A Nonlinear Model for Gene-Based Gene-Environment Interaction.

PubMed

Sa, Jian; Liu, Xu; He, Tao; Liu, Guifen; Cui, Yuehua

2016-06-04

A vast amount of literature has confirmed the role of gene-environment (G×E) interaction in the etiology of complex human diseases. Traditional methods are predominantly focused on the analysis of interaction between a single nucleotide polymorphism (SNP) and an environmental variable. Given that genes are the functional units, it is crucial to understand how gene effects (rather than single SNP effects) are influenced by an environmental variable to affect disease risk. Motivated by the increasing awareness of the power of gene-based association analysis over single variant based approach, in this work, we proposed a sparse principle component regression (sPCR) model to understand the gene-based G×E interaction effect on complex disease. We first extracted the sparse principal components for SNPs in a gene, then the effect of each principal component was modeled by a varying-coefficient (VC) model. The model can jointly model variants in a gene in which their effects are nonlinearly influenced by an environmental variable. In addition, the varying-coefficient sPCR (VC-sPCR) model has nice interpretation property since the sparsity on the principal component loadings can tell the relative importance of the corresponding SNPs in each component. We applied our method to a human birth weight dataset in Thai population. We analyzed 12,005 genes across 22 chromosomes and found one significant interaction effect using the Bonferroni correction method and one suggestive interaction. The model performance was further evaluated through simulation studies. Our model provides a system approach to evaluate gene-based G×E interaction.

A Combinatorial Approach to Detecting Gene-Gene and Gene-Environment Interactions in Family Studies

PubMed Central

Lou, Xiang-Yang; Chen, Guo-Bo; Yan, Lei; Ma, Jennie Z.; Mangold, Jamie E.; Zhu, Jun; Elston, Robert C.; Li, Ming D.

2008-01-01

Widespread multifactor interactions present a significant challenge in determining risk factors of complex diseases. Several combinatorial approaches, such as the multifactor dimensionality reduction (MDR) method, have emerged as a promising tool for better detecting gene-gene (G × G) and gene-environment (G × E) interactions. We recently developed a general combinatorial approach, namely the generalized multifactor dimensionality reduction (GMDR) method, which can entertain both qualitative and quantitative phenotypes and allows for both discrete and continuous covariates to detect G × G and G × E interactions in a sample of unrelated individuals. In this article, we report the development of an algorithm that can be used to study G × G and G × E interactions for family-based designs, called pedigree-based GMDR (PGMDR). Compared to the available method, our proposed method has several major improvements, including allowing for covariate adjustments and being applicable to arbitrary phenotypes, arbitrary pedigree structures, and arbitrary patterns of missing marker genotypes. Our Monte Carlo simulations provide evidence that the PGMDR method is superior in performance to identify epistatic loci compared to the MDR-pedigree disequilibrium test (PDT). Finally, we applied our proposed approach to a genetic data set on tobacco dependence and found a significant interaction between two taste receptor genes (i.e., TAS2R16 and TAS2R38) in affecting nicotine dependence. PMID:18834969

Simulating the Yield Impacts of Organ-Level Quantitative Trait Loci Associated With Drought Response in Maize: A “Gene-to-Phenotype” Modeling Approach

PubMed Central

Chenu, Karine; Chapman, Scott C.; Tardieu, François; McLean, Greg; Welcker, Claude; Hammer, Graeme L.

2009-01-01

Under drought, substantial genotype–environment (G × E) interactions impede breeding progress for yield. Identifying genetic controls associated with yield response is confounded by poor genetic correlations across testing environments. Part of this problem is related to our inability to account for the interplay of genetic controls, physiological traits, and environmental conditions throughout the crop cycle. We propose a modeling approach to bridge this “gene-to-phenotype” gap. For maize under drought, we simulated the impact of quantitative trait loci (QTL) controlling two key processes (leaf and silk elongation) that influence crop growth, water use, and grain yield. Substantial G × E interaction for yield was simulated for hypothetical recombinant inbred lines (RILs) across different seasonal patterns of drought. QTL that accelerated leaf elongation caused an increase in crop leaf area and yield in well-watered or preflowering water deficit conditions, but a reduction in yield under terminal stresses (as such “leafy” genotypes prematurely exhausted the water supply). The QTL impact on yield was substantially enhanced by including pleiotropic effects of these QTL on silk elongation and on consequent grain set. The simulations obtained illustrated the difficulty of interpreting the genetic control of yield for genotypes influenced only by the additive effects of QTL associated with leaf and silk growth. The results highlight the potential of integrative simulation modeling for gene-to-phenotype prediction and for exploiting G × E interactions for complex traits such as drought tolerance. PMID:19786622

Dissecting gene-environment interactions: A penalized robust approach accounting for hierarchical structures.

PubMed

Wu, Cen; Jiang, Yu; Ren, Jie; Cui, Yuehua; Ma, Shuangge

2018-02-10

Identification of gene-environment (G × E) interactions associated with disease phenotypes has posed a great challenge in high-throughput cancer studies. The existing marginal identification methods have suffered from not being able to accommodate the joint effects of a large number of genetic variants, while some of the joint-effect methods have been limited by failing to respect the "main effects, interactions" hierarchy, by ignoring data contamination, and by using inefficient selection techniques under complex structural sparsity. In this article, we develop an effective penalization approach to identify important G × E interactions and main effects, which can account for the hierarchical structures of the 2 types of effects. Possible data contamination is accommodated by adopting the least absolute deviation loss function. The advantage of the proposed approach over the alternatives is convincingly demonstrated in both simulation and a case study on lung cancer prognosis with gene expression measurements and clinical covariates under the accelerated failure time model. Copyright © 2017 John Wiley & Sons, Ltd.

Specification, testing, and interpretation of gene-by-measured-environment interaction models in the presence of gene-environment correlation

PubMed Central

Rathouz, Paul J.; Van Hulle, Carol A.; Lee Rodgers, Joseph; Waldman, Irwin D.; Lahey, Benjamin B.

2009-01-01

Purcell (2002) proposed a bivariate biometric model for testing and quantifying the interaction between latent genetic influences and measured environments in the presence of gene-environment correlation. Purcell’s model extends the Cholesky model to include gene-environment interaction. We examine a number of closely-related alternative models that do not involve gene-environment interaction but which may fit the data as well Purcell’s model. Because failure to consider these alternatives could lead to spurious detection of gene-environment interaction, we propose alternative models for testing gene-environment interaction in the presence of gene-environment correlation, including one based on the correlated factors model. In addition, we note mathematical errors in the calculation of effect size via variance components in Purcell’s model. We propose a statistical method for deriving and interpreting variance decompositions that are true to the fitted model. PMID:18293078

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

PubMed

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.

Gene-gene and gene-environment interactions: new insights into the prevention, detection and management of coronary artery disease.

PubMed

Lanktree, Matthew B; Hegele, Robert A

2009-02-26

Despite the recent success of genome-wide association studies (GWASs) in identifying loci consistently associated with coronary artery disease (CAD), a large proportion of the genetic components of CAD and its metabolic risk factors, including plasma lipids, type 2 diabetes and body mass index, remain unattributed. Gene-gene and gene-environment interactions might produce a meaningful improvement in quantification of the genetic determinants of CAD. Testing for gene-gene and gene-environment interactions is thus a new frontier for large-scale GWASs of CAD. There are several anecdotal examples of monogenic susceptibility to CAD in which the phenotype was worsened by an adverse environment. In addition, small-scale candidate gene association studies with functional hypotheses have identified gene-environment interactions. For future evaluation of gene-gene and gene-environment interactions to achieve the same success as the single gene associations reported in recent GWASs, it will be important to pre-specify agreed standards of study design and statistical power, environmental exposure measurement, phenomic characterization and analytical strategies. Here we discuss these issues, particularly in relation to the investigation and potential clinical utility of gene-gene and gene-environment interactions in CAD.

cDNA microarray reveals the alterations of cytoskeleton-related genes in osteoblast under high magneto-gravitational environment.

PubMed

Qian, Airong; Di, Shengmeng; Gao, Xiang; Zhang, Wei; Tian, Zongcheng; Li, Jingbao; Hu, Lifang; Yang, Pengfei; Yin, Dachuan; Shang, Peng

2009-07-01

The diamagnetic levitation as a novel ground-based model for simulating a reduced gravity environment has been widely applied in many fields. In this study, a special designed superconducting magnet, which can produce three apparent gravity levels (0, 1, and 2 g), namely high magneto-gravitational environment (HMGE), was used to simulate space gravity environment. The effects of HMGE on osteoblast gene expression profile were investigated by microarray. Genes sensitive to diamagnetic levitation environment (0 g), gravity changes, and high magnetic field changes were sorted on the basis of typical cell functions. Cytoskeleton, as an intracellular load-bearing structure, plays an important role in gravity perception. Therefore, 13 cytoskeleton-related genes were chosen according to the results of microarray analysis, and the expressions of these genes were found to be altered under HMGE by real-time PCR. Based on the PCR results, the expressions of WASF2 (WAS protein family, member 2), WIPF1 (WAS/WASL interacting protein family, member 1), paxillin, and talin 1 were further identified by western blot assay. Results indicated that WASF2 and WIPF1 were more sensitive to altered gravity levels, and talin 1 and paxillin were sensitive to both magnetic field and gravity changes. Our findings demonstrated that HMGE can affect osteoblast gene expression profile and cytoskeleton-related genes expression. The identification of mechanosensitive genes may enhance our understandings to the mechanism of bone loss induced by microgravity and may provide some potential targets for preventing and treating bone loss or osteoporosis.

System Analysis of LWDH Related Genes Based on Text Mining in Biological Networks

PubMed Central

Miao, Yingbo; Zhang, Liangcai; Wang, Yang; Feng, Rennan; Yang, Lei; Zhang, Shihua; Jiang, Yongshuai; Liu, Guiyou

2014-01-01

Liuwei-dihuang (LWDH) is widely used in traditional Chinese medicine (TCM), but its molecular mechanism about gene interactions is unclear. LWDH genes were extracted from the existing literatures based on text mining technology. To simulate the complex molecular interactions that occur in the whole body, protein-protein interaction networks (PPINs) were constructed and the topological properties of LWDH genes were analyzed. LWDH genes have higher centrality properties and may play important roles in the complex biological network environment. It was also found that the distances within LWDH genes are smaller than expected, which means that the communication of LWDH genes during the biological process is rapid and effectual. At last, a comprehensive network of LWDH genes, including the related drugs and regulatory pathways at both the transcriptional and posttranscriptional levels, was constructed and analyzed. The biological network analysis strategy used in this study may be helpful for the understanding of molecular mechanism of TCM. PMID:25243143

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

PubMed

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.

Quantitative gene-gene and gene-environment mapping for leaf shape variation using tree-based models.

PubMed

Fu, Guifang; Dai, Xiaotian; Symanzik, Jürgen; Bushman, Shaun

2017-01-01

Leaf shape traits have long been a focus of many disciplines, but the complex genetic and environmental interactive mechanisms regulating leaf shape variation have not yet been investigated in detail. The question of the respective roles of genes and environment and how they interact to modulate leaf shape is a thorny evolutionary problem, and sophisticated methodology is needed to address it. In this study, we investigated a framework-level approach that inputs shape image photographs and genetic and environmental data, and then outputs the relative importance ranks of all variables after integrating shape feature extraction, dimension reduction, and tree-based statistical models. The power of the proposed framework was confirmed by simulation and a Populus szechuanica var. tibetica data set. This new methodology resulted in the detection of novel shape characteristics, and also confirmed some previous findings. The quantitative modeling of a combination of polygenetic, plastic, epistatic, and gene-environment interactive effects, as investigated in this study, will improve the discernment of quantitative leaf shape characteristics, and the methods are ready to be applied to other leaf morphology data sets. Unlike the majority of approaches in the quantitative leaf shape literature, this framework-level approach is data-driven, without assuming any pre-known shape attributes, landmarks, or model structures. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Gene-environment interactions in mental disorders

PubMed Central

Tsuang, Ming T; Bar, Jessica L; Stone, William S; Faraone, Stephen V

2004-01-01

Research clearly shows that both nature and nurture play important roles in the genesis of psychopathology. In this paper, we focus on 'gene-environment interaction' in mental disorders, using genetic control of sensitivity to the environment as our definition of that term. We begin with an examination of methodological issues involving gene-environment interactions, with examples concerning psychiatric and neurological conditions. Then we review the interactions in psychiatric disorders using twin, adoption and association designs. Finally, we consider gene-environment interactions in selected neurodevelopmental disorders (autism and schizophrenia). PMID:16633461

Correcting systematic inflation in genetic association tests that consider interaction effects: application to a genome-wide association study of posttraumatic stress disorder.

PubMed

Almli, Lynn M; Duncan, Richard; Feng, Hao; Ghosh, Debashis; Binder, Elisabeth B; Bradley, Bekh; Ressler, Kerry J; Conneely, Karen N; Epstein, Michael P

2014-12-01

Genetic association studies of psychiatric outcomes often consider interactions with environmental exposures and, in particular, apply tests that jointly consider gene and gene-environment interaction effects for analysis. Using a genome-wide association study (GWAS) of posttraumatic stress disorder (PTSD), we report that heteroscedasticity (defined as variability in outcome that differs by the value of the environmental exposure) can invalidate traditional joint tests of gene and gene-environment interaction. To identify the cause of bias in traditional joint tests of gene and gene-environment interaction in a PTSD GWAS and determine whether proposed robust joint tests are insensitive to this problem. The PTSD GWAS data set consisted of 3359 individuals (978 men and 2381 women) from the Grady Trauma Project (GTP), a cohort study from Atlanta, Georgia. The GTP performed genome-wide genotyping of participants and collected environmental exposures using the Childhood Trauma Questionnaire and Trauma Experiences Inventory. We performed joint interaction testing of the Beck Depression Inventory and modified PTSD Symptom Scale in the GTP GWAS. We assessed systematic bias in our interaction analyses using quantile-quantile plots and genome-wide inflation factors. Application of the traditional joint interaction test to the GTP GWAS yielded systematic inflation across different outcomes and environmental exposures (inflation-factor estimates ranging from 1.07 to 1.21), whereas application of the robust joint test to the same data set yielded no such inflation (inflation-factor estimates ranging from 1.01 to 1.02). Simulated data further revealed that the robust joint test is valid in different heteroscedasticity models, whereas the traditional joint test is invalid. The robust joint test also has power similar to the traditional joint test when heteroscedasticity is not an issue. We believe the robust joint test should be used in candidate-gene studies and GWASs of psychiatric outcomes that consider environmental interactions. To make the procedure useful for applied investigators, we created a software tool that can be called from the popular PLINK package for analysis.

Correcting Systematic Inflation in Genetic Association Tests That Consider Interaction Effects

PubMed Central

Almli, Lynn M.; Duncan, Richard; Feng, Hao; Ghosh, Debashis; Binder, Elisabeth B.; Bradley, Bekh; Ressler, Kerry J.; Conneely, Karen N.; Epstein, Michael P.

2015-01-01

IMPORTANCE Genetic association studies of psychiatric outcomes often consider interactions with environmental exposures and, in particular, apply tests that jointly consider gene and gene-environment interaction effects for analysis. Using a genome-wide association study (GWAS) of posttraumatic stress disorder (PTSD), we report that heteroscedasticity (defined as variability in outcome that differs by the value of the environmental exposure) can invalidate traditional joint tests of gene and gene-environment interaction. OBJECTIVES To identify the cause of bias in traditional joint tests of gene and gene-environment interaction in a PTSD GWAS and determine whether proposed robust joint tests are insensitive to this problem. DESIGN, SETTING, AND PARTICIPANTS The PTSD GWAS data set consisted of 3359 individuals (978 men and 2381 women) from the Grady Trauma Project (GTP), a cohort study from Atlanta, Georgia. The GTP performed genome-wide genotyping of participants and collected environmental exposures using the Childhood Trauma Questionnaire and Trauma Experiences Inventory. MAIN OUTCOMES AND MEASURES We performed joint interaction testing of the Beck Depression Inventory and modified PTSD Symptom Scale in the GTP GWAS. We assessed systematic bias in our interaction analyses using quantile-quantile plots and genome-wide inflation factors. RESULTS Application of the traditional joint interaction test to the GTP GWAS yielded systematic inflation across different outcomes and environmental exposures (inflation-factor estimates ranging from 1.07 to 1.21), whereas application of the robust joint test to the same data set yielded no such inflation (inflation-factor estimates ranging from 1.01 to 1.02). Simulated data further revealed that the robust joint test is valid in different heteroscedasticity models, whereas the traditional joint test is invalid. The robust joint test also has power similar to the traditional joint test when heteroscedasticity is not an issue. CONCLUSIONS AND RELEVANCE We believe the robust joint test should be used in candidate-gene studies and GWASs of psychiatric outcomes that consider environmental interactions. To make the procedure useful for applied investigators, we created a software tool that can be called from the popular PLINK package for analysis. PMID:25354142

GeneChip Expression Profiling Reveals the Alterations of Energy Metabolism Related Genes in Osteocytes under Large Gradient High Magnetic Fields

PubMed Central

Wang, Yang; Chen, Zhi-Hao; Yin, Chun; Ma, Jian-Hua; Li, Di-Jie; Zhao, Fan; Sun, Yu-Long; Hu, Li-Fang; Shang, Peng; Qian, Ai-Rong

2015-01-01

The diamagnetic levitation as a novel ground-based model for simulating a reduced gravity environment has recently been applied in life science research. In this study a specially designed superconducting magnet with a large gradient high magnetic field (LG-HMF), which can provide three apparent gravity levels (μ-g, 1-g, and 2-g), was used to simulate a space-like gravity environment. Osteocyte, as the most important mechanosensor in bone, takes a pivotal position in mediating the mechano-induced bone remodeling. In this study, the effects of LG-HMF on gene expression profiling of osteocyte-like cell line MLO-Y4 were investigated by Affymetrix DNA microarray. LG-HMF affected osteocyte gene expression profiling. Differentially expressed genes (DEGs) and data mining were further analyzed by using bioinfomatic tools, such as DAVID, iReport. 12 energy metabolism related genes (PFKL, AK4, ALDOC, COX7A1, STC1, ADM, CA9, CA12, P4HA1, APLN, GPR35 and GPR84) were further confirmed by real-time PCR. An integrated gene interaction network of 12 DEGs was constructed. Bio-data mining showed that genes involved in glucose metabolic process and apoptosis changed notablly. Our results demostrated that LG-HMF affected the expression of energy metabolism related genes in osteocyte. The identification of sensitive genes to special environments may provide some potential targets for preventing and treating bone loss or osteoporosis. PMID:25635858

GeneChip expression profiling reveals the alterations of energy metabolism related genes in osteocytes under large gradient high magnetic fields.

PubMed

Wang, Yang; Chen, Zhi-Hao; Yin, Chun; Ma, Jian-Hua; Li, Di-Jie; Zhao, Fan; Sun, Yu-Long; Hu, Li-Fang; Shang, Peng; Qian, Ai-Rong

2015-01-01

The diamagnetic levitation as a novel ground-based model for simulating a reduced gravity environment has recently been applied in life science research. In this study a specially designed superconducting magnet with a large gradient high magnetic field (LG-HMF), which can provide three apparent gravity levels (μ-g, 1-g, and 2-g), was used to simulate a space-like gravity environment. Osteocyte, as the most important mechanosensor in bone, takes a pivotal position in mediating the mechano-induced bone remodeling. In this study, the effects of LG-HMF on gene expression profiling of osteocyte-like cell line MLO-Y4 were investigated by Affymetrix DNA microarray. LG-HMF affected osteocyte gene expression profiling. Differentially expressed genes (DEGs) and data mining were further analyzed by using bioinfomatic tools, such as DAVID, iReport. 12 energy metabolism related genes (PFKL, AK4, ALDOC, COX7A1, STC1, ADM, CA9, CA12, P4HA1, APLN, GPR35 and GPR84) were further confirmed by real-time PCR. An integrated gene interaction network of 12 DEGs was constructed. Bio-data mining showed that genes involved in glucose metabolic process and apoptosis changed notablly. Our results demostrated that LG-HMF affected the expression of energy metabolism related genes in osteocyte. The identification of sensitive genes to special environments may provide some potential targets for preventing and treating bone loss or osteoporosis.

Protein modeling and molecular dynamics simulation of SlWRKY4 protein cloned from drought tolerant tomato (Solanum habrochaites) line EC520061.

PubMed

Karkute, Suhas G; Easwaran, Murugesh; Gujjar, Ranjit Singh; Piramanayagam, Shanmughavel; Singh, Major

2015-10-01

WRKY genes are members of one of the largest families of plant transcription factors and play an important role in response to biotic and abiotic stresses, and overall growth and development. Understanding the interaction of WRKY proteins with other proteins/ligands in plant cells is of utmost importance to develop plants having tolerance to biotic and abiotic stresses. The SlWRKY4 gene was cloned from a drought tolerant wild species of tomato (Solanum habrochaites) and the secondary structure and 3D modeling of this protein were predicted using Schrödinger Suite-Prime. Predicted structures were also subjected to plot against Ramachandran's conformation, and the modeled structure was minimized using Macromodel. Finally, the minimized structure was simulated in the water environment to check the protein stability. The behavior of the modeled structure was well-simulated and analyzed through RMSD and RMSF of the protein. The present work provides the modeled 3D structure of SlWRKY4 that will help in understanding the mechanism of gene regulation by further in silico interaction studies.

Genotype-based association models of complex diseases to detect gene-gene and gene-environment interactions.

PubMed

Lobach, Iryna; Fan, Ruzong; Manga, Prashiela

A central problem in genetic epidemiology is to identify and rank genetic markers involved in a disease. Complex diseases, such as cancer, hypertension, diabetes, are thought to be caused by an interaction of a panel of genetic factors, that can be identified by markers, which modulate environmental factors. Moreover, the effect of each genetic marker may be small. Hence, the association signal may be missed unless a large sample is considered, or a priori biomedical data are used. Recent advances generated a vast variety of a priori information, including linkage maps and information about gene regulatory dependence assembled into curated pathway databases. We propose a genotype-based approach that takes into account linkage disequilibrium (LD) information between genetic markers that are in moderate LD while modeling gene-gene and gene-environment interactions. A major advantage of our method is that the observed genetic information enters a model directly thus eliminating the need to estimate haplotype-phase. Our approach results in an algorithm that is inexpensive computationally and does not suffer from bias induced by haplotype-phase ambiguity. We investigated our model in a series of simulation experiments and demonstrated that the proposed approach results in estimates that are nearly unbiased and have small variability. We applied our method to the analysis of data from a melanoma case-control study and investigated interaction between a set of pigmentation genes and environmental factors defined by age and gender. Furthermore, an application of our method is demonstrated using a study of Alcohol Dependence.

Gene-environment interaction and suicidal behavior.

PubMed

Roy, Alec; Sarchiopone, Marco; Carli, Vladimir

2009-07-01

Studies have increasingly shown that gene-environment interactions are important in psychiatry. Suicidal behavior is a major public health problem. Suicide is generally considered to be a multi-determined act involving various areas of proximal and distal risk. Genetic risk factors are estimated to account for approximately 30% to 40% of the variance in suicidal behavior. In this article, the authors review relevant studies concerning the interaction between the serotonin transporter gene and environmental variables as a model of gene-environment interactions that may have an impact on suicidal behavior. The findings reviewed here suggest that there may be meaningful interactions between distal and proximal suicide risk factors that may amplify the risk of suicidal behavior. Future studies of suicidal behavior should examine both genetic and environmental variables and examine for gene-environment interactions.

Measured Gene-by-Environment Interaction in Relation to Attention-Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Nigg, Joel; Nikolas, Molly; Burt, S. Alexandra

2010-01-01

Objective: To summarize and evaluate the state of knowledge regarding the role of measured gene-by-environment interactions in relation to attention-deficit/hyperactivity disorder. Method: A selective review of methodologic issues was followed by a systematic search for relevant articles on measured gene-by-environment interactions; the search…

Design and analysis issues in gene and environment studies

PubMed Central

2012-01-01

Both nurture (environmental) and nature (genetic factors) play an important role in human disease etiology. Traditionally, these effects have been thought of as independent. This perspective is ill informed for non-mendelian complex disorders which result as an interaction between genetics and environment. To understand health and disease we must study how nature and nurture interact. Recent advances in human genomics and high-throughput biotechnology make it possible to study large numbers of genetic markers and gene products simultaneously to explore their interactions with environment. The purpose of this review is to discuss design and analytic issues for gene-environment interaction studies in the “-omics” era, with a focus on environmental and genetic epidemiological studies. We present an expanded environmental genomic disease paradigm. We discuss several study design issues for gene-environmental interaction studies, including confounding and selection bias, measurement of exposures and genotypes. We discuss statistical issues in studying gene-environment interactions in different study designs, such as choices of statistical models, assumptions regarding biological factors, and power and sample size considerations, especially in genome-wide gene-environment studies. Future research directions are also discussed. PMID:23253229

Design and analysis issues in gene and environment studies.

PubMed

Liu, Chen-yu; Maity, Arnab; Lin, Xihong; Wright, Robert O; Christiani, David C

2012-12-19

Both nurture (environmental) and nature (genetic factors) play an important role in human disease etiology. Traditionally, these effects have been thought of as independent. This perspective is ill informed for non-mendelian complex disorders which result as an interaction between genetics and environment. To understand health and disease we must study how nature and nurture interact. Recent advances in human genomics and high-throughput biotechnology make it possible to study large numbers of genetic markers and gene products simultaneously to explore their interactions with environment. The purpose of this review is to discuss design and analytic issues for gene-environment interaction studies in the "-omics" era, with a focus on environmental and genetic epidemiological studies. We present an expanded environmental genomic disease paradigm. We discuss several study design issues for gene-environmental interaction studies, including confounding and selection bias, measurement of exposures and genotypes. We discuss statistical issues in studying gene-environment interactions in different study designs, such as choices of statistical models, assumptions regarding biological factors, and power and sample size considerations, especially in genome-wide gene-environment studies. Future research directions are also discussed.

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

PubMed

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.

Why study gene-environment interactions?

USDA-ARS?s Scientific Manuscript database

PURPOSE OF REVIEW: We examine the reasons for investigating gene-environment interactions and address recent reports evaluating interactions between genes and environmental modulators in relation to cardiovascular disease and its common risk factors. RECENT FINDINGS: Studies focusing on smoking, phy...

Genetic and environmental factors affecting cryptic variations in gene regulatory networks

PubMed Central

2013-01-01

Background Cryptic genetic variation (CGV) is considered to facilitate phenotypic evolution by producing visible variations in response to changes in the internal and/or external environment. Several mechanisms enabling the accumulation and release of CGVs have been proposed. In this study, we focused on gene regulatory networks (GRNs) as an important mechanism for producing CGVs, and examined how interactions between GRNs and the environment influence the number of CGVs by using individual-based simulations. Results Populations of GRNs were allowed to evolve under various stabilizing selections, and we then measured the number of genetic and phenotypic variations that had arisen. Our results showed that CGVs were not depleted irrespective of the strength of the stabilizing selection for each phenotype, whereas the visible fraction of genetic variation in a population decreased with increasing strength of selection. On the other hand, increasing the number of different environments that individuals encountered within their lifetime (i.e., entailing plastic responses to multiple environments) suppressed the accumulation of CGVs, whereas the GRNs with more genes and interactions were favored in such heterogeneous environments. Conclusions Given the findings that the number of CGVs in a population was largely determined by the size (order) of GRNs, we propose that expansion of GRNs and adaptation to novel environments are mutually facilitating and sustainable sources of evolvability and hence the origins of biological diversity and complexity. PMID:23622056

Genetic and environmental factors affecting cryptic variations in gene regulatory networks.

PubMed

Iwasaki, Watal M; Tsuda, Masaki E; Kawata, Masakado

2013-04-26

Cryptic genetic variation (CGV) is considered to facilitate phenotypic evolution by producing visible variations in response to changes in the internal and/or external environment. Several mechanisms enabling the accumulation and release of CGVs have been proposed. In this study, we focused on gene regulatory networks (GRNs) as an important mechanism for producing CGVs, and examined how interactions between GRNs and the environment influence the number of CGVs by using individual-based simulations. Populations of GRNs were allowed to evolve under various stabilizing selections, and we then measured the number of genetic and phenotypic variations that had arisen. Our results showed that CGVs were not depleted irrespective of the strength of the stabilizing selection for each phenotype, whereas the visible fraction of genetic variation in a population decreased with increasing strength of selection. On the other hand, increasing the number of different environments that individuals encountered within their lifetime (i.e., entailing plastic responses to multiple environments) suppressed the accumulation of CGVs, whereas the GRNs with more genes and interactions were favored in such heterogeneous environments. Given the findings that the number of CGVs in a population was largely determined by the size (order) of GRNs, we propose that expansion of GRNs and adaptation to novel environments are mutually facilitating and sustainable sources of evolvability and hence the origins of biological diversity and complexity.

ATHENA: A knowledge-based hybrid backpropagation-grammatical evolution neural network algorithm for discovering epistasis among quantitative trait Loci

PubMed Central

2010-01-01

Background Growing interest and burgeoning technology for discovering genetic mechanisms that influence disease processes have ushered in a flood of genetic association studies over the last decade, yet little heritability in highly studied complex traits has been explained by genetic variation. Non-additive gene-gene interactions, which are not often explored, are thought to be one source of this "missing" heritability. Methods Stochastic methods employing evolutionary algorithms have demonstrated promise in being able to detect and model gene-gene and gene-environment interactions that influence human traits. Here we demonstrate modifications to a neural network algorithm in ATHENA (the Analysis Tool for Heritable and Environmental Network Associations) resulting in clear performance improvements for discovering gene-gene interactions that influence human traits. We employed an alternative tree-based crossover, backpropagation for locally fitting neural network weights, and incorporation of domain knowledge obtainable from publicly accessible biological databases for initializing the search for gene-gene interactions. We tested these modifications in silico using simulated datasets. Results We show that the alternative tree-based crossover modification resulted in a modest increase in the sensitivity of the ATHENA algorithm for discovering gene-gene interactions. The performance increase was highly statistically significant when backpropagation was used to locally fit NN weights. We also demonstrate that using domain knowledge to initialize the search for gene-gene interactions results in a large performance increase, especially when the search space is larger than the search coverage. Conclusions We show that a hybrid optimization procedure, alternative crossover strategies, and incorporation of domain knowledge from publicly available biological databases can result in marked increases in sensitivity and performance of the ATHENA algorithm for detecting and modelling gene-gene interactions that influence a complex human trait. PMID:20875103

A cis-regulatory logic simulator.

PubMed

Zeigler, Robert D; Gertz, Jason; Cohen, Barak A

2007-07-27

A major goal of computational studies of gene regulation is to accurately predict the expression of genes based on the cis-regulatory content of their promoters. The development of computational methods to decode the interactions among cis-regulatory elements has been slow, in part, because it is difficult to know, without extensive experimental validation, whether a particular method identifies the correct cis-regulatory interactions that underlie a given set of expression data. There is an urgent need for test expression data in which the interactions among cis-regulatory sites that produce the data are known. The ability to rapidly generate such data sets would facilitate the development and comparison of computational methods that predict gene expression patterns from promoter sequence. We developed a gene expression simulator which generates expression data using user-defined interactions between cis-regulatory sites. The simulator can incorporate additive, cooperative, competitive, and synergistic interactions between regulatory elements. Constraints on the spacing, distance, and orientation of regulatory elements and their interactions may also be defined and Gaussian noise can be added to the expression values. The simulator allows for a data transformation that simulates the sigmoid shape of expression levels from real promoters. We found good agreement between sets of simulated promoters and predicted regulatory modules from real expression data. We present several data sets that may be useful for testing new methodologies for predicting gene expression from promoter sequence. We developed a flexible gene expression simulator that rapidly generates large numbers of simulated promoters and their corresponding transcriptional output based on specified interactions between cis-regulatory sites. When appropriate rule sets are used, the data generated by our simulator faithfully reproduces experimentally derived data sets. We anticipate that using simulated gene expression data sets will facilitate the direct comparison of computational strategies to predict gene expression from promoter sequence. The source code is available online and as additional material. The test sets are available as additional material.

Interactive Effects of in Utero Nutrition and Genetic Inheritance on Cognition: New Evidence Using Sibling Comparisons1

PubMed Central

Cook, C. Justin; Fletcher, Jason M.

2013-01-01

A large literature links early environments and later outcomes, such as cognition; however, little is known about the mechanisms. One potential mechanism is sensitivity to early environments that is moderated or amplified by the genotype. With this mechanism in mind, a complementary literature outside economics examines the interaction between genes and environments, but often problems of endogeneity and bias in estimation are uncorrected. A key issue in the literature is exploring environmental variation that is not exogenous, which is potentially problematic if there are gene-environment correlation or gene-gene interactions. Using sibling pairs with genetic data in the Wisconsin Longitudinal Study we extend a previous, and widely cited, gene-environment study that explores an interaction between the FADS2 gene, which is associated with the processing of essential fatty acids related to cognitive development, and early life nutrition in explaining later-life IQ. Our base OLS findings suggest that individuals with specific FADS2 variants gain roughly 0.15 standard deviations in IQ for each standard deviation increase in birth weight, our measure of the early nutrition environment; while, individuals with other variants of FADS2 do not have a statistically significant association with early nutrition, implying the genotype is influencing the effects of environmental exposure. When including family-level fixed effects, however, the magnitude of the gene-environment interaction is reduced by half and statistical significance dissipates, implying the interaction between FADS2 and early nutrition in explaining later life IQ may in part be due to unobserved, family-level factors. The example has wider implications for the practice of investigating gene-environment interactions when the environmental exposure is not exogenous and robustness to unobserved variation in the genome is not controlled for in the analysis. PMID:24172871

Gene-Environment Interactions in Schizophrenia: Review of Epidemiological Findings and Future Directions

PubMed Central

van Os, Jim; Rutten, Bart PF; Poulton, Richie

2008-01-01

Concern is building about high rates of schizophrenia in large cities, and among immigrants, cannabis users, and traumatized individuals, some of which likely reflects the causal influence of environmental exposures. This, in combination with very slow progress in the area of molecular genetics, has generated interest in more complicated models of schizophrenia etiology that explicitly posit gene-environment interactions (EU-GEI. European Network of Schizophrenia Networks for the Study of Gene Environment Interactions. Schizophrenia aetiology: do gene-environment interactions hold the key? [published online ahead of print April 25, 2008] Schizophr Res; S0920-9964(08) 00170–9). Although findings of epidemiological gene-environment interaction (G × E) studies are suggestive of widespread gene-environment interactions in the etiology of schizophrenia, numerous challenges remain. For example, attempts to identify gene-environment interactions cannot be equated with molecular genetic studies with a few putative environmental variables “thrown in”: G × E is a multidisciplinary exercise involving epidemiology, psychology, psychiatry, neuroscience, neuroimaging, pharmacology, biostatistics, and genetics. Epidemiological G × E studies using indirect measures of genetic risk in genetically sensitive designs have the advantage that they are able to model the net, albeit nonspecific, genetic load. In studies using direct molecular measures of genetic variation, a hypothesis-driven approach postulating synergistic effects between genes and environment impacting on a final common pathway, such as “sensitization” of mesolimbic dopamine neurotransmission, while simplistic, may provide initial focus and protection against the numerous false-positive and false-negative results that these investigations engender. Experimental ecogenetic approaches with randomized assignment may help to overcome some of the limitations of observational studies and allow for the additional elucidation of underlying mechanisms using a combination of functional enviromics and functional genomics. PMID:18791076

Chapter 20: geographic variability in growth of forest trees

Treesearch

Robert Z. Callaham

1962-01-01

Tree growth, like all plant characters, is a product of the interaction of genes and environment; however, the genes, environment, and interaction are not the same for every individual of a species. Genes exert master control over the plant's growth mechanisms. They control mechanisms for responding to environment and for utilizing environment in growth. Usually...

Disentangling Gene-Environment Correlations and Interactions on Adolescent Depressive Symptoms

ERIC Educational Resources Information Center

Lau, Jennifer Y. F.; Eley, Thalia C.

2008-01-01

Background: Genetic risks for depression may be expressed through greater exposure towards environmental stressors (gene-environment correlation, rGE) and increased susceptibility to these stressors (gene-environment interaction, G x E). While these effects are often studied independently, evidence supports their co-occurrence on depression.…

Modification of the association between early adversity and obsessive-compulsive disorder by polymorphisms in the MAOA, MAOB and COMT genes.

PubMed

McGregor, N W; Hemmings, S M J; Erdman, L; Calmarza-Font, I; Stein, D J; Lochner, C

2016-12-30

The monoamine oxidases (MAOA/B) and catechol-O-methyltransferase (COMT) enzymes break down regulatory components within serotonin and dopamine pathways, and polymorphisms within these genes are candidates for OCD susceptibility. Childhood trauma has been linked OCD psychopathology, but little attention has been paid to the interactions between genes and environment in OCD aetiology. This pilot study investigated gene-by-environment interactions between childhood trauma and polymorphisms in the MAOA, MAOB and COMT genes in OCD. Ten polymorphisms (MAOA: 3 variants, MAOB: 4 variants, COMT: 3 variants) were genotyped in a cohort of OCD patients and controls. Early-life trauma was assessed using the Childhood Trauma Questionnaire (CTQ). Gene-by-gene (GxG) and gene-by-environment interactions (GxE) of the variants and childhood trauma were assessed using logistic regression models. Significant GxG interactions were found between rs362204 (COMT) and two independent polymorphisms in the MAOB gene (rs1799836 and rs6651806). Haplotype associations for OCD susceptibility were found for MAOB. Investigation of GxE interactions indicated that the sexual abuse sub-category was significantly associated with all three genes in haplotype x environment interaction analyses. Preliminary findings indicate that polymorphisms within the MAOB and COMT genes interact resulting in risk for OCD. Childhood trauma interacts with haplotypes in COMT, MAOA and MAOB, increasing risk for OCD. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

NATURE VERSUS NURTURE: DEATH OF A DOGMA, AND THE ROAD AHEAD

PubMed Central

Traynor, Bryan J.; Singleton, Andrew B.

2010-01-01

Interaction between the genome and the environment has been widely discussed in the literature, but has the importance ascribed to understanding these interactions been overstated? In this opinion piece, we critically discuss gene-environment interactions and attempt to answer three key questions: First, is it likely that gene-environment interactions actually exist? Second, what is the realistic value of trying to unravel these interactions, both in terms of understanding disease pathogenesis and as a means of ameliorating disease? Finally, and most importantly, do the technologies and methodologies exist to facilitate an unbiased search for gene-environment interactions? Addressing these questions highlights key areas of feasibility that must be considered in this area of research. PMID:20955927

Latent variable models for gene-environment interactions in longitudinal studies with multiple correlated exposures.

PubMed

Tao, Yebin; Sánchez, Brisa N; Mukherjee, Bhramar

2015-03-30

Many existing cohort studies designed to investigate health effects of environmental exposures also collect data on genetic markers. The Early Life Exposures in Mexico to Environmental Toxicants project, for instance, has been genotyping single nucleotide polymorphisms on candidate genes involved in mental and nutrient metabolism and also in potentially shared metabolic pathways with the environmental exposures. Given the longitudinal nature of these cohort studies, rich exposure and outcome data are available to address novel questions regarding gene-environment interaction (G × E). Latent variable (LV) models have been effectively used for dimension reduction, helping with multiple testing and multicollinearity issues in the presence of correlated multivariate exposures and outcomes. In this paper, we first propose a modeling strategy, based on LV models, to examine the association between repeated outcome measures (e.g., child weight) and a set of correlated exposure biomarkers (e.g., prenatal lead exposure). We then construct novel tests for G × E effects within the LV framework to examine effect modification of outcome-exposure association by genetic factors (e.g., the hemochromatosis gene). We consider two scenarios: one allowing dependence of the LV models on genes and the other assuming independence between the LV models and genes. We combine the two sets of estimates by shrinkage estimation to trade off bias and efficiency in a data-adaptive way. Using simulations, we evaluate the properties of the shrinkage estimates, and in particular, we demonstrate the need for this data-adaptive shrinkage given repeated outcome measures, exposure measures possibly repeated and time-varying gene-environment association. Copyright © 2014 John Wiley & Sons, Ltd.

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

PubMed Central

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

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

PubMed

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.

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

ERIC Educational Resources Information Center

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…

Nature versus nurture: death of a dogma, and the road ahead.

PubMed

Traynor, Bryan J; Singleton, Andrew B

2010-10-21

Interaction between the genome and the environment has been widely discussed in the literature, but has the importance ascribed to understanding these interactions been overstated? In this opinion piece, we critically discuss gene-environment interactions and attempt to answer three key questions. First, is it likely that gene-environment interactions actually exist? Second, what is the realistic value of trying to unravel these interactions, both in terms of understanding disease pathogenesis and as a means of ameliorating disease? Finally, and most importantly, do the technologies and methodologies exist to facilitate an unbiased search for gene-environment interactions? Addressing these questions highlights key areas of feasibility that must be considered in this area of research. Copyright © 2010 Elsevier Inc. All rights reserved.

Boosting for detection of gene-environment interactions.

PubMed

Pashova, H; LeBlanc, M; Kooperberg, C

2013-01-30

In genetic association studies, it is typically thought that genetic variants and environmental variables jointly will explain more of the inheritance of a phenotype than either of these two components separately. Traditional methods to identify gene-environment interactions typically consider only one measured environmental variable at a time. However, in practice, multiple environmental factors may each be imprecise surrogates for the underlying physiological process that actually interacts with the genetic factors. In this paper, we develop a variant of L(2) boosting that is specifically designed to identify combinations of environmental variables that jointly modify the effect of a gene on a phenotype. Because the effect modifiers might have a small signal compared with the main effects, working in a space that is orthogonal to the main predictors allows us to focus on the interaction space. In a simulation study that investigates some plausible underlying model assumptions, our method outperforms the least absolute shrinkage and selection and Akaike Information Criterion and Bayesian Information Criterion model selection procedures as having the lowest test error. In an example for the Women's Health Initiative-Population Architecture using Genomics and Epidemiology study, the dedicated boosting method was able to pick out two single-nucleotide polymorphisms for which effect modification appears present. The performance was evaluated on an independent test set, and the results are promising. Copyright © 2012 John Wiley & Sons, Ltd.

Accounting for Population Structure in Gene-by-Environment Interactions in Genome-Wide Association Studies Using Mixed Models.

PubMed

Sul, Jae Hoon; Bilow, Michael; Yang, Wen-Yun; Kostem, Emrah; Furlotte, Nick; He, Dan; Eskin, Eleazar

2016-03-01

Although genome-wide association studies (GWASs) have discovered numerous novel genetic variants associated with many complex traits and diseases, those genetic variants typically explain only a small fraction of phenotypic variance. Factors that account for phenotypic variance include environmental factors and gene-by-environment interactions (GEIs). Recently, several studies have conducted genome-wide gene-by-environment association analyses and demonstrated important roles of GEIs in complex traits. One of the main challenges in these association studies is to control effects of population structure that may cause spurious associations. Many studies have analyzed how population structure influences statistics of genetic variants and developed several statistical approaches to correct for population structure. However, the impact of population structure on GEI statistics in GWASs has not been extensively studied and nor have there been methods designed to correct for population structure on GEI statistics. In this paper, we show both analytically and empirically that population structure may cause spurious GEIs and use both simulation and two GWAS datasets to support our finding. We propose a statistical approach based on mixed models to account for population structure on GEI statistics. We find that our approach effectively controls population structure on statistics for GEIs as well as for genetic variants.

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

PubMed Central

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

2014-01-01

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. PMID:25396097

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

PubMed

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.

The Impact of Gene-Environment Dependence and Misclassification in Genetic Association Studies Incorporating Gene-Environment Interactions

PubMed Central

Lindström, Sara; Yen, Yu-Chun; Spiegelman, Donna; Kraft, Peter

2009-01-01

The possibility of gene-environment interaction can be exploited to identify genetic variants associated with disease using a joint test of genetic main effect and gene-environment interaction. We consider how exposure misclassification and dependence between the true exposure E and the tested genetic variant G affect this joint test in absolute terms and relative to three other tests: the marginal test (G), the standard test for multiplicative gene-environment interaction (GE), and the case-only test for interaction (GE-CO). All tests can have inflated Type I error rate when E and G are correlated in the underlying population. For the GE and G-GE tests this inflation is only noticeable when the gene-environment dependence is unusually strong; the inflation can be large for the GE-CO test even for modest correlation. The joint G-GE test has greater power than the GE test generally, and greater power than the G test when there is no genetic main effect and the measurement error is small to moderate. The joint G-GE test is an attractive test for assessing genetic association when there is limited knowledge about casual mechanisms a priori, even in the presence of misclassification in environmental exposure measurement and correlation between exposure and genetic variants. PMID:19521099

Gene-Environment Interplay in Twin Models

PubMed Central

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

Transfection of the IHH gene into rabbit BMSCs in a simulated microgravity environment promotes chondrogenic differentiation and inhibits cartilage aging.

PubMed

Liu, Peng-Cheng; Liu, Kuan; Liu, Jun-Feng; Xia, Kuo; Chen, Li-Yang; Wu, Xing

2016-09-27

The effect of overexpressing the Indian hedgehog (IHH) gene on the chondrogenic differentiation of rabbit bone marrow-derived mesenchymal stem cells (BMSCs) was investigated in a simulated microgravity environment. An adenovirus plasmid encoding the rabbit IHH gene was constructed in vitro and transfected into rabbit BMSCs. Two large groups were used: conventional cell culture and induction model group and simulated microgravity environment group. Each large group was further divided into blank control group, GFP transfection group, and IHH transfection group. During differentiation induction, the expression levels of cartilage-related and cartilage hypertrophy-related genes and proteins in each group were determined. In the conventional model, the IHH transfection group expressed high levels of cartilage-related factors (Coll2 and ANCN) at the early stage of differentiation induction and expressed high levels of cartilage hypertrophy-related factors (Coll10, annexin 5, and ALP) at the late stage. Under the simulated microgravity environment, the IHH transfection group expressed high levels of cartilage-related factors and low levels of cartilage hypertrophy-related factors at all stages of differentiation induction. Under the simulated microgravity environment, transfection of the IHH gene into BMSCs effectively promoted the generation of cartilage and inhibited cartilage aging and osteogenesis. Therefore, this technique is suitable for cartilage tissue engineering.

Testing in semiparametric models with interaction, with applications to gene-environment interactions.

PubMed

Maity, Arnab; Carroll, Raymond J; Mammen, Enno; Chatterjee, Nilanjan

2009-01-01

Motivated from the problem of testing for genetic effects on complex traits in the presence of gene-environment interaction, we develop score tests in general semiparametric regression problems that involves Tukey style 1 degree-of-freedom form of interaction between parametrically and non-parametrically modelled covariates. We find that the score test in this type of model, as recently developed by Chatterjee and co-workers in the fully parametric setting, is biased and requires undersmoothing to be valid in the presence of non-parametric components. Moreover, in the presence of repeated outcomes, the asymptotic distribution of the score test depends on the estimation of functions which are defined as solutions of integral equations, making implementation difficult and computationally taxing. We develop profiled score statistics which are unbiased and asymptotically efficient and can be performed by using standard bandwidth selection methods. In addition, to overcome the difficulty of solving functional equations, we give easy interpretations of the target functions, which in turn allow us to develop estimation procedures that can be easily implemented by using standard computational methods. We present simulation studies to evaluate type I error and power of the method proposed compared with a naive test that does not consider interaction. Finally, we illustrate our methodology by analysing data from a case-control study of colorectal adenoma that was designed to investigate the association between colorectal adenoma and the candidate gene NAT2 in relation to smoking history.

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

PubMed

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.

Gene-Gene-Environment Interactions of Serotonin Transporter, Monoamine Oxidase A and Childhood Maltreatment Predict Aggressive Behavior in Chinese Adolescents

PubMed Central

Zhang, Yun; Ming, Qing-sen; Yi, Jin-yao; Wang, Xiang; Chai, Qiao-lian; Yao, Shu-qiao

2017-01-01

Gene-environment interactions that moderate aggressive behavior have been identified independently in the serotonin transporter (5-HTT) gene and monoamine oxidase A gene (MAOA). The aim of the present study was to investigate epistasis interactions between MAOA-variable number tandem repeat (VNTR), 5-HTTlinked polymorphism (LPR) and child abuse and the effects of these on aggressive tendencies in a group of otherwise healthy adolescents. A group of 546 Chinese male adolescents completed the Child Trauma Questionnaire and Youth self-report of the Child Behavior Checklist. Buccal cells were collected for DNA analysis. The effects of childhood abuse, MAOA-VNTR, 5-HTTLPR genotypes and their interactive gene-gene-environmental effects on aggressive behavior were analyzed using a linear regression model. The effect of child maltreatment was significant, and a three-way interaction among MAOA-VNTR, 5-HTTLPR and sexual abuse (SA) relating to aggressive behaviors was identified. Chinese male adolescents with high expression of the MAOA-VNTR allele and 5-HTTLPR “SS” genotype exhibited the highest aggression tendencies with an increase in SA during childhood. The findings reported support aggression being a complex behavior involving the synergistic effects of gene-gene-environment interactions. PMID:28203149

Information-Theoretic Metrics for Visualizing Gene-Environment Interactions

PubMed Central

Chanda, Pritam ; Zhang, Aidong ; Brazeau, Daniel ; Sucheston, Lara ; Freudenheim, Jo L. ; Ambrosone, Christine ; Ramanathan, Murali 

2007-01-01

The purpose of our work was to develop heuristics for visualizing and interpreting gene-environment interactions (GEIs) and to assess the dependence of candidate visualization metrics on biological and study-design factors. Two information-theoretic metrics, the k-way interaction information (KWII) and the total correlation information (TCI), were investigated. The effectiveness of the KWII and TCI to detect GEIs in a diverse range of simulated data sets and a Crohn disease data set was assessed. The sensitivity of the KWII and TCI spectra to biological and study-design variables was determined. Head-to-head comparisons with the relevance-chain, multifactor dimensionality reduction, and the pedigree disequilibrium test (PDT) methods were obtained. The KWII and TCI spectra, which are graphical summaries of the KWII and TCI for each subset of environmental and genotype variables, were found to detect each known GEI in the simulated data sets. The patterns in the KWII and TCI spectra were informative for factors such as case-control misassignment, locus heterogeneity, allele frequencies, and linkage disequilibrium. The KWII and TCI spectra were found to have excellent sensitivity for identifying the key disease-associated genetic variations in the Crohn disease data set. In head-to-head comparisons with the relevance-chain, multifactor dimensionality reduction, and PDT methods, the results from visual interpretation of the KWII and TCI spectra performed satisfactorily. The KWII and TCI are promising metrics for visualizing GEIs. They are capable of detecting interactions among numerous single-nucleotide polymorphisms and environmental variables for a diverse range of GEI models. PMID:17924337

[Association between MAOA-u VNTR polymorphism and its interaction with stressful life events and major depressive disorder in adolescents].

PubMed

Ma, Jing; Yu, Shun-Ying; Liang, Shan; Ding, Jun; Feng, Zhe; Yang, Fan; Gao, Wei-Jia; Lin, Jia-Ni; Huang, Chun-Xiang; Liu, Xue-Jun; Su, Lin-Yan

2013-07-01

To investigate whether the genetic polymorphism, upstream variable number of tandem repeats (uVNTR), in the monoamine oxidase A (MAOA) gene, is associated with major depressive disorder (MDD) in adolescents and to test whether there is gene-environment interaction between MAOA-uVNTR polymorphism and stressful life events (SLEs). A total of 394 Chinese Han subjects, including 187 adolescent patients with MDD and 207 normal students as a control group, were included in the study. Genotyping was performed by SNaP-shot assay. SLEs in the previous 12 months were evaluated. The groups were compared in terms of the frequency distributions of MAOA-uVNTR genotypes and alleles using statistical software. The binary logistic regression model of gene-environment interaction was established to analyze the association of the gene-environment interaction between MAOA-u VNTR genotypes and SLEs with adolescent MDD. The distribution profiles of MAOA-u VNTR genotypes and alleles were not related to the onset of MDD, severity of depression, comorbid anxiety and suicidal ideation/behavior/attempt in adolescents. The gene-environment interaction between MAOA-u VNTR genotypes and SLEs was not associated with MDD in male or female adolescents. It is not proven that MAOA-u VNTR polymorphism is associated with adolescent MDD. There is also no gene-environment interaction between MAOA-u VNTR polymorphism and SLEs that is associated with adolescent MDD.

A Versatile Omnibus Test for Detecting Mean and Variance Heterogeneity

PubMed Central

Bailey, Matthew; Kauwe, John S. K.; Maxwell, Taylor J.

2014-01-01

Recent research has revealed loci that display variance heterogeneity through various means such as biological disruption, linkage disequilibrium (LD), gene-by-gene (GxG), or gene-by-environment (GxE) interaction. We propose a versatile likelihood ratio test that allows joint testing for mean and variance heterogeneity (LRTMV) or either effect alone (LRTM or LRTV) in the presence of covariates. Using extensive simulations for our method and others we found that all parametric tests were sensitive to non-normality regardless of any trait transformations. Coupling our test with the parametric bootstrap solves this issue. Using simulations and empirical data from a known mean-only functional variant we demonstrate how linkage disequilibrium (LD) can produce variance-heterogeneity loci (vQTL) in a predictable fashion based on differential allele frequencies, high D’ and relatively low r2 values. We propose that a joint test for mean and variance heterogeneity is more powerful than a variance only test for detecting vQTL. This takes advantage of loci that also have mean effects without sacrificing much power to detect variance only effects. We discuss using vQTL as an approach to detect gene-by-gene interactions and also how vQTL are related to relationship loci (rQTL) and how both can create prior hypothesis for each other and reveal the relationships between traits and possibly between components of a composite trait. PMID:24482837

Gene-Environment Interactions in Asthma: Genetic and Epigenetic Effects.

PubMed

Lee, Jong-Uk; Kim, Jeong Dong; Park, Choon-Sik

2015-07-01

Over the past three decades, a large number of genetic studies have been aimed at finding genetic variants associated with the risk of asthma, applying various genetic and genomic approaches including linkage analysis, candidate gene polymorphism studies, and genome-wide association studies (GWAS). However, contrary to general expectation, even single nucleotide polymorphisms (SNPs) discovered by GWAS failed to fully explain the heritability of asthma. Thus, application of rare allele polymorphisms in well defined phenotypes and clarification of environmental factors have been suggested to overcome the problem of 'missing' heritability. Such factors include allergens, cigarette smoke, air pollutants, and infectious agents during pre- and post-natal periods. The first and simplest interaction between a gene and the environment is a candidate interaction of both a well known gene and environmental factor in a direct physical or chemical interaction such as between CD14 and endotoxin or between HLA and allergens. Several GWAS have found environmental interactions with occupational asthma, aspirin exacerbated respiratory disease, tobacco smoke-related airway dysfunction, and farm-related atopic diseases. As one of the mechanisms behind gene-environment interaction is epigenetics, a few studies on DNA CpG methylation have been reported on subphenotypes of asthma, pitching the exciting idea that it may be possible to intervene at the junction between the genome and the environment. Epigenetic studies are starting to include data from clinical samples, which will make them another powerful tool for re-search on gene-environment interactions in asthma.

Childhood temperament: passive gene-environment correlation, gene-environment interaction, and the hidden importance of the family environment.

PubMed

Lemery-Chalfant, Kathryn; Kao, Karen; Swann, Gregory; Goldsmith, H Hill

2013-02-01

Biological parents pass on genotypes to their children, as well as provide home environments that correlate with their genotypes; thus, the association between the home environment and children's temperament can be genetically (i.e., passive gene-environment correlation) or environmentally mediated. Furthermore, family environments may suppress or facilitate the heritability of children's temperament (i.e., gene-environment interaction). The sample comprised 807 twin pairs (mean age = 7.93 years) from the longitudinal Wisconsin Twin Project. Important passive gene-environment correlations emerged, such that home environments were less chaotic for children with high effortful control, and this association was genetically mediated. Children with high extraversion/surgency experienced more chaotic home environments, and this correlation was also genetically mediated. In addition, heritability of children's temperament was moderated by home environments, such that effortful control and extraversion/surgency were more heritable in chaotic homes, and negative affectivity was more heritable under crowded or unsafe home conditions. Modeling multiple types of gene-environment interplay uncovered the complex role of genetic factors and the hidden importance of the family environment for children's temperament and development more generally.

Gene x Environment Interactions in Reading Disability and Attention-Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Pennington, Bruce F.; McGrath, Lauren M.; Rosenberg, Jenni; Barnard, Holly; Smith, Shelley D.; Willcutt, Erik G.; Friend, Angela; DeFries, John C.; Olson, Richard K.

2009-01-01

This article examines Gene x Environment (G x E) interactions in two comorbid developmental disorders--reading disability (RD) and attention-deficit/hyperactivity disorder (ADHD)--as a window on broader issues on G x E interactions in developmental psychology. The authors first briefly review types of G x E interactions, methods for detecting…

Gene-Gene and Gene-Environment Interactions in Ulcerative Colitis

PubMed Central

Wang, Ming-Hsi; Fiocchi, Claudio; Zhu, Xiaofeng; Ripke, Stephan; Kamboh, M. Ilyas; Rebert, Nancy; Duerr, Richard H.; Achkar, Jean-Paul

2014-01-01

Genome-wide association studies (GWAS) have identified at least 133 ulcerative colitis (UC) associated loci. The role of genetic factors in clinical practice is not clearly defined. The relevance of genetic variants to disease pathogenesis is still uncertain because of not characterized gene-gene and gene-environment interactions. We examined the predictive value of combining the 133 UC risk loci with genetic interactions in an ongoing inflammatory bowel disease (IBD) GWAS. The Wellcome Trust Case-Control Consortium (WTCCC) IBD GWAS was used as a replication cohort. We applied logic regression (LR), a novel adaptive regression methodology, to search for high order interactions. Exploratory genotype correlations with UC sub-phenotypes (extent of disease, need of surgery, age of onset, extra-intestinal manifestations and primary sclerosing cholangitis (PSC)) were conducted. The combination of 133 UC loci yielded good UC risk predictability (area under the curve [AUC] of 0.86). A higher cumulative allele score predicted higher UC risk. Through LR, several lines of evidence for genetic interactions were identified and successfully replicated in the WTCCC cohort. The genetic interactions combined with the gene-smoking interaction significantly improved predictability in the model (AUC, from 0.86 to 0.89, P=3.26E-05). Explained UC variance increased from 37% to 42% after adding the interaction terms. A within case analysis found suggested genetic association with PSC. Our study demonstrates that the LR methodology allows the identification and replication of high order genetic interactions in UC GWAS datasets. UC risk can be predicted by a 133 loci and improved by adding gene-gene and gene-environment interactions. PMID:24241240

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

PubMed

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.

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

ERIC Educational Resources Information Center

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…

Comparative analysis of methods for detecting interacting loci

PubMed Central

2011-01-01

Background Interactions among genetic loci are believed to play an important role in disease risk. While many methods have been proposed for detecting such interactions, their relative performance remains largely unclear, mainly because different data sources, detection performance criteria, and experimental protocols were used in the papers introducing these methods and in subsequent studies. Moreover, there have been very few studies strictly focused on comparison of existing methods. Given the importance of detecting gene-gene and gene-environment interactions, a rigorous, comprehensive comparison of performance and limitations of available interaction detection methods is warranted. Results We report a comparison of eight representative methods, of which seven were specifically designed to detect interactions among single nucleotide polymorphisms (SNPs), with the last a popular main-effect testing method used as a baseline for performance evaluation. The selected methods, multifactor dimensionality reduction (MDR), full interaction model (FIM), information gain (IG), Bayesian epistasis association mapping (BEAM), SNP harvester (SH), maximum entropy conditional probability modeling (MECPM), logistic regression with an interaction term (LRIT), and logistic regression (LR) were compared on a large number of simulated data sets, each, consistent with complex disease models, embedding multiple sets of interacting SNPs, under different interaction models. The assessment criteria included several relevant detection power measures, family-wise type I error rate, and computational complexity. There are several important results from this study. First, while some SNPs in interactions with strong effects are successfully detected, most of the methods miss many interacting SNPs at an acceptable rate of false positives. In this study, the best-performing method was MECPM. Second, the statistical significance assessment criteria, used by some of the methods to control the type I error rate, are quite conservative, thereby limiting their power and making it difficult to fairly compare them. Third, as expected, power varies for different models and as a function of penetrance, minor allele frequency, linkage disequilibrium and marginal effects. Fourth, the analytical relationships between power and these factors are derived, aiding in the interpretation of the study results. Fifth, for these methods the magnitude of the main effect influences the power of the tests. Sixth, most methods can detect some ground-truth SNPs but have modest power to detect the whole set of interacting SNPs. Conclusion This comparison study provides new insights into the strengths and limitations of current methods for detecting interacting loci. This study, along with freely available simulation tools we provide, should help support development of improved methods. The simulation tools are available at: http://code.google.com/p/simulation-tool-bmc-ms9169818735220977/downloads/list. PMID:21729295

Comparative analysis of methods for detecting interacting loci.

