Science.gov

Sample records for gene-environment interaction analysis

  1. Variance components models for gene-environment interaction in twin analysis.

    PubMed

    Purcell, Shaun

    2002-12-01

    Gene-environment interaction is likely to be a common and important source of variation for complex behavioral traits. Often conceptualized as the genetic control of sensitivity to the environment, it can be incorporated in variance components twin analyses by partitioning genetic effects into a mean part, which is independent of the environment, and a part that is a linear function of the environment. The model allows for one or more environmental moderator variables (that possibly interact with each other) that may i). be continuous or binary ii). differ between twins within a pair iii). interact with residual environmental as well as genetic effects iv) have nonlinear moderating properties v). show scalar (different magnitudes) or qualitative (different genes) interactions vi). be correlated with genetic effects acting upon the trait, to allow for a test of gene-environment interaction in the presence of gene-environment correlation. Aspects and applications of a class of models are explored by simulation, in the context of both individual differences twin analysis and, in a companion paper (Purcell & Sham, 2002) sibpair quantitative trait locus linkage analysis. As well as elucidating environmental pathways, consideration of gene-environment interaction in quantitative and molecular studies will potentially direct and enhance gene-mapping efforts.

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

    PubMed

    Wei, Sheng; Wang, Li-E; McHugh, Michelle K; Han, Younghun; Xiong, Momiao; Amos, Christopher I; Spitz, Margaret R; Wei, Qingyi Wei

    2012-08-01

    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.

  3. BAYESIAN SEMIPARAMETRIC ANALYSIS FOR TWO-PHASE STUDIES OF GENE-ENVIRONMENT INTERACTION

    PubMed Central

    Ahn, Jaeil; Mukherjee, Bhramar; Gruber, Stephen B.; Ghosh, Malay

    2013-01-01

    The two-phase sampling design is a cost-efficient way of collecting expensive covariate information on a judiciously selected sub-sample. It is natural to apply such a strategy for collecting genetic data in a sub-sample enriched for exposure to environmental factors for gene-environment interaction (G × E) analysis. In this paper, we consider two-phase studies of G × E interaction where phase I data are available on exposure, covariates and disease status. Stratified sampling is done to prioritize individuals for genotyping at phase II conditional on disease and exposure. We consider a Bayesian analysis based on the joint retrospective likelihood of phase I and phase II data. We address several important statistical issues: (i) we consider a model with multiple genes, environmental factors and their pairwise interactions. We employ a Bayesian variable selection algorithm to reduce the dimensionality of this potentially high-dimensional model; (ii) we use the assumption of gene-gene and gene-environment independence to trade-off between bias and efficiency for estimating the interaction parameters through use of hierarchical priors reflecting this assumption; (iii) we posit a flexible model for the joint distribution of the phase I categorical variables using the non-parametric Bayes construction of Dunson and Xing (2009). We carry out a small-scale simulation study to compare the proposed Bayesian method with weighted likelihood and pseudo likelihood methods that are standard choices for analyzing two-phase data. The motivating example originates from an ongoing case-control study of colorectal cancer, where the goal is to explore the interaction between the use of statins (a drug used for lowering lipid levels) and 294 genetic markers in the lipid metabolism/cholesterol synthesis pathway. The sub-sample of cases and controls on which these genetic markers were measured is enriched in terms of statin users. The example and simulation results illustrate that the

  4. 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.

  5. Why study gene-environment interactions?

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  6. Genotype-Based Bayesian Analysis of Gene-Environment Interactions with Multiple Genetic Markers and Misclassification in Environmental Factors

    PubMed Central

    Lobach, Iryna; Fan, Ruzong

    2015-01-01

    A key component to understanding etiology of complex diseases, such as cancer, diabetes, alcohol dependence, is to investigate gene-environment interactions. This work is motivated by the following two concerns in the analysis of gene-environment interactions. First, multiple genetic markers in moderate linkage disequilibrium may be involved in susceptibility to a complex disease. Second, environmental factors may be subject to misclassification. We develop a genotype based Bayesian pseudolikelihood approach that accommodates linkage disequilibrium in genetic markers and misclassification in environmental factors. Since our approach is genotype based, it allows the observed genetic information to enter the model directly thus eliminating the need to infer haplotype phase and simplifying computations. Bayesian approach allows shrinking parameter estimates towards prior distribution to improve estimation and inference when environmental factors are subject to misclassification. 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 case-control study of interaction between early onset of drinking and genes involved in dopamine pathway. PMID:26180529

  7. Genotype-Based Bayesian Analysis of Gene-Environment Interactions with Multiple Genetic Markers and Misclassification in Environmental Factors.

    PubMed

    Lobach, Iryna; Fan, Ruzong

    A key component to understanding etiology of complex diseases, such as cancer, diabetes, alcohol dependence, is to investigate gene-environment interactions. This work is motivated by the following two concerns in the analysis of gene-environment interactions. First, multiple genetic markers in moderate linkage disequilibrium may be involved in susceptibility to a complex disease. Second, environmental factors may be subject to misclassification. We develop a genotype based Bayesian pseudolikelihood approach that accommodates linkage disequilibrium in genetic markers and misclassification in environmental factors. Since our approach is genotype based, it allows the observed genetic information to enter the model directly thus eliminating the need to infer haplotype phase and simplifying computations. Bayesian approach allows shrinking parameter estimates towards prior distribution to improve estimation and inference when environmental factors are subject to misclassification. 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 case-control study of interaction between early onset of drinking and genes involved in dopamine pathway.

  8. Biological Implications of Gene-Environment Interaction

    ERIC Educational Resources Information Center

    Rutter, Michael

    2008-01-01

    Gene-environment interaction (G x E) has been treated as both a statistical phenomenon and a biological reality. It is argued that, although there are important statistical issues that need to be considered, the focus has to be on the biological implications of G x E. Four reports of G x E deriving from the Dunedin longitudinal study are used as…

  9. Gene-environment interactions in sarcoidosis

    PubMed Central

    Culver, Daniel A.; Newman, Lee S.; Kavuru, Mani S.

    2007-01-01

    Susceptibility to most human diseases is polygenic, with complex interactions between functional polymorphisms of single genes governing disease incidence, phenotype, or both. In this context, the contribution of any discrete gene is generally modest for a single individual, but may confer substantial attributable risk on a population level. Environmental exposure can modify the effects of a polymorphism, either by providing a necessary substrate for development of human disease or because the effects of a given exposure modulate the effects of the gene. In several diseases, genetic polymorphisms have been shown to be context-dependent, i.e. the effects of a genetic variant are realized only in the setting of a relevant exposure. Since sarcoidosis susceptibility is dependent on both genetic and environmental modifiers, the study of gene-environment interactions may yield important pathogenetic information and will likely be crucial for uncovering the range of genetic susceptibility loci. However, the complexity of these relationships implies that investigations of gene-environment interactions will require the study of large cohorts with carefully-defined exposures and similar clinical phenotypes. A general principle is that the study of gene-environment interactions requires a sample size at least several-fold greater than for either factor alone. To date, the presence of environmental modifiers has been demonstrated for one sarcoidosis susceptibility locus, HLA-DQB1, in African-American families. This article reviews general considerations obtaining for the study of gene-environment interactions in sarcoidosis. It also describes the limited current understanding of the role of environmental influences on sarcoidosis susceptibility genes. PMID:17560304

  10. The role of environmental heterogeneity in meta-analysis of gene-environment interactions with quantitative traits.

    PubMed

    Li, Shi; Mukherjee, Bhramar; Taylor, Jeremy M G; Rice, Kenneth M; Wen, Xiaoquan; Rice, John D; Stringham, Heather M; Boehnke, Michael

    2014-07-01

    With challenges in data harmonization and environmental heterogeneity across various data sources, meta-analysis of gene-environment interaction studies can often involve subtle statistical issues. In this paper, we study the effect of environmental covariate heterogeneity (within and between cohorts) on two approaches for fixed-effect meta-analysis: the standard inverse-variance weighted meta-analysis and a meta-regression approach. Akin to the results in Simmonds and Higgins (), we obtain analytic efficiency results for both methods under certain assumptions. The relative efficiency of the two methods depends on the ratio of within versus between cohort variability of the environmental covariate. We propose to use an adaptively weighted estimator (AWE), between meta-analysis and meta-regression, for the interaction parameter. The AWE retains full efficiency of the joint analysis using individual level data under certain natural assumptions. Lin and Zeng (2010a, b) showed that a multivariate inverse-variance weighted estimator retains full efficiency as joint analysis using individual level data, if the estimates with full covariance matrices for all the common parameters are pooled across all studies. We show consistency of our work with Lin and Zeng (2010a, b). Without sacrificing much efficiency, the AWE uses only univariate summary statistics from each study, and bypasses issues with sharing individual level data or full covariance matrices across studies. We compare the performance of the methods both analytically and numerically. The methods are illustrated through meta-analysis of interaction between Single Nucleotide Polymorphisms in FTO gene and body mass index on high-density lipoprotein cholesterol data from a set of eight studies of type 2 diabetes.

  11. 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.

  12. 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

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

    PubMed

    Chaste, Pauline; Leboyer, Marion

    2012-09-01

    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.

  14. Functional Analysis of the Early Development of Self-Injurious Behavior: Incorporating Gene-Environment Interactions

    ERIC Educational Resources Information Center

    Langthorne, Paul; McGill, Peter

    2008-01-01

    The analysis of the early development of self-injurious behavior (SIB) has, to date, reflected the wider distinction between nature and nurture. Despite the status of genetic factors as risk markers for the later development of SIB, a model that accounts for their influence on early behavior-environment relations is lacking. In the current paper…

  15. 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.

  16. Semiparametric Bayesian analysis of gene-environment interactions with error in measurement of environmental covariates and missing genetic data

    PubMed Central

    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. PMID:21949562

  17. Rule based classifier for the analysis of gene-gene and gene-environment interactions in genetic association studies

    PubMed Central

    2011-01-01

    Background Several methods have been presented for the analysis of complex interactions between genetic polymorphisms and/or environmental factors. Despite the available methods, there is still a need for alternative methods, because no single method will perform well in all scenarios. The aim of this work was to evaluate the performance of three selected rule based classifier algorithms, RIPPER, RIDOR and PART, for the analysis of genetic association studies. Methods Overall, 42 datasets were simulated with three different case-control models, a varying number of subjects (300, 600), SNPs (500, 1500, 3000) and noise (5%, 10%, 20%). The algorithms were applied to each of the datasets with a set of algorithm-specific settings. Results were further investigated with respect to a) the Model, b) the Rules, and c) the Attribute level. Data analysis was performed using WEKA, SAS and PERL. Results The RIPPER algorithm discovered the true case-control model at least once in >33% of the datasets. The RIDOR and PART algorithm performed poorly for model detection. The RIPPER, RIDOR and PART algorithm discovered the true case-control rules in more than 83%, 83% and 44% of the datasets, respectively. All three algorithms were able to detect the attributes utilized in the respective case-control models in most datasets. Conclusions The current analyses substantiate the utility of rule based classifiers such as RIPPER, RIDOR and PART for the detection of gene-gene/gene-environment interactions in genetic association studies. These classifiers could provide a valuable new method, complementing existing approaches, in the analysis of genetic association studies. The methods provide an advantage in being able to handle both categorical and continuous variable types. Further, because the outputs of the analyses are easy to interpret, the rule based classifier approach could quickly generate testable hypotheses for additional evaluation. Since the algorithms are computationally

  18. Gene-environment interactions in esophageal cancer.

    PubMed

    Matejcic, Marco; Iqbal Parker, M

    2015-01-01

    Esophageal cancer (EC) is one of the most common malignancies in low- and medium-income countries and represents a disease of public health importance because of its poor prognosis and high mortality rate in these regions. The striking variation in the prevalence of EC among different ethnic groups suggests a significant contribution of population-specific environmental and dietary factors to susceptibility to the disease. Although individuals within a demarcated geographical area are exposed to the same environment and share similar dietary habits, not all of them will develop the disease; thus genetic susceptibility to environmental risk factors may play a key role in the development of EC. A wide range of xenobiotic-metabolizing enzymes are responsible for the metabolism of carcinogens introduced via the diet or inhaled from the environment. Such dietary or environmental carcinogens can bind to DNA, resulting in mutations that may lead to carcinogenesis. Genes involved in the biosynthesis of these enzymes are all subject to genetic polymorphisms that can lead to altered expression or activity of the encoded proteins. Genetic polymorphisms may, therefore, act as molecular biomarkers that can provide important predictive information about carcinogenesis. The aim of this review is to discuss our current knowledge on the genetic risk factors associated with the development of EC in different populations; it addresses mainly the topics of genetic polymorphisms, gene-environment interactions, and carcinogenesis. We have reviewed the published data on genetic polymorphisms of enzymes involved in the metabolism of xenobiotics and discuss some of the potential gene-environment interactions underlying esophageal carcinogenesis. The main enzymes discussed in this review are the glutathione S-transferases (GSTs), N-acetyltransferases (NATs), cytochrome P450s (CYPs), sulfotransferases (SULTs), UDP-glucuronosyltransferases (UGTs), and epoxide hydrolases (EHs), all of which

  19. Gene-environment interactions in obesity.

    PubMed

    Hetherington, Marion M; Cecil, Joanne E

    2010-01-01

    Obesity is a global and growing problem. The detrimental health consequences of obesity are significant and include co-morbidities such as diabetes, cancer and coronary heart disease. The marked rise in obesity observed over the last three decades suggests that behavioural and environmental factors underpin the chronic mismatch between energy intake and energy expenditure. However, not all individuals become obese, suggesting that there is considerable variation in responsiveness to 'obesogenic' environments. Some individuals defend easily against a propensity to accumulate fat mass and become overweight whilst others are predisposed to gain weight, possibly as a function of genotype. The genetic contribution to obesity is well established. Common obesity is polygenic, involving complex gene-gene and gene-environment interactions, and it is these interactions that produce the multi-factorial obese phenotypes. Candidate gene variants for polygenic obesity appear to disrupt pathways involved in the regulation of energy intake and expenditure and include adrenergic receptors, uncoupling proteins, PPARG, POMC, MC4R and a set of single nucleotide polymorphisms in the FTO locus. Notably, the FTO gene is the most robust gene for common obesity characterised to date, and recent data shows that the FTO locus seems to confer risk of obesity through increasing energy intake and reduced satiety. Gene variants involved in pathways regulating addiction and reward behaviours may also play a role in predisposition to obesity. Understanding the routes through which the genotype is expressed will ultimately provide opportunities for developing strategies to intervene, as the interaction between genotype and environment is potentially modifiable through behaviour change.

  20. Gene-Environment Interactions and the Etiology of Birth Defects.

    PubMed

    Krauss, Robert S; Hong, Mingi

    2016-01-01

    It is thought that most structural birth defects are caused by a complex combination of genetic and environmental factors that interact to interfere with morphogenetic processes. It is important not only to identify individual genetic and environmental risk factors for particular defects but also to identify which environmental factors interact specifically with which genetic variants that predispose to the same defect. Genomic and epidemiological studies are critical to this end. Development and analysis of model systems will also be essential for this goal, as well as for understanding the mechanisms that underlie specific gene-environment interactions.

  1. Environmental confounding in gene-environment interaction studies.

    PubMed

    Vanderweele, Tyler J; Ko, Yi-An; Mukherjee, Bhramar

    2013-07-01

    We show that, in the presence of uncontrolled environmental confounding, joint tests for the presence of a main genetic effect and gene-environment interaction will be biased if the genetic and environmental factors are correlated, even if there is no effect of either the genetic factor or the environmental factor on the disease. When environmental confounding is ignored, such tests will in fact reject the joint null of no genetic effect with a probability that tends to 1 as the sample size increases. This problem with the joint test vanishes under gene-environment independence, but it still persists if estimating the gene-environment interaction parameter itself is of interest. Uncontrolled environmental confounding will bias estimates of gene-environment interaction parameters even under gene-environment independence, but it will not do so if the unmeasured confounding variable itself does not interact with the genetic factor. Under gene-environment independence, if the interaction parameter without controlling for the environmental confounder is nonzero, then there is gene-environment interaction either between the genetic factor and the environmental factor of interest or between the genetic factor and the unmeasured environmental confounder. We evaluate several recently proposed joint tests in a simulation study and discuss the implications of these results for the conduct of gene-environment interaction studies.

  2. 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.

  3. Gene environment interaction from international cohorts

    PubMed Central

    Gaffney, Adam; Christiani, David C.

    2016-01-01

    Environmental and occupational pulmonary diseases impose a substantial burden of morbidity and mortality on the global population. However, it has been long observed that only some of those who are exposed to pulmonary toxicants go on to develop disease; increasingly, it is being recognized that genetic differences may underlie some of this person-to-person variability. Studies performed throughout the globe are demonstrating important gene-by-environment interactions for diseases as diverse as chronic beryllium disease, coal workers’ pneumoconiosis, silicosis, asbestosis, bysinnosis, occupational asthma, and pollution-associated asthma. These findings have, in many instances, elucidated the pathogenesis of these highly complex diseases. At the same time, however, translation of this research into clinical practice has, for good reasons, proceeded slowly. No genetic test has yet emerged with sufficiently robust operating characteristics to be clearly useful or practicable in an occupational or environmental setting. Additionally, occupational genetic testing raises serious ethical and policy concerns. Therefore, the primary objective must remain ensuring that the workplace and the environment are safe for all. PMID:26024343

  4. Genetic factors in nonsmokers with age-related macular degeneration revealed through genome-wide gene-environment interaction analysis.

    PubMed

    Naj, Adam C; Scott, William K; Courtenay, Monique D; Cade, William H; Schwartz, Stephen G; Kovach, Jaclyn L; Agarwal, Anita; Wang, Gaofeng; Haines, Jonathan L; Pericak-Vance, Margaret A

    2013-05-01

    Relatively little is known about the interaction between genes and environment in the complex etiology of age-related macular degeneration (AMD). This study aimed to identify novel factors associated with AMD by analyzing gene-smoking interactions in a genome-wide association study of 1207 AMD cases and 686 controls of Caucasian background with genotype data on 668,238 single nucleotide polymorphisms (SNPs) after quality control. Participants' history of smoking at least 100 cigarettes lifetime was determined by a self-administered questionnaire. SNP associations modeled the effect of the minor allele additively on AMD using logistic regression, with adjustment for age, sex, and ever/never smoking. Joint effects of SNPs and smoking were examined comparing a null model containing only age, sex, and smoking against an extended model including genotypic and interaction terms. Genome-wide significant main effects were detected at three known AMD loci: CFH (P = 7.51×10(-30) ), ARMS2 (P = 1.94×10(-23) ), and RDBP/CFB/C2 (P = 4.37×10(-10) ), while joint effects analysis revealed three genomic regions with P < 10(-5) . Analyses stratified by smoking found genetic associations largely restricted to nonsmokers, with one notable exception: the chromosome 18q22.1 intergenic SNP rs17073641 (between SERPINB8 and CDH7), more strongly associated in nonsmokers (OR = 0.57, P = 2.73 × 10(-5) ), with an inverse association among smokers (OR = 1.42, P = 0.00228), suggesting that smoking modifies the effect of some genetic polymorphisms on AMD risk.

  5. A general test for gene-environment interaction in sib pair-based association analysis of quantitative traits.

    PubMed

    van der Sluis, Sophie; Dolan, Conor V; Neale, Michael C; Posthuma, Danielle

    2008-07-01

    Several association studies support the hypothesis that genetic variants can modify the influence of environmental factors on behavioral outcomes, i.e., G x E interaction. The case-control design used in these studies is powerful, but population stratification with respect to allele frequencies can give rise to false positive or false negative associations. Stratification with respect to the environmental factors can lead to false positives or false negatives with respect to environmental main effects and G x E interaction effects as well. Here we present a model based on Fulker et al. (1999) and Purcell (2002) for the study of G x E interaction in family-based association designs, in which the effects of stratification can be controlled. Simulations illustrate the power to detect genetic and environmental main effects, and G x E interaction effects for the sib pair design. The power to detect interaction was studied in eight different situations, both with and without the presence of population stratification, and for categorical and continuous environmental factors. Results show that the power to detect genetic and environmental main effects, and G x E interaction effects, depends on the allele frequencies and the distribution of the environmental moderator. Admixture effects of realistic effect size lead only to very small stratification effects in the G x E component, so impractically large numbers of sib pairs are required to detect such stratification.

  6. Understanding risk for psychopathology through imaging gene-environment interactions

    PubMed Central

    Hyde, Luke W.; Bogdan, Ryan; Hariri, Ahmad R.

    2011-01-01

    Examining the interplay of genes, experience, and the brain is critical to understanding psychopathology. We review the recent gene-environment interaction (GxE) and imaging genetics literature with the goal of developing models to bridge these approaches within single imaging gene-environment interaction (IGxE) studies. We explore challenges inherent in both GxE and imaging genetics and highlight studies that address these limitations. In specifying IGxE models, we examine statistical methods for combining these approaches, and explore plausible biological mechanisms (e.g., epigenetics) through which these conditional mechanisms can be understood. Finally, we discuss the potential contribution that IGxE studies can make to understanding psychopathology and developing more personalized and effective prevention and treatment. PMID:21839667

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

    PubMed Central

    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 gene-environment interactions are now fairly common in human genetic research, and with the shift towards genome-wide association studies, genome-wide gene-environment interaction studies are beginning to emerge. Methods We summarize the basic ideas behind gene-environment interaction, and provide an overview of possible study designs and traditional analysis methods in the context of genome-wide analysis. We then discuss novel approaches beyond the traditional strategy of analyzing the interaction between the environmental factor and each polymorphism individually. Results Two-step filtering approaches that reduce the number of polymorphisms tested for interactions can substantially increase the power of genome-wide gene-environment studies. New analytical methods including data-mining approaches, and gene-level and pathway-level analyses, also have the capacity to improve our understanding of how complex genetic and environmental factors interact to influence psychological and psychiatric traits. Such methods, however, have not yet been utilized much in behavioral and mental health research. Conclusions Although methods to investigate gene-environment interactions are available, there is a need for further development and extension of these methods to identify gene-environment interactions in the context of genome-wide association studies. These novel approaches need to be applied in studies of psychology and psychiatry. PMID:23808649

  8. The importance of gene-environment interactions in human obesity.

    PubMed

    Reddon, Hudson; Guéant, Jean-Louis; Meyre, David

    2016-09-01

    The worldwide obesity epidemic has been mainly attributed to lifestyle changes. However, who becomes obese in an obesity-prone environment is largely determined by genetic factors. In the last 20 years, important progress has been made in the elucidation of the genetic architecture of obesity. In parallel with successful gene identifications, the number of gene-environment interaction (GEI) studies has grown rapidly. This paper reviews the growing body of evidence supporting gene-environment interactions in the field of obesity. Heritability, monogenic and polygenic obesity studies provide converging evidence that obesity-predisposing genes interact with a variety of environmental, lifestyle and treatment exposures. However, some skepticism remains regarding the validity of these studies based on several issues, which include statistical modelling, confounding, low replication rate, underpowered analyses, biological assumptions and measurement precision. What follows in this review includes (1) an introduction to the study of GEI, (2) the evidence of GEI in the field of obesity, (3) an outline of the biological mechanisms that may explain these interaction effects, (4) methodological challenges associated with GEI studies and potential solutions, and (5) future directions of GEI research. Thus far, this growing body of evidence has provided a deeper understanding of GEI influencing obesity and may have tremendous applications in the emerging field of personalized medicine and individualized lifestyle recommendations.

  9. Meta-regression of gene-environment interaction in genome-wide association studies.

    PubMed

    Xu, Xiaoxiao; Shi, Gang; Nehorai, Arye

    2013-12-01

    Genome-wide association studies (GWAS) have created heightened interest in understanding the effects of gene-environment interaction on complex human diseases or traits. Applying methods for analyzing such interaction can help uncover novel genes and identify environmental hazards that influence only certain genetically susceptible groups. However, the number of interaction analysis methods is still limited, so there is a need to develop more efficient and powerful methods. In this paper, we propose two novel meta-analysis methods of studying gene-environment interaction, based on meta-regression of estimated genetic effects on the environmental factor. The two methods can perform joint analysis of a single nucleotide polymorphism's (SNP) main and interaction effects, or analyze only the effect of the interaction. They can readily estimate any linear or non-linear interactions by simply modifying the gene-environment regression function. Thus, they are efficient methods to be applied to different scenarios. We use numerical examples to demonstrate the performance of our methods. We also compare them with two other methods commonly used in current GWAS, i.e., meta-analysis of SNP main effects (MAIN) and joint meta-analysis of SNP main and interaction effects (JMA). The results show that our methods are more powerful than MAIN when the interaction effect exists, and are comparable to JMAin the linear or quadratic interaction cases. In the numerical examples, we also investigate how the number of the divided groups and the sample size of the studies affect the performance of our methods.

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

    DTIC Science & Technology

    2006-05-01

    exposures, endocrine disruptors , estrogen receptor genes, gene-environment interaction, methodologic approaches to examining multiple exposures 16...phthalates and pyrethroid pesticides . o The collection of serial urine samples was completed. o The CDC has competed sample analysis and has...Environmental Epidemiology 2005). Teitelbaum SL, Gammon MD, Britton JA, Neugut AI, Levin B, Stellman SD. Reported residential pesticide use and breast

  11. 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.

  12. Gene-environment interactions in chronic obstructive pulmonary disease.

    PubMed

    Molfino, Nestor A; Coyle, Anthony J

    2008-01-01

    Chronic obstructive pulmonary disease (COPD) is one of the leading causes of death throughout the world and is largely associated with cigarette smoking. Despite the appreciation of the central role of smoking in the development of COPD, only a relatively small number of smokers (15%-20%) develop COPD. Recent studies depicting familial aggregation suggest that some subjects may have a genetic predisposition to developing COPD. In this respect, a number of single nucleotide polymorphisms have been reported in association with different COPD features (subphenotypes), although much of this data remains controversial. Classical genetic studies (including twin and family studies) assume an "equal-environment" scenario, but as gene-environment interactions occur in COPD, this assumption needs revision. Thus, new integrated models are needed to examine the major environmental factors associated with COPD which include smoking as well as air pollution, and respiratory infections, and not only genetic predisposition. Revisiting this area, may help answer the question of what has more bearing in the pathogenesis of COPD--the environment or the genomic sequence of the affected subjects. It is anticipated that an improved understanding of this interaction will both enable improved identification of individuals susceptible to developing this disease, as well as improved future treatments for this disease.

  13. Study of oral clefts: Indication of gene-environment interaction

    SciTech Connect

    Hwang, S.J.; Beaty, T.H.; Panny, S.

    1994-09-01

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

  14. Candidate Gene-Environment Interaction Research: Reflections and Recommendations

    PubMed Central

    Dick, Danielle M.; Agrawal, Arpana; Keller, Matthew C.; Adkins, Amy; Aliev, Fazil; Monroe, Scott; Hewitt, John K.; Kendler, Kenneth S.; Sher, Kenneth J.

    2014-01-01

    Studying how genetic predispositions come together with environmental factors to contribute to complex behavioral outcomes has great potential for advancing our understanding of the development of psychopathology. It represents a clear theoretical advance over studying these factors in isolation. However, research at the intersection of multiple fields creates many challenges. We review several reasons why the rapidly expanding candidate gene-environment interaction (cGxE) literature should be considered with a degree of caution. We discuss lessons learned about candidate gene main effects from the evolving genetics literature and how these inform the study of cGxE. We review the importance of the measurement of the gene and environment of interest in cGxE studies. We discuss statistical concerns with modeling cGxE that are frequently overlooked. And we review other challenges that have likely contributed to the cGxE literature being difficult to interpret, including low power and publication bias. Many of these issues are similar to other concerns about research integrity (e.g., high false positive rates) that have received increasing attention in the social sciences. We provide recommendations for rigorous research practices for cGxE studies that we believe will advance its potential to contribute more robustly to the understanding of complex behavioral phenotypes. PMID:25620996

  15. Subtle gene-environment interactions driving paranoia in daily life.

    PubMed

    Simons, C J P; Wichers, M; Derom, C; Thiery, E; Myin-Germeys, I; Krabbendam, L; van Os, J

    2009-02-01

    It has been suggested that genes impact on the degree to which minor daily stressors cause variation in the intensity of subtle paranoid experiences. The objective of the present study was to test the hypothesis that catechol-O-methyltransferase (COMT) Val(158)Met and brain-derived neurotrophic factor (BDNF) Val(66)Met in part mediate genetic effects on paranoid reactivity to minor stressors. In a general population sample of 579 young adult female twins, on the one hand, appraisals of (1) event-related stress and (2) social stress and, on the other hand, feelings of paranoia in the flow of daily life were assessed using momentary assessment technology for five consecutive days. Multilevel regression analyses were used to examine moderation of daily life stress-induced paranoia by COMT Val(158)Met and BDNF Val(66)Met genotypes. Catechol-O-methyltransferase Val carriers displayed more feelings of paranoia in response to event stress compared with Met carriers. Brain-derived neurotrophic factor Met carriers showed more social-stress-induced paranoia than individuals with the Val/Val genotype. Thus, paranoia in the flow of daily life may be the result of gene-environment interactions that can be traced to different types of stress being moderated by different types of genetic variation.

  16. Gene-environment interactions on the risk of esophageal cancer among Asian populations with the G48A polymorphism in the alcohol dehydrogenase-2 gene: a meta-analysis.

    PubMed

    Zhang, Long; Jiang, Yingjiu; Wu, Qingcheng; Li, Qiang; Chen, Dan; Xu, Ling; Zhang, Cheng; Zhang, Min; Ye, Ling

    2014-05-01

    The aim of this study is to investigate the gene-environment interactions between the G48A polymorphism in the alcohol dehydrogenase-2 (ADH2) gene and environmental factors in determining the risk of esophageal cancer (EC). A literature search was conducted in the PubMed, Embase, Web of Science, Cochrane Library, and Google Scholar databases to indentify eligible studies published before November 1, 2013. We performed a meta-analysis of 18 case-control studies with a total of 8,906 EC patients and 13,712 controls. The overall analysis suggested that individuals with the GG genotype were associated with a 2.77-fold increased risk of EC, compared with carriers of the GA and AA genotypes. In a stratified analysis by ethnic group, Japanese, Mainland Chinese, and Taiwan Chinese with the GG genotype had a significantly higher risk of EC, compared with Thai and Iranian populations, indicating ethnic variance in EC susceptibility. An analysis of combined effect indicated that GG genotype of ADH2 G48A was associated with the highest risk of EC in heavy drinkers and smokers. A striking difference was found to exist between males and females, showing gender variance for the association between ADH2 G48A and EC risk. This meta-analysis shows that the GG genotype of ADH2 G48A may be associated with an increased risk of EC in Asian populations. In addition, significant gene-environment interactions were found. Heavy drinkers, smokers, and males with the GG genotype may have a higher EC risk. Thus, our results shed new light on the complex gene-environment interactions that exist between environmental factors and ADH2 G48A polymorphism in EC risk.

  17. A systematic gene-gene and gene-environment interaction analysis of DNA repair genes XRCC1, XRCC2, XRCC3, XRCC4, and oral cancer risk.

    PubMed

    Yang, Cheng-Hong; Lin, Yu-Da; Yen, Ching-Yui; Chuang, Li-Yeh; Chang, Hsueh-Wei

    2015-04-01

    Oral cancer is the sixth most common cancer worldwide with a high mortality rate. Biomarkers that anticipate susceptibility, prognosis, or response to treatments are much needed. Oral cancer is a polygenic disease involving complex interactions among genetic and environmental factors, which require multifaceted analyses. Here, we examined in a dataset of 103 oral cancer cases and 98 controls from Taiwan the association between oral cancer risk and the DNA repair genes X-ray repair cross-complementing group (XRCCs) 1-4, and the environmental factors of smoking, alcohol drinking, and betel quid (BQ) chewing. We employed logistic regression, multifactor dimensionality reduction (MDR), and hierarchical interaction graphs for analyzing gene-gene (G×G) and gene-environment (G×E) interactions. We identified a significantly elevated risk of the XRCC2 rs2040639 heterozygous variant among smokers [adjusted odds ratio (OR) 3.7, 95% confidence interval (CI)=1.1-12.1] and alcohol drinkers [adjusted OR=5.7, 95% CI=1.4-23.2]. The best two-factor based G×G interaction of oral cancer included the XRCC1 rs1799782 and XRCC2 rs2040639 [OR=3.13, 95% CI=1.66-6.13]. For the G×E interaction, the estimated OR of oral cancer for two (drinking-BQ chewing), three (XRCC1-XRCC2-BQ chewing), four (XRCC1-XRCC2-age-BQ chewing), and five factors (XRCC1-XRCC2-age-drinking-BQ chewing) were 32.9 [95% CI=14.1-76.9], 31.0 [95% CI=14.0-64.7], 49.8 [95% CI=21.0-117.7] and 82.9 [95% CI=31.0-221.5], respectively. Taken together, the genotypes of XRCC1 rs1799782 and XRCC2 rs2040639 DNA repair genes appear to be significantly associated with oral cancer. These were enhanced by exposure to certain environmental factors. The observations presented here warrant further research in larger study samples to examine their relevance for routine clinical care in oncology.

  18. Gene-environment Interactions in the Etiology of Dental Caries.

    PubMed

    Yildiz, G; Ermis, R B; Calapoglu, N S; Celik, E U; Türel, G Y

    2016-01-01

    Dental caries is a multifactorial disease that can be conceptualized as an interaction between genetic and environmental risk factors. The aim of this study is to examine the effects of AMELX, CA6, DEFB1, and TAS2R38 gene polymorphism and gene-environment interactions on caries etiology and susceptibility in adults. Genomic DNA was extracted from the buccal mucosa, and adults aged 20 to 60 y were placed into 1 of 2 groups: low caries risk (DMFT ≤ 5; n = 77) and high caries risk (DMFT ≥ 14; n = 77). The frequency of AMELX (+522), CA6 (T55M), DEFB1 (G-20A), and TAS2R38 (A49P) single-nucleotide polymorphisms was genotyped with the polymerase chain reaction-restriction fragment length polymorphism method. Environmental risk factors examined in the study included plaque amount, toothbrushing frequency, dietary intake between meals, saliva secretion rate, saliva buffer capacity, mutans streptococci counts, and lactobacilli counts. There was no difference between the caries risk groups in relation to AMELX (+522) polymorphism (χ(2) test, P > 0.05). The distribution of CA6 genotype and allele frequencies in the low caries risk group did not differ from the high caries risk group (χ(2) test, P > 0.05). Polymorphism of DEFB1 (G-20A) was positively associated, and TAS2R38 (A49P) negatively associated, with caries risk (χ(2) test, P = 0.000). There were significant differences between caries susceptibility and each environmental risk factor, except for the saliva secretion rate (Mann-Whitney U test, P = 0.000). Based on stepwise multiple linear regression analyses, dental plaque amount, lactobacilli count, age, and saliva buffer capacity, as well as DEFB1 (G-20A), TAS2R38 (A49P), and CA6 (T55M) gene polymorphism, explained a total of 87.8% of the variations in DMFT scores. It can be concluded that variation in CA6 (T55M), DEFB1 (G-20A), and TAS2R38 (A49P) may be associated with caries experience in Turkish adults with a high level of dental plaque, lactobacilli count

  19. Efficient Designs of Gene-Environment Interaction Studies: Implications of Hardy-Weinberg Equilibrium and Gene-Environment Independence

    PubMed Central

    Chen, Jinbo; Kang, Guolian; VanderWeele, Tyler; Zhang, Cuilin; Mukherjee, Bhramar

    2012-01-01

    SUMMARY It is important to investigate whether genetic susceptible variants exercise the same effects in populations that are differentially exposed to environmental risk factors. Here, we assess the power of four two-phase case-control design strategies for assessing multiplicative gene-environment (G-E) interactions or for assessing genetic or environmental effects in the presence of G-E interactions. With a di-allelic SNP and a binary E, we obtained closed-form maximum likelihood estimates of both main effect and interaction odds ratio parameters under the constraints of G-E independence and Hardy-Weinberg Equilibrium, and used the Wald statistic for all tests. We concluded that i) for testing G-E interactions or genetic effects in the presence of G-E interactions when data for E is fully available, it is preferable to ascertain data for G in a subsample of cases with similar numbers of exposed and unexposed and a random subsample of controls; and ii) for testing G-E interactions or environmental effects in the presence of G-E interactions when data for G is fully available, it is preferable to ascertain data for E in a subsample of cases that has similar numbers for each genotype and a random subsample of controls. In addition, supplementing external control data to an existing casecontrol sample leads to improved power for assessing effects of G or E in the presence of G-E interactions. PMID:22362617

  20. 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.…

  1. 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

  2. Gene-Environment Interaction and Children’s Health and Development

    PubMed Central

    Wright, Robert O.; Christiani, David

    2010-01-01

    Purpose of Review A systematic approach to studying gene-environment interaction can have immediate impact on our understanding of how environmental factors induce developmental disease and toxicity and provide biological insight for potential treatment and prevention measures. Recent Findings Because DNA sequence is static, genetic studies typically are not conducted prospectively. This limits the ability to incorporate environmental data into an analysis, as such data is usually collected cross-sectionally. Prospective environmental data collection could account for the role of critical windows of susceptibility that likely corresponds to the expression of specific genes and gene pathways. The use of large scale genomic platforms to discover genetic variants that modify environmental exposure in conjunction with a priori planned replication studies would reduce the number of false positive results. Summary Using a genome-wide approach, combined with a prospective longitudinal of environmental exposure at critical developmental windows is the optimal design for gene-environment interaction research. This approach would discover susceptibility variants, then validate the findings in an independent sample of children. Designs which combine the strengths and methodologies of each field will yield data which can account for both genetic variability and the role of critical developmental windows in the etiology of childhood disease and development. PMID:20090521

  3. 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.

  4. Genetics and gene-environment interactions on longevity and lifespan

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Longevity is a complex trait and highly associated with healthspan – lifespan without major diseases. In human populations there is a large amount of variation in longevity, which can be attributed to genetics, environment, and interactions between them. The genetic contribution to longevity is abou...

  5. Celiac disease: a model disease for gene-environment interaction.

    PubMed

    Uibo, Raivo; Tian, Zhigang; Gershwin, M Eric

    2011-03-01

    Celiac sprue remains a model autoimmune disease for dissection of genetic and environmental influences on disease progression. The 2010 Congress of Autoimmunity included several key sessions devoted to genetics and environment. Several papers from these symposia were selected for in-depth discussion and publication. This issue is devoted to this theme. The goal is not to discuss genetic and environmental interactions, but rather to focus on key elements of diagnosis, the inflammatory response and the mechanisms of autoimmunity.

  6. 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.

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

    PubMed Central

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

    2015-01-01

    Kernel machine (KM) models are a powerful tool for exploring associations between sets of genetic variants and complex traits. While 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. Multi-kernel 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 multi-factor analyses, but requires the estimation of high dimensional nuisance parameters. Traditional estimation techniques, including regularization and the 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 multi-kernel 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. PMID:26139508

  8. 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.

  9. Gene-environment interactions and obesity: recent developments and future directions

    PubMed Central

    2015-01-01

    Obesity, a major public health concern, is a multifactorial disease caused by both environmental and genetic factors. Although recent genome-wide association studies have identified many loci related to obesity or body mass index, the identified variants explain only a small proportion of the heritability of obesity. Better understanding of the interplay between genetic and environmental factors is the basis for developing effective personalized obesity prevention and management strategies. This article reviews recent advances in identifying gene-environment interactions related to obesity and describes epidemiological designs and newly developed statistical approaches to characterizing and discovering gene-environment interactions on obesity risk. PMID:25951849

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

    PubMed Central

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

    2015-01-01

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

  11. 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.…

  12. 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…

  13. 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…

  14. CardioGxE, a catalog of gene-environment interactions for cardiometabolic traits

    PubMed Central

    2014-01-01

    Background Genetic understanding of complex traits has developed immensely over the past decade but remains hampered by incomplete descriptions of contribution to phenotypic variance. Gene-environment (GxE) interactions are one of these contributors and in the guise of diet and physical activity are important modulators of cardiometabolic phenotypes and ensuing diseases. Results We mined the scientific literature to collect GxE interactions from 386 publications for blood lipids, glycemic traits, obesity anthropometrics, vascular measures, inflammation and metabolic syndrome, and introduce CardioGxE, a gene-environment interaction resource. We then analyzed the genes and SNPs supporting cardiometabolic GxEs in order to demonstrate utility of GxE SNPs and to discern characteristics of these important genetic variants. We were able to draw many observations from our extensive analysis of GxEs. 1) The CardioGxE SNPs showed little overlap with variants identified by main effect GWAS, indicating the importance of environmental interactions with genetic factors on cardiometabolic traits. 2) These GxE SNPs were enriched in adaptation to climatic and geographical features, with implications on energy homeostasis and response to physical activity. 3) Comparison to gene networks responding to plasma cholesterol-lowering or regression of atherosclerotic plaques showed that GxE genes have a greater role in those responses, particularly through high-energy diets and fat intake, than do GWAS-identified genes for the same traits. Other aspects of the CardioGxE dataset were explored. Conclusions Overall, we demonstrate that SNPs supporting cardiometabolic GxE interactions often exhibit transcriptional effects or are under positive selection. Still, not all such SNPs can be assigned potential functional or regulatory roles often because data are lacking in specific cell types or from treatments that approximate the environmental factor of the GxE. With research on metabolic related

  15. Identifying gene-environment and gene-gene interactions using a progressive penalization approach.

    PubMed

    Zhu, Ruoqing; Zhao, Hongyu; Ma, Shuangge

    2014-05-01

    In genomic studies, identifying important gene-environment and gene-gene interactions is a challenging problem. In this study, we adopt the statistical modeling approach, where interactions are represented by product terms in regression models. For the identification of important interactions, we adopt penalization, which has been used in many genomic studies. Straightforward application of penalization does not respect the "main effect, interaction" hierarchical structure. A few recently proposed methods respect this structure by applying constrained penalization. However, they demand very complicated computational algorithms and can only accommodate a small number of genomic measurements. We propose a computationally fast penalization method that can identify important gene-environment and gene-gene interactions and respect a strong hierarchical structure. The method takes a stagewise approach and progressively expands its optimization domain to account for possible hierarchical interactions. It is applicable to multiple data types and models. A coordinate descent method is utilized to produce the entire regularized solution path. Simulation study demonstrates the superior performance of the proposed method. We analyze a lung cancer prognosis study with gene expression measurements and identify important gene-environment interactions.

  16. Tests for Gene-Environment Interactions and Joint Effects With Exposure Misclassification

    PubMed Central

    Boonstra, Philip S.; Mukherjee, Bhramar; Gruber, Stephen B.; Ahn, Jaeil; Schmit, Stephanie L.; Chatterjee, Nilanjan

    2016-01-01

    The number of methods for genome-wide testing of gene-environment (G-E) interactions continues to increase, with the aim of discovering new genetic risk factors and obtaining insight into the disease-gene-environment relationship. The relative performance of these methods, assessed on the basis of family-wise type I error rate and power, depends on underlying disease-gene-environment associations, estimates of which may be biased in the presence of exposure misclassification. This simulation study expands on a previously published simulation study of methods for detecting G-E interactions by evaluating the impact of exposure misclassification. We consider 7 single-step and modular screening methods for identifying G-E interaction at a genome-wide level and 7 joint tests for genetic association and G-E interaction, for which the goal is to discover new genetic susceptibility loci by leveraging G-E interaction when present. In terms of statistical power, modular methods that screen on the basis of the marginal disease-gene relationship are more robust to exposure misclassification. Joint tests that include main/marginal effects of a gene display a similar robustness, which confirms results from earlier studies. Our results offer an increased understanding of the strengths and limitations of methods for genome-wide searches for G-E interaction and joint tests in the presence of exposure misclassification. PMID:26755675

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

    PubMed Central

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

    2014-01-01

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

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

    DTIC Science & Technology

    2007-05-01

    TERMS epidemiology, environmental exposures, endocrine disruptors , estrogen receptor genes, gene-environment interaction, methodologic approaches...phthalates and pyrethroid pesticides . o The collection of serial urine samples was completed. W81XWH-04-1-0507 6 o The CDC has competed sample...manuscripts are in preparation. • Published manuscript examining combined effect of multiple exposures “Reported residential pesticide use and breast

  19. 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.

  20. Preliminary Evidence for a Gene-Environment Interaction in Predicting Alcohol Use Disorders in Adolescents

    PubMed Central

    Miranda, Robert; Reynolds, Elizabeth; Ray, Lara; Justus, Alicia; Knopik, Valerie S.; McGeary, John; Meyerson, Lori A.

    2013-01-01

    Background Emerging research suggests that genetic influences on adolescent drinking are moderated by environmental factors. The present study builds on molecular-genetic findings by conducting the first analysis of gene-environment interactions in the association between a functional single nucleotide polymorphism (SNP) of the µ-opioid receptor (OPRM1) gene (A118G) and risk for developing an alcohol use disorder (AUD) during adolescence. Specifically, we tested whether variation in parenting practices or affiliation with deviant peers moderated the link between the OPRM1 gene and risk for an AUD. Methods Adolescents reporting European ancestry (N = 104), ages 12–19 years (M = 15.60, SD = 1.77), were interviewed to ascertain AUD diagnoses, provided a DNA sample for genetic analyses, and completed measures of parental monitoring and deviant peer affiliation. Logistic regression was used to test the effects of environmental variable sand their interactions with OPRM1genotype as predictors of AUD diagnosis while controlling for age and sex. Results Case-control comparisons showed that the proportion of youth with an AUD (n = 18) significantly differed by genotype such that 33.3% of G allele carriers met criteria for an AUD compared to 10.8% of youth who were homozygous for the A allele (p = .006). The OPRM1 × parental monitoring (odds ratio = 0.16) and OPRM1 × deviant peer affiliation (odds ratio = 7.64) interactions were significant predictors of AUD risk, such that G allele carriers with high levels of deviant peer affiliation or lower levels of parental monitoring had the greatest likelihood of developing an AUD (p values < .01). Conclusions This study provides initial evidence that the association between the A118G SNP of the OPRM1 gene and risk for AUDs is moderated by modifiable factors. These results are limited, however, by the small sample size and require replication. PMID:23136901

  1. Tests for gene-environment interaction from case-control data: a novel study of type I error, power and designs.

    PubMed

    Mukherjee, Bhramar; Ahn, Jaeil; Gruber, Stephen B; Rennert, Gad; Moreno, Victor; Chatterjee, Nilanjan

    2008-11-01

    To evaluate the risk of a disease associated with the joint effects of genetic susceptibility and environmental exposures, epidemiologic researchers often test for non-multiplicative gene-environment effects from case-control studies. In this article, we present a comparative study of four alternative tests for interactions: (i) the standard case-control method; (ii) the case-only method, which requires an assumption of gene-environment independence for the underlying population; (iii) a two-step method that decides between the case-only and case-control estimators depending on a statistical test for the gene-environment independence assumption and (iv) a novel empirical-Bayes (EB) method that combines the case-control and case-only estimators depending on the sample size and strength of the gene-environment association in the data. We evaluate the methods in terms of integrated Type I error and power, averaged with respect to varying scenarios for gene-environment association that are likely to appear in practice. These unique studies suggest that the novel EB procedure overall is a promising approach for detection of gene-environment interactions from case-control studies. In particular, the EB procedure, unlike the case-only or two-step methods, can closely maintain a desired Type I error under realistic scenarios of gene-environment dependence and yet can be substantially more powerful than the traditional case-control analysis when the gene-environment independence assumption is satisfied, exactly or approximately. Our studies also reveal potential utility of some non-traditional case-control designs that samples controls at a smaller rate than the cases. Apart from the simulation studies, we also illustrate the different methods by analyzing interactions of two commonly studied genes, N-acetyl transferase type 2 and glutathione s-transferase M1, with smoking and dietary exposures, in a large case-control study of colorectal cancer.

  2. Genome-wide gene-environment interactions on quantitative traits using family data.

    PubMed

    Sitlani, Colleen M; Dupuis, Josée; Rice, Kenneth M; Sun, Fangui; Pitsillides, Achilleas N; Cupples, L Adrienne; Psaty, Bruce M

    2016-07-01

    Gene-environment interactions may provide a mechanism for targeting interventions to those individuals who would gain the most benefit from them. Searching for interactions agnostically on a genome-wide scale requires large sample sizes, often achieved through collaboration among multiple studies in a consortium. Family studies can contribute to consortia, but to do so they must account for correlation within families by using specialized analytic methods. In this paper, we investigate the performance of methods that account for within-family correlation, in the context of gene-environment interactions with binary exposures and quantitative outcomes. We simulate both cross-sectional and longitudinal measurements, and analyze the simulated data taking family structure into account, via generalized estimating equations (GEE) and linear mixed-effects models. With sufficient exposure prevalence and correct model specification, all methods perform well. However, when models are misspecified, mixed modeling approaches have seriously inflated type I error rates. GEE methods with robust variance estimates are less sensitive to model misspecification; however, when exposures are infrequent, GEE methods require modifications to preserve type I error rate. We illustrate the practical use of these methods by evaluating gene-drug interactions on fasting glucose levels in data from the Framingham Heart Study, a cohort that includes related individuals.

  3. 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

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

    PubMed

    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.

  5. A mechanism for gene-environment interaction in the etiology of congenital scoliosis.

    PubMed

    Sparrow, Duncan B; Chapman, Gavin; Smith, Allanceson J; Mattar, Muhammad Z; Major, Joelene A; O'Reilly, Victoria C; Saga, Yumiko; Zackai, Elaine H; Dormans, John P; Alman, Benjamin A; McGregor, Lesley; Kageyama, Ryoichiro; Kusumi, Kenro; Dunwoodie, Sally L

    2012-04-13

    Congenital scoliosis, a lateral curvature of the spine caused by vertebral defects, occurs in approximately 1 in 1,000 live births. Here we demonstrate that haploinsufficiency of Notch signaling pathway genes in humans can cause this congenital abnormality. We also show that in a mouse model, the combination of this genetic risk factor with an environmental condition (short-term gestational hypoxia) significantly increases the penetrance and severity of vertebral defects. We demonstrate that hypoxia disrupts FGF signaling, leading to a temporary failure of embryonic somitogenesis. Our results potentially provide a mechanism for the genesis of a host of common sporadic congenital abnormalities through gene-environment interaction.

  6. Importance of gene-environment interactions in the etiology of selected birth defects.

    PubMed

    Zhu, H; Kartiko, S; Finnell, R H

    2009-05-01

    It is generally understood that both genetic and environmental factors contribute to the highly complex etiology of structural birth defects, including neural tube defects, oral clefts and congenital heart defects, by disrupting highly regulated embryonic developmental processes. The intrauterine environment of the developing embryo/fetus is determined by maternal factors such as health/disease status, lifestyle, medication, exposure to environmental teratogens, as well as the maternal genotype. Certain genetic characteristics of the embryo/fetus also predispose it to developmental abnormalities. Epidemiologic and animal studies conducted over the last few decades have suggested that the interplay between genes and environmental factors underlies the etiological heterogeneity of these defects. It is now widely believed that the study of gene-environment interactions will lead to better understanding of the biological mechanisms and pathological processes that contribute to the development of complex birth defects. It is only through such an understanding that more efficient measures will be developed to prevent these severe, costly and often deadly defects. In this review, we attempt to summarize the complex clinical and experimental literature on current hypotheses of interactions between several select environmental factors and those genetic pathways in which they are most likely to have significant modifying effects. These include maternal folate nutritional status, maternal diabetes/obesity-related conditions, and maternal exposure to selected medications and environmental contaminants. Our goal is to highlight the potential gene-environment interactions affecting early embryogenesis that deserve comprehensive study.

  7. G x E: a NIAAA workshop on gene-environment interactions.

    PubMed

    Gunzerath, Lorraine; Goldman, David

    2003-03-01

    The National Institute on Alcohol Abuse and Alcoholism (NIAAA) sponsored a May 2002 workshop on gene-environment interaction (G x E) research to identify potential roadblocks to further research and to propose solutions to those roadblocks, to optimize investigative opportunities and multidisciplinary or multi-institution collaborations, and to explore ways that NIAAA can facilitate G x E studies. Sessions included panels on animal models; phenotypes; genetic findings in humans; study designs and analytical methods; and assessment of environmental risk. Key among the identified challenges to progress in G x E research were issues of study design and sampling strategies; logistic and methodological costs and constraints; availability and understanding of data analysis techniques; potential stigmatization of study populations; and organizational/bureaucratic structures that are inadequate to address the unique needs of large-scale, multicenter, longitudinal projects. Participants proposed a series of recommendations to address these issues. Session coordinators included: Gayle Boyd, Kendall Bryant, Page Chiapella, Vivian Faden, David Goldman, and Antonio Noronha. Session participants included: Laura Almasy, Henri Begleiter, Raul Caetano, Bruce Dudek, Mary Dufour, Cindy Ehlers, Mary-Anne Enoch, Joel Gelernter, David Goldman, Bridget Grant, Lorraine Gunzerath, Deborah Hasin, Andrew Heath, Victor Hesselbrock, J. Dee Higley, Shirley Hill, Kerry Jang, Raynard S. Kington, Rick Kittles, George Koob, Kenneth Leonard, Ting-Kai Li, Jeffrey Long, William McBride, Matthew McGue, Kathleen Merikangas, Tamara Phillips, Bernice Porjesz, Carol Prescott, Theodore Reich, John Rice, Richard Rose, Charmaine Royal, Arnold Sameroff, Marc Schuckit, Kenneth Sher, Renee Sieving, Robert Taylor, Michael Windle, and Robert Zucker.

  8. Characterization of gene-environment interactions for colorectal cancer susceptibility loci

    PubMed Central

    Hutter, Carolyn M.; Chang-Claude, Jenny; Slattery, Martha L.; Pflugeisen, Bethann M.; Lin, Yi; Duggan, David; Nan, Hongmei; Lemire, Mathieu; Rangrej, Jagadish; Figueiredo, Jane C.; Jiao, Shuo; Harrison, Tabitha A.; Liu, Yan; Chen, Lin S.; Stelling, Deanna L.; Warnick, Greg S.; Hoffmeister, Michael; Küry, Sébastien; Fuchs, Charles S.; Giovannucci, Edward; Hazra, Aditi; Kraft, Peter; Hunter, David J.; Gallinger, Steven; Zanke, Brent W.; Brenner, Hermann; Frank, Bernd; Ma, Jing; Ulrich, Cornelia M.; White, Emily; Newcomb, Polly A.; Kooperberg, Charles; LaCroix, Andrea Z.; Prentice, Ross L.; Jackson, Rebecca D.; Schoen, Robert E.; Chanock, Stephen J.; Berndt, Sonja I.; Hayes, Richard B.; Caan, Bette J.; Potter, John D.; Hsu, Li; Bézieau, Stéphane; Chan, Andrew T.; Hudson, Thomas J.; Peters, Ulrike

    2012-01-01

    Genome-wide association studies (GWAS) have identified over a dozen loci associated with colorectal cancer (CRC) risk. Here we examined potential effect-modification between single nucleotide polymorphisms (SNPs) at 10 of these loci and probable or established environmental risk factors for CRC in 7,016 CRC cases and 9,723 controls from nine cohort and case-control studies. We used meta-analysis of an efficient empirical-Bayes estimator to detect potential multiplicative interactions between each of the SNPs [rs16892766 at 8q23.3 (EIF3H/UTP23); rs6983267 at 8q24 (MYC); rs10795668 at 10p14 (FLJ3802842); rs3802842 at11q23 (LOC120376); rs4444235 at 14q22.2 (BMP4); rs4779584 at15q13 (GREM1); rs9929218 at16q22.1 (CDH1); rs4939827 at18q21 (SMAD7); rs10411210 at19q13.1 (RHPN2); and rs961253 at 20p12.3 (BMP2)] and select major CRC risk factors (sex, body mass index, height, smoking status, aspirin/non-steroidal anti-inflammatory drug use, alcohol use, and dietary intake of calcium, folate, red meat, processed meat, vegetables, fruit, and fiber). The strongest statistical evidence for a gene-environment interaction across studies was for vegetable consumption and rs16892766, located on chromosome 8q23.3, near the EIF3H and UTP23 genes (nominal p-interaction =1.3×10–4; adjusted p-value 0.02). The magnitude of the main effect of the SNP increased with increasing levels of vegetable consumption. No other interactions were statistically significant after adjusting for multiple comparisons. Overall, the association of most CRC susceptibility loci identified in initial GWAS appears to be invariant to the other risk factors considered; however, our results suggest potential modification of the rs16892766 effect by vegetable consumption. PMID:22367214

  9. 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

  10. [Detecting gene-gene/environment interactions by model-based multifactor dimensionality reduction].

    PubMed

    Fan, Wei; Shen, Chao; Guo, Zhirong

    2015-11-01

    This paper introduces a method called model-based multifactor dimensionality reduction (MB-MDR), which was firstly proposed by Calle et al., and can be applied for detecting gene-gene or gene-environment interactions in genetic studies. The basic principle and characteristics of MB-MDR as well as the operation in R program are briefly summarized. Besides, the detailed procedure of MB-MDR is illustrated by using example. Compared with classical MDR, MB-MDR has similar principle, which merges multi-locus genotypes into a one-dimensional construct and can be used in the study with small sample size. However, there is some difference between MB-MDR and classical MDR. First, it has higher statistical power than MDR and other MDR in the presence of different noises due to the different way the genotype cells merged. Second, compared with MDR, it can deal with all binary and quantitative traits, adjust marginal effects of factors and confounders. MBMDR could be a useful method in the analyses of gene-gene/environment interactions.

  11. 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

  12. The role of gene-environment correlations and interactions in middle childhood depressive symptoms.

    PubMed

    Wilkinson, Paul O; Trzaskowski, Maciej; Haworth, Claire M A; Eley, Thalia C

    2013-02-01

    Depression is known to be associated with a wide array of environmental factors. Such associations are due at least in part to genetic influences on both. This issue has been little explored with preadolescent children. Measures of family chaos and parenting style at age 9 and child depressive symptoms at age 12 were completed by 3,258 twin pairs from the Twins Early Development Study and their parents. Quantitative genetic modeling was used to explore common and unique genetic and environmental influences on both family environment and later depressive symptoms. Depressive symptoms at age 12 were significantly heritable. Moderate genetic effects influenced parenting style and family chaos at the age of 9, indicating gene-environment correlation. There were significant genetic correlations between family environment and depressive symptoms. There was some evidence of a Gene × Environment interaction, with stronger genetic effects on depressive symptoms for children with more suboptimal family environment. There was an Environment × Environment interaction, with effects of nonshared environment on depressive symptoms stronger for twins with more adverse parenting experiences. There is some evidence for gene-environment correlation between aspects of family environment in middle childhood and subsequent depressive symptoms. This suggests that one of the mechanisms by which genes lead to depressive symptoms may be by themselves influencing depressogenic environments.

  13. The role of gene-environment interactions in the development of food allergy.

    PubMed

    Neeland, Melanie R; Martino, David J; Allen, Katrina J

    2015-01-01

    The rates of IgE-mediated food allergy have increased globally, particularly in developed countries. The rising incidence is occurring more rapidly than changes to the genome sequence would allow, suggesting that environmental exposures that alter the immune response play an important role. Genetic factors may also be used to predict an increased predisposition to these environmental risk factors, giving rise to the concept of gene-environment interactions, whereby differential risk of environmental exposures is mediated through the genome. Increasing evidence also suggests a role for epigenetic mechanisms, which are sensitive to environmental exposures, in the development of food allergy. This paper discusses the current state of knowledge regarding the environmental and genetic risk factors for food allergy and how environmental exposures may interact with immune genes to modify disease risk or outcome.

