SE = 0.08, P sleep duration and depressive symptoms. Among individuals with sleep duration within the normal range (7-8.9 h/night), the total heritability (h2) of depressive symptoms was approximately 27%. However, among individuals with sleep duration within the low (sleep duration extremes (5 h/night: h2 = 53%; 10 h/night: h2 = 49%). Conclusion: Genetic contributions to depressive symptoms increase at both short and long sleep durations. Citation: Watson NF; Harden KP; Buchwald D; Vitiello MV; Pack AI; Stachan E; Goldberg J. Sleep duration and depressive symptoms: a gene-environment interaction. SLEEP 2014;37(2):351-358. PMID:24497663

The role of genes involved in neuroplasticity and neurogenesis in the observation of a gene-environment interaction (GxE) in schizophrenia.

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Le Strat, Yann; Ramoz, Nicolas; Gorwood, Philip

2009-05-01

Schizophrenia is a multifactorial disease characterized by a high heritability. Several candidate genes have been suggested, with the strongest evidences for genes encoding dystrobrevin binding protein 1 (DTNBP1), neuregulin 1 (NRG1), neuregulin 1 receptor (ERBB4) and disrupted in schizophrenia 1 (DISC1), as well as several neurotrophic factors. These genes are involved in neuronal plasticity and play also a role in adult neurogenesis. Therefore, the genetic basis of schizophrenia could involve different factors more or less specifically required for neuroplasticity, including the synapse maturation, potentiation and plasticity as well as neurogenesis. Following the model of Knudson in tumors, we propose a two-hit hypothesis of schizophrenia. In this model of gene-environment interaction, a variant in a gene related to neurogenesis is transmitted to the descent (first hit), and, secondarily, an environmental factor occurs during the development of the central nervous system (second hit). Both of these vulnerability and trigger factors are probably necessary to generate a deficit in neurogenesis and therefore to cause schizophrenia. The literature supporting this gene x environment hypothesis is reviewed, with emphasis on some molecular pathways, raising the possibility to propose more specific molecular medicine.

Gene-environment interaction: Does fluoride influence the reproductive hormones in male farmers modified by ERα gene polymorphisms?

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Ma, Qiang; Huang, Hui; Sun, Long; Zhou, Tong; Zhu, Jingyuan; Cheng, Xuemin; Duan, Lijv; Li, Zhiyuan; Cui, Liuxin; Ba, Yue

2017-12-01

The occurrence of endemic fluorosis is derived from high fluoride levels in drinking water and industrial fumes or dust. Reproductive disruption is also a major harm caused by fluoride exposure besides dental and skeletal lesions. However, few studies focus on the mechanism of fluoride exposure on male reproductive function, especially the possible interaction of fluoride exposure and gene polymorphism on male reproductive hormones. Therefore, we conducted a cross-sectional study in rural areas of Henan province in China to explore the interaction between the estrogen receptor alpha (ERα) gene and fluoride exposure on reproductive hormone levels in male farmers living in the endemic fluorosis villages. The results showed that fluoride exposure significantly increased the serum level of estradiol in the hypothalamic-pituitary-testicular (HPT) axis in male farmers. Moreover, the observations indicated that fluoride exposure and genetic markers had an interaction on serum concentration of follicle-stimulating hormone and estradiol, and the interaction among different loci of the ERα gene could impact the serum testosterone level. Findings in the present work suggest that chronic fluoride exposure in drinking water could modulate the levels of reproductive hormones in males living in endemic fluorosis areas, and the interaction between fluoride exposure and ERα polymorphisms might affect the serum levels of hormones in the HPT axis in male farmers. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evidence for plasticity genotypes in a gene-gene-environment interaction : the TRAILS study

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Nederhof, E; Bouma, Esther; Riese, Harriette; Laceulle, Odilia; Ormel, J.; Oldehinkel, A.J.

2010-01-01

The purpose was to study how functional polymorphisms in the brain derived neurotrophic factor gene (BDNF val66met) and the serotonin transporter gene linked promotor region (5-HTTLPR) interact with childhood adversities in predicting Effortful Control. Effortful Control refers to the ability to

Media portrayals and health inequalities: a case study of characterizations of Gene x Environment interactions.

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Horwitz, Allan V

2005-10-01

This article examines how genetic and environmental interactions associated with health inequalities are constructed and framed in the presentation of scientific research. It uses the example of a major article about depression in a longitudinal study of young adults that appeared in Science in 2003. This portrayal of findings related to health inequalities uses a genetic lens that privileges genetic influences and diminishes environmental ones. The emphasis on the genetic side of Gene x Environment interactions can serve to deflect attention away from the important impact of social inequalities on health.

Genetic susceptibility loci, environmental exposures, and Parkinson's disease: a case-control study of gene-environment interactions.

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Chung, Sun Ju; Armasu, Sebastian M; Anderson, Kari J; Biernacka, Joanna M; Lesnick, Timothy G; Rider, David N; Cunningham, Julie M; Ahlskog, J Eric; Frigerio, Roberta; Maraganore, Demetrius M

2013-06-01

Prior studies causally linked mutations in SNCA, MAPT, and LRRK2 genes with familial Parkinsonism. Genome-wide association studies have demonstrated association of single nucleotide polymorphisms (SNPs) in those three genes with sporadic Parkinson's disease (PD) susceptibility worldwide. Here we investigated the interactions between SNPs in those three susceptibility genes and environmental exposures (pesticides application, tobacco smoking, coffee drinking, and alcohol drinking) also associated with PD susceptibility. Pairwise interactions between environmental exposures and 18 variants (16 SNPs and two variable number tandem repeats, or "VNTRs") in SNCA, MAPT and LRRK2, were investigated using data from 1098 PD cases from the upper Midwest, USA and 1098 matched controls. Environmental exposures were assessed using a validated telephone interview script. Five pairwise interactions had uncorrected P-values coffee drinking × MAPT H1/H2 haplotype or MAPT rs16940806, and alcohol drinking × MAPT rs2435211. None of these interactions remained significant after Bonferroni correction. Secondary analyses in strata defined by type of control (sibling or unrelated), sex, or age at onset of the case also did not identify significant interactions after Bonferroni correction. This study documented limited pairwise interactions between established genetic and environmental risk factors for PD; however, the associations were not significant after correction for multiple testing. Copyright © 2013 Elsevier Ltd. All rights reserved.

Gene-environment interaction between the oxytocin receptor (OXTR) gene and parenting behaviour on children's theory of mind.

Science.gov (United States)

Wade, Mark; Hoffmann, Thomas J; Jenkins, Jennifer M

2015-12-01

Theory of mind (ToM) is the ability to interpret and understand human behaviour by representing the mental states of others. Like many human capacities, ToM is thought to develop through both complex biological and socialization mechanisms. However, no study has examined the joint effect of genetic and environmental influences on ToM. This study examined how variability in the oxytocin receptor gene (OXTR) and parenting behavior--two widely studied factors in ToM development-interacted to predict ToM in pre-school-aged children. Participants were 301 children who were part of an ongoing longitudinal birth cohort study. ToM was assessed at age 4.5 using a previously validated scale. Parenting was assessed through observations of mothers' cognitively sensitive behaviours. Using a family-based association design, it was suggestive that a particular variant (rs11131149) interacted with maternal cognitive sensitivity on children's ToM (P = 0.019). More copies of the major allele were associated with higher ToM as a function of increasing cognitive sensitivity. A sizeable 26% of the variability in ToM was accounted for by this interaction. This study provides the first empirical evidence of gene-environment interactions on ToM, supporting the notion that genetic factors may be modulated by potent environmental influences early in development. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Epistasis × environment interactions among Arabidopsis thaliana glucosinolate genes impact complex traits and fitness in the field

DEFF Research Database (Denmark)

Kerwin, Rachel E.; Feusier, Julie; Muok, Alise

2017-01-01

(GSL) defense chemistry, leaf damage, and relative fitness using mutant lines of Arabidopsis thaliana varying at pairs of causal aliphatic GSL defense genes to test the impact of epistatic and epistasis × environment interactions on adaptive trait variation. We found that aliphatic GSL accumulation...

Environmental heterogeneity generates opposite gene-by-environment interactions for two fitness-related traits within a population.

Science.gov (United States)

Culumber, Zachary W; Schumer, Molly; Monks, Scott; Tobler, Michael

2015-02-01

Theory predicts that environmental heterogeneity offers a potential solution to the maintenance of genetic variation within populations, but empirical evidence remains sparse. The live-bearing fish Xiphophorus variatus exhibits polymorphism at a single locus, with different alleles resulting in up to five distinct melanistic "tailspot" patterns within populations. We investigated the effects of heterogeneity in two ubiquitous environmental variables (temperature and food availability) on two fitness-related traits (upper thermal limits and body condition) in two different tailspot types (wild-type and upper cut crescent). We found gene-by-environment (G × E) interactions between tailspot type and food level affecting upper thermal limits (UTL), as well as between tailspot type and thermal environment affecting body condition. Exploring mechanistic bases underlying these G × E patterns, we found no differences between tailspot types in hsp70 gene expression despite significant overall increases in expression under both thermal and food stress. Similarly, there was no difference in routine metabolic rates between the tailspot types. The reversal of relative performance of the two tailspot types under different environmental conditions revealed a mechanism by which environmental heterogeneity can balance polymorphism within populations through selection on different fitness-related traits. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Gene x environment interactions in conduct disorder: Implications for future treatments.

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Holz, Nathalie E; Zohsel, Katrin; Laucht, Manfred; Banaschewski, Tobias; Hohmann, Sarah; Brandeis, Daniel

2016-08-18

Conduct disorder (CD) causes high financial and social costs, not only in affected families but across society, with only moderately effective treatments so far. There is consensus that CD is likely caused by the convergence of many different factors, including genetic and adverse environmental factors. There is ample evidence of gene-environment interactions in the etiology of CD on a behavioral level regarding genetically sensitive designs and candidate gene-driven approaches, most prominently and consistently represented by MAOA. However, conclusive indications of causal GxE patterns are largely lacking. Inconsistent findings, lack of replication and methodological limitations remain a major challenge. Likewise, research addressing the identification of affected brain pathways which reflect plausible biological mechanisms underlying GxE is still very sparse. Future research will have to take multilevel approaches into account, which combine genetic, environmental, epigenetic, personality, neural and hormone perspectives. A better understanding of relevant GxE patterns in the etiology of CD might enable researchers to design customized treatment options (e.g. biofeedback interventions) for specific subgroups of patients. Copyright © 2016 Elsevier Ltd. All rights reserved.

GENE X ENVIRONMENT INTERACTIONS IN SCHIZOPHRENIA AND BIPOLAR DISORDER:EVIDENCE FROM NEUROIMAGING

Directory of Open Access Journals (Sweden)

Pierre Alexis Geoffroy

2013-10-01

Full Text Available Introduction: Schizophrenia (SZ and Bipolar disorder (BD are considered as severe multifactorial diseases, stemming from genetic and environmental influences. Growing evidence supports gene x environment (GxE interactions in these disorders and neuroimaging studies can help us to understand how those factors mechanistically interact. No reviews synthesized the existing data of neuroimaging studies in these issues.Methods: We conduct a systematic review on the neuroimaging studies exploring GxE interactions relative to SZ or BD in PubMed.Results: First results of the influence of genetic and environmental risks on brain structures came from monozygotic twin pairs concordant and discordant for SZ or BD. Few structural magnetic resonance imaging (sMRI studies have explored the GxE interactions. No other imaging methods were found. Two main GxE interactions on brain volumes have arisen. First, an interaction between genetic liability to SZ and obstetric complications on gray matter, cerebrospinal fluid and hippocampal volumes. Second, cannabis use and genetic liability interaction effects on cortical thickness and white matter volumes.Conclusion: Combining GxE interactions and neuroimaging domains is a promising approach. Genetic risk and environmental exposures such as cannabis or obstetrical complications seem to interact leading to specific neuroimaging cerebral alterations in SZ. They are suggestive of GxE interactions that confer phenotypic abnormalities in SZ and possibly BD. We need further, larger neuroimaging studies of GxE interactions for which we may propose a framework focusing on GxE interactions data already known to have a clinical effect such as infections, early stress, urbanicity and substance abuse.

Gene-environment Interactions in Human Health: Case Studies and Strategies for developing new paradigms and research methodologies

Directory of Open Access Journals (Sweden)

Fatimah L.C. Jackson

2014-08-01

Full Text Available The synergistic effects of genes and the environment on health are explored in three case studies: adult lactase persistence, autism spectrum disorders, and the metabolic syndrome, providing examples of the interactive complexities underlying these phenotypes. Since the phenotypes are the initial targets of evolutionary processes, understanding the specific environmental contexts of the genetic, epigenetic, and proteomic changes associated with these phenotypes is essential in predicting their health implications. Robust databases must be developed on the local scale to deconstruct both the population substructure and the unique components of the environment that stimulate geographically-specific changes in gene expression patterns. To produce these databases and make valid predictions, new, locally-focused and information-dense models are needed that incorporate data on evolutionary ecology, environmental complexity, local geographic patterns of gene expression, and population substructure.

Metabolic syndrome, diabetes and atherosclerosis: Influence of gene-environment interaction

Energy Technology Data Exchange (ETDEWEB)

Andreassi, Maria Grazia, E-mail: andreas@ifc.cnr.it [CNR Institute of Clinical Physiology, G. Pasquinucci Hospital, Via Aurelia Sud, Massa (Italy)

2009-07-10

Despite remarkable progress in diagnosis and understanding of risk factors, cardiovascular disease (CVD) remains still the leading cause of morbidity and mortality in the world's developed countries. The metabolic syndrome, a cluster of risk factors (visceral obesity, insulin resistance, dyslipidaemia, and hypertension), is increasingly being recognized as a new risk factor for type 2 diabetes and atherosclerotic cardiovascular disease. Nevertheless, there is wide variation in both the occurrence of disease and age of onset, even in individuals who display very similar risk profiles. There is now compelling evidence that a complex interplay between genetic determinants and environmental factors (still largely unknown) is the reason for this large inter-individual variation in disease susceptibility. The purpose of the present review is to describe the current status of our knowledge concerning the gene-environment interactions potentially implicated in the pathogenesis of metabolic syndrome, diabetes and cardiovascular disease. It focuses predominantly on studies of genes (peroxisome proliferator-activated receptor-gamma, alcohol dehydrogenase type 1C, apolipoprotein E, glutathione S-transferases T1 and M1) that are known to be modified by dietary and lifestyle habits (fat diet, intake of alcohol and smoking habit). It also describes the limited current understanding of the role of genetic variants of xenobiotic metabolizing enzymes and their interactions with environmental toxicants. Additional studies are needed in order to clarify whether inter-individual differences in detoxification of environmental toxicants may have an essential role in the development of CVD and contribute to the emerging field of 'environmental cardiology'. Such knowledge may be particularly relevant for improving cardiovascular risk stratification and conceiving the development of 'personalized intervention program'.

Metabolic syndrome, diabetes and atherosclerosis: Influence of gene-environment interaction

International Nuclear Information System (INIS)

Andreassi, Maria Grazia

2009-01-01

Despite remarkable progress in diagnosis and understanding of risk factors, cardiovascular disease (CVD) remains still the leading cause of morbidity and mortality in the world's developed countries. The metabolic syndrome, a cluster of risk factors (visceral obesity, insulin resistance, dyslipidaemia, and hypertension), is increasingly being recognized as a new risk factor for type 2 diabetes and atherosclerotic cardiovascular disease. Nevertheless, there is wide variation in both the occurrence of disease and age of onset, even in individuals who display very similar risk profiles. There is now compelling evidence that a complex interplay between genetic determinants and environmental factors (still largely unknown) is the reason for this large inter-individual variation in disease susceptibility. The purpose of the present review is to describe the current status of our knowledge concerning the gene-environment interactions potentially implicated in the pathogenesis of metabolic syndrome, diabetes and cardiovascular disease. It focuses predominantly on studies of genes (peroxisome proliferator-activated receptor-gamma, alcohol dehydrogenase type 1C, apolipoprotein E, glutathione S-transferases T1 and M1) that are known to be modified by dietary and lifestyle habits (fat diet, intake of alcohol and smoking habit). It also describes the limited current understanding of the role of genetic variants of xenobiotic metabolizing enzymes and their interactions with environmental toxicants. Additional studies are needed in order to clarify whether inter-individual differences in detoxification of environmental toxicants may have an essential role in the development of CVD and contribute to the emerging field of 'environmental cardiology'. Such knowledge may be particularly relevant for improving cardiovascular risk stratification and conceiving the development of 'personalized intervention program'.

Gene-environment effects on hippocampal neurodevelopment

DEFF Research Database (Denmark)

Rosenthal, Eva Helga

Mental disorders like schizophrenia and autism put a heavy load on today’s societies, creating a steady call for revealing underlying disease mechanisms and the development of effective treatments. The etiology of major psychiatric illnesses is complex involving gene by environment susceptibility...... factors. Hence, a deeper understanding is needed of how cortical neurodevelopmental deficiencies can arise from such gene-environment interactions. The convergence of genetic and environmental risk factors is a recent field of research. It is now clear that disease, infection and stress factors may...... and antipsychotics mediate their effects on hippocampal neurodevelopment through deregulation of the Zbtb20 gene. A short presentation of the status of this work will shown....

Glucose Metabolism and AMPK Signaling Regulate Dopaminergic Cell Death Induced by Gene (α-Synuclein)-Environment (Paraquat) Interactions.

Science.gov (United States)

Anandhan, Annadurai; Lei, Shulei; Levytskyy, Roman; Pappa, Aglaia; Panayiotidis, Mihalis I; Cerny, Ronald L; Khalimonchuk, Oleh; Powers, Robert; Franco, Rodrigo

2017-07-01

While environmental exposures are not the single cause of Parkinson's disease (PD), their interaction with genetic alterations is thought to contribute to neuronal dopaminergic degeneration. However, the mechanisms involved in dopaminergic cell death induced by gene-environment interactions remain unclear. In this work, we have revealed for the first time the role of central carbon metabolism and metabolic dysfunction in dopaminergic cell death induced by the paraquat (PQ)-α-synuclein interaction. The toxicity of PQ in dopaminergic N27 cells was significantly reduced by glucose deprivation, inhibition of hexokinase with 2-deoxy-D-glucose (2-DG), or equimolar substitution of glucose with galactose, which evidenced the contribution of glucose metabolism to PQ-induced cell death. PQ also stimulated an increase in glucose uptake, and in the levels of glucose transporter type 4 (GLUT4) and Na + -glucose transporters isoform 1 (SGLT1) proteins, but only inhibition of GLUT-like transport with STF-31 or ascorbic acid reduced PQ-induced cell death. Importantly, while autophagy protein 5 (ATG5)/unc-51 like autophagy activating kinase 1 (ULK1)-dependent autophagy protected against PQ toxicity, the inhibitory effect of glucose deprivation on cell death progression was largely independent of autophagy or mammalian target of rapamycin (mTOR) signaling. PQ selectively induced metabolomic alterations and adenosine monophosphate-activated protein kinase (AMPK) activation in the midbrain and striatum of mice chronically treated with PQ. Inhibition of AMPK signaling led to metabolic dysfunction and an enhanced sensitivity of dopaminergic cells to PQ. In addition, activation of AMPK by PQ was prevented by inhibition of the inducible nitric oxide syntase (iNOS) with 1400W, but PQ had no effect on iNOS levels. Overexpression of wild type or A53T mutant α-synuclein stimulated glucose accumulation and PQ toxicity, and this toxic synergism was reduced by inhibition of glucose metabolism

Development and application of an interaction network ontology for literature mining of vaccine-associated gene-gene interactions.

Science.gov (United States)

Hur, Junguk; Özgür, Arzucan; Xiang, Zuoshuang; He, Yongqun

2015-01-01

Literature mining of gene-gene interactions has been enhanced by ontology-based name classifications. However, in biomedical literature mining, interaction keywords have not been carefully studied and used beyond a collection of keywords. In this study, we report the development of a new Interaction Network Ontology (INO) that classifies >800 interaction keywords and incorporates interaction terms from the PSI Molecular Interactions (PSI-MI) and Gene Ontology (GO). Using INO-based literature mining results, a modified Fisher's exact test was established to analyze significantly over- and under-represented enriched gene-gene interaction types within a specific area. Such a strategy was applied to study the vaccine-mediated gene-gene interactions using all PubMed abstracts. The Vaccine Ontology (VO) and INO were used to support the retrieval of vaccine terms and interaction keywords from the literature. INO is aligned with the Basic Formal Ontology (BFO) and imports terms from 10 other existing ontologies. Current INO includes 540 terms. In terms of interaction-related terms, INO imports and aligns PSI-MI and GO interaction terms and includes over 100 newly generated ontology terms with 'INO_' prefix. A new annotation property, 'has literature mining keywords', was generated to allow the listing of different keywords mapping to the interaction types in INO. Using all PubMed documents published as of 12/31/2013, approximately 266,000 vaccine-associated documents were identified, and a total of 6,116 gene-pairs were associated with at least one INO term. Out of 78 INO interaction terms associated with at least five gene-pairs of the vaccine-associated sub-network, 14 terms were significantly over-represented (i.e., more frequently used) and 17 under-represented based on our modified Fisher's exact test. These over-represented and under-represented terms share some common top-level terms but are distinct at the bottom levels of the INO hierarchy. The analysis of these

Using imputed genotype data in the joint score tests for genetic association and gene-environment interactions in case-control studies.

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Song, Minsun; Wheeler, William; Caporaso, Neil E; Landi, Maria Teresa; Chatterjee, Nilanjan

2018-03-01

Genome-wide association studies (GWAS) are now routinely imputed for untyped single nucleotide polymorphisms (SNPs) based on various powerful statistical algorithms for imputation trained on reference datasets. The use of predicted allele counts for imputed SNPs as the dosage variable is known to produce valid score test for genetic association. In this paper, we investigate how to best handle imputed SNPs in various modern complex tests for genetic associations incorporating gene-environment interactions. We focus on case-control association studies where inference for an underlying logistic regression model can be performed using alternative methods that rely on varying degree on an assumption of gene-environment independence in the underlying population. As increasingly large-scale GWAS are being performed through consortia effort where it is preferable to share only summary-level information across studies, we also describe simple mechanisms for implementing score tests based on standard meta-analysis of "one-step" maximum-likelihood estimates across studies. Applications of the methods in simulation studies and a dataset from GWAS of lung cancer illustrate ability of the proposed methods to maintain type-I error rates for the underlying testing procedures. For analysis of imputed SNPs, similar to typed SNPs, the retrospective methods can lead to considerable efficiency gain for modeling of gene-environment interactions under the assumption of gene-environment independence. Methods are made available for public use through CGEN R software package. © 2017 WILEY PERIODICALS, INC.

Complex Genotype by Environment interactions and changing genetic architectures across thermal environments in the Australian field cricket, Teleogryllus oceanicus

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Dowling Damian K

2011-07-01

Full Text Available Abstract Background Biologists studying adaptation under sexual selection have spent considerable effort assessing the relative importance of two groups of models, which hinge on the idea that females gain indirect benefits via mate discrimination. These are the good genes and genetic compatibility models. Quantitative genetic studies have advanced our understanding of these models by enabling assessment of whether the genetic architectures underlying focal phenotypes are congruent with either model. In this context, good genes models require underlying additive genetic variance, while compatibility models require non-additive variance. Currently, we know very little about how the expression of genotypes comprised of distinct parental haplotypes, or how levels and types of genetic variance underlying key phenotypes, change across environments. Such knowledge is important, however, because genotype-environment interactions can have major implications on the potential for evolutionary responses to selection. Results We used a full diallel breeding design to screen for complex genotype-environment interactions, and genetic architectures underlying key morphological traits, across two thermal environments (the lab standard 27°C, and the cooler 23°C in the Australian field cricket, Teleogryllus oceanicus. In males, complex three-way interactions between sire and dam parental haplotypes and the rearing environment accounted for up to 23 per cent of the scaled phenotypic variance in the traits we measured (body mass, pronotum width and testes mass, and each trait harboured significant additive genetic variance in the standard temperature (27°C only. In females, these three-way interactions were less important, with interactions between the paternal haplotype and rearing environment accounting for about ten per cent of the phenotypic variance (in body mass, pronotum width and ovary mass. Of the female traits measured, only ovary mass for crickets

Case-only gene-environment interaction between ALAD tagSNPs and occupational lead exposure in prostate cancer.

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Neslund-Dudas, Christine; Levin, Albert M; Rundle, Andrew; Beebe-Dimmer, Jennifer; Bock, Cathryn H; Nock, Nora L; Jankowski, Michelle; Datta, Indrani; Krajenta, Richard; Dou, Q Ping; Mitra, Bharati; Tang, Deliang; Rybicki, Benjamin A

2014-05-01

Black men have historically had higher blood lead levels than white men in the U.S. and have the highest incidence of prostate cancer in the world. Inorganic lead has been classified as a probable human carcinogen. Lead (Pb) inhibits delta-aminolevulinic acid dehydratase (ALAD), a gene recently implicated in other genitourinary cancers. The ALAD enzyme is involved in the second step of heme biosynthesis and is an endogenous inhibitor of the 26S proteasome, a master system for protein degradation and a current target of cancer therapy. Using a case-only study design, we assessed potential gene-environment (G × E) interactions between lifetime occupational Pb exposure and 11 tagSNPs within ALAD in black (N = 260) and white (N = 343) prostate cancer cases. Two ALAD tagSNPs in high linkage disequilibrium showed significant interaction with high Pb exposure among black cases (rs818684 interaction odds ratio or IOR = 2.73, 95% CI 1.43-5.22, P = 0.002; rs818689 IOR = 2.20, 95% CI 1.15-4.21, P = 0.017) and an additional tagSNP, rs2761016, showed G × E interaction with low Pb exposure (IOR = 2.08, 95% CI 1.13-3.84, P = 0.019). Further, the variant allele of rs818684 was associated with a higher Gleason grade in those with high Pb exposure among both blacks (OR 3.96, 95% CI 1.01-15.46, P = 0.048) and whites (OR 2.95, 95% CI 1.18-7.39, P = 0.020). Genetic variation in ALAD may modify associations between Pb and prostate cancer. Additional studies of ALAD, Pb, and prostate cancer are warranted and should include black men. Prostate 74:637-646, 2014. © 2014 Wiley Periodicals, Inc. © 2014 Wiley Periodicals, Inc.

Behavioral science and the study of gene-nutrition and gene-physical activity interactions in obesity research.

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Faith, Myles S

2008-12-01

This report summarizes emerging opportunities for behavioral science to help advance the field of gene-environment and gene-behavior interactions, based on presentations at The National Cancer Institute (NCI) Workshop, "Gene-Nutrition and Gene-Physical Activity Interactions in the Etiology of Obesity." Three opportunities are highlighted: (i) designing potent behavioral "challenges" in experiments, (ii) determining viable behavioral phenotypes for genetics studies, and (iii) identifying specific measures of the environment or environmental exposures. Additional points are underscored, including the need to incorporate novel findings from neuroimaging studies regarding motivation and drive for eating and physical activity. Advances in behavioral science theory and methods can play an important role in advancing understanding of gene-brain-behavior relationships in obesity onset.

I just ran a thousand analyses: benefits of multiple testing in understanding equivocal evidence on gene-environment interactions.

Directory of Open Access Journals (Sweden)

Vera E Heininga

Full Text Available In psychiatric genetics research, the volume of ambivalent findings on gene-environment interactions (G x E is growing at an accelerating pace. In response to the surging suspicions of systematic distortion, we challenge the notion of chance capitalization as a possible contributor. Beyond qualifying multiple testing as a mere methodological issue that, if uncorrected, leads to chance capitalization, we advance towards illustrating the potential benefits of multiple tests in understanding equivocal evidence in genetics literature.We focused on the interaction between the serotonin-transporter-linked promotor region (5-HTTLPR and childhood adversities with regard to depression. After testing 2160 interactions with all relevant measures available within the Dutch population study of adolescents TRAILS, we calculated percentages of significant (p < .05 effects for several subsets of regressions. Using chance capitalization (i.e. overall significance rate of 5% alpha and randomly distributed findings as a competing hypothesis, we expected more significant effects in the subsets of regressions involving: 1 interview-based instead of questionnaire-based measures; 2 abuse instead of milder childhood adversities; and 3 early instead of later adversities. Furthermore, we expected equal significance percentages across 4 male and female subsamples, and 5 various genotypic models of 5-HTTLPR.We found differences in the percentages of significant interactions among the subsets of analyses, including those regarding sex-specific subsamples and genetic modeling, but often in unexpected directions. Overall, the percentage of significant interactions was 7.9% which is only slightly above the 5% that might be expected based on chance.Taken together, multiple testing provides a novel approach to better understand equivocal evidence on G x E, showing that methodological differences across studies are a likely reason for heterogeneity in findings - but chance

Dopamine en overmatig alcoholgebruik: genen in interactie met hun omgeving [Dopamine and excessive alcohol consumption: how genes interact with their environment

OpenAIRE

Schellekens, A.F.A.; Scholte, R.H.J.; Engels, R.C.M.E.; Verkes, R.J.

2013-01-01

background Hereditary factors account for approximately 50% of the risk of developing alcohol dependence. Genes that affect the dopamine function in the brain have been extensively studied as candidate genes. aim To present the results of recent Dutch studies on the interaction between genes and their environment in relation to dopamine function and excessive alcohol use. method Two large scale research projects were recently carried out in order to study the relation between dopamine genes a...

Nature versus nurture: A systematic approach to elucidate gene-environment interactions in the development of myopic refractive errors.

Science.gov (United States)

Miraldi Utz, Virginia

2017-01-01

Myopia is the most common eye disorder and major cause of visual impairment worldwide. As the incidence of myopia continues to rise, the need to further understand the complex roles of molecular and environmental factors controlling variation in refractive error is of increasing importance. Tkatchenko and colleagues applied a systematic approach using a combination of gene set enrichment analysis, genome-wide association studies, and functional analysis of a murine model to identify a myopia susceptibility gene, APLP2. Differential expression of refractive error was associated with time spent reading for those with low frequency variants in this gene. This provides support for the longstanding hypothesis of gene-environment interactions in refractive error development.

[Dopamine and excessive alcohol consumption: how genes interact with their environment

NARCIS (Netherlands)

Schellekens, A.F.A.; Scholte, R.H.J.; Engels, R.C.M.E.; Verkes, R.J.

2013-01-01

SUMMARY BACKGROUND: Hereditary factors account for approximately 50% of the risk of developing alcohol dependence. Genes that affect the dopamine function in the brain have been extensively studied as candidate genes. AIM: To present the results of recent Dutch studies on the interaction between

Multiple analytical approaches reveal distinct gene-environment interactions in smokers and non smokers in lung cancer.

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Rakhshan Ihsan

Full Text Available Complex disease such as cancer results from interactions of multiple genetic and environmental factors. Studying these factors singularly cannot explain the underlying pathogenetic mechanism of the disease. Multi-analytical approach, including logistic regression (LR, classification and regression tree (CART and multifactor dimensionality reduction (MDR, was applied in 188 lung cancer cases and 290 controls to explore high order interactions among xenobiotic metabolizing genes and environmental risk factors. Smoking was identified as the predominant risk factor by all three analytical approaches. Individually, CYP1A1*2A polymorphism was significantly associated with increased lung cancer risk (OR = 1.69;95%CI = 1.11-2.59,p = 0.01, whereas EPHX1 Tyr113His and SULT1A1 Arg213His conferred reduced risk (OR = 0.40;95%CI = 0.25-0.65,p<0.001 and OR = 0.51;95%CI = 0.33-0.78,p = 0.002 respectively. In smokers, EPHX1 Tyr113His and SULT1A1 Arg213His polymorphisms reduced the risk of lung cancer, whereas CYP1A1*2A, CYP1A1*2C and GSTP1 Ile105Val imparted increased risk in non-smokers only. While exploring non-linear interactions through CART analysis, smokers carrying the combination of EPHX1 113TC (Tyr/His, SULT1A1 213GG (Arg/Arg or AA (His/His and GSTM1 null genotypes showed the highest risk for lung cancer (OR = 3.73;95%CI = 1.33-10.55,p = 0.006, whereas combined effect of CYP1A1*2A 6235CC or TC, SULT1A1 213GG (Arg/Arg and betel quid chewing showed maximum risk in non-smokers (OR = 2.93;95%CI = 1.15-7.51,p = 0.01. MDR analysis identified two distinct predictor models for the risk of lung cancer in smokers (tobacco chewing, EPHX1 Tyr113His, and SULT1A1 Arg213His and non-smokers (CYP1A1*2A, GSTP1 Ile105Val and SULT1A1 Arg213His with testing balance accuracy (TBA of 0.6436 and 0.6677 respectively. Interaction entropy interpretations of MDR results showed non-additive interactions of tobacco chewing with

Animal models of gene-environment interaction in schizophrenia: a dimensional perspective

Science.gov (United States)

Ayhan, Yavuz; McFarland, Ross; Pletnikov, Mikhail V.

2015-01-01

Schizophrenia has long been considered as a disorder with multifactorial origins. Recent discoveries have advanced our understanding of the genetic architecture of the disease. However, even with the increase of identified risk variants, heritability estimates suggest an important contribution of non-genetic factors. Various environmental risk factors have been proposed to play a role in the etiopathogenesis of schizophrenia. These include season of birth, maternal infections, obstetric complications, adverse events at early childhood, and drug abuse. Despite the progress in identification of genetic and environmental risk factors, we still have a limited understanding of the mechanisms whereby gene-environment interactions (GxE) operate in schizophrenia and psychoses at large. In this review we provide a critical analysis of current animal models of GxE relevant to psychotic disorders and propose that dimensional perspective will advance our understanding of the complex mechanisms of these disorders. PMID:26510407

Evaluation of two methods for assessing gene-environment interactions using data from the Danish case-control study of facial clefts

DEFF Research Database (Denmark)

Etheredge, Analee J; Christensen, Kaare; Del Junco, Deborah

2005-01-01

BACKGROUND: Epidemiological investigations have begun to consider gene-environment (GE) interactions as potential risk factors for many diseases, including several different birth defects. However, traditional methodological approaches for the analysis of case-control data tend to have low power ...

Social Integration and Sleep Disturbance: A Gene-Environment Interaction Study

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David A. Sbarra

2016-03-01

Full Text Available Objective: Low levels of perceived social integration, or loneliness, are associated with increased risk for a range of poor health outcomes. Sleep disturbance plays a central role in the evolutionary theory of loneliness, which provides a mechanistic account of how low levels of social integration may negatively impact health. No studies, however, have examined whether the association between social integration and sleep disturbance is consistent with a causal effect after accounting for genes that are common to both variables.  Method: Using twin data ('N' = 905 twin pairs from the nationally-representative Midlife in the United States (MIDUS survey, I evaluated a series of bivariate twin models exploring whether the phenotypic association between low social integration and sleep disturbance can be explained by shared genetics. In addition, the current study specified a series of quantitative models for studying gene x environment (G X E interactions to determine whether the genetic and environmental influences on sleep disturbance differ as a function of social integration. Results: The phenotypic association between social integration and sleep disturbance was fully accounted for by genes that are common between the two variables, suggesting that within-twin pair differences in social integration do not exert a causal influence on sleep disturbance. Social integration, however, moderated the non-shared environmental influence on sleep disturbances, with the greatest environmental influences observed at the lowest levels of social integration. Conclusions: The results of this study suggest that an essential feature of the evolutionary model of loneliness may need refinement or elaboration. The moderation findings are discussed in terms of the fit with a stress-buffering model of social support in which environmental influences on sleep disturbance are strongest when social resources are low.

Behavior of QQ-plots and genomic control in studies of gene-environment interaction.

Directory of Open Access Journals (Sweden)

Arend Voorman

2011-05-01

Full Text Available Genome-wide association studies of gene-environment interaction (GxE GWAS are becoming popular. As with main effects GWAS, quantile-quantile plots (QQ-plots and Genomic Control are being used to assess and correct for population substructure. However, in G x E work these approaches can be seriously misleading, as we illustrate; QQ-plots may give strong indications of substructure when absolutely none is present. Using simulation and theory, we show how and why spurious QQ-plot inflation occurs in G x E GWAS, and how this differs from main-effects analyses. We also explain how simple adjustments to standard regression-based methods used in G x E GWAS can alleviate this problem.

Animal models of gene-environment interaction in schizophrenia: A dimensional perspective.

Science.gov (United States)

Ayhan, Yavuz; McFarland, Ross; Pletnikov, Mikhail V

2016-01-01

Schizophrenia has long been considered as a disorder with multifactorial origins. Recent discoveries have advanced our understanding of the genetic architecture of the disease. However, even with the increase of identified risk variants, heritability estimates suggest an important contribution of non-genetic factors. Various environmental risk factors have been proposed to play a role in the etiopathogenesis of schizophrenia. These include season of birth, maternal infections, obstetric complications, adverse events at early childhood, and drug abuse. Despite the progress in identification of genetic and environmental risk factors, we still have a limited understanding of the mechanisms whereby gene-environment interactions (G × E) operate in schizophrenia and psychoses at large. In this review we provide a critical analysis of current animal models of G × E relevant to psychotic disorders and propose that dimensional perspective will advance our understanding of the complex mechanisms of these disorders. Copyright © 2015 Elsevier Ltd. All rights reserved.

Gene-gene interactions and gene polymorphisms of VEGFA and EG-VEGF gene systems in recurrent pregnancy loss.

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Su, Mei-Tsz; Lin, Sheng-Hsiang; Chen, Yi-Chi; Kuo, Pao-Lin

2014-06-01

Both vascular endothelial growth factor A (VEGFA) and endocrine gland-derived vascular endothelial growth factor (EG-VEGF) systems play major roles in angiogenesis. A body of evidence suggests VEGFs regulate critical processes during pregnancy and have been associated with recurrent pregnancy loss (RPL). However, little information is available regarding the interaction of these two major major angiogenesis-related systems in early human pregnancy. This study was conducted to investigate the association of gene polymorphisms and gene-gene interaction among genes in VEGFA and EG-VEGF systems and idiopathic RPL. A total of 98 women with history of idiopathic RPL and 142 controls were included, and 5 functional SNPs selected from VEGFA, KDR, EG-VEGF (PROK1), PROKR1 and PROKR2 were genotyped. We used multifactor dimensionality reduction (MDR) analysis to choose a best model and evaluate gene-gene interactions. Ingenuity pathways analysis (IPA) was introduced to explore possible complex interactions. Two receptor gene polymorphisms [KDR (Q472H) and PROKR2 (V331M)] were significantly associated with idiopathic RPL (P<0.01). The MDR test revealed that the KDR (Q472H) polymorphism was the best loci to be associated with RPL (P=0.02). IPA revealed EG-VEGF and VEGFA systems shared several canonical signaling pathways that may contribute to gene-gene interactions, including the Akt, IL-8, EGFR, MAPK, SRC, VHL, HIF-1A and STAT3 signaling pathways. Two receptor gene polymorphisms [KDR (Q472H) and PROKR2 (V331M)] were significantly associated with idiopathic RPL. EG-VEGF and VEGFA systems shared several canonical signaling pathways that may contribute to gene-gene interactions, including the Akt, IL-8, EGFR, MAPK, SRC, VHL, HIF-1A and STAT3.

Genomic Analysis of Genotype-by-Social Environment Interaction for Drosophila melanogaster Aggressive Behavior.

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Rohde, Palle Duun; Gaertner, Bryn; Ward, Kirsty; Sørensen, Peter; Mackay, Trudy F C

2017-08-01

Human psychiatric disorders such as schizophrenia, bipolar disorder, and attention-deficit/hyperactivity disorder often include adverse behaviors including increased aggressiveness. Individuals with psychiatric disorders often exhibit social withdrawal, which can further increase the probability of conducting a violent act. Here, we used the inbred, sequenced lines of the Drosophila Genetic Reference Panel (DGRP) to investigate the genetic basis of variation in male aggressive behavior for flies reared in a socialized and socially isolated environment. We identified genetic variation for aggressive behavior, as well as significant genotype-by-social environmental interaction (GSEI); i.e. , variation among DGRP genotypes in the degree to which social isolation affected aggression. We performed genome-wide association (GWA) analyses to identify genetic variants associated with aggression within each environment. We used genomic prediction to partition genetic variants into gene ontology (GO) terms and constituent genes, and identified GO terms and genes with high prediction accuracies in both social environments and for GSEI. The top predictive GO terms significantly increased the proportion of variance explained, compared to prediction models based on all segregating variants. We performed genomic prediction across environments, and identified genes in common between the social environments that turned out to be enriched for genome-wide associated variants. A large proportion of the associated genes have previously been associated with aggressive behavior in Drosophila and mice. Further, many of these genes have human orthologs that have been associated with neurological disorders, indicating partially shared genetic mechanisms underlying aggression in animal models and human psychiatric disorders. Copyright © 2017 by the Genetics Society of America.

Gene-Environment Interplay between Number of Friends and Prosocial Leadership Behavior in Children

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Rivizzigno, Alessandra S.; Brendgen, Mara; Feng, Bei; Vitaro, Frank; Dionne, Ginette; Tremblay, Richard E.; Boivin, Michel

2014-01-01

Enriched environments may moderate the effect of genetic factors on prosocial leadership (gene-environment interaction, G × E). However, positive environmental experiences may also themselves be influenced by a genetic disposition for prosocial leadership (gene-environment correlation, rGE). Relating these processes to friendships, the present…

Gene-Environment Interplay in Twin Models

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Hatemi, Peter K.

2013-01-01

In this article, we respond to Shultziner’s critique that argues that identical twins are more alike not because of genetic similarity, but because they select into more similar environments and respond to stimuli in comparable ways, and that these effects bias twin model estimates to such an extent that they are invalid. The essay further argues that the theory and methods that undergird twin models, as well as the empirical studies which rely upon them, are unaware of these potential biases. We correct this and other misunderstandings in the essay and find that gene-environment (GE) interplay is a well-articulated concept in behavior genetics and political science, operationalized as gene-environment correlation and gene-environment interaction. Both are incorporated into interpretations of the classical twin design (CTD) and estimated in numerous empirical studies through extensions of the CTD. We then conduct simulations to quantify the influence of GE interplay on estimates from the CTD. Due to the criticism’s mischaracterization of the CTD and GE interplay, combined with the absence of any empirical evidence to counter what is presented in the extant literature and this article, we conclude that the critique does not enhance our understanding of the processes that drive political traits, genetic or otherwise. PMID:24808718

The Interacting Effect of the BDNF Val66Met Polymorphism and Stressful Life Events on Adolescent Depression Is Not an Artifact of Gene-Environment Correlation: Evidence from a Longitudinal Twin Study

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Chen, Jie; Li, Xinying; McGue, Matt

2013-01-01

Background: Confounding introduced by gene-environment correlation (rGE) may prevent one from observing a true gene-environment interaction (G × E) effect on psychopathology. The present study investigated the interacting effect of the BDNF Val66Met polymorphism and stressful life events (SLEs) on adolescent depression while controlling for the…

Molecular genetic gene-environment studies using candidate genes in schizophrenia: a systematic review.

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Modinos, Gemma; Iyegbe, Conrad; Prata, Diana; Rivera, Margarita; Kempton, Matthew J; Valmaggia, Lucia R; Sham, Pak C; van Os, Jim; McGuire, Philip

2013-11-01

The relatively high heritability of schizophrenia suggests that genetic factors play an important role in the etiology of the disorder. On the other hand, a number of environmental factors significantly influence its incidence. As few direct genetic effects have been demonstrated, and there is considerable inter-individual heterogeneity in the response to the known environmental factors, interactions between genetic and environmental factors may be important in determining whether an individual develops the disorder. To date, a considerable number of studies of gene-environment interactions (G×E) in schizophrenia have employed a hypothesis-based molecular genetic approach using candidate genes, which have led to a range of different findings. This systematic review aims to summarize the results from molecular genetic candidate studies and to review challenges and opportunities of this approach in psychosis research. Finally, we discuss the potential of future prospects, such as new studies that combine hypothesis-based molecular genetic candidate approaches with agnostic genome-wide association studies in determining schizophrenia risk. © 2013 Elsevier B.V. All rights reserved.

Gene × Smoking Interactions on Human Brain Gene Expression: Finding Common Mechanisms in Adolescents and Adults

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Wolock, Samuel L.; Yates, Andrew; Petrill, Stephen A.; Bohland, Jason W.; Blair, Clancy; Li, Ning; Machiraju, Raghu; Huang, Kun; Bartlett, Christopher W.