PubMed

Chen, Li; Yu, Guoqiang; Langefeld, Carl D; Miller, David J; Guy, Richard T; Raghuram, Jayaram; Yuan, Xiguo; Herrington, David M; Wang, Yue

2011-07-05

Interactions among genetic loci are believed to play an important role in disease risk. While many methods have been proposed for detecting such interactions, their relative performance remains largely unclear, mainly because different data sources, detection performance criteria, and experimental protocols were used in the papers introducing these methods and in subsequent studies. Moreover, there have been very few studies strictly focused on comparison of existing methods. Given the importance of detecting gene-gene and gene-environment interactions, a rigorous, comprehensive comparison of performance and limitations of available interaction detection methods is warranted. We report a comparison of eight representative methods, of which seven were specifically designed to detect interactions among single nucleotide polymorphisms (SNPs), with the last a popular main-effect testing method used as a baseline for performance evaluation. The selected methods, multifactor dimensionality reduction (MDR), full interaction model (FIM), information gain (IG), Bayesian epistasis association mapping (BEAM), SNP harvester (SH), maximum entropy conditional probability modeling (MECPM), logistic regression with an interaction term (LRIT), and logistic regression (LR) were compared on a large number of simulated data sets, each, consistent with complex disease models, embedding multiple sets of interacting SNPs, under different interaction models. The assessment criteria included several relevant detection power measures, family-wise type I error rate, and computational complexity. There are several important results from this study. First, while some SNPs in interactions with strong effects are successfully detected, most of the methods miss many interacting SNPs at an acceptable rate of false positives. In this study, the best-performing method was MECPM. Second, the statistical significance assessment criteria, used by some of the methods to control the type I error rate, are quite conservative, thereby limiting their power and making it difficult to fairly compare them. Third, as expected, power varies for different models and as a function of penetrance, minor allele frequency, linkage disequilibrium and marginal effects. Fourth, the analytical relationships between power and these factors are derived, aiding in the interpretation of the study results. Fifth, for these methods the magnitude of the main effect influences the power of the tests. Sixth, most methods can detect some ground-truth SNPs but have modest power to detect the whole set of interacting SNPs. This comparison study provides new insights into the strengths and limitations of current methods for detecting interacting loci. This study, along with freely available simulation tools we provide, should help support development of improved methods. The simulation tools are available at: http://code.google.com/p/simulation-tool-bmc-ms9169818735220977/downloads/list.

Meta-analysis identifies gene-by-environment interactions as demonstrated in a study of 4,965 mice.

PubMed

Kang, Eun Yong; Han, Buhm; Furlotte, Nicholas; Joo, Jong Wha J; Shih, Diana; Davis, Richard C; Lusis, Aldons J; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study.

Meta-Analysis Identifies Gene-by-Environment Interactions as Demonstrated in a Study of 4,965 Mice

PubMed Central

Joo, Jong Wha J.; Shih, Diana; Davis, Richard C.; Lusis, Aldons J.; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study. PMID:24415945

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

PubMed Central

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

Integrative multicellular biological modeling: a case study of 3D epidermal development using GPU algorithms

PubMed Central

2010-01-01

Background Simulation of sophisticated biological models requires considerable computational power. These models typically integrate together numerous biological phenomena such as spatially-explicit heterogeneous cells, cell-cell interactions, cell-environment interactions and intracellular gene networks. The recent advent of programming for graphical processing units (GPU) opens up the possibility of developing more integrative, detailed and predictive biological models while at the same time decreasing the computational cost to simulate those models. Results We construct a 3D model of epidermal development and provide a set of GPU algorithms that executes significantly faster than sequential central processing unit (CPU) code. We provide a parallel implementation of the subcellular element method for individual cells residing in a lattice-free spatial environment. Each cell in our epidermal model includes an internal gene network, which integrates cellular interaction of Notch signaling together with environmental interaction of basement membrane adhesion, to specify cellular state and behaviors such as growth and division. We take a pedagogical approach to describing how modeling methods are efficiently implemented on the GPU including memory layout of data structures and functional decomposition. We discuss various programmatic issues and provide a set of design guidelines for GPU programming that are instructive to avoid common pitfalls as well as to extract performance from the GPU architecture. Conclusions We demonstrate that GPU algorithms represent a significant technological advance for the simulation of complex biological models. We further demonstrate with our epidermal model that the integration of multiple complex modeling methods for heterogeneous multicellular biological processes is both feasible and computationally tractable using this new technology. We hope that the provided algorithms and source code will be a starting point for modelers to develop their own GPU implementations, and encourage others to implement their modeling methods on the GPU and to make that code available to the wider community. PMID:20696053

Childhood Temperament: Passive Gene-Environment Correlation, Gene-Environment Interaction, and the Hidden Importance of the Family Environment

PubMed Central

Lemery-Chalfant, Kathryn; Kao, Karen; Swann, Gregory; Goldsmith, H. Hill

2013-01-01

Biological parents pass on genotypes to their children, as well as provide home environments that correlate with their genotypes; thus, the association between the home environment and children's temperament can be genetically (i.e. passive gene-environment correlation) or environmentally mediated. Furthermore, family environments may suppress or facilitate the heritability of children's temperament (i.e. gene-environment interaction). The sample comprised 807 twin pairs (M age = 7.93 years) from the longitudinal Wisconsin Twin Project. Important passive gene-environment correlations emerged, such that home environments were less chaotic for children with high Effortful Control, and this association was genetically mediated. Children with high Extraversion/Surgency experienced more chaotic home environments, and this correlation was also genetically mediated. In addition, heritability of children's temperament was moderated by home environments, such that Effortful Control and Extraversion/Surgency were more heritable in chaotic homes, and Negative Affectivity was more heritable under crowded or unsafe home conditions. Modeling multiple types of gene-environment interplay uncovered the complex role of genetic factors and the hidden importance of the family environment for children's temperament and development more generally. PMID:23398752

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

PubMed

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.

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

PubMed Central

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

IMPETUS - Interactive MultiPhysics Environment for Unified Simulations.

PubMed

Ha, Vi Q; Lykotrafitis, George

2016-12-08

We introduce IMPETUS - Interactive MultiPhysics Environment for Unified Simulations, an object oriented, easy-to-use, high performance, C++ program for three-dimensional simulations of complex physical systems that can benefit a large variety of research areas, especially in cell mechanics. The program implements cross-communication between locally interacting particles and continuum models residing in the same physical space while a network facilitates long-range particle interactions. Message Passing Interface is used for inter-processor communication for all simulations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effects of the Family Environment: Gene-Environment Interaction and Passive Gene-Environment Correlation

ERIC Educational Resources Information Center

Price, Thomas S.; Jaffee, Sara R.

2008-01-01

The classical twin study provides a useful resource for testing hypotheses about how the family environment influences children's development, including how genes can influence sensitivity to environmental effects. However, existing statistical models do not account for the possibility that children can inherit exposure to family environments…

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

ERIC Educational Resources Information Center

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…

A database of gene-environment interactions pertaining to blood lipid traits, cardiovascular disease and type 2 diabetes

USDA-ARS?s Scientific Manuscript database

As the role of the environment – diet, exercise, alcohol and tobacco use and sleep among others – is accorded a more prominent role in modifying the relationship between genetic variants and clinical measures of disease, consideration of gene-environment (GxE) interactions is a must. To facilitate i...

Gene-obesogenic environment interactions in the UK Biobank study.

PubMed

Tyrrell, Jessica; Wood, Andrew R; Ames, Ryan M; Yaghootkar, Hanieh; Beaumont, Robin N; Jones, Samuel E; Tuke, Marcus A; Ruth, Katherine S; Freathy, Rachel M; Davey Smith, George; Joost, Stéphane; Guessous, Idris; Murray, Anna; Strachan, David P; Kutalik, Zoltán; Weedon, Michael N; Frayling, Timothy M

2017-04-01

Previous studies have suggested that modern obesogenic environments accentuate the genetic risk of obesity. However, these studies have proven controversial as to which, if any, measures of the environment accentuate genetic susceptibility to high body mass index (BMI). We used up to 120 000 adults from the UK Biobank study to test the hypothesis that high-risk obesogenic environments and behaviours accentuate genetic susceptibility to obesity. We used BMI as the outcome and a 69-variant genetic risk score (GRS) for obesity and 12 measures of the obesogenic environment as exposures. These measures included Townsend deprivation index (TDI) as a measure of socio-economic position, TV watching, a 'Westernized' diet and physical activity. We performed several negative control tests, including randomly selecting groups of different average BMIs, using a simulated environment and including sun-protection use as an environment. We found gene-environment interactions with TDI (Pinteraction = 3 × 10 -10 ), self-reported TV watching (Pinteraction = 7 × 10 -5 ) and self-reported physical activity (Pinteraction = 5 × 10 -6 ). Within the group of 50% living in the most relatively deprived situations, carrying 10 additional BMI-raising alleles was associated with approximately 3.8 kg extra weight in someone 1.73 m tall. In contrast, within the group of 50% living in the least deprivation, carrying 10 additional BMI-raising alleles was associated with approximately 2.9 kg extra weight. The interactions were weaker, but present, with the negative controls, including sun-protection use, indicating that residual confounding is likely. Our findings suggest that the obesogenic environment accentuates the risk of obesity in genetically susceptible adults. Of the factors we tested, relative social deprivation best captures the aspects of the obesogenic environment responsible. © The Author 2017. Published by Oxford University Press on behalf of the International Epidemiological Association

Life events and borderline personality features: the influence of gene-environment interaction and gene-environment correlation.

PubMed

Distel, M A; Middeldorp, C M; Trull, T J; Derom, C A; Willemsen, G; Boomsma, D I

2011-04-01

Traumatic life events are generally more common in patients with borderline personality disorder (BPD) than in non-patients or patients with other personality disorders. This study investigates whether exposure to life events moderates the genetic architecture of BPD features. As the presence of genotype-environment correlation (rGE) can lead to spurious findings of genotype-environment interaction (G × E), we also test whether BPD features increase the likelihood of exposure to life events. The extent to which an individual is at risk to develop BPD was assessed with the Personality Assessment Inventory - Borderline features scale (PAI-BOR). Life events under study were a divorce/break-up, traffic accident, violent assault, sexual assault, robbery and job loss. Data were available for 5083 twins and 1285 non-twin siblings. Gene-environment interaction and correlation were assessed by using structural equation modelling (SEM) and the co-twin control design. There was evidence for both gene-environment interaction and correlation. Additive genetic influences on BPD features interacted with the exposure to sexual assault, with genetic variance being lower in exposed individuals. In individuals who had experienced a divorce/break-up, violent assault, sexual assault or job loss, environmental variance for BPD features was higher, leading to a lower heritability of BPD features in exposed individuals. Gene-environment correlation was present for some life events. The genes that influence BPD features thus also increased the likelihood of being exposed to certain life events. To our knowledge, this study is the first to test the joint effect of genetic and environmental influences and the exposure to life events on BPD features in the general population. Our results indicate the importance of both genetic vulnerability and life events.

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

PubMed

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.

The case-only test for gene-environment interaction is not uniformly powerful: an empirical example

PubMed Central

Wu, Chen; Chang, Jiang; Ma, Baoshan; Miao, Xiaoping; Zhou, Yifeng; Liu, Yu; Li, Yun; Wu, Tangchun; Hu, Zhibin; Shen, Hongbing; Jia, Weihua; Zeng, Yixin; Lin, Dongxin; Kraft, Peter

2016-01-01

The case-only test has been proposed as a more powerful approach to detect gene-environment (G×E) interactions. This approach assumes that the genetic and environmental factors are independent. While it is well known that Type I error rate will increase if this assumption is violated, it is less widely appreciated that gene-environment correlation can also lead to power loss. We illustrate this phenomenon by comparing the performance of the case-only test to other approaches to detect G×E interactions in a genome-wide association study of esophageal squamous carcinoma (ESCC) in Chinese populations. Some of these approaches do not use information on the correlation between exposure and genotype (standard logistic regression), while others seek to use this information in a robust fashion to boost power without increasing Type I error (two-step, empirical Bayes and cocktail methods). G×E interactions were identified involving drinking status and two regions containing genes in the alcohol metabolism pathway, 4q23 and 12q24. Although the case-only test yielded the most significant tests of G×E interaction in the 4q23 region, the case-only test failed to identify significant interactions in the 12q24 region which were readily identified using other approaches. The low power of the case-only test in the 12q24 region is likely due to the strong inverse association between the SNPs in this region and drinking status. This example underscores the need to consider multiple approaches to detect gene-environment interactions, as different tests are more or less sensitive to different alternative hypotheses and violations of the gene-environment independence assumption. PMID:23595356

Gene-Environment Interactions across Development: Exploring DRD2 Genotype and Prenatal Smoking Effects on Self-Regulation

ERIC Educational Resources Information Center

Wiebe, Sandra A.; Espy, Kimberly Andrews; Stopp, Christian; Respass, Jennifer; Stewart, Peter; Jameson, Travis R.; Gilbert, David G.; Huggenvik, Jodi I.

2009-01-01

Genetic factors dynamically interact with both pre- and postnatal environmental influences to shape development. Considerable attention has been devoted to gene-environment interactions (G x E) on important outcomes (A. Caspi & T. E. Moffitt, 2006). It is also important to consider the possibility that these G x E effects may vary across…

A laboratory simulation of Arabidopsis seed dormancy cycling provides new insight into its regulation by clock genes and the dormancy-related genes DOG1, MFT, CIPK23 and PHYA.

PubMed

Footitt, Steven; Ölçer-Footitt, Hülya; Hambidge, Angela J; Finch-Savage, William E

2017-08-01

Environmental signals drive seed dormancy cycling in the soil to synchronize germination with the optimal time of year, a process essential for species' fitness and survival. Previous correlation of transcription profiles in exhumed seeds with annual environmental signals revealed the coordination of dormancy-regulating mechanisms with the soil environment. Here, we developed a rapid and robust laboratory dormancy cycling simulation. The utility of this simulation was tested in two ways: firstly, using mutants in known dormancy-related genes [DELAY OF GERMINATION 1 (DOG1), MOTHER OF FLOWERING TIME (MFT), CBL-INTERACTING PROTEIN KINASE 23 (CIPK23) and PHYTOCHROME A (PHYA)] and secondly, using further mutants, we test the hypothesis that components of the circadian clock are involved in coordination of the annual seed dormancy cycle. The rate of dormancy induction and relief differed in all lines tested. In the mutants, dog1-2 and mft2, dormancy induction was reduced but not absent. DOG1 is not absolutely required for dormancy. In cipk23 and phyA dormancy, induction was accelerated. Involvement of the clock in dormancy cycling was clear when mutants in the morning and evening loops of the clock were compared. Dormancy induction was faster when the morning loop was compromised and delayed when the evening loop was compromised. © 2017 The Authors Plant, Cell & Environment Published by John Wiley & Sons Ltd.

Confirmatory and Competitive Evaluation of Alternative Gene-Environment Interaction Hypotheses

ERIC Educational Resources Information Center

Belsky, Jay; Pluess, Michael; Widaman, Keith F.

2013-01-01

Background: Most gene-environment interaction (GXE) research, though based on clear, vulnerability-oriented hypotheses, is carried out using exploratory rather than hypothesis-informed statistical tests, limiting power and making formal evaluation of competing GXE propositions difficult. Method: We present and illustrate a new regression technique…

Genes and environment in neonatal intraventricular hemorrhage.

PubMed

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.

Testing for gene-environment interaction under exposure misspecification.

PubMed

Sun, Ryan; Carroll, Raymond J; Christiani, David C; Lin, Xihong

2017-11-09

Complex interplay between genetic and environmental factors characterizes the etiology of many diseases. Modeling gene-environment (GxE) interactions is often challenged by the unknown functional form of the environment term in the true data-generating mechanism. We study the impact of misspecification of the environmental exposure effect on inference for the GxE interaction term in linear and logistic regression models. We first examine the asymptotic bias of the GxE interaction regression coefficient, allowing for confounders as well as arbitrary misspecification of the exposure and confounder effects. For linear regression, we show that under gene-environment independence and some confounder-dependent conditions, when the environment effect is misspecified, the regression coefficient of the GxE interaction can be unbiased. However, inference on the GxE interaction is still often incorrect. In logistic regression, we show that the regression coefficient is generally biased if the genetic factor is associated with the outcome directly or indirectly. Further, we show that the standard robust sandwich variance estimator for the GxE interaction does not perform well in practical GxE studies, and we provide an alternative testing procedure that has better finite sample properties. © 2017, The International Biometric Society.

Microbial diversity--insights from population genetics.

PubMed

Mes, Ted H M

2008-01-01

Although many environmental microbial populations are large and genetically diverse, both the level of diversity and the extent to which it is ecologically relevant remain enigmatic. Because the effective (or long-term) population size, N(e), is one of the parameters that determines population genetic diversity, tests and simulations that assume selectively neutral mutations may help to identify the processes that have shaped microbial diversity. Using ecologically important genes, tests of selective neutrality suggest that adaptive as well as non-adaptive types of selection act and that departure from neutrality may be widespread or restricted to small groups of genotypes. Population genetic simulations using population sizes between 10(3) and 10(7) suggest extremely high levels of microbial diversity in environments that sustain large populations. However, census and effective population sizes may differ considerably, and because we know nothing of the evolutionary history of environmental microbial populations, we also have no idea what N(e) of environmental populations is. On the one hand, this reflects our ignorance of the microbial world. On the other hand, the tests and simulations illustrate interactions between microbial diversity and microbial population genetics that should inform our thinking in microbial ecology. Because of the different views on microbial diversity across these disciplines, such interactions are crucial if we are to understand the role of genes in microbial communities.

Interactive Learning Environment: Web-based Virtual Hydrological Simulation System using Augmented and Immersive Reality

NASA Astrophysics Data System (ADS)

Demir, I.

2014-12-01

Recent developments in internet technologies make it possible to manage and visualize large data on the web. Novel visualization techniques and interactive user interfaces allow users to create realistic environments, and interact with data to gain insight from simulations and environmental observations. The hydrological simulation system is a web-based 3D interactive learning environment for teaching hydrological processes and concepts. The simulation systems provides a visually striking platform with realistic terrain information, and water simulation. Students can create or load predefined scenarios, control environmental parameters, and evaluate environmental mitigation alternatives. The web-based simulation system provides an environment for students to learn about the hydrological processes (e.g. flooding and flood damage), and effects of development and human activity in the floodplain. The system utilizes latest web technologies and graphics processing unit (GPU) for water simulation and object collisions on the terrain. Users can access the system in three visualization modes including virtual reality, augmented reality, and immersive reality using heads-up display. The system provides various scenarios customized to fit the age and education level of various users. This presentation provides an overview of the web-based flood simulation system, and demonstrates the capabilities of the system for various visualization and interaction modes.

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

PubMed

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 recommend to use internal weights from the study population itself to construct weighted GRS for GxE interaction studies. If the SNPs were chosen because a strong marginal genetic effect was hypothesized, GRS-marginal-internal should be used. If the SNPs were chosen because of their collective impact on the biological mechanisms mediating the environmental effect (hypothesis of predominant interactions) GRS-interaction-training should be applied.

Gene-Environment Interactions in Cancer Epidemiology: A National Cancer Institute Think Tank Report

PubMed Central

Hutter, Carolyn M.; Mechanic, Leah E.; Chatterjee, Nilanjan; Kraft, Peter; Gillander, Elizabeth M.

2014-01-01

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

Interaction of childhood urbanicity and variation in dopamine genes alters adult prefrontal function as measured by functional magnetic resonance imaging (fMRI).

PubMed

Reed, Jessica L; D'Ambrosio, Enrico; Marenco, Stefano; Ursini, Gianluca; Zheutlin, Amanda B; Blasi, Giuseppe; Spencer, Barbara E; Romano, Raffaella; Hochheiser, Jesse; Reifman, Ann; Sturm, Justin; Berman, Karen F; Bertolino, Alessandro; Weinberger, Daniel R; Callicott, Joseph H

2018-01-01

Brain phenotypes showing environmental influence may help clarify unexplained associations between urban exposure and psychiatric risk. Heritable prefrontal fMRI activation during working memory (WM) is such a phenotype. We hypothesized that urban upbringing (childhood urbanicity) would alter this phenotype and interact with dopamine genes that regulate prefrontal function during WM. Further, dopamine has been hypothesized to mediate urban-associated factors like social stress. WM-related prefrontal function was tested for main effects of urbanicity, main effects of three dopamine genes-catechol-O-methyltransferase (COMT), dopamine receptor D1 (DRD1), and dopamine receptor D2 (DRD2)-and, importantly, dopamine gene-by-urbanicity interactions. For COMT, three independent human samples were recruited (total n = 487). We also studied 253 subjects genotyped for DRD1 and DRD2. 3T fMRI activation during the N-back WM task was the dependent variable, while childhood urbanicity, dopamine genotype, and urbanicity-dopamine interactions were independent variables. Main effects of dopamine genes and of urbanicity were found. Individuals raised in an urban environment showed altered prefrontal activation relative to those raised in rural or town settings. For each gene, dopamine genotype-by-urbanicity interactions were shown in prefrontal cortex-COMT replicated twice in two independent samples. An urban childhood upbringing altered prefrontal function and interacted with each gene to alter genotype-phenotype relationships. Gene-environment interactions between multiple dopamine genes and urban upbringing suggest that neural effects of developmental environmental exposure could mediate, at least partially, increased risk for psychiatric illness in urban environments via dopamine genes expressed into adulthood.

An Investigation of the Potential of Interactive Simulations for Developing System Thinking Skills in Elementary School: A Case Study with Fifth-Graders and Sixth-Graders

ERIC Educational Resources Information Center

Evagorou, Maria; Korfiatis, Kostas; Nicolaou, Christiana; Constantinou, Costas

2009-01-01

The purpose of this study was to investigate the impact of a simulation-based learning environment on elementary school students' (11-12 years old) development of system thinking skills. The learning environment included interactive simulations using the Stagecast Creator software to simulate the ecosystem of a marsh. Simulations are an important…

Spatial interpretation of NASA's Marshall Space Flight Center Payload Operations Control Center using virtual reality technology

NASA Technical Reports Server (NTRS)

Lindsey, Patricia F.

1993-01-01

In its search for higher level computer interfaces and more realistic electronic simulations for measurement and spatial analysis in human factors design, NASA at MSFC is evaluating the functionality of virtual reality (VR) technology. Virtual reality simulation generates a three dimensional environment in which the participant appears to be enveloped. It is a type of interactive simulation in which humans are not only involved, but included. Virtual reality technology is still in the experimental phase, but it appears to be the next logical step after computer aided three-dimensional animation in transferring the viewer from a passive to an active role in experiencing and evaluating an environment. There is great potential for using this new technology when designing environments for more successful interaction, both with the environment and with another participant in a remote location. At the University of North Carolina, a VR simulation of a the planned Sitterson Hall, revealed a flaw in the building's design that had not been observed during examination of the more traditional building plan simulation methods on paper and on computer aided design (CAD) work station. The virtual environment enables multiple participants in remote locations to come together and interact with one another and with the environment. Each participant is capable of seeing herself and the other participants and of interacting with them within the simulated environment.

Gene-Environment Interactions in Cardiovascular Disease

PubMed Central

Flowers, Elena; Froelicher, Erika Sivarajan; Aouizerat, Bradley E.

2011-01-01

Background Historically, models to describe disease were exclusively nature-based or nurture-based. Current theoretical models for complex conditions such as cardiovascular disease acknowledge the importance of both biologic and non-biologic contributors to disease. A critical feature is the occurrence of interactions between numerous risk factors for disease. The interaction between genetic (i.e. biologic, nature) and environmental (i.e. non-biologic, nurture) causes of disease is an important mechanism for understanding both the etiology and public health impact of cardiovascular disease. Objectives The purpose of this paper is to describe theoretical underpinnings of gene-environment interactions, models of interaction, methods for studying gene-environment interactions, and the related concept of interactions between epigenetic mechanisms and the environment. Discussion Advances in methods for measurement of genetic predictors of disease have enabled an increasingly comprehensive understanding of the causes of disease. In order to fully describe the effects of genetic predictors of disease, it is necessary to place genetic predictors within the context of known environmental risk factors. The additive or multiplicative effect of the interaction between genetic and environmental risk factors is often greater than the contribution of either risk factor alone. PMID:21684212

Exposure enriched outcome dependent designs for longitudinal studies of gene-environment interaction.

PubMed

Sun, Zhichao; Mukherjee, Bhramar; Estes, Jason P; Vokonas, Pantel S; Park, Sung Kyun

2017-08-15

Joint effects of genetic and environmental factors have been increasingly recognized in the development of many complex human diseases. Despite the popularity of case-control and case-only designs, longitudinal cohort studies that can capture time-varying outcome and exposure information have long been recommended for gene-environment (G × E) interactions. To date, literature on sampling designs for longitudinal studies of G × E interaction is quite limited. We therefore consider designs that can prioritize a subsample of the existing cohort for retrospective genotyping on the basis of currently available outcome, exposure, and covariate data. In this work, we propose stratified sampling based on summaries of individual exposures and outcome trajectories and develop a full conditional likelihood approach for estimation that adjusts for the biased sample. We compare the performance of our proposed design and analysis with combinations of different sampling designs and estimation approaches via simulation. We observe that the full conditional likelihood provides improved estimates for the G × E interaction and joint exposure effects over uncorrected complete-case analysis, and the exposure enriched outcome trajectory dependent design outperforms other designs in terms of estimation efficiency and power for detection of the G × E interaction. We also illustrate our design and analysis using data from the Normative Aging Study, an ongoing longitudinal cohort study initiated by the Veterans Administration in 1963. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Computer and laboratory simulation of interactions between spacecraft surfaces and charged-particle environments

NASA Technical Reports Server (NTRS)

Stevens, N. J.

1979-01-01

Cases where the charged-particle environment acts on the spacecraft (e.g., spacecraft charging phenomena) and cases where a system on the spacecraft causes the interaction (e.g., high voltage space power systems) are considered. Both categories were studied in ground simulation facilities to understand the processes involved and to measure the pertinent parameters. Computer simulations are based on the NASA Charging Analyzer Program (NASCAP) code. Analytical models are developed in this code and verified against the experimental data. Extrapolation from the small test samples to space conditions are made with this code. Typical results from laboratory and computer simulations are presented for both types of interactions. Extrapolations from these simulations to performance in space environments are discussed.

Gene-environment interaction study for BMI reveals interactions between genetic factors and physical activity, alcohol consumption and socioeconomic status

PubMed Central

Karlsson, Torgny; Ek, Weronica E.

2017-01-01

Previous genome-wide association studies (GWAS) have identified hundreds of genetic loci to be associated with body mass index (BMI) and risk of obesity. Genetic effects can differ between individuals depending on lifestyle or environmental factors due to gene-environment interactions. In this study, we examine gene-environment interactions in 362,496 unrelated participants with Caucasian ancestry from the UK Biobank resource. A total of 94 BMI-associated SNPs, selected from a previous GWAS on BMI, were used to construct weighted genetic scores for BMI (GSBMI). Linear regression modeling was used to estimate the effect of gene-environment interactions on BMI for 131 lifestyle factors related to: dietary habits, smoking and alcohol consumption, physical activity, socioeconomic status, mental health, sleeping patterns, as well as female-specific factors such as menopause and childbirth. In total, 15 lifestyle factors were observed to interact with GSBMI, of which alcohol intake frequency, usual walking pace, and Townsend deprivation index, a measure of socioeconomic status, were all highly significant (p = 1.45*10−29, p = 3.83*10−26, p = 4.66*10−11, respectively). Interestingly, the frequency of alcohol consumption, rather than the total weekly amount resulted in a significant interaction. The FTO locus was the strongest single locus interacting with any of the lifestyle factors. However, 13 significant interactions were also observed after omitting the FTO locus from the genetic score. Our analyses indicate that many lifestyle factors modify the genetic effects on BMI with some groups of individuals having more than double the effect of the genetic score. However, the underlying causal mechanisms of gene-environmental interactions are difficult to deduce from cross-sectional data alone and controlled experiments are required to fully characterise the causal factors. PMID:28873402

Routine Discovery of Complex Genetic Models using Genetic Algorithms

PubMed Central

Moore, Jason H.; Hahn, Lance W.; Ritchie, Marylyn D.; Thornton, Tricia A.; White, Bill C.

2010-01-01

Simulation studies are useful in various disciplines for a number of reasons including the development and evaluation of new computational and statistical methods. This is particularly true in human genetics and genetic epidemiology where new analytical methods are needed for the detection and characterization of disease susceptibility genes whose effects are complex, nonlinear, and partially or solely dependent on the effects of other genes (i.e. epistasis or gene-gene interaction). Despite this need, the development of complex genetic models that can be used to simulate data is not always intuitive. In fact, only a few such models have been published. We have previously developed a genetic algorithm approach to discovering complex genetic models in which two single nucleotide polymorphisms (SNPs) influence disease risk solely through nonlinear interactions. In this paper, we extend this approach for the discovery of high-order epistasis models involving three to five SNPs. We demonstrate that the genetic algorithm is capable of routinely discovering interesting high-order epistasis models in which each SNP influences risk of disease only through interactions with the other SNPs in the model. This study opens the door for routine simulation of complex gene-gene interactions among SNPs for the development and evaluation of new statistical and computational approaches for identifying common, complex multifactorial disease susceptibility genes. PMID:20948983

Gene and environment interaction: is the differential susceptibility hypothesis relevant for obesity?

PubMed Central

Dalle Molle, Roberta; Fatemi, Hajar; Dagher, Alain; Levitan, Robert D.; Silveira, Patricia P.; Dubé, Laurette

2017-01-01

The differential susceptibility model states that a given genetic variant is associated with an increased risk of pathology in negative environments but greater than average resilience in enriched ones. While this theory was first implemented in psychiatric-genetic research, it may also help us to unravel the complex ways that genes and environments interact to influence feeding behavior and obesity. We reviewed evidence on gene vs. environment interactions that influence obesity development, aiming to support the applicability of the differential susceptibility model for this condition, and propose that various environmental “layers” relevant for human development should be considered when bearing the differential susceptibility model in mind. Mother-child relationship, socioeconomic status and individual's response are important modifiers of BMI and food intake when interacting with gene variants, “for better and for worse”. While only a few studies to date have investigated obesity outcomes using this approach, we propose that the differential susceptibility hypothesis is in fact highly applicable to the study of genetic and environmental influences on feeding behavior and obesity risk. PMID:28024828

Interphase Chromosome Conformation and Chromatin-Chromatin Interactions in Human Epithelial Cells Cultured Under Different Gravity Conditions

NASA Technical Reports Server (NTRS)

Zhang, Ye; Wong, Michael; Hada, Megumi; Wu, Honglu

2015-01-01

Microgravity has been shown to alter global gene expression patterns and protein levels both in cultured cells and animal models. It has been suggested that the packaging of chromatin fibers in the interphase nucleus is closely related to genome function, and the changes in transcriptional activity are tightly correlated with changes in chromatin folding. This study explores the changes of chromatin conformation and chromatin-chromatin interactions in the simulated microgravity environment, and investigates their correlation to the expression of genes located at different regions of the chromosome. To investigate the folding of chromatin in interphase under various culture conditions, human epithelial cells, fibroblasts, and lymphocytes were fixed in the G1 phase. Interphase chromosomes were hybridized with a multicolor banding in situ hybridization (mBAND) probe for chromosome 3 which distinguishes six regions of the chromosome as separate colors. After images were captured with a laser scanning confocal microscope, the 3-dimensional structure of interphase chromosome 3 was reconstructed at multi-mega base pair scale. In order to determine the effects of microgravity on chromosome conformation and orientation, measures such as distance between homologous pairs, relative orientation of chromosome arms about a shared midpoint, and orientation of arms within individual chromosomes were all considered as potentially impacted by simulated microgravity conditions. The studies revealed non-random folding of chromatin in interphase, and suggested an association of interphase chromatin folding with radiation-induced chromosome aberration hotspots. Interestingly, the distributions of genes with expression changes over chromosome 3 in cells cultured under microgravity environment are apparently clustered on specific loci and chromosomes. This data provides important insights into how mammalian cells respond to microgravity at molecular level.

Functional Logistic Regression Approach to Detecting Gene by Longitudinal Environmental Exposure Interaction in a Case-Control Study

PubMed Central

Wei, Peng; Tang, Hongwei; Li, Donghui

2014-01-01

Most complex human diseases are likely the consequence of the joint actions of genetic and environmental factors. Identification of gene-environment (GxE) interactions not only contributes to a better understanding of the disease mechanisms, but also improves disease risk prediction and targeted intervention. In contrast to the large number of genetic susceptibility loci discovered by genome-wide association studies, there have been very few successes in identifying GxE interactions which may be partly due to limited statistical power and inaccurately measured exposures. While existing statistical methods only consider interactions between genes and static environmental exposures, many environmental/lifestyle factors, such as air pollution and diet, change over time, and cannot be accurately captured at one measurement time point or by simply categorizing into static exposure categories. There is a dearth of statistical methods for detecting gene by time-varying environmental exposure interactions. Here we propose a powerful functional logistic regression (FLR) approach to model the time-varying effect of longitudinal environmental exposure and its interaction with genetic factors on disease risk. Capitalizing on the powerful functional data analysis framework, our proposed FLR model is capable of accommodating longitudinal exposures measured at irregular time points and contaminated by measurement errors, commonly encountered in observational studies. We use extensive simulations to show that the proposed method can control the Type I error and is more powerful than alternative ad hoc methods. We demonstrate the utility of this new method using data from a case-control study of pancreatic cancer to identify the windows of vulnerability of lifetime body mass index on the risk of pancreatic cancer as well as genes which may modify this association. PMID:25219575

Functional logistic regression approach to detecting gene by longitudinal environmental exposure interaction in a case-control study.

PubMed

Wei, Peng; Tang, Hongwei; Li, Donghui

2014-11-01

Most complex human diseases are likely the consequence of the joint actions of genetic and environmental factors. Identification of gene-environment (G × E) interactions not only contributes to a better understanding of the disease mechanisms, but also improves disease risk prediction and targeted intervention. In contrast to the large number of genetic susceptibility loci discovered by genome-wide association studies, there have been very few successes in identifying G × E interactions, which may be partly due to limited statistical power and inaccurately measured exposures. Although existing statistical methods only consider interactions between genes and static environmental exposures, many environmental/lifestyle factors, such as air pollution and diet, change over time, and cannot be accurately captured at one measurement time point or by simply categorizing into static exposure categories. There is a dearth of statistical methods for detecting gene by time-varying environmental exposure interactions. Here, we propose a powerful functional logistic regression (FLR) approach to model the time-varying effect of longitudinal environmental exposure and its interaction with genetic factors on disease risk. Capitalizing on the powerful functional data analysis framework, our proposed FLR model is capable of accommodating longitudinal exposures measured at irregular time points and contaminated by measurement errors, commonly encountered in observational studies. We use extensive simulations to show that the proposed method can control the Type I error and is more powerful than alternative ad hoc methods. We demonstrate the utility of this new method using data from a case-control study of pancreatic cancer to identify the windows of vulnerability of lifetime body mass index on the risk of pancreatic cancer as well as genes that may modify this association. © 2014 Wiley Periodicals, Inc.

The Oxytocin Receptor Gene (OXTR) in Relation to State Levels of Loneliness in Adolescence: Evidence for Micro-Level Gene-Environment Interactions

PubMed Central

van Roekel, Eeske; Verhagen, Maaike; Scholte, Ron H. J.; Kleinjan, Marloes; Goossens, Luc; Engels, Rutger C. M. E.

2013-01-01

Previous research has shown that the rs53576 variant of the oxytocin receptor gene (OXTR) is associated with trait levels of loneliness, but results are inconsistent. The aim of the present study is to examine micro-level effects of the OXTR rs53576 variant on state levels of loneliness in early adolescents. In addition, gene-environment interactions are examined between this OXTR variant and positive and negative perceptions of company. Data were collected in 278 adolescents (58% girls), by means of the Experience Sampling Method (ESM). Sampling periods consisted of six days with nine assessments per day. A relation was found between the OXTR rs53576 variant and state loneliness, in girls only. Girls carrying an A allele had higher levels of state loneliness than girls carrying the GG genotype. In addition, adolescents with an A allele were more affected by negative perceptions of company than GG carriers, on weekend days only. No significant gene-environment interactions were found with positive company. Adolescents carrying an A allele were more susceptible to negative environments during weekend days than GG carriers. Our findings emphasize the importance of operationalizing the phenotype and the environment accurately. PMID:24223720

The oxytocin receptor gene (OXTR) in relation to state levels of loneliness in adolescence: evidence for micro-level gene-environment interactions.

PubMed

van Roekel, Eeske; Verhagen, Maaike; Scholte, Ron H J; Kleinjan, Marloes; Goossens, Luc; Engels, Rutger C M E

2013-01-01

Previous research has shown that the rs53576 variant of the oxytocin receptor gene (OXTR) is associated with trait levels of loneliness, but results are inconsistent. The aim of the present study is to examine micro-level effects of the OXTR rs53576 variant on state levels of loneliness in early adolescents. In addition, gene-environment interactions are examined between this OXTR variant and positive and negative perceptions of company. Data were collected in 278 adolescents (58% girls), by means of the Experience Sampling Method (ESM). Sampling periods consisted of six days with nine assessments per day. A relation was found between the OXTR rs53576 variant and state loneliness, in girls only. Girls carrying an A allele had higher levels of state loneliness than girls carrying the GG genotype. In addition, adolescents with an A allele were more affected by negative perceptions of company than GG carriers, on weekend days only. No significant gene-environment interactions were found with positive company. Adolescents carrying an A allele were more susceptible to negative environments during weekend days than GG carriers. Our findings emphasize the importance of operationalizing the phenotype and the environment accurately.

Next-generation analysis of cataracts: determining knowledge driven gene-gene interactions using Biofilter, and gene-environment interactions using the PhenX Toolkit.

PubMed

Pendergrass, Sarah A; Verma, Shefali S; Holzinger, Emily R; Moore, Carrie B; Wallace, John; Dudek, Scott M; Huggins, Wayne; Kitchner, Terrie; Waudby, Carol; Berg, Richard; McCarty, Catherine A; Ritchie, Marylyn D

2013-01-01

Investigating the association between biobank derived genomic data and the information of linked electronic health records (EHRs) is an emerging area of research for dissecting the architecture of complex human traits, where cases and controls for study are defined through the use of electronic phenotyping algorithms deployed in large EHR systems. For our study, 2580 cataract cases and 1367 controls were identified within the Marshfield Personalized Medicine Research Project (PMRP) Biobank and linked EHR, which is a member of the NHGRI-funded electronic Medical Records and Genomics (eMERGE) Network. Our goal was to explore potential gene-gene and gene-environment interactions within these data for 529,431 single nucleotide polymorphisms (SNPs) with minor allele frequency > 1%, in order to explore higher level associations with cataract risk beyond investigations of single SNP-phenotype associations. To build our SNP-SNP interaction models we utilized a prior-knowledge driven filtering method called Biofilter to minimize the multiple testing burden of exploring the vast array of interaction models possible from our extensive number of SNPs. Using the Biofilter, we developed 57,376 prior-knowledge directed SNP-SNP models to test for association with cataract status. We selected models that required 6 sources of external domain knowledge. We identified 5 statistically significant models with an interaction term with p-value < 0.05, as well as an overall model with p-value < 0.05 associated with cataract status. We also conducted gene-environment interaction analyses for all GWAS SNPs and a set of environmental factors from the PhenX Toolkit: smoking, UV exposure, and alcohol use; these environmental factors have been previously associated with the formation of cataracts. We found a total of 288 models that exhibit an interaction term with a p-value ≤ 1×10(-4) associated with cataract status. Our results show these approaches enable advanced searches for epistasis and gene-environment interactions beyond GWAS, and that the EHR based approach provides an additional source of data for seeking these advanced explanatory models of the etiology of complex disease/outcome such as cataracts.

Genotype-Based Association Mapping of Complex Diseases: Gene-Environment Interactions with Multiple Genetic Markers and Measurement Error in Environmental Exposures

PubMed Central

Lobach, Irvna; Fan, Ruzone; Carroll, Raymond T.

2011-01-01

With the advent of dense single nucleotide polymorphism genotyping, population-based association studies have become the major tools for identifying human disease genes and for fine gene mapping of complex traits. We develop a genotype-based approach for association analysis of case-control studies of gene-environment interactions in the case when environmental factors are measured with error and genotype data are available on multiple genetic markers. To directly use the observed genotype data, we propose two genotype-based models: genotype effect and additive effect models. Our approach offers several advantages. First, the proposed risk functions can directly incorporate the observed genotype data while modeling the linkage disequihbrium information in the regression coefficients, thus eliminating the need to infer haplotype phase. Compared with the haplotype-based approach, an estimating procedure based on the proposed methods can be much simpler and significantly faster. In addition, there is no potential risk due to haplotype phase estimation. Further, by fitting the proposed models, it is possible to analyze the risk alleles/variants of complex diseases, including their dominant or additive effects. To model measurement error, we adopt the pseudo-likelihood method by Lobach et al. [2008]. Performance of the proposed method is examined using simulation experiments. An application of our method is illustrated using a population-based case-control study of association between calcium intake with the risk of colorectal adenoma development. PMID:21031455

Peer Influence, Genetic Propensity, and Binge Drinking: A Natural Experiment and a Replication.

PubMed

Guo, Guang; Li, Yi; Wang, Hongyu; Cai, Tianji; Duncan, Greg J

2015-11-01

The authors draw data from the College Roommate Study (ROOM) and the National Longitudinal Study of Adolescent Health to investigate gene-environment interaction effects on youth binge drinking. In ROOM, the environmental influence was measured by the precollege drinking behavior of randomly assigned roommates. Random assignment safeguards against friend selection and removes the threat of gene-environment correlation that makes gene-environment interaction effects difficult to interpret. On average, being randomly assigned a drinking peer as opposed to a nondrinking peer increased college binge drinking by 0.5-1.0 episodes per month, or 20%-40% the average amount of binge drinking. However, this peer influence was found only among youths with a medium level of genetic propensity for alcohol use; those with either a low or high genetic propensity were not influenced by peer drinking. A replication of the findings is provided in data drawn from Add Health. The study shows that gene-environment interaction analysis can uncover social-contextual effects likely to be missed by traditional sociological approaches.

Gene by Environment Interactions Influencing Reading Disability and the Inattentive Symptom Dimension of Attention Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Rosenberg, Jenni; Pennington, Bruce F.; Willcutt, Erik G.; Olson, Richard K.

2012-01-01

Background: Reading disability (RD) and attention deficit/hyperactivity disorder (ADHD) are comorbid and genetically correlated, especially the inattentive dimension of ADHD (ADHD-I). However, previous research indicates that RD and ADHD enter into opposite gene by environment (G x E) interactions. Methods: This study used behavioral genetic…

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

ERIC Educational Resources Information Center

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…

Genetic Interactions with Prenatal Social Environment: Effects on Academic and Behavioral Outcomes

ERIC Educational Resources Information Center

Conley, Dalton; Rauscher, Emily

2013-01-01

Numerous studies report gene-environment interactions, suggesting that specific alleles have different effects on social outcomes depending on environment. In all these studies, however, environmental conditions are potentially endogenous to unmeasured genetic characteristics. That is, it could be that the observed interaction effects actually…

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

ERIC Educational Resources Information Center

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…

[The role of genotype in the intergenerational transmission of experiences of childhood adversity].

PubMed

Reichl, Corinna; Kaess, Michael; Resch, Franz; Brunner, Romuald

2014-09-01

The prevalence of childhood abuse and maltreatment is estimated to lie at about 15% in the overall German population. Previous research suggested that about one third of all individuals who had experienced childhood adversity subsequently maltreated their own children or responded insensitively to their children's needs. Empirical studies imply that interindividual differences in the responsiveness to childhood adversity can partially be explained by gene-environment interactions. This article discusses the potential interplay of genes and environment in the context of transmitting maltreating behavior and (in)sensitive parenting against the background of current challenges in genetic research. Selected studies on gene × environment interactions are presented and relevant gene polymorphisms are identified. Overall, previous studies reported interactions between polymorphisms of the serotonergic, dopaminergic, oxytocin-related, and arginine vasopressin-related systems and childhood experiences of care and abuse in the prediction of social behaviors during mother-child interactions. The results indicate a differential susceptibility toward both negative and positive environments which is dependent on genetic characteristics. Future research should thus investigate the effects of children's presumed risk gene variants toward negative as well as positive parenting. This could contribute to a deeper understanding of the underlying mechanisms of the intergenerational transmission of abusive and beneficial parenting behavior and help to avoid false stigmatizations.

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

PubMed

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.

Quantitative gene-gene and gene-environment mapping for leaf shape variation using tree-based models

USDA-ARS?s Scientific Manuscript database

Leaf shape traits have long been a focus of many disciplines, but searching for complex genetic and environmental interactive mechanisms regulating leaf shape variation has not yet been well developed. The question of the respective roles of gene and environment and how they interplay to modulate l...

Commentary: Gene-Environment Interplay in the Context of Genetics, Epigenetics, and Gene Expression.

ERIC Educational Resources Information Center

Kramer, Douglas A.

2005-01-01

Objective: To comment on the article in this issue of the Journal by Professor Michael Rutter, "Environmentally Mediated Risks for Psychopathology: Research Strategies and Findings," in the context of current research findings on gene-environment interaction, epigenetics, and gene expression. Method: Animal and human studies are reviewed that…

Do little interactions get lost in dark random forests?

PubMed

Wright, Marvin N; Ziegler, Andreas; König, Inke R

2016-03-31

Random forests have often been claimed to uncover interaction effects. However, if and how interaction effects can be differentiated from marginal effects remains unclear. In extensive simulation studies, we investigate whether random forest variable importance measures capture or detect gene-gene interactions. With capturing interactions, we define the ability to identify a variable that acts through an interaction with another one, while detection is the ability to identify an interaction effect as such. Of the single importance measures, the Gini importance captured interaction effects in most of the simulated scenarios, however, they were masked by marginal effects in other variables. With the permutation importance, the proportion of captured interactions was lower in all cases. Pairwise importance measures performed about equal, with a slight advantage for the joint variable importance method. However, the overall fraction of detected interactions was low. In almost all scenarios the detection fraction in a model with only marginal effects was larger than in a model with an interaction effect only. Random forests are generally capable of capturing gene-gene interactions, but current variable importance measures are unable to detect them as interactions. In most of the cases, interactions are masked by marginal effects and interactions cannot be differentiated from marginal effects. Consequently, caution is warranted when claiming that random forests uncover interactions.

Gene-Environment Interaction in Externalizing Problems among Adolescents: Evidence from the Pelotas 1993 Birth Cohort Study

ERIC Educational Resources Information Center

Kieling, Christian; Hutz, Mara H.; Genro, Julia P.; Polanczyk, Guilherme V.; Anselmi, Luciana; Camey, Suzi; Hallal, Pedro C.; Barros, Fernando C.; Victora, Cesar G.; Menezes, Ana M. B.; Rohde, Luis Augusto

2013-01-01

Background: The study of gene-environment interactions (G by E) is one of the most promising strategies to uncover the origins of mental disorders. Replication of initial findings, however, is essential because there is a strong possibility of publication bias in the literature. In addition, there is a scarcity of research on the topic originated…

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

ERIC Educational Resources Information Center

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.…

A gene network simulator to assess reverse engineering algorithms.

PubMed

Di Camillo, Barbara; Toffolo, Gianna; Cobelli, Claudio

2009-03-01

In the context of reverse engineering of biological networks, simulators are helpful to test and compare the accuracy of different reverse-engineering approaches in a variety of experimental conditions. A novel gene-network simulator is presented that resembles some of the main features of transcriptional regulatory networks related to topology, interaction among regulators of transcription, and expression dynamics. The simulator generates network topology according to the current knowledge of biological network organization, including scale-free distribution of the connectivity and clustering coefficient independent of the number of nodes in the network. It uses fuzzy logic to represent interactions among the regulators of each gene, integrated with differential equations to generate continuous data, comparable to real data for variety and dynamic complexity. Finally, the simulator accounts for saturation in the response to regulation and transcription activation thresholds and shows robustness to perturbations. It therefore provides a reliable and versatile test bed for reverse engineering algorithms applied to microarray data. Since the simulator describes regulatory interactions and expression dynamics as two distinct, although interconnected aspects of regulation, it can also be used to test reverse engineering approaches that use both microarray and protein-protein interaction data in the process of learning. A first software release is available at http://www.dei.unipd.it/~dicamill/software/netsim as an R programming language package.

Interactive Web-based Floodplain Simulation System for Realistic Experiments of Flooding and Flood Damage

NASA Astrophysics Data System (ADS)

Demir, I.

2013-12-01

Recent developments in web technologies make it easy to manage and visualize large data sets with general public. Novel visualization techniques and dynamic user interfaces allow users to create realistic environments, and interact with data to gain insight from simulations and environmental observations. The floodplain simulation system is a web-based 3D interactive flood simulation environment to create real world flooding scenarios. The simulation systems provides a visually striking platform with realistic terrain information, and water simulation. Students can create and modify predefined scenarios, control environmental parameters, and evaluate flood mitigation techniques. The web-based simulation system provides an environment to children and adults learn about the flooding, flood damage, and effects of development and human activity in the floodplain. The system provides various scenarios customized to fit the age and education level of the users. This presentation provides an overview of the web-based flood simulation system, and demonstrates the capabilities of the system for various flooding and land use scenarios.

A PLSPM-Based Test Statistic for Detecting Gene-Gene Co-Association in Genome-Wide Association Study with Case-Control Design

PubMed Central

Zhang, Xiaoshuai; Yang, Xiaowei; Yuan, Zhongshang; Liu, Yanxun; Li, Fangyu; Peng, Bin; Zhu, Dianwen; Zhao, Jinghua; Xue, Fuzhong

2013-01-01

For genome-wide association data analysis, two genes in any pathway, two SNPs in the two linked gene regions respectively or in the two linked exons respectively within one gene are often correlated with each other. We therefore proposed the concept of gene-gene co-association, which refers to the effects not only due to the traditional interaction under nearly independent condition but the correlation between two genes. Furthermore, we constructed a novel statistic for detecting gene-gene co-association based on Partial Least Squares Path Modeling (PLSPM). Through simulation, the relationship between traditional interaction and co-association was highlighted under three different types of co-association. Both simulation and real data analysis demonstrated that the proposed PLSPM-based statistic has better performance than single SNP-based logistic model, PCA-based logistic model, and other gene-based methods. PMID:23620809

A PLSPM-based test statistic for detecting gene-gene co-association in genome-wide association study with case-control design.

PubMed

Zhang, Xiaoshuai; Yang, Xiaowei; Yuan, Zhongshang; Liu, Yanxun; Li, Fangyu; Peng, Bin; Zhu, Dianwen; Zhao, Jinghua; Xue, Fuzhong

2013-01-01

For genome-wide association data analysis, two genes in any pathway, two SNPs in the two linked gene regions respectively or in the two linked exons respectively within one gene are often correlated with each other. We therefore proposed the concept of gene-gene co-association, which refers to the effects not only due to the traditional interaction under nearly independent condition but the correlation between two genes. Furthermore, we constructed a novel statistic for detecting gene-gene co-association based on Partial Least Squares Path Modeling (PLSPM). Through simulation, the relationship between traditional interaction and co-association was highlighted under three different types of co-association. Both simulation and real data analysis demonstrated that the proposed PLSPM-based statistic has better performance than single SNP-based logistic model, PCA-based logistic model, and other gene-based methods.

Research Review: Gene-Environment Interaction Research in Youth Depression--A Systematic Review with Recommendations for Future Research

ERIC Educational Resources Information Center

Dunn, Erin C.; Uddin, Monica; Subramanian, S. V.; Smoller, Jordan W.; Galea, Sandro; Koenen, Karestan C.

2011-01-01

Background: Depression is a major public health problem among youth, currently estimated to affect as many as 9% of US children and adolescents. The recognition that both genes (nature) and environments (nurture) are important for understanding the etiology of depression has led to a rapid growth in research exploring gene-environment interactions…

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.

PubMed

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 SNPs estimated by a multivariate elastic net regression were shown to be a powerful tool to detect gene-environment interactions in scenarios of high Linkage disequilibrium and noise.

Intelligent Motion and Interaction Within Virtual Environments

NASA Technical Reports Server (NTRS)

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.

Refining the Candidate Environment: Interpersonal Stress, the Serotonin Transporter Polymorphism, and Gene-Environment Interactions in Major Depression.

PubMed

Vrshek-Schallhorn, Suzanne; Mineka, Susan; Zinbarg, Richard E; Craske, Michelle G; Griffith, James W; Sutton, Jonathan; Redei, Eva E; Wolitzky-Taylor, Kate; Hammen, Constance; Adam, Emma K

2014-05-01

Meta-analytic evidence supports a gene-environment (G×E) interaction between life stress and the serotonin transporter polymorphism (5-HTTLPR) on depression, but few studies have examined factors that influence detection of this effect, despite years of inconsistent results. We propose that the "candidate environment" (akin to a candidate gene) is key. Theory and evidence implicate major stressful life events (SLEs)-particularly major interpersonal SLEs-as well as chronic family stress. Participants ( N = 400) from the Youth Emotion Project (which began with 627 high school juniors oversampled for high neuroticism) completed up to five annual diagnostic and life stress interviews and provided DNA samples. A significant G×E effect for major SLEs and S -carrier genotype was accounted for significantly by major interpersonal SLEs but not significantly by major non-interpersonal SLEs. S -carrier genotype and chronic family stress also significantly interacted. Identifying such candidate environments may facilitate future G×E research in depression and psychopathology more broadly.

On meta- and mega-analyses for gene-environment interactions.

PubMed

Huang, Jing; Liu, Yulun; Vitale, Steve; Penning, Trevor M; Whitehead, Alexander S; Blair, Ian A; Vachani, Anil; Clapper, Margie L; Muscat, Joshua E; Lazarus, Philip; Scheet, Paul; Moore, Jason H; Chen, Yong

2017-12-01

Gene-by-environment (G × E) interactions are important in explaining the missing heritability and understanding the causation of complex diseases, but a single, moderately sized study often has limited statistical power to detect such interactions. With the increasing need for integrating data and reporting results from multiple collaborative studies or sites, debate over choice between mega- versus meta-analysis continues. In principle, data from different sites can be integrated at the individual level into a "mega" data set, which can be fit by a joint "mega-analysis." Alternatively, analyses can be done at each site, and results across sites can be combined through a "meta-analysis" procedure without integrating individual level data across sites. Although mega-analysis has been advocated in several recent initiatives, meta-analysis has the advantages of simplicity and feasibility, and has recently led to several important findings in identifying main genetic effects. In this paper, we conducted empirical and simulation studies, using data from a G × E study of lung cancer, to compare the mega- and meta-analyses in four commonly used G × E analyses under the scenario that the number of studies is small and sample sizes of individual studies are relatively large. We compared the two data integration approaches in the context of fixed effect models and random effects models separately. Our investigations provide valuable insights in understanding the differences between mega- and meta-analyses in practice of combining small number of studies in identifying G × E interactions. © 2017 WILEY PERIODICALS, INC.

The moderating effect of ANKK1 on the association of family environment with longitudinal executive function following traumatic brain injury in early childhood: A preliminary study.

PubMed

Smith-Paine, Julia; Wade, Shari L; Treble-Barna, Amery; Zhang, Nanhua; Zang, Huaiyu; Martin, Lisa J; Yeates, Keith Owen; Taylor, H Gerry; Kurowski, Brad G

2018-05-02

This study examined whether the ankyrin repeat and kinase domain containing 1 gene (ANKK1) C/T single-nucleotide polymorphism (SNP) rs1800497 moderated the association of family environment with long-term executive function (EF) following traumatic injury in early childhood. Caregivers of children with traumatic brain injury (TBI) and children with orthopedic injury (OI) completed the Behavior Rating Inventory of Executive Function (BRIEF) at post injury visits. DNA was collected to identify the rs1800497 genotype in the ANKK1 gene. General linear models examined gene-environment interactions as moderators of the effects of TBI on EF at two times post injury (12 months and 7 years). At 12 months post injury, analyses revealed a significant 3-way interaction of genotype with level of permissive parenting and injury type. Post-hoc analyses showed genetic effects were more pronounced for children with TBI from more positive family environments, such that children with TBI who were carriers of the risk allele (T-allele) had significantly poorer EF compared to non-carriers only when they were from more advantaged environments. At 7 years post injury, analyses revealed a significant 2-way interaction of genotype with level of authoritarian parenting. Post-hoc analyses found that carriers of the risk allele had significantly poorer EF compared to non-carriers only when they were from more advantaged environments. These results suggest a gene-environment interaction involving the ANKK1 gene as a predictor of EF in a pediatric injury population. The findings highlight the importance of considering environmental influences in future genetic studies on recovery following TBI and other traumatic injuries in childhood.

Social defeat interacts with Disc1 mutations in the mouse to affect behavior.

PubMed

Haque, F Nipa; Lipina, Tatiana V; Roder, John C; Wong, Albert H C

2012-08-01

DISC1 (Disrupted-in-schizophrenia 1) is a strong candidate susceptibility gene for psychiatric disease that was originally discovered in a family with a chromosomal translocation severing this gene. Although the family members with the translocation had an identical genetic mutation, their clinical diagnosis and presentation varied significantly. Gene-environment interactions have been proposed as a mechanism underlying the complex heritability and variable phenotype of psychiatric disorders such as major depressive disorder and schizophrenia. We hypothesized that gene-environment interactions would affect behavior in a mutant Disc1 mouse model. We examined the effect of chronic social defeat (CSD) as an environmental stressor in two lines of mice carrying different Disc1 point mutations, on behaviors relevant to psychiatric illness: locomotion in a novel open field (OF), pre-pulse inhibition (PPI) of the acoustic startle response, latent inhibition (LI), elevated plus maze (EPM), forced swim test (FST), sucrose consumption (SC), and the social interaction task for sociability and social novelty (SSN). We found that Disc1-L100P +/- and wild-type mice have similar anxiety responses to CSD, while Q31L +/- mice had a very different response. We also found evidence of significant gene-environment interactions in the OF, EPM and SSN. Copyright © 2012 Elsevier B.V. All rights reserved.

ReliefSeq: A Gene-Wise Adaptive-K Nearest-Neighbor Feature Selection Tool for Finding Gene-Gene Interactions and Main Effects in mRNA-Seq Gene Expression Data

PubMed Central

McKinney, Brett A.; White, Bill C.; Grill, Diane E.; Li, Peter W.; Kennedy, Richard B.; Poland, Gregory A.; Oberg, Ann L.

2013-01-01

Relief-F is a nonparametric, nearest-neighbor machine learning method that has been successfully used to identify relevant variables that may interact in complex multivariate models to explain phenotypic variation. While several tools have been developed for assessing differential expression in sequence-based transcriptomics, the detection of statistical interactions between transcripts has received less attention in the area of RNA-seq analysis. We describe a new extension and assessment of Relief-F for feature selection in RNA-seq data. The ReliefSeq implementation adapts the number of nearest neighbors (k) for each gene to optimize the Relief-F test statistics (importance scores) for finding both main effects and interactions. We compare this gene-wise adaptive-k (gwak) Relief-F method with standard RNA-seq feature selection tools, such as DESeq and edgeR, and with the popular machine learning method Random Forests. We demonstrate performance on a panel of simulated data that have a range of distributional properties reflected in real mRNA-seq data including multiple transcripts with varying sizes of main effects and interaction effects. For simulated main effects, gwak-Relief-F feature selection performs comparably to standard tools DESeq and edgeR for ranking relevant transcripts. For gene-gene interactions, gwak-Relief-F outperforms all comparison methods at ranking relevant genes in all but the highest fold change/highest signal situations where it performs similarly. The gwak-Relief-F algorithm outperforms Random Forests for detecting relevant genes in all simulation experiments. In addition, Relief-F is comparable to the other methods based on computational time. We also apply ReliefSeq to an RNA-Seq study of smallpox vaccine to identify gene expression changes between vaccinia virus-stimulated and unstimulated samples. ReliefSeq is an attractive tool for inclusion in the suite of tools used for analysis of mRNA-Seq data; it has power to detect both main effects and interaction effects. Software Availability: http://insilico.utulsa.edu/ReliefSeq.php. PMID:24339943

Interaction of rearing environment and reproductive tactic on gene expression profiles in Atlantic salmon

USGS Publications Warehouse

Aubin-Horth, N.; Letcher, B.H.; Hofmann, H.A.

2005-01-01

Organisms that share the same genotype can develop into divergent phenotypes, depending on environmental conditions. In Atlantic salmon, young males of the same age can be found either as sneakers or immature males that are future anadromous fish. Just as the organism-level phenotype varies between divergent male developmental trajectories, brain gene expression is expected to vary as well. We hypothesized that rearing environment can also have an important effect on gene expression in the brain and possibly interact with the reproductive tactic adopted. We tested this hypothesis by comparing brain gene expression profiles of the two male tactics in fish from the same population that were reared in either a natural stream or under laboratory conditions. We found that expression of certain genes was affected by rearing environment only, while others varied between male reproductive tactics independent of rearing environment. Finally, more than half of all genes that showed variable expression varied between the two male tactics only in one environment. Thus, in these fish, very different molecular pathways can give rise to similar macro-phenotypes depending on rearing environment. This result gives important insights into the molecular underpinnings of developmental plasticity in relationship to the environment. ?? 2005 The American Genetic Association.

Modeling Gene-Environment Interactions With Quasi-Natural Experiments.

PubMed

Schmitz, Lauren; Conley, Dalton

2017-02-01

This overview develops new empirical models that can effectively document Gene × Environment (G×E) interactions in observational data. Current G×E studies are often unable to support causal inference because they use endogenous measures of the environment or fail to adequately address the nonrandom distribution of genes across environments, confounding estimates. Comprehensive measures of genetic variation are incorporated into quasi-natural experimental designs to exploit exogenous environmental shocks or isolate variation in environmental exposure to avoid potential confounders. In addition, we offer insights from population genetics that improve upon extant approaches to address problems from population stratification. Together, these tools offer a powerful way forward for G×E research on the origin and development of social inequality across the life course. © 2015 Wiley Periodicals, Inc.

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).

PubMed

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.

The influence of urban/rural residency on depressive symptoms is moderated by the serotonin receptor 2A gene.

PubMed

Jokela, Markus; Lehtimäki, Terho; Keltikangas-Järvinen, Liisa

2007-10-05

Gene-environment interactions are thought to be involved in the development of depression. Here we examined the interaction effect between urban/rural residency and the serotonin receptor 2A (HTR2A) gene on subclinical depressive symptoms. The participants were 1,224 Finnish men and women being followed in the on-going population-based study of "Cardiovascular Risk in Young Finns". Urban/rural residency was determined on the basis of a (1) subjective report and (2) the population density of the residential area. Depressive symptoms were measured in two test settings four years apart. There was a significant gene-environment interaction, such that the urban residency was associated with low depressive symptoms in individuals carrying the T/T or T/C genotype of the T102C polymorphism, but not in those carrying the C/C genotype. The T allele was associated with high depressive symptoms in remote rural areas, but with low depressive symptoms in urban or suburban areas. The gene-environment interaction was not accounted by level of education, social support, unemployment, or partnership status. The HTR2A gene may be involved in the development of depression by influencing how individuals respond to environmental conditions. (c) 2007 Wiley-Liss, Inc.