  14. Gene-environment interaction effects on lung function- a genome-wide association study within the Framingham heart study

    PubMed Central

    2013-01-01

    Background Previous studies in occupational exposure and lung function have focused only on the main effect of occupational exposure or genetics on lung function. Some disease-susceptible genes may be missed due to their low marginal effects, despite potential involvement in the disease process through interactions with the environment. Through comprehensive genome-wide gene-environment interaction studies, we can uncover these susceptibility genes. Our objective in this study was to explore gene by occupational exposure interaction effects on lung function using both the individual SNPs approach and the genetic network approach. Methods The study population comprised the Offspring Cohort and the Third Generation from the Framingham Heart Study. We used forced expiratory volume in one second (FEV1) and ratio of FEV1 to forced vital capacity (FVC) as outcomes. Occupational exposures were classified using a population-specific job exposure matrix. We performed genome-wide gene-environment interaction analysis, using the Affymetrix 550 K mapping array for genotyping. A linear regression-based generalized estimating equation was applied to account for within-family relatedness. Network analysis was conducted using results from single-nucleotide polymorphism (SNP)-level analyses and from gene expression study results. Results There were 4,785 participants in total. SNP-level analysis and network analysis identified SNP rs9931086 (Pinteraction =1.16 × 10-7) in gene SLC38A8, which may significantly modify the effects of occupational exposure on FEV1. Genes identified from the network analysis included CTLA-4, HDAC, and PPAR-alpha. Conclusions Our study implies that SNP rs9931086 in SLC38A8 and genes CTLA-4, HDAC, and PPAR-alpha, which are related to inflammatory processes, may modify the effect of occupational exposure on lung function. PMID:24289273

  15. Gene-environment interactions in psychopathology throughout early childhood: a systematic review.

    PubMed

    Pinto, Raquel Q; Soares, Isabel; Carvalho-Correia, Eduarda; Mesquita, Ana R

    2015-12-01

    Up to 20% of children and adolescents worldwide suffer from mental health problems. Epidemiological studies have shown that some of these problems are already present at an early age. The recognition that psychopathology is a result of an interaction between individual experiences and genetic characteristics has led to an increase in the number of studies using a gene-environment approach (G×E). However, to date, there has been no systematic review of G×E studies on psychopathology in the first 6 years of life. Following a literature search and a selection process, 14 studies were identified and most (n=12) of the studies found at least one significant G×E effect. This review provides a systematic characterization of the published G×E studies, providing insights into the neurobiological and environmental determinants involved in the etiology of children's psychopathology.

  16. Gene-environment interaction signatures by quantitative mRNA profiling in exfoliated buccal mucosal cells.

    PubMed

    Spivack, Simon D; Hurteau, Gregory J; Jain, Ritu; Kumar, Shalini V; Aldous, Kenneth M; Gierthy, John F; Kaminsky, Laurence S

    2004-09-15

    Exfoliated cytologic specimens from mouth (buccal) epithelium may contain viable cells, permitting assay of gene expression for direct and noninvasive measurement of gene-environment interactions, such as for inhalation (e.g., tobacco smoke) exposures. We determined specific mRNA levels in exfoliated buccal cells collected by cytologic brush, using a recently developed RNA-specific real-time quantitative reverse transcription-PCR strategy. In a pilot study, metabolic activity of exfoliated buccal cells was verified by 3-[4,5-dimethylthiazol-2-yl]-2,5- diphenyltetrazolium assay in vitro. Transcriptional activity was observed, after timed in vivo exposure to mainstream tobacco smoke resulted in induction of CYP1B1 in serially collected buccal samples from the one subject examined. For a set of 11 subjects, mRNA expression of nine genes encoding carcinogen- and oxidant-metabolizing enzymes qualitatively detected in buccal cells was then shown to correlate with that in laser-microdissected lung from the same individuals (Chi2 = 52.91, P < 0.001). Finally, quantitative real-time reverse transcription-PCR assays for seven target gene (AhR, CYP1A1, CYP1B1, GSTM1, GSTM3, GSTP1, and GSTT1) and three reference gene [glyceraldehyde-3-phosphate dehydrogenase (GAPDH), beta-actin, and 36B4] transcripts were performed on buccal specimens from 42 subjects. In multivariate analyses, gender, tobacco smoke exposure, and other factors were associated with the level of expression of CYP1B1, GSTP1, and other transcripts on a gene-specific basis, but substantial interindividual variability in mRNA expression remained unexplained. Within the power limits of this pilot study, gene expression signature was not clearly predictive of lung cancer case or control status. This noninvasive and quantitative method may be incorporated into high-throughput human applications for probing gene-environment interactions associated with cancer.

  17. Local Area Disadvantage and Gambling Involvement and Disorder: Evidence for Gene-Environment Correlation and Interaction

    PubMed Central

    Slutske, Wendy S.; Deutsch, Arielle R.; Statham, Dixie B.; Martin, Nicholas G.

    2015-01-01

    Previous research has demonstrated that local area characteristics (such as disadvantage and gambling outlet density) and genetic risk factors are associated with gambling involvement and disordered gambling. These two lines of research were brought together in the present study by examining the extent to which genetic contributions to individual differences in gambling involvement and disorder contributed to being exposed to, and were also accentuated by, local area disadvantage. Participants were members of the national community-based Australian Twin Registry who completed a telephone interview in which the past-year frequency of gambling and symptoms of disordered gambling were assessed. Indicators of local area disadvantage were based on census data matched to the participants' postal codes. Univariate biometric model-fitting revealed that exposure to area disadvantage was partially explained by genetic factors. Bivariate biometric model-fitting was conducted to examine the evidence for gene-environment interaction while accounting for gene-environment correlation. These analyses demonstrated that: (a) a small portion of the genetic propensity to gamble was explained by moving to or remaining in a disadvantaged area, and (b) the remaining genetic and unique environmental variation in the frequency of participating in electronic machine gambling (among men and women) and symptoms of disordered gambling (among women) was greater in more disadvantaged localities. As the gambling industry continues to grow, it will be important to take into account the multiple contexts in which problematic gambling behavior can emerge -- from genes to geography -- as well as the ways in which such contexts may interact with each other. PMID:26147321

  18. 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

  19. 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.

  20. 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…

  1. Leveraging gene-environment interactions and endotypes for asthma gene discovery.

    PubMed

    Bønnelykke, Klaus; Ober, Carole

    2016-03-01

    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.

  2. Gene-environment interactions in the development of complex disease phenotypes.

    PubMed

    Ramos, Rosemarie G; Olden, Kenneth

    2008-03-01

    The lack of knowledge about the earliest events in disease development is due to the multi-factorial nature of disease risk. This information gap is the consequence of the lack of appreciation for the fact that most diseases arise from the complex interactions between genes and the environment as a function of the age or stage of development of the individual. Whether an environmental exposure causes illness or not is dependent on the efficiency of the so-called "environmental response machinery" (i.e., the complex of metabolic pathways that can modulate response to environmental perturbations) that one has inherited. Thus, elucidating the causes of most chronic diseases will require an understanding of both the genetic and environmental contribution to their etiology. Unfortunately, the exploration of the relationship between genes and the environment has been hampered in the past by the limited knowledge of the human genome, and by the inclination of scientists to study disease development using experimental models that consider exposure to a single environmental agent. Rarely in the past were interactions between multiple genes or between genes and environmental agents considered in studies of human disease etiology. The most critical issue is how to relate exposure-disease association studies to pathways and mechanisms. To understand how genes and environmental factors interact to perturb biological pathways to cause injury or disease, scientists will need tools with the capacity to monitor the global expression of thousands of genes, proteins and metabolites simultaneously. The generation of such data in multiple species can be used to identify conserved and functionally significant genes and pathways involved in gene-environment interactions. Ultimately, it is this knowledge that will be used to guide agencies such as the U.S. Department of Health and Human Services in decisions regarding biomedical research funding and policy.

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

    PubMed

    Burrows, Emma L; Hannan, Anthony J

    2016-04-01

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

  4. Rethinking expertise: A multifactorial gene-environment interaction model of expert performance.

    PubMed

    Ullén, Fredrik; Hambrick, David Zachary; Mosing, Miriam Anna

    2016-04-01

    Scientific interest in expertise-superior performance within a specific domain-has a long history in psychology. Although there is a broad consensus that a long period of practice is essential for expertise, a long-standing controversy in the field concerns the importance of other variables such as cognitive abilities and genetic factors. According to the influential deliberate practice theory, expert performance is essentially limited by a single variable: the amount of deliberate practice an individual has accumulated. Here, we provide a review of the literature on deliberate practice, expert performance, and its neural correlates. A particular emphasis is on recent studies indicating that expertise is related to numerous traits other than practice as well as genetic factors. We argue that deliberate practice theory is unable to account for major recent findings relating to expertise and expert performance, and propose an alternative multifactorial gene-environment interaction model of expertise, which provides an adequate explanation for the available empirical data and may serve as a useful framework for future empirical and theoretical work on expert performance.

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

    PubMed

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

    2014-07-01

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

  6. Drug metabolism and liver disease: a drug-gene-environment interaction.

    PubMed

    Zgheib, Nathalie K; Branch, Robert A

    2017-02-01

    Despite the central role of the liver in drug metabolism, surprisingly there is lack of certainty in anticipating the extent of modification of the clearance of a given drug in a given patient. The intent of this review is to provide a conceptual framework in considering the impact of liver disease on drug disposition and reciprocally the impact of drug disposition on liver disease. It is proposed that improved understanding of the situation is gained by considering the issue as a special example of a drug-gene-environment interaction. This requires an integration of knowledge of the drug's properties, knowledge of the gene products involved in its metabolism, and knowledge of the pathophysiology of its disposition. This will enhance the level of predictability of drug disposition and toxicity for a drug of interest in an individual patient. It is our contention that advances in pharmacology, pharmacogenomics, and hepatology, together with concerted interests in the academic, regulatory, and pharmaceutical industry communities provide an ideal immediate environment to move from a qualitative reactive approach to quantitative proactive approach in individualizing patient therapy in liver disease.

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

    PubMed Central

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

    2015-01-01

    Rooted in people’s preoccupation with how they are perceived and evaluated, shame and guilt are self-conscious emotions that play adaptive roles in social behavior, but can also contribute to psychopathology when dysregulated. Shame and guilt-proneness develop during childhood and adolescence, and are influenced by genetic and environmental factors that are little known to date. This study investigated the effects of early traumatic events and functional polymorphisms in the brain-derived neurotrophic factor (BDNF) gene and the serotonin transporter gene promoter (5-HTTLPR) on shame and guilt in adolescents. A sample of N = 271 healthy adolescents between 14 and 17 years of age filled in measures of early traumatic events and proneness to shame and guilt, and were genotyped for the BDNF Val66Met and 5-HTTLPR polymorphisms. Results of moderator analyses indicated that trauma intensity was positively associated with guilt-proneness only in carriers of the low-expressing Met allele of BDNF Val66Met. This is the first study that identifies a gene-environment interaction that significantly contributes to guilt proneness in adolescents, with potential implications for developmental psychopathology. PMID:26230319

  8. Gene-Environment Interaction in Adults’ IQ Scores: Measures of Past and Present Environment

    PubMed Central

    Willemsen, Gonneke; de Geus, Eco J. C.; Boomsma, Dorret I.; Posthuma, Danielle

    2008-01-01

    Gene-environment interaction was studied in a sample of young (mean age 26 years, N = 385) and older (mean age 49 years, N = 370) adult males and females. Full scale IQ scores (FSIQ) were analyzed using biometric models in which additive genetic (A), common environmental (C), and unique environmental (E) effects were allowed to depend on environmental measures. Moderators under study were parental and partner educational level, as well as urbanization level and mean real estate price of the participants’ residential area. Mean effects were observed for parental education, partner education and urbanization level. On average, FSIQ scores were roughly 5 points higher in participants with highly educated parents, compared to participants whose parents were less well educated. In older participants, IQ scores were about 2 points higher when their partners were highly educated. In younger males, higher urbanization levels were associated with slightly higher FSIQ scores. Our analyses also showed increased common environmental variation in older males whose parents were more highly educated, and increased unique environmental effects in older males living in more affluent areas. Contrary to studies in children, however, the variance attributable to additive genetic effects was stable across all levels of the moderators under study. Most results were replicated for VIQ and PIQ. PMID:18535898

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

    PubMed

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

    2015-05-01

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

  10. Identifying Gene-Environment Interactions in Schizophrenia: Contemporary Challenges for Integrated, Large-scale Investigations

    PubMed Central

    2014-01-01

    Recent years have seen considerable progress in epidemiological and molecular genetic research into environmental and genetic factors in schizophrenia, but methodological uncertainties remain with regard to validating environmental exposures, and the population risk conferred by individual molecular genetic variants is small. There are now also a limited number of studies that have investigated molecular genetic candidate gene-environment interactions (G × E), however, so far, thorough replication of findings is rare and G × E research still faces several conceptual and methodological challenges. In this article, we aim to review these recent developments and illustrate how integrated, large-scale investigations may overcome contemporary challenges in G × E research, drawing on the example of a large, international, multi–center study into the identification and translational application of G × E in schizophrenia. While such investigations are now well underway, new challenges emerge for G × E research from late-breaking evidence that genetic variation and environmental exposures are, to a significant degree, shared across a range of psychiatric disorders, with potential overlap in phenotype. PMID:24860087

  11. Education and alcohol use: A study of gene-environment interaction in young adulthood.

    PubMed

    Barr, Peter B; Salvatore, Jessica E; Maes, Hermine; Aliev, Fazil; Latvala, Antti; Viken, Richard; Rose, Richard J; Kaprio, Jaakko; Dick, Danielle M

    2016-08-01

    The consequences of heavy alcohol use remain a serious public health problem. Consistent evidence has demonstrated that both genetic and social influences contribute to alcohol use. Research on gene-environment interaction (GxE) has also demonstrated that these social and genetic influences do not act independently. Instead, certain environmental contexts may limit or exacerbate an underlying genetic predisposition. However, much of the work on GxE and alcohol use has focused on adolescence and less is known about the important environmental contexts in young adulthood. Using data from the young adult wave of the Finnish Twin Study, FinnTwin12 (N = 3402), we used biometric twin modeling to test whether education moderated genetic risk for alcohol use as assessed by drinking frequency and intoxication frequency. Education is important because it offers greater access to personal resources and helps determine one's position in the broader stratification system. Results from the twin models show that education did not moderate genetic variance components and that genetic risk was constant across levels of education. Instead, education moderated environmental variance so that under conditions of low education, environmental influences explained more of the variation in alcohol use outcomes. The implications and limitations of these results are discussed.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  13. 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…

  14. Testing gene-environment interactions in family-based association studies using trait-based ascertained samples

    PubMed Central

    Zhang, Weiming; Langefeld, Carl D.; Grunwald, Gary K.; Fingerlin, Tasha E.

    2014-01-01

    The study of gene-environment interactions is an increasingly important aspect of genetic epidemiological investigation. Historically, it has been difficult to study gene-environment interactions using a family-based design for quantitative traits or when parent-offspring trios were incomplete. The QBAT-I[1] provides researchers a tool to estimate and test for a gene-environment interaction in families of arbitrary structure that are sampled without regard to the phenotype of interest, but is vulnerable to inflated type I error if families are ascertained based on the phenotype. In this study, we verified the potential for type I error of the QBAT-I when applied to samples ascertained on a trait of interest. The magnitude of the inflation increases as the main genetic effect increases and as the ascertainment becomes more extreme. We propose an ascertainment-corrected score test that allows use of the QBAT-I to test for gene-environment interactions in ascertained samples. Our results indicate that the score test and an ad-hoc method we propose can often restore the nominal type I error rate, and in cases where complete restoration is not possible, dramatically reduce the inflation of the type I error rate in ascertained samples. PMID:23922213

  15. Toward a 3D model of human brain development for studying gene/environment interactions.

    PubMed

    Hogberg, Helena T; Bressler, Joseph; Christian, Kimberly M; Harris, Georgina; Makri, Georgia; O'Driscoll, Cliona; Pamies, David; Smirnova, Lena; Wen, Zhexing; Hartung, Thomas

    2013-01-01

    This project aims to establish and characterize an in vitro model of the developing human brain for the purpose of testing drugs and chemicals. To accurately assess risk, a model needs to recapitulate the complex interactions between different types of glial cells and neurons in a three-dimensional platform. Moreover, human cells are preferred over cells from rodents to eliminate cross-species differences in sensitivity to chemicals. Previously, we established conditions to culture rat primary cells as three-dimensional aggregates, which will be humanized and evaluated here with induced pluripotent stem cells (iPSCs). The use of iPSCs allows us to address gene/environment interactions as well as the potential of chemicals to interfere with epigenetic mechanisms. Additionally, iPSCs afford us the opportunity to study the effect of chemicals during very early stages of brain development. It is well recognized that assays for testing toxicity in the developing brain must consider differences in sensitivity and susceptibility that arise depending on the time of exposure. This model will reflect critical developmental processes such as proliferation, differentiation, lineage specification, migration, axonal growth, dendritic arborization and synaptogenesis, which will probably display differences in sensitivity to different types of chemicals. Functional endpoints will evaluate the complex cell-to-cell interactions that are affected in neurodevelopment through chemical perturbation, and the efficacy of drug intervention to prevent or reverse phenotypes. The model described is designed to assess developmental neurotoxicity effects on unique processes occurring during human brain development by leveraging human iPSCs from diverse genetic backgrounds, which can be differentiated into different cell types of the central nervous system. Our goal is to demonstrate the feasibility of the personalized model using iPSCs derived from individuals with neurodevelopmental disorders

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

    PubMed

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

    2016-11-01

    Both air pollution exposure and systemic inflammation have been linked to Parkinson's disease (PD). In the PASIDA study, 408 incident cases of PD diagnosed in 2006-2009 and their 495 population controls were interviewed and provided DNA samples. Markers of long term traffic related air pollution measures were derived from geographic information systems (GIS)-based modeling. Furthermore, we genotyped functional polymorphisms in genes encoding proinflammatory cytokines, namely rs1800629 in TNFα (tumor necrosis factor alpha) and rs16944 in IL1B (interleukin-1β). In logistic regression models, long-term exposure to NO2 increased PD risk overall (odds ratio (OR)=1.06 per 2.94μg/m(3) increase, 95% CI=1.00-1.13). The OR for PD in individuals with high NO2 exposure (≧75th percentile) and the AA genotype of IL1B rs16944 was 3.10 (95% CI=1.14-8.38) compared with individuals with lower NO2 exposure (<75th percentile) and the GG genotype. The interaction term was nominally significant on the multiplicative scale (p=0.01). We did not find significant gene-environment interactions with TNF rs1800629. Our finds may provide suggestive evidence that a combination of traffic-related air pollution and genetic variation in the proinflammatory cytokine gene IL1B contribute to risk of developing PD. However, as statistical evidence was only modest in this large sample we cannot rule out that these results represent a chance finding, and additional replication efforts are warranted.

  17. 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.

  18. Gene-environment interaction in problematic substance use: interaction between DRD4 and insecure attachments.

    PubMed

    Olsson, Craig A; Moyzis, Robert K; Williamson, Elizabeth; Ellis, Justine A; Parkinson-Bates, Mandy; Patton, George C; Dwyer, Terry; Romaniuk, Helena; Moore, Elya E

    2013-07-01

    To investigate the combined effect of an exon III variable number tandem repeat in the dopamine receptor gene (DRD4) and insecure attachment style on risk for tobacco, cannabis and alcohol use problems in young adulthood. It was hypothesized that (1) individuals with 5, 6, 7 or 8 repeats (labelled 7R+) would be at increased risk for problematic drug use, and (2) risk for drug use would be further increased in individuals with 7R+ repeats who also have a history of insecure parent-child attachment relations. Data were drawn from the Victorian Adolescent Health Cohort Study, an eight-wave longitudinal study of adolescent and young adult development. DRD4 genotypes were available for 839 participants. Risk attributable to the combined effects of 7R+ genotype and insecure attachments was evaluated within a sufficient causes framework under the assumptions of additive interaction using a two-by-four table format with a common reference group. 7R+ alleles were associated with higher tobacco, cannabis and alcohol use (binging). Insecure attachments were associated with higher tobacco and cannabis use but lower alcohol use. For tobacco, there was evidence of interaction for anxious but not avoidant attachments. For cannabis, there was evidence of interaction for both anxious and avoidant attachments, although the interaction for anxious attachments was more substantial. There is no evidence of interaction for binge drinking. Results are consistent with a generic reward deficit hypothesis of drug addiction for which the 7R+ disposition may play a role. Interaction between 7R+ alleles and attachment insecurity may intensify risk for problematic tobacco and cannabis use.

  19. 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.

  20. 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.

  1. Nrf2 regulates gene-environment interactions in an animal model of intrauterine inflammation: Implications for preterm birth and prematurity

    PubMed Central

    Sussan, Thomas E.; Sudini, Kuladeep; Talbot, C. Conover; Wang, Xiaobin; Wills-Karp, Marsha; Burd, Irina; Biswal, Shyam

    2017-01-01

    Preterm birth (PTB) is the leading cause of neonatal mortality, and surviving infants are at increased risk for lifelong disabilities. Intrauterine inflammation is an etiological factor that drives PTB, and oxidative stress is associated with PTB. Nuclear erythroid 2-related factor 2 (Nrf2) is a redox-sensitive transcription factor that is the key regulator of the response to oxidative and inflammatory stress. Here, we used the established mouse model of intrauterine inflammation-induced PTB to determine whether Nrf2 is a modifier of susceptibility to PTB and prematurity-related morbidity and mortality in the offspring. We determined that Nr2-deficient (Nrf2−/−) mice exhibited a greater sensitivity to intrauterine inflammation, as indicated by decreased time to delivery, reduced birthweight, and 100% mortality. Placentas from preterm Nrf2−/− mice showed elevated levels of markers of inflammation, oxidative stress, and cell death, and transcriptomic analysis identified numerous key signaling pathways that were differentially expressed between wild-type (WT) and Nrf2−/− mice in both preterm and control samples. Thus, Nrf2 could be a critical factor for gene-environment interactions that may determine susceptibility to PTB. Further studies are needed to determine if Nrf2 is a viable therapeutic target in women who are at risk for PTB and associated complications in the affected offspring. PMID:28071748

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

    PubMed Central

    Bureau, Alexandre; Croteau, Jordie; Couture, Christian; Vohl, Marie-Claude; Bouchard, Claude; Pérusse, Louis

    2015-01-01

    Effects of genetic variants on the risk of complex diseases estimated from association studies are typically small. Nonetheless, variants may have important effects in presence of specific levels of environmental exposures, and when a trait related to the disease (endophenotype) is either normal or impaired. We propose polytomous and transition models to represent the relationship between disease, endophenotype, genotype and environmental exposure in family studies. Model coefficients were estimated using generalized estimating equations and were used to derive gene-environment interaction effects and genotype effects at specific levels of exposure. In a simulation study, estimates of the effect of a genetic variant were substantially higher when both an endophenotype and an environmental exposure modifying the variant effect were taken into account, particularly under transition models, compared to the alternative of ignoring the endophenotype. Illustration of the proposed modeling with the metabolic syndrome, abdominal obesity, physical activity and polymorphisms in the NOX3 gene in the Quebec Family Study revealed that the positive association of the A allele of rs1375713 with the metabolic syndrome at high levels of physical activity was only detectable in subjects without abdominal obesity, illustrating the importance of taking into account the abdominal obesity endophenotype in this analysis. PMID:26284107

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

    PubMed Central

    Fan, Ruzong; Manga, Prashiela

    2015-01-01

    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. PMID:26191336

  4. The Cumulative Effect of Gene-Gene and Gene-Environment Interactions on the Risk of Prostate Cancer in Chinese Men

    PubMed Central

    Liu, Ming; Shi, Xiaohong; Yang, Fan; Wang, Jianye; Xu, Yong; Wei, Dong; Yang, Kuo; Zhang, Yaoguang; Wang, Xin; Liang, Siying; Chen, Xin; Sun, Liang; Zhu, Xiaoquan; Zhao, Chengxiao; Zhu, Ling; Tang, Lei; Zheng, Chenguang; Yang, Ze

    2016-01-01

    Prostate cancer (PCa) is a multifactorial disease involving complex genetic and environmental factors interactions. Gene-gene and gene-environment interactions associated with PCa in Chinese men are less studied. We explored the association between 36 SNPs and PCa in 574 subjects from northern China. Body mass index (BMI), smoking, and alcohol consumption were determined through self-administered questionnaires in 134 PCa patients. Then gene-gene and gene-environment interactions among the PCa-associated SNPs were analyzed using the generalized multifactor dimensionality reduction (GMDR) and logistic regression methods. Allelic and genotypic association analyses showed that six variants were associated with PCa and the cumulative effect suggested men who carried any combination of 1, 2, or ≥3 risk genotypes had a gradually increased PCa risk (odds ratios (ORs) = 1.79–4.41). GMDR analysis identified the best gene-gene interaction model with scores of 10 for both the cross-validation consistency and sign tests. For gene-environment interactions, rs6983561 CC and rs16901966 GG in individuals with a BMI ≥ 28 had ORs of 7.66 (p = 0.032) and 5.33 (p = 0.046), respectively. rs7679673 CC + CA and rs12653946 TT in individuals that smoked had ORs of 2.77 (p = 0.007) and 3.11 (p = 0.024), respectively. rs7679673 CC in individuals that consumed alcohol had an OR of 4.37 (p = 0.041). These results suggest that polymorphisms, either individually or by interacting with other genes or environmental factors, contribute to an increased risk of PCa. PMID:26828504

  5. The Cumulative Effect of Gene-Gene and Gene-Environment Interactions on the Risk of Prostate Cancer in Chinese Men.

    PubMed

    Liu, Ming; Shi, Xiaohong; Yang, Fan; Wang, Jianye; Xu, Yong; Wei, Dong; Yang, Kuo; Zhang, Yaoguang; Wang, Xin; Liang, Siying; Chen, Xin; Sun, Liang; Zhu, Xiaoquan; Zhao, Chengxiao; Zhu, Ling; Tang, Lei; Zheng, Chenguang; Yang, Ze

    2016-01-27

    Prostate cancer (PCa) is a multifactorial disease involving complex genetic and environmental factors interactions. Gene-gene and gene-environment interactions associated with PCa in Chinese men are less studied. We explored the association between 36 SNPs and PCa in 574 subjects from northern China. Body mass index (BMI), smoking, and alcohol consumption were determined through self-administered questionnaires in 134 PCa patients. Then gene-gene and gene-environment interactions among the PCa-associated SNPs were analyzed using the generalized multifactor dimensionality reduction (GMDR) and logistic regression methods. Allelic and genotypic association analyses showed that six variants were associated with PCa and the cumulative effect suggested men who carried any combination of 1, 2, or ≥3 risk genotypes had a gradually increased PCa risk (odds ratios (ORs) = 1.79-4.41). GMDR analysis identified the best gene-gene interaction model with scores of 10 for both the cross-validation consistency and sign tests. For gene-environment interactions, rs6983561 CC and rs16901966 GG in individuals with a BMI ≥ 28 had ORs of 7.66 (p = 0.032) and 5.33 (p = 0.046), respectively. rs7679673 CC + CA and rs12653946 TT in individuals that smoked had ORs of 2.77 (p = 0.007) and 3.11 (p = 0.024), respectively. rs7679673 CC in individuals that consumed alcohol had an OR of 4.37 (p = 0.041). These results suggest that polymorphisms, either individually or by interacting with other genes or environmental factors, contribute to an increased risk of PCa.

  6. Toll-like receptors and microbial exposure: gene-gene and gene-environment interaction in the development of atopy.

    PubMed

    Reijmerink, N E; Kerkhof, M; Bottema, R W B; Gerritsen, J; Stelma, F F; Thijs, C; van Schayck, C P; Smit, H A; Brunekreef, B; Postma, D S; Koppelman, G H

    2011-10-01

    Environmental and genetic factors contribute to atopy development. High microbial exposure may confer a protective effect on atopy. Toll-like receptors (TLRs) bind microbial products and are important in activating the immune system. To assess whether interactions between microbial exposures and genes encoding TLRs (and related genes) result in atopy, genes, environmental factors and gene-environment interactions of 66 single-nucleotide polymorphisms (SNPs) of 12 genes (TLR 1-6, 9 and 10, CD14, MD2, lipopolysaccharide-binding protein (LBP) and Dectin-1), and six proxy parameters of microbial exposure (sibship size, pets (three different parameters), day-care and intrauterine and childhood tobacco smoke exposure) were analysed for association with atopic phenotypes in 3,062 Dutch children (the Allergenic study). The presence of two or more older siblings increased the risk of developing high total immunoglobulin (Ig)E levels at different ages. This risk increased further in children aged 1-2 yrs carrying the minor allele of TLR6 SNP rs1039559. Furthermore, novel two- and three-factor gene-gene and gene-environment interactions were found (e.g. between sibship size, day-care and LBP SNP rs2232596). Larger sibship size is associated with increased total IgE levels. Furthermore, complex two- and three-factor interactions exist between genes and the environment. The TLRs and related genes interact with proxy parameters of high microbial exposure in atopy development.

  7. Epigenetic genes and emotional reactivity to daily life events: a multi-step gene-environment interaction study.

    PubMed

    Pishva, Ehsan; Drukker, Marjan; Viechtbauer, Wolfgang; Decoster, Jeroen; Collip, Dina; van Winkel, Ruud; Wichers, Marieke; Jacobs, Nele; Thiery, Evert; Derom, Catherine; Geschwind, Nicole; van den Hove, Daniel; Lataster, Tineke; Myin-Germeys, Inez; van Os, Jim; Rutten, Bart P F; Kenis, Gunter

    2014-01-01

    Recent human and animal studies suggest that epigenetic mechanisms mediate the impact of environment on development of mental disorders. Therefore, we hypothesized that polymorphisms in epigenetic-regulatory genes impact stress-induced emotional changes. A multi-step, multi-sample gene-environment interaction analysis was conducted to test whether 31 single nucleotide polymorphisms (SNPs) in epigenetic-regulatory genes, i.e. three DNA methyltransferase genes DNMT1, DNMT3A, DNMT3B, and methylenetetrahydrofolate reductase (MTHFR), moderate emotional responses to stressful and pleasant stimuli in daily life as measured by Experience Sampling Methodology (ESM). In the first step, main and interactive effects were tested in a sample of 112 healthy individuals. Significant associations in this discovery sample were then investigated in a population-based sample of 434 individuals for replication. SNPs showing significant effects in both the discovery and replication samples were subsequently tested in three other samples of: (i) 85 unaffected siblings of patients with psychosis, (ii) 110 patients with psychotic disorders, and iii) 126 patients with a history of major depressive disorder. Multilevel linear regression analyses showed no significant association between SNPs and negative affect or positive affect. No SNPs moderated the effect of pleasant stimuli on positive affect. Three SNPs of DNMT3A (rs11683424, rs1465764, rs1465825) and 1 SNP of MTHFR (rs1801131) moderated the effect of stressful events on negative affect. Only rs11683424 of DNMT3A showed consistent directions of effect in the majority of the 5 samples. These data provide the first evidence that emotional responses to daily life stressors may be moderated by genetic variation in the genes involved in the epigenetic machinery.

  8. Epigenetic Genes and Emotional Reactivity to Daily Life Events: A Multi-Step Gene-Environment Interaction Study

    PubMed Central

    Pishva, Ehsan; Drukker, Marjan; Viechtbauer, Wolfgang; Decoster, Jeroen; Collip, Dina; van Winkel, Ruud; Wichers, Marieke; Jacobs, Nele; Thiery, Evert; Derom, Catherine; Geschwind, Nicole; van den Hove, Daniel; Lataster, Tineke; Myin-Germeys, Inez; van Os, Jim

    2014-01-01

    Recent human and animal studies suggest that epigenetic mechanisms mediate the impact of environment on development of mental disorders. Therefore, we hypothesized that polymorphisms in epigenetic-regulatory genes impact stress-induced emotional changes. A multi-step, multi-sample gene-environment interaction analysis was conducted to test whether 31 single nucleotide polymorphisms (SNPs) in epigenetic-regulatory genes, i.e. three DNA methyltransferase genes DNMT1, DNMT3A, DNMT3B, and methylenetetrahydrofolate reductase (MTHFR), moderate emotional responses to stressful and pleasant stimuli in daily life as measured by Experience Sampling Methodology (ESM). In the first step, main and interactive effects were tested in a sample of 112 healthy individuals. Significant associations in this discovery sample were then investigated in a population-based sample of 434 individuals for replication. SNPs showing significant effects in both the discovery and replication samples were subsequently tested in three other samples of: (i) 85 unaffected siblings of patients with psychosis, (ii) 110 patients with psychotic disorders, and iii) 126 patients with a history of major depressive disorder. Multilevel linear regression analyses showed no significant association between SNPs and negative affect or positive affect. No SNPs moderated the effect of pleasant stimuli on positive affect. Three SNPs of DNMT3A (rs11683424, rs1465764, rs1465825) and 1 SNP of MTHFR (rs1801131) moderated the effect of stressful events on negative affect. Only rs11683424 of DNMT3A showed consistent directions of effect in the majority of the 5 samples. These data provide the first evidence that emotional responses to daily life stressors may be moderated by genetic variation in the genes involved in the epigenetic machinery. PMID:24967710

  9. Gene-Environment Interdependence

    ERIC Educational Resources Information Center

    Rutter, Michael

    2007-01-01

    Behavioural genetics was initially concerned with partitioning population variance into that due to genetics and that due to environmental influences. The implication was that the two were separate and it was assumed that gene-environment interactions were usually of so little importance that they could safely be ignored. Theoretical…

  10. Detecting Pathway-Based Gene-Gene and Gene-Environment Interactions in Pancreatic Cancer

    PubMed Central

    Duell, Eric J.; Bracci, Paige M.; Moore, Jason H.; Burk, Robert D.; Kelsey, Karl T.; Holly, Elizabeth A.

    2015-01-01

    Data mining and data reduction methods to detect interactions in epidemiologic data are being developed and tested. In these analyses, multifactor dimensionality reduction, focused interaction testing framework, and traditional logistic regression models were used to identify potential interactions with up to three factors. These techniques were used in a population-based case-control study of pancreatic cancer from the San Francisco Bay Area (308 cases, 964 controls). From 7 biochemical pathways, along with tobacco smoking, 26 polymorphisms in 20 genes were included in these analyses. Combinations of genetic markers and cigarette smoking were identified as potential risk factors for pancreatic cancer, including genes in base excision repair (OGG1), nucleotide excision repair (XPD, XPA, XPC), and double-strand break repair (XRCC3). XPD.751, XPD.312, and cigarette smoking were the best single-factor predictors of pancreatic cancer risk, whereas XRCC3.241*smoking and OGG1.326*XPC.PAT were the best two-factor predictors. There was some evidence for a three-factor combination of OGG1.326*XPD.751*smoking, but the covariate-adjusted relative-risk estimates lacked precision. Multifactor dimensionality reduction and focused interaction testing framework showed little concordance, whereas logistic regression allowed for covariate adjustment and model confirmation. Our data suggest that multiple common alleles from DNA repair pathways in combination with cigarette smoking may increase the risk for pancreatic cancer, and that multiple approaches to data screening and analysis are necessary to identify potentially new risk factor combinations. PMID:18559563

  11. 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

  12. Gene-environment interactions: key to unraveling the mystery of Parkinson's disease.

    PubMed

    Gao, Hui-Ming; Hong, Jau-Shyong

    2011-06-01

    Parkinson's disease (PD) is the second most common neurodegenerative disease. The gradual, irreversible loss of dopamine neurons in the substantia nigra is the signature lesion of PD. Clinical symptoms of PD become apparent when 50-60% of nigral dopamine neurons are lost. PD progresses insidiously for 5-7 years (preclinical period) and then continues to worsen even under the symptomatic treatment. To determine what triggers the disease onset and what drives the chronic, self-propelling neurodegenerative process becomes critical and urgent, since lack of such knowledge impedes the discovery of effective treatments to retard PD progression. At present, available therapeutics only temporarily relieve PD symptoms. While the identification of causative gene defects in familial PD uncovers important genetic influences in this disease, the majority of PD cases are sporadic and idiopathic. The current consensus suggests that PD develops from multiple risk factors including aging, genetic predisposition, and environmental exposure. Here, we briefly review research on the genetic and environmental causes of PD. We also summarize very recent genome-wide association studies on risk gene polymorphisms in the emergence of PD. We highlight the new converging evidence on gene-environment interplay in the development of PD with an emphasis on newly developed multiple-hit PD models involving both genetic lesions and environmental triggers.

  13. Gene-Environment Interactions Target Mitogen-activated Protein 3 Kinase 1 (MAP3K1) Signaling in Eyelid Morphogenesis*

    PubMed Central

    Mongan, Maureen; Meng, Qinghang; Wang, Jingjing; Kao, Winston W.-Y.; Puga, Alvaro; Xia, Ying

    2015-01-01

    Gene-environment interactions determine the biological outcomes through mechanisms that are poorly understood. Mouse embryonic eyelid closure is a well defined model to study the genetic control of developmental programs. Using this model, we investigated how exposure to dioxin-like environmental pollutants modifies the genetic risk of developmental abnormalities. Our studies reveal that mitogen-activated protein 3 kinase 1 (MAP3K1) signaling is a focal point of gene-environment cross-talk. Dioxin exposure, acting through the aryl hydrocarbon receptor (AHR), blocked eyelid closure in genetic mutants in which MAP3K1 signaling was attenuated but did not disturb this developmental program in either wild type or mutant mice with attenuated epidermal growth factor receptor or WNT signaling. Exposure also markedly inhibited c-Jun phosphorylation in Map3k1+/− embryonic eyelid epithelium, suggesting that dioxin-induced AHR pathways can synergize with gene mutations to inhibit MAP3K1 signaling. Our studies uncover a novel mechanism through which the dioxin-AHR axis interacts with the MAP3K1 signaling pathways during fetal development and provide strong empirical evidence that specific gene alterations can increase the risk of developmental abnormalities driven by environmental pollutant exposure. PMID:26109068

  14. Allowing for population stratification in case-only studies of gene-environment interaction, using genomic control.

    PubMed

    Yadav, Pankaj; Freitag-Wolf, Sandra; Lieb, Wolfgang; Dempfle, Astrid; Krawczak, Michael

    2015-10-01

    Gene-environment interactions (G × E) have attracted considerable research interest in the past owing to their scientific and public health implications, but powerful statistical methods are required to successfully track down G × E, particularly at a genome-wide level. Previously, a case-only (CO) design has been proposed as a means to identify G × E with greater efficiency than traditional case-control or cohort studies. However, as with genotype-phenotype association studies themselves, hidden population stratification (PS) can impact the validity of G × E studies using a CO design. Since this problem has been subject to little research to date, we used comprehensive simulation to systematically assess the type I error rate, power and effect size bias of CO studies of G × E in the presence of PS. Three types of PS were considered, namely genetic-only (PSG), environment-only (PSE), and joint genetic and environmental stratification (PSGE). Our results reveal that the type I error rate of an unadjusted Wald test, appropriate for the CO design, would be close to its nominal level (0.05 in our study) as long as PS involves only one interaction partner (i.e., either PSG or PSE). In contrast, if the study population is stratified with respect to both G and E (i.e., if there is PSGE), then the type I error rate is seriously inflated and estimates of the underlying G × E interaction are biased. Comparison of CO to a family-based case-parents design confirmed that the latter is more robust against PSGE, as expected. However, case-parent trios may be particularly unsuitable for G × E studies in view of the fact that they require genotype data from parents and that many diseases with an environmental component are likely to be of late onset. An alternative approach to adjusting for PS is principal component analysis (PCA), which has been widely used for this very purpose in past genome-wide association studies (GWAS). However, resolving genetic PS properly by PCA

  15. A Candidate-Pathway Approach to Identify Gene-Environment Interactions: Analyses of Colon Cancer Risk and Survival

    PubMed Central

    Sharafeldin, Noha; Slattery, Martha L.; Liu, Qi; Franco-Villalobos, Conrado; Caan, Bette J.; Potter, John D.

    2015-01-01

    Background: Genetic association studies have traditionally focused on associations between individual single nucleotide polymorphisms (SNPs) and disease. Standard analysis ignores interactions between multiple SNPs and environmental exposures explaining a small portion of disease heritability: the often-cited issue of “missing heritability.” Methods: We present a novel three-step analytic framework for modeling gene-environment interactions (GEIs) between an angiogenesis candidate-gene pathway and three lifestyle exposures (dietary protein, smoking, and alcohol consumption) on colon cancer risk and survival. Logic regression was used to summarize the gene-pathway effects, and GEIs were modeled using logistic regression and Cox proportional hazards models. We analyzed data from 1541 colon cancer case patients and 1934 control subjects in the Diet, Activity and Lifestyle as a Risk Factor for Colon Cancer Study. Results: We identified five statistically significant GEIs for colon cancer risk. For risk interaction, odds ratios (ORINT) and 95% confidence intervals (CIs) were FLT1(rs678714) and BMP4(rs17563) and smoking (ORINT = 1.64, 95% CI = 1.11 to 2.41 and ORINT = 1.60, 95% CI = 1.10 to 2.32, respectively); FLT1(rs2387632 OR rs9513070) and protein intake (ORINT = 1.69, 95% CI = 1.03 to 2.77); KDR(rs6838752) and TLR2(rs3804099) and alcohol (ORINT = 1.53, 95% CI = 1.10 to 2.13 and ORINT = 1.59, 95% CI = 1.05 to 2.38, respectively). Three GEIs between TNF, BMP1, and BMPR2 genes and the three exposures were statistically significant at the 5% level in relation to colon cancer survival but not after multiple-testing adjustment. Conclusions: Adopting a comprehensive biologically informed candidate-pathway approach identified GEI effects on colon cancer. Findings may have important implications for public health and personalized medicine targeting prevention and therapeutic strategies. Findings from this study need to be validated in other studies. PMID:26072521

  16. 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.

  17. The Heritability of Personality is not Always 50%: Gene-Environment Interactions and Correlations between Personality and Parenting

    PubMed Central

    Krueger, Robert F.; South, Susan; Johnson, Wendy; Iacono, William

    2008-01-01

    Twin studies of personality are consistent in attributing approximately half of the variance in personality to genetic effects, with the remaining variance attributed to environments that make people within the same families different. Such conclusions, however, are based on quantitative models of human individual differences that estimate genetic and environmental contributions as constants for entire populations. Recent advances in statistical modeling allow for the possibility of estimating genetic and environmental contributions contingent on other variables, allowing the quantification of phenomena that have traditionally been characterized as gene-environment interaction and correlation. We applied these newer models to understand how adolescents’ descriptions of their relationships with their parents might change or moderate the impact of genetic and environmental factors on personality. We documented notable moderation in the domains of positive and negative emotionality, with parental relationships acting to both enhance and diminish both genetic and environmental effects. We discuss how genetic and environmental contributions to personality might be more richly conceptualized as dynamic systems of gene-environment interplay – systems that are not captured by classical concepts, such as the overall heritability of personality. PMID:19012656

  18. 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

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

    PubMed

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

    2013-10-01

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

  20. Sequential tests for gene-environment interactions in matched case-control studies.

    PubMed

    Tweel, Ingeborg van der; Schipper, Maria

    2004-12-30

    The sample size necessary to detect a significant gene x environment interaction in an observational study can be large. For reasons of cost-effectiveness and efficient use of available biological samples we investigated the properties of sequential designs in matched case-control studies to test for both non-hierarchical and hierarchical interactions. We derived the test statistics Z and V and their characteristics when applied in a two-sided triangular test. Results of simulations show good agreement with theoretical values for V and the type I error. Power values were larger than their theoretical values for very large sample sizes. Median gain in efficiency was about 27 per cent. For a 'rare' phenotype gain in efficiency was larger when the alternative hypothesis was true than under the null hypothesis. Sequential designs lead to substantial efficiency gains in tests for interaction in matched case-control studies.

  1. Gene-Environment Interactions Controlling Energy and Glucose Homeostasis and the Developmental Origins of Obesity

    PubMed Central

    Bouret, Sebastien; Levin, Barry E.; Ozanne, Susan E.

    2015-01-01

    Obesity and type 2 diabetes mellitus (T2DM) often occur together and affect a growing number of individuals in both the developed and developing worlds. Both are associated with a number of other serious illnesses that lead to increased rates of mortality. There is likely a polygenic mode of inheritance underlying both disorders, but it has become increasingly clear that the pre- and postnatal environments play critical roles in pushing predisposed individuals over the edge into a disease state. This review focuses on the many genetic and environmental variables that interact to cause predisposed individuals to become obese and diabetic. The brain and its interactions with the external and internal environment are a major focus given the prominent role these interactions play in the regulation of energy and glucose homeostasis in health and disease. PMID:25540138

  2. Gene-environment interaction between the MMP9 C-1562T promoter variant and cigarette smoke in the pathogenesis of chronic obstructive pulmonary disease.

    PubMed

    Stankovic, Marija; Kojic, Snezana; Djordjevic, Valentina; Tomovic, Andrija; Nagorni-Obradovic, Ljudmila; Petrovic-Stanojevic, Natasa; Mitic-Milikic, Marija; Radojkovic, Dragica

    2016-07-01

    The aetiology of chronic obstructive pulmonary disease (COPD) is complex. While cigarette smoking is a well-established cause of COPD, a myriad of assessed genetic factors has given conflicting data. Since gene-environment interactions are thought to be implicated in aetiopathogenesis of COPD, we aimed to examine the matrix metalloproteinase (MMP) 9 C-1562T (rs3918242) functional variant and cigarette smoke in the pathogenesis of this disease. The distribution of the MMP9 C-1562T variant was analyzed in COPD patients and controls with normal pulmonary function from Serbia. Interaction between the C-1562T genetic variant and cigarette smoking was assessed using a case-control model. The response of the C-1562T promoter variant to cigarette smoke condensate (CSC) exposure was examined using a dual luciferase reporter assay. The frequency of T allele carriers was higher in the COPD group than in smoker controls (38.4% vs. 20%; OR = 2.7, P = 0.027). Interaction between the T allele and cigarette smoking was identified in COPD occurrence (OR = 4.38, P = 0.005) and severity (P = 0.001). A functional analysis of the C-1562T variant demonstrated a dose-dependent and allele-specific response (P < 0.01) to CSC. Significantly higher MMP9 promoter activity following CSC exposure was found for the promoter harboring the T allele compared to the promoter harboring the C allele (P < 0.05). Our study is the first to reveal an interaction between the MMP9-1562T allele and cigarette smoke in COPD, emphasising gene-environment interactions as a possible cause of lung damage in the pathogenesis of COPD. Environ. Mol. Mutagen. 57:447-454, 2016. © 2016 Wiley Periodicals, Inc.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 dys...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Purpose of review 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 diseas...

  5. The Behavioural Phenotype of Smith-Magenis Syndrome: Evidence for a Gene-Environment Interaction

    ERIC Educational Resources Information Center

    Taylor, L.; Oliver, C.

    2008-01-01

    Background: Behaviour problems and a preference for adult contact are reported to be prominent in the phenotype of Smith-Magenis syndrome. In this study we examined the relationship between social interactions and self-injurious and aggressive/disruptive behaviour in Smith-Magenis syndrome to explore potential operant reinforcement of problem…

  6. Gene Environment Interactions in Women With Breast and Secondary Lung Cancer

    DTIC Science & Technology

    2006-07-01

    or due to alterations in genes whose products interact or communicate with p53. Most mutations result in the inability of the protein to activate...p53 and smoking in breast cancer can be made. The p53 gene is mutated in about 50% of lung cancers. Among the 2,372 mutations recorded for lung...carcinogenesis by affecting expression of mutated genes [44]. Methylation profiles associated with certain types of cancer could be used to identify cancer

  7. Using mouse models of autism spectrum disorders to study the neurotoxicology of gene-environment interactions

    PubMed Central

    Schwartzer, Jared J.; Koenig, Claire M.; Berman, Robert F

    2012-01-01

    To better study the role of genetics in autism, mouse models have been developed which mimic the genetics of specific autism spectrum and related disorders. These models have facilitated research on the role genetic susceptibility factors in the pathogenesis of autism in the absence of environmental factors. Inbred mouse strains have been similarly studied to assess the role of environmental agents on neurodevelopment, typically without the complications of genetic heterogeneity of the human population. What has not been as actively pursued, however, is the methodical study of the interaction between these factors (e.g., gene and environmental interactions in neurodevelopment). This review suggests that a genetic predisposition paired with exposure to environmental toxicants play an important role in the etiology of neurodevelopmental disorders including autism, and may contribute to the largely unexplained rise in the number of children diagnosed with autism worldwide. Specifically, descriptions of the major mouse models of autism and toxic mechanisms of prevalent environmental chemicals are provided followed by a discussion of current and future research strategies to evaluate the role of gene and environment interactions in neurodevelopmental disorders. PMID:23010509

  8. Gene-environment interactions on mental development in African American, Dominican, and Caucasian Mothers and Newborns

    PubMed Central

    Wang, Shuang; Chanock, Stephen; Tang, Deliang; Li, Zhigang; Edwards, Susan; Jedrychowski, Wieslaw; Perera, Frederica P.

    2009-01-01

    The health impact of environmental toxins has gained increasing recognition over the years. Polycyclic aromatic hydrocarbons (PAHs) and environmental tobacco smoke (ETS) are known to affect nervous system development in children, but no studies have investigated how polymorphisms in PAH metabolic or detoxification genes affect child cognitive development following PAH exposure during pregnancy. In two parallel prospective cohort studies of nonsmoking African American and Dominican mothers and children in New York City and of Caucasian mothers and children in Krakow, Poland, we explored the effect of gene-PAH interaction on child mental development index (MDI), as measured by the Bayley Scales of Infant Development-Revised (BSID-II). Genes known to play important roles in the metabolic activation or detoxification of PAHs were selected. Genetic variations in these genes could influence susceptibility to adverse effects of PAHs in polluted air. We explored the effects of interactions between prenatal PAH exposure and 21 polymorphisms or haplotypes in these genes on MDI at 12, 24, and 36 months among 547 newborns and 806 mothers from three different ethnic groups: African Americans, Dominicans, and Caucasians. PAHs were measured by personal air monitoring of mothers during pregnancy. Significant interaction effects between haplotypes and PAHs were observed in mothers and their newborns in all three ethnic groups after Bonferroni correction for multiple comparisons. The strongest and most consistent effect observed was between PAH and haplotype ACCGGC of the CYP1B1 gene. PMID:19860743

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

    PubMed Central

    Follis, Jack L.; Smith, Caren E.; Tanaka, Toshiko; Garaulet, Marta; Gottlieb, Daniel J.; Hruby, Adela; Jacques, Paul F.; Kiefte-de Jong, Jessica C.; Lamon-Fava, Stefania; Scheer, Frank A.J.L.; Bartz, Traci M.; Kovanen, Leena; Wojczynski, Mary K.; Frazier-Wood, Alexis C.; Ahluwalia, Tarunveer S.; Perälä, Mia-Maria; Jonsson, Anna; Muka, Taulant; Kalafati, Ioanna P.; Mikkilä, Vera; Ordovás, José M.

    2015-01-01

    OBJECTIVE Common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs1387153, MTNR1B-rs10830963, NR1D1-rs2314339) and cardiometabolic traits (fasting glucose [FG], HOMA-insulin resistance, BMI, waist circumference, and HDL-cholesterol) to facilitate personalized recommendations. RESEARCH DESIGN AND METHODS We conducted inverse-variance weighted, fixed-effect meta-analyses of results of adjusted associations and interactions between dietary intake/sleep duration and selected variants on cardiometabolic traits from 15 cohort studies including up to 28,190 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. RESULTS We observed significant associations between relative macronutrient intakes and glycemic traits and short sleep duration (<7 h) and higher FG and replicated known MTNR1B associations with glycemic traits. No interactions were evident after accounting for multiple comparisons. However, we observed nominally significant interactions (all P < 0.01) between carbohydrate intake and MTNR1B-rs1387153 for FG with a 0.003 mmol/L higher FG with each additional 1% carbohydrate intake in the presence of the T allele, between sleep duration and CRY2-rs11605924 for HDL-cholesterol with a 0.010 mmol/L higher HDL-cholesterol with each additional hour of sleep in the presence of the A allele, and between long sleep duration (≥9 h) and MTNR1B-rs1387153 for BMI with a 0.60 kg/m2 higher BMI with long sleep duration in the presence of the T allele relative to normal sleep duration (≥7 to <9 h). CONCLUSIONS Our results suggest that lower carbohydrate intake and normal sleep duration may ameliorate cardiometabolic abnormalities conferred by common circadian-related genetic variants

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

    PubMed

    Nickels, Stefan; Truong, Thérèse; Hein, Rebecca; Stevens, Kristen; Buck, Katharina; Behrens, Sabine; Eilber, Ursula; Schmidt, Martina; Häberle, Lothar; Vrieling, Alina; Gaudet, Mia; Figueroa, Jonine; Schoof, Nils; Spurdle, Amanda B; Rudolph, Anja; Fasching, Peter A; Hopper, John L; Makalic, Enes; Schmidt, Daniel F; Southey, Melissa C; Beckmann, Matthias W; Ekici, Arif B; Fletcher, Olivia; Gibson, Lorna; Silva, Isabel dos Santos; Peto, Julian; Humphreys, Manjeet K; Wang, Jean; Cordina-Duverger, Emilie; Menegaux, Florence; Nordestgaard, Børge G; Bojesen, Stig E; Lanng, Charlotte; Anton-Culver, Hoda; Ziogas, Argyrios; Bernstein, Leslie; Clarke, Christina A; Brenner, Hermann; Müller, Heiko; Arndt, Volker; Stegmaier, Christa; Brauch, Hiltrud; Brüning, Thomas; Harth, Volker; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Lambrechts, Diether; Smeets, Dominiek; Neven, Patrick; Paridaens, Robert; Flesch-Janys, Dieter; Obi, Nadia; Wang-Gohrke, Shan; Couch, Fergus J; Olson, Janet E; Vachon, Celine M; Giles, Graham G; Severi, Gianluca; Baglietto, Laura; Offit, Kenneth; John, Esther M; Miron, Alexander; Andrulis, Irene L; Knight, Julia A; Glendon, Gord; Mulligan, Anna Marie; Chanock, Stephen J; Lissowska, Jolanta; Liu, Jianjun; Cox, Angela; Cramp, Helen; Connley, Dan; Balasubramanian, Sabapathy; Dunning, Alison M; Shah, Mitul; Trentham-Dietz, Amy; Newcomb, Polly; Titus, Linda; Egan, Kathleen; Cahoon, Elizabeth K; Rajaraman, Preetha; Sigurdson, Alice J; Doody, Michele M; Guénel, Pascal; Pharoah, Paul D P; Schmidt, Marjanka K; Hall, Per; Easton, Doug F; Garcia-Closas, Montserrat; Milne, Roger L; Chang-Claude, Jenny

    2013-01-01

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

  11. Gene-Environment Interaction of ApoE Genotype and Combat Exposure on PTSD

    PubMed Central

    Lyons, Michael J.; Genderson, Margo; Grant, Michael D.; Logue, Mark; Zink, Tyler; McKenzie, Ruth; Franz, Carol E.; Panizzon, Matthew; Lohr, James B.; Jerskey, Beth; Kremen, William S.

    2015-01-01

    Factors determining who develops PTSD following trauma are not well understood. The €4 allele of the apolipoprotein E (apoE) gene is associated with dementia and unfavorable outcome following brain insult. PTSD is also associated with dementia. Given evidence that psychological trauma adversely affects the brain, we hypothesized that the apoE genotype moderates effects of psychological trauma on PTSD pathogenesis. To investigate the moderation of the relationship between PTSD symptoms and combat exposure, we used 172 participants with combat trauma sustained during the Vietnam War. PTSD symptoms were the dependent variable and number of combat experiences, apoE genotype, and the combat experiences × apoE genotype interaction were predictors. We also examined the outcome of a diagnosis of PTSD (n = 39) versus no PTSD diagnosis (n = 131). The combat × apoE genotype interaction was significant for both PTSD symptoms (P = .014) and PTSD diagnosis (P = .009). ApoE genotype moderates the relationship between combat exposure and PTSD symptoms. Although the pathophysiology of PTSD is not well understood, the €4 allele is related to reduced resilience of the brain to insult. Our results are consistent with the €4 allele influencing the effects of psychological trauma on the brain, thereby affecting the risk of PTSD. PMID:24132908

  12. Gene-environment interaction of reelin and stress in cognitive behaviours in mice: Implications for schizophrenia.

    PubMed

    Schroeder, Anna; Buret, Laetitia; Hill, Rachel A; van den Buuse, Maarten

    2015-01-01

    Cognitive deficits are a particularly debilitating symptom group in schizophrenia. We investigated the effect of a 'two hit' combination of two factors implicated in schizophrenia development, reelin deficiency and stress, on cognitive behaviours in mice. Male and female heterozygous reelin mice (HRM) and wild-type (WT) controls received the stress hormone, corticosterone (CORT), during early adulthood to simulate chronic stress. The Y-maze, novel object recognition task (NORT), social interaction task and prepulse inhibition (PPI) were used to assess short-term spatial memory, visual non-spatial memory, social recognition memory and sensory gating, respectively. Reelin protein expression was measured in the prefrontal cortex (PFC) and hippocampus. CORT induced spatial memory deficits in male and female HRM but not in WT controls suggesting increased vulnerability of HRM to the effects of stress on cognition. By contrast, CORT disrupted PPI only in male WT mice, but not in male HRM, suggesting a protective role of reelin deficiency against effects of stress on PPI. Male HRM performed worse in the social recognition memory task compared to wild-type controls, irrespective of CORT treatment. No differences were detected in the NORT. Reelin protein expression was increased in the PFC of female CORT-treated HRM but there were no group differences in the hippocampus. Overall, these findings extend our understanding of the role of reelin-stress interactions in schizophrenia.

  13. Gene-environment interactions across development: Exploring DRD2 genotype and prenatal smoking effects on self-regulation.

    PubMed

    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 development, particularly for constructs like self-regulation that emerge slowly, depend on brain regions that change qualitatively in different developmental periods, and thus may be manifested differently. To illustrate one approach to exploring such developmental patterns, the relation between variation in the TaqIA polymorphism, related to D2 dopamine receptor expression and availability, and prenatal exposure to tobacco was examined in two exploratory studies. First, in 4-week-old neonates, genotype-exposure interactions were observed for attention and irritable reactivity, but not for stress dysregulation. Second, in preschool children, genotype was related to Preschool Trail Making Test (K. A. Espy and M. F. Cwik, 2004) task performance on conditions requiring executive control; children with both the A1+ genotype and a history of prenatal tobacco exposure displayed disproportionately poor performance. Despite study limitations, these results illustrate the importance of examining the interplay between genetic and prenatal environmental factors across development.

  14. Gli2 gene-environment interactions contribute to the etiological complexity of holoprosencephaly: evidence from a mouse model.

    PubMed

    Heyne, Galen W; Everson, Joshua L; Ansen-Wilson, Lydia J; Melberg, Cal G; Fink, Dustin M; Parins, Kia F; Doroodchi, Padydeh; Ulschmid, Caden M; Lipinski, Robert J

    2016-11-01

    Holoprosencephaly (HPE) is a common and severe human developmental abnormality marked by malformations of the forebrain and face. Although several genetic mutations have been linked to HPE, phenotypic outcomes range dramatically, and most cases cannot be attributed to a specific cause. Gene-environment interaction has been invoked as a premise to explain the etiological complexity of HPE, but identification of interacting factors has been extremely limited. Here, we demonstrate that mutations in Gli2, which encodes a Hedgehog pathway transcription factor, can cause or predispose to HPE depending upon gene dosage. On the C57BL/6J background, homozygous GLI2 loss of function results in the characteristic brain and facial features seen in severe human HPE, including midfacial hypoplasia, hypotelorism and medial forebrain deficiency with loss of ventral neurospecification. Although normally indistinguishable from wild-type littermates, we demonstrate that mice with single-allele Gli2 mutations exhibit increased penetrance and severity of HPE in response to low-dose teratogen exposure. This genetic predisposition is associated with a Gli2 dosage-dependent attenuation of Hedgehog ligand responsiveness at the cellular level. In addition to revealing a causative role for GLI2 in HPE genesis, these studies demonstrate a mechanism by which normally silent genetic and environmental factors can interact to produce severe outcomes. Taken together, these findings provide a framework for the understanding of the extreme phenotypic variability observed in humans carrying GLI2 mutations and a paradigm for reducing the incidence of this morbid birth defect.

  15. 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

  16. Gli2 gene-environment interactions contribute to the etiological complexity of holoprosencephaly: evidence from a mouse model

    PubMed Central

    Heyne, Galen W.; Everson, Joshua L.; Ansen-Wilson, Lydia J.; Melberg, Cal G.; Fink, Dustin M.; Parins, Kia F.; Doroodchi, Padydeh; Ulschmid, Caden M.