2013-01-01

Background: Numerous studies have examined gene × environment interactions (G × E) in cognitive and behavioral domains. However, these studies have been limited in that they have not been able to directly assess differential patterns of gene expression in the human brain. Here, we assessed G × E interactions using two publically available datasets…

Screening for interaction effects in gene expression data.

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Peter J Castaldi

Full Text Available Expression quantitative trait (eQTL studies are a powerful tool for identifying genetic variants that affect levels of messenger RNA. Since gene expression is controlled by a complex network of gene-regulating factors, one way to identify these factors is to search for interaction effects between genetic variants and mRNA levels of transcription factors (TFs and their respective target genes. However, identification of interaction effects in gene expression data pose a variety of methodological challenges, and it has become clear that such analyses should be conducted and interpreted with caution. Investigating the validity and interpretability of several interaction tests when screening for eQTL SNPs whose effect on the target gene expression is modified by the expression level of a transcription factor, we characterized two important methodological issues. First, we stress the scale-dependency of interaction effects and highlight that commonly applied transformation of gene expression data can induce or remove interactions, making interpretation of results more challenging. We then demonstrate that, in the setting of moderate to strong interaction effects on the order of what may be reasonably expected for eQTL studies, standard interaction screening can be biased due to heteroscedasticity induced by true interactions. Using simulation and real data analysis, we outline a set of reasonable minimum conditions and sample size requirements for reliable detection of variant-by-environment and variant-by-TF interactions using the heteroscedasticity consistent covariance-based approach.

Identifying gene-environment interactions in schizophrenia: contemporary challenges for integrated, large-scale investigations.

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van Os, Jim; Rutten, Bart P; Myin-Germeys, Inez; Delespaul, Philippe; Viechtbauer, Wolfgang; van Zelst, Catherine; Bruggeman, Richard; Reininghaus, Ulrich; Morgan, Craig; Murray, Robin M; Di Forti, Marta; McGuire, Philip; Valmaggia, Lucia R; Kempton, Matthew J; Gayer-Anderson, Charlotte; Hubbard, Kathryn; Beards, Stephanie; Stilo, Simona A; Onyejiaka, Adanna; Bourque, Francois; Modinos, Gemma; Tognin, Stefania; Calem, Maria; O'Donovan, Michael C; Owen, Michael J; Holmans, Peter; Williams, Nigel; Craddock, Nicholas; Richards, Alexander; Humphreys, Isla; Meyer-Lindenberg, Andreas; Leweke, F Markus; Tost, Heike; Akdeniz, Ceren; Rohleder, Cathrin; Bumb, J Malte; Schwarz, Emanuel; Alptekin, Köksal; Üçok, Alp; Saka, Meram Can; Atbaşoğlu, E Cem; Gülöksüz, Sinan; Gumus-Akay, Guvem; Cihan, Burçin; Karadağ, Hasan; Soygür, Haldan; Cankurtaran, Eylem Şahin; Ulusoy, Semra; Akdede, Berna; Binbay, Tolga; Ayer, Ahmet; Noyan, Handan; Karadayı, Gülşah; Akturan, Elçin; Ulaş, Halis; Arango, Celso; Parellada, Mara; Bernardo, Miguel; Sanjuán, Julio; Bobes, Julio; Arrojo, Manuel; Santos, Jose Luis; Cuadrado, Pedro; Rodríguez Solano, José Juan; Carracedo, Angel; García Bernardo, Enrique; Roldán, Laura; López, Gonzalo; Cabrera, Bibiana; Cruz, Sabrina; Díaz Mesa, Eva Ma; Pouso, María; Jiménez, Estela; Sánchez, Teresa; Rapado, Marta; González, Emiliano; Martínez, Covadonga; Sánchez, Emilio; Olmeda, Ma Soledad; de Haan, Lieuwe; Velthorst, Eva; van der Gaag, Mark; Selten, Jean-Paul; van Dam, Daniella; van der Ven, Elsje; van der Meer, Floor; Messchaert, Elles; Kraan, Tamar; Burger, Nadine; Leboyer, Marion; Szoke, Andrei; Schürhoff, Franck; Llorca, Pierre-Michel; Jamain, Stéphane; Tortelli, Andrea; Frijda, Flora; Vilain, Jeanne; Galliot, Anne-Marie; Baudin, Grégoire; Ferchiou, Aziz; Richard, Jean-Romain; Bulzacka, Ewa; Charpeaud, Thomas; Tronche, Anne-Marie; De Hert, Marc; van Winkel, Ruud; Decoster, Jeroen; Derom, Catherine; Thiery, Evert; Stefanis, Nikos C; Sachs, Gabriele; Aschauer, Harald; Lasser, Iris; Winklbaur, Bernadette; Schlögelhofer, Monika; Riecher-Rössler, Anita; Borgwardt, Stefan; Walter, Anna; Harrisberger, Fabienne; Smieskova, Renata; Rapp, Charlotte; Ittig, Sarah; Soguel-dit-Piquard, Fabienne; Studerus, Erich; Klosterkötter, Joachim; Ruhrmann, Stephan; Paruch, Julia; Julkowski, Dominika; Hilboll, Desiree; Sham, Pak C; Cherny, Stacey S; Chen, Eric Y H; Campbell, Desmond D; Li, Miaoxin; Romeo-Casabona, Carlos María; Emaldi Cirión, Aitziber; Urruela Mora, Asier; Jones, Peter; Kirkbride, James; Cannon, Mary; Rujescu, Dan; Tarricone, Ilaria; Berardi, Domenico; Bonora, Elena; Seri, Marco; Marcacci, Thomas; Chiri, Luigi; Chierzi, Federico; Storbini, Viviana; Braca, Mauro; Minenna, Maria Gabriella; Donegani, Ivonne; Fioritti, Angelo; La Barbera, Daniele; La Cascia, Caterina Erika; Mulè, Alice; Sideli, Lucia; Sartorio, Rachele; Ferraro, Laura; Tripoli, Giada; Seminerio, Fabio; Marinaro, Anna Maria; McGorry, Patrick; Nelson, Barnaby; Amminger, G Paul; Pantelis, Christos; Menezes, Paulo R; Del-Ben, Cristina M; Gallo Tenan, Silvia H; Shuhama, Rosana; Ruggeri, Mirella; Tosato, Sarah; Lasalvia, Antonio; Bonetto, Chiara; Ira, Elisa; Nordentoft, Merete; Krebs, Marie-Odile; Barrantes-Vidal, Neus; Cristóbal, Paula; Kwapil, Thomas R; Brietzke, Elisa; Bressan, Rodrigo A; Gadelha, Ary; Maric, Nadja P; Andric, Sanja; Mihaljevic, Marina; Mirjanic, Tijana

2014-07-01

Recent years have seen considerable progress in epidemiological and molecular genetic research into environmental and genetic factors in schizophrenia, but methodological uncertainties remain with regard to validating environmental exposures, and the population risk conferred by individual molecular genetic variants is small. There are now also a limited number of studies that have investigated molecular genetic candidate gene-environment interactions (G × E), however, so far, thorough replication of findings is rare and G × E research still faces several conceptual and methodological challenges. In this article, we aim to review these recent developments and illustrate how integrated, large-scale investigations may overcome contemporary challenges in G × E research, drawing on the example of a large, international, multi-center study into the identification and translational application of G × E in schizophrenia. While such investigations are now well underway, new challenges emerge for G × E research from late-breaking evidence that genetic variation and environmental exposures are, to a significant degree, shared across a range of psychiatric disorders, with potential overlap in phenotype. © The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Gene X Environment Interactions in Autism Spectrum Disorders: Role of Epigenetic Mechanisms

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Sylvie eTordjman

2014-08-01

Full Text Available Several studies support currently the hypothesis that autism etiology is based on a polygenic and epistatic model. However, despite advances in epidemiological, molecular and clinical genetics, the genetic risk factors remain difficult to identify, with the exception of a few chromosomal disorders and several single gene disorders associated with an increased risk for autism. Furthermore, several studies suggest a role of environmental factors in autism spectrum disorders (ASD. First, arguments for a genetic contribution to autism, based on updated family and twin studies, are examined. Second, a review of possible prenatal, perinatal and postnatal environmental risk factors for ASD are presented. Then, the hypotheses are discussed concerning the underlying mechanisms related to a role of environmental factors in the development of ASD in association with genetic factors. In particular, epigenetics as a candidate biological mechanism for gene X environment interactions is considered and the possible role of epigenetic mechanisms reported in genetic disorders associated with ASD is discussed. Furthermore, the example of in utero exposure to valproate provides a good illustration of epigenetic mechanisms involved in ASD and innovative therapeutic strategies. Epigenetic remodeling by environmental factors opens new perspectives for a better understanding, prevention and early therapeutic intervention of ASD.

The genetics of human longevity: an intricacy of genes, environment, culture and microbiome.

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Dato, Serena; Rose, Giuseppina; Crocco, Paolina; Monti, Daniela; Garagnani, Paolo; Franceschi, Claudio; Passarino, Giuseppe

2017-07-01

Approximately one-quarter of the variation in lifespan in developed countries can be attributed to genetic factors. However, even large population based studies investigating genetic influence on human lifespan have been disappointing, identifying only a few genes accounting for genetic susceptibility to longevity. Some environmental and lifestyle determinants associated with longevity have been identified, which interplay with genetic factors in an intricate way. The study of gene-environment and gene-gene interactions can significantly improve our chance to disentangle this complex scenario. In this review, we first describe the most recent approaches for genetic studies of longevity, from those enriched with health parameters and frailty measures to pathway-based and SNP-SNP interaction analyses. Then, we go deeper into the concept of "environmental influences" in human aging and longevity, focusing on the contribution of life style changes, social and cultural influences, as important determinants of survival differences among individuals in a population. Finally, we discuss the contribution of the microbiome in human longevity, as an example of complex interaction between organism and environment. In conclusion, evidences collected from the latest studies on human longevity provide a support for the collection of life-long genetic and environmental/lifestyle variables with beneficial or detrimental effects on health, to improve our understanding of the determinants of human lifespan. Copyright © 2017 Elsevier B.V. All rights reserved.

Gene-environment interaction and male reproductive function

DEFF Research Database (Denmark)

Axelsson, Jonatan; Bonde, Jens Peter; Giwercman, Yvonne L

2010-01-01

As genetic factors can hardly explain the changes taking place during short time spans, environmental and lifestyle-related factors have been suggested as the causes of time-related deterioration of male reproductive function. However, considering the strong heterogeneity of male fecundity between...... and within populations, genetic variants might be important determinants of the individual susceptibility to the adverse effects of environment or lifestyle. Although the possible mechanisms of such interplay in relation to the reproductive system are largely unknown, some recent studies have indicated...... that specific genotypes may confer a larger risk of male reproductive disorders following certain exposures. This paper presents a critical review of animal and human evidence on how genes may modify environmental effects on male reproductive function. Some examples have been found that support this mechanism...

Insights into significant pathways and gene interaction networks in peripheral blood mononuclear cells for early diagnosis of hepatocellular carcinoma

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Jian Xin Jiang

2016-01-01

Conclusions: Using identified DEGs, significantly changed biological processes such as nucleic acid metabolic process and KEGG pathways such as cytokine-cytokine receptor interaction in PBMCs of HCC patients were identified. In addition, several important hub genes, for example, CUL4A, and interleukin (IL 8 were also uncovered.

Attachment style and oxytocin receptor gene variation interact in influencing social anxiety.

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Notzon, S; Domschke, K; Holitschke, K; Ziegler, C; Arolt, V; Pauli, P; Reif, A; Deckert, J; Zwanzger, P

2016-01-01

Social anxiety has been suggested to be promoted by an insecure attachment style. Oxytocin is discussed as a mediator of trust and social bonding as well as a modulator of social anxiety. Applying a gene-environment (G × E) interaction approach, in the present pilot study the main and interactive effects of attachment styles and oxytocin receptor (OXTR) gene variation were probed in a combined risk factor model of social anxiety in healthy probands. Participants (N = 388; 219 females, 169 males; age 24.7 ± 4.7 years) were assessed for anxiety in social situations (Social Phobia and Anxiety Inventory) depending on attachment style (Adult Attachment Scale, AAS) and OXTR rs53576 A/G genotype. A less secure attachment style was significantly associated with higher social anxiety. This association was partly modulated by OXTR genotype, with a stronger negative influence of a less secure attachment style on social anxiety in A allele carriers as compared to GG homozygotes. The present pilot data point to a strong association of less secure attachment and social anxiety as well as to a gene-environment interaction effect of OXTR rs53576 genotype and attachment style on social anxiety possibly constituting a targetable combined risk marker of social anxiety disorder.

Gene-environment interplay in the etiology of psychosis.

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Zwicker, Alyson; Denovan-Wright, Eileen M; Uher, Rudolf

2018-01-15

Schizophrenia and other types of psychosis incur suffering, high health care costs and loss of human potential, due to the combination of early onset and poor response to treatment. Our ability to prevent or cure psychosis depends on knowledge of causal mechanisms. Molecular genetic studies show that thousands of common and rare variants contribute to the genetic risk for psychosis. Epidemiological studies have identified many environmental factors associated with increased risk of psychosis. However, no single genetic or environmental factor is sufficient to cause psychosis on its own. The risk of developing psychosis increases with the accumulation of many genetic risk variants and exposures to multiple adverse environmental factors. Additionally, the impact of environmental exposures likely depends on genetic factors, through gene-environment interactions. Only a few specific gene-environment combinations that lead to increased risk of psychosis have been identified to date. An example of replicable gene-environment interaction is a common polymorphism in the AKT1 gene that makes its carriers sensitive to developing psychosis with regular cannabis use. A synthesis of results from twin studies, molecular genetics, and epidemiological research outlines the many genetic and environmental factors contributing to psychosis. The interplay between these factors needs to be considered to draw a complete picture of etiology. To reach a more complete explanation of psychosis that can inform preventive strategies, future research should focus on longitudinal assessments of multiple environmental exposures within large, genotyped cohorts beginning early in life.

Evidence of gene-environment interactions between common breast cancer susceptibility loci and established environmental risk factors.

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Stefan Nickels

Full Text Available Various common genetic susceptibility loci have been identified for breast cancer; however, it is unclear how they combine with lifestyle/environmental risk factors to influence risk. We undertook an international collaborative study to assess gene-environment interaction for risk of breast cancer. Data from 24 studies of the Breast Cancer Association Consortium were pooled. Using up to 34,793 invasive breast cancers and 41,099 controls, we examined whether the relative risks associated with 23 single nucleotide polymorphisms were modified by 10 established environmental risk factors (age at menarche, parity, breastfeeding, body mass index, height, oral contraceptive use, menopausal hormone therapy use, alcohol consumption, cigarette smoking, physical activity in women of European ancestry. We used logistic regression models stratified by study and adjusted for age and performed likelihood ratio tests to assess gene-environment interactions. All statistical tests were two-sided. We replicated previously reported potential interactions between LSP1-rs3817198 and parity (Pinteraction = 2.4 × 10(-6 and between CASP8-rs17468277 and alcohol consumption (Pinteraction = 3.1 × 10(-4. Overall, the per-allele odds ratio (95% confidence interval for LSP1-rs3817198 was 1.08 (1.01-1.16 in nulliparous women and ranged from 1.03 (0.96-1.10 in parous women with one birth to 1.26 (1.16-1.37 in women with at least four births. For CASP8-rs17468277, the per-allele OR was 0.91 (0.85-0.98 in those with an alcohol intake of <20 g/day and 1.45 (1.14-1.85 in those who drank ≥ 20 g/day. Additionally, interaction was found between 1p11.2-rs11249433 and ever being parous (Pinteraction = 5.3 × 10(-5, with a per-allele OR of 1.14 (1.11-1.17 in parous women and 0.98 (0.92-1.05 in nulliparous women. These data provide first strong evidence that the risk of breast cancer associated with some common genetic variants may vary with environmental risk factors.

Gene-Environment Interaction in Parkinson's Disease: Coffee, ADORA2A, and CYP1A2.

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Chuang, Yu-Hsuan; Lill, Christina M; Lee, Pei-Chen; Hansen, Johnni; Lassen, Christina F; Bertram, Lars; Greene, Naomi; Sinsheimer, Janet S; Ritz, Beate

2016-01-01

Drinking caffeinated coffee has been reported to provide protection against Parkinson's disease (PD). Caffeine is an adenosine A2A receptor (encoded by the gene ADORA2A) antagonist that increases dopaminergic neurotransmission and Cytochrome P450 1A2 (gene: CYP1A2) metabolizes caffeine; thus, gene polymorphisms in ADORA2A and CYP1A2 may influence the effect coffee consumption has on PD risk. In a population-based case-control study (PASIDA) in Denmark (1,556 PD patients and 1,606 birth year- and gender-matched controls), we assessed interactions between lifetime coffee consumption and 3 polymorphisms in ADORA2A and CYP1A2 for all subjects, and incident and prevalent PD cases separately using logistic regression models. We also conducted a meta-analysis combining our results with those from previous studies. We estimated statistically significant interactions for ADORA2A rs5760423 and heavy vs. light coffee consumption in incident (OR interaction = 0.66 [95% CI 0.46-0.94], p = 0.02) but not prevalent PD. We did not observe interactions for CYP1A2 rs762551 and rs2472304 in incident or prevalent PD. In meta-analyses, PD associations with daily coffee consumption were strongest among carriers of variant alleles in both ADORA2A and CYP1A2. We corroborated results from a previous report that described interactions between ADORA2A and CYP1A2 polymorphisms and coffee consumption. Our results also suggest that survivor bias may affect results of studies that enroll prevalent PD cases. © 2017 S. Karger AG, Basel.

Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases

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Ma'ayan Avi

2007-10-01

Full Text Available Abstract Background In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP, generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Results Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Conclusion Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

Comparison of weighting approaches for genetic risk scores in gene-environment interaction studies.

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Hüls, Anke; Krämer, Ursula; Carlsten, Christopher; Schikowski, Tamara; Ickstadt, Katja; Schwender, Holger

2017-12-16

Weighted genetic risk scores (GRS), defined as weighted sums of risk alleles of single nucleotide polymorphisms (SNPs), are statistically powerful for detection gene-environment (GxE) interactions. To assign weights, the gold standard is to use external weights from an independent study. However, appropriate external weights are not always available. In such situations and in the presence of predominant marginal genetic effects, we have shown in a previous study that GRS with internal weights from marginal genetic effects ("GRS-marginal-internal") are a powerful and reliable alternative to single SNP approaches or the use of unweighted GRS. However, this approach might not be appropriate for detecting predominant interactions, i.e. interactions showing an effect stronger than the marginal genetic effect. In this paper, we present a weighting approach for such predominant interactions ("GRS-interaction-training") in which parts of the data are used to estimate the weights from the interaction terms and the remaining data are used to determine the GRS. We conducted a simulation study for the detection of GxE interactions in which we evaluated power, type I error and sign-misspecification. We compared this new weighting approach to the GRS-marginal-internal approach and to GRS with external weights. Our simulation study showed that in the absence of external weights and with predominant interaction effects, the highest power was reached with the GRS-interaction-training approach. If marginal genetic effects were predominant, the GRS-marginal-internal approach was more appropriate. Furthermore, the power to detect interactions reached by the GRS-interaction-training approach was only slightly lower than the power achieved by GRS with external weights. The power of the GRS-interaction-training approach was confirmed in a real data application to the Traffic, Asthma and Genetics (TAG) Study (N = 4465 observations). When appropriate external weights are unavailable, we

A gene-environment interaction analysis of plasma selenium with prevalent and incident diabetes: The Hortega study.

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Galan-Chilet, Inmaculada; Grau-Perez, Maria; De Marco, Griselda; Guallar, Eliseo; Martin-Escudero, Juan Carlos; Dominguez-Lucas, Alejandro; Gonzalez-Manzano, Isabel; Lopez-Izquierdo, Raul; Briongos-Figuero, Laisa Socorro; Redon, Josep; Chaves, Felipe Javier; Tellez-Plaza, Maria

2017-08-01

Selenium and single-nucleotide-polymorphisms in selenoprotein genes have been associated to diabetes. However, the interaction of selenium with genetic variation in diabetes and oxidative stress-related genes has not been evaluated as a potential determinant of diabetes risk. We evaluated the cross-sectional and prospective associations of plasma selenium concentrations with type 2 diabetes, and the interaction of selenium concentrations with genetic variation in candidate polymorphisms, in a representative sample of 1452 men and women aged 18-85 years from Spain. The geometric mean of plasma selenium levels in the study sample was 84.2µg/L. 120 participants had diabetes at baseline. Among diabetes-free participants who were not lost during the follow-up (N=1234), 75 developed diabetes over time. The multivariable adjusted odds ratios (95% confidence interval) for diabetes prevalence comparing the second and third to the first tertiles of plasma selenium levels were 1.80 (1.03, 3.14) and 1.97 (1.14, 3.41), respectively. The corresponding hazard ratios (95% CI) for diabetes incidence were 1.76 (0.96, 3.22) and 1.80 (0.98, 3.31), respectively. In addition, we observed significant interactions between selenium and polymorphisms in PPARGC1A, and in genes encoding mitochondrial proteins, such as BCS1L and SDHA, and suggestive interactions of selenium with other genes related to selenoproteins and redox metabolism. Plasma selenium was positively associated with prevalent and incident diabetes. While the statistical interactions of selenium with polymorphisms involved in regulation of redox and insulin signaling pathways provide biological plausibility to the positive associations of selenium with diabetes, further research is needed to elucidate the causal pathways underlying these associations. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Gene-Environment Interplay in the Association between Pubertal Timing and Delinquency in Adolescent Girls

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Harden, K. Paige; Mendle, Jane

2014-01-01

Early pubertal timing places girls at elevated risk for a breadth of negative outcomes, including involvement in delinquent behavior. While previous developmental research has emphasized the unique social challenges faced by early maturing girls, this relation is complicated by genetic influences for both delinquent behavior and pubertal timing, which are seldom controlled for in existing research. The current study uses genetically informed data on 924 female-female twin and sibling pairs drawn from the National Longitudinal Study of Adolescent Health to (1) disentangle biological versus environmental mechanisms for the effects of early pubertal timing and (2) test for gene-environment interactions. Results indicate that early pubertal timing influences girls’ delinquency through a complex interplay between biological risk and environmental experiences. Genes related to earlier age at menarche and higher perceived development significantly predict increased involvement in both non-violent and violent delinquency. Moreover, after accounting for this genetic association between pubertal timing and delinquency, the impact of non-shared environmental influences on delinquency are significantly moderated by pubertal timing, such that the non-shared environment is most important among early maturing girls. This interaction effect is particularly evident for non-violent delinquency. Overall, results suggest early maturing girls are vulnerable to an interaction between genetic and environmental risks for delinquent behavior. PMID:21668078

Gene-Environment Interaction Effects of Peer Deviance, Parental Knowledge and Stressful Life Events on Adolescent Alcohol Use.

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Cooke, Megan E; Meyers, Jacquelyn L; Latvala, Antti; Korhonen, Tellervo; Rose, Richard J; Kaprio, Jaakko; Salvatore, Jessica E; Dick, Danielle M

2015-10-01

The purpose of this study was to address two methodological issues that have called into question whether previously reported gene-environment interaction (GxE) effects for adolescent alcohol use are 'real'. These issues are (1) the potential correlation between the environmental moderator and the outcome across twins and (2) non-linear transformations of the behavioral outcome. Three environments that have been previously studied (peer deviance, parental knowledge, and potentially stressful life events) were examined here. For each moderator (peer deviance, parental knowledge, and potentially stressful life events), a series of models was fit to both a raw and transformed measure of monthly adolescent alcohol use in a sample that included 825 dizygotic (DZ) and 803 monozygotic (MZ) twin pairs. The results showed that the moderating effect of peer deviance was robust to transformation, and that although the significance of moderating effects of parental knowledge and potentially stressful life events were dependent on the scale of the adolescent alcohol use outcome, the overall results were consistent across transformation. In addition, the findings did not vary across statistical models. The consistency of the peer deviance results and the shift of the parental knowledge and potentially stressful life events results between trending and significant, shed some light on why previous findings for certain moderators have been inconsistent and emphasize the importance of considering both methodological issues and previous findings when conducting and interpreting GxE analyses.

A deeper look at two concepts of measuring gene-gene interactions: logistic regression and interaction information revisited.

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Mielniczuk, Jan; Teisseyre, Paweł

2018-03-01

Detection of gene-gene interactions is one of the most important challenges in genome-wide case-control studies. Besides traditional logistic regression analysis, recently the entropy-based methods attracted a significant attention. Among entropy-based methods, interaction information is one of the most promising measures having many desirable properties. Although both logistic regression and interaction information have been used in several genome-wide association studies, the relationship between them has not been thoroughly investigated theoretically. The present paper attempts to fill this gap. We show that although certain connections between the two methods exist, in general they refer two different concepts of dependence and looking for interactions in those two senses leads to different approaches to interaction detection. We introduce ordering between interaction measures and specify conditions for independent and dependent genes under which interaction information is more discriminative measure than logistic regression. Moreover, we show that for so-called perfect distributions those measures are equivalent. The numerical experiments illustrate the theoretical findings indicating that interaction information and its modified version are more universal tools for detecting various types of interaction than logistic regression and linkage disequilibrium measures. © 2017 WILEY PERIODICALS, INC.

Gene-Environment Interplay in Common Complex Diseases: Forging an Integrative Model—Recommendations From an NIH Workshop

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Bookman, Ebony B.; McAllister, Kimberly; Gillanders, Elizabeth; Wanke, Kay; Balshaw, David; Rutter, Joni; Reedy, Jill; Shaughnessy, Daniel; Agurs-Collins, Tanya; Paltoo, Dina; Atienza, Audie; Bierut, Laura; Kraft, Peter; Fallin, M. Daniele; Perera, Frederica; Turkheimer, Eric; Boardman, Jason; Marazita, Mary L.; Rappaport, Stephen M.; Boerwinkle, Eric; Suomi, Stephen J.; Caporaso, Neil E.; Hertz-Picciotto, Irva; Jacobson, Kristen C.; Lowe, William L.; Goldman, Lynn R.; Duggal, Priya; Gunnar, Megan R.; Manolio, Teri A.; Green, Eric D.; Olster, Deborah H.; Birnbaum, Linda S.

2011-01-01

Although it is recognized that many common complex diseases are a result of multiple genetic and environmental risk factors, studies of gene-environment interaction remain a challenge and have had limited success to date. Given the current state-of-the-science, NIH sought input on ways to accelerate investigations of gene-environment interplay in health and disease by inviting experts from a variety of disciplines to give advice about the future direction of gene-environment interaction studies. Participants of the NIH Gene-Environment Interplay Workshop agreed that there is a need for continued emphasis on studies of the interplay between genetic and environmental factors in disease and that studies need to be designed around a multifaceted approach to reflect differences in diseases, exposure attributes, and pertinent stages of human development. The participants indicated that both targeted and agnostic approaches have strengths and weaknesses for evaluating main effects of genetic and environmental factors and their interactions. The unique perspectives represented at the workshop allowed the exploration of diverse study designs and analytical strategies, and conveyed the need for an interdisciplinary approach including data sharing, and data harmonization to fully explore gene-environment interactions. Further, participants also emphasized the continued need for high-quality measures of environmental exposures and new genomic technologies in ongoing and new studies. PMID:21308768

Vulnerability or Sensitivity to the Environment? Methodological Issues, Trends, and Recommendations in Gene–Environment Interactions Research in Human Behavior

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Caroline Leighton

2017-06-01

Full Text Available Research on the potential role of gene–environment interactions (GxE in explaining vulnerability to psychopathology in humans has witnessed a shift from a diathesis-stress perspective to differential susceptibility approaches. This paper critically reviews methodological issues and trends in this body of research. Databases were screened for studies of GxE in the prediction of personality traits, behavior, and mental health disorders in humans published between January 2002 and January 2015. In total, 315 papers were included. Results showed that 34 candidate genes have been included in GxE studies. Independent of the type of environment studied (early or recent life events, positive or negative environments, about 67–83% of studies have reported significant GxE interactions, which is consistent with a social susceptibility model. The percentage of positive results does not seem to differ depending on the gene studied, although publication bias might be involved. However, the number of positive findings differs depending on the population studied (i.e., young adults vs. older adults. Methodological considerations limit the ability to draw strong conclusions, particularly as almost 90% (n = 283/315 of published papers are based on samples from North America and Europe, and about 70% of published studies (219/315 are based on samples that were also used in other reports. At the same time, there are clear indications of methodological improvements over time, as is shown by a significant increase in longitudinal and experimental studies as well as in improved minimum genotyping. Recommendations for future research, such as minimum quality assessment of genes and environmental factors, specifying theoretical models guiding the study, and taking into account of cultural, ethnic, and lifetime perspectives, are formulated.

Gene-environment interaction in Parkinson’s disease: coffee, ADORA2A, and CYP1A2

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Chuang, Yu-Hsuan; Lill, Christina M.; Lee, Pei-Chen; Hansen, Johnni; Lassen, Christina Funch; Bertram, Lars; Greene, Naomi; Sinsheimer, Janet S.; Ritz, Beate

2017-01-01

Background and purpose Drinking caffeinated coffee has been reported to protect against Parkinson’s disease (PD). Caffeine is an adenosine A2A receptor (encoded by the gene ADORA2A) antagonist that increases dopaminergic neurotransmission and Cytochrome P450 1A2 (gene: CYP1A2) metabolizes caffeine, thus gene polymorphisms in ADORA2A and CYP1A2 may influence the effect coffee consumption has on PD risk. Methods In a population-based case control study (PASIDA) in Denmark (1,556 PD patients and 1,606 birth year- and sex- matched controls), we assessed interactions between lifetime coffee consumption and three polymorphisms in ADORA2A and CYP1A2 for all subjects and incident and prevalent PD cases separately using logistic regression models. We also conducted a meta-analysis combining our results with those from previous studies. Results We estimated statistically significant interactions for ADORA2A rs5760423 and heavy vs. light coffee consumption in incident (OR interaction=0.66 [0.46–0.94], p=0.02) but not prevalent PD. We did not observe interactions for CYP1A2 rs762551 and rs2472304 in incident or prevalent PD. In meta-analyses, PD associations with daily coffee consumption were strongest among carriers of variant alleles in both ADORA2A and CYP1A2. Conclusion We corroborated results from a previous report that described interactions between ADORA2A and CYP1A2 polymorphisms and coffee consumption. Our results also suggest that survivor bias may affect results of studies that enrol prevalent PD cases. PMID:28135712

SLC6A1 gene involvement in susceptibility to attention-deficit/hyperactivity disorder: A case-control study and gene-environment interaction.

Science.gov (United States)

Yuan, Fang-Fen; Gu, Xue; Huang, Xin; Zhong, Yan; Wu, Jing

2017-07-03

Attention-deficit/hyperactivity disorder (ADHD) is an early onset childhood neurodevelopmental disorder with an estimated heritability of approximately 76%. We conducted a case-control study to explore the role of the SLC6A1 gene in ADHD. The genotypes of eight variants were determined using Sequenom MassARRAY technology. The participants in the study were 302 children with ADHD and 411 controls. ADHD symptoms were assessed using the Conners Parent Symptom Questionnaire. In our study, rs2944366 was consistently shown to be associated with the ADHD risk in the dominant model (odds ratio [OR]=0.554, 95% confidence interval [CI]=0.404-0.760), and nominally associated with Hyperactive index score (P=0.027). In addition, rs1170695 has been found to be associated with the ADHD risk in the addictive model (OR=1.457, 95%CI=1.173-1.809), while rs9990174 was associated with the Hyperactive index score (P=0.010). Intriguingly, gene-environmental interactions analysis consistently revealed the potential interactions of rs1170695 with blood lead (P mul =0.044) to modify the ADHD risk. Expression quantitative trait loci analysis suggested that these positive single nucleotide polymorphisms (SNPs) may mediate SLC6A1 gene expression. Therefore, our results suggest that selected SLC6A1 gene variants may have a significant effect on the ADHD risk. Copyright © 2017 Elsevier Inc. All rights reserved.

Gene-Environment Interaction in Parkinson's Disease

DEFF Research Database (Denmark)

Chuang, Yu-Hsuan; Lill, Christina M; Lee, Pei-Chen

2016-01-01

BACKGROUND AND PURPOSE: Drinking caffeinated coffee has been reported to provide protection against Parkinson's disease (PD). Caffeine is an adenosine A2A receptor (encoded by the gene ADORA2A) antagonist that increases dopaminergic neurotransmission and Cytochrome P450 1A2 (gene: CYP1A2...

Genetic risk for schizophrenia, obstetric complications, and adolescent school outcome: evidence for gene-environment interaction.

Science.gov (United States)

Forsyth, Jennifer K; Ellman, Lauren M; Tanskanen, Antti; Mustonen, Ulla; Huttunen, Matti O; Suvisaari, Jaana; Cannon, Tyrone D

2013-09-01

Low birth weight (LBW) and hypoxia are among the environmental factors most reliably associated with schizophrenia; however, the nature of this relationship is unclear and both gene-environment interaction and gene-environment covariation models have been proposed as explanations. High-risk (HR) designs that explore whether obstetric complications differentially predict outcomes in offspring at low risk (LR) vs HR for schizophrenia, while accounting for differences in rates of maternal risk factors, may shed light on this question. This study used prospectively obtained data to examine relationships between LBW and hypoxia on school outcome at age 15-16 years in a Finnish sample of 1070 offspring at LR for schizophrenia and 373 offspring at HR for schizophrenia, based on parental psychiatric history. Controlling for offspring sex, maternal smoking, social support, parity, age, and number of prenatal care visits, HR offspring performed worse than LR offspring across academic, nonacademic, and physical education domains. LBW predicted poorer academic and physical education performance in HR offspring, but not in LR offspring, and this association was similar for offspring of fathers vs mothers with schizophrenia. Hypoxia predicted poorer physical education score across risk groups. Rates of LBW and hypoxia were similar for LR and HR offspring and for offspring of fathers vs mothers with schizophrenia. Results support the hypothesis that genetic susceptibility to schizophrenia confers augmented vulnerability of the developing brain to the effects of obstetric complications, possibly via epigenetic mechanisms.

The interaction of combined effects of the BDNF and PRKCG genes and negative life events in major depressive disorder.

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Yang, Chunxia; Sun, Ning; Liu, Zhifen; Li, Xinrong; Xu, Yong; Zhang, Kerang

2016-03-30

Major depressive disorder (MDD) is a mental disorder that results from complex interplay between multiple and partially overlapping sets of susceptibility genes and environmental factors. The brain derived neurotrophic factor (BDNF) and Protein kinase C gamma type (PRKCG) are logical candidate genes in MDD. Among diverse environmental factors, negative life events have been suggested to exert a crucial impact on brain development. In the present study, we hypothesized that interactions between genetic variants in BDNF and PRKCG and negative life events may play an important role in the development of MDD. We recruited a total of 406 patients with MDD and 391 age- and gender-matched control subjects. Gene-environment interactions were analyzed using generalized multifactor dimensionality reduction (GMDR). Under a dominant model, we observed a significant three-way interaction among BDNF rs6265, PRKCG rs3745406, and negative life events. The gene-environment combination of PRKCG rs3745406 C allele, BDNF rs6265 G allele and high level of negative life events (C-G-HN) was significantly associated with MDD (OR, 5.97; 95% CI, 2.71-13.15). To our knowledge, this is the first report of evidence that the BDNF-PRKCG interaction may modify the relationship between negative life events and MDD in the Chinese population. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Molecular Aspects of Dopaminergic Neurodegeneration: Gene-Environment Interaction in Parkin Dysfunction

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Syed Z. Imam

2011-12-01

Full Text Available Parkinson’s disease (PD is a common neurodegenerative movement disorder that is characterized pathologically by a progressive loss of midbrain dopaminergic neurons and by protein inclusions, designated Lewy bodies and Lewy neurites. PD is one of the most common neurodegenerative diseases, affecting almost 1% of the population over 60 years old. Although the symptoms and neuropathology of PD have been well characterized, the underlying mechanisms and causes of the disease are still not clear. Genetic mutations can provide important clues to disease mechanism, but most PD cases are sporadic rather than familial; environmental factors have long been suspected to contribute to the disease. Although more than 90% of PD cases occur sporadically and are thought to be due, in part, to oxidative stress and mitochondrial dysfunction, the study of genetic mutations has provided great insight into the molecular mechanisms of PD. Furthermore, rotenone, a widely used pesticide, and paraquat and maneb cause a syndrome in rats and mice that mimics, both behaviorally and neurologically, the symptoms of PD. In the current review, we will discuss various aspects of gene-environment interaction that lead to progressive dopaminergic neurodegenration, mainly focusing on our current finding based on stress-mediated parkin dysfunction.

Analysis of Behavioral and Emotional Problems in Children Highlights the Role of Genotype 9 Environment Interaction

NARCIS (Netherlands)

Molenaar, D.; Middeldorp, C.M.; van Beijsterveldt, C.E.M.; Boomsma, D.I.

2015-01-01

This study tested for Genotype × Environment (G × E) interaction on behavioral and emotional problems in children using new methods that do not require identification of candidate genes or environments, can distinguish between interaction with shared and unique environment, and are insensitive to

Analysis of behavioral and emotional problems in children highlights the role of genotype × environment interaction

NARCIS (Netherlands)

Molenaar, D.; Middeldorp, C.; van Beijsterveldt, T.; Boomsma, D.I.

2015-01-01

This study tested for Genotype × Environment (G × E) interaction on behavioral and emotional problems in children using new methods that do not require identification of candidate genes or environments, can distinguish between interaction with shared and unique environment, and are insensitive to

Duplicability of self-interacting human genes.

LENUS (Irish Health Repository)

Pérez-Bercoff, Asa

2010-01-01

BACKGROUND: There is increasing interest in the evolution of protein-protein interactions because this should ultimately be informative of the patterns of evolution of new protein functions within the cell. One model proposes that the evolution of new protein-protein interactions and protein complexes proceeds through the duplication of self-interacting genes. This model is supported by data from yeast. We examined the relationship between gene duplication and self-interaction in the human genome. RESULTS: We investigated the patterns of self-interaction and duplication among 34808 interactions encoded by 8881 human genes, and show that self-interacting proteins are encoded by genes with higher duplicability than genes whose proteins lack this type of interaction. We show that this result is robust against the system used to define duplicate genes. Finally we compared the presence of self-interactions amongst proteins whose genes have duplicated either through whole-genome duplication (WGD) or small-scale duplication (SSD), and show that the former tend to have more interactions in general. After controlling for age differences between the two sets of duplicates this result can be explained by the time since the gene duplication. CONCLUSIONS: Genes encoding self-interacting proteins tend to have higher duplicability than proteins lacking self-interactions. Moreover these duplicate genes have more often arisen through whole-genome rather than small-scale duplication. Finally, self-interacting WGD genes tend to have more interaction partners in general in the PIN, which can be explained by their overall greater age. This work adds to our growing knowledge of the importance of contextual factors in gene duplicability.

Genome-wide identification of key modulators of gene-gene interaction networks in breast cancer.

Science.gov (United States)

Chiu, Yu-Chiao; Wang, Li-Ju; Hsiao, Tzu-Hung; Chuang, Eric Y; Chen, Yidong

2017-10-03

With the advances in high-throughput gene profiling technologies, a large volume of gene interaction maps has been constructed. A higher-level layer of gene-gene interaction, namely modulate gene interaction, is composed of gene pairs of which interaction strengths are modulated by (i.e., dependent on) the expression level of a key modulator gene. Systematic investigations into the modulation by estrogen receptor (ER), the best-known modulator gene, have revealed the functional and prognostic significance in breast cancer. However, a genome-wide identification of key modulator genes that may further unveil the landscape of modulated gene interaction is still lacking. We proposed a systematic workflow to screen for key modulators based on genome-wide gene expression profiles. We designed four modularity parameters to measure the ability of a putative modulator to perturb gene interaction networks. Applying the method to a dataset of 286 breast tumors, we comprehensively characterized the modularity parameters and identified a total of 973 key modulator genes. The modularity of these modulators was verified in three independent breast cancer datasets. ESR1, the encoding gene of ER, appeared in the list, and abundant novel modulators were illuminated. For instance, a prognostic predictor of breast cancer, SFRP1, was found the second modulator. Functional annotation analysis of the 973 modulators revealed involvements in ER-related cellular processes as well as immune- and tumor-associated functions. Here we present, as far as we know, the first comprehensive analysis of key modulator genes on a genome-wide scale. The validity of filtering parameters as well as the conservativity of modulators among cohorts were corroborated. Our data bring new insights into the modulated layer of gene-gene interaction and provide candidates for further biological investigations.

Genetic risk for violent behavior and environmental exposure to disadvantage and violent crime: the case for gene-environment interaction.

Science.gov (United States)

Barnes, J C; Jacobs, Bruce A

2013-01-01

Despite mounds of evidence to suggest that neighborhood structural factors predict violent behavior, almost no attention has been given to how these influences work synergistically (i.e., interact) with an individual's genetic propensity toward violent behavior. Indeed, two streams of research have, heretofore, flowed independently of one another. On one hand, criminologists have underscored the importance of neighborhood context in the etiology of violence. On the other hand, behavioral geneticists have argued that individual-level genetic propensities are important for understanding violence. The current study seeks to integrate these two compatible frameworks by exploring gene-environment interactions (GxE). Two GxEs were examined and supported by the data (i.e., the National Longitudinal Study of Adolescent Health). Using a scale of genetic risk based on three dopamine genes, the analysis revealed that genetic risk had a greater influence on violent behavior when the individual was also exposed to neighborhood disadvantage or when the individual was exposed to higher violent crime rates. The relevance of these findings for criminological theorizing was considered.

Gene-Diet Interaction and Precision Nutrition in Obesity

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Yoriko Heianza

2017-04-01

Full Text Available The rapid rise of obesity during the past decades has coincided with a profound shift of our living environment, including unhealthy dietary patterns, a sedentary lifestyle, and physical inactivity. Genetic predisposition to obesity may have interacted with such an obesogenic environment in determining the obesity epidemic. Growing studies have found that changes in adiposity and metabolic response to low-calorie weight loss diets might be modified by genetic variants related to obesity, metabolic status and preference to nutrients. This review summarized data from recent studies of gene-diet interactions, and discussed integration of research of metabolomics and gut microbiome, as well as potential application of the findings in precision nutrition.

The influence of host genotype X environment Interactions on the ...

African Journals Online (AJOL)

Mean squares for environments, genotypes and G x E interactions were highly significant (P<0.0001) for anthracnose infection. Significant G x E interactions, accounting for 19% of the treatment sums of squares, indicated that genotypes responded differentially to anthracnose infection across environments. The additive ...

A kernel regression approach to gene-gene interaction detection for case-control studies.

Science.gov (United States)

Larson, Nicholas B; Schaid, Daniel J

2013-11-01

Gene-gene interactions are increasingly being addressed as a potentially important contributor to the variability of complex traits. Consequently, attentions have moved beyond single locus analysis of association to more complex genetic models. Although several single-marker approaches toward interaction analysis have been developed, such methods suffer from very high testing dimensionality and do not take advantage of existing information, notably the definition of genes as functional units. Here, we propose a comprehensive family of gene-level score tests for identifying genetic elements of disease risk, in particular pairwise gene-gene interactions. Using kernel machine methods, we devise score-based variance component tests under a generalized linear mixed model framework. We conducted simulations based upon coalescent genetic models to evaluate the performance of our approach under a variety of disease models. These simulations indicate that our methods are generally higher powered than alternative gene-level approaches and at worst competitive with exhaustive SNP-level (where SNP is single-nucleotide polymorphism) analyses. Furthermore, we observe that simulated epistatic effects resulted in significant marginal testing results for the involved genes regardless of whether or not true main effects were present. We detail the benefits of our methods and discuss potential genome-wide analysis strategies for gene-gene interaction analysis in a case-control study design. © 2013 WILEY PERIODICALS, INC.

The complement system: a gateway to gene-environment interactions in schizophrenia pathogenesis.