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

PubMed Central

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

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

PubMed

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.

Interaction of phase variation, host and pressure/gas composition: pneumococcal gene expression of PsaA, SpxB, Ply and LytA in simulated middle ear environments.

PubMed

Li-Korotky, Ha-Sheng; Lo, Chia-Yee; Zeng, Fan-Rui; Lo, David; Banks, Juliane M

2009-10-01

Streptococcus pneumoniae, a leading cause of otitis media (OM), undergoes spontaneous intra-strain variations in colony morphology. Transparent (T) variants are more efficient in colonizing the nasopharynx while opaque (O) variants exhibit greater virulence during systemic infections. This study was intended to delineate the underlying molecular mechanisms by which the predominant S. pneumoniae variant efficiently infects the middle ear (ME) mucosa. Human ME epithelial cells were preconditioned for 24h under one of the three gas/pressure conditions designed to simulate those for (1) normal ME (NME), (2) ME with Eustachian tube obstruction (ETO) and (3) ME with tympanostomy tube placement (TT), and then were incubated with ∼ 10(7)CFU/ml of either T or O variants of S. pneumoniae (6A) for 3h. Relative expression levels of genes encoding virulence factors, PsaA (surface adhesion), SpxB (pyruvate oxidase), Ply (pneumolysin), and LytA (autolysin) were assessed separately in epithelium-attached and supernatant bacteria 3h post infection using real-time PCR. Basal levels of the virulence molecules in inocula were comparable between two variants. However, relative expression levels of the gene transcripts were significantly induced in epithelium-attached T variants 3h after infection. Comparing with NME and TT conditions, ETO environment produced the largest effect on the differential expression of the virulence genes in the infected ME epithelial cells between T (induced) and O (suppressed) phenotypic pneumococci. T variant is a predominant phenotype responsible for the pathogenesis of pneumococcal OM.

Examining Gene-Environment Interactions in Comorbid Depressive and Disruptive Behavior Disorders using a Bayesian Approach

PubMed Central

Adrian, Molly; Kiff, Cara; Glazner, Chris; Kohen, Ruth; Tracy, Julia Helen; Zhou, Chuan; McCauley, Elizabeth; Stoep, Ann Vander

2015-01-01

Objective The objective of this study was to apply a Bayesian statistical analytic approach that minimizes multiple testing problems to explore the combined effects of chronic low familial support and variants in 12 candidate genes on risk for a common and debilitating childhood mental health condition. Method Bayesian mixture modeling was used to examine gene by environment interactions among genetic variants and environmental factors (family support) associated in previous studies with the occurrence of comorbid depression and disruptive behavior disorders youth, using a sample of 255 children. Results One main effects, variants in the oxytocin receptor (OXTR, rs53576) was associated with increased risk for comorbid disorders. Two significant gene x environment and one signification gene x gene interaction emerged. Variants in the nicotinic acetylcholine receptor α5 subunit (CHRNA5, rs16969968) and in the glucocorticoid receptor chaperone protein FK506 binding protein 5 (FKBP5, rs4713902) interacted with chronic low family support in association with child mental health status. One gene x gene interaction, 5-HTTLPR variant of the serotonin transporter (SERT/SLC6A4) in combination with μ opioid receptor (OPRM1, rs1799971) was associated with comorbid depression and conduct problems. Conclusions Results indicate that Bayesian modeling is a feasible strategy for conducting behavioral genetics research. This approach, combined with an optimized genetic selection strategy (Vrieze, Iacono, & McGue, 2012), revealed genetic variants involved in stress regulation ( FKBP5, SERTxOPMR), social bonding (OXTR), and nicotine responsivity (CHRNA5) in predicting comorbid status. PMID:26228411

Gene-Environment Interplay in the Link of Friends' and Nonfriends' Behaviors with Children's Social Reticence in a Competitive Situation

ERIC Educational Resources Information Center

Guimond, Fanny-Alexandra; Brendgen, Mara; Vitaro, Frank; Forget-Dubois, Nadine; Dionne, Ginette; Tremblay, Richard E.; Boivin, Michel

2014-01-01

This study used a genetically informed design to assess the effects of friends' and nonfriends' reticent and dominant behaviors on children's observed social reticence in a competitive situation. Potential gene-environment correlations (rGE) and gene-environment interactions (GxE) in the link between (a) friends' and…

Cerebellum Transcriptome of Mice Bred for High Voluntary Activity Offers Insights into Locomotor Control and Reward-Dependent Behaviors.

PubMed

Caetano-Anollés, Kelsey; Rhodes, Justin S; Garland, Theodore; Perez, Sam D; Hernandez, Alvaro G; Southey, Bruce R; Rodriguez-Zas, Sandra L

2016-01-01

The role of the cerebellum in motivation and addictive behaviors is less understood than that in control and coordination of movements. High running can be a self-rewarding behavior exhibiting addictive properties. Changes in the cerebellum transcriptional networks of mice from a line selectively bred for High voluntary running (H) were profiled relative to an unselected Control (C) line. The environmental modulation of these changes was assessed both in activity environments corresponding to 7 days of Free (F) access to running wheel and to Blocked (B) access on day 7. Overall, 457 genes exhibited a significant (FDR-adjusted P-value < 0.05) genotype-by-environment interaction effect, indicating that activity genotype differences in gene expression depend on environmental access to running. Among these genes, network analysis highlighted 6 genes (Nrgn, Drd2, Rxrg, Gda, Adora2a, and Rab40b) connected by their products that displayed opposite expression patterns in the activity genotype contrast within the B and F environments. The comparison of network expression topologies suggests that selection for high voluntary running is linked to a predominant dysregulation of hub genes in the F environment that enables running whereas a dysregulation of ancillary genes is favored in the B environment that blocks running. Genes associated with locomotor regulation, signaling pathways, reward-processing, goal-focused, and reward-dependent behaviors exhibited significant genotype-by-environment interaction (e.g. Pak6, Adora2a, Drd2, and Arhgap8). Neuropeptide genes including Adcyap1, Cck, Sst, Vgf, Npy, Nts, Penk, and Tac2 and related receptor genes also exhibited significant genotype-by-environment interaction. The majority of the 183 differentially expressed genes between activity genotypes (e.g. Drd1) were under-expressed in C relative to H genotypes and were also under-expressed in B relative to F environments. Our findings indicate that the high voluntary running mouse line studied is a helpful model for understanding the molecular mechanisms in the cerebellum that influence locomotor control and reward-dependent behaviors.

Cerebellum Transcriptome of Mice Bred for High Voluntary Activity Offers Insights into Locomotor Control and Reward-Dependent Behaviors

PubMed Central

Caetano-Anollés, Kelsey; Rhodes, Justin S.; Garland, Theodore; Perez, Sam D.; Hernandez, Alvaro G.; Southey, Bruce R.; Rodriguez-Zas, Sandra L.

2016-01-01

The role of the cerebellum in motivation and addictive behaviors is less understood than that in control and coordination of movements. High running can be a self-rewarding behavior exhibiting addictive properties. Changes in the cerebellum transcriptional networks of mice from a line selectively bred for High voluntary running (H) were profiled relative to an unselected Control (C) line. The environmental modulation of these changes was assessed both in activity environments corresponding to 7 days of Free (F) access to running wheel and to Blocked (B) access on day 7. Overall, 457 genes exhibited a significant (FDR-adjusted P-value < 0.05) genotype-by-environment interaction effect, indicating that activity genotype differences in gene expression depend on environmental access to running. Among these genes, network analysis highlighted 6 genes (Nrgn, Drd2, Rxrg, Gda, Adora2a, and Rab40b) connected by their products that displayed opposite expression patterns in the activity genotype contrast within the B and F environments. The comparison of network expression topologies suggests that selection for high voluntary running is linked to a predominant dysregulation of hub genes in the F environment that enables running whereas a dysregulation of ancillary genes is favored in the B environment that blocks running. Genes associated with locomotor regulation, signaling pathways, reward-processing, goal-focused, and reward-dependent behaviors exhibited significant genotype-by-environment interaction (e.g. Pak6, Adora2a, Drd2, and Arhgap8). Neuropeptide genes including Adcyap1, Cck, Sst, Vgf, Npy, Nts, Penk, and Tac2 and related receptor genes also exhibited significant genotype-by-environment interaction. The majority of the 183 differentially expressed genes between activity genotypes (e.g. Drd1) were under-expressed in C relative to H genotypes and were also under-expressed in B relative to F environments. Our findings indicate that the high voluntary running mouse line studied is a helpful model for understanding the molecular mechanisms in the cerebellum that influence locomotor control and reward-dependent behaviors. PMID:27893846

Gene–environment interaction in tobacco-related cancers

PubMed Central

Taioli, Emanuela

2008-01-01

This review summarizes the carcinogenic effects of tobacco smoke and the basis for interaction between tobacco smoke and genetic factors. Examples of published papers on gene–tobacco interaction and cancer risk are presented. The assessment of gene–environment interaction in tobacco-related cancers has been more complex than originally expected for several reasons, including the multiplicity of genes involved in tobacco metabolism, the numerous substrates metabolized by the relevant genes and the interaction of smoking with other metabolic pathways. Future studies on gene–environment interaction and cancer risk should include biomarkers of smoking dose, along with markers of quantitative historical exposure to tobacco. Epigenetic studies should be added to classic genetic analyses, in order to better understand gene–environmental interaction and individual susceptibility. Other metabolic pathways in competition with tobacco genetic metabolism/repair should be incorporated in epidemiological studies to generate a more complete picture of individual cancer risk associated with environmental exposure to carcinogens. PMID:18550573

Genetics and Peer Relations: A Review

ERIC Educational Resources Information Center

Brendgen, Mara

2012-01-01

Researchers have become increasingly interested in uncovering how genetic factors work together with the peer environment in influencing development. This article offers an overview of the state of knowledge. It first describes the different types of gene-environment correlations (rGE) and gene-environment interactions (GxE) that are of relevance…

Simulating human behavior for national security human interactions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernard, Michael Lewis; Hart, Dereck H.; Verzi, Stephen J.

2007-01-01

This 3-year research and development effort focused on what we believe is a significant technical gap in existing modeling and simulation capabilities: the representation of plausible human cognition and behaviors within a dynamic, simulated environment. Specifically, the intent of the ''Simulating Human Behavior for National Security Human Interactions'' project was to demonstrate initial simulated human modeling capability that realistically represents intra- and inter-group interaction behaviors between simulated humans and human-controlled avatars as they respond to their environment. Significant process was made towards simulating human behaviors through the development of a framework that produces realistic characteristics and movement. The simulated humansmore » were created from models designed to be psychologically plausible by being based on robust psychological research and theory. Progress was also made towards enhancing Sandia National Laboratories existing cognitive models to support culturally plausible behaviors that are important in representing group interactions. These models were implemented in the modular, interoperable, and commercially supported Umbra{reg_sign} simulation framework.« less

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

PubMed

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.

Systems Modeling at Multiple Levels of Regulation: Linking Systems and Genetic Networks to Spatially Explicit Plant Populations

PubMed Central

Kitchen, James L.; Allaby, Robin G.

2013-01-01

Selection and adaptation of individuals to their underlying environments are highly dynamical processes, encompassing interactions between the individual and its seasonally changing environment, synergistic or antagonistic interactions between individuals and interactions amongst the regulatory genes within the individual. Plants are useful organisms to study within systems modeling because their sedentary nature simplifies interactions between individuals and the environment, and many important plant processes such as germination or flowering are dependent on annual cycles which can be disrupted by climate behavior. Sedentism makes plants relevant candidates for spatially explicit modeling that is tied in with dynamical environments. We propose that in order to fully understand the complexities behind plant adaptation, a system that couples aspects from systems biology with population and landscape genetics is required. A suitable system could be represented by spatially explicit individual-based models where the virtual individuals are located within time-variable heterogeneous environments and contain mutable regulatory gene networks. These networks could directly interact with the environment, and should provide a useful approach to studying plant adaptation. PMID:27137364

Linear Optics Simulation of Quantum Non-Markovian Dynamics

PubMed Central

Chiuri, Andrea; Greganti, Chiara; Mazzola, Laura; Paternostro, Mauro; Mataloni, Paolo

2012-01-01

The simulation of open quantum dynamics has recently allowed the direct investigation of the features of system-environment interaction and of their consequences on the evolution of a quantum system. Such interaction threatens the quantum properties of the system, spoiling them and causing the phenomenon of decoherence. Sometimes however a coherent exchange of information takes place between system and environment, memory effects arise and the dynamics of the system becomes non-Markovian. Here we report the experimental realisation of a non-Markovian process where system and environment are coupled through a simulated transverse Ising model. By engineering the evolution in a photonic quantum simulator, we demonstrate the role played by system-environment correlations in the emergence of memory effects. PMID:23236588

Development of an Interactive Augmented Environment and Its Application to Autonomous Learning for Quadruped Robots

NASA Astrophysics Data System (ADS)

Kobayashi, Hayato; Osaki, Tsugutoyo; Okuyama, Tetsuro; Gramm, Joshua; Ishino, Akira; Shinohara, Ayumi

This paper describes an interactive experimental environment for autonomous soccer robots, which is a soccer field augmented by utilizing camera input and projector output. This environment, in a sense, plays an intermediate role between simulated environments and real environments. We can simulate some parts of real environments, e.g., real objects such as robots or a ball, and reflect simulated data into the real environments, e.g., to visualize the positions on the field, so as to create a situation that allows easy debugging of robot programs. The significant point compared with analogous work is that virtual objects are touchable in this system owing to projectors. We also show the portable version of our system that does not require ceiling cameras. As an application in the augmented environment, we address the learning of goalie strategies on real quadruped robots in penalty kicks. We make our robots utilize virtual balls in order to perform only quadruped locomotion in real environments, which is quite difficult to simulate accurately. Our robots autonomously learn and acquire more beneficial strategies without human intervention in our augmented environment than those in a fully simulated environment.

Virtual environments simulation in research reactor

NASA Astrophysics Data System (ADS)

Muhamad, Shalina Bt. Sheik; Bahrin, Muhammad Hannan Bin

2017-01-01

Virtual reality based simulations are interactive and engaging. It has the useful potential in improving safety training. Virtual reality technology can be used to train workers who are unfamiliar with the physical layout of an area. In this study, a simulation program based on the virtual environment at research reactor was developed. The platform used for virtual simulation is 3DVia software for which it's rendering capabilities, physics for movement and collision and interactive navigation features have been taken advantage of. A real research reactor was virtually modelled and simulated with the model of avatars adopted to simulate walking. Collision detection algorithms were developed for various parts of the 3D building and avatars to restrain the avatars to certain regions of the virtual environment. A user can control the avatar to move around inside the virtual environment. Thus, this work can assist in the training of personnel, as in evaluating the radiological safety of the research reactor facility.

Virtual acoustic environments for comprehensive evaluation of model-based hearing devices.

PubMed

Grimm, Giso; Luberadzka, Joanna; Hohmann, Volker

2018-06-01

Create virtual acoustic environments (VAEs) with interactive dynamic rendering for applications in audiology. A toolbox for creation and rendering of dynamic virtual acoustic environments (TASCAR) that allows direct user interaction was developed for application in hearing aid research and audiology. The software architecture and the simulation methods used to produce VAEs are outlined. Example environments are described and analysed. With the proposed software, a tool for simulation of VAEs is available. A set of VAEs rendered with the proposed software was described.

Commentary: Fundamental problems with candidate gene-by-environment interaction studies - reflections on Moore and Thoemmes (2016).

PubMed

Border, Richard; Keller, Matthew C

2017-03-01

Moore and Thoemmes elaborate on one particular source of difficulty in the study of candidate gene-by-environment interactions (cG × E): how different biologically plausible configurations of gene-environment covariation can bias estimates of cG × E when not explicitly modeled. However, even if cG × E investigators were able to account for the sources of bias Moore and Thoemmes elaborate, it is unlikely that conventional approaches would yield reliable results. Published cG × E findings to date have generally employed inadequate analytic procedures, have relied on samples orders of magnitude too small to detect plausible effects, and have relied on a particular candidate gene approach that has been unfruitful and largely jettisoned in mainstream genetic analyses of complex traits. Analytic procedures for the study of gene-environment interplay must evolve to meet the challenges that the genetic architecture of complex traits presents, and investigators must collaborate on grander scales if we hope to begin to understand how specific genes and environments combine to affect behavior. © 2017 Association for Child and Adolescent Mental Health.

Effects of simulated microgravity on Streptococcus mutans physiology and biofilm structure.

PubMed

Cheng, Xingqun; Xu, Xin; Chen, Jing; Zhou, Xuedong; Cheng, Lei; Li, Mingyun; Li, Jiyao; Wang, Renke; Jia, Wenxiang; Li, Yu-Qing

2014-10-01

Long-term spaceflights will eventually become an inevitable occurrence. Previous studies have indicated that oral infectious diseases, including dental caries, were more prevalent in astronauts due to the effect of microgravity. However, the impact of the space environment, especially the microgravity environment, on the virulence factors of Streptococcus mutans, a major caries-associated bacterium, is yet to be explored. In the present study, we investigated the impact of simulated microgravity on the physiology and biofilm structure of S. mutans. We also explored the dual-species interaction between S. mutans and Streptococcus sanguinis under a simulated microgravity condition. Results indicated that the simulated microgravity condition can enhance the acid tolerance ability, modify the biofilm architecture and extracellular polysaccharide distribution of S. mutans, and increase the proportion of S. mutans within a dual-species biofilm, probably through the regulation of various gene expressions. We hypothesize that the enhanced competitiveness of S. mutans under simulated microgravity may cause a multispecies micro-ecological imbalance, which would result in the initiation of dental caries. Our current findings are consistent with previous studies, which revealed a higher astronaut-associated incidence of caries. Further research is required to explore the detailed mechanisms. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

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

PubMed Central

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

Gene-gene and gene-environment interactions defining lipid-related traits.

PubMed

Ordovás, José M; Robertson, Ruairi; Cléirigh, Ellen Ní

2011-04-01

Steps towards reducing chronic disease progression are continuously being taken through the form of genomic research. Studies over the last year have highlighted more and more polymorphisms, pathways and interactions responsible for metabolic disorders such as cardiovascular disease, obesity and dyslipidemia. Many of these chronic illnesses can be partially blamed by altered lipid metabolism, combined with individual genetic components. Critical evaluation and comparison of these recent studies is essential in order to comprehend the results, conclusions and future prospects in the field of genomics as a whole. Recent literature elucidates significant gene--diet and gene--environment interactions resulting in altered lipid metabolism, inflammation and other metabolic imbalances leading to cardiovascular disease and obesity. Epigenetic and epistatic interactions are now becoming more significantly associated with such disorders, as genomic research digs deeper into the complex nature of genetic individuality and heritability. The vast array of data collected from genome-wide association studies must now be empowered and explored through more complex interaction studies, using standardized methods and larger sample sizes. In doing so the etiology of chronic disease progression will be further understood.

Gender specific gene-environment interactions on laboratory-assessed aggression.

PubMed

Verona, Edelyn; Joiner, Thomas E; Johnson, Frank; Bender, Theodore W

2006-01-01

We examined gene-environment interactive effects on aggressive behavior among men and women genotyped (short versus long alleles) for the serotonin transporter gene. Aggressive behavior was indexed via a laboratory paradigm that measured the intensity and duration of shocks delivered to a putative "employee". Half of the participants were exposed to a physical stressor during the procedure (stress) and half were not (no-stress). Participants' physiological responses were gauged via acoustic startle eyeblink reactions (startle reactivity). Results were that men with the homozygous short (s/s) genotype showed increased aggression only under stress, whereas women and men carrying the long allele did not show differences in aggression in stress versus no-stress. However, although stress exposure produced increases in startle reactivity, there were no genotype or gender differences in physiology. These results replicate longitudinal research findings confirming the interactive effects of genes and environment on behavioral reactivity and on the development of externalizing psychopathological syndromes, at least in men.

Brain-derived neurotrophic factor as a model system for examining gene by environment interactions across development.

PubMed

Casey, B J; Glatt, C E; Tottenham, N; Soliman, F; Bath, K; Amso, D; Altemus, M; Pattwell, S; Jones, R; Levita, L; McEwen, B; Magariños, A M; Gunnar, M; Thomas, K M; Mezey, J; Clark, A G; Hempstead, B L; Lee, F S

2009-11-24

There has been a dramatic rise in gene x environment studies of human behavior over the past decade that have moved the field beyond simple nature versus nurture debates. These studies offer promise in accounting for more variability in behavioral and biological phenotypes than studies that focus on genetic or experiential factors alone. They also provide clues into mechanisms of modifying genetic risk or resilience in neurodevelopmental disorders. Yet, it is rare that these studies consider how these interactions change over the course of development. In this paper, we describe research that focuses on the impact of a polymorphism in a brain-derived neurotrophic factor (BDNF) gene, known to be involved in learning and development. Specifically we present findings that assess the effects of genotypic and environmental loadings on neuroanatomic and behavioral phenotypes across development. The findings illustrate the use of a genetic mouse model that mimics the human polymorphism, to constrain the interpretation of gene-environment interactions across development in humans.

Epistasis-list.org: A Curated Database of Gene-Gene and Gene-Environment Interactions in Human Epidemiology

EPA Science Inventory

The field of human genetics has experienced a paradigm shift in that common diseases are now thought to be due to the complex interactions among numerous genetic and environmental factors. This paradigm shift has prompted the development of myriad novel methods to detect such int...

iLOCi: a SNP interaction prioritization technique for detecting epistasis in genome-wide association studies

PubMed Central

2012-01-01

Background Genome-wide association studies (GWAS) do not provide a full account of the heritability of genetic diseases since gene-gene interactions, also known as epistasis are not considered in single locus GWAS. To address this problem, a considerable number of methods have been developed for identifying disease-associated gene-gene interactions. However, these methods typically fail to identify interacting markers explaining more of the disease heritability over single locus GWAS, since many of the interactions significant for disease are obscured by uninformative marker interactions e.g., linkage disequilibrium (LD). Results In this study, we present a novel SNP interaction prioritization algorithm, named iLOCi (Interacting Loci). This algorithm accounts for marker dependencies separately in case and control groups. Disease-associated interactions are then prioritized according to a novel ranking score calculated from the difference in marker dependencies for every possible pair between case and control groups. The analysis of a typical GWAS dataset can be completed in less than a day on a standard workstation with parallel processing capability. The proposed framework was validated using simulated data and applied to real GWAS datasets using the Wellcome Trust Case Control Consortium (WTCCC) data. The results from simulated data showed the ability of iLOCi to identify various types of gene-gene interactions, especially for high-order interaction. From the WTCCC data, we found that among the top ranked interacting SNP pairs, several mapped to genes previously known to be associated with disease, and interestingly, other previously unreported genes with biologically related roles. Conclusion iLOCi is a powerful tool for uncovering true disease interacting markers and thus can provide a more complete understanding of the genetic basis underlying complex disease. The program is available for download at http://www4a.biotec.or.th/GI/tools/iloci. PMID:23281813

Real-time, interactive, visually updated simulator system for telepresence

NASA Technical Reports Server (NTRS)

Schebor, Frederick S.; Turney, Jerry L.; Marzwell, Neville I.

1991-01-01

Time delays and limited sensory feedback of remote telerobotic systems tend to disorient teleoperators and dramatically decrease the operator's performance. To remove the effects of time delays, key components were designed and developed of a prototype forward simulation subsystem, the Global-Local Environment Telerobotic Simulator (GLETS) that buffers the operator from the remote task. GLETS totally immerses an operator in a real-time, interactive, simulated, visually updated artificial environment of the remote telerobotic site. Using GLETS, the operator will, in effect, enter into a telerobotic virtual reality and can easily form a gestalt of the virtual 'local site' that matches the operator's normal interactions with the remote site. In addition to use in space based telerobotics, GLETS, due to its extendable architecture, can also be used in other teleoperational environments such as toxic material handling, construction, and undersea exploration.

Dependence of the Linker Histone and Chromatin Condensation on the Nucleosome Environment.

PubMed

Perišić, Ognjen; Schlick, Tamar

2017-08-24

The linker histone (LH), an auxiliary protein that can bind to chromatin and interact with the linker DNA to form stem motifs, is a key element of chromatin compaction. By affecting the chromatin condensation level, it also plays an active role in gene expression. However, the presence and variable concentration of LH in chromatin fibers with different DNA linker lengths indicate that its folding and condensation are highly adaptable and dependent on the immediate nucleosome environment. Recent experimental studies revealed that the behavior of LH in mononucleosomes markedly differs from that in small nucleosome arrays, but the associated mechanism is unknown. Here we report a structural analysis of the behavior of LH in mononucleosomes and oligonucleosomes (2-6 nucleosomes) using mesoscale chromatin simulations. We show that the adapted stem configuration heavily depends on the strength of electrostatic interactions between LH and its parental DNA linkers, and that those interactions tend to be asymmetric in small oligonucleosome systems. Namely, LH in oligonucleosomes dominantly interacts with one DNA linker only, as opposed to mononucleosomes where LH has similar interactions with both linkers and forms a highly stable nucleosome stem. Although we show that the LH condensation depends sensitively on the electrostatic interactions with entering and exiting DNA linkers, other interactions, especially by nonparental cores and nonparental linkers, modulate the structural condensation by softening LH and thus making oligonucleosomes more flexible, in comparison to to mono- and dinucleosomes. We also find that the overall LH/chromatin interactions sensitively depend on the linker length because the linker length determines the maximal nucleosome stem length. For mononucleosomes with DNA linkers shorter than LH, LH condenses fully, while for DNA linkers comparable or longer than LH, the LH extension in mononucleosomes strongly follows the length of DNA linkers, unhampered by neighboring linker histones. Thus, LH is more condensed for mononucleosomes with short linkers, compared to oligonucleosomes, and its orientation is variable and highly environment-dependent. More generally, the work underscores the agility of LH whose folding dynamics critically controls genomic packaging and gene expression.

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

PubMed Central

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

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

PubMed

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 and mood disorders may also have partially independent etiological pathways. To identify where these pathways diverge, we need to understand the differential, phenotype-specific gene-environment interactions such as the ones observed in the present study, using suitably powered samples.

Distributed and collaborative synthetic environments

NASA Technical Reports Server (NTRS)

Bajaj, Chandrajit L.; Bernardini, Fausto

1995-01-01

Fast graphics workstations and increased computing power, together with improved interface technologies, have created new and diverse possibilities for developing and interacting with synthetic environments. A synthetic environment system is generally characterized by input/output devices that constitute the interface between the human senses and the synthetic environment generated by the computer; and a computation system running a real-time simulation of the environment. A basic need of a synthetic environment system is that of giving the user a plausible reproduction of the visual aspect of the objects with which he is interacting. The goal of our Shastra research project is to provide a substrate of geometric data structures and algorithms which allow the distributed construction and modification of the environment, efficient querying of objects attributes, collaborative interaction with the environment, fast computation of collision detection and visibility information for efficient dynamic simulation and real-time scene display. In particular, we address the following issues: (1) A geometric framework for modeling and visualizing synthetic environments and interacting with them. We highlight the functions required for the geometric engine of a synthetic environment system. (2) A distribution and collaboration substrate that supports construction, modification, and interaction with synthetic environments on networked desktop machines.

Early Adverse Environments and Genetic Influences on Age at First Sex: Evidence for Gene × Environment Interaction

ERIC Educational Resources Information Center

Carlson, Marie D.; Mendle, Jane; Harden, K. Paige

2014-01-01

Youth who experience adverse environments in early life initiate sexual activity at a younger age, on average, than those from more advantaged circumstances. Evolutionary theorists have posited that ecological stress precipitates earlier reproductive and sexual onset, but it is unclear how stressful environments interact with genetic influences on…

Bisphenol-A and Female Infertility: A Possible Role of Gene-Environment Interactions

PubMed Central

Huo, Xiaona; Chen, Dan; He, Yonghua; Zhu, Wenting; Zhou, Wei; Zhang, Jun

2015-01-01

Background: Bisphenol-A (BPA) is widely used and ubiquitous in the environment. Animal studies indicate that BPA affects reproduction, however, the gene-environment interaction mechanism(s) involved in this association remains unclear. We performed a literature review to summarize the evidence on this topic. Methods: A comprehensive search was conducted in PubMed using as keywords BPA, gene, infertility and female reproduction. Full-text articles in both human and animals published in English prior to December 2014 were selected. Results: Evidence shows that BPA can interfere with endocrine function of hypothalamic-pituitary axis, such as by changing gonadotropin-releasing hormones (GnRH) secretion in hypothalamus and promoting pituitary proliferation. Such actions affect puberty, ovulation and may even result in infertility. Ovary, uterus and other reproductive organs are also targets of BPA. BPA exposure impairs the structure and functions of female reproductive system in different times of life cycle and may contribute to infertility. Both epidemiological and experimental evidences demonstrate that BPA affects reproduction-related gene expression and epigenetic modification that are closely associated with infertility. The detrimental effects on reproduction may be lifelong and transgenerational. Conclusions: Evidence on gene-environment interactions, especially from human studies, is still limited. Further research on this topic is warranted. PMID:26371021

Rigorous tests of gene-environment interactions in a lab study of the oxytocin receptor gene (OXTR), alcohol exposure, and aggression.

PubMed

LoParo, Devon; Johansson, Ada; Walum, Hasse; Westberg, Lars; Santtila, Pekka; Waldman, Irwin

2016-07-01

Naturalistic studies of gene-environment interactions (G X E) have been plagued by several limitations, including difficulty isolating specific environmental risk factors from other correlated aspects of the environment, gene-environment correlation (rGE ), and the use of a single genetic variant to represent the influence of a gene. We present results from 235 Finnish young men in two lab studies of aggression and alcohol challenge that attempt to redress these limitations of the extant G X E literature. Specifically, we use a latent variable modeling approach in an attempt to more fully account for genetic variation across the oxytocin receptor gene (OXTR) and to robustly test its main effects on aggression and its interaction with alcohol exposure. We also modeled aggression as a latent variable comprising various indices, including the average and maximum levels of aggression, the earliest trial on which aggression was expressed, and the proportion of trials on which the minimum and maximum levels of aggression were expressed. The best fitting model for the genetic variation across OXTR included six factors derived from an exploratory factor analysis, roughly corresponding to six haplotype blocks. Aggression levels were higher on trials in which participants were administered alcohol, won, or were provoked. There was a significant main effect of OXTR on aggression across studies after controlling for covariates. The interaction of OXTR and alcohol was also significant across studies, such that OXTR had stronger effects on aggression in the alcohol administration condition. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Perceptions of the Effectiveness of System Dynamics-Based Interactive Learning Environments: An Empirical Study

ERIC Educational Resources Information Center

Qudrat-Ullah, Hassan

2010-01-01

The use of simulations in general and of system dynamics simulation based interactive learning environments (SDILEs) in particular is well recognized as an effective way of improving users' decision making and learning in complex, dynamic tasks. However, the effectiveness of SDILEs in classrooms has rarely been evaluated. This article describes…

Differential sensitivity to the environment: contribution of cognitive biases and genes to psychological wellbeing.

PubMed

Fox, E; Beevers, C G

2016-12-01

Negative cognitive biases and genetic variation have been associated with risk of psychopathology in largely independent lines of research. Here, we discuss ways in which these dynamic fields of research might be fruitfully combined. We propose that gene by environment (G × E) interactions may be mediated by selective cognitive biases and that certain forms of genetic 'reactivity' or 'sensitivity' may represent heightened sensitivity to the learning environment in a 'for better and for worse' manner. To progress knowledge in this field, we recommend including assessments of cognitive processing biases; examining G × E interactions in 'both' negative and positive environments; experimentally manipulating the environment when possible; and moving beyond single-gene effects to assess polygenic sensitivity scores. We formulate a new methodological framework encapsulating cognitive and genetic factors in the development of both psychopathology and optimal wellbeing that holds long-term promise for the development of new personalized therapies.

Comparative genomics of free-living Gammaproteobacteria: pathogenesis-related genes or interaction-related genes?

PubMed

Vázquez-Rosas-Landa, Mirna; Ponce-Soto, Gabriel Yaxal; Eguiarte, Luis E; Souza, V

2017-07-31

Bacteria have numerous strategies to interact with themselves and with their environment, but genes associated with these interactions are usually cataloged as pathogenic. To understand the role that these genes have not only in pathogenesis but also in bacterial interactions, we compared the genomes of eight bacteria from human-impacted environments with those of free-living bacteria from the Cuatro Ciénegas Basin (CCB), a relatively pristine oligotrophic site. Fifty-one genomes from CCB bacteria, including Pseudomonas, Vibrio, Photobacterium and Aeromonas, were analyzed. We found that the CCB strains had several virulence-related genes, 15 of which were common to all strains and were related to flagella and chemotaxis. We also identified the presence of Type III and VI secretion systems, which leads us to propose that these systems play an important role in interactions among bacterial communities beyond pathogenesis. None of the CCB strains had pathogenicity islands, despite having genes associated with antibiotics. Integrons were rare, while CRISPR elements were common. The idea that pathogenicity-related genes in many cases form part of a wider strategy used by bacteria to interact with other organisms could help us to understand the role of pathogenicity-related elements in an ecological and evolutionary framework leading toward a more inclusive One Health concept. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The psychiatric phenotype in triple X syndrome: New hypotheses illustrated in two cases

PubMed Central

Otter, Maarten; Schrander-Stumpel, Constance T. R. M.; Didden, Robert; Curfs, Leopold M. G.

2012-01-01

Background: Triple X syndrome (47,XXX or trisomy X) is a relatively frequent cytogenetic condition with a large variety of physical and behavioural phenotypes. Method: Two adult patients with a triple X karyotype are described. Results: Their karyotype was unknown until some years ago. What these patients have in common is that they were diagnosed with a broader autism phenotype, they were sexually abused, they suffer from psychotic illness and they show challenging behaviour, suicidality and a decline in occupational capacity. Discussion: These gene-environment interactions are discussed. Gene-environment interactions may explain the variety of behavioural and psychiatric phenotypes in triple X syndrome. Ongoing atypical development in adults is hypothesized. Conclusions: Gene-environment interactions and ongoing atypical development in adults should be taken into account in research concerning the psychiatric phenotype of developmental disorders, especially those involving triple X syndrome. PMID:22582855

An interactive physics-based unmanned ground vehicle simulator leveraging open source gaming technology: progress in the development and application of the virtual autonomous navigation environment (VANE) desktop

NASA Astrophysics Data System (ADS)

Rohde, Mitchell M.; Crawford, Justin; Toschlog, Matthew; Iagnemma, Karl D.; Kewlani, Guarav; Cummins, Christopher L.; Jones, Randolph A.; Horner, David A.

2009-05-01

It is widely recognized that simulation is pivotal to vehicle development, whether manned or unmanned. There are few dedicated choices, however, for those wishing to perform realistic, end-to-end simulations of unmanned ground vehicles (UGVs). The Virtual Autonomous Navigation Environment (VANE), under development by US Army Engineer Research and Development Center (ERDC), provides such capabilities but utilizes a High Performance Computing (HPC) Computational Testbed (CTB) and is not intended for on-line, real-time performance. A product of the VANE HPC research is a real-time desktop simulation application under development by the authors that provides a portal into the HPC environment as well as interaction with wider-scope semi-automated force simulations (e.g. OneSAF). This VANE desktop application, dubbed the Autonomous Navigation Virtual Environment Laboratory (ANVEL), enables analysis and testing of autonomous vehicle dynamics and terrain/obstacle interaction in real-time with the capability to interact within the HPC constructive geo-environmental CTB for high fidelity sensor evaluations. ANVEL leverages rigorous physics-based vehicle and vehicle-terrain interaction models in conjunction with high-quality, multimedia visualization techniques to form an intuitive, accurate engineering tool. The system provides an adaptable and customizable simulation platform that allows developers a controlled, repeatable testbed for advanced simulations. ANVEL leverages several key technologies not common to traditional engineering simulators, including techniques from the commercial video-game industry. These enable ANVEL to run on inexpensive commercial, off-the-shelf (COTS) hardware. In this paper, the authors describe key aspects of ANVEL and its development, as well as several initial applications of the system.

Construction of the model for the Genetic Analysis Workshop 14 simulated data: genotype-phenotype relationships, gene interaction, linkage, association, disequilibrium, and ascertainment effects for a complex phenotype.

PubMed

Greenberg, David A; Zhang, Junying; Shmulewitz, Dvora; Strug, Lisa J; Zimmerman, Regina; Singh, Veena; Marathe, Sudhir

2005-12-30

The Genetic Analysis Workshop 14 simulated dataset was designed 1) To test the ability to find genes related to a complex disease (such as alcoholism). Such a disease may be given a variety of definitions by different investigators, have associated endophenotypes that are common in the general population, and is likely to be not one disease but a heterogeneous collection of clinically similar, but genetically distinct, entities. 2) To observe the effect on genetic analysis and gene discovery of a complex set of gene x gene interactions. 3) To allow comparison of microsatellite vs. large-scale single-nucleotide polymorphism (SNP) data. 4) To allow testing of association to identify the disease gene and the effect of moderate marker x marker linkage disequilibrium. 5) To observe the effect of different ascertainment/disease definition schemes on the analysis. Data was distributed in two forms. Data distributed to participants contained about 1,000 SNPs and 400 microsatellite markers. Internet-obtainable data consisted of a finer 10,000 SNP map, which also contained data on controls. While disease characteristics and parameters were constant, four "studies" used varying ascertainment schemes based on differing beliefs about disease characteristics. One of the studies contained multiplex two- and three-generation pedigrees with at least four affected members. The simulated disease was a psychiatric condition with many associated behaviors (endophenotypes), almost all of which were genetic in origin. The underlying disease model contained four major genes and two modifier genes. The four major genes interacted with each other to produce three different phenotypes, which were themselves heterogeneous. The population parameters were calibrated so that the major genes could be discovered by linkage analysis in most datasets. The association evidence was more difficult to calibrate but was designed to find statistically significant association in 50% of datasets. We also simulated some marker x marker linkage disequilibrium around some of the genes and also in areas without disease genes. We tried two different methods to simulate the linkage disequilibrium.

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

PubMed

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.

The developmental origins of externalizing behavioral problems: parental disengagement and the role of gene-environment interplay.

PubMed

Boutwell, Brian B; Beaver, Kevin M; Barnes, James C; Vaske, Jamie

2012-05-30

A line of research has revealed that the influence of genes on behavioral development is closely tied to environmental experiences. Known as gene-environment interaction, research in this area is beginning to reveal that variation in parenting behaviors may moderate genetic influences on antisocial behaviors in children. Despite growing interest in gene-environment interaction research, little evidence exists concerning the role of maternal disengagement in the conditioning of genetic influences on childhood behavioral problems. The current study is intended to address this gap in the literature by analyzing a sample of twin pairs drawn from the Early Childhood Longitudinal Study, Birth Cohort (ECLS-B). Analysis of the ECLS-B provided evidence that maternal disengagement moderates genetic influences on the development of externalizing problems. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Interactive Simulated Patient: Experiences with Collaborative E-Learning in Medicine

ERIC Educational Resources Information Center

Bergin, Rolf; Youngblood, Patricia; Ayers, Mary K.; Boberg, Jonas; Bolander, Klara; Courteille, Olivier; Dev, Parvati; Hindbeck, Hans; Edward, Leonard E., II; Stringer, Jennifer R.; Thalme, Anders; Fors, Uno G. H.

2003-01-01

Interactive Simulated Patient (ISP) is a computer-based simulation tool designed to provide medical students with the opportunity to practice their clinical problem solving skills. The ISP system allows students to perform most clinical decision-making procedures in a simulated environment, including history taking in natural language, many…

Environments for online maritime simulators with cloud computing capabilities

NASA Astrophysics Data System (ADS)

Raicu, Gabriel; Raicu, Alexandra

2016-12-01

This paper presents the cloud computing environments, network principles and methods for graphical development in realistic naval simulation, naval robotics and virtual interactions. The aim of this approach is to achieve a good simulation quality in large networked environments using open source solutions designed for educational purposes. Realistic rendering of maritime environments requires near real-time frameworks with enhanced computing capabilities during distance interactions. E-Navigation concepts coupled with the last achievements in virtual and augmented reality will enhance the overall experience leading to new developments and innovations. We have to deal with a multiprocessing situation using advanced technologies and distributed applications using remote ship scenario and automation of ship operations.

Social Environmental Variation, Plasticity Genes, and Aggression: Evidence for the Differential Susceptibility Hypothesis

PubMed Central

Simons, Ronald L.; Lei, Man Kit; Beach, Steven R.H.; Brody, Gene H.; Philibert, Robert A.; Gibbons, Frederick X.

2011-01-01

Although G×E studies are typically based on the assumption that some individuals possess genetic variants that enhance their vulnerability to environmental adversity, the differential susceptibility perspective posits that these individuals are simply more susceptible to environmental influence than others. An important implication of this model is that those persons most vulnerable to adverse social environments are the same ones who reap the most benefit from environmental support. The present study tested several implications of this proposition. Using longitudinal data from a sample of several hundred African Americans, we found that relatively common variants of the dopamine receptor gene and the serotonin transporter gene interact with social environmental conditions to predict aggression in a manner consonant with differential susceptibility. When the social environment was adverse, individuals with these genetic variants manifested more aggression than other genotypes, whereas when the environment was supportive they demonstrated less aggression than other genotypes. Further, we found that these genetic variants interact with environmental conditions to foster various cognitive schemas and emotions in a manner consistent with differential susceptibility and that a latent construct formed by these schemas and emotions mediated the effect of gene by environment interaction on aggression. PMID:22199399

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wagner, Maggie R.; Lundberg, Derek S.; del Rio, Tijana G.

Bacteria living on and in leaves and roots influence many aspects of plant health, so the extent of a plant's genetic control over its microbiota is of great interest to crop breeders and evolutionary biologists. Laboratory-based studies, because they poorly simulate true environmental heterogeneity, may misestimate or totally miss the influence of certain host genes on the microbiome. Here we report a large-scale field experiment to disentangle the effects of genotype, environment, age and year of harvest on bacterial communities associated with leaves and roots of Boechera stricta (Brassicaceae), a perennial wild mustard. Host genetic control of the microbiome ismore » evident in leaves but not roots, and varies substantially among sites. Microbiome composition also shifts as plants age. Furthermore, a large proportion of leaf bacterial groups are shared with roots, suggesting inoculation from soil. Our results demonstrate how genotype-by-environment interactions contribute to the complexity of microbiome assembly in natural environments.« less

Gene-gene, gene-environment, gene-nutrient interactions and single nucleotide polymorphisms of inflammatory cytokines.

PubMed

Nadeem, Amina; Mumtaz, Sadaf; Naveed, Abdul Khaliq; Aslam, Muhammad; Siddiqui, Arif; Lodhi, Ghulam Mustafa; Ahmad, Tausif

2015-05-15

Inflammation plays a significant role in the etiology of type 2 diabetes mellitus (T2DM). The rise in the pro-inflammatory cytokines is the essential step in glucotoxicity and lipotoxicity induced mitochondrial injury, oxidative stress and beta cell apoptosis in T2DM. Among the recognized markers are interleukin (IL)-6, IL-1, IL-10, IL-18, tissue necrosis factor-alpha (TNF-α), C-reactive protein, resistin, adiponectin, tissue plasminogen activator, fibrinogen and heptoglobins. Diabetes mellitus has firm genetic and very strong environmental influence; exhibiting a polygenic mode of inheritance. Many single nucleotide polymorphisms (SNPs) in various genes including those of pro and anti-inflammatory cytokines have been reported as a risk for T2DM. Not all the SNPs have been confirmed by unifying results in different studies and wide variations have been reported in various ethnic groups. The inter-ethnic variations can be explained by the fact that gene expression may be regulated by gene-gene, gene-environment and gene-nutrient interactions. This review highlights the impact of these interactions on determining the role of single nucleotide polymorphism of IL-6, TNF-α, resistin and adiponectin in pathogenesis of T2DM.

Gene-Environment Correlation and Interaction in Peer Effects on Adolescent Alcohol and Tobacco Use

PubMed Central

Harden, K. Paige; Hill, Jennifer E.; Turkheimer, Eric; Emery, Robert E.

2010-01-01

Peer relationships are commonly thought to be critical for adolescent socialization, including the development of negative health behaviors such as alcohol and tobacco use. The interplay between genetic liability and peer influences on the development of adolescent alcohol and tobacco use was examined using a nationally-representative sample of adolescent sibling pairs and their best friends. Genetic factors, some of them related to an adolescent's own substance use and some of them independent of use, were associated with increased exposure to best friends with heavy substance use—a gene-environment correlation. Moreover, adolescents who were genetically liable to substance use were more vulnerable to the adverse influences of their best friends—a gene-environment interaction. PMID:18368474

Gravitational and magnetic field variations synergize to cause subtle variations in the global transcriptional state of Arabidopsis in vitro callus cultures

PubMed Central

2012-01-01

Background Biological systems respond to changes in both the Earth's magnetic and gravitational fields, but as experiments in space are expensive and infrequent, Earth-based simulation techniques are required. A high gradient magnetic field can be used to levitate biological material, thereby simulating microgravity and can also create environments with a reduced or an enhanced level of gravity (g), although special attention should be paid to the possible effects of the magnetic field (B) itself. Results Using diamagnetic levitation, we exposed Arabidopsis thaliana in vitro callus cultures to five environments with different levels of effective gravity and magnetic field strengths. The environments included levitation, i.e. simulated μg* (close to 0 g* at B = 10.1 T), intermediate g* (0.1 g* at B = 14.7 T) and enhanced gravity levels (1.9 g* at B = 14.7 T and 2 g* at B = 10.1 T) plus an internal 1 g* control (B = 16.5 T). The asterisk denotes the presence of the background magnetic field, as opposed to the effective gravity environments in the absence of an applied magnetic field, created using a Random Position Machine (simulated μg) and a Large Diameter Centrifuge (2 g). Microarray analysis indicates that changes in the overall gene expression of cultured cells exposed to these unusual environments barely reach significance using an FDR algorithm. However, it was found that gravitational and magnetic fields produce synergistic variations in the steady state of the transcriptional profile of plants. Transcriptomic results confirm that high gradient magnetic fields (i.e. to create μg* and 2 g* conditions) have a significant effect, mainly on structural, abiotic stress genes and secondary metabolism genes, but these subtle gravitational effects are only observable using clustering methodologies. Conclusions A detailed microarray dataset analysis, based on clustering of similarly expressed genes (GEDI software), can detect underlying global-scale responses, which cannot be detected by means of individual gene expression techniques using raw or corrected p values (FDR). A subtle, but consistent, genome-scale response to hypogravity environments was found, which was opposite to the response in a hypergravity environment. PMID:22435851

Genome-wide gene–environment interaction analysis for asbestos exposure in lung cancer susceptibility

PubMed Central

Wei, Qingyi Wei

2012-01-01

Asbestos exposure is a known risk factor for lung cancer. Although recent genome-wide association studies (GWASs) have identified some novel loci for lung cancer risk, few addressed genome-wide gene–environment interactions. To determine gene–asbestos interactions in lung cancer risk, we conducted genome-wide gene–environment interaction analyses at levels of single nucleotide polymorphisms (SNPs), genes and pathways, using our published Texas lung cancer GWAS dataset. This dataset included 317 498 SNPs from 1154 lung cancer cases and 1137 cancer-free controls. The initial SNP-level P-values for interactions between genetic variants and self-reported asbestos exposure were estimated by unconditional logistic regression models with adjustment for age, sex, smoking status and pack-years. The P-value for the most significant SNP rs13383928 was 2.17×10–6, which did not reach the genome-wide statistical significance. Using a versatile gene-based test approach, we found that the top significant gene was C7orf54, located on 7q32.1 (P = 8.90×10–5). Interestingly, most of the other significant genes were located on 11q13. When we used an improved gene-set-enrichment analysis approach, we found that the Fas signaling pathway and the antigen processing and presentation pathway were most significant (nominal P < 0.001; false discovery rate < 0.05) among 250 pathways containing 17 572 genes. We believe that our analysis is a pilot study that first describes the gene–asbestos interaction in lung cancer risk at levels of SNPs, genes and pathways. Our findings suggest that immune function regulation-related pathways may be mechanistically involved in asbestos-associated lung cancer risk. Abbreviations:CIconfidence intervalEenvironmentFDRfalse discovery rateGgeneGSEAgene-set-enrichment analysisGWASgenome-wide association studiesi-GSEAimproved gene-set-enrichment analysis approachORodds ratioSNPsingle nucleotide polymorphism PMID:22637743

A Java-Enabled Interactive Graphical Gas Turbine Propulsion System Simulator

NASA Technical Reports Server (NTRS)

Reed, John A.; Afjeh, Abdollah A.

1997-01-01

This paper describes a gas turbine simulation system which utilizes the newly developed Java language environment software system. The system provides an interactive graphical environment which allows the quick and efficient construction and analysis of arbitrary gas turbine propulsion systems. The simulation system couples a graphical user interface, developed using the Java Abstract Window Toolkit, and a transient, space- averaged, aero-thermodynamic gas turbine analysis method, both entirely coded in the Java language. The combined package provides analytical, graphical and data management tools which allow the user to construct and control engine simulations by manipulating graphical objects on the computer display screen. Distributed simulations, including parallel processing and distributed database access across the Internet and World-Wide Web (WWW), are made possible through services provided by the Java environment.

Mapping microbial ecosystems and spoilage-gene flow in breweries highlights patterns of contamination and resistance

PubMed Central

Bokulich, Nicholas A; Bergsveinson, Jordyn; Ziola, Barry; Mills, David A

2015-01-01

Distinct microbial ecosystems have evolved to meet the challenges of indoor environments, shaping the microbial communities that interact most with modern human activities. Microbial transmission in food-processing facilities has an enormous impact on the qualities and healthfulness of foods, beneficially or detrimentally interacting with food products. To explore modes of microbial transmission and spoilage-gene frequency in a commercial food-production scenario, we profiled hop-resistance gene frequencies and bacterial and fungal communities in a brewery. We employed a Bayesian approach for predicting routes of contamination, revealing critical control points for microbial management. Physically mapping microbial populations over time illustrates patterns of dispersal and identifies potential contaminant reservoirs within this environment. Habitual exposure to beer is associated with increased abundance of spoilage genes, predicting greater contamination risk. Elucidating the genetic landscapes of indoor environments poses important practical implications for food-production systems and these concepts are translatable to other built environments. DOI: http://dx.doi.org/10.7554/eLife.04634.001 PMID:25756611

Gene × environment interaction on intergroup bias: the role of 5-HTTLPR and perceived outgroup threat.

PubMed

Cheon, Bobby K; Livingston, Robert W; Hong, Ying-Yi; Chiao, Joan Y

2014-09-01

Perceived threat from outgroups is a consistent social-environmental antecedent of intergroup bias (i.e. prejudice, ingroup favoritism). The serotonin transporter gene polymorphism (5-HTTLPR) has been associated with individual variations in sensitivity to context, particularly stressful and threatening situations. Here, we examined how 5-HTTLPR and environmental factors signaling potential outgroup threat dynamically interact to shape intergroup bias. Across two studies, we provide novel evidence for a gene-environment interaction on the acquisition of intergroup bias and prejudice. Greater exposure to signals of outgroup threat, such as negative prior contact with outgroups and perceived danger from the social environment, were more predictive of intergroup bias among participants possessing at least one short allele (vs two long alleles) of 5-HTTLPR. Furthermore, this gene x environment interaction was observed for biases directed at diverse ethnic and arbitrarily-defined outgroups across measures reflecting intergroup biases in evaluation and discriminatory behavior. These findings reveal a candidate genetic mechanism for the acquisition of intergroup bias, and suggest that intergroup bias is dually inherited and transmitted through the interplay of social (i.e. contextual cues of outgroup threat) and biological mechanisms (i.e. genetic sensitivity toward threatening contexts) that regulate perceived intergroup threats. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

[From stone-craved genes to Michelangelo: significance and different aspects of gene-environment interaction].

PubMed

Lazary, Judit

2017-12-01

Although genetic studies have improved a lot in recent years, without clinical relevance sometimes their significance is devalued. Reviewing the major milestones of psychogenomics it can be seen that break-through success is just a question of time. Investigations of direct effect of genetic variants on phenotypes have not yielded positive findings. However, an important step was taken by adapting the gene-environment interaction model. In this model genetic vulnerability stepped into the place of "stone craved" pathology. Further progress happened when studies of environmental factors were combined with genetic function (epigenetics). This model provided the possibility for investigation of therapeutic interventions as environmental factors and it was proven that effective treatments exert a modifying effect on gene expression. Moreover, recent developments focus on therapeutic manipulation of gene function (e.g. chemogenetics). Instead of "stone craved" genes up-to-date dynamically interacting gene function became the basis of psychogenomics in which correction of the expression is a potential therapeutic tool. Keeping in mind these trends and developments, there is no doubt that genetics will be a fundamental part of daily clinical routine in the future.

Gene Polymorphism Association with Type 2 Diabetes and Related Gene-Gene and Gene-Environment Interactions in a Uyghur Population

PubMed Central

Xiao, Shan; Zeng, Xiaoyun; Fan, Yong; Su, Yinxia; Ma, Qi; Zhu, Jun; Yao, Hua

2016-01-01

Background We investigated the association between 8 single-nucleotide polymorphisms (SNPs) at 3 genetic loci (CDKAL1, CDKN2A/2B and FTO) with type 2 diabetes (T2D) in a Uyghur population. Material/Methods A case-control study of 879 Uyghur patients with T2D and 895 non-diabetic Uyghur controls was conducted at the Hospital of Xinjiang Medical University between 2010 and 2013. Eight SNPs in CDKAL1, CDKN2A/2B and FTO were analyzed using Sequenom MassARRAY®SNP genotyping. Factors associated with T2D were assessed by logistic regression analyses. Gene-gene and gene-environment interactions were analyzed by generalized multifactor dimensionality reduction. Results Genotype distributions of rs10811661 (CDKN2A/2B), rs7195539, rs8050136, and rs9939609 (FTO) and allele frequencies of rs8050136 and rs9939609 differed significantly between diabetes and control groups (all P<0.05). While rs10811661, rs8050136, and rs9939609 were eliminated after adjusting for covariates (P>0.05), rs7195539 distribution differed significantly in co-dominant and dominant models (P<0.05). In gene-gene interaction analysis, after adjusting for covariates the two-locus rs10811661-rs7195539 interaction model had a cross-validation consistency of 10/10 and the highest balanced accuracy of 0.5483 (P=0.014). In gene-environment interaction analysis, the 3-locus interaction model TG-HDL-family history of diabetes had a cross-validation consistency of 10/10 and the highest balanced accuracy of 0.7072 (P<0.001). The 4-locus interaction model, rs7195539-TG-HDL-family history of diabetes had a cross-validation consistency of 8/10 (P<0.001). Conclusions Polymorphisms in CDKN2A/2B and FTO, but not CDKAL1, may be associated with T2D, and alleles rs8050136 and rs9939609 are likely risk alleles for T2D in this population. There were potential interactions among CDKN2A/2B (rs10811661) – FTO (rs7195539) or FTO (rs7195539)-TG-HDL-family history of diabetes in the pathogenesis of T2D in a Uyghur population. PMID:26873362

A distinct and replicable variant of the squamous cell carcinoma gene inositol polyphosphate-5-phosphatase modifies the susceptibility of arsenic-associated skin lesions in Bangladesh.

PubMed

Seow, Wei Jie; Pan, Wen-Chi; Kile, Molly L; Tong, Lin; Baccarelli, Andrea A; Quamruzzaman, Quazi; Rahman, Mahmuder; Mostofa, Golam; Rakibuz-Zaman, Muhammad; Kibriya, Muhammad; Ahsan, Habibul; Lin, Xihong; Christiani, David C

2015-07-01

Single-nucleotide polymorphisms (SNPs) in inflammation, one-carbon metabolism, and skin cancer genes might influence susceptibility to arsenic-induced skin lesions. A case-control study was conducted in Pabna, Bangladesh (2001-2003), and the drinking-water arsenic concentration was measured for each participant. A panel of 25 candidate SNPs was analyzed in 540 cases and 400 controls. Logistic regression was used to estimate the association between each SNP and the potential for gene-environment interactions in the skin lesion risk, with adjustments for relevant covariates. Replication testing was conducted in an independent Bangladesh population with 488 cases and 2,794 controls. In the discovery population, genetic variants in the one-carbon metabolism genes phosphatidylethanolamine N-methyltransferase (rs2278952, P for interaction  = .004; rs897453, P for interaction = .05) and dihydrofolate reductase (rs1650697, P for interaction = .02), the inflammation gene interleukin 10 (rs3024496, P for interaction =.04), and the skin cancer genes inositol polyphosphate-5-phosphatase (INPP5A; rs1133400, P for interaction = .03) and xeroderma pigmentosum complementation group C (rs2228000, P for interaction = .01) significantly modified the association between arsenic and skin lesions after adjustments for multiple comparisons. The significant gene-environment interaction between a SNP in the INPP5A gene (rs1133400) and water arsenic with respect to the skin lesion risk was successfully replicated in an independent population (P for interaction = .03). Minor allele carriers of the skin cancer gene INPP5A modified the odds of arsenic-induced skin lesions in both main and replicative populations. Genetic variation in INPP5A appears to have a role in susceptibility to arsenic toxicity. © 2015 American Cancer Society.

Gene × environment interaction studies have not properly controlled for potential confounders: the problem and the (simple) solution.

PubMed

Keller, Matthew C

2014-01-01

Candidate gene × environment (G × E) interaction research tests the hypothesis that the effects of some environmental variable (e.g., childhood maltreatment) on some outcome measure (e.g., depression) depend on a particular genetic polymorphism. Because this research is inherently nonexperimental, investigators have been rightly concerned that detected interactions could be driven by confounders (e.g., ethnicity, gender, age, socioeconomic status) rather than by the specified genetic or environmental variables per se. In an attempt to eliminate such alternative explanations for detected G × E interactions, investigators routinely enter the potential confounders as covariates in general linear models. However, this practice does not control for the effects these variables might have on the G × E interaction. Rather, to properly control for confounders, researchers need to enter the covariate × environment and the covariate × gene interaction terms in the same model that tests the G × E term. In this manuscript, I demonstrate this point analytically and show that the practice of improperly controlling for covariates is the norm in the G × E interaction literature to date. Thus, many alternative explanations for G × E findings that investigators had thought were eliminated have not been. © 2013 Society of Biological Psychiatry Published by Society of Biological Psychiatry All rights reserved.

An Interactive Teaching System for Bond Graph Modeling and Simulation in Bioengineering

ERIC Educational Resources Information Center

Roman, Monica; Popescu, Dorin; Selisteanu, Dan

2013-01-01

The objective of the present work was to implement a teaching system useful in modeling and simulation of biotechnological processes. The interactive system is based on applications developed using 20-sim modeling and simulation software environment. A procedure for the simulation of bioprocesses modeled by bond graphs is proposed and simulators…

Mental and physical distress is modulated by a polymorphism in the 5-HT transporter gene interacting with social stressors and chronic disease burden.

PubMed

Grabe, H J; Lange, M; Wolff, B; Völzke, H; Lucht, M; Freyberger, H J; John, U; Cascorbi, I

2005-02-01

Previous studies have yielded conflicting results as to the putative role of the functional polymorphism of the promoter region of the serotonin transporter gene (SLC6A4) in the etiology of anxiety-related traits and depressive disorders. Recently, a significant gene-environment interaction was found between life stressors, the short allele of the SLC6A4 polymorphism and depression. The aim of the present study was to investigate if such a gene-environment interaction could be replicated within a different population with a different risk structure. A total of 1005 subjects from a general population sample (Study of Health in Pomerania) were genotyped. Mental and physical distress were assessed on 38 items of the modified complaint scale (BL-38). The interaction between the SLC6A4 genotype, social stressors and chronic diseases with regard to the BL-38 score was evaluated by ANOVA. There was no independent association of genotype with mental and physical distress. However, significant interactions between genotype, unemployment and chronic diseases (F = 6.6; df = 3, 671; P < 0.001) were found in females but not in males. The genotype explained 2% of the total variance of the BL-38 score and 9.1% of the explained variance. The results partly confirm previous findings of a significant gene-environment interaction of the short allele, indicating a higher mental vulnerability to social stressors and chronic diseases. The relevance of this finding is sustained by the fact that the sample characteristics and the risk structure were highly different from previous studies.

Design Patterns for Learning and Assessment: Facilitating the Introduction of a Complex Simulation-Based Learning Environment into a Community of Instructors

ERIC Educational Resources Information Center

Frezzo, Dennis C.; Behrens, John T.; Mislevy, Robert J.

2010-01-01

Simulation environments make it possible for science and engineering students to learn to interact with complex systems. Putting these capabilities to effective use for learning, and assessing learning, requires more than a simulation environment alone. It requires a conceptual framework for the knowledge, skills, and ways of thinking that are…

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

PubMed

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.

Effect of summer daylight exposure and genetic background on growth in growth hormone-deficient children.

PubMed

De Leonibus, C; Chatelain, P; Knight, C; Clayton, P; Stevens, A

2016-11-01

The response to growth hormone in humans is dependent on phenotypic, genetic and environmental factors. The present study in children with growth hormone deficiency (GHD) collected worldwide characterised gene-environment interactions on growth response to recombinant human growth hormone (r-hGH). Growth responses in children are linked to latitude, and we found that a correlate of latitude, summer daylight exposure (SDE), was a key environmental factor related to growth response to r-hGH. In turn growth response was determined by an interaction between both SDE and genes known to affect growth response to r-hGH. In addition, analysis of associated networks of gene expression implicated a role for circadian clock pathways and specifically the developmental transcription factor NANOG. This work provides the first observation of gene-environment interactions in children treated with r-hGH.