    2016-01-01

    ABSTRACT Holoprosencephaly (HPE) is a common and severe human developmental abnormality marked by malformations of the forebrain and face. Although several genetic mutations have been linked to HPE, phenotypic outcomes range dramatically, and most cases cannot be attributed to a specific cause. Gene-environment interaction has been invoked as a premise to explain the etiological complexity of HPE, but identification of interacting factors has been extremely limited. Here, we demonstrate that mutations in Gli2, which encodes a Hedgehog pathway transcription factor, can cause or predispose to HPE depending upon gene dosage. On the C57BL/6J background, homozygous GLI2 loss of function results in the characteristic brain and facial features seen in severe human HPE, including midfacial hypoplasia, hypotelorism and medial forebrain deficiency with loss of ventral neurospecification. Although normally indistinguishable from wild-type littermates, we demonstrate that mice with single-allele Gli2 mutations exhibit increased penetrance and severity of HPE in response to low-dose teratogen exposure. This genetic predisposition is associated with a Gli2 dosage-dependent attenuation of Hedgehog ligand responsiveness at the cellular level. In addition to revealing a causative role for GLI2 in HPE genesis, these studies demonstrate a mechanism by which normally silent genetic and environmental factors can interact to produce severe outcomes. Taken together, these findings provide a framework for the understanding of the extreme phenotypic variability observed in humans carrying GLI2 mutations and a paradigm for reducing the incidence of this morbid birth defect. PMID:27585885

  17. Gene-environment interaction in programming hippocampal plasticity: focus on adult neurogenesis

    PubMed Central

    Koehl, Muriel

    2015-01-01

    Interactions between genes and environment are a critical feature of development and both contribute to shape individuality. They are at the core of vulnerability resiliency for mental illnesses. During the early postnatal period, several brain structures involved in cognitive and emotional processing, such as the hippocampus, still develop and it is likely that interferences with this neuronal development, which is genetically determined, might lead to long-lasting structural and functional consequences and increase the risk of developing psychopathology. One particular target is adult neurogenesis, which is involved in the regulation of cognitive and emotional processes. Insights into the dynamic interplay between genes and environmental factors in setting up individual rates of neurogenesis have come from laboratory studies exploring experience-dependent changes in adult neurogenesis as a function of individual’s genetic makeup. These studies have implications for our understanding of the mechanisms regulating adult neurogenesis, which could constitute a link between environmental challenges and psychopathology. PMID:26300723

  18. Gene-Environment Interactions in Preventive Medicine: Current Status and Expectations for the Future.

    PubMed

    Narimatsu, Hiroto

    2017-01-30

    The progression of many common disorders involves a complex interplay of multiple factors, including numerous different genes and environmental factors. Gene-environmental cohort studies focus on the identification of risk factors that cannot be discovered by conventional epidemiological methodologies. Such epidemiological methodologies preclude precise predictions, because the exact risk factors can be revealed only after detailed analyses of the interactions among multiple factors, that is, between genes and environmental factors. To date, these cohort studies have reported some promising results. However, the findings do not yet have sufficient clinical significance for the development of precise, personalized preventive medicine. Especially, some promising preliminary studies have been conducted in terms of the prevention of obesity. Large-scale validation studies of those preliminary studies, using a prospective cohort design and long follow-ups, will produce useful and practical evidence for the development of preventive medicine in the future.

  19. Progress in the epidemiological understanding of gene-environment interactions in major diseases: cancer.

    PubMed

    Clavel, Jacqueline

    2007-04-01

    Cancer epidemiology has undergone marked development since the 1950s. One of the most spectacular and specific contributions was the demonstration of the massive effect of smoking on the occurrence of lung, larynx, and bladder cancer. Major chemical, physical, and biological carcinogenic agents have been identified in the working environment and in the overall environment. The chain of events from environmental exposures to cancer requires hundreds of polymorphic genes coding for proteins involved in the transport and metabolism of xenobiotics, or in repair, or in an immune or inflammatory response. The multifactorial and multistage characteristics of cancer create the theoretical conditions for statistical interactions that have been exceptionally detected. Over the last two decades, a considerable mass of data has been generated, mostly addressing the interactions between smoking and xenobiotic-metabolizing enzymes in smoking-related cancers. They were sometimes considered disappointing, but they actually brought a lot of information and raised many methodological issues. In parallel, the number of polymorphisms that can be considered candidate per function increased so much that multiple testing has become a major issue, and genome wide-screening approaches have more and more gained in interest. Facing the resulting complexity, some instruments are being set up: our studies are now equipped with carefully sampled biological collections, high-throughput genotyping systems are becoming available, work on statistical methodologies is ongoing, bioinformatics databases are growing larger and access to them is becoming simpler; international consortiums are being organized. The roles of environmental and genetic factors are being jointly elucidated. The basic rules of epidemiology, which are demanding with respect to sampling, with respect to the histological and molecular criteria for cancer classification, with respect to the evaluation of environmental exposures

  20. Progress in the epidemiological understanding of gene-environment interactions in major diseases: cancer

    PubMed Central

    Clavel, Jacqueline

    2007-01-01

    Cancer epidemiology has undergone marked development since the nineteen-fifties. One of the most spectacular and specific contributions was the demonstration of the massive effect of smoking on the occurrence of lung, larynx and bladder cancer. Major chemical, physical and biological carcinogenic agents have been identified in the working environment and in the overall environment. The chain of events from environmental exposures to cancer requires hundreds of polymorphic genes coding for proteins involved in the transport and metabolism of xenobiotics, or in repair, or in an immune or inflammatory response. The multifactorial and multistage characteristics of cancer create the theoretical conditions for statistical interactions which have been exceptionnally detected. Over the last two decades, a considerable mass of data has been generated, mostly addressing the interactions between smoking and xenobiotic-metabolizing enzymes in smoking-related cancers. They are sometimes considered disappointing but they actually brought a lot of information and raised many methodological issues. In parallel, the number of polymorphisms which can be considered candidate per function increased so much that multiple testing has become a major issue, and genome wide screening approaches have more and more gained in interest. Facing the resulting complexity, some instruments are being set up: our studies are now equipped with carefully sampled biological collections, high-throughput genotyping systems are becoming available, work on statistical methodologies is ongoing, bioinformatics databases are growing larger and access to them is becoming simpler; international consortiums are being organized. The roles of environmental and genetic factors are being jointly elucidated. The basic rules of epidemiology, which are demanding with respect to sampling, with respect to the histological and molecular criteria for cancer classification, with respect to the evaluation of environmental

  1. A new clinical evidence-based gene-environment interaction model of depression.

    PubMed

    Bagdy, Gyorgy; Juhasz, Gabriella; Gonda, Xenia

    2012-12-01

    In our current understanding of mood disorders, the role of genes is diverse including the mediation of the effects of provoking and protective factors. Different or partially overlapping gene sets play a major role in the development of personality traits including also affective temperaments, in the mediation of the effects of environmental factors, and in the interaction of these elements in the development of depression. Certain genes are associated with personality traits and temperaments including e.g., neuroticism, impulsivity, openness, rumination and extroversion. Environmental factors consist of external (early and provoking life events, seasonal changes, social support etc.) and internal factors (hormones, biological rhythm generators, comorbid disorders etc). Some of these environmental factors, such as early life events and some prenatal events directly influence the development of personality traits and temperaments. In the NEWMOOD cohort polymorphisms of the genes of the serotonin transporter, 5-HT1A, 5-HT1B and 5-HT2A and endocannabinoid CB1 receptors, tryptophan hydroxylase, CREB1, BDNF and GIRK provide evidence for the involvement of these genes in the development of depression. Based on their role in this process they could be assigned to different gene sets. The role of certain genes, such as promoter polymorphisms of the serotonin transporter (5-HTTLPR) and CB1 receptor has been shown in more than one of the above factors. Furthermore, gene-gene interactions of these promoters associated with anxiety suggest the application of these polymorphisms in personalized medicine. In this review we introduce a new model including environmental factors, genes, trait and temperament markers based on human genetic studies.

  2. Exposure enriched case-control (EECC) design for the assessment of gene-environment interaction

    PubMed Central

    Carroll, Raymond J.; Diao, Nancy; Christiani, David C.; Ryan, Louise M.

    2016-01-01

    Genetic susceptibility and environmental exposure both play an important role in the aetiology of many diseases. Case-control studies are often the first choice to explore the joint influence of genetic and environmental factors on the risk of developing a rare disease. In practice, however, such studies may have limited power, especially when susceptibility genes are rare and exposure distributions are highly skewed. We propose a variant of the classical case-control study, the exposure enriched case-control (EECC) design, where not only cases, but also high (or low) exposed individuals are oversampled, depending on the skewness of the exposure distribution. Of course, a traditional logistic regression model is no longer valid and results in biased parameter estimation. We show that addition of a simple covariate to the regression model removes this bias and yields reliable estimates of main and interaction effects of interest. We also discuss optimal design, showing that judicious over-sampling of high/low exposed individuals can boost study power considerably. We illustrate our results using data from a study involving arsenic exposure and detoxification genes in Bangladesh. PMID:27313007

  3. New perspectives on epidermal barrier dysfunction in atopic dermatitis: gene-environment interactions.

    PubMed

    Cork, Michael J; Robinson, Darren A; Vasilopoulos, Yiannis; Ferguson, Adam; Moustafa, Manar; MacGowan, Alice; Duff, Gordon W; Ward, Simon J; Tazi-Ahnini, Rachid

    2006-07-01

    Atopic dermatitis (AD) is a multifactorial, chronic inflammatory skin disorder in which genetic mutations and cutaneous hyperreactivity to environmental stimuli play a causative role. Genetic mutations alone might not be enough to cause clinical manifestations of AD, and this review will propose a new perspective on the importance of epidermal barrier dysfunction in genetically predisposed individuals, predisposing them to the harmful effects of environmental agents. The skin barrier is known to be damaged in patients with AD, both in acute eczematous lesions and also in clinically unaffected skin. Skin barrier function can be impaired first by a genetic predisposition to produce increased levels of stratum corneum chymotryptic enzyme. This protease enzyme causes premature breakdown of corneodesmosomes, leading to impairment of the epidermal barrier. The addition of environmental interactions, such as washing with soap and detergents, or long-term application of topical corticosteroids can further increase production of stratum corneum chymotryptic enzyme and impair epidermal barrier function. The epidermal barrier can also be damaged by exogenous proteases from house dust mites and Staphylococcus aureus. One or more of these factors in combination might lead to a defective barrier, thereby increasing the risk of allergen penetration and succeeding inflammatory reaction, thus contributing to exacerbations of this disease.

  4. Unraveling inflammatory responses using systems genetics and gene-environment interactions in macrophages

    PubMed Central

    Orozco, Luz D.; Bennett, Brian J.; Farber, Charles R.; Ghazalpour, Anatole; Pan, Calvin; Che, Nam; Wen, Pingzi; Qi, Hong Xiu; Mutukulu, Adonisa; Siemers, Nathan; Neuhaus, Isaac; Yordanova, Roumyana; Gargalovic, Peter; Pellegrini, Matteo; Kirchgessner, Todd; Lusis, Aldons J.

    2012-01-01

    SUMMARY Many common diseases have an important inflammatory component mediated in part by macrophages. Here we used a systems genetics strategy to examine the role of common genetic variation in macrophage responses to inflammatory stimuli. We examined genome-wide transcript levels in macrophages from 92 strains of the Hybrid Mouse Diversity Panel. We exposed macrophages to control media, bacterial lipopolysaccharide, or oxidized phospholipids. We performed association mapping under each condition and identified several thousand expression quantitative trait loci (eQTL), gene-by-environment interactions and several eQTL “hotspots” that specifically control LPS responses. We validated an eQTL hotspot in chromosome 8 using siRNA knock-down of candidate genes and identified the gene 2310061C15Rik, as a novel regulator of inflammatory responses in macrophages. We have created a public database where the data presented here can be used as a resource for understanding many common inflammatory traits which are modeled in the mouse, and for the dissection of regulatory relationships between genes. PMID:23101632

  5. Unraveling inflammatory responses using systems genetics and gene-environment interactions in macrophages.

    PubMed

    Orozco, Luz D; Bennett, Brian J; Farber, Charles R; Ghazalpour, Anatole; Pan, Calvin; Che, Nam; Wen, Pingzi; Qi, Hong Xiu; Mutukulu, Adonisa; Siemers, Nathan; Neuhaus, Isaac; Yordanova, Roumyana; Gargalovic, Peter; Pellegrini, Matteo; Kirchgessner, Todd; Lusis, Aldons J

    2012-10-26

    Many common diseases have an important inflammatory component mediated in part by macrophages. Here we used a systems genetics strategy to examine the role of common genetic variation in macrophage responses to inflammatory stimuli. We examined genome-wide transcript levels in macrophages from 92 strains of the Hybrid Mouse Diversity Panel. We exposed macrophages to control media, bacterial lipopolysaccharide (LPS), or oxidized phospholipids. We performed association mapping under each condition and identified several thousand expression quantitative trait loci (eQTL), gene-by-environment interactions, and eQTL "hot spots" that specifically control LPS responses. We used siRNA knockdown of candidate genes to validate an eQTL hot spot in chromosome 8 and identified the gene 2310061C15Rik as a regulator of inflammatory responses in macrophages. We have created a public database where the data presented here can be used as a resource for understanding many common inflammatory traits that are modeled in the mouse and for the dissection of regulatory relationships between genes.

  6. Gene-environment interactions in severe intraventricular hemorrhage of preterm neonates.

    PubMed

    Ment, Laura R; Adén, Ulrika; Lin, Aiping; Kwon, Soo Hyun; Choi, Murim; Hallman, Mikko; Lifton, Richard P; Zhang, Heping; Bauer, Charles R

    2014-01-01

    Intraventricular hemorrhage (IVH) of the preterm neonate is a complex developmental disorder, with contributions from both the environment and the genome. IVH, or hemorrhage into the germinal matrix of the developing brain with secondary periventricular infarction, occurs in that critical period of time before the 32nd to 33rd wk postconception and has been attributed to changes in cerebral blood flow to the immature germinal matrix microvasculature. Emerging data suggest that genes subserving coagulation, inflammatory, and vascular pathways and their interactions with environmental triggers may influence both the incidence and severity of cerebral injury and are the subject of this review. Polymorphisms in the Factor V Leiden gene are associated with the atypical timing of IVH, suggesting an as yet unknown environmental trigger. The methylenetetrahydrofolate reductase (MTHFR) variants render neonates more vulnerable to cerebral injury in the presence of perinatal hypoxia. The present study demonstrates that the MTHFR 677C>T polymorphism and low 5-min Apgar score additively increase the risk of IVH. Finally, review of published preclinical data suggests the stressors of delivery result in hemorrhage in the presence of mutations in collagen 4A1, a major structural protein of the developing cerebral vasculature. Maternal genetics and fetal environment may also play a role.

  7. Gene-Environment Interactions in ADHD: The Roles of SES and Chaos.

    PubMed

    Gould, Karen L; Coventry, William L; Olson, Richard K; Byrne, Brian

    2017-03-10

    Although attention-deficit/hyperactivity disorder (ADHD) is highly heritable, emerging evidence suggests symptoms are associated with interactions between genes and the environment (GxE) during development. This study tested whether heritability of ADHD symptoms is moderated by two environmental factors: socioeconomic status (SES) and chaos (household disorganisation). A population sample of 520 twin pairs (N = 1040, 52.3% female) from 6 to 15 years completed measures of behavior and home environment. Structural equation modelling was then used to test whether environmental factors were associated with a change in the extent to which genes explain variability in ADHD symptoms. Neither chaos nor SES moderated heritability, with consistent contributions from both genes and environment indicated across socioeconomic strata and levels of chaos. This finding contrasts with those of previous research, underlining the need to replicate results in the emerging field of GxE research across different populations and statistical methods. Robust findings may assist in developing targeted interventions for genetically vulnerable individuals.

  8. Gene-environment interactions in severe intraventricular hemorrhage of preterm neonates

    PubMed Central

    Ment, Laura R.; Ådén, Ulrika; Lin, Aiping; Kwon, Soo Hyun; Choi, Murim; Hallman, Mikko; Lifton, Richard P.; Zhang, Heping; Bauer, Charles R.

    2014-01-01

    Intraventricular hemorrhage (IVH) of the preterm neonate is a complex developmental disorder, with contributions from both the environment and the genome. IVH, or hemorrhage into the germinal matrix of the developing brain with secondary periventricular infarction, occurs in that critical period of time before the 32nd – 33rd week post-conception and has been attributed to changes in cerebral blood flow to the immature germinal matrix microvasculature. Emerging data suggest that genes subserving coagulation, inflammatory and vascular pathways, and their interactions with environmental triggers may influence both the incidence and severity of cerebral injury and are the subject of this review. Polymorphisms in the Factor V Leiden gene are associated with the atypical timing of IVH suggesting an as yet unknown environmental trigger. The methylenetetra-hydrofolate reeducates (MTHFR) variants render neonates more vulnerable to cerebral injury in the presence of perinatal hypoxia. The present study demonstrates that the MTHFR 677C>T polymorphism and low 5 minute Apgar score additively increase the risk of IVH. Finally, review of published preclinical data suggests the stressors of delivery result in hemorrhage in the presence of mutations in collagen 4A1 (COL4A1), a major structural protein of the developing cerebral vasculature. Maternal genetics and fetal environment may also play a role. PMID:24192699

  9. Gene-environment interactions in a mutant mouse kindred with native airway constrictor hyperresponsiveness.

    PubMed

    Pinto, Lawrence H; Eaton, Emily; Chen, Bohao; Fleisher, Jonah; Shuster, Dmitry; McCauley, Joel; Kedainis, Dalius; Siepka, Sandra M; Shimomura, Kazuhiro; Song, Eun-Joo; Husain, Aliya; Lakser, Oren J; Mitchell, Richard W; Dowell, Maria L; Brown, Melanie; Camoretti-Mercado, Blanca; Naclerio, Robert; Sperling, Anne I; Levin, Stephen I; Turek, Fred W; Solway, Julian

    2008-01-01

    We mutagenized male BTBR mice with N-ethyl-N-nitrosourea and screened 1315 of their G3 offspring for airway hyperresponsiveness. A phenovariant G3 mouse with exaggerated methacholine bronchoconstrictor response was identified and his progeny bred in a nonspecific-pathogen-free (SPF) facility where sentinels tested positive for minute virus of mice and mouse parvovirus and where softwood bedding was used. The mutant phenotype was inherited through G11 as a single autosomal semidominant mutation with marked gender restriction, with males exhibiting almost full penetrance and very few females phenotypically abnormal. Between G11 and G12, facility infection eradication was undertaken and bedding was changed to hardwood. We could no longer detect airway hyperresponsiveness in more than 37 G12 offspring of 26 hyperresponsive G11 males. Also, we could not identify the mutant phenotype among offspring of hyperresponsive G8-G10 sires rederived into an SPF facility despite 21 attempts. These two observations suggest that both genetic and environmental factors were needed for phenotype expression. We suspect that rederivation into an SPF facility or altered exposure to pathogens or other unidentified substances modified environmental interactions with the mutant allele, and so resulted in disappearance of the hyperresponsive phenotype. Our experience suggests that future searches for genes that confer susceptibility for airway hyperresponsiveness might not be able to identify some genes that confer susceptibility if the searches are performed in SPF facilities. Experimenters are advised to arrange for multigeneration constancy of mouse care in order to clone mutant genes. Indeed, we were not able to map the mutation before losing the phenotype.

  10. Gene-environment interactions and construct validity in preclinical models of psychiatric disorders.

    PubMed

    Burrows, Emma L; McOmish, Caitlin E; Hannan, Anthony J

    2011-08-01

    The contributions of genetic risk factors to susceptibility for brain disorders are often so closely intertwined with environmental factors that studying genes in isolation cannot provide the full picture of pathogenesis. With recent advances in our understanding of psychiatric genetics and environmental modifiers we are now in a position to develop more accurate animal models of psychiatric disorders which exemplify the complex interaction of genes and environment. Here, we consider some of the insights that have emerged from studying the relationship between defined genetic alterations and environmental factors in rodent models. A key issue in such animal models is the optimization of construct validity, at both genetic and environmental levels. Standard housing of laboratory mice and rats generally includes ad libitum food access and limited opportunity for physical exercise, leading to metabolic dysfunction under control conditions, and thus reducing validity of animal models with respect to clinical populations. A related issue, of specific relevance to neuroscientists, is that most standard-housed rodents have limited opportunity for sensory and cognitive stimulation, which in turn provides reduced incentive for complex motor activity. Decades of research using environmental enrichment has demonstrated beneficial effects on brain and behavior in both wild-type and genetically modified rodent models, relative to standard-housed littermate controls. One interpretation of such studies is that environmentally enriched animals more closely approximate average human levels of cognitive and sensorimotor stimulation, whereas the standard housing currently used in most laboratories models a more sedentary state of reduced mental and physical activity and abnormal stress levels. The use of such standard housing as a single environmental variable may limit the capacity for preclinical models to translate into successful clinical trials. Therefore, there is a need to

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

    PubMed Central

    Hollman, Antoinesha L.; Tchounwou, Paul B.; Huang, Hung-Chung

    2016-01-01

    Exposure to environmental hazards has been associated with diseases in humans. The identification of single nucleotide polymorphisms (SNPs) in human populations exposed to different environmental hazards, is vital for detecting the genetic risks of some important human diseases. Several studies in this field have been conducted on glutathione S-transferases (GSTs), a phase II detoxification superfamily, to investigate its role in the occurrence of diseases. Human GSTs consist of cytosolic and microsomal superfamilies that are further divided into subfamilies. Based on scientific search engines and a review of the literature, we have found a large amount of published articles on human GST super- and subfamilies that have greatly assisted in our efforts to examine their role in health and disease. Because of its polymorphic variations in relation to environmental hazards such as air pollutants, cigarette smoke, pesticides, heavy metals, carcinogens, pharmaceutical drugs, and xenobiotics, GST is considered as a significant biomarker. This review examines the studies on gene-environment interactions related to various diseases with respect to single nucleotide polymorphisms (SNPs) found in the GST superfamily. Overall, it can be concluded that interactions between GST genes and environmental factors play an important role in human diseases. PMID:27043589

  12. 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.

  13. Linking Genes to Cardiovascular Diseases: Gene Action and Gene-Environment Interactions.

    PubMed

    Pasipoularides, Ares

    2015-12-01

    A unique myocardial characteristic is its ability to grow/remodel in order to adapt; this is determined partly by genes and partly by the environment and the milieu intérieur. In the "post-genomic" era, a need is emerging to elucidate the physiologic functions of myocardial genes, as well as potential adaptive and maladaptive modulations induced by environmental/epigenetic factors. Genome sequencing and analysis advances have become exponential lately, with escalation of our knowledge concerning sometimes controversial genetic underpinnings of cardiovascular diseases. Current technologies can identify candidate genes variously involved in diverse normal/abnormal morphomechanical phenotypes, and offer insights into multiple genetic factors implicated in complex cardiovascular syndromes. The expression profiles of thousands of genes are regularly ascertained under diverse conditions. Global analyses of gene expression levels are useful for cataloging genes and correlated phenotypes, and for elucidating the role of genes in maladies. Comparative expression of gene networks coupled to complex disorders can contribute insights as to how "modifier genes" influence the expressed phenotypes. Increasingly, a more comprehensive and detailed systematic understanding of genetic abnormalities underlying, for example, various genetic cardiomyopathies is emerging. Implementing genomic findings in cardiology practice may well lead directly to better diagnosing and therapeutics. There is currently evolving a strong appreciation for the value of studying gene anomalies, and doing so in a non-disjointed, cohesive manner. However, it is challenging for many-practitioners and investigators-to comprehend, interpret, and utilize the clinically increasingly accessible and affordable cardiovascular genomics studies. This survey addresses the need for fundamental understanding in this vital area.

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

    PubMed

    Gaffney, Adam; Christiani, David C

    2015-06-01

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

  15. Classification and Clustering Methods for Multiple Environmental Factors in Gene-Environment Interaction: Application to the Multi-Ethnic Study of Atherosclerosis.

    PubMed

    Ko, Yi-An; Mukherjee, Bhramar; Smith, Jennifer A; Kardia, Sharon L R; Allison, Matthew; Diez Roux, Ana V

    2016-11-01

    There has been an increased interest in identifying gene-environment interaction (G × E) in the context of multiple environmental exposures. Most G × E studies analyze one exposure at a time, but we are exposed to multiple exposures in reality. Efficient analysis strategies for complex G × E with multiple environmental factors in a single model are still lacking. Using the data from the Multiethnic Study of Atherosclerosis, we illustrate a two-step approach for modeling G × E with multiple environmental factors. First, we utilize common clustering and classification strategies (e.g., k-means, latent class analysis, classification and regression trees, Bayesian clustering using Dirichlet Process) to define subgroups corresponding to distinct environmental exposure profiles. Second, we illustrate the use of an additive main effects and multiplicative interaction model, instead of the conventional saturated interaction model using product terms of factors, to study G × E with the data-driven exposure subgroups defined in the first step. We demonstrate useful analytical approaches to translate multiple environmental exposures into one summary class. These tools not only allow researchers to consider several environmental exposures in G × E analysis but also provide some insight into how genes modify the effect of a comprehensive exposure profile instead of examining effect modification for each exposure in isolation.

  16. Gene-environment interaction in progression of AMD: the CFH gene, smoking and exposure to chronic infection.

    PubMed

    Baird, Paul N; Robman, Luba D; Richardson, Andrea J; Dimitrov, Peter N; Tikellis, Gabriella; McCarty, Catherine A; Guymer, Robyn H

    2008-05-01

    A number of risk factors including the complement factor H (CFH) gene, smoking and Chlamydia pneumoniae have been associated with age-related macular degeneration (AMD). However, the mechanisms underlying how these risk factors might be involved in disease progression and disease aetiology is poorly understood. A cohort series of 233 individuals followed for AMD progression over a mean period of 7 years underwent a full eye examination, blood was taken for DNA and antibody titre and individuals completed a standard medical and general questionnaire. Y402H variants of the CFH gene were assessed with disease progression as well as examination of interaction between Y402H variants and smoking and Y402H variants and the pathogen C. pneumoniae. The CC risk genotype of Y402H was significantly associated with increased AMD progression [odds ratio (OR) 2.43, 95% confidence interval (95% CI) 1.07-5.49] as was smoking (OR 2.28, 95% CI 1.26-4.12). However, the risk of progression was greatly increased to almost 12-fold (OR 11.8, 95% CI 2.1-65.8) when, in addition to having the C risk allele, subjects also presented with the upper tertile of antibodies to the bacterial pathogen C. pneumoniae compared with those with the T allele of Y402H and the lowest antibody tertile. This demonstrates for the first time the existence of a gene environment-interaction between pathogenic load of C. pneumoniae and the CFH gene in the aetiology of AMD.

  17. Gene-environment interactions between ERCC2, ERCC3, XRCC1 and cadmium exposure in nasal polyposis disease.

    PubMed

    Khlifi, Rim; Olmedo, Pablo; Gil, Fernando; Hammami, Boutheina; Hamza-Chaffai, Amel; Rebai, Ahmed

    2016-11-12

    Gene-environment interactions have long been known to play an important role in complex disease aetiology, such as nasal polyposis (NP). The present study supports the concept that DNA repair gene polymorphisms play critical roles in modifying individual susceptibility to environmental diseases. In fact, we investigated the role of polymorphisms in DNA repair genes and cadmium as risk factors for Tunisian patients with NP. To the best of our knowledge, this is the first report on the impact of combined effects of cadmium and ERCC3 7122 A>G (rs4150407), ERCC2 Lys751Gln (rs13181) and XRCC1 Arg399Gln (rs25487) genes in the susceptibility to NP disease. Significant associations between the risk of developing NP disease and ERCC2 [odds ratio (OR) = 2.0, 95 % confidence interval (CI) = 1.1-3.7, p = 0.023] and ERCC3 (OR = 2.2, 95 % CI = 1.2-4.1, p = 0.013) genotypes polymorphisms were observed. Blood concentrations of Cd in NP patients (2.2 μg/L) were significantly higher than those of controls (0.5 μg/L). A significant interaction between ERCC3 (7122 A>G) polymorphism and blood-Cd levels (for the median of blood-Cd levels: OR = 3.8, 95 % CI = 1.3-10.8, p = 0.014 and for the 75th percentiles of blood-Cd levels: OR = 2.7, 95 % CI = 1.1-7.2, p = 0.041) was found in association with the risk of NP disease. In addition, when we stratified ERCC2, ERCC3 and XRCC1 polymorphism genotypes by the median and 75th percentiles of blood-Cd levels, we found also significant interactions between ERCC2 (Lys751Gln) and ERCC3 (7122 A>G) genotypes polymorphism and this metal in association with NP disease. However, no interaction was found between XRCC1 (Arg399Gln) polymorphism genotypes and Cd in association with NP disease.

  18. 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

  19. 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…

  20. 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…

  1. Detection of Epistatic and Gene-Environment Interactions Underlying Three Quality Traits in Rice Using High-Throughput Genome-Wide Data

    PubMed Central

    Xu, Haiming; Jiang, Beibei; Cao, Yujie; Zhang, Yingxin; Zhan, Xiaodeng; Shen, Xihong; Cheng, Shihua; Lou, Xiangyang; Cao, Liyong

    2015-01-01

    With development of sequencing technology, dense single nucleotide polymorphisms (SNPs) have been available, enabling uncovering genetic architecture of complex traits by genome-wide association study (GWAS). However, the current GWAS strategy usually ignores epistatic and gene-environment interactions due to absence of appropriate methodology and heavy computational burden. This study proposed a new GWAS strategy by combining the graphics processing unit- (GPU-) based generalized multifactor dimensionality reduction (GMDR) algorithm with mixed linear model approach. The reliability and efficiency of the analytical methods were verified through Monte Carlo simulations, suggesting that a population size of nearly 150 recombinant inbred lines (RILs) had a reasonable resolution for the scenarios considered. Further, a GWAS was conducted with the above two-step strategy to investigate the additive, epistatic, and gene-environment associations between 701,867 SNPs and three important quality traits, gelatinization temperature, amylose content, and gel consistency, in a RIL population with 138 individuals derived from super-hybrid rice Xieyou9308 in two environments. Four significant SNPs were identified with additive, epistatic, and gene-environment interaction effects. Our study showed that the mixed linear model approach combining with the GPU-based GMDR algorithm is a feasible strategy for implementing GWAS to uncover genetic architecture of crop complex traits. PMID:26345334

  2. Detection of Epistatic and Gene-Environment Interactions Underlying Three Quality Traits in Rice Using High-Throughput Genome-Wide Data.

    PubMed

    Xu, Haiming; Jiang, Beibei; Cao, Yujie; Zhang, Yingxin; Zhan, Xiaodeng; Shen, Xihong; Cheng, Shihua; Lou, Xiangyang; Cao, Liyong

    2015-01-01

    With development of sequencing technology, dense single nucleotide polymorphisms (SNPs) have been available, enabling uncovering genetic architecture of complex traits by genome-wide association study (GWAS). However, the current GWAS strategy usually ignores epistatic and gene-environment interactions due to absence of appropriate methodology and heavy computational burden. This study proposed a new GWAS strategy by combining the graphics processing unit- (GPU-) based generalized multifactor dimensionality reduction (GMDR) algorithm with mixed linear model approach. The reliability and efficiency of the analytical methods were verified through Monte Carlo simulations, suggesting that a population size of nearly 150 recombinant inbred lines (RILs) had a reasonable resolution for the scenarios considered. Further, a GWAS was conducted with the above two-step strategy to investigate the additive, epistatic, and gene-environment associations between 701,867 SNPs and three important quality traits, gelatinization temperature, amylose content, and gel consistency, in a RIL population with 138 individuals derived from super-hybrid rice Xieyou9308 in two environments. Four significant SNPs were identified with additive, epistatic, and gene-environment interaction effects. Our study showed that the mixed linear model approach combining with the GPU-based GMDR algorithm is a feasible strategy for implementing GWAS to uncover genetic architecture of crop complex traits.

  3. Genotype-based association mapping of complex diseases: gene-environment interactions with multiple genetic markers and measurement error in environmental exposures.

    PubMed

    Lobach, Iryna; Fan, Ruzong; Carroll, Raymond J

    2010-12-01

    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 disequilibrium 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.

  4. 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

  5. Evidence of gene-environment interaction for two genes on chromosome 4 and environmental tobacco smoke in controlling the risk of nonsyndromic cleft palate.

    PubMed

    Wu, Tao; Schwender, Holger; Ruczinski, Ingo; Murray, Jeffrey C; Marazita, Mary L; Munger, Ronald G; Hetmanski, Jacqueline B; Parker, Margaret M; Wang, Ping; Murray, Tanda; Taub, Margaret; Li, Shuai; Redett, Richard J; Fallin, M Daniele; Liang, Kung Yee; Wu-Chou, Yah Huei; Chong, Samuel S; Yeow, Vincent; Ye, Xiaoqian; Wang, Hong; Huang, Shangzhi; Jabs, Ethylin W; Shi, Bing; Wilcox, Allen J; Jee, Sun Ha; Scott, Alan F; Beaty, Terri H

    2014-01-01

    Nonsyndromic cleft palate (CP) is one of the most common human birth defects and both genetic and environmental risk factors contribute to its etiology. We conducted a genome-wide association study (GWAS) using 550 CP case-parent trios ascertained in an international consortium. Stratified analysis among trios with different ancestries was performed to test for GxE interactions with common maternal exposures using conditional logistic regression models. While no single nucleotide polymorphism (SNP) achieved genome-wide significance when considered alone, markers in SLC2A9 and the neighboring WDR1 on chromosome 4p16.1 gave suggestive evidence of gene-environment interaction with environmental tobacco smoke (ETS) among 259 Asian trios when the models included a term for GxE interaction. Multiple SNPs in these two genes were associated with increased risk of nonsyndromic CP if the mother was exposed to ETS during the peri-conceptual period (3 months prior to conception through the first trimester). When maternal ETS was considered, fifteen of 135 SNPs mapping to SLC2A9 and 9 of 59 SNPs in WDR1 gave P values approaching genome-wide significance (10(-6)interaction. SNPs rs3733585 and rs12508991 in SLC2A9 yielded P = 2.26×10(-7) in a test for GxETS interaction. SNPs rs6820756 and rs7699512 in WDR1 also yielded P = 1.79×10(-7) and P = 1.98×10(-7) in a 1 df test for GxE interaction. Although further replication studies are critical to confirming these findings, these results illustrate how genetic associations for nonsyndromic CP can be missed if potential GxE interaction is not taken into account, and this study suggest SLC2A9 and WDR1 should be considered as candidate genes for CP.

  6. Is the gene-environment interaction paradigm relevant to genome-wide studies? The case of education and body mass index.

    PubMed

    Boardman, Jason D; Domingue, Benjamin W; Blalock, Casey L; Haberstick, Brett C; Harris, Kathleen Mullan; McQueen, Matthew B

    2014-02-01

    This study uses data from the Framingham Heart Study to examine the relevance of the gene-environment interaction paradigm for genome-wide association studies (GWAS). We use completed college education as our environmental measure and estimate the interactive effect of genotype and education on body mass index (BMI) using 260,402 single-nucleotide polymorphisms (SNPs). Our results highlight the sensitivity of parameter estimates obtained from GWAS models and the difficulty of framing genome-wide results using the existing gene-environment interaction typology. We argue that SNP-environment interactions across the human genome are not likely to provide consistent evidence regarding genetic influences on health that differ by environment. Nevertheless, genome-wide data contain rich information about individual respondents, and we demonstrate the utility of this type of data. We highlight the fact that GWAS is just one use of genome-wide data, and we encourage demographers to develop methods that incorporate this vast amount of information from respondents into their analyses.

  7. Gene environment interaction in periphery and brain converge to modulate behavioral outcomes: Insights from the SP1 transient early in life interference rat model

    PubMed Central

    Asor, Eyal; Ben-Shachar, Dorit

    2016-01-01

    It is generally assumed that behavior results from an interaction between susceptible genes and environmental stimuli during critical life stages. The present article reviews the main theoretical and practical concepts in the research of gene environment interaction, emphasizing the need for models simulating real life complexity. We review a novel approach to study gene environment interaction in which a brief post-natal interference with the expression of multiple genes, by hindering the activity of the ubiquitous transcription factor specificity protein 1 (Sp1) is followed by later-in-life exposure of rats to stress. Finally, this review discusses the role of peripheral processes in behavioral responses, with the Sp1 model as one example demonstrating how specific behavioral patterns are linked to modulations in both peripheral and central physiological processes. We suggest that models, which take into account the tripartite reciprocal interaction between the central nervous system, peripheral systems and environmental stimuli will advance our understanding of the complexity of behavior. PMID:27679768

  8. 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.

  9. Multivariate dimensionality reduction approaches to identify gene-gene and gene-environment interactions underlying multiple complex traits.

    PubMed

    Xu, Hai-Ming; Sun, Xi-Wei; Qi, Ting; Lin, Wan-Yu; Liu, Nianjun; Lou, Xiang-Yang

    2014-01-01

    The elusive but ubiquitous multifactor interactions represent a stumbling block that urgently needs to be removed in searching for determinants involved in human complex diseases. The dimensionality reduction approaches are a promising tool for this task. Many complex diseases exhibit composite syndromes required to be measured in a cluster of clinical traits with varying correlations and/or are inherently longitudinal in nature (changing over time and measured dynamically at multiple time points). A multivariate approach for detecting interactions is thus greatly needed on the purposes of handling a multifaceted phenotype and longitudinal data, as well as improving statistical power for multiple significance testing via a two-stage testing procedure that involves a multivariate analysis for grouped phenotypes followed by univariate analysis for the phenotypes in the significant group(s). In this article, we propose a multivariate extension of generalized multifactor dimensionality reduction (GMDR) based on multivariate generalized linear, multivariate quasi-likelihood and generalized estimating equations models. Simulations and real data analysis for the cohort from the Study of Addiction: Genetics and Environment are performed to investigate the properties and performance of the proposed method, as compared with the univariate method. The results suggest that the proposed multivariate GMDR substantially boosts statistical power.

  10. Glutamatergic GRIN2B and polyaminergic ODC1 genes in suicide attempts: associations and gene-environment interactions with childhood/adolescent physical assault.

    PubMed

    Sokolowski, M; Ben-Efraim, Y J; Wasserman, J; Wasserman, D

    2013-09-01

    The complex etiology of suicidal behavior has frequently been investigated in relation to monoaminergic neurotransmission, but other neurosystems have shown alterations as well, involving excitatory glutamatergic and inhibitory γ-aminobutyric acid (GABA) molecular components, together with the modulating polyamines. Sufficiently powered and family-based association studies of glutamatergic and GABAergic genes with suicidal behavior are nonexistent, but several studies have been reported for polyamines. We therefore conducted, for the first time ever, an extensive family-based study of 113 candidate single-nucleotide polymorphisms (SNPs) located in 24 glutamatergic and GABA genes, in addition to interrelated polyaminergic genes, on the outcome of severe suicide attempts (SAs). The family-based analysis (n=660 trios) was supplemented with gene-environment interaction (G × E), case-control (n=519 controls) and subgroup analyses. The main observations were the previously unreported association and linkage of SNPs rs2268115 and rs220557 in GRIN2B, as well as of SNPs rs1049500 and rs2302614 in ODC1 (P<10(-2)). Furthermore, GRIN2B haplotypic associations were observed, in particular with a four-SNP AGGC haplotype (rs1805247-rs1806201-rs1805482-rs2268115; P<10(-5)), and a third SNP rs7559979 in ODC1 showed G × E with serious childhood/adolescent physical assault (P<10(-4)). SA subjects were characterized by transdiagnostic trait anger and past year alcohol-drug use disorders, but not by alcohol-drug use at SA, depression, anxiety or psychosis diagnoses. We also discuss a first ever confirmatory observation of SNP rs6526342 (polyaminergic SAT1) in SA, originally identified in completed suicides. The results suggest that specific genetic variants in a subset of glutamatergic (GRIN2B) and polyaminergic (ODC1) neurosystem genes may be of importance in certain suicidal subjects.

  11. Bayesian inference of gene-environment interaction from incomplete data: what happens when information on environment is disjoint from data on gene and disease?

    PubMed

    Gustafson, Paul; Burstyn, Igor

    2011-04-15

    Inference in gene-environment studies can sometimes exploit the assumption of mendelian randomization that genotype and environmental exposure are independent in the population under study. Moreover, in some such problems it is reasonable to assume that the disease risk for subjects without environmental exposure will not vary with genotype. When both assumptions can be invoked, we consider the prospects for inferring the dependence of disease risk on genotype and environmental exposure (and particularly the extent of any gene-environment interaction), without detailed data on environmental exposure. The data structure envisioned involves data on disease and genotype jointly, but only external information about the distribution of the environmental exposure in the population. This is relevant as for many environmental exposures individual-level measurements are costly and/or highly error-prone. Working in the setting where all relevant variables are binary, we examine the extent to which such data are informative about the interaction, via determination of the large-sample limit of the posterior distribution. The ideas are illustrated using data from a case-control study for bladder cancer involving smoking behaviour and the NAT2 genotype.

  12. Cytochrome P450 1B1, a new keystone in gene-environment interactions related to human head and neck cancer?

    PubMed

    Thier, Ricarda; Brüning, Thomas; Roos, Peter H; Bolt, Hermann M

    2002-06-01

    Alcohol consumption and tobacco smoking are major causes of head and neck cancers, and regional differences point to the importance of research into gene-environment interactions. Much interest has been focused on polymorphisms of CYP1A1 and of GSTM1 and GSTT1, but a number of studies have not demonstrated significant effects. This has mostly been ascribed to small sample sizes. In general, the impact of polymorphisms of metabolic enzymes appears inconsistent, with some reports of weak-to-moderate associations, and with others of no elevation of risks. The classical cytochrome P450 isoenzyme considered for metabolic activation of polycyclic aromatic hydrocarbons (PAH) is CYP1A1. A new member of the CYP1 family, CYP1B1, was cloned in 1994, currently representing the only member of the CYP1B subfamily. A number of single nucleotide polymorphisms of the CYP1B1 gene have been reported. The amino acid substitutions Val432Leu ( CYP1B1*3) and Asn453Ser ( CYP1B1*4), located in the heme binding domain of CYP1B1, appear as likely candidates to be linked with biological effects. CYP1B1 activates a wide range of PAH, aromatic and heterocyclic amines. Very recently, the CYP1B1 codon 432 polymorphism ( CYP1B1*3) has been identified as a susceptibility factor in smoking-related head-and-neck squamous cell cancer. The impact of this polymorphic variant of CYP1B1 on cancer risk was also reflected by an association with the frequency of somatic mutations of the p53 gene. Combined genotype analysis of CYP1B1 and the glutathione transferases GSTM1 or GSTT1 has pointed to interactive effects. This provides new molecular evidence that tobacco smoke-specific compounds relevant to head and neck carcinogenesis are metabolically activated through CYP1B1 and is consistent with a major pathogenetic relevance of PAH as ingredients of tobacco smoke.

  13. The role of 5-HTT LPR and GNβ3 825C>T polymorphisms and gene-environment interactions in irritable bowel syndrome (IBS)

    PubMed Central

    Saito, Yuri A.; Larson, Joseph J.; Atkinson, Elizabeth J.; Ryu, Euijung; Almazar, Ann E.; Petersen, Gloria M.; Talley, Nicholas J.

    2014-01-01

    Background Smaller studies have evaluated SLC6A4 5-HTTLPR and GNβ3 825C>T polymorphisms in IBS, and interactions between 5-HTT LPR with life events have been reported in the psychiatric literature, but gene-environment studies in IBS are lacking. Aims To assess the association of two polymorphisms with IBS and age of onset; and to assess whether there are gene-environment interactions with IBS. Methods Outpatients with IBS and controls completed a validated questionnaire and provided blood for DNA. Comparisons of genotype/allele frequencies between cases and controls were performed with logistic regression. Linear regression was used to evaluate the association between the variants and age of onset. Environmental variables tested included abuse, parental alcohol abuse, parental psychiatric disorders, and gastrointestinal infections. Results Genotyping was performed in 385 cases and 262 controls with median age of 50 yrs (range: 18.0–70.0) and 498 (77%) females. The IBS subtype distribution among cases was: 102 (26%) D-IBS, 40 (10%) C-IBS, 125 (32%) M-IBS, 118 (31%) other. No association was observed between IBS or age of onset and both variants. Significant interactions were observed between GI infection and the GNβ3 825T allele. For those reporting gastrointestinal infection, the OR for IBS was 3.9 (95%CI: 1.2–12.7) whereas the OR was 0.86 (95% CI: 0.65–1.13) for those without prior infection. Conclusions There was a significant interaction between the GNβ3 polymorphism and infection in the development of IBS, suggesting that its etiology is the result of a combination of specific genetic and environmental risk factors. PMID:22855291

  14. Assessing Gene-Environment Interactions for Common and Rare Variants with Binary Traits Using Gene-Trait Similarity Regression

    PubMed Central

    Zhao, Guolin; Marceau, Rachel; Zhang, Daowen; Tzeng, Jung-Ying

    2015-01-01

    Accounting for gene–environment (G×E) interactions in complex trait association studies can facilitate our understanding of genetic heterogeneity under different environmental exposures, improve the ability to discover susceptible genes that exhibit little marginal effect, provide insight into the biological mechanisms of complex diseases, help to identify high-risk subgroups in the population, and uncover hidden heritability. However, significant G×E interactions can be difficult to find. The sample sizes required for sufficient power to detect association are much larger than those needed for genetic main effects, and interactions are sensitive to misspecification of the main-effects model. These issues are exacerbated when working with binary phenotypes and rare variants, which bear less information on association. In this work, we present a similarity-based regression method for evaluating G×E interactions for rare variants with binary traits. The proposed model aggregates the genetic and G×E information across markers, using genetic similarity, thus increasing the ability to detect G×E signals. The model has a random effects interpretation, which leads to robustness against main-effect misspecifications when evaluating G×E interactions. We construct score tests to examine G×E interactions and a computationally efficient EM algorithm to estimate the nuisance variance components. Using simulations and data applications, we show that the proposed method is a flexible and powerful tool to study the G×E effect in common or rare variant studies with binary traits. PMID:25585620

  15. 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...

  16. An investigation of gene-environment interactions between 47 newly identified breast cancer susceptibility loci and environmental risk factors

    PubMed Central

    Rudolph, Anja; Milne, Roger L.; Truong, Thérèse; Knight, Julia A.; Seibold, Petra; Flesch-Janys, Dieter; Behrens, Sabine; Eilber, Ursula; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Dunning, Alison M.; Shah, Mitul; Munday, Hannah R.; Darabi, Hatef; Eriksson, Mikael; Brand, Judith S.; Olson, Janet; Vachon, Celine M.; Hallberg, Emily; Castelao, J. Esteban; Carracedo, Angel; Torres, Maria; Li, Jingmei; Humphreys, Keith; Cordina-Duverger, Emilie; Menegaux, Florence; Flyger, Henrik; Nordestgaard, Børge G.; Nielsen, Sune F.; Yesilyurt, Betul T.; Floris, Giuseppe; Leunen, Karin; Engelhardt, Ellen G.; Broeks, Annegien; Rutgers, Emiel J.; Glendon, Gord; Mulligan, Anna Marie; Cross, Simon; Reed, Malcolm; Gonzalez-Neira, Anna; Perez, José Ignacio Arias; Provenzano, Elena; Apicella, Carmel; Southey, Melissa C.; Spurdle, Amanda; Investigators, kConFab; Group, AOCS; Häberle, Lothar; Beckmann, Matthias W.; Ekici, Arif B.; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; McLean, Catriona; Baglietto, Laura; Chanock, Stephen J.; Lissowska, Jolanta; Sherman, Mark E.; Brüning, Thomas; Hamann, Ute; Ko, Yon-Dschun; Orr, Nick; Schoemaker, Minouk; Ashworth, Alan; Kosma, Veli-Matti; Kataja, Vesa; Hartikainen, Jaana M.; Mannermaa, Arto; Swerdlow, Anthony; Giles, Graham G.; Brenner, Hermann; Fasching, Peter A.; Chenevix-Trench, Georgia; Hopper, John; Benítez, Javier; Cox, Angela; Andrulis, Irene L.; Lambrechts, Diether; Gago-Dominguez, Manuela; Couch, Fergus; Czene, Kamila; Bojesen, Stig E.; Easton, Doug F.; Schmidt, Marjanka K.; Guénel, Pascal; Hall, Per; Pharoah, Paul D. P.; Garcia-Closas, Montserrat; Chang-Claude, Jenny

    2014-01-01

    A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated with estrogen receptor (ER) negative BC risk are modified by 13 environmental risk factors for BC. Data from 22 studies participating in BCAC were pooled, comprising up to 26,633 cases and 30,119 controls. Interactions between SNPs and environmental factors were evaluated using an empirical Bayes-type shrinkage estimator. Six SNPs showed interactions with associated p-values (pint) <1.1×10−3. None of the observed interactions was significant after accounting for multiple testing. The Bayesian False Discovery Probability was used to rank the findings, which indicated three interactions as being noteworthy at 1% prior probability of interaction. SNP rs6828523 was associated with increased ER-negative BC risk in women ≥170cm (OR=1.22, p=0.017), but inversely associated with ER-negative BC risk in women <160cm (OR=0.83, p=0.039, pint=1.9×10−4). The inverse association between rs4808801 and overall BC risk was stronger for women who had had four or more pregnancies (OR=0.85, p=2.0×10−4), and absent in women who had had just one (OR=0.96, p=0.19, pint = 6.1×10−4). SNP rs11242675 was inversely associated with overall BC risk in never/former smokers (OR=0.93, p=2.8×10−5), but no association was observed in current smokers (OR=1.07, p=0.14, pint = 3.4×10−4). In conclusion, recently identified breast cancer susceptibility loci are not strongly modified by established risk factors and the observed potential interactions require confirmation in independent studies. PMID:25227710

  17. Investigation of gene-environment interactions between 47 newly identified breast cancer susceptibility loci and environmental risk factors.

    PubMed

    Rudolph, Anja; Milne, Roger L; Truong, Thérèse; Knight, Julia A; Seibold, Petra; Flesch-Janys, Dieter; Behrens, Sabine; Eilber, Ursula; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; Dunning, Alison M; Shah, Mitul; Munday, Hannah R; Darabi, Hatef; Eriksson, Mikael; Brand, Judith S; Olson, Janet; Vachon, Celine M; Hallberg, Emily; Castelao, J Esteban; Carracedo, Angel; Torres, Maria; Li, Jingmei; Humphreys, Keith; Cordina-Duverger, Emilie; Menegaux, Florence; Flyger, Henrik; Nordestgaard, Børge G; Nielsen, Sune F; Yesilyurt, Betul T; Floris, Giuseppe; Leunen, Karin; Engelhardt, Ellen G; Broeks, Annegien; Rutgers, Emiel J; Glendon, Gord; Mulligan, Anna Marie; Cross, Simon; Reed, Malcolm; Gonzalez-Neira, Anna; Arias Perez, José Ignacio; Provenzano, Elena; Apicella, Carmel; Southey, Melissa C; Spurdle, Amanda; Häberle, Lothar; Beckmann, Matthias W; Ekici, Arif B; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; McLean, Catriona; Baglietto, Laura; Chanock, Stephen J; Lissowska, Jolanta; Sherman, Mark E; Brüning, Thomas; Hamann, Ute; Ko, Yon-Dschun; Orr, Nick; Schoemaker, Minouk; Ashworth, Alan; Kosma, Veli-Matti; Kataja, Vesa; Hartikainen, Jaana M; Mannermaa, Arto; Swerdlow, Anthony; Giles, Graham G; Brenner, Hermann; Fasching, Peter A; Chenevix-Trench, Georgia; Hopper, John; Benítez, Javier; Cox, Angela; Andrulis, Irene L; Lambrechts, Diether; Gago-Dominguez, Manuela; Couch, Fergus; Czene, Kamila; Bojesen, Stig E; Easton, Doug F; Schmidt, Marjanka K; Guénel, Pascal; Hall, Per; Pharoah, Paul D P; Garcia-Closas, Montserrat; Chang-Claude, Jenny

    2015-03-15

    A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated with estrogen receptor (ER) negative BC risk are modified by 13 environmental risk factors for BC. Data from 22 studies participating in BCAC were pooled, comprising up to 26,633 cases and 30,119 controls. Interactions between SNPs and environmental factors were evaluated using an empirical Bayes-type shrinkage estimator. Six SNPs showed interactions with associated p-values (pint ) <1.1 × 10(-3) . None of the observed interactions was significant after accounting for multiple testing. The Bayesian False Discovery Probability was used to rank the findings, which indicated three interactions as being noteworthy at 1% prior probability of interaction. SNP rs6828523 was associated with increased ER-negative BC risk in women ≥170 cm (OR = 1.22, p = 0.017), but inversely associated with ER-negative BC risk in women <160 cm (OR = 0.83, p = 0.039, pint = 1.9 × 10(-4) ). The inverse association between rs4808801 and overall BC risk was stronger for women who had had four or more pregnancies (OR = 0.85, p = 2.0 × 10(-4) ), and absent in women who had had just one (OR = 0.96, p = 0.19, pint = 6.1 × 10(-4) ). SNP rs11242675 was inversely associated with overall BC risk in never/former smokers (OR = 0.93, p = 2.8 × 10(-5) ), but no association was observed in current smokers (OR = 1.07, p = 0.14, pint = 3.4 × 10(-4) ). In conclusion, recently identified BC susceptibility loci are not strongly modified by established risk factors and the observed potential interactions require confirmation in independent studies.

  18. Effect of TNF and LTA polymorphisms on biological markers of response to oxidative stimuli in coal miners: a model of gene-environment interaction

    PubMed Central

    Nadif, R; Jedlicka, A; Mintz, M; Bertrand, J; Kleeberger, S; Kauffmann, F

    2003-01-01

    Introduction: Interaction between genetic background and oxidative environmental stimuli in the pathogenesis of human lung disease has been largely unexplored. Methods: A prospective epidemiological study was undertaken in 253 coal miners. Intermediate quantitative phenotypes of response to oxidant exposure, including erythrocyte glutathione peroxidase (GSH-Px) and catalase activities, were studied. Oxidant exposures studied were smoking habits and cumulative dust exposure assessed by job history and ambient measures. Disease phenotypes included subclinical computed tomography score at the first survey and x ray profusion grades twice, five years apart, to assess established coal workers' pneumoconiosis (CWP). Miners were genotyped for common functional polymorphisms in the gene for tumour necrosis factor α (TNF) and lymphotoxin α (LTA), two proinflammatory cytokines that have been implicated in the pathogenesis of chronic lung diseases. Results: Regarding gene-environment interaction on intermediate phenotypes, results showed interaction of a promoter polymorphism at the –308 position in TNF with occupational exposure on erythrocyte GSH-Px activity with a significant association in those with high exposure (p=0.003), whereas no association was observed among those with low exposure (interaction p=0.06). Regarding gene intermediate phenotype interaction on clinical outcome, results showed an association of CWP prevalence with an NcoI polymorphism in LTA in those with low catalase activity (p=0.05), whereas no association was observed in those with high activity (interaction p=0.03). No other significant association was observed. Conclusion: The results suggest that interactions of genetic background with environmental exposure and intermediate response phenotypes are important components in the pathogenesis of CWP. PMID:12566517

  19. The Influence of Gene-Environment Interactions on Alcohol Consumption and Alcohol Use Disorders: A Comprehensive Review

    PubMed Central

    Young-Wolff, Kelly C.; Enoch, Mary-Anne; Prescott, Carol A.

    2011-01-01

    Since 2005, a rapidly expanding literature has evaluated whether environmental factors such as socio-cultural context and environmental adversity interact with genetic influences on drinking behaviors. This article critically reviews empirical research on alcohol-related genotype-environment interactions (GxE) and provides a contextual framework for understanding how genetic factors combine with (or are shaped by) environmental influences to influence the development of drinking behaviors and alcohol use disorders. Collectively, evidence from twin, adoption, and molecular genetic studies indicates that the degree of importance of genetic influences on risk for drinking outcomes can vary in different populations and under different environmental circumstances. However, methodological limitations and lack of consistent replications in this literature make it difficult to draw firm conclusions regarding the nature and effect size of alcohol-related GxE. On the basis of this review, we describe several methodological challenges as they relate to current research on GxE in drinking behaviors and provide recommendations to aid future research. PMID:21530476

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

    PubMed

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

    2016-08-01

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

  1. Conceptual Shifts Needed to Understand the Dynamic Interactions of Genes, Environment, Epigenetics, Social Processes, and Behavioral Choices

    PubMed Central

    Niculescu, Mihai D.; Jackson, Robert T.

    2013-01-01

    Social and behavioral research in public health is often intimately tied to profound, but frequently neglected, biological influences from underlying genetic, environmental, and epigenetic events. The dynamic interplay between the life, social, and behavioral sciences often remains underappreciated and underutilized in addressing complex diseases and disorders and in developing effective remediation strategies. Using a case-study format, we present examples as to how the inclusion of genetic, environmental, and epigenetic data can augment social and behavioral health research by expanding the parameters of such studies, adding specificity to phenotypic assessments, and providing additional internal control in comparative studies. We highlight the important roles of gene–environment interactions and epigenetics as sources of phenotypic change and as a bridge between the life and social and behavioral sciences in the development of robust interdisciplinary analyses. PMID:23927503

  2. A Twin and Adoption Study of Reading Achievement: Exploration of Shared-Environmental and Gene-Environment-Interaction Effects

    ERIC Educational Resources Information Center

    Kirkpatrick, Robert M.; Legrand, Lisa N.; Iacono, William G.; McGue, Matt

    2011-01-01

    Existing behavior-genetic research implicates substantial influence of heredity and modest influence of shared environment on reading achievement and reading disability. Applying DeFries-Fulker analysis to a combined sample of twins and adoptees (N = 4886, including 266 reading-disabled probands), the present study replicates prior findings of…

  3. Gene--environment interactions influence feeding and anti-predator behavior in wild and transgenic coho salmon.

    PubMed

    Sundström, L F; Löhmus, M; Devlin, R H

    2016-01-01

    Environmental conditions are known to affect phenotypic development in many organisms, making the characteristics of an animal reared under one set of conditions not always representative of animals reared under a different set of conditions. Previous results show that such plasticity can also affect the phenotypes and ecological interactions of different genotypes, including animals anthropogenically generated by genetic modification. To understand how plastic development can affect behavior in animals of different genotypes, we examined the feeding and risk-taking behavior in growth-enhanced transgenic coho salmon (with two- to threefold enhanced daily growth rates compared to wild type) under a range of conditions. When compared to wild-type siblings, we found clear effects of the rearing environment on feeding and risk-taking in transgenic animals and noted that in some cases, this environmental effect was stronger than the effects of the genetic modification. Generally, transgenic fish, regardless of rearing conditions, behaved similar to wild-type fish reared under natural-like conditions. Instead, the more unusual phenotype was associated with wild-type fish reared under hatchery conditions, which possessed an extreme risk averse phenotype compared to the same strain reared in naturalized conditions. Thus, the relative performance of genotypes from one environment (e.g., laboratory) may not always accurately reflect ecological interactions as would occur in a different environment (e.g., nature). Further, when assessing risks of genetically modified organisms, it is important to understand how the environment affects phenotypic development, which in turn may variably influence consequences to ecosystem components across different conditions found in the complexity of nature.

  4. Have studies of the developmental regulation of behavioral phenotypes revealed the mechanisms of gene-environment interactions?

    PubMed Central

    Hall, F. Scott; Perona, Maria T. G.

    2012-01-01

    This review addresses the recent convergence of our long-standing knowledge of the regulation of behavioral phenotypes by developmental experience with recent advances in our understanding of mechanisms regulating gene expression. This review supports a particular perspective on the developmental regulation of behavioral phenotypes: That the role of common developmental experiences (e.g. maternal interactions, peer interactions, exposure to a complex environment, etc.) is to fit individuals to the circumstances of their lives within bounds determined by long-standing (evolutionary) mechanisms that have shaped responses to critical and fundamental types of experience via those aspects of gene structure that regulate gene expression. The phenotype of a given species is not absolute for a given genotype but rather variable within bounds that are determined by mechanisms regulated by experience (e.g. epigenetic mechanisms). This phenotypic variation is not necessarily random, or evenly distributed along a continuum of description or measurement, but often highly disjointed, producing distinct, even opposing, phenotypes. The potentiality for these varying phenotypes is itself the product of evolution, the potential for alternative phenotypes itself conveying evolutionary advantage. Examples of such phenotypic variation, resulting from environmental or experiential influences, have a long history of study in neurobiology, and a number of these will be discussed in this review: neurodevelopmental experiences that produce phenotypic variation in visual perception, cognitive function, and emotional behavior. Although other examples will be discussed, particular emphasis will be made on the role of social behavior on neurodevelopment and phenotypic determination. It will be argued that an important purpose of some aspects of social behavior is regulation of neurobehavioral phenotypes by experience via genetic regulatory mechanisms. PMID:22643448

  5. Environmental and genetic risk factors and gene-environment interactions in the pathogenesis of chronic obstructive lung disease.