Science.gov (United States)

Nimgaonkar, V L; Prasad, K M; Chowdari, K V; Severance, E G; Yolken, R H

2017-11-01

The pathogenesis of schizophrenia is considered to be multi-factorial, with likely gene-environment interactions (GEI). Genetic and environmental risk factors are being identified with increasing frequency, yet their very number vastly increases the scope of possible GEI, making it difficult to identify them with certainty. Accumulating evidence suggests a dysregulated complement pathway among the pathogenic processes of schizophrenia. The complement pathway mediates innate and acquired immunity, and its activation drives the removal of damaged cells, autoantigens and environmentally derived antigens. Abnormalities in complement functions occur in many infectious and autoimmune disorders that have been linked to schizophrenia. Many older reports indicate altered serum complement activity in schizophrenia, though the data are inconclusive. Compellingly, recent genome-wide association studies suggest repeat polymorphisms incorporating the complement 4A (C4A) and 4B (C4B) genes as risk factors for schizophrenia. The C4A/C4B genetic associations have re-ignited interest not only in inflammation-related models for schizophrenia pathogenesis, but also in neurodevelopmental theories, because rodent models indicate a role for complement proteins in synaptic pruning and neurodevelopment. Thus, the complement system could be used as one of the 'staging posts' for a variety of focused studies of schizophrenia pathogenesis. They include GEI studies of the C4A/C4B repeat polymorphisms in relation to inflammation-related or infectious processes, animal model studies and tests of hypotheses linked to autoimmune diseases that can co-segregate with schizophrenia. If they can be replicated, such studies would vastly improve our understanding of pathogenic processes in schizophrenia through GEI analyses and open new avenues for therapy.

Evidence for Gender-Dependent Genotype by Environment Interaction in Adult Depression.

Science.gov (United States)

Molenaar, Dylan; Middeldorp, Christel M; Willemsen, Gonneke; Ligthart, Lannie; Nivard, Michel G; Boomsma, Dorret I

2015-10-14

Depression in adults is heritable with about 40 % of the phenotypic variance due to additive genetic effects and the remaining phenotypic variance due to unique (unshared) environmental effects. Common environmental effects shared by family members are rarely found in adults. One possible explanation for this finding is that there is an interaction between genes and the environment which may mask effects of the common environment. To test this hypothesis, we investigated genotype by environment interaction in a large sample of female and male adult twins aged 18-70 years. The anxious depression subscale of the Adult Self Report from the Achenbach System of Empirically Based Assessment (Achenbach and Rescorla in Manual for the ASEBA adult: forms and profiles, 2003) was completed by 13,022 twins who participate in longitudinal studies of the Netherlands Twin Register. In a single group analysis, we found genotype by unique environment interaction, but no genotype by common environment interaction. However, when conditioning on gender, we observed genotype by common environment interaction in men, with larger common environmental variance in men who are genetically less at risk to develop depression. Although the effect size of the interaction is characterized by large uncertainty, the results show that there is at least some variance due to the common environment in adult depression in men.

Significant interactions between maternal PAH exposure and haplotypes in candidate genes on B[a]P-DNA adducts in a NYC cohort of non-smoking African-American and Dominican mothers and newborns

Science.gov (United States)

Tang, Deliang

2014-01-01

Polycyclic aromatic hydrocarbons (PAH) are a class of chemicals common in the environment. Certain PAH are carcinogenic, although the degree to which genetic variation influences susceptibility to carcinogenic PAH remains unclear. Also unknown is the influence of genetic variation on the procarcinogenic effect of in utero exposures to PAH. Benzo[a]pyrene (B[a]P) is a well-studied PAH that is classified as a probable human carcinogen. Within our New York City-based cohort, we explored interactions between maternal exposure to airborne PAH during pregnancy and maternal and newborn haplotypes (and in one case, a single-nucleotide polymorphism) in key B[a]P metabolism genes on B[a]P-DNA adducts in paired cord blood samples. The study subjects included non-smoking African-American (n = 132) and Dominican (n = 235) women with available data on maternal PAH exposure, paired cord adducts and genetic data who resided in the Washington Heights, Central Harlem and South Bronx neighborhoods of New York City. We selected seven maternal and newborn genes related to B[a]P metabolism, detoxification and repair for our analyses: CYP1A1, CYP1A2, CYP1B1, GSTM3, GSTT2, NQO1 and XRCC1. We found significant interactions between maternal PAH exposure and haplotype on cord B[a]P-DNA adducts in the following genes: maternal CYP1B1, XRCC1 and GSTM3, and newborn CYP1A2 and XRCC1 in African-Americans; and maternal XRCC1 and newborn NQO1 in Dominicans. These novel findings highlight differences in maternal and newborn genetic contributions to B[a]P-DNA adduct formation, as well as ethnic differences in gene–environment interactions, and have the potential to identify at-risk subpopulations who are susceptible to the carcinogenic potential of B[a]P. PMID:24177223

Explaining human uniqueness: genome interactions with environment, behaviour and culture.

Science.gov (United States)

Varki, Ajit; Geschwind, Daniel H; Eichler, Evan E

2008-10-01

What makes us human? Specialists in each discipline respond through the lens of their own expertise. In fact, 'anthropogeny' (explaining the origin of humans) requires a transdisciplinary approach that eschews such barriers. Here we take a genomic and genetic perspective towards molecular variation, explore systems analysis of gene expression and discuss an organ-systems approach. Rejecting any 'genes versus environment' dichotomy, we then consider genome interactions with environment, behaviour and culture, finally speculating that aspects of human uniqueness arose because of a primate evolutionary trend towards increasing and irreversible dependence on learned behaviours and culture - perhaps relaxing allowable thresholds for large-scale genomic diversity.

DISC1 mouse models as a tool to decipher gene-environment interactions in psychiatric disorders

Directory of Open Access Journals (Sweden)

Tyler eCash-Padgett

2013-09-01

Full Text Available DISC1 was discovered in a Scottish pedigree in which a chromosomal translocation that breaks this gene segregates with psychiatric disorders, mainly depression and schizophrenia. Linkage and association studies in diverse populations support DISC1 as a susceptibility gene to a variety of neuropsychiatric disorders. Many Disc1 mouse models have been generated to study its neuronal functions. These mouse models display variable phenotypes, some of them relevant to schizophrenia, others to depression.The Disc1 mouse models are popular genetic models for studying gene-environment interactions in schizophrenia. Five different Disc1 models have been combined with environmental factors. The environmental stressors employed can be classified as either early immune activation or later social paradigms. These studies cover major time points along the neurodevelopmental trajectory: prenatal, early postnatal, adolescence, and adulthood. Various combinations of molecular, anatomical and behavioral methods have been used to assess the outcomes. Additionally, three of the studies sought to rescue the resulting abnormalities.Here we provide background on the environmental paradigms used, summarize the results of these studies combining Disc1 mouse models with environmental stressors and discuss what we can learn and how to proceed. A major question is how the genetic and environmental factors determine which psychiatric disorder will be clinically manifested. To address this we can take advantage of the many Disc1 models available and expose them to the same environmental stressor. The complementary experiment would be to expose the same model to different environmental stressors. DISC1 is an ideal gene for this approach, since in the Scottish pedigree the same chromosomal translocation results in different psychiatric conditions.

Genotype x environment interaction and optimum resource ...

African Journals Online (AJOL)

... x E) interaction and to determine the optimum resource allocation for cassava yield trials. The effects of environment, genotype and G x E interaction were highly significant for all yield traits. Variations due to G x E interaction were greater than those due to genotypic differences for all yield traits. Genotype x location x year ...

Interactions of adolescent social experiences and dopamine genes to predict physical intimate partner violence perpetration.

Directory of Open Access Journals (Sweden)

Laura M Schwab-Reese

Full Text Available We examined the interactions between three dopamine gene alleles (DAT1, DRD2, DRD4 previously associated with violent behavior and two components of the adolescent environment (exposure to violence, school social environment to predict adulthood physical intimate partner violence (IPV perpetration among white men and women.We used data from Wave IV of the National Longitudinal Study of Adolescent to Adult Health, a cohort study following individuals from adolescence to adulthood. Based on the prior literature, we categorized participants as at risk for each of the three dopamine genes using this coding scheme: two 10-R alleles for DAT1; at least one A-1 allele for DRD2; at least one 7-R or 8-R allele for DRD4. Adolescent exposure to violence and school social environment was measured in 1994 and 1995 when participants were in high school or middle school. Intimate partner violence perpetration was measured in 2008 when participants were 24 to 32 years old. We used simple and multivariable logistic regression models, including interactions of genes and the adolescent environments for the analysis.Presence of risk alleles was not independently associated with IPV perpetration but increasing exposure to violence and disconnection from the school social environment was associated with physical IPV perpetration. The effects of these adolescent experiences on physical IPV perpetration varied by dopamine risk allele status. Among individuals with non-risk dopamine alleles, increased exposure to violence during adolescence and perception of disconnection from the school environment were significantly associated with increased odds of physical IPV perpetration, but individuals with high risk alleles, overall, did not experience the same increase.Our results suggested the effects of adolescent environment on adulthood physical IPV perpetration varied by genetic factors. This analysis did not find a direct link between risk alleles and violence, but

Genome-Wide Gene-Environment Study Identifies Glutamate Receptor Gene GRIN2A as a Parkinson's Disease Modifier Gene via Interaction with Coffee

Science.gov (United States)

Hamza, Taye H.; Chen, Honglei; Hill-Burns, Erin M.; Rhodes, Shannon L.; Montimurro, Jennifer; Kay, Denise M.; Tenesa, Albert; Kusel, Victoria I.; Sheehan, Patricia; Eaaswarkhanth, Muthukrishnan; Yearout, Dora; Samii, Ali; Roberts, John W.; Agarwal, Pinky; Bordelon, Yvette; Park, Yikyung; Wang, Liyong; Gao, Jianjun; Vance, Jeffery M.; Kendler, Kenneth S.; Bacanu, Silviu-Alin; Scott, William K.; Ritz, Beate; Nutt, John; Factor, Stewart A.; Zabetian, Cyrus P.; Payami, Haydeh

2011-01-01

Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD). We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC), and we performed a genome-wide association and interaction study (GWAIS), testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal components. We then stratified subjects as heavy or light coffee-drinkers and performed genome-wide association study (GWAS) in each group. We replicated the most significant SNP. Finally, we imputed the NGRC dataset, increasing genomic coverage to examine the region of interest in detail. The primary analyses (GWAIS, GWAS, Replication) were performed using genotyped data. In GWAIS, the most significant signal came from rs4998386 and the neighboring SNPs in GRIN2A. GRIN2A encodes an NMDA-glutamate-receptor subunit and regulates excitatory neurotransmission in the brain. Achieving P2df = 10−6, GRIN2A surpassed all known PD susceptibility genes in significance in the GWAIS. In stratified GWAS, the GRIN2A signal was present in heavy coffee-drinkers (OR = 0.43; P = 6×10−7) but not in light coffee-drinkers. The a priori Replication hypothesis that “Among heavy coffee-drinkers, rs4998386_T carriers have lower PD risk than rs4998386_CC carriers” was confirmed: ORReplication = 0.59, PReplication = 10−3; ORPooled = 0.51, PPooled = 7×10−8. Compared to light coffee-drinkers with rs4998386_CC genotype, heavy coffee-drinkers with rs4998386_CC genotype had 18% lower risk (P = 3×10−3), whereas heavy coffee-drinkers with rs4998386_TC genotype had 59% lower risk (P = 6×10−13). Imputation revealed a block of SNPs that achieved P2dfcoffee-drinkers. This study is proof of concept that inclusion of environmental factors can help identify genes that

Genome-wide gene-environment study identifies glutamate receptor gene GRIN2A as a Parkinson's disease modifier gene via interaction with coffee.

Science.gov (United States)

Hamza, Taye H; Chen, Honglei; Hill-Burns, Erin M; Rhodes, Shannon L; Montimurro, Jennifer; Kay, Denise M; Tenesa, Albert; Kusel, Victoria I; Sheehan, Patricia; Eaaswarkhanth, Muthukrishnan; Yearout, Dora; Samii, Ali; Roberts, John W; Agarwal, Pinky; Bordelon, Yvette; Park, Yikyung; Wang, Liyong; Gao, Jianjun; Vance, Jeffery M; Kendler, Kenneth S; Bacanu, Silviu-Alin; Scott, William K; Ritz, Beate; Nutt, John; Factor, Stewart A; Zabetian, Cyrus P; Payami, Haydeh

2011-08-01

Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD). We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC), and we performed a genome-wide association and interaction study (GWAIS), testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal components. We then stratified subjects as heavy or light coffee-drinkers and performed genome-wide association study (GWAS) in each group. We replicated the most significant SNP. Finally, we imputed the NGRC dataset, increasing genomic coverage to examine the region of interest in detail. The primary analyses (GWAIS, GWAS, Replication) were performed using genotyped data. In GWAIS, the most significant signal came from rs4998386 and the neighboring SNPs in GRIN2A. GRIN2A encodes an NMDA-glutamate-receptor subunit and regulates excitatory neurotransmission in the brain. Achieving P(2df) = 10(-6), GRIN2A surpassed all known PD susceptibility genes in significance in the GWAIS. In stratified GWAS, the GRIN2A signal was present in heavy coffee-drinkers (OR = 0.43; P = 6×10(-7)) but not in light coffee-drinkers. The a priori Replication hypothesis that "Among heavy coffee-drinkers, rs4998386_T carriers have lower PD risk than rs4998386_CC carriers" was confirmed: OR(Replication) = 0.59, P(Replication) = 10(-3); OR(Pooled) = 0.51, P(Pooled) = 7×10(-8). Compared to light coffee-drinkers with rs4998386_CC genotype, heavy coffee-drinkers with rs4998386_CC genotype had 18% lower risk (P = 3×10(-3)), whereas heavy coffee-drinkers with rs4998386_TC genotype had 59% lower risk (P = 6×10(-13)). Imputation revealed a block of SNPs that achieved P(2df)coffee-drinkers. This study is proof of concept that inclusion of environmental factors can help identify

Estimating genetic effect sizes under joint disease-endophenotype models in presence of gene-environment interactions

Directory of Open Access Journals (Sweden)

Alexandre eBureau

2015-07-01

Full Text Available Effects of genetic variants on the risk of complex diseases estimated from association studies are typically small. Nonetheless, variants may have important effects in presence of specific levels of environmental exposures, and when a trait related to the disease (endophenotype is either normal or impaired. We propose polytomous and transition models to represent the relationship between disease, endophenotype, genotype and environmental exposure in family studies. Model coefficients were estimated using generalized estimating equations and were used to derive gene-environment interaction effects and genotype effects at specific levels of exposure. In a simulation study, estimates of the effect of a genetic variant were substantially higher when both an endophenotype and an environmental exposure modifying the variant effect were taken into account, particularly under transition models, compared to the alternative of ignoring the endophenotype. Illustration of the proposed modeling with the metabolic syndrome, abdominal obesity, physical activity and polymorphisms in the NOX3 gene in the Quebec Family Study revealed that the positive association of the A allele of rs1375713 with the metabolic syndrome at high levels of physical activity was only detectable in subjects without abdominal obesity, illustrating the importance of taking into account the abdominal obesity endophenotype in this analysis.

Detection of Gene Interactions Based on Syntactic Relations

Directory of Open Access Journals (Sweden)

Mi-Young Kim

2008-01-01

Full Text Available Interactions between proteins and genes are considered essential in the description of biomolecular phenomena, and networks of interactions are applied in a system's biology approach. Recently, many studies have sought to extract information from biomolecular text using natural language processing technology. Previous studies have asserted that linguistic information is useful for improving the detection of gene interactions. In particular, syntactic relations among linguistic information are good for detecting gene interactions. However, previous systems give a reasonably good precision but poor recall. To improve recall without sacrificing precision, this paper proposes a three-phase method for detecting gene interactions based on syntactic relations. In the first phase, we retrieve syntactic encapsulation categories for each candidate agent and target. In the second phase, we construct a verb list that indicates the nature of the interaction between pairs of genes. In the last phase, we determine direction rules to detect which of two genes is the agent or target. Even without biomolecular knowledge, our method performs reasonably well using a small training dataset. While the first phase contributes to improve recall, the second and third phases contribute to improve precision. In the experimental results using ICML 05 Workshop on Learning Language in Logic (LLL05 data, our proposed method gave an F-measure of 67.2% for the test data, significantly outperforming previous methods. We also describe the contribution of each phase to the performance.

Childhood problem behavior and parental divorce: evidence for gene-environment interaction.

Science.gov (United States)

Robbers, Sylvana; van Oort, Floor; Huizink, Anja; Verhulst, Frank; van Beijsterveldt, Catharina; Boomsma, Dorret; Bartels, Meike

2012-10-01

The importance of genetic and environmental influences on children's behavioral and emotional problems may vary as a function of environmental exposure. We previously reported that 12-year-olds with divorced parents showed more internalizing and externalizing problems than children with married parents, and that externalizing problems in girls precede and predict later parental divorce. The aim of the current study was to investigate as to whether genetic and environmental influences on internalizing and externalizing problems were different for children from divorced versus non-divorced families. Maternal ratings on internalizing and externalizing problems were collected with the Child Behavior Checklist in 4,592 twin pairs at ages 3 and 12 years, of whom 367 pairs had experienced a parental divorce between these ages. Variance in internalizing and externalizing problems at ages 3 and 12 was analyzed with biometric models in which additive genetic and environmental effects were allowed to depend on parental divorce and sex. A difference in the contribution of genetic and environmental influences between divorced and non-divorced groups would constitute evidence for gene-environment interaction. For both pre- and post-divorce internalizing and externalizing problems, the total variances were larger for children from divorced families, which was mainly due to higher environmental variances. As a consequence, heritabilities were lower for children from divorced families, and the relative contributions of environmental influences were higher. Environmental influences become more important in explaining variation in children's problem behaviors in the context of parental divorce.

Early life adversity and serotonin transporter gene variation interact to affect DNA methylation of the corticotropin-releasing factor gene promoter region in the adult rat brain

NARCIS (Netherlands)

Doelen, R.H.A. van der; Arnoldussen, I.A.C.; Ghareh, H.; Och, L. van; Homberg, J.R.; Kozicz, L.T.

2015-01-01

The interaction between childhood maltreatment and the serotonin transporter (5-HTT) gene linked polymorphic region has been associated with increased risk to develop major depression. This Gene x Environment interaction has furthermore been linked with increased levels of anxiety and glucocorticoid

Differences and similarities in the serotonergic diathesis for suicide attempts and mood disorders: a 22-year longitudinal gene-environment study.

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Brezo, J; Bureau, A; Mérette, C; Jomphe, V; Barker, E D; Vitaro, F; Hébert, M; Carbonneau, R; Tremblay, R E; Turecki, G

2010-08-01

To investigate similarities and differences in the serotonergic diathesis for mood disorders and suicide attempts, we conducted a study in a cohort followed longitudinally for 22 years. A total of 1255 members of this cohort, which is representative of the French-speaking population of Quebec, were investigated. Main outcome measures included (1) mood disorders (bipolar disorder and major depression) and suicide attempts by early adulthood; (2) odds ratios and probabilities associated with 143 single nucleotide polymorphisms in 11 serotonergic genes, acting directly or as moderators in gene-environment interactions with childhood sexual or childhood physical abuse (CPA), and in gene-gene interactions; (3) regression coefficients for putative endophenotypes for mood disorders (childhood anxiousness) and suicide attempts (childhood disruptiveness). Five genes showed significant adjusted effects (HTR2A, TPH1, HTR5A, SLC6A4 and HTR1A). Of these, HTR2A variation influenced both suicide attempts and mood disorders, although through different mechanisms. In suicide attempts, HTR2A variants (rs6561333, rs7997012 and rs1885884) were involved through interactions with histories of sexual and physical abuse whereas in mood disorders through one main effect (rs9316235). In terms of phenotype-specific contributions, TPH1 variation (rs10488683) was relevant only in the diathesis for suicide attempts. Three genes contributed exclusively to mood disorders, one through a main effect (HTR5A (rs1657268)) and two through gene-environment interactions with CPA (HTR1A (rs878567) and SLC6A4 (rs3794808)). Childhood anxiousness did not mediate the effects of HTR2A and HTR5A on mood disorders, nor did childhood disruptiveness mediate the effects of TPH1 on suicide attempts. Of the serotonergic genes implicated in mood disorders and suicidal behaviors, four exhibited phenotype-specific effects, suggesting that despite their high concordance and common genetic determinants, suicide attempts

Gene-Environment Interplay between Parent-Child Relationship Problems and Externalizing Disorders in Adolescence and Young Adulthood

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Samek, Diana R.; Hicks, Brian M.; Keyes, Margaret A.; Bailey, Jennifer; McGue, Matt; Iacono, William G.

2014-01-01

Background Previous studies have shown that genetic risk for externalizing (EXT) disorders is greater in the context of adverse family environments during adolescence, but it is unclear whether these effects are long-lasting. The current study evaluated developmental changes in gene-environment interplay in the concurrent and prospective associations between parent-child relationship problems and EXT at ages 18 and 25. Method The sample included 1,382 twin pairs (48% male) from the Minnesota Twin Family Study, participating in assessments at ages 18 (M = 17.8 years, SD = 0.69) and 25 (M = 25.0 years, SD = 0.90). Perceptions of parent-child relationship problems were assessed using questionnaires. Structured interviews were used to assess symptoms of adult antisocial behavior and nicotine, alcohol, and illicit drug dependence. Results We detected a gene-environment interaction at age 18, such that the genetic influence on EXT was greater in the context of more parent-child relationship problems. This moderation effect was not present at age 25, nor did parent-relationship problems at age 18 moderate genetic influence on EXT at age 25. Rather, common genetic influences accounted for this longitudinal association. Conclusions Gene-environment interaction evident in the relationship between adolescent parent-child relationship problems and EXT is both proximal and developmentally limited. Common genetic influence, rather than a gene-environment interaction, accounts for the long-term association between parent-child relationship problems at age 18 and EXT at age 25. These results are consistent with a relatively pervasive importance of gene-environmental correlation in the transition from late adolescence to young adulthood. PMID:25066478

Risk score modeling of multiple gene to gene interactions using aggregated-multifactor dimensionality reduction

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Dai Hongying

2013-01-01

Full Text Available Abstract Background Multifactor Dimensionality Reduction (MDR has been widely applied to detect gene-gene (GxG interactions associated with complex diseases. Existing MDR methods summarize disease risk by a dichotomous predisposing model (high-risk/low-risk from one optimal GxG interaction, which does not take the accumulated effects from multiple GxG interactions into account. Results We propose an Aggregated-Multifactor Dimensionality Reduction (A-MDR method that exhaustively searches for and detects significant GxG interactions to generate an epistasis enriched gene network. An aggregated epistasis enriched risk score, which takes into account multiple GxG interactions simultaneously, replaces the dichotomous predisposing risk variable and provides higher resolution in the quantification of disease susceptibility. We evaluate this new A-MDR approach in a broad range of simulations. Also, we present the results of an application of the A-MDR method to a data set derived from Juvenile Idiopathic Arthritis patients treated with methotrexate (MTX that revealed several GxG interactions in the folate pathway that were associated with treatment response. The epistasis enriched risk score that pooled information from 82 significant GxG interactions distinguished MTX responders from non-responders with 82% accuracy. Conclusions The proposed A-MDR is innovative in the MDR framework to investigate aggregated effects among GxG interactions. New measures (pOR, pRR and pChi are proposed to detect multiple GxG interactions.

Confluence of genes, environment, development, and behavior in a post Genome-Wide Association Study world

DEFF Research Database (Denmark)

Vrieze, S. I.; Iacono, W. G.; McGue, M.

2012-01-01

This article serves to outline a research paradigm to investigate main effects and interactions of genes, environment, and development on behavior and psychiatric illness. We provide a historical context for candidate gene studies and genome-wide association studies, including benefits, limitations...

Cognitive endophenotypes, gene-environment interactions and experience-dependent plasticity in animal models of schizophrenia.

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Burrows, Emma L; Hannan, Anthony J

2016-04-01

Schizophrenia is a devastating brain disorder caused by a complex and heterogeneous combination of genetic and environmental factors. In order to develop effective new strategies to prevent and treat schizophrenia, valid animal models are required which accurately model the disorder, and ideally provide construct, face and predictive validity. The cognitive deficits in schizophrenia represent some of the most debilitating symptoms and are also currently the most poorly treated. Therefore it is crucial that animal models are able to capture the cognitive dysfunction that characterizes schizophrenia, as well as the negative and psychotic symptoms. The genomes of mice have, prior to the recent gene-editing revolution, proven the most easily manipulable of mammalian laboratory species, and hence most genetic targeting has been performed using mouse models. Importantly, when key environmental factors of relevance to schizophrenia are experimentally manipulated, dramatic changes in the phenotypes of these animal models are often observed. We will review recent studies in rodent models which provide insight into gene-environment interactions in schizophrenia. We will focus specifically on environmental factors which modulate levels of experience-dependent plasticity, including environmental enrichment, cognitive stimulation, physical activity and stress. The insights provided by this research will not only help refine the establishment of optimally valid animal models which facilitate development of novel therapeutics, but will also provide insight into the pathogenesis of schizophrenia, thus identifying molecular and cellular targets for future preclinical and clinical investigations. Copyright © 2015 Elsevier B.V. All rights reserved.

Gene-environment interaction and biological monitoring of occupational exposures

International Nuclear Information System (INIS)

Hirvonen, Ari

2005-01-01

Biological monitoring methods and biological limit values applied in occupational and environmental medicine have been traditionally developed on the assumption that individuals do not differ significantly in their biotransformation capacities. It has become clear, however, that this is not the case, but wide inter-individual differences exist in the metabolism of chemicals. Integration of the data on individual metabolic capacity in biological monitoring studies is therefore anticipated to represent a significant refinement of the currently used methods. We have recently conducted several biological monitoring studies on occupationally exposed subjects, which have included the determination of the workers' genotypes for the metabolic genes of potential importance for a given chemical exposure. The exposure levels have been measured by urine metabolites, adducts in blood macromolecules, and cytogenetic alterations in lymphocytes. Our studies indicate that genetic polymorphisms in metabolic genes may indeed be important modifiers of individual biological monitoring results of, e.g., carbon disulphide and styrene. The information is anticipated to be useful in insuring that the workplace is safe for everyone, including the most sensitive individuals. This knowledge could also be useful to occupational physicians, industrial hygienists, and regulatory bodies in charge of defining acceptable exposure limits for environmental and/or occupational pollutants

Genotypes Do Not Confer Risk For Delinquency ut Rather Alter Susceptibility to Positive and Negative Environmental Factors: Gene-Environment Interactions of BDNF Val66Met, 5-HTTLPR, and MAOA-uVNTR

Science.gov (United States)

Comasco, Erika; Hodgins, Sheilagh; Oreland, Lars; Åslund, Cecilia

2015-01-01

Background: Previous evidence of gene-by-environment interactions associated with emotional and behavioral disorders is contradictory. Differences in findings may result from variation in valence and dose of the environmental factor, and/or failure to take account of gene-by-gene interactions. The present study investigated interactions between the brain-derived neurotrophic factor gene (BDNF Val66Met), the serotonin transporter gene-linked polymorphic region (5-HTTLPR), the monoamine oxidase A (MAOA-uVNTR) polymorphisms, family conflict, sexual abuse, the quality of the child-parent relationship, and teenage delinquency. Methods: In 2006, as part of the Survey of Adolescent Life in Västmanland, Sweden, 1 337 high-school students, aged 17–18 years, anonymously completed questionnaires and provided saliva samples for DNA analyses. Results: Teenage delinquency was associated with two-, three-, and four-way interactions of each of the genotypes and the three environmental factors. Significant four-way interactions were found for BDNF Val66Met × 5-HTTLPR×MAOA-uVNTR × family conflicts and for BDNF Val66Met × 5-HTTLPR×MAOA-uVNTR × sexual abuse. Further, the two genotype combinations that differed the most in expression levels (BDNF Val66Met Val, 5-HTTLPR LL, MAOA-uVNTR LL [girls] and L [boys] vs BDNF Val66Met Val/Met, 5-HTTLPR S/LS, MAOA-uVNTR S/SS/LS) in interaction with family conflict and sexual abuse were associated with the highest delinquency scores. The genetic variants previously shown to confer vulnerability for delinquency (BDNF Val66Met Val/Met × 5-HTTLPR S × MAOA-uVNTR S) were associated with the lowest delinquency scores in interaction with a positive child-parent relationship. Conclusions: Functional variants of the MAOA-uVNTR, 5-HTTLPR, and BDNF Val66Met, either alone or in interaction with each other, may be best conceptualized as modifying sensitivity to environmental factors that confer either risk or protection for teenage delinquency. PMID

Genome-wide gene-environment study identifies glutamate receptor gene GRIN2A as a Parkinson's disease modifier gene via interaction with coffee.

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Taye H Hamza

2011-08-01

Full Text Available Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD. We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC, and we performed a genome-wide association and interaction study (GWAIS, testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal components. We then stratified subjects as heavy or light coffee-drinkers and performed genome-wide association study (GWAS in each group. We replicated the most significant SNP. Finally, we imputed the NGRC dataset, increasing genomic coverage to examine the region of interest in detail. The primary analyses (GWAIS, GWAS, Replication were performed using genotyped data. In GWAIS, the most significant signal came from rs4998386 and the neighboring SNPs in GRIN2A. GRIN2A encodes an NMDA-glutamate-receptor subunit and regulates excitatory neurotransmission in the brain. Achieving P(2df = 10(-6, GRIN2A surpassed all known PD susceptibility genes in significance in the GWAIS. In stratified GWAS, the GRIN2A signal was present in heavy coffee-drinkers (OR = 0.43; P = 6×10(-7 but not in light coffee-drinkers. The a priori Replication hypothesis that "Among heavy coffee-drinkers, rs4998386_T carriers have lower PD risk than rs4998386_CC carriers" was confirmed: OR(Replication = 0.59, P(Replication = 10(-3; OR(Pooled = 0.51, P(Pooled = 7×10(-8. Compared to light coffee-drinkers with rs4998386_CC genotype, heavy coffee-drinkers with rs4998386_CC genotype had 18% lower risk (P = 3×10(-3, whereas heavy coffee-drinkers with rs4998386_TC genotype had 59% lower risk (P = 6×10(-13. Imputation revealed a block of SNPs that achieved P(2df<5×10(-8 in GWAIS, and OR = 0.41, P = 3×10(-8 in heavy coffee-drinkers. This study is proof of

Interactive Environment Design in Smart City

Science.gov (United States)

Deng, DeXiang; Chen, LanSha; Zhou, Xi

2017-08-01

The interactive environment design of smart city is not just an interactive progress or interactive mode design, rather than generate an environment such as the “organic” life entity as human beings through interactive design, forming a smart environment with perception, memory, thinking, and reaction.

Clock genes × stress × reward interactions in alcohol and substance use disorders.

Science.gov (United States)

Perreau-Lenz, Stéphanie; Spanagel, Rainer

2015-06-01

Adverse life events and highly stressful environments have deleterious consequences for mental health. Those environmental factors can potentiate alcohol and drug abuse in vulnerable individuals carrying specific genetic risk factors, hence producing the final risk for alcohol- and substance-use disorders development. The nature of these genes remains to be fully determined, but studies indicate their direct or indirect relation to the stress hypothalamo-pituitary-adrenal (HPA) axis and/or reward systems. Over the past decade, clock genes have been revealed to be key-players in influencing acute and chronic alcohol/drug effects. In parallel, the influence of chronic stress and stressful life events in promoting alcohol and substance use and abuse has been demonstrated. Furthermore, the reciprocal interaction of clock genes with various HPA-axis components, as well as the evidence for an implication of clock genes in stress-induced alcohol abuse, have led to the idea that clock genes, and Period genes in particular, may represent key genetic factors to consider when examining gene × environment interaction in the etiology of addiction. The aim of the present review is to summarize findings linking clock genes, stress, and alcohol and substance abuse, and to propose potential underlying neurobiological mechanisms. Copyright © 2015 Elsevier Inc. All rights reserved.

Gene-environment interaction in the onset of eczema in infancy

DEFF Research Database (Denmark)

Bisgaard, Hans; Simpson, Angela; Palmer, Colin N A

2008-01-01

BACKGROUND: Loss-of-function variants in the gene encoding filaggrin (FLG) are major determinants of eczema. We hypothesized that weakening of the physical barrier in FLG-deficient individuals may potentiate the effect of environmental exposures. Therefore, we investigated whether there is an int......BACKGROUND: Loss-of-function variants in the gene encoding filaggrin (FLG) are major determinants of eczema. We hypothesized that weakening of the physical barrier in FLG-deficient individuals may potentiate the effect of environmental exposures. Therefore, we investigated whether...... there is an interaction between FLG loss-of-function mutations with environmental exposures (pets and dust mites) in relation to the development of eczema. METHODS AND FINDINGS: We used data obtained in early life in a high-risk birth cohort in Denmark and replicated the findings in an unselected birth cohort...... in the United Kingdom. Primary outcome was age of onset of eczema; environmental exposures included pet ownership and mite and pet allergen levels. In Copenhagen (n = 379), FLG mutation increased the risk of eczema during the first year of life (hazard ratio [HR] 2.26, 95% confidence interval [CI] 1.27-4.00, p...

Spatially Uniform ReliefF (SURF for computationally-efficient filtering of gene-gene interactions

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Greene Casey S

2009-09-01

Full Text Available Abstract Background Genome-wide association studies are becoming the de facto standard in the genetic analysis of common human diseases. Given the complexity and robustness of biological networks such diseases are unlikely to be the result of single points of failure but instead likely arise from the joint failure of two or more interacting components. The hope in genome-wide screens is that these points of failure can be linked to single nucleotide polymorphisms (SNPs which confer disease susceptibility. Detecting interacting variants that lead to disease in the absence of single-gene effects is difficult however, and methods to exhaustively analyze sets of these variants for interactions are combinatorial in nature thus making them computationally infeasible. Efficient algorithms which can detect interacting SNPs are needed. ReliefF is one such promising algorithm, although it has low success rate for noisy datasets when the interaction effect is small. ReliefF has been paired with an iterative approach, Tuned ReliefF (TuRF, which improves the estimation of weights in noisy data but does not fundamentally change the underlying ReliefF algorithm. To improve the sensitivity of studies using these methods to detect small effects we introduce Spatially Uniform ReliefF (SURF. Results SURF's ability to detect interactions in this domain is significantly greater than that of ReliefF. Similarly SURF, in combination with the TuRF strategy significantly outperforms TuRF alone for SNP selection under an epistasis model. It is important to note that this success rate increase does not require an increase in algorithmic complexity and allows for increased success rate, even with the removal of a nuisance parameter from the algorithm. Conclusion Researchers performing genetic association studies and aiming to discover gene-gene interactions associated with increased disease susceptibility should use SURF in place of ReliefF. For instance, SURF should be

Influence of 5-HTT variation, childhood trauma and self-efficacy on anxiety traits: a gene-environment-coping interaction study.

Science.gov (United States)

Schiele, Miriam A; Ziegler, Christiane; Holitschke, Karoline; Schartner, Christoph; Schmidt, Brigitte; Weber, Heike; Reif, Andreas; Romanos, Marcel; Pauli, Paul; Zwanzger, Peter; Deckert, Jürgen; Domschke, Katharina

2016-08-01

Environmental vulnerability factors such as adverse childhood experiences in interaction with genetic risk variants, e.g., the serotonin transporter gene linked polymorphic region (5-HTTLPR), are assumed to play a role in the development of anxiety and affective disorders. However, positive influences such as general self-efficacy (GSE) may exert a compensatory effect on genetic disposition, environmental adversity, and anxiety traits. We, thus, assessed childhood trauma (Childhood Trauma Questionnaire, CTQ) and GSE in 678 adults genotyped for 5-HTTLPR/rs25531 and their interaction on agoraphobic cognitions (Agoraphobic Cognitions Questionnaire, ACQ), social anxiety (Liebowitz Social Anxiety Scale, LSAS), and trait anxiety (State-Trait Anxiety Inventory, STAI-T). The relationship between anxiety traits and childhood trauma was moderated by self-efficacy in 5-HTTLPR/rs25531 LALA genotype carriers: LALA probands maltreated as children showed high anxiety scores when self-efficacy was low, but low anxiety scores in the presence of high self-efficacy despite childhood maltreatment. Our results extend previous findings regarding anxiety-related traits showing an interactive relationship between 5-HTT genotype and adverse childhood experiences by suggesting coping-related measures to function as an additional dimension buffering the effects of a gene-environment risk constellation. Given that anxiety disorders manifest already early in childhood, this insight could contribute to the improvement of psychotherapeutic interventions by including measures strengthening self-efficacy and inform early targeted preventive interventions in at-risk populations, particularly within the crucial time window of childhood and adolescence.

Conceptual shifts needed to understand the dynamic interactions of genes, environment, epigenetics, social processes, and behavioral choices.

Science.gov (United States)

Jackson, Fatimah L C; Niculescu, Mihai D; Jackson, Robert T

2013-10-01

Social and behavioral research in public health is often intimately tied to profound, but frequently neglected, biological influences from underlying genetic, environmental, and epigenetic events. The dynamic interplay between the life, social, and behavioral sciences often remains underappreciated and underutilized in addressing complex diseases and disorders and in developing effective remediation strategies. Using a case-study format, we present examples as to how the inclusion of genetic, environmental, and epigenetic data can augment social and behavioral health research by expanding the parameters of such studies, adding specificity to phenotypic assessments, and providing additional internal control in comparative studies. We highlight the important roles of gene-environment interactions and epigenetics as sources of phenotypic change and as a bridge between the life and social and behavioral sciences in the development of robust interdisciplinary analyses.

Differential gene expression and Hog1 interaction with osmoresponsive genes in the extremely halotolerant black yeast Hortaea werneckii

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Plemenitaš Ana

2007-08-01

Full Text Available Abstract Background Fluctuations in external salinity force eukaryotic cells to respond by changes in the gene expression of proteins acting in protective biochemical processes, thus counteracting the changing osmotic pressure. The high-osmolarity glycerol (HOG signaling pathway is essential for the efficient up-regulation of the osmoresponsive genes. In this study, the differential gene expression of the extremely halotolerant black yeast Hortaea werneckii was explored. Furthermore, the interaction of mitogen-activated protein kinase HwHog1 and RNA polymerase II with the chromatin in cells adapted to an extremely hypersaline environment was analyzed. Results A cDNA subtraction library was constructed for H. werneckii, adapted to moderate salinity or an extremely hypersaline environment of 4.5 M NaCl. An uncommon osmoresponsive set of 95 differentially expressed genes was identified. The majority of these had not previously been connected with the adaptation of salt-sensitive S. cerevisiae to hypersaline conditions. The transcriptional response in hypersaline-adapted and hypersaline-stressed cells showed that only a subset of the identified genes responded to acute salt-stress, whereas all were differentially expressed in adapted cells. Interaction with HwHog1 was shown for 36 of the 95 differentially expressed genes. The majority of the identified osmoresponsive and HwHog1-dependent genes in H. werneckii have not been previously reported as Hog1-dependent genes in the salt-sensitive S. cerevisiae. The study further demonstrated the co-occupancy of HwHog1 and RNA polymerase II on the chromatin of 17 up-regulated and 2 down-regulated genes in 4.5 M NaCl-adapted H. werneckii cells. Conclusion Extremely halotolerant H. werneckii represents a suitable and highly relevant organism to study cellular responses to environmental salinity. In comparison with the salt-sensitive S. cerevisiae, this yeast shows a different set of genes being expressed at

Inverse gene-for-gene interactions contribute additively to tan spot susceptibility in wheat.

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Liu, Zhaohui; Zurn, Jason D; Kariyawasam, Gayan; Faris, Justin D; Shi, Gongjun; Hansen, Jana; Rasmussen, Jack B; Acevedo, Maricelis

2017-06-01

Tan spot susceptibility is conferred by multiple interactions of necrotrophic effector and host sensitivity genes. Tan spot of wheat, caused by Pyrenophora tritici-repentis, is an important disease in almost all wheat-growing areas of the world. The disease system is known to involve at least three fungal-produced necrotrophic effectors (NEs) that interact with the corresponding host sensitivity (S) genes in an inverse gene-for-gene manner to induce disease. However, it is unknown if the effects of these NE-S gene interactions contribute additively to the development of tan spot. In this work, we conducted disease evaluations using different races and quantitative trait loci (QTL) analysis in a wheat recombinant inbred line (RIL) population derived from a cross between two susceptible genotypes, LMPG-6 and PI 626573. The two parental lines each harbored a single known NE sensitivity gene with LMPG-6 having the Ptr ToxC sensitivity gene Tsc1 and PI 626573 having the Ptr ToxA sensitivity gene Tsn1. Transgressive segregation was observed in the population for all races. QTL mapping revealed that both loci (Tsn1 and Tsc1) were significantly associated with susceptibility to race 1 isolates, which produce both Ptr ToxA and Ptr ToxC, and the two genes contributed additively to tan spot susceptibility. For isolates of races 2 and 3, which produce only Ptr ToxA and Ptr ToxC, only Tsn1 and Tsc1 were associated with tan spot susceptibility, respectively. This work clearly demonstrates that tan spot susceptibility in this population is due primarily to two NE-S interactions. Breeders should remove both sensitivity genes from wheat lines to obtain high levels of tan spot resistance.

A mechanistic explanation of popularity: genes, rule breaking, and evocative gene-environment correlations.

Science.gov (United States)

Burt, Alexandra

2009-04-01

Previous work has suggested that the serotonergic system plays a key role in "popularity" or likeability. A polymorphism within the 5HT-sub(2A) serotonin receptor gene (-G1438A) has also been associated with popularity, suggesting that genes may predispose individuals to particular social experiences. However, because genes cannot code directly for others' reactions, any legitimate association should be mediated via the individual's behavior (i.e., genes-->behaviors-->social consequences), a phenomenon referred to as an evocative gene-environment correlation (rGE). The current study aimed to identify one such mediating behavior. The author focused on rule breaking given its prior links to both the serotonergic system and to increased popularity during adolescence. Two samples of previously unacquainted late-adolescent boys completed a peer-based interaction paradigm designed to assess their popularity. Analyses revealed that rule breaking partially mediated the genetic effect on popularity, thereby furthering our understanding of the biological mechanisms that underlie popularity. Moreover, the present results represent the first meaningfully explicated evidence that genes predispose individuals not only to particular behaviors but also to the social consequences of those behaviors. (c) 2009 APA, all rights reserved.

Genome-wide gene-environment study identifies glutamate receptor gene GRIN2A as a Parkinson's disease modifier gene via interaction with coffee.

OpenAIRE

Taye H Hamza; Honglei Chen; Erin M Hill-Burns; Shannon L Rhodes; Jennifer Montimurro; Denise M Kay; Albert Tenesa; Victoria I Kusel; Patricia Sheehan; Muthukrishnan Eaaswarkhanth; Dora Yearout; Ali Samii; John W Roberts; Pinky Agarwal; Yvette Bordelon

2011-01-01

Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD). We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC), and we performed a genome-wide association and interaction study (GWAIS), testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal compo...

Methylobacterium-plant interaction genes regulated by plant exudate and quorum sensing molecules

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Manuella Nóbrega Dourado

2013-12-01

Full Text Available Bacteria from the genus Methylobacterium interact symbiotically (endophytically and epiphytically with different plant species. These interactions can promote plant growth or induce systemic resistance, increasing plant fitness. The plant colonization is guided by molecular communication between bacteria-bacteria and bacteria-plants, where the bacteria recognize specific exuded compounds by other bacteria (e.g. homoserine molecules and/or by the plant roots (e.g. flavonoids, ethanol and methanol, respectively. In this context, the aim of this study was to evaluate the effect of quorum sensing molecules (N-acyl-homoserine lactones and plant exudates (including ethanol in the expression of a series of bacterial genes involved in Methylobacterium-plant interaction. The selected genes are related to bacterial metabolism (mxaF, adaptation to stressful environment (crtI, phoU and sss, to interactions with plant metabolism compounds (acdS and pathogenicity (patatin and phoU. Under in vitro conditions, our results showed the differential expression of some important genes related to metabolism, stress and pathogenesis, thereby AHL molecules up-regulate all tested genes, except phoU, while plant exudates induce only mxaF gene expression. In the presence of plant exudates there is a lower bacterial density (due the endophytic and epiphytic colonization, which produce less AHL, leading to down regulation of genes when compared to the control. Therefore, bacterial density, more than plant exudate, influences the expression of genes related to plant-bacteria interaction.

Identification of human disease genes from interactome network using graphlet interaction.

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Xiao-Dong Wang

Full Text Available Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes.

Identification of Human Disease Genes from Interactome Network Using Graphlet Interaction

Science.gov (United States)

Yang, Lun; Wei, Dong-Qing; Qi, Ying-Xin; Jiang, Zong-Lai

2014-01-01

Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes. PMID:24465923

Maternal Genetic Variants of IL4/IL13 Pathway Genes on IgE With "Western or Eastern Environments/Lifestyles".