OncoSimulR: genetic simulation with arbitrary epistasis and mutator genes in asexual populations.

PubMed

Diaz-Uriarte, Ramon

2017-06-15

OncoSimulR implements forward-time genetic simulations of biallelic loci in asexual populations with special focus on cancer progression. Fitness can be defined as an arbitrary function of genetic interactions between multiple genes or modules of genes, including epistasis, restrictions in the order of accumulation of mutations, and order effects. Mutation rates can differ among genes, and can be affected by (anti)mutator genes. Also available are sampling from simulations (including single-cell sampling), plotting the genealogical relationships of clones and generating and plotting fitness landscapes. Implemented in R and C ++, freely available from BioConductor for Linux, Mac and Windows under the GNU GPL license. Version 2.5.9 or higher available from: http://www.bioconductor.org/packages/devel/bioc/html/OncoSimulR.html . GitHub repository at: https://github.com/rdiaz02/OncoSimul. ramon.diaz@iib.uam.es. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

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

PubMed

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

2017-12-01

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 phenotypes and reduces the risk of false-positive findings. We apply this method focusing on the role of perceived parental support, psychological control, and harsh punishment in depressive symptoms in adolescence. Analyses were conducted on 982 adolescents of Caucasian origin (M age (SD) = 13.78 (.94) years) genotyped for 4,947 SNPs in 263 genes, selected based on a literature survey. The Leuven Adolescent Perceived Parenting Scale (LAPPS) and the Parental Behavior Scale (PBS) were used to assess perceived parental psychological control, harsh punishment, and support. The Center for Epidemiologic Studies Depression Scale (CES-D) was the outcome. We used gene-based testing taking into account linkage disequilibrium to identify genes containing SNPs exhibiting an interaction with environmental factors yielding a p-value per single gene. Significant results at the corrected p-value of p < 1.90 × 10 -4 were examined in an independent replication sample of Dutch adolescents (N = 1354). Two genes showed evidence for interaction with perceived support: GABRR1 (p = 4.62 × 10 -5 ) and GABRR2 (p = 9.05 × 10 -6 ). No genes interacted significantly with psychological control or harsh punishment. Gene-based analysis was unable to confirm the interaction of GABRR1 or GABRR2 with support in the replication sample. However, for GABRR2, but not GABRR1, the correlation of the estimates between the two datasets was significant (r (46) = .32; p = .027) and a gene-based analysis of the combined datasets supported GABRR2 × support interaction (p = 1.63 × 10 -4 ). We present a gene-based method for gene-environment interactions in a polygenic context and show that genes interact differently with particular aspects of parenting. This accentuates the importance of polygenic approaches and the need to accurately assess environmental exposure in G × E. © 2017 Association for Child and Adolescent Mental Health.

Surgical model-view-controller simulation software framework for local and collaborative applications

PubMed Central

Sankaranarayanan, Ganesh; Halic, Tansel; Arikatla, Venkata Sreekanth; Lu, Zhonghua; De, Suvranu

2010-01-01

Purpose Surgical simulations require haptic interactions and collaboration in a shared virtual environment. A software framework for decoupled surgical simulation based on a multi-controller and multi-viewer model-view-controller (MVC) pattern was developed and tested. Methods A software framework for multimodal virtual environments was designed, supporting both visual interactions and haptic feedback while providing developers with an integration tool for heterogeneous architectures maintaining high performance, simplicity of implementation, and straightforward extension. The framework uses decoupled simulation with updates of over 1,000 Hz for haptics and accommodates networked simulation with delays of over 1,000 ms without performance penalty. Results The simulation software framework was implemented and was used to support the design of virtual reality-based surgery simulation systems. The framework supports the high level of complexity of such applications and the fast response required for interaction with haptics. The efficacy of the framework was tested by implementation of a minimally invasive surgery simulator. Conclusion A decoupled simulation approach can be implemented as a framework to handle simultaneous processes of the system at the various frame rates each process requires. The framework was successfully used to develop collaborative virtual environments (VEs) involving geographically distributed users connected through a network, with the results comparable to VEs for local users. PMID:20714933

Surgical model-view-controller simulation software framework for local and collaborative applications.

PubMed

Maciel, Anderson; Sankaranarayanan, Ganesh; Halic, Tansel; Arikatla, Venkata Sreekanth; Lu, Zhonghua; De, Suvranu

2011-07-01

Surgical simulations require haptic interactions and collaboration in a shared virtual environment. A software framework for decoupled surgical simulation based on a multi-controller and multi-viewer model-view-controller (MVC) pattern was developed and tested. A software framework for multimodal virtual environments was designed, supporting both visual interactions and haptic feedback while providing developers with an integration tool for heterogeneous architectures maintaining high performance, simplicity of implementation, and straightforward extension. The framework uses decoupled simulation with updates of over 1,000 Hz for haptics and accommodates networked simulation with delays of over 1,000 ms without performance penalty. The simulation software framework was implemented and was used to support the design of virtual reality-based surgery simulation systems. The framework supports the high level of complexity of such applications and the fast response required for interaction with haptics. The efficacy of the framework was tested by implementation of a minimally invasive surgery simulator. A decoupled simulation approach can be implemented as a framework to handle simultaneous processes of the system at the various frame rates each process requires. The framework was successfully used to develop collaborative virtual environments (VEs) involving geographically distributed users connected through a network, with the results comparable to VEs for local users.

The challenge of causal inference in gene-environment interaction research: leveraging research designs from the social sciences.

PubMed

Fletcher, Jason M; Conley, Dalton

2013-10-01

The integration of genetics and the social sciences will lead to a more complex understanding of the articulation between social and biological processes, although the empirical difficulties inherent in this integration are large. One key challenge is the implications of moving "outside the lab" and away from the experimental tools available for research with model organisms. Social science research methods used to examine human behavior in nonexperimental, real-world settings to date have not been fully taken advantage of during this disciplinary integration, especially in the form of gene-environment interaction research. This article outlines and provides examples of several prominent research designs that should be used in gene-environment research and highlights a key benefit to geneticists of working with social scientists.

Genes-environment interactions in obesity- and diabetes-associated pancreatic cancer: a GWAS data analysis.

PubMed

Tang, Hongwei; Wei, Peng; Duell, Eric J; Risch, Harvey A; Olson, Sara H; Bueno-de-Mesquita, H Bas; Gallinger, Steven; Holly, Elizabeth A; Petersen, Gloria M; Bracci, Paige M; McWilliams, Robert R; Jenab, Mazda; Riboli, Elio; Tjønneland, Anne; Boutron-Ruault, Marie Christine; Kaaks, Rudolf; Trichopoulos, Dimitrios; Panico, Salvatore; Sund, Malin; Peeters, Petra H M; Khaw, Kay-Tee; Amos, Christopher I; Li, Donghui

2014-01-01

Obesity and diabetes are potentially alterable risk factors for pancreatic cancer. Genetic factors that modify the associations of obesity and diabetes with pancreatic cancer have previously not been examined at the genome-wide level. Using genome-wide association studies (GWAS) genotype and risk factor data from the Pancreatic Cancer Case Control Consortium, we conducted a discovery study of 2,028 cases and 2,109 controls to examine gene-obesity and gene-diabetes interactions in relation to pancreatic cancer risk by using the likelihood-ratio test nested in logistic regression models and Ingenuity Pathway Analysis (IPA). After adjusting for multiple comparisons, a significant interaction of the chemokine signaling pathway with obesity (P = 3.29 × 10(-6)) and a near significant interaction of calcium signaling pathway with diabetes (P = 1.57 × 10(-4)) in modifying the risk of pancreatic cancer were observed. These findings were supported by results from IPA analysis of the top genes with nominal interactions. The major contributing genes to the two top pathways include GNGT2, RELA, TIAM1, and GNAS. None of the individual genes or single-nucleotide polymorphism (SNP) except one SNP remained significant after adjusting for multiple testing. Notably, SNP rs10818684 of the PTGS1 gene showed an interaction with diabetes (P = 7.91 × 10(-7)) at a false discovery rate of 6%. Genetic variations in inflammatory response and insulin resistance may affect the risk of obesity- and diabetes-related pancreatic cancer. These observations should be replicated in additional large datasets. A gene-environment interaction analysis may provide new insights into the genetic susceptibility and molecular mechanisms of obesity- and diabetes-related pancreatic cancer.

Differential sensitivity to the environment: contribution of cognitive biases and genes to psychological wellbeing

PubMed Central

Fox, E; Beevers, C G

2016-01-01

Negative cognitive biases and genetic variation have been associated with risk of psychopathology in largely independent lines of research. Here, we discuss ways in which these dynamic fields of research might be fruitfully combined. We propose that gene by environment (G × E) interactions may be mediated by selective cognitive biases and that certain forms of genetic ‘reactivity' or ‘sensitivity' may represent heightened sensitivity to the learning environment in a ‘for better and for worse' manner. To progress knowledge in this field, we recommend including assessments of cognitive processing biases; examining G × E interactions in ‘both' negative and positive environments; experimentally manipulating the environment when possible; and moving beyond single-gene effects to assess polygenic sensitivity scores. We formulate a new methodological framework encapsulating cognitive and genetic factors in the development of both psychopathology and optimal wellbeing that holds long-term promise for the development of new personalized therapies. PMID:27431291

ORCHIDS: an observational randomized controlled trial on childhood differential susceptibility.

PubMed

Chhangur, Rabia R; Weeland, Joyce; Overbeek, Geertjan; Matthys, Walterchj; Orobio de Castro, Bram

2012-10-29

A central tenet in developmental psychopathology is that childhood rearing experiences have a major impact on children's development. Recently, candidate genes have been identified that may cause children to be differentially susceptible to these experiences (i.e., susceptibility genes). However, our understanding of the differential impact of parenting is limited at best. Specifically, more experimental research is needed. The ORCHIDS study will investigate gene-(gene-)environment interactions to obtain more insight into a) moderating effects of polymorphisms on the link between parenting and child behavior, and b) behavioral mechanisms that underlie these gene-(gene-)environment interactions in an experimental design. The ORCHIDS study is a randomized controlled trial, in which the environment will be manipulated with an intervention (i.e., Incredible Years parent training). In a screening, families with children aged 4-8 who show mild to (sub)clinical behavior problems will be targeted through community records via two Dutch regional healthcare organizations. Assessments in both the intervention and control condition will be conducted at baseline (i.e., pretest), after 6 months (i.e., posttest), and after 10 months (i.e., follow-up). This study protocol describes the design of a randomized controlled trial that investigates gene-(gene-)environment interactions in the development of child behavior. Two hypotheses will be tested. First, we expect that children in the intervention condition who carry one or more susceptibility genes will show significantly lower levels of problem behavior and higher levels of prosocial behavior after their parent(s) received the Incredible Years training, compared to children without these genes, or children in the control group. Second, we expect that children carrying one or more susceptibility genes will show a heightened sensitivity to changes in parenting behaviors, and will manifest higher emotional synchronization in dyadic interchanges with their parents. This may lead to either more prosocial behavior or antisocial behavior depending on their parents' behavior. Dutch Trial Register (NTR3594).

The BDNF Val66Met Polymorphism Interacts with Maternal Parenting Influencing Adolescent Depressive Symptoms: Evidence of Differential Susceptibility Model.

PubMed

Zhang, Leilei; Li, Zhi; Chen, Jie; Li, Xinying; Zhang, Jianxin; Belsky, Jay

2016-03-01

Although depressive symptoms are common during adolescence, little research has examined gene-environment interaction on youth depression. This study chose the brain-derived neurotrophic factor (BDNF) gene, tested the interaction between a functional polymorphism resulting amino acid substitution of valine (Val) to methionine (Met) in the proBDNF protein at codon 66 (Val66Met), and maternal parenting on youth depressive symptoms in a sample of 780 community adolescents of Chinese Han ethnicity (aged 11-17, M = 13.6, 51.3 % females). Participants reported their depressive symptoms and perceived maternal parenting. Results indicated the BDNF Val66Met polymorphism significantly moderated the influence of maternal warmth-reasoning, but not harshness-hostility, on youth depressive symptoms. Confirmatory model evaluation indicated that the interaction effect involving warmth-reasoning conformed to the differential-susceptibility rather than diathesis-stress model of person-X-environment interaction. Thus, Val carriers experienced less depressive symptoms than Met homozygotes when mothering was more positive but more symptoms when mothering was less positive. The findings provided evidence in support of the differential susceptibility hypothesis of youth depressive symptoms and shed light on the importance of examining the gene-environment interaction from a developmental perspective.

Suboptimal evolutionary novel environments promote singular altered gravity responses of transcriptome during Drosophila metamorphosis

PubMed Central

2013-01-01

Background Previous experiments have shown that the reduced gravity aboard the International Space Station (ISS) causes important alterations in Drosophila gene expression. These changes were shown to be intimately linked to environmental space-flight related constraints. Results Here, we use an array of different techniques for ground-based simulation of microgravity effects to assess the effect of suboptimal environmental conditions on the gene expression of Drosophila in reduced gravity. A global and integrative analysis, using “gene expression dynamics inspector” (GEDI) self-organizing maps, reveals different degrees in the responses of the transcriptome when using different environmental conditions or microgravity/hypergravity simulation devices. Although the genes that are affected are different in each simulation technique, we find that the same gene ontology groups, including at least one large multigene family related with behavior, stress response or organogenesis, are over represented in each case. Conclusions These results suggest that the transcriptome as a whole can be finely tuned to gravity force. In optimum environmental conditions, the alteration of gravity has only mild effects on gene expression but when environmental conditions are far from optimal, the gene expression must be tuned greatly and effects become more robust, probably linked to the lack of experience of organisms exposed to evolutionary novel environments such as a gravitational free one. PMID:23806134

Breast and Prostate Cancer and Hormone-Related Gene Variant Study

Cancer.gov

The Breast and Prostate Cancer and Hormone-Related Gene Variant Study allows large-scale analyses of breast and prostate cancer risk in relation to genetic polymorphisms and gene-environment interactions that affect hormone metabolism.

Combining research approaches to advance our understanding of drug addiction.

PubMed

van den Bree, Marianne B M

2005-04-01

Drug addiction is a complex behavior, likely to be influenced by various genes, environmental factors, and gene-gene and gene-environment interactions. Various aspects of addiction are studied by different disciplines. Animal studies are increasing insight into brain regions and genes associated with addiction. Epidemiologic studies are establishing the factors increasing risk for initiation and continuation of substance use. Twin and adoption studies are increasing our understanding of the complex mechanisms involved in substance use, including comorbidity and gene environment interaction. Finally, molecular genetic studies in humans are starting to yield some converging findings. It is argued and illustrated with examples that greater awareness of progress in other disciplines can speed up our understanding of the complex processes involved in addiction. This should help our ability to identify who is at increased risk of becoming addicted and the development of prevention and intervention strategies targeted at an individual's specific needs.

A Tool to Simulate the Transmission, Reception, and Execution of Interactive TV Applications

PubMed Central

Kulesza, Raoni; Rodrigues, Thiago; Machado, Felipe A. L.; Santos, Celso A. S.

2017-01-01

The emergence of Interactive Digital Television (iDTV) opened a set of technological possibilities that go beyond those offered by conventional TV. Among these opportunities we can highlight interactive contents that run together with linear TV program (television service where the viewer has to watch a scheduled TV program at the particular time it is offered and on the particular channel it is presented on). However, developing interactive contents for this new platform is not as straightforward as, for example, developing Internet applications. One of the options to make this development process easier and safer is to use an iDTV simulator. However, after having investigated some of the existing iDTV simulation environments, we have found a limitation: these simulators mainly present solutions focused on the TV receiver, whose interactive content must be loaded in advance by the programmer to a local repository (e.g., Hard Drive, USB). Therefore, in this paper, we propose a tool, named BiS (Broadcast iDTV content Simulator), which makes possible a broader solution for the simulation of interactive contents. It allows simulating the transmission of interactive content along with the linear TV program (simulating the transmission of content over the air and in broadcast to the receivers). To enable this, we defined a generic and easy-to-customize communication protocol that was implemented in the tool. The proposed environment differs from others because it allows simulating reception of both linear content and interactive content while running Java applications to allow such a content presentation. PMID:28280770

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

PubMed

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 < 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.

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

PubMed

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.

Restrictions on biological adaptation in language evolution.

PubMed

Chater, Nick; Reali, Florencia; Christiansen, Morten H

2009-01-27

Language acquisition and processing are governed by genetic constraints. A crucial unresolved question is how far these genetic constraints have coevolved with language, perhaps resulting in a highly specialized and species-specific language "module," and how much language acquisition and processing redeploy preexisting cognitive machinery. In the present work, we explored the circumstances under which genes encoding language-specific properties could have coevolved with language itself. We present a theoretical model, implemented in computer simulations, of key aspects of the interaction of genes and language. Our results show that genes for language could have coevolved only with highly stable aspects of the linguistic environment; a rapidly changing linguistic environment does not provide a stable target for natural selection. Thus, a biological endowment could not coevolve with properties of language that began as learned cultural conventions, because cultural conventions change much more rapidly than genes. We argue that this rules out the possibility that arbitrary properties of language, including abstract syntactic principles governing phrase structure, case marking, and agreement, have been built into a "language module" by natural selection. The genetic basis of human language acquisition and processing did not coevolve with language, but primarily predates the emergence of language. As suggested by Darwin, the fit between language and its underlying mechanisms arose because language has evolved to fit the human brain, rather than the reverse.

Gene × environment interaction on intergroup bias: the role of 5-HTTLPR and perceived outgroup threat

PubMed Central

Livingston, Robert W.; Hong, Ying-Yi; Chiao, Joan Y.

2014-01-01

Perceived threat from outgroups is a consistent social-environmental antecedent of intergroup bias (i.e. prejudice, ingroup favoritism). The serotonin transporter gene polymorphism (5-HTTLPR) has been associated with individual variations in sensitivity to context, particularly stressful and threatening situations. Here, we examined how 5-HTTLPR and environmental factors signaling potential outgroup threat dynamically interact to shape intergroup bias. Across two studies, we provide novel evidence for a gene–environment interaction on the acquisition of intergroup bias and prejudice. Greater exposure to signals of outgroup threat, such as negative prior contact with outgroups and perceived danger from the social environment, were more predictive of intergroup bias among participants possessing at least one short allele (vs two long alleles) of 5-HTTLPR. Furthermore, this gene x environment interaction was observed for biases directed at diverse ethnic and arbitrarily-defined outgroups across measures reflecting intergroup biases in evaluation and discriminatory behavior. These findings reveal a candidate genetic mechanism for the acquisition of intergroup bias, and suggest that intergroup bias is dually inherited and transmitted through the interplay of social (i.e. contextual cues of outgroup threat) and biological mechanisms (i.e. genetic sensitivity toward threatening contexts) that regulate perceived intergroup threats. PMID:23887814

A numerical tool for reproducing driver behaviour: experiments and predictive simulations.

PubMed

Casucci, M; Marchitto, M; Cacciabue, P C

2010-03-01

This paper presents the simulation tool called SDDRIVE (Simple Simulation of Driver performance), which is the numerical computerised implementation of the theoretical architecture describing Driver-Vehicle-Environment (DVE) interactions, contained in Cacciabue and Carsten [Cacciabue, P.C., Carsten, O. A simple model of driver behaviour to sustain design and safety assessment of automated systems in automotive environments, 2010]. Following a brief description of the basic algorithms that simulate the performance of drivers, the paper presents and discusses a set of experiments carried out in a Virtual Reality full scale simulator for validating the simulation. Then the predictive potentiality of the tool is shown by discussing two case studies of DVE interactions, performed in the presence of different driver attitudes in similar traffic conditions.

Teaching Harmonic Motion in Trigonometry: Inductive Inquiry Supported by Physics Simulations

ERIC Educational Resources Information Center

Sokolowski, Andrzej; Rackley, Robin

2011-01-01

In this article, the authors present a lesson whose goal is to utilise a scientific environment to immerse a trigonometry student in the process of mathematical modelling. The scientific environment utilised during this activity is a physics simulation called "Wave on a String" created by the PhET Interactive Simulations Project at…

The Virtual Environment for Rapid Prototyping of the Intelligent Environment

PubMed Central

Bouzouane, Abdenour; Gaboury, Sébastien

2017-01-01

Advances in domains such as sensor networks and electronic and ambient intelligence have allowed us to create intelligent environments (IEs). However, research in IE is being held back by the fact that researchers face major difficulties, such as a lack of resources for their experiments. Indeed, they cannot easily build IEs to evaluate their approaches. This is mainly because of economic and logistical issues. In this paper, we propose a simulator to build virtual IEs. Simulators are a good alternative to physical IEs because they are inexpensive, and experiments can be conducted easily. Our simulator is open source and it provides users with a set of virtual sensors that simulates the behavior of real sensors. This simulator gives the user the capacity to build their own environment, providing a model to edit inhabitants’ behavior and an interactive mode. In this mode, the user can directly act upon IE objects. This simulator gathers data generated by the interactions in order to produce datasets. These datasets can be used by scientists to evaluate several approaches in IEs. PMID:29112175

Translating the simulation of procedural drilling techniques for interactive neurosurgical training.

PubMed

Stredney, Don; Rezai, Ali R; Prevedello, Daniel M; Elder, J Bradley; Kerwin, Thomas; Hittle, Bradley; Wiet, Gregory J

2013-10-01

Through previous efforts we have developed a fully virtual environment to provide procedural training of otologic surgical technique. The virtual environment is based on high-resolution volumetric data of the regional anatomy. These volumetric data help drive an interactive multisensory, ie, visual (stereo), aural (stereo), and tactile, simulation environment. Subsequently, we have extended our efforts to support the training of neurosurgical procedural technique as part of the Congress of Neurological Surgeons simulation initiative. To deliberately study the integration of simulation technologies into the neurosurgical curriculum and to determine their efficacy in teaching minimally invasive cranial and skull base approaches. We discuss issues of biofidelity and our methods to provide objective, quantitative and automated assessment for the residents. We conclude with a discussion of our experiences by reporting preliminary formative pilot studies and proposed approaches to take the simulation to the next level through additional validation studies. We have presented our efforts to translate an otologic simulation environment for use in the neurosurgical curriculum. We have demonstrated the initial proof of principles and define the steps to integrate and validate the system as an adjuvant to the neurosurgical curriculum.

The Virtual Environment for Rapid Prototyping of the Intelligent Environment.

PubMed

Francillette, Yannick; Boucher, Eric; Bouzouane, Abdenour; Gaboury, Sébastien

2017-11-07

Advances in domains such as sensor networks and electronic and ambient intelligence have allowed us to create intelligent environments (IEs). However, research in IE is being held back by the fact that researchers face major difficulties, such as a lack of resources for their experiments. Indeed, they cannot easily build IEs to evaluate their approaches. This is mainly because of economic and logistical issues. In this paper, we propose a simulator to build virtual IEs. Simulators are a good alternative to physical IEs because they are inexpensive, and experiments can be conducted easily. Our simulator is open source and it provides users with a set of virtual sensors that simulates the behavior of real sensors. This simulator gives the user the capacity to build their own environment, providing a model to edit inhabitants' behavior and an interactive mode. In this mode, the user can directly act upon IE objects. This simulator gathers data generated by the interactions in order to produce datasets. These datasets can be used by scientists to evaluate several approaches in IEs.

SPEEDES - A multiple-synchronization environment for parallel discrete-event simulation

NASA Technical Reports Server (NTRS)

Steinman, Jeff S.

1992-01-01

Synchronous Parallel Environment for Emulation and Discrete-Event Simulation (SPEEDES) is a unified parallel simulation environment. It supports multiple-synchronization protocols without requiring users to recompile their code. When a SPEEDES simulation runs on one node, all the extra parallel overhead is removed automatically at run time. When the same executable runs in parallel, the user preselects the synchronization algorithm from a list of options. SPEEDES currently runs on UNIX networks and on the California Institute of Technology/Jet Propulsion Laboratory Mark III Hypercube. SPEEDES also supports interactive simulations. Featured in the SPEEDES environment is a new parallel synchronization approach called Breathing Time Buckets. This algorithm uses some of the conservative techniques found in Time Bucket synchronization, along with the optimism that characterizes the Time Warp approach. A mathematical model derived from first principles predicts the performance of Breathing Time Buckets. Along with the Breathing Time Buckets algorithm, this paper discusses the rules for processing events in SPEEDES, describes the implementation of various other synchronization protocols supported by SPEEDES, describes some new ones for the future, discusses interactive simulations, and then gives some performance results.

Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases

PubMed Central

Ritchie, Marylyn D; White, Bill C; Parker, Joel S; Hahn, Lance W; Moore, Jason H

2003-01-01

Background Appropriate definition of neural network architecture prior to data analysis is crucial for successful data mining. This can be challenging when the underlying model of the data is unknown. The goal of this study was to determine whether optimizing neural network architecture using genetic programming as a machine learning strategy would improve the ability of neural networks to model and detect nonlinear interactions among genes in studies of common human diseases. Results Using simulated data, we show that a genetic programming optimized neural network approach is able to model gene-gene interactions as well as a traditional back propagation neural network. Furthermore, the genetic programming optimized neural network is better than the traditional back propagation neural network approach in terms of predictive ability and power to detect gene-gene interactions when non-functional polymorphisms are present. Conclusion This study suggests that a machine learning strategy for optimizing neural network architecture may be preferable to traditional trial-and-error approaches for the identification and characterization of gene-gene interactions in common, complex human diseases. PMID:12846935

Evidence of Reactive Gene-Environment Correlation in Preschoolers' Prosocial Play with Unfamiliar Peers

ERIC Educational Resources Information Center

DiLalla, Lisabeth Fisher; Bersted, Kyle; John, Sufna Gheyara

2015-01-01

The development of prosocial behaviors during the preschool years is essential for children's positive interactions with peers in school and other social situations. Although there is some evidence of genetic influences on prosocial behaviors, very little is known about how genes and environment, independently and in concert, affect prosocial…

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

ERIC Educational Resources Information Center

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…

Optimal Living Environments for the Elderly: A Design Simulation Approach.

ERIC Educational Resources Information Center

Hoffman, Stephanie B.; And Others

PLANNED AGE (Planned Alternatives for Gerontological Environments) is a consumer/advocate-oriented design simulation package that provides: (a) a medium for user-planner interaction in the design of living and service environments for the aged; (b) an educational, planning, design, and evaluation tool that can be used by the elderly, their…

Linking Gene, Brain, and Behavior

PubMed Central

Schmidt, Louis A.; Fox, Nathan A.; Perez-Edgar, Koraly; Hamer, Dean H.

2009-01-01

Gene-environment interactions involving exogenous environmental factors are known to shape behavior and personality development. Although gene-environment interactions involving endogenous environmental factors are hypothesized to play an equally important role, this conceptual approach has not been empirically applied in the study of early-developing temperament in humans. Here we report evidence for a gene-endoenvironment (i.e., resting frontal brain electroencephalogram, EEG, asymmetry) interaction in predicting child temperament. The DRD4 gene (long allele vs. short allele) moderated the relation between resting frontal EEG asymmetry (left vs. right) at 9 months and temperament at 48 months. Children who exhibited left frontal EEG asymmetry at 9 months and who possessed the DRD4 long allele were significantly more soothable at 48 months than other children. Among children with right frontal EEG asymmetry at 9 months, those with the DRD4 long allele had significantly more difficulties focusing and sustaining attention at 48 months than those with the DRD4 short allele. Resting frontal EEG asymmetry did not influence temperament in the absence of the DRD4 long allele. We discuss how the interaction of genetic and endoenvironment factors may confer risk and protection for different behavioral styles in children. PMID:19493320

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

PubMed

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.

Response of Human Prostate Cancer Cells to Mitoxantrone Treatment in Simulated Microgravity Environment

NASA Astrophysics Data System (ADS)

Zhang, Ye; Wu, Honglu

2012-07-01

RESPONSE OF HUMAN PROSTATE CANCER CELLS TO MITOXANTRONE TREATMENT IN SIMULATED MICROGRAVITY ENVIRONMENT Ye Zhang1,2, Christopher Edwards3, and Honglu Wu1 1 NASA-Johnson Space Center, Houston, TX 2 Wyle Integrated Science and Engineering Group, Houston, TX 3 Oregon State University, Corvallis, OR This study explores the changes in growth of human prostate cancer cells (LNCaP) and their response to the treatment of an antineoplastic agent, mitoxantrone, under the simulated microgravity condition. In comparison to static 1g, microgravity and simulated microgravity have been shown to alter global gene expression patterns and protein levels in various cultured cell models or animals. However, very little is known about the effect of altered gravity on the responses of cells to the treatment of drugs, especially chemotherapy drugs. To test the hypothesis that zero gravity would result in altered regulations of cells in response to antineoplastic agents, we cultured LNCaP cells in either a High Aspect Ratio Vessel (HARV) bioreactor at the rotating condition to model microgravity in space or in the static condition as control, and treated the cells with mitoxantrone. Cell growth, as well as expressions of oxidative stress related genes, were analyzed after the drug treatment. Compared to static 1g controls, the cells cultured in the simulated microgravity environment did not present significant differences in cell viability, growth rate, or cell cycle distribution. However, after mitoxantrone treatment, a significant proportion of bioreactor cultured cells became apoptotic or was arrested in G2. Several oxidative stress related genes also showed a higher expression level post mitoxantrone treatment. Our results indicate that simulated microgravity may alter the response of LNCaP cells to mitoxantrone treatment. Understanding the mechanisms by which cells respond to drugs differently in an altered gravity environment will be useful for the improvement of cancer treatment on the ground. This study explores the changes in growth of human prostate cancer cells (LNCaP) and their response to the treatment of an antineoplastic agent, mitoxantrone, under the simulated microgravity condition. In comparison to static 1g, microgravity and simulated microgravity have been shown to alter global gene expression patterns and protein levels in various cultured cell models or animals. However, very little is known about the effect of altered gravity on the responses of cells to the treatment of drugs, especially chemotherapy drugs. To test the hypothesis that zero gravity would result in altered regulations of cells in response to antineoplastic agents, we cultured LNCaP cells in either a High Aspect Ratio Vessel (HARV) bioreactor at the rotating condition to model microgravity in space or in the static condition as control, and treated the cells with mitoxantrone. Cell growth, as well as expressions of oxidative stress related genes, were analyzed after the drug treatment. Compared to static 1g controls, the cells cultured in the simulated microgravity environment did not present significant differences in cell viability, growth rate, or cell cycle distribution. However, after mitoxantrone treatment, a significant proportion of bioreactor cultured cells became apoptotic or was arrested in G2. Several oxidative stress related genes also showed a higher expression level post mitoxantrone treatment. Our results indicate that simulated microgravity may alter the response of LNCaP cells to mitoxantrone treatment. Understanding the mechanisms by which cells respond to drugs differently in an altered gravity environment will be useful for the improvement of cancer treatment on the ground.

Monoamine Oxidase A (MAOA) and Catechol-O-Methyltransferase (COMT) Gene Polymorphisms Interact with Maternal Parenting in Association with Adolescent Reactive Aggression but not Proactive Aggression: Evidence of Differential Susceptibility.

PubMed

Zhang, Wenxin; Cao, Cong; Wang, Meiping; Ji, Linqin; Cao, Yanmiao

2016-04-01

To date, whether and how gene-environment (G × E) interactions operate differently across distinct subtypes of aggression remains untested. More recently, in contrast with the diathesis-stress hypothesis, an alternative hypothesis of differential susceptibility proposes that individuals could be differentially susceptible to environments depending on their genotypes in a "for better and for worse" manner. The current study examined interactions between monoamine oxidase A (MAOA) T941G and catechol-O-methyltransferase (COMT) Val158Met polymorphisms with maternal parenting on two types of aggression: reactive and proactive. Moreover, whether these potential G × E interactions would be consistent with the diathesis-stress versus the differential susceptibility hypothesis was tested. Within the sample of 1399 Chinese Han adolescents (47.2 % girls, M age = 12.32 years, SD = 0.50), MAOA and COMT genes both interacted with positive parenting in their associations with reactive but not proactive aggression. Adolescents with T alleles/TT homozygotes of MAOA gene or Met alleles of COMT gene exhibited more reactive aggression when exposed to low positive parenting, but less reactive aggression when exposed to high positive parenting. These findings provide the first evidence for distinct G × E interaction effects on reactive versus proactive aggression and lend further support for the differential susceptibility hypothesis.

Managing biological networks by using text mining and computer-aided curation

NASA Astrophysics Data System (ADS)

Yu, Seok Jong; Cho, Yongseong; Lee, Min-Ho; Lim, Jongtae; Yoo, Jaesoo

2015-11-01

In order to understand a biological mechanism in a cell, a researcher should collect a huge number of protein interactions with experimental data from experiments and the literature. Text mining systems that extract biological interactions from papers have been used to construct biological networks for a few decades. Even though the text mining of literature is necessary to construct a biological network, few systems with a text mining tool are available for biologists who want to construct their own biological networks. We have developed a biological network construction system called BioKnowledge Viewer that can generate a biological interaction network by using a text mining tool and biological taggers. It also Boolean simulation software to provide a biological modeling system to simulate the model that is made with the text mining tool. A user can download PubMed articles and construct a biological network by using the Multi-level Knowledge Emergence Model (KMEM), MetaMap, and A Biomedical Named Entity Recognizer (ABNER) as a text mining tool. To evaluate the system, we constructed an aging-related biological network that consist 9,415 nodes (genes) by using manual curation. With network analysis, we found that several genes, including JNK, AP-1, and BCL-2, were highly related in aging biological network. We provide a semi-automatic curation environment so that users can obtain a graph database for managing text mining results that are generated in the server system and can navigate the network with BioKnowledge Viewer, which is freely available at http://bioknowledgeviewer.kisti.re.kr.

Genetic and environmental influences on the development of alcoholism: resilience vs. risk.

PubMed

Enoch, Mary-Anne

2006-12-01

The physiological changes of adolescence may promote risk-taking behaviors, including binge drinking. Approximately 40% of alcoholics were already drinking heavily in late adolescence. Most cases of alcoholism are established by the age of 30 years with the peak prevalence at 18-23 years of age. Therefore the key time frame for the development, and prevention, of alcoholism lies in adolescence and young adulthood. Severe childhood stressors have been associated with increased vulnerability to addiction, however, not all stress-exposed children go on to develop alcoholism. Origins of resilience can be both genetic (variation in alcohol-metabolizing genes, increased susceptibility to alcohol's sedative effects) and environmental (lack of alcohol availability, positive peer and parental support). Genetic vulnerability is likely to be conferred by multiple genes of small to modest effects, possibly only apparent in gene-environment interactions. For example, it has been shown that childhood maltreatment interacts with a monoamine oxidase A (MAOA) gene variant to predict antisocial behavior that is often associated with alcoholism, and an interaction between early life stress and a serotonin transporter promoter variant predicts alcohol abuse in nonhuman primates and depression in humans. In addition, a common Met158 variant in the catechol-O-methyltransferase (COMT) gene can confer both risk and resilience to alcoholism in different drinking environments. It is likely that a complex mix of gene(s)-environment(s) interactions underlie addiction vulnerability and development. Risk-resilience factors can best be determined in longitudinal studies, preferably starting during pregnancy. This kind of research is important for planning future measures to prevent harmful drinking in adolescence.

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

ERIC Educational Resources Information Center

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…

Intellectual Interest Mediates Gene x Socioeconomic Status Interaction on Adolescent Academic Achievement

ERIC Educational Resources Information Center

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

2012-01-01

Recent studies have demonstrated that genetic influences on cognitive ability and academic achievement are larger for children raised in higher socioeconomic status (SES) homes. However, little work has been done to document the psychosocial processes that underlie this Gene x Environment interaction. One process may involve the conversion of…

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

PubMed

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.

Genetic determinants of prepubertal and pubertal growth and development.

PubMed

Thomis, Martine A; Towne, Bradford

2006-12-01

This article surveys the current general understanding of genetic influences on within- and between-population variation in growth and development in the context of establishing an International Growth Standard for Preadolescent and Adolescent Children. Traditional genetic epidemiologic analysis methods are reviewed, and evidence from family studies for genetic effects on different measures of growth and development is then presented. Findings from linkage and association studies seeking to identify specific genomic locations and allelic variants of genes influencing variation in growth and maturation are then summarized. Special mention is made of the need to study the interactions between genes and environments. At present, specific genes and polymorphisms contributing to variation in growth and maturation are only beginning to be identified. Larger genetic epidemiologic studies are needed in different parts of the world to better explore population differences in gene frequencies and gene-environment interactions. As advances continue to be made in molecular and statistical genetic methods, the genetic architecture of complex processes, including those of growth and development, will become better elucidated. For now, it can only be concluded that although the fundamental genetic underpinnings of the growth and development of children worldwide are likely to be essentially the same, there are also likely to be differences between populations in the frequencies of allelic gene variants that influence growth and maturation and in the nature of gene-environment interactions. This does not necessarily preclude an international growth reference, but it does have important implications for the form that such a reference might ultimately take.

Imagine the Emotion: The Use of Mental Simulations in Supporting the Development of Emotional Skills of Preschool Children

ERIC Educational Resources Information Center

Jarczewska-Gerc, Ewa; Gorgolewska, Anna

2015-01-01

Emotional intelligence plays a great role in human adaptation to social environments. The individual level of emotional skills depends on one's genes, family environment, and socialisation, as well as personal experience and education. The purpose of the present study was to examine the educational influence of mental simulation in developing the…

Four-fluid MHD Simulations of the Plasma and Neutral Gas Environment of Comet Churyumov-Gerasimenko Near Perihelio

NASA Astrophysics Data System (ADS)

Huang, Z.; Toth, G.; Gombosi, T. I.; Jia, X.; Rubin, M.; Hansen, K. C.; Fougere, N.; Bieler, A. M.; Shou, Y.; Altwegg, K.; Combi, M. R.; Tenishev, V.

2015-12-01

The neutral and plasma environment is critical in understanding the interaction of comet Churyumov-Gerasimenko (CG), the target of the Rosetta mission, and the solar wind. To serve this need and support the Rosetta mission, we develop a 3-D four fluid model, which is based on BATS-R-US within the SWMF (Space Weather Modeling Framework) that solves the governing multi-fluid MHD equations and the Euler equations for the neutral gas fluid. These equations describe the behavior and interactions of the cometary heavy ions, the solar wind protons, the electrons, and the neutrals. This model incorporates different mass loading processes, including photo and electron impact ionization, charge exchange, dissociative ion-electron recombination, and collisional interactions between different fluids. We simulate the near nucleus plasma and neutral gas environment near perihelion with a realistic shape model of CG and compare our simulation results with Rosetta observations.

Gene-gene-environment interactions between drugs, transporters, receptors, and metabolizing enzymes: Statins, SLCO1B1, and CYP3A4 as an example.

PubMed

Sadee, Wolfgang

2013-09-01

Pharmacogenetic biomarker tests include mostly specific single gene-drug pairs, capable of accounting for a portion of interindividual variability in drug response and toxicity. However, multiple genes are likely to contribute, either acting independently or epistatically, with the CYP2C9-VKORC1-warfarin test panel, an example of a clinically used gene-gene-dug interaction. I discuss here further instances of gene-gene-drug interactions, including a proposed dynamic effect on statin therapy by genetic variants in both a transporter (SLCO1B1) and a metabolizing enzyme (CYP3A4) in liver cells, the main target site where statins block cholesterol synthesis. These examples set a conceptual framework for developing diagnostic panels involving multiple gene-drug combinations. Copyright © 2013 Wiley Periodicals, Inc.

Cancer risk and the complexity of the interactions between environmental and host factors: HENVINET interactive diagrams as simple tools for exploring and understanding the scientific evidence.

PubMed

Merlo, Domenico F; Filiberti, Rosangela; Kobernus, Michael; Bartonova, Alena; Gamulin, Marija; Ferencic, Zeljko; Dusinska, Maria; Fucic, Aleksandra

2012-06-28

Development of graphical/visual presentations of cancer etiology caused by environmental stressors is a process that requires combining the complex biological interactions between xenobiotics in living and occupational environment with genes (gene-environment interaction) and genomic and non-genomic based disease specific mechanisms in living organisms. Traditionally, presentation of causal relationships includes the statistical association between exposure to one xenobiotic and the disease corrected for the effect of potential confounders. Within the FP6 project HENVINET, we aimed at considering together all known agents and mechanisms involved in development of selected cancer types. Selection of cancer types for causal diagrams was based on the corpus of available data and reported relative risk (RR). In constructing causal diagrams the complexity of the interactions between xenobiotics was considered a priority in the interpretation of cancer risk. Additionally, gene-environment interactions were incorporated such as polymorphisms in genes for repair and for phase I and II enzymes involved in metabolism of xenobiotics and their elimination. Information on possible age or gender susceptibility is also included. Diagrams are user friendly thanks to multistep access to information packages and the possibility of referring to related literature and a glossary of terms. Diagrams cover both chemical and physical agents (ionizing and non-ionizing radiation) and provide basic information on the strength of the association between type of exposure and cancer risk reported by human studies and supported by mechanistic studies. Causal diagrams developed within HENVINET project represent a valuable source of information for professionals working in the field of environmental health and epidemiology, and as educational material for students. Cancer risk results from a complex interaction of environmental exposures with inherited gene polymorphisms, genetic burden collected during development and non genomic capacity of response to environmental insults. In order to adopt effective preventive measures and the associated regulatory actions, a comprehensive investigation of cancer etiology is crucial. Variations and fluctuations of cancer incidence in human populations do not necessarily reflect environmental pollution policies or population distribution of polymorphisms of genes known to be associated with increased cancer risk. Tools which may be used in such a comprehensive research, including molecular biology applied to field studies, require a methodological shift from the reductionism that has been used until recently as a basic axiom in interpretation of data. The complexity of the interactions between cells, genes and the environment, i.e. the resonance of the living matter with the environment, can be synthesized by systems biology. Within the HENVINET project such philosophy was followed in order to develop interactive causal diagrams for the investigation of cancers with possible etiology in environmental exposure. Causal diagrams represent integrated knowledge and seed tool for their future development and development of similar diagrams for other environmentally related diseases such as asthma or sterility. In this paper development and application of causal diagrams for cancer are presented and discussed.

Effects of data structure on the estimation of covariance functions to describe genotype by environment interactions in a reaction norm model

PubMed Central

Calus, Mario PL; Bijma, Piter; Veerkamp, Roel F

2004-01-01

Covariance functions have been proposed to predict breeding values and genetic (co)variances as a function of phenotypic within herd-year averages (environmental parameters) to include genotype by environment interaction. The objective of this paper was to investigate the influence of definition of environmental parameters and non-random use of sires on expected breeding values and estimated genetic variances across environments. Breeding values were simulated as a linear function of simulated herd effects. The definition of environmental parameters hardly influenced the results. In situations with random use of sires, estimated genetic correlations between the trait expressed in different environments were 0.93, 0.93 and 0.97 while simulated at 0.89 and estimated genetic variances deviated up to 30% from the simulated values. Non random use of sires, poor genetic connectedness and small herd size had a large impact on the estimated covariance functions, expected breeding values and calculated environmental parameters. Estimated genetic correlations between a trait expressed in different environments were biased upwards and breeding values were more biased when genetic connectedness became poorer and herd composition more diverse. The best possible solution at this stage is to use environmental parameters combining large numbers of animals per herd, while losing some information on genotype by environment interaction in the data. PMID:15339629

Gene by environment interactions influencing reading disability and the inattentive symptom dimension of attention deficit/hyperactivity disorder.

PubMed

Rosenberg, Jenni; Pennington, Bruce F; Willcutt, Erik G; Olson, Richard K

2012-03-01

Reading disability (RD) and attention deficit/hyperactivity disorder (ADHD) are comorbid and genetically correlated, especially the inattentive dimension of ADHD (ADHD-I). However, previous research indicates that RD and ADHD enter into opposite gene by environment (G × E) interactions. This study used behavioral genetic methods to replicate these opposite G × E interactions in a sample of same-sex monozygotic and dizygotic twin pairs from the Colorado Learning Disabilities Research Center (CLDRC; DeFries et al., 1997) and to test a genetic hypothesis for why these opposite interactions occur. We replicated opposite G × E interactions for RD (bioecological) and ADHD-I (diathesis-stress) with parental education in the same sample of participants. The genetic hypothesis for this opposite pattern of interactions is that only genes specific to each disorder enter into these opposite interactions, not the shared genes underlying their comorbidity. To test this hypothesis, we used single models with an exploratory three-way interaction, in which the G × E interactions for each disorder were moderated by comorbidity. Neither three-way interaction was significant. The heritability of RD did not vary as a function of parental education and ADHD-I. Similarly, the heritability of ADHD-I did not vary as a function of parental education and RD. We documented opposite G × E interactions in RD and ADHD-I in the same overall twin sample, but the explanation for this apparent paradox remains unclear. Examining specific genes and more specific environmental factors may help resolve the paradox. © 2011 The Authors. Journal of Child Psychology and Psychiatry © 2011 Association for Child and Adolescent Mental Health.

The heritable basis of gene-environment interactions in cardiometabolic traits.

PubMed

Poveda, Alaitz; Chen, Yan; Brändström, Anders; Engberg, Elisabeth; Hallmans, Göran; Johansson, Ingegerd; Renström, Frida; Kurbasic, Azra; Franks, Paul W

2017-03-01

Little is known about the heritable basis of gene-environment interactions in humans. We therefore screened multiple cardiometabolic traits to assess the probability that they are influenced by genotype-environment interactions. Fourteen established environmental risk exposures and 11 cardiometabolic traits were analysed in the VIKING study, a cohort of 16,430 Swedish adults from 1682 extended pedigrees with available detailed genealogical, phenotypic and demographic information, using a maximum likelihood variance decomposition method in Sequential Oligogenic Linkage Analysis Routines software. All cardiometabolic traits had statistically significant heritability estimates, with narrow-sense heritabilities (h 2 ) ranging from 24% to 47%. Genotype-environment interactions were detected for age and sex (for the majority of traits), physical activity (for triacylglycerols, 2 h glucose and diastolic BP), smoking (for weight), alcohol intake (for weight, BMI and 2 h glucose) and diet pattern (for weight, BMI, glycaemic traits and systolic BP). Genotype-age interactions for weight and systolic BP, genotype-sex interactions for BMI and triacylglycerols and genotype-alcohol intake interactions for weight remained significant after multiple test correction. Age, sex and alcohol intake are likely to be major modifiers of genetic effects for a range of cardiometabolic traits. This information may prove valuable for studies that seek to identify specific loci that modify the effects of lifestyle in cardiometabolic disease.

Mechanistic links between cellular trade-offs, gene expression, and growth.

PubMed

Weiße, Andrea Y; Oyarzún, Diego A; Danos, Vincent; Swain, Peter S

2015-03-03

Intracellular processes rarely work in isolation but continually interact with the rest of the cell. In microbes, for example, we now know that gene expression across the whole genome typically changes with growth rate. The mechanisms driving such global regulation, however, are not well understood. Here we consider three trade-offs that, because of limitations in levels of cellular energy, free ribosomes, and proteins, are faced by all living cells and we construct a mechanistic model that comprises these trade-offs. Our model couples gene expression with growth rate and growth rate with a growing population of cells. We show that the model recovers Monod's law for the growth of microbes and two other empirical relationships connecting growth rate to the mass fraction of ribosomes. Further, we can explain growth-related effects in dosage compensation by paralogs and predict host-circuit interactions in synthetic biology. Simulating competitions between strains, we find that the regulation of metabolic pathways may have evolved not to match expression of enzymes to levels of extracellular substrates in changing environments but rather to balance a trade-off between exploiting one type of nutrient over another. Although coarse-grained, the trade-offs that the model embodies are fundamental, and, as such, our modeling framework has potentially wide application, including in both biotechnology and medicine.

Effect of simulated microgravity on oxidation-sensitive gene expression in PC12 cells

NASA Astrophysics Data System (ADS)

Kwon, Ohwon; Sartor, Maureen; Tomlinson, Craig R.; Millard, Ronald W.; Olah, Mark E.; Sankovic, John M.; Banerjee, Rupak K.

2006-01-01

Oxygen utilization by and oxygen dependence of cellular processes may be different in biological systems that are exposed to microgravity (micro-g). A baseline in which cellular changes in oxygen sensitive molecular processes occur during micro-g conditions would be important to pursue this question. The objective of this research is to analyze oxidation-sensitive gene expression in a model cell line [rat pheochromocytoma (PC12)] under simulated micro-g conditions. The PC12 cell line is well characterized in its response to oxygen, and is widely recognized as a sensitive model for studying the responses of oxygen-sensitive molecular and cellular processes. This study uses the rotating wall vessel bioreactor (RWV) designed at NASA to simulate micro-g. Gene expression in PC12 cells in response to micro-g was analyzed by DNA microarray technology. The microarray analysis of PC12 cells cultured for 4 days under simulated micro-g under standardized oxygen environment conditions revealed more than 100 genes whose expression levels were changed at least twofold (up-regulation of 65 genes and down-regulation of 39 genes) compared with those from cells in the unit gravity (unit-g) control. This study observed that genes involved in the oxidoreductase activity category were most significantly differentially expressed under micro-g conditions. Also, known oxidation-sensitive transcription factors such as hypoxia-inducible factor-2α, c-myc, and the peroxisome proliferator-activated receptor-γ were changed significantly. Our initial results from the gene expression microarray studies may provide a context in which to evaluate the effect of varying oxygen environments on the background of differential gene regulation of biological processes under variable gravity conditions.

Effect of simulated microgravity on oxidation-sensitive gene expression in PC12 cells

PubMed Central

Kwon, Ohwon; Sartor, Maureen; Tomlinson, Craig R.; Millard, Ronald W.; Olah, Mark E.; Sankovic, John M.; Banerjee, Rupak K.

2008-01-01

Oxygen utilization by and oxygen dependence of cellular processes may be different in biological systems that are exposed to microgravity (micro-g). A baseline in which cellular changes in oxygen sensitive molecular processes occur during micro-g conditions would be important to pursue this question. The objective of this research is to analyze oxidation-sensitive gene expression in a model cell line [rat pheochromocytoma (PC12)] under simulated micro-g conditions. The PC12 cell line is well characterized in its response to oxygen, and is widely recognized as a sensitive model for studying the responses of oxygen-sensitive molecular and cellular processes. This study uses the rotating wall vessel bioreactor (RWV) designed at NASA to simulate micro-g. Gene expression in PC12 cells in response to micro-g was analyzed by DNA microarray technology. The microarray analysis of PC12 cells cultured for 4 days under simulated micro-g under standardized oxygen environment conditions revealed more than 100 genes whose expression levels were changed at least twofold (up-regulation of 65 genes and down-regulation of 39 genes) compared with those from cells in the unit gravity (unit-g) control. This study observed that genes involved in the oxidoreductase activity category were most significantly differentially expressed under micro-g conditions. Also, known oxidation-sensitive transcription factors such as hypoxia-inducible factor-2α, c-myc, and the peroxisome proliferator-activated receptor-γ were changed significantly. Our initial results from the gene expression microarray studies may provide a context in which to evaluate the effect of varying oxygen environments on the background of differential gene regulation of biological processes under variable gravity conditions. PMID:19081771

Gene-environment interactions in cancer epidemiology: a National Cancer Institute Think Tank report.

PubMed

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 < MAF < 0.05) genetic variants associated with cancer. The marginal effects of most of these variants have been small (odds ratios: 1.1-1.4). There remain unanswered questions on how best to incorporate the joint effects of genes and environment, including gene-environment (G × E) interactions, into epidemiologic studies of cancer. To help address these questions, and to better inform research priorities and allocation of resources, the National Cancer Institute sponsored a "Gene-Environment 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.

Genetic Modification of the Relationship between Parental Rejection and Adolescent Alcohol Use.

PubMed

Stogner, John M; Gibson, Chris L

2016-07-01

Parenting practices are associated with adolescents' alcohol consumption, however not all youth respond similarly to challenging family situations and harsh environments. This study examines the relationship between perceived parental rejection and adolescent alcohol use, and specifically evaluates whether youth who possess greater genetic sensitivity to their environment are more susceptible to negative parental relationships. Analyzing data from the National Longitudinal Study of Adolescent Health, we estimated a series of regression models predicting alcohol use during adolescence. A multiplicative interaction term between parental rejection and a genetic index was constructed to evaluate this potential gene-environment interaction. Results from logistic regression analyses show a statistically significant gene-environment interaction predicting alcohol use. The relationship between parental rejection and alcohol use was moderated by the genetic index, indicating that adolescents possessing more 'risk alleles' for five candidate genes were affected more by stressful parental relationships. Feelings of parental rejection appear to influence the alcohol use decisions of youth, but they do not do so equally for all. Higher scores on the constructed genetic sensitivity measure are related to increased susceptibility to negative parental relationships. © The Author 2016. Medical Council on Alcohol and Oxford University Press. All rights reserved.

Child Dopamine Transporter Genotype and Parenting: Evidence for Evocative Gene-Environment Correlations

PubMed Central

Hayden, Elizabeth P.; Hanna, Brigitte; Sheikh, Haroon I.; Laptook, Rebecca S.; Kim, Jiyon; Singh, Shiva M.; Klein, Daniel N.

2017-01-01

The dopamine transporter (DAT1) gene is implicated in psychopathology risk. While the processes by which this gene exerts its effects on risk are poorly understood, a small body of research suggests that DAT1 influences early emerging negative emotionality (NE), a marker of children’s psychopathology risk. As child NE evokes negative parenting practices, the DAT1 may also play a role in gene-environment correlations. To test this model, children (N = 365) were genotyped for DAT1 and participated in standardized parent-child interaction tasks with their primary caregiver. The DAT1 9-repeat variant was associated with child negative affect expressed toward the parent during parent-child interactions, and parents of children with a 9-repeat allele exhibited more hostility and lower guidance/engagement than parents of children without a 9-repeat allele. These gene-environment associations were partially mediated by child negative affect toward the parent. Findings implicate a specific polymorphism in eliciting negative parenting, suggesting that evocative associations play a role in elevating children’s risk for emotional trajectories toward psychopathology risk. PMID:23398760

Social environment influences the relationship between genotype and gene expression in wild baboons

PubMed Central

Runcie, Daniel E.; Wiedmann, Ralph T.; Archie, Elizabeth A.; Altmann, Jeanne; Wray, Gregory A.; Alberts, Susan C.; Tung, Jenny

2013-01-01

Variation in the social environment can have profound effects on survival and reproduction in wild social mammals. However, we know little about the degree to which these effects are influenced by genetic differences among individuals, and conversely, the degree to which social environmental variation mediates genetic reaction norms. To better understand these relationships, we investigated the potential for dominance rank, social connectedness and group size to modify the effects of genetic variation on gene expression in the wild baboons of the Amboseli basin. We found evidence for a number of gene–environment interactions (GEIs) associated with variation in the social environment, encompassing social environments experienced in adulthood as well as persistent effects of early life social environment. Social connectedness, maternal dominance rank and group size all interacted with genotype to influence gene expression in at least one sex, and either in early life or in adulthood. These results suggest that social and behavioural variation, akin to other factors such as age and sex, can impact the genotype–phenotype relationship. We conclude that GEIs mediated by the social environment are important in the evolution and maintenance of individual differences in wild social mammals, including individual differences in responses to social stressors. PMID:23569293

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

PubMed

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.

A latent variable approach to study gene-environment interactions in the presence of multiple correlated exposures.

PubMed

Sánchez, Brisa N; Kang, Shan; Mukherjee, Bhramar

2012-06-01

Many existing cohort studies initially designed to investigate disease risk as a function of environmental exposures have collected genomic data in recent years with the objective of testing for gene-environment interaction (G × E) effects. In environmental epidemiology, interest in G × E arises primarily after a significant effect of the environmental exposure has been documented. Cohort studies often collect rich exposure data; as a result, assessing G × E effects in the presence of multiple exposure markers further increases the burden of multiple testing, an issue already present in both genetic and environment health studies. Latent variable (LV) models have been used in environmental epidemiology to reduce dimensionality of the exposure data, gain power by reducing multiplicity issues via condensing exposure data, and avoid collinearity problems due to presence of multiple correlated exposures. We extend the LV framework to characterize gene-environment interaction in presence of multiple correlated exposures and genotype categories. Further, similar to what has been done in case-control G × E studies, we use the assumption of gene-environment (G-E) independence to boost the power of tests for interaction. The consequences of making this assumption, or the issue of how to explicitly model G-E association has not been previously investigated in LV models. We postulate a hierarchy of assumptions about the LV model regarding the different forms of G-E dependence and show that making such assumptions may influence inferential results on the G, E, and G × E parameters. We implement a class of shrinkage estimators to data adaptively trade-off between the most restrictive to most flexible form of G-E dependence assumption and note that such class of compromise estimators can serve as a benchmark of model adequacy in LV models. We demonstrate the methods with an example from the Early Life Exposures in Mexico City to Neuro-Toxicants Study of lead exposure, iron metabolism genes, and birth weight. © 2011, The International Biometric Society.

The Influences of the 2D Image-Based Augmented Reality and Virtual Reality on Student Learning

ERIC Educational Resources Information Center

Liou, Hsin-Hun; Yang, Stephen J. H.; Chen, Sherry Y.; Tarng, Wernhuar

2017-01-01

Virtual reality (VR) learning environments can provide students with concepts of the simulated phenomena, but users are not allowed to interact with real elements. Conversely, augmented reality (AR) learning environments blend real-world environments so AR could enhance the effects of computer simulation and promote students' realistic experience.…

A Model Supported Interactive Virtual Environment for Natural Resource Sharing in Environmental Education

ERIC Educational Resources Information Center

Barbalios, N.; Ioannidou, I.; Tzionas, P.; Paraskeuopoulos, S.

2013-01-01

This paper introduces a realistic 3D model supported virtual environment for environmental education, that highlights the importance of water resource sharing by focusing on the tragedy of the commons dilemma. The proposed virtual environment entails simulations that are controlled by a multi-agent simulation model of a real ecosystem consisting…

Amphetamine Self-Administration and Dopamine Function: Assessment of Gene x Environment Interactions in Lewis and Fischer 344 Rats

PubMed Central

Meyer, Andrew C.; Bardo, Michael T.

2015-01-01

Rationale Previous research suggests both genetic and environmental influences on substance abuse vulnerability. Objectives The current work sought to investigate the interaction of genes and environment on the acquisition of amphetamine self-administration, as well as amphetamine-stimulated dopamine (DA) release in nucleus accumbens shell using in vivo microdialysis. Methods Inbred Lewis (LEW) and Fischer (F344) rat strains were raised in either an enriched condition (EC), social condition (SC), or isolated condition (IC). Acquisition of amphetamine self-administration (0.1 mg/kg/infusion) was determined across an incrementing daily fixed ratio (FR) schedule. In a separate cohort of rats, extracellular DA and the metabolite dihydroxyphenylacetic acid (DOPAC) were measured in the nucleus accumbens shell following an acute amphetamine injection (1 mg/kg). Results “Addiction-prone” LEW had greater acquisition of amphetamine self-administration on a FR1 schedule compared to “addiction-resistant” F344 when raised in the SC environment. These genetic differences were negated in both the EC and IC environments, with enrichment buffering against self-administration and isolation enhancing self-administration in both strains. On a FR5 schedule, the isolation-induced increase in amphetamine self-administration was greater in F344 than LEW. While no group differences were obtained in extracellular DA, gene x environment differences were obtained in extracellular levels of the metabolite DOPAC. In IC rats only, LEW showed an attenuation in the amphetamine-induced decrease in DOPAC compared to F344. IC LEW rats also had an attenuated DOPAC response to amphetamine compared to EC LEW. Conclusions The current results demonstrate gene x environment interactions in amphetamine self-administration and amphetamine-induced changes in extracellular DOPAC in NAc shell. However, the behavioral and neurochemical differences were not related directly, indicating that mechanisms independent of DA metabolism in NAc shell likely mediate the gene x environment effects in amphetamine self-administration. PMID:25566972

Gene--Environment Interplay and Delinquent Involvement: Evidence of Direct, Indirect, and Interactive Effects

ERIC Educational Resources Information Center

Beaver, Kevin M.; DeLisi, Matt; Wright, John Paul; Vaughn, Michael G.

2009-01-01

Behavioral genetic research has revealed that biogenic factors play a role in the development of antisocial behaviors. Much of this research has also explicated the way in which the environment and genes may combine to create different phenotypes. The authors draw heavily from this literature and use data from the National Longitudinal Study of…

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

PubMed

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-Based Testing of Interactions in Association Studies of Quantitative Traits

PubMed Central

Ma, Li; Clark, Andrew G.; Keinan, Alon

2013-01-01

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. PMID:23468652

The relationship between glucocorticoid receptor polymorphisms, stressful life events, social support, and post-traumatic stress disorder.

PubMed

Lian, Yulong; Xiao, Jing; Wang, Qian; Ning, Li; Guan, Suzhen; Ge, Hua; Li, Fuye; Liu, Jiwen

2014-08-12

It is debatable whether or not glucocorticoid receptor (GR) polymorphisms moderate susceptibility to PTSD. Our objective was to examine the effects of stressful life events, social support, GR genotypes, and gene-environment interactions on the etiology of PTSD. Three tag single nucleotide polymorphisms, trauma events, stressful life events, and social support were assessed in 460 patients with PTSD and 1158 control subjects from a Chinese Han population. Gene-environment interactions were analyzed by generalized multifactor dimensionality reduction (GMDR). Variation in GR at rs41423247 and rs258747, stressful life events, social support, and the number of traumatic events were each separately associated with the risk for PTSD. A gene-environment interaction among the polymorphisms, rs41423247 and rs258747, the number of traumatic events, stressful life events, and social support resulted in an increased risk for PTSD. High-risk individuals (a large number of traumatic events, G allele of rs258747 and rs41423247, high level stressful life events, and low social support) had a 3.26-fold increased risk of developing PTSD compared to low-risk individuals. The association was statistically significant in the sub-groups with and without childhood trauma. Our data support the notion that stressful life events, the number of trauma events, and social support may play a contributing role in the risk for PTSD by interacting with GR gene polymorphisms.