    PubMed Central

    Walter, R; Gottlieb, D J; O'Connor, G T

    2000-01-01

    Current understanding of the pathogenesis of chronic obstructive pulmonary disease (COPD), a source of substantial morbidity and mortality in the United States, suggests that chronic inflammation leads to the airways obstruction and parenchymal destruction that characterize this condition. Environmental factors, especially tobacco smoke exposure, are known to accelerate longitudinal decline of lung function, and there is substantial evidence that upregulation of inflammatory pathways plays a vital role in this process. Genetic regulation of both inflammatory responses and anti-inflammatory protective mechanisms likely underlies the heritability of COPD observed in family studies. In alpha-1 protease inhibitor deficiency, the only genetic disorder known to cause COPD, lack of inhibition of elastase activity, results in the parenchymal destruction of emphysema. Other genetic polymorphisms have been hypothesized to alter the risk of COPD but have not been established as causes of this condition. It is likely that multiple genetic factors interacting with each other and with a number of environmental agents will be found to result in the development of COPD. PMID:10931792

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

    PubMed Central

    Kimura, Ryuichi; Tucci, Valter; Kaneda, Hideki; Wakana, Shigeharu; Osumi, Noriko

    2016-01-01

    Neurodevelopmental disorders such as autism spectrum disorder (ASD) and attention deficit and hyperactivity disorder (ADHD) have increased over the last few decades. These neurodevelopmental disorders are characterized by a complex etiology, which involves multiple genes and gene-environmental interactions. Various genes that control specific properties of neural development exert pivotal roles in the occurrence and severity of phenotypes associated with neurodevelopmental disorders. Moreover, paternal aging has been reported as one of the factors that contribute to the risk of ASD and ADHD. Here we report, for the first time, that paternal aging has profound effects on the onset of behavioral abnormalities in mice carrying a mutation of Pax6, a gene with neurodevelopmental regulatory functions. We adopted an in vitro fertilization approach to restrict the influence of additional factors. Comprehensive behavioral analyses were performed in Sey/+ mice (i.e., Pax6 mutant heterozygotes) born from in vitro fertilization of sperm taken from young or aged Sey/+ fathers. No body weight changes were found in the four groups, i.e., Sey/+ and wild type (WT) mice born to young or aged father. However, we found important differences in maternal separation-induced ultrasonic vocalizations of Sey/+ mice born from young father and in the level of hyperactivity of Sey/+ mice born from aged fathers in the open-field test, respectively, compared to WT littermates. Phenotypes of anxiety were observed in both genotypes born from aged fathers compared with those born from young fathers. No significant difference was found in social behavior and sensorimotor gating among the four groups. These results indicate that mice with a single genetic risk factor can develop different phenotypes depending on the paternal age. Our study advocates for serious considerations on the role of paternal aging in breeding strategies for animal studies. PMID:27855195

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

    PubMed

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

    2016-01-01

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

  8. Childhood gene-environment interactions and age-dependent effects of genetic variants associated with refractive error and myopia: The CREAM Consortium

    PubMed Central

    Fan, Qiao; Guo, Xiaobo; Tideman, J. Willem L.; Williams, Katie M.; Yazar, Seyhan; Hosseini, S. Mohsen; Howe, Laura D.; Pourcain, Beaté St; Evans, David M.; Timpson, Nicholas J.; McMahon, George; Hysi, Pirro G.; Krapohl, Eva; Wang, Ya Xing; Jonas, Jost B.; Baird, Paul Nigel; Wang, Jie Jin; Cheng, Ching-Yu; Teo, Yik-Ying; Wong, Tien-Yin; Ding, Xiaohu; Wojciechowski, Robert; Young, Terri L.; Pärssinen, Olavi; Oexle, Konrad; Pfeiffer, Norbert; Bailey-Wilson, Joan E.; Paterson, Andrew D.; Klaver, Caroline C. W.; Plomin, Robert; Hammond, Christopher J.; Mackey, David A.; He, Mingguang; Saw, Seang-Mei; Williams, Cathy; Guggenheim, Jeremy A.; Meguro, Akira; Wright, Alan F.; Hewitt, Alex W.; Young, Alvin L.; Veluchamy, Amutha Barathi; Metspalu, Andres; Paterson, Andrew D.; Döring, Angela; Khawaja, Anthony P.; Klein, Barbara E.; Pourcain, Beate St; Fleck, Brian; Klaver, Caroline C. W.; Hayward, Caroline; Williams, Cathy; Delcourt, Cécile; Pang, Chi Pui; Khor, Chiea-Chuen; Cheng, Ching-Yu; Gieger, Christian; Hammond, Christopher J.; Simpson, Claire L.; van Duijn, Cornelia M.; Mackey, David A.; Evans, David M.; Stambolian, Dwight; Chew, Emily; Tai, E-Shyong; Krapohl, Eva; Mihailov, Evelin; Smith, George Davey; McMahon, George; Biino, Ginevra; Campbell, Harry; Rudan, Igor; Seppälä, Ilkka; Kaprio, Jaakko; Wilson, James F.; Craig, Jamie E.; Tideman, J. Willem L.; Ried, Janina S.; Korobelnik, Jean-François; Guggenheim, Jeremy A.; Fondran, Jeremy R.; Wang, Jie Jin; Liao, Jiemin; Zhao, Jing Hua; Xie, Jing; Bailey-Wilson, Joan E.; Kemp, John P.; Lass, Jonathan H.; Jonas, Jost B.; Rahi, Jugnoo S.; Wedenoja, Juho; Mäkelä, Kari-Matti; Burdon, Kathryn P.; Williams, Katie M; Khaw, Kay-Tee; Yamashiro, Kenji; Oexle, Konrad; Howe, Laura D.; Chen, Li Jia; Xu, Liang; Farrer, Lindsay; Ikram, M. Kamran; Deangelis, Margaret M.; Morrison, Margaux; Schache, Maria; Pirastu, Mario; Miyake, Masahiro; Yap, Maurice K. H.; Fossarello, Maurizio; Kähönen, Mika; Tedja, Milly S.; He, Mingguang; Yoshimura, Nagahisa; Martin, Nicholas G.; Timpson, Nicholas J.; Wareham, Nick J.; Mizuki, Nobuhisa; Pfeiffer, Norbert; Pärssinen, Olavi; Raitakari, Olli; Polasek, Ozren; Tam, Pancy O.; Foster, Paul J.; Mitchell, Paul; Baird, Paul Nigel; Chen, Peng; Hysi, Pirro G.; Cumberland, Phillippa; Gharahkhani, Puya; Fan, Qiao; Höhn, René; Fogarty, Rhys D.; Luben, Robert N.; Igo Jr, Robert P.; Plomin, Robert; Wojciechowski, Robert; Klein, Ronald; Mohsen Hosseini, S.; Janmahasatian, Sarayut; Saw, Seang-Mei; Yazar, Seyhan; Ping Yip, Shea; Feng, Sheng; Vaccargiu, Simona; Panda-Jonas, Songhomitra; MacGregor, Stuart; Iyengar, Sudha K.; Rantanen, Taina; Lehtimäki, Terho; Young, Terri L.; Meitinger, Thomas; Wong, Tien-Yin; Aung, Tin; Haller, Toomas; Vitart, Veronique; Nangia, Vinay; Verhoeven, Virginie J. M.; Jhanji, Vishal; Zhao, Wanting; Chen, Wei; Zhou, Xiangtian; Guo, Xiaobo; Ding, Xiaohu; Wang, Ya Xing; Lu, Yi; Teo, Yik-Ying; Vatavuk, Zoran

    2016-01-01

    Myopia, currently at epidemic levels in East Asia, is a leading cause of untreatable visual impairment. Genome-wide association studies (GWAS) in adults have identified 39 loci associated with refractive error and myopia. Here, the age-of-onset of association between genetic variants at these 39 loci and refractive error was investigated in 5200 children assessed longitudinally across ages 7–15 years, along with gene-environment interactions involving the major environmental risk-factors, nearwork and time outdoors. Specific variants could be categorized as showing evidence of: (a) early-onset effects remaining stable through childhood, (b) early-onset effects that progressed further with increasing age, or (c) onset later in childhood (N = 10, 5 and 11 variants, respectively). A genetic risk score (GRS) for all 39 variants explained 0.6% (P = 6.6E–08) and 2.3% (P = 6.9E–21) of the variance in refractive error at ages 7 and 15, respectively, supporting increased effects from these genetic variants at older ages. Replication in multi-ancestry samples (combined N = 5599) yielded evidence of childhood onset for 6 of 12 variants present in both Asians and Europeans. There was no indication that variant or GRS effects altered depending on time outdoors, however 5 variants showed nominal evidence of interactions with nearwork (top variant, rs7829127 in ZMAT4; P = 6.3E–04). PMID:27174397

  9. Using gene-environment interaction analyses to clarify the role of well-done meat and heterocyclic amine exposure in the etiology of colorectal polyps123

    PubMed Central

    Fu, Zhenming; Shrubsole, Martha J; Li, Guoliang; Smalley, Walter E; Hein, David W; Chen, Zhi; Shyr, Yu; Cai, Qiuyin; Ness, Reid M

    2012-01-01

    Background: The role of well-done meat intake and meat-derived mutagen heterocyclic amine (HCA) exposure in the risk of colorectal neoplasm has been suggested but not yet established. Objective: With the use of gene-environment interaction analyses, we sought to clarify the association of HCA exposure with colorectal polyp risk. Design: In a case-control study including 2057 colorectal polyp patients and 3329 controls, we evaluated 16 functional genetic variants to construct an HCA-metabolizing score. To derive dietary HCA-exposure amount, data were collected regarding dietary intake of meat by cooking method and degree of doneness. Results: A 2-fold elevated risk associated with high red meat intake was found for colorectal polyps or adenomas in subjects with a high HCA-metabolizing risk score, whereas the risk was 1.3- to 1.4-fold among those with a low risk score (P-interaction ≤ 0.05). The interaction was stronger for the risk of advanced or multiple adenomas, in which an OR of 2.8 (95% CI: 1.8, 4.6) was observed for those with both a high HCA-risk score and high red meat intake (P-interaction = 0.01). No statistically significant interaction was found in analyses that used specific HCA exposure derived from dietary data. Conclusion: High red meat intake is associated with an elevated risk of colorectal polyps, and this association may be synergistically modified by genetic factors involved in HCA metabolism. PMID:23015320

  10. The immunogenetics of narcolepsy associated with A(H1N1)pdm09 vaccination (Pandemrix) supports a potent gene-environment interaction.

    PubMed

    Bomfim, I L; Lamb, F; Fink, K; Szakács, A; Silveira, A; Franzén, L; Azhary, V; Maeurer, M; Feltelius, N; Darin, N; Hallböök, T; Arnheim-Dahlström, L; Kockum, I; Olsson, T

    2017-03-23

    The influenza A(H1N1)pdm09 vaccination campaign from 2009 to 2010 was associated with a sudden increase in the incidence of narcolepsy in several countries. Narcolepsy with cataplexy is strongly associated with the human leukocyte antigen (HLA) class II DQB1*06:02 allele, and protective associations with the DQB1*06:03 allele have been reported. Several non-HLA gene loci are also associated, such as common variants of the T-cell receptor-α (TRA), the purinergic receptor P2RY11, cathepsin H (CTSH) and TNFSF4/OX40L/CD252. In this retrospective multicenter study, we investigated if these predisposing gene loci were also involved in vaccination-associated narcolepsy. We compared HLA- along with single-nucleotide polymorphism genotypes for non-HLA regions between 42 Pandemrix-vaccinated narcolepsy cases and 1990 population-based controls. The class II gene loci associations supported previous findings. Nominal association (P-value<0.05) with TRA as well as suggestive (P-value<0.1) associations with P2RY11 and CTSH were found. These associations suggest a very strong gene-environment interaction, in which the influenza A(H1N1)pdm09 strain or Pandemrix vaccine can act as potent environmental triggers.Genes and Immunity advance online publication, 23 March 2017; doi:10.1038/gene.2017.1.

  11. Nevoid basal cell carcinoma syndrome with medulloblastoma in an African-American boy: A rare case illustrating gene-environment interaction

    SciTech Connect

    Korczak, J.F.; Goldstein, A.M.; Kase, R.G.

    1997-03-31

    We present an 8-year-old African-American boy with medulloblastoma and nevoid basal cell carcinoma syndrome (NBCCS) who exhibited the radiosensitive response of basal cell carcinoma (BCC) formation in the area irradiated for medulloblastoma. Such a response is well-documented in Caucasian NBCCS patients with medulloblastoma. The propositus was diagnosed with medulloblastoma at the age of 2 years and underwent surgery, chemotherapy, and craniospinal irradiation. At the age of 6 years, he was diagnosed with NBCCS following his presentation with a large odontogenic keratocyst of the mandible, pits of the palms and soles and numerous BCCs in the area of the back and neck that had been irradiated previously for medulloblastoma. Examination of other relatives showed that the propositus mother also had NBCCS but was more mildly affected; in particular, she had no BCCs. This case illustrates complex gene-environment interaction, in that increased skin pigmentation in African-Americans is presumably protective against ultraviolet, but not ionizing, radiation. This case and other similar cases in the literature show the importance of considering NBCCS in the differential diagnosis of any patient who presents with a medulloblastoma, especially before the age of 5 years, and of examining other close relatives for signs of NBCCS to determine the patient`s at-risk status. Finally, for individuals who are radiosensitive, protocols that utilize chemotherapy in lieu of radiotherapy should be considered. 27 refs., 4 figs.

  12. Escitalopram affects cytoskeleton and synaptic plasticity pathways in a rat gene-environment interaction model of depression as revealed by proteomics. Part II: environmental challenge.

    PubMed

    Piubelli, Chiara; Vighini, Miriam; Mathé, Aleksander A; Domenici, Enrico; Carboni, Lucia

    2011-07-01

    Large-scale investigations aimed at elucidating the molecular mechanism of action of antidepressant treatment are achievable through the application of proteomic technologies. We performed a proteomic study on the Flinders Sensitive Line (FSL), a genetically selected rat model of depression, and the control Flinders Resistant Line (FRL). To evaluate gene-environment interactions, FSL and FRL animals were separated from their mothers for 3 h from postnatal days 2 to 14 (maternal separation; MS), since early-life trauma is considered an important antecedent of depression. All groups received either escitalopram (Esc) admixed to food pellets (25 mg/kg.d) or vehicle for 1 month. Protein extracts from prefrontal/frontal cortex and hippocampus were separated by 2D electrophoresis. Proteins differentially modulated were identified by mass spectrometry. Bioinformatics analyses were performed to discover gene ontology terms associated with the modulated proteins. This paper was focused on the modifications induced by the environmental challenge of MS, both on the predisposed genetic background and on the resistant phenotype. The combination between Esc treatment and MS was investigated by comparing the MS, Esc-treated rats with rats subjected to each single procedure. In MS rats, antidepressant treatment influenced mainly proteins involved in carbohydrate metabolism in FSL rats and in vesicle-mediated transport in FRL rats. When studying the interaction between Esc and MS vs. non-separated rats, proteins playing a role in cytoskeleton organization, neuronal development, vesicle-mediated transport and synaptic plasticity were identified. The results provide further support to the available reports that antidepressant treatment affects intracellular pathways and also suggest new potential targets for future therapeutic intervention.

  13. Meta-analysis of gene-environment-wide association scans accounting for education level identifies additional loci for refractive error.

    PubMed

    Fan, Qiao; Verhoeven, Virginie J M; Wojciechowski, Robert; Barathi, Veluchamy A; Hysi, Pirro G; Guggenheim, Jeremy A; Höhn, René; Vitart, Veronique; Khawaja, Anthony P; Yamashiro, Kenji; Hosseini, S Mohsen; Lehtimäki, Terho; Lu, Yi; Haller, Toomas; Xie, Jing; Delcourt, Cécile; Pirastu, Mario; Wedenoja, Juho; Gharahkhani, Puya; Venturini, Cristina; Miyake, Masahiro; Hewitt, Alex W; Guo, Xiaobo; Mazur, Johanna; Huffman, Jenifer E; Williams, Katie M; Polasek, Ozren; Campbell, Harry; Rudan, Igor; Vatavuk, Zoran; Wilson, James F; Joshi, Peter K; McMahon, George; St Pourcain, Beate; Evans, David M; Simpson, Claire L; Schwantes-An, Tae-Hwi; Igo, Robert P; Mirshahi, Alireza; Cougnard-Gregoire, Audrey; Bellenguez, Céline; Blettner, Maria; Raitakari, Olli; Kähönen, Mika; Seppala, Ilkka; Zeller, Tanja; Meitinger, Thomas; Ried, Janina S; Gieger, Christian; Portas, Laura; van Leeuwen, Elisabeth M; Amin, Najaf; Uitterlinden, André G; Rivadeneira, Fernando; Hofman, Albert; Vingerling, Johannes R; Wang, Ya Xing; Wang, Xu; Tai-Hui Boh, Eileen; Ikram, M Kamran; Sabanayagam, Charumathi; Gupta, Preeti; Tan, Vincent; Zhou, Lei; Ho, Candice E H; Lim, Wan'e; Beuerman, Roger W; Siantar, Rosalynn; Tai, E-Shyong; Vithana, Eranga; Mihailov, Evelin; Khor, Chiea-Chuen; Hayward, Caroline; Luben, Robert N; Foster, Paul J; Klein, Barbara E K; Klein, Ronald; Wong, Hoi-Suen; Mitchell, Paul; Metspalu, Andres; Aung, Tin; Young, Terri L; He, Mingguang; Pärssinen, Olavi; van Duijn, Cornelia M; Jin Wang, Jie; Williams, Cathy; Jonas, Jost B; Teo, Yik-Ying; Mackey, David A; Oexle, Konrad; Yoshimura, Nagahisa; Paterson, Andrew D; Pfeiffer, Norbert; Wong, Tien-Yin; Baird, Paul N; Stambolian, Dwight; Wilson, Joan E Bailey; Cheng, Ching-Yu; Hammond, Christopher J; Klaver, Caroline C W; Saw, Seang-Mei; Rahi, Jugnoo S; Korobelnik, Jean-François; Kemp, John P; Timpson, Nicholas J; Smith, George Davey; Craig, Jamie E; Burdon, Kathryn P; Fogarty, Rhys D; Iyengar, Sudha K; Chew, Emily; Janmahasatian, Sarayut; Martin, Nicholas G; MacGregor, Stuart; Xu, Liang; Schache, Maria; Nangia, Vinay; Panda-Jonas, Songhomitra; Wright, Alan F; Fondran, Jeremy R; Lass, Jonathan H; Feng, Sheng; Zhao, Jing Hua; Khaw, Kay-Tee; Wareham, Nick J; Rantanen, Taina; Kaprio, Jaakko; Pang, Chi Pui; Chen, Li Jia; Tam, Pancy O; Jhanji, Vishal; Young, Alvin L; Döring, Angela; Raffel, Leslie J; Cotch, Mary-Frances; Li, Xiaohui; Yip, Shea Ping; Yap, Maurice K H; Biino, Ginevra; Vaccargiu, Simona; Fossarello, Maurizio; Fleck, Brian; Yazar, Seyhan; Tideman, Jan Willem L; Tedja, Milly; Deangelis, Margaret M; Morrison, Margaux; Farrer, Lindsay; Zhou, Xiangtian; Chen, Wei; Mizuki, Nobuhisa; Meguro, Akira; Mäkelä, Kari Matti

    2016-03-29

    Myopia is the most common human eye disorder and it results from complex genetic and environmental causes. The rapidly increasing prevalence of myopia poses a major public health challenge. Here, the CREAM consortium performs a joint meta-analysis to test single-nucleotide polymorphism (SNP) main effects and SNP × education interaction effects on refractive error in 40,036 adults from 25 studies of European ancestry and 10,315 adults from 9 studies of Asian ancestry. In European ancestry individuals, we identify six novel loci (FAM150B-ACP1, LINC00340, FBN1, DIS3L-MAP2K1, ARID2-SNAT1 and SLC14A2) associated with refractive error. In Asian populations, three genome-wide significant loci AREG, GABRR1 and PDE10A also exhibit strong interactions with education (P<8.5 × 10(-5)), whereas the interactions are less evident in Europeans. The discovery of these loci represents an important advance in understanding how gene and environment interactions contribute to the heterogeneity of myopia.

  14. Gene-environment interactions in the causation of neural tube defects: folate deficiency increases susceptibility conferred by loss of Pax3 function.

    PubMed

    Burren, Katie A; Savery, Dawn; Massa, Valentina; Kok, Robert M; Scott, John M; Blom, Henk J; Copp, Andrew J; Greene, Nicholas D E

    2008-12-01

    Risk of neural tube defects (NTDs) is determined by genetic and environmental factors, among which folate status appears to play a key role. However, the precise nature of the link between low folate status and NTDs is poorly understood, and it remains unclear how folic acid prevents NTDs. We investigated the effect of folate level on risk of NTDs in splotch (Sp(2)(H)) mice, which carry a mutation in Pax3. Dietary folate restriction results in reduced maternal blood folate, elevated plasma homocysteine and reduced embryonic folate content. Folate deficiency does not cause NTDs in wild-type mice, but causes a significant increase in cranial NTDs among Sp(2)(H) embryos, demonstrating a gene-environment interaction. Control treatments, in which intermediate levels of folate are supplied, suggest that NTD risk is related to embryonic folate concentration, not maternal blood folate concentration. Notably, the effect of folate deficiency appears more deleterious in female embryos than males, since defects are not prevented by exogenous folic acid. Folate-deficient embryos exhibit developmental delay and growth retardation. However, folate content normalized to protein content is appropriate for developmental stage, suggesting that folate availability places a tight limit on growth and development. Folate-deficient embryos also exhibit a reduced ratio of s-adenosylmethionine (SAM) to s-adenosylhomocysteine (SAH). This could indicate inhibition of the methylation cycle, but we did not detect any diminution in global DNA methylation, in contrast to embryos in which the methylation cycle was specifically inhibited. Hence, folate deficiency increases the risk of NTDs in genetically predisposed splotch embryos, probably via embryonic growth retardation.

  15. Synaptoproteomic Analysis of a Rat Gene-Environment Model of Depression Reveals Involvement of Energy Metabolism and Cellular Remodeling Pathways

    PubMed Central

    Failler, Marion; Corna, Stefano; Racagni, Giorgio; Mathé, Aleksander A.; Popoli, Maurizio

    2015-01-01

    Background: Major depression is a severe mental illness that causes heavy social and economic burdens worldwide. A number of studies have shown that interaction between individual genetic vulnerability and environmental risk factors, such as stress, is crucial in psychiatric pathophysiology. In particular, the experience of stressful events in childhood, such as neglect, abuse, or parental loss, was found to increase the risk for development of depression in adult life. Here, to reproduce the gene x environment interaction, we employed an animal model that combines genetic vulnerability with early-life stress. Methods: The Flinders Sensitive Line rats (FSL), a validated genetic animal model of depression, and the Flinders Resistant Line (FRL) rats, their controls, were subjected to a standard protocol of maternal separation (MS) from postnatal days 2 to 14. A basal comparison between the two lines for the outcome of the environmental manipulation was performed at postnatal day 73, when the rats were into adulthood. We carried out a global proteomic analysis of purified synaptic terminals (synaptosomes), in order to study a subcellular compartment enriched in proteins involved in synaptic function. Two-dimensional gel electrophoresis (2-DE), mass spectrometry, and bioinformatic analysis were used to analyze proteins and related functional networks that were modulated by genetic susceptibility (FSL vs. FRL) or by exposure to early-life stress (FRL + MS vs. FRL and FSL + MS vs. FSL). Results: We found that, at a synaptic level, mainly proteins and molecular pathways related to energy metabolism and cellular remodeling were dysregulated. Conclusions: The present results, in line with previous works, suggest that dysfunction of energy metabolism and cytoskeleton dynamics at a synaptic level could be features of stress-related pathologies, in particular major depression. PMID:25522407

  16. Gene-environment interaction for polymorphisms in ataxia telangiectasia-mutated gene and radiation exposure in carcinogenesis: results from two literature-based meta-analyses of 27120 participants

    PubMed Central

    Wu, Di; He, Hua; Wang, Mengmeng; Ge, Tingwen; Liu, Yudi; Tian, Huimin; Cui, Jiuwei; Jia, Lin; Wan, Ziqiang; Han, Fujun

    2016-01-01

    Purpose We conducted two meta-analyses of ATM genetic polymorphisms and cancer risk in individuals with or without radiation exposure to determine whether there was a joint effect between the ATM gene and radiation exposure in carcinogenesis. Results rs1801516, which was the only ATM polymorphism investigated by more than 3 studies of radiation exposure, was eligible for the present study. The meta-analysis of 23333 individuals without radiation exposure from 24 studies showed no association between the rs1801516 polymorphism and cancer risk, without heterogeneity across studies. The meta-analysis of 3787 individuals with radiation exposure from 6 studies showed a significant association between the rs1801516 polymorphism and a decreased cancer risk, with heterogeneity across studies. There was a borderline-significant difference between the ORs of the two meta-analyses (P = 0.066), and the difference was significant when only Caucasians were included (P = 0.011). Materials and methods Publications were identified by searching PubMed, EMBASE, Web of Science, and CNKI databases. Odds ratios (ORs) were calculated to estimate the association between ATM genetic polymorphisms and cancer risk. Tests of interaction were used to compare differences between the ORs of the two meta-analyses. Conclusions Our meta-analyses confirmed the presence of a gene-environment interaction between the rs1801516 polymorphism and radiation exposure in carcinogenesis, whereas no association was found between the rs1801516 polymorphism and cancer risk for individuals without radiation exposure. The heterogeneity observed in the meta-analysis of individuals with radiation exposure might be due to gene-ethnicity or gene-gene interactions. Further studies are needed to elucidate sources of the heterogeneity. PMID:27764772

  17. Gene-environment studies: any advantage over environmental studies?

    PubMed

    Bermejo, Justo Lorenzo; Hemminki, Kari

    2007-07-01

    Gene-environment studies have been motivated by the likely existence of prevalent low-risk genes that interact with common environmental exposures. The present study assessed the statistical advantage of the simultaneous consideration of genes and environment to investigate the effect of environmental risk factors on disease. In particular, we contemplated the possibility that several genes modulate the environmental effect. Environmental exposures, genotypes and phenotypes were simulated according to a wide range of parameter settings. Different models of gene-gene-environment interaction were considered. For each parameter combination, we estimated the probability of detecting the main environmental effect, the power to identify the gene-environment interaction and the frequency of environmentally affected individuals at which environmental and gene-environment studies show the same statistical power. The proportion of cases in the population attributable to the modeled risk factors was also calculated. Our data indicate that environmental exposures with weak effects may account for a significant proportion of the population prevalence of the disease. A general result was that, if the environmental effect was restricted to rare genotypes, the power to detect the gene-environment interaction was higher than the power to identify the main environmental effect. In other words, when few individuals contribute to the overall environmental effect, individual contributions are large and result in easily identifiable gene-environment interactions. Moreover, when multiple genes interacted with the environment, the statistical benefit of gene-environment studies was limited to those studies that included major contributors to the gene-environment interaction. The advantage of gene-environment over plain environmental studies also depends on the inheritance mode of the involved genes, on the study design and, to some extend, on the disease prevalence.

  18. Genes, Environment, and Human Behavior.

    ERIC Educational Resources Information Center

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

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

  19. Impact of variation in the BDNF gene on social stress sensitivity and the buffering impact of positive emotions: replication and extension of a gene-environment interaction.

    PubMed

    van Winkel, Mark; Peeters, Frenk; van Winkel, Ruud; Kenis, Gunter; Collip, Dina; Geschwind, Nicole; Jacobs, Nele; Derom, Catherine; Thiery, Evert; van Os, Jim; Myin-Germeys, Inez; Wichers, Marieke

    2014-06-01

    A previous study reported that social stress sensitivity is moderated by the brain-derived-neurotrophic-factor(Val66Met) (BDNF rs6265) genotype. Additionally, positive emotions partially neutralize this moderating effect. The current study aimed to: (i) replicate in a new independent sample of subjects with residual depressive symptoms the moderating effect of BDNF(Val66Met) genotype on social stress sensitivity, (ii) replicate the neutralizing impact of positive emotions, (iii) extend these analyses to other variations in the BDNF gene in the new independent sample and the original sample of non-depressed individuals. Previous findings were replicated in an experience sampling method (ESM) study. Negative Affect (NA) responses to social stress were stronger in "Val/Met" carriers of BDNF(Val66Met) compared to "Val/Val" carriers. Positive emotions neutralized the moderating effect of BDNF(Val66Met) genotype on social stress sensitivity in a dose-response fashion. Finally, two of four additional BDNF SNPs (rs11030101, rs2049046) showed similar moderating effects on social stress-sensitivity across both samples. The neutralizing effect of positive emotions on the moderating effects of these two additional SNPs was found in one sample. In conclusion, ESM has important advantages in gene-environment (GxE) research and may attribute to more consistent findings in future GxE research. This study shows how the impact of BDNF genetic variation on depressive symptoms may be explained by its impact on subtle daily life responses to social stress. Further, it shows that the generation of positive affect (PA) can buffer social stress sensitivity and partially undo the genetic susceptibility.

  20. Gene-Environment-Wide Association Studies: Emerging Approaches

    PubMed Central

    Thomas, Duncan

    2010-01-01

    Despite the yield of recent genome-wide association (GWA) studies, the identified variants explain only a small proportion of the heritability of most complex diseases. This unexplained heritability could be partly due to gene-environment (G×E) interactions or more complex pathways involving multiple genes and exposures. This article provides a tutorial on the available epidemiological designs and statistical analysis approaches for studying specific G×E interactions and choosing the most appropriate methods. I discuss the approaches that are being developed to study entire pathways and available techniques for mining interactions in GWA data. I also explore approaches to marrying hypothesis-driven pathway-based approaches with “agnostic” GWA studies. PMID:20212493

  1. [Gene-environment interaction for the HIF1-A 1772C>T polymorphisms and cigarette smoking increase susceptibility to abdominal aortic aneurysm].

    PubMed

    Strauss, Ewa; Waliszewski, Krzysztof; Oszkinis, Grzegorz; Staniszewski, Ryszard

    2012-01-01

    Pathological changes in the vascular vessels, such as the presence of atherosclerotic plaques or aneurysmal dilatations, are associated with the local conditions of ischemial/hypoxia. Polymorphisms in the HIF1A gene, encoding an oxygen-regulated HIF-1 subunit (HIF-1a), determine inter-individual variability in vascular response to hypoxia. Stimulation of selected pathways, related to this response (i.e. angiogenesis) is impaired by cigarette smoke exposure. In this work, we examined the associations between 1772C>T polymorphism (rs11549465) located in the coding region of HIF1A gene (Pro582-Ser), smoking and the occurrence of abdominal aortic aneurysm (AAA). Moreover, the relations of these factors with the presence of peripheral arterial disease (PAD) in patients with AAA were studied. The case-control study was designed, in which a group of 1060 Caucasian subjects: 535 AAA patients and 525 controls, was analyzed. Data regarding smoking status were collected using questionnaire. Past and current smokers were analyzed together. In the group of 220 AAA subjects the coexistence of PAD was characterized. HIF-1A genotypes were assessed by PCR-RFLP method. Genetic-environmental interactions were examined by a two-by-four tables. In these analyzes, logistic regression models were used to adjusting for the relevant covariates. The frequency of HIF1A 1772T allele in AAA group (0,067) was similar to that observed in the control group (0,070). In the analyses of genetic-environmental interactions was observed that the co-occurrence of HIF1A 1772CT and TT genotypes and exposure to tobacco smoke has a strong multiplicative effect on the susceptibility to the AAA development. The age and gender adjusted odds ratios (ORs) were: 7,6 for smoking alone (p<0,0001); 0,65 for 1772CT and TT genotypes alone (p=0,3) and 14,4for smoking plus 1772CT and TT genotypes (p<0,0001). The proportion of smokers carrying 1772T allele was higher among patients with advanced form of PAD (femoro

  2. The impact of exposure-biased sampling designs on detection of gene-environment interactions in case-control studies with potential exposure misclassification.

    PubMed

    Stenzel, Stephanie L; Ahn, Jaeil; Boonstra, Philip S; Gruber, Stephen B; Mukherjee, Bhramar

    2015-05-01

    With limited funding and biological specimen availability, choosing an optimal sampling design to maximize power for detecting gene-by-environment (G-E) interactions is critical. Exposure-enriched sampling is often used to select subjects with rare exposures for genotyping to enhance power for tests of G-E effects. However, exposure misclassification (MC) combined with biased sampling can affect characteristics of tests for G-E interaction and joint tests for marginal association and G-E interaction. Here, we characterize the impact of exposure-biased sampling under conditions of perfect exposure information and exposure MC on properties of several methods for conducting inference. We assess the Type I error, power, bias, and mean squared error properties of case-only, case-control, and empirical Bayes methods for testing/estimating G-E interaction and a joint test for marginal G (or E) effect and G-E interaction across three biased sampling schemes. Properties are evaluated via empirical simulation studies. With perfect exposure information, exposure-enriched sampling schemes enhance power as compared to random selection of subjects irrespective of exposure prevalence but yield bias in estimation of the G-E interaction and marginal E parameters. Exposure MC modifies the relative performance of sampling designs when compared to the case of perfect exposure information. Those conducting G-E interaction studies should be aware of exposure MC properties and the prevalence of exposure when choosing an ideal sampling scheme and method for characterizing G-E interactions and joint effects.

  3. The Dopamine Receptor D4 7-Repeat Allele and Prenatal Smoking in ADHD-Affected Children and Their Unaffected Siblings: No Gene-Environment Interaction

    ERIC Educational Resources Information Center

    Altink, Marieke E.; Arias-Vasquez, Alejandro; Franke, Barbara; Slaats-Willemse, Dorine I. E.; Buschgens, Cathelijne J. M.; Rommelse, Nanda N. J.; Fliers, Ellen A.; Anney, Richard; Brookes, Keeley-Joanne; Chen, Wai; Gill, Michael; Mulligan, Aisling; Sonuga-Barke, Edmund; Thompson, Margaret; Sergeant, Joseph A.; Faraone, Stephen V.; Asherson, Philip; Buitelaar, Jan K.

    2008-01-01

    Background: The dopamine receptor D4 ("DRD4") 7-repeat allele and maternal smoking during pregnancy are both considered as risk factors in the aetiology of attention deficit hyperactivity disorder (ADHD), but few studies have been conducted on their interactive effects in causing ADHD. The purpose of this study is to examine the gene by…

  4. Age at onset of psychotic disorder: cannabis, BDNF Val66Met, and sex-specific models of gene-environment interaction.

    PubMed

    Decoster, Jeroen; van Os, Jim; Kenis, Gunter; Henquet, Cecile; Peuskens, Joseph; De Hert, Marc; van Winkel, Ruud

    2011-04-01

    Discovering modifiable predictors for age at onset may help to identify predictors of transition to psychotic disorder in the "at-risk mental state." Inconsistent effects of sex, BDNF Val66Met (rs6265), and cannabis use on age of onset were previously reported. BDNF Val66Met and cannabis use before illness onset were retrospectively assessed in a sample of 585 patients with schizophrenia and their association with age at onset was evaluated. Cannabis use was significantly associated with earlier age at onset of psychotic disorder (AOP; average difference 2.7 years, P < 0.001), showing dose-response effects with higher frequency and earlier age at first use. There was a weak association between BDNF Val66Met genotype and AOP (difference 1.2 years; P = 0.050). No evidence was found for BDNF × cannabis interaction (interaction χ(2) (1) = 0.65, P = 0.420). However, a significant BDNF × cannabis × sex interaction was found (interaction χ(2) (1) = 4.99, P = 0.026). In female patients, cannabis use was associated with earlier AOP in BDNF Met-carriers (difference 7 years), but not in Val/Val-genotypes. In male patients, cannabis use was associated with earlier AOP irrespective of BDNF Val66Met genotype (difference 1.3 years). BDNF Val66Met genotype in the absence of cannabis use did not influence AOP, neither in female or male patients with psychotic disorder. Complex interactions between cannabis and BDNF may shape age at onset in female individuals at risk of psychotic disorder. No compelling evidence was found that BDNF genotype is associated with age at onset of psychotic disorder in the absence of cannabis use.

  5. Narrative review of genes, environment, and cigarettes.

    PubMed

    Do, Elizabeth; Maes, Hermine

    2016-08-01

    Tobacco use remains the leading cause of preventable death in the US, emphasizing the need to understand which genes and environments are involved in the establishment of cigarette use behaviors. However, to date, no comprehensive review of the influence of genes, the environment, and their interaction on cigarette use exists. This narrative review provides a description of gene variants and environmental factors associated with cigarette use, as well as an overview of studies investigating gene-environment interaction (GxE) in cigarette use. GxE studies of cigarette use have been useful in demonstrating that the influence of genes changes as a function of both the phenotype being measured and the environment. However, it is difficult to determine how the effect of genes contributing to different phenotypes of cigarette use changes as a function of the environment. This suggests the need for more studies of GxE, to parse out the effects of genes and the environment across the development of cigarette use phenotypes, which may help to inform potential prevention and intervention efforts aimed at reducing the prevalence of cigarette use. Key Messages No comprehensive reviews of the influence of genes, the environment, and their interaction on cigarette use exist currently. The influence of genes may change as a function of the environment and the phenotype being measured. It is difficult to determine how the effect of genes contributing to different phenotypes of cigarette use changes according to environmental context, suggesting the need for more studies of gene-environment interaction related to cigarette use to parse out effects.

  6. Gene-environment interactions affect long-term depression (LTD) through changes in dopamine receptor affinity in Snap25 deficient mice

    PubMed Central

    Baca, Michael; Allan, Andrea M.; Partridge, L. Donald; Wilson, Michael C.

    2013-01-01

    Genes and environmental conditions interact in the development of cognitive capacities and each plays an important role in neuropsychiatric disorders such as attention deficit/hyperactivity disorder (ADHD) and schizophrenia. Multiple studies have indicated that the gene for the SNARE protein SNAP-25 is a candidate susceptibility gene for ADHD, as well as schizophrenia, while maternal smoking is a candidate environmental risk factor for ADHD. We utilized mice heterozygous for a Snap25 null allele and deficient in SNAP-25 expression to model genetic effects in combination with prenatal exposure to nicotine to explore genetic and environmental interactions in synaptic plasticity and behavior. We show that SNAP-25 deficient mice exposed to prenatal nicotine exhibit hyperactivity and deficits in social interaction. Using a high frequency stimulus electrophysiological paradigm for long-term depression (LTD) induction, we examined the roles of dopaminergic D2 receptors (D2Rs) and cannabinoid CB1 receptors (CB1Rs), both critical for LTD induction in the striatum. We found that prenatal exposure to nicotine in Snap25 heterozygote null mice produced a deficit in the D2R-dependent induction of LTD, although CB1R regulation of plasticity was not impaired. We also show that prenatal nicotine exposure altered the affinity and/or receptor coupling of D2Rs, but not the number of these receptors in heterozygote null Snap25 mutants. These results refine the observations made in the coloboma mouse mutant, a proposed mouse model of ADHD, and illustrate how gene × environmental influences can interact to perturb neural functions that regulate behavior. PMID:23939223

  7. Current research trends in early life stress and depression: review of human studies on sensitive periods, gene-environment interactions, and epigenetics.

    PubMed

    Heim, Christine; Binder, Elisabeth B

    2012-01-01

    Early life stress, such as childhood abuse, neglect and loss, is a well established major risk factor for developing depressive disorders later in life. We here summarize and discuss current developments in human research regarding the link between early life stress and depression. Specifically, we review the evidence for the existence of sensitive periods for the adverse effects of early life stress in humans. We further review the current state of knowledge regarding gene×environment (G×E) interactions in the effects of early life stress. While multiple genes operate in multiple environments to induce risk for depression after early life stress, these same genes also seem to enhance the beneficial effects of a positive early environment. Also, we discuss the epigenetic mechanisms that might underlie these G×E interactions. Finally, we discuss the potential importance of identifying sensitive time periods of opportunity, as well as G×E interactions and epigenetic mechanisms, for early interventions that might prevent or reverse the detrimental outcomes of early life stress and its transmission across generations.

  8. Gene-environment interaction between DRD4 7-repeat VNTR and early child-care experiences predicts self-regulation abilities in prekindergarten.

    PubMed

    Berry, Daniel; McCartney, Kathleen; Petrill, Stephen; Deater-Deckard, Kirby; Blair, Clancy

    2014-04-01

    Intervention studies indicate that children's early child-care experiences can be leveraged to foster their development of effective self-regulation skills. It is less clear whether typical child-care experiences play a similar role. In addition, evidence suggests that children with a common variant of the DRD4 gene (48-bp VNTR, 7-repeat) may be more sensitive to their experiences than those without this variant. Using data from the NICHD Study of Early Child Care and Youth Development, we considered the degree to which children's early child-care experiences-quantity, quality, and type-were associated with their attention and self-regulation abilities in prekindergarten, and, in particular, whether these relations were conditional on DRD4 genotype. G × E interactions were evident across multiple neuropsychological and observational measures of children's attention and self-regulation abilities. Across most outcome measures, DRD4 7+ children spending fewer hours in child care showed more effective attention/self-regulation abilities. For those without a copy of the DRD4 7-repeat allele, such associations were typically null. The results for child-care quality and type indicated no interactions with genotype; the main-effect associations were somewhat inconsistent.

  9. CYP1A1 genetic polymorphism and polycyclic aromatic hydrocarbons on pulmonary function in the elderly: haplotype-based approach for gene-environment interaction.

    PubMed

    Choi, Yoon-Hyeong; Kim, Jin Hee; Hong, Yun-Chul

    2013-08-29

    Lung function may be impaired by environmental pollutants not only acting alone, but working with genetic factors as well. Few epidemiologic studies have been conducted to explore the interplay of polycyclic aromatic hydrocarbons (PAHs) exposure and genetic polymorphism on lung function in the elderly. For genetic polymorphism, haplotype is considered a more informative unit than single nucleotide polymorphism markers. Therefore, we examined the role of haplotype based-CYP1A1 polymorphism in the effect of PAHs exposure on lung function in 422 participants from a community-based panel of elderly adults in Seoul, Korea. Linear mixed effect models were fit to evaluate the association of PAH exposure markers (urinary 1-hydroxypyrene and 2-naphthol) with FVC, FEV₁, FEV₁/FVC, and FEF₂₅₋₇₅, and then the interaction with CYP1A1 haplotype constructed from three single nucleotide polymorphisms of the gene (rs4646421/rs4646422/rs1048943). Urinary 1-hydroxypyrene levels were inversely associated with FEV₁/FVC (p<0.05), whereas urinary 2-naphthol levels failed to show associations with lung function. Urinary 1-hydroxypyrene was significantly associated with decrease in FEV₁/FVC among participants with rs4646421 variants (CT+TT), rs4646422 wild-type (GG), and rs1048943 wild-type (AA). At least one TGA haplotype predicted a 0.88% (95% confidence interval, 0.31-1.45%) reduction in FEV₁/FVC with an interquartile range increase in 1-hydroxypyrene, whereas no relationship was observed in participants without TGA haplotype (p for interaction=0.045). Similar patterns were also observed in FEF₂₅₋₇₅. We did not find any main effects of CYP1A1 genetic polymorphisms on lung functions. Our findings suggest that PAH exposure producing 1-hydroxypyrene as a metabolite compromises lung function in the elderly, and that haplotype-based CYP1A1 polymorphism modifies the risk.

  10. 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

  11. Can genes play a role in explaining frequent job changes? An examination of gene-environment interaction from human capital theory.

    PubMed

    Chi, Wei; Li, Wen-Dong; Wang, Nan; Song, Zhaoli

    2016-07-01

    This study examined how a dopamine genetic marker, DRD4 7 Repeat allele, interacted with early life environmental factors (i.e., family socioeconomic status, and neighborhood poverty) to influence job change frequency in adulthood using a national representative sample from the United States. The dopamine gene played a moderating role in the relationship between early life environments and later job change behaviors, which was meditated through educational achievement. In particular, higher family socioeconomic status was associated with higher educational achievement, and thereafter higher frequency of voluntary job changes and lower frequency of involuntary job changes; such relationships were stronger (i.e., more positive or negative) for individuals with more DRD4 7R alleles. In contrast, higher neighborhood poverty was associated with lower educational achievement, and thereafter lower frequency of voluntary job change and higher frequency of involuntary job change; such relationships were again stronger (i.e., more positive or negative) for individuals with more DRD4 7R alleles. The results demonstrated that molecular genetics using DNA information, along with early life environmental factors, can bring new insights to enhance our understanding of job change frequency in individuals' early career development. (PsycINFO Database Record

  12. Witnessing Substance Use and Same-Day Antisocial Behavior among At-Risk Adolescents: Gene-Environment Interaction in a 30-Day Ecological Momentary Assessment Study

    PubMed Central

    Russell, Michael A.; Wang, Lin; Odgers, Candice L.

    2017-01-01

    Many young adolescents are embedded in neighborhoods, schools, and homes where alcohol and drugs are frequently used. However, little is known about (a) how witnessing others’ substance use affects adolescents in their daily lives and (b) which adolescents will be most affected. The current study used ecological momentary assessment with 151 young adolescents (ages 11–15) to examine the daily association between witnessing substance use and antisocial behavior across 38 consecutive days. Results from multilevel logistic regression models indicated that adolescents were more likely to engage in antisocial behavior on days when they witnessed others using substances—an association that held both when substance use was witnessed inside the home as well as outside the home (e.g., at school or in their neighborhoods). A significant gene-by-environment interaction suggested that the same-day association between witnessing substance use and antisocial behavior was significantly stronger among adolescents with, versus without, with the DRD4-7R allele. The implications of our findings for theory and research related to adolescent antisocial behavior are discussed. PMID:26648004

  13. Nature, nurture and neurology: gene-environment interactions in neurodegenerative disease. FEBS Anniversary Prize Lecture delivered on 27 June 2004 at the 29th FEBS Congress in Warsaw.

    PubMed

    Spires, Tara L; Hannan, Anthony J

    2005-05-01

    Neurodegenerative disorders, such as Huntington's, Alzheimer's, and Parkinson's diseases, affect millions of people worldwide and currently there are few effective treatments and no cures for these diseases. Transgenic mice expressing human transgenes for huntingtin, amyloid precursor protein, and other genes associated with familial forms of neurodegenerative disease in humans provide remarkable tools for studying neurodegeneration because they mimic many of the pathological and behavioural features of the human conditions. One of the recurring themes revealed by these various transgenic models is that different diseases may share similar molecular and cellular mechanisms of pathogenesis. Cellular mechanisms known to be disrupted at early stages in multiple neurodegenerative disorders include gene expression, protein interactions (manifesting as pathological protein aggregation and disrupted signaling), synaptic function and plasticity. Recent work in mouse models of Huntington's disease has shown that enriching the environment of transgenic animals delays the onset and slows the progression of Huntington's disease-associated motor and cognitive symptoms. Environmental enrichment is known to induce various molecular and cellular changes in specific brain regions of wild-type animals, including altered gene expression profiles, enhanced neurogenesis and synaptic plasticity. The promising effects of environmental stimulation, demonstrated recently in models of neurodegenerative disease, suggest that therapy based on the principles of environmental enrichment might benefit disease sufferers and provide insight into possible mechanisms of neurodegeneration and subsequent identification of novel therapeutic targets. Here, we review the studies of environmental enrichment relevant to some major neurodegenerative diseases and discuss their research and clinical implications.

  14. Invited commentary: genes, environment, and hybrid vigor.

    PubMed

    Gwinn, Marta; Guessous, Idris; Khoury, Muin J

    2009-09-15

    In the 1950s, case-control studies of smoking and lung cancer established a paradigm for epidemiologic studies of risk factors for chronic diseases. Since then, thousands of case-control studies have examined possible associations of countless risk factors with numerous diseases, rarely finding associations as strong or consistent as that of smoking with lung cancer. Recently, researchers have applied advances in molecular genetics to conduct candidate gene and genome-wide association studies of lung cancer. Skeptics among both epidemiologists and geneticists have argued that genomic research adds little value when most cases of disease can be attributed to a preventable exposure; however, well-conducted studies of gene-environment interactions that draw on data from more than 50 years of research in toxicology, pathophysiology, and behavioral science offer important models for the development of more comprehensive approaches to understanding the etiology of chronic diseases.

  15. Gene-environment interactions in the pre-Industrial Era: the cancer of King Ferrante I of Aragon (1431-1494).

    PubMed

    Ottini, Laura; Falchetti, Mario; Marinozzi, Silvia; Angeletti, Luciana Rita; Fornaciari, Gino

    2011-03-01

    King Ferrante I of Aragon, leading figure of the Italian Renaissance, died in 1494. The autopsy of his mummy revealed a tumor infiltrating the small pelvis. We examined the histologic and molecular features of this ancient tumor to investigate its primary origin. Hematoxylin-eosin, Van Gieson, and Alcian Blue staining showed neoplastic cells infiltrating muscular fibers and forming pseudo-glandular lumina disseminated in fibrous stroma with scarce mucus. A strong immunoreactivity of the neoplastic cells was shown for pancytokeratins and proliferating cell nuclear antigen. Molecular fingerprints were investigated by examining K-ras, BRAF, and microsatellite instability in ancient tumor DNA. Sequencing analysis showed G-to-A transition in codon 12 of K-ras. BRAF mutations and microsatellite instability were not observed. Because the presence of K-ras codon 12 mutation could be associated with exposure to chemical carcinogens, possibly present in some food items, paleodietary reconstruction of the King Ferrante I was carried out by carbon (δ(13)C ) and nitrogen (δ(15)N) stable isotopes analysis. δ(13)C and δ(15)N values found in bone collagen of the King were consistent with a massive intake of animal proteins. Overall, our data show that the tumor of Ferrante I was a mucinous adenocarcinoma with molecular fingerprints characteristic of colorectal carcinogenesis linked to K-ras pathway. Paleodietary reconstruction and historical chronicles indicate a strong consumption of meat by the King. The possible abundance of dietary carcinogens, related to meat consumption, could explain the K-ras mutation causing the colorectal tumor that killed Ferrante I more than 5 centuries ago.

  16. Replication of a gene-environment interaction Via Multimodel inference: additive-genetic variance in adolescents' general cognitive ability increases with family-of-origin socioeconomic status.

    PubMed

    Kirkpatrick, Robert M; McGue, Matt; Iacono, William G

    2015-03-01

    The present study of general cognitive ability attempts to replicate and extend previous investigations of a biometric moderator, family-of-origin socioeconomic status (SES), in a sample of 2,494 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings assessed with individually administered IQ tests. We hypothesized that SES would covary positively with additive-genetic variance and negatively with shared-environmental variance. Important potential confounds unaddressed in some past studies, such as twin-specific effects, assortative mating, and differential heritability by trait level, were found to be negligible. In our main analysis, we compared models by their sample-size corrected AIC, and base our statistical inference on model-averaged point estimates and standard errors. Additive-genetic variance increased with SES-an effect that was statistically significant and robust to model specification. We found no evidence that SES moderated shared-environmental influence. We attempt to explain the inconsistent replication record of these effects, and provide suggestions for future research.

  17. Replication of a Gene-Environment Interaction via Multimodel Inference: Additive-Genetic Variance in Adolescents’ General Cognitive Ability Increases with Family-of-Origin Socioeconomic Status

    PubMed Central

    Kirkpatrick, Robert M.; McGue, Matt; Iacono, William G.

    2015-01-01

    The present study of general cognitive ability attempts to replicate and extend previous investigations of a biometric moderator, family-of-origin socioeconomic status (SES), in a sample of 2,494 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings assessed with individually administered IQ tests. We hypothesized that SES would covary positively with additive-genetic variance and negatively with shared-environmental variance. Important potential confounds unaddressed in some past studies, such as twin-specific effects, assortative mating, and differential heritability by trait level, were found to be negligible. In our main analysis, we compared models by their sample-size corrected AIC, and base our statistical inference on model-averaged point estimates and standard errors. Additive-genetic variance increased with SES—an effect that was statistically significant and robust to model specification. We found no evidence that SES moderated shared-environmental influence. We attempt to explain the inconsistent replication record of these effects, and provide suggestions for future research. PMID:25539975

  18. Gene-Environment Interplay between Peer Rejection and Depressive Behavior in Children

    ERIC Educational Resources Information Center

    Brendgen, Mara; Vitaro, Frank; Boivin, Michel; Girard, Alain; Bukowski, William M.; Dionne, Ginette; Tremblay, Richard E.; Perusse, Daniel

    2009-01-01

    Background: Genetic risk for depressive behavior may increase the likelihood of exposure to environmental stressors (gene-environment correlation, rGE). By the same token, exposure to environmental stressors may moderate the effect of genes on depressive behavior (gene-environment interaction, GxE). Relating these processes to a peer-related…

  19. 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…

  20. Gene-Environment Processes Linking Aggression, Peer Victimization, and the Teacher-Child Relationship

    ERIC Educational Resources Information Center

    Brendgen, Mara; Boivin, Michel; Dionne, Ginette; Barker, Edward D.; Vitaro, Frank; Girard, Alain; Tremblay, Richard; Perusse, Daniel

    2011-01-01

    Aggressive behavior in middle childhood is at least partly explained by genetic factors. Nevertheless, estimations of simple effects ignore possible gene-environment interactions (G x E) or gene-environment correlations (rGE) in the etiology of aggression. The present study aimed to simultaneously test for G x E and rGE processes between…

  1. Gene-environment interplay between cannabis and psychosis.

    PubMed

    Henquet, Cécile; Di Forti, Marta; Morrison, Paul; Kuepper, Rebecca; Murray, Robin M

    2008-11-01

    Cannabis use is considered a contributory cause of schizophrenia and psychotic illness. However, only a small proportion of cannabis users develop psychosis. This can partly be explained by the amount and duration of the consumption of cannabis and by its strength but also by the age at which individuals are first exposed to cannabis. Genetic factors, in particular, are likely to play a role in the short- and the long-term effects cannabis may have on psychosis outcome. This review will therefore consider the interplay between genes and exposure to cannabis in the development of psychotic symptoms and schizophrenia. Studies using genetic, epidemiological, experimental, and observational techniques will be discussed to investigate gene-environment correlation gene-environment interaction, and higher order interactions within the cannabis-psychosis association. Evidence suggests that mechanisms of gene-environment interaction are likely to underlie the association between cannabis and psychosis. In this respect, multiple variations within multiple genes--rather than single genetic polymorphisms--together with other environmental factors (eg, stress) may interact with cannabis to increase the risk of psychosis. Further research on these higher order interactions is needed to better understand the biological pathway by which cannabis use, in some individuals, may cause psychosis in the short- and long term.

  2. Community-Based Participatory Research and Gene-Environment Interaction Methodologies Addressing Environmental Justice among Migrant and Seasonal Farmworker Women and Children in Texas: “From Mother to Child Project”

    PubMed Central

    Hernández-Valero, María A.; Herrera, Angelica P.; Zahm, Sheila H.; Jones, Lovell A.

    2013-01-01

    The “From Mother to Child Project” is a molecular epidemiological study that employs a community- based participatory research (CBPR) approach and gene-environment interaction research to address environmental justice in migrant and seasonal farmworker (MSF) women and children of Mexican origin home-based in Baytown and La Joya, Texas. This paper presents the background and rationale for the study and describes the study design and methodology. Preliminary data showed that MSF women and children in Texas have measurable levels of pesticides in their blood and urine, some of which were banned in the United States decades ago and are possible human carcinogens. Polymorphisms in genes involved in chemical detoxification and DNA repair have been associated with susceptibility to genetic damage and cancer development in populations exposed to environmental toxins. The “From Mother to Child Project” is testing three hypotheses: (1) MSF women and children who are occupationally exposed to pesticides are at higher risk for DNA damage than are non-exposed women and children. (2) Both, the extent of pesticide exposure and type of polymorphisms in chemical detoxification and DNA repair genes contribute to the extent of DNA damage observed in study participants. (3) The mutagenic potency levels measured in the organic compounds extracted from the urine and serum of study participants will correlate with the total concentrations of pesticides and with the measured DNA damage in study participants. The study will enroll 800 participants: 200 MSF mother-child pairs; 200 children (one per family) whose parents have never worked in agriculture, matched with the MSF children by ethnicity, age ± 2 years, gender, and city of residence; and these children’s mothers. Personal interviews with the mothers are used to gather data for both mothers and children on sociodemographic characteristics; pesticide exposure at work and home; medical and reproductive history; dietary

  3. 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.

  4. PIA: ISOPHOT Interactive Analysis

    NASA Astrophysics Data System (ADS)

    Gabriel, Carlos; Acosta, Jose; Heinrichsen, Ingolf; Skaley, Detlef; Tai, Wai Ming; Morris, Huw; Merluzzi, Paola

    2014-08-01

    ISOPHOT is one of the instruments on board the Infrared Space Observatory (ISO). ISOPHOT Interactive Analysis (PIA) is a scientific and calibration interactive data analysis tool for ISOPHOT data reduction. Written in IDL under Xwindows, PIA offers a full context sensitive graphical interface for retrieving, accessing and analyzing ISOPHOT data. It is available in two nearly identical versions; a general observers version omits the calibration sequences.

  5. 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…

  6. Genes, environments, and developmental research: methods for a multi-site study of early substance abuse.

    PubMed

    Costello, E Jane; Eaves, Lindon; Sullivan, Patrick; Kennedy, Martin; Conway, Kevin; Adkins, Daniel E; Angold, A; Clark, Shaunna L; Erkanli, Alaattin; McClay, Joseph L; Copeland, William; Maes, Hermine H; Liu, Youfang; Patkar, Ashwin A; Silberg, Judy; van den Oord, Edwin

    2013-04-01

    The importance of including developmental and environmental measures in genetic studies of human pathology is widely acknowledged, but few empirical studies have been published. Barriers include the need for longitudinal studies that cover relevant developmental stages and for samples large enough to deal with the challenge of testing gene-environment-development interaction. A solution to some of these problems is to bring together existing data sets that have the necessary characteristics. As part of the National Institute on Drug Abuse-funded Gene-Environment-Development Initiative, our goal is to identify exactly which genes, which environments, and which developmental transitions together predict the development of drug use and misuse. Four data sets were used of which common characteristics include (1) general population samples, including males and females; (2) repeated measures across adolescence and young adulthood; (3) assessment of nicotine, alcohol, and cannabis use and addiction; (4) measures of family and environmental risk; and (5) consent for genotyping DNA from blood or saliva. After quality controls, 2,962 individuals provided over 15,000 total observations. In the first gene-environment analyses, of alcohol misuse and stressful life events, some significant gene-environment and gene-development effects were identified. We conclude that in some circumstances, already collected data sets can be combined for gene-environment and gene-development analyses. This greatly reduces the cost and time needed for this type of research. However, care must be taken to ensure careful matching across studies and variables.