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Zhang, Guicheng; Khoo, Siew-Kim; Mäkelä, Mika J; Candelaria, Pierre; Hayden, Catherine M; von Hertzen, Leena; Laatikainen, Tiina; Vartiainen, Erkki; Goldblatt, Jack; Haahtela, Tari; LeSouëf, Peter N

2014-07-01

We investigated maternal genetic effects of four IL-4/IL-13 pathway genes as well as their interactions with the "Western or Eastern lifestyles/environments" on IgE in Karelian children. This study included 609 children and their mothers. Total IgE levels in children and mothers were measured and 10 single nucleotide polymorphisms (SNPs) in IL-4, IL-4Ra, IL-13, and STAT6 were genotyped in mothers and their children. The maternal G allele of IL-13 130 (rs20541) was significantly (P=0.001) associated with decreased IgE in children in the Karelian population (Pooling Finnish and Russian children), as well as in Finnish (P=0.030) and Russian children (P=0.018). The IgE levels were significantly (P=0.001) higher in Russian children whose mothers were homozygous for the G allele of the IL-4Ra 50 (rs1805010) SNP than that in Russian children of mothers who were AG heterozygotes or AA homozygotes. After accounting for children's genotypes, we observed interactive effects on children's IgE for maternal IL-13 130 genotypes (P=0.014) and maternal IL-4Ra 50 genotypes (P=0.0003) with "Western or Eastern" lifestyles/environments. With the adjustment for multiple comparisons using a false discovery rate (FDR) of 0.05, the interactive effect of the maternal IL-4Ra50 SNP was significant. Maternal genetic variants in IL-4/IL-13 pathway genes, such as IL-13 130 and IL-4Ra50, influenced IgE levels in school children that were independent of the children's genetic effects. These effects differ in "Western or Eastern" environments.

Neighborhood alcohol outlet density and genetic influences on alcohol use: evidence for gene-environment interaction.

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Slutske, Wendy S; Deutsch, Arielle R; Piasecki, Thomas M

2018-05-07

Genetic influences on alcohol involvement are likely to vary as a function of the 'alcohol environment,' given that exposure to alcohol is a necessary precondition for genetic risk to be expressed. However, few gene-environment interaction studies of alcohol involvement have focused on characteristics of the community-level alcohol environment. The goal of this study was to examine whether living in a community with more alcohol outlets would facilitate the expression of the genetic propensity to drink in a genetically-informed national survey of United States young adults. The participants were 2434 18-26-year-old twin, full-, and half-sibling pairs from Wave III of the National Longitudinal Study of Adolescent to Adult Health. Participants completed in-home interviews in which alcohol use was assessed. Alcohol outlet densities were extracted from state-level liquor license databases aggregated at the census tract level to derive the density of outlets. There was evidence that the estimates of genetic and environmental influences on alcohol use varied as a function of the density of alcohol outlets in the community. For example, the heritability of the frequency of alcohol use for those residing in a neighborhood with ten or more outlets was 74% (95% confidence limits = 55-94%), compared with 16% (95% confidence limits = 0-34%) for those in a neighborhood with zero outlets. This moderating effect of alcohol outlet density was not explained by the state of residence, population density, or neighborhood sociodemographic characteristics. The results suggest that living in a neighborhood with many alcohol outlets may be especially high-risk for those individuals who are genetically predisposed to frequently drink.

Insights into significant pathways and gene interaction networks underlying breast cancer cell line MCF-7 treated with 17β-estradiol (E2).

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Huan, Jinliang; Wang, Lishan; Xing, Li; Qin, Xianju; Feng, Lingbin; Pan, Xiaofeng; Zhu, Ling

2014-01-01

Estrogens are known to regulate the proliferation of breast cancer cells and to alter their cytoarchitectural and phenotypic properties, but the gene networks and pathways by which estrogenic hormones regulate these events are only partially understood. We used global gene expression profiling by Affymetrix GeneChip microarray analysis, with KEGG pathway enrichment, PPI network construction, module analysis and text mining methods to identify patterns and time courses of genes that are either stimulated or inhibited by estradiol (E2) in estrogen receptor (ER)-positive MCF-7 human breast cancer cells. Of the genes queried on the Affymetrix Human Genome U133 plus 2.0 microarray, we identified 628 (12h), 852 (24h) and 880 (48 h) differentially expressed genes (DEGs) that showed a robust pattern of regulation by E2. From pathway enrichment analysis, we found out the changes of metabolic pathways of E2 treated samples at each time point. At 12h time point, the changes of metabolic pathways were mainly focused on pathways in cancer, focal adhesion, and chemokine signaling pathway. At 24h time point, the changes were mainly enriched in neuroactive ligand-receptor interaction, cytokine-cytokine receptor interaction and calcium signaling pathway. At 48 h time point, the significant pathways were pathways in cancer, regulation of actin cytoskeleton, cell adhesion molecules (CAMs), axon guidance and ErbB signaling pathway. Of interest, our PPI network analysis and module analysis found that E2 treatment induced enhancement of PRSS23 at the three time points and PRSS23 was in the central position of each module. Text mining results showed that the important genes of DEGs have relationship with signal pathways, such as ERbB pathway (AREG), Wnt pathway (NDP), MAPK pathway (NTRK3, TH), IP3 pathway (TRA@) and some transcript factors (TCF4, MAF). Our studies highlight the diverse gene networks and metabolic and cell regulatory pathways through which E2 operates to achieve its

Gene-by-Psychosocial Factor Interactions Influence Diastolic Blood Pressure in European and African Ancestry Populations: Meta-Analysis of Four Cohort Studies

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Jennifer A. Smith

2017-12-01

Full Text Available Inter-individual variability in blood pressure (BP is influenced by both genetic and non-genetic factors including socioeconomic and psychosocial stressors. A deeper understanding of the gene-by-socioeconomic/psychosocial factor interactions on BP may help to identify individuals that are genetically susceptible to high BP in specific social contexts. In this study, we used a genomic region-based method for longitudinal analysis, Longitudinal Gene-Environment-Wide Interaction Studies (LGEWIS, to evaluate the effects of interactions between known socioeconomic/psychosocial and genetic risk factors on systolic and diastolic BP in four large epidemiologic cohorts of European and/or African ancestry. After correction for multiple testing, two interactions were significantly associated with diastolic BP. In European ancestry participants, outward/trait anger score had a significant interaction with the C10orf107 genomic region (p = 0.0019. In African ancestry participants, depressive symptom score had a significant interaction with the HFE genomic region (p = 0.0048. This study provides a foundation for using genomic region-based longitudinal analysis to identify subgroups of the population that may be at greater risk of elevated BP due to the combined influence of genetic and socioeconomic/psychosocial risk factors.

An ancestry-based approach for detecting interactions.

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Park, Danny S; Eskin, Itamar; Kang, Eun Yong; Gamazon, Eric R; Eng, Celeste; Gignoux, Christopher R; Galanter, Joshua M; Burchard, Esteban; Ye, Chun J; Aschard, Hugues; Eskin, Eleazar; Halperin, Eran; Zaitlen, Noah

2018-02-01

Epistasis and gene-environment interactions are known to contribute significantly to variation of complex phenotypes in model organisms. However, their identification in human association studies remains challenging for myriad reasons. In the case of epistatic interactions, the large number of potential interacting sets of genes presents computational, multiple hypothesis correction, and other statistical power issues. In the case of gene-environment interactions, the lack of consistently measured environmental covariates in most disease studies precludes searching for interactions and creates difficulties for replicating studies. In this work, we develop a new statistical approach to address these issues that leverages genetic ancestry, defined as the proportion of ancestry derived from each ancestral population (e.g., the fraction of European/African ancestry in African Americans), in admixed populations. We applied our method to gene expression and methylation data from African American and Latino admixed individuals, respectively, identifying nine interactions that were significant at Pancestry can be a useful proxy for unknown and unmeasured covariates in the search for interaction effects. These results have important implications for our understanding of the genetic architecture of complex traits. © 2017 WILEY PERIODICALS, INC.

Chemical-gene interaction networks and causal reasoning for ...

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Evaluating the potential human health and ecological risks associated with exposures to complex chemical mixtures in the environment is one of the main challenges of chemical safety assessment and environmental protection. There is a need for approaches that can help to integrate chemical monitoring and biological effects data to evaluate risks associated with chemicals present in the environment. Here, we used prior knowledge about chemical-gene interactions to develop a knowledge assembly model for detected chemicals at five locations near the North Branch and Chisago wastewater treatment plants (WWTP) in the St. Croix River Basin, MN and WI. The assembly model was used to generate hypotheses about the biological impacts of the chemicals at each location. The hypotheses were tested using empirical hepatic gene expression data from fathead minnows exposed for 12 d at each location. Empirical gene expression data were also mapped to the assembly models to evaluate the likelihood of a chemical contributing to the observed biological responses using richness and concordance statistics. The prior knowledge approach was able predict the observed biological pathways impacted at one site but not the other. Atrazine was identified as a potential contributor to the observed gene expression responses at a location upstream of the North Branch WTTP. Four chemicals were identified as contributors to the observed biological responses at the effluent and downstream o

Interactions Between Variation in Candidate Genes and Environmental Factors in the Etiology of Schizophrenia and Bipolar Disorder: a Systematic Review.

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Misiak, Błażej; Stramecki, Filip; Gawęda, Łukasz; Prochwicz, Katarzyna; Sąsiadek, Maria M; Moustafa, Ahmed A; Frydecka, Dorota

2017-08-18

Schizophrenia and bipolar disorder (BD) are complex and multidimensional disorders with high heritability rates. The contribution of genetic factors to the etiology of these disorders is increasingly being recognized as the action of multiple risk variants with small effect sizes, which might explain only a minor part of susceptibility. On the other site, numerous environmental factors have been found to play an important role in their causality. Therefore, in recent years, several studies focused on gene × environment interactions that are believed to bridge the gap between genetic underpinnings and environmental insults. In this article, we performed a systematic review of studies investigating gene × environment interactions in BD and schizophrenia spectrum phenotypes. In the majority of studies from this field, interacting effects of variation in genes encoding catechol-O-methyltransferase (COMT), brain-derived neurotrophic factor (BDNF), and FK506-binding protein 5 (FKBP5) have been explored. Almost consistently, these studies revealed that polymorphisms in COMT, BDNF, and FKBP5 genes might interact with early life stress and cannabis abuse or dependence, influencing various outcomes of schizophrenia spectrum disorders and BD. Other interactions still require further replication in larger clinical and non-clinical samples. In addition, future studies should address the direction of causality and potential mechanisms of the relationship between gene × environment interactions and various categories of outcomes in schizophrenia and BD.

Testing differential susceptibility: Plasticity genes, the social environment, and their interplay in adolescent response inhibition.

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Richards, Jennifer S; Arias Vásquez, Alejandro; van Rooij, Daan; van der Meer, Dennis; Franke, Barbara; Hoekstra, Pieter J; Heslenfeld, Dirk J; Oosterlaan, Jaap; Faraone, Stephen V; Hartman, Catharina A; Buitelaar, Jan K

2017-06-01

Impaired inhibitory control is a key feature of attention-deficit/hyperactivity disorder (ADHD). We investigated gene-environment interaction (GxE) as a possible contributing factor to response inhibition variation in context of the differential susceptibility theory. This states individuals carrying plasticity gene variants will be more disadvantaged in negative, but more advantaged in positive environments. Behavioural and neural measures of response inhibition were assessed during a Stop-signal task in participants with (N = 197) and without (N = 295) ADHD, from N = 278 families (age M = 17.18, SD =3.65). We examined GxE between candidate plasticity genes (DAT1, 5-HTT, DRD4) and social environments (maternal expressed emotion, peer affiliation). A DRD4 × Positive peer affiliation interaction was found on the right fusiform gyrus (rFG) activation during successful inhibition. Further, 5-HTT short allele carriers showed increased rFG activation during failed inhibitions. Maternal warmth and positive peer affiliation were positively associated with right inferior frontal cortex activation during successful inhibition. Deviant peer affiliation was positively related to the error rate. While a pattern of differential genetic susceptibility was found, more clarity on the role of the FG during response inhibition is warranted before firm conclusions can be made. Positive and negative social environments were related to inhibitory control. This extends previous research emphasizing adverse environments.

Interactive effects of 5-HTTLPR genotype and rearing environment on affective attitude towards own infant in Japanese mothers.

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Sawano, Erika; Doi, Hirokazu; Nagai, Tomoko; Ikeda, Satoko; Shinohara, Kauyuki

2017-05-15

Maternal positive attitude towards one's own infant is the cornerstone of effective parenting. Previous research has revealed an influence of both genetic and environmental factors on maternal parenting behavior, but little is known of the potential gene-environment interaction in shaping a mother's affective attitude. To address this gap, we investigated the effect of a mother's childhood rearing environment and a serotonin transporter gene polymorphism (5-HTTLPR) on affective attitude towards her infant. Our analyses found an interactive effect between rearing environment and 5-HTTLPR genotype on maternal attitude. Specifically, a poor rearing environment (characterized by low maternal care and high paternal overprotection) decreased positive attitude towards one's own infant in mothers with homozygous short allele genotype. In contrast, this detrimental effect was almost eliminated in long allele carriers. Altogether, our results indicate that the 5-HTTLPR gene moderates the influence of experienced rearing environment on maternal parental behavior in a manner consistent with the notion that the short 5-HTTLPR allele amplifies environmental influence. Copyright © 2016 Elsevier B.V. All rights reserved.

Interactions of early adversity with stress-related gene polymorphisms impact regional brain structure in females.

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Gupta, Arpana; Labus, Jennifer; Kilpatrick, Lisa A; Bonyadi, Mariam; Ashe-McNalley, Cody; Heendeniya, Nuwanthi; Bradesi, Sylvie; Chang, Lin; Mayer, Emeran A

2016-04-01

Early adverse life events (EALs) have been associated with regional thinning of the subgenual cingulate cortex (sgACC), a brain region implicated in the development of disorders of mood and affect, and often comorbid functional pain disorders, such as irritable bowel syndrome (IBS). Regional neuroinflammation related to chronic stress system activation has been suggested as a possible mechanism underlying these neuroplastic changes. However, the interaction of genetic and environmental factors in these changes is poorly understood. The current study aimed to evaluate the interactions of EALs and candidate gene polymorphisms in influencing thickness of the sgACC. 210 female subjects (137 healthy controls; 73 IBS) were genotyped for stress and inflammation-related gene polymorphisms. Genetic variation with EALs, and diagnosis on sgACC thickness was examined, while controlling for race, age, and total brain volume. Compared to HCs, IBS had significantly reduced sgACC thickness (p = 0.03). Regardless of disease group (IBS vs. HC), thinning of the left sgACC was associated with a significant gene-gene environment interaction between the IL-1β genotype, the NR3C1 haplotype, and a history of EALs (p = 0.05). Reduced sgACC thickness in women with the minor IL-1β allele, was associated with EAL total scores regardless of NR3C1 haplotype status (p = 0.02). In subjects homozygous for the major IL-1β allele, reduced sgACC with increasing levels of EALs was seen only with the less common NR3C1 haplotype (p = 0.02). These findings support an interaction between polymorphisms related to stress and inflammation and early adverse life events in modulating a key region of the emotion arousal circuit.

Unstable maternal environment, separation anxiety, and heightened CO2 sensitivity induced by gene-by-environment interplay.

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Francesca R D'Amato

2011-04-01

Full Text Available In man, many different events implying childhood separation from caregivers/unstable parental environment are associated with heightened risk for panic disorder in adulthood. Twin data show that the occurrence of such events in childhood contributes to explaining the covariation between separation anxiety disorder, panic, and the related psychobiological trait of CO(2 hypersensitivity. We hypothesized that early interference with infant-mother interaction could moderate the interspecific trait of response to CO(2 through genetic control of sensitivity to the environment.Having spent the first 24 hours after birth with their biological mother, outbred NMRI mice were cross-fostered to adoptive mothers for the following 4 post-natal days. They were successively compared to normally-reared individuals for: number of ultrasonic vocalizations during isolation, respiratory physiology responses to normal air (20%O(2, CO(2-enriched air (6% CO(2, hypoxic air (10%O(2, and avoidance of CO(2-enriched environments.Cross-fostered pups showed significantly more ultrasonic vocalizations, more pronounced hyperventilatory responses (larger tidal volume and minute volume increments to CO(2-enriched air and heightened aversion towards CO(2-enriched environments, than normally-reared individuals. Enhanced tidal volume increment response to 6%CO(2 was present at 16-20, and 75-90 postnatal days, implying the trait's stability. Quantitative genetic analyses of unrelated individuals, sibs and half-sibs, showed that the genetic variance for tidal volume increment during 6%CO(2 breathing was significantly higher (Bartlett χ = 8.3, p = 0.004 among the cross-fostered than the normally-reared individuals, yielding heritability of 0.37 and 0.21 respectively. These results support a stress-diathesis model whereby the genetic influences underlying the response to 6%CO(2 increase their contribution in the presence of an environmental adversity. Maternal grooming

The antibiotic resistome: gene flow in environments, animals and human beings.

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Hu, Yongfei; Gao, George F; Zhu, Baoli

2017-06-01

The antibiotic resistance is natural in bacteria and predates the human use of antibiotics. Numerous antibiotic resistance genes (ARGs) have been discovered to confer resistance to a wide range of antibiotics. The ARGs in natural environments are highly integrated and tightly regulated in specific bacterial metabolic networks. However, the antibiotic selection pressure conferred by the use of antibiotics in both human medicine and agriculture practice leads to a significant increase of antibiotic resistance and a steady accumulation of ARGs in bacteria. In this review, we summarized, with an emphasis on an ecological point of view, the important research progress regarding the collective ARGs (antibiotic resistome) in bacterial communities of natural environments, human and animals, i.e., in the one health settings.We propose that the resistance gene flow in nature is "from the natural environments" and "to the natural environments"; human and animals, as intermediate recipients and disseminators, contribute greatly to such a resistance gene "circulation."

Predictability of Genetic Interactions from Functional Gene Modules

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Jonathan H. Young

2017-02-01

Full Text Available Characterizing genetic interactions is crucial to understanding cellular and organismal response to gene-level perturbations. Such knowledge can inform the selection of candidate disease therapy targets, yet experimentally determining whether genes interact is technically nontrivial and time-consuming. High-fidelity prediction of different classes of genetic interactions in multiple organisms would substantially alleviate this experimental burden. Under the hypothesis that functionally related genes tend to share common genetic interaction partners, we evaluate a computational approach to predict genetic interactions in Homo sapiens, Drosophila melanogaster, and Saccharomyces cerevisiae. By leveraging knowledge of functional relationships between genes, we cross-validate predictions on known genetic interactions and observe high predictive power of multiple classes of genetic interactions in all three organisms. Additionally, our method suggests high-confidence candidate interaction pairs that can be directly experimentally tested. A web application is provided for users to query genes for predicted novel genetic interaction partners. Finally, by subsampling the known yeast genetic interaction network, we found that novel genetic interactions are predictable even when knowledge of currently known interactions is minimal.

Gene-Environment Interplay, Family Relationships, and Child Adjustment

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Horwitz, Briana N.; Neiderhiser, Jenae M.

2011-01-01

This paper reviews behavioral genetic research from the past decade that has moved beyond simply studying the independent influences of genes and environments. The studies considered in this review have instead focused on understanding gene-environment interplay, including genotype-environment correlation (rGE) and genotype x environment…

Methodological issues in detecting gene-gene interactions in breast cancer susceptibility: a population-based study in Ontario

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Onay Venus

2007-08-01

Full Text Available Abstract Background There is growing evidence that gene-gene interactions are ubiquitous in determining the susceptibility to common human diseases. The investigation of such gene-gene interactions presents new statistical challenges for studies with relatively small sample sizes as the number of potential interactions in the genome can be large. Breast cancer provides a useful paradigm to study genetically complex diseases because commonly occurring single nucleotide polymorphisms (SNPs may additively or synergistically disturb the system-wide communication of the cellular processes leading to cancer development. Methods In this study, we systematically studied SNP-SNP interactions among 19 SNPs from 18 key genes involved in major cancer pathways in a sample of 398 breast cancer cases and 372 controls from Ontario. We discuss the methodological issues associated with the detection of SNP-SNP interactions in this dataset by applying and comparing three commonly used methods: the logistic regression model, classification and regression trees (CART, and the multifactor dimensionality reduction (MDR method. Results Our analyses show evidence for several simple (two-way and complex (multi-way SNP-SNP interactions associated with breast cancer. For example, all three methods identified XPD-[Lys751Gln]*IL10-[G(-1082A] as the most significant two-way interaction. CART and MDR identified the same critical SNPs participating in complex interactions. Our results suggest that the use of multiple statistical approaches (or an integrated approach rather than a single methodology could be the best strategy to elucidate complex gene interactions that have generally very different patterns. Conclusion The strategy used here has the potential to identify complex biological relationships among breast cancer genes and processes. This will lead to the discovery of novel biological information, which will improve breast cancer risk management.

Gene-environment interaction from international cohorts: impact on development and evolution of occupational and environmental lung and airway disease.

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Gaffney, Adam; Christiani, David C

2015-06-01

Environmental and occupational pulmonary diseases impose a substantial burden of morbidity and mortality on the global population. However, it has been long observed that only some of those who are exposed to pulmonary toxicants go on to develop disease; increasingly, it is being recognized that genetic differences may underlie some of this person-to-person variability. Studies performed throughout the globe are demonstrating important gene-environment interactions for diseases as diverse as chronic beryllium disease, coal workers' pneumoconiosis, silicosis, asbestosis, byssinosis, occupational asthma, and pollution-associated asthma. These findings have, in many instances, elucidated the pathogenesis of these highly complex diseases. At the same time, however, translation of this research into clinical practice has, for good reasons, proceeded slowly. No genetic test has yet emerged with sufficiently robust operating characteristics to be clearly useful or practicable in an occupational or environmental setting. In addition, occupational genetic testing raises serious ethical and policy concerns. Therefore, the primary objective must remain ensuring that the workplace and the environment are safe for all. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

The role of gene-gene interaction in the prediction of criminal behavior.

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Boutwell, Brian B; Menard, Scott; Barnes, J C; Beaver, Kevin M; Armstrong, Todd A; Boisvert, Danielle

2014-04-01

A host of research has examined the possibility that environmental risk factors might condition the influence of genes on various outcomes. Less research, however, has been aimed at exploring the possibility that genetic factors might interact to impact the emergence of human traits. Even fewer studies exist examining the interaction of genes in the prediction of behavioral outcomes. The current study expands this body of research by testing the interaction between genes involved in neural transmission. Our findings suggest that certain dopamine genes interact to increase the odds of criminogenic outcomes in a national sample of Americans. Copyright © 2014 Elsevier Inc. All rights reserved.

Determining Semantically Related Significant Genes.

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Taha, Kamal

2014-01-01

GO relation embodies some aspects of existence dependency. If GO term xis existence-dependent on GO term y, the presence of y implies the presence of x. Therefore, the genes annotated with the function of the GO term y are usually functionally and semantically related to the genes annotated with the function of the GO term x. A large number of gene set enrichment analysis methods have been developed in recent years for analyzing gene sets enrichment. However, most of these methods overlook the structural dependencies between GO terms in GO graph by not considering the concept of existence dependency. We propose in this paper a biological search engine called RSGSearch that identifies enriched sets of genes annotated with different functions using the concept of existence dependency. We observe that GO term xcannot be existence-dependent on GO term y, if x- and y- have the same specificity (biological characteristics). After encoding into a numeric format the contributions of GO terms annotating target genes to the semantics of their lowest common ancestors (LCAs), RSGSearch uses microarray experiment to identify the most significant LCA that annotates the result genes. We evaluated RSGSearch experimentally and compared it with five gene set enrichment systems. Results showed marked improvement.

[Gene-gene interaction on central obesity in school-aged children in China].

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Fu, L W; Zhang, M X; Wu, L J; Gao, L W; Mi, J

2017-07-10

Objective: To investigate possible effect of 6 obesity-associated SNPs in contribution to central obesity and examine whether there is an interaction in the 6 SNPs in the cause of central obesity in school-aged children in China. Methods: A total of 3 502 school-aged children who were included in Beijing Child and Adolescent Metabolic Syndrome (BCAMS) Study were selected, and based on the age and sex specific waist circumference (WC) standards in the BCAMS study, 1 196 central obese cases and 2 306 controls were identified. Genomic DNA was extracted from peripheral blood white cells using the salt fractionation method. A total of 6 single nucleotide polymorphisms ( FTO rs9939609, MC4R rs17782313, BDNF rs6265, PCSK1 rs6235, SH2B1 rs4788102, and CSK rs1378942) were genotyped by TaqMan allelic discrimination assays with the GeneAmp 7900 sequence detection system (Applied Biosystems, Foster City, CA, USA). Logistic regression model was used to investigate the association between 6 SNPs and central obesity. Gene-gene interactions among 6 polymorphic loci were analyzed by using the Generalized Multifactor Dimensionality Reduction (GMDR) method, and then logistic regression model was constructed to confirm the best combination of loci identified in the GMDR. Results: After adjusting gender, age, Tanner stage, physical activity and family history of obesity, the FTO rs9939609-A, MC4R rs17782313-C and BDNF rs6265-G alleles were associated with central obesity under additive genetic model ( OR =1.24, 95 %CI : 1.06-1.45, P =0.008; OR =1.26, 95 %CI : 1.11-1.43, P =2.98×10(-4); OR =1.18, 95 % CI : 1.06-1.32, P =0.003). GMDR analysis showed a significant gene-gene interaction between MC4R rs17782313 and BDNF rs6265 ( P =0.001). The best two-locus combination showed the cross-validation consistency of 10/10 and testing accuracy of 0.539. This interaction showed the maximum consistency and minimum prediction error among all gene-gene interaction models evaluated. Moreover, the

Significance of Cuscutain, a cysteine protease from Cuscuta reflexa, in host-parasite interactions.

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Bleischwitz, Marc; Albert, Markus; Fuchsbauer, Hans-Lothar; Kaldenhoff, Ralf

2010-10-22

Plant infestation with parasitic weeds like Cuscuta reflexa induces morphological as well as biochemical changes in the host and the parasite. These modifications could be caused by a change in protein or gene activity. Using a comparative macroarray approach Cuscuta genes specifically upregulated at the host attachment site were identified. One of the infestation specific Cuscuta genes encodes a cysteine protease. The protein and its intrinsic inhibitory peptide were heterologously expressed, purified and biochemically characterized. The haustoria specific enzyme was named cuscutain in accordance with similar proteins from other plants, e.g. papaya. The role of cuscutain and its inhibitor during the host parasite interaction was studied by external application of an inhibitor suspension, which induced a significant reduction of successful infection events. The study provides new information about molecular events during the parasitic plant--host interaction. Inhibition of cuscutain cysteine proteinase could provide means for antagonizing parasitic plants.

Case-only study of interactions between metabolic enzymes and smoking in colorectal cancer

International Nuclear Information System (INIS)

Fan, Chunhong; Jin, Mingjuan; Chen, Kun; Zhang, Yongjing; Zhang, Shuangshuang; Liu, Bing

2007-01-01

Gene-gene and gene-environment interactions involved in the metabolism of carcinogens may increase the risk of cancer. Our objective was to measure the interactions between common polymorphisms of P450 (CYP1A2, CYP1B1, CYP2E1), GSTM1 and T1, SULT1A1 and cigarette smoking in colorectal cancer (CRC). A case-only design was conducted in a Chinese population including 207 patients with sporadic CRC. Unconditional logistic regression analysis was performed adjusting for age, gender, alcohol consumption, and cigarette smoking. The interaction odds ratio (COR) for the gene-gene interaction between CYP1B1 1294G and SULT1A1 638A allele was 2.68 (95% CI: 1.16–6.26). The results of the gene-environment analyses revealed that an interaction existed between cigarette smoking and the CYP1B1 1294G allele for CRC (COR = 2.62, 95%CI: 1.01–6.72), the COR for the interaction of CYP1B1 1294G and smoking history > 35 pack-years was 3.47 (95%CI: 1.12–10.80). No other significant gene-gene and gene-environment interactions were observed. Our results showed that the interaction between polymorphisms in CYP1B1 1294G and SULT1A1*2 may play a significant role on CRC in the Chinese population. Also, it is suggested that the association between cigarette smoking and CRC could be differentiated by the CYP1B1 1294G allele

Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits

DEFF Research Database (Denmark)

Dashti, Hassan S; Follis, Jack L; Smith, Caren E

2015-01-01

OBJECTIVE: Common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs13871...

Gene-environment interactions of circadian-related genes for cardiometabolic traits

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Objective: Common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs1387153,...

GxGrare: gene-gene interaction analysis method for rare variants from high-throughput sequencing data.

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Kwon, Minseok; Leem, Sangseob; Yoon, Joon; Park, Taesung

2018-03-19

With the rapid advancement of array-based genotyping techniques, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with common complex diseases. However, it has been shown that only a small proportion of the genetic etiology of complex diseases could be explained by the genetic factors identified from GWAS. This missing heritability could possibly be explained by gene-gene interaction (epistasis) and rare variants. There has been an exponential growth of gene-gene interaction analysis for common variants in terms of methodological developments and practical applications. Also, the recent advancement of high-throughput sequencing technologies makes it possible to conduct rare variant analysis. However, little progress has been made in gene-gene interaction analysis for rare variants. Here, we propose GxGrare which is a new gene-gene interaction method for the rare variants in the framework of the multifactor dimensionality reduction (MDR) analysis. The proposed method consists of three steps; 1) collapsing the rare variants, 2) MDR analysis for the collapsed rare variants, and 3) detect top candidate interaction pairs. GxGrare can be used for the detection of not only gene-gene interactions, but also interactions within a single gene. The proposed method is illustrated with 1080 whole exome sequencing data of the Korean population in order to identify causal gene-gene interaction for rare variants for type 2 diabetes. The proposed GxGrare performs well for gene-gene interaction detection with collapsing of rare variants. GxGrare is available at http://bibs.snu.ac.kr/software/gxgrare which contains simulation data and documentation. Supported operating systems include Linux and OS X.

Analysis of Behavioral and Emotional Problems in Children Highlights the Role of Genotype × Environment Interaction.

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Molenaar, Dylan; Middeldorp, Christel; van Beijsterveldt, Toos; Boomsma, Dorret I

2015-01-01

This study tested for Genotype × Environment (G × E) interaction on behavioral and emotional problems in children using new methods that do not require identification of candidate genes or environments, can distinguish between interaction with shared and unique environment, and are insensitive to scale effects. Parental ratings of problem behavior from 14,755 twin pairs (5.3 years, SD = 0.22) indicated G × E interaction on emotional liability, social isolation, aggression, attention problems, dependency, anxiety, and physical coordination. Environmental influences increased in children who were genetically more predisposed to problem behavior, with ~20% of the variance due to G × E interaction (8% for anxiety to 37% for attention problems). Ignoring G × E interaction does not greatly bias heritability estimates, but it does offer a comprehensive model of the etiology for childhood problems. © 2015 The Authors. Child Development © 2015 Society for Research in Child Development, Inc.

Contemporary state of spacecraft/environment interaction research

CERN Document Server

Novikov, L S

1999-01-01

Various space environment effects on spacecraft materials and equipment, and the reverse effects of spacecrafts and rockets on space environment are considered. The necessity of permanent updating and perfection of our knowledge on spacecraft/environment interaction processes is noted. Requirements imposed on models of space environment in theoretical and experimental researches of various aspects of the spacecraft/environment interaction problem are formulated. In this field, main problems which need to be solved today and in the nearest future are specified. The conclusion is made that the joint analysis of both aspects of spacecraft/environment interaction problem promotes the most effective solution of the problem.

An environmental analysis of genes associated with schizophrenia: hypoxia and vascular factors as interacting elements in the neurodevelopmental model.

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Schmidt-Kastner, R; van Os, J; Esquivel, G; Steinbusch, H W M; Rutten, B P F

2012-12-01

Investigating and understanding gene-environment interaction (G × E) in a neurodevelopmentally and biologically plausible manner is a major challenge for schizophrenia research. Hypoxia during neurodevelopment is one of several environmental factors related to the risk of schizophrenia, and links between schizophrenia candidate genes and hypoxia regulation or vascular expression have been proposed. Given the availability of a wealth of complex genetic information on schizophrenia in the literature without knowledge on the connections to environmental factors, we now systematically collected genes from candidate studies (using SzGene), genome-wide association studies (GWAS) and copy number variation (CNV) analyses, and then applied four criteria to test for a (theoretical) link to ischemia-hypoxia and/or vascular factors. In all, 55% of the schizophrenia candidate genes (n=42 genes) met the criteria for a link to ischemia-hypoxia and/or vascular factors. Genes associated with schizophrenia showed a significant, threefold enrichment among genes that were derived from microarray studies of the ischemia-hypoxia response (IHR) in the brain. Thus, the finding of a considerable match between genes associated with the risk of schizophrenia and IHR and/or vascular factors is reproducible. An additional survey of genes identified by GWAS and CNV analyses suggested novel genes that match the criteria. Findings for interactions between specific variants of genes proposed to be IHR and/or vascular factors with obstetric complications in patients with schizophrenia have been reported in the literature. Therefore, the extended gene set defined here may form a reasonable and evidence-based starting point for hypothesis-based testing of G × E interactions in clinical genetic and translational neuroscience studies.

Phenotypic effects of repeated psychosocial stress during adolescence in mice mutant for the schizophrenia risk gene neuregulin-1: a putative model of gene × environment interaction.

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Desbonnet, Lieve; O'Tuathaigh, Colm; Clarke, Gerard; O'Leary, Claire; Petit, Emilie; Clarke, Niamh; Tighe, Orna; Lai, Donna; Harvey, Richard; Cryan, John F; Dinan, Timothy G; Waddington, John L

2012-05-01

There is a paucity of animal models by which the contributions of environmental and genetic factors to the pathobiology of psychosis can be investigated. This study examined the individual and combined effects of chronic social stress during adolescence and deletion of the schizophrenia risk gene neuregulin-1 (NRG1) on adult mouse phenotype. Mice were exposed to repeated social defeat stress during adolescence and assessed for exploratory behaviour, working memory, sucrose preference, social behaviour and prepulse inhibition in adulthood. Thereafter, in vitro cytokine responses to mitogen stimulation and corticosterone inhibition were assayed in spleen cells, with measurement of cytokine and brain-derived neurotrophic factor (BDNF) mRNA in frontal cortex, hippocampus and striatum. NRG1 mutants exhibited hyperactivity, decreased anxiety, impaired sensorimotor gating and reduced preference for social novelty. The effects of stress on exploratory/anxiety-related parameters, spatial working memory, sucrose preference and basal cytokine levels were modified by NRG1 deletion. Stress also exerted varied effect on spleen cytokine response to concanavalin A and brain cytokine and BDNF mRNA expression in NRG1 mutants. The experience of psychosocial stress during adolescence may trigger further pathobiological features that contribute to the development of schizophrenia, particularly in those with underlying NRG1 gene abnormalities. This model elaborates the importance of gene × environment interactions in the etiology of schizophrenia. Copyright © 2012 Elsevier Inc. All rights reserved.

Effects of prenatal hypoxia on schizophrenia-related phenotypes in heterozygous reeler mice: a gene × environment interaction study.

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Howell, Kristy R; Pillai, Anilkumar

2014-08-01

Both genetic and environmental factors play important roles in the pathophysiology of schizophrenia. Although prenatal hypoxia is a potential environmental factor implicated in schizophrenia, very little is known about the consequences of combining models of genetic risk factor with prenatal hypoxia. Heterozygous reeler (haploinsufficient for reelin; HRM) and wild-type (WT) mice were exposed to prenatal hypoxia (9% oxygen for two hour) or normoxia at embryonic day 17 (E17). Behavioral (Prepulse inhibition, Y-maze and Open field) and functional (regional volume in frontal cortex and hippocampus as well as hippocampal blood flow) tests were performed at 3 months of age. The levels of hypoxia and stress-related molecules such as hypoxia-inducible factor-1 α (HIF-1α), vascular endothelial factor (VEGF), VEGF receptor-2 (VEGFR2/Flk1) and glucocorticoid receptor (GR) were examined in frontal cortex and hippocampus at E18, 1 month and 3 months of age. In addition, serum VEGF and corticosterone levels were also examined. Prenatal hypoxia induced anxiety-like behavior in both HRM and WT mice. A significant reduction in hippocampal blood flow, but no change in brain regional volume was observed following prenatal hypoxia. Significant age and region-dependent changes in HIF-1α, VEGF, Flk1 and GR were found following prenatal hypoxia. Serum VEGF and corticosterone levels were found decreased following prenatal hypoxia. None of the above prenatal hypoxia-induced changes were either diminished or exacerbated due to reelin deficiency. These results argue against any gene-environment interaction between hypoxia and reelin deficiency. Copyright © 2014 Elsevier B.V. and ECNP. All rights reserved.

REVIEW: Genome-wide findings in schizophrenia and the role of gene-environment interplay.

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Van Winkel, Ruud; Esquivel, Gabriel; Kenis, Gunter; Wichers, Marieke; Collip, Dina; Peerbooms, Odette; Rutten, Bart; Myin-Germeys, Inez; Van Os, Jim

2010-10-01

The recent advent of genome-wide mass-marker technology has resulted in renewed optimism to unravel the genetic architecture of psychotic disorders. Genome-wide association studies have identified a number of common polymorphisms robustly associated with schizophrenia, in ZNF804A, transcription factor 4, major histocompatibility complex, and neurogranin. In addition, copy number variants (CNVs) in 1q21.1, 2p16.3, 15q11.2, 15q13.3, 16p11.2, and 22q11.2 were convincingly implicated in schizophrenia risk. Furthermore, these studies have suggested considerable genetic overlap with bipolar disorder (particularly for common polymorphisms) and neurodevelopmental disorders such as autism (particularly for CNVs). The influence of these risk variants on relevant intermediate phenotypes needs further study. In addition, there is a need for etiological models of psychosis integrating genetic risk with environmental factors associated with the disorder, focusing specifically on environmental impact on gene expression (epigenetics) and convergence of genes and environment on common biological pathways bringing about larger effects than those of genes or environment in isolation (gene-environment interaction). Collaborative efforts that bring together expertise in statistics, genetics, epidemiology, experimental psychiatry, brain imaging, and clinical psychiatry will be required to succeed in this challenging task. © 2010 Blackwell Publishing Ltd.

Significance of Cuscutain, a cysteine protease from Cuscuta reflexa, in host-parasite interactions

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Fuchsbauer Hans-Lothar

2010-10-01

Full Text Available Abstract Background Plant infestation with parasitic weeds like Cuscuta reflexa induces morphological as well as biochemical changes in the host and the parasite. These modifications could be caused by a change in protein or gene activity. Using a comparative macroarray approach Cuscuta genes specifically upregulated at the host attachment site were identified. Results One of the infestation specific Cuscuta genes encodes a cysteine protease. The protein and its intrinsic inhibitory peptide were heterologously expressed, purified and biochemically characterized. The haustoria specific enzyme was named cuscutain in accordance with similar proteins from other plants, e.g. papaya. The role of cuscutain and its inhibitor during the host parasite interaction was studied by external application of an inhibitor suspension, which induced a significant reduction of successful infection events. Conclusions The study provides new information about molecular events during the parasitic plant - host interaction. Inhibition of cuscutain cysteine proteinase could provide means for antagonizing parasitic plants.

Crowdsourcing the nodulation gene network discovery environment.

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Li, Yupeng; Jackson, Scott A

2016-05-26

The Legumes (Fabaceae) are an economically and ecologically important group of plant species with the conspicuous capacity for symbiotic nitrogen fixation in root nodules, specialized plant organs containing symbiotic microbes. With the aim of understanding the underlying molecular mechanisms leading to nodulation, many efforts are underway to identify nodulation-related genes and determine how these genes interact with each other. In order to accurately and efficiently reconstruct nodulation gene network, a crowdsourcing platform, CrowdNodNet, was created. The platform implements the jQuery and vis.js JavaScript libraries, so that users are able to interactively visualize and edit the gene network, and easily access the information about the network, e.g. gene lists, gene interactions and gene functional annotations. In addition, all the gene information is written on MediaWiki pages, enabling users to edit and contribute to the network curation. Utilizing the continuously updated, collaboratively written, and community-reviewed Wikipedia model, the platform could, in a short time, become a comprehensive knowledge base of nodulation-related pathways. The platform could also be used for other biological processes, and thus has great potential for integrating and advancing our understanding of the functional genomics and systems biology of any process for any species. The platform is available at http://crowd.bioops.info/ , and the source code can be openly accessed at https://github.com/bioops/crowdnodnet under MIT License.

Interaction between ADH1B*3 and alcohol-facilitating social environments in alcohol behaviors among college students of african descent.

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Desalu, Jessica M; Zaso, Michelle J; Kim, Jueun; Belote, John M; Park, Aesoon

2017-06-01

Although alcohol-facilitating social environmental factors, such as alcohol offers and high perceived peer drinking norms, have been extensively studied as determinants of college drinking, their role among college students of African descent remains understudied. Furthermore, gene-environment interaction research suggests that the effects of alcohol-facilitating environments may differ as a function of genetic factors. Specifically, the alcohol dehydrogenase gene's ADH1B*3 allele, found almost exclusively in persons of African descent, may modulate the association of risky social environments with alcohol behaviors. The current study examined whether the ADH1B*3 allele attenuated the relationship between alcohol-facilitating environments (ie, alcohol offers and perceived peer drinking norms) and alcohol behaviors. Participants were 241 undergraduate students who self-identified as being of African descent (mean age = 20 years [SD = 4.11]; 66% female). Significant interaction effects of ADH1B*3 with alcohol offers were found on alcohol use frequency (incidence rate ratio [IRR] = 1.14) and on drinking consequences (IRR = 1.21). ADH1B*3 also interacted with perceived peer norms on drinking consequences (IRR = 1.41). Carriers of the ADH1B*3 allele drank less frequently and experienced fewer negative consequences than non-carriers when exposed to lower levels of alcohol offers and perceived peer drinking. In contrast, in high alcohol-facilitating environments, no protective genetic effect was observed. This study demonstrates that ADH1B*3 may protect college students of African descent against alcohol outcomes, although only in low alcohol-facilitating environments. Findings add to the growing body of knowledge regarding genetic and social determinants of alcohol behaviors among college students of African descent. (Am J Addict 2017;26:349-356). © 2017 American Academy of Addiction Psychiatry.

Detection of gene-environment interactions in the presence of linkage disequilibrium and noise by using genetic risk scores with internal weights from elastic net regression.

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Hüls, Anke; Ickstadt, Katja; Schikowski, Tamara; Krämer, Ursula

2017-06-12

For the analysis of gene-environment (GxE) interactions commonly single nucleotide polymorphisms (SNPs) are used to characterize genetic susceptibility, an approach that mostly lacks power and has poor reproducibility. One promising approach to overcome this problem might be the use of weighted genetic risk scores (GRS), which are defined as weighted sums of risk alleles of gene variants. The gold-standard is to use external weights from published meta-analyses. In this study, we used internal weights from the marginal genetic effects of the SNPs estimated by a multivariate elastic net regression and thereby provided a method that can be used if there are no external weights available. We conducted a simulation study for the detection of GxE interactions and compared power and type I error of single SNPs analyses with Bonferroni correction and corresponding analysis with unweighted and our weighted GRS approach in scenarios with six risk SNPs and an increasing number of highly correlated (up to 210) and noise SNPs (up to 840). Applying weighted GRS increased the power enormously in comparison to the common single SNPs approach (e.g. 94.2% vs. 35.4%, respectively, to detect a weak interaction with an OR ≈ 1.04 for six uncorrelated risk SNPs and n = 700 with a well-controlled type I error). Furthermore, weighted GRS outperformed the unweighted GRS, in particular in the presence of SNPs without any effect on the phenotype (e.g. 90.1% vs. 43.9%, respectively, when 20 noise SNPs were added to the six risk SNPs). This outperforming of the weighted GRS was confirmed in a real data application on lung inflammation in the SALIA cohort (n = 402). However, in scenarios with a high number of noise SNPs (>200 vs. 6 risk SNPs), larger sample sizes are needed to avoid an increased type I error, whereas a high number of correlated SNPs can be handled even in small samples (e.g. n = 400). In conclusion, weighted GRS with weights from the marginal genetic effects of the

Chronic and Acute Stress, Gender, and Serotonin Transporter Gene-Environment Interactions Predicting Depression Symptoms in Youth

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Hammen, Constance; Brennan, Patricia A.; Keenan-Miller, Danielle; Hazel, Nicholas A.; Najman, Jake M.