Heuristic Identification of Biological Architectures for Simulating Complex Hierarchical Genetic Interactions

PubMed Central

Moore, Jason H; Amos, Ryan; Kiralis, Jeff; Andrews, Peter C

2015-01-01

Simulation plays an essential role in the development of new computational and statistical methods for the genetic analysis of complex traits. Most simulations start with a statistical model using methods such as linear or logistic regression that specify the relationship between genotype and phenotype. This is appealing due to its simplicity and because these statistical methods are commonly used in genetic analysis. It is our working hypothesis that simulations need to move beyond simple statistical models to more realistically represent the biological complexity of genetic architecture. The goal of the present study was to develop a prototype genotype–phenotype simulation method and software that are capable of simulating complex genetic effects within the context of a hierarchical biology-based framework. Specifically, our goal is to simulate multilocus epistasis or gene–gene interaction where the genetic variants are organized within the framework of one or more genes, their regulatory regions and other regulatory loci. We introduce here the Heuristic Identification of Biological Architectures for simulating Complex Hierarchical Interactions (HIBACHI) method and prototype software for simulating data in this manner. This approach combines a biological hierarchy, a flexible mathematical framework, a liability threshold model for defining disease endpoints, and a heuristic search strategy for identifying high-order epistatic models of disease susceptibility. We provide several simulation examples using genetic models exhibiting independent main effects and three-way epistatic effects. PMID:25395175

Protein-Protein Interactions in a Crowded Environment: An Analysis via Cross-Docking Simulations and Evolutionary Information

PubMed Central

Lopes, Anne; Sacquin-Mora, Sophie; Dimitrova, Viktoriya; Laine, Elodie; Ponty, Yann; Carbone, Alessandra

2013-01-01

Large-scale analyses of protein-protein interactions based on coarse-grain molecular docking simulations and binding site predictions resulting from evolutionary sequence analysis, are possible and realizable on hundreds of proteins with variate structures and interfaces. We demonstrated this on the 168 proteins of the Mintseris Benchmark 2.0. On the one hand, we evaluated the quality of the interaction signal and the contribution of docking information compared to evolutionary information showing that the combination of the two improves partner identification. On the other hand, since protein interactions usually occur in crowded environments with several competing partners, we realized a thorough analysis of the interactions of proteins with true partners but also with non-partners to evaluate whether proteins in the environment, competing with the true partner, affect its identification. We found three populations of proteins: strongly competing, never competing, and interacting with different levels of strength. Populations and levels of strength are numerically characterized and provide a signature for the behavior of a protein in the crowded environment. We showed that partner identification, to some extent, does not depend on the competing partners present in the environment, that certain biochemical classes of proteins are intrinsically easier to analyze than others, and that small proteins are not more promiscuous than large ones. Our approach brings to light that the knowledge of the binding site can be used to reduce the high computational cost of docking simulations with no consequence in the quality of the results, demonstrating the possibility to apply coarse-grain docking to datasets made of thousands of proteins. Comparison with all available large-scale analyses aimed to partner predictions is realized. We release the complete decoys set issued by coarse-grain docking simulations of both true and false interacting partners, and their evolutionary sequence analysis leading to binding site predictions. Download site: http://www.lgm.upmc.fr/CCDMintseris/ PMID:24339765

Gene-Diet Interaction and Precision Nutrition in Obesity

PubMed Central

Heianza, Yoriko; Qi, Lu

2017-01-01

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. PMID:28387720

Collaborative voxel-based surgical virtual environments.

PubMed

Acosta, Eric; Muniz, Gilbert; Armonda, Rocco; Bowyer, Mark; Liu, Alan

2008-01-01

Virtual Reality-based surgical simulators can utilize Collaborative Virtual Environments (C-VEs) to provide team-based training. To support real-time interactions, C-VEs are typically replicated on each user's local computer and a synchronization method helps keep all local copies consistent. This approach does not work well for voxel-based C-VEs since large and frequent volumetric updates make synchronization difficult. This paper describes a method that allows multiple users to interact within a voxel-based C-VE for a craniotomy simulator being developed. Our C-VE method requires smaller update sizes and provides faster synchronization update rates than volumetric-based methods. Additionally, we address network bandwidth/latency issues to simulate networked haptic and bone drilling tool interactions with a voxel-based skull C-VE.

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

PubMed

Leighton, Caroline; Botto, Alberto; Silva, Jaime R; Jiménez, Juan Pablo; Luyten, Patrick

2017-01-01

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.

Review of the Gene-Environment Interaction Literature in Cancer: What Do We Know?

PubMed

Simonds, Naoko I; Ghazarian, Armen A; Pimentel, Camilla B; Schully, Sheri D; Ellison, Gary L; Gillanders, Elizabeth M; Mechanic, Leah E

2016-07-01

Risk of cancer is determined by a complex interplay of genetic and environmental factors. Although the study of gene-environment interactions (G×E) has been an active area of research, little is reported about the known findings in the literature. To examine the state of the science in G×E research in cancer, we performed a systematic review of published literature using gene-environment or pharmacogenomic flags from two curated databases of genetic association studies, the Human Genome Epidemiology (HuGE) literature finder and Cancer Genome-Wide Association and Meta Analyses Database (CancerGAMAdb), from January 1, 2001, to January 31, 2011. A supplemental search using HuGE was conducted for articles published from February 1, 2011, to April 11, 2013. A 25% sample of the supplemental publications was reviewed. A total of 3,019 articles were identified in the original search. From these articles, 243 articles were determined to be relevant based on inclusion criteria (more than 3,500 interactions). From the supplemental search (1,400 articles identified), 29 additional relevant articles (1,370 interactions) were included. The majority of publications in both searches examined G×E in colon, rectal, or colorectal; breast; or lung cancer. Specific interactions examined most frequently included environmental factors categorized as energy balance (e.g., body mass index, diet), exogenous (e.g., oral contraceptives) and endogenous hormones (e.g., menopausal status), chemical environment (e.g., grilled meats), and lifestyle (e.g., smoking, alcohol intake). In both searches, the majority of interactions examined were using loci from candidate genes studies and none of the studies were genome-wide interaction studies (GEWIS). The most commonly reported measure was the interaction P-value, of which a sizable number of P-values were considered statistically significant (i.e., <0.05). In addition, the magnitude of interactions reported was modest. Observations of published literature suggest that opportunity exists for increased sample size in G×E research, including GWAS-identified loci in G×E studies, exploring more GWAS approaches in G×E such as GEWIS, and improving the reporting of G×E findings. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Review of the Gene-Environment Interaction Literature in Cancer: What do we know?

PubMed Central

Simonds, Naoko I.; Ghazarian, Armen A.; Pimentel, Camilla B.; Schully, Sheri D.; Ellison, Gary L.; Gillanders, Elizabeth M.; Mechanic, Leah E.

2016-01-01

Background Risk of cancer is determined by a complex interplay of genetic and environmental factors. Although the study of gene-environment (GxE) interactions has been an active area of research, little is reported about the known findings in the literature. Methods To examine the state of the science in GxE research in cancer, we performed a systematic review of published literature using gene-environment or pharmacogenomic flags from two curated databases of genetic association studies, the Human Genome Epidemiology (HuGE) literature finder and Cancer Genome-Wide Association and Meta Analyses Database (CancerGAMAdb), from January 1, 2001, to January 31, 2011. A supplemental search using HuGE was conducted for articles published February 1, 2011, to April 11, 2013. A 25% sample of the supplemental publications was reviewed. Results A total of 3,019 articles were identified in the original search. From these articles, 243 articles were determined to be relevant based on inclusion criteria (more than 3,500 interactions). From the supplemental search (1,400 articles identified), 29 additional relevant articles (1,370 interactions) were included. The majority of publications in both searches examined GxE in colon, rectal, or colorectal cancer types; breast; or lung cancer. Specific interactions examined most frequently included environmental factors categorized as energy balance (e.g., body mass index (BMI), diet), exogenous (e.g., oral contraceptives) and endogenous hormones (e.g., menopausal status), chemical environment (e.g., grilled meats), and lifestyle (e.g., smoking, alcohol intake). In both searches, the majority of interactions examined were using loci from candidate genes studies and none of the studies were genome-wide interaction studies (GEWIS). The most commonly reported measure was the interaction p-value, of which a sizable number of p-values were considered statistically significant (i.e., < 0.05). In addition, the magnitudes of interactions reported were modest. Conclusion Observations of published literature suggest that opportunity exists for increased sample size in GxE research, including GWAS identified loci in GxE studies, exploring more GWAS approaches in GxE such as GEWIS, and improving the reporting of GxE findings. PMID:27061572

Using the PhysX engine for physics-based virtual surgery with force feedback.

PubMed

Maciel, Anderson; Halic, Tansel; Lu, Zhonghua; Nedel, Luciana P; De, Suvranu

2009-09-01

The development of modern surgical simulators is highly challenging, as they must support complex simulation environments. The demand for higher realism in such simulators has driven researchers to adopt physics-based models, which are computationally very demanding. This poses a major problem, since real-time interactions must permit graphical updates of 30 Hz and a much higher rate of 1 kHz for force feedback (haptics). Recently several physics engines have been developed which offer multi-physics simulation capabilities, including rigid and deformable bodies, cloth and fluids. While such physics engines provide unique opportunities for the development of surgical simulators, their higher latencies, compared to what is necessary for real-time graphics and haptics, offer significant barriers to their use in interactive simulation environments. In this work, we propose solutions to this problem and demonstrate how a multimodal surgical simulation environment may be developed based on NVIDIA's PhysX physics library. Hence, models that are undergoing relatively low-frequency updates in PhysX can exist in an environment that demands much higher frequency updates for haptics. We use a collision handling layer to interface between the physical response provided by PhysX and the haptic rendering device to provide both real-time tissue response and force feedback. Our simulator integrates a bimanual haptic interface for force feedback and per-pixel shaders for graphics realism in real time. To demonstrate the effectiveness of our approach, we present the simulation of the laparoscopic adjustable gastric banding (LAGB) procedure as a case study. To develop complex and realistic surgical trainers with realistic organ geometries and tissue properties demands stable physics-based deformation methods, which are not always compatible with the interaction level required for such trainers. We have shown that combining different modelling strategies for behaviour, collision and graphics is possible and desirable. Such multimodal environments enable suitable rates to simulate the major steps of the LAGB procedure.

Simulation tools for robotics research and assessment

NASA Astrophysics Data System (ADS)

Fields, MaryAnne; Brewer, Ralph; Edge, Harris L.; Pusey, Jason L.; Weller, Ed; Patel, Dilip G.; DiBerardino, Charles A.

2016-05-01

The Robotics Collaborative Technology Alliance (RCTA) program focuses on four overlapping technology areas: Perception, Intelligence, Human-Robot Interaction (HRI), and Dexterous Manipulation and Unique Mobility (DMUM). In addition, the RCTA program has a requirement to assess progress of this research in standalone as well as integrated form. Since the research is evolving and the robotic platforms with unique mobility and dexterous manipulation are in the early development stage and very expensive, an alternate approach is needed for efficient assessment. Simulation of robotic systems, platforms, sensors, and algorithms, is an attractive alternative to expensive field-based testing. Simulation can provide insight during development and debugging unavailable by many other means. This paper explores the maturity of robotic simulation systems for applications to real-world problems in robotic systems research. Open source (such as Gazebo and Moby), commercial (Simulink, Actin, LMS), government (ANVEL/VANE), and the RCTA-developed RIVET simulation environments are examined with respect to their application in the robotic research domains of Perception, Intelligence, HRI, and DMUM. Tradeoffs for applications to representative problems from each domain are presented, along with known deficiencies and disadvantages. In particular, no single robotic simulation environment adequately covers the needs of the robotic researcher in all of the domains. Simulation for DMUM poses unique constraints on the development of physics-based computational models of the robot, the environment and objects within the environment, and the interactions between them. Most current robot simulations focus on quasi-static systems, but dynamic robotic motion places an increased emphasis on the accuracy of the computational models. In order to understand the interaction of dynamic multi-body systems, such as limbed robots, with the environment, it may be necessary to build component-level computational models to provide the necessary simulation fidelity for accuracy. However, the Perception domain remains the most problematic for adequate simulation performance due to the often cartoon nature of computer rendering and the inability to model realistic electromagnetic radiation effects, such as multiple reflections, in real-time.

What Gene-Environment Interactions Can Tell Us about Social Competence in Typical and Atypical Populations

ERIC Educational Resources Information Center

Iarocci, Grace; Yager, Jodi; Elfers, Theo

2007-01-01

Social competence is a complex human behaviour that is likely to involve a system of genes that interacts with a myriad of environmental risk and protective factors. The search for its genetic and environmental origins and influences is equally complex and will require a multidimensional conceptualization and multiple methods and levels of…

Host genotype and age shape the leaf and root microbiomes of a wild perennial plant

DOE PAGES

Wagner, Maggie R.; Lundberg, Derek S.; del Rio, Tijana G.; ...

2016-07-12

Bacteria living on and in leaves and roots influence many aspects of plant health, so the extent of a plant's genetic control over its microbiota is of great interest to crop breeders and evolutionary biologists. Laboratory-based studies, because they poorly simulate true environmental heterogeneity, may misestimate or totally miss the influence of certain host genes on the microbiome. Here we report a large-scale field experiment to disentangle the effects of genotype, environment, age and year of harvest on bacterial communities associated with leaves and roots of Boechera stricta (Brassicaceae), a perennial wild mustard. Host genetic control of the microbiome ismore » evident in leaves but not roots, and varies substantially among sites. Microbiome composition also shifts as plants age. Furthermore, a large proportion of leaf bacterial groups are shared with roots, suggesting inoculation from soil. Our results demonstrate how genotype-by-environment interactions contribute to the complexity of microbiome assembly in natural environments.« less

Original BPC3 Research Plan

Cancer.gov

The Breast and Prostate Cancer and Hormone-Related Gene Variant Study allows large-scale analyses of breast and prostate cancer risk in relation to genetic polymorphisms and gene-environment interactions that affect hormone metabolism.

MAOA genotype, social exclusion and aggression: an experimental test of a gene-environment interaction.

PubMed

Gallardo-Pujol, D; Andrés-Pueyo, A; Maydeu-Olivares, A

2013-02-01

In 2002, Caspi and colleagues provided the first epidemiological evidence that genotype may moderate individuals' responses to environmental determinants. However, in a correlational study great care must be taken to ensure the proper estimation of the causal relationship. Here, a randomized experiment was performed to test the hypothesis that the MAOA gene promoter polymorphism (MAOA-LPR) interacts with environmental adversity in determining aggressive behavior using laboratory analogs of real-life conditions. A sample of 57 Caucasian male students of Catalan and Spanish origin was recruited at the University of Barcelona. Ostracism, or social exclusion, was induced as environmental adversity using the Cyberball software. Laboratory aggression was assessed with the Point Subtraction Aggression Paradigm (PSAP), which was used as an analog of antisocial behavior. We also measured aggressiveness by means of the reduced version of the Aggression Questionnaire. The MAOA-LPR polymorphism showed a significant effect on the number of aggressive responses in the PSAP (F(1,53) = 4.63, P = 0.03, partial η(2) = 0.08), as well as social exclusion (F(1,53) = 8.03, P = 0.01, partial η(2) = 0.13). Most notably, however, we found that the MAOA-LPR polymorphism interacts significantly with social exclusion in order to provoke aggressive behavior (F(1,53) = 4.42, P = 0.04, partial η(2) = 0.08), remarkably, the low-activity allele of the MAOA-LPR polymorphism carriers in the ostracized group show significantly higher aggression scores than the rest. Our results support the notion that gene-environment interactions can be successfully reproduced within a laboratory using analogs and an appropriate design. We provide guidelines to test gene-environment interactions hypotheses under controlled, experimental settings. © 2012 The Authors. Genes, Brain and Behavior © 2012 Blackwell Publishing Ltd and International Behavioural and Neural Genetics Society.

MAOA, childhood maltreatment and antisocial behavior: Meta-analysis of a gene-environment interaction

PubMed Central

Byrd, Amy L.; Manuck, Stephen B.

2013-01-01

Background In a seminal study of gene-environment interaction, childhood maltreatment predicted antisocial behavior more strongly in males carrying an MAOA promoter variant of lesser, compared to higher, transcriptional efficiency. Many further investigations have been reported, including studies of other early environmental exposures and females. Here we report a meta-analysis of studies testing the interaction of MAOA genotype and childhood adversities on antisocial outcomes in predominantly non-clinical samples. Method Included were 27 peer-reviewed, English-language studies published through August, 2012, that contained indicators of maltreatment or “other” family (e.g., parenting, sociodemographic) hardships; MAOA genotype; indices of aggressive and antisocial behavior; and statistical test of genotype-environment interaction. Studies of forensic and exclusively clinical samples, clinical cohorts lacking proportionally matched controls, or outcomes non-specific for antisocial behavior were excluded. The Liptak-Stouffer weighted Z-test for meta-analysis was implemented to maximize study inclusion and calculated separately for male and female cohorts. Results Across 20 male cohorts, early adversity presaged antisocial outcomes more strongly for low, relative to high, activity MAOA genotype (P=.0044). Stratified analyses showed the interaction specific to maltreatment (P=.0000008) and robust to several sensitivity analyses. Across 11 female cohorts, MAOA did not interact with combined early life adversities, whereas maltreatment alone predicted antisocial behaviors preferentially, but weakly, in females of high activity MAOA genotype (P=.02). Conclusions We found common regulatory variation in MAOA to moderate effects of childhood maltreatment on male antisocial behaviors, confirming a sentinel finding in research on gene-environment interaction. An analogous, but less consistent, finding in females warrants further investigation. PMID:23786983

MAOA, childhood maltreatment, and antisocial behavior: meta-analysis of a gene-environment interaction.

PubMed

Byrd, Amy L; Manuck, Stephen B

2014-01-01

In a seminal study of gene-environment interaction, childhood maltreatment predicted antisocial behavior more strongly in male subjects carrying an MAOA promoter variant of lesser, compared with higher, transcriptional efficiency. Many further investigations have been reported, including studies of other early environmental exposures and female subjects. Here, we report a meta-analysis of studies testing the interaction of MAOA genotype and childhood adversities on antisocial outcomes in predominantly nonclinical samples. Included were 27 peer-reviewed, English-language studies published through August, 2012, that contained indicators of maltreatment or other family (e.g., parenting, sociodemographic) hardships; MAOA genotype; indices of aggressive and antisocial behavior; and statistical test of genotype-environment interaction. Studies of forensic and exclusively clinical samples, clinical cohorts lacking proportionally matched control subjects, or outcomes nonspecific for antisocial behavior were excluded. The Liptak-Stouffer weighted Z-test for meta-analysis was implemented to maximize study inclusion and calculated separately for male and female cohorts. Across 20 male cohorts, early adversity presaged antisocial outcomes more strongly for low-activity, relative to high- activity, MAOA genotype (p = .0044). Stratified analyses showed the interaction specific to maltreatment (p = .00000082) and robust to several sensitivity analyses. Across 11 female cohorts, MAOA did not interact with combined early life adversities, whereas maltreatment alone predicted antisocial behaviors preferentially, but weakly, in female subjects of high-activity MAOA genotype (p = .02). We found common regulatory variation in MAOA to moderate effects of childhood maltreatment on male antisocial behaviors, confirming a sentinel finding in research on gene-environment interaction. An analogous, but less consistent, finding in female subjects warrants further investigation. Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

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

PubMed

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.

How Genes and the Social Environment Moderate Each Other

PubMed Central

Leve, Leslie D.; Neiderhiser, Jenae M.

2013-01-01

Recent research has suggested that the social environment can moderate the expression of genetic influences on health and that genetic influences can shape an individual’s sensitivity to the social environment. Evidence supports 4 major mechanisms: genes can influence an individual’s response to environmental stress, genes may enhance an individual’s sensitivity to both favorable and adverse environments, inherited characteristics may better fit with some environments than with others, and inherited capabilities may only become manifest in challenging or responsive environments. Further progress depends on better recognition of patterns of gene–environment interaction, improved methods of assessing the environment and its impact on genetic mechanisms, the use of appropriately designed laboratory studies, identification of heritable differences in an individual before environmental moderation occurs, and clarification of the timing of the impact of social and genetic moderation. PMID:23927504

Quantitative Modeling of Human-Environment Interactions in Preindustrial Time

NASA Astrophysics Data System (ADS)

Sommer, Philipp S.; Kaplan, Jed O.

2017-04-01

Quantifying human-environment interactions and anthropogenic influences on the environment prior to the Industrial revolution is essential for understanding the current state of the earth system. This is particularly true for the terrestrial biosphere, but marine ecosystems and even climate were likely modified by human activities centuries to millennia ago. Direct observations are however very sparse in space and time, especially as one considers prehistory. Numerical models are therefore essential to produce a continuous picture of human-environment interactions in the past. Agent-based approaches, while widely applied to quantifying human influence on the environment in localized studies, are unsuitable for global spatial domains and Holocene timescales because of computational demands and large parameter uncertainty. Here we outline a new paradigm for the quantitative modeling of human-environment interactions in preindustrial time that is adapted to the global Holocene. Rather than attempting to simulate agency directly, the model is informed by a suite of characteristics describing those things about society that cannot be predicted on the basis of environment, e.g., diet, presence of agriculture, or range of animals exploited. These categorical data are combined with the properties of the physical environment in coupled human-environment model. The model is, at its core, a dynamic global vegetation model with a module for simulating crop growth that is adapted for preindustrial agriculture. This allows us to simulate yield and calories for feeding both humans and their domesticated animals. We couple this basic caloric availability with a simple demographic model to calculate potential population, and, constrained by labor requirements and land limitations, we create scenarios of land use and land cover on a moderate-resolution grid. We further implement a feedback loop where anthropogenic activities lead to changes in the properties of the physical environment, e.g., through soil erosion.

Prevention of asthma: where are we in the 21st century?

PubMed

Propp, Phaedra; Becker, Allan

2013-12-01

Asthma is the most common chronic disease of childhood and, in the latter part of the 20th century, reached epidemic proportions. Asthma is generally believed to result from gene-environment interactions. There is consensus that a 'window of opportunity' exists during pregnancy and early in life when environmental factors may influence its development. We review multiple environmental, biologic and sociologic factors that may be important in the development of asthma. Meta-analyses of studies have demonstrated that multifaceted interventions are required in order to develop asthma prevention. Multifaceted allergen reduction studies have shown clinical benefits. Asthma represents a dysfunctional interaction with our genes and the environment to which they are exposed, especially in fetal and early infant life. The increasing prevalence of asthma also may be an indication of increased population risk for the development of other chronic non-communicable autoimmune diseases. This review will focus on the factors which may be important in the primary prevention of asthma. Better understanding of the complex gene-environment interactions involved in the development of asthma will provide insight into personalized interventions for asthma prevention.

A new approach in the design of an interactive environment for teaching Hamiltonian digraphs

NASA Astrophysics Data System (ADS)

Iordan, A. E.; Panoiu, M.

2014-03-01

In this article the authors present the necessary steps in object orientated design of an interactive environment that is dedicated to the process of acquaintances assimilation in Hamiltonian graphs theory domain, especially for the simulation of algorithms which determine the Hamiltonian trails and circuits. The modelling of the interactive environment is achieved through specific UML diagrams representing the steps of analysis, design and implementation. This interactive environment is very useful for both students and professors, because computer programming domain, especially digraphs theory domain is comprehended and assimilated with difficulty by students.

Novel Web-based Education Platforms for Information Communication utilizing Gamification, Virtual and Immersive Reality

NASA Astrophysics Data System (ADS)

Demir, I.

2015-12-01

Recent developments in internet technologies make it possible to manage and visualize large data on the web. Novel visualization techniques and interactive user interfaces allow users to create realistic environments, and interact with data to gain insight from simulations and environmental observations. This presentation showcase information communication interfaces, games, and virtual and immersive reality applications for supporting teaching and learning of concepts in atmospheric and hydrological sciences. The information communication platforms utilizes latest web technologies and allow accessing and visualizing large scale data on the web. The simulation system is a web-based 3D interactive learning environment for teaching hydrological and atmospheric processes and concepts. The simulation systems provides a visually striking platform with realistic terrain and weather information, and water simulation. The web-based simulation system provides an environment for students to learn about the earth science processes, and effects of development and human activity on the terrain. Users can access the system in three visualization modes including virtual reality, augmented reality, and immersive reality using heads-up display. The system provides various scenarios customized to fit the age and education level of various users.

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

PubMed Central

2011-01-01

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 reared at the cooler temperature (23°C), exhibited significant levels of additive genetic variance. Conclusions Our results show that the genetics underlying phenotypic expression can be complex, context-dependent and different in each of the sexes. We discuss the implications of these results, particularly in terms of the evolutionary processes that hinge on good and compatible genes models. PMID:21791118

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

PubMed

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.

Allelic-based gene-gene interaction associated with quantitative traits.

PubMed

Jung, Jeesun; Sun, Bin; Kwon, Deukwoo; Koller, Daniel L; Foroud, Tatiana M

2009-05-01

Recent studies have shown that quantitative phenotypes may be influenced not only by multiple single nucleotide polymorphisms (SNPs) within a gene but also by the interaction between SNPs at unlinked genes. We propose a new statistical approach that can detect gene-gene interactions at the allelic level which contribute to the phenotypic variation in a quantitative trait. By testing for the association of allelic combinations at multiple unlinked loci with a quantitative trait, we can detect the SNP allelic interaction whether or not it can be detected as a main effect. Our proposed method assigns a score to unrelated subjects according to their allelic combination inferred from observed genotypes at two or more unlinked SNPs, and then tests for the association of the allelic score with a quantitative trait. To investigate the statistical properties of the proposed method, we performed a simulation study to estimate type I error rates and power and demonstrated that this allelic approach achieves greater power than the more commonly used genotypic approach to test for gene-gene interaction. As an example, the proposed method was applied to data obtained as part of a candidate gene study of sodium retention by the kidney. We found that this method detects an interaction between the calcium-sensing receptor gene (CaSR), the chloride channel gene (CLCNKB) and the Na, K, 2Cl cotransporter gene (CLC12A1) that contributes to variation in diastolic blood pressure.

Differential susceptibility to maternal expressed emotion in children with ADHD and their siblings? Investigating plasticity genes, prosocial and antisocial behaviour.

PubMed

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

2015-02-01

The differential susceptibility theory states that children differ in their susceptibility towards environmental experiences, partially due to plasticity genes. Individuals carrying specific variants in such genes will be more disadvantaged in negative but, conversely, more advantaged in positive environments. Understanding gene-environment interactions may help unravel the causal mechanisms involved in multifactorial psychiatric disorders such as Attention-Deficit/Hyperactivity Disorder (ADHD). The differential susceptibility theory was examined by investigating the presence of interaction effects between maternal expressed emotion (EE; warmth and criticism) and the solitary and combined effects of plasticity genes (DAT1, DRD4, 5-HTT) on prosocial and antisocial behaviour (measured with parent- and self-reports) in children with ADHD and their siblings (N = 366, M = 17.11 years, 74.9% male). Maternal warmth was positively associated with prosocial behaviour and negatively with antisocial behaviour, while maternal criticism was positively associated with antisocial behaviour and negatively with prosocial behaviour. No evidence of differential susceptibility was found. The current study found no evidence for differential susceptibility based on the selected plasticity genes, in spite of strong EE-behaviour associations. It is likely that additional factors play a role in the complex relationship between genes, environment and behaviour.

Differential Susceptibility to Maternal Expressed Emotion in Children with ADHD and their Siblings? Investigating Plasticity Genes, Prosocial and Antisocial Behaviour

PubMed Central

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

2014-01-01

Background The differential susceptibility theory states that children differ in their susceptibility towards environmental experiences, partially due to plasticity genes. Individuals carrying specific variants in such genes will be more disadvantaged in negative but, conversely, more advantageous in positive environments. Understanding gene-environment interactions may help unravel the causal mechanisms involved in multifactorial psychiatric disorders such as Attention-Deficit/Hyperactivity Disorder (ADHD). Methods The differential susceptibility theory was examined by investigating the presence of interaction effects between maternal expressed emotion (EE; warmth and criticism) and the solitary and combined effects of plasticity genes (DAT1, DRD4, 5-HTT) on prosocial and antisocial behaviour (measured with parent- and self-reports) in children with ADHD and their siblings (N=366, M=17.11 years, 74.9 % male). Results Maternal warmth was positively associated with prosocial behaviour and negatively with antisocial behaviour, while maternal criticism was positively associated with antisocial behaviour and negatively with prosocial behaviour. No evidence of differential susceptibility was found. Conclusions The current study found no evidence for differential susceptibility based on the selected plasticity genes, in spite of strong EE-behaviour associations. It is likely that additional factors play a role in the complex relationship between genes, environment and behaviour. PMID:24929324

The Effects of an Energy-Environment Simulator Upon Selected Energy-Related Attitudes of Science Students and In-Service Teachers.

ERIC Educational Resources Information Center

Dunlop, David L.

This document is the outcome of a study designed to investigate the energy-related attitudes of several different groups of science students and science teachers both before and after working with an energy-environment simulator for approximately an hour. During the interaction with the simulator, the participants decided upon the variables they…

Differential network analysis reveals the genome-wide landscape of estrogen receptor modulation in hormonal cancers

PubMed Central

Hsiao, Tzu-Hung; Chiu, Yu-Chiao; Hsu, Pei-Yin; Lu, Tzu-Pin; Lai, Liang-Chuan; Tsai, Mong-Hsun; Huang, Tim H.-M.; Chuang, Eric Y.; Chen, Yidong

2016-01-01

Several mutual information (MI)-based algorithms have been developed to identify dynamic gene-gene and function-function interactions governed by key modulators (genes, proteins, etc.). Due to intensive computation, however, these methods rely heavily on prior knowledge and are limited in genome-wide analysis. We present the modulated gene/gene set interaction (MAGIC) analysis to systematically identify genome-wide modulation of interaction networks. Based on a novel statistical test employing conjugate Fisher transformations of correlation coefficients, MAGIC features fast computation and adaption to variations of clinical cohorts. In simulated datasets MAGIC achieved greatly improved computation efficiency and overall superior performance than the MI-based method. We applied MAGIC to construct the estrogen receptor (ER) modulated gene and gene set (representing biological function) interaction networks in breast cancer. Several novel interaction hubs and functional interactions were discovered. ER+ dependent interaction between TGFβ and NFκB was further shown to be associated with patient survival. The findings were verified in independent datasets. Using MAGIC, we also assessed the essential roles of ER modulation in another hormonal cancer, ovarian cancer. Overall, MAGIC is a systematic framework for comprehensively identifying and constructing the modulated interaction networks in a whole-genome landscape. MATLAB implementation of MAGIC is available for academic uses at https://github.com/chiuyc/MAGIC. PMID:26972162

Genetics of borderline personality disorder: systematic review and proposal of an integrative model.

PubMed

Amad, Ali; Ramoz, Nicolas; Thomas, Pierre; Jardri, Renaud; Gorwood, Philip

2014-03-01

Borderline personality disorder (BPD) is one of the most common mental disorders and is characterized by a pervasive pattern of emotional lability, impulsivity, interpersonal difficulties, identity disturbances, and disturbed cognition. Here, we performed a systematic review of the literature concerning the genetics of BPD, including familial and twin studies, association studies, and gene-environment interaction studies. Moreover, meta-analyses were performed when at least two case-control studies testing the same polymorphism were available. For each gene variant, a pooled odds ratio (OR) was calculated using fixed or random effects models. Familial and twin studies largely support the potential role of a genetic vulnerability at the root of BPD, with an estimated heritability of approximately 40%. Moreover, there is evidence for both gene-environment interactions and correlations. However, association studies for BPD are sparse, making it difficult to draw clear conclusions. According to our meta-analysis, no significant associations were found for the serotonin transporter gene, the tryptophan hydroxylase 1 gene, or the serotonin 1B receptor gene. We hypothesize that such a discrepancy (negative association studies but high heritability of the disorder) could be understandable through a paradigm shift, in which "plasticity" genes (rather than "vulnerability" genes) would be involved. Such a framework postulates a balance between positive and negative events, which interact with plasticity genes in the genesis of BPD. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

PubMed

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-Diet Interactions in Childhood Obesity

PubMed Central

Garver, William S

2011-01-01

Childhood overweight and obesity have reached epidemic proportions worldwide, and the increase in weight-associated co-morbidities including premature type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease will soon become major healthcare and economic problems. A number of studies now indicate that the childhood obesity epidemic which has emerged during the past 30 years is a complex multi-factorial disease resulting from interaction of susceptibility genes with an obesogenic environment. This review will focus on gene-diet interactions suspected of having a prominent role in promoting childhood obesity. In particular, the specific genes that will be presented (FTO, MC4R, and NPC1) have recently been associated with childhood obesity through a genome-wide association study (GWAS) and were shown to interact with nutritional components to increase weight gain. Although a fourth gene (APOA2) has not yet been associated with childhood obesity, this review will also present information on what now represents the best characterized gene-diet interaction in promoting weight gain. PMID:22043166

D-VASim: an interactive virtual laboratory environment for the simulation and analysis of genetic circuits.

PubMed

Baig, Hasan; Madsen, Jan

2017-01-15

Simulation and behavioral analysis of genetic circuits is a standard approach of functional verification prior to their physical implementation. Many software tools have been developed to perform in silico analysis for this purpose, but none of them allow users to interact with the model during runtime. The runtime interaction gives the user a feeling of being in the lab performing a real world experiment. In this work, we present a user-friendly software tool named D-VASim (Dynamic Virtual Analyzer and Simulator), which provides a virtual laboratory environment to simulate and analyze the behavior of genetic logic circuit models represented in an SBML (Systems Biology Markup Language). Hence, SBML models developed in other software environments can be analyzed and simulated in D-VASim. D-VASim offers deterministic as well as stochastic simulation; and differs from other software tools by being able to extract and validate the Boolean logic from the SBML model. D-VASim is also capable of analyzing the threshold value and propagation delay of a genetic circuit model. D-VASim is available for Windows and Mac OS and can be downloaded from bda.compute.dtu.dk/downloads/. haba@dtu.dk, jama@dtu.dk. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Reaction norm model with unknown environmental covariate to analyze heterosis by environment interaction.

PubMed

Su, G; Madsen, P; Lund, M S

2009-05-01

Crossbreeding is currently increasing in dairy cattle production. Several studies have shown an environment-dependent heterosis [i.e., an interaction between heterosis and environment (H x E)]. An H x E interaction is usually estimated from a few discrete environment levels. The present study proposes a reaction norm model to describe H x E interaction, which can deal with a large number of environment levels using few parameters. In the proposed model, total heterosis consists of an environment-independent part, which is described as a function of heterozygosity, and an environment-dependent part, which is described as a function of heterozygosity and environmental value (e.g., herd-year effect). A Bayesian approach is developed to estimate the environmental covariates, the regression coefficients of the reaction norm, and other parameters of the model simultaneously in both linear and nonlinear reaction norms. In the nonlinear reaction norm model, the H x E is approximated using linear splines. The approach was tested using simulated data, which were generated using an animal model with a reaction norm for heterosis. The simulation study includes 4 scenarios (the combinations of moderate vs. low heritability and moderate vs. low herd-year variation) of H x E interaction in a nonlinear form. In all scenarios, the proposed model predicted total heterosis very well. The correlation between true heterosis and predicted heterosis was 0.98 in the scenarios with low herd-year variation and 0.99 in the scenarios with moderate herd-year variation. This suggests that the proposed model and method could be a good approach to analyze H x E interactions and predict breeding values in situations in which heterosis changes gradually and continuously over an environmental gradient. On the other hand, it was found that a model ignoring H x E interaction did not significantly harm the prediction of breeding value under the simulated scenarios in which the variance for environment-dependent heterosis effects was small (as it generally is), and sires were randomly used over production environments.

Rule-Based Simulation of Multi-Cellular Biological Systems—A Review of Modeling Techniques

PubMed Central

Hwang, Minki; Garbey, Marc; Berceli, Scott A.; Tran-Son-Tay, Roger

2011-01-01

Emergent behaviors of multi-cellular biological systems (MCBS) result from the behaviors of each individual cells and their interactions with other cells and with the environment. Modeling MCBS requires incorporating these complex interactions among the individual cells and the environment. Modeling approaches for MCBS can be grouped into two categories: continuum models and cell-based models. Continuum models usually take the form of partial differential equations, and the model equations provide insight into the relationship among the components in the system. Cell-based models simulate each individual cell behavior and interactions among them enabling the observation of the emergent system behavior. This review focuses on the cell-based models of MCBS, and especially, the technical aspect of the rule-based simulation method for MCBS is reviewed. How to implement the cell behaviors and the interactions with other cells and with the environment into the computational domain is discussed. The cell behaviors reviewed in this paper are division, migration, apoptosis/necrosis, and differentiation. The environmental factors such as extracellular matrix, chemicals, microvasculature, and forces are also discussed. Application examples of these cell behaviors and interactions are presented. PMID:21369345

Advances in asthma and allergy genetics in 2007.

PubMed

Vercelli, Donata

2008-08-01

This review discusses the main advances in the genetics of asthma and allergy published in the Journal in 2007. The association studies discussed herein addressed 3 main topics: the effect of the environment and gene-environment interactions on asthma/allergy susceptibility, the contribution of T(H)2 immunity gene variants to allergic inflammation, and the role of filaggrin mutations in atopic dermatitis and associated phenotypes. Other articles revealed novel, potentially important candidate genes or confirmed known ones. Collectively, the works published in 2007 reiterate that allergy and asthma are typical complex diseases; that is, they are disorders in which intricate interactions among environmental and genetic factors modify disease susceptibility by altering the fundamental structural and functional properties of target organs at critical developmental windows.

Functional regression method for whole genome eQTL epistasis analysis with sequencing data.

PubMed

Xu, Kelin; Jin, Li; Xiong, Momiao

2017-05-18

Epistasis plays an essential rule in understanding the regulation mechanisms and is an essential component of the genetic architecture of the gene expressions. However, interaction analysis of gene expressions remains fundamentally unexplored due to great computational challenges and data availability. Due to variation in splicing, transcription start sites, polyadenylation sites, post-transcriptional RNA editing across the entire gene, and transcription rates of the cells, RNA-seq measurements generate large expression variability and collectively create the observed position level read count curves. A single number for measuring gene expression which is widely used for microarray measured gene expression analysis is highly unlikely to sufficiently account for large expression variation across the gene. Simultaneously analyzing epistatic architecture using the RNA-seq and whole genome sequencing (WGS) data poses enormous challenges. We develop a nonlinear functional regression model (FRGM) with functional responses where the position-level read counts within a gene are taken as a function of genomic position, and functional predictors where genotype profiles are viewed as a function of genomic position, for epistasis analysis with RNA-seq data. Instead of testing the interaction of all possible pair-wises SNPs, the FRGM takes a gene as a basic unit for epistasis analysis, which tests for the interaction of all possible pairs of genes and use all the information that can be accessed to collectively test interaction between all possible pairs of SNPs within two genome regions. By large-scale simulations, we demonstrate that the proposed FRGM for epistasis analysis can achieve the correct type 1 error and has higher power to detect the interactions between genes than the existing methods. The proposed methods are applied to the RNA-seq and WGS data from the 1000 Genome Project. The numbers of pairs of significantly interacting genes after Bonferroni correction identified using FRGM, RPKM and DESeq were 16,2361, 260 and 51, respectively, from the 350 European samples. The proposed FRGM for epistasis analysis of RNA-seq can capture isoform and position-level information and will have a broad application. Both simulations and real data analysis highlight the potential for the FRGM to be a good choice of the epistatic analysis with sequencing data.

Interactions between genetic variation and cellular environment in skeletal muscle gene expression.

PubMed

Taylor, D Leland; Knowles, David A; Scott, Laura J; Ramirez, Andrea H; Casale, Francesco Paolo; Wolford, Brooke N; Guan, Li; Varshney, Arushi; Albanus, Ricardo D'Oliveira; Parker, Stephen C J; Narisu, Narisu; Chines, Peter S; Erdos, Michael R; Welch, Ryan P; Kinnunen, Leena; Saramies, Jouko; Sundvall, Jouko; Lakka, Timo A; Laakso, Markku; Tuomilehto, Jaakko; Koistinen, Heikki A; Stegle, Oliver; Boehnke, Michael; Birney, Ewan; Collins, Francis S

2018-01-01

From whole organisms to individual cells, responses to environmental conditions are influenced by genetic makeup, where the effect of genetic variation on a trait depends on the environmental context. RNA-sequencing quantifies gene expression as a molecular trait, and is capable of capturing both genetic and environmental effects. In this study, we explore opportunities of using allele-specific expression (ASE) to discover cis-acting genotype-environment interactions (GxE)-genetic effects on gene expression that depend on an environmental condition. Treating 17 common, clinical traits as approximations of the cellular environment of 267 skeletal muscle biopsies, we identify 10 candidate environmental response expression quantitative trait loci (reQTLs) across 6 traits (12 unique gene-environment trait pairs; 10% FDR per trait) including sex, systolic blood pressure, and low-density lipoprotein cholesterol. Although using ASE is in principle a promising approach to detect GxE effects, replication of such signals can be challenging as validation requires harmonization of environmental traits across cohorts and a sufficient sampling of heterozygotes for a transcribed SNP. Comprehensive discovery and replication will require large human transcriptome datasets, or the integration of multiple transcribed SNPs, coupled with standardized clinical phenotyping.

Molecular recognition of avirulence protein (avrxa5) by eukaryotic transcription factor xa5 of rice (Oryza sativa L.): insights from molecular dynamics simulations.

PubMed

Dehury, Budheswar; Maharana, Jitendra; Sahoo, Bikash Ranjan; Sahu, Jagajjit; Sen, Priyabrata; Modi, Mahendra Kumar; Barooah, Madhumita

2015-04-01

The avirulence gene avrxa5 of bacterial blight pathogen Xanthomonas oryzae pv. oryzae (Xoo) recognized by the resistant rice lines having corresponding resistance (xa5) gene in a gene-for-gene manner. We used a combinatorial approach involving protein-protein docking, molecular dynamics (MD) simulations and binding free energy calculations to gain novel insights into the gene-for-gene mechanism that governs the direct interaction of R-Avr protein. From the best three binding poses predicted by molecular docking, MD simulations were performed to explore the dynamic binding mechanism of xa5 and avrxa5. Molecular Mechanics/Poisson Boltzmann Surface Area (MM/PBSA) techniques were employed to calculate the binding free energy and to uncover the thriving force behind the molecular recognition of avrxa5 by eukaryotic transcription factor xa5. Binding free energy analysis revealed van der Waals term as the most constructive component that favors the xa5 and avrxa5 interaction. In addition, hydrogen bonds (H-bonds) and essential electrostatic interactions analysis highlighted amino acid residues Lys54/Asp870, Lys56/Ala868, Lys56/Ala866, Lys56/Glu871, Ile59/His862, Gly61/Phe858, His62/Arg841, His62/Leu856, Ser101/Ala872 and Ser105/Asp870 plays pivotal role for the energetically stability of the R-Avr complex. Insights gained from the present study are expected to unveil the molecular mechanisms that define the transcriptional activator mediated transcriptome modification in host plants. Copyright © 2015 Elsevier Inc. All rights reserved.

Finding gene-environment interactions for phobias.

PubMed

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.

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

PubMed

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.

Gene-environment interactions in the aetiology of systemic lupus erythematosus.

PubMed

Jönsen, Andreas; Bengtsson, Anders A; Nived, Ola; Truedsson, Lennart; Sturfelt, Gunnar

2007-12-01

Systemic lupus erythematosus (SLE) is a disease that displays a multitude of symptoms and a vast array of autoantibodies. The disease course may vary substantially between patients. The current understanding of SLE aetiology includes environmental factors acting on a genetically prone individual during an undetermined time period resulting in autoimmunity and finally surpassing that individual's disease threshold. Genetic differences and environmental factors may interact specifically in the pathogenetic processes and may influence disease development and modify the disease course. Identification of these factors and their interactions in the pathogenesis of SLE is vital in understanding the disease and may contribute to identify new treatment targets and perhaps also aid in disease prevention. However, there are several problems that need to be overcome, such as the protracted time frame of environmental influence, time dependent epigenetic alterations and the possibility that different pathogenetic pathways may result in a similar disease phenotype. This is mirrored by the relatively few studies that suggest specific gene-environment interactions. These include an association between SLE diagnosis and glutation S-transferase gene variants combined with occupational sun exposure as well as variants of the N-acetyl transferase gene in combination with either aromatic amine exposure or hydralazine. With increased knowledge on SLE pathogenesis, the role of environmental factors and their genetic interactions may be further elucidated.

PROP taster status interacts with the built environment to influence children's food acceptance and body weight status.

PubMed

Burd, Carlye; Senerat, Araliya; Chambers, Earle; Keller, Kathleen L

2013-04-01

Eating behaviors and obesity are complex phenotypes influenced by genes and the environment, but few studies have investigated the interaction of these two variables. The purpose of this study was to use a gene-environment interaction model to test for differences in children's food acceptance and body weights. Inherited ability to taste 6-n-propylthiouracil (PROP) was assessed as a marker of oral taste responsiveness. Food environment was classified as "healthy" or "unhealthy" based on proximity to outlets that sell fruits/vegetables and fast foods using Geographic Information Systems (GIS). The cohort consisted of 120 children, ages 4-6 years, recruited from New York City over 2005-2010. Home address and other demographic variables were reported by parents and PROP status, food acceptance, and anthropometrics were assessed in the laboratory. Based on a screening test, children were classified as PROP tasters or non-tasters. Hierarchical linear models analysis of variance was performed to examine differences in food acceptance and body mass index (BMI) z-scores as a function of PROP status, the food environment ("healthy" vs. "unhealthy"), and their interaction. Results showed an interaction between taster status and the food environment on BMI z-score and food acceptance. Non-taster children living in healthy food environments had greater acceptance of vegetables than taster children living in healthy food environments (P ≤ 0.005). Moreover, non-tasters from unhealthy food environments had higher BMI z-scores than all other groups (P ≤ 0.005). Incorporating genetic markers of taste into studies that assess the built environment may improve the ability of these measures to predict risk for obesity and eating behaviors. Copyright © 2012 The Obesity Society.

PROP taster status interacts with the built environment to influence children's food acceptance and body weight status

PubMed Central

Burd, Carlye; Senerat, Araliya; Chambers, Earle; Keller, Kathleen L.

2012-01-01

Eating behaviors and obesity are complex phenotypes influenced by genes and access to foods in the environment, but few studies have investigated the interaction of these two variables. The purpose of this study was to use a gene-environment interaction model to test for differences in children's food acceptance and body weights. Inherited ability to taste 6-n-propylthiouracil (PROP) was assessed as a marker of oral taste responsiveness. Food environment was classified as “healthy” or “unhealthy” based on proximity to outlets that sell fruits/vegetables and fast foods using Geographic Information Systems (GIS). The cohort consisted of 120 children, ages 4–6 years, recruited from New York City over 2005–2010. Home address and other demographic variables were reported by parents and PROP status, food acceptance, and anthropometrics were assessed in the laboratory. Based on a screening test, children were classified as PROP tasters or non-tasters. Hierarchical linear models analysis of variance was performed to examine differences in food acceptance and body mass index (BMI) z-scores as a function of PROP status, the food environment (“healthy” vs. “unhealthy”), and their interaction. Results showed an interaction between taster status and the food environment on BMI z-score and food acceptance. Non-taster children living in healthy food environments had greater acceptance of vegetables than taster children living in healthy food environments (p≤0.005). Moreover, non-tasters from unhealthy food environments had higher BMI z-scores than all other groups (p≤0.005). Incorporating genetic markers of taste into studies that assess the built environment may improve the ability of these measures to predict risk for obesity and eating behaviors. PMID:23401219

Genomic models with genotype × environment interaction for predicting hybrid performance: an application in maize hybrids.

PubMed

Acosta-Pech, Rocío; Crossa, José; de Los Campos, Gustavo; Teyssèdre, Simon; Claustres, Bruno; Pérez-Elizalde, Sergio; Pérez-Rodríguez, Paulino

2017-07-01

A new genomic model that incorporates genotype × environment interaction gave increased prediction accuracy of untested hybrid response for traits such as percent starch content, percent dry matter content and silage yield of maize hybrids. The prediction of hybrid performance (HP) is very important in agricultural breeding programs. In plant breeding, multi-environment trials play an important role in the selection of important traits, such as stability across environments, grain yield and pest resistance. Environmental conditions modulate gene expression causing genotype × environment interaction (G × E), such that the estimated genetic correlations of the performance of individual lines across environments summarize the joint action of genes and environmental conditions. This article proposes a genomic statistical model that incorporates G × E for general and specific combining ability for predicting the performance of hybrids in environments. The proposed model can also be applied to any other hybrid species with distinct parental pools. In this study, we evaluated the predictive ability of two HP prediction models using a cross-validation approach applied in extensive maize hybrid data, comprising 2724 hybrids derived from 507 dent lines and 24 flint lines, which were evaluated for three traits in 58 environments over 12 years; analyses were performed for each year. On average, genomic models that include the interaction of general and specific combining ability with environments have greater predictive ability than genomic models without interaction with environments (ranging from 12 to 22%, depending on the trait). We concluded that including G × E in the prediction of untested maize hybrids increases the accuracy of genomic models.

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

USDA-ARS?s Scientific Manuscript database

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,...

The COPD Knowledge Base: enabling data analysis and computational simulation in translational COPD research.

PubMed

Cano, Isaac; Tényi, Ákos; Schueller, Christine; Wolff, Martin; Huertas Migueláñez, M Mercedes; Gomez-Cabrero, David; Antczak, Philipp; Roca, Josep; Cascante, Marta; Falciani, Francesco; Maier, Dieter

2014-11-28

Previously we generated a chronic obstructive pulmonary disease (COPD) specific knowledge base (http://www.copdknowledgebase.eu) from clinical and experimental data, text-mining results and public databases. This knowledge base allowed the retrieval of specific molecular networks together with integrated clinical and experimental data. The COPDKB has now been extended to integrate over 40 public data sources on functional interaction (e.g. signal transduction, transcriptional regulation, protein-protein interaction, gene-disease association). In addition we integrated COPD-specific expression and co-morbidity networks connecting over 6 000 genes/proteins with physiological parameters and disease states. Three mathematical models describing different aspects of systemic effects of COPD were connected to clinical and experimental data. We have completely redesigned the technical architecture of the user interface and now provide html and web browser-based access and form-based searches. A network search enables the use of interconnecting information and the generation of disease-specific sub-networks from general knowledge. Integration with the Synergy-COPD Simulation Environment enables multi-scale integrated simulation of individual computational models while integration with a Clinical Decision Support System allows delivery into clinical practice. The COPD Knowledge Base is the only publicly available knowledge resource dedicated to COPD and combining genetic information with molecular, physiological and clinical data as well as mathematical modelling. Its integrated analysis functions provide overviews about clinical trends and connections while its semantically mapped content enables complex analysis approaches. We plan to further extend the COPDKB by offering it as a repository to publish and semantically integrate data from relevant clinical trials. The COPDKB is freely available after registration at http://www.copdknowledgebase.eu.

Gene-Environment Studies and Borderline Personality Disorder: A Review

PubMed Central

Carpenter, Ryan W.; Tomko, Rachel L.; Boomsma, Dorret I.

2014-01-01

We review recent gene-environment studies relevant to borderline personality disorder, including those focusing on impulsivity, emotion sensitivity, suicidal behavior, aggression and anger, and the borderline personality phenotype itself. Almost all the studies reviewed suffered from a number of methodological and statistical problems, limiting the conclusions that currently can be drawn. The best evidence to date supports a gene-environment correlation (rGE) model for borderline personality traits and a range of adverse life events, indicating that those at risk for BPD are also at increased risk for exposure to environments that may trigger BPD. We provide suggestions regarding future research on GxE interaction and rGE effects in borderline personality. PMID:23250817

Genetic susceptibility to family environment: BDNF Val66met and 5-HTTLPR influence depressive symptoms.

PubMed

Dalton, Elizabeth D; Hammen, Constance L; Najman, Jake M; Brennan, Patricia A

2014-12-01

Functional genetic polymorphisms associated with Brain-Derived Neurotrophic Factor (BDNF) and serotonin (5-HTTLPR) have demonstrated associations with depression in interaction with environmental stressors. In light of evidence for biological connections between BDNF and serotonin, it is prudent to consider genetic epistasis between variants in these genes in the development of depressive symptoms. The current study examined the effects of val66met, 5-HTTLPR, and family environment quality on youth depressive symptoms in adolescence and young adulthood in a longitudinal sample oversampled for maternal depression history. A differential susceptibility model was tested, comparing the effects of family environment on depression scores across different levels of a cumulative plasticity genotype, defined as presence of both, either, or neither plasticity alleles (defined here as val66met Met and 5-HTTLPR 'S'). Cumulative plasticity genotype interacted with family environment quality to predict depression among males and females at age 15. After age 15, however, the interaction of cumulative plasticity genotype and early family environment quality was only predictive of depression among females. Results supported a differential susceptibility model at age 15, such that plasticity allele presence was associated with more or less depressive symptoms depending on valence of the family environment, and a diathesis-stress model of gene-environment interaction after age 15. These findings, although preliminary because of the small sample size, support prior results indicating interactive effects of 5-HTTLPR, val66met, and environmental stress, and suggest that family environment may have a stronger influence on genetically susceptible women than men.

Interaction between Calpain 5, Peroxisome proliferator-activated receptor-gamma and Peroxisome proliferator-activated receptor-delta genes: a polygenic approach to obesity

PubMed Central

Sáez, María E; Grilo, Antonio; Morón, Francisco J; Manzano, Luis; Martínez-Larrad, María T; González-Pérez, Antonio; Serrano-Hernando, Javier; Ruiz, Agustín; Ramírez-Lorca, Reposo; Serrano-Ríos, Manuel

2008-01-01

Context Obesity is a multifactorial disorder, that is, a disease determined by the combined effect of genes and environment. In this context, polygenic approaches are needed. Objective To investigate the possibility of the existence of a crosstalk between the CALPAIN 10 homologue CALPAIN 5 and nuclear receptors of the peroxisome proliferator-activated receptors family. Design Cross-sectional, genetic association study and gene-gene interaction analysis. Subjects The study sample comprise 1953 individuals, 725 obese (defined as body mass index ≥ 30) and 1228 non obese subjects. Results In the monogenic analysis, only the peroxisome proliferator-activated receptor delta (PPARD) gene was associated with obesity (OR = 1.43 [1.04–1.97], p = 0.027). In addition, we have found a significant interaction between CAPN5 and PPARD genes (p = 0.038) that reduces the risk for obesity in a 55%. Conclusion Our results suggest that CAPN5 and PPARD gene products may also interact in vivo. PMID:18657264

Parallel-distributed mobile robot simulator

NASA Astrophysics Data System (ADS)

Okada, Hiroyuki; Sekiguchi, Minoru; Watanabe, Nobuo

1996-06-01

The aim of this project is to achieve an autonomous learning and growth function based on active interaction with the real world. It should also be able to autonomically acquire knowledge about the context in which jobs take place, and how the jobs are executed. This article describes a parallel distributed movable robot system simulator with an autonomous learning and growth function. The autonomous learning and growth function which we are proposing is characterized by its ability to learn and grow through interaction with the real world. When the movable robot interacts with the real world, the system compares the virtual environment simulation with the interaction result in the real world. The system then improves the virtual environment to match the real-world result more closely. This the system learns and grows. It is very important that such a simulation is time- realistic. The parallel distributed movable robot simulator was developed to simulate the space of a movable robot system with an autonomous learning and growth function. The simulator constructs a virtual space faithful to the real world and also integrates the interfaces between the user, the actual movable robot and the virtual movable robot. Using an ultrafast CG (computer graphics) system (FUJITSU AG series), time-realistic 3D CG is displayed.

The transcriptomic responses of the eastern oyster, Crassostrea virginica, to environmental conditions.

PubMed

Chapman, Robert W; Mancia, Annalaura; Beal, Marion; Veloso, Artur; Rathburn, Charles; Blair, Anne; Holland, A F; Warr, G W; Didinato, Guy; Sokolova, Inna M; Wirth, Edward F; Duffy, Edward; Sanger, Denise

2011-04-01

Understanding the mechanisms by which organisms adapt to environmental conditions is a fundamental question for ecology and evolution. In this study, we evaluate changes in gene expression of a marine mollusc, the eastern oyster Crassostrea virginica, associated with the physico-chemical conditions and the levels of metals and other contaminants in their environment. The results indicate that transcript signatures can effectively disentangle the complex interactive gene expression responses to the environment and are also capable of disentangling the complex dynamic effects of environmental factors on gene expression. In this context, the mapping of environment to gene and gene to environment is reciprocal and mutually reinforcing. In general, the response of transcripts to the environment is driven by major factors known to affect oyster physiology such as temperature, pH, salinity, and dissolved oxygen, with pollutant levels playing a relatively small role, at least within the range of concentrations found in the studied oyster habitats. Further, the two environmental factors that dominate these effects (temperature and pH) interact in a dynamic and nonlinear fashion to impact gene expression. Transcriptomic data obtained in our study provide insights into the mechanisms of physiological responses to temperature and pH in oysters that are consistent with the known effects of these factors on physiological functions of ectotherms and indicate important linkages between transcriptomics and physiological outcomes. Should these linkages hold in further studies and in other organisms, they may provide a novel integrated approach for assessing the impacts of climate change, ocean acidification and anthropogenic contaminants on aquatic organisms via relatively inexpensive microarray platforms. © 2011 Blackwell Publishing Ltd.

Does Parental Divorce Moderate the Heritability of Body Dissatisfaction? An Extension of Previous Gene-Environment Interaction Effects

PubMed Central

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

2015-01-01

Objective 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-report measure of body dissatisfaction. The primary aim of the present study was to examine whether these findings extend to a different dimension of body dissatisfaction, body image perceptions. Method Participants were 1,534 female twins from the Minnesota Twin Family Study, ages 16–20 years. The Body Rating Scale (BRS) was used to assess body image perceptions. Results 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 to the intact families. Discussion 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 x environment interactions using diverse measures. PMID:26314278

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

PubMed

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.

Gene-environment interaction involving recently identified colorectal cancer susceptibility loci

PubMed Central

Kantor, Elizabeth D.; Hutter, Carolyn M.; Minnier, Jessica; Berndt, Sonja I.; Brenner, Hermann; Caan, Bette J.; Campbell, Peter T.; Carlson, Christopher S.; Casey, Graham; Chan, Andrew T.; Chang-Claude, Jenny; Chanock, Stephen J.; Cotterchio, Michelle; Du, Mengmeng; Duggan, David; Fuchs, Charles S.; Giovannucci, Edward L.; Gong, Jian; Harrison, Tabitha A.; Hayes, Richard B.; Henderson, Brian E.; Hoffmeister, Michael; Hopper, John L.; Jenkins, Mark A.; Jiao, Shuo; Kolonel, Laurence N.; Le Marchand, Loic; Lemire, Mathieu; Ma, Jing; Newcomb, Polly A.; Ochs-Balcom, Heather M.; Pflugeisen, Bethann M.; Potter, John D.; Rudolph, Anja; Schoen, Robert E.; Seminara, Daniela; Slattery, Martha L.; Stelling, Deanna L.; Thomas, Fridtjof; Thornquist, Mark; Ulrich, Cornelia M.; Warnick, Greg S.; Zanke, Brent W.; Peters, Ulrike; Hsu, Li; White, Emily

2014-01-01

BACKGROUND Genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) that are associated with risk of colorectal cancer (CRC). Prior research has evaluated the presence of gene-environment interaction involving the first 10 identified susceptibility loci, but little work has been conducted on interaction involving SNPs at recently identified susceptibility loci, including: rs10911251, rs6691170, rs6687758, rs11903757, rs10936599, rs647161, rs1321311, rs719725, rs1665650, rs3824999, rs7136702, rs11169552, rs59336, rs3217810, rs4925386, and rs2423279. METHODS Data on 9160 cases and 9280 controls from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and Colon Cancer Family Registry (CCFR) were used to evaluate the presence of interaction involving the above-listed SNPs and sex, body mass index (BMI), alcohol consumption, smoking, aspirin use, post-menopausal hormone (PMH) use, as well as intake of dietary calcium, dietary fiber, dietary folate, red meat, processed meat, fruit, and vegetables. Interaction was evaluated using a fixed-effects meta-analysis of an efficient Empirical Bayes estimator, and permutation was used to account for multiple comparisons. RESULTS None of the permutation-adjusted p-values reached statistical significance. CONCLUSIONS The associations between recently identified genetic susceptibility loci and CRC are not strongly modified by sex, BMI, alcohol, smoking, aspirin, PMH use, and various dietary factors. IMPACT Results suggest no evidence of strong gene-environment interactions involving the recently identified 16 susceptibility loci for CRC taken one at a time. PMID:24994789

Detection and characterization of gene-gene and gene-environment interactions in common human diseases and complex clinical endpoints

EPA Science Inventory

Biological organisms are complex systems that dynamically integrate inputs from a multitude of physiological and environmental factors. Therefore, in addressing questions concerning the etiology of complex health outcomes, it is essential that the systemic nature of biology be ta...

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

USDA-ARS?s Scientific Manuscript database

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, MTNR1B-rs1...

Darwin's legacy II: why biology is not physics, or why it has taken a century to see the dependence of genes on the environment.