  7. Genes, environments, and developmental GEWIS: Methods for a multi-site study of early substance abuse

    PubMed Central

    Costello, E. J.; Eaves, Lindon; Sullivan, Patrick; Kennedy, Martin; Conway, Kevin; Adkins, Daniel E.; Angold, A.; Clark, Shaunna L; Erkanli, Alaattin; McClay, Joseph L; Copeland, William; Maes, Hermine H.; Liu, Youfang; Patkar, Ashwin A.; Silberg, Judy; van den Oord, Edwin

    2013-01-01

    The importance of including developmental and environmental measures in genetic studies of human pathology is widely acknowledged, but few empirical studies have been published. Barriers include the need for longitudinal studies that cover relevant developmental stages and for samples large enough to deal with the challenge of testing gene-environment-development interaction. A solution to some of these problems is to bring together existing data sets that have the necessary characteristics. As part of the NIDA-funded Gene-Environment-Development Initiative (GEDI) our goal is to identify exactly which genes, which environments, and which developmental transitions together predict the development of drug use and misuse. Four data sets were used whose common characteristics include (1) general population samples including males and females; (2) repeated measures across adolescence and young adulthood; (3) assessment of nicotine, alcohol and cannabis use and addiction; (4) measures of family and environmental risk; and (5) consent for genotyping DNA from blood or saliva. After quality controls, 2,962 individuals provided over 15,000 total observations. In the first gene-environment analyses, of alcohol misuse and stressful life events, some significant gene-environment and gene-development effects were identified. We conclude that in some circumstances, already-collected data sets can be combined for gene-environment and gene-development analyses. This greatly reduces the cost and time needed for this type of research. However, care must be taken to ensure careful matching across studies and variables. PMID:23461817

  8. 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…

  9. When Chocolate Seeking Becomes Compulsion: Gene-Environment Interplay

    PubMed Central

    Patella, Loris; Andolina, Diego; Valzania, Alessandro; Latagliata, Emanuele Claudio; Felsani, Armando; Pompili, Assunta; Gasbarri, Antonella; Puglisi-Allegra, Stefano; Ventura, Rossella

    2015-01-01

    Background Eating disorders appear to be caused by a complex interaction between environmental and genetic factors, and compulsive eating in response to adverse circumstances characterizes many eating disorders. Materials and Methods We compared compulsion-like eating in the form of conditioned suppression of palatable food-seeking in adverse situations in stressed C57BL/6J and DBA/2J mice, two well-characterized inbred strains, to determine the influence of gene-environment interplay on this behavioral phenotype. Moreover, we tested the hypothesis that low accumbal D2 receptor (R) availability is a genetic risk factor of food compulsion-like behavior and that environmental conditions that induce compulsive eating alter D2R expression in the striatum. To this end, we measured D1R and D2R expression in the striatum and D1R, D2R and α1R levels in the medial prefrontal cortex, respectively, by western blot. Results Exposure to environmental conditions induces compulsion-like eating behavior, depending on genetic background. This behavioral pattern is linked to decreased availability of accumbal D2R. Moreover, exposure to certain environmental conditions upregulates D2R and downregulates α1R in the striatum and medial prefrontal cortex, respectively, of compulsive animals. These findings confirm the function of gene-environment interplay in the manifestation of compulsive eating and support the hypothesis that low accumbal D2R availability is a “constitutive” genetic risk factor for compulsion-like eating behavior. Finally, D2R upregulation and α1R downregulation in the striatum and medial prefrontal cortex, respectively, are potential neuroadaptive responses that parallel the shift from motivated to compulsive eating. PMID:25781028

  10. 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

  11. INCA- INTERACTIVE CONTROLS ANALYSIS

    NASA Technical Reports Server (NTRS)

    Bauer, F. H.

    1994-01-01

    The Interactive Controls Analysis (INCA) program was developed to provide a user friendly environment for the design and analysis of linear control systems, primarily feedback control systems. INCA is designed for use with both small and large order systems. Using the interactive graphics capability, the INCA user can quickly plot a root locus, frequency response, or time response of either a continuous time system or a sampled data system. The system configuration and parameters can be easily changed, allowing the INCA user to design compensation networks and perform sensitivity analysis in a very convenient manner. A journal file capability is included. This stores an entire sequence of commands, generated during an INCA session into a file which can be accessed later. Also included in INCA are a context-sensitive help library, a screen editor, and plot windows. INCA is robust to VAX-specific overflow problems. The transfer function is the basic unit of INCA. Transfer functions are automatically saved and are available to the INCA user at any time. A powerful, user friendly transfer function manipulation and editing capability is built into the INCA program. The user can do all transfer function manipulations and plotting without leaving INCA, although provisions are made to input transfer functions from data files. By using a small set of commands, the user may compute and edit transfer functions, and then examine these functions by using the ROOT_LOCUS, FREQUENCY_RESPONSE, and TIME_RESPONSE capabilities. Basic input data, including gains, are handled as single-input single-output transfer functions. These functions can be developed using the function editor or by using FORTRAN- like arithmetic expressions. In addition to the arithmetic functions, special functions are available to 1) compute step, ramp, and sinusoid functions, 2) compute closed loop transfer functions, 3) convert from S plane to Z plane with optional advanced Z transform, and 4) convert from Z

  12. Gene-environment interplay in Drosophila melanogaster: chronic nutritional deprivation in larval life affects adult fecal output.

    PubMed

    Urquhart-Cronish, Mackenzie; Sokolowski, Marla B

    2014-10-01

    Life history consequences of stress in early life are varied and known to have lasting impacts on the fitness of an organism. Gene-environment interactions play a large role in how phenotypic differences are mediated by stressful conditions during development. Here we use natural allelic 'rover/sitter' variants of the foraging (for) gene and chronic early life nutrient deprivation to investigate gene-environment interactions on excretion phenotypes. Excretion assay analysis and a fully factorial nutritional regimen encompassing the larval and adult life cycle of Drosophila melanogaster were used to assess the effects of larval and adult nutritional stress on adult excretion phenotypes. Natural allelic variants of for exhibited differences in the number of fecal spots when they were nutritionally deprived as larvae and well fed as adults. for mediates the excretion response to chronic early-life nutritional stress in mated female, virgin female, and male rovers and sitters. Transgenic manipulations of for in a sitter genetic background under larval but not adult food deprivation increases the number of fecal spots. Our study shows that food deprivation early in life affects adult excretion phenotypes and these excretion differences are mediated by for.

  13. 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…

  14. Gene-Environment Interplay in Internalizing Disorders: Consistent Findings across Six Environmental Risk Factors

    ERIC Educational Resources Information Center

    Hicks, Brian M.; Dirago, Ana C.; Iacono, William G.; McGue, Matt

    2009-01-01

    Background: Behavior genetic methods can help to elucidate gene-environment (G-E) interplay in the development of internalizing (INT) disorders (i.e., major depression and anxiety disorders). To date, however, no study has conducted a comprehensive analysis examining multiple environmental risk factors with the purpose of delineating general…

  15. Interactive Controls Analysis (INCA)

    NASA Technical Reports Server (NTRS)

    Bauer, Frank H.

    1989-01-01

    Version 3.12 of INCA provides user-friendly environment for design and analysis of linear control systems. System configuration and parameters easily adjusted, enabling INCA user to create compensation networks and perform sensitivity analysis in convenient manner. Full complement of graphical routines makes output easy to understand. Written in Pascal and FORTRAN.

  16. Research in interactive scene analysis

    NASA Technical Reports Server (NTRS)

    Tenenbaum, J. M.; Barrow, H. G.; Weyl, S. A.

    1976-01-01

    Cooperative (man-machine) scene analysis techniques were developed whereby humans can provide a computer with guidance when completely automated processing is infeasible. An interactive approach promises significant near-term payoffs in analyzing various types of high volume satellite imagery, as well as vehicle-based imagery used in robot planetary exploration. This report summarizes the work accomplished over the duration of the project and describes in detail three major accomplishments: (1) the interactive design of texture classifiers; (2) a new approach for integrating the segmentation and interpretation phases of scene analysis; and (3) the application of interactive scene analysis techniques to cartography.

  17. Integrating nutrigenomics data to identify cardiometabolic gene-environment interactions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Nutrition is a key factor in health and in many age-related diseases. This is particularly the case for cardiometabolic diseases such as cardiovascular disease, type 2 diabetes and hypertension, and is often precluded by obesity, glucose impairment and metabolic syndrome. Our research objectives are...

  18. Interactive Astronomical Data Analysis Facility

    NASA Technical Reports Server (NTRS)

    Klinglesmith, D. A., III

    1980-01-01

    A description is given of the Interactive Astronomical Data Analysis Facility (IADAF) which performs interactive analysis of astronomical data for resident and visiting scientists. The facilities include a Grant measuring engine, a PDS 1010A microdensitometer, a COMTAL image display system and a PDP 11/40 computer system. Both hardware and software systems are examined, including a description of thirteen overlay programs. Some uses of the IADAF are indicated.

  19. Interactive Image Analysis System Design,

    DTIC Science & Technology

    1982-12-01

    This report describes a design for an interactive image analysis system (IIAS), which implements terrain data extraction techniques. The design... analysis system. Additionally, the system is fully capable of supporting many generic types of image analysis and data processing, and is modularly...employs commercially available, state of the art minicomputers and image display devices with proven software to achieve a cost effective, reliable image

  20. The Gene, Environment Association Studies consortium (GENEVA): maximizing the knowledge obtained from GWAS by collaboration across studies of multiple conditions.

    PubMed

    Cornelis, Marilyn C; Agrawal, Arpana; Cole, John W; Hansel, Nadia N; Barnes, Kathleen C; Beaty, Terri H; Bennett, Siiri N; Bierut, Laura J; Boerwinkle, Eric; Doheny, Kimberly F; Feenstra, Bjarke; Feingold, Eleanor; Fornage, Myriam; Haiman, Christopher A; Harris, Emily L; Hayes, M Geoffrey; Heit, John A; Hu, Frank B; Kang, Jae H; Laurie, Cathy C; Ling, Hua; Manolio, Teri A; Marazita, Mary L; Mathias, Rasika A; Mirel, Daniel B; Paschall, Justin; Pasquale, Louis R; Pugh, Elizabeth W; Rice, John P; Udren, Jenna; van Dam, Rob M; Wang, Xiaojing; Wiggs, Janey L; Williams, Kayleen; Yu, Kai

    2010-05-01

    Genome-wide association studies (GWAS) have emerged as powerful means for identifying genetic loci related to complex diseases. However, the role of environment and its potential to interact with key loci has not been adequately addressed in most GWAS. Networks of collaborative studies involving different study populations and multiple phenotypes provide a powerful approach for addressing the challenges in analysis and interpretation shared across studies. The Gene, Environment Association Studies (GENEVA) consortium was initiated to: identify genetic variants related to complex diseases; identify variations in gene-trait associations related to environmental exposures; and ensure rapid sharing of data through the database of Genotypes and Phenotypes. GENEVA consists of several academic institutions, including a coordinating center, two genotyping centers and 14 independently designed studies of various phenotypes, as well as several Institutes and Centers of the National Institutes of Health led by the National Human Genome Research Institute. Minimum detectable effect sizes include relative risks ranging from 1.24 to 1.57 and proportions of variance explained ranging from 0.0097 to 0.02. Given the large number of research participants (N>80,000), an important feature of GENEVA is harmonization of common variables, which allow analyses of additional traits. Environmental exposure information available from most studies also enables testing of gene-environment interactions. Facilitated by its sizeable infrastructure for promoting collaboration, GENEVA has established a unified framework for genotyping, data quality control, analysis and interpretation. By maximizing knowledge obtained through collaborative GWAS incorporating environmental exposure information, GENEVA aims to enhance our understanding of disease etiology, potentially identifying opportunities for intervention.

  1. Microcomputer Applications in Interaction Analysis.

    ERIC Educational Resources Information Center

    Wadham, Rex A.

    The Timed Interval Categorical Observation Recorder (TICOR), a portable, battery powered microcomputer designed to automate the collection of sequential and simultaneous behavioral observations and their associated durations, was developed to overcome problems in gathering subtle interaction analysis data characterized by sequential flow of…

  2. Gene-Environment Interplay, Family Relationships, and Child Adjustment

    ERIC Educational Resources Information Center

    Horwitz, Briana N.; Neiderhiser, Jenae M.

    2011-01-01

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

  3. Gene-environment correlations in the stress-depression relationship.

    PubMed

    Schnittker, Jason

    2010-09-01

    A critical feature of the social stress model is the apparent relationship between stress and depression. Although many studies have demonstrated a connection between the two, the relationship may be contaminated by genes affecting both stress and depression. Using a sample of identical and fraternal twins, this study explores genetic influences on depression and assorted sources of stress while explicitly estimating, and thereby controlling for, gene-environment correlations. I consider both stress and depression in a fine-grained fashion. For the former, the study explores assorted sources of stress, including health and disability, family, unemployment, discrimination, and perceived neighborhood safety, as gene-environment correlations may be stronger for some forms of stress than others. For the latter, the study explores both depressive symptoms and major depressive disorders, as each may entail a different epidemiological process, especially with respect to genes. The results reveal that most, but not all, measures of stress have moderate heritabilities, suggesting that genes influence exposure to the environment in a broad fashion. Yet, despite this, the relationship between stress and depression is generally robust to gene-environment correlations. There are some notable exceptions. For example, allowing for gene-environment correlations, marital conflict is generally unrelated to depression. Moreover, gene-environment correlations are generally stronger for major depression than for depressive symptoms, encouraging further elaboration of the distinction between the onset of depression and its recurrence, especially in the context of genes. These exceptions do not put limits on environmental influence, but do suggest that genes operate in a complex life-course fashion.

  4. Kernel Approach for Modeling Interaction Effects in Genetic Association Studies of Complex Quantitative Traits

    PubMed Central

    Broadaway, K. Alaine; Duncan, Richard; Conneely, Karen N.; Almli, Lynn M.; Bradley, Bekh; Ressler, Kerry J.; Epstein, Michael P.

    2015-01-01

    The etiology of complex traits likely involves the effects of genetic and environmental factors, along with complicated interaction effects between them. Consequently, there has been interest in applying genetic association tests of complex traits that account for potential modification of the genetic effect in the presence of an environmental factor. One can perform such an analysis using a joint test of gene and gene-environment interaction. An optimal joint test would be one that remains powerful under a variety of models ranging from those of strong gene-environment interaction effect to those of little or no gene-environment interaction effect. To fill this demand, we have extended a kernel-machine based approach for association mapping of multiple SNPs to consider joint tests of gene and gene-environment interaction. The kernel-based approach for joint testing is promising, since it incorporates linkage disequilibrium information from multiple SNPs simultaneously in analysis and permits flexible modeling of interaction effects. Using simulated data, we show that our kernel-machine approach typically outperforms the traditional joint test under strong gene-environment interaction models and further outperforms the traditional main-effect association test under models of weak or no gene-environment interaction effects. We illustrate our test using genome-wide association data from the Grady Trauma Project, a cohort of highly traumatized, at-risk individuals, which has previously been investigated for interaction effects. PMID:25885490

  5. Gene-environment interplay in attention-deficit hyperactivity disorder and the importance of a developmental perspective.

    PubMed

    Thapar, Anita; Langley, Kate; Asherson, Philip; Gill, Michael

    2007-01-01

    Attention-deficit hyperactivity disorder (ADHD) varies in its clinical presentation and course. Susceptibility gene variants for ADHD and associated antisocial behaviour are being identified with emerging evidence of gene-environment interaction. Genes and environmental factors that influence the origins of disorder are not necessarily the same as those that contribute to its course and outcome.

  6. Research in interactive scene analysis

    NASA Technical Reports Server (NTRS)

    Tenenbaum, J. M.; Garvey, T. D.; Weyl, S. A.; Wolf, H. C.

    1975-01-01

    An interactive scene interpretation system (ISIS) was developed as a tool for constructing and experimenting with man-machine and automatic scene analysis methods tailored for particular image domains. A recently developed region analysis subsystem based on the paradigm of Brice and Fennema is described. Using this subsystem a series of experiments was conducted to determine good criteria for initially partitioning a scene into atomic regions and for merging these regions into a final partition of the scene along object boundaries. Semantic (problem-dependent) knowledge is essential for complete, correct partitions of complex real-world scenes. An interactive approach to semantic scene segmentation was developed and demonstrated on both landscape and indoor scenes. This approach provides a reasonable methodology for segmenting scenes that cannot be processed completely automatically, and is a promising basis for a future automatic system. A program is described that can automatically generate strategies for finding specific objects in a scene based on manually designated pictorial examples.

  7. Interactive cutting path analysis programs

    NASA Technical Reports Server (NTRS)

    Weiner, J. M.; Williams, D. S.; Colley, S. R.

    1975-01-01

    The operation of numerically controlled machine tools is interactively simulated. Four programs were developed to graphically display the cutting paths for a Monarch lathe, Cintimatic mill, Strippit sheet metal punch, and the wiring path for a Standard wire wrap machine. These programs are run on a IMLAC PDS-ID graphic display system under the DOS-3 disk operating system. The cutting path analysis programs accept input via both paper tape and disk file.

  8. A gene-environment study of the paraoxonase 1 gene and pesticides in amyotrophic lateral sclerosis.

    PubMed

    Morahan, Julia M; Yu, Bing; Trent, Ronald J; Pamphlett, Roger

    2007-05-01

    Sporadic amyotrophic lateral sclerosis (SALS) causes progressive muscle weakness because of the loss of motor neurons. SALS has been associated with exposure to environmental toxins, including pesticides and chemical warfare agents, many of which are organophosphates. The enzyme paraoxonase 1 (PON1) detoxifies organophosphates and the efficacy of this enzyme varies with polymorphisms in the PON1 gene. To determine if an impaired ability to break down organophosphates underlies some cases of SALS, we compared the frequencies of PON1 polymorphisms in SALS patients and controls and investigated gene-environment interactions with self-reported pesticide/herbicide exposure. The PON1 coding polymorphisms L55M, Q192R and I102V, and the promoter polymorphisms -909c>g, -832g>a, -162g>a and -108c>t, were genotyped in 143 SALS patients and 143 matched controls. Statistical comparisons were carried out at allele, genotype and haplotype levels. The PON1 promoter allele -108t, which reduces PON1 expression, was strongly associated with SALS. Overall, promoter haplotypes that decrease PON1 expression were associated with SALS, whereas haplotypes that increase expression were associated with controls. Coding polymorphisms did not correlate with SALS. Gene-environment interactions were identified at the allele level for some promoter SNPs and pesticide/herbicide exposure, but not at the genotype or haplotype level. In conclusion, some PON1 promoter polymorphisms may predispose to SALS, possibly by making motor neurons more susceptible to organophosphate-containing toxins.

  9. 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.

  10. Child dopamine active transporter 1 genotype and parenting: evidence for evocative gene-environment correlations.

    PubMed

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

    2013-02-01

    The dopamine active transporter 1 (DAT1) gene is implicated in psychopathology risk. Although the processes by which this gene exerts its effects on risk are poorly understood, a small body of research suggests that the DAT1 gene influences early emerging negative emotionality, a marker of children's psychopathology risk. As child negative emotionality evokes negative parenting practices, the DAT1 gene may also play a role in gene-environment correlations. To test this model, children (N = 365) were genotyped for the DAT1 gene and participated in standardized parent-child interaction tasks with their primary caregiver. The DAT1 gene 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. The 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.

  11. Participant Interaction in Asynchronous Learning Environments: Evaluating Interaction Analysis Methods

    ERIC Educational Resources Information Center

    Blanchette, Judith

    2012-01-01

    The purpose of this empirical study was to determine the extent to which three different objective analytical methods--sequence analysis, surface cohesion analysis, and lexical cohesion analysis--can most accurately identify specific characteristics of online interaction. Statistically significant differences were found in all points of…

  12. Confluence of Genes, Environment, Development, and Behavior in a Post-GWAS World

    PubMed Central

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

    2012-01-01

    This article serves to outline a research paradigm to investigate main effects and interactions of genes, environment, and development on behavior and psychiatric illness. We provide a historical context for candidate gene studies and genome-wide association studies, including benefits, limitations, and expected payoff. Using substance use and abuse as our driving example, we then turn to the importance of etiological psychological theory in guiding genetic, environmental, and developmental research, as well as the utility of refined phenotypic measures, such as endophenotypes, in the pursuit of etiological understanding and focused tests of genetic and environmental associations. Phenotypic measurement has received considerable attention and is informed by psychometrics, while the environment remains relatively poorly measured and is often confounded with genetic effects (i.e., gene-environment correlation). Genetically-informed designs which—thanks to ever cheaper genotyping—are no longer are limited to twin and adoption studies, are required to understand environmental influences. Finally, we outline the vast amount of individual differences in structural genomic variation, most of which remains to be leveraged in genetic association tests. While the genetic data can be burdensomely massive (tens of millions of variants per person), we argue that improved understanding of genomic structure and function will provide investigators with new tools to test specific a priori hypotheses derived from etiological psychological theory, much like current candidate gene research, but with less confusion and more payoff than candidate gene research has to date. PMID:23062291

  13. Interactive computer code for dynamic and soil structure interaction analysis

    SciTech Connect

    Mulliken, J.S.

    1995-12-01

    A new interactive computer code is presented in this paper for dynamic and soil-structure interaction (SSI) analyses. The computer program FETA (Finite Element Transient Analysis) is a self contained interactive graphics environment for IBM-PC`s that is used for the development of structural and soil models as well as post-processing dynamic analysis output. Full 3-D isometric views of the soil-structure system, animation of displacements, frequency and time domain responses at nodes, and response spectra are all graphically available simply by pointing and clicking with a mouse. FETA`s finite element solver performs 2-D and 3-D frequency and time domain soil-structure interaction analyses. The solver can be directly accessed from the graphical interface on a PC, or run on a number of other computer platforms.

  14. Analysis of ISS Plasma Interaction

    NASA Technical Reports Server (NTRS)

    Reddell, Brandon; Alred, John; Kramer, Leonard; Mikatarian, Ron; Minow, Joe; Koontz, Steve

    2006-01-01

    To date, the International Space Station (ISS) has been one of the largest objects flown in lower earth orbit (LEO). The ISS utilizes high voltage solar arrays (160V) that are negatively grounded leading to pressurized elements that can float negatively with respect to the plasma. Because laboratory measurements indicate a dielectric breakdown potential difference of 80V, arcing could occur on the ISS structure. To overcome the possibility of arcing and clamp the potential of the structure, two Plasma Contactor Units (PCUs) were designed, built, and flown. Also a limited amount of measurements of the floating potential for the present ISS configuration were made by a Floating Potential Probe (FPP), indicating a minimum potential of 24 Volts at the measurement location. A predictive tool, the ISS Plasma Interaction Model (PIM) has been developed accounting for the solar array electron collection, solar array mast wire and effective conductive area on the structure. The model has been used for predictions of the present ISS configuration. The conductive area has been inferred based on available floating potential measurements. Analysis of FPP and PCU data indicated distribution of the conductive area along the Russian segment of the ISS structure. A significant input to PIM is the plasma environment. The International Reference Ionosphere (IRI 2001) was initially used to obtain plasma temperature and density values. However, IRI provides mean parameters, leading to difficulties in interpretation of on-orbit data, especially at eclipse exit where maximum charging can occur. This limits our predicative capability. Satellite and Incoherent Scatter Radar (ISR) data of plasma parameters have also been collected. Approximately 130,000 electron temperature (Te) and density (Ne) pairs for typical ISS eclipse exit conditions have been extracted from the reduced Langmuir probe data flown aboard the NASA DE-2 satellite. Additionally, another 18,000 Te and Ne pairs of ISR data

  15. An attachment perspective on borderline personality disorder: advances in gene-environment considerations.

    PubMed

    Steele, Howard; Siever, Larry

    2010-02-01

    Accumulating evidence points to severe relationship dysfunction as the core epigenetic expression of borderline personality disorder (BPD). In adulthood, BPD is typified by disorganization within and across interpersonal domains of functioning. When interacting with their infants, mothers with BPD show marked withdrawal and frightening or frightened behavior, leading to disorganized infant-mother attachments. Linked to both infant disorganization and BPD is a maternal state of mind typified by unresolved mourning regarding past loss or trauma. Early risk factors for BPD in adulthood include maternal withdrawal in infancy and separation of 1 month or more from mother in the first 5 years of life. Likely contributing biological factors include genes linked to dopamine, serotonin, the hypothalamic-pituitary-adrenal axis, and neuropeptides. The complex gene-environment picture emerging confers risk or protection against BPD pathology in ways consistent with infants varying biological sensitivity to context. This line of research may refine early risk assessment and preventive mental health services.

  16. 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

  17. 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.

  18. Dyadic Interracial Interactions: A Meta-Analysis

    ERIC Educational Resources Information Center

    Toosi, Negin R.; Babbitt, Laura G.; Ambady, Nalini; Sommers, Samuel R.

    2012-01-01

    This meta-analysis examined over 40 years of research on interracial interactions by exploring 4 types of outcomes: explicit attitudes toward interaction partners, participants' self-reports of their own emotional state, nonverbal or observed behavior, and objective measures of performance. Data were collected from 108 samples (N = 12,463)…

  19. Gene-Environment Interplay and Psychopathology: Multiple Varieties but Real Effects

    ERIC Educational Resources Information Center

    Rutter, Michael; Moffitt, Terrie E.; Caspi, Avshalom

    2006-01-01

    Gene-environment interplay is a general term that covers several divergent concepts with different meanings and different implications. In this review, we evaluate research evidence on four varieties of gene-environment interplay. First, we consider epigenetic mechanisms by which environmental influences alter the effects of genes. Second, we…

  20. Energy component analysis of π interactions.

    PubMed

    Sherrill, C David

    2013-04-16

    Fundamental features of biomolecules, such as their structure, solvation, and crystal packing and even the docking of drugs, rely on noncovalent interactions. Theory can help elucidate the nature of these interactions, and energy component analysis reveals the contributions from the various intermolecular forces: electrostatics, London dispersion terms, induction (polarization), and short-range exchange-repulsion. Symmetry-adapted perturbation theory (SAPT) provides one method for this type of analysis. In this Account, we show several examples of how SAPT provides insight into the nature of noncovalent π-interactions. In cation-π interactions, the cation strongly polarizes electrons in π-orbitals, leading to substantially attractive induction terms. This polarization is so important that a cation and a benzene attract each other when placed in the same plane, even though a consideration of the electrostatic interactions alone would suggest otherwise. SAPT analysis can also support an understanding of substituent effects in π-π interactions. Trends in face-to-face sandwich benzene dimers cannot be understood solely in terms of electrostatic effects, especially for multiply substituted dimers, but SAPT analysis demonstrates the importance of London dispersion forces. Moreover, detailed SAPT studies also reveal the critical importance of charge penetration effects in π-stacking interactions. These effects arise in cases with substantial orbital overlap, such as in π-stacking in DNA or in crystal structures of π-conjugated materials. These charge penetration effects lead to attractive electrostatic terms where a simpler analysis based on atom-centered charges, electrostatic potential plots, or even distributed multipole analysis would incorrectly predict repulsive electrostatics. SAPT analysis of sandwich benzene, benzene-pyridine, and pyridine dimers indicates that dipole/induced-dipole terms present in benzene-pyridine but not in benzene dimer are relatively

  1. Analysis of the interaction between experimental and applied behavior analysis.

    PubMed

    Virues-Ortega, Javier; Hurtado-Parrado, Camilo; Cox, Alison D; Pear, Joseph J

    2014-01-01

    To study the influences between basic and applied research in behavior analysis, we analyzed the coauthorship interactions of authors who published in JABA and JEAB from 1980 to 2010. We paid particular attention to authors who published in both JABA and JEAB (dual authors) as potential agents of cross-field interactions. We present a comprehensive analysis of dual authors' coauthorship interactions using social networks methodology and key word analysis. The number of dual authors more than doubled (26 to 67) and their productivity tripled (7% to 26% of JABA and JEAB articles) between 1980 and 2010. Dual authors stood out in terms of number of collaborators, number of publications, and ability to interact with multiple groups within the field. The steady increase in JEAB and JABA interactions through coauthors and the increasing range of topics covered by dual authors provide a basis for optimism regarding the progressive integration of basic and applied behavior analysis.

  2. Evocative gene-environment correlation in the mother-child relationship: a twin study of interpersonal processes.

    PubMed

    Klahr, Ashlea M; Thomas, Katherine M; Hopwood, Christopher J; Klump, Kelly L; Burt, S Alexandra

    2013-02-01

    The behavior genetic literature suggests that genetically influenced characteristics of the child elicit specific behaviors from the parent. However, little is known about the processes by which genetically influenced child characteristics evoke parental responses. Interpersonal theory provides a useful framework for identifying reciprocal behavioral processes between children and mothers. The theory posits that, at any given moment, interpersonal behavior varies along the orthogonal dimensions of warmth and control and that the interpersonal behavior of one individual tends to elicit corresponding or contrasting behavior from the other (i.e., warmth elicits warmth, whereas control elicits submission). The current study thus examined these dimensions of interpersonal behavior as they relate to the parent-child relationship in 546 twin families. A computer joystick was used to rate videos of mother-child interactions in real time, yielding information on mother and child levels of warmth and control throughout the interaction. Analyses indicated that maternal control, but not maternal warmth, was influenced by evocative gene-environment correlational processes, such that genetic influences on maternal control and child control were largely overlapping. Moreover, these common genetic influences were present both cross-sectionally and over the course of the interaction. Such findings not only confirm the presence of evocative gene-environment correlational processes in the mother-child relationship but also illuminate at least one of the specific interpersonal behaviors that underlie this evocative process.

  3. Vehicle systems: coupled and interactive dynamics analysis

    NASA Astrophysics Data System (ADS)

    Vantsevich, Vladimir V.

    2014-11-01

    This article formulates a new direction in vehicle dynamics, described as coupled and interactive vehicle system dynamics. Formalised procedures and analysis of case studies are presented. An analytical consideration, which explains the physics of coupled system dynamics and its consequences for dynamics of a vehicle, is given for several sets of systems including: (i) driveline and suspension of a 6×6 truck, (ii) a brake mechanism and a limited slip differential of a drive axle and (iii) a 4×4 vehicle steering system and driveline system. The article introduces a formal procedure to turn coupled system dynamics into interactive dynamics of systems. A new research direction in interactive dynamics of an active steering and a hybrid-electric power transmitting unit is presented and analysed to control power distribution between the drive axles of a 4×4 vehicle. A control strategy integrates energy efficiency and lateral dynamics by decoupling dynamics of the two systems thus forming their interactive dynamics.

  4. Computational analysis of ramjet engine inlet interaction

    NASA Technical Reports Server (NTRS)

    Duncan, Beverly; Thomas, Scott

    1992-01-01

    A computational analysis of a ramjet engine at Mach 3.5 has been conducted and compared to results obtained experimentally. This study focuses on the behavior of the inlet both with and without combustor backpressure. Increased backpressure results in separation of the body side boundary layer and a resultant static pressure rise in the inlet throat region. The computational results compare well with the experimental data for static pressure distribution through the engine, inlet throat flow profiles, and mass capture. The computational analysis slightly underpredicts the thickness of the engine body surface boundary layer and the extent of the interaction caused by backpressure; however, the interaction is observed at approximately the same level of backpressure both experimentally and computationally. This study demonstrates the ability of two different Navier-Stokes codes, namely RPLUS and PARC, to calculate the flow features of this ramjet engine and to provide more detailed information on the process of inlet interaction and unstart.

  5. Generalized Structured Component Analysis with Latent Interactions

    ERIC Educational Resources Information Center

    Hwang, Heungsun; Ho, Moon-Ho Ringo; Lee, Jonathan

    2010-01-01

    Generalized structured component analysis (GSCA) is a component-based approach to structural equation modeling. In practice, researchers may often be interested in examining the interaction effects of latent variables. However, GSCA has been geared only for the specification and testing of the main effects of variables. Thus, an extension of GSCA…

  6. Dissecting cause and effect in the pathogenesis of psychiatric disorders: genes, environment and behaviour.

    PubMed

    Gray, Laura; Hannan, Anthiny J

    2007-08-01

    It has long been established that the development of psychiatric illness results from a complex interplay between genetic and environmental factors. Postmortem and genetic linkage studies have identified a number of promising candidate genes which have been reinforced by replication and functional studies. However, the fact that concordance rates for monozygotic twins rarely approach 100% highlights the involvement of environmental factors. Whilst epidemiological studies of psychiatric cohorts have demonstrated potential risk factors, such studies are clearly limited and in many cases the potential mechanism linking a given risk factor with pathogenesis remains unclear. A very powerful method of elucidating the mechanisms underlying gene-environment interactions is the use of appropriate animal models of psychiatric pathology. Whilst animals cannot be used to map the entire complexity of diseases such as schizophrenia, dissecting the symptom profile into more simply encapsulated traits or endophenotypes has proved to be a successful approach. Such endophenotypes provide a measurable link between aetiological factors and phenotypic outcome. Given the potential for the careful control and modification of an experimental animal's environment, the combination of studies of candidate genes with investigations of environmental factors is an effective heuristic tool, allowing examination of behavioural endophenotypes in conjunction with cellular and molecular outcomes. This review will consider the extant genetic, molecular, pharmacological and lesion-based models of psychiatric disorders, and the relevant methods of environmental manipulation appearing in the literature. We will discuss studies where such models have been combined, and the potential for future experimentation in this area.

  7. SpecViz: Interactive Spectral Data Analysis

    NASA Astrophysics Data System (ADS)

    Earl, Nicholas Michael; STScI

    2016-06-01

    The astronomical community is about to enter a new generation of scientific enterprise. With next-generation instrumentation and advanced capabilities, the need has arisen to equip astronomers with the necessary tools to deal with large, multi-faceted data. The Space Telescope Science Institute has initiated a data analysis forum for the creation, development, and maintenance of software tools for the interpretation of these new data sets. SpecViz is a spectral 1-D interactive visualization and analysis application built with Python in an open source development environment. A user-friendly GUI allows for a fast, interactive approach to spectral analysis. SpecViz supports handling of unique and instrument-specific data, incorporation of advanced spectral unit handling and conversions in a flexible, high-performance interactive plotting environment. Active spectral feature analysis is possible through interactive measurement and statistical tools. It can be used to build wide-band SEDs, with the capability of combining or overplotting data products from various instruments. SpecViz sports advanced toolsets for filtering and detrending spectral lines; identifying, isolating, and manipulating spectral features; as well as utilizing spectral templates for renormalizing data in an interactive way. SpecViz also includes a flexible model fitting toolset that allows for multi-component models, as well as custom models, to be used with various fitting and decomposition routines. SpecViz also features robust extension via custom data loaders and connection to the central communication system underneath the interface for more advanced control. Incorporation with Jupyter notebooks via connection with the active iPython kernel allows for SpecViz to be used in addition to a user’s normal workflow without demanding the user drastically alter their method of data analysis. In addition, SpecViz allows the interactive analysis of multi-object spectroscopy in the same straight

  8. Network Analysis of Social Interactions in Laboratories

    NASA Astrophysics Data System (ADS)

    Warren, Aaron R.

    2008-10-01

    An ongoing study of the structure, function, and evolution of individual activity within lab groups is introduced. This study makes extensive use of techniques from social network analysis. These techniques allow rigorous quantification and hypothesis-testing of the interactions inherent in social groups and the impact of intrinsic characteristics of individuals on their social interactions. As these techniques are novel within the physics education research community, an overview of their meaning and application is given. We then present preliminary results from videotaped laboratory groups involving mixed populations of traditional and non-traditional students in an introductory algebra-based physics course.

  9. Interactive Visual Analysis within Dynamic Ocean Models

    NASA Astrophysics Data System (ADS)

    Butkiewicz, T.

    2012-12-01

    The many observation and simulation based ocean models available today can provide crucial insights for all fields of marine research and can serve as valuable references when planning data collection missions. However, the increasing size and complexity of these models makes leveraging their contents difficult for end users. Through a combination of data visualization techniques, interactive analysis tools, and new hardware technologies, the data within these models can be made more accessible to domain scientists. We present an interactive system that supports exploratory visual analysis within large-scale ocean flow models. The currents and eddies within the models are illustrated using effective, particle-based flow visualization techniques. Stereoscopic displays and rendering methods are employed to ensure that the user can correctly perceive the complex 3D structures of depth-dependent flow patterns. Interactive analysis tools are provided which allow the user to experiment through the introduction of their customizable virtual dye particles into the models to explore regions of interest. A multi-touch interface provides natural, efficient interaction, with custom multi-touch gestures simplifying the otherwise challenging tasks of navigating and positioning tools within a 3D environment. We demonstrate the potential applications of our visual analysis environment with two examples of real-world significance: Firstly, an example of using customized particles with physics-based behaviors to simulate pollutant release scenarios, including predicting the oil plume path for the 2010 Deepwater Horizon oil spill disaster. Secondly, an interactive tool for plotting and revising proposed autonomous underwater vehicle mission pathlines with respect to the surrounding flow patterns predicted by the model; as these survey vessels have extremely limited energy budgets, designing more efficient paths allows for greater survey areas.

  10. Latent Class Analysis of Antisocial Behavior: Interaction of Serotonin Transporter Genotype and Maltreatment

    PubMed Central

    Li, James J.

    2010-01-01

    To improve understanding about genetic and environmental influences on antisocial behavior (ASB), we tested the association of the 44-base pair polymorphism of the serotonin transporter gene (5-HTTLPR) and maltreatment using latent class analysis in 2,488 boys and girls from Wave 1 of the National Longitudinal Study of Adolescent Health. In boys, ASB was defined by three classes (Exclusive Covert, Mixed Covert and Overt, and No Problems) whereas in girls, ASB was defined by two classes (Exclusive Covert, No Problems). In boys, 5-HTTLPR and maltreatment were not significantly related to ASB. However, in girls, maltreatment, but not 5-HTTLPR, was significantly associated with ASB. A significant interaction between 5-HTTLPR and maltreatment was also observed, where maltreated girls homozygous for the short allele were 12 times more likely to be classified in the Exclusive Covert group than in the No Problems group. Structural differences in the latent structure of ASB at Wave 2 and Wave 3 prevented repeat LCA modeling. However, using counts of ASB, 5-HTTLPR, maltreatment, and its interaction were unrelated to overt and covert ASB at Wave 2 and only maltreatment was related to covert ASB at Wave 3. We discuss these findings within the context of sex differences in ASB and relevant models of gene-environment interplay across developmental periods. PMID:20405199

  11. Bayesian analysis of genetic interactions in case-control studies, with application to adiponectin genes and colorectal cancer risk.

    PubMed

    Yi, Nengjun; Kaklamani, Virginia G; Pasche, Boris

    2011-01-01

    Complex diseases such as cancers are influenced by interacting networks of genetic and environmental factors. However, a joint analysis of multiple genes and environmental factors is challenging, owing to potentially large numbers of correlated and complex variables. We describe Bayesian generalized linear models for simultaneously analyzing covariates, main effects of numerous loci, gene-gene and gene-environment interactions in population case-control studies. Our Bayesian models use Student-t prior distributions with different shrinkage parameters for different types of effects, allowing reliable estimates of main effects and interactions and hence increasing the power for detection of real signals. We implement a fast and stable algorithm for fitting models by extending available tools for classical generalized linear models to the Bayesian case. We propose a novel method to interpret and visualize models with multiple interactions by computing the average predictive probability. Simulations show that the method has the potential to dissect interacting networks of complex diseases. Application of the method to a large case-control study of adiponectin genes and colorectal cancer risk highlights the previous results and detects new epistatic interactions and sex-specific effects that warrant follow-up in independent studies.

  12. Quantitative Analysis of Triple Mutant Genetic Interactions

    PubMed Central

    Braberg, Hannes; Alexander, Richard; Shales, Michael; Xu, Jiewei; Franks-Skiba, Kathleen E.; Wu, Qiuqin; Haber, James E.; Krogan, Nevan J.

    2014-01-01

    The quantitative analysis of genetic interactions between pairs of gene mutations has proven effective for characterizing cellular functions but can miss important interactions for functionally redundant genes. To address this limitation, we have developed an approach termed Triple Mutant Analysis (TMA). The procedure relies on a query strain that contains two deletions in a pair of redundant or otherwise related genes, that is crossed against a panel of candidate deletion strains to isolate triple mutants and measure their growth. A central feature of TMA is to interrogate mutants that are synthetically sick when two other genes are deleted but interact minimally with either single deletion. This approach has been valuable for discovering genes that restore critical functions when the principle actors are deleted. TMA has also uncovered double mutant combinations that produce severe defects because a third protein becomes deregulated and acts in a deleterious fashion, and it has revealed functional differences between proteins presumed to act together. The protocol is optimized for Singer ROTOR pinning robots, takes 3 weeks to complete, and measures interactions for up to 30 double mutants against a library of 1536 single mutants. PMID:25010907

  13. Low cost real time interactive analysis system

    NASA Technical Reports Server (NTRS)

    Stetina, F.

    1988-01-01

    Efforts continue to develop a low cost real time interactive analysis system for the reception of satellite data. A multi-purpose ingest hardware software frame formatter was demonstrated for GOES and TIROS data and work is proceeding on extending the capability to receive GMS data. A similar system was proposed as an archival and analysis system for use with INSAT data and studies are underway to modify the system to receive the planned SeaWiFS (ocean color) data. This system was proposed as the core of a number of international programs in support of U.S. AID activities. Systems delivered or nearing final testing are listed.

  14. An unsteady helicopter rotor: Fuselage interaction analysis

    NASA Technical Reports Server (NTRS)

    Lorber, Peter F.; Egolf, T. Alan

    1988-01-01

    A computational method was developed to treat unsteady aerodynamic interactions between a helicopter rotor, wake, and fuselage and between the main and tail rotors. An existing lifting line prescribed wake rotor analysis and a source panel fuselage analysis were coupled and modified to predict unsteady fuselage surface pressures and airloads. A prescribed displacement technique is used to position the rotor wake about the fuselage. Either a rigid blade or an aeroelastic blade analysis may be used to establish rotor operating conditions. Sensitivity studies were performed to determine the influence of the wake fuselage geometry on the computation. Results are presented that describe the induced velocities, pressures, and airloads on the fuselage and on the rotor. The ability to treat arbitrary geometries is demonstrated using a simulated helicopter fuselage. The computational results are compared with fuselage surface pressure measurements at several locations. No experimental data was available to validate the primary product of the analysis: the vibratory airloads on the entire fuselage. A main rotor-tail rotor interaction analysis is also described, along with some hover and forward flight.

  15. Interactive multi-mode blade impact analysis

    NASA Technical Reports Server (NTRS)

    Alexander, A.; Cornell, R. W.

    1978-01-01

    The theoretical methodology used in developing an analysis for the response of turbine engine fan blades subjected to soft-body (bird) impacts is reported, and the computer program developed using this methodology as its basis is described. This computer program is an outgrowth of two programs that were previously developed for the purpose of studying problems of a similar nature (a 3-mode beam impact analysis and a multi-mode beam impact analysis). The present program utilizes an improved missile model that is interactively coupled with blade motion which is more consistent with actual observations. It takes into account local deformation at the impact area, blade camber effects, and the spreading of the impacted missile mass on the blade surface. In addition, it accommodates plate-type mode shapes. The analysis capability in this computer program represents a significant improvement in the development of the methodology for evaluating potential fan blade materials and designs with regard to foreign object impact resistance.

  16. Interactive analysis of geodata based intelligence

    NASA Astrophysics Data System (ADS)

    Wagner, Boris; Eck, Ralf; Unmüessig, Gabriel; Peinsipp-Byma, Elisabeth

    2016-05-01

    When a spatiotemporal events happens, multi-source intelligence data is gathered to understand the problem, and strategies for solving the problem are investigated. The difficulties arising from handling spatial and temporal intelligence data represent the main problem. The map might be the bridge to visualize the data and to get the most understand model for all stakeholders. For the analysis of geodata based intelligence data, a software was developed as a working environment that combines geodata with optimized ergonomics. The interaction with the common operational picture (COP) is so essentially facilitated. The composition of the COP is based on geodata services, which are normalized by international standards of the Open Geospatial Consortium (OGC). The basic geodata are combined with intelligence data from images (IMINT) and humans (HUMINT), stored in a NATO Coalition Shared Data Server (CSD). These intelligence data can be combined with further information sources, i.e., live sensors. As a result a COP is generated and an interaction suitable for the specific workspace is added. This allows the users to work interactively with the COP, i.e., searching with an on board CSD client for suitable intelligence data and integrate them into the COP. Furthermore, users can enrich the scenario with findings out of the data of interactive live sensors and add data from other sources. This allows intelligence services to contribute effectively to the process by what military and disaster management are organized.

  17. MIBSA: Multi Interacting Blocks for Slope Analysis

    NASA Astrophysics Data System (ADS)

    Dattola, Giuseppe; Crosta, Giovanni; Castellanza, Riccardo; di Prisco, Claudio

    2016-04-01

    As it is well known, the slope instabilities have very important consequences in terms of human lives and activities. So predicting the evolution in time and space of slope mass movements becomes fundamental. This is even more relevant when we consider that the triggering mechanisms are a rising ground water level and the occurrence of earthquakes. Therefore, seasonal rainfall has a direct influence on the triggering of large rock and earthslide with a composite failure surface and causing differential behaviors within the sliding mass. In this contribution, a model describing the slope mass by means of an array of blocks that move on a prefixed failure surface, is defined. A shear band located at the base of each block, whose behavior is modelled via a viscous plastic model based on the Perzyna's approach, controls the slip velocity of the block. The motion of the blocks is obtained by solving the second balance equation in which the normal and tangential interaction forces are obtained by a specific interaction model. The model has been implemented in an original code and it is used to perform a parametric analysis that describes the effects of block interactions under a transient ground water oscillation. The numerical results confirm that the normal and tangential interactions between blocks can inhibit or induce the slope movements. The model is tested against some real case studies. This model is under development to add the dynamic effects generated by earthquake shaking.

  18. Breast Cancer Risk – Genes, Environment and Clinics

    PubMed Central

    Fasching, P. A.; Ekici, A. B.; Adamietz, B. R.; Wachter, D. L.; Hein, A.; Bayer, C. M.; Häberle, L.; Loehberg, C. R.; Jud, S. M.; Heusinger, K.; Rübner, M.; Rauh, C.; Bani, M. R.; Lux, M. P.; Schulz-Wendtland, R.; Hartmann, A.; Beckmann, M. W.

    2011-01-01

    The information available about breast cancer risk factors has increased dramatically during the last 10 years. In particular, studies of low-penetrance genes and mammographic density have improved our understanding of breast cancer risk. In addition, initial steps have been taken in investigating interactions between genes and environmental factors. This review concerns with actual data on this topic. Several genome-wide association studies (GWASs) with a case–control design, as well as large-scale validation studies, have identified and validated more than a dozen single nucleotide polymorphisms (SNPs) associated with breast cancer risk. They are located not only in or close to genes known to be involved in cancer pathogenesis, but also in genes not previously associated with breast cancer pathogenesis, or may even not be related to any genes. SNPs have also been identified that alter the lifetime risk in BRCA mutation carriers. With regard to nongenetic risk factors, studies of postmenopausal hormone replacement therapy (HRT) have revealed important information on how to weigh up the risks and benefits of HRT. Mammographic density (MD) has become an accepted and important breast cancer risk factor. Lifestyle and nutritional considerations have become an integral part of most studies of breast cancer risk, and some improvements have been made in this field as well. More than 10 years after the publication of the first breast cancer prevention studies with tamoxifen, other substances such as raloxifene and aromatase inhibitors have been investigated and have also been shown to have preventive potential. Finally, mammographic screening systems have been implemented in most Western countries during the last decade. These may be developed further by including more individualized methods of predicting the patientʼs breast cancer risk. PMID:25253900

  19. Interactive analysis environment of unified accelerator libraries

    NASA Astrophysics Data System (ADS)

    Fine, V.; Malitsky, N.; Talman, R.

    2006-04-01

    Unified Accelerator Libraries (UAL, http://www.ual.bnl.gov) software is an open accelerator simulation environment addressing a broad spectrum of accelerator tasks ranging from efficient online-oriented modeling to full-scale realistic beam dynamics studies. The paper introduces a new package integrating UAL simulation algorithms with the QT-based Graphical User Interface and the ROOT data analysis and visualization framework ( http://root.cern.ch). The primary user application is implemented as an interactive and configurable Accelerator Physics Player. Its interface to visualization components is based on the QT layer ( http://root.bnl.gov) supported by the STAR experiment.

  20. ERROR ANALYSIS OF COMPOSITE SHOCK INTERACTION PROBLEMS.

    SciTech Connect

    LEE,T.MU,Y.ZHAO,M.GLIMM,J.LI,X.YE,K.

    2004-07-26

    We propose statistical models of uncertainty and error in numerical solutions. To represent errors efficiently in shock physics simulations we propose a composition law. The law allows us to estimate errors in the solutions of composite problems in terms of the errors from simpler ones as discussed in a previous paper. In this paper, we conduct a detailed analysis of the errors. One of our goals is to understand the relative magnitude of the input uncertainty vs. the errors created within the numerical solution. In more detail, we wish to understand the contribution of each wave interaction to the errors observed at the end of the simulation.

  1. Analysis of interacting dual lifting ejector systems

    NASA Technical Reports Server (NTRS)

    Lund, T. S.; Tavella, D. A.; Roberts, L.

    1986-01-01

    An analytical treatment is presented for a flowfield generated by a pair of interacting, two-dimensional parallel jets, representative of the two exhaust streams issuing from the thrust augmentor nozzles of dual lifting jet VTOL aircraft propulsion systems. Predictions of the analysis for the ratio of primary to secondary velocity are in close agreement with experimentally observed values, if the spreading rate parameter is allowed to assume a value greater than that which applies to a free jet. Theoretical results are combined with existing experimental data for unventilated jets, in order to arrive at an estimate of the thrust augmentation produced by a jet pair with an arbitrary degree of ventilation.

  2. Digraph matrix analysis applications to systems interactions

    SciTech Connect

    Alesso, H.P.; Altenbach, T.; Lappa, D.; Kimura, C.; Sacks, I.J.; Ashmore, B.C.; Fromme, D.; Smith, C.F.; Williams, W.

    1984-01-01

    Complex events such as Three Mile Island-2, Brown's Ferry-3 and Crystal River-3 have demonstrated that previously unidentified system interdependencies can be important to safety. A major aspect of these events was dependent faults (common cause/mode failures). The term systems interactions has been introduced by the Nuclear Regulatory Commission (NRC) to identify the concepts of spatial and functional coupling of systems which can lead to system interdependencies. Spatial coupling refers to dependencies resulting from a shared environmental condition; functional coupling refers to both dependencies resulting from components shared between safety and/or support systems, and to dependencies involving human actions. The NRC is currently developing guidelines to search for and evaluate adverse systems interactions at light water reactors. One approach utilizes graph theoretical methods and is called digraph matrix analysis (DMA). This methodology has been specifically tuned to the systems interaction problem. The objective of this paper is to present results from two DMA applications and to contrast them with the results from more traditional fault tree approaches.

  3. Numerical analysis of soil-structure interaction

    NASA Astrophysics Data System (ADS)

    Vanlangen, Harry

    1991-05-01

    A study to improve some existing procedures for the finite element analysis of soil deformation and collapse is presented. Special attention is paid to problems of soil structure interaction. Emphasis is put on the behavior of soil rather than on that of structures. This seems to be justifiable if static interaction of stiff structures and soft soil is considered. In such a case nonlinear response will exclusively stem from soil deformation. In addition, the quality of the results depends to a high extent on the proper modeling of soil flow along structures and not on the modeling of the structure itself. An exception is made when geotextile reinforcement is considered. In that case the structural element, i.e., the geotextile, is highly flexible. The equation of continuum equilibrium, which serves as a starting point for the finite element formulation of large deformation elastoplasticity, is discussed with special attention being paid to the interpretation of some objective stress rate tensors. The solution of nonlinear finite element equations is addressed. Soil deformation in the prefailure range is discussed. Large deformation effect in the analysis of soil deformation is touched on.

  4. Mark 3 interactive data analysis system

    NASA Technical Reports Server (NTRS)

    Ryan, J. W.; Ma, C.; Schupler, B. P.

    1980-01-01

    The interactive data analysis system, a major subset of the total Mark 3 very long baseline interferometry (VLBI) software system is described. The system consists of two major and a number of small programs. These programs provide for the scientific analysis of the observed values of delay and delay rate generated by the VLBI data reduction programs and product the geophysical and astrometric parameters which are among the ultimate products of VLBI. The two major programs are CALC and SOLVE. CALC generates the theoretical values of VLBI delay rate as well as partial derivatives based on apriori values of the geophysical and astronometric parameters. SOLVE is a least squares parameters estimation program which yields the geophysical and astrometric parameters using the observed values by the data processing system and theoretical values and partial derivatives provided by CALC. SOLVE is a highly interactive program in which the user selects the exact form of the recovered parameters and the data to be accepted into the solution.

  5. A Multidimensional Analysis Tool for Visualizing Online Interactions

    ERIC Educational Resources Information Center

    Kim, Minjeong; Lee, Eunchul

    2012-01-01

    This study proposes and verifies the performance of an analysis tool for visualizing online interactions. A review of the most widely used methods for analyzing online interactions, including quantitative analysis, content analysis, and social network analysis methods, indicates these analysis methods have some limitations resulting from their…

  6. Biometric Modeling of Gene-Environment Interplay: The Intersection of Theory and Method and Applications for Social Inequality.

    PubMed

    South, Susan C; Hamdi, Nayla R; Krueger, Robert F

    2017-02-01

    For more than a decade, biometric moderation models have been used to examine whether genetic and environmental influences on individual differences might vary within the population. These quantitative Gene × Environment interaction models have the potential to elucidate not only when genetic and environmental influences on a phenotype might differ, but also why, as they provide an empirical test of several theoretical paradigms that serve as useful heuristics to explain etiology-diathesis-stress, bioecological, differential susceptibility, and social control. In the current article, we review how these developmental theories align with different patterns of findings from statistical models of gene-environment interplay. We then describe the extant empirical evidence, using work by our own research group and others, to lay out genetically informative plausible accounts of how phenotypes related to social inequality-physical health and cognition-might relate to these theoretical models.

  7. Satiety and the Self-Regulation of Food Take in Children: a Potential Role for Gene-Environment Interplay.

    PubMed

    Hughes, Sheryl O; Frazier-Wood, Alexis C

    2016-03-01

    Child eating self-regulation refers to behaviors that enable children to start and stop eating in a manner consistent with maintaining energy balance. Perturbations in these behaviors, manifesting as poorer child eating self-regulation, are associated with higher child weight status. Initial research into child eating self-regulation focused on the role of parent feeding styles and behaviors. However, we argue that child eating self-regulation is better understood as arising from a complex interplay between the child and their feeding environment, and highlight newer research into the heritable child characteristics, such as cognitive ability, that play an important role in this dynamic. Therefore, child eating self-regulation arises from gene-environment interactions. Identifying the genes and environmental influences contributing to these will help us tailor our parental feeding advice to the unique nature of the child. In this way, we will devise more effective advice for preventing childhood obesity.

  8. Satiety and the self-regulation of food take in children: A potential role for gene-environment interplay

    PubMed Central

    Hughes, Sheryl O.

    2016-01-01

    Child eating self-regulation refers to behaviors that enable children to start and stop eating in a manner consistent with maintaining energy balance. Perturbations in these behaviors, manifesting as poorer child eating self-regulation, are associated with higher child weight status. Initial research into child eating self-regulation focused on the role of parent feeding styles and behaviors. However, we argue that child eating self-regulation is better understood as arising from a complex interplay between the child and their feeding environment, and highlight newer research into the heritable child characteristics, such as cognitive ability, that play an important role in this dynamic. Therefore, child eating self-regulation arises from gene-environment interactions. Identifying the genes and environmental influences contributing to these will help us tailor our parental feeding advice to the unique nature of the child. In this way, we will devise more effective advice for preventing childhood obesity. PMID:26847550

  9. Gene-Environment Correlation Underlying the Association between Parental Negativity and Adolescent Externalizing Problems

    ERIC Educational Resources Information Center

    Marceau, Kristine; Horwitz, Briana N.; Narusyte, Jurgita; Ganiban, Jody M.; Spotts, Erica L.; Reiss, David; Neiderhiser, Jenae M.

    2013-01-01

    Studies of adolescent or parent-based twins suggest that gene-environment correlation (rGE) is an important mechanism underlying parent-adolescent relationships. However, information on how parents' and children's genes and environments influence correlated parent "and" child behaviors is needed to distinguish types of rGE. The present…

  10. Systems analysis of host-parasite interactions.

    PubMed

    Swann, Justine; Jamshidi, Neema; Lewis, Nathan E; Winzeler, Elizabeth A

    2015-01-01

    Parasitic diseases caused by protozoan pathogens lead to hundreds of thousands of deaths per year in addition to substantial suffering and socioeconomic decline for millions of people worldwide. The lack of effective vaccines coupled with the widespread emergence of drug-resistant parasites necessitates that the research community take an active role in understanding host-parasite infection biology in order to develop improved therapeutics. Recent advances in next-generation sequencing and the rapid development of publicly accessible genomic databases for many human pathogens have facilitated the application of systems biology to the study of host-parasite interactions. Over the past decade, these technologies have led to the discovery of many important biological processes governing parasitic disease. The integration and interpretation of high-throughput -omic data will undoubtedly generate extraordinary insight into host-parasite interaction networks essential to navigate the intricacies of these complex systems. As systems analysis continues to build the foundation for our understanding of host-parasite biology, this will provide the framework necessary to drive drug discovery research forward and accelerate the development of new antiparasitic therapies.

  11. Gene Environment Risk Assessment and Colorectal Cancer Screening in an Average Risk Population: A Randomized, Controlled Trial

    PubMed Central

    Weinberg, David S.; Myers, Ronald E.; Keenan, Eileen; Ruth, Karen; Sifri, Randa; Ziring, Barry; Ross, Eric; Manne, Sharon L.

    2015-01-01

    Background New methods are needed to improve health behaviors such as adherence to colorectal cancer (CRC) screening. There is increasing availability of personalized genetic information to inform medical decisions. It is not known if such information motivates behavioral change. Objective To determine, in average risk persons, if individualized gene-environment risk assessment about CRC susceptibility improves adherence to screening. Design Two-arm, randomized, controlled trial Setting Four medical school affiliated primary care practices Patients 783 patients at average risk for CRC, but not adherent with screening at study entry Intervention Patients were randomized to usual care or to receipt of Gene Environmental Risk Assessment (GERA), which assessed Methylene Tetrahydrofolate Reductase (MTHFR) polymorphisms and serum folate level. Based on pre-specified polymorphism/folate level combinations, GERA participants were told they were at either “elevated” or at “average” risk for CRC. Measurements The primary outcome was receipt of CRC screening within 6 months of study entry. Results CRC screening rates were not statistically significantly different between usual care (35.7%) and GERA (33.1%) arms overall. After adjustment for baseline participant factors, the odds ratio (OR) for screening completion for GERA vs usual care was 0.88 (95% CI 0.64 - 1.22). Within the GERA arm, there was no significant difference in screening rates between GERA average risk (38.1%) and GERA elevated risk (26.9%) groups. Odds ratios for elevated vs. average risk remained non-significant after adjustment for covariates (OR=0.75, 95% CI 0.39 - 1.42). Limitations Only one personalized, gene-environment interaction and only one health behavior, colorectal cancer screening, were assessed. Conclusion In average risk persons, there was no positive association between CRC screening uptake and feedback of a single personalized gene-environment risk assessment (GERA). Additional

  12. DICON: interactive visual analysis of multidimensional clusters.

    PubMed

    Cao, Nan; Gotz, David; Sun, Jimeng; Qu, Huamin

    2011-12-01

    Clustering as a fundamental data analysis technique has been widely used in many analytic applications. However, it is often difficult for users to understand and evaluate multidimensional clustering results, especially the quality of clusters and their semantics. For large and complex data, high-level statistical information about the clusters is often needed for users to evaluate cluster quality while a detailed display of multidimensional attributes of the data is necessary to understand the meaning of clusters. In this paper, we introduce DICON, an icon-based cluster visualization that embeds statistical information into a multi-attribute display to facilitate cluster interpretation, evaluation, and comparison. We design a treemap-like icon to represent a multidimensional cluster, and the quality of the cluster can be conveniently evaluated with the embedded statistical information. We further develop a novel layout algorithm which can generate similar icons for similar clusters, making comparisons of clusters easier. User interaction and clutter reduction are integrated into the system to help users more effectively analyze and refine clustering results for large datasets. We demonstrate the power of DICON through a user study and a case study in the healthcare domain. Our evaluation shows the benefits of the technique, especially in support of complex multidimensional cluster analysis.

  13. Atlas Multimedia Educational Lab for Interactive Analysis

    SciTech Connect

    Pequenao, Joao

    2008-04-01

    AMELIA is an application with focus on particle physics processes in ATLAS. This will allow students and othe users to decode the collision events that unfold after the head-on collisions of protons at the Large hadron Collider. AMELIA uses the Irrlicht engine for the 3D graphics and wxWidgets for the interface. It uses the best aspects of technical animation and allows users to control 3D representations of collision events and to manipulate 3D models of the detector and see how particles are detected as they pass through. It allows the user to rotate, zoom and select virtual pieces of the ATLAS detector and events. The characteristics of the events (momentum etc.) can also be read, and one can select tracks for analysis, activate context-oriented media, etc. This framework intends to integrate different types of media into a single product. This way, videos, animations, sound, interactive visualization and data analysis will be bound together in the same package.-

  14. Gene-environment interactions and the impact on obesity and lipid profile phenotypes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Sequencing the human genome provided the data, human intellectual capital and technology, particularly in terms of infrastructure and methodologies, to begin discovering genes involved in a wide range of human diseases and afflictions. This has led to a resurgence in genetics with the advent of geno...