2010-01-01

Background: Many recent studies of serotonin transporter gene by environment effects predicting depression have used stress assessments with undefined or poor psychometric methods, possibly contributing to wide variation in findings. The present study attempted to distinguish between effects of acute and chronic stress to predict depressive…

Gene-by-environment effect of house dust mite on purinergic receptor P2Y12 (P2RY12) and lung function in children with asthma.

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Bunyavanich, S; Boyce, J A; Raby, B A; Weiss, S T

2012-02-01

Distinct receptors likely exist for leukotriene (LT)E(4), a potent mediator of airway inflammation. Purinergic receptor P2Y12 is needed for LTE(4)-induced airways inflammation, and P2Y12 antagonism attenuates house dust mite-induced pulmonary eosinophilia in mice. Although experimental data support a role for P2Y12 in airway inflammation, its role in human asthma has never been studied. To test for association between variants in the P2Y12 gene (P2RY12) and lung function in human subjects with asthma, and to examine for gene-by-environment interaction with house dust mite exposure. Nineteen single nucleotide polymorphisms (SNPs) in P2RY12 were genotyped in 422 children with asthma and their parents (n = 1266). Using family based methods, we tested for associations between these SNPs and five lung function measures. We performed haplotype association analyses and tested for gene-by-environment interactions using house dust mite exposure. We used the false discovery rate to account for multiple comparisons. Five SNPs in P2RY12 were associated with multiple lung function measures (P-values 0.006–0.025). Haplotypes in P2RY12 were also associated with lung function (P-values 0.0055–0.046). House dust mite exposure modulated associations between P2RY12 and lung function, with minor allele homozygotes exposed to house dust mite demonstrating worse lung function than those unexposed (significant interaction P-values 0.0028–0.040). The P2RY12 variants were associated with lung function in a large family-based asthma cohort. House dust mite exposure caused significant gene-by-environment effects. Our findings add the first human evidence to experimental data supporting a role for P2Y12 in lung function. P2Y12 could represent a novel target for asthma treatment.

A multilevel prediction of physiological response to challenge: Interactions among child maltreatment, neighborhood crime, endothelial nitric oxide synthase gene (eNOS), and GABA(A) receptor subunit alpha-6 gene (GABRA6).

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Lynch, Michael; Manly, Jody Todd; Cicchetti, Dante

2015-11-01

Physiological response to stress has been linked to a variety of healthy and pathological conditions. The current study conducted a multilevel examination of interactions among environmental toxins (i.e., neighborhood crime and child maltreatment) and specific genetic polymorphisms of the endothelial nitric oxide synthase gene (eNOS) and GABA(A) receptor subunit alpha-6 gene (GABRA6). One hundred eighty-six children were recruited at age 4. The presence or absence of child maltreatment as well as the amount of crime that occurred in their neighborhood during the previous year were determined at that time. At age 9, the children were brought to the lab, where their physiological response to a cognitive challenge (i.e., change in the amplitude of the respiratory sinus arrhythmia) was assessed and DNA samples were collected for subsequent genotyping. The results confirmed that complex Gene × Gene, Environment × Environment, and Gene × Environment interactions were associated with different patterns of respiratory sinus arrhythmia reactivity. The implications for future research and evidence-based intervention are discussed.

Developmentally Sensitive Interaction Effects of Genes and the Social Environment on Total and Subcortical Brain Volumes.

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Jennifer S Richards

Full Text Available Smaller total brain and subcortical volumes have been linked to psychopathology including attention-deficit/hyperactivity disorder (ADHD. Identifying mechanisms underlying these alterations, therefore, is of great importance. We investigated the role of gene-environment interactions (GxE in interindividual variability of total gray matter (GM, caudate, and putamen volumes. Brain volumes were derived from structural magnetic resonance imaging scans in participants with (N = 312 and without ADHD (N = 437 from N = 402 families (age M = 17.00, SD = 3.60. GxE effects between DAT1, 5-HTT, and DRD4 and social environments (maternal expressed warmth and criticism; positive and deviant peer affiliation as well as the possible moderating effect of age were examined using linear mixed modeling. We also tested whether findings depended on ADHD severity. Deviant peer affiliation was associated with lower caudate volume. Participants with low deviant peer affiliations had larger total GM volumes with increasing age. Likewise, developmentally sensitive GxE effects were found on total GM and putamen volume. For total GM, differential age effects were found for DAT1 9-repeat and HTTLPR L/L genotypes, depending on the amount of positive peer affiliation. For putamen volume, DRD4 7-repeat carriers and DAT1 10/10 homozygotes showed opposite age relations depending on positive peer affiliation and maternal criticism, respectively. All results were independent of ADHD severity. The presence of differential age-dependent GxE effects might explain the diverse and sometimes opposing results of environmental and genetic effects on brain volumes observed so far.

Developmentally Sensitive Interaction Effects of Genes and the Social Environment on Total and Subcortical Brain Volumes.

Science.gov (United States)

Richards, Jennifer S; Arias Vásquez, Alejandro; Franke, Barbara; Hoekstra, Pieter J; Heslenfeld, Dirk J; Oosterlaan, Jaap; Faraone, Stephen V; Buitelaar, Jan K; Hartman, Catharina A

2016-01-01

Smaller total brain and subcortical volumes have been linked to psychopathology including attention-deficit/hyperactivity disorder (ADHD). Identifying mechanisms underlying these alterations, therefore, is of great importance. We investigated the role of gene-environment interactions (GxE) in interindividual variability of total gray matter (GM), caudate, and putamen volumes. Brain volumes were derived from structural magnetic resonance imaging scans in participants with (N = 312) and without ADHD (N = 437) from N = 402 families (age M = 17.00, SD = 3.60). GxE effects between DAT1, 5-HTT, and DRD4 and social environments (maternal expressed warmth and criticism; positive and deviant peer affiliation) as well as the possible moderating effect of age were examined using linear mixed modeling. We also tested whether findings depended on ADHD severity. Deviant peer affiliation was associated with lower caudate volume. Participants with low deviant peer affiliations had larger total GM volumes with increasing age. Likewise, developmentally sensitive GxE effects were found on total GM and putamen volume. For total GM, differential age effects were found for DAT1 9-repeat and HTTLPR L/L genotypes, depending on the amount of positive peer affiliation. For putamen volume, DRD4 7-repeat carriers and DAT1 10/10 homozygotes showed opposite age relations depending on positive peer affiliation and maternal criticism, respectively. All results were independent of ADHD severity. The presence of differential age-dependent GxE effects might explain the diverse and sometimes opposing results of environmental and genetic effects on brain volumes observed so far.

Developmental and genetic modulation of arsenic biotransformation: A gene by environment interaction?

International Nuclear Information System (INIS)

Meza, Mercedes; Gandolfi, A. Jay; Klimecki, Walter T.

2007-01-01

The complexity of arsenic toxicology has confounded the identification of specific pathways of disease causation. One focal point of arsenic research is aimed at fully characterizing arsenic biotransformation in humans, a process that appears to be quite variable, producing a mixture of several arsenic species with greatly differing toxic potencies. In an effort to characterize genetic determinants of variability in arsenic biotransformation, a genetic association study of 135 subjects in western Sonora, Mexico was performed by testing 23 polymorphic sites in three arsenic biotransformation candidate genes. One gene, arsenic 3 methyltransferase (AS3MT), was strongly associated with the ratio of urinary dimethylarsinic acid to monomethylarsonic acid (D/M) in children (7-11 years) but not in adults (18-79 years). Subsequent analyses revealed that the high D/M values associated with variant AS3MT alleles were primarily due to lower levels of monomethylarsonic acid as percent of total urinary arsenic (%MMA5). In light of several reports of arsenic-induced disease being associated with relatively high %MMA5 levels, these findings raise the possibility that variant AS3MT individuals may suffer less risk from arsenic exposure than non-variant individuals. These analyses also provide evidence that, in this population, regardless of AS3MT variant status, children tend to have lower %MMA5 values than adults, suggesting that the global developmental regulation of arsenic biotransformation may interact with genetic variants in metabolic genes to result in novel genetic effects such as those in this report

Gene/Environment Interaction in Atherosclerosis: An Example of Clinical Medicine as Seen from the Evolutionary Perspective

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Gerhard Mertens

2010-01-01

The chronic multifactorial disease of atherosclerosis clearly illustrates the Darwinian paradigm. Recent research, combining the effects of genes and environment, has provided surprising clues to the pathogenesis of this major public health problem. This example makes a strong case for recognizing evolution biology as a basic science for medicine.

Environmental factors as modulators of neurodegeneration: insights from gene-environment interactions in Huntington's disease.

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Mo, Christina; Hannan, Anthony J; Renoir, Thibault

2015-05-01

Unlike many other neurodegenerative diseases with established gene-environment interactions, Huntington's disease (HD) is viewed as a disorder governed by genetics. The cause of the disease is a highly penetrant tandem repeat expansion encoding an extended polyglutamine tract in the huntingtin protein. In the year 2000, a pioneering study showed that the disease could be delayed in transgenic mice by enriched housing conditions. This review describes subsequent human and preclinical studies identifying environmental modulation of motor, cognitive, affective and other symptoms found in HD. Alongside the behavioral observations we also discuss potential mechanisms and the relevance to other neurodegenerative disorders, including Alzheimer's and Parkinson's disease. In mouse models of HD, increased sensorimotor and cognitive stimulation can delay or ameliorate various endophenotypes. Potential mechanisms include increased trophic support, synaptic plasticity, adult neurogenesis, and other forms of experience-dependent cellular plasticity. Subsequent clinical investigations support a role for lifetime activity levels in modulating the onset and progression of HD. Stress can accelerate memory and olfactory deficits and exacerbate cellular dysfunctions in HD mice. In the absence of effective treatments to slow the course of HD, environmental interventions offer feasible approaches to delay the disease, however further preclinical and human studies are needed in order to generate clinical recommendations. Environmental interventions could be combined with future pharmacological therapies and stimulate the identification of enviromimetics, drugs which mimic or enhance the beneficial effects of cognitive stimulation and physical activity. Copyright © 2015. Published by Elsevier Ltd.

Systematic Search for Gene-Gene Interaction Effect on Prostate Cancer Risk

Science.gov (United States)

2013-07-01

Systematic Search for Gene-Gene Interaction 5a. CONTRACT NUMBER Effect on Prostate Cancer Risk 5b. GRANT NUMBER W81XWH-09-1-0488 5c. PROGRAM...Supported by this grant ) 1. Tao S, Wang Z, Feng J, Hsu FC, Jin G, Kin ST, Zhang Z, Gronberg H, Zheng, SL, Isaacs WB, XU J, Sun J. A Genome-Wide Search for...order interactions among estrogen- metabolism genes in sporadic breast cancer. Am J Hum Genet, 69, 138-47. 48. Marchini, J., Donnelly, P. and Cardon

Gene-diet-interactions in folate-mediated one-carbon metabolism modify colon cancer risk.

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Liu, Amy Y; Scherer, Dominique; Poole, Elizabeth; Potter, John D; Curtin, Karen; Makar, Karen; Slattery, Martha L; Caan, Bette J; Ulrich, Cornelia M

2013-04-01

The importance of folate-mediated one-carbon metabolism (FOCM) in colorectal carcinogenesis is emphasized by observations that high dietary folate intake is associated with decreased risk of colon cancer (CC) and its precursors. Additionally, polymorphisms in FOCM-related genes have been repeatedly associated with risk, supporting a causal relationship between folate and colorectal carcinogenesis. We investigated ten candidate polymorphisms with defined or probable functional impact in eight FOCM-related genes (SHMT1, DHFR, DNMT1, MTHFD1, MTHFR, MTRR, TCN2, and TDG) in 1609 CC cases and 1974 controls for association with CC risk and for interaction with dietary factors. No polymorphism was statistically significantly associated with overall risk of CC. However, statistically significant interactions modifying CC risk were observed for DNMT1 I311V with dietary folate, methionine, vitamin B2 , and vitamin B12 intake and for MTRR I22M with dietary folate, a predefined one-carbon dietary pattern, and vitamin B6 intake. We observed statistically significant gene-diet interactions with five additional polymorphisms. Our results provide evidence that FOCM-related dietary intakes modify the association between CC risk and FOCM allelic variants. These findings add to observations showing that folate-related gene-nutrient interactions play an important role in modifying the risk of CC. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Learning Motivation Mediates Gene-by-Socioeconomic Status Interaction on Mathematics Achievement in Early Childhood

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Tucker-Drob, Elliot M.; Harden, K. Paige

2012-01-01

There is accumulating evidence that genetic influences on achievement are more pronounced among children living in higher socioeconomic status homes, and that these gene-by-environment interactions occur prior to children's entry into formal schooling. We hypothesized that one pathway through which socioeconomic status promotes genetic influences…

An Empirical Comparison of Joint and Stratified Frameworks for Studying G × E Interactions: Systolic Blood Pressure and Smoking in the CHARGE Gene-Lifestyle Interactions Working Group

NARCIS (Netherlands)

Sung, Y.J. (Yun Ju); T.W. Winkler (Thomas W.); A.K. Manning (Alisa); H. Aschard (Hugues); V. Gudnason (Vilmundur); T.B. Harris (Tamara); A.V. Smith (Albert Vernon); E.A. Boerwinkle (Eric); M.R. Brown; A.C. Morrison (Alanna); M. Fornage (Myriam); L.-A. Lin (Li-An); Richard, M. (Melissa); T.M. Bartz (Traci M.); B.M. Psaty (Bruce); C. Hayward (Caroline); O. Polasek (Ozren); J. Marten (Jonathan); I. Rudan (Igor); M.F. Feitosa (Mary Furlan); A. Kraja (Aldi); M.A. Province (Mike); Deng, X. (Xuan); Fisher, V.A. (Virginia A.); Y. Zhou (Yanhua); L.F. Bielak (Lawrence F.); J.A. Smith (Jennifer A); J.E. Huffman (Jennifer); S. Padmanabhan (Sandosh); B.H. Smith (Blair); Ding, J. (Jingzhong); Y. Liu (YongMei); Lohman, K. (Kurt); C. Bouchard (Claude); T. Rankinen (Tuomo); Rice, T.K. (Treva K.); D.K. Arnett (Donna); K. Schwander; X. Guo (Xiuqing); W. Palmas (Walter); Rotter, J.I. (Jerome I.); Alfred, T. (Tamuno); E.P. Bottinger (Erwin); R.J.F. Loos (Ruth); N. Amin (Najaf); O.H. Franco (Oscar); C.M. van Duijn (Cornelia); D. Vojinovic (Dina); D.I. Chasman (Daniel); P.M. Ridker (Paul); L.M. Rose (Lynda); S.L.R. Kardia (Sharon); X. Zhu (Xiaofeng); K.M. Rice (Kenneth); I.B. Borecki (Ingrid); D.C. Rao (Dabeeru C.); Gauderman, W.J. (W. James); L.A. Cupples (Adrienne)

2016-01-01

textabstractStudying gene-environment (G × E) interactions is important, as they extend our knowledge of the genetic architecture of complex traits and may help to identify novel variants not detected via analysis of main effects alone. The main statistical framework for studying G × E interactions

Learning Abilities and Disabilities: Generalist Genes, Specialist Environments.

Science.gov (United States)

Kovas, Yulia; Plomin, Robert

2007-10-01

Twin studies comparing identical and fraternal twins consistently show substantial genetic influence on individual differences in learning abilities such as reading and mathematics, as well as in other cognitive abilities such as spatial ability and memory. Multivariate genetic research has shown that the same set of genes is largely responsible for genetic influence on these diverse cognitive areas. We call these "generalist genes." What differentiates these abilities is largely the environment, especially nonshared environments that make children growing up in the same family different from one another. These multivariate genetic findings of generalist genes and specialist environments have far-reaching implications for diagnosis and treatment of learning disabilities and for understanding the brain mechanisms that mediate these effects.

Prioritization of gene regulatory interactions from large-scale modules in yeast

Directory of Open Access Journals (Sweden)

Bringas Ricardo

2008-01-01

Full Text Available Abstract Background The identification of groups of co-regulated genes and their transcription factors, called transcriptional modules, has been a focus of many studies about biological systems. While methods have been developed to derive numerous modules from genome-wide data, individual links between regulatory proteins and target genes still need experimental verification. In this work, we aim to prioritize regulator-target links within transcriptional modules based on three types of large-scale data sources. Results Starting with putative transcriptional modules from ChIP-chip data, we first derive modules in which target genes show both expression and function coherence. The most reliable regulatory links between transcription factors and target genes are established by identifying intersection of target genes in coherent modules for each enriched functional category. Using a combination of genome-wide yeast data in normal growth conditions and two different reference datasets, we show that our method predicts regulatory interactions with significantly higher predictive power than ChIP-chip binding data alone. A comparison with results from other studies highlights that our approach provides a reliable and complementary set of regulatory interactions. Based on our results, we can also identify functionally interacting target genes, for instance, a group of co-regulated proteins related to cell wall synthesis. Furthermore, we report novel conserved binding sites of a glycoprotein-encoding gene, CIS3, regulated by Swi6-Swi4 and Ndd1-Fkh2-Mcm1 complexes. Conclusion We provide a simple method to prioritize individual TF-gene interactions from large-scale transcriptional modules. In comparison with other published works, we predict a complementary set of regulatory interactions which yields a similar or higher prediction accuracy at the expense of sensitivity. Therefore, our method can serve as an alternative approach to prioritization for

Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks.

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Deeter, Anthony; Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui

2017-01-01

The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways.

Intelligent Motion and Interaction Within Virtual Environments

Science.gov (United States)

Ellis, Stephen R. (Editor); Slater, Mel (Editor); Alexander, Thomas (Editor)

2007-01-01

What makes virtual actors and objects in virtual environments seem real? How can the illusion of their reality be supported? What sorts of training or user-interface applications benefit from realistic user-environment interactions? These are some of the central questions that designers of virtual environments face. To be sure simulation realism is not necessarily the major, or even a required goal, of a virtual environment intended to communicate specific information. But for some applications in entertainment, marketing, or aspects of vehicle simulation training, realism is essential. The following chapters will examine how a sense of truly interacting with dynamic, intelligent agents may arise in users of virtual environments. These chapters are based on presentations at the London conference on Intelligent Motion and Interaction within a Virtual Environments which was held at University College, London, U.K., 15-17 September 2003.

The SKP1-like gene family of Arabidopsis exhibits a high degree of differential gene expression and gene product interaction during development.

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Mohammad H Dezfulian

Full Text Available The Arabidopsis thaliana genome encodes several families of polypeptides that are known or predicted to participate in the formation of the SCF-class of E3-ubiquitin ligase complexes. One such gene family encodes the Skp1-like class of polypeptide subunits, where 21 genes have been identified and are known to be expressed in Arabidopsis. Phylogenetic analysis based on deduced polypeptide sequence organizes the family of ASK proteins into 7 clades. The complexity of the ASK gene family, together with the close structural similarity among its members raises the prospect of significant functional redundancy among select paralogs. We have assessed the potential for functional redundancy within the ASK gene family by analyzing an expanded set of criteria that define redundancy with higher resolution. The criteria used include quantitative expression of locus-specific transcripts using qRT-PCR, assessment of the sub-cellular localization of individual ASK:YFP auto-fluorescent fusion proteins expressed in vivo as well as the in planta assessment of individual ASK-F-Box protein interactions using bimolecular fluorescent complementation techniques in combination with confocal imagery in live cells. The results indicate significant functional divergence of steady state transcript abundance and protein-protein interaction specificity involving ASK proteins in a pattern that is poorly predicted by sequence-based phylogeny. The information emerging from this and related studies will prove important for defining the functional intersection of expression, localization and gene product interaction that better predicts the formation of discrete SCF complexes, as a prelude to investigating their molecular mode of action.

Genome-wide diet-gene interaction analyses for risk of colorectal cancer.

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Jane C Figueiredo

2014-04-01

Full Text Available Dietary factors, including meat, fruits, vegetables and fiber, are associated with colorectal cancer; however, there is limited information as to whether these dietary factors interact with genetic variants to modify risk of colorectal cancer. We tested interactions between these dietary factors and approximately 2.7 million genetic variants for colorectal cancer risk among 9,287 cases and 9,117 controls from ten studies. We used logistic regression to investigate multiplicative gene-diet interactions, as well as our recently developed Cocktail method that involves a screening step based on marginal associations and gene-diet correlations and a testing step for multiplicative interactions, while correcting for multiple testing using weighted hypothesis testing. Per quartile increment in the intake of red and processed meat were associated with statistically significant increased risks of colorectal cancer and vegetable, fruit and fiber intake with lower risks. From the case-control analysis, we detected a significant interaction between rs4143094 (10p14/near GATA3 and processed meat consumption (OR = 1.17; p = 8.7E-09, which was consistently observed across studies (p heterogeneity = 0.78. The risk of colorectal cancer associated with processed meat was increased among individuals with the rs4143094-TG and -TT genotypes (OR = 1.20 and OR = 1.39, respectively and null among those with the GG genotype (OR = 1.03. Our results identify a novel gene-diet interaction with processed meat for colorectal cancer, highlighting that diet may modify the effect of genetic variants on disease risk, which may have important implications for prevention.

Comparison of information-theoretic to statistical methods for gene-gene interactions in the presence of genetic heterogeneity

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Sucheston Lara

2010-09-01

Full Text Available Abstract Background Multifactorial diseases such as cancer and cardiovascular diseases are caused by the complex interplay between genes and environment. The detection of these interactions remains challenging due to computational limitations. Information theoretic approaches use computationally efficient directed search strategies and thus provide a feasible solution to this problem. However, the power of information theoretic methods for interaction analysis has not been systematically evaluated. In this work, we compare power and Type I error of an information-theoretic approach to existing interaction analysis methods. Methods The k-way interaction information (KWII metric for identifying variable combinations involved in gene-gene interactions (GGI was assessed using several simulated data sets under models of genetic heterogeneity driven by susceptibility increasing loci with varying allele frequency, penetrance values and heritability. The power and proportion of false positives of the KWII was compared to multifactor dimensionality reduction (MDR, restricted partitioning method (RPM and logistic regression. Results The power of the KWII was considerably greater than MDR on all six simulation models examined. For a given disease prevalence at high values of heritability, the power of both RPM and KWII was greater than 95%. For models with low heritability and/or genetic heterogeneity, the power of the KWII was consistently greater than RPM; the improvements in power for the KWII over RPM ranged from 4.7% to 14.2% at for α = 0.001 in the three models at the lowest heritability values examined. KWII performed similar to logistic regression. Conclusions Information theoretic models are flexible and have excellent power to detect GGI under a variety of conditions that characterize complex diseases.

An Interactive Database of Cocaine-Responsive Gene Expression

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Willard M. Freeman

2002-01-01

Full Text Available The postgenomic era of large-scale gene expression studies is inundating drug abuse researchers and many other scientists with findings related to gene expression. This information is distributed across many different journals, and requires laborious literature searches. Here, we present an interactive database that combines existing information related to cocaine-mediated changes in gene expression in an easy-to-use format. The database is limited to statistically significant changes in mRNA or protein expression after cocaine administration. The Flash-based program is integrated into a Web page, and organizes changes in gene expression based on neuroanatomical region, general function, and gene name. Accompanying each gene is a description of the gene, links to the original publications, and a link to the appropriate OMIM (Online Mendelian Inheritance in Man entry. The nature of this review allows for timely modifications and rapid inclusion of new publications, and should help researchers build second-generation hypotheses on the role of gene expression changes in the physiology and behavior of cocaine abuse. Furthermore, this method of organizing large volumes of scientific information can easily be adapted to assist researchers in fields outside of drug abuse.

Dopamine en overmatig alcoholgebruik: genen in interactie met hun omgeving [Dopamine and excessive alcohol consumption: how genes interact with their environment

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Schellekens, A.F.A.; Scholte, R.H.J.; Engels, R.C.M.E.; Verkes, R.J.

2013-01-01

background Hereditary factors account for approximately 50% of the risk of developing alcohol dependence. Genes that affect the dopamine function in the brain have been extensively studied as candidate genes. aim To present the results of recent Dutch studies on the interaction between genes and

Ultrahigh-dimensional variable selection method for whole-genome gene-gene interaction analysis

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Ueki Masao

2012-05-01

Full Text Available Abstract Background Genome-wide gene-gene interaction analysis using single nucleotide polymorphisms (SNPs is an attractive way for identification of genetic components that confers susceptibility of human complex diseases. Individual hypothesis testing for SNP-SNP pairs as in common genome-wide association study (GWAS however involves difficulty in setting overall p-value due to complicated correlation structure, namely, the multiple testing problem that causes unacceptable false negative results. A large number of SNP-SNP pairs than sample size, so-called the large p small n problem, precludes simultaneous analysis using multiple regression. The method that overcomes above issues is thus needed. Results We adopt an up-to-date method for ultrahigh-dimensional variable selection termed the sure independence screening (SIS for appropriate handling of numerous number of SNP-SNP interactions by including them as predictor variables in logistic regression. We propose ranking strategy using promising dummy coding methods and following variable selection procedure in the SIS method suitably modified for gene-gene interaction analysis. We also implemented the procedures in a software program, EPISIS, using the cost-effective GPGPU (General-purpose computing on graphics processing units technology. EPISIS can complete exhaustive search for SNP-SNP interactions in standard GWAS dataset within several hours. The proposed method works successfully in simulation experiments and in application to real WTCCC (Wellcome Trust Case–control Consortium data. Conclusions Based on the machine-learning principle, the proposed method gives powerful and flexible genome-wide search for various patterns of gene-gene interaction.

Ontology-based literature mining of E. coli vaccine-associated gene interaction networks.

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Hur, Junguk; Özgür, Arzucan; He, Yongqun

2017-03-14

Pathogenic Escherichia coli infections cause various diseases in humans and many animal species. However, with extensive E. coli vaccine research, we are still unable to fully protect ourselves against E. coli infections. To more rational development of effective and safe E. coli vaccine, it is important to better understand E. coli vaccine-associated gene interaction networks. In this study, we first extended the Vaccine Ontology (VO) to semantically represent various E. coli vaccines and genes used in the vaccine development. We also normalized E. coli gene names compiled from the annotations of various E. coli strains using a pan-genome-based annotation strategy. The Interaction Network Ontology (INO) includes a hierarchy of various interaction-related keywords useful for literature mining. Using VO, INO, and normalized E. coli gene names, we applied an ontology-based SciMiner literature mining strategy to mine all PubMed abstracts and retrieve E. coli vaccine-associated E. coli gene interactions. Four centrality metrics (i.e., degree, eigenvector, closeness, and betweenness) were calculated for identifying highly ranked genes and interaction types. Using vaccine-related PubMed abstracts, our study identified 11,350 sentences that contain 88 unique INO interactions types and 1,781 unique E. coli genes. Each sentence contained at least one interaction type and two unique E. coli genes. An E. coli gene interaction network of genes and INO interaction types was created. From this big network, a sub-network consisting of 5 E. coli vaccine genes, including carA, carB, fimH, fepA, and vat, and 62 other E. coli genes, and 25 INO interaction types was identified. While many interaction types represent direct interactions between two indicated genes, our study has also shown that many of these retrieved interaction types are indirect in that the two genes participated in the specified interaction process in a required but indirect process. Our centrality analysis of

Beyond main effects of gene-sets: harsh parenting moderates the association between a dopamine gene-set and child externalizing behavior.

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Windhorst, Dafna A; Mileva-Seitz, Viara R; Rippe, Ralph C A; Tiemeier, Henning; Jaddoe, Vincent W V; Verhulst, Frank C; van IJzendoorn, Marinus H; Bakermans-Kranenburg, Marian J

2016-08-01

In a longitudinal cohort study, we investigated the interplay of harsh parenting and genetic variation across a set of functionally related dopamine genes, in association with children's externalizing behavior. This is one of the first studies to employ gene-based and gene-set approaches in tests of Gene by Environment (G × E) effects on complex behavior. This approach can offer an important alternative or complement to candidate gene and genome-wide environmental interaction (GWEI) studies in the search for genetic variation underlying individual differences in behavior. Genetic variants in 12 autosomal dopaminergic genes were available in an ethnically homogenous part of a population-based cohort. Harsh parenting was assessed with maternal (n = 1881) and paternal (n = 1710) reports at age 3. Externalizing behavior was assessed with the Child Behavior Checklist (CBCL) at age 5 (71 ± 3.7 months). We conducted gene-set analyses of the association between variation in dopaminergic genes and externalizing behavior, stratified for harsh parenting. The association was statistically significant or approached significance for children without harsh parenting experiences, but was absent in the group with harsh parenting. Similarly, significant associations between single genes and externalizing behavior were only found in the group without harsh parenting. Effect sizes in the groups with and without harsh parenting did not differ significantly. Gene-environment interaction tests were conducted for individual genetic variants, resulting in two significant interaction effects (rs1497023 and rs4922132) after correction for multiple testing. Our findings are suggestive of G × E interplay, with associations between dopamine genes and externalizing behavior present in children without harsh parenting, but not in children with harsh parenting experiences. Harsh parenting may overrule the role of genetic factors in externalizing behavior. Gene-based and gene

FunGeneNet: a web tool to estimate enrichment of functional interactions in experimental gene sets.

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Tiys, Evgeny S; Ivanisenko, Timofey V; Demenkov, Pavel S; Ivanisenko, Vladimir A

2018-02-09

Estimation of functional connectivity in gene sets derived from genome-wide or other biological experiments is one of the essential tasks of bioinformatics. A promising approach for solving this problem is to compare gene networks built using experimental gene sets with random networks. One of the resources that make such an analysis possible is CrossTalkZ, which uses the FunCoup database. However, existing methods, including CrossTalkZ, do not take into account individual types of interactions, such as protein/protein interactions, expression regulation, transport regulation, catalytic reactions, etc., but rather work with generalized types characterizing the existence of any connection between network members. We developed the online tool FunGeneNet, which utilizes the ANDSystem and STRING to reconstruct gene networks using experimental gene sets and to estimate their difference from random networks. To compare the reconstructed networks with random ones, the node permutation algorithm implemented in CrossTalkZ was taken as a basis. To study the FunGeneNet applicability, the functional connectivity analysis of networks constructed for gene sets involved in the Gene Ontology biological processes was conducted. We showed that the method sensitivity exceeds 0.8 at a specificity of 0.95. We found that the significance level of the difference between gene networks of biological processes and random networks is determined by the type of connections considered between objects. At the same time, the highest reliability is achieved for the generalized form of connections that takes into account all the individual types of connections. By taking examples of the thyroid cancer networks and the apoptosis network, it is demonstrated that key participants in these processes are involved in the interactions of those types by which these networks differ from random ones. FunGeneNet is a web tool aimed at proving the functionality of networks in a wide range of sizes of

Novel interactions between vertebrate Hox genes

NARCIS (Netherlands)

Hooiveld, MHW; Morgan, R; Rieden, PID; Houtzager, E; Pannese, M; Damen, K; Boncinelli, E; Durston, AJ

1999-01-01

Understanding why metazoan Hox/HOM-C genes are expressed in spatiotemporal sequences showing colinearity with their genomic sequence is a central challenge in developmental biology. Here, we studied the consequences of ectopically expressing Hox genes to investigate whether Hox-Hox interactions

Using Nematostella vectensis to study the interactions between genome, epigenome and bacteria in a changing environment

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Sebastian Fraune

2016-08-01

Full Text Available The phenotype of an animal cannot be explained entirely by its genes. It is now clear that factors other than the genome contribute to the ecology and evolution of animals. Two fundamentally important factors are the associated microbiota and epigenetic regulations. Unlike the genes and regulatory regions of the genome, epigenetics and microbial composition can be rapidly modified, and may thus represent mechanisms for rapid acclimation to a changing environment. At present, the individual functions of epigenetics, microbiomes, and genomic mutations are largely studied in isolation, particularly for species in marine ecosystems. This single variable approach leaves significant questions open for how these mechanisms intersect in the acclimation and adaptation of organisms in different environments. Here, we propose that the starlet sea anemone, Nematostella vectensis, is a model of choice to investigate the complex interplay between adaptation as well as physiological and molecular plasticity in coastal ecosystems. N. vectensis’ geographic range spans four distinct coastlines, including a wide thermocline along the Atlantic coast of North America. N. vectensis is a particularly powerful invertebrate model for studying genome-environment interactions due to (1 the availability of a well-annotated genome, including preexisting data on genome methylation, histone modifications and miRNAs, (2 an extensive molecular toolkit including well-developed protocols for gene suppression and transgenesis, and (3 the simplicity of culture and experimentation in the laboratory. Taken together, N. vectensis has the tractability to connect the functional relationships between a host animal, microbes, and genome modifications to determine mechanisms underlying phenotypic plasticity and local adaptation.

Response to angiotensin-converting enzyme inhibition is selectively blunted by high sodium in angiotensin-converting enzyme DD genotype: evidence for gene-environment interaction in healthy volunteers.

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Lely, A Titia; Heerspink, Hiddo J Lambers; Zuurman, Mike; Visser, Folkert W; Kocks, Menno J A; Boomsma, Frans; Navis, Gerjan

2010-12-01

Renin-angiotensin-aldosterone system blockade is a cornerstone in cardiovascular protection. Angiotensin-converting enzyme (ACE)-DD genotype has been associated with resistance to angiotensin-converting enzyme inhibition (ACEi), but data are conflicting. As sodium intake modifies the effect of ACEi as well as the genotype-phenotype relationship, we hypothesize gene-environment interaction between sodium-status, the response to ACEi, and ACE genotype. Thirty-five male volunteers (26 ± 9 years; II n = 6, ID n = 18, DD n = 11) were studied during placebo and ACEi (double blind, enalapril 20 mg/day) on low [7 days 50 mmol Na/day (low salt)] and high [7 days 200 mmol Na/day (high salt)] sodium, with a washout of 6 weeks in-between. After each period mean arterial pressure (MAP) was measured before and during graded infusion of angiotensin II (Ang II). During high salt, ACEi reduced MAP in II and ID, but not in DD [II: 88 (78-94) versus 76 (72-88); ID: 87 (84-91) versus 83 (79-87); both P DD: 86 (82-96) versus 88 (80-90); ns, P DD: 84 (80-91) versus 81 (75-85); all P DD, with an 18% rise in MAP during the highest dose versus 22 and 31% in ID and II (P DD genotype during high salt, accompanied by blunted sensitivity to Ang II. Low salt corrects both abnormalities. Further analysis of this gene-environment interaction in patients may contribute to strategies for improvement of individual treatment efficacy.

Combining many interaction networks to predict gene function and analyze gene lists.

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Mostafavi, Sara; Morris, Quaid

2012-05-01

In this article, we review how interaction networks can be used alone or in combination in an automated fashion to provide insight into gene and protein function. We describe the concept of a "gene-recommender system" that can be applied to any large collection of interaction networks to make predictions about gene or protein function based on a query list of proteins that share a function of interest. We discuss these systems in general and focus on one specific system, GeneMANIA, that has unique features and uses different algorithms from the majority of other systems. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Student-Teacher Interaction in Online Learning Environments

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Wright, Robert D., Ed.

2015-01-01

As face-to-face interaction between student and instructor is not present in online learning environments, it is increasingly important to understand how to establish and maintain social presence in online learning. "Student-Teacher Interaction in Online Learning Environments" provides successful strategies and procedures for developing…

Gene-based testing of interactions in association studies of quantitative traits.

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Li Ma

Full Text Available Various methods have been developed for identifying gene-gene interactions in genome-wide association studies (GWAS. However, most methods focus on individual markers as the testing unit, and the large number of such tests drastically erodes statistical power. In this study, we propose novel interaction tests of quantitative traits that are gene-based and that confer advantage in both statistical power and biological interpretation. The framework of gene-based gene-gene interaction (GGG tests combine marker-based interaction tests between all pairs of markers in two genes to produce a gene-level test for interaction between the two. The tests are based on an analytical formula we derive for the correlation between marker-based interaction tests due to linkage disequilibrium. We propose four GGG tests that extend the following P value combining methods: minimum P value, extended Simes procedure, truncated tail strength, and truncated P value product. Extensive simulations point to correct type I error rates of all tests and show that the two truncated tests are more powerful than the other tests in cases of markers involved in the underlying interaction not being directly genotyped and in cases of multiple underlying interactions. We applied our tests to pairs of genes that exhibit a protein-protein interaction to test for gene-level interactions underlying lipid levels using genotype data from the Atherosclerosis Risk in Communities study. We identified five novel interactions that are not evident from marker-based interaction testing and successfully replicated one of these interactions, between SMAD3 and NEDD9, in an independent sample from the Multi-Ethnic Study of Atherosclerosis. We conclude that our GGG tests show improved power to identify gene-level interactions in existing, as well as emerging, association studies.

Gene by Environment Research to Prevent Externalizing Problem Behavior : Ethical Questions Raised from a Public Healthcare Perspective

NARCIS (Netherlands)

Chhangur, Rabia R.; Weeland, Joyce; Matthys, Walter; Overbeek, Geertjan

2015-01-01

The main public health advantages of examining gene by environment interactions (i.e., G x E) in externalizing behavior lie in the realm of personalized interventions. Nevertheless, the incorporation of genetic data in randomized controlled trials is fraught with difficulties and raises ethical

Gene by environment research to prevent externalizing problem behavior: Ethical questions raised from a public healthcare perspective

NARCIS (Netherlands)

Chhangur, R.R.; Weeland, J.; Matthys, W.; Overbeek, G.

2015-01-01

The main public health advantages of examining gene by environment interactions (i.e., G × E) in externalizing behavior lie in the realm of personalized interventions. Nevertheless, the incorporation of genetic data in randomized controlled trials is fraught with difficulties and raises ethical

Degenerative periodontal-diseases and oral osteonecrosis: The role of gene-environment interactions

International Nuclear Information System (INIS)

Baldi, D.; Izzotti, A.; Bonica, P.; Pera, P.; Pulliero, A.

2009-01-01

Chronic-degenerative dentistry diseases, including periodontal diseases and oral osteonecrosis, are widespread in human populations and represent a significant problem for public health. These diseases result from pathogenic mechanisms created by the interaction between environmental genotoxic risk-factors and genetic assets conferring individual susceptibility. Osteonecrosis occurs in subjects undergoing exposure to high doses of DNA-damaging agents for chemo- and radiotherapy of neoplastic diseases. In susceptible patients, ionizing radiation and biphosphonate-chemotherapy induce severe, progressive, and irreversible degeneration of facial bones, resulting in avascular necrosis of the jaw. This may also occur in patients receiving biphosphonate for osteoporosis therapy. Periodontal diseases include chronic, aggressive, and necrotizing periodontitis, often resulting in severe alteration of periodontal tissues and tooth loss. Cigarette smoking and chronic inflammation caused by specific bacteria are the main risk factors for periodontitis. Oxidative damage plays a fundamental pathogenic role, as established by detection of mitochondrial DNA damage in the gingival tissue of patients with periodontitis. Endogenous risk factors in dental diseases include polymorphisms for metabolic enzymes such as glutathione transferases M1 and T1, N-acetyl transferase 2, and CYP 1A1. Other genetic polymorphisms that confer susceptibility to dentistry diseases affect genes encoding metalloproteases (involved in periodontal tissue remodeling and degradation), cytokines (involved in inflammation), prothrombin, and DNA repair activities. These findings provide evidence that dentistry diseases are related to risk factors associated with environmental mutagenesis. This issue warrants future investigations aimed at improving oral health and preventing oral degenerative diseases using molecular and experimental approaches currently utilized in mutagenicity studies.

Degenerative periodontal-diseases and oral osteonecrosis: The role of gene-environment interactions

Energy Technology Data Exchange (ETDEWEB)

Baldi, D. [Department of Medical, Biophysical, and Dentistry Sciences and Technologies, University of Genoa (Italy); Izzotti, A. [Department of Health Sciences, University of Genoa, Via A. Pastore 1 (Italy); Bonica, P.; Pera, P. [Department of Medical, Biophysical, and Dentistry Sciences and Technologies, University of Genoa (Italy); Pulliero, A., E-mail: alessandra.pulliero@unige.it [Department of Health Sciences, University of Genoa, Via A. Pastore 1 (Italy)

2009-07-10

Chronic-degenerative dentistry diseases, including periodontal diseases and oral osteonecrosis, are widespread in human populations and represent a significant problem for public health. These diseases result from pathogenic mechanisms created by the interaction between environmental genotoxic risk-factors and genetic assets conferring individual susceptibility. Osteonecrosis occurs in subjects undergoing exposure to high doses of DNA-damaging agents for chemo- and radiotherapy of neoplastic diseases. In susceptible patients, ionizing radiation and biphosphonate-chemotherapy induce severe, progressive, and irreversible degeneration of facial bones, resulting in avascular necrosis of the jaw. This may also occur in patients receiving biphosphonate for osteoporosis therapy. Periodontal diseases include chronic, aggressive, and necrotizing periodontitis, often resulting in severe alteration of periodontal tissues and tooth loss. Cigarette smoking and chronic inflammation caused by specific bacteria are the main risk factors for periodontitis. Oxidative damage plays a fundamental pathogenic role, as established by detection of mitochondrial DNA damage in the gingival tissue of patients with periodontitis. Endogenous risk factors in dental diseases include polymorphisms for metabolic enzymes such as glutathione transferases M1 and T1, N-acetyl transferase 2, and CYP 1A1. Other genetic polymorphisms that confer susceptibility to dentistry diseases affect genes encoding metalloproteases (involved in periodontal tissue remodeling and degradation), cytokines (involved in inflammation), prothrombin, and DNA repair activities. These findings provide evidence that dentistry diseases are related to risk factors associated with environmental mutagenesis. This issue warrants future investigations aimed at improving oral health and preventing oral degenerative diseases using molecular and experimental approaches currently utilized in mutagenicity studies.

Genotype x Environment Interaction and Yield Stability of Maize ...

African Journals Online (AJOL)

Most of the cultivars had significant deviation mean square (S2di), implying that these cultivars had unstable performance across the testing environments. However, Additive Main Effect and Multiplicative Interaction (AMMI) analysis showed Gibe-1 (mean yield, 7.40 t ha-1) had relatively stable performance across the ...

Antimicrobial-Resistant Bacterial Populations and Antimicrobial Resistance Genes Obtained from Environments Impacted by Livestock and Municipal Waste.

Directory of Open Access Journals (Sweden)

Getahun E Agga

Full Text Available This study compared the populations of antimicrobial-resistant bacteria and the repertoire of antimicrobial resistance genes in four environments: effluent of three municipal wastewater treatment facilities, three cattle feedlot runoff catchment ponds, three swine waste lagoons, and two "low impact" environments (an urban lake and a relict prairie. Multiple liquid and solid samples were collected from each environment. The prevalences and concentrations of antimicrobial-resistant (AMR Gram-negative (Escherichia coli and Salmonella enterica and Gram-positive (enterococci bacteria were determined from individual samples (n = 174. The prevalences of 84 antimicrobial resistance genes in metagenomic DNA isolated from samples pooled (n = 44 by collection date, location, and sample type were determined. The prevalences and concentrations of AMR E. coli and Salmonella were similar among the livestock and municipal sample sources. The levels of erythromycin-resistant enterococci were significantly higher in liquid samples from cattle catchment ponds and swine waste lagoons than in liquid samples from municipal wastewater treatment facilities, but solid samples from these environments did not differ significantly. Similarly, trimethoprim/sulfamethoxazole-resistant E. coli concentrations were significantly higher in swine liquid than in municipal liquid samples, but there was no difference in solid samples. Multivariate analysis of the distribution of antimicrobial resistance genes using principal coordinate analysis showed distinct clustering of samples with livestock (cattle and swine, low impact environment and municipal samples forming three separate clusters. The numbers of class A beta-lactamase, class C beta-lactamase, and fluoroquinolone resistance genes detected were significantly higher (P < 0.05 in municipal samples than in cattle runoff or swine lagoon samples. In conclusion, we report that AMR is a very widespread phenomenon and that similar

WAVE: Interactive Wave-based Sound Propagation for Virtual Environments.

Science.gov (United States)

Mehra, Ravish; Rungta, Atul; Golas, Abhinav; Ming Lin; Manocha, Dinesh

2015-04-01

We present an interactive wave-based sound propagation system that generates accurate, realistic sound in virtual environments for dynamic (moving) sources and listeners. We propose a novel algorithm to accurately solve the wave equation for dynamic sources and listeners using a combination of precomputation techniques and GPU-based runtime evaluation. Our system can handle large environments typically used in VR applications, compute spatial sound corresponding to listener's motion (including head tracking) and handle both omnidirectional and directional sources, all at interactive rates. As compared to prior wave-based techniques applied to large scenes with moving sources, we observe significant improvement in runtime memory. The overall sound-propagation and rendering system has been integrated with the Half-Life 2 game engine, Oculus-Rift head-mounted display, and the Xbox game controller to enable users to experience high-quality acoustic effects (e.g., amplification, diffraction low-passing, high-order scattering) and spatial audio, based on their interactions in the VR application. We provide the results of preliminary user evaluations, conducted to study the impact of wave-based acoustic effects and spatial audio on users' navigation performance in virtual environments.