PubMed

Singh, Rama S

2015-01-01

Genes and environment make the organism. Darwin stood firm in his denial of any direct role of environment in the modification of heredity. His theory of evolution heralded two debates: one about the importance and adequacy of natural selection as the main mechanism of evolution, and the other about the role of genes versus environment in the modification of phenotype and evolution. Here, I provide an overview of the second debate and show that the reasons for the gene versus environment battle were twofold: first, there was confusion about the role of environment in modifying the inheritance of a trait versus the evolution of that trait, and second, there was misunderstanding about the meaning of environment and its interaction with genes in the production of phenotypes. It took nearly a century to see that environment does not directly affect the inheritance of a phenotype (i.e., its heredity), but it is nevertheless the primary mover of phenotypic evolution. Effects of genes and environment are not separate but interdependent. One cannot separate the effect of genes from that of environment, or nature from nurture. To answer the question posed in the title, it is partly because the 20th century has been a century of unending progress in genetics. But also because unlike physics, biology is not colorblind; progress in biology has often been delayed beyond the Kuhnian paradigm change due to built-in interest in negating the influence of environment. Those who are against evolution, of course, cannot be expected to understand the role of environment in evolution. Those for it, many biologists included, believing in the supremacy of genes empowers them by giving adaptation a solely gene-directed (self-driven) "teleological" interpretation.

A low Earth orbit molecular beam space simulation facility

NASA Technical Reports Server (NTRS)

Cross, J. B.

1984-01-01

A brief synopsis of the low Earth orbit (LEO) satellite environment is presented including neutral and ionic species. Two ground based atomic and molecular beam instruments are described which are capable of simulating the interaction of spacecraft surfaces with the LEO environment and detecting the results of these interactions. The first detects mass spectrometrically low level fluxes of reactively and nonreactively surface scattered species as a function of scattering angle and velocity while the second ultrahigh velocity (UHV) molecular beam, laser induced fluorescence apparatus is capable of measuring chemiluminescence produced by either gas phase or gas-surface interactions. A number of proposed experiments are described.

A membrane computing simulator of trans-hierarchical antibiotic resistance evolution dynamics in nested ecological compartments (ARES).

PubMed

Campos, Marcelino; Llorens, Carlos; Sempere, José M; Futami, Ricardo; Rodriguez, Irene; Carrasco, Purificación; Capilla, Rafael; Latorre, Amparo; Coque, Teresa M; Moya, Andres; Baquero, Fernando

2015-08-05

Antibiotic resistance is a major biomedical problem upon which public health systems demand solutions to construe the dynamics and epidemiological risk of resistant bacteria in anthropogenically-altered environments. The implementation of computable models with reciprocity within and between levels of biological organization (i.e. essential nesting) is central for studying antibiotic resistances. Antibiotic resistance is not just the result of antibiotic-driven selection but more properly the consequence of a complex hierarchy of processes shaping the ecology and evolution of the distinct subcellular, cellular and supra-cellular vehicles involved in the dissemination of resistance genes. Such a complex background motivated us to explore the P-system standards of membrane computing an innovative natural computing formalism that abstracts the notion of movement across membranes to simulate antibiotic resistance evolution processes across nested levels of micro- and macro-environmental organization in a given ecosystem. In this article, we introduce ARES (Antibiotic Resistance Evolution Simulator) a software device that simulates P-system model scenarios with five types of nested computing membranes oriented to emulate a hierarchy of eco-biological compartments, i.e. a) peripheral ecosystem; b) local environment; c) reservoir of supplies; d) animal host; and e) host's associated bacterial organisms (microbiome). Computational objects emulating molecular entities such as plasmids, antibiotic resistance genes, antimicrobials, and/or other substances can be introduced into this framework and may interact and evolve together with the membranes, according to a set of pre-established rules and specifications. ARES has been implemented as an online server and offers additional tools for storage and model editing and downstream analysis. The stochastic nature of the P-system model implemented in ARES explicitly links within and between host dynamics into a simulation, with feedback reciprocity among the different units of selection influenced by antibiotic exposure at various ecological levels. ARES offers the possibility of modeling predictive multilevel scenarios of antibiotic resistance evolution that can be interrogated, edited and re-simulated if necessary, with different parameters, until a correct model description of the process in the real world is convincingly approached. ARES can be accessed at http://gydb.org/ares.

Stochastic simulation of multiscale complex systems with PISKaS: A rule-based approach.

PubMed

Perez-Acle, Tomas; Fuenzalida, Ignacio; Martin, Alberto J M; Santibañez, Rodrigo; Avaria, Rodrigo; Bernardin, Alejandro; Bustos, Alvaro M; Garrido, Daniel; Dushoff, Jonathan; Liu, James H

2018-03-29

Computational simulation is a widely employed methodology to study the dynamic behavior of complex systems. Although common approaches are based either on ordinary differential equations or stochastic differential equations, these techniques make several assumptions which, when it comes to biological processes, could often lead to unrealistic models. Among others, model approaches based on differential equations entangle kinetics and causality, failing when complexity increases, separating knowledge from models, and assuming that the average behavior of the population encompasses any individual deviation. To overcome these limitations, simulations based on the Stochastic Simulation Algorithm (SSA) appear as a suitable approach to model complex biological systems. In this work, we review three different models executed in PISKaS: a rule-based framework to produce multiscale stochastic simulations of complex systems. These models span multiple time and spatial scales ranging from gene regulation up to Game Theory. In the first example, we describe a model of the core regulatory network of gene expression in Escherichia coli highlighting the continuous model improvement capacities of PISKaS. The second example describes a hypothetical outbreak of the Ebola virus occurring in a compartmentalized environment resembling cities and highways. Finally, in the last example, we illustrate a stochastic model for the prisoner's dilemma; a common approach from social sciences describing complex interactions involving trust within human populations. As whole, these models demonstrate the capabilities of PISKaS providing fertile scenarios where to explore the dynamics of complex systems. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

A proposal for an open source graphical environment for simulating x-ray optics

NASA Astrophysics Data System (ADS)

Sanchez del Rio, Manuel; Rebuffi, Luca; Demsar, Janez; Canestrari, Niccolo; Chubar, Oleg

2014-09-01

A new graphic environment to drive X-ray optics simulation packages such as SHADOW and SRW is proposed. The aim is to simulate a virtual experiment, including the description of the electron beam and simulate the emitted radiation, the optics, the scattering by the sample and radiation detection. Python is chosen as common interaction language. The ingredients of the new application, a glossary of variables for optical component, the selection of visualization tools, and the integration of all these components in a high level workflow environment built on Orange are presented.

LiveInventor: An Interactive Development Environment for Robot Autonomy

NASA Technical Reports Server (NTRS)

Neveu, Charles; Shirley, Mark

2003-01-01

LiveInventor is an interactive development environment for robot autonomy developed at NASA Ames Research Center. It extends the industry-standard OpenInventor graphics library and scenegraph file format to include kinetic and kinematic information, a physics-simulation library, an embedded Scheme interpreter, and a distributed communication system.

Virtual environment display for a 3D audio room simulation

NASA Astrophysics Data System (ADS)

Chapin, William L.; Foster, Scott

1992-06-01

Recent developments in virtual 3D audio and synthetic aural environments have produced a complex acoustical room simulation. The acoustical simulation models a room with walls, ceiling, and floor of selected sound reflecting/absorbing characteristics and unlimited independent localizable sound sources. This non-visual acoustic simulation, implemented with 4 audio ConvolvotronsTM by Crystal River Engineering and coupled to the listener with a Poihemus IsotrakTM, tracking the listener's head position and orientation, and stereo headphones returning binaural sound, is quite compelling to most listeners with eyes closed. This immersive effect should be reinforced when properly integrated into a full, multi-sensory virtual environment presentation. This paper discusses the design of an interactive, visual virtual environment, complementing the acoustic model and specified to: 1) allow the listener to freely move about the space, a room of manipulable size, shape, and audio character, while interactively relocating the sound sources; 2) reinforce the listener's feeling of telepresence into the acoustical environment with visual and proprioceptive sensations; 3) enhance the audio with the graphic and interactive components, rather than overwhelm or reduce it; and 4) serve as a research testbed and technology transfer demonstration. The hardware/software design of two demonstration systems, one installed and one portable, are discussed through the development of four iterative configurations. The installed system implements a head-coupled, wide-angle, stereo-optic tracker/viewer and multi-computer simulation control. The portable demonstration system implements a head-mounted wide-angle, stereo-optic display, separate head and pointer electro-magnetic position trackers, a heterogeneous parallel graphics processing system, and object oriented C++ program code.

Interactions between Early Parenting and a Polymorphism of the Child’s Dopamine Transporter Gene in Predicting Future Child Conduct Disorder Symptoms

PubMed Central

Lahey, Benjamin B.; Rathouz, Paul J.; Lee, Steve S.; Chronis-Tuscano, Andrea; Pelham, William E.; Waldman, Irwin D.; Cook, Edwin H.

2010-01-01

Mounting evidence suggests that genetic risks for mental disorders often interact with the social environment, but most studies still ignore environmental moderation of genetic influences. We tested interactions between maternal parenting and the variable number tandem repeat (VNTR) polymorphism in the 3′ untranslated region (UTR) of the dopamine transporter gene in the child to increase understanding of gene-environment interactions involving early parenting. Participants were part of a 9-year longitudinal study of 4–6-year-old children who met criteria for attention-deficit/hyperactivity disorder (ADHD) and demographically matched controls. Maternal parenting was observed during standard mother-child interactions in wave 1. The child’s conduct disorder (CD) symptoms 5–8 years later were measured using separate structured diagnostic interviews of the mother and youth. Controlling for ADHD symptoms and child disruptive behavior during the mother-child interaction, there was a significant inverse relation between levels of both positive and negative parenting at 4–6 years and the number of later CD symptoms, but primarily among children with two copies of the 9-repeat allele of the VNTR. The significant interaction with negative parenting was replicated in parent and youth reports of CD symptoms separately. PMID:21171728

Vestibular-visual interactions in flight simulators

NASA Technical Reports Server (NTRS)

Clark, B.

1977-01-01

All 139 research papers published under this ten-year program are listed. Experimental work was carried out at the Ames Research Center involving man's sensitivity to rotational acceleration, and psychophysical functioning of the semicircular canals; vestibular-visual interactions and effects of other sensory systems were studied in flight simulator environments. Experiments also dealt with the neurophysiological vestibular functions of animals, and flight management investigations of man-vehicle interactions.

Genome-wide assessment of gene-by-smoking interactions in COPD.

PubMed

Park, Boram; Koo, So-My; An, Jaehoon; Lee, MoonGyu; Kang, Hae Yeon; Qiao, Dandi; Cho, Michael H; Sung, Joohon; Silverman, Edwin K; Yang, Hyeon-Jong; Won, Sungho

2018-06-18

Cigarette smoke exposure is a major risk factor in chronic obstructive pulmonary disease (COPD) and its interactions with genetic variants could affect lung function. However, few gene-smoking interactions have been reported. In this report, we evaluated the effects of gene-smoking interactions on lung function using Korea Associated Resource (KARE) data with the spirometric variables-forced expiratory volume in 1 s (FEV 1 ). We found that variations in FEV 1 were different among smoking status. Thus, we considered a linear mixed model for association analysis under heteroscedasticity according to smoking status. We found a previously identified locus near SOX9 on chromosome 17 to be the most significant based on a joint test of the main and interaction effects of smoking. Smoking interactions were replicated with Gene-Environment of Interaction and phenotype (GENIE), Multi-Ethnic Study of Atherosclerosis-Lung (MESA-Lung), and COPDGene studies. We found that individuals with minor alleles, rs17765644, rs17178251, rs11870732, and rs4793541, tended to have lower FEV 1 values, and lung function decreased much faster with age for smokers. There have been very few reports to replicate a common variant gene-smoking interaction, and our results revealed that statistical models for gene-smoking interaction analyses should be carefully selected.

The Dopamine D2 Receptor Gene, Perceived Parental Support, and Adolescent Loneliness: Longitudinal Evidence for Gene-Environment Interactions

ERIC Educational Resources Information Center

van Roekel, Eeske; Goossens, Luc; Scholte, Ron H. J.; Engels, Rutger C. M. E.; Verhagen, Maaike

2011-01-01

Background: Loneliness is a common problem in adolescence. Earlier research focused on genes within the serotonin and oxytocin systems, but no studies have examined the role of dopamine-related genes in loneliness. In the present study, we focused on the dopamine D2 receptor gene (DRD2). Methods: Associations among the DRD2, sex, parental support,…

SIMPAVE : evaluation of virtual environments for pavement construction simulations

DOT National Transportation Integrated Search

2007-05-01

In the last couple of years, the authors have been developing virtual simulations for modeling the construction of asphalt pavements. The simulations are graphically rich, interactive, three-dimensional, with realistic physics, and allow multiple peo...

Nutrient-gene interactions in early pregnancy: a vascular hypothesis.

PubMed

Steegers-Theunissen, R P M; Steegers, E A P

2003-02-10

It is hypothesized that the following periconceptional and early pregnancy nutrient-gene interactions link vascular-related reproductive complications and cardiovascular diseases in adulthood: (1) Maternal and paternal genetically controlled nutrient status affects the quality of gametes and fertilization capacity; (2) The embryonic genetic constitution, derived from both parents, and the maternal genetically controlled nutrient environment determine embryogenesis and fetal growth; (3) Trophoblast invasion of decidua and spiral arteries is driven by genes derived from both parents as well as by maternal nutritional factors; (4) Angiogenesis, vasculogenesis and vascular function are dependent on the genetic constitution of the embryo, derived from both parents, and the maternal genetically controlled nutritional environment.Early intra-uterine programming of vessels may concern the same (in)dependent determinants of vascular-related complications during pregnancy and cardiovascular diseases in later life.

Two Applications of Simulation in the Educational Environment. Tech Memo.

ERIC Educational Resources Information Center

Thomas, David B.

Two educational computer simulations are described in this paper. One of the simulations is STATSIM, a series of exercises applicable to statistical instruction. The content of the other simulation is comprised of mathematical learning models. Student involvement, the interactive nature of the simulations, and terminal display of materials are…

MESA: An Interactive Modeling and Simulation Environment for Intelligent Systems Automation

NASA Technical Reports Server (NTRS)

Charest, Leonard

1994-01-01

This report describes MESA, a software environment for creating applications that automate NASA mission opterations. MESA enables intelligent automation by utilizing model-based reasoning techniques developed in the field of Artificial Intelligence. Model-based reasoning techniques are realized in Mesa through native support of causal modeling and discrete event simulation.

Exploration of protein-protein interaction effects on α-2-macroglobulin in an inhibition of serine protease through gene expression and molecular simulations studies.

PubMed

Sivakamavalli, Jeyachandran; Selvaraj, Chandrabose; Singh, Sanjeev Kumar; Vaseeharan, Baskaralingam

2014-01-01

In Prophenoloxidase (ProPO) cascade, two targets namely serine protease and α-2-macroglobulin are key regulators involved in the defense system of crustaceans. In biological systems, routine role of cell systems requires the understanding in protein-protein interactions through experimental and theoretical concepts, which might yield useful insights into the cellular responses. Response of cells to regulating the immune system is governed by the interactions-involved biomolecular simulations. Unfortunately, studies on the inhibitors (SP and α-2M) that negatively regulate the proPO system or melanization in penaeid shrimp are not yet available. In order to understand how these interactions change the proPO mechanism in Indian white shrimp Fenneropenaeus indicus was determined. In F. indicus, innate immune system is in a sensitive balance of intricate interactions; elucidating these interactions by the integration of in silico and in vitro has great potential. We have determined the expression of both the SP and α-2M enzymes in regulatory mechanism, which are analyzed through qRT-PCR, protein-protein docking, and simulation studies. From this work, we propose a novel approach for studying an organism at the systems level by integrating genome-wide computational analysis and the gene expression data.

Review: the Contribution of both Nature and Nurture to Carcinogenesis and Progression in Solid Tumours.

PubMed

Hyndman, Iain Joseph

2016-04-01

Cancer is a leading cause of mortality worldwide. Cancer arises due to a series of somatic mutations that accumulate within the nucleus of a cell which enable the cell to proliferate in an unregulated manner. These mutations arise as a result of both endogenous and exogenous factors. Genes that are commonly mutated in cancer cells are involved in cell cycle regulation, growth and proliferation. It is known that both nature and nurture play important roles in cancer development through complex gene-environment interactions; however, the exact mechanism of these interactions in carcinogenesis is presently unclear. Key environmental factors that play a role in carcinogenesis include smoking, UV light and oncoviruses. Angiogenesis, inflammation and altered cell metabolism are important factors in carcinogenesis and are influenced by both genetic and environmental factors. Although the exact mechanism of nature-nurture interactions in solid tumour formation are not yet fully understood, it is evident that neither nature nor nurture can be considered in isolation. By understanding more about gene-environment interactions, it is possible that cancer mortality could be reduced.

Physical Models and Virtual Reality Simulators in Otolaryngology.

PubMed

Javia, Luv; Sardesai, Maya G

2017-10-01

The increasing role of simulation in the medical education of future otolaryngologists has followed suit with other surgical disciplines. Simulators make it possible for the resident to explore and learn in a safe and less stressful environment. The various subspecialties in otolaryngology use physical simulators and virtual-reality simulators. Although physical simulators allow the operator to make direct contact with its components, virtual-reality simulators allow the operator to interact with an environment that is computer generated. This article gives an overview of the various types of physical simulators and virtual-reality simulators used in otolaryngology that have been reported in the literature. Copyright © 2017 Elsevier Inc. All rights reserved.

Translating the Simulation of Procedural Drilling Techniques for Interactive Neurosurgical Training

PubMed Central

Stredney, Don; Rezai, Ali R.; Prevedello, Daniel M.; Elder, J. Bradley; Kerwin, Thomas; Hittle, Bradley; Wiet, Gregory J.

2014-01-01

Background Through previous and concurrent efforts, we have developed a fully virtual environment to provide procedural training of otologic surgical technique. The virtual environment is based on high-resolution volumetric data of the regional anatomy. This volumetric data helps drive an interactive multi-sensory, i.e., visual (stereo), aural (stereo), and tactile simulation environment. Subsequently, we have extended our efforts to support the training of neurosurgical procedural technique as part of the CNS simulation initiative. Objective The goal of this multi-level development is to deliberately study the integration of simulation technologies into the neurosurgical curriculum and to determine their efficacy in teaching minimally invasive cranial and skull base approaches. Methods We discuss issues of biofidelity as well as our methods to provide objective, quantitative automated assessment for the residents. Results We conclude with a discussion of our experiences by reporting on preliminary formative pilot studies and proposed approaches to take the simulation to the next level through additional validation studies. Conclusion We have presented our efforts to translate an otologic simulation environment for use in the neurosurgical curriculum. We have demonstrated the initial proof of principles and define the steps to integrate and validate the system as an adjuvant to the neurosurgical curriculum. PMID:24051887

Genes Interacting with Occupational Exposures to Low Molecular Weight Agents and Irritants on Adult-Onset Asthma in Three European Studies

PubMed Central

Rava, Marta; Ahmed, Ismail; Kogevinas, Manolis; Le Moual, Nicole; Bouzigon, Emmanuelle; Curjuric, Ivan; Dizier, Marie-Hélène; Dumas, Orianne; Gonzalez, Juan R.; Imboden, Medea; Mehta, Amar J.; Tubert-Bitter, Pascale; Zock, Jan-Paul; Jarvis, Deborah; Probst-Hensch, Nicole M.; Demenais, Florence; Nadif, Rachel

2016-01-01

Background: The biological mechanisms by which cleaning products and disinfectants—an emerging risk factor—affect respiratory health remain incompletely evaluated. Studying genes by environment interactions (G × E) may help identify new genes related to adult-onset asthma. Objectives: We identified interactions between genetic polymorphisms of a large set of genes involved in the response to oxidative stress and occupational exposures to low molecular weight (LMW) agents or irritants on adult-onset asthma. Methods: Our data came from three large European cohorts: Epidemiological Family-based Study of the Genetics and Environment of Asthma (EGEA), Swiss Cohort Study on Air Pollution and Lung and Heart Disease in Adults (SAPALDIA), and European Community Respiratory Health Survey in Adults (ECRHS). A candidate pathway–based strategy identified 163 genes involved in the response to oxidative stress and potentially related to exposures to LMW agents/irritants. Occupational exposures were evaluated using an asthma job-exposure matrix and job-specific questionnaires for cleaners and healthcare workers. Logistic regression models were used to detect G × E interactions, adjusted for age, sex, and population ancestry, in 2,599 adults (mean age, 47 years; 60% women, 36% exposed, 18% asthmatics). p-Values were corrected for multiple comparisons. Results: Ever exposure to LMW agents/irritants was associated with current adult-onset asthma [OR = 1.28 (95% CI: 1.04, 1.58)]. Eight single nucleotide polymorphism (SNP) by exposure interactions at five loci were found at p < 0.005: PLA2G4A (rs932476, chromosome 1), near PLA2R1 (rs2667026, chromosome 2), near RELA (rs931127, rs7949980, chromosome 11), PRKD1 (rs1958980, rs11847351, rs1958987, chromosome 14), and PRKCA (rs6504453, chromosome 17). Results were consistent across the three studies and after accounting for smoking. Conclusions: Using a pathway-based selection process, we identified novel genes potentially involved in adult asthma by interaction with occupational exposure. These genes play a role in the NF-κB pathway, which is involved in inflammation. Citation: Rava M, Ahmed I, Kogevinas M, Le Moual N, Bouzigon E, Curjuric I, Dizier MH, Dumas O, Gonzalez JR, Imboden M, Mehta AJ, Tubert-Bitter P, Zock JP, Jarvis D, Probst-Hensch NM, Demenais F, Nadif R. 2017. Genes interacting with occupational exposures to low molecular weight agents and irritants on adult-onset asthma in three European studies. Environ Health Perspect 125:207–214; http://dx.doi.org/10.1289/EHP376 PMID:27504716

From Interaction to Co-Association —A Fisher r-To-z Transformation-Based Simple Statistic for Real World Genome-Wide Association Study

PubMed Central

Yuan, Zhongshang; Liu, Hong; Zhang, Xiaoshuai; Li, Fangyu; Zhao, Jinghua; Zhang, Furen; Xue, Fuzhong

2013-01-01

Currently, the genetic variants identified by genome wide association study (GWAS) generally only account for a small proportion of the total heritability for complex disease. One crucial reason is the underutilization of gene-gene joint effects commonly encountered in GWAS, which includes their main effects and co-association. However, gene-gene co-association is often customarily put into the framework of gene-gene interaction vaguely. From the causal graph perspective, we elucidate in detail the concept and rationality of gene-gene co-association as well as its relationship with traditional gene-gene interaction, and propose two Fisher r-to-z transformation-based simple statistics to detect it. Three series of simulations further highlight that gene-gene co-association refers to the extent to which the joint effects of two genes differs from the main effects, not only due to the traditional interaction under the nearly independent condition but the correlation between two genes. The proposed statistics are more powerful than logistic regression under various situations, cannot be affected by linkage disequilibrium and can have acceptable false positive rate as long as strictly following the reasonable GWAS data analysis roadmap. Furthermore, an application to gene pathway analysis associated with leprosy confirms in practice that our proposed gene-gene co-association concepts as well as the correspondingly proposed statistics are strongly in line with reality. PMID:23923021

Building interactive virtual environments for simulated training in medicine using VRML and Java/JavaScript.

PubMed

Korocsec, D; Holobar, A; Divjak, M; Zazula, D

2005-12-01

Medicine is a difficult thing to learn. Experimenting with real patients should not be the only option; simulation deserves a special attention here. Virtual Reality Modelling Language (VRML) as a tool for building virtual objects and scenes has a good record of educational applications in medicine, especially for static and animated visualisations of body parts and organs. However, to create computer simulations resembling situations in real environments the required level of interactivity and dynamics is difficult to achieve. In the present paper we describe some approaches and techniques which we used to push the limits of the current VRML technology further toward dynamic 3D representation of virtual environments (VEs). Our demonstration is based on the implementation of a virtual baby model, whose vital signs can be controlled from an external Java application. The main contributions of this work are: (a) outline and evaluation of the three-level VRML/Java implementation of the dynamic virtual environment, (b) proposal for a modified VRML Timesensor node, which greatly improves the overall control of system performance, and (c) architecture of the prototype distributed virtual environment for training in neonatal resuscitation comprising the interactive virtual newborn, active bedside monitor for vital signs and full 3D representation of the surgery room.

Using evolutionary computations to understand the design and evolution of gene and cell regulatory networks.

PubMed

Spirov, Alexander; Holloway, David

2013-07-15

This paper surveys modeling approaches for studying the evolution of gene regulatory networks (GRNs). Modeling of the design or 'wiring' of GRNs has become increasingly common in developmental and medical biology, as a means of quantifying gene-gene interactions, the response to perturbations, and the overall dynamic motifs of networks. Drawing from developments in GRN 'design' modeling, a number of groups are now using simulations to study how GRNs evolve, both for comparative genomics and to uncover general principles of evolutionary processes. Such work can generally be termed evolution in silico. Complementary to these biologically-focused approaches, a now well-established field of computer science is Evolutionary Computations (ECs), in which highly efficient optimization techniques are inspired from evolutionary principles. In surveying biological simulation approaches, we discuss the considerations that must be taken with respect to: (a) the precision and completeness of the data (e.g. are the simulations for very close matches to anatomical data, or are they for more general exploration of evolutionary principles); (b) the level of detail to model (we proceed from 'coarse-grained' evolution of simple gene-gene interactions to 'fine-grained' evolution at the DNA sequence level); (c) to what degree is it important to include the genome's cellular context; and (d) the efficiency of computation. With respect to the latter, we argue that developments in computer science EC offer the means to perform more complete simulation searches, and will lead to more comprehensive biological predictions. Copyright © 2013 Elsevier Inc. All rights reserved.

Effective Student Learning of Fractions with an Interactive Simulation

ERIC Educational Resources Information Center

Hensberry, Karina K. R.; Moore, Emily B.; Perkins, Katherine K.

2015-01-01

Computer technology, when coupled with reform-based teaching practices, has been shown to be an effective way to support student learning of mathematics. The quality of the technology itself, as well as how it is used, impacts how much students learn. Interactive simulations are dynamic virtual environments similar to virtual manipulatives that…

Developing Interactive Educational Engineering Software for the World Wide Web with Java.

ERIC Educational Resources Information Center

Reed, John A.; Afjeh, Abdollah A.

1998-01-01

Illustrates the design and implementation of a Java applet for use in educational propulsion engineering curricula. The Java Gas Turbine Simulator applet provides an interactive graphical environment which allows the rapid, efficient construction and analysis of arbitrary gas turbine systems. The simulator can be easily accessed from the World…

Interactive Simulations: Improving Learning Retention in Knowledge-Based Online Training Courses

ERIC Educational Resources Information Center

Boyd, James L.

2017-01-01

The purpose of this quasi-experimental quantitative study was to investigate whether online interactive simulations would provide a positive improvement in learners' ability to apply critical thinking skills in a dangerous work environment. The course in which an improvement in critical thinking skills was the target outcome was a course which…

Genetic variation in biotransformation enzymes, air pollution exposures, and risk of spina bifida.

PubMed

Padula, Amy M; Yang, Wei; Schultz, Kathleen; Lurmann, Fred; Hammond, S Katharine; Shaw, Gary M

2018-05-01

Spina bifida is a birth defect characterized by incomplete closure of the embryonic neural tube. Genetic factors as well as environmental factors have been observed to influence risks for spina bifida. Few studies have investigated possible gene-environment interactions that could contribute to spina bifida risk. The aim of this study is to examine the interaction between gene variants in biotransformation enzyme pathways and ambient air pollution exposures and risk of spina bifida. We evaluated the role of air pollution exposure during pregnancy and gene variants of biotransformation enzymes from bloodspots and buccal cells in a California population-based case-control (86 cases of spina bifida and 208 non-malformed controls) study. We considered race/ethnicity and folic acid vitamin use as potential effect modifiers and adjusted for those factors and smoking. We observed gene-environment interactions between each of the five pollutants and several gene variants: NO (ABCC2), NO 2 (ABCC2, SLC01B1), PM 10 (ABCC2, CYP1A1, CYP2B6, CYP2C19, CYP2D6, NAT2, SLC01B1, SLC01B3), PM 2.5 (CYP1A1 and CYP1A2). These analyses show positive interactions between air pollution exposure during early pregnancy and gene variants associated with metabolizing enzymes. These exploratory results suggest that some individuals based on their genetic background may be more susceptible to the adverse effects of pollution. © 2018 Wiley Periodicals, Inc.

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

PubMed

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

PubMed Central

Zhao, Wei; He, Zihuai; Kardia, Sharon L. R.; Faul, Jessica D.

2017-01-01

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). PMID:28961216

Visualization and Tracking of Parallel CFD Simulations

NASA Technical Reports Server (NTRS)

Vaziri, Arsi; Kremenetsky, Mark

1995-01-01

We describe a system for interactive visualization and tracking of a 3-D unsteady computational fluid dynamics (CFD) simulation on a parallel computer. CM/AVS, a distributed, parallel implementation of a visualization environment (AVS) runs on the CM-5 parallel supercomputer. A CFD solver is run as a CM/AVS module on the CM-5. Data communication between the solver, other parallel visualization modules, and a graphics workstation, which is running AVS, are handled by CM/AVS. Partitioning of the visualization task, between CM-5 and the workstation, can be done interactively in the visual programming environment provided by AVS. Flow solver parameters can also be altered by programmable interactive widgets. This system partially removes the requirement of storing large solution files at frequent time steps, a characteristic of the traditional 'simulate (yields) store (yields) visualize' post-processing approach.

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

PubMed Central

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

2009-01-01

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. PMID:18802414

Biomarkers of susceptibility to chemical carcinogens: the example of non-Hodgkin lymphomas.

PubMed

Kelly, Rachel S; Vineis, Paolo

2014-09-01

Genetic susceptibly to suspected chemical and environmental carcinogens may modify the response to exposure. The aim of this review was to explore the issues involved in the study of gene-environment interactions, and to consider the use of susceptibility biomarkers in cancer epidemiology, using non-Hodgkin lymphoma (NHL) as an example. PubMed, EMBASE and Web of Science were searched for peer-reviewed articles considering biomarkers of susceptibility to chemical, agricultural and industrial carcinogens in the aetiology of NHL. The results suggest a modifying role for genetic susceptibility to a number of occupational and environmental exposures including organochlorines, chlorinated solvents, chlordanes and benzene in the aetiology of NHL. The potential importance of these gene-environment interactions in NHL may help to explain the lack of definitive carcinogens identified to date for this malignancy. Although a large number of genetic variants and gene-environment interactions have been explored for NHL, to date replication is lacking and therefore the findings remain to be validated. These findings highlight the need for novel standardized methodologies in the study of genetic susceptibility to chemical carcinogens. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Individualized weight management: what can be learned from nutrigenomics and nutrigenetics?

PubMed

Rudkowska, Iwona; Pérusse, Louis

2012-01-01

The rise in the prevalence of obesity observed over the past decades is taken by many as an indication of the predominance of environmental factors (the so-called obesogenic environment) over genetic factors in explaining why obesity has reached epidemic proportions. While a changing environment favoring increased food intake and decreased physical activity levels has clearly contributed to shifting the distribution of body mass index (BMI) at the population level, not everyone is becoming overweight or obese. This suggests that there are genetic factors interacting with environmental factors to predispose some individuals to obesity. This gene-environment interaction is not only important in determining an individual's susceptibility to obesity but can also influence the outcome of weight-loss programs and weight-management strategies in overweight and obese subjects. This chapter reviews the role of gene-nutrient interactions in the context of weight management. The first section reviews the application of transcriptomics in human nutrition intervention studies on the molecular impact of caloric restriction and macronutrient composition. The second section reviews the effects of various obesity candidate gene polymorphisms on the response of body weight or weight-related phenotypes to weight-loss programs which include nutritional interventions. Copyright © 2012 Elsevier Inc. All rights reserved.

Relations between three dopaminergic system genes, school attachment, and adolescent delinquency.

PubMed

Fine, Adam; Mahler, Alissa; Simmons, Cortney; Chen, Chuansheng; Moyzis, Robert; Cauffman, Elizabeth

2016-11-01

Both environmental factors and genetic variation, particularly in genes responsible for the dopaminergic system such as DRD4, DRD2, and DAT1 (SLC6A3), affect adolescent delinquency. The school context, despite its developmental importance, has been overlooked in gene-environment research. Using data from the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development (NICHD ECCYD), this study examined key interactions between school attachment and (a) each of the DRD4, DRD2, and DAT1 (SLC6A3) genotypes; and (b) a polygenic score. Results indicate that there is a main effect of school attachment, unlike genetic variation, on delinquency. Interestingly, there are important interactive effects of school attachment and dopaminergic genotypes on delinquency. Carriers of the DRD2-A1 allele were differentially affected by both positive and negative school environments, whereas DAT1-10R carriers fared the same as 9R homozygotes in poorer and moderate school environments, but fared disproportionately better in more positive environments. Contrary to expectations, youth without the DRD4-7R allele were particularly affected by the school environment. These findings contribute to the literature considering the roles of both context and genes in delinquency research, and inform our understanding of the individual-level traits that influence sensitivity to particular contexts. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Assessing interactions between HLA-DRB1*15 and infectious mononucleosis on the risk of multiple sclerosis.

PubMed

Disanto, Giulio; Hall, Carolina; Lucas, Robyn; Ponsonby, Anne-Louise; Berlanga-Taylor, Antonio J; Giovannoni, Gavin; Ramagopalan, Sreeram V

2013-09-01

Gene-environment interactions may shed light on the mechanisms underlying multiple sclerosis (MS). We pooled data from two case-control studies on incident demyelination and used different methods to assess interaction between HLA-DRB1*15 (DRB1-15) and history of infectious mononucleosis (IM). Individuals exposed to both factors were at substantially increased risk of disease (OR=7.32, 95% CI=4.92-10.90). In logistic regression models, DRB1-15 and IM status were independent predictors of disease while their interaction term was not (DRB1-15*IM: OR=1.35, 95% CI=0.79-2.23). However, interaction on an additive scale was evident (Synergy index=2.09, 95% CI=1.59-2.59; excess risk due to interaction=3.30, 95%CI=0.47-6.12; attributable proportion due to interaction=45%, 95% CI=22-68%). This suggests, if the additive model is appropriate, the DRB1-15 and IM may be involved in the same causal process leading to MS and highlights the benefit of reporting gene-environment interactions on both a multiplicative and additive scale.

Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environment.

PubMed

Yao, Yao; Storme, Veronique; Marchal, Kathleen; Van de Peer, Yves

2016-01-01

We developed a bio-inspired robot controller combining an artificial genome with an agent-based control system. The genome encodes a gene regulatory network (GRN) that is switched on by environmental cues and, following the rules of transcriptional regulation, provides output signals to actuators. Whereas the genome represents the full encoding of the transcriptional network, the agent-based system mimics the active regulatory network and signal transduction system also present in naturally occurring biological systems. Using such a design that separates the static from the conditionally active part of the gene regulatory network contributes to a better general adaptive behaviour. Here, we have explored the potential of our platform with respect to the evolution of adaptive behaviour, such as preying when food becomes scarce, in a complex and changing environment and show through simulations of swarm robots in an A-life environment that evolution of collective behaviour likely can be attributed to bio-inspired evolutionary processes acting at different levels, from the gene and the genome to the individual robot and robot population.

Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environment

PubMed Central

Yao, Yao; Storme, Veronique; Marchal, Kathleen

2016-01-01

We developed a bio-inspired robot controller combining an artificial genome with an agent-based control system. The genome encodes a gene regulatory network (GRN) that is switched on by environmental cues and, following the rules of transcriptional regulation, provides output signals to actuators. Whereas the genome represents the full encoding of the transcriptional network, the agent-based system mimics the active regulatory network and signal transduction system also present in naturally occurring biological systems. Using such a design that separates the static from the conditionally active part of the gene regulatory network contributes to a better general adaptive behaviour. Here, we have explored the potential of our platform with respect to the evolution of adaptive behaviour, such as preying when food becomes scarce, in a complex and changing environment and show through simulations of swarm robots in an A-life environment that evolution of collective behaviour likely can be attributed to bio-inspired evolutionary processes acting at different levels, from the gene and the genome to the individual robot and robot population. PMID:28028477

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

PubMed

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.

Genetic Expression Outside the Skin: Clues to Mechanisms of Genotype × Environment Interaction

PubMed Central

Reiss, David; Leve, Leslie D.

2007-01-01

The rapidly moving study of Gene × Environment interaction needs interim conceptual tools to track progress, integrate findings, and apply this knowledge to preventive intervention. We define two closely related concepts: the social mediation of the expression of genetic influences and the interaction between the entire genotype and the social environment (Genotype × Environment interaction; G×E). G×E interaction, the primary focus of this report, assesses individual differences in the full genotype using twin, sibling, and adoption designs and, for the most part, employs fine-grained analyses of relational processes in the social environment. In comparison, studies of Allele × Environment interaction (A×E) assess the influence on development of one or more measured polymorphisms as modified by environmental factors. G×E studies build on work showing how the social environment responds to genetic influences and how genetic influences shape the social environment. Recent G×E research has yielded new insight into variations in the sensitivity of the social environment to genotypic influences and provides clues to the specificity and timing of these environmental responses that can be leveraged to inform preventive interventions aimed at reducing genetic risk for problem behavior. PMID:17931431

Folate and Breast Cancer: Role of Intake, Blood Levels, and Metabolic Gene Polymorphisms

DTIC Science & Technology

2006-06-01

polymorphisms . The specific aims are 1) methodological training in the analysis of gene - gene and gene -environment interactions by studying folate...evaluation of folate intake, plasma folate, and metabolic gene polymorphisms in relation to breast cancer risk: Months 1-19. b. Prepare blood samples...isolated for the folate and gene polymorphism assays among the 184 cases and matched controls. The folate assays are on-going at this time and over

Robust discovery of genetic associations incorporating gene-environment interaction and independence.

PubMed

Tchetgen Tchetgen, Eric

2011-03-01

This article considers the detection and evaluation of genetic effects incorporating gene-environment interaction and independence. Whereas ordinary logistic regression cannot exploit the assumption of gene-environment independence, the proposed approach makes explicit use of the independence assumption to improve estimation efficiency. This method, which uses both cases and controls, fits a constrained retrospective regression in which the genetic variant plays the role of the response variable, and the disease indicator and the environmental exposure are the independent variables. The regression model constrains the association of the environmental exposure with the genetic variant among the controls to be null, thus explicitly encoding the gene-environment independence assumption, which yields substantial gain in accuracy in the evaluation of genetic effects. The proposed retrospective regression approach has several advantages. It is easy to implement with standard software, and it readily accounts for multiple environmental exposures of a polytomous or of a continuous nature, while easily incorporating extraneous covariates. Unlike the profile likelihood approach of Chatterjee and Carroll (Biometrika. 2005;92:399-418), the proposed method does not require a model for the association of a polytomous or continuous exposure with the disease outcome, and, therefore, it is agnostic to the functional form of such a model and completely robust to its possible misspecification.

Genetic Influences on Peer and Family Relationships Across Adolescent Development: Introduction to the Special Issue.

PubMed

Mullineaux, Paula Y; DiLalla, Lisabeth Fisher

2015-07-01

Nearly all aspects of human development are influenced by genetic and environmental factors, which conjointly shape development through several gene-environment interplay mechanisms. More recently, researchers have begun to examine the influence of genetic factors on peer and family relationships across the pre-adolescent and adolescent time periods. This article introduces the special issue by providing a critical overview of behavior genetic methodology and existing research demonstrating gene-environment processes operating on the link between peer and family relationships and adolescent adjustment. The overview is followed by a summary of new research studies, which use genetically informed samples to examine how peer and family environment work together with genetic factors to influence behavioral outcomes across adolescence. The studies in this special issue provide further evidence of gene-environment interplay through innovative behavior genetic methodological approaches across international samples. Results from the quantitative models indicate environmental moderation of genetic risk for coercive adolescent-parent relationships and deviant peer affiliation. The molecular genetics studies provide support for a gene-environment interaction differential susceptibility model for dopamine regulation genes across positive and negative peer and family environments. Overall, the findings from the studies in this special issue demonstrate the importance of considering how genes and environments work in concert to shape developmental outcomes during adolescence.

Gene-environment interaction in the etiology of mathematical ability using SNP sets.

PubMed

Docherty, Sophia J; Kovas, Yulia; Plomin, Robert

2011-01-01

Mathematics ability and disability is as heritable as other cognitive abilities and disabilities, however its genetic etiology has received relatively little attention. In our recent genome-wide association study of mathematical ability in 10-year-old children, 10 SNP associations were nominated from scans of pooled DNA and validated in an individually genotyped sample. In this paper, we use a 'SNP set' composite of these 10 SNPs to investigate gene-environment (GE) interaction, examining whether the association between the 10-SNP set and mathematical ability differs as a function of ten environmental measures in the home and school in a sample of 1888 children with complete data. We found two significant GE interactions for environmental measures in the home and the school both in the direction of the diathesis-stress type of GE interaction: The 10-SNP set was more strongly associated with mathematical ability in chaotic homes and when parents are negative.

Impact of simulated microgravity on the normal developmental time line of an animal-bacteria symbiosis

PubMed Central

Foster, Jamie S.; Khodadad, Christina L. M.; Ahrendt, Steven R.; Parrish, Mirina L.

2013-01-01

The microgravity environment during space flight imposes numerous adverse effects on animal and microbial physiology. It is unclear, however, how microgravity impacts those cellular interactions between mutualistic microbes and their hosts. Here, we used the symbiosis between the host squid Euprymna scolopes and its luminescent bacterium Vibrio fischeri as a model system. We examined the impact of simulated microgravity on the timeline of bacteria-induced development in the host light organ, the site of the symbiosis. To simulate the microgravity environment, host squid and symbiosis-competent bacteria were incubated together in high-aspect ratio rotating wall vessel bioreactors and examined throughout the early stages of the bacteria-induced morphogenesis. The host innate immune response was suppressed under simulated microgravity; however, there was an acceleration of bacteria-induced apoptosis and regression in the host tissues. These results suggest that the space flight environment may alter the cellular interactions between animal hosts and their natural healthy microbiome. PMID:23439280

The dopamine D2 receptor gene and depressive and anxious symptoms in childhood: associations and evidence for gene–environment correlation and gene–environment interaction

PubMed Central

Hayden, Elizabeth P.; Klein, Daniel N.; Dougherty, Lea R.; Olino, Thomas M.; Laptook, Rebecca S.; Dyson, Margaret W.; Bufferd, Sara J.; Durbin, C. Emily; Sheikh, Haroon I.; Singh, Shiva M.

2012-01-01

Objectives Research implicates the A1 allele of the dopamine D2 receptor gene (DRD2) Taq1A polymorphism in the development of depression and anxiety. Furthermore, recent papers suggest that children with A1 allele of this gene may receive less positive parenting, and that the effects of this gene on child symptoms may be moderated by parenting. We sought to replicate and extend these findings using behavioral measures in a nonclinical sample of young children. Methods In a sample of 473 preschool-aged children and their mothers, structured clinical interview measures and maternal reports of child symptoms were collected, and standardized observations of parent–child interactions were conducted. Results An association was detected between the DRD2 A1 allele and symptoms of depression and anxiety indexed using interview and parent report methods. As found in previous reports, children with the DRD2 A1 allele received less supportive parenting and displayed higher levels of negative emotionality during parent–child interactions. Tests of mediation and moderation were conducted. Conclusion We found associations between the DRD2 A1 allele and early-emerging anxious and depressive symptoms in a community sample of preschool-aged children, and evidence of a gene–environment correlation and moderation of the main effect of child genotype on child symptoms by parenting. PMID:20526230

Gene-environment interaction in major depression: focus on experience-dependent biological systems.

PubMed

Lopizzo, Nicola; Bocchio Chiavetto, Luisella; Cattane, Nadia; Plazzotta, Giona; Tarazi, Frank I; Pariante, Carmine M; Riva, Marco A; Cattaneo, Annamaria

2015-01-01

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 lifelong 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 × 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, we aim to underlie the role of genetic and epigenetic processes involved in stress- and neuroplasticity-related biological systems on the development of MDD after exposure to early life stress, thereby building the basis for future research and clinical interventions.

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

PubMed

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.

The population genetics of X-autosome synthetic lethals and steriles.

PubMed

Lachance, Joseph; Johnson, Norman A; True, John R

2011-11-01

Epistatic interactions are widespread, and many of these interactions involve combinations of alleles at different loci that are deleterious when present in the same individual. The average genetic environment of sex-linked genes differs from that of autosomal genes, suggesting that the population genetics of interacting X-linked and autosomal alleles may be complex. Using both analytical theory and computer simulations, we analyzed the evolutionary trajectories and mutation-selection balance conditions for X-autosome synthetic lethals and steriles. Allele frequencies follow a set of fundamental trajectories, and incompatible alleles are able to segregate at much higher frequencies than single-locus expectations. Equilibria exist, and they can involve fixation of either autosomal or X-linked alleles. The exact equilibrium depends on whether synthetic alleles are dominant or recessive and whether fitness effects are seen in males, females, or both sexes. When single-locus fitness effects and synthetic incompatibilities are both present, population dynamics depend on the dominance of alleles and historical contingency (i.e., whether X-linked or autosomal mutations occur first). Recessive synthetic lethality can result in high-frequency X-linked alleles, and dominant synthetic lethality can result in high-frequency autosomal alleles. Many X-autosome incompatibilities in natural populations may be cryptic, appearing to be single-locus effects because one locus is fixed. We also discuss the implications of these findings with respect to standing genetic variation and the origins of Haldane's rule.

ISS Radiation Shielding and Acoustic Simulation Using an Immersive Environment

NASA Technical Reports Server (NTRS)

Verhage, Joshua E.; Sandridge, Chris A.; Qualls, Garry D.; Rizzi, Stephen A.

2002-01-01

The International Space Station Environment Simulator (ISSES) is a virtual reality application that uses high-performance computing, graphics, and audio rendering to simulate the radiation and acoustic environments of the International Space Station (ISS). This CAVE application allows the user to maneuver to different locations inside or outside of the ISS and interactively compute and display the radiation dose at a point. The directional dose data is displayed as a color-mapped sphere that indicates the relative levels of radiation from all directions about the center of the sphere. The noise environment is rendered in real time over headphones or speakers and includes non-spatial background noise, such as air-handling equipment, and spatial sounds associated with specific equipment racks, such as compressors or fans. Changes can be made to equipment rack locations that produce changes in both the radiation shielding and system noise. The ISSES application allows for interactive investigation and collaborative trade studies between radiation shielding and noise for crew safety and comfort.

Gene-environment interaction on neural mechanisms of orthographic processing in Chinese children

PubMed Central

Su, Mengmeng; Wang, Jiuju; Maurer, Urs; Zhang, Yuping; Li, Jun; McBride-Chang, Catherine; Tardif, Twila; Liu, Youyi; Shu, Hua

2015-01-01

The ability to process and identify visual words requires efficient orthographic processing of print, consisting of letters in alphabetic languages or characters in Chinese. The N170 is a robust neural marker for orthographic processes. Both genetic and environmental factors, such as home literacy, have been shown to influence orthographic processing at the behavioral level, but their relative contributions and interactions are not well understood. The present study aimed to reveal possible gene-by-environment interactions on orthographic processing at the behavioral and neural level in a normal children sample. Sixty 12 year old Chinese children from a 10-year longitudinal sample underwent an implicit visual-word color decision task on real words and stroke combinations. The ERP analysis focused on the increase of the occipito-temporal N170 to words compared to stroke combinations. The genetic analysis focused on two SNPs (rs1419228, rs1091047) in the gene DCDC2 based on previous findings linking these 2 SNPs to orthographic coding. Home literacy was measured previously as the number of children's books at home, when the children were at the age of 3. Relative to stroke combinations, real words evoked greater N170 in bilateral posterior brain regions. A significant interaction between rs1091047 and home literacy was observed on the changes of N170 comparing real words to stroke combinations in the left hemisphere. Particularly, children carrying the major allele “G” showed a similar N170 effect irrespective of their environment, while children carrying the minor allele “C” showed a smaller N170 effect in low home-literacy environment than those in good environment. PMID:26294811

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

PubMed

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.

Design of a simulation environment for laboratory management by robot organizations

NASA Technical Reports Server (NTRS)

Zeigler, Bernard P.; Cellier, Francois E.; Rozenblit, Jerzy W.

1988-01-01

This paper describes the basic concepts needed for a simulation environment capable of supporting the design of robot organizations for managing chemical, or similar, laboratories on the planned U.S. Space Station. The environment should facilitate a thorough study of the problems to be encountered in assigning the responsibility of managing a non-life-critical, but mission valuable, process to an organized group of robots. In the first phase of the work, we seek to employ the simulation environment to develop robot cognitive systems and strategies for effective multi-robot management of chemical experiments. Later phases will explore human-robot interaction and development of robot autonomy.

i3Drive, a 3D interactive driving simulator.

PubMed

Ambroz, Miha; Prebil, Ivan

2010-01-01

i3Drive, a wheeled-vehicle simulator, can accurately simulate vehicles of various configurations with up to eight wheels in real time on a desktop PC. It presents the vehicle dynamics as an interactive animation in a virtual 3D environment. The application is fully GUI-controlled, giving users an easy overview of the simulation parameters and letting them adjust those parameters interactively. It models all relevant vehicle systems, including the mechanical models of the suspension, power train, and braking and steering systems. The simulation results generally correspond well with actual measurements, making the system useful for studying vehicle performance in various driving scenarios. i3Drive is thus a worthy complement to other, more complex tools for vehicle-dynamics simulation and analysis.

Modelling, Simulation, Animation, and Real-Time Control (Mosart) for a Class of Electromechanical Systems: A System-Theoretic Approach

ERIC Educational Resources Information Center

Rodriguez, Armando A.; Metzger, Richard P.; Cifdaloz, Oguzhan; Dhirasakdanon, Thanate; Welfert, Bruno

2004-01-01

This paper describes an interactive modelling, simulation, animation, and real-time control (MoSART) environment for a class of 'cart-pendulum' electromechanical systems that may be used to enhance learning within differential equations and linear algebra classes. The environment is useful for conveying fundamental mathematical/systems concepts…

On the use of sibling recurrence risks to select environmental factors liable to interact with genetic risk factors.

PubMed

Kazma, Rémi; Bonaïti-Pellié, Catherine; Norris, Jill M; Génin, Emmanuelle

2010-01-01

Gene-environment interactions are likely to be involved in the susceptibility to multifactorial diseases but are difficult to detect. Available methods usually concentrate on some particular genetic and environmental factors. In this paper, we propose a new method to determine whether a given exposure is susceptible to interact with unknown genetic factors. Rather than focusing on a specific genetic factor, the degree of familial aggregation is used as a surrogate for genetic factors. A test comparing the recurrence risks in sibs according to the exposure of indexes is proposed and its power is studied for varying values of model parameters. The Exposed versus Unexposed Recurrence Analysis (EURECA) is valuable for common diseases with moderate familial aggregation, only when the role of exposure has been clearly outlined. Interestingly, accounting for a sibling correlation for the exposure increases the power of EURECA. An application on a sample ascertained through one index affected with type 2 diabetes is presented where gene-environment interactions involving obesity and physical inactivity are investigated. Association of obesity with type 2 diabetes is clearly evidenced and a potential interaction involving this factor is suggested in Hispanics (P=0.045), whereas a clear gene-environment interaction is evidenced involving physical inactivity only in non-Hispanic whites (P=0.028). The proposed method might be of particular interest before genetic studies to help determine the environmental risk factors that will need to be accounted for to increase the power to detect genetic risk factors and to select the most appropriate samples to genotype.

A First Life with Computerized Business Simulations

ERIC Educational Resources Information Center

Thavikulwat, Precha

2011-01-01

The author discusses the theoretical lens, origins, and environment of his work on computerized business simulations. Key ideas that inform his work include the two dimensions (control and interaction) of computerized simulation, the two ways of representing a natural process (phenotypical and genotypical) in a simulation, which he defines as a…

Association of Polyaminergic Loci With Anxiety, Mood Disorders, and Attempted Suicide

PubMed Central

Fiori, Laura M.; Wanner, Brigitte; Jomphe, Valérie; Croteau, Jordie; Vitaro, Frank

2010-01-01

Background The polyamine system has been implicated in a number of psychiatric conditions, which display both alterations in polyamine levels and altered expression of genes related to polyamine metabolism. Studies have identified associations between genetic variants in spermidine/spermine N1-acetyltransferase (SAT1) and both anxiety and suicide, and several polymorphisms appear to play important roles in determining gene expression. Methodology/Principal Findings We genotyped 63 polymorphisms, spread across four polyaminergic genes (SAT1, spermine synthase (SMS), spermine oxidase (SMOX), and ornithine aminotransferase like-1 (OATL1)), in 1255 French-Canadian individuals who have been followed longitudinally for 22 years. We assessed univariate associations with anxiety, mood disorders, and attempted suicide, as assessed during early adulthood. We also investigated the involvement of gene-environment interactions in terms of childhood abuse, and assessed internalizing and externalizing symptoms as endophenotypes mediating these interactions. Overall, each gene was associated with at least one main outcome: anxiety (SAT1, SMS), mood disorders (SAT1, SMOX), and suicide attempts (SAT1, OATL1). Several SAT1 polymorphisms displayed disease-specific risk alleles, and polymorphisms in this gene were involved in gene-gene interactions with SMS to confer risk for anxiety disorders, as well as gene-environment interactions between childhood physical abuse and mood disorders. Externalizing behaviors demonstrated significant mediation with regards to the association between OATL1 and attempted suicide, however there was no evidence that externalizing or internalizing behaviors were appropriate endophenotypes to explain the associations with mood or anxiety disorders. Finally, childhood sexual abuse did not demonstrate mediating influences on any of our outcomes. Conclusions/Significance These results demonstrate that genetic variants in polyaminergic genes are associated with psychiatric conditions, each of which involves a set of separate and distinct risk alleles. As several of these polymorphisms are associated with gene expression, these findings may provide mechanisms to explain the alterations in polyamine metabolism which have been observed in psychiatric disorders. PMID:21152090

Association of polyaminergic loci with anxiety, mood disorders, and attempted suicide.

PubMed

Fiori, Laura M; Wanner, Brigitte; Jomphe, Valérie; Croteau, Jordie; Vitaro, Frank; Tremblay, Richard E; Bureau, Alexandre; Turecki, Gustavo

2010-11-30

The polyamine system has been implicated in a number of psychiatric conditions, which display both alterations in polyamine levels and altered expression of genes related to polyamine metabolism. Studies have identified associations between genetic variants in spermidine/spermine N1-acetyltransferase (SAT1) and both anxiety and suicide, and several polymorphisms appear to play important roles in determining gene expression. We genotyped 63 polymorphisms, spread across four polyaminergic genes (SAT1, spermine synthase (SMS), spermine oxidase (SMOX), and ornithine aminotransferase like-1 (OATL1)), in 1255 French-Canadian individuals who have been followed longitudinally for 22 years. We assessed univariate associations with anxiety, mood disorders, and attempted suicide, as assessed during early adulthood. We also investigated the involvement of gene-environment interactions in terms of childhood abuse, and assessed internalizing and externalizing symptoms as endophenotypes mediating these interactions. Overall, each gene was associated with at least one main outcome: anxiety (SAT1, SMS), mood disorders (SAT1, SMOX), and suicide attempts (SAT1, OATL1). Several SAT1 polymorphisms displayed disease-specific risk alleles, and polymorphisms in this gene were involved in gene-gene interactions with SMS to confer risk for anxiety disorders, as well as gene-environment interactions between childhood physical abuse and mood disorders. Externalizing behaviors demonstrated significant mediation with regards to the association between OATL1 and attempted suicide, however there was no evidence that externalizing or internalizing behaviors were appropriate endophenotypes to explain the associations with mood or anxiety disorders. Finally, childhood sexual abuse did not demonstrate mediating influences on any of our outcomes. These results demonstrate that genetic variants in polyaminergic genes are associated with psychiatric conditions, each of which involves a set of separate and distinct risk alleles. As several of these polymorphisms are associated with gene expression, these findings may provide mechanisms to explain the alterations in polyamine metabolism which have been observed in psychiatric disorders.

Autism risk factors: genes, environment, and gene-environment interactions

PubMed Central

Chaste, Pauline; Leboyer, Marion

2012-01-01

The aim of this review is to summarize the key findings from genetic and epidemiological research, which show that autism is a complex disorder resulting from the combination of genetic and environmental factors. Remarkable advances in the knowledge of genetic causes of autism have resulted from the great efforts made in the field of genetics. The identification of specific alleles contributing to the autism spectrum has supplied important pieces for the autism puzzle. However, many questions remain unanswered, and new questions are raised by recent results. Moreover, given the amount of evidence supporting a significant contribution of environmental factors to autism risk, it is now clear that the search for environmental factors should be reinforced. One aspect of this search that has been neglected so far is the study of interactions between genes and environmental factors. PMID:23226953

Predicting type 2 diabetes using genetic and environmental risk factors in a multi-ethnic Malaysian cohort.

PubMed

Abdullah, N; Abdul Murad, N A; Mohd Haniff, E A; Syafruddin, S E; Attia, J; Oldmeadow, C; Kamaruddin, M A; Abd Jalal, N; Ismail, N; Ishak, M; Jamal, R; Scott, R J; Holliday, E G

2017-08-01

Malaysia has a high and rising prevalence of type 2 diabetes (T2D). While environmental (non-genetic) risk factors for the disease are well established, the role of genetic variations and gene-environment interactions remain understudied in this population. This study aimed to estimate the relative contributions of environmental and genetic risk factors to T2D in Malaysia and also to assess evidence for gene-environment interactions that may explain additional risk variation. This was a case-control study including 1604 Malays, 1654 Chinese and 1728 Indians from the Malaysian Cohort Project. The proportion of T2D risk variance explained by known genetic and environmental factors was assessed by fitting multivariable logistic regression models and evaluating McFadden's pseudo R 2 and the area under the receiver-operating characteristic curve (AUC). Models with and without the genetic risk score (GRS) were compared using the log likelihood ratio Chi-squared test and AUCs. Multiplicative interaction between genetic and environmental risk factors was assessed via logistic regression within and across ancestral groups. Interactions were assessed for the GRS and its 62 constituent variants. The models including environmental risk factors only had pseudo R 2 values of 16.5-28.3% and AUC of 0.75-0.83. Incorporating a genetic score aggregating 62 T2D-associated risk variants significantly increased the model fit (likelihood ratio P-value of 2.50 × 10 -4 -4.83 × 10 -12 ) and increased the pseudo R 2 by about 1-2% and AUC by 1-3%. None of the gene-environment interactions reached significance after multiple testing adjustment, either for the GRS or individual variants. For individual variants, 33 out of 310 tested associations showed nominal statistical significance with 0.001 < P < 0.05. This study suggests that known genetic risk variants contribute a significant but small amount to overall T2D risk variation in Malaysian population groups. If gene-environment interactions involving common genetic variants exist, they are likely of small effect, requiring substantially larger samples for detection. Copyright © 2017 The Royal Society for Public Health. All rights reserved.

GENE-ENVIRONMENT INTERACTIONS: A REVIEW OF EFFECTS ON REPRODUCTION AND DEVELOPMENT

EPA Science Inventory

Polymorphisms in genes can lead to differences in the level of susceptibility of individuals to potentially adverse effects of environmental influences, such as chemical exposure, on prenatal development or male or female reproductive function. We have reviewed the literature in ...

Four-fluid MHD Simulations of the Plasma and Neutral Gas Environment of Comet Churyumov-Gerasimenko Near Perihelion

NASA Astrophysics Data System (ADS)

Huang, Z.; Toth, G.; Gombosi, T.; Jia, X.; Rubin, M.; Fougere, N.; Tenishev, V.; Combi, M.; Bieler, A.; Hansen, K.; Shou, Y.; Altwegg, K.

2015-10-01

We develop a 3-D four fluid model to study the plasma environment of comet Churyumov- Gerasimenko (CG), which is the target of the Rosetta mission. Our model is based on BATS-R-US within the SWMF (Space Weather Modeling Framework) that solves the governing multifluid MHD equations and and the Euler equations for the neutral gas fluid. These equations describe the behavior and interactions of the cometary heavy ions, the solar wind protons, the electrons, and the neutrals. This model incorporates mass loading processes, including photo and electron impact ionization, furthermore taken into account are charge exchange, dissociative ion-electron recombination, as well as collisional interactions between different fluids. We simulate the near nucleus plasma and neutral gas environment with a realistic shape model of CG near perihelion and compare our simulation results with Rosetta observations.