  15. Heritability for Adolescent Antisocial Behavior Differs with Socioeconomic Status: Gene-Environment Interaction

    ERIC Educational Resources Information Center

    Tuvblad, Catherine; Grann, Martin; Lichtenstein, Paul

    2006-01-01

    Background: Socioeconomic status is often assumed to be of importance for the development of antisocial behavior, yet it explains only a fraction of the variance. One explanation for this paradox could be that socioeconomic status moderates the influence of genetic and environmental effects on antisocial behavior. Method: TCHAD is a Swedish…

  16. Gene-Gene and Gene-Environment Interactions in the Etiology of Breast Cancer

    DTIC Science & Technology

    2007-06-01

    Egusi Vegetable 1 2 3 4 5 67. Egusi Tomato Vegetable 1 2 3 4 5 68. Egusi Okra 1 2 3 4 5 69. Okra soup 1 2 3 4 5 Disclaimer: This is...unpublished 70. Okra Tomato 1 2 3 4 5 71. Okra Vegetable 1 2 3 4 5 72. Okra Tomato Vegetable 1 2 3 4 5 73. Ogbolo Tomato 1 2 3 4 5 74. Ogbolo... Okra 1 2 3 4 5 75. Ogbolo Vegetable 1 2 3 4 5 76. Ewedu Tomato 1 2 3 4 5 77. Banga ( Palm Sauce) 1 2 3 4 5 78. Banga Tomato 1 2 3 4 5 79

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  18. Gene environment interaction of GALNT2 and APOE gene with hypertension in the Chinese Han Population.

    PubMed

    Zhang, Xuejuan; Zhao, Haiping; Zhang, Jietao; Han, Di; Zheng, Yu; Guo, Xiaozi; He, Dian; Guo, Jin; Wang, Yingcui

    2015-01-01

    In some GWAs studies, GALNT2 and APOE polymorphisms have been identified to be related to alterations of plasma or serum HDL-C and TG concentrations. The purpose of our study is to assess the contribution of GALNT2 rs4846914, APOE rs429358, rs7412, rs405509 variants, and several environmental factors to the development of hypertension disease in the China Han population. A hospital-based case-control study was conducted. Cases were hypertension (n=211) and controls were normal participants (n=434). The AA, AG, and GG genotype frequencies of GALNT2 rs4846914 were 22.8%, 43.1%, and 34.1% in hypertension subjects, and 35.3%, 44.2%, and 20.5% in controls (P<0.05), respectively. The OR of the AG genotype adjusted for all risk factors compared to the AA genotype was 1.61 (95%CI: 1.02 to 2.56) and to the GG genotype 2.67 (95%CI: 1.59 to 4.488). There was no significant difference between the APOE rs429358, rs7412, and rs405509 genotype frequencies in hypertension and control subjects. The present work indicates that SNP rs4846914 in GALNT2 gene is related to an increased risk of hypertension in China Han population, but the APOE gene is not.

  19. Gene-environment interactions in susceptibility to fumonisin-induced neural tube defects

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Fumonisin B1 (FB1) is a mycotoxin produced by a common fungal contaminant of corn. In populations that rely on maize-based foods as a dietary staple, consumption of FB1-contaminated food during early pregnancy is associated with increased risk for neural tube defects (NTDs). Administration of FB1 ...

  20. Gene-environment interactions in asthma: with apologies to William of Ockham.

    PubMed

    Martinez, Fernando D

    2007-01-01

    Many environmental factors and a large number of genetic polymorphisms have been reported to be associated with asthma risk in different locales and at different ages. It seems that what we call asthma is a heterogeneous set of conditions for which the only common feature is recurrent airway obstruction that is at least partially responsive to usual asthma therapy. Recent studies in which environmental factors and genetic variants were studied concomitantly have suggested a potential unifying concept for the disease. It seems that asthma is a genetically mediated development dysregulation of diverse immune and airway responses to a variety of specific and nonspecific exposures. It thus seems improbable that most genetic variants associated with asthma influence the disease regardless of which environmental factors trigger it and at which lifetime phase they are present. More likely, the most important gene variants for asthma are polymorphisms that exert their influence on the network system controlling biological responses to asthma-related exposures.

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

    DTIC Science & Technology

    2008-05-01

    present in many consumer products as well as many common household materials such as plastics and fragrances . Given the rising rates of asthma and...Prevention, Atlanta, GA , USA cDepartment of Pediatrics, Mount Sinai School of Medicine, New York, NY, USA Received 30 March 2007; received in revised form...purposes such as adding flexibility to plastics and making fragrances last ARTICLE IN PRESS S.L. Teitelbaum et al. / Environmental Research 106 (2008) 257

  2. Histone Deacetylases and Mood Disorders: Epigenetic Programming in Gene-Environment Interactions

    PubMed Central

    Machado-Vieira, Rodrigo; Ibrahim, Lobna; Zarate, Carlos A.

    2010-01-01

    Epigenetics involves molecular mechanisms related to gene expression independent of DNA sequence, mostly mediated by modification of chromatin histones. It has recently been suggested that these transcriptional changes may be implicated in the pathophysiology of mood disorders. In addition, histone deacetylase (HDAC) inhibitors have been shown to control epigenetic programming associated with the regulation of cognition and behavior, and may reverse dysfunctional epigenetic regulation associated with early life events in preclinical models. In this context, the active and continuous adaptation of chromatin, and the access of gene promoters to transcription factor mechanisms may represent a potential therapeutic target in the treatment of mood disorders such as bipolar disorder (BD) and major depressive disorder (MDD). Notably, the standard mood stabilizer valproate (VPA) has been shown to modulate the epigenome by inhibiting HDACs. However, several potential limitations are associated with this class of agents, including lack of selectivity for specific HDAC isoforms as well as risk of potentially serious side effects. Further studies regarding the potential role of chromatin remodeling in the mechanism of action of antidepressants and mood stabilizers are necessary to clarify the potential role of this class of agents as therapeutics for mood disorders. PMID:20961400

  3. Gene Environment Interactions in Women With Breast and Secondary Lung Cancer

    DTIC Science & Technology

    2005-07-01

    expression is correlated with benzo [ a ] pyrene -DNA adducts in carcinoma cell lines. Carcinogenesis 1995; 16:2117-2124. 16. Phillips, E.N., et al...with Breast and Secondary Lung Cancer PRINCIPAL INVESTIGATOR: Meredith A . Tennis Peter G...Secondary Lung Cancer 5b. GRANT NUMBER DAMD17-03-1-0300 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Meredith A . Tennis 5d. PROJECT NUMBER Peter G

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

    DTIC Science & Technology

    2005-05-01

    essential for primary prevention. 14. SUBJECT TERMS 15. NUMBER OF PAGES Epidemiology, environmental exposure, endocrine disruptors , estrogen 7 receptor...residential pesticide use on Long Island, NY" 4 W81XWH-04-1-0507 o American Association for Cancer Research (AACR) and co-chaired mini-symposium on "The...estrogens, including bisphenol A, phthalates and pyrethroid pesticides . "o The collection of serial urine samples will be completed in April 2005. "o

  5. 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…

  6. 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 ...

  7. Gene-environment interplay in the link of friends' and nonfriends' behaviors with children's social reticence in a competitive situation.

    PubMed

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

    2014-03-01

    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 nonfriends' behaviors and (b) children's social reticence were examined. The sample comprised 466 twin children (i.e., the target children), each of whom was assessed in kindergarten together with a same-sex friend and two nonfriend classmates of either sex. Multilevel regression analyses revealed that children with a genetic disposition for social reticence showed more reticent behavior in the competitive situation and were more likely to affiliate with reticent friends (i.e., rGE). Moreover, a higher level of children's reticent behavior was predicted by their friends' higher social reticence (particularly for girls) and their friends' higher social dominance, independently of children's genetic disposition. Children's social reticence was also predicted by their nonfriends' behaviors. Specifically, children were less reticent when male nonfriends showed high levels of social reticence in the competitive situation, and this was particularly true for children with a genetic disposition for social reticence (i.e., GxE). Moreover, children genetically vulnerable for social reticence seemed to foster dominant behavior in their female nonfriend peers (i.e., rGE). In turn, male nonfriends seemed to be more dominant as soon as the target children were reticent, even if the target children did not have a stable genetic disposition for this behavior.

  8. Exclusively visual analysis of classroom group interactions

    NASA Astrophysics Data System (ADS)

    Tucker, Laura; Scherr, Rachel E.; Zickler, Todd; Mazur, Eric

    2016-12-01

    Large-scale audiovisual data that measure group learning are time consuming to collect and analyze. As an initial step towards scaling qualitative classroom observation, we qualitatively coded classroom video using an established coding scheme with and without its audio cues. We find that interrater reliability is as high when using visual data only—without audio—as when using both visual and audio data to code. Also, interrater reliability is high when comparing use of visual and audio data to visual-only data. We see a small bias to code interactions as group discussion when visual and audio data are used compared with video-only data. This work establishes that meaningful educational observation can be made through visual information alone. Further, it suggests that after initial work to create a coding scheme and validate it in each environment, computer-automated visual coding could drastically increase the breadth of qualitative studies and allow for meaningful educational analysis on a far greater scale.

  9. Results from Action Analysis in an Interactive Learning Environment

    ERIC Educational Resources Information Center

    Scheuer, Oliver; Muhlenbrock, Martin; Melis, Erica

    2007-01-01

    Recently, there is a growing interest in the automatic analysis of learner activity in web-based learning environments. The approach and system SIAM (System for Interaction Analysis by Machine learning) presented in this article aims at helping to establish a basis for the automatic analysis of interaction data by developing a data logging and…

  10. Cognitive change in aging: identifying gene-environment correlation and nonshared environment mechanisms.

    PubMed

    Deater-Deckard, Kirby; Mayr, Ulrich

    2005-03-01

    We describe gene-environment processes that may help account for individual differences in successful aging. Our emphasis is on successful aging in the cognitive domain, wherein individuals come to use a variety of strategies to cope with changes in cognitive capacities. We focus on the role of executive control in particular and define gene-environment correlation and nonshared environmental mechanisms. The quantitative genetic methods used to identify these mechanisms are described, with examples from research in childhood, where such studies are now common. Future work will be most effective if it is guided by life-span development frameworks that address these processes, such as the developmental genotype-->environment theory of Scarr and McCartney and the selection/optimization/compensation theory of Baltes and Baltes.

  11. Interaction Pattern Analysis in cMOOCs Based on the Connectivist Interaction and Engagement Framework

    ERIC Educational Resources Information Center

    Wang, Zhijun; Anderson, Terry; Chen, Li; Barbera, Elena

    2017-01-01

    Connectivist learning is interaction-centered learning. A framework describing interaction and cognitive engagement in connectivist learning was constructed using logical reasoning techniques. The framework and analysis was designed to help researchers and learning designers understand and adapt the characteristics and principles of interaction in…

  12. An Empirical Analysis of Interactivity in Teleconference.

    ERIC Educational Resources Information Center

    Mishra, Sanjaya

    1999-01-01

    Reports on the nature of interaction during one-way video and two-way audio teleconference sessions at the Indira Gandhi National Open University (IGNOU) based on recording of actual interaction and participants' reactions. Suggests a design for an ideal teleconference session, based on findings of the study. Includes seven tables. (AEF)

  13. Interactive Graphics Tools for Analysis of MOLA and Other Data

    NASA Technical Reports Server (NTRS)

    Frey, H.; Roark, J.; Sakimoto, S.

    2000-01-01

    We have developed several interactive analysis tools based on the IDL programming language for the analysis of Mars Orbiting Laser Altimeter (MOLA) profile and gridded data which are available to the general community.

  14. Gene-environment interplay in Drosophila melanogaster: chronic food deprivation in early life affects adult exploratory and fitness traits.

    PubMed

    Burns, James Geoffrey; Svetec, Nicolas; Rowe, Locke; Mery, Frederic; Dolan, Michael J; Boyce, W Thomas; Sokolowski, Marla B

    2012-10-16

    Early life adversity has known impacts on adult health and behavior, yet little is known about the gene-environment interactions (GEIs) that underlie these consequences. We used the fruit fly Drosophila melanogaster to show that chronic early nutritional adversity interacts with rover and sitter allelic variants of foraging (for) to affect adult exploratory behavior, a phenotype that is critical for foraging, and reproductive fitness. Chronic nutritional adversity during adulthood did not affect rover or sitter adult exploratory behavior; however, early nutritional adversity in the larval period increased sitter but not rover adult exploratory behavior. Increasing for gene expression in the mushroom bodies, an important center of integration in the fly brain, changed the amount of exploratory behavior exhibited by sitter adults when they did not experience early nutritional adversity but had no effect in sitters that experienced early nutritional adversity. Manipulation of the larval nutritional environment also affected adult reproductive output of sitters but not rovers, indicating GEIs on fitness itself. The natural for variants are an excellent model to examine how GEIs underlie the biological embedding of early experience.

  15. VIC: A Computer Analysis of Verbal Interaction Category Systems.

    ERIC Educational Resources Information Center

    Kline, John A.; And Others

    VIC is a computer program for the analysis of verbal interaction category systems, especially the Flanders interaction analysis system. The observer codes verbal behavior on coding sheets for later machine scoring. A matrix is produced by the program showing the number and percentages of times that a particular cell describes classroom behavior.…

  16. Analysis of Human-Spacesuit Interaction

    NASA Technical Reports Server (NTRS)

    Thomas, Neha

    2015-01-01

    Astronauts sustain injuries of various natures such as finger delamination, joint pain, and redness due to their interaction with the space suit. The role of the Anthropometry and Biomechanics Facility is to understand the biomechanics, environmental variables, and ergonomics of the suit. This knowledge is then used to make suggestions for improvement in future iterations of the space suit assembly to prevent injuries while allowing astronauts maneuverability, comfort, and tactility. The projects I was involved in were the Extravehicular Mobility Unit (EMU) space suit stiffness study and the glove feasibility study. The EMU project looked at the forces exerted on the shoulder, arm, and wrist when subjects performed kinematic tasks with and without a pressurized suit. The glove study consisted of testing three conditions - the Series 4000 glove, the Phase VI glove, and the no glove condition. With more than forty channels of sensor data total, it was critical to develop programs that could analyze data with basic descriptive statistics and generate relevant graphs to help understand what happens within the space suit and glove. In my project I created a Graphical User Interface (GUI) in MATLAB that would help me visualize what each sensor was doing within a task. The GUI is capable of displaying overlain plots and can be synchronized with video. This was helpful during the stiffness testing to visualize how the forces on the arm acted while the subject performed tasks such as shoulder adduction/abduction and bicep curls. The main project of focus, however, was the glove comparison study. I wrote MATLAB programs which generated movies of the strain vectors during specific tasks. I also generated graphs that summarized the differences between each glove for the strain, shear and FSR sensors. Preliminary results indicate that the Phase VI glove places less strain and shear on the hand. Future work includes continued data analysis of surveys and sensor data. In the end

  17. Protein interaction discovery using parallel analysis of translated ORFs (PLATO).

    PubMed

    Zhu, Jian; Larman, H Benjamin; Gao, Geng; Somwar, Romel; Zhang, Zijuan; Laserson, Uri; Ciccia, Alberto; Pavlova, Natalya; Church, George; Zhang, Wei; Kesari, Santosh; Elledge, Stephen J

    2013-04-01

    Identifying physical interactions between proteins and other molecules is a critical aspect of biological analysis. Here we describe PLATO, an in vitro method for mapping such interactions by affinity enrichment of a library of full-length open reading frames displayed on ribosomes, followed by massively parallel analysis using DNA sequencing. We demonstrate the broad utility of the method for human proteins by identifying known and previously unidentified interacting partners of LYN kinase, patient autoantibodies, and the small-molecules gefitinib and dasatinib.

  18. A novel statistic for genome-wide interaction analysis.

    PubMed

    Wu, Xuesen; Dong, Hua; Luo, Li; Zhu, Yun; Peng, Gang; Reveille, John D; Xiong, Momiao

    2010-09-23

    Although great progress in genome-wide association studies (GWAS) has been made, the significant SNP associations identified by GWAS account for only a few percent of the genetic variance, leading many to question where and how we can find the missing heritability. There is increasing interest in genome-wide interaction analysis as a possible source of finding heritability unexplained by current GWAS. However, the existing statistics for testing interaction have low power for genome-wide interaction analysis. To meet challenges raised by genome-wide interactional analysis, we have developed a novel statistic for testing interaction between two loci (either linked or unlinked). The null distribution and the type I error rates of the new statistic for testing interaction are validated using simulations. Extensive power studies show that the developed statistic has much higher power to detect interaction than classical logistic regression. The results identified 44 and 211 pairs of SNPs showing significant evidence of interactions with FDR<0.001 and 0.001interacting pairs of SNPs in genes LST1/NCR3, CXCR5/BCL9L, and GLS2, some of which were located in the target sites of miR-324-3p, miR-433, and miR-382, as well as 15 pairs of interacting SNPs that had nonsynonymous substitutions. Our results demonstrated that genome-wide interaction analysis is a valuable tool for finding remaining missing heritability unexplained by the current GWAS, and the developed novel statistic is able to search significant interaction between SNPs across the genome. Real data analysis showed that the results of genome-wide interaction analysis can be replicated in two independent studies.

  19. Theoretical analysis of dynamic processes for interacting molecular motors

    NASA Astrophysics Data System (ADS)

    Teimouri, Hamid; Kolomeisky, Anatoly B.; Mehrabiani, Kareem

    2015-02-01

    Biological transport is supported by the collective dynamics of enzymatic molecules that are called motor proteins or molecular motors. Experiments suggest that motor proteins interact locally via short-range potentials. We investigate the fundamental role of these interactions by carrying out an analysis of a new class of totally asymmetric exclusion processes, in which interactions are accounted for in a thermodynamically consistent fashion. This allows us to explicitly connect microscopic features of motor proteins with their collective dynamic properties. A theoretical analysis that combines various mean-field calculations and computer simulations suggests that the dynamic properties of molecular motors strongly depend on the interactions, and that the correlations are stronger for interacting motor proteins. Surprisingly, it is found that there is an optimal strength of interactions (weak repulsion) that leads to a maximal particle flux. It is also argued that molecular motor transport is more sensitive to attractive interactions. Applications of these results for kinesin motor proteins are discussed.

  20. Mutual Group Hypnosis: A Social Interaction Analysis.

    ERIC Educational Resources Information Center

    Sanders, Shirley

    Mutual Group Hypnosis is discussed in terms of its similarity to group dynamics in general and in terms of its similarity to a social interaction program (Role Modeling) designed to foster the expression of warmth and acceptance among group members. Hypnosis also fosters a regression to prelogical thought processes in the service of the ego. Group…

  1. Computational Analysis of Towed Ballute Interactions

    NASA Technical Reports Server (NTRS)

    Gnoffo, Peter A.; Anderson, Brian P.

    2002-01-01

    A ballute (balloon-parachute) is an inflatable, aerodynamic drag device for application to planetary entry vehicles. Ballutes may be directly attached to a vehicle, increasing its cross-sectional area upon inflation, or towed behind the vehicle as a semi-independent device that can be quickly cut free when the requisite change in velocity is achieved. The aerothermodynamics of spherical and toroidal towed ballutes are considered in the present study. A limiting case of zero towline length (clamped system) is also considered. A toroidal system can be designed (ignoring influence of the tethers) such that all flow processed by the bow shock of the towing spacecraft passes through the hole in the toroid. For a spherical ballute, towline length is a critical parameter that affects aeroheating on the ballute being towed through the spacecraft wake. In both cases, complex and often unsteady interactions ensue in which the spacecraft and its wake resemble an aero spike situated in front of the ballute. The strength of the interactions depends upon system geometry and Reynolds number. We show how interactions may envelope the base of the towing spacecraft or impinge on the ballute surface with adverse consequences to its thermal protection system. Geometric constraints to minimize or eliminate such adverse interactions are discussed. The towed, toroidal system and the clamped, spherical system show greatest potential for a baseline design approach.

  2. Analysis of geophysical measurements and spacecraft interactions

    NASA Astrophysics Data System (ADS)

    Bass, J. N.; Bhavnani, K. H.; Bonito, N. A.; Bounar, K. H.; Grady, P. L.

    1993-01-01

    Investigations were supported to analyze geophysical measurements with integrated applications of ephemerides physics and mathematics of the ionosphere and near space. The projects undertaken included analytical and computational simulation of the interactive spacecraft processes associated with the following: charging, contamination, liquid venting, and critical ionization velocity; data based and analytical investigations of trapped particles, dosage, magnetic fields, and instrumentation for the CRRES experiment; and data based studies of auroral electron and ion precipitation including neural network techniques, ionospheric scintillation and OTH backscatter, and atmospheric density and orbital decay. Systems were developed and applied for calibration and processing of the CRRES and APEX magnetometers, and for generation of satellite attitude and ephemeris. Techniques employed for applying coordinate systems, depicting vehicle and astronomical circumstances, and interactively presenting data in conventional and color formats are also described.

  3. Quest: The Interactive Test Analysis System.

    ERIC Educational Resources Information Center

    Adams, Raymond J.; Khoo, Siek-Toon

    The Quest program offers a comprehensive test and questionnaire analysis environment by providing a data analyst (a computer program) with access to the most recent developments in Rasch measurement theory, as well as a range of traditional analysis procedures. This manual helps the user use Quest to construct and validate variables based on…

  4. PIC. Profile of Interaction in the Classroom. A Quick Feedback of Interaction Analysis.

    ERIC Educational Resources Information Center

    Brunner, Ellen

    The Profile of Interaction in the Classroom (PIC) is a short-cut method of interaction analysis that can provide the quick feedback essential to effective supervision of instruction. And because the PIC contains a record of all the behaviors that occurred in the classroom, as well as the sequence, the data may be used to build a traditional…

  5. Interactive visualization and analysis of transitional flow.

    PubMed

    Johnson, Gregory P; Calo, Victor M; Gaither, Kelly P

    2008-01-01

    A stand-alone visualization application has been developed by a multi-disciplinary, collaborative team with the sole purpose of creating an interactive exploration environment allowing turbulent flow researchers to experiment and validate hypotheses using visualization. This system has specific optimizations made in data management, caching computations, and visualization allowing for the interactive exploration of datasets on the order of 1TB in size. Using this application, the user (co-author Calo) is able to interactively visualize and analyze all regions of a transitional flow volume, including the laminar, transitional and fully turbulent regions. The underlying goal of the visualizations produced from these transitional flow simulations is to localize turbulent spots in the laminar region of the boundary layer, determine under which conditions they form, and follow their evolution. The initiation of turbulent spots, which ultimately lead to full turbulence, was located via a proposed feature detection condition and verified by experimental results. The conditions under which these turbulent spots form and coalesce are validated and presented.

  6. Interpretations of education about gene-environment influences on health in rural Ethiopia: the context of a neglected tropical disease

    PubMed Central

    Tora, Abebayehu; Ayode, Desta; Tadele, Getnet; Farrell, David; Davey, Gail; McBride, Colleen M.

    2016-01-01

    Background Misunderstandings of the role of genetics in disease development are associated with stigmatizing behaviors and fatalistic attitudes about prevention. This report describes an evaluation of community understanding of an educational module about genetic and environmental influences on the development of podoconiosis, a neglected tropical disease endemic in highland Ethiopia. Methods A qualitative process assessment was conducted as part of a large prospective intervention trial in August 2013, in Wolaita Zone, southern Ethiopia. Sixty five participants were purposively selected from 600 households randomized to receive the inherited susceptibility module. The educational module used pictorial representations and oral explanations of the interaction of inherited sensitivity and soil exposure and was delivered by lay health educators in participants' homes. Data were collected using semi-structured individual interviews (IDIs) or focus group discussions (FGDs). Results Qualitative analyses showed that most participants improved their understanding of inherited soil sensitivity and susceptibility to podoconiosis. Participants linked their new understanding to decreased stigma-related attitudes. The module also corrected misconceptions that the condition was contagious, again diminishing stigmatizing attitudes. Lastly, these improvements in understanding increased the perceived value of foot protection. Conclusions Taken together, these improvements support the acceptability, feasibility and potential benefits of implementing gene-environment education in low and middle income countries. PMID:27114426

  7. 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.

  8. Spacelab data analysis and interactive control study

    NASA Technical Reports Server (NTRS)

    Tarbell, T. D.; Drake, J. F.

    1980-01-01

    The study consisted of two main tasks, a series of interviews of Spacelab users and a survey of data processing and display equipment. Findings from the user interviews on questions of interactive control, downlink data formats, and Spacelab computer software development are presented. Equipment for quick look processing and display of scientific data in the Spacelab Payload Operations Control Center (POCC) was surveyed. Results of this survey effort are discussed in detail, along with recommendations for NASA development of several specific display systems which meet common requirements of many Spacelab experiments.

  9. Theoretical Analysis of Dynamic Processes for Interacting Molecular Motors.

    PubMed

    Teimouri, Hamid; Kolomeisky, Anatoly B; Mehrabiani, Kareem

    2015-02-13

    Biological transport is supported by collective dynamics of enzymatic molecules that are called motor proteins or molecular motors. Experiments suggest that motor proteins interact locally via short-range potentials. We investigate the fundamental role of these interactions by analyzing a new class of totally asymmetric exclusion processes where interactions are accounted for in a thermodynamically consistent fashion. It allows us to connect explicitly microscopic features of motor proteins with their collective dynamic properties. Theoretical analysis that combines various mean-field calculations and computer simulations suggests that dynamic properties of molecular motors strongly depend on interactions, and correlations are stronger for interacting motor proteins. Surprisingly, it is found that there is an optimal strength of interactions (weak repulsion) that leads to a maximal particle flux. It is also argued that molecular motors transport is more sensitive to attractive interactions. Applications of these results for kinesin motor proteins are discussed.

  10. MURR nodal analysis with simple interactive simulation

    NASA Astrophysics Data System (ADS)

    Enani, Mohammad Abdulsamad

    The main goal of this research is to design and produce computer codes that should do a NODAL analysis of the core of Missouri University Research Reactor 'MURR' with a simple neutron transient simulation. These codes should be executed on any of the family of the widely used modern IBM/PC (or IBM/PS) microcomputers (or compatibles). The nodal analysis code should find the power (or flux) distribution inside the reactor core and calculate fuel burnup for each of the fuel elements by using the nodal analysis technique described in chapter 3. The simulator code is a relatively simple, educational aid of MURR reactor kinetics simulation that uses one group point reactor model.

  11. Interactive Textiles Front End Analysis. Phase 1

    DTIC Science & Technology

    1998-11-01

    them with a thin film of piezoelectric materials, such as PZT (lead zirconate titanate), PVDF (polyvinyldiflouride) and zinc oxide. In the second...APPROACH: Pursue design, analysis, and testing of three sound reduction schemes: (1) tiles comprising a PVDF actuator, a distributed thin film PVDF ...Structural Composites: Piezoelectric Film Deposition on Intercalated Carbon Fibers Principle Investigator: R. Dillon; Nebraska Univ Engineering (Mech) Dept

  12. An integrated platform for biomolecule interaction analysis

    NASA Astrophysics Data System (ADS)

    Jan, Chia-Ming; Tsai, Pei-I.; Chou, Shin-Ting; Lee, Shu-Sheng; Lee, Chih-Kung

    2013-02-01

    We developed a new metrology platform which can detect real-time changes in both a phase-interrogation mode and intensity mode of a SPR (surface plasmon resonance). We integrated a SPR and ellipsometer to a biosensor chip platform to create a new biomolecular interaction measurement mechanism. We adopted a conductive ITO (indium-tinoxide) film to the bio-sensor platform chip to expand the dynamic range and improve measurement accuracy. The thickness of the conductive film and the suitable voltage constants were found to enhance performance. A circularly polarized ellipsometry configuration was incorporated into the newly developed platform to measure the label-free interactions of recombinant human C-reactive protein (CRP) with immobilized biomolecule target monoclonal human CRP antibody at various concentrations. CRP was chosen as it is a cardiovascular risk biomarker and is an acute phase reactant as well as a specific prognostic indicator for inflammation. We found that the sensitivity of a phaseinterrogation SPR is predominantly dependent on the optimization of the sample incidence angle. The effect of the ITO layer effective index under DC and AC effects as well as an optimal modulation were experimentally performed and discussed. Our experimental results showed that the modulated dynamic range for phase detection was 10E-2 RIU based on a current effect and 10E-4 RIU based on a potential effect of which a 0.55 (°/RIU) measurement was found by angular-interrogation. The performance of our newly developed metrology platform was characterized to have a higher sensitivity and less dynamic range when compared to a traditional full-field measurement system.

  13. Framework for Interactive Parallel Dataset Analysis on the Grid

    SciTech Connect

    Alexander, David A.; Ananthan, Balamurali; Johnson, Tony; Serbo, Victor; /SLAC

    2007-01-10

    We present a framework for use at a typical Grid site to facilitate custom interactive parallel dataset analysis targeting terabyte-scale datasets of the type typically produced by large multi-institutional science experiments. We summarize the needs for interactive analysis and show a prototype solution that satisfies those needs. The solution consists of desktop client tool and a set of Web Services that allow scientists to sign onto a Grid site, compose analysis script code to carry out physics analysis on datasets, distribute the code and datasets to worker nodes, collect the results back to the client, and to construct professional-quality visualizations of the results.

  14. Mass spectrometric analysis of protein–ligand interactions

    PubMed Central

    Ishii, Kentaro; Noda, Masanori; Uchiyama, Susumu

    2016-01-01

    The interactions of small molecules with proteins (protein–ligand interactions) mediate various biological phenomena including signal transduction and protein transcription and translation. Synthetic compounds such as drugs can also bind to target proteins, leading to the inhibition of protein–ligand interactions. These interactions typically accompany association–dissociation equilibrium according to the free energy difference between free and bound states; therefore, the quantitative biophysical analysis of the interactions, which uncovers the stoichiometry and dissociation constant, is important for understanding biological reactions as well as for rational drug development. Mass spectrometry (MS) has been used to determine the precise molecular masses of molecules. Recent advancements in MS enable us to determine the molecular masses of protein–ligand complexes without disrupting the non-covalent interactions through the gentle desolvation of the complexes by increasing the vacuum pressure of a chamber in a mass spectrometer. This method is called MS under non-denaturing conditions or native MS and allows the unambiguous determination of protein–ligand interactions. Under a few assumptions, MS has also been applied to determine the dissociation constants for protein–ligand interactions. The structural information of a protein–ligand interaction, such as the location of the interaction and conformational change in a protein, can also be analyzed using hydrogen/deuterium exchange MS. In this paper, we briefly describe the history, principle, and recent applications of MS for the study of protein–ligand interactions. PMID:27924262

  15. Digital interactive image analysis by array processing

    NASA Technical Reports Server (NTRS)

    Sabels, B. E.; Jennings, J. D.

    1973-01-01

    An attempt is made to draw a parallel between the existing geophysical data processing service industries and the emerging earth resources data support requirements. The relationship of seismic data analysis to ERTS data analysis is natural because in either case data is digitally recorded in the same format, resulting from remotely sensed energy which has been reflected, attenuated, shifted and degraded on its path from the source to the receiver. In the seismic case the energy is acoustic, ranging in frequencies from 10 to 75 cps, for which the lithosphere appears semi-transparent. In earth survey remote sensing through the atmosphere, visible and infrared frequency bands are being used. Yet the hardware and software required to process the magnetically recorded data from the two realms of inquiry are identical and similar, respectively. The resulting data products are similar.

  16. Interactive Spectral Analysis and Computation (ISAAC)

    NASA Technical Reports Server (NTRS)

    Lytle, D. M.

    1992-01-01

    Isaac is a task in the NSO external package for IRAF. A descendant of a FORTRAN program written to analyze data from a Fourier transform spectrometer, the current implementation has been generalized sufficiently to make it useful for general spectral analysis and other one dimensional data analysis tasks. The user interface for Isaac is implemented as an interpreted mini-language containing a powerful, programmable vector calculator. Built-in commands provide much of the functionality needed to produce accurate line lists from input spectra. These built-in functions include automated spectral line finding, least squares fitting of Voigt profiles to spectral lines including equality constraints, various filters including an optimal filter construction tool, continuum fitting, and various I/O functions.

  17. Large-Scale Identification and Analysis of Suppressive Drug Interactions

    PubMed Central

    Cokol, Murat; Weinstein, Zohar B.; Yilancioglu, Kaan; Tasan, Murat; Doak, Allison; Cansever, Dilay; Mutlu, Beste; Li, Siyang; Rodriguez-Esteban, Raul; Akhmedov, Murodzhon; Guvenek, Aysegul; Cokol, Melike; Cetiner, Selim; Giaever, Guri; Iossifov, Ivan; Nislow, Corey; Shoichet, Brian; Roth, Frederick P.

    2014-01-01

    SUMMARY One drug may suppress the effects of another. Although knowledge of drug suppression is vital to avoid efficacy-reducing drug interactions or discover countermeasures for chemical toxins, drug-drug suppression relationships have not been systematically mapped. Here, we analyze the growth response of Saccharomyces cerevisiae to anti-fungal compound (“drug”) pairs. Among 440 ordered drug pairs, we identified 94 suppressive drug interactions. Using only pairs not selected on the basis of their suppression behavior, we provide an estimate of the prevalence of suppressive interactions between anti-fungal compounds as 17%. Analysis of the drug suppression network suggested that Bromopyruvate is a frequently suppressive drug and Staurosporine is a frequently suppressed drug. We investigated potential explanations for suppressive drug interactions, including chemogenomic analysis, coaggregation, and pH effects, allowing us to explain the interaction tendencies of Bromopyruvate. PMID:24704506

  18. Quantitative analysis of intermolecular interactions in orthorhombic rubrene

    SciTech Connect

    Hathwar, Venkatesha R.; Sist, Mattia; Jørgensen, Mads R. V.; Mamakhel, Aref H.; Wang, Xiaoping; Hoffmann, Christina M.; Sugimoto, Kunihisa; Overgaard, Jacob; Iversen, Bo Brummerstedt

    2015-08-14

    Rubrene is one of the most studied organic semiconductors to date due to its high charge carrier mobility which makes it a potentially applicable compound in modern electronic devices. Previous electronic device characterizations and first principles theoretical calculations assigned the semiconducting properties of rubrene to the presence of a large overlap of the extended π-conjugated core between molecules. We present here the electron density distribution in rubrene at 20 K and at 100 K obtained using a combination of high-resolution X-ray and neutron diffraction data. The topology of the electron density and energies of intermolecular interactions are studied quantitatively. Specifically, the presence of Cπ...Cπinteractions between neighbouring tetracene backbones of the rubrene molecules is experimentally confirmed from a topological analysis of the electron density, Non-Covalent Interaction (NCI) analysis and the calculated interaction energy of molecular dimers. A significant contribution to the lattice energy of the crystal is provided by H—H interactions. The electron density features of H—H bonding, and the interaction energy of molecular dimers connected by H—H interaction clearly demonstrate an importance of these weak interactions in the stabilization of the crystal structure. Finally, the quantitative nature of the intermolecular interactions is virtually unchanged between 20 K and 100 K suggesting that any changes in carrier transport at these low temperatures would have a different origin. The obtained experimental results are further supported by theoretical calculations.

  19. Quantitative analysis of intermolecular interactions in orthorhombic rubrene

    PubMed Central

    Hathwar, Venkatesha R.; Sist, Mattia; Jørgensen, Mads R. V.; Mamakhel, Aref H.; Wang, Xiaoping; Hoffmann, Christina M.; Sugimoto, Kunihisa; Overgaard, Jacob; Iversen, Bo Brummerstedt

    2015-01-01

    Rubrene is one of the most studied organic semiconductors to date due to its high charge carrier mobility which makes it a potentially applicable compound in modern electronic devices. Previous electronic device characterizations and first principles theoretical calculations assigned the semiconducting properties of rubrene to the presence of a large overlap of the extended π-conjugated core between molecules. We present here the electron density distribution in rubrene at 20 K and at 100 K obtained using a combination of high-resolution X-ray and neutron diffraction data. The topology of the electron density and energies of intermolecular interactions are studied quantitatively. Specifically, the presence of Cπ⋯Cπ interactions between neighbouring tetracene backbones of the rubrene molecules is experimentally confirmed from a topological analysis of the electron density, Non-Covalent Interaction (NCI) analysis and the calculated interaction energy of molecular dimers. A significant contribution to the lattice energy of the crystal is provided by H—H interactions. The electron density features of H—H bonding, and the interaction energy of molecular dimers connected by H—H interaction clearly demonstrate an importance of these weak interactions in the stabilization of the crystal structure. The quantitative nature of the intermolecular interactions is virtually unchanged between 20 K and 100 K suggesting that any changes in carrier transport at these low temperatures would have a different origin. The obtained experimental results are further supported by theoretical calculations. PMID:26306198

  20. Quantitative analysis of intermolecular interactions in orthorhombic rubrene

    DOE PAGES

    Hathwar, Venkatesha R.; Sist, Mattia; Jørgensen, Mads R. V.; ...

    2015-08-14

    Rubrene is one of the most studied organic semiconductors to date due to its high charge carrier mobility which makes it a potentially applicable compound in modern electronic devices. Previous electronic device characterizations and first principles theoretical calculations assigned the semiconducting properties of rubrene to the presence of a large overlap of the extended π-conjugated core between molecules. We present here the electron density distribution in rubrene at 20 K and at 100 K obtained using a combination of high-resolution X-ray and neutron diffraction data. The topology of the electron density and energies of intermolecular interactions are studied quantitatively. Specifically,more » the presence of Cπ...Cπinteractions between neighbouring tetracene backbones of the rubrene molecules is experimentally confirmed from a topological analysis of the electron density, Non-Covalent Interaction (NCI) analysis and the calculated interaction energy of molecular dimers. A significant contribution to the lattice energy of the crystal is provided by H—H interactions. The electron density features of H—H bonding, and the interaction energy of molecular dimers connected by H—H interaction clearly demonstrate an importance of these weak interactions in the stabilization of the crystal structure. Finally, the quantitative nature of the intermolecular interactions is virtually unchanged between 20 K and 100 K suggesting that any changes in carrier transport at these low temperatures would have a different origin. The obtained experimental results are further supported by theoretical calculations.« less

  1. The First Pilot Genome-Wide Gene-Environment Study of Depression in the Japanese Population

    PubMed Central

    Otowa, Takeshi; Kawamura, Yoshiya; Tsutsumi, Akizumi; Kawakami, Norito; Kan, Chiemi; Shimada, Takafumi; Umekage, Tadashi; Kasai, Kiyoto; Tokunaga, Katsushi; Sasaki, Tsukasa

    2016-01-01

    Stressful events have been identified as a risk factor for depression. Although gene–environment (G × E) interaction in a limited number of candidate genes has been explored, no genome-wide search has been reported. The aim of the present study is to identify genes that influence the association of stressful events with depression. Therefore, we performed a genome-wide G × E interaction analysis in the Japanese population. A genome-wide screen with 320 subjects was performed using the Affymetrix Genome-Wide Human Array 6.0. Stressful life events were assessed using the Social Readjustment Rating Scale (SRRS) and depression symptoms were assessed with self-rating questionnaires using the Center for Epidemiologic Studies Depression (CES-D) scale. The p values for interactions between single nucleotide polymorphisms (SNPs) and stressful events were calculated using the linear regression model adjusted for sex and age. After quality control of genotype data, a total of 534,848 SNPs on autosomal chromosomes were further analyzed. Although none surpassed the level of the genome-wide significance, a marginal significant association of interaction between SRRS and rs10510057 with depression were found (p = 4.5 × 10−8). The SNP is located on 10q26 near Regulators of G-protein signaling 10 (RGS10), which encodes a regulatory molecule involved in stress response. When we investigated a similar G × E interaction between depression (K6 scale) and work-related stress in an independent sample (n = 439), a significant G × E effect on depression was observed (p = 0.015). Our findings suggest that rs10510057, interacting with stressors, may be involved in depression risk. Incorporating G × E interaction into GWAS can contribute to find susceptibility locus that are potentially missed by conventional GWAS. PMID:27529621

  2. Thermal analysis of SC quadrupoles in accelerator interaction regions

    SciTech Connect

    Novitski, Igor; Zlobin, Alexander V.; /Fermilab

    2006-09-01

    This paper presents results of a thermal analysis and operation margin calculation performed for NbTi and Nb{sub 3}Sn low-beta quadrupoles in collider interaction regions. Results of the thermal analysis for NbTi quadrupoles are compared with the relevant experimental data. An approach to quench limit measurements for Nb{sub 3}Sn quadrupoles is discussed.

  3. Package for Interactive Analysis of Line Emission

    NASA Technical Reports Server (NTRS)

    Kashyap, Vinay; Hunter, Paul (Technical Monitor)

    2005-01-01

    PINTofALE is an IDL based package to analyze high-resolution grating spectra. The first version was made available to the public on 3 February 2001. Since then we have carried out numerous changes and subsidiary releases. The current release is version 2.0 (released 6 Apr 2004), and we are preparing to release v2.1 within the next month. The changes include bug fixes, upgrades to handle higher versions of IDL and the CHIANTI database, enhancements in user-friendliness, handling of instrument response matrices, and the release of a Markov Chain Monte Carlo based DEM fitting routines. A detailed description of the package, together with fairly detailed documentation, example walk-throughs, and downloadable tar files, are available on-line from http://hea.harvard.edu/PINTofALE/ The website also lists papers that have used PINTofALE in their analysis.

  4. Toward Interactive Scenario Analysis and Exploration

    SciTech Connect

    Gayle, Thomas R.; Summers, Kenneth Lee; Jungels, John; Oppel III, Fred J.

    2015-01-01

    As Modeling and Simulation (M&S) tools have matured, their applicability and importance have increased across many national security challenges. In particular, they provide a way to test how something may behave without the need to do real world testing. However, current and future changes across several factors including capabilities, policy, and funding are driving a need for rapid response or evaluation in ways that many M&S tools cannot address. Issues around large data, computational requirements, delivery mechanisms, and analyst involvement already exist and pose significant challenges. Furthermore, rising expectations, rising input complexity, and increasing depth of analysis will only increase the difficulty of these challenges. In this study we examine whether innovations in M&S software coupled with advances in ''cloud'' computing and ''big-data'' methodologies can overcome many of these challenges. In particular, we propose a simple, horizontally-scalable distributed computing environment that could provide the foundation (i.e. ''cloud'') for next-generation M&S-based applications based on the notion of ''parallel multi-simulation''. In our context, the goal of parallel multi- simulation is to consider as many simultaneous paths of execution as possible. Therefore, with sufficient resources, the complexity is dominated by the cost of single scenario runs as opposed to the number of runs required. We show the feasibility of this architecture through a stable prototype implementation coupled with the Umbra Simulation Framework [6]. Finally, we highlight the utility through multiple novel analysis tools and by showing the performance improvement compared to existing tools.

  5. Size-exclusion chromatography system for macromolecular interaction analysis

    DOEpatents

    Stevens, Fred J.

    1988-01-01

    A low pressure, microcomputer controlled system employing high performance liquid chromatography (HPLC) allows for precise analysis of the interaction of two reversibly associating macromolecules such as proteins. Since a macromolecular complex migrates faster than its components during size-exclusion chromatography, the difference between the elution profile of a mixture of two macromolecules and the summation of the elution profiles of the two components provides a quantifiable indication of the degree of molecular interaction. This delta profile is used to qualitatively reveal the presence or absence of significant interaction or to rank the relative degree of interaction in comparing samples and, in combination with a computer simulation, is further used to quantify the magnitude of the interaction in an arrangement wherein a microcomputer is coupled to analytical instrumentation in a novel manner.

  6. Phase space analysis of some interacting Chaplygin gas models

    NASA Astrophysics Data System (ADS)

    Khurshudyan, M.; Myrzakulov, R.

    2017-02-01

    In this paper we discuss a phase space analysis of various interacting Chaplygin gas models in general relativity. Linear and nonlinear sign changeable interactions are considered. For each case appropriate late time attractors of field equations are found. The Chaplygin gas is one of the dark fluids actively considered in modern cosmology due to the fact that it is a joint model of dark energy and dark matter.

  7. Functional Interaction Network Construction and Analysis for Disease Discovery.

    PubMed

    Wu, Guanming; Haw, Robin

    2017-01-01

    Network-based approaches project seemingly unrelated genes or proteins onto a large-scale network context, therefore providing a holistic visualization and analysis platform for genomic data generated from high-throughput experiments, reducing the dimensionality of data via using network modules and increasing the statistic analysis power. Based on the Reactome database, the most popular and comprehensive open-source biological pathway knowledgebase, we have developed a highly reliable protein functional interaction network covering around 60 % of total human genes and an app called ReactomeFIViz for Cytoscape, the most popular biological network visualization and analysis platform. In this chapter, we describe the detailed procedures on how this functional interaction network is constructed by integrating multiple external data sources, extracting functional interactions from human curated pathway databases, building a machine learning classifier called a Naïve Bayesian Classifier, predicting interactions based on the trained Naïve Bayesian Classifier, and finally constructing the functional interaction database. We also provide an example on how to use ReactomeFIViz for performing network-based data analysis for a list of genes.

  8. NASTRAN analysis of Tokamak vacuum vessel using interactive graphics

    NASA Technical Reports Server (NTRS)

    Miller, A.; Badrian, M.

    1978-01-01

    Isoparametric quadrilateral and triangular elements were used to represent the vacuum vessel shell structure. For toroidally symmetric loadings, MPCs were employed across model boundaries and rigid format 24 was invoked. Nonsymmetric loadings required the use of the cyclic symmetry analysis available with rigid format 49. NASTRAN served as an important analysis tool in the Tokamak design effort by providing a reliable means for assessing structural integrity. Interactive graphics were employed in the finite element model generation and in the post-processing of results. It was felt that model generation and checkout with interactive graphics reduced the modelling effort and debugging man-hours significantly.

  9. A genetic ensemble approach for gene-gene interaction identification

    PubMed Central

    2010-01-01

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

  10. Distributed and interactive visual analysis of omics data.

    PubMed

    Farag, Yehia; Berven, Frode S; Jonassen, Inge; Petersen, Kjell; Barsnes, Harald

    2015-11-03

    The amount of publicly shared proteomics data has grown exponentially over the last decade as the solutions for sharing and storing the data have improved. However, the use of the data is often limited by the manner of which it is made available. There are two main approaches: download and inspect the proteomics data locally, or interact with the data via one or more web pages. The first is limited by having to download the data and thus requires local computational skills and resources, while the latter most often is limited in terms of interactivity and the analysis options available. A solution is to develop web-based systems supporting distributed and fully interactive visual analysis of proteomics data. The use of a distributed architecture makes it possible to perform the computational analysis at the server, while the results of the analysis can be displayed via a web browser without the need to download the whole dataset. Here the challenges related to developing such systems for omics data will be discussed. Especially how this allows for multiple connected interactive visual displays of omics dataset in a web-based setting, and the benefits this provide for computational analysis of proteomics data.This article is part of a Special Issue entitled: Computational Proteomics.

  11. Visual Interaction with Dimensionality Reduction: A Structured Literature Analysis.

    PubMed

    Sacha, Dominik; Zhang, Leishi; Sedlmair, Michael; Lee, John A; Peltonen, Jaakko; Weiskopf, Daniel; North, Stephen C; Keim, Daniel A

    2017-01-01

    Dimensionality Reduction (DR) is a core building block in visualizing multidimensional data. For DR techniques to be useful in exploratory data analysis, they need to be adapted to human needs and domain-specific problems, ideally, interactively, and on-the-fly. Many visual analytics systems have already demonstrated the benefits of tightly integrating DR with interactive visualizations. Nevertheless, a general, structured understanding of this integration is missing. To address this, we systematically studied the visual analytics and visualization literature to investigate how analysts interact with automatic DR techniques. The results reveal seven common interaction scenarios that are amenable to interactive control such as specifying algorithmic constraints, selecting relevant features, or choosing among several DR algorithms. We investigate specific implementations of visual analysis systems integrating DR, and analyze ways that other machine learning methods have been combined with DR. Summarizing the results in a "human in the loop" process model provides a general lens for the evaluation of visual interactive DR systems. We apply the proposed model to study and classify several systems previously described in the literature, and to derive future research opportunities.

  12. Recent applications of hydrophilic interaction liquid chromatography in pharmaceutical analysis.

    PubMed

    Zhang, Qian; Yang, Feng-Qing; Ge, Liya; Hu, Yuan-Jia; Xia, Zhi-Ning

    2017-01-01

    Hydrophilic interaction liquid chromatography, an alternative liquid chromatography mode, is of particular interest in separating hydrophilic and polar ionic compounds. Compared with traditional liquid chromatography techniques, hydrophilic interaction liquid chromatography offers specific advantages mainly including: (1) relatively green and water-soluble mobile phase composition, which enhances the solubility of hydrophilic and polar ionic compounds; (2) no need for ion-pairing reagents and high content of organic solvent, which benefits mass spectrometry detection; (3) high orthogonality to reverse-phase liquid chromatography, well adapted to two-dimensional liquid chromatography for complicated samples. Therefore, hydrophilic interaction liquid chromatography has been rapidly developed in many areas over the past decades. This review summarizes the recent progress (from 2012 to July 2016) of hydrophilic interaction liquid chromatography in pharmaceutical analysis, with the focus on detecting chemical drugs in various matrices, charactering active compounds of natural products and assessing biotherapeutics through typical structure unit. Moreover, the retention mechanism and behavior of analytes in hydrophilic interaction liquid chromatography as well as some novel hydrophilic interaction liquid chromatography columns used for pharmaceutical analysis are also described.

  13. iSat Surface Charging and Thruster Plume Interactions Analysis

    NASA Technical Reports Server (NTRS)

    Parker, L. Neergaard; Willis, E. M.; Minow, J. I.

    2016-01-01

    Characterizing the electromagnetic interaction of a satellite in low Earth, high inclination orbit with the space plasma environment and identifying viable charging mitigation strategies is a critical mission design task. High inclination orbits expose the vehicle to auroral charging environments that can potentially charge surfaces to kilovolt potentials and electric thruster propulsion systems will interact with the ambient plasma environment throughout the orbit. NASA is designing the Iodine Satellite (iSAT) cubesat mission to demonstrate operations of an iodine electric thruster system. The spacecraft will be deployed as a secondary payload from a launch vehicle which has not yet been identified so the program must plan for the worst case environments over a range of orbital inclinations. We will first present results from a NASA and Air Force Charging Analyzer Program (Nascap) -2k surface charging calculation used to evaluate the effects of auroral charging on the spacecraft and to provide the charging levels at other locations in orbit for a thruster plume interaction analysis for the iSAT mission. We will then discuss results from the thruster interactions analysis using the Electric Propulsion Interactions Code (EPIC) with inputs from Nascap-2k. The results of these analyses are being used by the iSAT program to better understand how their spacecraft will interact with the space plasma environment in the range of environments that could be encountered when the final mission orbit is selected.

  14. Morphological Analysis and Interaction of Chlorophyll and BSA

    PubMed Central

    Gorza, Filipe D. S.; Pedro, Graciela C.; Trescher, Tarquin F.; da Silva, Romário J.; Silva, Josmary R.; de Souza, Nara C.

    2014-01-01

    Interactions between proteins and drugs, which can lead to formation of stable drug-protein complexes, have important implications on several processes related to human health. These interactions can affect, for instance, free concentration, biological activity, and metabolism of the drugs in the blood stream. Here, we report on the UV-Visible spectroscopic investigation on the interaction of bovine serum albumin (BSA) with chlorophyll (Chl) in aqueous solution under physiological conditions. Binding constants at different temperatures—obtained by using the Benesi-Hildebrand equation—were found to be of the same order of magnitude (~104 M−1) indicating low affinity of Chl with BSA. We have found a hyperchromism, which suggested an interaction between BSA and Chl occurring through conformational changes of BSA caused by exposition of tryptophan to solvent. Films from BSA and Chl obtained at different Chl concentrations showed fractal structures, which were characterized by fractal dimension calculated from microscopic image analysis. PMID:24963490

  15. iSat Surface Charging and Thruster Plume Interactions Analysis

    NASA Technical Reports Server (NTRS)

    Parker, L. Neergaard; Willis, E.; Minow, J.

    2016-01-01

    NASA is designing the Iodine Satellite (iSAT) cubesat mission to demonstrate operations of an iodine electric thruster system. The spacecraft will be deployed as a secondary payload from a launch vehicle which has not yet been identified so the program must plan for the worst case environments over a range of orbital inclinations. We present results from a NASA and Air Force Charging Analyzer Program (NASCAP-2K) surface charging calculation used to evaluate the effects of charging on the spacecraft and to provide the charging levels at other locations in orbit for a thruster plume interaction analysis for the iSAT mission. We will then discuss results from the thruster interactions analysis using the Electric Propulsion Interactions Code (EPIC). The results of these analyses are being used by the iSAT program for a range of environments that could be encountered when the final mission orbit is selected.

  16. Direct numerical simulation and analysis of shock turbulence interaction

    NASA Technical Reports Server (NTRS)

    Lee, Sangsan; Lele, Sanjiva K.; Moin, Parviz

    1991-01-01

    Two kinds of linear analysis, rapid distortion theory (RDT) and linear interaction analysis (LIA), were used to investigate the effects of a shock wave on turbulence. Direct numerical simulations of two-dimensional isotropic turbulence interaction with a normal shock were also performed. The results from RDT and LIA are in good agreement for weak shock waves, where the effects of shock front curvature and shock front unsteadiness are not significant in producing vorticity. The linear analyses predict wavenumber-dependent amplification of the upstream one-dimensional energy spectrum, leading to turbulence scale length scale decrease through the interaction. Instantaneous vorticity fields show that vortical structures are enhanced while they are compressed in the shock normal direction. Entrophy amplfication through the shock wave compares favorably with the results of linear analyses.

  17. Computer-Based Interaction Analysis with DEGREE Revisited

    ERIC Educational Resources Information Center

    Barros, B.; Verdejo, M. F.

    2016-01-01

    We review our research with "DEGREE" and analyse how our work has impacted the collaborative learning community since 2000. Our research is framed within the context of computer-based interaction analysis and the development of computer-supported collaborative learning (CSCL) tools. We identify some aspects of our work which have been…

  18. Analysis of Verbal Interaction in Supervisory Conferences with Student Teachers.

    ERIC Educational Resources Information Center

    Wulff, John W.

    The purpose of the study was to engage college supervisors in analysis of the verbal interaction they employed in conferences with student teachers. Subjects in the study were 14 pairs of college supervisors-elementary student teachers in the Dept. of Elementary Education at a state college in New York during the spring semester of 1971. An…

  19. Graphical Interaction Analysis Impact on Groups Collaborating through Blogs

    ERIC Educational Resources Information Center

    Fessakis, Georgios; Dimitracopoulou, Angelique; Palaiodimos, Aggelos

    2013-01-01

    This paper presents empirical research results regarding the impact of Interaction Analysis (IA) graphs on groups of students collaborating through online blogging according to a "learning by design" scenario. The IA graphs used are of two categories; the first category summarizes quantitatively the activity of the users for each blog,…

  20. MOVANAID: An Interactive Aid for Analysis of Movement Capabilities.

    ERIC Educational Resources Information Center

    Cooper, George E.; And Others

    A computer-drive interactive aid for movement analysis, called MOVANAID, has been developed to be of assistance in the performance of certain Army intelligence processing tasks in a tactical environment. It can compute fastest travel times and paths through road networks for military units of various types, as well as fastest times in which…

  1. COINGRAD; Control Oriented Interactive Graphical Analysis and Design.

    ERIC Educational Resources Information Center

    Volz, Richard A.; And Others

    The computer is currently a vital tool in engineering analysis and design. With the introduction of moderately priced graphics terminals, it will become even more important in the future as rapid graphic interaction between the engineer and the computer becomes more feasible in computer-aided design (CAD). To provide a vehicle for introducing…

  2. Interaction Analysis in Foreign Language Teaching: A Rationale.

    ERIC Educational Resources Information Center

    Swanson, Maria Antonieta Medina

    A system for observing and coding verbal interchanges between the teacher and his pupils, at all instructional levels, is described in this study. The system, widely known as the Flanders System of Interaction Analysis, is reviewed in terms of its effect on the classroom behavior of teachers and on student attitudes. The application of the…

  3. Stochastic Process Analysis of Interactive Discourse in Early Counseling Interviews.

    ERIC Educational Resources Information Center

    Friedlander, Myrna L.; Phillips, Susan D.

    1984-01-01

    Examined patterns of interactive discourse to suggest how client and counselor establish a working alliance in their early interviews. Based on classification of 312 conversational turns from 14 dyads, a stochastic analysis was conducted. Results showed the sequences of talk were highly stable and predictable. (JAC)

  4. Testing Main Effects and Interactions in Latent Curve Analysis

    ERIC Educational Resources Information Center

    Curran, Patrick J.; Bauer, Daniel J.; Willoughby, Michael T.

    2004-01-01

    A key strength of latent curve analysis (LCA) is the ability to model individual variability in rates of change as a function of 1 or more explanatory variables. The measurement of time plays a critical role because the explanatory variables multiplicatively interact with time in the prediction of the repeated measures. However, this interaction…

  5. Group Interaction Analysis for Improvement of Classroom Discussion.

    ERIC Educational Resources Information Center

    Perry, Constance M.

    In order to improve the quality of classroom discussion, Group Interaction Analysis (GIA) is suggested as a means of increasing an individual's awareness of the role he assumes in group discussions. GIA is a systemized technique involving the observation of both beneficial and non-beneficial discussion activities. These activities are: (1) fact…

  6. Links between Friends' Physical Aggression and Adolescents' Physical Aggression: What Happens If Gene-Environment Correlations are Controlled?

    ERIC Educational Resources Information Center

    Vitaro, Frank; Brendgen, Mara; Girard, Alain; Dionne, Ginette; Tremblay, Richard E.; Boivin, Michel

    2016-01-01

    Exposure to deviant friends has been found to be a powerful source of influence on children's and adolescents' aggressive behavior. However, the contribution of deviant friends may have been overestimated because of a possible non-accounted gene-environment correlation (rGE). In this study, we used a cross-lagged design to test whether friends'…

  7. Analysis of Geophysical Data Bases and Models for Spacecraft Interactions.

    DTIC Science & Technology

    1986-10-31

    electrons, protons, ions (major species), and measured dose. - Evaluation of magnetic field models (Delta B Model). - Quasi- static Data Bases, Analysis ...AIB4 889 ANALYSIS OF GEOPHYSICRL DATA BASES AND MODELS FOR 1/3 SPACECRAFT INTERACTIONS(U) RADEX INC CARLISLE MA J N BAS ET AL 31 OCT 86 AFGL-TR-86...1114 11116 MICROCOPY RESOLUTION TEST CHART NATI()NAL BUREAU flE SIANDARD % 43 A oJ P=I -- % AFGL-TR-86-0221 0 00 ANALYSIS OF GEOPHYSICAL DATA BASES

  8. Interactive analysis of a large aperture Earth observations satellite

    NASA Technical Reports Server (NTRS)

    Wright, R. L.; Deryder, D. D.; Ferebee, M. J., Jr.; Smith, J. C.

    1983-01-01

    A system level design and analysis has been conducted on an Earth Observation Satellite (EOS) system using the Interactive Design and Evaluation of Advanced Spacecraft (IDEAS) computer-aided design and analysis program. The IDEAS program consists of about 40 user-friendly technical modules and an interactive graphics display. The reflector support system and feed mast of the EOS spacecraft are constructed with box-truss structural concept, a lattice configuration which can be packaged for delivery in a single Shuttle flight and deployed in orbit. The deployed spacecraft consists of a 120-m by 60-m parabolic focal axis. The spacecraft was modeled for structural, thermal, and control systems analysis and structural elements were designed. On-orbit dynamic and thermal loading analyses were conducted; spacecraft weights and developmental and first unit costs were determined.