Paternal Aging Affects Behavior in Pax6 Mutant Mice: A Gene/Environment Interaction in Understanding Neurodevelopmental Disorders.

Science.gov (United States)

Yoshizaki, Kaichi; Furuse, Tamio; Kimura, Ryuichi; Tucci, Valter; Kaneda, Hideki; Wakana, Shigeharu; Osumi, Noriko

2016-01-01

Neurodevelopmental disorders such as autism spectrum disorder (ASD) and attention deficit and hyperactivity disorder (ADHD) have increased over the last few decades. These neurodevelopmental disorders are characterized by a complex etiology, which involves multiple genes and gene-environmental interactions. Various genes that control specific properties of neural development exert pivotal roles in the occurrence and severity of phenotypes associated with neurodevelopmental disorders. Moreover, paternal aging has been reported as one of the factors that contribute to the risk of ASD and ADHD. Here we report, for the first time, that paternal aging has profound effects on the onset of behavioral abnormalities in mice carrying a mutation of Pax6, a gene with neurodevelopmental regulatory functions. We adopted an in vitro fertilization approach to restrict the influence of additional factors. Comprehensive behavioral analyses were performed in Sey/+ mice (i.e., Pax6 mutant heterozygotes) born from in vitro fertilization of sperm taken from young or aged Sey/+ fathers. No body weight changes were found in the four groups, i.e., Sey/+ and wild type (WT) mice born to young or aged father. However, we found important differences in maternal separation-induced ultrasonic vocalizations of Sey/+ mice born from young father and in the level of hyperactivity of Sey/+ mice born from aged fathers in the open-field test, respectively, compared to WT littermates. Phenotypes of anxiety were observed in both genotypes born from aged fathers compared with those born from young fathers. No significant difference was found in social behavior and sensorimotor gating among the four groups. These results indicate that mice with a single genetic risk factor can develop different phenotypes depending on the paternal age. Our study advocates for serious considerations on the role of paternal aging in breeding strategies for animal studies.

Paternal Aging Affects Behavior in Pax6 Mutant Mice: A Gene/Environment Interaction in Understanding Neurodevelopmental Disorders.

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Kaichi Yoshizaki

Full Text Available Neurodevelopmental disorders such as autism spectrum disorder (ASD and attention deficit and hyperactivity disorder (ADHD have increased over the last few decades. These neurodevelopmental disorders are characterized by a complex etiology, which involves multiple genes and gene-environmental interactions. Various genes that control specific properties of neural development exert pivotal roles in the occurrence and severity of phenotypes associated with neurodevelopmental disorders. Moreover, paternal aging has been reported as one of the factors that contribute to the risk of ASD and ADHD. Here we report, for the first time, that paternal aging has profound effects on the onset of behavioral abnormalities in mice carrying a mutation of Pax6, a gene with neurodevelopmental regulatory functions. We adopted an in vitro fertilization approach to restrict the influence of additional factors. Comprehensive behavioral analyses were performed in Sey/+ mice (i.e., Pax6 mutant heterozygotes born from in vitro fertilization of sperm taken from young or aged Sey/+ fathers. No body weight changes were found in the four groups, i.e., Sey/+ and wild type (WT mice born to young or aged father. However, we found important differences in maternal separation-induced ultrasonic vocalizations of Sey/+ mice born from young father and in the level of hyperactivity of Sey/+ mice born from aged fathers in the open-field test, respectively, compared to WT littermates. Phenotypes of anxiety were observed in both genotypes born from aged fathers compared with those born from young fathers. No significant difference was found in social behavior and sensorimotor gating among the four groups. These results indicate that mice with a single genetic risk factor can develop different phenotypes depending on the paternal age. Our study advocates for serious considerations on the role of paternal aging in breeding strategies for animal studies.

Gene-by-social-environment interaction (GxSE) between ADCYAP1R1 genotype and neighborhood crime predicts major depression symptoms in trauma-exposed women.

Science.gov (United States)

Lowe, Sarah R; Pothen, John; Quinn, James W; Rundle, Andrew; Bradley, Bekh; Galea, Sandro; Ressler, Kerry J; Koenen, Karestan C

2015-11-15

Few studies have explored interactions between genes and social environmental exposures (GxSEs) for trauma-related psychopathology, including symptoms of posttraumatic stress (PTS) and major depression (MD). The extant literature suggests the possibility of a GxSE between the rs2267735 variant of the ADCYAP1R1 gene and neighborhood crime. The current study aimed to explore this possibility among a predominantly African American sample of trauma-exposed women. Female participants (N=1361) were recruited from a public hospital, and completed measures of PTS and MD symptoms and provided DNA samples. Participants' home addresses were mapped onto 300 neighborhoods (2010 census tracts), and data on crime within neighborhoods was collected. Multilevel models detected a significant GxSE between rs2267735 and neighborhood crime for MD symptoms (p=.01). Having two copies of the risk (C) allele was associated with higher MD symptoms for participants living in high-crime neighborhoods. At least six limitations are noteworthy: (1) low statistical power; (2) use of self-report symptom inventories; (3) lack of information on symptom onset; (4) homogeneous sample from a single metropolitan area; (5) non-specific index of crime; and (6) use of census tracts to define neighborhoods. The results provide further evidence of GxSEs for psychiatric outcomes among trauma-exposed populations. Further investigations of genetic factors for trauma-related psychopathology should include careful assessments of the social environment. Copyright © 2015 Elsevier B.V. All rights reserved.

Tracking microorganisms and gene in the environment

International Nuclear Information System (INIS)

Atlas, R.M.; Sayler, G.S.

1988-01-01

Studies have been conducted to determine the sensitivities and limitations of various methods for determining the fate of genetically engineered microorganisms (GEMs) and their genes in the environment. Selective viable plate count procedures can be designed to detect the introduced organisms with high sensitivity; but they are restricted by potential mutations affecting the expression of the selective characteristic in the introduced organism, the occurrence of the particular selective characteristic in the indigenous organisms, and the need to culture the organism. The accuracy of this approach is greatly improved by colony hybridization procedures that use a specific gene probe to detect the introduced genes, but this approach is still only as sensitive as the plating procedure. Direct extraction of DNA from environmental samples, coupled with dot blot hybridization with radiolabeled probe DNA or solution hybridization, gives a high degree of both sensitivity and precision. This approach does not require culturing of the organism; and even if an introduced gene moves into a new organism or if the introduced organism is viable but nonculturable, the gene probe methods will detect the persistence of the introduced genes in the environment. Efficient direct DNA extraction methods have been developed and tested following in vitro experimental additions of GEMs to sediment and water samples

Association testing to detect gene-gene interactions on sex chromosomes in trio data

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Yeonok eLee

2013-11-01

Full Text Available Autism Spectrum Disorder (ASD occurs more often among males than females in a 4:1 ratio. Among theories used to explain the causes of ASD, the X chromosome and the Y chromosome theories attribute ASD to X-linked mutation and the male-limited gene expressions on the Y chromosome, respectively. Despite the rationale of the theory, studies have failed to attribute the sex-biased ratio to the significant linkage or association on the regions of interest on X chromosome. We further study the gender biased ratio by examining the possible interaction effects between two genes in the sex chromosomes. We propose a logistic regression model with mixed effects to detect gene-gene interactions on sex chromosomes. We investigated the power and type I error rates of the approach for a range of minor allele frequencies and varying linkage disequilibrium between markers and QTLs. We also evaluated the robustness of the model to population stratification. We applied the model to a trio-family data set with an ASD affected male child to study gene-gene interactions on sex chromosomes.

Genes, Environment, and Human Behavior.

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Bloom, Mark V.; Cutter, Mary Ann; Davidson, Ronald; Dougherty, Michael J.; Drexler, Edward; Gelernter, Joel; McCullough, Laurence B.; McInerney, Joseph D.; Murray, Jeffrey C.; Vogler, George P.; Zola, John

This curriculum module explores genes, environment, and human behavior. This book provides materials to teach about the nature and methods of studying human behavior, raise some of the ethical and public policy dilemmas emerging from the Human Genome Project, and provide professional development for teachers. An extensive Teacher Background…

Network Graph Analysis of Gene-Gene Interactions in Genome-Wide Association Study Data

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Sungyoung Lee

2012-12-01

Full Text Available Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs. For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR is one of the powerful and efficient methods for detecting high-order gene-gene (GxG interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI. Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.

Network graph analysis of gene-gene interactions in genome-wide association study data.

Science.gov (United States)

Lee, Sungyoung; Kwon, Min-Seok; Park, Taesung

2012-12-01

Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene (GxG) interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.

Differential reconstructed gene interaction networks for deriving toxicity threshold in chemical risk assessment.

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Yang, Yi; Maxwell, Andrew; Zhang, Xiaowei; Wang, Nan; Perkins, Edward J; Zhang, Chaoyang; Gong, Ping

2013-01-01

Pathway alterations reflected as changes in gene expression regulation and gene interaction can result from cellular exposure to toxicants. Such information is often used to elucidate toxicological modes of action. From a risk assessment perspective, alterations in biological pathways are a rich resource for setting toxicant thresholds, which may be more sensitive and mechanism-informed than traditional toxicity endpoints. Here we developed a novel differential networks (DNs) approach to connect pathway perturbation with toxicity threshold setting. Our DNs approach consists of 6 steps: time-series gene expression data collection, identification of altered genes, gene interaction network reconstruction, differential edge inference, mapping of genes with differential edges to pathways, and establishment of causal relationships between chemical concentration and perturbed pathways. A one-sample Gaussian process model and a linear regression model were used to identify genes that exhibited significant profile changes across an entire time course and between treatments, respectively. Interaction networks of differentially expressed (DE) genes were reconstructed for different treatments using a state space model and then compared to infer differential edges/interactions. DE genes possessing differential edges were mapped to biological pathways in databases such as KEGG pathways. Using the DNs approach, we analyzed a time-series Escherichia coli live cell gene expression dataset consisting of 4 treatments (control, 10, 100, 1000 mg/L naphthenic acids, NAs) and 18 time points. Through comparison of reconstructed networks and construction of differential networks, 80 genes were identified as DE genes with a significant number of differential edges, and 22 KEGG pathways were altered in a concentration-dependent manner. Some of these pathways were perturbed to a degree as high as 70% even at the lowest exposure concentration, implying a high sensitivity of our DNs approach

Functional modules by relating protein interaction networks and gene expression.

Science.gov (United States)

Tornow, Sabine; Mewes, H W

2003-11-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

Double-Bottom Chaotic Map Particle Swarm Optimization Based on Chi-Square Test to Determine Gene-Gene Interactions

Science.gov (United States)

Yang, Cheng-Hong; Chang, Hsueh-Wei

2014-01-01

Gene-gene interaction studies focus on the investigation of the association between the single nucleotide polymorphisms (SNPs) of genes for disease susceptibility. Statistical methods are widely used to search for a good model of gene-gene interaction for disease analysis, and the previously determined models have successfully explained the effects between SNPs and diseases. However, the huge numbers of potential combinations of SNP genotypes limit the use of statistical methods for analysing high-order interaction, and finding an available high-order model of gene-gene interaction remains a challenge. In this study, an improved particle swarm optimization with double-bottom chaotic maps (DBM-PSO) was applied to assist statistical methods in the analysis of associated variations to disease susceptibility. A big data set was simulated using the published genotype frequencies of 26 SNPs amongst eight genes for breast cancer. Results showed that the proposed DBM-PSO successfully determined two- to six-order models of gene-gene interaction for the risk association with breast cancer (odds ratio > 1.0; P value <0.05). Analysis results supported that the proposed DBM-PSO can identify good models and provide higher chi-square values than conventional PSO. This study indicates that DBM-PSO is a robust and precise algorithm for determination of gene-gene interaction models for breast cancer. PMID:24895547

Gene Dosage Analysis in a Clinical Environment: Gene-Targeted Microarrays as the Platform-of-Choice

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Donald R. Love

2013-03-01

Full Text Available The role of gene deletion and duplication in the aetiology of disease has become increasingly evident over the last decade. In addition to the classical deletion/duplication disorders diagnosed using molecular techniques, such as Duchenne Muscular Dystrophy and Charcot-Marie-Tooth Neuropathy Type 1A, the significance of partial or whole gene deletions in the pathogenesis of a large number single-gene disorders is becoming more apparent. A variety of dosage analysis methods are available to the diagnostic laboratory but the widespread application of many of these techniques is limited by the expense of the kits/reagents and restrictive targeting to a particular gene or portion of a gene. These limitations are particularly important in the context of a small diagnostic laboratory with modest sample throughput. We have developed a gene-targeted, custom-designed comparative genomic hybridisation (CGH array that allows twelve clinical samples to be interrogated simultaneously for exonic deletions/duplications within any gene (or panel of genes on the array. We report here on the use of the array in the analysis of a series of clinical samples processed by our laboratory over a twelve-month period. The array has proven itself to be robust, flexible and highly suited to the diagnostic environment.

The interaction between cannabis use and the Val158Met polymorphism of the COMT gene in psychosis: A transdiagnostic meta - analysis

NARCIS (Netherlands)

Vaessen, Thomas Stephanus Johannes; de Jong, Lea; Schäfer, Annika Theresia; Damen, Thomas; Uittenboogaard, Aniek; Krolinski, Pauline; Nwosu, Chinyere Vicky; Pinckaers, Florentina Maria Egidius; Rotee, Iris Leah Marije; Smeets, Antonius Petrus Wilhelmus; Ermiş, Ayşegül; Kennedy, James L.; Nieman, Dorien H.; Tiwari, Arun; van Os, Jim; Drukker, Marjan

2018-01-01

Neither environmental nor genetic factors are sufficient to predict the transdiagnostic expression of psychosis. Therefore, analysis of gene-environment interactions may be productive. A meta-analysis was performed using papers investigating the interaction between cannabis use and catechol-O-methyl

Gene-physical activity interactions and their impact on diabetes

DEFF Research Database (Denmark)

Oskari Kilpeläinen, Tuomas; Franks, Paul W

2014-01-01

to an equal bout of physical activity. Individuals with specific genetic profiles are also expected to be more responsive to the beneficial effects of physical activity in the prevention of type 2 diabetes. Identification of such gene-physical activity interactions could give new insights into the biological...... the reader to the recent advances in the genetics of type 2 diabetes, summarize the current evidence on gene-physical activity interactions in relation to type 2 diabetes, and outline how information on gene-physical activity interactions might help improve the prevention and treatment of type 2 diabetes....... Finally, we will discuss the existing and emerging strategies that might enhance our ability to identify and exploit gene-physical activity interactions in the etiology of type 2 diabetes. © 2014 S. Karger AG, Basel....

Interaction between the SLC19A1 gene and maternal first trimester fever on offspring neural tube defects.

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Pei, Lijun; Zhu, Huiping; Ye, Rongwei; Wu, Jilei; Liu, Jianmeng; Ren, Aiguo; Li, Zhiwen; Zheng, Xiaoying

2015-01-01

Many studies have indicated that the reduced folate carrier gene (SLC19A1) is associated with an increased risk of neural tube defects (NTDs). However, the interaction between the SLC19A1 gene variant and maternal fever exposure and NTD risk remains unknown. The aim of this study was to investigate whether the risk for NTDs was influenced by the interactions between the SLC19A1 (rs1051266) variant and maternal first trimester fever. We investigated the potential interaction between maternal first trimester fever and maternal or offspring SLC19A1 polymorphism through a population-based case-control study. One hundred and four nuclear families with NTDs and 100 control families with nonmal newborns were included in the study. SLC19A1 polymorphism was determined using polymerase chain reaction-restricted fragment length polymorphism. Mothers who had the GG/GA genotype and first trimester fever had an elevated risk of NTDs (adjusted odds ratio, 11.73; 95% confidence interval, 3.02-45.58) as compared to absence of maternal first trimester fever and AA genotype after adjusting for maternal education, paternal education, and age, and had a significant interactive coefficient (γ = 3.17) between maternal GG/GA genotype and first trimester fever. However, there was no interaction between offspring's GG/GA genotype and maternal first trimester fever (the interactive coefficient γ = 0.97) after adjusting for confounding factors. Our findings suggested that the risk of NTDs was potentially influenced by a gene-environment interaction between maternal SLC19A1 rs1051266 GG/GA genotype and first trimester fever. Maternal GG/GA genotype may strengthen the effect of maternal fever exposure on NTD risk in this Chinese population. © 2014 Wiley Periodicals, Inc.

Confluence of genes, environment, development, and behavior in a post Genome-Wide Association Study world.

Science.gov (United States)

Vrieze, Scott I; Iacono, William G; McGue, Matt

2012-11-01

This article serves to outline a research paradigm to investigate main effects and interactions of genes, environment, and development on behavior and psychiatric illness. We provide a historical context for candidate gene studies and genome-wide association studies, including benefits, limitations, and expected payoffs. Using substance use and abuse as our driving example, we then turn to the importance of etiological psychological theory in guiding genetic, environmental, and developmental research, as well as the utility of refined phenotypic measures, such as endophenotypes, in the pursuit of etiological understanding and focused tests of genetic and environmental associations. Phenotypic measurement has received considerable attention in the history of psychology and is informed by psychometrics, whereas the environment remains relatively poorly measured and is often confounded with genetic effects (i.e., gene-environment correlation). Genetically informed designs, which are no longer limited to twin and adoption studies thanks to ever-cheaper genotyping, are required to understand environmental influences. Finally, we outline the vast amount of individual difference in structural genomic variation, most of which remains to be leveraged in genetic association tests. Although the genetic data can be massive and burdensome (tens of millions of variants per person), we argue that improved understanding of genomic structure and function will provide investigators with new tools to test specific a priori hypotheses derived from etiological psychological theory, much like current candidate gene research but with less confusion and more payoff than candidate gene research has to date.

A preliminary investigation into genotype x environment interaction ...

African Journals Online (AJOL)

uvp

2014-08-24

Aug 24, 2014 ... Genotype x environment interaction (G x E) in dairy cattle is a contentious ... environments, if it exists, with a negative impact on genetic response ..... interaction for Holstein milk yield in Colombia, Mexico and Puerto Rico.

Interactions between the vascular endothelial growth factor gene polymorphism and life events in susceptibility to major depressive disorder in a Chinese population.

Science.gov (United States)

Han, Dong; Qiao, Zhengxue; Chen, Lu; Qiu, Xiaohui; Fang, Deyu; Yang, Xiuxian; Ma, Jingsong; Chen, Mingqi; Yang, Jiarun; Wang, Lin; Zhu, Xiongzhao; Zhang, Congpei; Yang, Yanjie; Pan, Hui

2017-08-01

Recent studies suggest that vascular endothelial growth factor (VEGF) is involved in the development of major depressive disorder. The aim of this study is to investigate the interaction between vascular endothelial growth factor (VEGF) polymorphism (+405G/C, rs2010963) and negative life events in the pathogenesis of major depressive disorder (MDD). DNA genotyping was performed on peripheral blood leukocytes in 274 patients with MDD and 273 age-and sex-matched controls. The frequency and severity of negative life events were assessed by the Life Events Scale (LES). A logistics method was employed to assess the gene-environment interaction (G×E). Differences in rs2010963 genotype distributions were observed between MDD patients and controls. Significant G×E interactions between allelic variation of rs2010963 and negative life events were observed. Individuals carrying the C alleles were susceptible to MDD only when exposed to high-negative life events. These results indicate that interactions between the VEGF rs2010963 polymorphism and environment increases the risk of developing MDD. Copyright © 2017 Elsevier B.V. All rights reserved.

Multiple genetic interaction experiments provide complementary information useful for gene function prediction.

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Magali Michaut

Full Text Available Genetic interactions help map biological processes and their functional relationships. A genetic interaction is defined as a deviation from the expected phenotype when combining multiple genetic mutations. In Saccharomyces cerevisiae, most genetic interactions are measured under a single phenotype - growth rate in standard laboratory conditions. Recently genetic interactions have been collected under different phenotypic readouts and experimental conditions. How different are these networks and what can we learn from their differences? We conducted a systematic analysis of quantitative genetic interaction networks in yeast performed under different experimental conditions. We find that networks obtained using different phenotypic readouts, in different conditions and from different laboratories overlap less than expected and provide significant unique information. To exploit this information, we develop a novel method to combine individual genetic interaction data sets and show that the resulting network improves gene function prediction performance, demonstrating that individual networks provide complementary information. Our results support the notion that using diverse phenotypic readouts and experimental conditions will substantially increase the amount of gene function information produced by genetic interaction screens.

A comparative study on the flow experience in web-based and text-based interaction environments.

Science.gov (United States)

Huang, Li-Ting; Chiu, Chen-An; Sung, Kai; Farn, Cheng-Kiang

2011-01-01

The purpose of this study was to explore a substantial phenomenon related to flow experiences (immersion) in text-based interaction systems. Most previous research emphasizes the effects of challenge/skill, focused attention, telepresence, web characteristics, and systems' interface design on users' flow experiences in online environments. However, text-based interaction systems without telepresence features and web characteristics still seem to create opportunities for flow experience. To explore this phenomenon, this study incorporates subject involvement and interpersonal interaction as critical antecedents into the model of flow experience, as well as considers the existence of telepresence. Results reveal that subject involvement, interpersonal interaction, and interactivity speed are critical to focused attention, which enhances users' immersion. With regard to the effect of telepresence, the perceived attractiveness of the interface is a significant facilitator determining users' immersion in web-based, rather than in text-based, interaction environments. Interactivity speed is unrelated to immersion in both web-based and text-based interaction environments. The influence of interpersonal involvement is diminished in web-based interaction environments. The implications and limitations of this study are discussed.

The Interaction of TXNIP and AFq1 Genes Increases the Susceptibility of Schizophrenia.

Science.gov (United States)

Su, Yousong; Ding, Wenhua; Xing, Mengjuan; Qi, Dake; Li, Zezhi; Cui, Donghong

2017-08-01

Although previous studies showed the reduced risk of cancer in patients with schizophrenia, whether patients with schizophrenia possess genetic factors that also contribute to tumor suppressor is still unknown. In the present study, based on our previous microarray data, we focused on the tumor suppressor genes TXNIP and AF1q, which differentially expressed in patients with schizophrenia. A total of 413 patients and 578 healthy controls were recruited. We found no significant differences in genotype, allele, or haplotype frequencies at the selected five single nucleotide polymorphisms (SNPs) (rs2236566 and rs7211 in TXNIP gene; rs10749659, rs2140709, and rs3738481 in AF1q gene) between patients with schizophrenia and controls. However, we found the association between the interaction of TXNIP and AF1q with schizophrenia by using the MDR method followed by traditional statistical analysis. The best gene-gene interaction model identified was a three-locus model TXNIP (rs2236566, rs7211)-AF1q (rs2140709). After traditional statistical analysis, we found the high-risk genotype combination was rs2236566 (GG)-rs7211(CC)-rs2140709(CC) (OR = 1.35 [1.03-1.76]). The low-risk genotype combination was rs2236566 (GT)-rs7211(CC)-rs2140709(CC) (OR = 0.67 [0.49-0.91]). Our finding suggested statistically significant role of interaction of TXNIP and AF1q polymorphisms (TXNIP-rs2236566, TXNIP-rs7211, and AF1q-rs2769605) in schizophrenia susceptibility.

Interactive learning environments in augmented reality technology

Directory of Open Access Journals (Sweden)

Rafał Wojciechowski

2010-01-01

Full Text Available In this paper, the problem of creation of learning environments based on augmented reality (AR is considered. The concept of AR is presented as a tool for safe and cheap experimental learning. In AR learning environments students may acquire knowledge by personally carrying out experiments on virtual objects by manipulating real objects located in real environments. In the paper, a new approach to creation of interactive educational scenarios, called Augmented Reality Interactive Scenario Modeling (ARISM, is mentioned. In this approach, the process of building learning environments is divided into three stages, each of them performed by users with different technical and domain knowledge. The ARISM approach enables teachers who are not computer science experts to create AR learning environments adapted to the needs of their students.

Gene-environment interaction and male reproductive function

DEFF Research Database (Denmark)

Axelsson, Jonatan; Bonde, Jens Peter; Giwercman, Yvonne L

2010-01-01

As genetic factors can hardly explain the changes taking place during short time spans, environmental and lifestyle-related factors have been suggested as the causes of time-related deterioration of male reproductive function. However, considering the strong heterogeneity of male fecundity between...... that specific genotypes may confer a larger risk of male reproductive disorders following certain exposures. This paper presents a critical review of animal and human evidence on how genes may modify environmental effects on male reproductive function. Some examples have been found that support this mechanism...... of reproduction, namely environmental and lifestyle factors as the cause of sperm DNA damage. It remains to be investigated to what extent such genetic changes, by natural conception or through the use of assisted reproductive techniques, are transmitted to the next generation, thereby causing increased morbidity...

Genome-Wide Association Study (GWAS) and Genome-Wide Environment Interaction Study (GWEIS) of Depressive Symptoms in African American and Hispanic/Latina Women

Science.gov (United States)

Dunn, Erin C.; Wiste, Anna; Radmanesh, Farid; Almli, Lynn M.; Gogarten, Stephanie M.; Sofer, Tamar; Faul, Jessica D.; Kardia, Sharon L.R.; Smith, Jennifer A.; Weir, David R.; Zhao, Wei; Soare, Thomas W.; Mirza, Saira S.; Hek, Karin; Tiemeier, Henning W.; Goveas, Joseph S.; Sarto, Gloria E.; Snively, Beverly M.; Cornelis, Marilyn; Koenen, Karestan C.; Kraft, Peter; Purcell, Shaun; Ressler, Kerry J.; Rosand, Jonathan; Wassertheil-Smoller, Sylvia; Smoller, Jordan W.

2016-01-01

Background Genome-wide association studies (GWAS) have been unable to identify variants linked to depression. We hypothesized that examining depressive symptoms and considering gene-environment interaction (G×E) might improve efficiency for gene discovery. We therefore conducted a GWAS and genome-wide environment interaction study (GWEIS) of depressive symptoms. Methods Using data from the SHARe cohort of the Women’s Health Initiative, comprising African Americans (n=7179) and Hispanics/Latinas (n=3138), we examined genetic main effects and G×E with stressful life events and social support. We also conducted a heritability analysis using genome-wide complex trait analysis (GCTA). Replication was attempted in four independent cohorts. Results No SNPs achieved genome-wide significance for main effects in either discovery sample. The top signals in African Americans were rs73531535 (located 20kb from GPR139, p=5.75×10−8) and rs75407252 (intronic to CACNA2D3, p=6.99×10−7). In Hispanics/Latinas, the top signals were rs2532087 (located 27kb from CD38, p=2.44×10−7) and rs4542757 (intronic to DCC, p=7.31×10−7). In the GWEIS with stressful life events, one interaction signal was genome-wide significant in African Americans (rs4652467; p=4.10×10−10; located 14kb from CEP350). This interaction was not observed in a smaller replication cohort. Although heritability estimates for depressive symptoms and stressful life events were each less than 10%, they were strongly genetically correlated (rG=0.95), suggesting that common variation underlying depressive symptoms and stressful life event exposure, though modest on their own, were highly overlapping in this sample. Conclusions Our results underscore the need for larger samples, more GWEIS, and greater investigation into genetic and environmental determinants of depressive symptoms in minorities. PMID:27038408

Designing persuasive interactive environments : a hands-on workshop to explore interactivity and persuasion in design

NARCIS (Netherlands)

Rozendaal, Marco; Bekker, Tilde; Vermeeren, Arnold; Kanis, Marije; Aprile, Walter; van der Helm, Aadjan; Middendorf, Wouter

2012-01-01

Ambient Intelligent environments are interactive environments that sense human behaviour and can respond intelligently. This workshop explores how interactive environments can be designed with persuasive quality, influencing human experience and behaviour. The workshop follows a

Mining disease genes using integrated protein-protein interaction and gene-gene co-regulation information.

Science.gov (United States)

Li, Jin; Wang, Limei; Guo, Maozu; Zhang, Ruijie; Dai, Qiguo; Liu, Xiaoyan; Wang, Chunyu; Teng, Zhixia; Xuan, Ping; Zhang, Mingming

2015-01-01

In humans, despite the rapid increase in disease-associated gene discovery, a large proportion of disease-associated genes are still unknown. Many network-based approaches have been used to prioritize disease genes. Many networks, such as the protein-protein interaction (PPI), KEGG, and gene co-expression networks, have been used. Expression quantitative trait loci (eQTLs) have been successfully applied for the determination of genes associated with several diseases. In this study, we constructed an eQTL-based gene-gene co-regulation network (GGCRN) and used it to mine for disease genes. We adopted the random walk with restart (RWR) algorithm to mine for genes associated with Alzheimer disease. Compared to the Human Protein Reference Database (HPRD) PPI network alone, the integrated HPRD PPI and GGCRN networks provided faster convergence and revealed new disease-related genes. Therefore, using the RWR algorithm for integrated PPI and GGCRN is an effective method for disease-associated gene mining.

Combining ability × environment interaction and genetic analysis for agronomic traits in safflower (Carthamus tinctorius L.: biplot as a tool for diallel data

Directory of Open Access Journals (Sweden)

Pooran Golkar

2017-09-01

Full Text Available Combining ability × environment interaction is considerable to identify the effect of environment on the combining ability and gene action of the traits to select appropriate parents for safflower hybrid production. The 36 genotype (28 F2 progenies of eight-parent half-diallel crosses across 8 parental genotypes of safflower were studied to investigate the mentioned parameters across different geographical regions of Iran. The results indicated significant differences among parents for general and specific combining ability, except for seeds per capitulum across three environments. The overall results indicated that K21 and Mex.22-191 were excellent parents with greater general combining ability for the improvement of seed yield in safflower. The K21 × Mex.22-191 hybrid could be, therefore, employed for the production of high seed yield in safflower breeding. The estimates of genetic variance components recommended the importance of additive- dominance genetic effects that contributed to variation in yield per plant. Such gene action expression for seed yield needs auxiliary methods based on hybridization and selection for seed yield advancement in safflower.

Genes and Aggressive Behavior: Epigenetic Mechanisms Underlying Individual Susceptibility to Aversive Environments

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Sara Palumbo

2018-06-01

Full Text Available Over the last two decades, the study of the relationship between nature and nurture in shaping human behavior has encountered a renewed interest. Behavioral genetics showed that distinct polymorphisms of genes that code for proteins that control neurotransmitter metabolic and synaptic function are associated with individual vulnerability to aversive experiences, such as stressful and traumatic life events, and may result in an increased risk of developing psychopathologies associated with violence. On the other hand, recent studies indicate that experiencing aversive events modulates gene expression by introducing stable changes to DNA without modifying its sequence, a mechanism known as “epigenetics”. For example, experiencing adversities during periods of maximal sensitivity to the environment, such as prenatal life, infancy and early adolescence, may introduce lasting epigenetic marks in genes that affect maturational processes in brain, thus favoring the emergence of dysfunctional behaviors, including exaggerate aggression in adulthood. The present review discusses data from recent research, both in humans and animals, concerning the epigenetic regulation of four genes belonging to the neuroendocrine, serotonergic and oxytocinergic pathways—Nuclear receptor subfamily 3-group C-member 1 (NR3C1, oxytocin receptor (OXTR, solute carrier-family 6 member 4 (SLC6A4 and monoamine oxidase A (MAOA—and their role in modulating vulnerability to proactive and reactive aggressive behavior. Behavioral genetics and epigenetics are shedding a new light on the fine interaction between genes and environment, by providing a novel tool to understand the molecular events that underlie aggression. Overall, the findings from these studies carry important implications not only for neuroscience, but also for social sciences, including ethics, philosophy and law.

Large-scale extraction of gene interactions from full-text literature using DeepDive.

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Mallory, Emily K; Zhang, Ce; Ré, Christopher; Altman, Russ B

2016-01-01

A complete repository of gene-gene interactions is key for understanding cellular processes, human disease and drug response. These gene-gene interactions include both protein-protein interactions and transcription factor interactions. The majority of known interactions are found in the biomedical literature. Interaction databases, such as BioGRID and ChEA, annotate these gene-gene interactions; however, curation becomes difficult as the literature grows exponentially. DeepDive is a trained system for extracting information from a variety of sources, including text. In this work, we used DeepDive to extract both protein-protein and transcription factor interactions from over 100,000 full-text PLOS articles. We built an extractor for gene-gene interactions that identified candidate gene-gene relations within an input sentence. For each candidate relation, DeepDive computed a probability that the relation was a correct interaction. We evaluated this system against the Database of Interacting Proteins and against randomly curated extractions. Our system achieved 76% precision and 49% recall in extracting direct and indirect interactions involving gene symbols co-occurring in a sentence. For randomly curated extractions, the system achieved between 62% and 83% precision based on direct or indirect interactions, as well as sentence-level and document-level precision. Overall, our system extracted 3356 unique gene pairs using 724 features from over 100,000 full-text articles. Application source code is publicly available at https://github.com/edoughty/deepdive_genegene_app russ.altman@stanford.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Changing expression of vertebrate immunity genes in an anthropogenic environment: a controlled experiment.

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Hablützel, Pascal I; Brown, Martha; Friberg, Ida M; Jackson, Joseph A

2016-09-01

The effect of anthropogenic environments on the function of the vertebrate immune system is a problem of general importance. For example, it relates to the increasing rates of immunologically-based disease in modern human populations and to the desirability of identifying optimal immune function in domesticated animals. Despite this importance, our present understanding is compromised by a deficit of experimental studies that make adequately matched comparisons between wild and captive vertebrates. We transferred post-larval fishes (three-spined sticklebacks), collected in the wild, to an anthropogenic (captive) environment. We then monitored, over 11 months, how the systemic expression of immunity genes changed in comparison to cohort-matched wild individuals in the originator population (total n = 299). We found that a range of innate (lyz, defbl2, il1r-like, tbk1) and adaptive (cd8a, igmh) immunity genes were up-regulated in captivity, accompanied by an increase in expression of the antioxidant enzyme, gpx4a. For some genes previously known to show seasonality in the wild, this appeared to be reduced in captive fishes. Captive fishes tended to express immunity genes, including igzh, foxp3b, lyz, defbl2, and il1r-like, more variably. Furthermore, although gene co-expression patterns (analyzed through gene-by-gene correlations and mutual information theory based networks) shared common structure in wild and captive fishes, there was also significant divergence. For one gene in particular, defbl2, high expression was associated with adverse health outcomes in captive fishes. Taken together, these results demonstrate widespread regulatory changes in the immune system in captive populations, and that the expression of immunity genes is more constrained in the wild. An increase in constitutive systemic immune activity, such as we observed here, may alter the risk of immunopathology and contribute to variance in health in vertebrate populations exposed to

Artificial neural network inference (ANNI: a study on gene-gene interaction for biomarkers in childhood sarcomas.

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Dong Ling Tong

Full Text Available OBJECTIVE: To model the potential interaction between previously identified biomarkers in children sarcomas using artificial neural network inference (ANNI. METHOD: To concisely demonstrate the biological interactions between correlated genes in an interaction network map, only 2 types of sarcomas in the children small round blue cell tumors (SRBCTs dataset are discussed in this paper. A backpropagation neural network was used to model the potential interaction between genes. The prediction weights and signal directions were used to model the strengths of the interaction signals and the direction of the interaction link between genes. The ANN model was validated using Monte Carlo cross-validation to minimize the risk of over-fitting and to optimize generalization ability of the model. RESULTS: Strong connection links on certain genes (TNNT1 and FNDC5 in rhabdomyosarcoma (RMS; FCGRT and OLFM1 in Ewing's sarcoma (EWS suggested their potency as central hubs in the interconnection of genes with different functionalities. The results showed that the RMS patients in this dataset are likely to be congenital and at low risk of cardiomyopathy development. The EWS patients are likely to be complicated by EWS-FLI fusion and deficiency in various signaling pathways, including Wnt, Fas/Rho and intracellular oxygen. CONCLUSIONS: The ANN network inference approach and the examination of identified genes in the published literature within the context of the disease highlights the substantial influence of certain genes in sarcomas.

When chocolate seeking becomes compulsion: gene-environment interplay.

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Enrico Patrono

Full Text Available Eating disorders appear to be caused by a complex interaction between environmental and genetic factors, and compulsive eating in response to adverse circumstances characterizes many eating disorders.We compared compulsion-like eating in the form of conditioned suppression of palatable food-seeking in adverse situations in stressed C57BL/6J and DBA/2J mice, two well-characterized inbred strains, to determine the influence of gene-environment interplay on this behavioral phenotype. Moreover, we tested the hypothesis that low accumbal D2 receptor (R availability is a genetic risk factor of food compulsion-like behavior and that environmental conditions that induce compulsive eating alter D2R expression in the striatum. To this end, we measured D1R and D2R expression in the striatum and D1R, D2R and α1R levels in the medial prefrontal cortex, respectively, by western blot.Exposure to environmental conditions induces compulsion-like eating behavior, depending on genetic background. This behavioral pattern is linked to decreased availability of accumbal D2R. Moreover, exposure to certain environmental conditions upregulates D2R and downregulates α1R in the striatum and medial prefrontal cortex, respectively, of compulsive animals. These findings confirm the function of gene-environment interplay in the manifestation of compulsive eating and support the hypothesis that low accumbal D2R availability is a "constitutive" genetic risk factor for compulsion-like eating behavior. Finally, D2R upregulation and α1R downregulation in the striatum and medial prefrontal cortex, respectively, are potential neuroadaptive responses that parallel the shift from motivated to compulsive eating.

The Tangled Tale of Genes and Environment: Moore's The Dependent Gene: The Fallacy of “nature VS. Nurture”

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Schneider, Susan M

2007-01-01

Nature–nurture views that smack of genetic determinism remain prevalent. Yet, the increasing knowledge base shows ever more clearly that environmental factors and genes form a fully interactional system at all levels. Moore's book covers the major topics of discovery and dispute, including behavior genetics and the twin studies, developmental psychobiology, and developmental systems theory. Knowledge of this larger life-sciences context for behavior principles will become increasingly important as the full complexity of gene–environment relations is revealed. Behavior analysis both contributes to and gains from the larger battle for the recognition of how nature and nurture really work.

CASES ON COLLABORATION IN VIRTUAL LEARNIONG ENVIRONMENTS: Processes and Interactions

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Reviewed by Yasin OZARSLAN

2010-01-01

Full Text Available Collaboration in Virtual Learning Environment brings meaningful learning interactions between learners in virtual environments. This book collects case studies of collaborative virtual learning environments focusing on the nature of human interactions in virtual spaces and defining the types and qualities of learning processes in these spaces from the perspectives of learners, teachers, designers, and professional and academic developers in various disciplines, learning communities and universities from around the world. This book addresses the research cases on experiences, implementations, and applications of virtual learning environments.The book's broader audience is anyone who is interested in areas such as collaborative virtual learning environments, interactive technologies and virtual communities, social interaction and social competence, distance education and collaborative learning. The book is edited by Donna Russell who is an Assistant Professor at the University of Missouri-Kansas City and co-owner of Arete‘ Consulting, LLC. It is consisted of 358 pages covering 19 articles and provides information about context for characteristics and implications of the varied virtual learning environments. Topics covered in this book are argumentative interactions and learning, collaborative learning and work in digital libraries, collaborative virtual learning environments , digital communities to enhance retention, distance education ,interactive technologies and virtual communities, massively multi-user virtual environments, online graduate community, online training programs, social interaction and social competence and virtual story-worlds.

Computational modeling identifies key gene regulatory interactions underlying phenobarbital-mediated tumor promotion

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Luisier, Raphaëlle; Unterberger, Elif B.; Goodman, Jay I.; Schwarz, Michael; Moggs, Jonathan; Terranova, Rémi; van Nimwegen, Erik

2014-01-01

Gene regulatory interactions underlying the early stages of non-genotoxic carcinogenesis are poorly understood. Here, we have identified key candidate regulators of phenobarbital (PB)-mediated mouse liver tumorigenesis, a well-characterized model of non-genotoxic carcinogenesis, by applying a new computational modeling approach to a comprehensive collection of in vivo gene expression studies. We have combined our previously developed motif activity response analysis (MARA), which models gene expression patterns in terms of computationally predicted transcription factor binding sites with singular value decomposition (SVD) of the inferred motif activities, to disentangle the roles that different transcriptional regulators play in specific biological pathways of tumor promotion. Furthermore, transgenic mouse models enabled us to identify which of these regulatory activities was downstream of constitutive androstane receptor and β-catenin signaling, both crucial components of PB-mediated liver tumorigenesis. We propose novel roles for E2F and ZFP161 in PB-mediated hepatocyte proliferation and suggest that PB-mediated suppression of ESR1 activity contributes to the development of a tumor-prone environment. Our study shows that combining MARA with SVD allows for automated identification of independent transcription regulatory programs within a complex in vivo tissue environment and provides novel mechanistic insights into PB-mediated hepatocarcinogenesis. PMID:24464994

Expression and clinical significance of Pax6 gene in retinoblastoma

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Hai-Dong Huang

2013-07-01

Full Text Available AIM: To discuss the expression and clinical significance of Pax6 gene in retinoblastoma(Rb. METHODS: Totally 15 cases of fresh Rb organizations were selected as observation group and 15 normal retinal organizations as control group. Western-Blot and reverse transcriptase polymerase chain reaction(RT-PCRmethods were used to detect Pax6 protein and Pax6 mRNA expressions of the normal retina organizations and Rb organizations. At the same time, Western Blot method was used to detect the Pax6 gene downstream MATH5 and BRN3b differentiation gene protein level expression. After the comparison between two groups, the expression and clinical significance of Pax6 gene in Rb were discussed. RESULTS: In the observation group, average value of mRNA expression of Pax6 gene was 0.99±0.03; average value of Pax6 gene protein expression was 2.07±0.15; average value of BRN3b protein expression was 0.195±0.016; average value of MATH5 protein expression was 0.190±0.031. They were significantly higher than the control group, and the differences were statistically significant(PCONCLUSION: Abnormal expression of Pax6 gene is likely to accelerate the occurrence of Rb.

Chemical compounds from anthropogenic environment and immune evasion mechanisms: potential interactions

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Kravchenko, Julia; Corsini, Emanuela; Williams, Marc A.; Decker, William; Manjili, Masoud H.; Otsuki, Takemi; Singh, Neetu; Al-Mulla, Faha; Al-Temaimi, Rabeah; Amedei, Amedeo; Colacci, Anna Maria; Vaccari, Monica; Mondello, Chiara; Scovassi, A. Ivana; Raju, Jayadev; Hamid, Roslida A.; Memeo, Lorenzo; Forte, Stefano; Roy, Rabindra; Woodrick, Jordan; Salem, Hosni K.; Ryan, Elizabeth P.; Brown, Dustin G.; Lowe, Leroy; Lyerly, H.Kim

2015-01-01

An increasing number of studies suggest an important role of host immunity as a barrier to tumor formation and progression. Complex mechanisms and multiple pathways are involved in evading innate and adaptive immune responses, with a broad spectrum of chemicals displaying the potential to adversely influence immunosurveillance. The evaluation of the cumulative effects of low-dose exposures from the occupational and natural environment, especially if multiple chemicals target the same gene(s) or pathway(s), is a challenge. We reviewed common environmental chemicals and discussed their potential effects on immunosurveillance. Our overarching objective was to review related signaling pathways influencing immune surveillance such as the pathways involving PI3K/Akt, chemokines, TGF-β, FAK, IGF-1, HIF-1α, IL-6, IL-1α, CTLA-4 and PD-1/PDL-1 could individually or collectively impact immunosurveillance. A number of chemicals that are common in the anthropogenic environment such as fungicides (maneb, fluoxastrobin and pyroclostrobin), herbicides (atrazine), insecticides (pyridaben and azamethiphos), the components of personal care products (triclosan and bisphenol A) and diethylhexylphthalate with pathways critical to tumor immunosurveillance. At this time, these chemicals are not recognized as human carcinogens; however, it is known that they these chemicalscan simultaneously persist in the environment and appear to have some potential interfere with the host immune response, therefore potentially contributing to promotion interacting with of immune evasion mechanisms, and promoting subsequent tumor growth and progression. PMID:26002081

Resonance interaction energy between two entangled atoms in a photonic bandgap environment.