The influence of gene-environment interactions on GHR and IGF-1 expression and their association with growth in brook charr, Salvelinus fontinalis (Mitchill)

PubMed Central

Côté, Guillaume; Perry, Guy; Blier, Pierre; Bernatchez, Louis

2007-01-01

Background Quantitative reaction norm theory proposes that genotype-by-environment interaction (GxE) results from inter-individual differences of expression in adaptive suites of genes in distinct environments. However, environmental norms for actual gene suites are poorly documented. In this study, we investigated the effects of GxE interactions on levels of gene transcription and growth by documenting the impact of rearing environment (freshwater vs. saltwater), sex and genotypic (low vs. high estimated breeding value EBV) effects on the transcription level of insulin-like growth factor (IGF-1) and growth hormone receptor (GHR) in brook charr (Salvelinus fontinalis). Results Males grew faster than females (μ♀ = 1.20 ± 0.07 g·d-1, μ♂ = 1.46 ± 0.06 g·d-1) and high-EBV fish faster than low-EBV fish (μLOW = 0.97 ± 0.05 g·d-1, μHIGH = 1.58 ± 0.07 g·d-1; p < 0.05). However, growth was markedly lower in saltwater-reared fish than freshwater sibs (μFW = 1.52 ± 0.07 g·d-1, μSW = 1.15 ± 0.06 g·d-1), yet GHR mRNA transcription level was significantly higher in saltwater than in freshwater (μSW = 0.85 ± 0.05, μFW = 0.61 ± 0.05). The ratio of actual growth to units in assayed mRNA ('individual transcript efficiency', iTE; g·d-1·u-1) also differed among EBV groups (μLOW = 2.0 ± 0.24 g·d-1·u-1; μHIGH = 3.7 ± 0.24 g·d-1·u-1) and environments (μSW = 2.0 ± 0.25 g·d-1·u-1; μFW = 3.7 ± 0.25 g·d-1·u-1) for GHR. Males had a lower iTE for GHR than females (μ♂ = 2.4 ± 0.29 g·d-1·u-1; μ♀ = 3.1 ± 0.23 g·d-1·u-1). There was no difference in IGF-1 transcription level between environments (p > 0.7) or EBV groups (p > 0.15) but the level of IGF-1 was four times higher in males than females (μ♂ = 2.4 ± 0.11, μ♀ = 0.58 ± 0.09; p < 0.0001). We detected significant sexual differences in iTE (μ♂ = 1.3 ± 0.59 g·d-1·u-1; μ♀ = 3.9 ± 0.47 g·d-1·u-1), salinities (μSW = 2.3 ± 0.52 g·d-1·u-1; μFW = 3.7 ± 0.53 g·d-1·u-1) and EBV-groups (μLOW = 2.4 ± 0.49 g·d-1·u-1; μHIGH = 3.8 ± 0.49 g·d-1·u-1). Interaction between EBV-group and environment was detected for both GHR (p = 0.027) and IGF-1 (p = 0.019), and for iTE in the two genes (p < 0.0001; p < 0.05, respectively), where increased divergence in levels of GHR and IGF-1 transcription occurred among EBV-groups in the saltwater environment. Conclusion Our results show that both environment and sex have major impacts on the expression of mRNA for two key genes involved in the physiological pathway for growth. We also demonstrate for the first time, at least in fish, genotype-by-environment interaction at the level of individual gene transcription. This work contributes significantly to ongoing efforts towards documenting environmentally and sexually induced variance of gene activity and understanding the resulting phenotypes. PMID:18154679

Leveraging Gene-Environment Interactions and Endotypes for Asthma Gene Discovery

PubMed Central

Bønnelykke, Klaus; Ober, Carole

2016-01-01

Asthma is a heterogeneous clinical syndrome that includes subtypes of disease with different underlying causes and disease mechanisms. Asthma is caused by a complex interaction between genes and environmental exposures; early-life exposures in particular play an important role. Asthma is also heritable, and a number of susceptibility variants have been discovered in genome-wide association studies, although the known risk alleles explain only a small proportion of the heritability. In this review, we present evidence supporting the hypothesis that focusing on more specific asthma phenotypes, such as childhood asthma with severe exacerbations, and on relevant exposures that are involved in gene-environment interactions (GEIs), such as rhinovirus infections, will improve detection of asthma genes and our understanding of the underlying mechanisms. We will discuss the challenges of considering GEIs and the advantages of studying responses to asthma-associated exposures in clinical birth cohorts, as well as in cell models of GEIs, to dissect the context-specific nature of genotypic risks, to prioritize variants in genome-wide association studies, and to identify pathways involved in pathogenesis in subgroups of patients. We propose that such approaches, in spite of their many challenges, present great opportunities for better understanding of asthma pathogenesis and heterogeneity and, ultimately, for improving prevention and treatment of disease. PMID:26947980

Genetic Basis Underlying Correlations Among Growth Duration and Yield Traits Revealed by GWAS in Rice (Oryza sativa L.).

PubMed

Li, Fengmei; Xie, Jianyin; Zhu, Xiaoyang; Wang, Xueqiang; Zhao, Yan; Ma, Xiaoqian; Zhang, Zhanying; Rashid, Muhammad A R; Zhang, Zhifang; Zhi, Linran; Zhang, Shuyang; Li, Jinjie; Li, Zichao; Zhang, Hongliang

2018-01-01

Avoidance of disadvantageous genetic correlations among growth duration and yield traits is critical in developing crop varieties that efficiently use light and energy resources and produce high yields. To understand the genetic basis underlying the correlations among heading date and three major yield traits in rice, we investigated the four traits in a diverse and representative core collection of 266 cultivated rice accessions in both long-day and short-day environments, and conducted the genome-wide association study using 4.6 million single nucleotide polymorphisms (SNPs). There were clear positive correlation between heading date and grain number per panicle, and negative correlation between grain number per panicle and panicle number, as well as different degrees of correlations among other traits in different subspecies and environments. We detected 47 pleiotropic genes in 15 pleiotropic quantitative trait loci (pQTLs), 18 pleiotropic genes containing 37 pleiotropic SNPs in 8 pQTLs, 27 pQTLs with r 2 of linkage disequilibrium higher than 0.2, and 39 pairs of interactive genes from 8 metabolic pathways that may contribute to the above phenotypic correlations, but these genetic bases were different for correlations among different traits. Distributions of haplotypes revealed that selection for pleiotropic genes or interactive genes controlling different traits focused on genotypes with weak effect or on those balancing two traits that maximized production but sometimes their utilization strategies depend on the traits and environment. Detection of pQTLs and interactive genes and associated molecular markers will provide an ability to overcome disadvantageous correlations and to utilize the advantageous correlations among traits through marker-assisted selection in breeding.

On meta- and mega-analyses for gene–environment interactions

PubMed Central

Huang, Jing; Liu, Yulun; Vitale, Steve; Penning, Trevor M.; Whitehead, Alexander S.; Blair, Ian A.; Vachani, Anil; Clapper, Margie L.; Muscat, Joshua E.; Lazarus, Philip; Scheet, Paul; Moore, Jason H.; Chen, Yong

2017-01-01

Gene-by-environment (G × E) interactions are important in explaining the missing heritability and understanding the causation of complex diseases, but a single, moderately sized study often has limited statistical power to detect such interactions. With the increasing need for integrating data and reporting results from multiple collaborative studies or sites, debate over choice between mega- versus meta-analysis continues. In principle, data from different sites can be integrated at the individual level into a “mega” data set, which can be fit by a joint “mega-analysis.” Alternatively, analyses can be done at each site, and results across sites can be combined through a “meta-analysis” procedure without integrating individual level data across sites. Although mega-analysis has been advocated in several recent initiatives, meta-analysis has the advantages of simplicity and feasibility, and has recently led to several important findings in identifying main genetic effects. In this paper, we conducted empirical and simulation studies, using data from a G × E study of lung cancer, to compare the mega- and meta-analyses in four commonly used G × E analyses under the scenario that the number of studies is small and sample sizes of individual studies are relatively large. We compared the two data integration approaches in the context of fixed effect models and random effects models separately. Our investigations provide valuable insights in understanding the differences between mega- and meta-analyses in practice of combining small number of studies in identifying G × E interactions. PMID:29110346

Moderation of maltreatment effects on childhood borderline personality symptoms by gender and oxytocin receptor and FK506 binding protein 5 genes.

PubMed

Cicchetti, Dante; Rogosch, Fred A; Hecht, Kathryn F; Crick, Nicki R; Hetzel, Susan

2014-08-01

In this investigation, gene-environment-gender interaction effects in predicting child borderline personality disorder symptomatology among maltreated and nonmaltreated low-income children (N = 1,051) were examined. In the context of a summer research camp, adult-, peer-, and self-report assessments of borderline precursor indicators were obtained, as well as child self-report on the Borderline Personality Features Scale for Children. Genetic variants of the oxytocin receptor genotype and the FK506 binding protein 5 gene CATT haplotype were investigated. Children who self-reported high levels of borderline personality symptomatology were differentiated by adults, peers, and additional self-report on indicators of emotional instability, conflictual relationships with peers and adults, preoccupied attachment, and indicators of self-harm and suicidal ideation. Maltreated children also were more likely to evince many of these difficulties relative to nonmaltreated children. A series of analyses of covariance, controlling for age and ancestrally informative markers, indicated significant Maltreatment × Gene × Gender three-way interactions. Consideration of the maltreatment parameters of subtype, onset, and recency expanded understanding of variation among maltreated children. The three-way interaction effects demonstrated differential patterns among girls and boys. Among girls, the gene-environment interaction was more consistent with a diathesis-stress model, whereas among boys a differential-sensitivity interaction effect was indicated. Moreover, the genetic variants associated with greater risk for higher borderline symptomatology, dependent on maltreatment experiences, were opposite in girls compared to boys. The findings have important implications for understanding variability in early predictors of borderline personality pathology.

Performance implications of leader briefings and team-interaction training for team adaptation to novel environments.

PubMed

Marks, M A; Zaccaro, S J; Mathieu, J E

2000-12-01

The authors examined how leader briefings and team-interaction training influence team members' knowledge structures concerning processes related to effective performance in both routine and novel environments. Two-hundred thirty-seven undergraduates from a large mid-Atlantic university formed 79 three-member tank platoon teams and participated in a low-fidelity tank simulation. Team-interaction training, leader briefings, and novelty of performance environment were manipulated. Findings indicated that both leader briefings and team-interaction training affected the development of mental models, which in turn positively influenced team communication processes and team performance. Mental models and communication processes predicted performance more strongly in novel than in routine environments. Implications for the role of team-interaction training, leader briefings, and mental models as mechanisms for team adaptation are discussed.

Gene-environment interactions in geriatric depression.

PubMed

Lotrich, Francis E

2011-06-01

In older adults, several environmental challenges can potentially trigger the onset of an episode of major depression. Vulnerability to these challenges can be influenced by genetics. There is accumulating evidence for an interaction between stress and a serotonin transporter polymorphism, though there is also heterogeneity among studies. Other relevant genes include those encoding for the neuroendocrine stress axis, growth factors, and other monoaminergic systems. Each of these may interact with either predisposing traumas in early childhood or precipitating events later in life. Copyright © 2011 Elsevier Inc. All rights reserved.

A virtual therapeutic environment with user projective agents.

PubMed

Ookita, S Y; Tokuda, H

2001-02-01

Today, we see the Internet as more than just an information infrastructure, but a socializing place and a safe outlet of inner feelings. Many personalities develop aside from real world life due to its anonymous environment. Virtual world interactions are bringing about new psychological illnesses ranging from netaddiction to technostress, as well as online personality disorders and conflicts in multiple identities that exist in the virtual world. Presently, there are no standard therapy models for the virtual environment. There are very few therapeutic environments, or tools especially made for virtual therapeutic environments. The goal of our research is to provide the therapy model and middleware tools for psychologists to use in virtual therapeutic environments. We propose the Cyber Therapy Model, and Projective Agents, a tool used in the therapeutic environment. To evaluate the effectiveness of the tool, we created a prototype system, called the Virtual Group Counseling System, which is a therapeutic environment that allows the user to participate in group counseling through the eyes of their Projective Agent. Projective Agents inherit the user's personality traits. During the virtual group counseling, the user's Projective Agent interacts and collaborates to recover and increase their psychological growth. The prototype system provides a simulation environment where psychologists can adjust the parameters and customize their own simulation environment. The model and tool is a first attempt toward simulating online personalities that may exist only online, and provide data for observation.

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

PubMed

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.

Multifluid MHD Simulations of the Plasma Environment of Comet Churyumov-Gerasimenko at Different Heliocentric Distances

NASA Astrophysics Data System (ADS)

Huang, Z.; Jia, X.; Rubin, M.; Fougere, N.; Gombosi, T. I.; Tenishev, V.; Combi, M. R.; Bieler, A. M.; Toth, G.; Hansen, K. C.; Shou, Y.

2014-12-01

We study the plasma environment of the comet Churyumov-Gerasimenko, which is the target of the Rosetta mission, by performing large scale numerical simulations. Our model is based on BATS-R-US within the Space Weather Modeling Framework that solves the governing multifluid MHD equations, which describe the behavior of the cometary heavy ions, the solar wind protons, and electrons. The model includes various mass loading processes, including ionization, charge exchange, dissociative ion-electron recombination, as well as collisional interactions between different fluids. The neutral background used in our MHD simulations is provided by a kinetic Direct Simulation Monte Carlo (DSMC) model. We will simulate how the cometary plasma environment changes at different heliocentric distances.

Interactome of Obesity: Obesidome : Genetic Obesity, Stress Induced Obesity, Pathogenic Obesity Interaction.

PubMed

Geronikolou, Styliani A; Pavlopoulou, Athanasia; Cokkinos, Dennis; Chrousos, George

2017-01-01

Obesity is a chronic disease of increasing prevalence reaching epidemic proportions. Genetic defects as well as epigenetic effects contribute to the obesity phenotype. Investigating gene (e.g. MC4R defects)-environment (behavior, infectious agents, stress) interactions is a relative new field of great research interest. In this study, we have made an effort to create an interactome (henceforth referred to as "obesidome"), where extrinsic stressors response, intrinsic predisposition, immunity response to inflammation and autonomous nervous system implications are integrated. These pathways are presented in one interactome network for the first time. In our study, obesity-related genes/gene products were found to form a complex interactions network.

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

PubMed Central

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:25522433

Supportive Family Environments, Genes That Confer Sensitivity, and Allostatic Load Among Rural African American Emerging Adults: A Prospective Analysis

PubMed Central

Brody, Gene H.; Yu, Tianyi; Chen, Yi-fu; Kogan, Steven M.; Evans, Gary W.; Windle, Michael; Gerrard, Meg; Gibbons, Frederick X.; Simons, Ronald L.; Philibert, Robert A.

2012-01-01

The purpose of this study was to investigate interactions between exposure to supportive family environments and genetic characteristics, which were hypothesized to forecast variations in allostatic load (AL) in a representative sample of 315 rural African American youths. Data on family environments were gathered when youths were 11–13, and genetic data were collected when they were 16, years of age. Data on AL were obtained at the beginning of emerging adulthood, age 19 years. The data analyses revealed that, as predicted, emerging adults exposed to less supportive family environments across preadolescence manifested higher levels of AL when they carried the short (s) allele at the 5-HTTLPR and an allele of DRD4 with 7 or more repeats. This is an E(family environment) × G(5-HTTLPR status) × G(DRD4 status) interaction. These data suggest that African American youths carrying genes that confer sensitivity who are exposed to less supportive family environments may be at greater risk for adverse physical health consequences that AL presages. PMID:22468688

Empirically Derived and Simulated Sensitivity of Vegetation to Climate Across Global Gradients of Temperature and Precipitation

NASA Astrophysics Data System (ADS)

Quetin, G. R.; Swann, A. L. S.

2017-12-01

Successfully predicting the state of vegetation in a novel environment is dependent on our process level understanding of the ecosystem and its interactions with the environment. We derive a global empirical map of the sensitivity of vegetation to climate using the response of satellite-observed greenness and leaf area to interannual variations in temperature and precipitation. Our analysis provides observations of ecosystem functioning; the vegetation interactions with the physical environment, across a wide range of climates and provide a functional constraint for hypotheses engendered in process-based models. We infer mechanisms constraining ecosystem functioning by contrasting how the observed and simulated sensitivity of vegetation to climate varies across climate space. Our analysis yields empirical evidence for multiple physical and biological mediators of the sensitivity of vegetation to climate as a systematic change across climate space. Our comparison of remote sensing-based vegetation sensitivity with modeled estimates provides evidence for which physiological mechanisms - photosynthetic efficiency, respiration, water supply, atmospheric water demand, and sunlight availability - dominate the ecosystem functioning in places with different climates. Earth system models are generally successful in reproducing the broad sign and shape of ecosystem functioning across climate space. However, this general agreement breaks down in hot wet climates where models simulate less leaf area during a warmer year, while observations show a mixed response but overall more leaf area during warmer years. In addition, simulated ecosystem interaction with temperature is generally larger and changes more rapidly across a gradient of temperature than is observed. We hypothesize that the amplified interaction and change are both due to a lack of adaptation and acclimation in simulations. This discrepancy with observations suggests that simulated responses of vegetation to global warming, and feedbacks between vegetation and climate, are too strong in the models.

Gene-environment interplay in the etiology of psychosis.

PubMed

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.

Is Lead Exposure in Early Life An Environmental Risk Factor for Schizophrenia? Neurobiological Connections and Testable Hypotheses

PubMed Central

Guilarte, Tomás R.; Opler, Mark; Pletnikov, Mikhail

2013-01-01

Schizophrenia is a devastating neuropsychiatric disorder of unknown etiology. There is general agreement in the scientific community that schizophrenia is a disorder of neurodevelopmental origin in which both genes and environmental factors come together to produce a schizophrenia phenotype later in life. The challenging questions have been which genes and what environmental factors? Although there is evidence that different chromosome loci and several genes impart susceptibility for schizophrenia; and epidemiological studies point to broad aspects of the environment, only recently there has been an interest in studying gene × environment interactions. Recent evidence of a potential association between prenatal lead (Pb2+) exposure and schizophrenia precipitated the search for plausible neurobiological connections. The most promising connection is that in schizophrenia and in developmental Pb2+ exposure there is strong evidence for hypoactivity of the N-methyl-d-aspartate (NMDA) subtype of excitatory amino acid receptors as an underlying neurobiological mechanism in both conditions. A hypofunction of the NMDA receptor (NMDAR) complex during critical periods of development may alter neurobiological processes that are essential for brain growth and wiring, synaptic plasticity and cognitive and behavioral outcomes associated with schizophrenia. We also describe on-going proof of concept gene-environment interaction studies of early life Pb2+ exposure in mice expressing the human mutant form of the disrupted in schizophrenia 1 (DISC-1) gene, a gene that is strongly associated with schizophrenia and allied mental disorders. PMID:22178136

Assessment of the Potential Impacts of Wheat Plant Traits across Environments by Combining Crop Modeling and Global Sensitivity Analysis

PubMed Central

Casadebaig, Pierre; Zheng, Bangyou; Chapman, Scott; Huth, Neil; Faivre, Robert; Chenu, Karine

2016-01-01

A crop can be viewed as a complex system with outputs (e.g. yield) that are affected by inputs of genetic, physiology, pedo-climatic and management information. Application of numerical methods for model exploration assist in evaluating the major most influential inputs, providing the simulation model is a credible description of the biological system. A sensitivity analysis was used to assess the simulated impact on yield of a suite of traits involved in major processes of crop growth and development, and to evaluate how the simulated value of such traits varies across environments and in relation to other traits (which can be interpreted as a virtual change in genetic background). The study focused on wheat in Australia, with an emphasis on adaptation to low rainfall conditions. A large set of traits (90) was evaluated in a wide target population of environments (4 sites × 125 years), management practices (3 sowing dates × 3 nitrogen fertilization levels) and CO2 (2 levels). The Morris sensitivity analysis method was used to sample the parameter space and reduce computational requirements, while maintaining a realistic representation of the targeted trait × environment × management landscape (∼ 82 million individual simulations in total). The patterns of parameter × environment × management interactions were investigated for the most influential parameters, considering a potential genetic range of +/- 20% compared to a reference cultivar. Main (i.e. linear) and interaction (i.e. non-linear and interaction) sensitivity indices calculated for most of APSIM-Wheat parameters allowed the identification of 42 parameters substantially impacting yield in most target environments. Among these, a subset of parameters related to phenology, resource acquisition, resource use efficiency and biomass allocation were identified as potential candidates for crop (and model) improvement. PMID:26799483

Assessment of the Potential Impacts of Wheat Plant Traits across Environments by Combining Crop Modeling and Global Sensitivity Analysis.

PubMed

Casadebaig, Pierre; Zheng, Bangyou; Chapman, Scott; Huth, Neil; Faivre, Robert; Chenu, Karine

2016-01-01

A crop can be viewed as a complex system with outputs (e.g. yield) that are affected by inputs of genetic, physiology, pedo-climatic and management information. Application of numerical methods for model exploration assist in evaluating the major most influential inputs, providing the simulation model is a credible description of the biological system. A sensitivity analysis was used to assess the simulated impact on yield of a suite of traits involved in major processes of crop growth and development, and to evaluate how the simulated value of such traits varies across environments and in relation to other traits (which can be interpreted as a virtual change in genetic background). The study focused on wheat in Australia, with an emphasis on adaptation to low rainfall conditions. A large set of traits (90) was evaluated in a wide target population of environments (4 sites × 125 years), management practices (3 sowing dates × 3 nitrogen fertilization levels) and CO2 (2 levels). The Morris sensitivity analysis method was used to sample the parameter space and reduce computational requirements, while maintaining a realistic representation of the targeted trait × environment × management landscape (∼ 82 million individual simulations in total). The patterns of parameter × environment × management interactions were investigated for the most influential parameters, considering a potential genetic range of +/- 20% compared to a reference cultivar. Main (i.e. linear) and interaction (i.e. non-linear and interaction) sensitivity indices calculated for most of APSIM-Wheat parameters allowed the identification of 42 parameters substantially impacting yield in most target environments. Among these, a subset of parameters related to phenology, resource acquisition, resource use efficiency and biomass allocation were identified as potential candidates for crop (and model) improvement.

Dissection of complicate genetic architecture and breeding perspective of cottonseed traits by genome-wide association study.

PubMed

Du, Xiongming; Liu, Shouye; Sun, Junling; Zhang, Gengyun; Jia, Yinhua; Pan, Zhaoe; Xiang, Haitao; He, Shoupu; Xia, Qiuju; Xiao, Songhua; Shi, Weijun; Quan, Zhiwu; Liu, Jianguang; Ma, Jun; Pang, Baoyin; Wang, Liru; Sun, Gaofei; Gong, Wenfang; Jenkins, Johnie N; Lou, Xiangyang; Zhu, Jun; Xu, Haiming

2018-06-13

Cottonseed is one of the most important raw materials for plant protein, oil and alternative biofuel for diesel engines. Understanding the complex genetic basis of cottonseed traits is requisite for achieving efficient genetic improvement of the traits. However, it is not yet clear about their genetic architecture in genomic level. GWAS has been an effective way to explore genetic basis of quantitative traits in human and many crops. This study aims to dissect genetic mechanism seven cottonseed traits by a GWAS for genetic improvement. A genome-wide association study (GWAS) based on a full gene model with gene effects as fixed and gene-environment interaction as random, was conducted for protein, oil and 5 fatty acids using 316 accessions and ~ 390 K SNPs. Totally, 124 significant quantitative trait SNPs (QTSs), consisting of 16, 21, 87 for protein, oil and fatty acids (palmitic, linoleic, oleic, myristic, stearic), respectively, were identified and the broad-sense heritability was estimated from 71.62 to 93.43%; no QTS-environment interaction was detected for the protein, the palmitic and the oleic contents; the protein content was predominantly controlled by epistatic effects accounting for 65.18% of the total variation, but the oil content and the fatty acids except the palmitic were mainly determined by gene main effects and no epistasis was detected for the myristic and the stearic. Prediction of superior pure line and hybrid revealed the potential of the QTSs in the improvement of cottonseed traits, and the hybrid could achieve higher or lower genetic values compared with pure lines. This study revealed complex genetic architecture of seven cottonseed traits at whole genome-wide by mixed linear model approach; the identified genetic variants and estimated genetic component effects of gene, gene-gene and gene-environment interaction provide cotton geneticist or breeders new knowledge on the genetic mechanism of the traits and the potential molecular breeding design strategy.

Robot, computer problem solving system

NASA Technical Reports Server (NTRS)

Becker, J. D.

1972-01-01

The development of a computer problem solving system is reported that considers physical problems faced by an artificial robot moving around in a complex environment. Fundamental interaction constraints with a real environment are simulated for the robot by visual scan and creation of an internal environmental model. The programming system used in constructing the problem solving system for the simulated robot and its simulated world environment is outlined together with the task that the system is capable of performing. A very general framework for understanding the relationship between an observed behavior and an adequate description of that behavior is included.

Developmental programming: Interaction between prenatal BPA and postnatal overfeeding on cardiac tissue gene expression in female sheep.

PubMed

Koneva, L A; Vyas, A K; McEachin, R C; Puttabyatappa, M; Wang, H-S; Sartor, M A; Padmanabhan, V

2017-01-01

Epidemiologic studies and studies in rodents point to potential risks from developmental exposure to BPA on cardiometabolic diseases. Furthermore, it is becoming increasingly evident that the manifestation and severity of adverse outcomes is the result of interaction between developmental insults and the prevailing environment. Consistent with this premise, recent studies in sheep found prenatal BPA treatment prevented the adverse effects of postnatal obesity in inducing hypertension. The gene networks underlying these complex interactions are not known. mRNA-seq of myocardium was performed on four groups of four female sheep to assess the effects of prenatal BPA exposure, postnatal overfeeding and their interaction on gene transcription, pathway perturbations and functional effects. The effects of prenatal exposure to BPA, postnatal overfeeding, and prenatal BPA with postnatal overfeeding all resulted in transcriptional changes (85-141 significant differentially expressed genes). Although the effects of prenatal BPA and postnatal overfeeding did not involve dysregulation of many of the same genes, they affected a remarkably similar set of biological pathways. Furthermore, an additive or synergistic effect was not found in the combined treatment group, but rather prenatal BPA treatment led to a partial reversal of the effects of overfeeding alone. Many genes previously known to be affected by BPA and involved in obesity, hypertension, or heart disease were altered following these treatments, and AP-1, EGR1, and EGFR were key hubs affected by BPA and/or overfeeding. Environ. Mol. Mutagen. 58:4-18, 2017. © 2016 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Environmental and gene-environment interactions and risk of rheumatoid arthritis

PubMed Central

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

Enacting the molecular imperative: How gene-environment interaction research links bodies and environments in the post-genomic age.

PubMed

Darling, Katherine Weatherford; Ackerman, Sara L; Hiatt, Robert H; Lee, Sandra Soo-Jin; Shim, Janet K

2016-04-01

Despite a proclaimed shift from 'nature versus nurture' to 'genes and environment' paradigms within biomedical and genomic science, capturing the environment and identifying gene-environment interactions (GEIs) has remained a challenge. What does 'the environment' mean in the post-genomic age? In this paper, we present qualitative data from a study of 33 principal investigators funded by the U.S. National Institutes of Health to conduct etiological research on three complex diseases (cancer, cardiovascular disease and diabetes). We examine their research practices and perspectives on the environment through the concept of molecularization: the social processes and transformations through which phenomena (diseases, identities, pollution, food, racial/ethnic classifications) are re-defined in terms of their molecular components and described in the language of molecular biology. We show how GEI researchers' expansive conceptualizations of the environment ultimately yield to the imperative to molecularize and personalize the environment. They seek to 'go into the body' and re-work the boundaries between bodies and environments. In the process, they create epistemic hinges to facilitate a turn from efforts to understand social and environmental exposures outside the body, to quantifying their effects inside the body. GEI researchers respond to these emergent imperatives with a mixture of excitement, ambivalence and frustration. We reflect on how GEI researchers struggle to make meaning of molecules in their work, and how they grapple with molecularization as a methodological and rhetorical imperative as well as a process transforming biomedical research practices. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Comparative Study on Multifactor Dimensionality Reduction Methods for Detecting Gene-Gene Interactions with the Survival Phenotype

PubMed Central

Lee, Seungyeoun; Kim, Yongkang; Kwon, Min-Seok; Park, Taesung

2015-01-01

Genome-wide association studies (GWAS) have extensively analyzed single SNP effects on a wide variety of common and complex diseases and found many genetic variants associated with diseases. However, there is still a large portion of the genetic variants left unexplained. This missing heritability problem might be due to the analytical strategy that limits analyses to only single SNPs. One of possible approaches to the missing heritability problem is to consider identifying multi-SNP effects or gene-gene interactions. The multifactor dimensionality reduction method has been widely used to detect gene-gene interactions based on the constructive induction by classifying high-dimensional genotype combinations into one-dimensional variable with two attributes of high risk and low risk for the case-control study. Many modifications of MDR have been proposed and also extended to the survival phenotype. In this study, we propose several extensions of MDR for the survival phenotype and compare the proposed extensions with earlier MDR through comprehensive simulation studies. PMID:26339630

Simulation of the low earth orbital atomic oxygen interaction with materials by means of an oxygen ion beam

NASA Technical Reports Server (NTRS)

Banks, Bruce A.; Rutledge, Sharon K.; Paulsen, Phillip E.; Steuber, Thomas J.

1989-01-01

Atomic oxygen is the predominant species in low-Earth orbit between the altitudes of 180 and 650 km. These highly reactive atoms are a result of photodissociation of diatomic oxygen molecules from solar photons having a wavelength less than or equal to 2430A. Spacecraft in low-Earth orbit collide with atomic oxygen in the 3P ground state at impact energies of approximately 4.2 to 4.5 eV. As a consequence, organic materials previously used for high altitude geosynchronous spacecraft are severely oxidized in the low-Earth orbital environment. The evaluation of materials durability to atomic oxygen requires ground simulation of this environment to cost effectively screen materials for durability. Directed broad beam oxygen sources are necessary to evaluate potential spacecraft materials performance before and after exposure to the simulated low-Earth orbital environment. This paper presents a description of a low energy, broad oxygen ion beam source used to simulate the low-Earth orbital atomic oxygen environment. The results of materials interaction with this beam and comparison with actual in-space tests of the same meterials will be discussed. Resulting surface morphologies appear to closely replicate those observed in space tests.

MONALISA for stochastic simulations of Petri net models of biochemical systems.

PubMed

Balazki, Pavel; Lindauer, Klaus; Einloft, Jens; Ackermann, Jörg; Koch, Ina

2015-07-10

The concept of Petri nets (PN) is widely used in systems biology and allows modeling of complex biochemical systems like metabolic systems, signal transduction pathways, and gene expression networks. In particular, PN allows the topological analysis based on structural properties, which is important and useful when quantitative (kinetic) data are incomplete or unknown. Knowing the kinetic parameters, the simulation of time evolution of such models can help to study the dynamic behavior of the underlying system. If the number of involved entities (molecules) is low, a stochastic simulation should be preferred against the classical deterministic approach of solving ordinary differential equations. The Stochastic Simulation Algorithm (SSA) is a common method for such simulations. The combination of the qualitative and semi-quantitative PN modeling and stochastic analysis techniques provides a valuable approach in the field of systems biology. Here, we describe the implementation of stochastic analysis in a PN environment. We extended MONALISA - an open-source software for creation, visualization and analysis of PN - by several stochastic simulation methods. The simulation module offers four simulation modes, among them the stochastic mode with constant firing rates and Gillespie's algorithm as exact and approximate versions. The simulator is operated by a user-friendly graphical interface and accepts input data such as concentrations and reaction rate constants that are common parameters in the biological context. The key features of the simulation module are visualization of simulation, interactive plotting, export of results into a text file, mathematical expressions for describing simulation parameters, and up to 500 parallel simulations of the same parameter sets. To illustrate the method we discuss a model for insulin receptor recycling as case study. We present a software that combines the modeling power of Petri nets with stochastic simulation of dynamic processes in a user-friendly environment supported by an intuitive graphical interface. The program offers a valuable alternative to modeling, using ordinary differential equations, especially when simulating single-cell experiments with low molecule counts. The ability to use mathematical expressions provides an additional flexibility in describing the simulation parameters. The open-source distribution allows further extensions by third-party developers. The software is cross-platform and is licensed under the Artistic License 2.0.

Semiparametric Bayesian analysis of gene-environment interactions with error in measurement of environmental covariates and missing genetic data.

PubMed

Lobach, Iryna; Mallick, Bani; Carroll, Raymond J

2011-01-01

Case-control studies are widely used to detect gene-environment interactions in the etiology of complex diseases. Many variables that are of interest to biomedical researchers are difficult to measure on an individual level, e.g. nutrient intake, cigarette smoking exposure, long-term toxic exposure. Measurement error causes bias in parameter estimates, thus masking key features of data and leading to loss of power and spurious/masked associations. We develop a Bayesian methodology for analysis of case-control studies for the case when measurement error is present in an environmental covariate and the genetic variable has missing data. This approach offers several advantages. It allows prior information to enter the model to make estimation and inference more precise. The environmental covariates measured exactly are modeled completely nonparametrically. Further, information about the probability of disease can be incorporated in the estimation procedure to improve quality of parameter estimates, what cannot be done in conventional case-control studies. A unique feature of the procedure under investigation is that the analysis is based on a pseudo-likelihood function therefore conventional Bayesian techniques may not be technically correct. We propose an approach using Markov Chain Monte Carlo sampling as well as a computationally simple method based on an asymptotic posterior distribution. Simulation experiments demonstrated that our method produced parameter estimates that are nearly unbiased even for small sample sizes. An application of our method is illustrated using a population-based case-control study of the association between calcium intake with the risk of colorectal adenoma development.

Virtual environment display for a 3D audio room simulation

NASA Technical Reports Server (NTRS)

Chapin, William L.; Foster, Scott H.

1992-01-01

The development of a virtual environment simulation system integrating a 3D acoustic audio model with an immersive 3D visual scene is discussed. The system complements the acoustic model and is specified to: allow the listener to freely move about the space, a room of manipulable size, shape, and audio character, while interactively relocating the sound sources; reinforce the listener's feeling of telepresence in the acoustical environment with visual and proprioceptive sensations; enhance the audio with the graphic and interactive components, rather than overwhelm or reduce it; and serve as a research testbed and technology transfer demonstration. The hardware/software design of two demonstration systems, one installed and one portable, are discussed through the development of four iterative configurations.

Agreement for NASA/OAST - USAF/AFSC space interdependency on spacecraft environment interaction

NASA Technical Reports Server (NTRS)

Pike, C. P.; Stevens, N. J.

1980-01-01

A joint AF/NASA comprehensive program on spacecraft environment interactions consists of combined contractual and in house efforts aimed at understanding spacecraft environment ineraction phenomena and relating ground test results to space conditions. Activities include: (1) a concerted effort to identify project related environmental interactions; (2) a materials investigation to measure the basic properties of materials and develop or modify materials as needed; and (3) a ground simulation investigation to evaluate basic plasma interaction phenomena and provide inputs to the analytical modeling investigation. Systems performance is evaluated by both ground tests and analysis. There is an environmental impact investigation to determine the effect of future large spacecraft on the charged particle environment. Space flight investigations are planned to verify the results. The products of this program are test standards and design guidelines which summarize the technology, specify test criteria, and provide techniques to minimize or eliminate system interactions with the charged particle environment.

[New approaches in pharmacology: numerical modelling and simulation].

PubMed

Boissel, Jean-Pierre; Cucherat, Michel; Nony, Patrice; Dronne, Marie-Aimée; Kassaï, Behrouz; Chabaud, Sylvie

2005-01-01

The complexity of pathophysiological mechanisms is beyond the capabilities of traditional approaches. Many of the decision-making problems in public health, such as initiating mass screening, are complex. Progress in genomics and proteomics, and the resulting extraordinary increase in knowledge with regard to interactions between gene expression, the environment and behaviour, the customisation of risk factors and the need to combine therapies that individually have minimal though well documented efficacy, has led doctors to raise new questions: how to optimise choice and the application of therapeutic strategies at the individual rather than the group level, while taking into account all the available evidence? This is essentially a problem of complexity with dimensions similar to the previous ones: multiple parameters with nonlinear relationships between them, varying time scales that cannot be ignored etc. Numerical modelling and simulation (in silico investigations) have the potential to meet these challenges. Such approaches are considered in drug innovation and development. They require a multidisciplinary approach, and this will involve modification of the way research in pharmacology is conducted.

Research on Intelligent Synthesis Environments

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.; Lobeck, William E.

2002-01-01

Four research activities related to Intelligent Synthesis Environment (ISE) have been performed under this grant. The four activities are: 1) non-deterministic approaches that incorporate technologies such as intelligent software agents, visual simulations and other ISE technologies; 2) virtual labs that leverage modeling, simulation and information technologies to create an immersive, highly interactive virtual environment tailored to the needs of researchers and learners; 3) advanced learning modules that incorporate advanced instructional, user interface and intelligent agent technologies; and 4) assessment and continuous improvement of engineering team effectiveness in distributed collaborative environments.

Research on Intelligent Synthesis Environments

NASA Astrophysics Data System (ADS)

Noor, Ahmed K.; Loftin, R. Bowen

2002-12-01

Four research activities related to Intelligent Synthesis Environment (ISE) have been performed under this grant. The four activities are: 1) non-deterministic approaches that incorporate technologies such as intelligent software agents, visual simulations and other ISE technologies; 2) virtual labs that leverage modeling, simulation and information technologies to create an immersive, highly interactive virtual environment tailored to the needs of researchers and learners; 3) advanced learning modules that incorporate advanced instructional, user interface and intelligent agent technologies; and 4) assessment and continuous improvement of engineering team effectiveness in distributed collaborative environments.

Distributed interactive communication in simulated space-dwelling groups.

PubMed

Brady, Joseph V; Hienz, Robert D; Hursh, Steven R; Ragusa, Leonard C; Rouse, Charles O; Gasior, Eric D

2004-03-01

This report describes the development and preliminary application of an experimental test bed for modeling human behavior in the context of a computer generated environment to analyze the effects of variations in communication modalities, incentives and stressful conditions. In addition to detailing the methodological development of a simulated task environment that provides for electronic monitoring and recording of individual and group behavior, the initial substantive findings from an experimental analysis of distributed interactive communication in simulated space dwelling groups are described. Crews of three members each (male and female) participated in simulated "planetary missions" based upon a synthetic scenario task that required identification, collection, and analysis of geologic specimens with a range of grade values. The results of these preliminary studies showed clearly that cooperative and productive interactions were maintained between individually isolated and distributed individuals communicating and problem-solving effectively in a computer-generated "planetary" environment over extended time intervals without benefit of one another's physical presence. Studies on communication channel constraints confirmed the functional interchangeability between available modalities with the highest degree of interchangeability occurring between Audio and Text modes of communication. The effects of task-related incentives were determined by the conditions under which they were available with Positive Incentives effectively attenuating decrements in performance under stressful time pressure. c2003 Elsevier Ltd. All rights reserved.

Linear score tests for variance components in linear mixed models and applications to genetic association studies.

PubMed

Qu, Long; Guennel, Tobias; Marshall, Scott L

2013-12-01

Following the rapid development of genome-scale genotyping technologies, genetic association mapping has become a popular tool to detect genomic regions responsible for certain (disease) phenotypes, especially in early-phase pharmacogenomic studies with limited sample size. In response to such applications, a good association test needs to be (1) applicable to a wide range of possible genetic models, including, but not limited to, the presence of gene-by-environment or gene-by-gene interactions and non-linearity of a group of marker effects, (2) accurate in small samples, fast to compute on the genomic scale, and amenable to large scale multiple testing corrections, and (3) reasonably powerful to locate causal genomic regions. The kernel machine method represented in linear mixed models provides a viable solution by transforming the problem into testing the nullity of variance components. In this study, we consider score-based tests by choosing a statistic linear in the score function. When the model under the null hypothesis has only one error variance parameter, our test is exact in finite samples. When the null model has more than one variance parameter, we develop a new moment-based approximation that performs well in simulations. Through simulations and analysis of real data, we demonstrate that the new test possesses most of the aforementioned characteristics, especially when compared to existing quadratic score tests or restricted likelihood ratio tests. © 2013, The International Biometric Society.

A Comparison Study of Augmented Reality versus Interactive Simulation Technology to Support Student Learning of a Socio-Scientific Issue

ERIC Educational Resources Information Center

Chang, Hsin-Yi; Hsu, Ying-Shao; Wu, Hsin-Kai

2016-01-01

We investigated the impact of an augmented reality (AR) versus interactive simulation (IS) activity incorporated in a computer learning environment to facilitate students' learning of a socio-scientific issue (SSI) on nuclear power plants and radiation pollution. We employed a quasi-experimental research design. Two classes (a total of 45…

An integrated approach to infer dynamic protein-gene interactions - A case study of the human P53 protein.

PubMed

Wang, Junbai; Wu, Qianqian; Hu, Xiaohua Tony; Tian, Tianhai

2016-11-01

Investigating the dynamics of genetic regulatory networks through high throughput experimental data, such as microarray gene expression profiles, is a very important but challenging task. One of the major hindrances in building detailed mathematical models for genetic regulation is the large number of unknown model parameters. To tackle this challenge, a new integrated method is proposed by combining a top-down approach and a bottom-up approach. First, the top-down approach uses probabilistic graphical models to predict the network structure of DNA repair pathway that is regulated by the p53 protein. Two networks are predicted, namely a network of eight genes with eight inferred interactions and an extended network of 21 genes with 17 interactions. Then, the bottom-up approach using differential equation models is developed to study the detailed genetic regulations based on either a fully connected regulatory network or a gene network obtained by the top-down approach. Model simulation error, parameter identifiability and robustness property are used as criteria to select the optimal network. Simulation results together with permutation tests of input gene network structures indicate that the prediction accuracy and robustness property of the two predicted networks using the top-down approach are better than those of the corresponding fully connected networks. In particular, the proposed approach reduces computational cost significantly for inferring model parameters. Overall, the new integrated method is a promising approach for investigating the dynamics of genetic regulation. Copyright © 2016 Elsevier Inc. All rights reserved.

Understanding the Molecular Mechanisms Underpinning Gene by Environment Interactions in Psychiatric Disorders: The FKBP5 Model.

PubMed

Matosin, Natalie; Halldorsdottir, Thorhildur; Binder, Elisabeth B

2018-05-15

Epidemiologic and genetic studies suggest common environmental and genetic risk factors for a number of psychiatric disorders, including depression, bipolar disorder, and schizophrenia. Genetic and environmental factors, especially adverse life events, not only have main effects on disease development but also may interact to shape risk and resilience. Such gene by adversity interactions have been described for FKBP5, an endogenous regulator of the stress-neuroendocrine system, conferring risk for a number of psychiatric disorders. In this review, we present a molecular and cellular model of the consequences of FKBP5 by early adversity interactions. We illustrate how altered genetic and epigenetic regulation of FKBP5 may contribute to disease risk by covering evidence from clinical and preclinical studies of FKBP5 dysregulation, known cell-type and tissue-type expression patterns of FKBP5 in humans and animals, and the role of FKBP5 as a stress-responsive molecular hub modulating many cellular pathways. FKBP5 presents the possibility to better understand the molecular and cellular factors contributing to a disease-relevant gene by environment interaction, with implications for the development of biomarkers and interventions for psychiatric disorders. Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

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

PubMed Central

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

A novel differential susceptibility gene: CHRNA4 and moderation of the effect of maltreatment on child personality.

PubMed

Grazioplene, Rachael G; Deyoung, Colin G; Rogosch, Fred A; Cicchetti, Dante

2013-08-01

The differential susceptibility hypothesis states that some genetic variants that confer risk in adverse environments are beneficial in normal or nurturing environments. The cholinergic system is promising as a source of susceptibility genes because of its involvement in learning and neural plasticity. The cholinergic receptor gene CHRNA4 has been linked to characteristics related to the personality traits Neuroticism and Openness/Intellect. The effects of interaction between CHRNA4 genotype and maltreatment status on child personality were examined in a well matched sample of 339 maltreated and 275 non-maltreated children (aged 8-13 years). Variation in CHRNA4 interacted with childhood maltreatment to predict personality in a manner indicating differential susceptibility. The interaction of CHRNA4 and maltreatment status predicted Neuroticism and Openness/Intellect. Maltreated children with the rs1044396 T/T genotype scored highest on Neuroticism and showed no effect of genotype on Openness/Intellect. Non-maltreated children with this genotype scored lowest on Neuroticism and highest on Openness/Intellect. Variation in CHRNA4 appears to contribute to personality by affecting degree of developmental sensitivity to both normal and adverse environments. © 2012 The Authors. Journal of Child Psychology and Psychiatry © 2012 Association for Child and Adolescent Mental Health.

Serious Gaming for Test & Evaluation of Clean-Slate (Ab Initio) National Airspace System (NAS) Designs

NASA Technical Reports Server (NTRS)

Allen, B. Danette; Alexandrov, Natalia

2016-01-01

Incremental approaches to air transportation system development inherit current architectural constraints, which, in turn, place hard bounds on system capacity, efficiency of performance, and complexity. To enable airspace operations of the future, a clean-slate (ab initio) airspace design(s) must be considered. This ab initio National Airspace System (NAS) must be capable of accommodating increased traffic density, a broader diversity of aircraft, and on-demand mobility. System and subsystem designs should scale to accommodate the inevitable demand for airspace services that include large numbers of autonomous Unmanned Aerial Vehicles and a paradigm shift in general aviation (e.g., personal air vehicles) in addition to more traditional aerial vehicles such as commercial jetliners and weather balloons. The complex and adaptive nature of ab initio designs for the future NAS requires new approaches to validation, adding a significant physical experimentation component to analytical and simulation tools. In addition to software modeling and simulation, the ability to exercise system solutions in a flight environment will be an essential aspect of validation. The NASA Langley Research Center (LaRC) Autonomy Incubator seeks to develop a flight simulation infrastructure for ab initio modeling and simulation that assumes no specific NAS architecture and models vehicle-to-vehicle behavior to examine interactions and emergent behaviors among hundreds of intelligent aerial agents exhibiting collaborative, cooperative, coordinative, selfish, and malicious behaviors. The air transportation system of the future will be a complex adaptive system (CAS) characterized by complex and sometimes unpredictable (or unpredicted) behaviors that result from temporal and spatial interactions among large numbers of participants. A CAS not only evolves with a changing environment and adapts to it, it is closely coupled to all systems that constitute the environment. Thus, the ecosystem that contains the system and other systems evolves with the CAS as well. The effects of the emerging adaptation and co-evolution are difficult to capture with only combined mathematical and computational experimentation. Therefore, an ab initio flight simulation environment must accommodate individual vehicles, groups of self-organizing vehicles, and large-scale infrastructure behavior. Inspired by Massively Multiplayer Online Role Playing Games (MMORPG) and Serious Gaming, the proposed ab initio simulation environment is similar to online gaming environments in which player participants interact with each other, affect their environment, and expect the simulation to persist and change regardless of any individual player's active participation.

Gaming-simulation and health education an overview.

PubMed

Greenblat, C S

1977-01-01

Simulation entails abstraction and representation from a larger system in terms of process as well as structure. Central features are identified and simplified, less important elements are omitted from the model. In medical and health education, simulation enables learners to practice in an environment where mistakes are not costly, such as with simulated patients. Gaming-simulation incorporates role-playing into a defined system of interaction simulating a real world system and is characterized by the degree of structure of the roles and the focus on role interactions. Employment of gaming-simulation is embryonic in health education. Examples included in this Monograph concern problems of aging, hemophiliacs, and the dying; teaching interpersonal skills in psychiatric nursing; interactions of health care systems with their communities; and several other topics. Evaluation is discussed in a separate paper. A variety of health care gaming resources are described.

Studying social interactions through immersive virtual environment technology: virtues, pitfalls, and future challenges

PubMed Central

Bombari, Dario; Schmid Mast, Marianne; Canadas, Elena; Bachmann, Manuel

2015-01-01

The goal of the present review is to explain how immersive virtual environment technology (IVET) can be used for the study of social interactions and how the use of virtual humans in immersive virtual environments can advance research and application in many different fields. Researchers studying individual differences in social interactions are typically interested in keeping the behavior and the appearance of the interaction partner constant across participants. With IVET researchers have full control over the interaction partners, can standardize them while still keeping the simulation realistic. Virtual simulations are valid: growing evidence shows that indeed studies conducted with IVET can replicate some well-known findings of social psychology. Moreover, IVET allows researchers to subtly manipulate characteristics of the environment (e.g., visual cues to prime participants) or of the social partner (e.g., his/her race) to investigate their influences on participants’ behavior and cognition. Furthermore, manipulations that would be difficult or impossible in real life (e.g., changing participants’ height) can be easily obtained with IVET. Beside the advantages for theoretical research, we explore the most recent training and clinical applications of IVET, its integration with other technologies (e.g., social sensing) and future challenges for researchers (e.g., making the communication between virtual humans and participants smoother). PMID:26157414

Studying social interactions through immersive virtual environment technology: virtues, pitfalls, and future challenges.

PubMed

Bombari, Dario; Schmid Mast, Marianne; Canadas, Elena; Bachmann, Manuel

2015-01-01

The goal of the present review is to explain how immersive virtual environment technology (IVET) can be used for the study of social interactions and how the use of virtual humans in immersive virtual environments can advance research and application in many different fields. Researchers studying individual differences in social interactions are typically interested in keeping the behavior and the appearance of the interaction partner constant across participants. With IVET researchers have full control over the interaction partners, can standardize them while still keeping the simulation realistic. Virtual simulations are valid: growing evidence shows that indeed studies conducted with IVET can replicate some well-known findings of social psychology. Moreover, IVET allows researchers to subtly manipulate characteristics of the environment (e.g., visual cues to prime participants) or of the social partner (e.g., his/her race) to investigate their influences on participants' behavior and cognition. Furthermore, manipulations that would be difficult or impossible in real life (e.g., changing participants' height) can be easily obtained with IVET. Beside the advantages for theoretical research, we explore the most recent training and clinical applications of IVET, its integration with other technologies (e.g., social sensing) and future challenges for researchers (e.g., making the communication between virtual humans and participants smoother).

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

PubMed

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.

Gene-Environment Interplay in Physical, Psychological, and Cognitive Domains in Mid to Late Adulthood: Is APOE a Variability Gene?

PubMed

Reynolds, Chandra A; Gatz, Margaret; Christensen, Kaare; Christiansen, Lene; Dahl Aslan, Anna K; Kaprio, Jaakko; Korhonen, Tellervo; Kremen, William S; Krueger, Robert; McGue, Matt; Neiderhiser, Jenae M; Pedersen, Nancy L

2016-01-01

Despite emerging interest in gene-environment interaction (GxE) effects, there is a dearth of studies evaluating its potential relevance apart from specific hypothesized environments and biometrical variance trends. Using a monozygotic within-pair approach, we evaluated evidence of G×E for body mass index (BMI), depressive symptoms, and cognition (verbal, spatial, attention, working memory, perceptual speed) in twin studies from four countries. We also evaluated whether APOE is a 'variability gene' across these measures and whether it partly represents the 'G' in G×E effects. In all three domains, G×E effects were pervasive across country and gender, with small-to-moderate effects. Age-cohort trends were generally stable for BMI and depressive symptoms; however, they were variable-with both increasing and decreasing age-cohort trends-for different cognitive measures. Results also suggested that APOE may represent a 'variability gene' for depressive symptoms and spatial reasoning, but not for BMI or other cognitive measures. Hence, additional genes are salient beyond APOE.

The Dopamine Receptor D4 Gene ("DRD4") Moderates Family Environmental Effects on ADHD

ERIC Educational Resources Information Center

Martel, Michelle M.; Nikolas, Molly; Jernigan, Katherine; Friderici, Karen; Waldman, Irwin; Nigg, Joel T.

2011-01-01

Attention-Deficit/Hyperactivity Disorder (ADHD) is a prime candidate for exploration of gene-by-environment interaction (i.e., G x E), particularly in relation to dopamine system genes, due to strong evidence that dopamine systems are dysregulated in the disorder. Using a G x E design, we examined whether the "DRD4" promoter 120-bp tandem repeat…

Life Events, Genetic Susceptibility, and Smoking among Adolescents

PubMed Central

Pampel, Fred C.; Boardman, Jason D.; Daw, Jonathan; Stallings, Michael C.; Smolen, Andrew; Haberstick, Brett; Widaman, Keith F.; Neppl, Tricia K.; Conger, Rand D.

2015-01-01

Although stressful life events during adolescence are associated with the adoption of unhealthy behaviors such as smoking, both social circumstances and physical traits can moderate the relationship. This study builds on the stress paradigm and gene-environment approach to social behavior by examining how a polymorphism in the serotonin transporter gene 5-HTTLPR moderates the effect of life events on adolescent smoking. Tests of interaction hypotheses use data from the Family Transitions Project, a longitudinal study of 7th graders followed for 5 years. A sibling-pair design with separate models for the gender composition of pairs (brothers, sisters, or brother/sister) controls for unmeasured family background. The results show that negative life events are significantly and positively associated with smoking. Among brother pairs but not other pairs, the results provide evidence of gene-environment interaction by showing that life events more strongly influence smoking behavior for those with more copies of the 5-HTTLPR S allele. PMID:26463545

Real Time Bicycle Simulation Study of Bicyclists’ Behaviors and their Implication on Safety

DOT National Transportation Integrated Search

2017-06-30

The main goal of this study was to build a bicycle simulator and study the interaction between cyclists and other roadway users. The simulator developed was used in conjunction with Oculus Rift goggles to create a virtual cycling environment. The vir...

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

PubMed

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-set analyses offer promising new alternatives to analyses focusing on single candidate polymorphisms when examining the interplay between genetic and environmental factors.

The Genetic Architecture of Noise-Induced Hearing Loss: Evidence for a Gene-by-Environment Interaction.

PubMed

Lavinsky, Joel; Ge, Marshall; Crow, Amanda L; Pan, Calvin; Wang, Juemei; Salehi, Pezhman; Myint, Anthony; Eskin, Eleazar; Allayee, Hooman; Lusis, Aldons J; Friedman, Rick A

2016-10-13

The discovery of environmentally specific genetic effects is crucial to the understanding of complex traits, such as susceptibility to noise-induced hearing loss (NIHL). We describe the first genome-wide association study (GWAS) for NIHL in a large and well-characterized population of inbred mouse strains, known as the Hybrid Mouse Diversity Panel (HMDP). We recorded auditory brainstem response (ABR) thresholds both pre and post 2-hr exposure to 10-kHz octave band noise at 108 dB sound pressure level in 5-6-wk-old female mice from the HMDP (4-5 mice/strain). From the observation that NIHL susceptibility varied among the strains, we performed a GWAS with correction for population structure and mapped a locus on chromosome 6 that was statistically significantly associated with two adjacent frequencies. We then used a "genetical genomics" approach that included the analysis of cochlear eQTLs to identify candidate genes within the GWAS QTL. In order to validate the gene-by-environment interaction, we compared the effects of the postnoise exposure locus with that from the same unexposed strains. The most significant SNP at chromosome 6 (rs37517079) was associated with noise susceptibility, but was not significant at the same frequencies in our unexposed study. These findings demonstrate that the genetic architecture of NIHL is distinct from that of unexposed hearing levels and provide strong evidence for gene-by-environment interactions in NIHL. Copyright © 2016 Lavinsky et al.

Applying a Framework for Student Modeling in Exploratory Learning Environments: Comparing Data Representation Granularity to Handle Environment Complexity

ERIC Educational Resources Information Center

Fratamico, Lauren; Conati, Cristina; Kardan, Samad; Roll, Ido

2017-01-01

Interactive simulations can facilitate inquiry learning. However, similarly to other Exploratory Learning Environments, students may not always learn effectively in these unstructured environments. Thus, providing adaptive support has great potential to help improve student learning with these rich activities. Providing adaptive support requires a…

Cortico-limbic connectivity in MAOA-L carriers is vulnerable to acute tryptophan depletion.

PubMed

Eisner, Patrick; Klasen, Martin; Wolf, Dhana; Zerres, Klaus; Eggermann, Thomas; Eisert, Albrecht; Zvyagintsev, Mikhail; Sarkheil, Pegah; Mathiak, Krystyna A; Zepf, Florian; Mathiak, Klaus

2017-03-01

A gene-environment interaction between expression genotypes of the monoamine oxidase A (MAOA) and adverse childhood experience increases the risk of antisocial behavior. However, the neural underpinnings of this interaction remain uninvestigated. A cortico-limbic circuit involving the prefrontal cortex (PFC) and the amygdala is central to the suppression of aggressive impulses and is modulated by serotonin (5-HT). MAOA genotypes may modulate the vulnerability of this circuit and increase the risk for emotion regulation deficits after specific life events. Acute tryptophan depletion (ATD) challenges 5-HT regulation and may identify vulnerable neuronal circuits, contributing to the gene-environment interaction. Functional magnetic resonance imaging measured the resting-state state activity in 64 healthy males in a double-blind, placebo-controlled study. Cortical maps of amygdala correlation identified the impact of ATD and its interaction with low- (MAOA-L) and high-expression variants (MAOA-H) of MAOA on cortico-limbic connectivity. Across all Regions of Interest (ROIs) exhibiting an ATD effect on cortico-limbic connectivity, MAOA-L carriers were more susceptible to ATD than MAOA-H carriers. In particular, the MAOA-L group exhibited a larger reduction of amygdala connectivity with the right prefrontal cortex and a larger increase of amygdala connectivity with the insula and dorsal PCC. MAOA-L carriers were more susceptable to a central 5-HT challenge in cortico-limbic networks. Such vulnerability of the cortical serotonergic system may contribute to the emergence of antisocial behavior after systemic challenges, observed as gene-environment interaction. Hum Brain Mapp 38:1622-1635, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

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

PubMed

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.

Traffic and Driving Simulator Based on Architecture of Interactive Motion.

PubMed

Paz, Alexander; Veeramisti, Naveen; Khaddar, Romesh; de la Fuente-Mella, Hanns; Modorcea, Luiza

2015-01-01

This study proposes an architecture for an interactive motion-based traffic simulation environment. In order to enhance modeling realism involving actual human beings, the proposed architecture integrates multiple types of simulation, including: (i) motion-based driving simulation, (ii) pedestrian simulation, (iii) motorcycling and bicycling simulation, and (iv) traffic flow simulation. The architecture has been designed to enable the simulation of the entire network; as a result, the actual driver, pedestrian, and bike rider can navigate anywhere in the system. In addition, the background traffic interacts with the actual human beings. This is accomplished by using a hybrid mesomicroscopic traffic flow simulation modeling approach. The mesoscopic traffic flow simulation model loads the results of a user equilibrium traffic assignment solution and propagates the corresponding traffic through the entire system. The microscopic traffic flow simulation model provides background traffic around the vicinities where actual human beings are navigating the system. The two traffic flow simulation models interact continuously to update system conditions based on the interactions between actual humans and the fully simulated entities. Implementation efforts are currently in progress and some preliminary tests of individual components have been conducted. The implementation of the proposed architecture faces significant challenges ranging from multiplatform and multilanguage integration to multievent communication and coordination.

Traffic and Driving Simulator Based on Architecture of Interactive Motion

PubMed Central

Paz, Alexander; Veeramisti, Naveen; Khaddar, Romesh; de la Fuente-Mella, Hanns; Modorcea, Luiza

2015-01-01

This study proposes an architecture for an interactive motion-based traffic simulation environment. In order to enhance modeling realism involving actual human beings, the proposed architecture integrates multiple types of simulation, including: (i) motion-based driving simulation, (ii) pedestrian simulation, (iii) motorcycling and bicycling simulation, and (iv) traffic flow simulation. The architecture has been designed to enable the simulation of the entire network; as a result, the actual driver, pedestrian, and bike rider can navigate anywhere in the system. In addition, the background traffic interacts with the actual human beings. This is accomplished by using a hybrid mesomicroscopic traffic flow simulation modeling approach. The mesoscopic traffic flow simulation model loads the results of a user equilibrium traffic assignment solution and propagates the corresponding traffic through the entire system. The microscopic traffic flow simulation model provides background traffic around the vicinities where actual human beings are navigating the system. The two traffic flow simulation models interact continuously to update system conditions based on the interactions between actual humans and the fully simulated entities. Implementation efforts are currently in progress and some preliminary tests of individual components have been conducted. The implementation of the proposed architecture faces significant challenges ranging from multiplatform and multilanguage integration to multievent communication and coordination. PMID:26491711

Epigenetics and obesity: the devil is in the details.

PubMed

Franks, Paul W; Ling, Charlotte

2010-12-21

Obesity is a complex disease with multiple well-defined risk factors. Nevertheless, susceptibility to obesity and its sequelae within obesogenic environments varies greatly from one person to the next, suggesting a role for gene × environment interactions in the etiology of the disorder. Epigenetic regulation of the human genome provides a putative mechanism by which specific environmental exposures convey risk for obesity and other human diseases and is one possible mechanism that underlies the gene × environment/treatment interactions observed in epidemiological studies and clinical trials. A study published in BMC Medicine this month by Wang et al. reports on an examination of DNA methylation in peripheral blood leukocytes of lean and obese adolescents, comparing methylation patterns between the two groups. The authors identified two genes that were differentially methylated, both of which have roles in immune function. Here we overview the findings from this study in the context of those emerging from other recent genetic and epigenetic studies, discuss the strengths and weaknesses of the study and speculate on the future of epigenetics in chronic disease research.

Telearch - Integrated visual simulation environment for collaborative virtual archaeology.

NASA Astrophysics Data System (ADS)

Kurillo, Gregorij; Forte, Maurizio

Archaeologists collect vast amounts of digital data around the world; however, they lack tools for integration and collaborative interaction to support reconstruction and interpretation process. TeleArch software is aimed to integrate different data sources and provide real-time interaction tools for remote collaboration of geographically distributed scholars inside a shared virtual environment. The framework also includes audio, 2D and 3D video streaming technology to facilitate remote presence of users. In this paper, we present several experimental case studies to demonstrate the integration and interaction with 3D models and geographical information system (GIS) data in this collaborative environment.

Environmental stress alters genetic regulation of novelty seeking in vervet monkeys.

PubMed

Fairbanks, L A; Bailey, J N; Breidenthal, S E; Laudenslager, M L; Kaplan, J R; Jorgensen, M J

2011-08-01

Considerable attention has been paid to identifying genetic influences and gene-environment interactions that increase vulnerability to environmental stressors, with promising but inconsistent results. A nonhuman primate model is presented here that allows assessment of genetic influences in response to a stressful life event for a behavioural trait with relevance for psychopathology. Genetic and environmental influences on free-choice novelty seeking behaviour were assessed in a pedigreed colony of vervet monkeys before and after relocation from a low stress to a higher stress environment. Heritability of novelty seeking scores, and genetic correlations within and between environments were conducted using variance components analysis. The results showed that novelty seeking was markedly inhibited in the higher stress environment, with effects persisting across a 2-year period for adults but not for juveniles. There were significant genetic contributions to novelty seeking scores in each year (h(2) = 0.35-0.43), with high genetic correlations within each environment (rhoG > 0.80) and a lower genetic correlation (rhoG = 0.35, non-significant) between environments. There were also significant genetic contributions to individual change scores from before to after the move (h(2) = 0.48). These results indicate that genetic regulation of novelty seeking was modified by the level of environmental stress, and they support a role for gene-environment interactions in a behavioural trait with relevance for mental health. © 2011 The Authors. Genes, Brain and Behavior © 2011 Blackwell Publishing Ltd and International Behavioural and Neural Genetics Society.

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

PubMed

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.

The association of interacting neighborhood gene-environment risk with cortisol and blood pressure in African-American adults

PubMed Central

Coulon, Sandra M.; Wilson, Dawn K.; Van Horn, M. L.; Hand, Gregory A.; Kresovich, Stephen

2016-01-01

Background African-American adults are disproportionately affected by stress-related chronic conditions like high blood pressure (BP), and both environmental stress and genetic risk may play a role in its development. Purpose This study tested whether the dual risk of low neighborhood socioeconomic status (SES) and glucocorticoid genetic sensitivity interacted to predict waking cortisol and BP. Methods Cross-sectional waking cortisol and BP were collected from 208 African-American adults who were participating in a follow-up visit as part of the Positive Action for Today’s Health trial. Three single nucleotide polymorphisms were genotyped, salivary cortisol samples were collected, and neighborhood SES was calculated using 2010 Census data. Results The sample was mostly female (65%), with weight classified as overweight or obese (MBMI=32.74, SD=8.88), and a mean age of 55.64 (SD=15.21). The gene-by-neighborhood SES interaction predicted cortisol (B=0.235, p=.001, r2=.036), but not BP. For adults with high genetic risk, waking cortisol was lower with lower SES but higher with higher SES (B=0.87). Lower neighborhood SES was also related to higher systolic BP (B=−0.794, p=.028). Conclusions Findings demonstrated an interaction whereby African-American adults with high genetic sensitivity had high levels of waking cortisol with higher neighborhood SES, and low levels with lower neighborhood SES. This moderation effect is consistent with a differential susceptibility gene-environment pattern, rather than a dual-risk pattern. These findings contribute to a growing body of evidence that demonstrates the importance of investigating complex gene-environment relations in order to better understand stress-related health disparities. PMID:26685668

Learning directed acyclic graphs from large-scale genomics data.

PubMed

Nikolay, Fabio; Pesavento, Marius; Kritikos, George; Typas, Nassos

2017-09-20

In this paper, we consider the problem of learning the genetic interaction map, i.e., the topology of a directed acyclic graph (DAG) of genetic interactions from noisy double-knockout (DK) data. Based on a set of well-established biological interaction models, we detect and classify the interactions between genes. We propose a novel linear integer optimization program called the Genetic-Interactions-Detector (GENIE) to identify the complex biological dependencies among genes and to compute the DAG topology that matches the DK measurements best. Furthermore, we extend the GENIE program by incorporating genetic interaction profile (GI-profile) data to further enhance the detection performance. In addition, we propose a sequential scalability technique for large sets of genes under study, in order to provide statistically significant results for real measurement data. Finally, we show via numeric simulations that the GENIE program and the GI-profile data extended GENIE (GI-GENIE) program clearly outperform the conventional techniques and present real data results for our proposed sequential scalability technique.

Using CLIPS to represent knowledge in a VR simulation

NASA Technical Reports Server (NTRS)

Engelberg, Mark L.

1994-01-01

Virtual reality (VR) is an exciting use of advanced hardware and software technologies to achieve an immersive simulation. Until recently, the majority of virtual environments were merely 'fly-throughs' in which a user could freely explore a 3-dimensional world or a visualized dataset. Now that the underlying technologies are reaching a level of maturity, programmers are seeking ways to increase the complexity and interactivity of immersive simulations. In most cases, interactivity in a virtual environment can be specified in the form 'whenever such-and-such happens to object X, it reacts in the following manner.' CLIPS and COOL provide a simple and elegant framework for representing this knowledge-base in an efficient manner that can be extended incrementally. The complexity of a detailed simulation becomes more manageable when the control flow is governed by CLIPS' rule-based inference engine as opposed to by traditional procedural mechanisms. Examples in this paper will illustrate an effective way to represent VR information in CLIPS, and to tie this knowledge base to the input and output C routines of a typical virtual environment.

Geant4 hadronic physics for space radiation environment.

PubMed

Ivantchenko, Anton V; Ivanchenko, Vladimir N; Molina, Jose-Manuel Quesada; Incerti, Sebastien L

2012-01-01

To test and to develop Geant4 (Geometry And Tracking version 4) Monte Carlo hadronic models with focus on applications in a space radiation environment. The Monte Carlo simulations have been performed using the Geant4 toolkit. Binary (BIC), its extension for incident light ions (BIC-ion) and Bertini (BERT) cascades were used as main Monte Carlo generators. For comparisons purposes, some other models were tested too. The hadronic testing suite has been used as a primary tool for model development and validation against experimental data. The Geant4 pre-compound (PRECO) and de-excitation (DEE) models were revised and improved. Proton, neutron, pion, and ion nuclear interactions were simulated with the recent version of Geant4 9.4 and were compared with experimental data from thin and thick target experiments. The Geant4 toolkit offers a large set of models allowing effective simulation of interactions of particles with matter. We have tested different Monte Carlo generators with our hadronic testing suite and accordingly we can propose an optimal configuration of Geant4 models for the simulation of the space radiation environment.

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

PubMed

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.

Specific interactions between DNA and regulatory protein controlled by ligand-binding: Ab initio molecular simulation

NASA Astrophysics Data System (ADS)

Matsushita, Y.; Murakawa, T.; Shimamura, K.; Oishi, M.; Ohyama, T.; Kurita, N.

2015-02-01

The catabolite activator protein (CAP) is one of the regulatory proteins controlling the transcription mechanism of gene. Biochemical experiments elucidated that the complex of CAP with cyclic AMP (cAMP) is indispensable for controlling the mechanism, while previous molecular simulations for the monomer of CAP+cAMP complex revealed the specific interactions between CAP and cAMP. However, the effect of cAMP-binding to CAP on the specific interactions between CAP and DNA is not elucidated at atomic and electronic levels. We here considered the ternary complex of CAP, cAMP and DNA in solvating water molecules and investigated the specific interactions between them at atomic and electronic levels using ab initio molecular simulations based on classical molecular dynamics and ab initio fragment molecular orbital methods. The results highlight the important amino acid residues of CAP for the interactions between CAP and cAMP and between CAP and DNA.

Mapping Quantitative Traits in Unselected Families: Algorithms and Examples

PubMed Central

Dupuis, Josée; Shi, Jianxin; Manning, Alisa K.; Benjamin, Emelia J.; Meigs, James B.; Cupples, L. Adrienne; Siegmund, David

2009-01-01

Linkage analysis has been widely used to identify from family data genetic variants influencing quantitative traits. Common approaches have both strengths and limitations. Likelihood ratio tests typically computed in variance component analysis can accommodate large families but are highly sensitive to departure from normality assumptions. Regression-based approaches are more robust but their use has primarily been restricted to nuclear families. In this paper, we develop methods for mapping quantitative traits in moderately large pedigrees. Our methods are based on the score statistic which in contrast to the likelihood ratio statistic, can use nonparametric estimators of variability to achieve robustness of the false positive rate against departures from the hypothesized phenotypic model. Because the score statistic is easier to calculate than the likelihood ratio statistic, our basic mapping methods utilize relatively simple computer code that performs statistical analysis on output from any program that computes estimates of identity-by-descent. This simplicity also permits development and evaluation of methods to deal with multivariate and ordinal phenotypes, and with gene-gene and gene-environment interaction. We demonstrate our methods on simulated data and on fasting insulin, a quantitative trait measured in the Framingham Heart Study. PMID:19278016

Augmented Reality Simulations on Handheld Computers

ERIC Educational Resources Information Center

Squire, Kurt; Klopfer, Eric

2007-01-01

Advancements in handheld computing, particularly its portability, social interactivity, context sensitivity, connectivity, and individuality, open new opportunities for immersive learning environments. This article articulates the pedagogical potential of augmented reality simulations in environmental engineering education by immersing students in…

Workstation Meets Playstation.

ERIC Educational Resources Information Center

Salopek, Jennifer J.

1998-01-01

Discusses the use of simulation, a form of interactive multimedia training that re-creates the work environment to a degree of near realism, as a training method. Discusses the benefits of simulations and the cost and process of developing materials. (JOW)

Magnetic Levitation of MC3T3 Osteoblast Cells as a Ground-Based Simulation of Microgravity

PubMed Central

Kidder, Louis S.; Williams, Philip C.; Xu, Wayne Wenzhong

2009-01-01

Diamagnetic samples placed in a strong magnetic field and a magnetic field gradient experience a magnetic force. Stable magnetic levitation occurs when the magnetic force exactly counter balances the gravitational force. Under this condition, a diamagnetic sample is in a simulated microgravity environment. The purpose of this study is to explore if MC3T3-E1 osteoblastic cells can be grown in magnetically simulated hypo-g and hyper-g environments and determine if gene expression is differentially expressed under these conditions. The murine calvarial osteoblastic cell line, MC3T3-E1, grown on Cytodex-3 beads, were subjected to a net gravitational force of 0, 1 and 2 g in a 17 T superconducting magnet for 2 days. Microarray analysis of these cells indicated that gravitational stress leads to up and down regulation of hundreds of genes. The methodology of sustaining long-term magnetic levitation of biological systems are discussed. PMID:20052306

Plasticity of genetic interactions in metabolic networks of yeast.

PubMed

Harrison, Richard; Papp, Balázs; Pál, Csaba; Oliver, Stephen G; Delneri, Daniela

2007-02-13

Why are most genes dispensable? The impact of gene deletions may depend on the environment (plasticity), the presence of compensatory mechanisms (mutational robustness), or both. Here, we analyze the interaction between these two forces by exploring the condition-dependence of synthetic genetic interactions that define redundant functions and alternative pathways. We performed systems-level flux balance analysis of the yeast (Saccharomyces cerevisiae) metabolic network to identify genetic interactions and then tested the model's predictions with in vivo gene-deletion studies. We found that the majority of synthetic genetic interactions are restricted to certain environmental conditions, partly because of the lack of compensation under some (but not all) nutrient conditions. Moreover, the phylogenetic cooccurrence of synthetically interacting pairs is not significantly different from random expectation. These findings suggest that these gene pairs have at least partially independent functions, and, hence, compensation is only a byproduct of their evolutionary history. Experimental analyses that used multiple gene deletion strains not only confirmed predictions of the model but also showed that investigation of false predictions may both improve functional annotation within the model and also lead to the discovery of higher-order genetic interactions. Our work supports the view that functional redundancy may be more apparent than real, and it offers a unified framework for the evolution of environmental adaptation and mutational robustness.

Gene-Environment Interaction in the Etiology of Mathematical Ability Using SNP Sets

PubMed Central

Kovas, Yulia; Plomin, Robert

2010-01-01

Mathematics ability and disability is as heritable as other cognitive abilities and disabilities, however its genetic etiology has received relatively little attention. In our recent genome-wide association study of mathematical ability in 10-year-old children, 10 SNP associations were nominated from scans of pooled DNA and validated in an individually genotyped sample. In this paper, we use a ‘SNP set’ composite of these 10 SNPs to investigate gene-environment (GE) interaction, examining whether the association between the 10-SNP set and mathematical ability differs as a function of ten environmental measures in the home and school in a sample of 1888 children with complete data. We found two significant GE interactions for environmental measures in the home and the school both in the direction of the diathesis-stress type of GE interaction: The 10-SNP set was more strongly associated with mathematical ability in chaotic homes and when parents are negative. PMID:20978832

Oxytocin receptors (OXTR) and early parental care: An interaction that modulates psychiatric disorders.

PubMed

Cataldo, Ilaria; Azhari, Atiqah; Lepri, Bruno; Esposito, Gianluca

2017-10-21

Oxytocin plays an important role in the modulation of social behavior in both typical and atypical contexts. Also, the quality of early parental care sets the foundation for long-term psychosocial development. Here, we review studies that investigated how oxytocin receptor (OXTR) interacts with early parental care experiences to influence the development of psychiatric disorders. Using Pubmed, Scopus and PsycInfo databases, we utilized the keyword "OXTR" before subsequently searching for specific OXTR single nucleotide polymorphisms (SNPs), generating a list of 598 studies in total. The papers were catalogued in a database and filtered for gene-environment interaction, psychiatric disorders and involvement of parental care. In particular, rs53576 and rs2254298 were found to be significantly involved in gene-environment interactions that modulated risk for psychopathology and the following psychiatric disorders: disruptive behavior, depression, anxiety, eating disorder and borderline personality disorder. These results illustrate the importance of OXTR in mediating the impact of parental care on the emergence of psychopathology. Copyright © 2017 Elsevier Ltd. All rights reserved.

Creating Simulations for Political Science Education

ERIC Educational Resources Information Center

Asal, Victor; Blake, Elizabeth L.

2006-01-01

Simulations, particularly human-to-human interactions, offer social science students the opportunity to learn from firsthand experience, and can be an important and useful addition to an educator's teaching repertoire. However, it can be difficult for an instructor to know how to structure a simulation environment to meet specific educational…

Moderating Effects of Autism on Parent Views of Genetic Screening for Aggression

ERIC Educational Resources Information Center

May, Michael E.; Brandt, Rachel C.; Bohannan, Joseph K.

2012-01-01

Advances in gene-environment interaction research have revealed genes that are associated with aggression. However, little is known about parent perceptions of genetic screening for behavioral symptoms like aggression as opposed to diagnosing disabilities. These perceptions may influence future research endeavors involving genetic linkage studies…

International Cancer of the Head and Neck, Genetics and Environment (InterCHANGE) Study

ClinicalTrials.gov

2013-10-29

Evaluate the Association Between Certain Environmental Exposures (e.g. Cigarette Smoking, Alcohol Drinking, Betel Nut Chewing…) and Head and Neck Cancers; Assess the Effect of Genetic Factors, Including Both SNP and Copy Number Variation (CNV) Through Analysis of Both Main Effect and Gene-gene Interaction

Development of a virtual flight simulator.

PubMed

Kuntz Rangel, Rodrigo; Guimarães, Lamartine N F; de Assis Correa, Francisco

2002-10-01

We present the development of a flight simulator that allows the user to interact in a created environment by means of virtual reality devices. This environment simulates the sight of a pilot in an airplane cockpit. The environment is projected in a helmet visor and allows the pilot to see inside as well as outside the cockpit. The movement of the airplane is independent of the movement of the pilot's head, which means that the airplane might travel in one direction while the pilot is looking at a 30 degrees angle with respect to the traveled direction. In this environment, the pilot will be able to take off, fly, and land the airplane. So far, the objects in the environment are geometrical figures. This is an ongoing project, and only partial results are available now.

Association of Positive and Negative Parenting Behavior with Childhood ADHD: Interactions with Offspring Monoamine Oxidase A (MAO-A) Genotype

ERIC Educational Resources Information Center

Li, James J.; Lee, Steve S.

2012-01-01

Relatively little is known about the potential interplay between genetic and environmental influences on attention-deficit/hyperactivity disorder (ADHD), including gene-environment interaction (GxE). There is evidence that parenting behavior interacts with offspring genotype in the development of externalizing problems, but studies have largely…

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

PubMed

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 chain reaction approach to modelling gene pathways.

PubMed

Cheng, Gary C; Chen, Dung-Tsa; Chen, James J; Soong, Seng-Jaw; Lamartiniere, Coral; Barnes, Stephen

2012-08-01

BACKGROUND: Of great interest in cancer prevention is how nutrient components affect gene pathways associated with the physiological events of puberty. Nutrient-gene interactions may cause changes in breast or prostate cells and, therefore, may result in cancer risk later in life. Analysis of gene pathways can lead to insights about nutrient-gene interactions and the development of more effective prevention approaches to reduce cancer risk. To date, researchers have relied heavily upon experimental assays (such as microarray analysis, etc.) to identify genes and their associated pathways that are affected by nutrient and diets. However, the vast number of genes and combinations of gene pathways, coupled with the expense of the experimental analyses, has delayed the progress of gene-pathway research. The development of an analytical approach based on available test data could greatly benefit the evaluation of gene pathways, and thus advance the study of nutrient-gene interactions in cancer prevention. In the present study, we have proposed a chain reaction model to simulate gene pathways, in which the gene expression changes through the pathway are represented by the species undergoing a set of chemical reactions. We have also developed a numerical tool to solve for the species changes due to the chain reactions over time. Through this approach we can examine the impact of nutrient-containing diets on the gene pathway; moreover, transformation of genes over time with a nutrient treatment can be observed numerically, which is very difficult to achieve experimentally. We apply this approach to microarray analysis data from an experiment which involved the effects of three polyphenols (nutrient treatments), epigallo-catechin-3-O-gallate (EGCG), genistein, and resveratrol, in a study of nutrient-gene interaction in the estrogen synthesis pathway during puberty. RESULTS: In this preliminary study, the estrogen synthesis pathway was simulated by a chain reaction model. By applying it to microarray data, the chain reaction model computed a set of reaction rates to examine the effects of three polyphenols (EGCG, genistein, and resveratrol) on gene expression in this pathway during puberty. We first performed statistical analysis to test the time factor on the estrogen synthesis pathway. Global tests were used to evaluate an overall gene expression change during puberty for each experimental group. Then, a chain reaction model was employed to simulate the estrogen synthesis pathway. Specifically, the model computed the reaction rates in a set of ordinary differential equations to describe interactions between genes in the pathway (A reaction rate K of A to B represents gene A will induce gene B per unit at a rate of K; we give details in the "method" section). Since disparate changes of gene expression may cause numerical error problems in solving these differential equations, we used an implicit scheme to address this issue. We first applied the chain reaction model to obtain the reaction rates for the control group. A sensitivity study was conducted to evaluate how well the model fits to the control group data at Day 50. Results showed a small bias and mean square error. These observations indicated the model is robust to low random noises and has a good fit for the control group. Then the chain reaction model derived from the control group data was used to predict gene expression at Day 50 for the three polyphenol groups. If these nutrients affect the estrogen synthesis pathways during puberty, we expect discrepancy between observed and expected expressions. Results indicated some genes had large differences in the EGCG (e.g., Hsd3b and Sts) and the resveratrol (e.g., Hsd3b and Hrmt12) groups. CONCLUSIONS: In the present study, we have presented (I) experimental studies of the effect of nutrient diets on the gene expression changes in a selected estrogen synthesis pathway. This experiment is valuable because it allows us to examine how the nutrient-containing diets regulate gene expression in the estrogen synthesis pathway during puberty; (II) global tests to assess an overall association of this particular pathway with time factor by utilizing generalized linear models to analyze microarray data; and (III) a chain reaction model to simulate the pathway. This is a novel application because we are able to translate the gene pathway into the chemical reactions in which each reaction channel describes gene-gene relationship in the pathway. In the chain reaction model, the implicit scheme is employed to efficiently solve the differential equations. Data analysis results show the proposed model is capable of predicting gene expression changes and demonstrating the effect of nutrient-containing diets on gene expression changes in the pathway. One of the objectives of this study is to explore and develop a numerical approach for simulating the gene expression change so that it can be applied and calibrated when the data of more time slices are available, and thus can be used to interpolate the expression change at a desired time point without conducting expensive experiments for a large amount of time points. Hence, we are not claiming this is either essential or the most efficient way for simulating this problem, rather a mathematical/numerical approach that can model the expression change of a large set of genes of a complex pathway. In addition, we understand the limitation of this experiment and realize that it is still far from being a complete model of predicting nutrient-gene interactions. The reason is that in the present model, the reaction rates were estimated based on available data at two time points; hence, the gene expression change is dependent upon the reaction rates and a linear function of the gene expressions. More data sets containing gene expression at various time slices are needed in order to improve the present model so that a non-linear variation of gene expression changes at different time can be predicted.

Effect of summer daylight exposure and genetic background on growth in growth hormone-deficient children

PubMed Central

De Leonibus, C; Chatelain, P; Knight, C; Clayton, P; Stevens, A

2016-01-01

The response to growth hormone in humans is dependent on phenotypic, genetic and environmental factors. The present study in children with growth hormone deficiency (GHD) collected worldwide characterised gene–environment interactions on growth response to recombinant human growth hormone (r-hGH). Growth responses in children are linked to latitude, and we found that a correlate of latitude, summer daylight exposure (SDE), was a key environmental factor related to growth response to r-hGH. In turn growth response was determined by an interaction between both SDE and genes known to affect growth response to r-hGH. In addition, analysis of associated networks of gene expression implicated a role for circadian clock pathways and specifically the developmental transcription factor NANOG. This work provides the first observation of gene–environment interactions in children treated with r-hGH. PMID:26503811

Considering the Activity in Interactivity: A Multimodal Perspective

ERIC Educational Resources Information Center

Schwartz, Ruth N.

2010-01-01

What factors contribute to effective multimedia learning? Increasingly, interactivity is considered a critical component that can foster learning in multimedia environments, including simulations and games. Although a number of recent studies investigate interactivity as a factor in the effective design of multimedia instruction, most examine only…

The influence of a novel simulated learning environment upon student clinical subjective refraction performance: A pilot study.

PubMed

Woodman-Pieterse, Emily C; De Souza, Neilsen J; Vincent, Stephen J

2016-07-01

Optometry students are taught the process of subjective refraction through lectures and laboratory-based practicals before progressing to supervised clinical practice. Simulated leaning environments (SLEs) form part of an emerging technology used in a range of health disciplines; however, there is limited evidence regarding the effectiveness of clinical simulators as educational tools. Forty optometry students (20 fourth year and 20 fifth year) were assessed twice by a qualified optometrist (two examinations separated by four to eight weeks), while completing a monocular non-cycloplegic subjective refraction on the same patient with an unknown refractive error, simulated using contact lenses. Half of the students were granted access to an online simulated learning environment, The Brien Holden Vision Institute (BHVI) Virtual Refractor, and the remaining students formed a control group. The primary outcome measures at each visit were; accuracy of the clinical refraction compared to a qualified optometrist and relative to the Optometry Council of Australia and New Zealand (OCANZ) subjective refraction examination criteria. Secondary measures of interest included descriptors of student SLE engagement, student self-reported confidence levels and correlations between performance in the simulated and real-world clinical environment. Eighty per cent of students in the intervention group interacted with the simulated learning environment (for an average of 100 minutes); however, there was no correlation between measures of student engagement with the BHVI Virtual Refractor and speed or accuracy of clinical subjective refractions. Fifth year students were typically more confident and refracted more accurately and more quickly than fourth year students. A year group by experimental group interaction (p = 0.03) was observed for accuracy of the spherical component of refraction and post hoc analysis revealed that less experienced students exhibited greater gains in clinical accuracy following exposure to the SLE intervention. Short-term exposure to a SLE can positively influence clinical subjective refraction outcomes for less experienced optometry students and may be of benefit in increasing the skills of novice refractionists to levels appropriate for commencing supervised clinical interactions. © 2016 Optometry Australia.

Association Between Four Polymorphisms in lncRNA and Risk of Lung Cancer in a Chinese Never-Smoking Female Population.

PubMed

Gao, Min; Li, Hang; Lv, Xiaoting; Zhou, Baosen; Yin, Zhihua

2018-06-07

Long noncoding RNAs (lncRNAs) play important roles in the development of human cancers. This is the first case-control study of the association between specific polymorphisms in lncRNA genes and the risk of lung cancer, as well as the gene-environment interaction between the polymorphisms and cooking oil fume exposure in Chinese never-smoking females. A hospital-based case-control study was carried out in Shenyang, Liaoning province. The study included 395 cases and 556 controls. The polymorphisms of rs4785367, rs3803662, rs10750417, and rs1814343 in lncRNA genes were analyzed. The gene-environment interactions were explored on both additive and multiplicative scale. In addition, the results were listed as follows: for rs3803662, compared with the individuals carrying homozygous TT genotype, those with homozygous CC genotype had the decreased risk of lung cancer (adjusted odds ratio [OR] = 0.61, 95% confidence interval [CI] = 0.40-0.92, p = 0.018). As for rs4785367, compared with homozygous TT, homozygous CC could lessen the risk of lung cancer (adjusted OR = 0.54, 95% CI = 0.33-0.89, p = 0.016). The recessive models of rs3803662 and rs4785367 showed significant association (adjusted OR = 0.65, 95% CIs = 0.44-0.97, p = 0.033; adjusted OR = 0.54, 95% CIs = 0.33-0.88, p = 0.014). The C allele of rs3803662 was suggested to be protective allele of lung cancer (adjusted OR = 0.80, 95% CI = 0.66-0.97, p = 0.023). However, rs10750417 and rs1814343 polymorphisms were not significantly associated with lung cancer risks. The measures of additive interaction and logistic models suggested that the gene-environment interactions were not statistically significant on both additive and multiplicative scales.

[The nature of personality: a co-evolutionary perspective].

PubMed

Asendorpf, J B

1996-01-01

Personality psychologists' attempts to explain human diversity have traditionally focused upon processes of person-situation interaction, and genotype-environment interaction. The great variability of genotypes and environments within cultures has remained unexplained in these efforts. Which processes may be responsible for the genetic and environmental variability within cultures? Answers to this question are sought in processes of genetic-cultural coevolution: mutation and sexual recombination of genes, innovation and synthesis of memes (units of cultural transmission), genotype-->environment and meme-->environment effects, and frequency-dependent natural and cultural selection. This twofold evolutionary explanation of personality differences within cultures suggests that a solid foundation of personality psychology requires bridging biology and cultural science.

Risk, individual differences, and environment: an Agent-Based Modeling approach to sexual risk-taking.

PubMed

Nagoski, Emily; Janssen, Erick; Lohrmann, David; Nichols, Eric

2012-08-01

Risky sexual behaviors, including the decision to have unprotected sex, result from interactions between individuals and their environment. The current study explored the use of Agent-Based Modeling (ABM)-a methodological approach in which computer-generated artificial societies simulate human sexual networks-to assess the influence of heterogeneity of sexual motivation on the risk of contracting HIV. The models successfully simulated some characteristics of human sexual systems, such as the relationship between individual differences in sexual motivation (sexual excitation and inhibition) and sexual risk, but failed to reproduce the scale-free distribution of number of partners observed in the real world. ABM has the potential to inform intervention strategies that target the interaction between an individual and his or her social environment.

The Challenge of Grounding Planning in Simulation with an Interactive Model Development Environment

NASA Technical Reports Server (NTRS)

Clement, Bradley J.; Frank, Jeremy D.; Chachere, John M.; Smith, Tristan B.; Swanson, Keith J.

2011-01-01

A principal obstacle to fielding automated planning systems is the difficulty of modeling. Physical systems are modeled conventionally based on specification documents and the modeler's understanding of the system. Thus, the model is developed in a way that is disconnected from the system's actual behavior and is vulnerable to manual error. Another obstacle to fielding planners is testing and validation. For a space mission, generated plans must be validated often by translating them into command sequences that are run in a simulation testbed. Testing in this way is complex and onerous because of the large number of possible plans and states of the spacecraft. Though, if used as a source of domain knowledge, the simulator can ease validation. This paper poses a challenge: to ground planning models in the system physics represented by simulation. A proposed, interactive model development environment illustrates the integration of planning and simulation to meet the challenge. This integration reveals research paths for automated model construction and validation.

Single Nucleotide Variations of the Human GR Gene Manifested as Pathologic Mutations or Polymorphisms.

PubMed

Kino, Tomoshige

2018-05-11

The human genome contains numerous single nucleotide variations (SNVs), and the human GR gene harbors ∼450 of these genetic changes. Among them, extremely rare non-synonymous variants known as pathologic GR gene mutations develop a characteristic pathologic condition, familial/sporadic generalized glucocorticoid resistance syndrome, by replacing the amino acids critical for GR protein structure and functions, whereas others known as pathologic polymorphisms develop mild manifestations recognized mainly at population bases by changing the GR activities slightly. Recent progress on the structural analysis to the GR protein and subsequent computer-based structural simulation revealed details of the molecular defects caused by such pathologic GR gene mutations, including their impact on the receptor interaction to ligands, nuclear receptor coactivators (NCoAs) or DNA glucocorticoid response elements (GREs). Indeed, those found in the GR ligand-binding domain significantly damage protein structure of the ligand-binding pocket and/or the activation function-2 transactivation domain and change their molecular interaction to glucocorticoids or the LxxLL signature motif of NCoAs. Two mutations found in GR DBD also affect interaction of the mutant receptors to GRE DNA by affecting the critical amino acid for the interaction or changing local hydrophobic circumstance. In this review, we discuss recent findings on the structural simulation of the pathologic GR mutants in connection to their functional and clinical impacts along with brief explanation to recent research achievement on the GR polymorphisms.

Enacting the molecular imperative: How gene-environment interaction research links bodies and environments in the Post-Genomic Age

PubMed Central

Darling, Katherine Weatherford; Ackerman, Sara L.; Hiatt, Robert H.; Lee, Sandra Soo-Jin; Shim, Janet K.

2016-01-01

Despite a proclaimed shift from ‘nature versus nurture’ to ‘genes and environment’ paradigms within biomedical and genomic science, capturing the environment and identifying gene-environment interactions (GEIs) has remained a challenge. What does ‘the environment’ mean in the post-genomic age? In this paper, we present qualitative data from a study of 33 principal investigators funded by the U.S. National Institutes of Health to conduct etiological research on three complex diseases (cancer, cardiovascular disease and diabetes). We examine their research practices and perspectives on the environment through the concept of molecularization: the social processes and transformations through which phenomena (diseases, identities, pollution, food, racial/ethnic classifications) are re-defined in terms of their molecular components and described in the language of molecular biology. We show how GEI researchers’ expansive conceptualizations of the environment ultimately yield to the imperative to molecularize and personalize the environment. They seek to ‘go into the body’ and re-work the boundaries between bodies and environments. In the process, they create epistemic hinges to facilitate a turn from efforts to understand social and environmental exposures outside the body, to quantifying their effects inside the body. GEI researchers respond to these emergent imperatives with a mixture of excitement, ambivalence and frustration. We reflect on how GEI researchers struggle to make meaning of molecules in their work, and how they grapple with molecularization as a methodological and rhetorical imperative as well as a process transforming biomedical research practices. PMID:26994357

Early Life Precursors, Epigenetics, and the Development of Food Allergy1

PubMed Central

Hong, Xiumei; Wang, Xiaobin

2012-01-01

Food allergy (FA), a major clinical and public health concern worldwide, is caused by a complex interplay of environmental exposures, genetic variants, gene-environment interactions, and epigenetic alterations. This review summarizes recent advances surrounding these key factors, with a particular focus on the potential role of epigenetics in the development of FA. Epidemiologic studies have reported a number of non-genetic factors that may influence the risk of FA, such as timing of food introduction and feeding pattern, diet/nutrition, exposure to environmental tobacco smoking, prematurity and low birthweight, microbial exposure, and race/ethnicity. Current studies on the genetics of FA are mainly conducted using candidate gene approaches, which have linked more than 10 genes to the genetic susceptibility of FA. Studies on gene-environment interactions of FA are very limited. Epigenetic alteration has been proposed as one of the mechanisms to mediate the influence of early-life environmental exposures and gene-environment interactions on the development of diseases later in life. The role of epigenetics in the regulation of the immune system and the epigenetic effects of some FA-associated environmental exposures are discussed in this review. There is a particular lack of large-scale prospective birth cohort studies that simultaneously assess the inter-relationships of early life exposures, genetic susceptibility, epigenomic alterations and the development of FA. The identification of these key factors and their independent and joint contributions to FA will allow us to gain important insight into the biological mechanisms by which environmental exposures and genetic susceptibility affect the risk of FA, and will provide essential information to develop more effective new paradigms in the diagnosis, prevention and management of FA. PMID:22777545

ARENA - A Collaborative Immersive Environment for Virtual Fieldwork

NASA Astrophysics Data System (ADS)

Kwasnitschka, T.

2012-12-01

Whenever a geoscientific study area is not readily accessible, as is the case on the deep seafloor, it is difficult to apply traditional but effective methods of fieldwork, which often require physical presence of the observer. The Artificial Research Environment for Networked Analysis (ARENA), developed at GEOMAR | Helmholtz Centre for Ocean Research Kiel within the Cluster of Excellence "The Future Ocean", provides a backend solution to robotic research on the seafloor by means of an immersive simulation environment for marine research: A hemispherical screen of 6m diameter covering the entire lower hemisphere surrounds a group of up to four researchers at once. A variety of open source (e.g. Microsoft Research World Wide Telescope) and commercial software platforms allow the interaction with e.g. in-situ recorded video, vector maps, terrain, textured geometry, point cloud and volumetric data in four dimensions. Data can be put into a holistic, georeferenced context and viewed on scales stretching from centimeters to global. Several input devices from joysticks to gestures and vocalized commands allow interaction with the simulation, depending on individual preference. Annotations added to the dataset during the simulation session catalyze the following quantitative evaluation. Both the special simulator design, making data perception a group experience, and the ability to connect remote instances or scaled down versions of ARENA over the Internet are significant advantages over established immersive simulation environments.

Novel 3D/VR interactive environment for MD simulations, visualization and analysis.

PubMed

Doblack, Benjamin N; Allis, Tim; Dávila, Lilian P

2014-12-18

The increasing development of computing (hardware and software) in the last decades has impacted scientific research in many fields including materials science, biology, chemistry and physics among many others. A new computational system for the accurate and fast simulation and 3D/VR visualization of nanostructures is presented here, using the open-source molecular dynamics (MD) computer program LAMMPS. This alternative computational method uses modern graphics processors, NVIDIA CUDA technology and specialized scientific codes to overcome processing speed barriers common to traditional computing methods. In conjunction with a virtual reality system used to model materials, this enhancement allows the addition of accelerated MD simulation capability. The motivation is to provide a novel research environment which simultaneously allows visualization, simulation, modeling and analysis. The research goal is to investigate the structure and properties of inorganic nanostructures (e.g., silica glass nanosprings) under different conditions using this innovative computational system. The work presented outlines a description of the 3D/VR Visualization System and basic components, an overview of important considerations such as the physical environment, details on the setup and use of the novel system, a general procedure for the accelerated MD enhancement, technical information, and relevant remarks. The impact of this work is the creation of a unique computational system combining nanoscale materials simulation, visualization and interactivity in a virtual environment, which is both a research and teaching instrument at UC Merced.

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

PubMed Central

Doblack, Benjamin N.; Allis, Tim; Dávila, Lilian P.

2014-01-01

The increasing development of computing (hardware and software) in the last decades has impacted scientific research in many fields including materials science, biology, chemistry and physics among many others. A new computational system for the accurate and fast simulation and 3D/VR visualization of nanostructures is presented here, using the open-source molecular dynamics (MD) computer program LAMMPS. This alternative computational method uses modern graphics processors, NVIDIA CUDA technology and specialized scientific codes to overcome processing speed barriers common to traditional computing methods. In conjunction with a virtual reality system used to model materials, this enhancement allows the addition of accelerated MD simulation capability. The motivation is to provide a novel research environment which simultaneously allows visualization, simulation, modeling and analysis. The research goal is to investigate the structure and properties of inorganic nanostructures (e.g., silica glass nanosprings) under different conditions using this innovative computational system. The work presented outlines a description of the 3D/VR Visualization System and basic components, an overview of important considerations such as the physical environment, details on the setup and use of the novel system, a general procedure for the accelerated MD enhancement, technical information, and relevant remarks. The impact of this work is the creation of a unique computational system combining nanoscale materials simulation, visualization and interactivity in a virtual environment, which is both a research and teaching instrument at UC Merced. PMID:25549300

Virtual Learning Environment for Interactive Engagement with Advanced Quantum Mechanics

ERIC Educational Resources Information Center

Pedersen, Mads Kock; Skyum, Birk; Heck, Robert; Müller, Romain; Bason, Mark; Lieberoth, Andreas; Sherson, Jacob F.

2016-01-01

A virtual learning environment can engage university students in the learning process in ways that the traditional lectures and lab formats cannot. We present our virtual learning environment "StudentResearcher," which incorporates simulations, multiple-choice quizzes, video lectures, and gamification into a learning path for quantum…

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

PubMed

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.

Understanding the Relative Contributions of Direct Environmental Effects and Passive Genotype-Environment Correlations in the Association between Familial Risk Factors and Child Disruptive Behavior Disorders

PubMed Central

Bornovalova, Marina A.; Cummings, Jenna R.; Hunt, Elizabeth; Blazei, Ryan; Malone, Steve; Iacono, William G.

2013-01-01

Background: Previous work reports an association between familial risk factors stemming from parental characteristics and offspring disruptive behavior disorders (DBDs). This association may reflect a) the direct effects of familial environment, and b) a passive gene-environment correlation, wherein the parents provide both the genes and the environment. The current study examined the contributions of direct environmental influences and passive gene-environment correlations by comparing the effects of familial risk factors on child DBDs in genetically related (biological) and non-related (adoptive) families. Method: Participants were 402 adoptive and 204 biological families. Familial environment was defined as maternal and paternal maladaptive parenting and antisociality, marital conflict, and divorce; offspring DBDs included attention deficit/hyperactivity disorder, conduct disorder, and oppositional defiant disorder. Mixed-level regressions estimated the main effects of familial environment, adoption status, and the familial environment by adoption status interaction term, which tested for a presence of passive gene-environment correlations. Results: There was a main effect of maternal and paternal maladaptive parenting and marital discord on child DBDs, indicating a direct environmental effect. There was no direct environmental effect of maternal or paternal antisociality, but maternal and paternal antisociality had stronger associations with child DBDs in biological families than adoptive families, indicating the presence of a passive gene-environment correlation. Conclusions: Many familial risk factors affected children equally across genetically-related and non-related families, providing evidence for direct environmental effects. The relationship of parental antisociality and offspring DBDs was best explained by a passive gene-environment correlation, where a general vulnerability toward externalizing psychopathology is passed down by the parents to the children. PMID:23714724

Galaxy properties and the cosmic web in simulations

NASA Astrophysics Data System (ADS)

Metuki, Ofer; Libeskind, Noam I.; Hoffman, Yehuda; Crain, Robert A.; Theuns, Tom

2015-01-01

We seek to understand the relationship between galaxy properties and their local environment, which calls for a proper formulation of the notion of environment. We analyse the Galaxies-Intergalactic Medium Interaction Calculation suite of cosmological hydrodynamical simulations within the framework of the cosmic web as formulated by Hoffman et al., focusing on properties of simulated dark matter haloes and luminous galaxies with respect to voids, sheets, filaments, and knots - the four elements of the cosmic web. We find that the mass functions of haloes depend on environment, which drives other environmental dependence of galaxy formation. The web shapes the halo mass function, and through the strong dependence of the galaxy properties on the mass of their host haloes, it also shapes the galaxy-(web) environment dependence.

Simulation fails to replicate stress in trainees performing a technical procedure in the clinical environment.

PubMed

Baker, B G; Bhalla, A; Doleman, B; Yarnold, E; Simons, S; Lund, J N; Williams, J P

2017-01-01

Simulation-based training (SBT) has become an increasingly important method by which doctors learn. Stress has an impact upon learning, performance, technical, and non-technical skills. However, there are currently no studies that compare stress in the clinical and simulated environment. We aimed to compare objective (heart rate variability, HRV) and subjective (state trait anxiety inventory, STAI) measures of stress theatre with a simulated environment. HRV recordings were obtained from eight anesthetic trainees performing an uncomplicated rapid sequence induction at pre-determined procedural steps using a wireless Polar RS800CX monitor © in an emergency theatre setting. This was repeated in the simulated environment. Participants completed an STAI before and after the procedure. Eight trainees completed the study. The theatre environment caused an increase in objective stress vs baseline (p = .004). There was no significant difference between average objective stress levels across all time points (p = .20) between environments. However, there was a significant interaction between the variables of objective stress and environment (p = .045). There was no significant difference in subjective stress (p = .27) between environments. Simulation was unable to accurately replicate the stress of the technical procedure. This is the first study that compares the stress during SBT with the theatre environment and has implications for the assessment of simulated environments for use in examinations, rating of technical and non-technical skills, and stress management training.

Effects of Simulated Microgravity on a Host-Pathogen System

NASA Technical Reports Server (NTRS)

Gilbert, Rachel; Lo, Rachel; Bhattacharya, Sharmila

2017-01-01

While it has been shown that decades of astronauts and cosmonauts can suffer from illnesses both during and after spaceflight, the underlying causes are still poorly understood, due in part to the fact that there are so many variables to consider when investigating the human immune system in a complex environment. Invertebrates have become popular models for studying human disease because they are cheap, highly amenable to experimental manipulation, and have innate immune systems with a high genetic similarity to humans. Fruit flies (Drosophila melanogaster) have been shown to experience a dramatic shift in immune gene expression following spaceflight, but are still able to fight off infections when exposed to bacteria. However, the common bacterial pathogen Serratia marcescens was shown to become more lethal to fruit flies after being cultured in space, suggesting that not only do we need to consider host changes in susceptibility, but also changes in the pathogen itself after spaceflight conditions. Being able to simulate spaceflight conditions in a controlled environment on the ground gives us the ability to not only evaluate the effects of microgravity on the host immune system, but also how the microorganisms that cause immune disorders are being affected by these drastic environmental shifts. In this study, I use a ground-based simulated microgravity environment to examine the genetic changes associated with increased S. marcescens virulence in order to understand how microgravity is affecting this pathogen, as well as how these genetic changes influence and interact with the host immune system. This study will provide us with more directed approaches to studying the effects of spaceflight on human beings, with the ultimate goal of being able to counteract immune dysfunction in future space exploration.

Microarray analysis of genes differentially expressed in HepG2 cells cultured in simulated microgravity: preliminary report

NASA Technical Reports Server (NTRS)

Khaoustov, V. I.; Risin, D.; Pellis, N. R.; Yoffe, B.; McIntire, L. V. (Principal Investigator)

2001-01-01

Developed at NASA, the rotary cell culture system (RCCS) allows the creation of unique microgravity environment of low shear force, high-mass transfer, and enables three-dimensional (3D) cell culture of dissimilar cell types. Recently we demonstrated that a simulated microgravity is conducive for maintaining long-term cultures of functional hepatocytes and promote 3D cell assembly. Using deoxyribonucleic acid (DNA) microarray technology, it is now possible to measure the levels of thousands of different messenger ribonucleic acids (mRNAs) in a single hybridization step. This technique is particularly powerful for comparing gene expression in the same tissue under different environmental conditions. The aim of this research was to analyze gene expression of hepatoblastoma cell line (HepG2) during early stage of 3D-cell assembly in simulated microgravity. For this, mRNA from HepG2 cultured in the RCCS was analyzed by deoxyribonucleic acid microarray. Analyses of HepG2 mRNA by using 6K glass DNA microarray revealed changes in expression of 95 genes (overexpression of 85 genes and downregulation of 10 genes). Our preliminary results indicated that simulated microgravity modifies the expression of several genes and that microarray technology may provide new understanding of the fundamental biological questions of how gravity affects the development and function of individual cells.

Are there genetic influences on addiction: evidence from family, adoption and twin studies.

PubMed

Agrawal, Arpana; Lynskey, Michael T

2008-07-01

In this exciting era of gene discovery, we review evidence from family, adoption and twin studies that examine the genetic basis for addiction. With a focus on the classical twin design that utilizes data on monozygotic and dizygotic twins, we discuss support in favor of heritable influences on alcohol, nicotine, cannabis and other illicit drug dependence. We review whether these genetic factors also influence earlier stages (e.g. experimentation) of the addictive process and whether there are genetic influences specific to each psychoactive substance. Converging evidence from these studies supports the role of moderate to high genetic influences on addiction with estimates ranging from 0.30 to 0.70. The changing role of these heritable factors as a function of gender, age and cultural characteristics is also discussed. We highlight the importance of the interplay between genes and the environment as it relates to risk for addiction and the utility of the children-of-twins design for emerging studies of gene-environment interaction is presented. Despite the advances being made by low-cost high-throughput whole genome association assays, we posit that information garnered from twin studies, especially extended twin designs with power to examine gene-environment interactions, will continue to form the foundation for genomic research.

Development of a Prototype Simulation Executive with Zooming in the Numerical Propulsion System Simulation

NASA Technical Reports Server (NTRS)

Reed, John A.; Afjeh, Abdollah A.

1995-01-01

A major difficulty in designing aeropropulsion systems is that of identifying and understanding the interactions between the separate engine components and disciplines (e.g., fluid mechanics, structural mechanics, heat transfer, material properties, etc.). The traditional analysis approach is to decompose the system into separate components with the interaction between components being evaluated by the application of each of the single disciplines in a sequential manner. Here, one discipline uses information from the calculation of another discipline to determine the effects of component coupling. This approach, however, may not properly identify the consequences of these effects during the design phase, leaving the interactions to be discovered and evaluated during engine testing. This contributes to the time and cost of developing new propulsion systems as, typically, several design-build-test cycles are needed to fully identify multidisciplinary effects and reach the desired system performance. The alternative to sequential isolated component analysis is to use multidisciplinary coupling at a more fundamental level. This approach has been made more plausible due to recent advancements in computation simulation along with application of concurrent engineering concepts. Computer simulation systems designed to provide an environment which is capable of integrating the various disciplines into a single simulation system have been proposed and are currently being developed. One such system is being developed by the Numerical Propulsion System Simulation (NPSS) project. The NPSS project, being developed at the Interdisciplinary Technology Office at the NASA Lewis Research Center is a 'numerical test cell' designed to provide for comprehensive computational design and analysis of aerospace propulsion systems. It will provide multi-disciplinary analyses on a variety of computational platforms, and a user-interface consisting of expert systems, data base management and visualization tools, to allow the designer to investigate the complex interactions inherent in these systems. An interactive programming software system, known as the Application Visualization System (AVS), was utilized for the development of the propulsion system simulation. The modularity of this system provides the ability to couple propulsion system components, as well as disciplines, and provides for the ability to integrate existing, well established analysis codes into the overall system simulation. This feature allows the user to customize the simulation model by inserting desired analysis codes. The prototypical simulation environment for multidisciplinary analysis, called Turbofan Engine System Simulation (TESS), which incorporates many of the characteristics of the simulation environment proposed herein, is detailed.

Induction of three-dimensional assembly of human liver cells by simulated microgravity

NASA Technical Reports Server (NTRS)

Khaoustov, V. I.; Darlington, G. J.; Soriano, H. E.; Krishnan, B.; Risin, D.; Pellis, N. R.; Yoffe, B.

1999-01-01

The establishment of long-term cultures of functional primary human liver cells (PHLC) is formidable. Developed at NASA, the Rotary Cell Culture System (RCCS) allows the creation of the unique microgravity environment of low shear force, high-mass transfer, and 3-dimensional cell culture of dissimilar cell types. The aim of our study was to establish long-term hepatocyte cultures in simulated microgravity. PHLC were harvested from human livers by collagenase perfusion and were cultured in RCCS. PHLC aggregates were readily formed and increased up to 1 cm long. The expansion of PHLC in bioreactors was further evaluated with microcarriers and biodegradable scaffolds. While microcarriers were not conducive to formation of spheroids, PHLC cultured with biodegradable scaffolds formed aggregates up to 3 cm long. Analyses of PHLC spheroids revealed tissue-like structures composed of hepatocytes, biliary epithelial cells, and/or progenitor liver cells that were arranged as bile duct-like structures along nascent vascular sprouts. Electron microscopy revealed groups of cohesive hepatocytes surrounded by complex stromal structures and reticulin fibers, bile canaliculi with multiple microvilli, and tight cellular junctions. Albumin mRNA was expressed throughout the 60-d culture. A simulated microgravity environment is conducive to maintaining long-term cultures of functional hepatocytes. This model system will assist in developing improved protocols for autologous hepatocyte transplantation, gene therapy, and liver assist devices, and facilitate studies of liver regeneration and cell-to-cell interactions that occur in vivo.

Providing Interactive Access to Cave Geology for All Students, Regardless of Physical Ability

NASA Astrophysics Data System (ADS)

Atchison, C. `; Stredney, D.; Hittle, B.; Irving, K.; Toomey, R. S., III; Lemon, N. N.; Price, A.; Kerwin, T.

2013-12-01

Based on an identified need to accommodate students with mobility impairments in field-based instructional experiences, this presentation will discuss current efforts to promote participation, broaden diversity, and impart a historical perspective in the geosciences through the use of an interactive virtual environment. Developed through the integration of emerging simulation technologies, this prototypical virtual environment is created from LIDAR data of the Historic Tour route of Mammoth Cave National Park. The educational objectives of the simulation focus on four primary locations within the tour route that provide evidence of the hydrologic impact on the cave and karst formation. The overall objective is to provide a rich experience of a geological field-based learning for all students, regardless of their physical abilities. Employing a virtual environment that interchangeably uses two and three-dimensional representation of geoscience content, this synthetic field-based cave and karst module will provide an opportunity to assess the effectiveness in engaging the student community, and its efficacy in the curriculum when used as an alternative representation of a traditional field experience. The expected outcome is that based on the level of interactivity, the simulated environment will provide adequate pedagogical representation for content transfer without the need for physical experience in the uncontrolled field environment. Additionally, creating such an environment will impact all able-bodied students by providing supplemental resources that can both precede a traditional field experience and allow for students to re-examine a field site long after a the field experience, in both current formal and informal educational settings.

Evidence of reactive gene-environment correlation in preschoolers' prosocial play with unfamiliar peers.

PubMed

DiLalla, Lisabeth Fisher; Bersted, Kyle; John, Sufna Gheyara

2015-10-01

The development of prosocial behaviors during the preschool years is essential for children's positive interactions with peers in school and other social situations. Although there is some evidence of genetic influences on prosocial behaviors, very little is known about how genes and environment, independently and in concert, affect prosocial behaviors in young children. This study of 126 twin and sibling pairs examined 5-year-old preschool children's positive behaviors (prosocial and easy-going) while playing freely with an unfamiliar, same-age, same-sex peer. Children were randomly paired, allowing us to rule out passive (parent-influenced environment) and active (child-driven peer choices) gene-environment correlations as potential influences on the results. We found evidence of reactive gene-environment correlation, demonstrating that children who are genetically more likely to act prosocially and to be temperamentally outgoing appear to evoke more prosocial and easy-going behaviors from an unfamiliar peer. We also found that both dominant genetic and nonshared environmental factors were significant influences on preschoolers' prosocial play behaviors, but that neither genetic nor shared environmental factors were significant for easy-going play behaviors. These findings shed important light on influences of prosocial behaviors in preschoolers. Via inherited tendencies, preschool children's positive behaviors evoke similar positive behaviors from their play peers. Given that prosocial behaviors are preludes to a large range of important socially appropriate behaviors, prosocial children should be encouraged to interact with their peers to potentially create a more positive atmosphere within social contexts. (c) 2015 APA, all rights reserved).

Aerothermodynamic Analyses of Towed Ballutes

NASA Technical Reports Server (NTRS)

Gnoffo, Peter A.; Buck, Greg; Moss, James N.; Nielsen, Eric; Berger, Karen; Jones, William T.; Rudavsky, Rena

2006-01-01

A ballute (balloon-parachute) is an inflatable, aerodynamic drag device for application to planetary entry vehicles. Two challenging aspects of aerothermal simulation of towed ballutes are considered. The first challenge, simulation of a complete system including inflatable tethers and a trailing toroidal ballute, is addressed using the unstructured-grid, Navier-Stokes solver FUN3D. Auxiliary simulations of a semi-infinite cylinder using the rarefied flow, Direct Simulation Monte Carlo solver, DSV2, provide additional insight into limiting behavior of the aerothermal environment around tethers directly exposed to the free stream. Simulations reveal pressures higher than stagnation and corresponding large heating rates on the tether as it emerges from the spacecraft base flow and passes through the spacecraft bow shock. The footprint of the tether shock on the toroidal ballute is also subject to heating amplification. Design options to accommodate or reduce these environments are discussed. The second challenge addresses time-accurate simulation to detect the onset of unsteady flow interactions as a function of geometry and Reynolds number. Video of unsteady interactions measured in the Langley Aerothermodynamic Laboratory 20-Inch Mach 6 Air Tunnel and CFD simulations using the structured grid, Navier-Stokes solver LAURA are compared for flow over a rigid spacecraft-sting-toroid system. The experimental data provides qualitative information on the amplitude and onset of unsteady motion which is captured in the numerical simulations. The presence of severe unsteady fluid - structure interactions is undesirable and numerical simulation must be able to predict the onset of such motion.

A family-based study of gene variants and maternal folate and choline in neuroblastoma: A Report from the Children’s Oncology Group

PubMed Central

Mazul, Angela L; Siega-Riz, Anna Maria; Weinberg, Clarice R; Engel, Stephanie M.; Zou, Fei; Carrier, Kathryn S.; Basta, Patricia V; Vaksman, Zalman; Maris, John M; Diskin, Sharon J; Maxen, Charlene; Naranjo, Arlene; Olshan, Andrew F

2016-01-01

Purpose Neuroblastoma is a childhood cancer of the sympathetic nervous system with embryonic origins. Previous epidemiologic studies suggest maternal vitamin supplementation during pregnancy reduces the risk of neuroblastoma. We hypothesized offspring and maternal genetic variants in folate-related and choline-related genes are associated with neuroblastoma and modify the effects of maternal intake of folate, choline and folic acid. Methods The Neuroblastoma Epidemiology in North America (NENA) study recruited 563 affected children and their parents through the Children’s Oncology Group’s Childhood Cancer Research Network. We used questionnaires to ascertain pre-pregnancy supplementation and estimate usual maternal dietary intake of folate, choline and folic acid. We genotyped 955 genetic variants related to folate or choline using DNA extracted from saliva samples and used a log-linear model to estimate both child and maternal risk ratios and stratum-specific risk ratios for gene-environment interactions. Results Overall, no maternal or offspring genotypic results met criteria for a false discovery rate (FDR) Q-value <0.2. Associations were also null for gene-environment interaction with pre-pregnancy vitamin supplementation, dietary folic acid and folate. FDR significant gene-choline interactions were found for offspring SNPs rs10489810 and rs9966612 located in MTHFD1L and TYMS, respectively, with maternal choline dietary intake dichotomized at the first quartile. Conclusion These results suggest that variants related to one-carbon metabolism are not strongly associated with neuroblastoma. Choline-related variants may play a role; however, the functional consequences of the interacting variants are unknown and require independent replication. PMID:27541142

Genetics of Addiction: Future Focus on Gene × Environment Interaction?

PubMed

Vink, Jacqueline M

2016-09-01

The heritability of substance use is moderate to high. Successful efforts to find genetic variants associated with substance use (smoking, alcohol, cannabis) have been undertaken by large consortia. However, the proportion of phenotypic variance explained by the identified genetic variants is small. Interestingly, there is overlap between the genetic variants that influence different substances. Moreover, there are sets of "substance-specific" genes and sets of genes contributing to a "vulnerability for addictive behavior" in general. It is important to recognize that genes alone do not determine addiction phenotypes: Environmental factors such as parental monitoring, peer pressure, or socioeconomic status also play an important role. Despite a rich epidemiologic literature focused on the social determinants of substance use, few studies have examined the moderation of genetic influences like gene-environment (G × E) interactions. Understanding this balance may hold the key to understanding the individual differences in substance use, abuse, and addictive behavior. Recommendations for future research are described in this commentary and include increasing the power of G × E studies by using state-of-the-art methods such as polygenic risk scores instead of single genetic variants and taking genetic overlap between substances into account. Future genetic studies should also investigate environmental risk factors for addictive behavior more extensively to unravel the interaction between nature and nurture. Focusing on G × E interactions not only will give insight into the underlying biological mechanism but will also characterize subgroups (based on environmental factors) at high risk for addictive behaviors. With this information, we could bridge the gap between fundamental research and applications for society.

A family-based study of gene variants and maternal folate and choline in neuroblastoma: a report from the Children's Oncology Group.

PubMed

Mazul, Angela L; Siega-Riz, Anna Maria; Weinberg, Clarice R; Engel, Stephanie M; Zou, Fei; Carrier, Kathryn S; Basta, Patricia V; Vaksman, Zalman; Maris, John M; Diskin, Sharon J; Maxen, Charlene; Naranjo, Arlene; Olshan, Andrew F

2016-10-01

Neuroblastoma is a childhood cancer of the sympathetic nervous system with embryonic origins. Previous epidemiologic studies suggest maternal vitamin supplementation during pregnancy reduces the risk of neuroblastoma. We hypothesized offspring and maternal genetic variants in folate-related and choline-related genes are associated with neuroblastoma and modify the effects of maternal intake of folate, choline, and folic acid. The Neuroblastoma Epidemiology in North America (NENA) study recruited 563 affected children and their parents through the Children's Oncology Group's Childhood Cancer Research Network. We used questionnaires to ascertain pre-pregnancy supplementation and estimate usual maternal dietary intake of folate, choline, and folic acid. We genotyped 955 genetic variants related to folate or choline using DNA extracted from saliva samples and used a log-linear model to estimate both child and maternal risk ratios and stratum-specific risk ratios for gene-environment interactions. Overall, no maternal or offspring genotypic results met criteria for a false discovery rate (FDR) Q-value <0.2. Associations were also null for gene-environment interaction with pre-pregnancy vitamin supplementation, dietary folic acid, and folate. FDR-significant gene-choline interactions were found for offspring SNPs rs10489810 and rs9966612 located in MTHFD1L and TYMS, respectively, with maternal choline dietary intake dichotomized at the first quartile. These results suggest that variants related to one-carbon metabolism are not strongly associated with neuroblastoma. Choline-related variants may play a role; however, the functional consequences of the interacting variants are unknown and require independent replication.

BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks.

PubMed

Maere, Steven; Heymans, Karel; Kuiper, Martin

2005-08-15

The Biological Networks Gene Ontology tool (BiNGO) is an open-source Java tool to determine which Gene Ontology (GO) terms are significantly overrepresented in a set of genes. BiNGO can be used either on a list of genes, pasted as text, or interactively on subgraphs of biological networks visualized in Cytoscape. BiNGO maps the predominant functional themes of the tested gene set on the GO hierarchy, and takes advantage of Cytoscape's versatile visualization environment to produce an intuitive and customizable visual representation of the results.

Ab initio folding of proteins using all-atom discrete molecular dynamics

PubMed Central

Ding, Feng; Tsao, Douglas; Nie, Huifen; Dokholyan, Nikolay V.

2008-01-01

Summary Discrete molecular dynamics (DMD) is a rapid sampling method used in protein folding and aggregation studies. Until now, DMD was used to perform simulations of simplified protein models in conjunction with structure-based force fields. Here, we develop an all-atom protein model and a transferable force field featuring packing, solvation, and environment-dependent hydrogen bond interactions. Using the replica exchange method, we perform folding simulations of six small proteins (20–60 residues) with distinct native structures. In all cases, native or near-native states are reached in simulations. For three small proteins, multiple folding transitions are observed and the computationally-characterized thermodynamics are in quantitative agreement with experiments. The predictive power of all-atom DMD highlights the importance of environment-dependent hydrogen bond interactions in modeling protein folding. The developed approach can be used for accurate and rapid sampling of conformational spaces of proteins and protein-protein complexes, and applied to protein engineering and design of protein-protein interactions. PMID:18611374

Tool Integration and Environment Architectures

DTIC Science & Technology

1991-05-01

include the Interactive Development Environment (IDE) Software Through Pictures (STP), Sabre-C and FrameMaker coalition, and the Verdix Ada Development...System (VADS) APSE, which includes the VADS compiler and choices of CADRE Teamwork or STP and FrameMaker or Interleaf. The key characteristic of...remote procedure execution to achieve a simulation of a homoge- neous repository (i.e., a simulation that the data in a FrameMaker document resides in one

Event Generators for Simulating Heavy Ion Interactions of Interest in Evaluating Risks in Human Spaceflight

NASA Technical Reports Server (NTRS)

Wilson, Thomas L.; Pinsky, Lawrence; Andersen, Victor; Empl, Anton; Lee, Kerry; Smirmov, Georgi; Zapp, Neal; Ferrari, Alfredo; Tsoulou, Katerina; Roesler, Stefan;

Tools and Equipment Modeling for Automobile Interactive Assembling Operating Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu Dianliang; Zhu Hongmin; Shanghai Key Laboratory of Advance Manufacturing Environment

Tools and equipment play an important role in the simulation of virtual assembly, especially in the assembly process simulation and plan. Because of variety in function and complexity in structure and manipulation, the simulation of tools and equipments remains to be a challenge for interactive assembly operation. Based on analysis of details and characteristics of interactive operations for automobile assembly, the functional requirement for tools and equipments of automobile assembly is given. Then, a unified modeling method for information expression and function realization of general tools and equipments is represented, and the handling methods of manual, semi-automatic, automatic tools andmore » equipments are discussed. Finally, the application in assembly simulation of rear suspension and front suspension of Roewe 750 automobile is given. The result shows that the modeling and handling methods are applicable in the interactive simulation of various tools and equipments, and can also be used for supporting assembly process planning in virtual environment.« less

Effects of circadian clock genes and environmental factors on cognitive aging in old adults in a Taiwanese population.

PubMed

Lin, Eugene; Kuo, Po-Hsiu; Liu, Yu-Li; Yang, Albert C; Kao, Chung-Feng; Tsai, Shih-Jen

2017-04-11

Previous animal studies have indicated associations between circadian clock genes and cognitive impairment . In this study, we assessed whether 11 circadian clockgenes are associated with cognitive aging independently and/or through complex interactions in an old Taiwanese population. We also analyzed the interactions between environmental factors and these genes in influencing cognitive aging. A total of 634 Taiwanese subjects aged over 60 years from the Taiwan Biobank were analyzed. Mini-Mental State Examinations (MMSE) were administered to all subjects, and MMSE scores were used to evaluate cognitive function. Our data showed associations between cognitive aging and single nucleotide polymorphisms (SNPs) in 4 key circadian clock genes, CLOCK rs3749473 (p = 0.0017), NPAS2 rs17655330 (p = 0.0013), RORA rs13329238 (p = 0.0009), and RORB rs10781247 (p = 7.9 x 10-5). We also found that interactions between CLOCK rs3749473, NPAS2 rs17655330, RORA rs13329238, and RORB rs10781247 affected cognitive aging (p = 0.007). Finally, we investigated the influence of interactions between CLOCK rs3749473, RORA rs13329238, and RORB rs10781247 with environmental factors such as alcohol consumption, smoking status, physical activity, and social support on cognitive aging (p = 0.002 ~ 0.01). Our study indicates that circadian clock genes such as the CLOCK, NPAS2, RORA, and RORB genes may contribute to the risk of cognitive aging independently as well as through gene-gene and gene-environment interactions.