  9. Quantitative Analysis of Single-Molecule RNA-Protein Interaction

    PubMed Central

    Fuhrmann, Alexander; Schoening, Jan C.; Anselmetti, Dario; Staiger, Dorothee; Ros, Robert

    2009-01-01

    Abstract RNA-binding proteins impact gene expression at the posttranscriptional level by interacting with cognate cis elements within the transcripts. Here, we apply dynamic single-molecule force spectroscopy to study the interaction of the Arabidopsis glycine-rich RNA-binding protein AtGRP8 with its RNA target. A dwell-time-dependent analysis of the single-molecule data in combination with competition assays and site-directed mutagenesis of both the RNA target and the RNA-binding domain of the protein allowed us to distinguish and quantify two different binding modes. For dwell times <0.21 s an unspecific complex with a lifetime of 0.56 s is observed, whereas dwell times >0.33 s result in a specific interaction with a lifetime of 208 s. The corresponding reaction lengths are 0.28 nm for the unspecific and 0.55 nm for the specific AtGRP8-RNA interactions, indicating formation of a tighter complex with increasing dwell time. These two binding modes cannot be dissected in ensemble experiments. Quantitative titration in RNA bandshift experiments yields an ensemble-averaged equilibrium constant of dissociation of KD = 2 × 10−7 M. Assuming comparable on-rates for the specific and nonspecific binding modes allows us to estimate their free energies as ΔG0 = −42 kJ/mol and ΔG0 = −28 kJ/mol for the specific and nonspecific binding modes, respectively. Thus, we show that single-molecule force spectroscopy with a refined statistical analysis is a potent tool for the analysis of protein-RNA interactions without the drawback of ensemble averaging. This makes it possible to discriminate between different binding modes or sites and to analyze them quantitatively. We propose that this method could be applied to complex interactions of biomolecules in general, and be of particular interest for the investigation of multivalent binding reactions. PMID:19527663

  10. Analysis of the interaction of two parallel surface cracks

    NASA Astrophysics Data System (ADS)

    Hahn, Jeeyeon

    The objective of this research is to analyze and predict the interaction of surface cracks that occur in parallel planes. Multiple cracks may form in aging aircraft that forms at stress concentrations such as fastener holes and notched components by stress corrosion and fatigue cracking. The lifetime of the structures are significantly affected by the interaction between these cracks. Depending on relative positions and orientations of neighboring cracks, local stress fields and crack driving forces can be affected by the presence of adjacent cracks. Even small subcritical cracks may rapidly grow to a size that will cause failure in service due to interaction and coalescence with other cracks. The interaction behavior and crack propagation direction of two parallel surface cracks is studied using three-dimensional finite element analysis (FEA). FEA models with wide range of crack configurations in a finite plate under tension are evaluated to investigate the correlation between the crack shapes and the separation distance between two cracks. The relative distance (vertical and horizontal) between two cracks and size and shape of these cracks are varied to create different stress interaction fields. Stress intensity factors (SIF) along the crack fronts are obtained from FEA, and then, cracking behaviors of the cracks are predicted by considering the influence of the interaction on the SIF and the coalescence of two cracks. The results obtained are then compared with existing experimental and analytical data for validation. All of the data analyses are presented in tabular forms and figures.

  11. Quantitative analysis of protein-ligand interactions by NMR.

    PubMed

    Furukawa, Ayako; Konuma, Tsuyoshi; Yanaka, Saeko; Sugase, Kenji

    2016-08-01

    Protein-ligand interactions have been commonly studied through static structures of the protein-ligand complex. Recently, however, there has been increasing interest in investigating the dynamics of protein-ligand interactions both for fundamental understanding of the underlying mechanisms and for drug development. NMR is a versatile and powerful tool, especially because it provides site-specific quantitative information. NMR has widely been used to determine the dissociation constant (KD), in particular, for relatively weak interactions. The simplest NMR method is a chemical-shift titration experiment, in which the chemical-shift changes of a protein in response to ligand titration are measured. There are other quantitative NMR methods, but they mostly apply only to interactions in the fast-exchange regime. These methods derive the dissociation constant from population-averaged NMR quantities of the free and bound states of a protein or ligand. In contrast, the recent advent of new relaxation-based experiments, including R2 relaxation dispersion and ZZ-exchange, has enabled us to obtain kinetic information on protein-ligand interactions in the intermediate- and slow-exchange regimes. Based on R2 dispersion or ZZ-exchange, methods that can determine the association rate, kon, dissociation rate, koff, and KD have been developed. In these approaches, R2 dispersion or ZZ-exchange curves are measured for multiple samples with different protein and/or ligand concentration ratios, and the relaxation data are fitted to theoretical kinetic models. It is critical to choose an appropriate kinetic model, such as the two- or three-state exchange model, to derive the correct kinetic information. The R2 dispersion and ZZ-exchange methods are suitable for the analysis of protein-ligand interactions with a micromolar or sub-micromolar dissociation constant but not for very weak interactions, which are typical in very fast exchange. This contrasts with the NMR methods that are used

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

    PubMed

    Davids, Keith; Baker, Joseph

    2007-01-01

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

  13. Genes, Environment and Sport Performance : Why the Nature-Nurture Dualism is no Longer Relevant.

    PubMed

    Davids, Keith; Baker, Joseph

    2007-11-01

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

  14. Early-life stress and antidepressant treatment involve synaptic signaling and Erk kinases in a gene-environment model of depression.

    PubMed

    Musazzi, Laura; Mallei, Alessandra; Tardito, Daniela; Gruber, Susanne H M; El Khoury, Aram; Racagni, Giorgio; Mathé, Aleksander A; Popoli, Maurizio

    2010-06-01

    Stress has been shown to interact with genetic vulnerability in pathogenesis of psychiatric disorders. Here we investigated the outcome of interaction between genetic vulnerability and early-life stress, by employing a rodent model that combines an inherited trait of vulnerability in Flinders Sensitive Line (FSL) rats, with early-life stress (maternal separation). Basal differences in synaptic signaling between FSL rats and their controls were studied, as well as the consequences of early-life stress in adulthood, and their response to chronic antidepressant treatment (escitalopram). FSL rats showed basal differences in the activation of synapsin I and Erk1/2, as well as in alpha CaM kinase II/syntaxin-1 and alpha CaM kinase II/NMDA-receptor interactions in purified hippocampal synaptosomes. In addition, FSL rats displayed a blunted response of Erk-MAP kinases and other differences in the outcome of early-life stress in adulthood. Escitalopram treatment restored some but not all alterations observed in FSL rats after early-life stress. The marked alterations found in key regulators of presynaptic release/neurotransmission in the basal FSL rats, and as a result of early-life stress, suggest synaptic dysfunction. These results show that early gene-environment interaction may cause life-long synaptic changes affecting the course of depressive-like behavior and response to drugs.

  15. Analysis of biomolecular interactions using affinity microcolumns: A review

    PubMed Central

    Zheng, Xiwei; Li, Zhao; Beeram, Sandya; Podariu, Maria; Matsuda, Ryan; Pfaunmiller, Erika L.; White, Christopher J.; Carter, NaTasha; Hage, David S.

    2014-01-01

    Affinity chromatography has become an important tool for characterizing biomolecular interactions. The use of affinity microcolumns, which contain immobilized binding agents and have volumes in the mid-to-low microliter range, has received particular attention in recent years. Potential advantages of affinity microcolumns include the many analysis and detection formats that can be used with these columns, as well as the need for only small amounts of supports and immobilized binding agents. This review examines how affinity microcolumns have been used to examine biomolecular interactions. Both capillary-based microcolumns and short microcolumns are considered. The use of affinity microcolumns with zonal elution and frontal analysis methods are discussed. The techniques of peak decay analysis, ultrafast affinity extraction, split-peak analysis, and band-broadening studies are also explored. The principles of these methods are examined and various applications are provided to illustrate the use of these methods with affinity microcolumns. It is shown how these techniques can be utilized to provide information on the binding strength and kinetics of an interaction, as well as on the number and types of binding sites. It is further demonstrated how information on competition or displacement effects can be obtained by these methods. PMID:24572459

  16. Protein-protein interactions: methods for detection and analysis.

    PubMed Central

    Phizicky, E M; Fields, S

    1995-01-01

    The function and activity of a protein are often modulated by other proteins with which it interacts. This review is intended as a practical guide to the analysis of such protein-protein interactions. We discuss biochemical methods such as protein affinity chromatography, affinity blotting, coimmunoprecipitation, and cross-linking; molecular biological methods such as protein probing, the two-hybrid system, and phage display: and genetic methods such as the isolation of extragenic suppressors, synthetic mutants, and unlinked noncomplementing mutants. We next describe how binding affinities can be evaluated by techniques including protein affinity chromatography, sedimentation, gel filtration, fluorescence methods, solid-phase sampling of equilibrium solutions, and surface plasmon resonance. Finally, three examples of well-characterized domains involved in multiple protein-protein interactions are examined. The emphasis of the discussion is on variations in the approaches, concerns in evaluating the results, and advantages and disadvantages of the techniques. PMID:7708014

  17. Wave function analysis of MHC-peptide interactions.

    PubMed

    Cárdenas, Constanza; Obregón, Mateo; Balbín, Alejandro; Villaveces, José Luis; Patarroyo, Manuel E

    2007-01-01

    We have carried out an analysis of the wave function data for three MHC-peptide complexes: HLA-DRbeta1*0101-HA, HLA-DRbeta1*0401-HA and HLA-DRbeta1*0401-Col. We used quantum chemistry computer programs to generate wave function coefficients for these complexes, from which we obtained both molecular and atomic orbital data for both pocket and peptide amino acids within each pocket region. From these discriminated data, interaction molecular orbitals (IMOs) were identified as those with large and similar atomic orbital coefficient contributions from both pocket and peptide amino acids. The present results correlate well with our previous research where only electrostatic moments were used to explore molecular component interactions. Furthermore, we show a quantum chemical methodology to produce more fine-grained results concerning amino acid behavior in the MHC-peptide interaction.

  18. Analysis of DNA interactions using single-molecule force spectroscopy.

    PubMed

    Ritzefeld, Markus; Walhorn, Volker; Anselmetti, Dario; Sewald, Norbert

    2013-06-01

    Protein-DNA interactions are involved in many biochemical pathways and determine the fate of the corresponding cell. Qualitative and quantitative investigations on these recognition and binding processes are of key importance for an improved understanding of biochemical processes and also for systems biology. This review article focusses on atomic force microscopy (AFM)-based single-molecule force spectroscopy and its application to the quantification of forces and binding mechanisms that lead to the formation of protein-DNA complexes. AFM and dynamic force spectroscopy are exciting tools that allow for quantitative analysis of biomolecular interactions. Besides an overview on the method and the most important immobilization approaches, the physical basics of the data evaluation is described. Recent applications of AFM-based force spectroscopy to investigate DNA intercalation, complexes involving DNA aptamers and peptide- and protein-DNA interactions are given.

  19. Social Network Extraction and Analysis Based on Multimodal Dyadic Interaction

    PubMed Central

    Escalera, Sergio; Baró, Xavier; Vitrià, Jordi; Radeva, Petia; Raducanu, Bogdan

    2012-01-01

    Social interactions are a very important component in people’s lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Times’ Blogging Heads opinion blog. The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The links’ weights are a measure of the “influence” a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network. PMID:22438733

  20. Social network extraction and analysis based on multimodal dyadic interaction.

    PubMed

    Escalera, Sergio; Baró, Xavier; Vitrià, Jordi; Radeva, Petia; Raducanu, Bogdan

    2012-01-01

    Social interactions are a very important component in people's lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Times' Blogging Heads opinion blog. The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The links' weights are a measure of the "influence" a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network.

  1. Time-Frequency Analysis Reveals Pairwise Interactions in Insect Swarms

    NASA Astrophysics Data System (ADS)

    Puckett, James G.; Ni, Rui; Ouellette, Nicholas T.

    2015-06-01

    The macroscopic emergent behavior of social animal groups is a classic example of dynamical self-organization, and is thought to arise from the local interactions between individuals. Determining these interactions from empirical data sets of real animal groups, however, is challenging. Using multicamera imaging and tracking, we studied the motion of individual flying midges in laboratory mating swarms. By performing a time-frequency analysis of the midge trajectories, we show that the midge behavior can be segmented into two distinct modes: one that is independent and composed of low-frequency maneuvers, and one that consists of higher-frequency nearly harmonic oscillations conducted in synchrony with another midge. We characterize these pairwise interactions, and make a hypothesis as to their biological function.

  2. Stability and modal analysis of shock/boundary layer interactions

    NASA Astrophysics Data System (ADS)

    Nichols, Joseph W.; Larsson, Johan; Bernardini, Matteo; Pirozzoli, Sergio

    2017-02-01

    The dynamics of oblique shock wave/turbulent boundary layer interactions is analyzed by mining a large-eddy simulation (LES) database for various strengths of the incoming shock. The flow dynamics is first analyzed by means of dynamic mode decomposition (DMD), which highlights the simultaneous occurrence of two types of flow modes, namely a low-frequency type associated with breathing motion of the separation bubble, accompanied by flapping motion of the reflected shock, and a high-frequency type associated with the propagation of instability waves past the interaction zone. Global linear stability analysis performed on the mean LES flow fields yields a single unstable zero-frequency mode, plus a variety of marginally stable low-frequency modes whose stability margin decreases with the strength of the interaction. The least stable linear modes are grouped into two classes, one of which bears striking resemblance to the breathing mode recovered from DMD and another class associated with revolving motion within the separation bubble. The results of the modal and linear stability analysis support the notion that low-frequency dynamics is intrinsic to the interaction zone, but some continuous forcing from the upstream boundary layer may be required to keep the system near a limit cycle. This can be modeled as a weakly damped oscillator with forcing, as in the early empirical model by Plotkin (AIAA J 13:1036-1040, 1975).

  3. Quantitative analysis of triple-mutant genetic interactions.

    PubMed

    Braberg, Hannes; Alexander, Richard; Shales, Michael; Xu, Jiewei; Franks-Skiba, Kathleen E; Wu, Qiuqin; Haber, James E; Krogan, Nevan J

    2014-08-01

    The quantitative analysis of genetic interactions between pairs of gene mutations has proven to be effective for characterizing cellular functions, but it can miss important interactions for functionally redundant genes. To address this limitation, we have developed an approach termed triple-mutant analysis (TMA). The procedure relies on a query strain that contains two deletions in a pair of redundant or otherwise related genes, which is crossed against a panel of candidate deletion strains to isolate triple mutants and measure their growth. A central feature of TMA is to interrogate mutants that are synthetically sick when two other genes are deleted but interact minimally with either single deletion. This approach has been valuable for discovering genes that restore critical functions when the principal actors are deleted. TMA has also uncovered double-mutant combinations that produce severe defects because a third protein becomes deregulated and acts in a deleterious fashion, and it has revealed functional differences between proteins presumed to act together. The protocol is optimized for Singer ROTOR pinning robots, takes 3 weeks to complete and measures interactions for up to 30 double mutants against a library of 1,536 single mutants.

  4. Functional analysis of molecular interactions in synthetic auxin response circuits

    PubMed Central

    Lanctot, Amy; Hageman, Amber; Nemhauser, Jennifer L.

    2016-01-01

    Auxin-regulated transcription pivots on the interaction between the AUXIN/INDOLE-3-ACETIC ACID (Aux/IAA) repressor proteins and the AUXIN RESPONSE FACTOR (ARF) transcription factors. Recent structural analyses of ARFs and Aux/IAAs have raised questions about the functional complexes driving auxin transcriptional responses. To parse the nature and significance of ARF–DNA and ARF–Aux/IAA interactions, we analyzed structure-guided variants of synthetic auxin response circuits in the budding yeast Saccharomyces cerevisiae. Our analysis revealed that promoter architecture could specify ARF activity and that ARF19 required dimerization at two distinct domains for full transcriptional activation. In addition, monomeric Aux/IAAs were able to repress ARF activity in both yeast and plants. This systematic, quantitative structure-function analysis identified a minimal complex—comprising a single Aux/IAA repressing a pair of dimerized ARFs—sufficient for auxin-induced transcription. PMID:27647902

  5. Visual exploration and analysis of human-robot interaction rules

    NASA Astrophysics Data System (ADS)

    Zhang, Hui; Boyles, Michael J.

    2013-01-01

    We present a novel interaction paradigm for the visual exploration, manipulation and analysis of human-robot interaction (HRI) rules; our development is implemented using a visual programming interface and exploits key techniques drawn from both information visualization and visual data mining to facilitate the interaction design and knowledge discovery process. HRI is often concerned with manipulations of multi-modal signals, events, and commands that form various kinds of interaction rules. Depicting, manipulating and sharing such design-level information is a compelling challenge. Furthermore, the closed loop between HRI programming and knowledge discovery from empirical data is a relatively long cycle. This, in turn, makes design-level verification nearly impossible to perform in an earlier phase. In our work, we exploit a drag-and-drop user interface and visual languages to support depicting responsive behaviors from social participants when they interact with their partners. For our principal test case of gaze-contingent HRI interfaces, this permits us to program and debug the robots' responsive behaviors through a graphical data-flow chart editor. We exploit additional program manipulation interfaces to provide still further improvement to our programming experience: by simulating the interaction dynamics between a human and a robot behavior model, we allow the researchers to generate, trace and study the perception-action dynamics with a social interaction simulation to verify and refine their designs. Finally, we extend our visual manipulation environment with a visual data-mining tool that allows the user to investigate interesting phenomena such as joint attention and sequential behavioral patterns from multiple multi-modal data streams. We have created instances of HRI interfaces to evaluate and refine our development paradigm. As far as we are aware, this paper reports the first program manipulation paradigm that integrates visual programming

  6. Imalytics Preclinical: Interactive Analysis of Biomedical Volume Data

    PubMed Central

    Gremse, Felix; Stärk, Marius; Ehling, Josef; Menzel, Jan Robert; Lammers, Twan; Kiessling, Fabian

    2016-01-01

    A software tool is presented for interactive segmentation of volumetric medical data sets. To allow interactive processing of large data sets, segmentation operations, and rendering are GPU-accelerated. Special adjustments are provided to overcome GPU-imposed constraints such as limited memory and host-device bandwidth. A general and efficient undo/redo mechanism is implemented using GPU-accelerated compression of the multiclass segmentation state. A broadly applicable set of interactive segmentation operations is provided which can be combined to solve the quantification task of many types of imaging studies. A fully GPU-accelerated ray casting method for multiclass segmentation rendering is implemented which is well-balanced with respect to delay, frame rate, worst-case memory consumption, scalability, and image quality. Performance of segmentation operations and rendering are measured using high-resolution example data sets showing that GPU-acceleration greatly improves the performance. Compared to a reference marching cubes implementation, the rendering was found to be superior with respect to rendering delay and worst-case memory consumption while providing sufficiently high frame rates for interactive visualization and comparable image quality. The fast interactive segmentation operations and the accurate rendering make our tool particularly suitable for efficient analysis of multimodal image data sets which arise in large amounts in preclinical imaging studies. PMID:26909109

  7. PCLOOK32: an interactive program for the analysis of spectra

    NASA Astrophysics Data System (ADS)

    Tomasi, D.; Macchiavelli, A. O.

    1999-05-01

    In this work we present an interactive program for the analysis of one-dimensional spectra developed to work on a personal computer (PC) platform. This 32-bit program named PCLOOK32, runs as a Windows95/NT application with a graphical user interface that allows the access to different functions via mouse operations. Although tailored to basic or applied nuclear physics work, it can be easily adapted to other applications. Windows95 and WindowsNT are registered trademarks of Microsoft Corporation

  8. The thermodynamic analysis of weak protein interactions using sedimentation equilibrium

    PubMed Central

    Dolinska, Monika B.; Wingfield, Paul T.

    2014-01-01

    Proteins self-associate to form dimers and tetramers. Purified proteins are used to study the thermodynamics of protein interactions using the analytical ultracentrifuge. In this approach, monomer – dimer equilibrium constants are directly measured at various temperatures. Data analysis is used to derive thermodynamic parameters such as Gibbs free energy, enthalpy and entropy which can predict which major forces are involved in protein association. PMID:25081741

  9. Structural mode significance using INCA. [Interactive Controls Analysis computer program

    NASA Technical Reports Server (NTRS)

    Bauer, Frank H.; Downing, John P.; Thorpe, Christopher J.

    1990-01-01

    Structural finite element models are often too large to be used in the design and analysis of control systems. Model reduction techniques must be applied to reduce the structural model to manageable size. In the past, engineers either performed the model order reduction by hand or used distinct computer programs to retrieve the data, to perform the significance analysis and to reduce the order of the model. To expedite this process, the latest version of INCA has been expanded to include an interactive graphical structural mode significance and model order reduction capability.

  10. Three-dimensional structural analysis using interactive graphics

    NASA Technical Reports Server (NTRS)

    Biffle, J.; Sumlin, H. A.

    1975-01-01

    The application of computer interactive graphics to three-dimensional structural analysis was described, with emphasis on the following aspects: (1) structural analysis, and (2) generation and checking of input data and examination of the large volume of output data (stresses, displacements, velocities, accelerations). Handling of three-dimensional input processing with a special MESH3D computer program was explained. Similarly, a special code PLTZ may be used to perform all the needed tasks for output processing from a finite element code. Examples were illustrated.

  11. Supporting secure programming in web applications through interactive static analysis.

    PubMed

    Zhu, Jun; Xie, Jing; Lipford, Heather Richter; Chu, Bill

    2014-07-01

    Many security incidents are caused by software developers' failure to adhere to secure programming practices. Static analysis tools have been used to detect software vulnerabilities. However, their wide usage by developers is limited by the special training required to write rules customized to application-specific logic. Our approach is interactive static analysis, to integrate static analysis into Integrated Development Environment (IDE) and provide in-situ secure programming support to help developers prevent vulnerabilities during code construction. No additional training is required nor are there any assumptions on ways programs are built. Our work is motivated in part by the observation that many vulnerabilities are introduced due to failure to practice secure programming by knowledgeable developers. We implemented a prototype interactive static analysis tool as a plug-in for Java in Eclipse. Our technical evaluation of our prototype detected multiple zero-day vulnerabilities in a large open source project. Our evaluations also suggest that false positives may be limited to a very small class of use cases.

  12. Supporting secure programming in web applications through interactive static analysis

    PubMed Central

    Zhu, Jun; Xie, Jing; Lipford, Heather Richter; Chu, Bill

    2013-01-01

    Many security incidents are caused by software developers’ failure to adhere to secure programming practices. Static analysis tools have been used to detect software vulnerabilities. However, their wide usage by developers is limited by the special training required to write rules customized to application-specific logic. Our approach is interactive static analysis, to integrate static analysis into Integrated Development Environment (IDE) and provide in-situ secure programming support to help developers prevent vulnerabilities during code construction. No additional training is required nor are there any assumptions on ways programs are built. Our work is motivated in part by the observation that many vulnerabilities are introduced due to failure to practice secure programming by knowledgeable developers. We implemented a prototype interactive static analysis tool as a plug-in for Java in Eclipse. Our technical evaluation of our prototype detected multiple zero-day vulnerabilities in a large open source project. Our evaluations also suggest that false positives may be limited to a very small class of use cases. PMID:25685513

  13. Genome-wide association interaction analysis for Alzheimer's disease

    PubMed Central

    Gusareva, Elena S.; Carrasquillo, Minerva M.; Bellenguez, Céline; Cuyvers, Elise; Colon, Samuel; Graff-Radford, Neill R.; Petersen, Ronald C.; Dickson, Dennis W.; Mahachie Johna, Jestinah M.; Bessonov, Kyrylo; Van Broeckhoven, Christine; Williams, Julie; Amouyel, Philippe; Sleegers, Kristel; Ertekin-Taner, Nilüfer; Lambert, Jean-Charles; Van Steen, Kristel

    2015-01-01

    We propose a minimal protocol for exhaustive genome-wide association interaction analysis that involves screening for epistasis over large-scale genomic data combining strengths of different methods and statistical tools. The different steps of this protocol are illustrated on a real-life data application for Alzheimer's disease (AD) (2259 patients and 6017 controls from France). Particularly, in the exhaustive genome-wide epistasis screening we identified AD-associated interacting SNPs-pair from chromosome 6q11.1 (rs6455128, the KHDRBS2 gene) and 13q12.11 (rs7989332, the CRYL1 gene) (p = 0.006, corrected for multiple testing). A replication analysis in the independent AD cohort from Germany (555 patients and 824 controls) confirmed the discovered epistasis signal (p = 0.036). This signal was also supported by a meta-analysis approach in 5 independent AD cohorts that was applied in the context of epistasis for the first time. Transcriptome analysis revealed negative correlation between expression levels of KHDRBS2 and CRYL1 in both the temporal cortex (β = −0.19, p = 0.0006) and cerebellum (β = −0.23, p < 0.0001) brain regions. This is the first time a replicable epistasis associated with AD was identified using a hypothesis free screening approach. PMID:24958192

  14. Analysis of human emotion in human-robot interaction

    NASA Astrophysics Data System (ADS)

    Blar, Noraidah; Jafar, Fairul Azni; Abdullah, Nurhidayu; Muhammad, Mohd Nazrin; Kassim, Anuar Muhamed

    2015-05-01

    There is vast application of robots in human's works such as in industry, hospital, etc. Therefore, it is believed that human and robot can have a good collaboration to achieve an optimum result of work. The objectives of this project is to analyze human-robot collaboration and to understand humans feeling (kansei factors) when dealing with robot that robot should adapt to understand the humans' feeling. Researches currently are exploring in the area of human-robot interaction with the intention to reduce problems that subsist in today's civilization. Study had found that to make a good interaction between human and robot, first it is need to understand the abilities of each. Kansei Engineering in robotic was used to undergo the project. The project experiments were held by distributing questionnaire to students and technician. After that, the questionnaire results were analyzed by using SPSS analysis. Results from the analysis shown that there are five feelings which significant to the human in the human-robot interaction; anxious, fatigue, relaxed, peaceful, and impressed.

  15. Protein-protein interaction network analysis of cirrhosis liver disease

    PubMed Central

    Safaei, Akram; Rezaei Tavirani, Mostafa; Arefi Oskouei, Afsaneh; Zamanian Azodi, Mona; Mohebbi, Seyed Reza; Nikzamir, Abdol Rahim

    2016-01-01

    Aim: Evaluation of biological characteristics of 13 identified proteins of patients with cirrhotic liver disease is the main aim of this research. Background: In clinical usage, liver biopsy remains the gold standard for diagnosis of hepatic fibrosis. Evaluation and confirmation of liver fibrosis stages and severity of chronic diseases require a precise and noninvasive biomarkers. Since the early detection of cirrhosis is a clinical problem, achieving a sensitive, specific and predictive novel method based on biomarkers is an important task. Methods: Essential analysis, such as gene ontology (GO) enrichment and protein-protein interactions (PPI) was undergone EXPASy, STRING Database and DAVID Bioinformatics Resources query. Results: Based on GO analysis, most of proteins are located in the endoplasmic reticulum lumen, intracellular organelle lumen, membrane-enclosed lumen, and extracellular region. The relevant molecular functions are actin binding, metal ion binding, cation binding and ion binding. Cell adhesion, biological adhesion, cellular amino acid derivative, metabolic process and homeostatic process are the related processes. Protein-protein interaction network analysis introduced five proteins (fibroblast growth factor receptor 4, tropomyosin 4, tropomyosin 2 (beta), lectin, Lectin galactoside-binding soluble 3 binding protein and apolipoprotein A-I) as hub and bottleneck proteins. Conclusion: Our result indicates that regulation of lipid metabolism and cell survival are important biological processes involved in cirrhosis disease. More investigation of above mentioned proteins will provide a better understanding of cirrhosis disease. PMID:27099671

  16. What's wrong with my mouse cage? Methodological considerations for modeling lifestyle factors and gene-environment interactions in mice.

    PubMed

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

    2016-05-30

    The mechanistic understanding of lifestyle contributions to disease has been largely driven by work in laboratory rodent models using environmental interventions. These interventions show an array of methodologies and sometimes unclear collective conclusions, hampering clinical interpretations. Here we discuss environmental enrichment, exercise and stress interventions to illustrate how different protocols can affect the interpretations of environmental factors in disease. We use Huntington's disease (HD) as an example because its mouse models exhibit excellent validity and HD was the first genetic animal model in which environmental stimulation was found to be beneficial. We make a number of observations and recommendations. Firstly, environmental enrichment and voluntary exercise generally show benefits across laboratories and mouse models. However, the extent to which these environmental interventions have beneficial effects depends on parameters such as the structural complexity of the cage in the case of enrichment, the timing of the intervention and the nature of the control conditions. In particular, clinical interpretations should consider deprived control living conditions and the ethological relevance of the enrichment. Secondly, stress can have negative effects on the phenotype in mouse models of HD and other brain disorders. When modeling stress, the effects of more than one type of experimental stressor should be investigated due to the heterogeneity and complexity of stress responses. With stress in particular, but ideally in all studies, both sexes should be used and the randomized group sizes need to be sufficiently powered to detect any sex effects. Opportunities for clinical translation will be guided by the 'environmental construct validity' of the preclinical data, including the culmination of complementary protocols across multiple animal models. Environmental interventions in mouse models of HD provide illustrative examples of how valid preclinical studies can lead to conclusions relevant to clinical populations.

  17. 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,…

  18. Gene-Environment Contributions to the Development of Infant Vagal Reactivity: The Interaction of Dopamine and Maternal Sensitivity

    ERIC Educational Resources Information Center

    Propper, Cathi; Moore, Ginger A.; Mills-Koonce, W. Roger; Halpern, Carolyn Tucker; Hill-Soderlund, Ashley L.; Calkins, Susan D.; Carbone, Mary Anna; Cox, Martha

    2008-01-01

    This study investigated dopamine receptor genes ("DRD2" and "DRD4") and maternal sensitivity as predictors of infant respiratory sinus arrhythmia (RSA) and RSA reactivity, purported indices of vagal tone and vagal regulation, in a challenge task at 3, 6, and 12 months in 173 infant-mother dyads. Hierarchical linear modeling (HLM) revealed that at…

  19. Neuronal connectivity as a convergent target of gene-environment interactions that confer risk for Autism Spectrum Disorders

    PubMed Central

    Stamou, Marianna; Streifel, Karin M.; Goines, Paula E.; Lein, Pamela J.

    2013-01-01

    Evidence implicates environmental factors in the pathogenesis of Autism Spectrum Disorders (ASD). However, the identity of specific environmental chemicals that influence ASD risk, severity or treatment outcome remains elusive. The impact of any given environmental exposure likely varies across a population according to individual genetic substrates, and this increases the difficulty of identifying clear associations between exposure and ASD diagnoses. Heritable genetic vulnerabilities may amplify adverse effects triggered by environmental exposures if genetic and environmental factors converge to dysregulate the same signaling systems at critical times of development. Thus, one strategy for identifying environmental risk factors for ASD is to screen for environmental factors that modulate the same signaling pathways as ASD susceptibility genes. Recent advances in defining the molecular and cellular pathology of ASD point to altered patterns of neuronal connectivity in the developing brain as the neurobiological basis of these disorders. Studies of syndromic ASD and rare highly penetrant mutations or CNVs in ASD suggest that ASD risk genes converge on several major signaling pathways linked to altered neuronal connectivity in the developing brain. This review briefly summarizes the evidence implicating dysfunctional signaling via Ca2+-dependent mechanisms, extracellular signal-regulated kinases (ERK)/phosphatidylinositol-3-kinases (PI3K) and neuroligin-neurexin-SHANK as convergent molecular mechanisms in ASD, and then discusses examples of environmental chemicals for which there is emerging evidence of their potential to interfere with normal neuronal connectivity via perturbation of these signaling pathways. PMID:23269408

  20. Linkages between Children's and Their Friends' Social and Physical Aggression: Evidence for a Gene-Environment Interaction?

    ERIC Educational Resources Information Center

    Brendgen, Mara; Boivin, Michel; Vitaro, Frank; Bukowski, William M.; Dionne, Ginette; Tremblay, Richard E.; Perusse, Daniel

    2008-01-01

    Based on a sample of 406 seven-year-old twins, this study examined whether exposure to friends' social or physical aggression, respectively, moderates the effect of heritability on children's own social and physical aggression. Univariate analyses showed that children's own social and physical aggression were significantly explained by genetic…

  1. 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...

  2. 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…

  3. Open Environment for Multimodal Interactive Connectivity Visualization and Analysis

    PubMed Central

    Chen, Gang; Cox, Robert W.; Saad, Ziad S.

    2016-01-01

    Abstract Brain connectivity investigations are becoming increasingly multimodal and they present challenges for quantitatively characterizing and interactively visualizing data. In this study, we present a new set of network-based software tools for combining functional and anatomical connectivity from magnetic resonance imaging (MRI) data. The computational tools are available as part of Functional and Tractographic Connectivity Analysis Toolbox (FATCAT), a toolbox that interfaces with Analysis of Functional NeuroImages (AFNI) and SUrface MApping (SUMA) for interactive queries and visualization. This includes a novel, tractographic mini-probabilistic approach to improve streamline tracking in networks. We show how one obtains more robust tracking results for determining white matter connections by utilizing the uncertainty of the estimated diffusion tensor imaging (DTI) parameters and a few Monte Carlo iterations. This allows for thresholding based on the number of connections between target pairs to reduce the presence of tracts likely due to noise. To assist users in combining data, we describe an interface for navigating and performing queries in two-dimensional and three-dimensional data defined over voxel, surface, tract, and graph domains. These varied types of information can be visualized simultaneously and the queries performed interactively using SUMA and AFNI. The methods have been designed to increase the user's ability to visualize and combine functional MRI and DTI modalities, particularly in the context of single-subject inferences (e.g., in deep brain stimulation studies). Finally, we present a multivariate framework for statistically modeling network-based features in group analysis, which can be implemented for both functional and structural studies. PMID:26447394

  4. Rotor-Fuselage Interaction: Analysis and Validation with Experiment

    NASA Technical Reports Server (NTRS)

    Berry, John D.; Bettschart, Nicolas

    1997-01-01

    The problem of rotor-fuselage aerodynamic interaction has to be considered in industry applications from various aspects. First, in order to increase helicopter speed and reduce operational costs, rotorcraft tend to be more and more compact, with a main rotor closer to the fuselage surface. This creates significant perturbations both on the main rotor and on the fuselage, including steady and unsteady effects due to blade and wake passage and perturbed inflow at the rotor disk. Furthermore,the main rotor wake affects the tail boom, empennage and anti-torque system. This has important consequences for helicopter control and vibrations at low speeds and also on tail rotor acoustics (main rotor wake-tail rotor interactions). This report describes the US Army-France MOD cooperative work on this problem from both the theoretical and experimental aspects. Using experimental 3D velocity field and fuselage surface pressure measurements, three codes that model the interactions of a helicopter rotor with a fuselage are compared. These comparisons demonstrate some of the strengths and weaknesses of current models for the combined rotor-fuselage analysis.

  5. An analysis of blade vortex interaction aerodynamics and acoustics

    NASA Technical Reports Server (NTRS)

    Lee, D. J.

    1985-01-01

    The impulsive noise associated with helicopter flight due to Blade-Vortex Interaction, sometimes called blade slap is analyzed especially for the case of a close encounter of the blade-tip vortex with a following blade. Three parts of the phenomena are considered: the tip-vortex structure generated by the rotating blade, the unsteady pressure produced on the following blade during the interaction, and the acoustic radiation due to the unsteady pressure field. To simplify the problem, the analysis was confined to the situation where the vortex is aligned parallel to the blade span in which case the maximum acoustic pressure results. Acoustic radiation due to the interaction is analyzed in space-fixed coordinates and in the time domain with the unsteady pressure on the blade surface as the source of chordwise compact, but spanwise non-compact radiation. Maximum acoustic pressure is related to the vortex core size and Reynolds number which are in turn functions of the blade-tip aerodynamic parameters. Finally noise reduction and performance are considered.

  6. Flow analysis of nozzle installations with strong airplane flow interactions

    NASA Technical Reports Server (NTRS)

    Roberts, D. W.

    1982-01-01

    A numerical procedure has been developed to calculate the flow fields resulting from the viscous-inviscid interactions that occur when a strong jet exhaust and aircraft flow field coupling exists. The approach used in the current procedure is to divide the interaction region into zones which are either predominantly viscous or inviscid. The flow in the inviscid zone, which surrounds most of the aircraft, is calculated using an existing linearized potential flow code. The viscous flow zone, which encompasses the jet plume, is modeled using a parabolized Navier-Stokes code. The key feature of the present procedure is the coupling of the zonal solutions such that sufficient information is transferred between the zones to preserve the effects of the interactions. The zonal boundaries overlap with the boundary conditions being the information link between zones. An iteraction scheme iterates the coupled analysis until convergence has been obtained. The procedure has been successfully used for several test cases for which the computed results are presented.

  7. Quantitative analysis of harmonic convergence in mosquito auditory interactions.

    PubMed

    Aldersley, Andrew; Champneys, Alan; Homer, Martin; Robert, Daniel

    2016-04-01

    This article analyses the hearing and behaviour of mosquitoes in the context of inter-individual acoustic interactions. The acoustic interactions of tethered live pairs of Aedes aegypti mosquitoes, from same and opposite sex mosquitoes of the species, are recorded on independent and unique audio channels, together with the response of tethered individual mosquitoes to playbacks of pre-recorded flight tones of lone or paired individuals. A time-dependent representation of each mosquito's non-stationary wing beat frequency signature is constructed, based on Hilbert spectral analysis. A range of algorithmic tools is developed to automatically analyse these data, and used to perform a robust quantitative identification of the 'harmonic convergence' phenomenon. The results suggest that harmonic convergence is an active phenomenon, which does not occur by chance. It occurs for live pairs, as well as for lone individuals responding to playback recordings, whether from the same or opposite sex. Male-female behaviour is dominated by frequency convergence at a wider range of harmonic combinations than previously reported, and requires participation from both partners in the duet. New evidence is found to show that male-male interactions are more varied than strict frequency avoidance. Rather, they can be divided into two groups: convergent pairs, typified by tightly bound wing beat frequencies, and divergent pairs, that remain widely spaced in the frequency domain. Overall, the results reveal that mosquito acoustic interaction is a delicate and intricate time-dependent active process that involves both individuals, takes place at many different frequencies, and which merits further enquiry.

  8. Quantitative analysis of harmonic convergence in mosquito auditory interactions

    PubMed Central

    Aldersley, Andrew; Champneys, Alan; Robert, Daniel

    2016-01-01

    This article analyses the hearing and behaviour of mosquitoes in the context of inter-individual acoustic interactions. The acoustic interactions of tethered live pairs of Aedes aegypti mosquitoes, from same and opposite sex mosquitoes of the species, are recorded on independent and unique audio channels, together with the response of tethered individual mosquitoes to playbacks of pre-recorded flight tones of lone or paired individuals. A time-dependent representation of each mosquito's non-stationary wing beat frequency signature is constructed, based on Hilbert spectral analysis. A range of algorithmic tools is developed to automatically analyse these data, and used to perform a robust quantitative identification of the ‘harmonic convergence’ phenomenon. The results suggest that harmonic convergence is an active phenomenon, which does not occur by chance. It occurs for live pairs, as well as for lone individuals responding to playback recordings, whether from the same or opposite sex. Male–female behaviour is dominated by frequency convergence at a wider range of harmonic combinations than previously reported, and requires participation from both partners in the duet. New evidence is found to show that male–male interactions are more varied than strict frequency avoidance. Rather, they can be divided into two groups: convergent pairs, typified by tightly bound wing beat frequencies, and divergent pairs, that remain widely spaced in the frequency domain. Overall, the results reveal that mosquito acoustic interaction is a delicate and intricate time-dependent active process that involves both individuals, takes place at many different frequencies, and which merits further enquiry. PMID:27053654

  9. POD Analysis of Jet-Plume/Afterbody-Wake Interaction

    NASA Astrophysics Data System (ADS)

    Murray, Nathan E.; Seiner, John M.; Jansen, Bernard J.; Gui, Lichuan; Sockwell, Shuan; Joachim, Matthew

    2009-11-01

    The understanding of the flow physics in the base region of a powered rocket is one of the keys to designing the next generation of reusable launchers. The base flow features affect the aerodynamics and the heat loading at the base of the vehicle. Recent efforts at the National Center for Physical Acoustics at the University of Mississippi have refurbished two models for studying jet-plume/afterbody-wake interactions in the NCPA's 1-foot Tri-Sonic Wind Tunnel Facility. Both models have a 2.5 inch outer diameter with a nominally 0.5 inch diameter centered exhaust nozzle. One of the models is capable of being powered with gaseous H2 and O2 to study the base flow in a fully combusting senario. The second model uses hi-pressure air to drive the exhaust providing an unheated representative flow field. This unheated model was used to acquire PIV data of the base flow. Subsequently, a POD analysis was performed to provide a first look at the large-scale structures present for the interaction between an axisymmetric jet and an axisymmetric afterbody wake. PIV and Schlieren data are presented for a single jet-exhaust to free-stream flow velocity along with the POD analysis of the base flow field.

  10. Graph spectral analysis of protein interaction network evolution.

    PubMed

    Thorne, Thomas; Stumpf, Michael P H

    2012-10-07

    We present an analysis of protein interaction network data via the comparison of models of network evolution to the observed data. We take a bayesian approach and perform posterior density estimation using an approximate bayesian computation with sequential Monte Carlo method. Our approach allows us to perform model selection over a selection of potential network growth models. The methodology we apply uses a distance defined in terms of graph spectra which captures the network data more naturally than previously used summary statistics such as the degree distribution. Furthermore, we include the effects of sampling into the analysis, to properly correct for the incompleteness of existing datasets, and have analysed the performance of our method under various degrees of sampling. We consider a number of models focusing not only on the biologically relevant class of duplication models, but also including models of scale-free network growth that have previously been claimed to describe such data. We find a preference for a duplication-divergence with linear preferential attachment model in the majority of the interaction datasets considered. We also illustrate how our method can be used to perform multi-model inference of network parameters to estimate properties of the full network from sampled data.

  11. Characterization of the proteasome interaction network using a QTAX-based tag-team strategy and protein interaction network analysis.

    PubMed

    Guerrero, Cortnie; Milenkovic, Tijana; Przulj, Natasa; Kaiser, Peter; Huang, Lan

    2008-09-09

    Quantitative analysis of tandem-affinity purified cross-linked (x) protein complexes (QTAX) is a powerful technique for the identification of protein interactions, including weak and/or transient components. Here, we apply a QTAX-based tag-team mass spectrometry strategy coupled with protein network analysis to acquire a comprehensive and detailed assessment of the protein interaction network of the yeast 26S proteasome. We have determined that the proteasome network is composed of at least 471 proteins, significantly more than the total number of proteins identified by previous reports using proteasome subunits as baits. Validation of the selected proteasome-interacting proteins by reverse copurification and immunoblotting experiments with and without cross-linking, further demonstrates the power of the QTAX strategy for capturing protein interactions of all natures. In addition, >80% of the identified interactions have been confirmed by existing data using protein network analysis. Moreover, evidence obtained through network analysis links the proteasome to protein complexes associated with diverse cellular functions. This work presents the most complete analysis of the proteasome interaction network to date, providing an inclusive set of physical interaction data consistent with physiological roles for the proteasome that have been suggested primarily through genetic analyses. Moreover, the methodology described here is a general proteomic tool for the comprehensive study of protein interaction networks.

  12. Bispectral pairwise interacting source analysis for identifying systems of cross-frequency interacting brain sources from electroencephalographic or magnetoencephalographic signals

    NASA Astrophysics Data System (ADS)

    Chella, Federico; Pizzella, Vittorio; Zappasodi, Filippo; Nolte, Guido; Marzetti, Laura

    2016-05-01

    Brain cognitive functions arise through the coordinated activity of several brain regions, which actually form complex dynamical systems operating at multiple frequencies. These systems often consist of interacting subsystems, whose characterization is of importance for a complete understanding of the brain interaction processes. To address this issue, we present a technique, namely the bispectral pairwise interacting source analysis (biPISA), for analyzing systems of cross-frequency interacting brain sources when multichannel electroencephalographic (EEG) or magnetoencephalographic (MEG) data are available. Specifically, the biPISA makes it possible to identify one or many subsystems of cross-frequency interacting sources by decomposing the antisymmetric components of the cross-bispectra between EEG or MEG signals, based on the assumption that interactions are pairwise. Thanks to the properties of the antisymmetric components of the cross-bispectra, biPISA is also robust to spurious interactions arising from mixing artifacts, i.e., volume conduction or field spread, which always affect EEG or MEG functional connectivity estimates. This method is an extension of the pairwise interacting source analysis (PISA), which was originally introduced for investigating interactions at the same frequency, to the study of cross-frequency interactions. The effectiveness of this approach is demonstrated in simulations for up to three interacting source pairs and for real MEG recordings of spontaneous brain activity. Simulations show that the performances of biPISA in estimating the phase difference between the interacting sources are affected by the increasing level of noise rather than by the number of the interacting subsystems. The analysis of real MEG data reveals an interaction between two pairs of sources of central mu and beta rhythms, localizing in the proximity of the left and right central sulci.

  13. Safety Analysis of FMS/CTAS Interactions During Aircraft Arrivals

    NASA Technical Reports Server (NTRS)

    Leveson, Nancy G.

    1998-01-01

    This grant funded research on human-computer interaction design and analysis techniques, using future ATC environments as a testbed. The basic approach was to model the nominal behavior of both the automated and human procedures and then to apply safety analysis techniques to these models. Our previous modeling language, RSML, had been used to specify the system requirements for TCAS II for the FAA. Using the lessons learned from this experience, we designed a new modeling language that (among other things) incorporates features to assist in designing less error-prone human-computer interactions and interfaces and in detecting potential HCI problems, such as mode confusion. The new language, SpecTRM-RL, uses "intent" abstractions, based on Rasmussen's abstraction hierarchy, and includes both informal (English and graphical) specifications and formal, executable models for specifying various aspects of the system. One of the goals for our language was to highlight the system modes and mode changes to assist in identifying the potential for mode confusion. Three published papers resulted from this research. The first builds on the work of Degani on mode confusion to identify aspects of the system design that could lead to potential hazards. We defined and modeled modes differently than Degani and also defined design criteria for SpecTRM-RL models. Our design criteria include the Degani criteria but extend them to include more potential problems. In a second paper, Leveson and Palmer showed how the criteria for indirect mode transitions could be applied to a mode confusion problem found in several ASRS reports for the MD-88. In addition, we defined a visual task modeling language that can be used by system designers to model human-computer interaction. The visual models can be translated into SpecTRM-RL models, and then the SpecTRM-RL suite of analysis tools can be used to perform formal and informal safety analyses on the task model in isolation or integrated with

  14. Co-evolutionary Analysis of Domains in Interacting Proteins Reveals Insights into Domain–Domain Interactions Mediating Protein–Protein Interactions

    PubMed Central

    Jothi, Raja; Cherukuri, Praveen F.; Tasneem, Asba; Przytycka, Teresa M.

    2006-01-01

    Recent advances in functional genomics have helped generate large-scale high-throughput protein interaction data. Such networks, though extremely valuable towards molecular level understanding of cells, do not provide any direct information about the regions (domains) in the proteins that mediate the interaction. Here, we performed co-evolutionary analysis of domains in interacting proteins in order to understand the degree of co-evolution of interacting and non-interacting domains. Using a combination of sequence and structural analysis, we analyzed protein–protein interactions in F1-ATPase, Sec23p/Sec24p, DNA-directed RNA polymerase and nuclear pore complexes, and found that interacting domain pair(s) for a given interaction exhibits higher level of co-evolution than the noninteracting domain pairs. Motivated by this finding, we developed a computational method to test the generality of the observed trend, and to predict large-scale domain–domain interactions. Given a protein–protein interaction, the proposed method predicts the domain pair(s) that is most likely to mediate the protein interaction. We applied this method on the yeast interactome to predict domain–domain interactions, and used known domain–domain interactions found in PDB crystal structures to validate our predictions. Our results show that the prediction accuracy of the proposed method is statistically significant. Comparison of our prediction results with those from two other methods reveals that only a fraction of predictions are shared by all the three methods, indicating that the proposed method can detect known interactions missed by other methods. We believe that the proposed method can be used with other methods to help identify previously unrecognized domain–domain interactions on a genome scale, and could potentially help reduce the search space for identifying interaction sites. PMID:16949097

  15. Genes, environment and gene expression in colon tissue: a pathway approach to determining functionality.

    PubMed

    Slattery, Martha L; Pellatt, Daniel F; Wolff, Roger K; Lundgreen, Abbie

    2016-01-01

    Genetic and environmental factors have been shown to work together to alter cancer risk. In this study we evaluate previously identified gene and lifestyle interactions in a candidate pathway that were associated with colon cancer risk to see if these interactions altered gene expression. We analyzed non-tumor RNA-seq data from 144 colon cancer patients who had genotype, recent cigarette smoking, diet, body mass index (BMI), and recent aspirin/non-steroidal anti-inflammatory use data. Using a false discovery rate of 0.1, we evaluated differential gene expression between high and low levels of lifestyle exposure and genotypes using DESeq2. Thirteen pathway genes and 17 SNPs within those genes were associated with altered expression of other genes in the pathway. BMI, NSAIDs use and dietary components of the oxidative balance score (OBS) also were associated with altered gene expression. SNPs previously identified as interacting with these lifestyle factors, altered expression of pathway genes. NSAIDs interacted with 10 genes (15 SNPs) within those genes to alter expression of 28 pathway genes; recent cigarette smoking interacted with seven genes (nine SNPs) to alter expression of 27 genes. BMI interacted with FLT1, KDR, SEPN1, TERT, TXNRD2, and VEGFA to alter expression of eight genes. Three genes (five SNPs) interacted with OBS to alter expression of 12 genes. These data provide support for previously identified lifestyle and gene interactions associated with colon cancer in that they altered expression of key pathway genes. The need to consider lifestyle factors in conjunction with genetic factors is illustrated.

  16. Atom depth analysis delineates mechanisms of protein intermolecular interactions

    SciTech Connect

    Alocci, Davide; Bernini, Andrea; Niccolai, Neri

    2013-07-12

    Highlights: •3D atom depth analysis is proposed to identify different layers in protein structures. •Amino acid contents for each layers have been analyzed for a large protein dataset. •Charged amino acids in the most external layer are present at very different extents. •Atom depth indexes of K residues reflect their side chains flexibility. •Mobile surface charges can be responsible for long range protein–protein recognition. -- Abstract: The systematic analysis of amino acid distribution, performed inside a large set of resolved protein structures, sheds light on possible mechanisms driving non random protein–protein approaches. Protein Data Bank entries have been selected using as filters a series of restrictions ensuring that the shape of protein surface is not modified by interactions with large or small ligands. 3D atom depth has been evaluated for all the atoms of the 2,410 selected structures. The amino acid relative population in each of the structural layers formed by grouping atoms on the basis of their calculated depths, has been evaluated. We have identified seven structural layers, the inner ones reproducing the core of proteins and the outer one incorporating their most protruding moieties. Quantitative analysis of amino acid contents of structural layers identified, as expected, different behaviors. Atoms of Q, R, K, N, D residues are increasingly more abundant in going from core to surfaces. An opposite trend is observed for V, I, L, A, C, and G. An intermediate behavior is exhibited by P, S, T, M, W, H, F and Y. The outer structural layer hosts predominantly E and K residues whose charged moieties, protruding from outer regions of the protein surface, reorient free from steric hindrances, determining specific electrodynamics maps. This feature may represent a protein signature for long distance effects, driving the formation of encounter complexes and the eventual short distance approaches that are required for protein

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

    PubMed Central

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

    2007-01-01

    Background Gene-gene and gene-environment interactions involved in the metabolism of carcinogens may increase the risk of cancer. Our objective was to measure the interactions between common polymorphisms of P450 (CYP1A2, CYP1B1, CYP2E1), GSTM1 and T1, SULT1A1 and cigarette smoking in colorectal cancer (CRC). Methods A case-only design was conducted in a Chinese population including 207 patients with sporadic CRC. Unconditional logistic regression analysis was performed adjusting for age, gender, alcohol consumption, and cigarette smoking. Results The interaction odds ratio (COR) for the gene-gene interaction between CYP1B1 1294G and SULT1A1 638A allele was 2.68 (95% CI: 1.16–6.26). The results of the gene-environment analyses revealed that an interaction existed between cigarette smoking and the CYP1B1 1294G allele for CRC (COR = 2.62, 95%CI: 1.01–6.72), the COR for the interaction of CYP1B1 1294G and smoking history > 35 pack-years was 3.47 (95%CI: 1.12–10.80). No other significant gene-gene and gene-environment interactions were observed. Conclusion Our results showed that the interaction between polymorphisms in CYP1B1 1294G and SULT1A1*2 may play a significant role on CRC in the Chinese population. Also, it is suggested that the association between cigarette smoking and CRC could be differentiated by the CYP1B1 1294G allele. PMID:17603900

  18. Hydrophilic interaction chromatography (HILIC) in the analysis of antibiotics.

    PubMed

    Kahsay, Getu; Song, Huiying; Van Schepdael, Ann; Cabooter, Deirdre; Adams, Erwin

    2014-01-01

    This paper presents a general overview of the application of hydrophilic interaction chromatography (HILIC) in the analysis of antibiotics in different sample matrices including pharmaceutical, plasma, serum, fermentation broths, environmental water, animal origin, plant origin, etc. Specific applications of HILIC for analysis of aminoglycosides, β-lactams, tetracyclines and other antibiotics are reviewed. HILIC can be used as a valuable alternative LC mode for separating small polar compounds. Polar samples usually show good solubility in the mobile phase containing some water used in HILIC, which overcomes the drawbacks of the poor solubility often encountered in normal phase LC. HILIC is suitable for analyzing compounds in complex systems that elute near the void in reversed-phase chromatography. Ion-pair reagents are not required in HILIC which makes it convenient to couple with MS hence its increased popularity in recent years. In this review, the retention mechanism in HILIC is briefly discussed and a list of important applications is provided including main experimental conditions and a brief summary of the results. The references provide a comprehensive overview and insight into the application of HILIC in antibiotics analysis.

  19. Interactive flutter analysis and parametric study for conceptual wing design

    NASA Technical Reports Server (NTRS)

    Mukhopadhyay, Vivek

    1995-01-01

    An interactive computer program was developed for wing flutter analysis in the conceptual design stage. The objective was to estimate the flutter instability boundary of a flexible cantilever wing, when well defined structural and aerodynamic data are not available, and then study the effect of change in Mach number, dynamic pressure, torsional frequency, sweep, mass ratio, aspect ratio, taper ratio, center of gravity, and pitch inertia, to guide the development of the concept. The software was developed on MathCad (trademark) platform for Macintosh, with integrated documentation, graphics, database and symbolic mathematics. The analysis method was based on nondimensional parametric plots of two primary flutter parameters, namely Regier number and Flutter number, with normalization factors based on torsional stiffness, sweep, mass ratio, aspect ratio, center of gravity location and pitch inertia radius of gyration. The plots were compiled in a Vaught Corporation report from a vast database of past experiments and wind tunnel tests. The computer program was utilized for flutter analysis of the outer wing of a Blended Wing Body concept, proposed by McDonnell Douglas Corporation. Using a set of assumed data, preliminary flutter boundary and flutter dynamic pressure variation with altitude, Mach number and torsional stiffness were determined.

  20. Fluid Structure Interaction Analysis on Sidewall Aneurysm Models

    NASA Astrophysics Data System (ADS)

    Hao, Qing

    2016-11-01

    Wall shear stress is considered as an important factor for cerebral aneurysm growth and rupture. The objective of present study is to evaluate wall shear stress in aneurysm sac and neck by a fluid-structure-interaction (FSI) model, which was developed and validated against the particle image velocimetry (PIV) data. In this FSI model, the flow characteristics in a straight tube with different asymmetric aneurysm sizes over a range of Reynolds numbers from 200 to 1600 were investigated. The FSI results agreed well with PIV data. It was found that at steady flow conditions, when Reynolds number above 700, one large recirculating vortex would be formed, occupying the entire aneurysm sac. The center of the vortex is located at region near to the distal neck. A pair of counter rotating vortices would however be formed at Reynolds number below 700. Wall shear stresses reached highest level at the distal neck of the aneurysmal sac. The vortex strength, in general, is stronger at higher Reynolds number. Fluid Structure Interaction Analysis on Sidewall Aneurysm Models.

  1. Radial sets: interactive visual analysis of large overlapping sets.

    PubMed

    Alsallakh, Bilal; Aigner, Wolfgang; Miksch, Silvia; Hauser, Helwig

    2013-12-01

    In many applications, data tables contain multi-valued attributes that often store the memberships of the table entities to multiple sets such as which languages a person masters, which skills an applicant documents, or which features a product comes with. With a growing number of entities, the resulting element-set membership matrix becomes very rich of information about how these sets overlap. Many analysis tasks targeted at set-typed data are concerned with these overlaps as salient features of such data. This paper presents Radial Sets, a novel visual technique to analyze set memberships for a large number of elements. Our technique uses frequency-based representations to enable quickly finding and analyzing different kinds of overlaps between the sets, and relating these overlaps to other attributes of the table entities. Furthermore, it enables various interactions to select elements of interest, find out if they are over-represented in specific sets or overlaps, and if they exhibit a different distribution for a specific attribute compared to the rest of the elements. These interactions allow formulating highly-expressive visual queries on the elements in terms of their set memberships and attribute values. As we demonstrate via two usage scenarios, Radial Sets enable revealing and analyzing a multitude of overlapping patterns between large sets, beyond the limits of state-of-the-art techniques.

  2. Major component analysis of dynamic networks of physiologic organ interactions

    NASA Astrophysics Data System (ADS)

    Liu, Kang K. L.; Bartsch, Ronny P.; Ma, Qianli D. Y.; Ivanov, Plamen Ch

    2015-09-01

    The human organism is a complex network of interconnected organ systems, where the behavior of one system affects the dynamics of other systems. Identifying and quantifying dynamical networks of diverse physiologic systems under varied conditions is a challenge due to the complexity in the output dynamics of the individual systems and the transient and nonlinear characteristics of their coupling. We introduce a novel computational method based on the concept of time delay stability and major component analysis to investigate how organ systems interact as a network to coordinate their functions. We analyze a large database of continuously recorded multi-channel physiologic signals from healthy young subjects during night-time sleep. We identify a network of dynamic interactions between key physiologic systems in the human organism. Further, we find that each physiologic state is characterized by a distinct network structure with different relative contribution from individual organ systems to the global network dynamics. Specifically, we observe a gradual decrease in the strength of coupling of heart and respiration to the rest of the network with transition from wake to deep sleep, and in contrast, an increased relative contribution to network dynamics from chin and leg muscle tone and eye movement, demonstrating a robust association between network topology and physiologic function.

  3. Transcription Profiling Analysis of Mango–Fusarium mangiferae Interaction

    PubMed Central

    Liu, Feng; Wu, Jing-bo; Zhan, Ru-lin; Ou, Xiong-chang

    2016-01-01

    Malformation caused by Fusarium mangiferae is one of the most destructive mango diseases affecting the canopy and floral development, leading to dramatic reduction in fruit yield. To further understand the mechanism of interaction between mango and F. mangiferae, we monitored the transcriptome profiles of buds from susceptible mango plants, which were challenged with F. mangiferae. More than 99 million reads were deduced by RNA-sequencing and were assembled into 121,267 unigenes. Based on the sequence similarity searches, 61,706 unigenes were identified, of which 21,273 and 50,410 were assigned to gene ontology categories and clusters of orthologous groups, respectively, and 33,243 were mapped to 119 KEGG pathways. The differentially expressed genes of mango were detected, having 15,830, 26,061, and 20,146 DEGs respectively, after infection for 45, 75, and 120 days. The analysis of the comparative transcriptome suggests that basic defense mechanisms play important roles in disease resistance. The data also show the transcriptional responses of interactions between mango and the pathogen and more drastic changes in the host transcriptome in response to the pathogen. These results could be used to develop new methods to broaden the resistance of mango to malformation, including the over-expression of key mango genes. PMID:27683574

  4. Understanding metallic bonding: Structure, process and interaction by Rasch analysis

    NASA Astrophysics Data System (ADS)

    Cheng, Maurice M. W.; Oon, Pey-Tee

    2016-08-01

    This paper reports the results of a survey of 3006 Year 10-12 students on their understandings of metallic bonding. The instrument was developed based on Chi's ontological categories of scientific concepts and students' understanding of metallic bonding as reported in the literature. The instrument has two parts. Part one probed into students' understanding of metallic bonding as (a) a submicro structure of metals, (b) a process in which individual metal atoms lose their outermost shell electrons to form a 'sea of electrons' and octet metal cations or (c) an all-directional electrostatic force between delocalized electrons and metal cations, that is, an interaction. Part two assessed students' explanation of malleability of metals, for example (a) as a submicro structural rearrangement of metal atoms/cations or (b) based on all-directional electrostatic force. The instrument was validated by the Rasch Model. Psychometric assessment showed that the instrument possessed reasonably good properties of measurement. Results revealed that it was reliable and valid for measuring students' understanding of metallic bonding. Analysis revealed that the structure, process and interaction understandings were unidimensional and in an increasing order of difficulty. Implications for the teaching of metallic bonding, particular through the use of diagrams, critiques and model-based learning, are discussed.