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Notararigo, Valentina; Passante, Roberto; Rizzuto, Lucia

2018-03-26

We consider the resonance interaction energy between two identical entangled atoms, where one is in the excited state and the other in the ground state. They interact with the quantum electromagnetic field in the vacuum state and are placed in a photonic-bandgap environment with a dispersion relation quadratic near the gap edge and linear for low frequencies, while the atomic transition frequency is assumed to be inside the photonic gap and near its lower edge. This problem is strictly related to the coherent resonant energy transfer between atoms in external environments. The analysis involves both an isotropic three-dimensional model and the one-dimensional case. The resonance interaction asymptotically decays faster with distance compared to the free-space case, specifically as 1/r 2 compared to the 1/r free-space dependence in the three-dimensional case, and as 1/r compared to the oscillatory dependence in free space for the one-dimensional case. Nonetheless, the interaction energy remains significant and much stronger than dispersion interactions between atoms. On the other hand, spontaneous emission is strongly suppressed by the environment and the correlated state is thus preserved by the spontaneous-decay decoherence effects. We conclude that our configuration is suitable for observing the elusive quantum resonance interaction between entangled atoms.

Genomewide Expression and Functional Interactions of Genes under Drought Stress in Maize

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Nepolean Thirunavukkarasu

2017-01-01

Full Text Available A genomewide transcriptome assay of two subtropical genotypes of maize was used to observe the expression of genes at seedling stage of drought stress. The number of genes expressed differentially was greater in HKI1532 (a drought tolerant genotype than in PC3 (a drought sensitive genotype, indicating primary differences at the transcriptional level in stress tolerance. The global coexpression networks of the two genotypes differed significantly with respect to the number of modules and the coexpression pattern within the modules. A total of 174 drought-responsive genes were selected from HKI1532, and their coexpression network revealed key correlations between different adaptive pathways, each cluster of the network representing a specific biological function. Transcription factors related to ABA-dependent stomatal closure, signalling, and phosphoprotein cascades work in concert to compensate for reduced photosynthesis. Under stress, water balance was maintained by coexpression of the genes involved in osmotic adjustments and transporter proteins. Metabolism was maintained by the coexpression of genes involved in cell wall modification and protein and lipid metabolism. The interaction of genes involved in crucial biological functions during stress was identified and the results will be useful in targeting important gene interactions to understand drought tolerance in greater detail.

Bayesian logistic regression in detection of gene-steroid interaction for cancer at PDLIM5 locus.

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Wang, Ke-Sheng; Owusu, Daniel; Pan, Yue; Xie, Changchun

2016-06-01

The PDZ and LIM domain 5 (PDLIM5) gene may play a role in cancer, bipolar disorder, major depression, alcohol dependence and schizophrenia; however, little is known about the interaction effect of steroid and PDLIM5 gene on cancer. This study examined 47 single-nucleotide polymorphisms (SNPs) within the PDLIM5 gene in the Marshfield sample with 716 cancer patients (any diagnosed cancer, excluding minor skin cancer) and 2848 noncancer controls. Multiple logistic regression model in PLINK software was used to examine the association of each SNP with cancer. Bayesian logistic regression in PROC GENMOD in SAS statistical software, ver. 9.4 was used to detect gene- steroid interactions influencing cancer. Single marker analysis using PLINK identified 12 SNPs associated with cancer (Plogistic regression in PROC GENMOD showed that both rs6532496 and rs951613 revealed strong gene-steroid interaction effects (OR=2.18, 95% CI=1.31-3.63 with P = 2.9 × 10⁻³ for rs6532496 and OR=2.07, 95% CI=1.24-3.45 with P = 5.43 × 10⁻³ for rs951613, respectively). Results from Bayesian logistic regression showed stronger interaction effects (OR=2.26, 95% CI=1.2-3.38 for rs6532496 and OR=2.14, 95% CI=1.14-3.2 for rs951613, respectively). All the 12 SNPs associated with cancer revealed significant gene-steroid interaction effects (P logistic regression and OR=2.59, 95% CI=1.4-3.97 from Bayesian logistic regression; respectively). This study provides evidence of common genetic variants within the PDLIM5 gene and interactions between PLDIM5 gene polymorphisms and steroid use influencing cancer.

[Analytic methods for seed models with genotype x environment interactions].

Science.gov (United States)

Zhu, J

1996-01-01

Genetic models with genotype effect (G) and genotype x environment interaction effect (GE) are proposed for analyzing generation means of seed quantitative traits in crops. The total genetic effect (G) is partitioned into seed direct genetic effect (G0), cytoplasm genetic of effect (C), and maternal plant genetic effect (Gm). Seed direct genetic effect (G0) can be further partitioned into direct additive (A) and direct dominance (D) genetic components. Maternal genetic effect (Gm) can also be partitioned into maternal additive (Am) and maternal dominance (Dm) genetic components. The total genotype x environment interaction effect (GE) can also be partitioned into direct genetic by environment interaction effect (G0E), cytoplasm genetic by environment interaction effect (CE), and maternal genetic by environment interaction effect (GmE). G0E can be partitioned into direct additive by environment interaction (AE) and direct dominance by environment interaction (DE) genetic components. GmE can also be partitioned into maternal additive by environment interaction (AmE) and maternal dominance by environment interaction (DmE) genetic components. Partitions of genetic components are listed for parent, F1, F2 and backcrosses. A set of parents, their reciprocal F1 and F2 seeds is applicable for efficient analysis of seed quantitative traits. MINQUE(0/1) method can be used for estimating variance and covariance components. Unbiased estimation for covariance components between two traits can also be obtained by the MINQUE(0/1) method. Random genetic effects in seed models are predictable by the Adjusted Unbiased Prediction (AUP) approach with MINQUE(0/1) method. The jackknife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects, which can be further used in a t-test for parameter. Unbiasedness and efficiency for estimating variance components and predicting genetic effects are tested by

A functional polymorphism in a serotonin transporter gene (5-HTTLPR) interacts with 9/11 to predict gun-carrying behavior.

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Barnes, J C; Beaver, Kevin M; Boutwell, Brian B

2013-01-01

On September 11, 2001, one of the deadliest terrorist attacks in US history took place on American soil and people around the world were impacted in myriad ways. Building on prior literature which suggests individuals are more likely to purchase a gun for self-protection if they are fearful of being victimized, the authors hypothesized that the terrorist attacks of 9/11 would lead to an increase in gun carrying among US residents. At the same time, a line of research has shown that a polymorphism in the 5-HTT gene (i.e., 5-HTTLPR) interacts with environmental stressors to predict a range of psychopathologies and behaviors. Thus, it was hypothesized that 9/11 and 5-HTTLPR would interact to predict gun carrying. The results supported both hypotheses by revealing a positive association between 9/11 and gun carrying (b = .426, odds ratio = 1.531, standard error for b = .194, z = 2.196, p = .028) in the full sample of respondents (n = 15,052) and a statistically significant interaction between 9/11 and 5-HTTLPR in the prediction of gun carrying (b = -1.519, odds ratio = .219, standard error for b = .703, z = -2.161, p = .031) in the genetic subsample of respondents (n = 2,350). This is one of the first studies to find an association between 9/11 and gun carrying and, more importantly, is the first study to report a gene-environment interaction (GxE) between a measured gene and a terrorist attack.

Social Interaction Development through Immersive Virtual Environments

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Beach, Jason; Wendt, Jeremy

2014-01-01

The purpose of this pilot study was to determine if participants could improve their social interaction skills by participating in a virtual immersive environment. The participants used a developing virtual reality head-mounted display to engage themselves in a fully-immersive environment. While in the environment, participants had an opportunity…

46 CFR 4.03-65 - Significant harm to the environment.

Science.gov (United States)

2010-10-01

... 46 Shipping 1 2010-10-01 2010-10-01 false Significant harm to the environment. 4.03-65 Section 4... MARINE CASUALTIES AND INVESTIGATIONS Definitions § 4.03-65 Significant harm to the environment. Significant harm to the environment means— (a) In the navigable waters of the United States, a discharge of...

Gene expression results in lipopolysaccharide-stimulated monocytes depend significantly on the choice of reference genes

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Øvstebø Reidun

2010-05-01

Full Text Available Abstract Background Gene expression in lipopolysaccharide (LPS-stimulated monocytes is mainly studied by quantitative real-time reverse transcription PCR (RT-qPCR using GAPDH (glyceraldehyde 3-phosphate dehydrogenase or ACTB (beta-actin as reference gene for normalization. Expression of traditional reference genes has been shown to vary substantially under certain conditions leading to invalid results. To investigate whether traditional reference genes are stably expressed in LPS-stimulated monocytes or if RT-qPCR results are dependent on the choice of reference genes, we have assessed and evaluated gene expression stability of twelve candidate reference genes in this model system. Results Twelve candidate reference genes were quantified by RT-qPCR in LPS-stimulated, human monocytes and evaluated using the programs geNorm, Normfinder and BestKeeper. geNorm ranked PPIB (cyclophilin B, B2M (beta-2-microglobulin and PPIA (cyclophilin A as the best combination for gene expression normalization in LPS-stimulated monocytes. Normfinder suggested TBP (TATA-box binding protein and B2M as the best combination. Compared to these combinations, normalization using GAPDH alone resulted in significantly higher changes of TNF-α (tumor necrosis factor-alpha and IL10 (interleukin 10 expression. Moreover, a significant difference in TNF-α expression between monocytes stimulated with equimolar concentrations of LPS from N. meningitides and E. coli, respectively, was identified when using the suggested combinations of reference genes for normalization, but stayed unrecognized when employing a single reference gene, ACTB or GAPDH. Conclusions Gene expression levels in LPS-stimulated monocytes based on RT-qPCR results differ significantly when normalized to a single gene or a combination of stably expressed reference genes. Proper evaluation of reference gene stabiliy is therefore mandatory before reporting RT-qPCR results in LPS-stimulated monocytes.

Genes related to antioxidant metabolism are involved in Methylobacterium mesophilicum-soybean interaction.

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Araújo, Welington Luiz; Santos, Daiene Souza; Dini-Andreote, Francisco; Salgueiro-Londoño, Jennifer Katherine; Camargo-Neves, Aline Aparecida; Andreote, Fernando Dini; Dourado, Manuella Nóbrega

2015-10-01

The genus Methylobacterium is composed of pink-pigmented methylotrophic bacterial species that are widespread in natural environments, such as soils, stream water and plants. When in association with plants, this genus colonizes the host plant epiphytically and/or endophytically. This association is known to promote plant growth, induce plant systemic resistance and inhibit plant infection by phytopathogens. In the present study, we focused on evaluating the colonization of soybean seedling-roots by Methylobacterium mesophilicum strain SR1.6/6. We focused on the identification of the key genes involved in the initial step of soybean colonization by methylotrophic bacteria, which includes the plant exudate recognition and adaptation by planktonic bacteria. Visualization by scanning electron microscopy revealed that M. mesophilicum SR1.6/6 colonizes soybean roots surface effectively at 48 h after inoculation, suggesting a mechanism for root recognition and adaptation before this period. The colonization proceeds by the development of a mature biofilm on roots at 96 h after inoculation. Transcriptomic analysis of the planktonic bacteria (with plant) revealed the expression of several genes involved in membrane transport, thus confirming an initial metabolic activation of bacterial responses when in the presence of plant root exudates. Moreover, antioxidant genes were mostly expressed during the interaction with the plant exudates. Further evaluation of stress- and methylotrophic-related genes expression by qPCR showed that glutathione peroxidase and glutathione synthetase genes were up-regulated during the Methylobacterium-soybean interaction. These findings support that glutathione (GSH) is potentially a key molecule involved in cellular detoxification during plant root colonization. In addition to methylotrophic metabolism, antioxidant genes, mainly glutathione-related genes, play a key role during soybean exudate recognition and adaptation, the first step in

Gene-Environment Interaction and Breast Cancer on Long Island, NY

National Research Council Canada - National Science Library

Teitelbaum, Susan

2006-01-01

...), a large population-based, case-control study of the environment and breast cancer. Participants completed an in-person interviewer-administered interview, donated blood and urine samples, and had home environment samples...

You've gotta be lucky: Coverage and the elusive gene-gene interaction.

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Reimherr, Matthew; Nicolae, Dan L

2011-01-01

Genome-wide association studies (GWAS) have led to a large number of single-SNP association findings, but there has been, so far, no investigation resulting in the discovery of a replicable gene-gene interaction. In this paper, we examine some of the possible explanations for the lack of findings, and argue that coverage of causal variation not only has a large effect on the loss in power, but that the effect is larger than in the single-SNP analyses. We show that the product of linkage disequilibrium measures, r², between causal and tested SNPs offers a good approximation to the loss in efficiency as defined by the ratio of sample sizes that lead to similar power. We also demonstrate that, in addition to the huge search space, the loss in power due to coverage when using commercially available platforms makes the search for gene-gene interactions daunting. © 2010 The Authors Annals of Human Genetics © 2010 Blackwell Publishing Ltd/University College London.

Designing learning environments to teach interactive Quantum Physics

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Gómez Puente, Sonia M.; Swagten, Henk J. M.

2012-10-01

This study aims at describing and analysing systematically an interactive learning environment designed to teach Quantum Physics, a second-year physics course. The instructional design of Quantum Physics is a combination of interactive lectures (using audience response systems), tutorials and self-study in unit blocks, carried out with small groups. Individual formative feedback was introduced as a rapid assessment tool to provide an overview on progress and identify gaps by means of questioning students at three levels: conceptual; prior knowledge; homework exercises. The setup of Quantum Physics has been developed as a result of several loops of adjustments and improvements from a traditional-like type of teaching to an interactive classroom. Results of this particular instructional arrangement indicate significant gains in students' achievements in comparison with the traditional structure of this course, after recent optimisation steps such as the implementation of an individual feedback system.

Gene-Gene Interactions in the Folate Metabolic Pathway and the Risk of Conotruncal Heart Defects

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Philip J. Lupo

2010-01-01

Full Text Available Conotruncal and related heart defects (CTRD are common, complex malformations. Although there are few established risk factors, there is evidence that genetic variation in the folate metabolic pathway influences CTRD risk. This study was undertaken to assess the association between inherited (i.e., case and maternal gene-gene interactions in this pathway and the risk of CTRD. Case-parent triads (n=727, ascertained from the Children's Hospital of Philadelphia, were genotyped for ten functional variants of nine folate metabolic genes. Analyses of inherited genotypes were consistent with the previously reported association between MTHFR A1298C and CTRD (adjusted P=.02, but provided no evidence that CTRD was associated with inherited gene-gene interactions. Analyses of the maternal genotypes provided evidence of a MTHFR C677T/CBS 844ins68 interaction and CTRD risk (unadjusted P=.02. This association is consistent with the effects of this genotype combination on folate-homocysteine biochemistry but remains to be confirmed in independent study populations.

Trends in gastrectomy and ADH1B and ALDH2 genotypes in Japanese alcoholic men and their gene-gastrectomy, gene-gene and gene-age interactions for risk of alcoholism.

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Yokoyama, Akira; Yokoyama, Tetsuji; Matsui, Toshifumi; Mizukami, Takeshi; Kimura, Mitsuru; Matsushita, Sachio; Higuchi, Susumu; Maruyama, Katsuya

2013-01-01

The life-time drinking profiles of Japanese alcoholics have shown that gastrectomy increases susceptibility to alcoholism. We investigated the trends in gastrectomy and alcohol dehydrogenase-1B (ADH1B) and aldehyde dehydrogenase-2 (ALDH2) genotypes and their interactions in alcoholics. This survey was conducted on 4879 Japanese alcoholic men 40 years of age or older who underwent routine gastrointestinal endoscopic screening during the period 1996-2010. ADH1B/ALDH2 genotyping was performed in 3702 patients. A history of gastrectomy was found in 508 (10.4%) patients. The reason for the gastrectomy was peptic ulcer in 317 patients and gastric cancer in 187 patients. The frequency of gastrectomy had gradually decreased from 13.3% in 1996-2000 to 10.5% in 2001-2005 and to 7.8% in 2006-2010 (P alcoholism-susceptibility genotypes, ADH1B*1/*1 and ALDH2*1/*1, modestly but significantly tended not to occur in the same individual (P = 0.026). The frequency of ADH1B*1/*1 decreased with ascending age groups. The high frequency of history of gastrectomy suggested that gastrectomy is still a risk factor for alcoholism, although the percentage decreased during the period. The alcoholism-susceptibility genotype ADH1B*1/*1 was less frequent in the gastrectomy group, suggesting a competitive gene-gastrectomy interaction for alcoholism. A gene-gene interaction and gene-age interactions regarding the ADH1B genotype were observed.

Human-Computer Interaction in Smart Environments

Science.gov (United States)

Paravati, Gianluca; Gatteschi, Valentina

2015-01-01

Here, we provide an overview of the content of the Special Issue on “Human-computer interaction in smart environments”. The aim of this Special Issue is to highlight technologies and solutions encompassing the use of mass-market sensors in current and emerging applications for interacting with Smart Environments. Selected papers address this topic by analyzing different interaction modalities, including hand/body gestures, face recognition, gaze/eye tracking, biosignal analysis, speech and activity recognition, and related issues.

Gene-environment interaction in atopic diseases

DEFF Research Database (Denmark)

Kahr, Niklas; Naeser, Vibeke; Stensballe, Lone Graff

2015-01-01

INTRODUCTION: The development of atopic diseases early in life suggests an important role of perinatal risk factors. OBJECTIVES: To study whether early-life exposures modify the genetic influence on atopic diseases in a twin population. METHODS: Questionnaire data on atopic diseases from 850....... Significant predictors of atopic diseases were identified with logistic regression and subsequently tested for genetic effect modification using variance components analysis. RESULTS: After multivariable adjustment, prematurity (gestational age below 32 weeks) [odds ratio (OR) = 1.93, confidence interval (CI...... stratified by exposure status showed no significant change in the heritability of asthma according to the identified risk factors. CONCLUSION: In this population-based study of children, there was no evidence of genetic effect modification of atopic diseases by several identified early-life risk factors...

The role of gene-environment interplay in occupational and environmental diseases: current concepts and knowledge gaps.

Science.gov (United States)

Kwo, Elizabeth; Christiani, David

2017-03-01

The interplay between genetic susceptibilities and environmental exposures in the pathogenesis of a variety of diseases is an area of increased scientific, epidemiologic, and social interest. Given the variation in methodologies used in the field, this review aims to create a framework to help understand occupational exposures as they currently exist and provide a foundation for future inquiries into the biological mechanisms of the gene-environment interactions. Understanding of this complex interplay will be important in the context of occupational health, given the public health concerns surrounding a variety of occupational exposures. Studies found evidence that suggest genetics influence the progression of disease postberyllium exposure through genetically encoded major histocompatibility complex, class II, DP alpha 2 (HLA-DP2)-peptide complexes as it relates to T-helper cells. This was characterized at the molecular level by the accumulation of Be-responsive CD4 T cells in the lung, which resulted in posttranslational change in the HLA-DPB1 complex. These studies provide important evidence of gene-environment association, and many provide insights into specific pathogenic mechanisms. The following includes a review of the literature regarding gene-environment associations with a focus on pulmonary diseases as they relate to the workplace.

Effects of circadian clock genes and health-related behavior on metabolic syndrome in a Taiwanese population: Evidence from association and interaction analysis.

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Eugene Lin

Full Text Available Increased risk of developing metabolic syndrome (MetS has been associated with the circadian clock genes. In this study, we assessed whether 29 circadian clock-related genes (including ADCYAP1, ARNTL, ARNTL2, BHLHE40, CLOCK, CRY1, CRY2, CSNK1D, CSNK1E, GSK3B, HCRTR2, KLF10, NFIL3, NPAS2, NR1D1, NR1D2, PER1, PER2, PER3, REV1, RORA, RORB, RORC, SENP3, SERPINE1, TIMELESS, TIPIN, VIP, and VIPR2 are associated with MetS and its individual components independently and/or through complex interactions in a Taiwanese population. We also analyzed the interactions between environmental factors and these genes in influencing MetS and its individual components. A total of 3,000 Taiwanese subjects from the Taiwan Biobank were assessed in this study. Metabolic traits such as waist circumference, triglyceride, high-density lipoprotein cholesterol, systolic and diastolic blood pressure, and fasting glucose were measured. Our data showed a nominal association of MetS with several single nucleotide polymorphisms (SNPs in five key circadian clock genes including ARNTL, GSK3B, PER3, RORA, and RORB; but none of these SNPs persisted significantly after performing Bonferroni correction. Moreover, we identified the effect of GSK3B rs2199503 on high fasting glucose (P = 0.0002. Additionally, we found interactions among the ARNTL rs10832020, GSK3B rs2199503, PER3 rs10746473, RORA rs8034880, and RORB rs972902 SNPs influenced MetS (P < 0.001 ~ P = 0.002. Finally, we investigated the influence of interactions between ARNTL rs10832020, GSK3B rs2199503, PER3 rs10746473, and RORB rs972902 with environmental factors such as alcohol consumption, smoking status, and physical activity on MetS and its individual components (P < 0.001 ~ P = 0.002. Our study indicates that circadian clock genes such as ARNTL, GSK3B, PER3, RORA, and RORB genes may contribute to the risk of MetS independently as well as through gene-gene and gene-environment interactions.

Effect of the environment on horizontal gene transfer between bacteria and archaea.

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Fuchsman, Clara A; Collins, Roy Eric; Rocap, Gabrielle; Brazelton, William J

2017-01-01

Horizontal gene transfer, the transfer and incorporation of genetic material between different species of organisms, has an important but poorly quantified role in the adaptation of microbes to their environment. Previous work has shown that genome size and the number of horizontally transferred genes are strongly correlated. Here we consider how genome size confuses the quantification of horizontal gene transfer because the number of genes an organism accumulates over time depends on its evolutionary history and ecological context (e.g., the nutrient regime for which it is adapted). We investigated horizontal gene transfer between archaea and bacteria by first counting reciprocal BLAST hits among 448 bacterial and 57 archaeal genomes to find shared genes. Then we used the DarkHorse algorithm, a probability-based, lineage-weighted method (Podell & Gaasterland, 2007), to identify potential horizontally transferred genes among these shared genes. By removing the effect of genome size in the bacteria, we have identified bacteria with unusually large numbers of shared genes with archaea for their genome size. Interestingly, archaea and bacteria that live in anaerobic and/or high temperature conditions are more likely to share unusually large numbers of genes. However, high salt was not found to significantly affect the numbers of shared genes. Numbers of shared (genome size-corrected, reciprocal BLAST hits) and transferred genes (identified by DarkHorse) were strongly correlated. Thus archaea and bacteria that live in anaerobic and/or high temperature conditions are more likely to share horizontally transferred genes. These horizontally transferred genes are over-represented by genes involved in energy conversion as well as the transport and metabolism of inorganic ions and amino acids. Anaerobic and thermophilic bacteria share unusually large numbers of genes with archaea. This is mainly due to horizontal gene transfer of genes from the archaea to the bacteria. In

Effect of the environment on horizontal gene transfer between bacteria and archaea

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Clara A. Fuchsman

2017-09-01

Full Text Available Background Horizontal gene transfer, the transfer and incorporation of genetic material between different species of organisms, has an important but poorly quantified role in the adaptation of microbes to their environment. Previous work has shown that genome size and the number of horizontally transferred genes are strongly correlated. Here we consider how genome size confuses the quantification of horizontal gene transfer because the number of genes an organism accumulates over time depends on its evolutionary history and ecological context (e.g., the nutrient regime for which it is adapted. Results We investigated horizontal gene transfer between archaea and bacteria by first counting reciprocal BLAST hits among 448 bacterial and 57 archaeal genomes to find shared genes. Then we used the DarkHorse algorithm, a probability-based, lineage-weighted method (Podell & Gaasterland, 2007, to identify potential horizontally transferred genes among these shared genes. By removing the effect of genome size in the bacteria, we have identified bacteria with unusually large numbers of shared genes with archaea for their genome size. Interestingly, archaea and bacteria that live in anaerobic and/or high temperature conditions are more likely to share unusually large numbers of genes. However, high salt was not found to significantly affect the numbers of shared genes. Numbers of shared (genome size-corrected, reciprocal BLAST hits and transferred genes (identified by DarkHorse were strongly correlated. Thus archaea and bacteria that live in anaerobic and/or high temperature conditions are more likely to share horizontally transferred genes. These horizontally transferred genes are over-represented by genes involved in energy conversion as well as the transport and metabolism of inorganic ions and amino acids. Conclusions Anaerobic and thermophilic bacteria share unusually large numbers of genes with archaea. This is mainly due to horizontal gene transfer of

Inference of gene-phenotype associations via protein-protein interaction and orthology.

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Panwen Wang

Full Text Available One of the fundamental goals of genetics is to understand gene functions and their associated phenotypes. To achieve this goal, in this study we developed a computational algorithm that uses orthology and protein-protein interaction information to infer gene-phenotype associations for multiple species. Furthermore, we developed a web server that provides genome-wide phenotype inference for six species: fly, human, mouse, worm, yeast, and zebrafish. We evaluated our inference method by comparing the inferred results with known gene-phenotype associations. The high Area Under the Curve values suggest a significant performance of our method. By applying our method to two human representative diseases, Type 2 Diabetes and Breast Cancer, we demonstrated that our method is able to identify related Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The web server can be used to infer functions and putative phenotypes of a gene along with the candidate genes of a phenotype, and thus aids in disease candidate gene discovery. Our web server is available at http://jjwanglab.org/PhenoPPIOrth.

Human-Computer Interaction in Smart Environments

Directory of Open Access Journals (Sweden)

Gianluca Paravati

2015-08-01

Full Text Available Here, we provide an overview of the content of the Special Issue on “Human-computer interaction in smart environments”. The aim of this Special Issue is to highlight technologies and solutions encompassing the use of mass-market sensors in current and emerging applications for interacting with Smart Environments. Selected papers address this topic by analyzing different interaction modalities, including hand/body gestures, face recognition, gaze/eye tracking, biosignal analysis, speech and activity recognition, and related issues.

Challenges and Opportunities in Genome-Wide Environmental Interaction (GWEI) studies

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Aschard, Hugues; Lutz, Sharon; Maus, Bärbel; Duell, Eric J.; Fingerlin, Tasha; Chatterjee, Nilanjan; Kraft, Peter; Van Steen, Kristel

2012-01-01

The interest in performing gene-environment interaction studies has seen a significant increase with the increase of advanced molecular genetics techniques. Practically, it became possible to investigate the role of environmental factors in disease risk and hence to investigate their role as genetic effect modifiers. The understanding that genetics is important in the uptake and metabolism of toxic substances is an example of how genetic profiles can modify important environmental risk factors to disease. Several rationales exist to set up gene-environment interaction studies and the technical challenges related to these studies – when the number of environmental or genetic risk factors is relatively small – has been described before. In the post-genomic era, it is now possible to study thousands of genes and their interaction with the environment. This brings along a whole range of new challenges and opportunities. Despite a continuing effort in developing efficient methods and optimal bioinformatics infrastructures to deal with the available wealth of data, the challenge remains how to best present and analyze Genome-Wide Environmental Interaction (GWEI) studies involving multiple genetic and environmental factors. Since GWEIs are performed at the intersection of statistical genetics, bioinformatics and epidemiology, usually similar problems need to be dealt with as for Genome-Wide Association gene-gene Interaction (GWAI) studies. However, additional complexities need to be considered which are typical for large-scale epidemiological studies, but are also related to “joining” two heterogeneous types of data in explaining complex disease trait variation or for prediction purposes. PMID:22760307

VIGO: Instrumental Interaction in Multi-Surface Environments

DEFF Research Database (Denmark)

Klokmose, Clemens Nylandsted; Beaudouin-Lafon, Michel

2009-01-01

This paper addresses interaction in multi-surface environments and questions whether the current application-centric approaches to user interfaces are adequate in this context, and presents an alternative approach based on instrumental interaction. The paper presents the VIGO (Views, Instruments...

Problem solving environment for distributed interactive applications

NARCIS (Netherlands)

Rycerz, K.; Bubak, M.; Sloot, P.; Getov, V.; Gorlatch, S.; Bubak, M.; Priol, T.

2008-01-01

Interactive Problem Solving Environments (PSEs) offer an integrated approach for constructing and running complex systems, such as distributed simulation systems. To achieve efficient execution of High Level Architecture (HLA)-based distributed interactive simulations on the Grid, we introduce a PSE

Protein Annotation from Protein Interaction Networks and Gene Ontology

OpenAIRE

Nguyen, Cao D.; Gardiner, Katheleen J.; Cios, Krzysztof J.

2011-01-01

We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precis...

QTL and QTL x environment effects on agronomic and nitrogen acquisition traits in rice.

Science.gov (United States)

Senthilvel, Senapathy; Vinod, Kunnummal Kurungara; Malarvizhi, Palaniappan; Maheswaran, Marappa

2008-09-01

Agricultural environments deteriorate due to excess nitrogen application. Breeding for low nitrogen responsive genotypes can reduce soil nitrogen input. Rice genotypes respond variably to soil available nitrogen. The present study attempted quantification of genotype x nitrogen level interaction and mapping of quantitative trait loci (QTLs) associated with nitrogen use efficiency (NUE) and other associated agronomic traits. Twelve parameters were observed across a set of 82 double haploid (DH) lines derived from IR64/Azucena. Three nitrogen regimes namely, native (0 kg/ha; no nitrogen applied), optimum (100 kg/ha) and high (200 kg/ha) replicated thrice were the environments. The parents and DH lines were significantly varying for all traits under different nitrogen regimes. All traits except plant height recorded significant genotype x environment interaction. Individual plant yield was positively correlated with nitrogen use efficiency and nitrogen uptake. Sixteen QTLs were detected by composite interval mapping. Eleven QTLs showed significant QTL x environment interactions. On chromosome 3, seven QTLs were detected associated with nitrogen use, plant yield and associated traits. A QTL region between markers RZ678, RZ574 and RZ284 was associated with nitrogen use and yield. This chromosomal region was enriched with expressed gene sequences of known key nitrogen assimilation genes.

Chemical compounds from anthropogenic environment and immune evasion mechanisms: potential interactions.

Science.gov (United States)

Kravchenko, Julia; Corsini, Emanuela; Williams, Marc A; Decker, William; Manjili, Masoud H; Otsuki, Takemi; Singh, Neetu; Al-Mulla, Faha; Al-Temaimi, Rabeah; Amedei, Amedeo; Colacci, Anna Maria; Vaccari, Monica; Mondello, Chiara; Scovassi, A Ivana; Raju, Jayadev; Hamid, Roslida A; Memeo, Lorenzo; Forte, Stefano; Roy, Rabindra; Woodrick, Jordan; Salem, Hosni K; Ryan, Elizabeth P; Brown, Dustin G; Bisson, William H; Lowe, Leroy; Lyerly, H Kim

2015-06-01

An increasing number of studies suggest an important role of host immunity as a barrier to tumor formation and progression. Complex mechanisms and multiple pathways are involved in evading innate and adaptive immune responses, with a broad spectrum of chemicals displaying the potential to adversely influence immunosurveillance. The evaluation of the cumulative effects of low-dose exposures from the occupational and natural environment, especially if multiple chemicals target the same gene(s) or pathway(s), is a challenge. We reviewed common environmental chemicals and discussed their potential effects on immunosurveillance. Our overarching objective was to review related signaling pathways influencing immune surveillance such as the pathways involving PI3K/Akt, chemokines, TGF-β, FAK, IGF-1, HIF-1α, IL-6, IL-1α, CTLA-4 and PD-1/PDL-1 could individually or collectively impact immunosurveillance. A number of chemicals that are common in the anthropogenic environment such as fungicides (maneb, fluoxastrobin and pyroclostrobin), herbicides (atrazine), insecticides (pyridaben and azamethiphos), the components of personal care products (triclosan and bisphenol A) and diethylhexylphthalate with pathways critical to tumor immunosurveillance. At this time, these chemicals are not recognized as human carcinogens; however, it is known that they these chemicalscan simultaneously persist in the environment and appear to have some potential interfere with the host immune response, therefore potentially contributing to promotion interacting with of immune evasion mechanisms, and promoting subsequent tumor growth and progression. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Network Diffusion-Based Prioritization of Autism Risk Genes Identifies Significantly Connected Gene Modules

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Ettore Mosca

2017-09-01

Full Text Available Autism spectrum disorder (ASD is marked by a strong genetic heterogeneity, which is underlined by the low overlap between ASD risk gene lists proposed in different studies. In this context, molecular networks can be used to analyze the results of several genome-wide studies in order to underline those network regions harboring genetic variations associated with ASD, the so-called “disease modules.” In this work, we used a recent network diffusion-based approach to jointly analyze multiple ASD risk gene lists. We defined genome-scale prioritizations of human genes in relation to ASD genes from multiple studies, found significantly connected gene modules associated with ASD and predicted genes functionally related to ASD risk genes. Most of them play a role in synapsis and neuronal development and function; many are related to syndromes that can be in comorbidity with ASD and the remaining are involved in epigenetics, cell cycle, cell adhesion and cancer.

Optimization of dairy cattle breeding programs for different environment with genotype by environment interaction

NARCIS (Netherlands)

Mulder, H.A.; Veerkamp, R.F.; Ducro, B.J.; Arendonk, van J.A.M.; Bijma, P.

2006-01-01

Dairy cattle breeding organizations tend to sell semen to breeders operating in different environments and genotype × environment interaction may play a role. The objective of this study was to investigate optimization of dairy cattle breeding programs for 2 environments with genotype × environment

Integrated bioinformatic analysis unveils significant genes and pathways in the pathogenesis of supratentorial primitive neuroectodermal tumor

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Wang G

2018-04-01

Full Text Available Guang-Yu Wang,1,* Ling Li,2,* Bo Liu,1 Xiao Han,1 Chun-Hua Wang,1 Ji-Wen Wang3 1Department of Neurosurgery, 2Department of Pediatrics, Qilu Children’s Hospital of Shandong University, Jinan, Shandong, 3Department of Neurology, Shanghai Children’s Medical Center, Shanghai Jiaotong University School of Medicine, Pudong New District, Shanghai, People’s Republic of China *These authors contributed equally to this work Purpose: This study aimed to explore significant genes and pathways involved in the pathogenesis of supratentorial primitive neuroectodermal tumor (sPNET. Materials and methods: Gene expression profile of GSE14295 was downloaded from publicly available Gene Expression Omnibus (GEO database. Differentially expressed genes (DEGs were screened out in primary sPNET samples compared with normal fetal and adult brain reference samples (sPNET vs fetal brain and sPNET vs adult brain. Pathway enrichment analysis of these DEGs was conducted, followed by protein–protein interaction (PPI network construction and significant module selection. Additionally, transcription factors (TFs regulating the common DEGs in the two comparison groups were identified, and the regulatory network was constructed. Results: In total, 526 DEGs (99 up- and 427 downregulated in sPNET vs fetal brain and 815 DEGs (200 up- and 615 downregulated in sPNET vs adult brain were identified. DEGs in sPNET vs fetal brain and sPNET vs adult brain were associated with calcium signaling pathway, cell cycle, and p53 signaling pathway. CDK1, CDC20, BUB1B, and BUB1 were hub nodes in the PPI networks of DEGs in sPNET vs fetal brain and sPNET vs adult brain. Significant modules were extracted from the PPI networks. In addition, 64 upregulated and 200 downregulated overlapping DEGs were identified in both sPNET vs fetal brain and sPNET vs adult brain. The genes involved in the regulatory network upon overlapping DEGs and the TFs were correlated with calcium signaling pathway

DGIdb 3.0: a redesign and expansion of the drug-gene interaction database.

Science.gov (United States)

Cotto, Kelsy C; Wagner, Alex H; Feng, Yang-Yang; Kiwala, Susanna; Coffman, Adam C; Spies, Gregory; Wollam, Alex; Spies, Nicholas C; Griffith, Obi L; Griffith, Malachi

2018-01-04

The drug-gene interaction database (DGIdb, www.dgidb.org) consolidates, organizes and presents drug-gene interactions and gene druggability information from papers, databases and web resources. DGIdb normalizes content from 30 disparate sources and allows for user-friendly advanced browsing, searching and filtering for ease of access through an intuitive web user interface, application programming interface (API) and public cloud-based server image. DGIdb v3.0 represents a major update of the database. Nine of the previously included 24 sources were updated. Six new resources were added, bringing the total number of sources to 30. These updates and additions of sources have cumulatively resulted in 56 309 interaction claims. This has also substantially expanded the comprehensive catalogue of druggable genes and anti-neoplastic drug-gene interactions included in the DGIdb. Along with these content updates, v3.0 has received a major overhaul of its codebase, including an updated user interface, preset interaction search filters, consolidation of interaction information into interaction groups, greatly improved search response times and upgrading the underlying web application framework. In addition, the expanded API features new endpoints which allow users to extract more detailed information about queried drugs, genes and drug-gene interactions, including listings of PubMed IDs, interaction type and other interaction metadata.

Who possesses drug resistance genes in the aquatic environment?: sulfamethoxazole (SMX) resistance genes among the bacterial community in water environment of Metro-Manila, Philippines.

Science.gov (United States)

Suzuki, Satoru; Ogo, Mitsuko; Miller, Todd W; Shimizu, Akiko; Takada, Hideshige; Siringan, Maria Auxilia T

2013-01-01

Recent evidence has shown that antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) are ubiquitous in natural environments, including sites considered pristine. To understand the origin of ARGs and their dynamics, we must first define their actual presence in the natural bacterial assemblage. Here we found varying distribution profiles of sul genes in "colony forming bacterial assemblages" and "natural bacterial assemblages." Our monitoring for antibiotic contamination revealed that sulfamethoxazole (SMX) is a major contaminant in aquatic environments of Metro-Manila, which would have been derived from human and animal use, and subsequently decreased through the process of outflow from source to the sea. The SMX-resistant bacterial rate evaluated by the colony forming unit showed 10 to 86% of the total colony numbers showed higher rates from freshwater sites compared to marine sites. When sul genes were quantified by qPCR, colony-forming bacteria conveyed sul1 and sul2 genes in freshwater and seawater (10(-5)-10(-2) copy/16S) but not sul3. Among the natural bacterial assemblage, all sul1, sul2, and sul3 were detected (10(-5)-10(-3) copy/16S), whereas all sul genes were at an almost non-detectable level in the freshwater assemblage. This study suggests that sul1 and sul2 are main sul genes in culturable bacteria, whereas sul3 is conveyed by non-culturable bacteria in the sea. As a result marine bacteria possess sul1, sul2 and sul3 genes in the marine environment.

Who Possesses Drug Resistance Genes in the Aquatic Environment? : Sulfamethoxazole (SMX Resistance Genes among the Bacterial Community in Water Environment of Metro-Manila, Philippines

Directory of Open Access Journals (Sweden)

Satoru eSuzuki

2013-04-01

Full Text Available Recent evidence has shown that antibiotic resistant bacteria (ARB and antibiotic resistance genes (ARG are ubiquitous in natural environments, including sites considered pristine. To understand the origin of ARGs and their dynamics, we must first define their actual presence in the natural bacterial assemblage. Here we found varying distribution profiles of sul genes in colony forming bacterial assemblages and natural bacterial assemblages. Our monitoring for antibiotic contamination revealed that sulfamethoxazole (SMX is a major contaminant in aquatic environments of Metro-Manila, which would have been derived from human and animal use, and subsequently decreased through the process of outflow from source to the sea. The SMX-resistant bacterial rate evaluated by the colony forming unit showed 10 to 86 % of the total colony numbers showed higher rates from freshwater sites compared to marine sites. When sul genes were quantified by qPCR, colony-forming bacteria conveyed sul1 and sul2 genes in freshwater and seawater (10-5-10-2 copy/16S but not sul3. Among the natural bacterial assemblage, all sul1, sul2 and sul3 were detected (10-5-10-3 copy/16S, whereas all sul genes were at an almost non-detectable level in the freshwater assemblage. This study suggests that sul1 and sul2 are main sul genes in culturable bacteria, whereas sul3 is conveyed by non-culturable bacteria in the sea. As a result marine bacteria possess sul1, sul2 and sul3 genes in the marine environment.

Exploring Plant Co-Expression and Gene-Gene Interactions with CORNET 3.0.

Science.gov (United States)

Van Bel, Michiel; Coppens, Frederik

2017-01-01

Selecting and filtering a reference expression and interaction dataset when studying specific pathways and regulatory interactions can be a very time-consuming and error-prone task. In order to reduce the duplicated efforts required to amass such datasets, we have created the CORNET (CORrelation NETworks) platform which allows for easy access to a wide variety of data types: coexpression data, protein-protein interactions, regulatory interactions, and functional annotations. The CORNET platform outputs its results in either text format or through the Cytoscape framework, which is automatically launched by the CORNET website.CORNET 3.0 is the third iteration of the web platform designed for the user exploration of the coexpression space of plant genomes, with a focus on the model species Arabidopsis thaliana. Here we describe the platform: the tools, data, and best practices when using the platform. We indicate how the platform can be used to infer networks from a set of input genes, such as upregulated genes from an expression experiment. By exploring the network, new target and regulator genes can be discovered, allowing for follow-up experiments and more in-depth study. We also indicate how to avoid common pitfalls when evaluating the networks and how to avoid over interpretation of the results.All CORNET versions are available at http://bioinformatics.psb.ugent.be/cornet/ .

Differences in lateral gene transfer in hypersaline versus thermal environments

Directory of Open Access Journals (Sweden)

House Christopher H

2011-07-01

Full Text Available Abstract Background The role of lateral gene transfer (LGT in the evolution of microorganisms is only beginning to be understood. While most LGT events occur between closely related individuals, inter-phylum and inter-domain LGT events are not uncommon. These distant transfer events offer potentially greater fitness advantages and it is for this reason that these "long distance" LGT events may have significantly impacted the evolution of microbes. One mechanism driving distant LGT events is microbial transformation. Theoretically, transformative events can occur between any two species provided that the DNA of one enters the habitat of the other. Two categories of microorganisms that are well-known for LGT are the thermophiles and halophiles. Results We identified potential inter-class LGT events into both a thermophilic class of Archaea (Thermoprotei and a halophilic class of Archaea (Halobacteria. We then categorized these LGT genes as originating in thermophiles and halophiles respectively. While more than 68% of transfer events into Thermoprotei taxa originated in other thermophiles, less than 11% of transfer events into Halobacteria taxa originated in other halophiles. Conclusions Our results suggest that there is a fundamental difference between LGT in thermophiles and halophiles. We theorize that the difference lies in the different natures of the environments. While DNA degrades rapidly in thermal environments due to temperature-driven denaturization, hypersaline environments are adept at preserving DNA. Furthermore, most hypersaline environments, as topographical minima, are natural collectors of cellular debris. Thus halophiles would in theory be exposed to a greater diversity and quantity of extracellular DNA than thermophiles.

Differences in lateral gene transfer in hypersaline versus thermal environments.

Science.gov (United States)

Rhodes, Matthew E; Spear, John R; Oren, Aharon; House, Christopher H

2011-07-08

The role of lateral gene transfer (LGT) in the evolution of microorganisms is only beginning to be understood. While most LGT events occur between closely related individuals, inter-phylum and inter-domain LGT events are not uncommon. These distant transfer events offer potentially greater fitness advantages and it is for this reason that these "long distance" LGT events may have significantly impacted the evolution of microbes. One mechanism driving distant LGT events is microbial transformation. Theoretically, transformative events can occur between any two species provided that the DNA of one enters the habitat of the other. Two categories of microorganisms that are well-known for LGT are the thermophiles and halophiles. We identified potential inter-class LGT events into both a thermophilic class of Archaea (Thermoprotei) and a halophilic class of Archaea (Halobacteria). We then categorized these LGT genes as originating in thermophiles and halophiles respectively. While more than 68% of transfer events into Thermoprotei taxa originated in other thermophiles, less than 11% of transfer events into Halobacteria taxa originated in other halophiles. Our results suggest that there is a fundamental difference between LGT in thermophiles and halophiles. We theorize that the difference lies in the different natures of the environments. While DNA degrades rapidly in thermal environments due to temperature-driven denaturization, hypersaline environments are adept at preserving DNA. Furthermore, most hypersaline environments, as topographical minima, are natural collectors of cellular debris. Thus halophiles would in theory be exposed to a greater diversity and quantity of extracellular DNA than thermophiles.