  5. An interactive system for analysis of global cloud imagery

    NASA Technical Reports Server (NTRS)

    Woodberry, Karen; Tanaka, Ken; Hendon, Harry; Salby, Murry

    1991-01-01

    Synoptic images of the global cloud pattern composited from six contemporaneous satellites provide an unprecedented view of the global cloud field. Having horizontal resolution of about 0.5 deg and temporal resolution of 3 h, the global cloud imagery (GCI) resolves most of the variability of organized convection, including several harmonics of the diurnal cycle. Although the GCI has these attractive features, the dense and 3D nature of that data make it a formidable volume of information to treat in a practical and efficient manner. An interactive image-analysis system (IAS) has been developed to investigate the space-time variability of global cloud behavior. In the IAS, data, hardware, and software are integrated into a single system providing a variety of space-time covariance analyses in a menu-driven format. Owing to its customized architecture and certain homogeneous properties of the GCI, the IAS calculates such quantities effectively. Many covariance statistics are derived from 3D data with interactive speed, allowing the user to interrogate the archive iteratively in a single session. The 3D nature of those analyses and the speed with which they are performed distinguish the IAS from conventional image processing of 2D data.

  6. From superhydrophobicity to icephobicity: forces and interaction analysis

    PubMed Central

    Hejazi, Vahid; Sobolev, Konstantin; Nosonovsky, Michael

    2013-01-01

    The term “icephobicity” has emerged in the literature recently. An extensive discussion took place on whether the icephobicity is related to the superhydrophobicity, and the consensus is that there is no direct correlation. Besides the parallel between the icephobicity and superhydrophobicity for water/ice repellency, there are similarities on other levels including the hydrophobic effect/hydrophobic interactions, mechanisms of protein folding and ice crystal formation. In this paper, we report how ice adhesion is different from water using force balance analysis, and why superhydrophobic surfaces are not necessary icephobic. We also present experimental data on anti-icing of various surfaces and suggest a definition of icephobicity, which is broad enough to cover a variety of situations relevant to de-icing including low adhesion strength and delayed ice crystallization and bouncing. PMID:23846773

  7. Interactive Visual Analysis of High Throughput Text Streams

    SciTech Connect

    Steed, Chad A; Potok, Thomas E; Patton, Robert M; Goodall, John R; Maness, Christopher S; Senter, James K; Potok, Thomas E

    2012-01-01

    The scale, velocity, and dynamic nature of large scale social media systems like Twitter demand a new set of visual analytics techniques that support near real-time situational awareness. Social media systems are credited with escalating social protest during recent large scale riots. Virtual communities form rapidly in these online systems, and they occasionally foster violence and unrest which is conveyed in the users language. Techniques for analyzing broad trends over these networks or reconstructing conversations within small groups have been demonstrated in recent years, but state-of- the-art tools are inadequate at supporting near real-time analysis of these high throughput streams of unstructured information. In this paper, we present an adaptive system to discover and interactively explore these virtual networks, as well as detect sentiment, highlight change, and discover spatio- temporal patterns.

  8. Image pattern recognition supporting interactive analysis and graphical visualization

    NASA Technical Reports Server (NTRS)

    Coggins, James M.

    1992-01-01

    Image Pattern Recognition attempts to infer properties of the world from image data. Such capabilities are crucial for making measurements from satellite or telescope images related to Earth and space science problems. Such measurements can be the required product itself, or the measurements can be used as input to a computer graphics system for visualization purposes. At present, the field of image pattern recognition lacks a unified scientific structure for developing and evaluating image pattern recognition applications. The overall goal of this project is to begin developing such a structure. This report summarizes results of a 3-year research effort in image pattern recognition addressing the following three principal aims: (1) to create a software foundation for the research and identify image pattern recognition problems in Earth and space science; (2) to develop image measurement operations based on Artificial Visual Systems; and (3) to develop multiscale image descriptions for use in interactive image analysis.

  9. Remodelling by early-life stress of NMDA receptor-dependent synaptic plasticity in a gene-environment rat model of depression.

    PubMed

    Ryan, Ben; Musazzi, Laura; Mallei, Alessandra; Tardito, Daniela; Gruber, Suzanne H M; El Khoury, Aram; Anwyl, Roger; Racagni, Giorgio; Mathé, Aleksander A; Rowan, Michael J; Popoli, Maurizio

    2009-05-01

    An animal model of depression combining genetic vulnerability and early-life stress (ELS) was prepared by submitting the Flinders Sensitive Line (FSL) rats to a standard paradigm of maternal separation. We analysed hippocampal synaptic transmission and plasticity in vivo and ionotropic receptors for glutamate in FSL rats, in their controls Flinders Resistant Line (FRL) rats, and in both lines subjected to ELS. A strong inhibition of long-term potentiation (LTP) and lower synaptic expression of NR1 subunit of the NMDA receptor were found in FSL rats. Remarkably, ELS induced a remodelling of synaptic plasticity only in FSL rats, reducing inhibition of LTP; this was accompanied by marked increase of synaptic NR1 subunit and GluR2/3 subunits of AMPA receptors. Chronic treatment with escitalopram inhibited LTP in FRL rats, but this effect was attenuated by prior ELS. The present results suggest that early gene-environment interactions cause lifelong synaptic changes affecting functional and molecular aspects of plasticity, partly reversed by antidepressant treatments.

  10. 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…

  11. Interactive Analysis using PROOF in a GRID Infrastructure

    NASA Astrophysics Data System (ADS)

    Yaiza Rodríguez Marrero, Ana; González Caballero, Isidro; Cuesta Noriega, Alberto; Matorras Weinig, Francisco

    2011-12-01

    Current high energy physics experiments aim to explore new territories where new physics is expected. In order to achieve that, a huge amount of data has to be collected and analyzed. The accomplishment of these scientific projects require computing resources beyond the capabilities of a single user or group, thus the data is treated under the grid infrastructure. Despite the reduction applied to the data, the sample used in the last step of the analysis is still large. At this phase, interactivity contributes to a faster optimization of the final cuts in order to improve the results. The Parallel ROOT Facility (PROOF) is intended to speed up even further this procedure providing the user analysis results within a shorter time by simultaneously using more cores. Taking profit of the computing resources and facilities available at Instituto de Física de Cantabria (IFCA), shared between two major projects LHC-CMS Tier-2 and GRID-CSIC, we have developed a setup that integrates PROOF with SGE as local resource management system and GPFS as file system, both common to the grid infrastructure. The setup was also integrated in a similar infrastructure for the LHC-CMS Tier-3 at Universidad de Oviedo that uses Torque (PBS) as local job manager and Hadoop as file system. In addition, to ease the transition from a sequential analysis code to PROOF, an analysis framework based on the TSelector class is provided. Integrating PROOF in a cluster provides users the potential usage of thousands of cores (1,680 in the IFCA case). Performance measurements have been done showing a speed improvement closely correlated with the number of cores used.

  12. Recent insights into plant-virus interactions through proteomic analysis.

    PubMed

    Di Carli, Mariasole; Benvenuto, Eugenio; Donini, Marcello

    2012-10-05

    Plant viruses represent a major threat for a wide range of host species causing severe losses in agricultural practices. The full comprehension of mechanisms underlying events of virus-host plant interaction is crucial to devise novel plant resistance strategies. Until now, functional genomics studies in plant-virus interaction have been limited mainly on transcriptomic analysis. Only recently are proteomic approaches starting to provide important contributions to this area of research. Classical two-dimensional electrophoresis (2-DE) coupled to mass spectrometry (MS) is still the most widely used platform in plant proteome analysis, although in the last years the application of quantitative "second generation" proteomic techniques (such as differential in gel electrophoresis, DIGE, and gel-free protein separation methods) are emerging as more powerful analytical approaches. Apparently simple, plant-virus interactions reveal a really complex pathophysiological context, in which resistance, defense and susceptibility, and direct virus-induced reactions interplay to trigger expression responses of hundreds of genes. Given that, this review is specifically focused on comparative proteome-based studies on pathogenesis of several viral genera, including some of the most important and widespread plant viruses of the genus Tobamovirus, Sobemovirus, Cucumovirus and Potyvirus. In all, this overview reveals a widespread repression of proteins associated with the photosynthetic apparatus, while energy metabolism/protein synthesis and turnover are typically up-regulated, indicating a major redirection of cell metabolism. Other common features include the modulation of metabolisms concerning sugars, cell wall, and reactive oxigen species as well as pathogenesis-related (PR) proteins. The fine-tuning between plant development and antiviral defense mechanisms determines new patterns of regulation of common metabolic pathways. By offering a 360-degree view of protein modulation

  13. A Workshop in the Analysis of Teaching; Interaction Analysis, Nonverbal Communication, Microteaching, Simulation.

    ERIC Educational Resources Information Center

    Frymier, Jack R., Ed.

    1968-01-01

    Articles is this issue represent the substantive content of a series of 25 workshops sponsored by the American Association of Colleges for Teacher Education (AACTE). The four major articles discuss innovative models based on four approaches for improving teacher performance: (1) "Interaction Analysis" by Edmund J. Amidon, San Francisco State…

  14. Observed positive parenting behaviors and youth genotype: evidence for gene-environment correlations and moderation by parent personality traits.

    PubMed

    Oppenheimer, Caroline W; Hankin, Benjamin L; Jenness, Jessica L; Young, Jami F; Smolen, Andrew

    2013-02-01

    Gene-environment correlations (rGE) have been demonstrated in behavioral genetic studies, but rGE have proven elusive in molecular genetic research. Significant gene-environment correlations may be difficult to detect because potential moderators could reduce correlations between measured genetic variants and the environment. Molecular genetic studies investigating moderated rGE are lacking. This study examined associations between child catechol-O-methyltransferase genotype and aspects of positive parenting (responsiveness and warmth), and whether these associations were moderated by parental personality traits (neuroticism and extraversion) among a general community sample of third, sixth, and ninth graders (N = 263) and their parents. Results showed that parent personality traits moderated the rGE association between youths' genotype and coded observations of positive parenting. Parents with low levels of neuroticism and high levels of extraversion exhibited greater sensitive responsiveness and warmth, respectively, to youth with the valine/valine genotype. Moreover, youth with this genotype exhibited lower levels of observed anger. There was no association between the catechol-O-methyltransferase genotype and parenting behaviors for parents high on neuroticism and low on extraversion. Findings highlight the importance of considering moderating variables that may influence child genetic effects on the rearing environment. Implications for developmental models of maladaptive and adaptive child outcomes, and interventions for psychopathology, are discussed within a developmental psychopathology framework.

  15. Boys' serotonin transporter genotype affects maternal behavior through self-control: a case of evocative gene-environment correlation.

    PubMed

    Pener-Tessler, Roni; Avinun, Reut; Uzefovsky, Florina; Edelman, Shany; Ebstein, Richard P; Knafo, Ariel

    2013-02-01

    Self-control, involving processes such as delaying gratification, concentrating, planning, following instructions, and adapting emotions and behavior to situational requirements and social norms, may have a profound impact on children's adjustment. The importance of self-control suggests that parents are likely to modify their parenting based on children's ability for self-control. We study the effect of children's self-control, a trait partially molded by genetics, on their mothers' parenting, a process of evocative gene-environment correlation. Israeli 3.5-year-old twins (N = 320) participated in a lab session in which their mothers' parenting was observed. DNA was available from most children (N = 228). Mothers described children's self-control in a questionnaire. Boys were lower in self-control and received less positive parenting from their mothers, in comparison with girls. For boys, and not for girls, the serotonin transporter linked polymorphic region gene predicted mothers' levels of positive parenting, an effect mediated by boys' self-control. The implications of this evocative gene-environment correlation and the observed sex differences are discussed.

  16. Analysis of Metabolites in Stem Parasitic Plant Interactions: Interaction of Cuscuta–Momordica versus Cassytha–Ipomoea

    PubMed Central

    Furuhashi, Takeshi; Nakamura, Takemichi; Iwase, Koji

    2016-01-01

    Cuscuta and Cassytha are two well-known stem parasitic plant genera with reduced leaves and roots, inducing haustoria in their stems. Their similar appearance in the field has been recognized, but few comparative studies on their respective plant interactions are available. To compare their interactions, we conducted a metabolite analysis of both the Cassytha–Ipomoea and the Cuscuta–Momordica interaction. We investigated the energy charge of the metabolites by UFLC (ultra-high performance liquid chromatography), and conducted GC-MS (gas chromatography-mass spectrometry) analysis for polar metabolites (e.g., saccharides, polyols) and steroids. The energy charge after parasitization changed considerably in Cassytha but not in Cusucta. Cuscuta changed its steroid pattern during the plant interaction, whereas Cassytha did not. In the polar metabolite analysis, the laminaribiose increase after parasitization was conspicuous in Cuscuta, but not in Cassytha. This metabolite profile difference points to different lifestyles and parasitic strategies. PMID:27941603

  17. Control system design and analysis using the INteractive Controls Analysis (INCA) program

    NASA Technical Reports Server (NTRS)

    Bauer, Frank H.; Downing, John P.

    1987-01-01

    The INteractive Controls Analysis (INCA) program was developed at the Goddard Space Flight Center to provide a user friendly efficient environment for the design and analysis of linear control systems. Since its inception, INCA has found extensive use in the design, development, and analysis of control systems for spacecraft, instruments, robotics, and pointing systems. Moreover, the results of the analytic tools imbedded in INCA have been flight proven with at least three currently orbiting spacecraft. This paper describes the INCA program and illustrates, using a flight proven example, how the package can perform complex design analyses with relative ease.

  18. Interactive retinal blood flow analysis of the macular region.

    PubMed

    Tian, Jing; Somfai, Gábor Márk; Campagnoli, Thalmon R; Smiddy, William E; Debuc, Delia Cabrera

    2016-03-01

    The study of retinal hemodynamics plays an important role to understand the onset and progression of diabetic retinopathy. In this work, we developed an interactive retinal analysis tool to quantitatively measure the blood flow velocity (BFV) and blood flow rate (BFR) in the macular region using the Retinal Function Imager (RFI). By employing a high definition stroboscopic fundus camera, the RFI device is able to assess retinal blood flow characteristics in vivo. However, the measurements of BFV using a user-guided vessel segmentation tool may induce significant inter-observer differences and BFR is not provided in the built-in software. In this work, we have developed an interactive tool to assess the retinal BFV and BFR in the macular region. Optical coherence tomography data was registered with the RFI image to locate the fovea accurately. The boundaries of the vessels were delineated on a motion contrast enhanced image and BFV was computed by maximizing the cross-correlation of pixel intensities in a ratio video. Furthermore, we were able to calculate the BFR in absolute values (μl/s). Experiments were conducted on 122 vessels from 5 healthy and 5 mild non-proliferative diabetic retinopathy (NPDR) subjects. The Pearson's correlation of the vessel diameter measurements between our method and manual labeling on 40 vessels was 0.984. The intraclass correlation (ICC) of BFV between our proposed method and built-in software was 0.924 and 0.830 for vessels from healthy and NPDR subjects, respectively. The coefficient of variation between repeated sessions was reduced significantly from 22.5% to 15.9% in our proposed method (p<0.001).

  19. Regional Analysis of Energy, Water, Land and Climate Interactions

    NASA Astrophysics Data System (ADS)

    Tidwell, V. C.; Averyt, K.; Harriss, R. C.; Hibbard, K. A.; Newmark, R. L.; Rose, S. K.; Shevliakova, E.; Wilson, T.

    2014-12-01

    Energy, water, and land systems interact in many ways and are impacted by management and climate change. These systems and their interactions often differ in significant ways from region-to-region. To explore the coupled energy-water-land system and its relation to climate change and management a simple conceptual model of demand, endowment and technology (DET) is proposed. A consistent and comparable analysis framework is needed as climate change and resource management practices have the potential to impact each DET element, resource, and region differently. These linkages are further complicated by policy and trade agreements where endowments of one region are used to meet demands in another. This paper reviews the unique DET characteristics of land, energy and water resources across the United States. Analyses are conducted according to the eight geographic regions defined in the 2014 National Climate Assessment. Evident from the analyses are regional differences in resources endowments in land (strong East-West gradient in forest, cropland and desert), water (similar East-West gradient), and energy. Demands likewise vary regionally reflecting differences in population density and endowment (e.g., higher water use in West reflecting insufficient precipitation to support dryland farming). The effect of technology and policy are particularly evident in differences in the energy portfolios across the eight regions. Integrated analyses that account for the various spatial and temporal differences in regional energy, water and land systems are critical to informing effective policy requirements for future energy, climate and resource management. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

  20. Interactive Retinal Blood Flow Analysis of the Macular Region

    PubMed Central

    Tian, Jing; Somfai, Gábor Márk; Campagnoli, Thalmon R.; Smiddy, William E.; Debuc, Delia Cabrera

    2015-01-01

    The study of retinal hemodynamics plays an important role to understand the onset and progression of diabetic retinopathy which is a leading cause of blindness in American adults. In this work, we developed an interactive retinal analysis tool to quantitatively measure the blood flow velocity (BFV) and blood flow rate (BFR) in the macular region using the Retinal Function Imager (RFI-3005, Optical Imaging, Rehovot, Israel). By employing a high definition stroboscopic fundus camera, the RFI device is able to assess retinal blood flow characteristics in vivo even in the capillaries. However, the measurements of BFV using a user-guided vessel segmentation tool may induce significant inter-observer differences and BFR is not provided in the built-in software. In this work, we have developed an interactive tool to assess the retinal BFV as well as BFR in the macular region. Optical coherence tomography (OCT) data from commercially available devices were registered with the RFI image to locate the fovea accurately. The boundaries of the vessels were delineated on a motion contrast enhanced image and BFV was computed by maximizing the cross-correlation of pixel intensities in a ratio video. Furthermore, we were able to calculate the BFR in absolute values (μl/s) which other currently available devices targeting the retinal microcirculation are not yet capable of. Experiments were conducted on 122 vessels from 5 healthy and 5 mild non-proliferative diabetic retinopathy (NPDR) subjects. The Pearson's correlation of the vessel diameter measurements between our method and manual labeling on 40 vessels was 0.984. The intraclass correlation (ICC) of BFV between our proposed method and built-in software were 0.924 and 0.830 for vessels from healthy and NPDR subjects, respectively. The coefficient of variation between repeated sessions was reduced significantly from 22.5% in the RFI built-in software to 15.9% in our proposed method (p<0.001). PMID:26569349

  1. Interactive Analysis of Hyperspectral Data under Linearity Constraints

    NASA Astrophysics Data System (ADS)

    Schmidt, A.; Treguier, E.; Schmidt, F.; Moussaoui, S.; Pelloquin, C.

    2010-12-01

    Large data sets delivered by imaging spectrometers are interesting in many ways in the Planetary Sciences. Due to the size of the data and lack of ground truth, which often prohibit conventional exploratory data analysis methods, interactive but unsupervised analysis methods could be a way of discovering relevant information about the sources that make up the data. In this work, we investigate some of the opportunities and limitations of such analyses based on non-negative matrix approximation in planetary settings. Since typically there often is no ground truth to compare to, the degrees of freedom inherent in the aforementioned approximation techniques often has to be constrained by users to discover physically valid sources and patterns. One way of going about this is to present users with different valid solutions have them choose the one or ones that fit their knowledge of the environment best. Recent developments have made it possible to exploit linear mixing constraints and present results to users in real or near-real time; thus, the approach has become practicable. The general setting of the problem is as follows: By considering P pixels of an hyperspectral image acquired at L frequency bands, the observed spectra are gathered in a PxL data matrix X. Each row of this matrix contains a measured spectrum at a pixel with spatial index p=1..P. According to the linear mixing model, the p-th spectrum, 1<=p<=P, can be expressed as a linear combination of r, 1<=r<=R, pure spectra of the surface components. Thus, X=AxS+E, E being an error matrix, should be minimised, where X, A, and S have only non-negative entries. The rows of matrix S now contain the pure surface spectra of the R components, and each entry of A corresponds to the abundance of the r-th component in pixel with spatial index p. For a qualitative and quantitative description of the observed scene composition, the estimation problem consists of finding matrices S and A which allow to explain the data

  2. Ageing, genes, environment and epigenetics: what twin studies tell us now, and in the future.

    PubMed

    Steves, Claire Joanne; Spector, Timothy D; Jackson, Stephen H D

    2012-09-01

    Compared with younger people, older people are much more variable in their organ function, and these large individual differences contribute to the complexity of geriatric medicine. What determines this variability? Is it due to the accumulation of different life experiences, or because of the variation in the genes we are born with, or an interaction of both? This paper reviews key findings from ageing twin cohorts probing these questions. Twin studies are the perfect natural experiment to dissect out genes and life experiences. We discuss the paradox that ageing is strongly determined by heritable factors (an influence that often gets stronger with time), yet longevity and lifespan seem not to be so heritable. We then focus on the intriguing question of why DNA sequence-identical twins might age differently. Animal studies are increasingly showing that epigenetic modifications occurring in early development and adulthood, might be key to ageing phenomena but this is difficult to investigate longitudinally in human populations, due to ethical problems of intervention and long lifespan. We propose that identical twin studies using new and existing cohorts may be useful human models in which to investigate the interaction between the environment and genetics, mediated by epigenetic modifications.

  3. Theoretical analysis of magnetic field interactions with aortic blood flow

    SciTech Connect

    Kinouchi, Y.; Yamaguchi, H.; Tenforde, T.S.

    1996-04-01

    The flow of blood in the presence of a magnetic field gives rise to induced voltages in the major arteries of the central circulatory system. Under certain simplifying conditions, such as the assumption that the length of major arteries (e.g., the aorta) is infinite and that the vessel walls are not electrically conductive, the distribution of induced voltages and currents within these blood vessels can be calculated with reasonable precision. However, the propagation of magnetically induced voltages and currents from the aorta into neighboring tissue structures such as the sinuatrial node of the heart has not been previously determined by any experimental or theoretical technique. In the analysis presented in this paper, a solution of the complete Navier-Stokes equation was obtained by the finite element technique for blood flow through the ascending and descending aortic vessels in the presence of a uniform static magnetic field. Spatial distributions of the magnetically induced voltage and current were obtained for the aortic vessel and surrounding tissues under the assumption that the wall of the aorta is electrically conductive. Results are presented for the calculated values of magnetically induced voltages and current densities in the aorta and surrounding tissue structures, including the sinuatrial node, and for their field-strength dependence. In addition, an analysis is presented of magnetohydrodynamic interactions that lead to a small reduction of blood volume flow at high field levels above approximately 10 tesla (T). Quantitative results are presented on the offsetting effects of oppositely directed blood flows in the ascending and descending aortic segments, and a quantitative estimate is made of the effects of assuming an infinite vs. a finite length of the aortic vessel in calculating the magnetically induced voltage and current density distribution in tissue.

  4. Structural Analysis of Chemokine Receptor-Ligand Interactions.

    PubMed

    Arimont, Marta; Sun, Shan-Liang; Leurs, Rob; Smit, Martine; de Esch, Iwan J P; de Graaf, Chris

    2017-03-10

    This review focuses on the construction and application of structural chemokine receptor models for the elucidation of molecular determinants of chemokine receptor modulation and the structure-based discovery and design of chemokine receptor ligands. A comparative analysis of ligand binding pockets in chemokine receptors is presented, including a detailed description of the CXCR4, CCR2, CCR5, CCR9, and US28 X-ray structures, and their implication for modeling molecular interactions of chemokine receptors with small-molecule ligands, peptide ligands, and large antibodies and chemokines. These studies demonstrate how the integration of new structural information on chemokine receptors with extensive structure-activity relationship and site-directed mutagenesis data facilitates the prediction of the structure of chemokine receptor-ligand complexes that have not been crystallized. Finally, a review of structure-based ligand discovery and design studies based on chemokine receptor crystal structures and homology models illustrates the possibilities and challenges to find novel ligands for chemokine receptors.

  5. Human Interactive Analysis Using Video: Mapping the Dynamics of Complex Work Environments.

    ERIC Educational Resources Information Center

    Terrell, William R.; And Others

    1992-01-01

    Explains human interactive analysis as an architecture for using computer interactive technologies in the analysis of complex work environments. A project at the Naval Training Systems Center that used video-audio data to develop a multimedia database is described; the analysis and management of data are discussed; and decision processes are…

  6. Using Interactive Graphics to Teach Multivariate Data Analysis to Psychology Students

    ERIC Educational Resources Information Center

    Valero-Mora, Pedro M.; Ledesma, Ruben D.

    2011-01-01

    This paper discusses the use of interactive graphics to teach multivariate data analysis to Psychology students. Three techniques are explored through separate activities: parallel coordinates/boxplots; principal components/exploratory factor analysis; and cluster analysis. With interactive graphics, students may perform important parts of the…

  7. Physical punishment and childhood aggression: the role of gender and gene-environment interplay.

    PubMed

    Boutwell, Brian B; Franklin, Cortney A; Barnes, J C; Beaver, Kevin M

    2011-01-01

    A large body of research has linked spanking with a range of adverse outcomes in children, including aggression, psychopathology, and criminal involvement. Despite evidence concerning the association of spanking with antisocial behavior, not all children who are spanked develop antisocial traits. Given the heterogeneous effects of spanking on behavior, it is possible that a third variable may condition the influence of corporal punishment on child development. We test this possibility using data drawn from a nationally representative dataset of twin siblings. Our findings suggest that genetic risk factors condition the effects of spanking on antisocial behavior. Moreover, our results provide evidence that the interaction between genetic risk factors and corporal punishment may be particularly salient for males.

  8. Orbiter subsystem hardware/software interaction analysis. Volume 8: AFT reaction control system, part 2

    NASA Technical Reports Server (NTRS)

    Becker, D. D.

    1980-01-01

    The orbiter subsystems and interfacing program elements which interact with the orbiter computer flight software are analyzed. The failure modes identified in the subsystem/element failure mode and effects analysis are examined. Potential interaction with the software is examined through an evaluation of the software requirements. The analysis is restricted to flight software requirements and excludes utility/checkout software. The results of the hardware/software interaction analysis for the forward reaction control system are presented.

  9. Microfluidic large scale integration of viral-host interaction analysis.

    PubMed

    Ben-Ari, Ya'ara; Glick, Yair; Kipper, Sarit; Schwartz, Nika; Avrahami, Dorit; Barbiro-Michaely, Efrat; Gerber, Doron

    2013-06-21

    Viral-host interactions represent potential drug targets for novel antiviral strategies (Flisiak et al., Hepatology, 2008, 47, 817-26). Hence, it is important to establish an adequate platform for identifying and analyzing such interactions. In this review, we discuss bottlenecks in conventional protein-protein interaction methodologies and present the contribution of innovative microfluidic-based technologies towards a solution to these problems with respect to viral-host proteomics.

  10. Interactive display/graphics systems for remote sensor data analysis

    NASA Technical Reports Server (NTRS)

    Eppler, W. G.; Loe, D. L.; Wilson, E. L.; Whitley, S. L.; Sachen, R. J.

    1970-01-01

    A color-television display system and interactive graphics equipment on-line to an IBM 360/44 computer are used to develop a variety of interactive displays which aid in analyzing remote sensor data. These interactive displays are used to: (1) analyze data from a multispectral scanner; (2) develop automatic pattern recognition systems based on multispectral scanner measurements; and (3) analyze data from non-imaging sensors such as the infrared radiometer and microwave scatterometer.

  11. The Autism Birth Cohort: a paradigm for gene-environment-timing research.

    PubMed

    Stoltenberg, C; Schjølberg, S; Bresnahan, M; Hornig, M; Hirtz, D; Dahl, C; Lie, K K; Reichborn-Kjennerud, T; Schreuder, P; Alsaker, E; Øyen, A-S; Magnus, P; Surén, P; Susser, E; Lipkin, W I

    2010-07-01

    The reported prevalence of autism spectrum disorders (ASDs) has increased by 5- to 10-fold over the past 20 years. Whether ASDs are truly more frequent is controversial; nonetheless, the burden is profound in human and economic terms. Although autism is among the most heritable of mental disorders, its pathogenesis remains obscure. Environmental factors are proposed; however, none is implicated. Furthermore, there are no biomarkers to screen for ASD or risk of ASD. The Autism Birth Cohort (ABC) was initiated to analyze gene x environment x timing interactions and enable early diagnosis. It uses a large, unselected birth cohort in which cases are prospectively ascertained through population screening. Samples collected serially through pregnancy and childhood include parental blood, maternal urine, cord blood, milk teeth and rectal swabs. More than 107,000 children are continuously screened through questionnaires, referral, and a national registry. Cases are compared with a control group from the same cohort in a 'nested case-control' design. Early screening and diagnostic assessments and re-assessments are designed to provide a rich view of longitudinal trajectory. Genetic, proteomic, immunologic, metagenomic and microbiological tools will be used to exploit unique biological samples. The ABC is a paradigm for analyzing the role of genetic and environmental factors in complex disorders.

  12. Use of the Twin Design to Examine Evocative Gene-Environment Effects within a Conversational Context

    PubMed Central

    DeThorne, Laura Segebart; Hart, Sara Ann

    2010-01-01

    The purpose of this study was to highlight the role of twin designs in understanding children’s conversational interactions. Specifically, we (a) attempted to replicate the findings of genetic effects on children’s conversational language use reported in DeThorne et al. (2008), and (b) examined whether the language used by examiners in their conversation with twins reflected differences in the children’s genetic similarity. Behavioral genetic analyses included intraclass correlations and model fitting procedures applied to 514 same-sex twins (202 MZ, 294 DZ, 10 unknown zygosity) from the Western Reserve Reading Project (Petrill, Deater-Deckard, Thompson, DeThorne, & Schatschneider, 2006). Analyses focused on child and examiner measures of talkativeness, average utterance length, vocabulary diversity, and grammatical complexity from a fifteen-minute conversational exchange. Substantial genetic effects on children’s conversational language measures replicated results from DeThorne et al. (2008) using an expanded sample. However, no familiality was reflected in the examiner language measures. Modest phenotypic correlations between child and examiner language measures suggested that differences in examiner language use may elicit differences in child language use, but evidence of evocative rGE in which genetic differences across children evoke differences in examiner language use, was not found. The discussion focuses on a comparison of findings to previous studies and implications for future research. PMID:22102850

  13. SEPAC data analysis in support of the environmental interaction program

    NASA Technical Reports Server (NTRS)

    Lin, Chin S.

    1991-01-01

    Data analyses of the Space Experiments with Particle Accelerators (SEPAC) data and computer modeling were conducted to investigate spacecraft environmental effects associated with injection of electron beams, plasma clouds, and neutral gas clouds from the Shuttle orbiter. The data analysis indicates that Extremely Low Frequency oscillations from 150 to 200 Hz were seen in the Langmuir probe current when the beam was fired in a continuous mode. The strongest oscillations occurred when the ambient pressure was augmented by neutral gas releases from the SEPAC plasma accelerator magnetoplasma-dynamic (MPD) arcjet. To understand the dependence of spacecraft charging potential on beam density and other plasma parameters, a two-dimensional electrostatic particle code was used to simulate the injection of electron beams from an infinite conductor into a plasma. The simulations show that the conductor charging potential depends critically on the reflection coefficient of the conductor surface, which is defined as the percentage of incident particles reflected by the conductor. The ionization effects on spacecraft charging were examined by including interactions of electrons with neutral gas. The simulations show that the conductor charging potential decreases with increasing neutral background density due to the production of secondary electrons near the conductor surface. The simulations also indicate that the beam radius is generally proportional to the beam electron gyroradius when the conductor is charged to a large potential. It appears that the charge buildup at the beam stagnation point causes the beam radial expansion. A survey of the simulation results suggests that the ratio of the beam radius to the beam electron gyroradius increases with the square root of beam density and decreases inversely with beam injection velocity. These results are useful for explaining the spacecraft charging phenomena observed during SEPAC experiments from Spacelab 1.

  14. Analysis and Interpretation of Interactions in Agricultural Research

    Technology Transfer Automated Retrieval System (TEKTRAN)

    When reporting on well conducted research, a characteristic of a complete and proper manuscript is one that includes analyses and interpretations of all interactions. The purpose of this article is to provide specific guidelines on how to analyze and interpret interactions of fixed effects in resear...

  15. Control-structure-thermal interactions in analysis of lunar telescopes

    NASA Technical Reports Server (NTRS)

    Thompson, Roger C.

    1992-01-01

    The lunar telescope project was an excellent model for the CSTI study because a telescope is a very sensitive instrument, and thermal expansion or mechanical vibration of the mirror assemblies will rapidly degrade the resolution of the device. Consequently, the interactions are strongly coupled. The lunar surface experiences very large temperature variations that range from approximately -180 C to over 100 C. Although the optical assemblies of the telescopes will be well insulated, the temperature of the mirrors will inevitably fluctuate in a similar cycle, but of much smaller magnitude. In order to obtain images of high quality and clarity, allowable thermal deformations of any point on a mirror must be less than 1 micron. Initial estimates indicate that this corresponds to a temperature variation of much less than 1 deg through the thickness of the mirror. Therefore, a lunar telescope design will most probably include active thermal control, a means of controlling the shape of the mirrors, or a combination of both systems. Historically, the design of a complex vehicle was primarily a sequential process in which the basic structure was defined without concurrent detailed analyses or other subsystems. The basic configuration was then passed to the different teams responsible for each subsystem, and their task was to produce a workable solution without requiring major alterations to any principal components or subsystems. Consequently, the final design of the vehicle was not always the most efficient, owing to the fact that each subsystem design was partially constrained by the previous work. This procedure was necessary at the time because the analysis process was extremely time-consuming and had to be started over with each significant alteration of the vehicle. With recent advances in the power and capacity of small computers, and the parallel development of powerful software in structural, thermal, and control system analysis, it is now possible to produce very

  16. On the properties of Se⋯N interaction: the analysis of substituent effects by energy decomposition and orbital interaction.

    PubMed

    Zhou, Fangfang; Liu, Ruirui; Tang, Jia; Li, Ping; Cui, Yahui; Zhang, Houyu

    2016-01-01

    The nature and strength of intermolecular Se⋯N interaction between selenium-containing compounds HSeX (X = CH3, NH2, CF3, OCH3, CN, OH, NO2, Cl, F), and NH3 have been investigated at the MP2/aug-cc-pVDZ level. The Se⋯N interaction is found to be dependent on the substituent groups, which greatly affect the positive electrostatic potential of Se atoms and the accepting electron ability of X-Se σ(∗) antibonding orbital. Energy decomposition of the Se ⋯N interaction reveals that electrostatic and induction forces are comparable in the weak-bonded complexes and induction becomes more significant in the complexes with strong electron-withdrawing substituents. Natural bond orbital (NBO) analysis indicates that the primary source of the induction is the electron transfer from the N lone pair to the X-Se σ(∗) antibonding orbital. The geometry of the complex and the interaction directionality of NH3 to X-Se bond can be regarded as a consequence of the exchange-repulsion. The topological analysis on the electron density reveals the nature of closed-shell interaction in these X-Se⋯N contacts. The Se⋯N interaction in the complexes with the strong electron-withdrawing substituent has a partly covalent character.

  17. Organochlorine Pesticides Exposure and Bladder Cancer: Evaluation from a Gene-Environment Perspective in a Hospital-Based Case-Control Study in the Canary Islands (Spain).

    PubMed

    Boada, L D; Henríquez-Hernández, L A; Zumbado, M; Almeida-González, M; Álvarez-León, E E; Navarro, P; Luzardo, O P

    2016-01-01

    The incidence of bladder cancer has increased significantly since the 1950s. Pesticide exposure has been linked with increasing bladder cancer incidence, although the evidence is inconclusive. However, most epidemiological studies did not evaluate the potential role played by the organochlorine pesticides, the most widely used pesticides in Western countries from the 1940s to the 1970s. Organochlorine pesticides were banned in the late 1970s because of their persistence in the environment and their carcinogenic and mutagenic effects. Organochlorine pesticides were employed in huge amounts in the Spanish archipelago of the Canary Islands; the authors, therefore, evaluated the role played by organochlorine pesticides exposure on bladder cancer. Serum levels of the most prevalent organochlorine pesticides used in the agriculture of these Islands (dichlorodiphenyltrichloroethane [p,p'-DDT], and its metabolites dichlorodiphenyldichloroethylene [p,p'-DDE] and dichlorodiphenyldichloroethane [p,p'-DDD], hexachlorobenzene, hexachlorocyclohexane isomers, aldrin, dieldrin, endrin, heptachlor, cis-chlordane, trans-chlordane, α- and β-endosulfan, endosulfan sulfate, methoxychlor, and mirex) were measured in 140 bladder cancer cases and 206 controls. GST-M1 and GST-T1 gene polymorphisms were genotyped by polymerase chain reaction (PCR)-based methods. These results showed that serum levels of organochlorine pesticides did not increase bladder cancer risk. On the contrary, total burden of hexachlorocyclohexanes was found to be negatively associated to bladder cancer (odds ratio [OR] = 0.929, 95% confidence interval [CI]: 0.865-0.997; P = .041). This effect disappeared when the distribution of the gluthathione S-transferase polymorphisms was introduced in the statistical model. These results indicate that organochlorine pesticides are not a risk factor for bladder cancer. However, these findings provide additional evidence of gene-environment interactions for organochlorine

  18. Interactive display/graphics systems for remote sensor data analysis.

    NASA Technical Reports Server (NTRS)

    Eppler, W. G.; Loe, D. L.; Wilson, E. L.; Whitley, S. L.; Sachen, R. J.

    1971-01-01

    Using a color-television display system and interactive graphics equipment on-line to an IBM 360/44 computer, investigators at the Manned Spacecraft Center have developed a variety of interactive displays which aid in analyzing remote sensor data. This paper describes how such interactive displays are used to: (1) analyze data from a multispectral scanner, (2) develop automatic pattern recognition systems based on multispectral scanner measurements, and (3) analyze data from nonimaging sensors such as the infrared radiometer and microwave scatterometer.

  19. Probabilistic Analysis of International Space Station Plasma Interaction

    NASA Astrophysics Data System (ADS)

    Reddell, B.; Alred, J.; Kramer, L.; Mikatarian, R.; Minow, J.; Koontz, S.

    2005-12-01

    To date, the International Space Station (ISS) has been one of the largest objects flown in lower earth orbit (LEO). The ISS utilizes high voltage solar arrays (160V) that are negatively grounded leading to pressurized elements that can float negatively with respect to the plasma. Because laboratory measurements indicate a dielectric breakdown potential difference of 80V, arcing could occur on the ISS structure. To overcome the possibility of arcing and clamp the potential of the structure, two Plasma Contactor Units (PCUs) were designed, built, and flown. Also a limited amount of measurements of the floating potential for the present ISS configuration were made by a Floating Potential Probe (FPP), indicating a minimum potential of -24 Volts at the measurement location. A predictive tool, the ISS Plasma Interaction Model (PIM) has been developed accounting for the solar array electron collection, solar array mast wire and effective conductive area on the structure. The model has been used for predictions of the present ISS configuration. The conductive area has been inferred based on available floating potential measurements. Analysis of FPP and PCU data indicated distribution of the conductive area along the Russian segment of the ISS structure. A significant input to PIM is the plasma environment. The International Reference Ionosphere (IRI 2001) was initially used to obtain plasma temperature and density values. However, IRI provides mean parameters, leading to difficulties in interpretation of on-orbit data, especially at eclipse exit where maximum charging can occur. This limits our predicative capability. Satellite and Incoherent Scatter Radar (ISR) data of plasma parameters have also been collected. Approximately 130,000 electron temperature (Te) and density (Ne) pairs for typical ISS eclipse exit conditions have been extracted from the reduced Langmuir probe data flown aboard the NASA DE-2 satellite. Additionally, another 18,000 Te and Ne pairs of ISR data

  20. Sensitivity analysis of random shell-model interactions

    NASA Astrophysics Data System (ADS)

    Krastev, Plamen; Johnson, Calvin

    2010-02-01

    The input to the configuration-interaction shell model includes many dozens or even hundreds of independent two-body matrix elements. Previous studies have shown that when fitting to experimental low-lying spectra, the greatest sensitivity is to only a few linear combinations of matrix elements. Following Brown and Richter [1], here we consider general two-body interactions in the 1s-0d shell and find that the low-lying spectra are also only sensitive to a few linear combinations of two-body matrix elements. We find out in particular the ground state energies for both the random and non-random (here given by the USDB) interaction are dominated by similar matrix elements, which we try to interpret in terms of monopole and contact interactions, while the excitation energies have completely different character. [4pt] [1] B. Alex Brown and W. A. Richter, Phys. Rev. C 74, 034315 (2006) )

  1. Fluorescence spectroscopic analysis on interaction of fleroxacin with pepsin.

    PubMed

    Lian, Shuqin; Wang, Guirong; Zhou, Liping; Yang, Dongzhi

    2013-01-01

    The interaction between fleroxacin (FLX) and pepsin was investigated by spectrofluorimetry. The effects of FLX on pepsin showed that the microenvironment of tryptophan residues and molecular conformation of pepsin were changed based on fluorescence quenching and synchronous fluorescence spectroscopy in combination with three-dimensional fluorescence spectroscopy. Static quenching was suggested and it was proved that the fluorescence quenching of pepsin by FLX was related to the formation of a new complex and a non-radiation energy transfer. The quenching constants KSV , binding constants K and binding sites n were calculated at different temperatures. The molecular interaction distance (r = 6.71) and energy transfer efficiency (E = 0.216) between pepsin and FLX were obtained according to the Forster mechanism of non-radiation energy transfer. Hydrophobic and electrostatic interaction played a major role in FLX-pepsin association. In addition, the hydrophobic interaction and binding free energy were further tested by molecular modeling study.

  2. Analysis of IUE spectra using the interactive data language

    NASA Technical Reports Server (NTRS)

    Joseph, C. L.

    1981-01-01

    The Interactive Data Language (IDL) is used to analyze high resolution spectra from the IUE. Like other interactive languages, IDL is designed for use by the scientist rather than the professional programmer, allowing him to conceive of his data as simple entities and to operate on this data with minimal difficulty. A package of programs created to analyze interstellar absorption lines is presented as an example of the graphical power of IDL.

  3. An interactive virtual environment for finite element analysis

    SciTech Connect

    Bradshaw, S.; Canfield, T.; Kokinis, J.; Disz, T.

    1995-06-01

    Virtual environments (VE) provide a powerful human-computer interface that opens the door to exciting new methods of interaction with high-performance computing applications in several areas of research. The authors are interested in the use of virtual environments as a user interface to real-time simulations used in rapid prototyping procedures. Consequently, the authors are developing methods for coupling finite element models of complex mechanical systems with a VE interface for real-time interaction.

  4. A Transactional Analysis of Interaction-Free Measurements

    NASA Astrophysics Data System (ADS)

    Cramer, John G.

    2006-02-01

    The transactional interpretation of quantum mechanics is applied to the "interaction-free" measurement scenario of Elitzur and Vaidman and to the Quantum Zeno Effect version of the measurement scenario by Kwiat, et al. It is shown that the non-classical information provided by the measurement scheme is supplied by the probing of the intervening object by incomplete offer and confirmation waves that do not form complete transactions or lead to real interactions.

  5. A Transactional Analysis of Quantum Interaction-Free Measurements

    NASA Astrophysics Data System (ADS)

    Cramer, John G.

    2000-04-01

    In 1993 Elitzur and Vaidmann(A. C. Elitzur and L. Vaidman, Found. Physics 23), 987-997 (1993). (EV) demonstrated that quantum mechanics permits the use of light quanta to examine an object without a single photon having actually interacted with the object, requiring only the possibility of such an interaction. The EV scenario has recently been carried out in the laboratory and its predictions verified. EV discussed their scenario in terms of the Copenhagen interpretation of quantum mechanics, in which the interaction-free result is rather mysterious, using a ``knowledge'' not available classically. They also used the Everett-Wheeler interpretation and suggested that the information indicating the presence of the opaque object comes from an interaction in a separate Everett-Wheeler universe, with the information communicated to our universe through the absence of interference. In the present work, we will examine the EV interaction-free scenario in terms of the transactional interpretation of quantum mechanics(J. G. Cramer, Reviews of Modern Physics 58), 647-687 (1986); see http://www.npl.washington.edu/ti and will provide a more plausible account of the physical processes that make possible quantum interaction-free measurements.

  6. An Interactional Analysis of One-to-One Pastoral Care Delivery within a Primary School

    ERIC Educational Resources Information Center

    Bradley, Louise; Butler, Carly W.

    2017-01-01

    Despite an interactional analysis being able to offer valuable insight into the institutional workings of pastoral care practice, pastoral care delivery remains largely unstudied. This paper will contribute new knowledge to the field of counselling and education by offering an interactional analysis of one-to-one pastoral care provision within a…

  7. Orbiter subsystem hardware/software interaction analysis. Volume 8: Forward reaction control system

    NASA Technical Reports Server (NTRS)

    Becker, D. D.

    1980-01-01

    The results of the orbiter hardware/software interaction analysis for the AFT reaction control system are presented. The interaction between hardware failure modes and software are examined in order to identify associated issues and risks. All orbiter subsystems and interfacing program elements which interact with the orbiter computer flight software are analyzed. The failure modes identified in the subsystem/element failure mode and effects analysis are discussed.

  8. An interaction stress analysis of nanoscale elastic asperity contacts.

    PubMed

    Rahmat, Meysam; Ghiasi, Hossein; Hubert, Pascal

    2012-01-07

    A new contact mechanics model is presented and experimentally examined at the nanoscale. The current work addresses the well-established field of contact mechanics, but at the nanoscale where interaction stresses seem to be effective. The new model combines the classic Hertz theory with the new interaction stress concept to provide the stress field in contact bodies with adhesion. Hence, it benefits from the simplicity of non-adhesive models, while offering the same applicability as more complicated models. In order to examine the model, a set of atomic force microscopy experiments were performed on substrates made from single-walled carbon nanotube buckypaper. The stress field in the substrate was obtained by superposition of the Hertzian stress field and the interaction stress field, and then compared to other contact models. Finally, the effect of indentation depth on the stress field was studied for the interaction model as well as for the Hertz, Derjaguin-Muller-Toporov, and Johnson-Kendall-Roberts models. Thus, the amount of error introduced by using the Hertz theory to model contacts with adhesion was found for different indentation depths. It was observed that in the absence of interaction stress data, the Hertz theory predictions led to smaller errors compared to other contact-with-adhesion models.

  9. EDP: A computer program for analysis of biotic interactions

    NASA Astrophysics Data System (ADS)

    Gibson, Michael A.; Bolton, James C.

    1992-07-01

    Analyzing fossils for evidence of biotic interactions such as parasitism, commensalism, and predation can be accomplished using skeletal relationships (e.g. overlapping growth) on individual specimens and statistical information on populations of specimens. The latter approach provides information for use in larger scale paleocommunity analyses. This approach requires a large data set and extensive amounts of information management. The types of information that are needed include data concerning the identity of host and epibiont species, orientation of epibionts on hosts, position of encrustation, growth directions, region of occurrence, and associated fauna. We have written the Epibiont Digitizing Program (EDP) to collect the data necessary to study biotic interactions in the fossil record. The program is operator-interactive at all stages and versatile enough to allow modification depending upon the specific needs of the researcher.

  10. Generating mammalian sirtuin tools for protein-interaction analysis.

    PubMed

    Hershberger, Kathleen A; Motley, Jonathan; Hirschey, Matthew D; Anderson, Kristin A

    2013-01-01

    The sirtuins are a family of NAD(+)-dependent deacylases with important effects on aging, cancer, and metabolism. Sirtuins exert their biological effects by catalyzing deacetylation and/or deacylation reactions in which Acyl groups are removed from lysine residues of specific proteins. A current challenge is to identify specific sirtuin target proteins against the high background of acetylated proteins recently identified by proteomic surveys. New evidence indicates that bona fide sirtuin substrate proteins form stable physical associations with their sirtuin regulator. Therefore, identification of sirtuin interacting proteins could be a useful aid in focusing the search for substrates. Described here is a method for identifying sirtuin protein interactors. Employing basic techniques of molecular cloning and immunochemistry, the method describes the generation of mammalian sirtuin protein expression plasmids and their use to overexpress and immunoprecipitate sirtuins with their interacting partners. Also described is the use of the Database for Annotation, Visualization, and Integrated Discovery for interpreting the sirtuin protein-interaction data obtained.

  11. Combining microsimulation and spatial interaction models for retail location analysis

    NASA Astrophysics Data System (ADS)

    Nakaya, Tomoki; Fotheringham, A. Stewart; Hanaoka, Kazumasa; Clarke, Graham; Ballas, Dimitris; Yano, Keiji

    2007-12-01

    Although the disaggregation of consumers is crucial in understanding the fragmented markets that are dominant in many developed countries, it is not always straightforward to carry out such disaggregation within conventional retail modelling frameworks due to the limitations of data. In particular, consumer grouping based on sampled data is not assured to link with the other statistics that are vital in estimating sampling biases and missing variables in the sampling survey. To overcome this difficulty, we propose a useful combination of spatial interaction modelling and microsimulation approaches for the reliable estimation of retail interactions based on a sample survey of consumer behaviour being linked with other areal statistics. We demonstrate this approach by building an operational retail interaction model to estimate expenditure flows from households to retail stores in a local city in Japan, Kusatsu City.

  12. Rod-cone interactions and analysis of retinal disease.

    PubMed Central

    Arden, G B; Hogg, C R

    1985-01-01

    Cone flicker threshold rises as the rods dark adapt, though the cone threshold to continuous light remains constant. The rise is normally about 1 log unit, but in certain patients who complain of night blindness it may be as great as 2.5 log units. In these persons the kinetics of the rod-cone interaction are those of the recovery of rod sensitivity. The rods impose a low-pass filter on the cones. This effect is absent in congenital nyctalopia and X-linked retinoschisis. We suggest that cone flicker is maintained through a feedback system involving horizontal cells, and when the rod dark current returns in dark adaptation this feedback is altered. Rod cone interaction thus tests rod dark current, and cases of abnormal interaction in patients with retinitis pigmentosa occur, which indicate that the transduction mechanism and the membrane dark current may be differentially affected. Images PMID:3873959

  13. A Time Domain Analysis of Gust-Cascade Interaction Noise

    NASA Technical Reports Server (NTRS)

    Nallasamy, M.; Hixon, R.; Sawyer, S. D.; Dyson, R. W.

    2003-01-01

    The gust response of a 2 D cascade is studied by solving the full nonlinear Euler equations employing higher order accurate spatial differencing and time stepping techniques. The solutions exhibit the exponential decay of the two circumferential mode orders of the cutoff blade passing frequency (BPF) tone and propagation of one circumferential mode order at 2BPF, as would be expected for the flow configuration considered. Two frequency excitations indicate that the interaction between the frequencies and the self interaction contribute to the amplitude of the propagating mode.

  14. An impedance analysis of double-stream interaction in semiconductors

    NASA Technical Reports Server (NTRS)

    Chen, P. W.; Durney, C. H.

    1972-01-01

    The electromagnetic waves propagating through a drifting semiconductor plasma are studied from a macroscopic point of view in terms of double-stream interaction. The possible existing waves (helicon waves, longitudinal waves, ordinary waves, and pseudolongitudinal waves) which depend upon the orientation of the dc external magnetic field are derived. A powerful impedance concept is introduced to investigate the wave behavior of longitudinal (space charge) waves or pseudolongitudinal waves in a semiconductor plasma. The impedances due to one- and two-carrier stream interactions were calculated theoretically.

  15. Mathematical Analysis of a Coarsening Model with Local Interactions

    NASA Astrophysics Data System (ADS)

    Helmers, Michael; Niethammer, Barbara; Velázquez, Juan J. L.

    2016-10-01

    We consider particles on a one-dimensional lattice whose evolution is governed by nearest-neighbor interactions where particles that have reached size zero are removed from the system. Concentrating on configurations with infinitely many particles, we prove existence of solutions under a reasonable density assumption on the initial data and show that the vanishing of particles and the localized interactions can lead to non-uniqueness. Moreover, we provide a rigorous upper coarsening estimate and discuss generic statistical properties as well as some non-generic behavior of the evolution by means of heuristic arguments and numerical observations.

  16. Isothermal calorimetric analysis of lectin-sugar interaction.

    PubMed

    Takeda, Yoichi; Matsuo, Ichiro

    2014-01-01

    Isothermal titration calorimetry (ITC) is a powerful tool for analyzing lectin-glycan interactions because it can measure the binding affinity and thermodynamic properties such as ∆H and ΔS in a single experiment without any chemical modification or immobilization. Here we describe a method for preparing glycan and lectin solution to minimize the buffer mismatch, setting parameters, and performing experiments.

  17. Modeling Heterogeneity in Social Interaction Processes Using Multilevel Survival Analysis

    ERIC Educational Resources Information Center

    Stoolmiller, Mike; Snyder, James

    2006-01-01

    More than 15 years ago, survival or hazard regression analyses were introduced to psychology (W. Gardner & W. A. Griffin, 1989; W. A. Griffin & W. Gardner, 1989) as powerful methodological tools for studying real time social interaction processes among dyads. Almost no additional published applications have appeared, although such data are…

  18. Studying bubble-particle interactions by zeta potential distribution analysis.

    PubMed

    Wu, Chendi; Wang, Louxiang; Harbottle, David; Masliyah, Jacob; Xu, Zhenghe

    2015-07-01

    Over a decade ago, Xu and Masliyah pioneered an approach to characterize the interactions between particles in dynamic environments of multicomponent systems by measuring zeta potential distributions of individual components and their mixtures. Using a Zetaphoremeter, the measured zeta potential distributions of individual components and their mixtures were used to determine the conditions of preferential attachment in multicomponent particle suspensions. The technique has been applied to study the attachment of nano-sized silica and alumina particles to sub-micron size bubbles in solutions with and without the addition of surface active agents (SDS, DAH and DF250). The degree of attachment between gas bubbles and particles is shown to be a function of the interaction energy governed by the dispersion, electrostatic double layer and hydrophobic forces. Under certain chemical conditions, the attachment of nano-particles to sub-micron size bubbles is shown to be enhanced by in-situ gas nucleation induced by hydrodynamic cavitation for the weakly interacting systems, where mixing of the two individual components results in negligible attachment. Preferential interaction in complex tertiary particle systems demonstrated strong attachment between micron-sized alumina and gas bubbles, with little attachment between micron-sized alumina and silica, possibly due to instability of the aggregates in the shear flow environment.

  19. Multi-Dimensional Analysis of Dynamic Human Information Interaction

    ERIC Educational Resources Information Center

    Park, Minsoo

    2013-01-01

    Introduction: This study aims to understand the interactions of perception, effort, emotion, time and performance during the performance of multiple information tasks using Web information technologies. Method: Twenty volunteers from a university participated in this study. Questionnaires were used to obtain general background information and…

  20. Analysis of magnetic field plasma interactions using microparticles as probes

    NASA Astrophysics Data System (ADS)

    Dropmann, Michael; Laufer, Rene; Herdrich, Georg; Matthews, Lorin S.; Hyde, Truell W.

    2015-08-01

    The interaction between a magnetic field and plasma close to a nonconductive surface is of interest for both science and technology. In space, crustal magnetic fields on celestial bodies without atmosphere can interact with the solar wind. In advanced technologies such as those used in fusion or spaceflight, magnetic fields can be used to either control a plasma or protect surfaces exposed to the high heat loads produced by plasma. In this paper, a method will be discussed for investigating magnetic field plasma interactions close to a nonconductive surface inside a Gaseous Electronics Conference reference cell employing dust particles as probes. To accomplish this, a magnet covered by a glass plate was exposed to a low power argon plasma. The magnetic field was strong enough to magnetize the electrons, while not directly impacting the dynamics of the ions or the dust particles used for diagnostics. In order to investigate the interaction of the plasma with the magnetic field and the nonconductive surface, micron-sized dust particles were introduced into the plasma and their trajectories were recorded with a high-speed camera. Based on the resulting particle trajectories, the accelerations of the dust particles were determined and acceleration maps over the field of view were generated which are representative of the forces acting on the particles. The results show that the magnetic field is responsible for the development of strong electric fields in the plasma, in both horizontal and vertical directions, leading to complex motion of the dust particles.

  1. A dynamical proximity analysis of interacting galaxy pairs

    NASA Technical Reports Server (NTRS)

    Chatterjee, Tapan K.

    1990-01-01

    Using the impulsive approximation to study the velocity changes of stars during disk-sphere collisions and a method due to Bottlinger to study the post collision orbits of stars, the formation of various types of interacting galaxies is studied as a function of the distance of closest approach between the two galaxies.

  2. A Cross-Cultural Analysis of Imagined Interactions

    ERIC Educational Resources Information Center

    McCann, Robert M.; Honeycutt, James M.

    2006-01-01

    This study examines imagined interactions (IIs) among young adults in the United States, Thailand, and Japan. A comparison of means across cultures on II characteristics reveals that the Japanese participants have the widest variety of II partners, whereas the American participants are the most self-dominant in their IIs and demonstrate the most…

  3. NMR-based analysis of protein-ligand interactions.

    PubMed

    Cala, Olivier; Guillière, Florence; Krimm, Isabelle

    2014-02-01

    Physiological processes are mainly controlled by intermolecular recognition mechanisms involving protein-protein and protein-ligand (low molecular weight molecules) interactions. One of the most important tools for probing these interactions is high-field solution nuclear magnetic resonance (NMR) through protein-observed and ligand-observed experiments, where the protein receptor or the organic compounds are selectively detected. NMR binding experiments rely on comparison of NMR parameters of the free and bound states of the molecules. Ligand-observed methods are not limited by the protein molecular size and therefore have great applicability for analysing protein-ligand interactions. The use of these NMR techniques has considerably expanded in recent years, both in chemical biology and in drug discovery. We review here three major ligand-observed NMR methods that depend on the nuclear Overhauser effect-transferred nuclear Overhauser effect spectroscopy, saturation transfer difference spectroscopy and water-ligand interactions observed via gradient spectroscopy experiments-with the aim of reporting recent developments and applications for the characterization of protein-ligand complexes, including affinity measurements and structural determination.

  4. Tangent map analysis of the beam-beam interaction

    SciTech Connect

    Lee, S.Y.; Tepikian, S.

    1989-01-01

    We studied the tangent map of the beam-beam interaction and found no evidence of beam-beam instability for /epsilon/ = 0.04. Tracking study with tune modulation shows however large emittance growth due to the sum resonances. The emittance growth is due to the multiple crossing of the sum resonances. 12 refs., 7 figs.

  5. Interaction Analysis in Performing Arts: A Case Study in Multimodal Choreography

    NASA Astrophysics Data System (ADS)

    Christou, Maria; Luciani, Annie

    The growing overture towards interacting virtual words and the variety of uses, have brought great changes in the performing arts, that worth a profound analysis in order to understand the emerging issues. We examine the performance conception for its embodiment capacity with a methodology based on interaction analysis. Finally, we propose a new situation of multimodal choreography that respects the aforementioned analysis, and we evaluate the results on a simulation exercise.

  6. The Influence of Major Life Events on Economic Attitudes in a World of Gene-Environment Interplay

    PubMed Central

    Hatemi, Peter K.

    2014-01-01

    The role of “genes” on political attitudes has gained attention across disciplines. However, person-specific experiences have yet to be incorporated into models that consider genetic influences. Relying on a gene-environment interplay approach, this study explicates how life-events, such as losing one’s job or suffering a financial loss, influence economic policy attitudes. The results indicate genetic and environmental variance on support for unions, immigration, capitalism, socialism and property tax is moderated by financial risks. Changes in the magnitude of genetic influences, however, are temporary. After two years, the phenotypic effects of the life events remain on most attitudes, but changes in the sources of individual differences do not. Univariate twin models that estimate the independent contributions of genes and environment on the variation of attitudes appear to provide robust baseline indicators of sources of individual differences. These estimates, however, are not event or day specific. In this way, genetic influences add stability, while environment cues change, and this process is continually updated. PMID:24860199

  7. The Influence of Major Life Events on Economic Attitudes in a World of Gene-Environment Interplay.

    PubMed

    Hatemi, Peter K

    2013-10-01

    The role of "genes" on political attitudes has gained attention across disciplines. However, person-specific experiences have yet to be incorporated into models that consider genetic influences. Relying on a gene-environment interplay approach, this study explicates how life-events, such as losing one's job or suffering a financial loss, influence economic policy attitudes. The results indicate genetic and environmental variance on support for unions, immigration, capitalism, socialism and property tax is moderated by financial risks. Changes in the magnitude of genetic influences, however, are temporary. After two years, the phenotypic effects of the life events remain on most attitudes, but changes in the sources of individual differences do not. Univariate twin models that estimate the independent contributions of genes and environment on the variation of attitudes appear to provide robust baseline indicato