Estimating Risks and Relative Risks in Case-Base Studies under the Assumptions of Gene-Environment Independence and Hardy-Weinberg Equilibrium

Science.gov (United States)

Chui, Tina Tsz-Ting; Lee, Wen-Chung

2014-01-01

Many diseases result from the interactions between genes and the environment. An efficient method has been proposed for a case-control study to estimate the genetic and environmental main effects and their interactions, which exploits the assumptions of gene-environment independence and Hardy-Weinberg equilibrium. To estimate the absolute and relative risks, one needs to resort to an alternative design: the case-base study. In this paper, the authors show how to analyze a case-base study under the above dual assumptions. This approach is based on a conditional logistic regression of case-counterfactual controls matched data. It can be easily fitted with readily available statistical packages. When the dual assumptions are met, the method is approximately unbiased and has adequate coverage probabilities for confidence intervals. It also results in smaller variances and shorter confidence intervals as compared with a previous method for a case-base study which imposes neither assumption. PMID:25137392

Estimating risks and relative risks in case-base studies under the assumptions of gene-environment independence and Hardy-Weinberg equilibrium.

Directory of Open Access Journals (Sweden)

Tina Tsz-Ting Chui

Full Text Available Many diseases result from the interactions between genes and the environment. An efficient method has been proposed for a case-control study to estimate the genetic and environmental main effects and their interactions, which exploits the assumptions of gene-environment independence and Hardy-Weinberg equilibrium. To estimate the absolute and relative risks, one needs to resort to an alternative design: the case-base study. In this paper, the authors show how to analyze a case-base study under the above dual assumptions. This approach is based on a conditional logistic regression of case-counterfactual controls matched data. It can be easily fitted with readily available statistical packages. When the dual assumptions are met, the method is approximately unbiased and has adequate coverage probabilities for confidence intervals. It also results in smaller variances and shorter confidence intervals as compared with a previous method for a case-base study which imposes neither assumption.

GBOOST: a GPU-based tool for detecting gene-gene interactions in genome-wide case control studies.

Science.gov (United States)

Yung, Ling Sing; Yang, Can; Wan, Xiang; Yu, Weichuan

2011-05-01

Collecting millions of genetic variations is feasible with the advanced genotyping technology. With a huge amount of genetic variations data in hand, developing efficient algorithms to carry out the gene-gene interaction analysis in a timely manner has become one of the key problems in genome-wide association studies (GWAS). Boolean operation-based screening and testing (BOOST), a recent work in GWAS, completes gene-gene interaction analysis in 2.5 days on a desktop computer. Compared with central processing units (CPUs), graphic processing units (GPUs) are highly parallel hardware and provide massive computing resources. We are, therefore, motivated to use GPUs to further speed up the analysis of gene-gene interactions. We implement the BOOST method based on a GPU framework and name it GBOOST. GBOOST achieves a 40-fold speedup compared with BOOST. It completes the analysis of Wellcome Trust Case Control Consortium Type 2 Diabetes (WTCCC T2D) genome data within 1.34 h on a desktop computer equipped with Nvidia GeForce GTX 285 display card. GBOOST code is available at http://bioinformatics.ust.hk/BOOST.html#GBOOST.

Maternal-by-environment but not genotype-by-environment interactions in a fish without parental care.

Science.gov (United States)

Vega-Trejo, Regina; Head, Megan L; Jennions, Michael D; Kruuk, Loeske E B

2018-01-01

The impact of environmental conditions on the expression of genetic variance and on maternal effects variance remains an important question in evolutionary quantitative genetics. We investigate here the effects of early environment on variation in seven adult life history, morphological, and secondary sexual traits (including sperm characteristics) in a viviparous poeciliid fish, the mosquitofish Gambusia holbrooki. Specifically, we manipulated food availability during early development and then assessed additive genetic and maternal effects contributions to the overall phenotypic variance in adults. We found higher heritability for female than male traits, but maternal effects variance for traits in both sexes. An interaction between maternal effects variance and rearing environment affected two adult traits (female age at maturity and male size at maturity), but there was no evidence of trade-offs in maternal effects across environments. Our results illustrate (i) the potential for pre-natal maternal effects to interact with offspring environment during development, potentially affecting traits through to adulthood and (ii) that genotype-by-environment interactions might be overestimated if maternal-by-environment interactions are not accounted for, similar to heritability being overestimated if maternal effects are ignored. We also discuss the potential for dominance genetic variance to contribute to the estimate of maternal effects variance.

Genome-wide analysis of E. coli cell-gene interactions.

Science.gov (United States)

Cardinale, S; Cambray, G

2017-11-23

The pursuit of standardization and reliability in synthetic biology has achieved, in recent years, a number of advances in the design of more predictable genetic parts for biological circuits. However, even with the development of high-throughput screening methods and whole-cell models, it is still not possible to predict reliably how a synthetic genetic construct interacts with all cellular endogenous systems. This study presents a genome-wide analysis of how the expression of synthetic genes is affected by systematic perturbations of cellular functions. We found that most perturbations modulate expression indirectly through an effect on cell size, putting forward the existence of a generic Size-Expression interaction in the model prokaryote Escherichia coli. The Size-Expression interaction was quantified by inserting a dual fluorescent reporter gene construct into each of the 3822 single-gene deletion strains comprised in the KEIO collection. Cellular size was measured for single cells via flow cytometry. Regression analyses were used to discriminate between expression-specific and gene-specific effects. Functions of the deleted genes broadly mapped onto three systems with distinct primary influence on the Size-Expression map. Perturbations in the Division and Biosynthesis (DB) system led to a large-cell and high-expression phenotype. In contrast, disruptions of the Membrane and Motility (MM) system caused small-cell and low-expression phenotypes. The Energy, Protein synthesis and Ribosome (EPR) system was predominantly associated with smaller cells and positive feedback on ribosome function. Feedback between cell growth and gene expression is widespread across cell systems. Even though most gene disruptions proximally affect one component of the Size-Expression interaction, the effect therefore ultimately propagates to both. More specifically, we describe the dual impact of growth on cell size and gene expression through cell division and ribosomal content

Interactions of psychosocial factors with built environments in explaining adolescents' active transportation.

Science.gov (United States)

Wang, Xiaobo; Conway, Terry L; Cain, Kelli L; Frank, Lawrence D; Saelens, Brian E; Geremia, Carrie; Kerr, Jacqueline; Glanz, Karen; Carlson, Jordan A; Sallis, James F

2017-07-01

The present study examined independent and interacting associations of psychosocial and neighborhood built environment variables with adolescents' reported active transportation. Moderating effects of adolescent sex were explored. Mixed-effects regression models were conducted on data from the Teen Environment and Neighborhood observational study (N=928) in the Seattle, WA and Baltimore regions 2009-2011. Frequency index of active transportation to neighborhood destinations (dependent variable) and 7 psychosocial measures were reported by adolescents. Built environment measures included home walkability and count of nearby parks and recreation facilities using GIS procedures and streetscape quality from environmental audits. Results indicated all 3 environmental variables and 3 psychosocial variables (self-efficacy, social support from peers, and enjoyment of physical activity) had significant positive main effects with active transportation (Pstransportation (Pstransportation was found among adolescents with the combination of activity-supportive built environment and positive psychosocial characteristics. Three-way interactions with sex indicated similar associations for girls and boys, with one exception. Results provided modest support for the ecological model principle of interactions across levels, highlight the importance of both built environment and psychosocial factors in shaping adolescents' active transportation, demonstrated the possibility of sex-specific findings, and suggested strategies for improving adolescents' active transportation may be most effective when targeting multiple levels of influence. Copyright © 2017 Elsevier Inc. All rights reserved.

Genome-wide search for gene-gene interactions in colorectal cancer.

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Shuo Jiao

Full Text Available Genome-wide association studies (GWAS have successfully identified a number of single-nucleotide polymorphisms (SNPs associated with colorectal cancer (CRC risk. However, these susceptibility loci known today explain only a small fraction of the genetic risk. Gene-gene interaction (GxG is considered to be one source of the missing heritability. To address this, we performed a genome-wide search for pair-wise GxG associated with CRC risk using 8,380 cases and 10,558 controls in the discovery phase and 2,527 cases and 2,658 controls in the replication phase. We developed a simple, but powerful method for testing interaction, which we term the Average Risk Due to Interaction (ARDI. With this method, we conducted a genome-wide search to identify SNPs showing evidence for GxG with previously identified CRC susceptibility loci from 14 independent regions. We also conducted a genome-wide search for GxG using the marginal association screening and examining interaction among SNPs that pass the screening threshold (p<10(-4. For the known locus rs10795668 (10p14, we found an interacting SNP rs367615 (5q21 with replication p = 0.01 and combined p = 4.19×10(-8. Among the top marginal SNPs after LD pruning (n = 163, we identified an interaction between rs1571218 (20p12.3 and rs10879357 (12q21.1 (nominal combined p = 2.51×10(-6; Bonferroni adjusted p = 0.03. Our study represents the first comprehensive search for GxG in CRC, and our results may provide new insight into the genetic etiology of CRC.

The evolutionary ecology of cytonuclear interactions in angiosperms.

Science.gov (United States)

Caruso, Christina M; Case, Andrea L; Bailey, Maia F

2012-11-01

Interactions between cytoplasmic and nuclear genomes have significant evolutionary consequences. In angiosperms, the most common cytonuclear interaction is between mitochondrial genes that disrupt pollen production (cytoplasmic male sterility, CMS) and nuclear genes that restore it (nuclear male fertility restorers, Rf). The outcome of CMS/Rf interactions can depend on whether Rf alleles have negative pleiotropic effects on fitness. Although these fitness costs are often considered to be independent of the ecological context, we argue that the effects of Rf alleles on fitness should be context dependent. Thus, measuring the cost of restoration across a range of environments could help explain geographic and phylogenetic variation in the distribution of Rf alleles and the outcome of CMS/Rf interactions. Copyright © 2012 Elsevier Ltd. All rights reserved.

The interaction of BDNF and NTRK2 gene increases the susceptibility of paranoid schizophrenia.

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Zheng Lin

Full Text Available The association between BDNF gene functional Val66Met polymorphism rs6265 and the schizophrenia is far from being consistent. In addition to the heterogeneous in schizophrenia per se leading to the inconsistent results, the interaction among multi-genes is probably playing the main role in the pathogenesis of schizophrenia, but not a single gene. Neurotrophic tyrosine kinase receptor 2 (NTRK2 is the high-affinity receptor of BDNF, and was reported to be associated with mood disorders, though no literature reported the association with schizophrenia. Thus, in the present study, total 402 patients with paranoid schizophrenia (the most common subtype of schizophrenia and matched 406 healthy controls were recruited to investigate the role of rs6265 in BDNF, three polymorphisms in NTRK2 gene (rs1387923, rs2769605 and rs1565445 and their interaction in the susceptibility to paranoid schizophrenia in a Chinese Han population. We did not observe significant differences in allele and genotype frequencies between patients and healthy controls for all four polymorphisms separately. The haplotype analysis also showed no association between haplotype of NTRK2 genes (rs1387923, rs2769605, and rs1565445 and paranoid schizophrenia. However, we found the association between the interaction of BDNF and NTRK2 with paranoid schizophrenia by using the MDR method followed by conventional statistical analysis. The best gene-gene interaction model was a three-locus model (BDNF rs6265, NTRK2 rs1387923 and NTRK2 rs2769605, in which one low-risk and three high-risk four-locus genotype combinations were identified. Our findings implied that single polymorphism of rs6265 rs1387923, rs2769605, and rs1565445 in BDNF and NTRK2 were not associated with the development of paranoid schizophrenia in a Han population, however, the interaction of BDNF and NTRK2 genes polymorphisms (BDNF-rs6265, NTRK2-rs1387923 and NTRK2-rs2769605 may be involved in the susceptibility to paranoid

The interaction of BDNF and NTRK2 gene increases the susceptibility of paranoid schizophrenia.

Science.gov (United States)

Lin, Zheng; Su, Yousong; Zhang, Chengfang; Xing, Mengjuan; Ding, Wenhua; Liao, Liwei; Guan, Yangtai; Li, Zezhi; Cui, Donghong

2013-01-01

The association between BDNF gene functional Val66Met polymorphism rs6265 and the schizophrenia is far from being consistent. In addition to the heterogeneous in schizophrenia per se leading to the inconsistent results, the interaction among multi-genes is probably playing the main role in the pathogenesis of schizophrenia, but not a single gene. Neurotrophic tyrosine kinase receptor 2 (NTRK2) is the high-affinity receptor of BDNF, and was reported to be associated with mood disorders, though no literature reported the association with schizophrenia. Thus, in the present study, total 402 patients with paranoid schizophrenia (the most common subtype of schizophrenia) and matched 406 healthy controls were recruited to investigate the role of rs6265 in BDNF, three polymorphisms in NTRK2 gene (rs1387923, rs2769605 and rs1565445) and their interaction in the susceptibility to paranoid schizophrenia in a Chinese Han population. We did not observe significant differences in allele and genotype frequencies between patients and healthy controls for all four polymorphisms separately. The haplotype analysis also showed no association between haplotype of NTRK2 genes (rs1387923, rs2769605, and rs1565445) and paranoid schizophrenia. However, we found the association between the interaction of BDNF and NTRK2 with paranoid schizophrenia by using the MDR method followed by conventional statistical analysis. The best gene-gene interaction model was a three-locus model (BDNF rs6265, NTRK2 rs1387923 and NTRK2 rs2769605), in which one low-risk and three high-risk four-locus genotype combinations were identified. Our findings implied that single polymorphism of rs6265 rs1387923, rs2769605, and rs1565445 in BDNF and NTRK2 were not associated with the development of paranoid schizophrenia in a Han population, however, the interaction of BDNF and NTRK2 genes polymorphisms (BDNF-rs6265, NTRK2-rs1387923 and NTRK2-rs2769605) may be involved in the susceptibility to paranoid schizophrenia.

Genes, environment and sport performance: why the nature-nurture dualism is no longer relevant.

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Davids, Keith; Baker, Joseph

2007-01-01

The historical debate on the relative influences of genes (i.e. nature) and environment (i.e. nurture) on human behaviour has been characterised by extreme positions leading to reductionist and polemic conclusions. Our analysis of research on sport and exercise behaviours shows that currently there is little support for either biologically or environmentally deterministic perspectives on elite athletic performance. In sports medicine, recent molecular biological advances in genomic studies have been over-interpreted, leading to a questionable 'single-gene-as-magic-bullet' philosophy adopted by some practitioners. Similarly, although extensive involvement in training and practice is needed at elite levels, it has become apparent that the acquisition of expertise is not merely about amassing a requisite number of practice hours. Although an interactionist perspective has been mooted over the years, a powerful explanatory framework has been lacking. In this article, we propose how the complementary nature of degenerate neurobiological systems might provide the theoretical basis for explaining the interactive influence of genetic and environmental constraints on elite athletic performance. We argue that, due to inherent human degeneracy, there are many different trajectories to achieving elite athletic performance. While the greatest training responses may be theoretically associated with the most favourable genotypes being exposed to highly specialised training environments, this is a rare and complex outcome. The concept of degeneracy provides us with a basis for understanding why each of the major interacting constraints might act in a compensatory manner on the acquisition of elite athletic performance.

Gene interactions and genetics for yield and its attributes in grass ...

Indian Academy of Sciences (India)

A. K. PARIHAR

explaining the manifestation of complex traits such as yield. ... interactions (i, j, l) contributed towards the inheritance of traits in the given crosses. ... Keywords. grass pea; scaling test; gene interactions; gene effects; heritability; Lathyrus sativus.

Mapping of Wnt-Frizzled interactions by multiplex CRISPR targeting of receptor gene families.

Science.gov (United States)

Voloshanenko, Oksana; Gmach, Philipp; Winter, Jan; Kranz, Dominique; Boutros, Michael

2017-11-01

Signaling pathway modules are often encoded by several closely related paralogous genes that can have redundant roles and are therefore difficult to analyze by loss-of-function analysis. A typical example is the Wnt signaling pathway, which in mammals is mediated by 19 Wnt ligands that can bind to 10 Frizzled (FZD) receptors. Although significant progress in understanding Wnt-FZD receptor interactions has been made in recent years, tools to generate systematic interaction maps have been largely lacking. Here we generated cell lines with multiplex mutant alleles of FZD1 , FZD2 , and FZD7 and demonstrate that these cells are unresponsive to canonical Wnt ligands. Subsequently, we performed genetic rescue experiments with combinations of FZDs and canonical Wnts to create a functional ligand-receptor interaction map. These experiments showed that whereas several Wnt ligands, such as Wnt3a, induce signaling through a broad spectrum of FZD receptors, others, such as Wnt8a, act through a restricted set of FZD genes. Together, our results map functional interactions of FZDs and 10 Wnt ligands and demonstrate how multiplex targeting by clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 can be used to systematically elucidate the functions of multigene families.-Voloshanenko, O., Gmach, P., Winter, J., Kranz, D., Boutros, M. Mapping of Wnt-Frizzled interactions by multiplex CRISPR targeting of receptor gene families. © The Author(s).

Family environment and adult resilience: contributions of positive parenting and the oxytocin receptor gene

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Bekh Bradley

2013-09-01

Full Text Available Background: Abundant research shows that childhood adversity increases the risk for adult psychopathology while research on influences of positive family environment on risk for psychopathology is limited. Similarly, a growing body of research examines genetic and gene by environment predictors of psychopathology, yet such research on predictors of resilience is sparse. Objectives: We examined the role of positive factors in childhood family environment (CFE and the OXTR rs53576 genotype in predicting levels of adult resilient coping and positive affect. We also examined whether the relationship between positive factors in the CFEs and adult resilient coping and positive affect varied across OXTR rs53576 genotype. Methods: We gathered self-report data on childhood environment, trauma history, and adult resilience and positive affect in a sample of 971 African American adults. Results: We found that positive CFE was positively associated with higher levels of resilient coping and positive affect in adulthood after controlling for childhood maltreatment, other trauma, and symptoms of posttraumatic stress disorder. We did not find a direct effect of OXTR 53576 on a combined resilient coping/positive-affect-dependent variable, but we did find an interaction of OXTR rs53576 with family environment. Conclusions: Our data suggest that even in the face of adversity, positive aspects of the family environment may contribute to resilience. These results highlight the importance of considering protective developmental experiences and the interaction of such experiences with genetic variants in risk and resilience research.For the abstract or full text in other languages, please see Supplementary files under Article Tools online

Influence of SNPs in nutrient-sensitive candidate genes and gene-diet interactions on blood lipids

DEFF Research Database (Denmark)

Brahe, Lena Kirchner; Angquist, Lars; Larsen, Lesli Hingstrup

2013-01-01

Blood lipid response to a given dietary intervention could be determined by the effect of diet, gene variants or gene-diet interactions. The objective of the present study was to investigate whether variants in presumed nutrient-sensitive genes involved in lipid metabolism modified lipid profile ...

IGEMS: The Consortium on Interplay of Genes and Environment Across Multiple Studies

DEFF Research Database (Denmark)

Pedersen, Nancy L; Christensen, Kaare; Dahl, Anna K

2013-01-01

The Interplay of Genes and Environment across Multiple Studies (IGEMS) group is a consortium of eight longitudinal twin studies established to explore the nature of social context effects and gene-environment interplay in late-life functioning. The resulting analysis of the combined data from ove...

Dopamine genes (DRD2/ANKK1-TaqA1 and DRD4-7R and executive function: their interaction with obesity.

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Mar Ariza

Full Text Available Obesity is a multifactorial disease caused by the interaction between genotype and environment, and it is considered to be a type of addictive alteration. The A1 allele of the DRD2/ANKK1-TaqIA gene has been associated with addictive disorders, with obesity and with the performance in executive functions. The 7 repeat allele of the DRD4 gene has likewise been associated with the performance in executive functions, as well as with addictive behaviors and impulsivity. Participants were included in the obesity group (N = 42 if their body mass index (BMI was equal to or above 30, and in the lean group (N = 42 if their BMI was below 25. The DRD2/ANKK1-TaqIA and DRD4 VNTR polymorphisms were obtained. All subjects underwent neuropsychological assessment. Eating behavior traits were evaluated. The 'DRD2/ANKK1-TaqIA A1-allele status' had a significant effect on almost all the executive variables, but no significant 'DRD4 7R-allele status' effects were observed for any of the executive variables analyzed. There was a significant 'group' x 'DRD2/ANKK1-TaqIA A1-allele status' interaction effect on LN and 'group' x 'DRD4 7R-allele status' interaction effect on TMT B-A score. Being obese and a carrier of the A1 allele of DRD2/ANKK1-TaqIA or the 7R allele of DRD4 VNTR polymorphisms could confer a weakness as regards the performance of executive functions.

genotype by environment interaction and grain yield stability

African Journals Online (AJOL)

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among environments, GXE interaction and Interaction Principal Component Analysis (IPCA-I) but ... value closer to zero, Genotype Selection Index (GSI) of 4 each and AMMI stability value (ASV) of 0.124 and. 0.087 ..... Analysis of variance for grain yield using Additive Mean Effect and Multiple Interactions (AMMI) model.

Non-formal Learning through Ludic Engagement within Interactive Environments

DEFF Research Database (Denmark)

Petersson, Eva

Adaptive responsive environments that encourage interaction for children with severe disabilities offer a distinct potential for play and learning in rehabilitation. Physical training and therapy for these children is often enduring, tedious, and boring through repetition – and this is often...... the case for both the child and the facilitator/therapist. Despite this, little is yet known about how the utilization of empowering technology influences the users’ communication and learning. The aim of this thesis is twofold: to contribute to the understanding of the role of action and interaction...... in the learning involved when people with different abilities are using interactive environments, and to make a contribution to the research field by concluding at tentative generalizations on design for non-formal learning in interactive environments.      The thesis consists of seven studies which analyze...

Ranking candidate disease genes from gene expression and protein interaction: a Katz-centrality based approach.

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Jing Zhao

Full Text Available Many diseases have complex genetic causes, where a set of alleles can affect the propensity of getting the disease. The identification of such disease genes is important to understand the mechanistic and evolutionary aspects of pathogenesis, improve diagnosis and treatment of the disease, and aid in drug discovery. Current genetic studies typically identify chromosomal regions associated specific diseases. But picking out an unknown disease gene from hundreds of candidates located on the same genomic interval is still challenging. In this study, we propose an approach to prioritize candidate genes by integrating data of gene expression level, protein-protein interaction strength and known disease genes. Our method is based only on two, simple, biologically motivated assumptions--that a gene is a good disease-gene candidate if it is differentially expressed in cases and controls, or that it is close to other disease-gene candidates in its protein interaction network. We tested our method on 40 diseases in 58 gene expression datasets of the NCBI Gene Expression Omnibus database. On these datasets our method is able to predict unknown disease genes as well as identifying pleiotropic genes involved in the physiological cellular processes of many diseases. Our study not only provides an effective algorithm for prioritizing candidate disease genes but is also a way to discover phenotypic interdependency, cooccurrence and shared pathophysiology between different disorders.

Association and interaction analyses of 5-HT3 receptor and serotonin transporter genes with alcohol, cocaine, and nicotine dependence using the SAGE data.

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Yang, Jiekun; Li, Ming D

2014-07-01

Previous studies have implicated genes encoding the 5-HT3AB receptors (HTR3A and HTR3B) and the serotonin transporter (SLC6A4), both independently and interactively, in alcohol (AD), cocaine (CD), and nicotine dependence (ND). However, whether these genetic effects also exist in subjects with comorbidities remains largely unknown. We used 1,136 African-American (AA) and 2,428 European-American (EA) subjects from the Study of Addiction: Genetics and Environment (SAGE) to determine associations between 88 genotyped or imputed variants within HTR3A, HTR3B, and SLC6A4 and three types of addictions, which were measured by DSM-IV diagnoses of AD, CD, and ND and the Fagerström Test for Nicotine Dependence (FTND), an independent measure of ND commonly used in tobacco research. Individual SNP-based association analysis revealed a significant association of rs2066713 in SLC6A4 with FTND in AA (β = -1.39; P = 1.6E - 04). Haplotype-based association analysis found one major haplotype formed by SNPs rs3891484 and rs3758987 in HTR3B that was significantly associated with AD in the AA sample, and another major haplotype T-T-G, formed by SNPs rs7118530, rs12221649, and rs2085421 in HTR3A, which showed significant association with FTND in the EA sample. Considering the biologic roles of the three genes and their functional relations, we used the GPU-based Generalized Multifactor Dimensionality Reduction (GMDR-GPU) program to test SNP-by-SNP interactions within the three genes and discovered two- to five-variant models that have significant impacts on AD, CD, ND, or FTND. Interestingly, most of the SNPs included in the genetic interaction model(s) for each addictive phenotype are either overlapped or in high linkage disequilibrium for both AA and EA samples, suggesting these detected variants in HTR3A, HTR3B, and SLC6A4 are interactively contributing to etiology of the three addictive phenotypes examined in this study.

Alteration of synaptic activity-regulating genes underlying functional improvement by long-term exposure to an enriched environment in the adult brain.

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Lee, Min-Young; Yu, Ji Hea; Kim, Ji Yeon; Seo, Jung Hwa; Park, Eun Sook; Kim, Chul Hoon; Kim, Hyongbum; Cho, Sung-Rae

2013-01-01

Housing animals in an enriched environment (EE) enhances behavioral function. However, the mechanism underlying this EE-mediated functional improvement and the resultant changes in gene expression have yet to be elucidated. We attempted to investigate the underlying mechanisms associated with long-term exposure to an EE by evaluating gene expression patterns. We housed 6-week-old CD-1 (ICR) mice in standard cages or an EE comprising a running wheel, novel objects, and social interaction for 2 months. Motor and cognitive performances were evaluated using the rotarod test and passive avoidance test, and gene expression profile was investigated in the cerebral hemispheres using microarray and gene set enrichment analysis (GSEA). In behavioral assessment, an EE significantly enhanced rotarod performance and short-term working memory. Microarray analysis revealed that genes associated with neuronal activity were significantly altered by an EE. GSEA showed that genes involved in synaptic transmission and postsynaptic signal transduction were globally upregulated, whereas those associated with reuptake by presynaptic neurotransmitter transporters were downregulated. In particular, both microarray and GSEA demonstrated that EE exposure increased opioid signaling, acetylcholine release cycle, and postsynaptic neurotransmitter receptors but decreased Na+ / Cl- -dependent neurotransmitter transporters, including dopamine transporter Slc6a3 in the brain. Western blotting confirmed that SLC6A3, DARPP32 (PPP1R1B), and P2RY12 were largely altered in a region-specific manner. An EE enhanced motor and cognitive function through the alteration of synaptic activity-regulating genes, improving the efficient use of neurotransmitters and synaptic plasticity by the upregulation of genes associated with postsynaptic receptor activity and downregulation of presynaptic reuptake by neurotransmitter transporters.

Diet-gene interactions between dietary fat intake and common polymorphisms in determining lipid metabolism

Energy Technology Data Exchange (ETDEWEB)

Corella, D.

2009-07-01

Current dietary guidelines for fat intake have not taken into consideration the possible genetic differences underlying the individual variability in responsiveness to dietary components. Genetic variability has been identified in humans for all the known lipid metabolism-related genes resulting in a plethora of candidate genes and genetic variants to examine in diet-gene interaction studies focused on fat consumption. Some examples of fat-gene interaction are reviewed. These include: the interaction between total intake and the 14C/T in the hepatic lipase gene promoter in determining high-density lipoprotein cholesterol (HDL-C) metabolism; the interaction between polyunsaturated fatty acids (PUFA) and the 5G/A polymorphism in the APOA1 gene plasma HDL-C concentrations; the interaction between PUFA and the L162V polymorphism in the PPARA gene in determining triglycerides and APOC3 concentrations; and the interaction between PUFA intake and the -1131T>C in the APOA5 gene in determining triglyceride metabolism. Although hundreds of diet-gene interaction studies in lipid metabolism have been published, the level of evidence to make specific nutritional recommendations to the population is still low and more research in nutrigenetics has to be undertaken. (Author) 31 refs.

Interaction between CRHR1 and BDNF genes increases the risk of recurrent major depressive disorder in Chinese population.

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Zheman Xiao

Full Text Available BACKGROUND: An important etiological hypothesis about depression is stress has neurotoxic effects that damage the hippocampal cells. Corticotropin-releasing hormone (CRH regulates brain-derived neurotrophic factor (BDNF expression through influencing cAMP and Ca2+ signaling pathways during the course. The aim of this study is to examine the single and combined effects of CRH receptor 1 (CRHR1 and BDNF genes in recurrent major depressive disorder (MDD. METHODOLOGY/PRINCIPAL FINDING: The sample consists of 181 patients with recurrent MDD and 186 healthy controls. Whether genetic variations interaction between CRHR1 and BDNF genes might be associated with increased susceptibility to recurrent MDD was studied by using a gene-based association analysis of single-nucleotide polymorphisms (SNPs. CRHR1 gene (rs1876828, rs242939 and rs242941 and BDNF gene (rs6265 were identified in the samples of patients diagnosed with recurrent MDD and matched controls. Allelic association between CRHR1 rs242939 and recurrent MDD was found in our sample (allelic: p = 0.018, genotypic: p = 0.022 with an Odds Ratio 0.454 (95% CI 0.266-0.775. A global test of these four haplotypes showed a significant difference between recurrent MDD group and control group (chi-2 = 13.117, df = 3, P = 0.016. Furthermore, BDNF and CRHR1 interactions were found in the significant 2-locus, gene-gene interaction models (p = 0.05 using a generalized multifactor dimensionality reduction (GMDR method. CONCLUSION: Our results suggest that an interaction between CRHR1 and BDNF genes constitutes susceptibility to recurrent MDD.

Integration of human adipocyte chromosomal interactions with adipose gene expression prioritizes obesity-related genes from GWAS.

Science.gov (United States)

Pan, David Z; Garske, Kristina M; Alvarez, Marcus; Bhagat, Yash V; Boocock, James; Nikkola, Elina; Miao, Zong; Raulerson, Chelsea K; Cantor, Rita M; Civelek, Mete; Glastonbury, Craig A; Small, Kerrin S; Boehnke, Michael; Lusis, Aldons J; Sinsheimer, Janet S; Mohlke, Karen L; Laakso, Markku; Pajukanta, Päivi; Ko, Arthur

2018-04-17

Increased adiposity is a hallmark of obesity and overweight, which affect 2.2 billion people world-wide. Understanding the genetic and molecular mechanisms that underlie obesity-related phenotypes can help to improve treatment options and drug development. Here we perform promoter Capture Hi-C in human adipocytes to investigate interactions between gene promoters and distal elements as a transcription-regulating mechanism contributing to these phenotypes. We find that promoter-interacting elements in human adipocytes are enriched for adipose-related transcription factor motifs, such as PPARG and CEBPB, and contribute to heritability of cis-regulated gene expression. We further intersect these data with published genome-wide association studies for BMI and BMI-related metabolic traits to identify the genes that are under genetic cis regulation in human adipocytes via chromosomal interactions. This integrative genomics approach identifies four cis-eQTL-eGene relationships associated with BMI or obesity-related traits, including rs4776984 and MAP2K5, which we further confirm by EMSA, and highlights 38 additional candidate genes.

Identifying Gene-Environment Interactions in Schizophrenia

DEFF Research Database (Denmark)

van Os, Jim; Rutten, Bart P; Myin-Germeys, Inez

2014-01-01

Recent years have seen considerable progress in epidemiological and molecular genetic research into environmental and genetic factors in schizophrenia, but methodological uncertainties remain with regard to validating environmental exposures, and the population risk conferred by individual...... of G × E in schizophrenia. While such investigations are now well underway, new challenges emerge for G × E research from late-breaking evidence that genetic variation and environmental exposures are, to a significant degree, shared across a range of psychiatric disorders, with potential overlap...

How much can a large population study on genes, environments, their interactions and common diseases contribute to the health of the American people?

Science.gov (United States)

Chaufan, Claudia

2007-10-01

I offer a critical perspective on a large-scale population study on gene-environment interactions and common diseases proposed by the US Secretary of Health and Human Services' Advisory Committee on Genetics, Health, and Society (SACGHS). I argue that for scientific and policy reasons this and similar studies have little to add to current knowledge about how to prevent, treat, or decrease inequalities in common diseases, all of which are major claims of the proposal. I use diabetes as an exemplar of the diseases that the study purports to illuminate. I conclude that the question is not whether the study will meet expectations or whether the current emphasis on a genetic paradigm is real or imagined, desirable or not. Rather, the question is why, given the flaws of the science underwriting the study, its assumptions remain unchallenged. Future research should investigate the reasons for this immunity from criticism and for the popularity of this and similar projects among laypersons as well as among intellectuals.

Gene-diet interaction effects on BMI levels in the Singapore Chinese population.

Science.gov (United States)

Chang, Xuling; Dorajoo, Rajkumar; Sun, Ye; Han, Yi; Wang, Ling; Khor, Chiea-Chuen; Sim, Xueling; Tai, E-Shyong; Liu, Jianjun; Yuan, Jian-Min; Koh, Woon-Puay; van Dam, Rob M; Friedlander, Yechiel; Heng, Chew-Kiat

2018-02-24

Recent genome-wide association studies (GWAS) have identified 97 body-mass index (BMI) associated loci. We aimed to evaluate if dietary intake modifies BMI associations at these loci in the Singapore Chinese population. We utilized GWAS information from six data subsets from two adult Chinese population (N = 7817). Seventy-eight genotyped or imputed index BMI single nucleotide polymorphisms (SNPs) that passed quality control procedures were available in all datasets. Alternative Healthy Eating Index (AHEI)-2010 score and ten nutrient variables were evaluated. Linear regression analyses between z score transformed BMI (Z-BMI) and dietary factors were performed. Interaction analyses were performed by introducing the interaction term (diet x SNP) in the same regression model. Analysis was carried out in each cohort individually and subsequently meta-analyzed using the inverse-variance weighted method. Analyses were also evaluated with a weighted gene-risk score (wGRS) contructed by BMI index SNPs from recent large-scale GWAS studies. Nominal associations between Z-BMI and AHEI-2010 and some dietary factors were identified (P = 0.047-0.010). The BMI wGRS was robustly associated with Z-BMI (P = 1.55 × 10 - 15 ) but not with any dietary variables. Dietary variables did not significantly interact with the wGRS to modify BMI associations. When interaction analyses were repeated using individual SNPs, a significant association between cholesterol intake and rs4740619 (CCDC171) was identified (β = 0.077, adjP interaction  = 0.043). The CCDC171 gene locus may interact with cholesterol intake to increase BMI in the Singaporean Chinese population, however most known obesity risk loci were not associated with dietary intake and did not interact with diet to modify BMI levels.

Gene-environment interactions in cancer epidemiology: a National Cancer Institute Think Tank report.

Science.gov (United States)

Hutter, Carolyn M; Mechanic, Leah E; Chatterjee, Nilanjan; Kraft, Peter; Gillanders, Elizabeth M

2013-11-01

Cancer risk is determined by a complex interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified hundreds of common (minor allele frequency [MAF] > 0.05) and less common (0.01 Think Tank" on January 10-11, 2012. The objective of the Think Tank was to facilitate discussions on (1) the state of the science, (2) the goals of G × E interaction studies in cancer epidemiology, and (3) opportunities for developing novel study designs and analysis tools. This report summarizes the Think Tank discussion, with a focus on contemporary approaches to the analysis of G × E interactions. Selecting the appropriate methods requires first identifying the relevant scientific question and rationale, with an important distinction made between analyses aiming to characterize the joint effects of putative or established genetic and environmental factors and analyses aiming to discover novel risk factors or novel interaction effects. Other discussion items include measurement error, statistical power, significance, and replication. Additional designs, exposure assessments, and analytical approaches need to be considered as we move from the current small number of success stories to a fuller understanding of the interplay of genetic and environmental factors. © 2013 WILEY PERIODICALS, INC.

Genome-environment interactions and prospective technology assessment: evolution from pharmacogenomics to nutrigenomics and ecogenomics.

Science.gov (United States)

Ozdemir, Vural; Motulsky, Arno G; Kolker, Eugene; Godard, Béatrice

2009-02-01

The relationships between food, nutrition science, and health outcomes have been mapped over the past century. Genomic variation among individuals and populations is a new factor that enriches and challenges our understanding of these complex relationships. Hence, the confluence of nutritional science and genomics-nutrigenomics--was the focus of the OMICS: A Journal of Integrative Biology in December 2008 (Part 1). The 2009 Special Issue (Part 2) concludes the analysis of nutrigenomics research and innovations. Together, these two issues expand the scope and depth of critical scholarship in nutrigenomics, in keeping with an integrated multidisciplinary analysis across the bioscience, omics technology, social, ethical, intellectual property and policy dimensions. Historically, the field of pharmacogenetics provided the first examples of specifically identifiable gene variants predisposing to unexpected responses to drugs since the 1950s. Brewer coined the term ecogenetics in 1971 to broaden the concept of gene-environment interactions from drugs and nutrition to include environmental agents in general. In the mid-1990s, introduction of high-throughput technologies led to the terms pharmacogenomics, nutrigenomics and ecogenomics to describe, respectively, the contribution of genomic variability to differential responses to drugs, food, and environment defined in the broadest sense. The distinctions, if any, between these newer fields (e.g., nutrigenomics) and their predecessors (e.g., nutrigenetics) remain to be delineated. For nutrigenomics, its reliance on genome-wide analyses may lead to detection of new biological mechanisms governing host response to food. Recognizing "genome-environment interactions" as the conceptual thread that connects and runs through pharmacogenomics, nutrigenomics, and ecogenomics may contribute toward anticipatory governance and prospective real-time analysis of these omics fields. Such real-time analysis of omics technologies and

Gene-gene and gene-environment interactions in prostate, breast and colorectal cancer

DEFF Research Database (Denmark)

Kopp, Tine Iskov

The incidence of cancer in the western world has increased steeply during the last 50 years. For three of the most prevalent cancer types in Denmark, prostate, breast and colorectal cancer (PC, BC and CRC, respectively), only a small fraction (1-15%) of the incidences are caused by highly penetrant...... in alcohol-related BC in postmenopausal women involving a specific polymorphism in PPARG (coding the peroxisome proliferatoractivated receptor (PPARγ)) and its interaction with the aromatase (encoded by CYP19A1) was investigated (Paper V-VI). The Danish prospective “Diet, Cancer and Health” cohort study...... as having strong influence on carcinogenesis. Therefore, very frequent, low effect polymorphisms may have a greater contribution on a population level in combination with environmental factors. Indeed, several dietary and life style factors are now well-established risk factors for different cancer types...

Assessment of gene-by-sex interaction effect on bone mineral density

DEFF Research Database (Denmark)

Liu, Ching-Ti; Estrada, Karol; Yerges-Armstrong, Laura M

2012-01-01

Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however, the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome-wide, and ......Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however, the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome...

Global map of physical interactions among differentially expressed genes in multiple sclerosis relapses and remissions.

Science.gov (United States)

Tuller, Tamir; Atar, Shimshi; Ruppin, Eytan; Gurevich, Michael; Achiron, Anat

2011-09-15

Multiple sclerosis (MS) is a central nervous system autoimmune inflammatory T-cell-mediated disease with a relapsing-remitting course in the majority of patients. In this study, we performed a high-resolution systems biology analysis of gene expression and physical interactions in MS relapse and remission. To this end, we integrated 164 large-scale measurements of gene expression in peripheral blood mononuclear cells of MS patients in relapse or remission and healthy subjects, with large-scale information about the physical interactions between these genes obtained from public databases. These data were analyzed with a variety of computational methods. We find that there is a clear and significant global network-level signal that is related to the changes in gene expression of MS patients in comparison to healthy subjects. However, despite the clear differences in the clinical symptoms of MS patients in relapse versus remission, the network level signal is weaker when comparing patients in these two stages of the disease. This result suggests that most of the genes have relatively similar expression levels in the two stages of the disease. In accordance with previous studies, we found that the pathways related to regulation of cell death, chemotaxis and inflammatory response are differentially expressed in the disease in comparison to healthy subjects, while pathways related to cell adhesion, cell migration and cell-cell signaling are activated in relapse in comparison to remission. However, the current study includes a detailed report of the exact set of genes involved in these pathways and the interactions between them. For example, we found that the genes TP53 and IL1 are 'network-hub' that interacts with many of the differentially expressed genes in MS patients versus healthy subjects, and the epidermal growth factor receptor is a 'network-hub' in the case of MS patients with relapse versus remission. The statistical approaches employed in this study enabled us

Designing learning environments to teach interactive Quantum Physics

NARCIS (Netherlands)

Gómez Puente, S.M.; Swagten, H.J.M.

2012-01-01

This study aims at describing and analysing systematically an interactive learning environment designed to teach Quantum Physics, a second-year physics course. The instructional design of Quantum Physics is a combination of interactive lectures (using audience response systems), tutorials and

Involvement in the professional environment and its significance for lifelong learning

Directory of Open Access Journals (Sweden)

Litvinova E.Yu.

2017-07-01

Full Text Available The analysis of the existing definitions of a phenomenon of the professional environment and various approaches to understanding of her components is presented in article. The attention is paid to consideration of such social and psychological components of the professional environment as professional culture, professional groups and communities. On the basis of the theoretical analysis the author's understanding of functions of the professional environment is offered, also the model of dynamics of an involvement developed by authors on professional environment is provided, its stages are described. The involvement on professional environment is considered as the steady condition of active interaction of the subject with the professional environment which is shown in behavioral activity both in the environment and beyond its limits as the representative of this professional environment. The multidimensionality and relevance of studying of interference of the professional environment and professional education is accented. Arguments for benefit of rapprochement of the educational and professional environment are adduced. In the article the need of studying of interrelation of the involvement in professional environment and the involvement in lifelong education as conditions of successful adaptation and development of the modern professional is proved for the first time.

Interaction between prenatal pesticide exposure and a common polymorphism in the PON1 gene on DNA methylation in genes associated with cardio-metabolic disease risk-an exploratory study

DEFF Research Database (Denmark)

Declerck, Ken; Remy, Sylvie; Wohlfahrt-Veje, Christine

2017-01-01

BACKGROUND: Prenatal environmental conditions may influence disease risk in later life. We previously found a gene-environment interaction between the paraoxonase 1 (PON1) Q192R genotype and prenatal pesticide exposure leading to an adverse cardio-metabolic risk profile at school age. However...... was observed in prenatally pesticide exposed children carrying the PON1 192R-allele. Differentially methylated genes were enriched in several neuroendocrine signaling pathways including dopamine-DARPP32 feedback (appetite, reward pathways), corticotrophin releasing hormone signaling, nNOS, neuregulin signaling...

Assessing SNP-SNP interactions among DNA repair, modification and metabolism related pathway genes in breast cancer susceptibility.

Directory of Open Access Journals (Sweden)

Yadav Sapkota

Full Text Available Genome-wide association studies (GWASs have identified low-penetrance common variants (i.e., single nucleotide polymorphisms, SNPs associated with breast cancer susceptibility. Although GWASs are primarily focused on single-locus effects, gene-gene interactions (i.e., epistasis are also assumed to contribute to the genetic risks for complex diseases including breast cancer. While it has been hypothesized that moderately ranked (P value based weak single-locus effects in GWASs could potentially harbor valuable information for evaluating epistasis, we lack systematic efforts to investigate SNPs showing consistent associations with weak statistical significance across independent discovery and replication stages. The objectives of this study were i to select SNPs showing single-locus effects with weak statistical significance for breast cancer in a GWAS and/or candidate-gene studies; ii to replicate these SNPs in an independent set of breast cancer cases and controls; and iii to explore their potential SNP-SNP interactions contributing to breast cancer susceptibility. A total of 17 SNPs related to DNA repair, modification and metabolism pathway genes were selected since these pathways offer a priori knowledge for potential epistatic interactions and an overall role in breast carcinogenesis. The study design included predominantly Caucasian women (2,795 cases and 4,505 controls from Alberta, Canada. We observed two two-way SNP-SNP interactions (APEX1-rs1130409 and RPAP1-rs2297381; MLH1-rs1799977 and MDM2-rs769412 in logistic regression that conferred elevated risks for breast cancer (P(interaction<7.3 × 10(-3. Logic regression identified an interaction involving four SNPs (MBD2-rs4041245, MLH1-rs1799977, MDM2-rs769412, BRCA2-rs1799943 (P(permutation = 2.4 × 10(-3. SNPs involved in SNP-SNP interactions also showed single-locus effects with weak statistical significance, while BRCA2-rs1799943 showed stronger statistical significance (P

GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature

Directory of Open Access Journals (Sweden)

Ning Ye

2015-01-01

Full Text Available The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures.

Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment.