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Sample records for gene-environment interaction analysis

  1. Gene-environment interaction.

    PubMed

    Manuck, Stephen B; McCaffery, Jeanne M

    2014-01-01

    With the advent of increasingly accessible technologies for typing genetic variation, studies of gene-environment (G×E) interactions have proliferated in psychological research. Among the aims of such studies are testing developmental hypotheses and models of the etiology of behavioral disorders, defining boundaries of genetic and environmental influences, and identifying individuals most susceptible to risk exposures or most amenable to preventive and therapeutic interventions. This research also coincides with the emergence of unanticipated difficulties in detecting genetic variants of direct association with behavioral traits and disorders, which may be obscured if genetic effects are expressed only in predisposing environments. In this essay we consider these and other rationales for positing G×E interactions, review conceptual models meant to inform G×E interpretations from a psychological perspective, discuss points of common critique to which G×E research is vulnerable, and address the role of the environment in G×E interactions.

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

    PubMed Central

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

    2013-01-01

    Background Obesity and diabetes are potentially alterable risk factors for pancreatic cancer. Genetic factors that modify the associations of obesity and diabetes with pancreatic cancer have previously not been examined at the genome-wide level. Methods Using GWAS genotype and risk factor data from the Pancreatic Cancer Case Control Consortium, we conducted a discovery study of 2,028 cases and 2,109 controls to examine gene-obesity and gene-diabetes interactions in relation to pancreatic cancer risk by employing the likelihood ratio test (LRT) nested in logistic regression models and Ingenuity Pathway Analysis (IPA). Results After adjusting for multiple comparisons, a significant interaction of the chemokine signaling pathway with obesity (P = 3.29 × 10−6) and a near significant interaction of calcium signaling pathway with diabetes (P = 1.57 × 10−4) in modifying the risk of pancreatic cancer was observed. These findings were supported by results from IPA analysis of the top genes with nominal interactions. The major contributing genes to the two top pathways include GNGT2, RELA, TIAM1 and GNAS. None of the individual genes or SNPs except one SNP remained significant after adjusting for multiple testing. Notably, SNP rs10818684 of the PTGS1 gene showed an interaction with diabetes (P = 7.91 × 10−7) at a false discovery rate of 6%. Conclusions Genetic variations in inflammatory response and insulin resistance may affect the risk of obesity and diabetes-related pancreatic cancer. These observations should be replicated in additional large datasets. Impact Gene-environment interaction analysis may provide new insights into the genetic susceptibility and molecular mechanisms of obesity- and diabetes-related pancreatic cancer. PMID:24136929

  3. Genome-wide analysis of gestational gene-environment interactions in the developing kidney

    PubMed Central

    Yan, Lei; Yao, Xiao; Bachvarov, Dimcho; Saifudeen, Zubaida

    2014-01-01

    The G protein-coupled bradykinin B2 receptor (Bdkrb2) plays an important role in regulation of blood pressure under conditions of excess salt intake. Our previous work has shown that Bdkrb2 also plays a developmental role since Bdkrb2−/− embryos, but not their wild-type or heterozygous littermates, are prone to renal dysgenesis in response to gestational high salt intake. Although impaired terminal differentiation and apoptosis are consistent findings in the Bdkrb2−/− mutant kidneys, the developmental pathways downstream of gene-environment interactions leading to the renal phenotype remain unknown. Here, we performed genome-wide transcriptional profiling on embryonic kidneys from salt-stressed Bdkrb2+/+ and Bdkrb2−/− embryos. The results reveal significant alterations in key pathways regulating Wnt signaling, apoptosis, embryonic development, and cell-matrix interactions. In silico analysis reveal that nearly 12% of differentially regulated genes harbor one or more Pax2 DNA-binding sites in their promoter region. Further analysis shows that metanephric kidneys of salt-stressed Bdkrb2−/− have a significant downregulation of Pax2 gene expression. This was corroborated in Bdkrb2−/−;Pax2GFP+/tg mice, demonstrating that Pax2 transcriptional activity is significantly repressed by gestational salt-Bdkrb2 interactions. We conclude that gestational gene (Bdkrb2) and environment (salt) interactions cooperate to impact gene expression programs in the developing kidney. Suppression of Pax2 likely contributes to the defects in epithelial survival, growth, and differentiation in salt-stressed BdkrB2−/− mice. PMID:25005792

  4. 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...

  5. 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…

  6. 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

  7. Integrative Analysis of Gene-Environment Interactions under a Multi-response Partially Linear Varying Coefficient Model

    PubMed Central

    Wu, Cen; Cui, Yuehua; Ma, Shuangge

    2014-01-01

    Consider the integrative analysis of genetic data with multiple correlated response variables. The goal is to identify important gene-environment (G×E) interactions along with main gene and environment effects that are associated with the responses. The homogeneity and heterogeneity models can be adopted to describe the genetic basis of multiple responses. To accommodate possible nonlinear effects of some environment effects, a multi-response partially linear varying coefficient (MPLVC) model is assumed. Penalization is adopted for marker selection. The proposed penalization method can select genetic variants with G×E interactions, no G×E interactions, and no main effects simultaneously. It adopts different penalties to accommodate the homogeneity and heterogeneity models. The proposed method can be effectively computed using a coordinate descent algorithm. Simulation study and the analysis of Health Professional’s Follow-up Study (HPFS), which has two correlated continuous traits, SNP measurements, and multiple environment effects, show superior performance of the proposed method over its competitors. PMID:25146388

  8. BAYESIAN METHODS FOR GENETIC ASSOCIATION ANALYSIS WITH HETEROGENEOUS SUBGROUPS: FROM META-ANALYSES TO GENE-ENVIRONMENT INTERACTIONS

    PubMed Central

    Wen, Xiaoquan; Stephens, Matthew

    2015-01-01

    Genetic association analyses often involve data from multiple potentially-heterogeneous subgroups. The expected amount of heterogeneity can vary from modest (e.g. a typical meta-analysis), to large (e.g. a strong gene-environment interaction). However, existing statistical tools are limited in their ability to address such heterogeneity. Indeed, most genetic association meta-analyses use a “fixed effects” analysis, which assumes no heterogeneity. Here we develop and apply Bayesian association methods to address this problem. These methods are easy to apply (in the simplest case, requiring only a point estimate for the genetic effect, and its standard error, from each subgroup), and effectively include standard frequentist meta-analysis methods, including the usual “fixed effects” analysis, as special cases. We apply these tools to two large genetic association studies: one a meta-analysis of genome-wide association studies from the Global Lipids consortium, and the second a cross-population analysis for expression quantitative trait loci (eQTLs). In the Global Lipids data we find, perhaps surprisingly, that effects are generally quite homogeneous across studies. In the eQTL study we find that eQTLs are generally shared among different continental groups, and discuss consequences of this for study design. PMID:26413181

  9. 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.

  10. 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…

  11. 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

  12. 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.

  13. 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

  14. Gene-environment interactions in ocular diseases.

    PubMed

    Sacca, S C; Bolognesi, C; Battistella, A; Bagnis, A; Izzotti, A

    2009-07-10

    Degenerative ocular diseases are widespread in the population and represent a major cause of reversible and irreversible blindness. Scientific evidences have been accumulating supporting the role of genotoxic damage and gene environment interactions in the pathogenesis of these diseases mainly including glaucoma, age-related macular degeneration, and cataract. Glaucoma, in its degenerative form, is characterized by the degeneration of the trabecular meshwork, the tissue of the anterior chamber of the eye devoted to aqueous-humour outflow. Such a degenerative process results in intra-ocular pressure increase and progressive damage of optic nerve head. Oxidative stress and DNA damage play an important role in inducing the degeneration of these well differentiated target tissues in which DNA damage results in a progressive cell loss. Macular degeneration is a common age-related disease affecting the central regions of the retina inducing progressive accumulation of oxidized lipoproteins and neovascularization. Environmental genotoxic risk factors include diet, light, and cigarette smoke paralleled by individual susceptibility as determined by adverse genetic assets. Cataract is a progressive opacity of the crystalline lens resulting from molecular damages induced by various risk factors including UV-containing light. This disease has been related to a failure in antioxidant defences. Experimental study provides evidence that cataract patients possess higher basal level of DNA damage, as evaluated by Comet test, in lymphocytes than controls. This finding is paralleled by the higher susceptibility to oxidative stress observed in the same patients. These novel experimental data further support the role of DNA damage as a main factor contributing to cataract onset. In conclusion, the examined degenerative ocular diseases recognise environmental risk factors often displaying genotoxic attitudes. Whenever these factors target individuals who are susceptible due their

  15. Gene-environment interactions in human disease: nuisance or opportunity?

    PubMed

    Ober, Carole; Vercelli, Donata

    2011-03-01

    Many environmental risk factors for common, complex human diseases have been revealed by epidemiologic studies, but how genotypes at specific loci modulate individual responses to environmental risk factors is largely unknown. Gene-environment interactions will be missed in genome-wide association studies and could account for some of the 'missing heritability' for these diseases. In this review, we focus on asthma as a model disease for studying gene-environment interactions because of relatively large numbers of candidate gene-environment interactions with asthma risk in the literature. Identifying these interactions using genome-wide approaches poses formidable methodological problems, and elucidating molecular mechanisms for these interactions has been challenging. We suggest that studying gene-environment interactions in animal models, although more tractable, might not be sufficient to shed light on the genetic architecture of human diseases. Lastly, we propose avenues for future studies to find gene-environment interactions.

  16. 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.

  17. Gene-Environment Interaction in Psychological Traits and Disorders

    PubMed Central

    Dick, Danielle M.

    2013-01-01

    There has been an explosion of interest in studying gene-environment interactions (GxE) as they relate to the development of psychopathol-ogy. In this article, I review different methodologies to study gene-environment interaction, providing an overview of methods from animal and human studies and illustrations of gene-environment interactions detected using these various methodologies. Gene-environment interaction studies that examine genetic influences as modeled latently (e.g., from family, twin, and adoption studies) are covered, as well as studies of measured genotypes. Importantly, the explosion of interest in gene-environment interactions has raised a number of challenges, including difficulties with differentiating various types of interactions, power, and the scaling of environmental measures, which have profound implications for detecting gene-environment interactions. Taking research on gene-environment interactions to the next level will necessitate close collaborations between psychologists and geneticists so that each field can take advantage of the knowledge base of the other. PMID:21219196

  18. Replication and meta-analysis of the gene-environment interaction between body mass index and the interleukin-6 promoter polymorphism with higher insulin resistance.

    PubMed

    Underwood, Patricia C; Chamarthi, Bindu; Williams, Jonathan S; Sun, Bei; Vaidya, Anand; Raby, Benjamin A; Lasky-Su, Jessica; Hopkins, Paul N; Adler, Gail K; Williams, Gordon H

    2012-05-01

    Insulin resistance (IR) is a complex disorder caused by an interplay of both genetic and environmental factors. Recent studies identified a significant interaction between body mass index (BMI) and the rs1800795 polymorphism of the interleukin-6 gene that influences both IR and onset of type 2 diabetes mellitus, with obese individuals homozygous for the C allele demonstrating the highest level of IR and greatest risk for type 2 diabetes mellitus. Replication of a gene-environment interaction is important to confirm the validity of the initial finding and extend the generalizability of the results to other populations. Thus, the objective of this study was to replicate this gene-environment interaction on IR in a hypertensive population and perform a meta-analysis with prior published results. The replication analysis was performed using white individuals with hypertension from the Hypertensive Pathotype cohort (N = 311), genotyped for rs1800795. Phenotype studies were conducted after participants consumed 2 diets--high sodium (200 mmol/d) and low sodium (10 mmol/d)--for 7 days each. Measurements for plasma glucose, insulin, and interleukin-6 were obtained after 8 hours of fasting. Insulin resistance was characterized by the homeostatic model assessment (HOMA-IR). In Hypertensive Pathotype, BMI was a significant effect modifier of the relationship between rs1800795 and HOMA-IR; higher BMI was associated with higher HOMA-IR among homozygote CC individuals when compared with major allele G carriers (P = .003). Furthermore, the meta-analysis in 1028 individuals confirmed the result, demonstrating the same significant interaction between rs1800795 and BMI on HOMA-IR (P = 1.05 × 10(-6)). This rare replication of a gene-environment interaction extends the generalizability of the results to hypertension while highlighting this polymorphism as a marker of IR in obese individuals.

  19. 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.

  20. Gene-environment interaction and risk of breast cancer.

    PubMed

    Rudolph, Anja; Chang-Claude, Jenny; Schmidt, Marjanka K

    2016-01-19

    Hereditary, genetic factors as well as lifestyle and environmental factors, for example, parity and body mass index, predict breast cancer development. Gene-environment interaction studies may help to identify subgroups of women at high-risk of breast cancer and can be leveraged to discover new genetic risk factors. A few interesting results in studies including over 30,000 breast cancer cases and healthy controls indicate that such interactions exist. Explorative gene-environment interaction studies aiming to identify new genetic or environmental factors are scarce and still underpowered. Gene-environment interactions might be stronger for rare genetic variants, but data are lacking. Ongoing initiatives to genotype larger sample sets in combination with comprehensive epidemiologic databases will provide further opportunities to study gene-environment interactions in breast cancer. However, based on the available evidence, we conclude that associations between the common genetic variants known today and breast cancer risk are only weakly modified by environmental factors, if at all.

  1. Next-generation analysis of cataracts: determining knowledge driven gene-gene interactions using biofilter, and gene-environment interactions using the Phenx Toolkit*.

    PubMed

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

    2015-01-01

    Investigating the association between biobank derived genomic data and the information of linked electronic health records (EHRs) is an emerging area of research for dissecting the architecture of complex human traits, where cases and controls for study are defined through the use of electronic phenotyping algorithms deployed in large EHR systems. For our study, cataract cases and controls were identified within the Marshfield Personalized Medicine Research Project (PMRP) biobank and linked EHR, which is a member of the NHGRI-funded electronic Medical Records and Genomics (eMERGE) Network. Our goal was to explore potential gene-gene and gene-environment interactions within these data for 527,953 and 527,936 single nucleotide polymorphisms (SNPs) for gene-gene and gene-environment analyses, respectively, with minor allele frequency > 1%, in order to explore higher level associations with cataract risk beyond investigations of single SNP-phenotype associations. To build our SNP-SNP interaction models we utilized a prior-knowledge driven filtering method called Biofilter to minimize the multiple testing burden of exploring the vast array of interaction models possible from our extensive number of SNPs. Using Biofilter, we developed 57,376 prior-knowledge directed SNP-SNP models to test for association with cataract status. We selected models that required 6 sources of external domain knowledge. We identified 13 statistically significant SNP-SNP models with an interaction with p-value < 1 × 10(-4), as well as an overall model with p-value < 0.01 associated with cataract status. We also conducted gene-environment interaction analyses for all GWAS SNPs and a set of environmental factors from the PhenX Toolkit: smoking, UV exposure, and alcohol use;these environmental factors have been previously associated with the formation of cataracts. We found a total of 782 gene-environment models that exhibit an interaction with a p-value < 1 × 10(-4) associatedwith cataract

  2. SYMPHONY, an information-theoretic method for gene-gene and gene-environment interaction analysis of disease syndromes.

    PubMed

    Knights, J; Yang, J; Chanda, P; Zhang, A; Ramanathan, M

    2013-06-01

    We develop an information-theoretic method for gene-gene (GGI) and gene-environmental interactions (GEI) analysis of syndromes, defined as a phenotype vector comprising multiple quantitative traits (QTs). The K-way interaction information (KWII), an information-theoretic metric, was derived for multivariate normal distributed phenotype vectors. The utility of the method was challenged with three simulated data sets, the Genetic Association Workshop-15 (GAW15) rheumatoid arthritis data set, a high-density lipoprotein (HDL) and atherosclerosis data set from a mouse QT locus study, and the 1000 Genomes data. The dependence of the KWII on effect size, minor allele frequency, linkage disequilibrium, population stratification/admixture, as well as the power and computational time requirements of the novel method was systematically assessed in simulation studies. In these studies, phenotype vectors containing two and three constituent multivariate normally distributed QTs were used and the KWII was found to be effective at detecting GEI associated with the phenotype. High KWII values were observed for variables and variable combinations associated with the syndrome phenotype compared with uninformative variables not associated with the phenotype. The KWII values for the phenotype-associated combinations increased monotonically with increasing effect size values. The KWII also exhibited utility in simulations with non-linear dependence between the constituent QTs. Analysis of the HDL and atherosclerosis data set indicated that the simultaneous analysis of both phenotypes identified interactions not detected in the analysis of the individual traits. The information-theoretic approach may be useful for non-parametric analysis of GGI and GEI of complex syndromes.

  3. Resilience and measured gene-environment interactions.

    PubMed

    Kim-Cohen, Julia; Turkewitz, Rebecca

    2012-11-01

    The past decade has witnessed an exponential growth in studies that have attempted to identify the genetic polymporphisms that moderate the influence of environmental risks on mental disorders. What tends to be neglected in these Gene × Environment (G × E) interaction studies has been a focus on resilience, which refers to a dynamic pattern of positive adaptation despite the experience of a significant trauma or adversity. In this article, we argue that one step toward advancing the field of developmental psychopathology would be for G × E research to consider resilience instead of focusing almost exclusively on mental disorders. After providing an up-to-date summary on the expanding definitions and models of resilience, and the available evidence regarding measured G × E studies of childhood maltreatment, we discuss why resilience would be a worthwhile phenotype for studies of measured G × E. First, although G × E hypotheses require that there be an environmental risk (e-risk) involved in a causal process that leads to psychopathology, e-risks are typically not included in the diagnostic criteria for most psychiatric disorders. In contrast, resilience by definition includes an e-risk. Second, G × E hypotheses require that there is evidence of variability in response to an environmental stressor, and resilience often represents the positive end on this continuum of adaptation. Third, both resilience and G × E are best understood from a developmental perspective. Fourth, although resilient outcomes are not public health concerns, the types of adversities (e.g., childhood maltreatment, poverty, or exposure to natural disasters) that are often investigated in studies of resilience certainly are. Understanding how some individuals, perhaps because of their genetic makeup, are able to withstand such adversities can inform prevention and intervention efforts to improve mental health.

  4. Resilience and measured gene-environment interactions.

    PubMed

    Kim-Cohen, Julia; Turkewitz, Rebecca

    2012-11-01

    The past decade has witnessed an exponential growth in studies that have attempted to identify the genetic polymporphisms that moderate the influence of environmental risks on mental disorders. What tends to be neglected in these Gene × Environment (G × E) interaction studies has been a focus on resilience, which refers to a dynamic pattern of positive adaptation despite the experience of a significant trauma or adversity. In this article, we argue that one step toward advancing the field of developmental psychopathology would be for G × E research to consider resilience instead of focusing almost exclusively on mental disorders. After providing an up-to-date summary on the expanding definitions and models of resilience, and the available evidence regarding measured G × E studies of childhood maltreatment, we discuss why resilience would be a worthwhile phenotype for studies of measured G × E. First, although G × E hypotheses require that there be an environmental risk (e-risk) involved in a causal process that leads to psychopathology, e-risks are typically not included in the diagnostic criteria for most psychiatric disorders. In contrast, resilience by definition includes an e-risk. Second, G × E hypotheses require that there is evidence of variability in response to an environmental stressor, and resilience often represents the positive end on this continuum of adaptation. Third, both resilience and G × E are best understood from a developmental perspective. Fourth, although resilient outcomes are not public health concerns, the types of adversities (e.g., childhood maltreatment, poverty, or exposure to natural disasters) that are often investigated in studies of resilience certainly are. Understanding how some individuals, perhaps because of their genetic makeup, are able to withstand such adversities can inform prevention and intervention efforts to improve mental health. PMID:23062298

  5. Gene-environment interactions in major depressive disorder.

    PubMed

    Klengel, Torsten; Binder, Elisabeth B

    2013-02-01

    Family, twin, and epidemiologic studies have suggested that both genes and environment are important risk factors for the development of major depressive disorder (MDD). In the absence of consistent and strong main genetic effects, numerous studies have supported gene-environment interactions in this disorder. While the impact of negative environmental factors, such as early life stress, traumatic experiences, and negative life events have been established as risk factors, they are not sufficient to predict MDD. This article will review evidence suggesting that genetic variants moderate the effects of adversities on the development of MDD, with a focus on the importance of careful characterization of the stressful life events as well as systemic and molecular mechanisms that potentially mediate these gene-environment interactions.

  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. PMID:27503943

  9. A penalized robust method for identifying gene-environment interactions.

    PubMed

    Shi, Xingjie; Liu, Jin; Huang, Jian; Zhou, Yong; Xie, Yang; Ma, Shuangge

    2014-04-01

    In high-throughput studies, an important objective is to identify gene-environment interactions associated with disease outcomes and phenotypes. Many commonly adopted methods assume specific parametric or semiparametric models, which may be subject to model misspecification. In addition, they usually use significance level as the criterion for selecting important interactions. In this study, we adopt the rank-based estimation, which is much less sensitive to model specification than some of the existing methods and includes several commonly encountered data and models as special cases. Penalization is adopted for the identification of gene-environment interactions. It achieves simultaneous estimation and identification and does not rely on significance level. For computation feasibility, a smoothed rank estimation is further proposed. Simulation shows that under certain scenarios, for example, with contaminated or heavy-tailed data, the proposed method can significantly outperform the existing alternatives with more accurate identification. We analyze a lung cancer prognosis study with gene expression measurements under the AFT (accelerated failure time) model. The proposed method identifies interactions different from those using the alternatives. Some of the identified genes have important implications.

  10. Gene-environment interaction in posttraumatic stress disorder: an update.

    PubMed

    Koenen, Karestan C; Amstadter, Ananda B; Nugent, Nicole R

    2009-10-01

    The authors provide a detailed review of the extant gene-environment interaction (GxE) research in the etiology of posttraumatic stress disorder (PTSD). They begin with a discussion of why PTSD is uniquely fitting for the innovative framework of GxE methodology, followed by a review of the heritability and main effect molecular genetics studies of PTSD. Next, they discuss the six GxE investigations to date on PTSD. They end with a discussion of future directions and significance of this research, with an emphasis on the expansion of psychosocial factors that may be fitting environmental variables for inclusion in this new research area. The authors posit that GxE research is vital to elucidating risk and resilience following exposure to a potentially traumatic event.

  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. PMID:25773632

  12. 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.

  13. Gene-environment interaction in posttraumatic stress disorder

    PubMed Central

    Nugent, Nicole R.; Amstadter, Ananda B.

    2009-01-01

    The purpose of this article is to encourage research investigating the role of measured gene-environment interaction (G × E) in the etiology of posttraumatic stress disorder (PTSD). PTSD is uniquely suited to the study of G × E as the diagnosis requires exposure to a potentially-traumatic life event. PTSD is also moderately heritable; however, the role of genetic factors in PTSD etiology has been largely neglected both by trauma researchers and psychiatric geneticists. First, we summarize evidence for genetic influences on PTSD from family, twin, and molecular genetic studies. Second, we discuss the key challenges in G × E studies of PTSD and offer practical strategies for addressing these challenges and for discovering replicable G × E for PTSD. Finally, we propose some promising new directions for PTSD G × E research. We suggest that G × E research in PTSD is essential to understanding vulnerability and resilience following exposure to a traumatic event. PMID:18297420

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

    PubMed Central

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

    2013-01-01

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

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

    PubMed

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

    2013-02-01

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

  16. Gene-environment interaction and male reproductive function.

    PubMed

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

    2010-05-01

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

  17. 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.

  18. Sleep Duration and Depressive Symptoms: A Gene-Environment Interaction

    PubMed Central

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

    2014-01-01

    Objective: We used quantitative genetic models to assess whether sleep duration modifies genetic and environmental influences on depressive symptoms. Method: Participants were 1,788 adult twins from 894 same-sex twin pairs (192 male and 412 female monozygotic [MZ] pairs, and 81 male and 209 female dizygotic [DZ] pairs] from the University of Washington Twin Registry. Participants self-reported habitual sleep duration and depressive symptoms. Data were analyzed using quantitative genetic interaction models, which allowed the magnitude of additive genetic, shared environmental, and non-shared environmental influences on depressive symptoms to vary with sleep duration. Results: Within MZ twin pairs, the twin who reported longer sleep duration reported fewer depressive symptoms (ec = -0.17, SE = 0.06, P < 0.05). There was a significant gene × sleep duration interaction effect on depressive symptoms (a'c = 0.23, SE = 0.08, P < 0.05), with the interaction occurring on genetic influences that are common to both sleep duration and depressive symptoms. Among individuals with sleep duration within the normal range (7-8.9 h/night), the total heritability (h2) of depressive symptoms was approximately 27%. However, among individuals with sleep duration within the low (< 7 h/night) or high (≥ 9 h/night) range, increased genetic influence on depressive symptoms was observed, particularly at sleep duration extremes (5 h/night: h2 = 53%; 10 h/night: h2 = 49%). Conclusion: Genetic contributions to depressive symptoms increase at both short and long sleep durations. Citation: Watson NF; Harden KP; Buchwald D; Vitiello MV; Pack AI; Stachan E; Goldberg J. Sleep duration and depressive symptoms: a gene-environment interaction. SLEEP 2014;37(2):351-358. PMID:24497663

  19. 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.

  20. 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

  1. Information-theoretic metrics for visualizing gene-environment interactions.

    PubMed

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

    2007-11-01

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

  2. 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.

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

    PubMed Central

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

    2014-01-01

    Cancer risk is determined by a complex interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified hundreds of common (minor allele frequency [MAF]>0.05) and less common (0.01gene-environment 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 10th–011th, 2012. The objective of the Think Tank was to facilitate discussions on: 1) the state of the science; 2) the goals of gene-environment 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 gene-environment 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. PMID:24123198

  4. 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

  5. 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.…

  6. Comparisons of power of statistical methods for gene-environment interaction analyses.

    PubMed

    Ege, Markus J; Strachan, David P

    2013-10-01

    Any genome-wide analysis is hampered by reduced statistical power due to multiple comparisons. This is particularly true for interaction analyses, which have lower statistical power than analyses of associations. To assess gene-environment interactions in population settings we have recently proposed a statistical method based on a modified two-step approach, where first genetic loci are selected by their associations with disease and environment, respectively, and subsequently tested for interactions. We have simulated various data sets resembling real world scenarios and compared single-step and two-step approaches with respect to true positive rate (TPR) in 486 scenarios and (study-wide) false positive rate (FPR) in 252 scenarios. Our simulations confirmed that in all two-step methods the two steps are not correlated. In terms of TPR, two-step approaches combining information on gene-disease association and gene-environment association in the first step were superior to all other methods, while preserving a low FPR in over 250 million simulations under the null hypothesis. Our weighted modification yielded the highest power across various degrees of gene-environment association in the controls. An optimal threshold for step 1 depended on the interacting allele frequency and the disease prevalence. In all scenarios, the least powerful method was to proceed directly to an unbiased full interaction model, applying conventional genome-wide significance thresholds. This simulation study confirms the practical advantage of two-step approaches to interaction testing over more conventional one-step designs, at least in the context of dichotomous disease outcomes and other parameters that might apply in real-world settings.

  7. 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

  8. 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.

  9. 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. PMID:26139508

  10. 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.

  11. 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

  12. 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

  13. Genetics, environment, and gene-environment interactions in the development of systemic rheumatic diseases.

    PubMed

    Sparks, Jeffrey A; Costenbader, Karen H

    2014-11-01

    Rheumatic diseases offer distinct challenges to researchers because of heterogeneity in disease phenotypes, low disease incidence, and geographic variation in genetic and environmental factors. Emerging research areas, including epigenetics, metabolomics, and the microbiome, may provide additional links between genetic and environmental risk factors in the pathogenesis of rheumatic disease. This article reviews the methods used to establish genetic and environmental risk factors and studies gene-environment interactions in rheumatic diseases, and provides specific examples of successes and challenges in identifying gene-environment interactions in rheumatoid arthritis, systemic lupus erythematosus, and ankylosing spondylitis. Emerging research strategies and future challenges are discussed.

  14. Gene-environment Interaction Models to Unmask Susceptibility Mechanisms in Parkinson's Disease

    PubMed Central

    Chou, Vivian P.; Ko, Novie; Holman, Theodore R.; Manning-Boğ, Amy B.

    2014-01-01

    Lipoxygenase (LOX) activity has been implicated in neurodegenerative disorders such as Alzheimer's disease, but its effects in Parkinson's disease (PD) pathogenesis are less understood. Gene-environment interaction models have utility in unmasking the impact of specific cellular pathways in toxicity that may not be observed using a solely genetic or toxicant disease model alone. To evaluate if distinct LOX isozymes selectively contribute to PD-related neurodegeneration, transgenic (i.e. 5-LOX and 12/15-LOX deficient) mice can be challenged with a toxin that mimics cell injury and death in the disorder. Here we describe the use of a neurotoxin, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), which produces a nigrostriatal lesion to elucidate the distinct contributions of LOX isozymes to neurodegeneration related to PD. The use of MPTP in mouse, and nonhuman primate, is well-established to recapitulate the nigrostriatal damage in PD. The extent of MPTP-induced lesioning is measured by HPLC analysis of dopamine and its metabolites and semi-quantitative Western blot analysis of striatum for tyrosine hydroxylase (TH), the rate-limiting enzyme for the synthesis of dopamine. To assess inflammatory markers, which may demonstrate LOX isozyme-selective sensitivity, glial fibrillary acidic protein (GFAP) and Iba-1 immunohistochemistry are performed on brain sections containing substantia nigra, and GFAP Western blot analysis is performed on striatal homogenates. This experimental approach can provide novel insights into gene-environment interactions underlying nigrostriatal degeneration and PD. PMID:24430802

  15. 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…

  16. 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…

  17. 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.…

  18. A Platform for the Remote Conduct of Gene-Environment Interaction Studies

    PubMed Central

    Gallacher, John; Collins, Rory; Elliott, Paul; Palmer, Stephen; Burton, Paul; Mitchell, Clive; John, Gareth; Lyons, Ronan

    2013-01-01

    Background Gene-environment interaction studies offer the prospect of robust causal inference through both gene identification and instrumental variable approaches. As such they are a major and much needed development. However, conducting these studies using traditional methods, which require direct participant contact, is resource intensive. The ability to conduct gene-environment interaction studies remotely would reduce costs and increase capacity. Aim To develop a platform for the remote conduct of gene-environment interaction studies. Methods A random sample of 15,000 men and women aged 50+ years and living in Cardiff, South Wales, of whom 6,012 were estimated to have internet connectivity, were mailed inviting them to visit a web-site to join a study of successful ageing. Online consent was obtained for questionnaire completion, cognitive testing, re-contact, record linkage and genotyping. Cognitive testing was conducted using the Cardiff Cognitive Battery. Bio-sampling was randomised to blood spot, buccal cell or no request. Results A heterogeneous sample of 663 (4.5% of mailed sample and 11% of internet connected sample) men and women (47% female) aged 50–87 years (median = 61 yrs) from diverse backgrounds (representing the full range of deprivation scores) was recruited. Bio-samples were donated by 70% of those agreeing to do so. Self report questionnaires and cognitive tests showed comparable distributions to those collected using face-to-face methods. Record linkage was achieved for 99.9% of participants. Conclusion This study has demonstrated that remote methods are suitable for the conduct of gene-environment interaction studies. Up-scaling these methods provides the opportunity to increase capacity for large-scale gene-environment interaction studies. PMID:23349852

  19. 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

  20. A unified set-based test with adaptive filtering for gene-environment interaction analyses.

    PubMed

    Liu, Qianying; Chen, Lin S; Nicolae, Dan L; Pierce, Brandon L

    2016-06-01

    In genome-wide gene-environment interaction (GxE) studies, a common strategy to improve power is to first conduct a filtering test and retain only the SNPs that pass the filtering in the subsequent GxE analyses. Inspired by two-stage tests and gene-based tests in GxE analysis, we consider the general problem of jointly testing a set of parameters when only a few are truly from the alternative hypothesis and when filtering information is available. We propose a unified set-based test that simultaneously considers filtering on individual parameters and testing on the set. We derive the exact distribution and approximate the power function of the proposed unified statistic in simplified settings, and use them to adaptively calculate the optimal filtering threshold for each set. In the context of gene-based GxE analysis, we show that although the empirical power function may be affected by many factors, the optimal filtering threshold corresponding to the peak of the power curve primarily depends on the size of the gene. We further propose a resampling algorithm to calculate P-values for each gene given the estimated optimal filtering threshold. The performance of the method is evaluated in simulation studies and illustrated via a genome-wide gene-gender interaction analysis using pancreatic cancer genome-wide association data. PMID:26496228

  1. A unified set-based test with adaptive filtering for gene-environment interaction analyses

    PubMed Central

    Liu, Qianying; Chen, Lin S.; Nicolae, Dan L.; Pierce, Brandon L.

    2015-01-01

    Summary In genome-wide gene-environment interaction (GxE) studies, a common strategy to improve power is to first conduct a filtering test and retain only the SNPs that pass the filtering in the subsequent GxE analyses. Inspired by two-stage tests and gene-based tests in GxE analysis, we consider the general problem of jointly testing a set of parameters when only a few are truly from the alternative hypothesis and when filtering information is available. We propose a unified set-based test that simultaneously considers filtering on individual parameters and testing on the set. We derive the exact distribution and approximate the power function of the proposed unified statistic in simplified settings, and use them to adaptively calculate the optimal filtering threshold for each set. In the context of gene-based GxE analysis, we show that although the empirical power function may be affected by many factors, the optimal filtering threshold corresponding to the peak of the power curve primarily depends on the size of the gene. We further propose a resampling algorithm to calculate p-values for each gene given the estimated optimal filtering threshold. The performance of the method is evaluated in simulation studies and illustrated via a genome-wide gene-gender interaction analysis using pancreatic cancer genome-wide association data. PMID:26496228

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

    PubMed Central

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

    2016-01-01

    A vast amount of literature has confirmed the role of gene-environment (G×E) interaction in the etiology of complex human diseases. Traditional methods are predominantly focused on the analysis of interaction between a single nucleotide polymorphism (SNP) and an environmental variable. Given that genes are the functional units, it is crucial to understand how gene effects (rather than single SNP effects) are influenced by an environmental variable to affect disease risk. Motivated by the increasing awareness of the power of gene-based association analysis over single variant based approach, in this work, we proposed a sparse principle component regression (sPCR) model to understand the gene-based G×E interaction effect on complex disease. We first extracted the sparse principal components for SNPs in a gene, then the effect of each principal component was modeled by a varying-coefficient (VC) model. The model can jointly model variants in a gene in which their effects are nonlinearly influenced by an environmental variable. In addition, the varying-coefficient sPCR (VC-sPCR) model has nice interpretation property since the sparsity on the principal component loadings can tell the relative importance of the corresponding SNPs in each component. We applied our method to a human birth weight dataset in Thai population. We analyzed 12,005 genes across 22 chromosomes and found one significant interaction effect using the Bonferroni correction method and one suggestive interaction. The model performance was further evaluated through simulation studies. Our model provides a system approach to evaluate gene-based G×E interaction. PMID:27271617

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

    PubMed

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

    2016-01-01

    A vast amount of literature has confirmed the role of gene-environment (G×E) interaction in the etiology of complex human diseases. Traditional methods are predominantly focused on the analysis of interaction between a single nucleotide polymorphism (SNP) and an environmental variable. Given that genes are the functional units, it is crucial to understand how gene effects (rather than single SNP effects) are influenced by an environmental variable to affect disease risk. Motivated by the increasing awareness of the power of gene-based association analysis over single variant based approach, in this work, we proposed a sparse principle component regression (sPCR) model to understand the gene-based G×E interaction effect on complex disease. We first extracted the sparse principal components for SNPs in a gene, then the effect of each principal component was modeled by a varying-coefficient (VC) model. The model can jointly model variants in a gene in which their effects are nonlinearly influenced by an environmental variable. In addition, the varying-coefficient sPCR (VC-sPCR) model has nice interpretation property since the sparsity on the principal component loadings can tell the relative importance of the corresponding SNPs in each component. We applied our method to a human birth weight dataset in Thai population. We analyzed 12,005 genes across 22 chromosomes and found one significant interaction effect using the Bonferroni correction method and one suggestive interaction. The model performance was further evaluated through simulation studies. Our model provides a system approach to evaluate gene-based G×E interaction. PMID:27271617

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

    PubMed

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

    2016-06-04

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

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

    PubMed

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

    2016-02-01

    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.

  6. 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

  7. Methods for Investigating Gene-Environment Interactions in Candidate Pathway and Genome-Wide Association Studies

    PubMed Central

    Thomas, Duncan

    2010-01-01

    Despite the considerable enthusiasm about the yield of novel and replicated discoveries of genetic associations from the new generation of genome-wide association studies (GWAS), the proportion of the heritability of most complex diseases that have been studied to date remains small. Some of this “dark matter” could be due to gene-environment (G×E) interactions or more complex pathways involving multiple genes and exposures. We review the basic epidemiologic study design and statistical analysis approaches to studying G×E interactions individually and then consider more comprehensive approaches to studying entire pathways or GWAS data. In addition to the usual issues in genetic association studies, particular care is needed in exposure assessment and very large sample sizes are required. Although hypothesis-driven pathway-based and “agnostic” GWAS approaches are generally viewed as opposite poles, we suggest that the two can be usefully married using hierarchical modeling strategies that exploit external pathway knowledge in mining genome-wide data. PMID:20070199

  8. Powerful Cocktail Methods for Detecting Genome-wide Gene-Environment Interaction

    PubMed Central

    Hsu, Li; Jiao, Shuo; Dai, James Y.; Hutter, Carolyn; Peters, Ulrike; Kooperberg, Charles

    2013-01-01

    Identifying gene and environment interaction (GxE) can provide insights into biological networks of complex diseases, identify novel genes that act synergistically with environmental factors, and inform risk prediction. However, despite the fact that hundreds of novel disease-associated loci have been identified from genome-wide association studies (GWAS), few GxEs have been discovered. One reason is that most studies are underpowered for detecting these interactions. Several new methods have been proposed to improve power for GxE analysis, but performance varies with scenario. In this article we present a module-based approach to integrating various methods that exploits each method’s most appealing aspects. There are three modules in our approach: 1) a screening module for prioritizing SNPs; 2) a multiple comparison module for testing GxE; and 3) a GxE testing module. We combine all three of these modules and develop two novel “cocktail” methods. We demonstrate that the proposed cocktail methods maintain the type I error, and that the power tracks well with the best existing methods, despite that the best methods may be different under various scenarios and interaction models. For GWAS, where the true interaction models are unknown, methods like our “cocktail” methods that are powerful under a wide range of situations are particularly appealing. Broadly speaking, the modular approach is conceptually straightforward and computationally simple. It builds on common test statistics and is easily implemented without additional computational efforts. It also allows for an easy incorporation of new methods as they are developed. Our work provides a comprehensive and powerful tool for devising effective strategies for genome-wide detection of gene-environment interactions. PMID:22714933

  9. Detecting Gene-Environment Interactions for a Quantitative Trait in a Genome-Wide Association Study.

    PubMed

    Zhang, Pingye; Lewinger, Juan Pablo; Conti, David; Morrison, John L; Gauderman, W James

    2016-07-01

    A genome-wide association study (GWAS) typically is focused on detecting marginal genetic effects. However, many complex traits are likely to be the result of the interplay of genes and environmental factors. These SNPs may have a weak marginal effect and thus unlikely to be detected from a scan of marginal effects, but may be detectable in a gene-environment (G × E) interaction analysis. However, a genome-wide interaction scan (GWIS) using a standard test of G × E interaction is known to have low power, particularly when one corrects for testing multiple SNPs. Two 2-step methods for GWIS have been previously proposed, aimed at improving efficiency by prioritizing SNPs most likely to be involved in a G × E interaction using a screening step. For a quantitative trait, these include a method that screens on marginal effects [Kooperberg and Leblanc, 2008] and a method that screens on variance heterogeneity by genotype [Paré et al., 2010] In this paper, we show that the Paré et al. approach has an inflated false-positive rate in the presence of an environmental marginal effect, and we propose an alternative that remains valid. We also propose a novel 2-step approach that combines the two screening approaches, and provide simulations demonstrating that the new method can outperform other GWIS approaches. Application of this method to a G × Hispanic-ethnicity scan for childhood lung function reveals a SNP near the MARCO locus that was not identified by previous marginal-effect scans. PMID:27230133

  10. Gene-Environment Interactions in Stress Response Contribute Additively to a Genotype-Environment Interaction

    PubMed Central

    Matsui, Takeshi; Ehrenreich, Ian M.

    2016-01-01

    How combinations of gene-environment interactions collectively give rise to genotype-environment interactions is not fully understood. To shed light on this problem, we genetically dissected an environment-specific poor growth phenotype in a cross of two budding yeast strains. This phenotype is detectable when certain segregants are grown on ethanol at 37°C (‘E37’), a condition that differs from the standard culturing environment in both its carbon source (ethanol as opposed to glucose) and temperature (37°C as opposed to 30°C). Using recurrent backcrossing with phenotypic selection, we identified 16 contributing loci. To examine how these loci interact with each other and the environment, we focused on a subset of four loci that together can lead to poor growth in E37. We measured the growth of all 16 haploid combinations of alleles at these loci in all four possible combinations of carbon source (ethanol or glucose) and temperature (30 or 37°C) in a nearly isogenic population. This revealed that the four loci act in an almost entirely additive manner in E37. However, we also found that these loci have weaker effects when only carbon source or temperature is altered, suggesting that their effect magnitudes depend on the severity of environmental perturbation. Consistent with such a possibility, cloning of three causal genes identified factors that have unrelated functions in stress response. Thus, our results indicate that polymorphisms in stress response can show effects that are intensified by environmental stress, thereby resulting in major genotype-environment interactions when multiple of these variants co-occur. PMID:27437938

  11. False Appearance of Gene-Environment Interactions in Genetic Association Studies.

    PubMed

    Su, Yi-Shan; Lee, Wen-Chung

    2016-03-01

    Under the assumption of gene-environment independence, unknown/unmeasured environmental factors, irrespective of what they may be, cannot confound the genetic effects. This may lead many people to believe that genetic heterogeneity across different levels of the studied environmental exposure should only mean gene-environment interaction--even though other environmental factors are not adjusted for. However, this is not true if the odds ratio is the effect measure used for quantifying genetic effects. This is because the odds ratio is a "noncollapsible" measure--a marginal odds ratio is not a weighted average of the conditional odds ratios, but instead has a tendency toward the null. In this study, the authors derive formulae for gene-environment interaction bias due to noncollapsibility. They use computer simulation and real data example to show that the bias can be substantial for common diseases. For genetic association study of nonrare diseases, researchers are advised to use collapsible measures, such as risk ratio or peril ratio.

  12. 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.

  13. 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. PMID:24957535

  14. What gene-environment interactions can tell us about social competence in typical and atypical populations.

    PubMed

    Iarocci, Grace; Yager, Jodi; Elfers, Theo

    2007-10-01

    Social competence is a complex human behaviour that is likely to involve a system of genes that interacts with a myriad of environmental risk and protective factors. The search for its genetic and environmental origins and influences is equally complex and will require a multidimensional conceptualization and multiple methods and levels of analysis. Behavioural genetic research can begin to address the fundamental yet complex question of how children develop social competence by uncovering the various influences on social development and disentangling variance due to multiple genes, environments and experiences. In this paper, we review the current status of research on sociability, face recognition, emotion recognition, and theory of mind (TOM)--well defined and measured constructs that are likely to be useful indices for detecting genetic and environmental influences on social competence. We also propose specific milestones as indices of further progress in the field: the development of an operational definition of the construct of social competence, the identification of social endophenotypes-psychological processes that are validly and reliably measured components of social competence, and improving specificity and homogeneity with regard to social endophenotypes within a population of study by employing 'extreme social phenotypes'. These efforts will lead to a better understanding of the specific contributions to the normal variation of social competence in the general population as well as to atypical social development.

  15. 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. PMID:12658122

  16. 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.

  17. 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

  18. 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. PMID:26357960

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

    PubMed

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

    2013-09-01

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

  20. 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

  1. Key Considerations and Methods in the Study of Gene-Environment Interactions.

    PubMed

    Simon, Paul H G; Sylvestre, Marie-Pierre; Tremblay, Johanne; Hamet, Pavel

    2016-08-01

    With increased involvement of genetic data in most epidemiological investigations, gene-environment (G × E) interactions now stand as a topic, which must be meticulously assessed and thoroughly understood. The level, mode, and outcomes of interactions between environmental factors and genetic traits have the capacity to modulate disease risk. These must, therefore, be carefully evaluated as they have the potential to offer novel insights on the "missing heritability problem", reaching beyond our current limitations. First, we review a definition of G × E interactions. We then explore how concepts such as the early manifestation of the genetic components of a disease, the heterogeneity of complex traits, the clear definition of epidemiological strata, and the effect of varying physiological conditions can affect our capacity to detect (or miss) G × E interactions. Lastly, we discuss the shortfalls of regression models to study G × E interactions and how other methods such as the ReliefF algorithm, pattern recognition methods, or the LASSO (Least Absolute Shrinkage and Selection Operator) method can enable us to more adequately model G × E interactions. Overall, we present the elements to consider and a path to follow when studying genetic determinants of disease in order to uncover potential G × E interactions.

  2. The logistic regression model for gene-environment interactions using both case-parent trios and unrelated case-controls.

    PubMed

    Guo, Chao-Yu; Chen, Yu-Jing; Chen, Yi-Hau

    2014-07-01

    One of the greatest challenges in genetic studies is the determination of gene-environment interactions due to underlying complications and inadequate statistical power. With the increased sample size gained by using case-parent trios and unrelated cases and controls, the performance may be much improved. Focusing on a dichotomous trait, a two-stage approach was previously proposed to deal with gene-environment interaction when utilizing mixed study samples. Theoretically, the two-stage association analysis uses likelihood functions such that the computational algorithms may not converge in the maximum likelihood estimation with small study samples. In an effort to avoid such convergence issues, we propose a logistic regression framework model, based on the combined haplotype relative risk (CHRR) method, which intuitively pools the case-parent trios and unrelated subjects in a two by two table. A positive feature of the logistic regression model is the effortless adjustment for either discrete or continuous covariates. According to computer simulations, under the circumstances in which the two-stage test converges in larger sample sizes, we discovered that the performances of the two tests were quite similar; the two-stage test is more powerful under the dominant and additive disease models, but the extended CHRR is more powerful under the recessive disease model. PMID:24766627

  3. Systems-Level Nutrition Approaches to Define Phenotypes Resulting from Complex Gene-Environment Interactions.

    PubMed

    Kaput, Jim

    2016-01-01

    High-throughput metabolomic, proteomic, and genomic technologies have delivered 21st-century data showing that humans cannot be randomized into groups: individuals are genetically and biochemically distinct. Gene-environment interactions caused by unique dietary and lifestyle factors contribute to the heterogeneity in physiologies observed in human studies. The risk factors determined for populations (i.e. the population-attributable risk) cannot be applied to the individual. Developing individual risk/benefit factors in light of the genetic diversity of human populations, the complexity of foods, culture and lifestyle, and the variety in metabolic processes that lead to health or disease are significant challenges for personalizing dietary advice for healthy or diseased individuals. PMID:26764468

  4. Gene-environment interactions and the enteric nervous system: Neural plasticity and Hirschsprung disease prevention.

    PubMed

    Heuckeroth, Robert O; Schäfer, Karl-Herbert

    2016-09-15

    Intestinal function is primarily controlled by an intrinsic nervous system of the bowel called the enteric nervous system (ENS). The cells of the ENS are neural crest derivatives that migrate into and through the bowel during early stages of organogenesis before differentiating into a wide variety of neurons and glia. Although genetic factors critically underlie ENS development, it is now clear that many non-genetic factors may influence the number of enteric neurons, types of enteric neurons, and ratio of neurons to glia. These non-genetic influences include dietary nutrients and medicines that may impact ENS structure and function before or after birth. This review summarizes current data about gene-environment interactions that affect ENS development and suggests that these factors may contribute to human intestinal motility disorders like Hirschsprung disease or irritable bowel syndrome.

  5. 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

  6. Gene-environment interactions in the etiology of obesity: defining the fundamentals.

    PubMed

    Bouchard, Claude

    2008-12-01

    The concept of gene-environment interaction refers to a situation where the response or the adaptation to an environmental factor, a behavior, or a change in behavior is conditional on the genotype of the individual. Of particular interest for our understanding of the etiology of human obesity is the role played by genotype-nutrition and genotype-physical activity interactions. Evidence for the presence of such interaction effects affecting body mass and body composition comes from experimental studies undertaken with pairs of monozygotic twins and with nuclear families. These studies reveal that there are large individual differences in the responsiveness to well-defined energy balance manipulations. Overfeeding as well as negative energy balance protocols indicate that the response to these standardized experimental treatments is strongly influenced by one's genetic background. The genes that are responsible for the individual differences in the sensitivity to alterations in energy balance remain to be fully identified. They are likely to be numerous considering the complexity of the biological systems that are involved in body weight regulation. A number of research designs and technologies are available to identify these genes and to delineate the nature and the extent of the genetic polymorphisms involved. It was the purpose of the workshop to define the conditions under which gene-behavior interaction effects of relevance to human obesity could be reliably identified.

  7. Discovering gene-environment interactions in glioblastoma through a comprehensive data integration bioinformatics method.

    PubMed

    Kunkle, Brian; Yoo, Changwon; Roy, Deodutta

    2013-03-01

    Glioblastoma multiforme (GBM) is the most common and aggressive type of human brain tumor. Although considerable efforts to delineate the underlying pathophysiological pathways have been made during the last decades, only very limited progress on treatment have been achieved because molecular pathways that drive the aggressive nature of GBM are largely unknown. Recent studies have emphasized the importance of environmental factors and the role of gene-environment interactions (GEI) in the development of GBM. Factors such as small sample sizes and study costs have limited the conduct of GEI studies in brain tumors however. Additionally, advances in high-throughput microarrays have produced a wealth of information concerning molecular biology of glioma. In particular, microarrays have been used to obtain genetic and epigenetic changes between normal non-tumor tissue and glioma tissue. Due to the relative rarity of gliomas, microarray data for these tumors is often the product of small studies, and thus pooling this data becomes desirable. To address the challenge of small sample sizes and GEI study difficulties, we introduce a comprehensive bioinformatics method using genetic variations (copy number variations and small-scale variations) and environmental data integration that links with glioblastoma (GEG) to identify: (1) genes that interact with chemicals and have genetic variants linked to the development of GBM, (2) important pathways that may be influenced by environmental exposures (or endogenous chemicals), and (3) genes with variants in GBM that have been understudied in relation to GBM development. The first step in our GEG method identified genes responsive to environmental exposures using the Environmental Genome Project, Comparative Toxicology, and Seattle SNPs databases. These environmentally responsive genes were then compared to a curated list of genes containing copy number variation and/or mutations in GBM. This comparison produced a list of genes

  8. 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…

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

    PubMed

    Mandelli, Laura; Serretti, Alessandro

    2013-12-01

    Increasing evidence supports the involvement of both heritable and environmental risk factors in major depression (MD) and suicidal behavior (SB). Studies investigating gene-environment interaction (G × E) may be useful for elucidating the role of biological mechanisms in the risk for mental disorders. In the present paper, we review the literature regarding the interaction between genes modulating brain functions and stressful life events in the etiology of MD and SB and discuss their potential added benefit compared to genetic studies only. Within the context of G × E investigation, thus far, only a few reliable results have been obtained, although some genes have consistently shown interactive effects with environmental risk in MD and, to a lesser extent, in SB. Further investigation is required to disentangle the direct and mediated effects that are common or specific to MD and SB. Since traditional G × E studies overall suffer from important methodological limitations, further effort is required to develop novel methodological strategies with an interdisciplinary approach. PMID:23886513

  10. CHRM2, parental monitoring, and adolescent externalizing behavior: evidence for gene-environment interaction.

    PubMed

    Dick, Danielle M; Meyers, Jacquelyn L; Latendresse, Shawn J; Creemers, Hanneke E; Lansford, Jennifer E; Pettit, Gregory S; Bates, John E; Dodge, Kenneth A; Budde, John; Goate, Alison; Buitelaar, Jan K; Ormel, Johannes; Verhulst, Frank C; Huizink, Anja C

    2011-04-01

    Psychologists, with their long-standing tradition of studying mechanistic processes, can make important contributions to further characterizing the risk associated with genes identified as influencing risk for psychiatric disorders. We report one such effort with respect to CHRM2, which codes for the cholinergic muscarinic 2 receptor and was of interest originally for its association with alcohol dependence. We tested for association between CHRM2 and prospectively measured externalizing behavior in a longitudinal, community-based sample of adolescents, as well as for moderation of this association by parental monitoring. We found evidence for an interaction in which the association between the genotype and externalizing behavior was stronger in environments with lower parental monitoring. There was also suggestion of a crossover effect, in which the genotype associated with the highest levels of externalizing behavior under low parental monitoring had the lowest levels of externalizing behavior at the extreme high end of parental monitoring. The difficulties involved in distinguishing mechanisms of gene-environment interaction are discussed.

  11. Heavy metals, organic solvents, and multiple sclerosis: An exploratory look at gene-environment interactions.

    PubMed

    Napier, Melanie D; Poole, Charles; Satten, Glen A; Ashley-Koch, Allison; Marrie, Ruth Ann; Williamson, Dhelia M

    2016-01-01

    Exposure to heavy metals and organic solvents are potential etiologic factors for multiple sclerosis (MS), but their interaction with MS-associated genes is under-studied. The authors explored the relationship between environmental exposure to lead, mercury, and solvents and 58 single-nucleotide polymorphisms (SNPs) in MS-associated genes. Data from a population-based case-control study of 217 prevalent MS cases and 496 age-, race-, gender-, and geographically matched controls were used to fit conditional logistic regression models of the association between the chemical, gene, and MS, adjusting for education and ancestry. MS cases were more likely than controls to report lead (odds ratio [OR] = 2.03; 95% confidence interval [CI]: 1.07, 3.86) and mercury exposure (OR = 2.06; 95% CI: 1.08, 3.91). Findings of potential gene-environment interactions between SNPs in TNF-α, TNF-β, TCA-β, VDR, MBP, and APOE, and lead, mercury, or solvents should be considered cautiously due to limited sample size.

  12. 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. PMID:26947980

  13. 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.

  14. Heavy metals, organic solvents and multiple sclerosis: an exploratory look at gene-environment interactions

    PubMed Central

    Napier, Melanie D.; Poole, Charles; Satten, Glen A.; Ashley-Koch, Allison; Marrie, Ruth Ann; Williamson, Dhelia M.

    2015-01-01

    Exposure to heavy metals and organic solvents are potential etiologic factors for multiple sclerosis (MS), but their interaction with MS-associated genes is under-studied. We explored the relationship between environmental exposure to lead, mercury, and solvents and 58 single nucleotide polymorphisms (SNPs) in MS-associated genes. Data from a population-based case-control study of 217 prevalent MS cases and 496 age-, race-, gender-, and geographically-matched controls were used to fit conditional logistic regression models of the association between the chemical, gene, and MS, adjusting for education and ancestry. MS cases were more likely than controls to report lead (odds ratio (OR)=2.03; 95% confidence interval (CI): 1.07, 3.86) and mercury exposure (OR=2.06; 95% CI: 1.08, 3.91). Findings of potential gene-environment interactions between SNPs in TNF-α, TNF-β, TCA-β, VDR, MBP, and APOE, and lead, mercury, or solvents should be considered cautiously due to limited sample size. PMID:25137520

  15. Gene-gene and gene-environment interactions on risk of male infertility: Focus on the metabolites.

    PubMed

    Hu, Weiyue; Chen, Minjian; Wu, Wei; Lu, Jing; Zhao, Dan; Pan, Feng; Lu, Chuncheng; Xia, Yankai; Hu, Lingqing; Chen, Daozhen; Sha, Jiahao; Wang, Xinru

    2016-05-01

    Infertility affects about 17% couples, and males contribute to half of the cases. Compared with independent effects of genetic and environmental factors, interactions between them help in the understanding of the susceptibility to male infertility. Thus, we genotyped 25 polymorphisms, measured 16 urinary chemical concentrations and explored interactions between gene-gene and gene-environment in 1039 Han Chinese using metabolomic analysis. We first observed that GSTT1 might interact with GSTM1 (Pinter=6.33×10(-8)). Furthermore, an interaction between GSTM1 and 4-n-octylphenol (4-n-OP) was identified (Pinter=7.00×10(-3)), as well as a 2-order interaction among GSTT1, GSTM1 and 4-n-OP (Pinter=0.04). Subjects with GSTT1-present and GSTM1-null genotypes were susceptible to male infertility when exposed to 4-n-OP (OR=14.05, 95% CI=4.78-60.20, P=2.34×10(-5)). Most metabolites identified were involved in the tricarboxylic acid cycle. In conclusion, it is a novel study of the interaction on male infertility from the aspect of metabolomics.

  16. Powerful Set-Based Gene-Environment Interaction Testing Framework for Complex Diseases.

    PubMed

    Jiao, Shuo; Peters, Ulrike; Berndt, Sonja; Bézieau, Stéphane; Brenner, Hermann; Campbell, Peter T; Chan, Andrew T; Chang-Claude, Jenny; Lemire, Mathieu; Newcomb, Polly A; Potter, John D; Slattery, Martha L; Woods, Michael O; Hsu, Li

    2015-12-01

    Identification of gene-environment interaction (G × E) is important in understanding the etiology of complex diseases. Based on our previously developed Set Based gene EnviRonment InterAction test (SBERIA), in this paper we propose a powerful framework for enhanced set-based G × E testing (eSBERIA). The major challenge of signal aggregation within a set is how to tell signals from noise. eSBERIA tackles this challenge by adaptively aggregating the interaction signals within a set weighted by the strength of the marginal and correlation screening signals. eSBERIA then combines the screening-informed aggregate test with a variance component test to account for the residual signals. Additionally, we develop a case-only extension for eSBERIA (coSBERIA) and an existing set-based method, which boosts the power not only by exploiting the G-E independence assumption but also by avoiding the need to specify main effects for a large number of variants in the set. Through extensive simulation, we show that coSBERIA and eSBERIA are considerably more powerful than existing methods within the case-only and the case-control method categories across a wide range of scenarios. We conduct a genome-wide G × E search by applying our methods to Illumina HumanExome Beadchip data of 10,446 colorectal cancer cases and 10,191 controls and identify two novel interactions between nonsteroidal anti-inflammatory drugs (NSAIDs) and MINK1 and PTCHD3.

  17. Powerful Set-Based Gene-Environment Interaction Testing Framework for Complex Diseases.

    PubMed

    Jiao, Shuo; Peters, Ulrike; Berndt, Sonja; Bézieau, Stéphane; Brenner, Hermann; Campbell, Peter T; Chan, Andrew T; Chang-Claude, Jenny; Lemire, Mathieu; Newcomb, Polly A; Potter, John D; Slattery, Martha L; Woods, Michael O; Hsu, Li

    2015-12-01

    Identification of gene-environment interaction (G × E) is important in understanding the etiology of complex diseases. Based on our previously developed Set Based gene EnviRonment InterAction test (SBERIA), in this paper we propose a powerful framework for enhanced set-based G × E testing (eSBERIA). The major challenge of signal aggregation within a set is how to tell signals from noise. eSBERIA tackles this challenge by adaptively aggregating the interaction signals within a set weighted by the strength of the marginal and correlation screening signals. eSBERIA then combines the screening-informed aggregate test with a variance component test to account for the residual signals. Additionally, we develop a case-only extension for eSBERIA (coSBERIA) and an existing set-based method, which boosts the power not only by exploiting the G-E independence assumption but also by avoiding the need to specify main effects for a large number of variants in the set. Through extensive simulation, we show that coSBERIA and eSBERIA are considerably more powerful than existing methods within the case-only and the case-control method categories across a wide range of scenarios. We conduct a genome-wide G × E search by applying our methods to Illumina HumanExome Beadchip data of 10,446 colorectal cancer cases and 10,191 controls and identify two novel interactions between nonsteroidal anti-inflammatory drugs (NSAIDs) and MINK1 and PTCHD3. PMID:26095235

  18. Potential role of gene-environment interactions in ion transport mechanisms in the etiology of renal cell cancer

    PubMed Central

    Deckers, Ivette A. G.; van den Brandt, Piet A.; van Engeland, Manon; van Schooten, Frederik J.; Godschalk, Roger W. L.; Keszei, András P.; Hogervorst, Janneke G. F.; Schouten, Leo J.

    2016-01-01

    We investigated the ion transport mechanism (ITM) in renal cell cancer (RCC) etiology using gene-environment interactions between candidate single nucleotide polymorphisms (SNPs) and associated environmental factors, including dietary intakes of sodium, potassium and fluid, hypertension and diuretic medication. A literature-based selection of 13 SNPs in ten ITM genes were successfully genotyped in toenail DNA of 3,048 subcohort members and 419 RCC cases from the Netherlands Cohort Study. Diet and lifestyle were measured with baseline questionnaires. Cox regression analyses were conducted for main effects and gene-environment interactions. ADD1_rs4961 was significantly associated with RCC risk, showing a Hazard Ratio (HR) of 1.24 (95% confidence intervals (CI): 1.01–1.53) for the GT + TT (versus GG) genotype. Four of 65 tested gene-environment interactions were statistically significant. Three of these interactions clustered in SLC9A3_rs4957061, including the ones with fluid and potassium intake, and diuretic medication. For fluid intake, the RCC risk was significantly lower for high versus low intake in participants with the CC genotype (HR(95% CI): 0.47(0.26–0.86)), but not for the CT + TT genotype (P-interaction = 0.002). None of the main genetic effects and gene-environment interactions remained significant after adjustment for multiple testing. Data do not support the general hypothesis that the ITM is a disease mechanism in RCC etiology. PMID:27686058

  19. 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.

  20. 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. PMID:27367897

  1. [Gene-environment-interaction of ODD and Conduct Disorder Versus "Anethic Psychopathy"].

    PubMed

    Schepker, Renate; Schmeck, Klaus; Kölch, Michael; Schepker, Klaus

    2015-01-01

    Gene-environment-interaction of ODD and Conduct Disorder Versus »Anethic Psychopathy«. In 1934, Kramer and von der Leyen demonstrated in a sophisticated longitudinal study with eleven conduct disordered and neglected children labelled as »anethic psychopaths« that »anethic traits« subsided in a favourable educational setting. Sound prognoses, due to the diversity of environmental factors, were found to be impossible. On the contrary they stated that negative labelling led to an affirmation of a negative prognosis. In theory, they supposed a genetic predisposition resulting in a heightened sensitivity to the environment. This early theory of epigenetics radically contradicted the Nazi dogma of hereditability and ostracism and the selection procedures in mainstream psychiatry at that time. The debate ended with von der Leyen's suicide and the prohibition of medical work and publication towards Kramer. Even after the end of the Nazi policy of »eradication of the socially debased«, this early theory was not taken on again, nor dignified.

  2. 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. PMID:24860087

  3. 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

  4. Elucidating risk mechanisms of gene-environment interactions on pediatric anxiety: integrating findings from neuroscience.

    PubMed

    Lau, Jennifer Y F; Pine, Daniel S

    2008-03-01

    Recent findings of gene-environment interaction on child and adolescent anxiety generate interest in mechanisms through which genetic risks are expressed. Current findings from neuroscience suggest avenues for exploring putative mechanisms. Specifically recent documentations of abnormality in brain function among anxious adolescents may reflect the end-result of gene expression. In turn these inherited predispositions may increase the likelihood of psychopathology in the presence of stress. The aim of the current article is to consider putative mechanisms reflecting genetic sensitivity to the environment (G x E). Thus we review data implicating biased processing of threat information and anomalies in brain circuitry in the expression of pediatric anxiety. These data suggest that links across development among genes, brain, psychological processes, and behavior are far from established. Accordingly, the article proposes strategies for examining these links. Exploring these relationships during development is crucial, given that these early life processes may potentially shape longer-term patterns of emotional behavior, and therefore life-long trajectories of anxiety.

  5. 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

  6. Detecting Gene-Environment Interactions in Human Birth Defects: Study Designs and Statistical Methods

    PubMed Central

    Tai, Caroline G.; Graff, Rebecca E.; Liu, Jinghua; Passarelli, Michael N.; Mefford, Joel A.; Shaw, Gary M.; Hoffmann, Thomas J.; Witte, John S.

    2015-01-01

    Background The National Birth Defects Prevention Study (NBDPS) contains a wealth of information on affected and unaffected family triads, and thus provides numerous opportunities to study gene-environment interactions (GxE) in the etiology of birth defect outcomes. Depending on the research objective, several analytic options exist to estimate GxE effects that utilize varying combinations of individuals drawn from available triads. Methods In this paper we discuss several considerations in the collection of genetic data and environmental exposures. We will also present several population- and family-based approaches that can be applied to data from the NBDPS including case-control, case-only, family-based trio, and maternal versus fetal effects. For each, we describe the data requirements, applicable statistical methods, advantages and disadvantages. Discussion A range of approaches can be used to evaluate potentially important GxE effects in the NBDPS. Investigators should be aware of the limitations inherent to each approach when choosing a study design and interpreting results. PMID:26010994

  7. [Gene-environment-interaction of ODD and Conduct Disorder Versus "Anethic Psychopathy"].

    PubMed

    Schepker, Renate; Schmeck, Klaus; Kölch, Michael; Schepker, Klaus

    2015-01-01

    Gene-environment-interaction of ODD and Conduct Disorder Versus »Anethic Psychopathy«. In 1934, Kramer and von der Leyen demonstrated in a sophisticated longitudinal study with eleven conduct disordered and neglected children labelled as »anethic psychopaths« that »anethic traits« subsided in a favourable educational setting. Sound prognoses, due to the diversity of environmental factors, were found to be impossible. On the contrary they stated that negative labelling led to an affirmation of a negative prognosis. In theory, they supposed a genetic predisposition resulting in a heightened sensitivity to the environment. This early theory of epigenetics radically contradicted the Nazi dogma of hereditability and ostracism and the selection procedures in mainstream psychiatry at that time. The debate ended with von der Leyen's suicide and the prohibition of medical work and publication towards Kramer. Even after the end of the Nazi policy of »eradication of the socially debased«, this early theory was not taken on again, nor dignified. PMID:25968413

  8. 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.

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

    PubMed

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

    2016-07-01

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

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

    PubMed

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

    2016-07-01

    Research on gene-environment interaction was facilitated by breakthroughs in molecular biology in the late 20th century, especially in the study of mental health. There is a reliable interaction between candidate genes for depression and childhood adversity in relation to mental health outcomes. The aim of this paper is to explore the role of culture in this process in an urban community in Brazil. The specific cultural factor examined is cultural consonance, or the degree to which individuals are able to successfully incorporate salient cultural models into their own beliefs and behaviors. It was hypothesized that cultural consonance in family life would mediate the interaction of genotype and childhood adversity. In a study of 402 adult Brazilians from diverse socioeconomic backgrounds, conducted from 2011 to 2014, the interaction of reported childhood adversity and a polymorphism in the 2A serotonin receptor was associated with higher depressive symptoms. Further analysis showed that the gene-environment interaction was mediated by cultural consonance in family life, and that these effects were more pronounced in lower social class neighborhoods. The findings reinforce the role of the serotonergic system in the regulation of stress response and learning and memory, and how these processes in turn interact with environmental events and circumstances. Furthermore, these results suggest that gene-environment interaction models should incorporate a wider range of environmental experience and more complex pathways to better understand how genes and the environment combine to influence mental health outcomes. PMID:27270123

  11. 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...

  12. 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…

  13. 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

  14. 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.

  15. 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

  16. 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

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

    PubMed

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

    2012-06-01

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

  18. 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…

  19. 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

  20. 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

  1. Multiple Analytical Approaches Reveal Distinct Gene-Environment Interactions in Smokers and Non Smokers in Lung Cancer

    PubMed Central

    Ihsan, Rakhshan; Chauhan, Pradeep Singh; Mishra, Ashwani Kumar; Yadav, Dhirendra Singh; Kaushal, Mishi; Sharma, Jagannath Dev; Zomawia, Eric; Verma, Yogesh; Kapur, Sujala; Saxena, Sunita

    2011-01-01

    with SULT1A1 Arg213His and EPHX1 Tyr113His in smokers and SULT1A1 Arg213His with GSTP1 Ile105Val and CYP1A1*2C in nonsmokers. These results identified distinct gene-gene and gene environment interactions in smokers and non-smokers, which confirms the importance of multifactorial interaction in risk assessment of lung cancer. PMID:22206016

  2. The heritability of personality is not always 50%: gene-environment interactions and correlations between personality and parenting.

    PubMed

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

    2008-12-01

    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 both to 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.

  3. Effects of the XRCC1 gene-environment interactions on DNA damage in healthy Japanese workers.

    PubMed

    Weng, Zuquan; Lu, Yuquan; Weng, Huachuan; Morimoto, Kanehisa

    2008-12-01

    X-ray repair crosscomplementing group 1 (XRCC1) has a central role in base excision repair (BER) and single-strand break repair (SSBR). XRCC1 gene polymorphisms (codons 194, 280, and 399) have been identified, and in some cases have been reported to contribute to variations in DNA repair capacity and susceptibility to cancer. To further characterize the effects of XRCC1 gene polymorphisms and their possible interactions with environmental factors on individual levels of DNA damage, we investigated the XRCC1 genotypes of 222 healthy Japanese workers and analyzed data with respect to smoking, drinking habits, age, and health practice index (HPI). Our results showed that poor HPI would associate with a higher level of tail moment (TM). Individuals with one or two XRCC1(R280H) variant alleles exhibited significantly higher TM values, and these differences were enhanced by alcohol consumption and aging, whereas smoking and poor HPI may cover up the differences. On the other hand, using a stratified analysis, we found that the XRCC1(R194W) variant was associated with a higher TM value in the 40-50 year-old age group, and the XRCC1(R399Q) variant was associated with a lower TM value in the < or =20 pack-years group or in the 40-50 year-old age group. These data suggest that XRCC1 polymorphisms could influence individual DNA repair capacity by interacting with lifestyle factors, and specifically, the data indicated that the XRCC1(R280H) allele may be more important than codon 194 or 399 alleles.

  4. Gene-environment interactions controlling energy and glucose homeostasis and the developmental origins of obesity.

    PubMed

    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.

  5. 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

  6. 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…

  7. 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...

  8. 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...

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

    ERIC Educational Resources Information Center

    Iarocci, Grace; Yager, Jodi; Elfers, Theo

    2007-01-01

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

  10. GENE-ENVIRONMENT INTERACTION AND THE GNB3 GENE IN THE ATHEROSCLEROSIS RISK IN COMMUNITIES STUDY

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The purpose of this study was to investigate the interaction between the G-protein beta-3 (GNB3) 825C>T polymorphism and physical activity in relation to prevalent obesity and hypertension. The GNB3 825C>T genotype was measured in a sample of 14 716 African Americans (AAs) and whites from the Athero...

  11. 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. PMID:27270564

  12. Gene-Environment Interaction Effects on the Development of Immune Responses in the 1st Year of Life

    PubMed Central

    Hoffjan, Sabine; Nicolae, Dan; Ostrovnaya, Irina; Roberg, Kathy; Evans, Michael; Mirel, Daniel B.; Steiner, Lori; Walker, Karen; Shult, Peter; Gangnon, Ronald E.; Gern, James E.; Martinez, Fernando D.; Lemanske, Robert F.; Ober, Carole

    2005-01-01

    Asthma is a common disease that results from both genetic and environmental risk factors. Children attending day care in the 1st year of life have lower risks for developing asthma, although the mechanism for this “day care” effect is largely unknown. We investigated the interactions between day care exposure in the 1st 6 mo of life and genotypes for 72 polymorphisms at 45 candidate loci and their effects on cytokine response profiles and on the development of atopic phenotypes in the 1st year of life in the Childhood Onset of Asthma (COAST) cohort of children. Six interactions (at four polymorphisms in three loci) with “day care” that had an effect on early-life immune phenotypes were significant at P<.001. The estimated false-discovery rate was 33%, indicating that an estimated four P values correspond to true associations. Moreover, the “day care” effect at some loci was accounted for by the increased number of viral infections among COAST children attending day care, whereas interactions at other loci were independent of the number of viral infections, indicating the presence of additional risk factors associated with day care environment. This study identified significant gene-environment interactions influencing the early patterning of the immune system and the subsequent development of asthma and highlights the importance of considering environmental risk factors in genetic analyses. PMID:15726497

  13. Viewpoint: using gene-environment interactions to dissect the effects of complex mixtures.

    PubMed

    Thomas, Duncan C

    2007-12-01

    Teasing out the health effects of constituents of complex mixtures poses formidable statistical challenges owing to the problem of multicollinearity. While statistical devices such as regression on principal components, model selection, and model averaging offer some approaches to this problem, incorporation of external information is likely to be more helpful. I explore a general hierarchical modeling framework that would allow such information as sources, genetic interactions, and toxicology to be included in the higher levels of the model.

  14. 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

  15. The implications of gene-environment interactions in depression: will cause inform cure?

    PubMed

    Uher, R

    2008-12-01

    In a number of human diseases, including depression, interactions between genetic and environmental factors have been identified in the absence of direct genotype-disorder associations. The lack of genes with major direct pathogenic effect suggests that genotype-specific vulnerabilities are balanced by adaptive advantages and implies aetiological heterogeneity. A model of depression is proposed that incorporates the interacting genetic and environmental factors over the life course and provides an explanatory framework for the heterogeneous aetiology of depression. Early environmental influences act on the genome to shape the adaptability to environmental changes in later life. The possibility is explored that genotype- and epigenotype-related traits can be harnessed to develop personalized therapeutic interventions. As diagnosis of depression alone is a weak predictor of response to specific treatments, aetiological subtypes can be used to inform the choice between treatments. As a specific application of this notion, a hypothesis is proposed regarding relative responsiveness of aetiological subtypes of depression to psychological treatment and antidepressant medication. Other testable predictions are likely to emerge from the general framework of interacting genetic, epigenetic and environmental mechanisms in depression.

  16. Accounting for error due to misclassification of exposures in case-control studies of gene-environment interaction.

    PubMed

    Zhang, Li; Mukherjee, Bhramar; Ghosh, Malay; Gruber, Stephen; Moreno, Victor

    2008-07-10

    We consider analysis of data from an unmatched case-control study design with a binary genetic factor and a binary environmental exposure when both genetic and environmental exposures could be potentially misclassified. We devise an estimation strategy that corrects for misclassification errors and also exploits the gene-environment independence assumption. The proposed corrected point estimates and confidence intervals for misclassified data reduce back to standard analytical forms as the misclassification error rates go to zero. We illustrate the methods by simulating unmatched case-control data sets under varying levels of disease-exposure association and with different degrees of misclassification. A real data set on a case-control study of colorectal cancer where a validation subsample is available for assessing genotyping error is used to illustrate our methods.

  17. 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

  18. 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.

  19. 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

  20. Gene-environment interaction of ApoE genotype and combat exposure on PTSD.

    PubMed

    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

    2013-10-01

    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

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

    PubMed Central

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

    2010-01-01

    Genetic factors dynamically interact with both pre- and postnatal environmental influences to shape development. Considerable attention has been devoted to gene-environment interactions (GxE) on important outcomes (Caspi & Moffitt, 2006). It is also important to consider the possibility that these GxE 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 explore 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 Trails-P task performance on conditions requiring executive control, and 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. PMID:19209988

  2. 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

  3. 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

  4. 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.

  5. Three Approaches to Modeling Gene-Environment Interactions in Longitudinal Family Data: Gene-Smoking Interactions in Blood Pressure.

    PubMed

    Basson, Jacob; Sung, Yun Ju; de Las Fuentes, Lisa; Schwander, Karen L; Vazquez, Ana; Rao, Dabeeru C

    2016-01-01

    Blood pressure (BP) has been shown to be substantially heritable, yet identified genetic variants explain only a small fraction of the heritability. Gene-smoking interactions have detected novel BP loci in cross-sectional family data. Longitudinal family data are available and have additional promise to identify BP loci. However, this type of data presents unique analysis challenges. Although several methods for analyzing longitudinal family data are available, which method is the most appropriate and under what conditions has not been fully studied. Using data from three clinic visits from the Framingham Heart Study, we performed association analysis accounting for gene-smoking interactions in BP at 31,203 markers on chromosome 22. We evaluated three different modeling frameworks: generalized estimating equations (GEE), hierarchical linear modeling, and pedigree-based mixed modeling. The three models performed somewhat comparably, with multiple overlaps in the most strongly associated loci from each model. Loci with the greatest significance were more strongly supported in the longitudinal analyses than in any of the component single-visit analyses. The pedigree-based mixed model was more conservative, with less inflation in the variant main effect and greater deflation in the gene-smoking interactions. The GEE, but not the other two models, resulted in substantial inflation in the tail of the distribution when variants with minor allele frequency <1% were included in the analysis. The choice of analysis method should depend on the model and the structure and complexity of the familial and longitudinal data.

  6. 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

  7. Gene-environment interactions and intermediate phenotypes: early trauma and depression.

    PubMed

    Hornung, Orla P; Heim, Christine M

    2014-01-01

    This review focuses on current research developments in the study of gene by early life stress (ELS) interactions and depression. ELS refers to aversive experiences during childhood and adolescence such as sexual, physical or emotional abuse, emotional or physical neglect as well as parental loss. Previous research has focused on investigating and characterizing the specific role of ELS within the pathogenesis of depression and linking these findings to neurobiological changes of the brain, especially the stress response system. The latest findings highlight the role of genetic factors that increase vulnerability or, likewise, promote resilience to depression after childhood trauma. Considering intermediate phenotypes has further increased our understanding of the complex relationship between early trauma and depression. Recent findings with regard to epigenetic changes resulting from adverse environmental events during childhood promote current endeavors to identify specific target areas for prevention and treatment schemes regarding the long-term impact of ELS. Taken together, the latest research findings have underscored the essential role of genotypes and epigenetic processes within the development of depression after childhood trauma, thereby building the basis for future research and clinical interventions.

  8. Gene-environment interactions and intermediate phenotypes: early trauma and depression.

    PubMed

    Hornung, Orla P; Heim, Christine M

    2014-01-01

    This review focuses on current research developments in the study of gene by early life stress (ELS) interactions and depression. ELS refers to aversive experiences during childhood and adolescence such as sexual, physical or emotional abuse, emotional or physical neglect as well as parental loss. Previous research has focused on investigating and characterizing the specific role of ELS within the pathogenesis of depression and linking these findings to neurobiological changes of the brain, especially the stress response system. The latest findings highlight the role of genetic factors that increase vulnerability or, likewise, promote resilience to depression after childhood trauma. Considering intermediate phenotypes has further increased our understanding of the complex relationship between early trauma and depression. Recent findings with regard to epigenetic changes resulting from adverse environmental events during childhood promote current endeavors to identify specific target areas for prevention and treatment schemes regarding the long-term impact of ELS. Taken together, the latest research findings have underscored the essential role of genotypes and epigenetic processes within the development of depression after childhood trauma, thereby building the basis for future research and clinical interventions. PMID:24596569

  9. 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

  10. Gender-specific gene-environment interaction in alcohol dependence: the impact of daily life events and GABRA2.

    PubMed

    Perry, Brea L; Pescosolido, Bernice A; Bucholz, Kathleen; Edenberg, Howard; Kramer, John; Kuperman, Samuel; Schuckit, Marc Alan; Nurnberger, John I

    2013-09-01

    Gender-moderated gene-environment interactions are rarely explored, raising concerns about inaccurate specification of etiological models and inferential errors. The current study examined the influence of gender, negative and positive daily life events, and GABRA2 genotype (SNP rs279871) on alcohol dependence, testing two- and three-way interactions between these variables using multi-level regression models fit to data from 2,281 White participants in the Collaborative Study on the Genetics of Alcoholism. Significant direct effects of variables of interest were identified, as well as gender-specific moderation of genetic risk on this SNP by social experiences. Higher levels of positive life events were protective for men with the high-risk genotype, but not among men with the low-risk genotype or women, regardless of genotype. Our findings support the disinhibition theory of alcohol dependence, suggesting that gender differences in social norms, constraints and opportunities, and behavioral undercontrol may explain men and women's distinct patterns of association.

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

    PubMed

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

    2015-05-15

    Inflammation plays a significant role in the etiology of type 2 diabetes mellitus (T2DM). The rise in the pro-inflammatory cytokines is the essential step in glucotoxicity and lipotoxicity induced mitochondrial injury, oxidative stress and beta cell apoptosis in T2DM. Among the recognized markers are interleukin (IL)-6, IL-1, IL-10, IL-18, tissue necrosis factor-alpha (TNF-α), C-reactive protein, resistin, adiponectin, tissue plasminogen activator, fibrinogen and heptoglobins. Diabetes mellitus has firm genetic and very strong environmental influence; exhibiting a polygenic mode of inheritance. Many single nucleotide polymorphisms (SNPs) in various genes including those of pro and anti-inflammatory cytokines have been reported as a risk for T2DM. Not all the SNPs have been confirmed by unifying results in different studies and wide variations have been reported in various ethnic groups. The inter-ethnic variations can be explained by the fact that gene expression may be regulated by gene-gene, gene-environment and gene-nutrient interactions. This review highlights the impact of these interactions on determining the role of single nucleotide polymorphism of IL-6, TNF-α, resistin and adiponectin in pathogenesis of T2DM. PMID:25987962

  12. 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.

  13. The clinical application of UGT1A1 pharmacogenetic testing: Gene-environment interactions

    PubMed Central

    2010-01-01

    Over the past decade, the number of pharmacogenetic tests has increased considerably, allowing for the development of our knowledge of their clinical application. The uridine diphosphate glucuronosyltransferase 1A1 gene (UGT1A1) assay is an example of a pharmacogenetic test. Numerous variants have been found in UGT1A1, the main conjugating enzyme of bilirubin and drugs such as the anticancer drug irinotecan. Recently, the US Food and Drug Administration (FDA) recommended testing for the presence of UGT1A1*28, an allele correlated with decreased transcriptional activity, to predict patients at risk of irinotecan toxicity. The administration of other drugs -- such as inhibitors of the UGT1A1 enzyme -- can clinically mimic the *28 phenotype, whereas inducers of UGT1A1 can increase the glucuronidation rate of the enzyme. The *28 polymorphism is not present in all ethnicities at a similar frequency, which suggests that it is important to study different populations to determine the clinical relevance of testing for UGT1A1*28 and to identify other clinically relevant UGT1A1 variants. Environmental factors such as lifestyle can also affect UGT1A1 activity. This review is a critical analysis of studies on drugs that can be affected by the presence of UGT1A1*28, the distribution of this polymorphism around the globe, distinct variants that may be clinically significant in African and Asian populations and how lifestyle can affect treatment outcomes that depend on UGT1A1 activity. PMID:20511137

  14. Molecular pathways: gene-environment interactions regulating dietary fiber induction of proliferation and apoptosis via butyrate for cancer prevention.

    PubMed

    Bultman, Scott J

    2014-02-15

    Gene-environment interactions are so numerous and biologically complicated that it can be challenging to understand their role in cancer. However, dietary fiber and colorectal cancer prevention may represent a tractable model system. Fiber is fermented by colonic bacteria into short-chain fatty acids such as butyrate. One molecular pathway that has emerged involves butyrate having differential effects depending on its concentration and the metabolic state of the cell. Low-moderate concentrations, which are present near the base of colonic crypts, are readily metabolized in the mitochondria to stimulate cell proliferation via energetics. Higher concentrations, which are present near the lumen, exceed the metabolic capacity of the colonocyte. Unmetabolized butyrate enters the nucleus and functions as a histone deacetylase (HDAC) inhibitor that epigenetically regulates gene expression to inhibit cell proliferation and induce apoptosis as the colonocytes exfoliate into the lumen. Butyrate may therefore play a role in normal homeostasis by promoting turnover of the colonic epithelium. Because cancerous colonocytes undergo the Warburg effect, their preferred energy source is glucose instead of butyrate. Consequently, even moderate concentrations of butyrate accumulate in cancerous colonocytes and function as HDAC inhibitors to inhibit cell proliferation and induce apoptosis. These findings implicate a bacterial metabolite with metaboloepigenetic properties in tumor suppression.

  15. Genetic gating of human fear learning and extinction: possible implications for gene-environment interaction in anxiety disorder.

    PubMed

    Lonsdorf, Tina B; Weike, Almut I; Nikamo, Pernilla; Schalling, Martin; Hamm, Alfons O; Ohman, Arne

    2009-02-01

    Pavlovian fear conditioning is a widely used model of the acquisition and extinction of fear. Neural findings suggest that the amygdala is the core structure for fear acquisition, whereas prefrontal cortical areas are given pivotal roles in fear extinction. Forty-eight volunteers participated in a fear-conditioning experiment, which used fear potentiation of the startle reflex as the primary measure to investigate the effect of two genetic polymorphisms (5-HTTLPR and COMTval158met) on conditioning and extinction of fear. The 5-HTTLPR polymorphism, located in the serotonin transporter gene, is associated with amygdala reactivity and neuroticism, whereas the COMTval158met polymorphism, which is located in the gene coding for catechol-O-methyltransferase (COMT), a dopamine-degrading enzyme, affects prefrontal executive functions. Our results show that only carriers of the 5-HTTLPR s allele exhibited conditioned startle potentiation, whereas carriers of the COMT met/met genotype failed to extinguish conditioned fear. These results may have interesting implications for understanding gene-environment interactions in the development and treatment of anxiety disorders.

  16. Enacting the molecular imperative: How gene-environment interaction research links bodies and environments in the post-genomic age.

    PubMed

    Darling, Katherine Weatherford; Ackerman, Sara L; Hiatt, Robert H; Lee, Sandra Soo-Jin; Shim, Janet K

    2016-04-01

    Despite a proclaimed shift from 'nature versus nurture' to 'genes and environment' paradigms within biomedical and genomic science, capturing the environment and identifying gene-environment interactions (GEIs) has remained a challenge. What does 'the environment' mean in the post-genomic age? In this paper, we present qualitative data from a study of 33 principal investigators funded by the U.S. National Institutes of Health to conduct etiological research on three complex diseases (cancer, cardiovascular disease and diabetes). We examine their research practices and perspectives on the environment through the concept of molecularization: the social processes and transformations through which phenomena (diseases, identities, pollution, food, racial/ethnic classifications) are re-defined in terms of their molecular components and described in the language of molecular biology. We show how GEI researchers' expansive conceptualizations of the environment ultimately yield to the imperative to molecularize and personalize the environment. They seek to 'go into the body' and re-work the boundaries between bodies and environments. In the process, they create epistemic hinges to facilitate a turn from efforts to understand social and environmental exposures outside the body, to quantifying their effects inside the body. GEI researchers respond to these emergent imperatives with a mixture of excitement, ambivalence and frustration. We reflect on how GEI researchers struggle to make meaning of molecules in their work, and how they grapple with molecularization as a methodological and rhetorical imperative as well as a process transforming biomedical research practices. PMID:26994357

  17. 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. PMID:26024343

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

    PubMed Central

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

    2016-01-01

    The purpose of this study was to address two methodological issues that have called into question whether previously reported gene-environment interaction (GxE) effects for adolescent alcohol use are “real.” These issues are (1) the potential correlation between the environmental moderator and the outcome across twins and (2) non-linear transformations of the behavioral outcome. Three environments that have been previously reported on (peer deviance, parental knowledge, and potentially stressful life events) were examined here. For each moderator (peer deviance, parental knowledge, and potentially stressful life events), a series of models was fit to both a raw and transformed measure of monthly adolescent alcohol use in a sample that included 825 DZ and 803 MZ twin pairs. The results showed that the moderating effect of peer deviance was robust to transformation, and that although the significance of moderating effects of parental knowledge and potentially stressful life events were dependent on the scale of the adolescent alcohol use outcome, the overall results were consistent across transformation. In addition, the findings did not vary across statistical models. The consistency of the peer deviance results and the shift of the parental knowledge and potentially stressful life events results between trending and significant, shed some light on why previous findings for certain moderators have been inconsistent and emphasize the importance of considering both methodological issues and previous findings when conducting and interpreting GxE analyses. PMID:26290350

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

    PubMed

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

    2015-10-01

    The purpose of this study was to address two methodological issues that have called into question whether previously reported gene-environment interaction (GxE) effects for adolescent alcohol use are 'real'. These issues are (1) the potential correlation between the environmental moderator and the outcome across twins and (2) non-linear transformations of the behavioral outcome. Three environments that have been previously studied (peer deviance, parental knowledge, and potentially stressful life events) were examined here. For each moderator (peer deviance, parental knowledge, and potentially stressful life events), a series of models was fit to both a raw and transformed measure of monthly adolescent alcohol use in a sample that included 825 dizygotic (DZ) and 803 monozygotic (MZ) twin pairs. The results showed that the moderating effect of peer deviance was robust to transformation, and that although the significance of moderating effects of parental knowledge and potentially stressful life events were dependent on the scale of the adolescent alcohol use outcome, the overall results were consistent across transformation. In addition, the findings did not vary across statistical models. The consistency of the peer deviance results and the shift of the parental knowledge and potentially stressful life events results between trending and significant, shed some light on why previous findings for certain moderators have been inconsistent and emphasize the importance of considering both methodological issues and previous findings when conducting and interpreting GxE analyses. PMID:26290350

  20. 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.

  1. Enacting the molecular imperative: How gene-environment interaction research links bodies and environments in the post-genomic age.

    PubMed

    Darling, Katherine Weatherford; Ackerman, Sara L; Hiatt, Robert H; Lee, Sandra Soo-Jin; Shim, Janet K

    2016-04-01

    Despite a proclaimed shift from 'nature versus nurture' to 'genes and environment' paradigms within biomedical and genomic science, capturing the environment and identifying gene-environment interactions (GEIs) has remained a challenge. What does 'the environment' mean in the post-genomic age? In this paper, we present qualitative data from a study of 33 principal investigators funded by the U.S. National Institutes of Health to conduct etiological research on three complex diseases (cancer, cardiovascular disease and diabetes). We examine their research practices and perspectives on the environment through the concept of molecularization: the social processes and transformations through which phenomena (diseases, identities, pollution, food, racial/ethnic classifications) are re-defined in terms of their molecular components and described in the language of molecular biology. We show how GEI researchers' expansive conceptualizations of the environment ultimately yield to the imperative to molecularize and personalize the environment. They seek to 'go into the body' and re-work the boundaries between bodies and environments. In the process, they create epistemic hinges to facilitate a turn from efforts to understand social and environmental exposures outside the body, to quantifying their effects inside the body. GEI researchers respond to these emergent imperatives with a mixture of excitement, ambivalence and frustration. We reflect on how GEI researchers struggle to make meaning of molecules in their work, and how they grapple with molecularization as a methodological and rhetorical imperative as well as a process transforming biomedical research practices.

  2. 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.

  3. 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.

  4. 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…

  5. 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…

  6. 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

  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

    Asor, Eyal; Ben-Shachar, Dorit

    2016-09-22

    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. 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

  9. Gene-environment interaction between dopamine receptor D4 7-repeat polymorphism and early maternal sensitivity predicts inattention trajectories across middle childhood.

    PubMed

    Berry, Daniel; Deater-Deckard, Kirby; McCartney, Kathleen; Wang, Zhe; Petrill, Stephen A

    2013-05-01

    Evidence suggests that the 7-repeat variant of a 48 base pair variable number tandem repeat polymorphism in the dopamine receptor D4 (DRD4) gene may be associated with the development of attention problems. A parallel literature suggests that genes linked to dopaminergic functioning may be associated with differential sensitivity to context, such that the direction of the genetic effect is hypothesized to vary across environmental experience. Guided by these literatures, we used data from the NICHD Study of Early Child Care and Youth Development to consider (a) whether individual differences in children's inattention problems across middle childhood are predicted by gene-environment interactions between the DRD4 gene 7-repeat polymorphism and children's experiences of maternal sensitivity across infancy and early childhood and (b) the degree to which such interactions are consistent with the differential-sensitivity model. Largely consistent with the hypothesized model, gene-environment interactions indicated that, in the context of insensitive early maternal care, the DRD4 7-repeat polymorphism was associated with higher levels of inattention. Although somewhat less consistently, there was also evidence that, in the context of highly sensitive care, the 7-repeat polymorphism was associated with lower levels of inattention. Overall, the magnitude of the absolute genetic effect increased over time, as children's inattention trajectories diverged.

  10. 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.

  11. 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. PMID:24784984

  12. Characterization of gene-environment interactions by behavioral profiling of selectively bred rats: the effect of NMDA receptor inhibition and social isolation.

    PubMed

    Petrovszki, Zita; Adam, Gabor; Tuboly, Gabor; Kekesi, Gabriella; Benedek, Gyorgy; Keri, Szabolcs; Horvath, Gyongyi

    2013-03-01

    Gene-environment interactions have an important role in the development of psychiatric disorders. To generate and validate a new substrain of rats with signs related to schizophrenia, we used selective breeding after postweaning social isolation and chronic ketamine treatment through several generations of animals and compared the subsequent strain to naive rats that were not genetically manipulated. We further investigated whether social isolation and ketamine treatment augmented the appearance of schizophrenic-like signs in these rats. Four experimental groups were studied (n=6-15 rats/group): naive rats without any treatment (NaNo); naive rats with postweaning social isolation and ketamine treatment (NaTr); 15th generation of selectively bred animals without any treatment (SelNo) or selectively bred rats with both isolation and ketamine treatment (SelTr). The startle reaction, tail-flick and novel object recognition tests were used to classify the animals into low- or high-risk for schizophrenia. Reduced pain sensitivity, higher degree of the startle reaction, disturbed prepulse inhibition, altered motor activity and decreased differentiation index in the memory test were observed in the 15th generation of the substrain, along with enhanced grooming behavior. Five functional indices (TF latency, startle reaction, prepulse inhibition, differentiation index, and grooming activity) were rated from 0 to 2, and the analysis of the summarized score revealed that the NaNo group had the lowest overall indication of schizophrenic-like signs, while the SelTr animals scored the highest, suggesting that both heritable and environmental factors were important in the generation of the behavioral alterations. We assume that further breeding after this complex treatment may lead to a valid and reliable animal model of schizophrenia. PMID:23195116

  13. 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

  14. 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...

  15. 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

  16. 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.

  17. Neuregulin 1: a prime candidate for research into gene-environment interactions in schizophrenia? Insights from genetic rodent models.

    PubMed

    Karl, Tim

    2013-01-01

    Schizophrenia is a multi-factorial disease characterized by a high heritability and environmental risk factors. In recent years, an increasing number of researchers worldwide have started investigating the "two-hit hypothesis" of schizophrenia predicting that genetic and environmental risk factors (GxE) interactively cause the development of the disorder. This work is starting to produce valuable new animal models and reveal novel insights into the pathophysiology of schizophrenia. This mini review will focus on recent advancements in the field made by challenging mutant and transgenic rodent models for the schizophrenia candidate gene neuregulin 1 (NRG1) with particular environmental factors. It will outline results obtained from mouse and rat models for various Nrg1 isoforms/isoform types (e.g., transmembrane domain Nrg1, Type II Nrg1), which have been exposed to different forms of stress (acute versus chronic, restraint versus social) and housing conditions (standard laboratory versus minimally enriched housing). These studies suggest Nrg1 as a prime candidate for GxE interactions in schizophrenia rodent models and that the use of rodent models will enable a better understanding of GxE interactions and the underlying mechanisms. PMID:23966917

  18. Gene/environment interactions in the pathogenesis of autoimmunity: new insights on the role of Toll-like receptors.

    PubMed

    Gianchecchi, Elena; Fierabracci, Alessandra

    2015-11-01

    Autoimmune disorders are increasing worldwide. Although their pathogenesis has not been elucidated yet, a complex interaction of genetic and environmental factors is involved in their onset. Toll-like receptors (TLRs) represent a family of pattern recognition receptors involved in the recognition and in the defense of the host from invading microorganisms. They sense a wide range of pathogen associated molecular patterns (PAMPs) deriving from metabolic pathways selective of bacterial, viral, fungal and protozoan microorganisms. TLR activation plays a critical role in the activation of the downstream signaling pathway by interacting and recruiting several adaptor molecules. Although TLRs are involved in the protection of the host, several studies suggest that, in certain conditions, they play a critical role in the pathogenesis of autoimmune diseases. We review the most recent advances showing a correlation between some single nucleotide polymorphisms or copy number variations in TLR genes or in adaptor molecules involved in TLR signaling and the onset of several autoimmune conditions, such as Type I diabetes, autoimmune polyendocrinopathy candidiasis-ectodermal dystrophy, rheumatoid arthritis, systemic lupus erythematosus and systemic sclerosis. In light of the foregoing we finally propose that molecules involved in TLR pathway may represent the targets for novel therapeutic treatments in order to stop autoimmune processes.

  19. Gene/environment interactions in the pathogenesis of autoimmunity: new insights on the role of Toll-like receptors.

    PubMed

    Gianchecchi, Elena; Fierabracci, Alessandra

    2015-11-01

    Autoimmune disorders are increasing worldwide. Although their pathogenesis has not been elucidated yet, a complex interaction of genetic and environmental factors is involved in their onset. Toll-like receptors (TLRs) represent a family of pattern recognition receptors involved in the recognition and in the defense of the host from invading microorganisms. They sense a wide range of pathogen associated molecular patterns (PAMPs) deriving from metabolic pathways selective of bacterial, viral, fungal and protozoan microorganisms. TLR activation plays a critical role in the activation of the downstream signaling pathway by interacting and recruiting several adaptor molecules. Although TLRs are involved in the protection of the host, several studies suggest that, in certain conditions, they play a critical role in the pathogenesis of autoimmune diseases. We review the most recent advances showing a correlation between some single nucleotide polymorphisms or copy number variations in TLR genes or in adaptor molecules involved in TLR signaling and the onset of several autoimmune conditions, such as Type I diabetes, autoimmune polyendocrinopathy candidiasis-ectodermal dystrophy, rheumatoid arthritis, systemic lupus erythematosus and systemic sclerosis. In light of the foregoing we finally propose that molecules involved in TLR pathway may represent the targets for novel therapeutic treatments in order to stop autoimmune processes. PMID:26184547

  20. Gene-environment interactions in human health: case studies and strategies for developing new paradigms and research methodologies.

    PubMed

    Jackson, Fatimah L C

    2014-01-01

    THE SYNERGISTIC EFFECTS OF GENES AND THE ENVIRONMENT ON HEALTH ARE EXPLORED IN THREE CASE STUDIES: adult lactase persistence, autism spectrum disorders, and the metabolic syndrome, providing examples of the interactive complexities underlying these phenotypes. Since the phenotypes are the initial targets of evolutionary processes, understanding the specific environmental contexts of the genetic, epigenetic, and environmental changes associated with these phenotypes is essential in predicting their health implications. Robust databases must be developed on the local scale to deconstruct both the population substructure and the unique components of the environment that stimulate geographically specific changes in gene expression patterns. To produce these databases and make valid predictions, new, locally focused, and information-dense models are needed that incorporate data on evolutionary ecology, environmental complexity, local geographic patterns of gene expression, and population substructure. PMID:25221564

  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. 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. PMID:27039510

  5. 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

  6. 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

  7. Gene-environment interactions in male reproductive health: special reference to the aryl hydrocarbon receptor signaling pathway.

    PubMed

    Brokken, Leon J S; Giwercman, Yvonne Lundberg

    2014-01-01

    Over the last few decades, there have been numerous reports of adverse effects on the reproductive health of wildlife and laboratory animals caused by exposure to endocrine disrupting chemicals (EDCs). The increasing trends in human male reproductive disorders and the mounting evidence for causative environmental factors have therefore sparked growing interest in the health threat posed to humans by EDCs, which are substances in our food, environment and consumer items that interfere with hormone action, biosynthesis or metabolism, resulting in disrupted tissue homeostasis or reproductive function. The mechanisms of EDCs involve a wide array of actions and pathways. Examples include the estrogenic, androgenic, thyroid and retinoid pathways, in which the EDCs may act directly as agonists or antagonists, or indirectly via other nuclear receptors. Dioxins and dioxin-like EDCs exert their biological and toxicological actions through activation of the aryl hydrocarbon-receptor, which besides inducing transcription of detoxifying enzymes also regulates transcriptional activity of other nuclear receptors. There is increasing evidence that genetic predispositions may modify the susceptibility to adverse effects of toxic chemicals. In this review, potential consequences of hereditary predisposition and EDCs are discussed, with a special focus on the currently available publications on interactions between dioxin and androgen signaling.

  8. Gene-environment interactions in male reproductive health: special reference to the aryl hydrocarbon receptor signaling pathway.

    PubMed

    Brokken, Leon J S; Giwercman, Yvonne Lundberg

    2014-01-01

    Over the last few decades, there have been numerous reports of adverse effects on the reproductive health of wildlife and laboratory animals caused by exposure to endocrine disrupting chemicals (EDCs). The increasing trends in human male reproductive disorders and the mounting evidence for causative environmental factors have therefore sparked growing interest in the health threat posed to humans by EDCs, which are substances in our food, environment and consumer items that interfere with hormone action, biosynthesis or metabolism, resulting in disrupted tissue homeostasis or reproductive function. The mechanisms of EDCs involve a wide array of actions and pathways. Examples include the estrogenic, androgenic, thyroid and retinoid pathways, in which the EDCs may act directly as agonists or antagonists, or indirectly via other nuclear receptors. Dioxins and dioxin-like EDCs exert their biological and toxicological actions through activation of the aryl hydrocarbon-receptor, which besides inducing transcription of detoxifying enzymes also regulates transcriptional activity of other nuclear receptors. There is increasing evidence that genetic predispositions may modify the susceptibility to adverse effects of toxic chemicals. In this review, potential consequences of hereditary predisposition and EDCs are discussed, with a special focus on the currently available publications on interactions between dioxin and androgen signaling. PMID:24369137

  9. Arsenic metabolism efficiency has a causal role in arsenic toxicity: Mendelian randomization and gene-environment interaction

    PubMed Central

    Pierce, Brandon L; Tong, Lin; Argos, Maria; Gao, Jianjun; Jasmine, Farzana; Roy, Shantanu; Paul-Brutus, Rachelle; Rahaman, Ronald; Rakibuz-Zaman, Muhammad; Parvez, Faruque; Ahmed, Alauddin; Quasem, Iftekhar; Hore, Samar K; Alam, Shafiul; Islam, Tariqul; Harjes, Judith; Sarwar, Golam; Slavkovich, Vesna; Gamble, Mary V; Chen, Yu; Yunus, Mohammad; Rahman, Mahfuzar; Baron, John A; Graziano, Joseph H; Ahsan, Habibul

    2013-01-01

    Background Arsenic exposure through drinking water is a serious global health issue. Observational studies suggest that individuals who metabolize arsenic efficiently are at lower risk for toxicities such as arsenical skin lesions. Using two single nucleotide polymorphisms (SNPs) in the 10q24.32 region (near AS3MT) that show independent associations with metabolism efficiency, Mendelian randomization can be used to assess whether the association between metabolism efficiency and skin lesions is likely to be causal. Methods Using data on 2060 arsenic-exposed Bangladeshi individuals, we estimated associations for two 10q24.32 SNPs with relative concentrations of three urinary arsenic species (representing metabolism efficiency): inorganic arsenic (iAs), monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA). SNP-based predictions of iAs%, MMA% and DMA% were tested for association with skin lesion status among 2483 cases and 2857 controls. Results Causal odds ratios for skin lesions were 0.90 (95% confidence interval [CI]: 0.87, 0.95), 1.19 (CI: 1.10, 1.28) and 1.23 (CI: 1.12, 1.36) for a one standard deviation increase in DMA%, MMA% and iAs%, respectively. We demonstrated genotype-arsenic interaction, with metabolism-related variants showing stronger associations with skin lesion risk among individuals with high arsenic exposure (synergy index: 1.37; CI: 1.11, 1.62). Conclusions We provide strong evidence for a causal relationship between arsenic metabolism efficiency and skin lesion risk. Mendelian randomization can be used to assess the causal role of arsenic exposure and metabolism in a wide array of health conditions. Developing interventions that increase arsenic metabolism efficiency are likely to reduce the impact of arsenic exposure on health. PMID:24536095

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

    PubMed

    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

    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

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

    PubMed

    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

    2016-05-13

    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).

  12. 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

  13. Assessing causal relationships in genomics: From Bradford-Hill criteria to complex gene-environment interactions and directed acyclic graphs

    PubMed Central

    2011-01-01

    Observational studies of human health and disease (basic, clinical and epidemiological) are vulnerable to methodological problems -such as selection bias and confounding- that make causal inferences problematic. Gene-disease associations are no exception, as they are commonly investigated using observational designs. A rich body of knowledge exists in medicine and epidemiology on the assessment of causal relationships involving personal and environmental causes of disease; it includes seminal causal criteria developed by Austin Bradford Hill and more recently applied directed acyclic graphs (DAGs). However, such knowledge has seldom been applied to assess causal relationships in clinical genetics and genomics, even in studies aimed at making inferences relevant for human health. Conversely, incorporating genetic causal knowledge into clinical and epidemiological causal reasoning is still a largely unexplored area. As the contribution of genetics to the understanding of disease aetiology becomes more important, causal assessment of genetic and genomic evidence becomes fundamental. The method we develop in this paper provides a simple and rigorous first step towards this goal. The present paper is an example of integrative research, i.e., research that integrates knowledge, data, methods, techniques, and reasoning from multiple disciplines, approaches and levels of analysis to generate knowledge that no discipline alone may achieve. PMID:21658235

  14. Gene-environment interaction: Introduction

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The execution and completion of the Human Genome Project was surrounded by great expectations and many overstated promises, and for the first time in history, the information revolution has made of the general public a first row spectator of the scientific advances in real time. Therefore, the publi...

  15. Cross-cultural gene- environment interactions in depression, post-traumatic stress disorder, and the cortisol awakening response: FKBP5 polymorphisms and childhood trauma in South Asia.

    PubMed

    Kohrt, Brandon A; Worthman, Carol M; Ressler, Kerry J; Mercer, Kristina B; Upadhaya, Nawaraj; Koirala, Suraj; Nepal, Mahendra K; Sharma, Vidya Dev; Binder, Elisabeth B

    2015-01-01

    Despite increased attention to global mental health, psychiatric genetic research has been dominated by studies in high-income countries, especially with populations of European descent. The objective of this study was to assess single nucleotide polymorphisms (SNPs) in the FKBP5 gene in a population living in South Asia. Among adults in Nepal, depression was assessed with the Beck Depression Inventory (BDI), post-traumatic stress disorder (PTSD) with the PTSD Checklist-Civilian Version (PCL-C), and childhood maltreatment with the Childhood Trauma Questionnaire (CTQ). FKBP5 SNPs were genotyped for 682 participants. Cortisol awakening response (CAR) was assessed in a subsample of 118 participants over 3 days. The FKBP5 tag-SNP rs9296158 showed a main effect on depressive symptoms (p = 0.03). Interaction of rs9296158 and childhood maltreatment predicted adult depressive symptoms (p = 0.02) but not PTSD. Childhood maltreatment associated with endocrine response in individuals homozygous for the A allele, demonstrated by a negative CAR and overall hypocortisolaemia in the rs9296158 AA genotype and childhood maltreatment group (p < 0.001). This study replicated findings related to FKBP5 and depression but not PTSD. Gene-environment studies should take differences in prevalence and cultural significance of phenotypes and exposures into account when interpreting cross-cultural findings.

  16. 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.

  17. Cross-cultural gene- environment interactions in depression, post-traumatic stress disorder, and the cortisol awakening response: FKBP5 polymorphisms and childhood trauma in South Asia.

    PubMed

    Kohrt, Brandon A; Worthman, Carol M; Ressler, Kerry J; Mercer, Kristina B; Upadhaya, Nawaraj; Koirala, Suraj; Nepal, Mahendra K; Sharma, Vidya Dev; Binder, Elisabeth B

    2015-01-01

    Despite increased attention to global mental health, psychiatric genetic research has been dominated by studies in high-income countries, especially with populations of European descent. The objective of this study was to assess single nucleotide polymorphisms (SNPs) in the FKBP5 gene in a population living in South Asia. Among adults in Nepal, depression was assessed with the Beck Depression Inventory (BDI), post-traumatic stress disorder (PTSD) with the PTSD Checklist-Civilian Version (PCL-C), and childhood maltreatment with the Childhood Trauma Questionnaire (CTQ). FKBP5 SNPs were genotyped for 682 participants. Cortisol awakening response (CAR) was assessed in a subsample of 118 participants over 3 days. The FKBP5 tag-SNP rs9296158 showed a main effect on depressive symptoms (p = 0.03). Interaction of rs9296158 and childhood maltreatment predicted adult depressive symptoms (p = 0.02) but not PTSD. Childhood maltreatment associated with endocrine response in individuals homozygous for the A allele, demonstrated by a negative CAR and overall hypocortisolaemia in the rs9296158 AA genotype and childhood maltreatment group (p < 0.001). This study replicated findings related to FKBP5 and depression but not PTSD. Gene-environment studies should take differences in prevalence and cultural significance of phenotypes and exposures into account when interpreting cross-cultural findings. PMID:26100613

  18. A variable-number-of-tandem-repeats polymorphism in the dopamine D4 receptor gene affects social adaptation of alcohol use: investigation of a gene-environment interaction.

    PubMed

    Larsen, Helle; van der Zwaluw, Carmen S; Overbeek, Geertjan; Granic, Isabela; Franke, Barbara; Engels, Rutger C M E

    2010-08-01

    Research suggests that people adapt their own drinking behavior to that of other people. According to a genetic-differences approach, some individuals may be more inclined than others to adapt their alcohol consumption level to that of other people. Using a 3 (drinking condition) x 2 (genotype) experimental design (N = 113), we tested whether susceptibility to alcohol-related cues (i.e., seeing someone drink) was related to the variable number of tandem repeats in exon 3 of the D4 dopamine receptor gene. A strong gene-environment interaction showed that participants carrying at least one copy of the 7-repeat allele consumed substantially more alcohol in the presence of a heavy-drinking individual than did participants without this allele. This study highlights that individual variability in sensitivity to other people's drinking behavior may be attributable to genetic differences. Carrying the 7-repeat allele may increase the risk for heavy alcohol use or abuse in the company of heavy-drinking peers.

  19. 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. PMID:27145764

  20. 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.

  1. Molecular and genomic approach for understanding the gene-environment interaction between Nrf2 deficiency and carcinogenic nickel-induced DNA damage.

    PubMed

    Kim, Hye Lim; Seo, Young Rok

    2012-12-01

    Nickel (Ⅱ) is a toxic and carcinogenic metal which induces a redox imbalance following oxidative stress. Nuclear factor erythroid-2 related factor 2 (Nrf2) is a redox factor that regulates oxidation/reduction status and consequently mediates cytoprotective responses against exposure to environmental toxicants. In this study, we investigated the protective roles of the Nrf2 gene against oxidative stress and DNA damage induced by nickel at sub-lethal doses. Under nickel exposure conditions, we detected significantly increased intracellular ROS generation, in addition to higher amounts of DNA damage using comet assay and γ-H2AX immunofluorescence staining in Nrf2 lacking cells, as compared to Nrf2 wild-type cells. In addition, we attempted to identify potential nickel and Nrf2-responsive targets and the relevant pathway. The genomic expression data were analyzed using microarray for the selection of synergistic effect-related genes by Nrf2 knockdown under nickel treatment. In particular, altered expressions of 6 upregulated genes (CAV1, FOSL2, MICA, PIM2, RUNX1 and SLC7A6) and 4 downregulated genes (APLP1, CLSPN, PCAF and PRAME) were confirmed by qRT-PCR. Additionally, using bioinformatics tool, we found that these genes functioned principally in a variety of molecular processes, including oxidative stress response, necrosis, DNA repair and cell survival. Thus, we describe the potential biomarkers regarded as molecular candidates for Nrf2-related cellular protection against nickel exposure. In conclusion, these findings indicate that Nrf2 is an important factor with a protective role in the suppression of mutagenicity and carcinogenicity by environmental nickel exposure in terms of gene-environment interaction. PMID:23023193

  2. Analysis of gene-environment interactions in postnatal development of the mammalian intestine.

    PubMed

    Rakoff-Nahoum, Seth; Kong, Yong; Kleinstein, Steven H; Subramanian, Sathish; Ahern, Philip P; Gordon, Jeffrey I; Medzhitov, Ruslan

    2015-02-17

    Unlike mammalian embryogenesis, which takes place in the relatively predictable and stable environment of the uterus, postnatal development can be affected by a multitude of highly variable environmental factors, including diet, exposure to noxious substances, and microorganisms. Microbial colonization of the intestine is thought to play a particularly important role in postnatal development of the gastrointestinal, metabolic, and immune systems. Major changes in environmental exposure occur right after birth, upon weaning, and during pubertal maturation into adulthood. These transitions include dramatic changes in intestinal contents and require appropriate adaptations to meet changes in functional demands. Here, we attempt to both characterize and provide mechanistic insights into postnatal intestinal ontogeny. We investigated changes in global intestinal gene expression through postnatal developmental transitions. We report profound alterations in small and large intestinal transcriptional programs that accompany both weaning and puberty in WT mice. Using myeloid differentiation factor 88 (MyD88)/TIR-domain-containing adapter-inducing interferon-β (TRIF) double knockout littermates, we define the role of toll-like receptors (TLRs) and interleukin (IL)-1 receptor family member signaling in postnatal gene expression programs and select ontogeny-specific phenotypes, such as vascular and smooth muscle development and neonatal epithelial and mast cell homeostasis. Metaanalysis of the effect of the microbiota on intestinal gene expression allowed for mechanistic classification of developmentally regulated genes by TLR/IL-1R (TIR) signaling and/or indigenous microbes. We find that practically every aspect of intestinal physiology is affected by postnatal transitions. Developmental timing, microbial colonization, and TIR signaling seem to play distinct and specific roles in regulation of gene-expression programs throughout postnatal development.

  3. 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.

  4. 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…

  5. Gene-Environment Interplay in Twin Models

    PubMed Central

    Hatemi, Peter K.

    2013-01-01

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

  6. Gene-Environment Interplay in Twin Models.

    PubMed

    Verhulst, Brad; Hatemi, Peter K

    2013-07-01

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

  7. Sensitivity analysis for interactions under unmeasured confounding.

    PubMed

    Vanderweele, Tyler J; Mukherjee, Bhramar; Chen, Jinbo

    2012-09-28

    We develop a sensitivity analysis technique to assess the sensitivity of interaction analyses to unmeasured confounding. We give bias formulas for sensitivity analysis for interaction under unmeasured confounding on both additive and multiplicative scales. We provide simplified formulas in the case in which either one of the two factors does not interact with the unmeasured confounder in its effects on the outcome. An interesting consequence of the results is that if the two exposures of interest are independent (e.g., gene-environment independence), even under unmeasured confounding, if the estimate of the interaction is nonzero, then either there is a true interaction between the two factors or there is an interaction between one of the factors and the unmeasured confounder; an interaction must be present in either scenario. We apply the results to two examples drawn from the literature.

  8. 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.

  9. 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

  10. 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.

  11. Gene-environment and gene-gene interactions of specific MTHFR, MTR and CBS gene variants in relation to homocysteine in black South Africans.

    PubMed

    Nienaber-Rousseau, Cornelie; Ellis, Suria M; Moss, Sarah J; Melse-Boonstra, Alida; Towers, G Wayne

    2013-11-01

    The methylenetetrahydrofolate reductase (MTHFR), cystathione-β-synthase (CBS) and methionine synthase (MTR) genes interact with each other and the environment. These interactions could influence homocysteine (Hcy) and diseases contingent thereon. We determined single nucleotide polymorphisms (SNPs) within these genes, their relationships and interactions with total Hcy concentrations within black South Africans to address the increased prevalence of diseases associated with Hcy. The MTHFR 677 TT and MTR 2756 AA genotypes were associated with higher Hcy concentrations (16.6 and 10.1 μmol/L; p<0.05) compared to subjects harboring the MTHFR 677 CT/CC and the MTR 2756 AG genotypes (10.5, 9.7 and 9.5 μmol/L, respectively). The investigated CBS genotypes did not influence Hcy. We demonstrated interactions between the area of residence and the CBS T833C/844ins68 genotypes (p=0.005) so that when harboring the wildtype allele, rural subjects had significantly higher Hcy than their urban counterparts, but when hosting the variant allele the environment made no difference to Hcy. Between the CBS T833C/844ins68 or G9276A and MTHFR C677T genotypes, there were two-way interactions (p=0.003 and=0.004, respectively), with regard to Hcy. Subjects harboring the MTHFR 677 TT genotype in combination with the CBS 833 TT/homozygous 844 non-insert or the MTHFR 677 TT genotype in combination with the CBS 9276 GA/GG displayed higher Hcy concentrations. Therefore, some of the investigated genotypes affected Hcy; residential area changed the way in which the CBS T833C/844ins68 SNPs influenced Hcy concentrations highlighting the importance of environmental factors; and gene-gene interactions allude to epistatic effects.

  12. Identification of gene-gene and gene-environment interactions within the fibrinogen gene cluster for fibrinogen levels in three ethnically diverse populations.

    PubMed

    Jeff, Janina M; Brown-Gentry, Kristin; Crawford, Dana C

    2015-01-01

    Elevated levels of plasma fibrinogen are associated with clot formation in the absence of inflammation or injury and is a biomarker for arterial clotting, the leading cause of cardiovascular disease. Fibrinogen levels are heritable with >50% attributed to genetic factors, however little is known about possible genetic modifiers that might explain the missing heritability. The fibrinogen gene cluster is comprised of three genes (FGA, FGB, and FGG) that make up the fibrinogen polypeptide essential for fibrinogen production in the blood. Given the known interaction with these genes, we tested 25 variants in the fibrinogen gene cluster for gene x gene and gene x environment interactions in 620 non-Hispanic blacks, 1,385 non-Hispanic whites, and 664 Mexican Americans from a cross-sectional dataset enriched with environmental data, the Third National Health and Nutrition Examination Survey (NHANES III). Using a multiplicative approach, we added cross product terms (gene x gene or gene x environment) to a linear regression model and declared significance at p < 0.05. We identified 19 unique gene x gene and 13 unique gene x environment interactions that impact fibrinogen levels in at least one population at p < 0.05. Over 90% of the gene x gene interactions identified include a variant in the rate-limiting gene, FGB that is essential for the formation of the fibrinogen polypeptide. We also detected gene x environment interactions with fibrinogen variants and sex, smoking, and body mass index. These findings highlight the potential for the discovery of genetic modifiers for complex phenotypes in multiple populations and give a better understanding of the interaction between genes and/or the environment for fibrinogen levels. The need for more powerful and robust methods to identify genetic modifiers is still warranted. PMID:25592583

  13. IDENTIFICATION OF GENE-GENE AND GENE-ENVIRONMENT INTERACTIONS WITHIN THE FIBRINOGEN GENE CLUSTER FOR FIBRINOGEN LEVELS IN THREE ETHNICALLY DIVERSE POPULATIONS

    PubMed Central

    Jeff, Janina M.; Brown-Gentry, Kristin; Crawford, Dana C.

    2014-01-01

    Elevated levels of plasma fibrinogen are associated with clot formation in the absence of inflammation or injury and is a biomarker for arterial clotting, the leading cause of cardiovascular disease. Fibrinogen levels are heritable with >50% attributed to genetic factors, however little is known about possible genetic modifiers that might explain the missing heritability. The fibrinogen gene cluster is comprised of three genes (FGA, FGB, and FGG) that make up the fibrinogen polypeptide essential for fibrinogen production in the blood. Given the known interaction with these genes, we tested 25 variants in the fibrinogen gene cluster for gene × gene and gene × environment interactions in 620 non-Hispanic blacks, 1,385 non-Hispanic whites, and 664 Mexican Americans from a cross-sectional dataset enriched with environmental data, the Third National Health and Nutrition Examination Survey (NHANES III). Using a multiplicative approach, we added cross product terms (gene × gene or gene × environment) to a linear regression model and declared significance at p < 0.05. We identified 19 unique gene × gene and 13 unique gene × environment interactions that impact fibrinogen levels in at least one population at p <0.05. Over 90% of the gene × gene interactions identified include a variant in the rate-limiting gene, FGB that is essential for the formation of the fibrinogen polypeptide. We also detected gene × environment interactions with fibrinogen variants and sex, smoking, and body mass index. These findings highlight the potential for the discovery of genetic modifiers for complex phenotypes in multiple populations and give a better understanding of the interaction between genes and/or the environment for fibrinogen levels. The need for more powerful and robust methods to identify genetic modifiers is still warranted. PMID:25592583

  14. Identification of gene-gene and gene-environment interactions within the fibrinogen gene cluster for fibrinogen levels in three ethnically diverse populations.

    PubMed

    Jeff, Janina M; Brown-Gentry, Kristin; Crawford, Dana C

    2015-01-01

    Elevated levels of plasma fibrinogen are associated with clot formation in the absence of inflammation or injury and is a biomarker for arterial clotting, the leading cause of cardiovascular disease. Fibrinogen levels are heritable with >50% attributed to genetic factors, however little is known about possible genetic modifiers that might explain the missing heritability. The fibrinogen gene cluster is comprised of three genes (FGA, FGB, and FGG) that make up the fibrinogen polypeptide essential for fibrinogen production in the blood. Given the known interaction with these genes, we tested 25 variants in the fibrinogen gene cluster for gene x gene and gene x environment interactions in 620 non-Hispanic blacks, 1,385 non-Hispanic whites, and 664 Mexican Americans from a cross-sectional dataset enriched with environmental data, the Third National Health and Nutrition Examination Survey (NHANES III). Using a multiplicative approach, we added cross product terms (gene x gene or gene x environment) to a linear regression model and declared significance at p < 0.05. We identified 19 unique gene x gene and 13 unique gene x environment interactions that impact fibrinogen levels in at least one population at p < 0.05. Over 90% of the gene x gene interactions identified include a variant in the rate-limiting gene, FGB that is essential for the formation of the fibrinogen polypeptide. We also detected gene x environment interactions with fibrinogen variants and sex, smoking, and body mass index. These findings highlight the potential for the discovery of genetic modifiers for complex phenotypes in multiple populations and give a better understanding of the interaction between genes and/or the environment for fibrinogen levels. The need for more powerful and robust methods to identify genetic modifiers is still warranted.

  15. 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…

  16. HTR1B, ADIPOR1, PPARGC1A, and CYP19A1 and Obesity in a Cohort of Caucasians and African Americans: An Evaluation of Gene-Environment Interactions and Candidate Genes

    PubMed Central

    Edwards, Todd L.; Velez Edwards, Digna R.; Villegas, Raquel; Cohen, Sarah S.; Buchowski, Maciej S.; Fowke, Jay H.; Schlundt, David; Long, Ji Rong; Cai, Qiuyin; Zheng, Wei; Shu, Xiao-Ou; Hargreaves, Margaret K.; Jeffrey, Smith; Williams, Scott M.; Signorello, Lisa B.; Blot, William J.; Matthews, Charles E.

    2012-01-01

    The World Health Organization estimates that the number of obese and overweight adults has increased to 1.6 billion, with concomitant increases in comorbidity. While genetic factors for obesity have been extensively studied in Caucasians, fewer studies have investigated genetic determinants of body mass index (BMI; weight (kg)/height (m)2) in African Americans. A total of 38 genes and 1,086 single nucleotide polymorphisms (SNPs) in African Americans (n = 1,173) and 897 SNPs in Caucasians (n = 1,165) were examined in the Southern Community Cohort Study (2002–2009) for associations with BMI and gene × environment interactions. A statistically significant association with BMI survived correction for multiple testing at rs4140535 (β = −0.04, 95% confidence interval: −0.06, −0.02; P = 5.76 × 10−5) in African Americans but not in Caucasians. Gene-environment interactions were observed with cigarette smoking and a SNP in ADIPOR1 in African Americans, as well as between a different SNP in ADIPOR1 and physical activity in Caucasians. A SNP in PPARGC1A interacted with alcohol consumption in African Americans, and a different SNP in PPARGC1A was nominally associated in Caucasians. A SNP in CYP19A1 interacted with dietary energy intake in African Americans, and another SNP in CYP191A had an independent association with BMI in Caucasians. PMID:22106445

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

    PubMed

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

    2013-09-26

    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.

  18. Chronic exposure of mutant DISC1 mice to lead produces sex-dependent abnormalities consistent with schizophrenia and related mental disorders: a gene-environment interaction study.

    PubMed

    Abazyan, Bagrat; Dziedzic, Jenifer; Hua, Kegang; Abazyan, Sofya; Yang, Chunxia; Mori, Susumu; Pletnikov, Mikhail V; Guilarte, Tomas R

    2014-05-01

    The glutamatergic hypothesis of schizophrenia suggests that hypoactivity of the N-methyl-D-aspartate receptor (NMDAR) is an important factor in the pathophysiology of schizophrenia and related mental disorders. The environmental neurotoxicant, lead (Pb(2+)), is a potent and selective antagonist of the NMDAR. Recent human studies have suggested an association between prenatal Pb(2+) exposure and the increased likelihood of schizophrenia later in life, possibly via interacting with genetic risk factors. In order to test this hypothesis, we examined the neurobehavioral consequences of interaction between Pb(2+) exposure and mutant disrupted in schizophrenia 1 (mDISC1), a risk factor for major psychiatric disorders. Mutant DISC1 and control mice born by the same dams were raised and maintained on a regular diet or a diet containing moderate levels of Pb(2+). Chronic, lifelong exposure of mDISC1 mice to Pb(2+) was not associated with gross developmental abnormalities but produced sex-dependent hyperactivity, exaggerated responses to the NMDAR antagonist, MK-801, mildly impaired prepulse inhibition of the acoustic startle, and enlarged lateral ventricles. Together, these findings support the hypothesis that environmental toxins could contribute to the pathogenesis of mental disease in susceptible individuals.

  19. 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.

  20. 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.

  1. Fetal Alcohol Spectrum Disorders: Gene-Environment Interactions, Predictive Biomarkers, and the Relationship Between Structural Alterations in the Brain and Functional Outcomes

    PubMed Central

    Reynolds, James N.; Weinberg, Joanne; Clarren, Sterling; Beaulieu, Christian; Rasmussen, Carmen; Kobor, Michael; Dube, Marie-Pierre; Goldowitz, Daniel

    2016-01-01

    Prenatal alcohol exposure is a major, preventable cause of behavioral and cognitive deficits in children. Despite extensive research, a unique neurobehavioral profile for children affected by prenatal alcohol exposure remains elusive. A fundamental question that must be addressed is how genetic and environmental factors interact with gestational alcohol exposure to produce neurobehavioral and neurobiological deficits in children. The core objectives of the NeuroDevNet team in fetal alcohol spectrum disorders is to create an integrated research program of basic and clinical investigations that will (1) identify genetic and epigenetic modifications that may be predictive of the neurobehavioral and neurobiological dysfunctions in offspring induced by gestational alcohol exposure and (2) determine the relationship between structural alterations in the brain induced by gestational alcohol exposure and functional outcomes in offspring. The overarching hypothesis to be tested is that neurobehavioral and neurobiological dysfunctions induced by gestational alcohol exposure are correlated with the genetic background of the affected child and/or epigenetic modifications in gene expression. The identification of genetic and/or epigenetic markers that are predictive of the severity of behavioral and cognitive deficits in children affected by gestational alcohol exposure will have a profound impact on our ability to identify children at risk. PMID:21575841

  2. 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 PMID:27077527

  3. 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. PMID:15885086

  4. 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

  5. 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. PMID:25539975

  6. 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

  7. 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.

  8. 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…

  9. 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…

  10. 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…

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

    PubMed

    Horwitz, Briana N; Neiderhiser, Jenae M

    2011-08-01

    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 × environment interaction (G × E). Studies have suggested that rGE is an important pathway through which family relationships are associated with child adjustment. Also important are direct causal influences of family relationships on child adjustment, independent of genetic confounds. Other studies have indicated that genetic and environmental influences on child adjustment are moderated by different levels of family relationships in G × E interactions. Genetically informed studies that have examined family relations have been critical to advancing our understanding of gene - environment interplay.

  12. Gene-environment studies and borderline personality disorder: a review.

    PubMed

    Carpenter, Ryan W; Tomko, Rachel L; Trull, Timothy J; Boomsma, Dorret I

    2013-01-01

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

  13. Parallel Multifactor Dimensionality Reduction: A tool for the large scale analysis of gene-gene interactions

    PubMed Central

    Bush, William S.; Dudek, Scott M.; Ritchie, Marylyn D.

    2016-01-01

    Summary Parallel multifactor dimensionality reduction is a tool for large scale analysis of gene-gene and gene-environment interactions. The MDR algorithm was redesigned to allow an unlimited number of study subjects, total variables, and variable states, and to remove restrictions on the order of interactions being analyzed. In addition, the algorithm is markedly more efficient, with an approximately 150-fold decrease in runtime for equivalent analyses. To facilitate the processing of large datasets, the algorithm was made parallel. PMID:16809395

  14. Gene-environment mismatch in decompression sickness and air embolism.

    PubMed

    Alcock, Joe; Brainard, Andrew H

    2010-08-01

    Decompression sickness causes injury and death in SCUBA divers when air bubbles obstruct the flow of blood. Platelets aggregate in response to gas and promote inflammation. Inflammation in decompression sickness may have its origin in the innate immune system's response to pathogens. Bubbles are often found in tissues during gas-forming infections and in infection-prone states. In these diseases, intravascular gas offers a signal of infection to immune cells. Platelet activation by gas may often accompany a beneficial immune response to pathogens. Pathologic bubble-platelet interaction in decompression illness may be an example of gene-environment mismatch.

  15. Risk, Resilience, and Gene-Environment Interplay in Primates

    PubMed Central

    Suomi, Stephen J.

    2011-01-01

    Objectives: The primary objectives of the body of research reported here was to demonstrate significant interactions between genetic and social environmental factors that clearly influenced both the biological and behavioral responses of rhesus monkeys to social stressors such as separation from familial and/or familiar conspecifics throughout development and to investigate possible mechanisms underlying such interactions. Methods: Prospective longitudinal studies of rhesus monkeys reared in both captive and naturalistic settings have examined individual differences in biological and behavioral responses to stress throughout the lifespan. Results: Approximately 20% of monkeys in both settings consistently display unusually fearful and anxious-like behavioral reactions to novel, mildly stressful social situations and depressive-like symptoms following repeated separations from familial and/or familiar conspecifics during their infant and juvenile years, as well as profound and prolonged activation of the hypothalamic-pituitary-adrenal (HPA) axis in both situations. Both genetic and experiential factors – as well as their interaction -- are implicated in these reactions to social stress. For example, a specific polymorphism in the serotonin transporter gene is associated with deficits in neonatal neurobehavioral functioning and in extreme behavioral and adreno-cortical responses to social separation among infant and juvenile monkeys who experienced insecure early attachments but not in monkeys who developed secure attachment relationships with their mothers during infancy (maternal “buffering”). Similar instances of maternal “buffering” have been demonstrated in significant gene-environment interplay involving several other “candidate” gene polymorphisms. Moreover, because the attachment style of a monkey mother is typically “copied” by her daughters when they become mothers themselves, similar “buffering” is likely to occur for the next

  16. 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…

  17. Joint Testing of Genotypic and Gene-Environment Interaction Identified Novel Association for BMP4 with Non-Syndromic CL/P in an Asian Population Using Data from an International Cleft Consortium

    PubMed Central

    Chen, Qianqian; Wang, Hong; Schwender, Holger; Zhang, Tianxiao; Hetmanski, Jacqueline B.; Chou, Yah-Huei Wu; Ye, Xiaoqian; Yeow, Vincent; Chong, Samuel S.; Zhang, Bo; Jabs, Ethylin Wang; Parker, Margaret M.; Scott, Alan F.; Beaty, Terri H.

    2014-01-01

    Background Non-syndromic cleft lip with or without cleft palate (NSCL/P) is a common disorder with complex etiology. The Bone Morphogenetic Protein 4 gene (BMP4) has been considered a prime candidate gene with evidence accumulated from animal experimental studies, human linkage studies, as well as candidate gene association studies. The aim of the current study is to test for linkage and association between BMP4 and NSCL/P that could be missed in genome-wide association studies (GWAS) when genotypic (G) main effects alone were considered. Methodology/Principal Findings We performed the analysis considering G and interactions with multiple maternal environmental exposures using additive conditional logistic regression models in 895 Asian and 681 European complete NSCL/P trios. Single nucleotide polymorphisms (SNPs) that passed the quality control criteria among 122 genotyped and 25 imputed single nucleotide variants in and around the gene were used in analysis. Selected maternal environmental exposures during 3 months prior to and through the first trimester of pregnancy included any personal tobacco smoking, any environmental tobacco smoke in home, work place or any nearby places, any alcohol consumption and any use of multivitamin supplements. A novel significant association held for rs7156227 among Asian NSCL/P and non-syndromic cleft lip and palate (NSCLP) trios after Bonferroni correction which was not seen when G main effects alone were considered in either allelic or genotypic transmission disequilibrium tests. Odds ratios for carrying one copy of the minor allele without maternal exposure to any of the four environmental exposures were 0.58 (95%CI = 0.44, 0.75) and 0.54 (95%CI = 0.40, 0.73) for Asian NSCL/P and NSCLP trios, respectively. The Bonferroni P values corrected for the total number of 117 tested SNPs were 0.0051 (asymptotic P = 4.39*10−5) and 0.0065 (asymptotic P = 5.54*10−5), accordingly. In European trios, no significant

  18. 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…

  19. 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

  20. Identification of FAM13A gene associated with the ratio of FEV1 to FVC in Korean population by genome-wide association studies including gene-environment interactions.

    PubMed

    Kim, Soriul; Kim, Hyun; Cho, Namhan; Lee, Seung Ku; Han, Bok-Ghee; Sull, Jae Woong; Jee, Sun Ha; Shin, Chol

    2015-03-01

    Chronic obstructive pulmonary disease (COPD) is a complex, multifactorial disease. Although smoking is a main risk factor for obstructive impairment, not all smokers develop this critical disease. We conducted a genome-wide association study to identify the association between genetic variants and pulmonary function and also examined how these variants relate to lung impairment in accordance with smoking behaviors. Using two community-based cohorts, the Ansan cohort (n=4319) and the Ansung cohort (n=3674), in the Korean Genome Epidemiology Study, we analyzed the association between genetic variants (single-nucleotide polymorphisms and haplotypes) and the ratio of FEV1 to FVC (FEV1/FVC) using multivariate linear regression models. Similar analyses were conducted after stratification by smoking status. Four genome-wide significant signals in the FAM13A gene (the strongest signal at rs2609264, P=1.76 × 10(-7) in a combined set) were associated with FEV1/FVC. For the association with ratio, the effect size in the CTGA haplotype (risk haplotype) was -0.57% (s.e., 0.11; P=2.10 × 10(-7)) as compared with the TCAG haplotype (reference haplotype) in a combined set. There was also a significant interaction of FAM13A haplotypes with heavy smoking on FEV1/FVC (P for interaction=0.028). We confirmed the previously reported association of FAM13A in 4q22.1 with pulmonary function. The FAM13A haplotypes also interacted with heavy smoking to affect the risk of reduced pulmonary function.

  1. 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

  2. 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…

  3. 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…

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

    PubMed

    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

  5. 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.

  6. Gene-environment interactions of selected pharmacogenes in arterial hypertension.

    PubMed

    Bochud, Murielle; Guessous, Idris

    2012-11-01

    Hypertension affects approximately 1 billion people worldwide. Owing to population aging, hypertension-related cardiovascular burden is expected to rise in the near future. In addition to genetic variants influencing the blood pressure response to antihypertensive drugs, several genes encoding for drug-metabolizing or -transporting enzymes have been associated with blood pressure and/or hypertension in humans (e.g., ACE, CYP1A2, CYP3A5, ABCB1 and MTHFR) regardless of drug treatment. These genes are also involved in the metabolism and transport of endogenous substances and their effects may be modified by selected environmental factors, such as diet or lifestyle. However, little is currently known on the complex interplay between environmental factors, endogenous factors, genetic variants and drugs on blood pressure control. This review will discuss the respective role of population-based primary prevention and personalized medicine for arterial hypertension, taking a pharmacogenomics' perspective focusing on selected pharmacogenes. PMID:23234325

  7. 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...

  8. 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.

  9. 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…

  10. 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…

  11. 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

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

    PubMed

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

    2015-07-01

    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, because 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.

  13. 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.

  14. 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.

  15. A partially linear tree-based regression model for assessing complex joint gene-gene and gene-environment effects.

    PubMed

    Chen, Jinbo; Yu, Kai; Hsing, Ann; Therneau, Terry M

    2007-04-01

    The success of genetic dissection of complex diseases may greatly benefit from judicious exploration of joint gene effects, which, in turn, critically depends on the power of statistical tools. Standard regression models are convenient for assessing main effects and low-order gene-gene interactions but not for exploring complex higher-order interactions. Tree-based methodology is an attractive alternative for disentangling possible interactions, but it has difficulty in modeling additive main effects. This work proposes a new class of semiparametric regression models, termed partially linear tree-based regression (PLTR) models, which exhibit the advantages of both generalized linear regression and tree models. A PLTR model quantifies joint effects of genes and other risk factors by a combination of linear main effects and a non-parametric tree -structure. We propose an iterative algorithm to fit the PLTR model, and a unified resampling approach for identifying and testing the significance of the optimal "pruned" tree nested within the tree resultant from the fitting algorithm. Simulation studies showed that the resampling procedure maintained the correct type I error rate. We applied the PLTR model to assess the association between biliary stone risk and 53 single nucleotide polymorphisms (SNPs) in the inflammation pathway in a population-based case-control study. The analysis yielded an interesting parsimonious summary of the joint effect of all SNPs. The proposed model is also useful for exploring gene-environment interactions and has broad implications for applying the tree methodology to genetic epidemiology research.

  16. Gene-environment and protein-degradation signatures characterize genomic and phenotypic diversity in wild Caenorhabditis elegans populations

    PubMed Central

    2013-01-01

    Background Analyzing and understanding the relationship between genotypes and phenotypes is at the heart of genetics. Research on the nematode Caenorhabditis elegans has been instrumental for unraveling genotype-phenotype relations, and has important implications for understanding the biology of mammals, but almost all studies, including forward and reverse genetic screens, are limited by investigations in only one canonical genotype. This hampers the detection and functional analysis of allelic variants, which play a key role in controlling many complex traits. It is therefore essential to explore the full potential of the natural genetic variation and evolutionary context of the genotype-phenotype map in wild C. elegans populations. Results We used multiple wild C. elegans populations freshly isolated from local sites to investigate gene sequence polymorphisms and a multitude of phenotypes including the transcriptome, fitness, and behavioral traits. The genotype, transcriptome, and a number of fitness traits showed a direct link with the original site of the strains. The separation between the isolation sites was prevalent on all chromosomes, but chromosome V was the largest contributor to this variation. These results were supported by a differential food preference of the wild isolates for naturally co-existing bacterial species. Comparing polymorphic genes between the populations with a set of genes extracted from 19 different studies on gene expression in C. elegans exposed to biotic and abiotic factors, such as bacteria, osmotic pressure, and temperature, revealed a significant enrichment for genes involved in gene-environment interactions and protein degradation. Conclusions We found that wild C. elegans populations are characterized by gene-environment signatures, and we have unlocked a wealth of genotype-phenotype relations for the first time. Studying natural isolates provides a treasure trove of evidence compared with that unearthed by the current

  17. 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…

  18. Interactive teaching: a concept analysis.

    PubMed

    Ridley, Renee T

    2007-05-01

    Interactive teaching is conceptually analyzed using the strategies of Walker and Avant to promote a common understanding of interactive teaching and to clearly explicate interactive teaching characteristics that will foster the construct validity of using interactive teaching in pedagogical research. In doing so, nurse researchers will be able to better understand and integrate interactive teaching into their research protocols, ultimately providing evidence for educators to use in determining the most effective teaching methods to incorporate into curricula. Interactive teaching is defined and examined using relevant sources; related concepts are analyzed and compared with these definitions. Antecedents, critical attributes, and consequences of interactive teaching are identified and applied in model, borderline, and contrary cases. Concluding remarks and suggestions are presented. PMID:17547343

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

    PubMed

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

    2012-11-01

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

  20. CABIN: Collective Analysis of Biological Interaction Networks

    SciTech Connect

    Singhal, Mudita; Domico, Kelly O.

    2007-06-01

    The importance of understanding biological interaction networks has fueled the development of numerous interaction data generation techniques, databases and prediction tools. However not all prediction tools and databases predict interactions with one hundred percent accuracy. Generation of high confidence interaction networks formulates the first step towards deciphering unknown protein functions, determining protein complexes and inventing drugs. The CABIN: Collective Analysis of Biological Interaction Networks software is an exploratory data analysis tool that enables analysis and integration of interactions evidence obtained from multiple sources, thereby increasing the confidence of computational predictions as well as validating experimental observations. CABIN has been written in JavaTM and is available as a plugin for Cytoscape – an open source network visualization tool.

  1. 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. PMID:26372295

  2. 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. PMID:25396097

  3. Automated Instruction of Flanders Interaction Analysis.

    ERIC Educational Resources Information Center

    Swigger, Kathleen M.

    A series of computer-assisted instruction (CAI) lessons were written for use by students enrolled in a methods course in social studies education at the University of Iowa. Lessons provide instruction in the Flanders Interaction Analysis method which makes classroom verbal communication more effective. An interaction module was designed to help…

  4. PERMANENT ROCKBOLT AND TEMPORARY CHANNEL INTERACTION ANALYSIS

    SciTech Connect

    J. Keifer; M. Taylor

    1995-03-14

    The purpose of this analysis is to evaluate the interaction of a quality assurance (QA) classified item (QA-1 and QA-5) with an item of temporary function (QA: NONE), in accordance with Requirement 8 of the Determination of Importance Evaluation (DIE) (Reference Section 5.1). This interaction analysis will be done by determining the forces on ''Williams'' rockbolts transferred from temporary function channels under maximum capacity loads, and ensuring that these loads do not compromise the critical characteristics of these rockbolts.

  5. 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…

  6. 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.

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

    PubMed

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

    2013-11-01

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

  8. 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.

  9. Expert system interaction with existing analysis codes

    SciTech Connect

    Ransom, V.H.; Fink, R.K.; Bertch, W.J.; Callow, R.A.

    1986-01-01

    Coupling expert systems with existing engineering analysis codes is a promising area in the field of artificial intelligence. The added intelligence can provide for easier and less costly use of the code and also reduce the potential for code misuse. This paper will discuss the methods available to allow interaction between an expert system and a large analysis code running on a mainframe. Concluding remarks will identify potential areas of expert system application with specific areas that are being considered in a current research program. The difficulty of interaction between an analysis code and an expert system is due to the incompatibility between the FORTRAN environment used for the analysis code and the AI environment used for the expert system. Three methods, excluding file transfer techniques, are discussed to help overcome this incompatibility. The first method is linking the FORTRAN routines to the LISP environment on the same computer. Various LISP dialects available on mainframes and their interlanguage communication capabilities are discussed. The second method involves network interaction between a LISP machine and a mainframe computer. Comparisons between the linking method and networking are noted. The third method involves the use of an expert system tool that is campatible with a FORTRAN environment. Several available tools are discussed. With the interaction methods identified, several potential application areas are considered. Selection of the specific areas that will be developed for the pilot project and applied to a thermal-hydraulic energy analysis code are noted.

  10. 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.

  11. 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.

  12. Interaction Analysis: Theory, Research and Application.

    ERIC Educational Resources Information Center

    Amidon, Edmund J., Ed.; Hough, John J., Ed.

    This volume of selected readings developed for students and practitioners at various levels of sophistication is intended to be representative of work done to date on interaction analysis. The contents include journal articles, papers read at professional meetings, abstracts of doctoral dissertations, and selections from larger monographs, plus 12…

  13. 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…

  14. Multiple Regression Analysis and Automatic Interaction Detection.

    ERIC Educational Resources Information Center

    Koplyay, Janos B.

    The Automatic Interaction Detector (AID) is discussed as to its usefulness in multiple regression analysis. The algorithm of AID-4 is a reversal of the model building process; it starts with the ultimate restricted model, namely, the whole group as a unit. By a unique splitting process maximizing the between sum of squares for the categories of…

  15. Interactive Test Analysis: Development, Implementation, and Evaluation.

    ERIC Educational Resources Information Center

    Lipe, Gary

    An interactive test analysis system was developed which interfaces a 3M DATRONICS system with a XEROX Sigma 9 computer. The computer programs were written in A Programming Language (APL). The current implementation of the program is characterized by its capability to: read responses from a DATRONIC answer sheet; allow the faculty member the option…

  16. Genes, Environments, Personality, and Successful Aging: Toward a Comprehensive Developmental Model in Later Life

    PubMed Central

    Krueger, Robert F.; South, Susan C.; Gruenewald, Tara L.; Seeman, Teresa E.; Roberts, Brent W.

    2012-01-01

    Background. Outcomes in aging and health research, such as longevity, can be conceptualized as reflecting both genetic and environmental (nongenetic) effects. Parsing genetic and environmental influences can be challenging, particularly when taking a life span perspective, but an understanding of how genetic variants and environments relate to successful aging is critical to public health and intervention efforts. Methods. We review the literature, and survey promising methods, to understand this interplay. We also propose the investigation of personality as a nexus connecting genetics, environments, and health outcomes. Results. Personality traits may reflect psychological mechanisms by which underlying etiologic (genetic and environmental) effects predispose individuals to broad propensities to engage in (un)healthy patterns of behavior across the life span. In terms of methodology, traditional behavior genetic approaches have been used profitably to understand how genetic factors and environments relate to health and personality in somewhat separate literatures; we discuss how other behavior genetic approaches can help connect these literatures and provide new insights. Conclusions. Co-twin control designs can be employed to help determine causality via a closer approximation of the idealized counterfactual design. Gene-by-environment interaction (G × E) designs can be employed to understand how individual difference characteristics, such as personality, might moderate genetic and environmental influences on successful aging outcomes. Application of such methods can clarify the interplay of genes, environments, personality, and successful aging. PMID:22454369

  17. Genes, environment, and individual differences in responding to treatment for depression.

    PubMed

    Uher, Rudolf

    2011-01-01

    A principal weakness of evidence-based psychiatry is that it does not account for the individual variability in therapeutic response among individuals with the same diagnosis. The aim of personalized psychiatry is to remediate this shortcoming and to use predictors to select treatment that is most likely to be beneficial for an individual. This article reviews the evidence that genetic variation, environmental exposures, and gene-environment interactions shape mental illness and influence treatment outcomes, with a primary focus on depression. Several genetic polymorphisms have been identified that influence the outcome of specific treatments, but the strength and generalizability of such influences are not sufficient to justify personalized prescribing. Environmental exposures in early life, such as childhood maltreatment, exert long-lasting influences that are moderated by inherited genetic variation and mediated through stable epigenetic mechanisms such as tissue- and gene-specific DNA methylation. Pharmacological and psychological treatments act on and against the background of genetic disposition, with epigenetic annotation resulting from previous experiences. Research in animal models suggests the possibility that epigenetic interventions may modify the impact of environmental stressors on mental health. Gaps in evidence are identified that need to be bridged before knowledge about cause can inform cure in personalized psychiatry.

  18. 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

  19. 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

  20. Interaction analysis and psychology: a dialogical perspective.

    PubMed

    Grossen, Michèle

    2010-03-01

    Interaction analysis is not a prerogative of any discipline in social sciences. It has its own history within each disciplinary field and is related to specific research objects. From the standpoint of psychology, this article first draws upon a distinction between factorial and dialogical conceptions of interaction. It then briefly presents the basis of a dialogical approach in psychology and focuses upon four basic assumptions. Each of them is examined on a theoretical and on a methodological level with a leading question: to what extent is it possible to develop analytical tools that are fully coherent with dialogical assumptions? The conclusion stresses the difficulty of developing methodological tools that are fully consistent with dialogical assumptions and argues that there is an unavoidable tension between accounting for the complexity of an interaction and using methodological tools which necessarily "monologise" this complexity.

  1. Interaction analysis and psychology: a dialogical perspective.

    PubMed

    Grossen, Michèle

    2010-03-01

    Interaction analysis is not a prerogative of any discipline in social sciences. It has its own history within each disciplinary field and is related to specific research objects. From the standpoint of psychology, this article first draws upon a distinction between factorial and dialogical conceptions of interaction. It then briefly presents the basis of a dialogical approach in psychology and focuses upon four basic assumptions. Each of them is examined on a theoretical and on a methodological level with a leading question: to what extent is it possible to develop analytical tools that are fully coherent with dialogical assumptions? The conclusion stresses the difficulty of developing methodological tools that are fully consistent with dialogical assumptions and argues that there is an unavoidable tension between accounting for the complexity of an interaction and using methodological tools which necessarily "monologise" this complexity. PMID:19866243

  2. An interactive meteorological display and analysis system

    NASA Technical Reports Server (NTRS)

    Desjardins, M. L.; Petersen, R. A.

    1983-01-01

    The GEMPAK system, a general meteorological software package being developed at NASA/Goddard Space Flight Center to support mesoscale meteorological research programs, is described. The primary purpose of the system is to provide analysis support and data integration techniques for conventional and satellite derived data sets. Current capabilities of the system range from data listing and editing to interactive objective analysis procedures and coordinate transformations. Output graphics use a graphics subroutine package designed to support meteorological plotting functions. A flexible diagnostics package is currently under development.

  3. Proteomic analysis of SETD6 interacting proteins

    PubMed Central

    Cohn, Ofir; Chen, Ayelet; Feldman, Michal; Levy, Dan

    2016-01-01

    SETD6 (SET-domain-containing protein 6) is a mono-methyltransferase that has been shown to methylate RelA and H2AZ. Using a proteomic approach we recently identified several new SETD6 substrates. To identify novel SETD6 interacting proteins, SETD6 was immunoprecipitated (IP) from Human erythromyeloblastoid leukemia K562 cells. SETD6 binding proteins were subjected to mass-spectrometry analysis resulting in 115 new SETD6 binding candidates. STRING database was used to map the SETD6 interactome network. Network enrichment analysis of biological processes with Gene Ontology (GO) database, identified three major groups; metabolic processes, muscle contraction and protein folding. PMID:26937450

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Multiplicative interaction in network meta-analysis.

    PubMed

    Piepho, Hans-Peter; Madden, Laurence V; Williams, Emlyn R

    2015-02-20

    Meta-analysis of a set of clinical trials is usually conducted using a linear predictor with additive effects representing treatments and trials. Additivity is a strong assumption. In this paper, we consider models for two or more treatments that involve multiplicative terms for interaction between treatment and trial. Multiplicative models provide information on the sensitivity of each treatment effect relative to the trial effect. In developing these models, we make use of a two-way analysis-of-variance approach to meta-analysis and consider fixed or random trial effects. It is shown using two examples that models with multiplicative terms may fit better than purely additive models and provide insight into the nature of the trial effect. We also show how to model inconsistency using multiplicative terms.

  9. ALS: A bucket of genes, environment, metabolism and unknown ingredients.

    PubMed

    Zufiría, Mónica; Gil-Bea, Francisco Javier; Fernández-Torrón, Roberto; Poza, Juan José; Muñoz-Blanco, Jose Luis; Rojas-García, Ricard; Riancho, Javier; de Munain, Adolfo López

    2016-07-01

    The scientific scenario of amyotrophic lateral sclerosis (ALS) has dramatically changed since TDP-43 aggregates were discovered in 2006 as the main component of the neuronal inclusions seen in the disease, and more recently, when the implication of C9ORF72 expansion in familial and sporadic cases of ALS and frontotemporal dementia was confirmed. These discoveries have enlarged an extense list of genes implicated in different cellular processes such as RNA processing or autophagia among others and have broaden the putative molecular targets of the disease. Some of ALS-related genes such as TARDBP or SOD1 among others have important roles in the regulation of glucose and fatty acids metabolism, so that an impairment of fatty acids (FA) consumption and ketogenic deficits during exercise in ALS patients would connect the physiopathology with some of the more intriguing epidemiological traits of the disease. The current understanding of ALS as part of a continuum with other neurodegenerative diseases and a crossroads between genetic, neurometabolic and environmental factors represent a fascinating model of interaction that could be translated to other neurodegenerative diseases. In this review we summarize the most relevant data obtained in the ten last years and the key lines for future research in ALS.

  10. ALS: A bucket of genes, environment, metabolism and unknown ingredients.

    PubMed

    Zufiría, Mónica; Gil-Bea, Francisco Javier; Fernández-Torrón, Roberto; Poza, Juan José; Muñoz-Blanco, Jose Luis; Rojas-García, Ricard; Riancho, Javier; de Munain, Adolfo López

    2016-07-01

    The scientific scenario of amyotrophic lateral sclerosis (ALS) has dramatically changed since TDP-43 aggregates were discovered in 2006 as the main component of the neuronal inclusions seen in the disease, and more recently, when the implication of C9ORF72 expansion in familial and sporadic cases of ALS and frontotemporal dementia was confirmed. These discoveries have enlarged an extense list of genes implicated in different cellular processes such as RNA processing or autophagia among others and have broaden the putative molecular targets of the disease. Some of ALS-related genes such as TARDBP or SOD1 among others have important roles in the regulation of glucose and fatty acids metabolism, so that an impairment of fatty acids (FA) consumption and ketogenic deficits during exercise in ALS patients would connect the physiopathology with some of the more intriguing epidemiological traits of the disease. The current understanding of ALS as part of a continuum with other neurodegenerative diseases and a crossroads between genetic, neurometabolic and environmental factors represent a fascinating model of interaction that could be translated to other neurodegenerative diseases. In this review we summarize the most relevant data obtained in the ten last years and the key lines for future research in ALS. PMID:27236050

  11. The shaping of personality: genes, environments, and chance encounters.

    PubMed

    Zuckerman, Marvin

    2004-02-01

    I started my career as a clinical psychologist with an interest in personality assessment. But a loss of faith in psychoanalytic theory, projective tests, and clinical case studies in general led to a shift in my interests to personality research. Subsequent jobs at research institutes and universities allowed me to indulge in science. I developed the trait-state concept and its application in tests for affect measurement. For 10 years I did experimental research in the field of sensory deprivation. The sensation seeking idea and tests evolved from this work but soon expanded to many other areas. Research in the biological basis of sensation seeking started with genetic and psychophysiological research, but research conducted in other laboratories also pointed to a psychopharmacological basis for the trait. Over the last several decades, I have formulated a psychobiological model for personality. I have used factor analysis and the biosocial model to develop an "alternative-five" factorial trait structure for personality.

  12. 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.

  13. 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.

  14. Interactive Fringe processing algorithm for interferogram analysis

    NASA Astrophysics Data System (ADS)

    Parthiban, V.; Sirohi, Rajpal S.

    A highly flexible algorithm for interferogram processing which enables the operator to interact with the computer at every stage, is presented. This algorithm developed on a PDP 11/23 microcomputer, uses Fortran callable subroutines based on Intellect 100 image processing hardware and a CUB R-G-B monitor. It also uses a single frame buffer of 512 x 512 x 8 pixels. This software employs a pseudo-colour mapping technique which helps the operator to select the optimum threshold values. Manual editing of the processed fringe pattern is also possible to enable removal of unwanted kinks and to connect any discontinuities. A fringe scanning subroutine is used to number the fringes and to store the peak coordinates in a data file for fringe analysis. The algorithm is employed for the analysis of an interferogram obtained from an inverting interferometer and the results are presented.

  15. Parallel interactive data analysis with PROOF

    NASA Astrophysics Data System (ADS)

    Ballintijn, Maarten; Biskup, Marek; Brun, René; Canal, Philippe; Feichtinger, Derek; Ganis, Gerardo; Kickinger, Günter; Peters, Andreas; Rademakers, Fons

    2006-04-01

    The Parallel ROOT Facility, PROOF, enables the analysis of much larger data sets on a shorter time scale. It exploits the inherent parallelism in data of uncorrelated events via a multi-tier architecture that optimizes I/O and CPU utilization in heterogeneous clusters with distributed storage. The system provides transparent and interactive access to gigabytes today. Being part of the ROOT framework PROOF inherits the benefits of a performant object storage system and a wealth of statistical and visualization tools. This paper describes the data analysis model of ROOT and the latest developments on closer integration of PROOF into that model and the ROOT user environment, e.g. support for PROOF-based browsing of trees stored remotely, and the popular TTree::Draw() interface. We also outline the ongoing developments aimed to improve the flexibility and user-friendliness of the system.

  16. 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…

  17. 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…

  18. 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.

  19. 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

  20. Early respiratory infections: the role of passive smoking in gene-environment interaction.

    PubMed

    Brescianini, Sonia; Fagnani, Corrado; Aquilini, Elisabetta; Annesi-Maesano, Isabella; Stazi, Maria A

    2016-06-01

    This study aims to: (i) estimate genetic and environmental components of four early respiratory diseases and (ii) test if these components are modified by parental smoking exposure. Study subjects were 2068 Italian twins aged 3-17. We performed biometric modeling under the assumptions of the twin design. For bronchitis and bronchiolitis, variance was mostly explained by shared environment, with no modification effect by parental smoking. For pneumonia and wheezy bronchitis, shared environmental component was larger among passive smokers, while genetic component was predominant among non-smokers. In the etiology of pneumonia and wheezy bronchitis, parental smoking could be a major familial factor. PMID:27013548

  1. 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...

  2. 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 ...

  3. Gene-environment interactions in rare diseases that include common birth defects.

    PubMed

    Graham, John M; Shaw, Gary M

    2005-11-01

    Rare syndromes often feature specific types of birth defects that frequently are major diagnostic clues to the presence of a given disorder. Despite this specificity, not everyone with the same syndrome is equally or comparably affected, and not everyone with a specific birth defect manifests the same syndrome or is affected with all the features of a particular syndrome. A symposium sponsored by the National Institutes of Health Office of Rare Diseases, and the National Toxicology Program Center for the Evaluation of Risks to Human Reproduction attempted to explore how much of this variability is due to genetic factors and how much is due to environmental factors. The specific types of birth defects examined included cardiovascular defects, holoprosencephaly, clefts of the lip and/or palate, neural tube defects, and diaphragmatic hernias.

  4. 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...

  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 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 ...

  7. Histamine regulation of microglia: Gene-environment interaction in the regulation of central nervous system inflammation.

    PubMed

    Frick, Luciana; Rapanelli, Maximiliano; Abbasi, Eeman; Ohtsu, Hiroshi; Pittenger, Christopher

    2016-10-01

    Microglia mediate neuroinflammation and regulate brain development and homeostasis. Microglial abnormalities are implicated in a range of neuropsychiatric pathology, including Tourette syndrome (TS) and autism. Histamine (HA) is both a neurotransmitter and an immune modulator. HA deficiency has been implicated as a rare cause of TS and may contribute to other neuropsychiatric conditions. In vitro studies suggest that HA can regulate microglia, but this has never been explored in vivo. We used immunohistochemistry to examine the effects of HA deficiency in histidine decarboxylase (Hdc) knockout mice and of HA receptor stimulation in wild-type animals. We find HA to regulate microglia in vivo, via the H4 receptor. Chronic HA deficiency in Hdc knockout mice reduces ramifications of microglia in the striatum and (at trend level) in the hypothalamus, but not elsewhere in the brain. Depletion of histaminergic neurons in the hypothalamus has a similar effect. Microglia expressing IGF-1 are particularly reduced, However, the microglial response to challenge with lipopolysacchariade (LPS) is potentiated in Hdc knockout mice. Genetic abnormalities in histaminergic signaling may produce a vulnerability to inflammatory challenge, setting the state for pathogenically dysregulated neuroimmune responses.

  8. Gene-environment interactions related to body mass: School policies and social context as environmental moderators

    PubMed Central

    Boardman, Jason D.; Roettger, Michael E.; Domingue, Benjamin W.; McQueen, Matthew B.; Haberstick, Brett C.; Harris, Kathleen M.

    2012-01-01

    This paper highlights the role of institutional resources and policies, whose origins lie in political processes, in shaping the genetic etiology of body mass among a national sample of adolescents. Using data from Waves I and II of the National Longitudinal Study of Adolescent Health, we decompose the variance of body mass into environmental and genetic components. We then examine the extent to which the genetic influences on body mass are different across the 134 schools in the study. Taking advantage of school differences in both health-related policies and social norms regarding body size, we examine how institutional resources and policies alter the relative impact of genetic influences on body mass. For the entire sample, we estimate a heritability of .82, with the remaining .18 due to unique environmental factors. However, we also show variation about this estimate and provide evidence suggesting that social norms and institutional policies often mask genetic vulnerabilities to increased weight. Empirically, we demonstrate that more-restrictive school policies and policies designed to curb weight gain are also associated with decreases the proportion of variance in body mass that is due to additive genetic influences. PMID:23236222

  9. Atlas Multimedia Educational Lab for Interactive Analysis

    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 ofmore » 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.-« less

  10. 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.

  11. 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…

  12. A review of gene-environment correlations and their implications for autism: a conceptual model.

    PubMed

    Meek, Shantel E; Lemery-Chalfant, Kathryn; Jahromi, Laudan B; Valiente, Carlos

    2013-07-01

    A conceptual model is proposed that explains how gene-environment correlations and the multiplier effect function in the context of social development in individuals with autism. The review discusses the current state of autism genetic research, including its challenges, such as the genetic and phenotypic heterogeneity of the disorder, and its limitations, such as the lack of interdisciplinary work between geneticists and social scientists. We discuss literature on gene-environment correlations in the context of social development and draw implications for individuals with autism. The review expands upon genes, behaviors, types of environmental exposure, and exogenous variables relevant to social development in individuals on the autism spectrum, and explains these factors in the context of the conceptual model to provide a more in-depth understanding of how the effects of certain genetic variants can be multiplied by the environment to cause largely phenotypic individual differences. Using the knowledge gathered from gene-environment correlations and the multiplier effect, we outline novel intervention directions and implications.

  13. Gene-gene and gene-environment interplay represent specific susceptibility for different types of ischaemic stroke and leukoaraiosis.

    PubMed

    Szolnoki, Zoltán; Melegh, Béla

    2006-01-01

    Stroke is a very frequent entity. It is the third leading cause of death and the leading cause of adult disability in the developed world. At a population level, the common sporadic form of ischaemic stroke is underpinned by both environmental and genetic risk factors. Typically, in clinical practice, environmental risk factors such as hypertension, diabetes mellitus, smoking, alcohol consumption, and other factors, are usually considered to be more important than genetic factors. However, it is the interplay of both environmental and common genetic factors [such as the Leiden V, methylenetetrahydrofolate reductase C677T, apolipopotein E 4, endothelial nitric oxide synthase G894T, angiotensin-converting enzyme I/D and angiotensin II type 1 receptor A1166C mutations and polymorphisms] that leads to the development of ischaemic stroke. Indeed, a complex network of interactions between genetic factors and clinical risk factors can be supposed. This review evaluates the possible roles of gene-gene and gene-environment interactions concerning the above genetic factors in the evolution of ischaemic stroke and leukoaraiosis. A knowledge of the specific genetic patterns which are associated with a significant risk of ischaemic stroke or leukoaraiosis may also draw attention to a large population at an increased risk of circulatory disorders. This may facilitate the choice of more effective and specific prevention on the basis of the genotype.

  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. 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

  16. 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.

  17. Combinatorial analysis of interacting RNA molecules.

    PubMed

    Li, Thomas J X; Reidys, Christian M

    2011-09-01

    Recently several minimum free energy (MFE) folding algorithms for predicting the joint structure of two interacting RNA molecules have been proposed. Their folding targets are interaction structures, that can be represented as diagrams with two backbones drawn horizontally on top of each other such that (1) intramolecular and intermolecular bonds are noncrossing and (2) there is no "zigzag" configuration. This paper studies joint structures with arc-length at least four in which both, interior and exterior stack-lengths are at least two (no isolated arcs). The key idea in this paper is to consider a new type of shape, based on which joint structures can be derived via symbolic enumeration. Our results imply simple asymptotic formulas for the number of joint structures with surprisingly small exponential growth rates. They are of interest in the context of designing prediction algorithms for RNA-RNA interactions. PMID:21689666

  18. 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.

  19. 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…

  20. Interactive Graphics Analysis for Aircraft Design

    NASA Technical Reports Server (NTRS)

    Townsend, J. C.

    1983-01-01

    Program uses higher-order far field drag minimization. Computer program WDES WDEM preliminary aerodynamic design tool for one or two interacting, subsonic lifting surfaces. Subcritical wing design code employs higher-order far-field drag minimization technique. Linearized aerodynamic theory used. Program written in FORTRAN IV.

  1. 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…

  2. 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. PMID:26538244

  3. 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

  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. 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.

  6. Theoretical Analysis of Dynamic Processes for Interacting Molecular Motors

    PubMed Central

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

    2015-01-01

    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. PMID:25688287

  7. A Discourse Analysis of Teacher-Student Classroom Interactions

    ERIC Educational Resources Information Center

    Shepherd, Michael Andrew

    2010-01-01

    This dissertation explores the role of classroom discourse in balancing teacher control over lesson content and student participation in educational interactions. The results of a discourse analysis of teacher-student interactions in video-recordings of eight third-grade math and language arts lessons reveal that the role of discourse in this…

  8. Interacting Online: A Content Analysis of Museum Education Websites

    ERIC Educational Resources Information Center

    Saiki, Diana

    2010-01-01

    The purpose of this research was to assess the degree of viewer interaction capabilities of features found on the education portion of museum websites. A content analysis was completed where features were categorized by learning levels including: narrative (the learner is a passive recipient), interactive (the learner chooses what he/she views),…

  9. Interpersonal Communication Skills: The Marriage of Interaction Analysis and Microcounseling

    ERIC Educational Resources Information Center

    Bradley, Curtis H.

    1976-01-01

    Describes microcounseling and interaction analysis, provides a reationale for the "marriage" of these two successful innovations, and demonstrates how the combination can provide an objective and systematic technology for the development of effective interpersonal communication skills.

  10. Analysis of interaction in binary odorant mixtures.

    PubMed

    Smith, B H

    1998-12-01

    An understanding of the olfactory system of any animal must account for how odor mixtures are perceived and processed. The present experiments apply associationist models to the study of how elements are processed in binary odorant mixtures. Using experimental designs for Proboscis Extension Conditioning of honey bees, I show that learning about a pure odorant element is frequently affected by its occurrence in a mixture with a second odorant. Presence of a background odor when an odorant is associated with sucrose reinforcement decreases the rate and/or asymptotic level of associative strength that accumulates to that odorant. This interaction is in part due to synthetic qualities that arise in sensory transduction and initial processing. In addition, it involves an attention-like processing system like that involved in overshadowing. Therefore, a model that includes representations of the component and configural qualities of odorants in mixtures is needed to provide a more complete account of learning about odor mixtures. PMID:9877404

  11. 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.

  12. 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.

  13. Methods for the analysis of protein-chromatin interactions.

    PubMed

    Brickwood, Sarah J; Myers, Fiona A; Chandler, Simon P

    2002-01-01

    The analysis of protein interactions with chromatin is vital for the understanding of DNA sequence recognition in vivo. Chromatin binding requires the interaction of proteins with DNA lying on the macromolecular protein surface of nucleosomes, a situation that can alter factor binding characteristics substantially when compared with naked DNA. It is therefore important to study these protein-DNA interactions in the context of a chromatin substrate, the more physiologically relevant binding situation. In this article we review techniques used in the investigation of protein interactions with defined nucleosomal templates. PMID:11876294

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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

  19. Quantitative analysis of intermolecular interactions in orthorhombic rubrene

    DOE PAGES

    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,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

  20. Quantitative analysis of intermolecular interactions in orthorhombic rubrene.

    PubMed

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

    2015-09-01

    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

  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. A Hierarchical Factor Model of Executive Functions in Adolescents: Evidence of Gene-Environment Interplay

    PubMed Central

    Li, James J.; Chung, Tammy A.; Vanyukov, Michael M.; Wood, D. Scott; Ferrell, Robert; Clark, Duncan B.

    2015-01-01

    Executive functions (EF) are a complex set of neurodevelopmental, higher-ordered processes that are especially salient during adolescence. Disruptions to these processes are predictive of psychiatric problems in later adolescence and adulthood. The objectives of the current study were to characterize the latent structure of EF using bifactor analysis and to investigate the independent and interactive effects of genes and environments on EF during adolescence. Using a representative young adolescent sample, we tested the interaction of a polymorphism in the serotonin transporter gene (5-HTTLPR) and parental supervision for EF through hierarchical linear regression. To account for the possibility of a hierarchical factor structure for EF, a bifactor analysis was conducted on the eight subtests of the Delis-Kaplan Executive Functions System (D-KEFS). The bifactor analysis revealed the presence of a general EF construct and three EF subdomains (i.e., conceptual flexibility, inhibition, and fluency). A significant 5-HTTLPR by parental supervision interaction was found for conceptual flexibility, but not for general EF, fluency or inhibition. Specifically, youth with the L/L genotype had significantly lower conceptual flexibility scores compared to youth with S/S or S/L genotypes given low levels of parental supervision. Our findings indicate that adolescents with the L/L genotype were especially vulnerable to poor parental supervision on EF. This vulnerability may be amenable to preventive interventions. PMID:25499600

  3. Gene-environment correlation underlying the association between parental negativity and adolescent externalizing problems.

    PubMed

    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 study used the novel Extended Children of Twins model to distinguish types of rGE underlying associations between negative parenting and adolescent (age 11-22 years) externalizing problems with a Swedish sample of 909 twin parents and their adolescent offspring and a U.S.-based sample of 405 adolescent siblings and their parents. Results suggest that evocative rGE, not passive rGE or direct environmental effects of parenting on adolescent externalizing, explains associations between maternal and paternal negativity and adolescent externalizing problems.

  4. Adding Graphical Interactive FITS Image Interaction to Data Analysis in IPython Notebooks

    NASA Astrophysics Data System (ADS)

    Jeschke, E.

    2014-05-01

    IPython notebooks are becoming a popular and viable approach for documenting data analysis procedures and helping produce open, reproducible science. Recent developments in the IPython project allow notebooks to be published and viewed on the web, providing a nearly seamless transition from data analysis to publication. In this talk we will review and demonstrate the ipython notebook as a data analysis tool, and show how graphical FITS image interaction can be integrated in the workflow to simplify some cumbersome tasks.

  5. 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.

  6. 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.

  7. Additive gene-environment effects on hippocampal structure in healthy humans.

    PubMed

    Rabl, Ulrich; Meyer, Bernhard M; Diers, Kersten; Bartova, Lucie; Berger, Andreas; Mandorfer, Dominik; Popovic, Ana; Scharinger, Christian; Huemer, Julia; Kalcher, Klaudius; Pail, Gerald; Haslacher, Helmuth; Perkmann, Thomas; Windischberger, Christian; Brocke, Burkhard; Sitte, Harald H; Pollak, Daniela D; Dreher, Jean-Claude; Kasper, Siegfried; Praschak-Rieder, Nicole; Moser, Ewald; Esterbauer, Harald; Pezawas, Lukas

    2014-07-23

    Hippocampal volume loss has been related to chronic stress as well as genetic factors. Although genetic and environmental variables affecting hippocampal volume have extensively been studied and related to mental illness, limited evidence is available with respect to G × E interactions on hippocampal volume. The present MRI study investigated interaction effects on hippocampal volume between three well-studied functional genetic variants (COMT Val158Met, BDNF Val66Met, 5-HTTLPR) associated with hippocampal volume and a measure of environmental adversity (life events questionnaire) in a large sample of healthy humans (n = 153). All three variants showed significant interactions with environmental adversity with respect to hippocampal volume. Observed effects were additive by nature and driven by both recent as well as early life events. A consecutive analysis of hippocampal subfields revealed a spatially distinct profile for each genetic variant suggesting a specific role of 5-HTTLPR for the subiculum, BDNF Val66Met for CA4/dentate gyrus, and COMT Val158Met for CA2/3 volume changes. The present study underscores the importance of G × E interactions as determinants of hippocampal volume, which is crucial for the neurobiological understanding of stress-related conditions, such as mood disorders or post-traumatic stress disorder (PTSD). PMID:25057194

  8. Additive gene-environment effects on hippocampal structure in healthy humans.

    PubMed

    Rabl, Ulrich; Meyer, Bernhard M; Diers, Kersten; Bartova, Lucie; Berger, Andreas; Mandorfer, Dominik; Popovic, Ana; Scharinger, Christian; Huemer, Julia; Kalcher, Klaudius; Pail, Gerald; Haslacher, Helmuth; Perkmann, Thomas; Windischberger, Christian; Brocke, Burkhard; Sitte, Harald H; Pollak, Daniela D; Dreher, Jean-Claude; Kasper, Siegfried; Praschak-Rieder, Nicole; Moser, Ewald; Esterbauer, Harald; Pezawas, Lukas

    2014-07-23

    Hippocampal volume loss has been related to chronic stress as well as genetic factors. Although genetic and environmental variables affecting hippocampal volume have extensively been studied and related to mental illness, limited evidence is available with respect to G × E interactions on hippocampal volume. The present MRI study investigated interaction effects on hippocampal volume between three well-studied functional genetic variants (COMT Val158Met, BDNF Val66Met, 5-HTTLPR) associated with hippocampal volume and a measure of environmental adversity (life events questionnaire) in a large sample of healthy humans (n = 153). All three variants showed significant interactions with environmental adversity with respect to hippocampal volume. Observed effects were additive by nature and driven by both recent as well as early life events. A consecutive analysis of hippocampal subfields revealed a spatially distinct profile for each genetic variant suggesting a specific role of 5-HTTLPR for the subiculum, BDNF Val66Met for CA4/dentate gyrus, and COMT Val158Met for CA2/3 volume changes. The present study underscores the importance of G × E interactions as determinants of hippocampal volume, which is crucial for the neurobiological understanding of stress-related conditions, such as mood disorders or post-traumatic stress disorder (PTSD).

  9. 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.

  10. Apache Drill: Interactive Ad-Hoc Analysis at Scale.

    PubMed

    Hausenblas, Michael; Nadeau, Jacques

    2013-06-01

    Apache Drill is a distributed system for interactive ad-hoc analysis of large-scale datasets. Designed to handle up to petabytes of data spread across thousands of servers, the goal of Drill is to respond to ad-hoc queries in a low-latency manner. In this article, we introduce Drill's architecture, discuss its extensibility points, and put it into the context of the emerging offerings in the interactive analytics realm.

  11. Interactive analysis of systems biology molecular expression data

    PubMed Central

    Zhang, Mingwu; Ouyang, Qi; Stephenson, Alan; Kane, Michael D; Salt, David E; Prabhakar, Sunil; Burgner, John; Buck, Charles; Zhang, Xiang

    2008-01-01

    Background Systems biology aims to understand biological systems on a comprehensive scale, such that the components that make up the whole are connected to one another and work through dependent interactions. Molecular correlations and comparative studies of molecular expression are crucial to establishing interdependent connections in systems biology. The existing software packages provide limited data mining capability. The user must first generate visualization data with a preferred data mining algorithm and then upload the resulting data into the visualization package for graphic visualization of molecular relations. Results Presented is a novel interactive visual data mining application, SysNet that provides an interactive environment for the analysis of high data volume molecular expression information of most any type from biological systems. It integrates interactive graphic visualization and statistical data mining into a single package. SysNet interactively presents intermolecular correlation information with circular and heatmap layouts. It is also applicable to comparative analysis of molecular expression data, such as time course data. Conclusion The SysNet program has been utilized to analyze elemental profile changes in response to an increasing concentration of iron (Fe) in growth media (an ionomics dataset). This study case demonstrates that the SysNet software is an effective platform for interactive analysis of molecular expression information in systems biology. PMID:18312669

  12. Interactive Fringe Analysis System: Applications To Moire Contourogram And Interferogram

    NASA Astrophysics Data System (ADS)

    Yatagai, T.; Idesawa, M.; Yamaashi, Y.; Suzuki, M.

    1982-10-01

    A general purpose fringe pattern processing facility was developed in order to analyze moire photographs used for scoliosis diagnoses and interferometric patterns in optical shops. A TV camera reads a fringe profile to be analyzed, and peaks of the fringe are detected by a microcomputer. Fringe peak correction and fringe order determination are performed with the man-machine interactive software developed. A light pen facility and an image digitizer are employed for interaction. In the case of two-dimensional fringe analysis, we analyze independently analysis lines parallel to each other and a reference line perpendicular to the parallel analysis lines. Fringe orders of parallel analysis lines are uniquely determined by using the fringe order of the reference line. Some results of analysis of moire contourograms, interferometric testing of silicon wafers, and holographic measurement of thermal deformation are presented.

  13. Kinetic analysis of drug-protein interactions by affinity chromatography.

    PubMed

    Bi, Cong; Beeram, Sandya; Li, Zhao; Zheng, Xiwei; Hage, David S

    2015-10-01

    Information on the kinetics of drug-protein interactions is of crucial importance in drug discovery and development. Several methods based on affinity chromatography have been developed in recent years to examine the association and dissociation rates of these processes. These techniques include band-broadening measurements, the peak decay method, peak fitting methods, the split-peak method, and free fraction analysis. This review will examine the general principles and applications of these approaches and discuss their use in the characterization, screening and analysis of drug-protein interactions in the body. PMID:26724332

  14. Distributed and interactive visual analysis of omics data.

    PubMed

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

    2015-11-01

    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.

  15. 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.

  16. Weak-wave analysis of shock interaction with a slipstream

    NASA Technical Reports Server (NTRS)

    Barger, Raymond L.

    1988-01-01

    A weak wave analysis of shock interaction with a slipstream is presented. The theory is compared to that for the acoustic case and to the exact nonlinear analysis. Sample calculations indicate that the weak wave theory yields a good approximation to the exact solution when the shock waves are sufficiently weak that the associated entropy increase is negligible. A qualitative discussion of the case of counterflowing streams is also included.

  17. 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

  18. Analysis of Stable and Transient Protein-Protein Interactions

    PubMed Central

    Byrum, Stephanie; Smart, Sherri K.; Larson, Signe; Tackett, Alan J.

    2012-01-01

    The assembly of proteins into defined complexes drives a plethora of cellular activities. These protein complexes often have a set of more stably interacting proteins as well as more unstable or transient interactions. Studying the in vivo components of these protein complexes is challenging as many of the techniques used for isolation result in the purification of only the most stable components and the transient interactions are lost. A technology called transient isotopic differentiation of interactions as random or targeted (transient I-DIRT) has been developed to identify these transiently interacting proteins as well as the stable interactions. Described here are the detailed methodological approaches used for a transient I-DIRT analysis of a multi-subunit complex, NuA3, that acetylates histone H3 and functions to activate gene transcription. Transcription is known to involve a concert of protein assemblies performing different activities on the chromatin/gene template, thus understanding the less stable or transient protein interactions with NuA3 will shed light onto the protein complexes that function synergistically, or antagonistically, to regulate gene transcription and chromatin remodeling. PMID:22183593

  19. 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.

  20. Interactive visual analysis of families of function graphs.

    PubMed

    Konyha, Zoltán; Matković, Kresimir; Gracanin, Denis; Jelović, Mario; Hauser, Helwig

    2006-01-01

    The analysis and exploration of multidimensional and multivariate data is still one of the most challenging areas in the field of visualization. In this paper, we describe an approach to visual analysis of an especially challenging set of problems that exhibit a complex internal data structure. We describe the interactive visual exploration and analysis of data that includes several (usually large) families of function graphs fi (x, t). We describe analysis procedures and practical aspects of the interactive visual analysis specific to this type of data (with emphasis on the function graph characteristic of the data). We adopted the well-proven approach of multiple, linked views with advanced interactive brushing to assess the data. Standard views such as histograms, scatterplots, and parallel coordinates are used to jointly visualize data. We support iterative visual analysis by providing means to create complex, composite brushes that span multiple views and that are constructed using different combination schemes. We demonstrate that engineering applications represent a challenging but very applicable area for visual analytics. As a case study, we describe the optimization of a fuel injection system in diesel engines of passenger cars.

  1. 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…

  2. 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…

  3. Analysis of Lipolytic Protein Trafficking and Interactions in Adipocytes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This work examined the colocalization, trafficking, and interactions of key proteins involved in lipolysis during brief cAMP-dependent protein kinase A (PKA) activation. Double label immunofluorescence analysis of 3T3-L1 adipocytes indicated that PKA activation increases the translocation of hormon...

  4. 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,…

  5. 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'…

  6. Modern tools for the time-discrete dynamics and optimization of gene-environment networks

    NASA Astrophysics Data System (ADS)

    Defterli, Ozlem; Fügenschuh, Armin; Weber, Gerhard Wilhelm

    2011-12-01

    In this study, we discuss the models of genetic regulatory systems, so-called gene-environment networks. The dynamics of such kind of systems are described by a class of time-continuous ordinary differential equations having a general form E˙=M(E)E, where E is a vector of gene-expression levels and environmental factors and M(E) is the matrix having functional entries containing unknown parameters to be optimized. Accordingly, time-discrete versions of that model class are studied and improved by introducing 3rd-order Heun's method and 4th-order classical Runge-Kutta method. The corresponding iteration formulas are derived and their matrix algebras are obtained. After that, we use nonlinear mixed-integer programming for the parameter estimation in the considered model and present the solution of a constrained and regularized given mixed-integer problem as an example. By using this solution and applying both the new and existing discretization schemes, we generate corresponding time-series of gene-expressions for each method. The comparison of the experimental data and the calculated approximate results is additionally done with the help of the figures to exercise the performance of the numerical schemes on this example.

  7. Gene-environment correlation linking aggression and peer victimization: do classroom behavioral norms matter?

    PubMed

    Brendgen, Mara; Girard, Alain; Vitaro, Frank; Dionne, Ginette; Boivin, Michel

    2015-01-01

    Using a genetically informed design based on 197 Monozygotic and Dizygotic twin pairs assessed in grade 4, this study examined 1) whether, in line with a gene-environment correlation (rGE), a genetic disposition for physical aggression or relational aggression puts children at risk of being victimized by their classmates, and 2) whether this rGE is moderated by classroom injunctive norm salience in regard to physical or relational aggression. Physical aggression and relational aggression, as well as injunctive classroom norm salience in regard to these behaviors, were measured via peer nominations. Peer victimization was measured via self-reports. Multi-Level Mixed modeling revealed that children with a genetic disposition for either aggressive behavior are at higher risk of being victimized by their peers only when classroom norms are unfavourable toward such behaviors. However, when classroom injunctive norms favor aggressive behaviors, a genetic disposition for physical or relational aggression may actually protect children against peer victimization. These results lend further support to the notion that bullying interventions must include the larger peer context instead of a sole focus on victims and bullies.

  8. Interactive effects of in utero nutrition and genetic inheritance on cognition: new evidence using sibling comparisons.

    PubMed

    Cook, C Justin; Fletcher, Jason M

    2014-03-01

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

  9. 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.

  10. 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

  11. Analysis of biomolecular interactions using affinity microcolumns: a review.

    PubMed

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

    2014-10-01

    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

  12. Factor analysis of the Iowa family interaction rating scales.

    PubMed

    Williamson, Hannah C; Bradbury, Thomas N; Trail, Thomas E; Karney, Benjamin R

    2011-12-01

    Observational coding systems are uniquely suited for investigating interactional processes in couples and families, but their validity in diverse populations is unknown. We addressed this issue by applying factor analysis to interactional data collected from couples in low-income neighborhoods and coded with the widely used Iowa Family Interaction Rating Scales (IFIRS). Our sample of 414 low-income, ethnically diverse newlywed couples each provided 24-min samples of problem-solving and social support behavior. Interrater reliabilities were strong, and the resultant factors--reflecting positive, negative, and effective communication--were very similar to those obtained with White middle-class samples. Additionally, couples were more negative, less positive, and less effective in problem-solving conversations than in socially supportive conversations, further supporting the validity of the IFIRS in this population. We conclude by discussing the strengths and shortcomings of the IFIRS when used in a low-income, ethnically diverse population.

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

    PubMed

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

    2015-06-26

    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. PMID:26197145

  14. 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

  15. 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.

  16. Interaction Analysis of a Two-Component System Using Nanodiscs

    PubMed Central

    Hörnschemeyer, Patrick; Liss, Viktoria; Heermann, Ralf; Jung, Kirsten; Hunke, Sabine

    2016-01-01

    Two-component systems are the major means by which bacteria couple adaptation to environmental changes. All utilize a phosphorylation cascade from a histidine kinase to a response regulator, and some also employ an accessory protein. The system-wide signaling fidelity of two-component systems is based on preferential binding between the signaling proteins. However, information on the interaction kinetics between membrane embedded histidine kinase and its partner proteins is lacking. Here, we report the first analysis of the interactions between the full-length membrane-bound histidine kinase CpxA, which was reconstituted in nanodiscs, and its cognate response regulator CpxR and accessory protein CpxP. Using surface plasmon resonance spectroscopy in combination with interaction map analysis, the affinity of membrane-embedded CpxA for CpxR was quantified, and found to increase by tenfold in the presence of ATP, suggesting that a considerable portion of phosphorylated CpxR might be stably associated with CpxA in vivo. Using microscale thermophoresis, the affinity between CpxA in nanodiscs and CpxP was determined to be substantially lower than that between CpxA and CpxR. Taken together, the quantitative interaction data extend our understanding of the signal transduction mechanism used by two-component systems. PMID:26882435

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

    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).

  18. 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

  19. MicroScale Thermophoresis: Interaction analysis and beyond

    NASA Astrophysics Data System (ADS)

    Jerabek-Willemsen, Moran; André, Timon; Wanner, Randy; Roth, Heide Marie; Duhr, Stefan; Baaske, Philipp; Breitsprecher, Dennis

    2014-12-01

    MicroScale Thermophoresis (MST) is a powerful technique to quantify biomolecular interactions. It is based on thermophoresis, the directed movement of molecules in a temperature gradient, which strongly depends on a variety of molecular properties such as size, charge, hydration shell or conformation. Thus, this technique is highly sensitive to virtually any change in molecular properties, allowing for a precise quantification of molecular events independent of the size or nature of the investigated specimen. During a MST experiment, a temperature gradient is induced by an infrared laser. The directed movement of molecules through the temperature gradient is detected and quantified using either covalently attached or intrinsic fluorophores. By combining the precision of fluorescence detection with the variability and sensitivity of thermophoresis, MST provides a flexible, robust and fast way to dissect molecular interactions. In this review, we present recent progress and developments in MST technology and focus on MST applications beyond standard biomolecular interaction studies. By using different model systems, we introduce alternative MST applications - such as determination of binding stoichiometries and binding modes, analysis of protein unfolding, thermodynamics and enzyme kinetics. In addition, wedemonstrate the capability of MST to quantify high-affinity interactions with dissociation constants (Kds) in the low picomolar (pM) range as well as protein-protein interactions in pure mammalian cell lysates.

  20. 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

  1. Interaction analysis method for the Hanford Waste Vitrification Plant

    SciTech Connect

    Grant, P.R.; Deshotels, R.L.; Van Katwijk, C.

    1993-08-01

    In order to anticipate potential problems as early as possible during the design effort, a method for interaction analysis was developed to meet the specific hazards of the Hanford Waste Vitrification Plant (HWVP). The requirement for interaction analysis is given in DOE Order 6430.1B and DOE-STD-1021-92. The purpose of the interaction analysis is to ensure that non-safety class items will not fail in a manner that will adversely affect the ability of any safety class item to perform its safety function. In the HWVP there are few structures, equipment, or controls that are safety class. In addition to damage due to failure of non-safety class items as a result of natural phenomena, threats to HWVP safety class items include the following: room flooding from firewater, leakage of chemically reactive liquids, high-pressure gas impingement from leaking piping, rocket-type impact from broken pressurized gas cylinders, loss of control of mobile equipment, cryogenic liquid spill, fire, and smoke. The time needed to perform the interaction analysis is minimized by consolidating safety class items into segregated areas. Each area containing safety class items is evaluated, and any potential threat to the safety functions is noted. After relocation of safety class items is considered, items that pose a threat are generally upgraded to eliminate the threat to the safety class items. Upgrading is the preferred option when relocation is not possible. An example will illustrate the method and application in the phased design, procurement, and construction environment of the HWVP.

  2. 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

  3. Genome-wide association interaction analysis for Alzheimer's disease.

    PubMed

    Gusareva, Elena S; Carrasquillo, Minerva M; Bellenguez, Céline; Cuyvers, Elise; Colon, Samuel; Graff-Radford, Neill R; Petersen, Ronald C; Dickson, Dennis W; Mahachie John, Jestinah M; Bessonov, Kyrylo; Van Broeckhoven, Christine; Harold, Denise; Williams, Julie; Amouyel, Philippe; Sleegers, Kristel; Ertekin-Taner, Nilüfer; Lambert, Jean-Charles; Van Steen, Kristel; Ramirez, Alfredo

    2014-11-01

    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.

  4. 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. PMID:25685513

  5. 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.

  6. Expression and interaction analysis of Arabidopsis Skp1-related genes.

    PubMed

    Takahashi, Naoki; Kuroda, Hirofumi; Kuromori, Takashi; Hirayama, Takashi; Seki, Motoaki; Shinozaki, Kazuo; Shimada, Hiroaki; Matsui, Minami

    2004-01-01

    Specific protein degradation has been observed in several aspects of development and differentiation in many organisms. One example of such proteolysis is regulated by protein polyubiquitination that is promoted by the SCF complex consisting of Skp1, cullin, and an F-box protein. We examined the activities of the Arabidopsis Skp1-related proteins (ASKs). Among 19 annotated ASK genes, we isolated 16 of the corresponding cDNAs (ASK1, 2, 3, 4, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19), and examined their gene products for interactions with 24 representatives of F-box proteins carrying various classes of the C-terminal domains using the yeast two-hybrid system. As a result, we found diverse binding specificities: ASK1, ASK2, ASK11 and ASK12 interacted well with COI1, FKF1, UFO-like protein, LRR-containing F-box proteins, and other F-box proteins with unknown C-terminal motifs. We also observed specific interaction between F-box proteins and ASK3, ASK9, ASK13, ASK14, ASK16 and ASK18. In contrast, we detected no interaction between any of the 12 ASK proteins and F-box proteins containing CRFA, CRFB or CRFC domains. Both histochemical and RT-PCR analysis of eight ASK genes expression revealed unique expression patterns for the respective genes. PMID:14749489

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

    PubMed Central

    Cook, C. Justin; Fletcher, Jason M.

    2013-01-01

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

  8. 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.

  9. Improved Statistics for Genome-Wide Interaction Analysis

    PubMed Central

    Ueki, Masao; Cordell, Heather J.

    2012-01-01

    Recently, Wu and colleagues [1] proposed two novel statistics for genome-wide interaction analysis using case/control or case-only data. In computer simulations, their proposed case/control statistic outperformed competing approaches, including the fast-epistasis option in PLINK and logistic regression analysis under the correct model; however, reasons for its superior performance were not fully explored. Here we investigate the theoretical properties and performance of Wu et al.'s proposed statistics and explain why, in some circumstances, they outperform competing approaches. Unfortunately, we find minor errors in the formulae for their statistics, resulting in tests that have higher than nominal type 1 error. We also find minor errors in PLINK's fast-epistasis and case-only statistics, although theory and simulations suggest that these errors have only negligible effect on type 1 error. We propose adjusted versions of all four statistics that, both theoretically and in computer simulations, maintain correct type 1 error rates under the null hypothesis. We also investigate statistics based on correlation coefficients that maintain similar control of type 1 error. Although designed to test specifically for interaction, we show that some of these previously-proposed statistics can, in fact, be sensitive to main effects at one or both loci, particularly in the presence of linkage disequilibrium. We propose two new “joint effects” statistics that, provided the disease is rare, are sensitive only to genuine interaction effects. In computer simulations we find, in most situations considered, that highest power is achieved by analysis under the correct genetic model. Such an analysis is unachievable in practice, as we do not know this model. However, generally high power over a wide range of scenarios is exhibited by our joint effects and adjusted Wu statistics. We recommend use of these alternative or adjusted statistics and urge caution when using Wu et al

  10. Improved statistics for genome-wide interaction analysis.

    PubMed

    Ueki, Masao; Cordell, Heather J

    2012-01-01

    Recently, Wu and colleagues [1] proposed two novel statistics for genome-wide interaction analysis using case/control or case-only data. In computer simulations, their proposed case/control statistic outperformed competing approaches, including the fast-epistasis option in PLINK and logistic regression analysis under the correct model; however, reasons for its superior performance were not fully explored. Here we investigate the theoretical properties and performance of Wu et al.'s proposed statistics and explain why, in some circumstances, they outperform competing approaches. Unfortunately, we find minor errors in the formulae for their statistics, resulting in tests that have higher than nominal type 1 error. We also find minor errors in PLINK's fast-epistasis and case-only statistics, although theory and simulations suggest that these errors have only negligible effect on type 1 error. We propose adjusted versions of all four statistics that, both theoretically and in computer simulations, maintain correct type 1 error rates under the null hypothesis. We also investigate statistics based on correlation coefficients that maintain similar control of type 1 error. Although designed to test specifically for interaction, we show that some of these previously-proposed statistics can, in fact, be sensitive to main effects at one or both loci, particularly in the presence of linkage disequilibrium. We propose two new "joint effects" statistics that, provided the disease is rare, are sensitive only to genuine interaction effects. In computer simulations we find, in most situations considered, that highest power is achieved by analysis under the correct genetic model. Such an analysis is unachievable in practice, as we do not know this model. However, generally high power over a wide range of scenarios is exhibited by our joint effects and adjusted Wu statistics. We recommend use of these alternative or adjusted statistics and urge caution when using Wu et al

  11. Interactive Analysis and Scripting in CIAO 2.0

    NASA Astrophysics Data System (ADS)

    Doe, S.; Noble, M.; Smith, R.

    Interpreted scripting languages are now recognized as essential components in the programmer's (and user's) tool chest, and, as amply demonstrated at ADASS 1999, have infiltrated the scientific community with great effect. In this paper we discuss the utilization of the S-Lang interpreted language within the Chandra Data Analysis System (CIAO, or Chandra Interactive Analysis of Observations). In only a few months, with substantial reuse and comparatively little manpower and code bloat, this effort has increased by an order of magnitude the analytical power and extensibility of CIAO. We summarize our design and implementation, and show brief fitting, modeling, and visualization threads that demonstrate capabilities roughly comparable with those of commercial packages. Finally, we present a beta version of the CIAO spectroscopic analysis module, GUIDE -- largely a collection of S-Lang scripts, glued with C++ enhancements to Sherpa and ChIPS -- to illustrate in more depth the range of new functionality and the rapid prototyping now available in CIAO.

  12. Global Interactions Analysis of Epileptic ECoG Data

    NASA Astrophysics Data System (ADS)

    Ortega, Guillermo J.; Sola, Rafael G.; Pastor, Jesús

    2007-05-01

    Localization of the epileptogenic zone is an important issue in epileptology, even though there is not a unique definition of the epileptic focus. The objective of the present study is to test ultrametric analysis to uncover cortical interactions in human epileptic data. Correlation analysis has been carried out over intraoperative Electro-Corticography (ECoG) data in 2 patients suffering from temporal lobe epilepsy (TLE). Recordings were obtained using a grid of 20 electrodes (5×4) covering the lateral temporal lobe and a strip of either 4 or 8 electrodes at the mesial temporal lobe. Ultrametric analysis was performed in the averaged final correlation matrices. By using the matrix of linear correlation coefficients and the appropriate metric distance between pairs of electrodes time series, we were able to construct Minimum Spanning Trees (MST). The topological connectivity displayed by these trees gives useful and valuable information regarding physiological and pathological information in the temporal lobe of epileptic patients.

  13. 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,…

  14. 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. PMID:26279343

  15. 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…

  16. 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…

  17. 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.

  18. 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…

  19. Development of a Genotyping Microarray for Studying the Role of Gene-Environment Interactions in Risk for Lung Cancer

    PubMed Central

    Baldwin, Don A.; Sarnowski, Christopher P.; Reddy, Sabrina A.; Blair, Ian A.; Clapper, Margie; Lazarus, Philip; Li, Mingyao; Muscat, Joshua E.; Penning, Trevor M.; Vachani, Anil; Whitehead, Alexander S.

    2013-01-01

    A microarray (LungCaGxE), based on Illumina BeadChip technology, was developed for high-resolution genotyping of genes that are candidates for involvement in environmentally driven aspects of lung cancer oncogenesis and/or tumor growth. The iterative array design process illustrates techniques for managing large panels of candidate genes and optimizing marker selection, aided by a new bioinformatics pipeline component, Tagger Batch Assistant. The LungCaGxE platform targets 298 genes and the proximal genetic regions in which they are located, using ∼13,000 DNA single nucleotide polymorphisms (SNPs), which include haplotype linkage markers with a minimum allele frequency of 1% and additional specifically targeted SNPs, for which published reports have indicated functional consequences or associations with lung cancer or other smoking-related diseases. The overall assay conversion rate was 98.9%; 99.0% of markers with a minimum Illumina design score of 0.6 successfully generated allele calls using genomic DNA from a study population of 1873 lung-cancer patients and controls. PMID:24294113

  20. 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...

  1. 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

  2. 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

  3. 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.

  4. Exploratory analysis of environmental interactions in central California

    USGS Publications Warehouse

    De Cola, Lee; Falcone, Neil L.

    1996-01-01

    As part of its global change research program, the United States Geological Survey (USGS) has produced raster data that describe the land cover of the United States using a consistent format. The data consist of elevations, satellite measurements, computed vegetation indices, land cover classes, and ancillary political, topographic and hydrographic information. This open-file report uses some of these data to explore the environment of a (256-km)? region of central California. We present various visualizations of the data, multiscale correlations between topography and vegetation, a path analysis of more complex statistical interactions, and a map that portrays the influence of agriculture on the region's vegetation. An appendix contains C and Mathematica code used to generate the graphics and some of the analysis.

  5. 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. PMID:27053654

  6. 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

  7. 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.

  8. Graph spectral analysis of protein interaction network evolution.

    PubMed

    Thorne, Thomas; Stumpf, Michael P H

    2012-10-01

    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.

  9. 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.

  10. 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.

  11. 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

  12. Phylogenetic analysis of modularity in protein interaction networks

    PubMed Central

    Erten, Sinan; Li, Xin; Bebek, Gurkan; Li, Jing; Koyutürk, Mehmet

    2009-01-01

    Background In systems biology, comparative analyses of molecular interactions across diverse species indicate that conservation and divergence of networks can be used to understand functional evolution from a systems perspective. A key characteristic of these networks is their modularity, which contributes significantly to their robustness, as well as adaptability. Consequently, analysis of modular network structures from a phylogenetic perspective may be useful in understanding the emergence, conservation, and diversification of functional modularity. Results In this paper, we propose a phylogenetic framework for analyzing network modules, with applications that extend well beyond network-based phylogeny reconstruction. Our approach is based on identification of modular network components from each network separately, followed by projection of these modules onto the networks of other species to compare different networks. Subsequently, we use the conservation of various modules in each network to assess the similarity between different networks. Compared to traditional methods that rely on topological comparisons, our approach has key advantages in (i) avoiding intractable graph comparison problems in comparative network analysis, (ii) accounting for noise and missing data through flexible treatment of network conservation, and (iii) providing insights on the evolution of biological systems through investigation of the evolutionary trajectories of network modules. We test our method, MOPHY, on synthetic data generated by simulation of network evolution, as well as existing protein-protein interaction data for seven diverse species. Comprehensive experimental results show that MOPHY is promising in reconstructing evolutionary histories of extant networks based on conservation of modularity, it is highly robust to noise, and outperforms existing methods that quantify network similarity in terms of conservation of network topology. Conclusion These results establish

  13. Laboratory modeling and analysis of aircraft-lightning interactions

    NASA Technical Reports Server (NTRS)

    Turner, C. D.; Trost, T. F.

    1982-01-01

    Modeling studies of the interaction of a delta wing aircraft with direct lightning strikes were carried out using an approximate scale model of an F-106B. The model, which is three feet in length, is subjected to direct injection of fast current pulses supplied by wires, which simulate the lightning channel and are attached at various locations on the model. Measurements are made of the resulting transient electromagnetic fields using time derivative sensors. The sensor outputs are sampled and digitized by computer. The noise level is reduced by averaging the sensor output from ten input pulses at each sample time. Computer analysis of the measured fields includes Fourier transformation and the computation of transfer functions for the model. Prony analysis is also used to determine the natural frequencies of the model. Comparisons of model natural frequencies extracted by Prony analysis with those for in flight direct strike data usually show lower damping in the in flight case. This is indicative of either a lightning channel with a higher impedance than the wires on the model, only one attachment point, or short streamers instead of a long channel.

  14. 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.

  15. 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.

  16. 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.

  17. Transcription Profiling Analysis of Mango-Fusarium mangiferae Interaction.

    PubMed

    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

  18. 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

  19. 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.

  20. Interactive visualization and analysis of multimodal datasets for surgical applications.

    PubMed

    Kirmizibayrak, Can; Yim, Yeny; Wakid, Mike; Hahn, James

    2012-12-01

    Surgeons use information from multiple sources when making surgical decisions. These include volumetric datasets (such as CT, PET, MRI, and their variants), 2D datasets (such as endoscopic videos), and vector-valued datasets (such as computer simulations). Presenting all the information to the user in an effective manner is a challenging problem. In this paper, we present a visualization approach that displays the information from various sources in a single coherent view. The system allows the user to explore and manipulate volumetric datasets, display analysis of dataset values in local regions, combine 2D and 3D imaging modalities and display results of vector-based computer simulations. Several interaction methods are discussed: in addition to traditional interfaces including mouse and trackers, gesture-based natural interaction methods are shown to control these visualizations with real-time performance. An example of a medical application (medialization laryngoplasty) is presented to demonstrate how the combination of different modalities can be used in a surgical setting with our approach.

  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. PMID:24051816

  2. ISO Data Archive and ISO Interactive Analysis Systems

    NASA Astrophysics Data System (ADS)

    Arviset, Christophe; Gabriel, Carlos; Ott, Stephan; Salama, Alberto; Hernández, José; Dowson, John; Osuna, Pedro

    The ISO Data Archive (IDA) has been available since December 1998. Through its pioneering Java user interface, it offers fast and easy access to the ISO data products and auxiliary data. Powerful and modular query panels enable searches of the observation catalogue, aided by icons and postcard viewers and a FITS file display tool. Standard or custom datasets can be chosen for retrieval, both for archived and on-the-fly re-calibrated data products. Moreover, the IDA open and flexible design allows interoperability with other archives, like SIMBAD, Vizier, NED, ADS, IRAS/IRSA. General descriptions of the PHT and CAM ISO Interactive Analysis (IA) systems are given including reduction of data from raw format to final images and spectra.

  3. Performance of a modular interactive data analysis system (MIDAS)

    SciTech Connect

    Maples, C.; Weaver, D.; Logan, D.; Rathbun, W.

    1983-01-01

    A processor cluster, part of a multiprocessor system named MIDAS (modular interactive data analysis system), has been constructed and tested. The architecture permits considerable flexibility in organizing the processing elements for different applications. The current tests involved 8 general CPUs from commercial computers, 2 special purpose pipelined processors and a specially designed communications system. Results on a variety of programs indicated that the cluster performs from 8 to 16 times faster than a standard computer with an identical CPU. The range represents the effect of differing CPU and I/O requirements-ranging from CPU intensive to I/O intensive. A benchmark test indicated that the cluster performed at approximately 85percent the speed of the CDC 7600. Plans for further cluster enhancements and multicluster operation are discussed. 5 references.

  4. 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.

  5. 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.

  6. An interactive modular design for computerized photometry in spectrochemical analysis

    NASA Technical Reports Server (NTRS)

    Bair, V. L.

    1980-01-01

    A general functional description of totally automatic photometry of emission spectra is not available for an operating environment in which the sample compositions and analysis procedures are low-volume and non-routine. The advantages of using an interactive approach to computer control in such an operating environment are demonstrated. This approach includes modular subroutines selected at multiple-option, menu-style decision points. This style of programming is used to trace elemental determinations, including the automated reading of spectrographic plates produced by a 3.4 m Ebert mount spectrograph using a dc-arc in an argon atmosphere. The simplified control logic and modular subroutine approach facilitates innovative research and program development, yet is easily adapted to routine tasks. Operator confidence and control are increased by the built-in options including degree of automation, amount of intermediate data printed out, amount of user prompting, and multidirectional decision points.

  7. 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

  8. 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…

  9. 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.

  10. 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…

  11. Social Network Analysis to Examine Interaction Patterns in Knowledge Building Communities

    ERIC Educational Resources Information Center

    Philip, Donald N.

    2010-01-01

    This paper describes use of social network analysis to examine student interaction patterns in a Grade 5/6 Knowledge Building class. The analysis included face-to-face interactions and interactions in the Knowledge Forum[R] Knowledge Building environment. It is argued that sociogram data are useful to reveal group processes; in sociological terms,…

  12. Mechanical force analysis of peptide interactions using atomic force microscopy.

    PubMed

    Nakamura, Chikashi; Takeda, Seiji; Kageshima, Masami; Ito, Miyuki; Sugimoto, Naoki; Sekizawa, Kazuko; Miyake, Jun

    2004-01-01

    Some peptides have previously been reported to bind low molecular weight chemicals. One such peptide with the amino acid sequence His-Ala-Ser-Tyr-Ser was selectively screened from a phage library and bound to a cationic porphyrin, 5,10,15,20-tetrakis(N-methylpyridinium-4-yl)-21H,23H-porphine (TMpyP), with a binding constant of 10(5) M(-1) (J. Kawakami, T. Kitano, and N. Sugimoto, Chemical Communications, 1999, pp. 1765-1766). The proposed binding was due to pi-electron stacking from two aromatic amino acids of histidine and tyrosine. In this study, the weak interactions between TMpyP and the peptide were further investigated by force curve analysis using atomic force microscopy (AFM). The mechanical force required to unbind the peptide-porphyrin complex was measured by vertical movement of the AFM tip. Peptide self-assembled monolayers were formed on both a gold-coated mica substrate and a gold-coated AFM tip. The TMpyPs could bind between the two peptide layers when the peptide-immobilized AFM tip contacted the peptide-immobilized substrate in solution containing TMpyP. In the retracting process a force that ruptured the interaction between TMpyPs and peptides was observed. The unbinding force values correlated to the concentration of TMpyP. A detection limit of 100 ng/mL porphyrin was obtained for the force measurement, and was similar to surface plasmon resonance sensor detection limits. Furthermore, we calculated the product of the observed force and the length of the molecular elongation to determine the work required to unbind the complexes. The obtained values of unbinding work were in a reasonable range compared to the binding energy of porphyrin-peptide.

  13. Kinetic analysis of biomolecular interactions by surface plasmon enhanced ellipsometry

    NASA Astrophysics Data System (ADS)

    Cho, Hyun Mo; Chegal, Won; Cho, Yong Jai; Won, Jong Myoung; Lee, Hak Min; Jo, Jae Heung

    2011-10-01

    We present the application of ellipsometry to the phase measurement of surface plasmon resonance (SPR) in biomolecular detection. In this work, the experimental setup for the SPR sensor was based on a custom-built rotating analyzer ellipsometer, which was equipped with a SPR cell and a microfluidic system. We investigate the sensitivity of SPR sensor which is dependent on the thickness and roughness of metal film, alignment of optical system, and stability of microfluidics. In the drug discovery process, to directly monitor the interaction of small molecule-protein, it is necessary to design a high-sensitivity SPR sensor with a sensitivity of greater than 1 pg/mm2. Our sensor demonstrates a much better sensitivity in comparison to other SPR sensors based on reflectometry or phase measurements. The results of calibration indicate that the phase change, δ▵, had an almost linear response to the concentration of ethanol in the double-distilled water solutions. A quantitative analysis of refractive index variation was possible using the results of the ellipsometric model fits for the multilayered thin film on the gold film. Thus, this method is applicable not only to sensor applications, such as affinity biosensors, but also to highly sensitive kinetics for drug discovery. In this paper, we demonstrate how a custom-built rotating analyzer ellipsometer in the SPR condition can be used to directly obtain the interactions and binding kinetics of analytes (biotins, peptides) with immobilized ligand (streptavidin, antibody). We achieved a detection limit of lower than 1.0 x10-7 RIU, which is the equivalent of 0.1 pg/mm2.

  14. 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).

  15. 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.

  16. Gastroschisis: a gene-environment model involving the VEGF-NOS3 pathway.

    PubMed

    Lammer, Edward J; Iovannisci, David M; Tom, Lauren; Schultz, Kathy; Shaw, Gary M

    2008-08-15

    Gastroschisis is a severe major malformation in which an infant is delivered with a portion of intestines and possible other abdominal organs extruding through a defect in the abdominal wall, usually to the right of the umbilical cord. Etiologies of gastroschisis are largely unknown, and even its pathogenesis is poorly understood. Several recent epidemiological studies have identified interactions between maternal smoking during pregnancy, genetic variants of endothelial nitric oxide synthase, and risk for gastroschisis. We present a brief review of the endothelial nitric oxide synthase pathway and its relationship to vasculogenesis, suggesting that disruption of this pathway by environmental exposures or by genetic variation may represent one pathogenetic model for gastroschisis.

  17. 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

  18. rs1495741 as a tag single nucleotide polymorphism of N-acetyltransferase 2 acetylator phenotype associates bladder cancer risk and interacts with smoking: A systematic review and meta-analysis.

    PubMed

    Ma, Chong; Gu, Liyan; Yang, Mingyuan; Zhang, Zhensheng; Zeng, Shuxiong; Song, Ruixiang; Xu, Chuanliang; Sun, Yinghao

    2016-08-01

    Rs1495741 has been identified to infer N-acetyltransferase 2 (NAT2) acetylator phenotype, and to decrease the risk of bladder cancer. However, a number of studies conducted in various regions showed controversial results. To quantify the association between rs1495741 and the risk of bladder cancer and to estimate the interaction effect of this genetic variant with smoking, we performed a systematic literature review and meta-analysis involving 14,815 cases and 58,282 controls from 29 studies. Our results indicates rs1495741 significantly associated with bladder cancer risk (OR = 0.85, 95% CI = 0.82-0.89, test for heterogeneity P = 0.36, I = 7.0%). And we verified this association in populations from Europe, America, and Asia. Further, our stratified meta-analysis showed rs1495741's role is typically evident only in ever smokers, which suggests its interaction with smoking. This study may provide new insight into gene-environment study on bladder cancer.

  19. 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. PMID:22826292

  20. Genome-wide gene-gene interaction analysis for next-generation sequencing.

    PubMed

    Zhao, Jinying; Zhu, Yun; Xiong, Momiao

    2016-03-01

    The critical barrier in interaction analysis for next-generation sequencing (NGS) data is that the traditional pairwise interaction analysis that is suitable for common variants is difficult to apply to rare variants because of their prohibitive computational time, large number of tests and low power. The great challenges for successful detection of interactions with NGS data are (1) the demands in the paradigm of changes in interaction analysis; (2) severe multiple testing; and (3) heavy computations. To meet these challenges, we shift the paradigm of interaction analysis between two SNPs to interaction analysis between two genomic regions. In other words, we take a gene as a unit of analysis and use functional data analysis techniques as dimensional reduction tools to develop a novel statistic to collectively test interaction between all possible pairs of SNPs within two genome regions. By intensive simulations, we demonstrate that the functional logistic regression for interaction analysis has the correct type 1 error rates and higher power to detect interaction than the currently used methods. The proposed method was applied to a coronary artery disease dataset from the Wellcome Trust Case Control Consortium (WTCCC) study and the Framingham Heart Study (FHS) dataset, and the early-onset myocardial infarction (EOMI) exome sequence datasets with European origin from the NHLBI's Exome Sequencing Project. We discovered that 6 of 27 pairs of significantly interacted genes in the FHS were replicated in the independent WTCCC study and 24 pairs of significantly interacted genes after applying Bonferroni correction in the EOMI study.

  1. 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.

  2. 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.

  3. High school students presenting science: An interactional sociolinguistic analysis

    NASA Astrophysics Data System (ADS)

    Bleicher, Robert

    Presenting science is an authentic activity of practicing scientists. Thus, effective communication of science is an important skill to nurture in high school students who are learning science. This study examines strategies employed by high school students as they make science presentations; it assesses students' conceptual understandings of particular science topics through their presentations and investigates gender differences. Data are derived from science presentation given by eight high school students, three females and five males who attended a summer science program. Data sources included videotaped presentations, ethnographic fieldnotes, interviews with presenters and members of the audience, and presenter notes and overheads. Presentations were transcribed and submitted to discourse analysis from an interactional sociolinguistic perspective. This article focuses on the methodology employed and how it helps inform the above research questions. The author argues that use of this methodology leads to findings that inform important social-communicative issues in the learning of science. Practical advice for teaching students to present science, implications for use of presentations to assess conceptual learning, and indications of some possible gender differences are discussed.Received: 14 April 1993; Revised: 15 February 1994;

  4. Chromatographic analysis of olopatadine in hydrophilic interaction liquid chromatography.

    PubMed

    Maksić, Jelena; Jovanović, Marko; Rakić, Tijana; Popović, Igor; Ivanović, Darko; Jančić-Stojanović, Biljana

    2015-01-01

    In this paper, chromatographic analysis of active substance olopatadine hydrochloride, which is used in eye drops as antihistaminic agent, and its impurity E isomer by hydrophilic interaction liquid chromatography (HILIC) and application of design of experiments (DoE) methodology are presented. In addition, benzalkonium chloride is very often used as a preservative in eye drops. Therefore, the evaluation of its chromatographic behavior in HILIC was carried out as well. In order to estimate chromatographic behavior and set optimal chromatographic conditions, DoE methodology was applied. After the selection of important chromatographic factors, Box-Behnken design was utilized, and on the basis of the obtained models factor effects were examined. Then, multi-objective robust optimization is performed aiming to obtain chromatographic conditions that comply with several quality criteria simultaneously: adequate and robust separation of critical peak pair and maximum retention of the first eluting peak. The optimal conditions are identified by using grid point search methodology. The experimental verification confirmed the adequacy of the defined optimal conditions. Finally, under optimal chromatographic conditions, the method was validated and applicability of the proposed method was confirmed.

  5. 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…

  6. 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.

  7. 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

  8. Research on Gene-Environment Interplay in the Era of "Big Data".

    PubMed

    Heath, Andrew C; Lessov-Schlaggar, Christina N; Lian, Min; Miller, Ruth; Duncan, Alexis E; Madden, Pamela A F

    2016-09-01

    Successful identification of genetic risk factors in genomewide association studies typically has depended on meta-analyses combining data from large numbers of studies involving tens or hundreds of thousands of participants. This poses a challenge for research on Gene × Environment interaction (G × E) effects, where characterization of environmental exposures is quite limited in most studies and often varies idiosyncratically between studies. Yet the importance of environmental exposures in the etiology of many disorders-and especially alcohol, tobacco, and drug use disorders-is undeniable. We discuss the potential for "big-data" approaches (e.g., aggregating data from state databases) to generate consistent measures of neighborhood environment across multiple studies, requiring only information about residential address (or ideally residential history) to make progress in G × E analyses. Big-data approaches may also help address limits to the generalizability of existing research literature, such as those that arise because of the limited numbers of severely alcohol-dependent mothers represented in prospective research studies. PMID:27588523

  9. Research on Gene-Environment Interplay in the Era of "Big Data".

    PubMed

    Heath, Andrew C; Lessov-Schlaggar, Christina N; Lian, Min; Miller, Ruth; Duncan, Alexis E; Madden, Pamela A F

    2016-09-01

    Successful identification of genetic risk factors in genomewide association studies typically has depended on meta-analyses combining data from large numbers of studies involving tens or hundreds of thousands of participants. This poses a challenge for research on Gene × Environment interaction (G × E) effects, where characterization of environmental exposures is quite limited in most studies and often varies idiosyncratically between studies. Yet the importance of environmental exposures in the etiology of many disorders-and especially alcohol, tobacco, and drug use disorders-is undeniable. We discuss the potential for "big-data" approaches (e.g., aggregating data from state databases) to generate consistent measures of neighborhood environment across multiple studies, requiring only information about residential address (or ideally residential history) to make progress in G × E analyses. Big-data approaches may also help address limits to the generalizability of existing research literature, such as those that arise because of the limited numbers of severely alcohol-dependent mothers represented in prospective research studies.

  10. 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.

  11. "Tooling Up To Go the Distance" Video Interaction Analysis.

    ERIC Educational Resources Information Center

    Fulford, Catherine P.; Zhang, Shuqiang

    A new video evaluation instrument is demonstrated. It is designed specifically for distance education, to be used for instructional design consultation, distance education teacher training, or research. Categories include students interacting with teachers, with other students, and content. Analyzing interaction in two-way television requires an…

  12. 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

  13. Effective field theory analysis of the self-interacting chameleon

    NASA Astrophysics Data System (ADS)

    Sanctuary, Hillary; Sturani, Riccardo

    2010-08-01

    We analyse the phenomenology of a self-interacting scalar field in the context of the chameleon scenario originally proposed by Khoury and Weltman. In the absence of self-interactions, this type of scalar field can mediate long range interactions and simultaneously evade constraints from violation of the weak equivalence principle. By applying to such a scalar field the effective field theory method proposed for Einstein gravity by Goldberger and Rothstein, we give a thorough perturbative evaluation of the importance of non-derivative self-interactions in determining the strength of the chameleon mediated force in the case of orbital motion. The self-interactions are potentially dangerous as they can change the long range behaviour of the field. Nevertheless, we show that they do not lead to any dramatic phenomenological consequence with respect to the linear case and solar system constraints are fulfilled.

  14. Proteomic tools for the analysis of transient interactions between metalloproteins.

    PubMed

    Martínez-Fábregas, Jonathan; Rubio, Silvia; Díaz-Quintana, Antonio; Díaz-Moreno, Irene; De la Rosa, Miguel Á

    2011-05-01

    Metalloproteins play major roles in cell metabolism and signalling pathways. In many cases, they show moonlighting behaviour, acting in different processes, depending on the physiological state of the cell. To understand these multitasking proteins, we need to discover the partners with which they carry out such novel functions. Although many technological and methodological tools have recently been reported for the detection of protein interactions, specific approaches to studying the interactions involving metalloproteins are not yet well developed. The task is even more challenging for metalloproteins, because they often form short-lived complexes that are difficult to detect. In this review, we gather the different proteomic techniques and biointeractomic tools reported in the literature. All of them have shown their applicability to the study of transient and weak protein-protein interactions, and are therefore suitable for metalloprotein interactions.

  15. 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.

  16. Proteomics Analysis Reveals Novel RASSF2 Interaction Partners

    PubMed Central

    Barnoud, Thibaut; Wilkey, Daniel W.; Merchant, Michael L.; Clark, Jennifer A.; Donninger, Howard

    2016-01-01

    RASSF2 is a tumor suppressor that shares homology with other Ras-association domain (RASSF) family members. It is a powerful pro-apoptotic K-Ras effector that is frequently inactivated in many human tumors. The exact mechanism by which RASSF2 functions is not clearly defined, but it likely acts as a scaffolding protein, modulating the activity of other pro-apoptotic effectors, thereby regulating and integrating tumor suppressor pathways. However, only a limited number of RASSF2 interacting partners have been identified to date. We used a proteomics based approach to identify additional RASSF2 interactions, and thereby gain a better insight into the mechanism of action of RASSF2. We identified several proteins, including C1QBP, Vimentin, Protein phosphatase 1G and Ribonuclease inhibitor that function in diverse biological processes, including protein post-translational modifications, epithelial-mesenchymal transition, cell migration and redox homeostasis, which have not previously been reported to interact with RASSF2. We independently validated two of these novel interactions, C1QBP and Vimentin and found that the interaction with C1QBP was enhanced by K-Ras whereas, interestingly, the Vimentin interaction was reduced by K-Ras. Additionally, RASSF2/K-Ras regulated the acetylation of Vimentin. Our data thus reveal novel mechanisms by which RASSF2 may exert its functions, several of which may be Ras-regulated. PMID:26999212

  17. 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.

  18. Constructing Mother-Infant Interactions: A Cognitive-Developmental Analysis of Young Mothers' Interactive Schemes.

    ERIC Educational Resources Information Center

    Peterson, Rita Bowdish

    This study examines the developmental status of young mothers' social and logical-physical reasoning in relation to the characteristics of their interactions with their infants. A total of 36 mothers 15 to 21 years of age and their 4-month-old infants were videotaped in their homes during play, infant teaching, and bathing. Selman's "concepts of…

  19. Validation of PhenX measures in the personalized medicine research project for use in gene/environment studies

    PubMed Central

    2014-01-01

    symptoms associated with a major depressive episode. Conclusions The approach employed resulted in a high response rate and valuable data for future gene/environment analyses. These results and high response rate highlight the utility of the PhenX Toolkit to collect valid phenotypic data that can be shared across groups to facilitate gene/environment studies. PMID:24423110

  20. An interaction stress analysis of nanoscale elastic asperity contacts

    NASA Astrophysics Data System (ADS)

    Rahmat, Meysam; Ghiasi, Hossein; Hubert, Pascal

    2011-12-01

    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.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Surface plasmon resonance analysis of interactions between diacylglycerol acyltransferase and its interacting molecules.

    PubMed

    Kamisaka, Yasushi; Goto, Rie; Shibakami, Motonari; Yoshioka, Kyoko; Sato, Yukari

    2011-01-01

    To measure the interactions of diacylglycerol acyltransferase (DGAT) by surface plasmon resonance (SPR), we immobilized Saccharomyces cerevisiae DGAT2 encoded by DGA1 on a BIACORE sensor chip surface. We used N-terminally truncated Dga1p with a FLAG tag at the C-terminus, which was purified to apparent homogeneity, maintaining significant DGAT activity (Kamisaka et al., Appl. Microbiol. Biotechnol., 88, 105-115 (2010)). Truncated Dga1p with a FLAG tag was immobilized with an anti-FLAG antibody that had been coupled with an L1 chip surface consisting of a carboxymethyl dextran matrix with additional hydrophobic alkane groups. The Dga1p-immobilized chip surface was analyzed for interactions of Dga1p with oleoyl-CoA, its substrate, and anti-Dga1p IgG, its interacting protein, by SPR. The binding of these analytes with the Dga1p-immobilized chip surface was specific, because butyryl-CoA, which cannot be used as a substrate for DGAT, and anti-glyceraldehyde-3-phosphate dehydrogenase IgG, did not induce any signals on SPR. Furthermore, injection of organic compounds such as xanthohumol, a DGAT inhibitor, into the Dga1p-immobilized chip surface induced significant SPR signals, probably due to interaction with DGAT. Another DGAT inhibitor, piperine, did not induce SPR signals on application, but induced them due to piperine on application together with oleoyl-CoA, in which piperine can be incorporated into the micelles of oleoyl-CoA. The results indicate that the Dga1p-immobilized L1 chip surface recognized DGAT inhibitors. Taking all this together, SPR measurement using the Dga1p-immobilized L1 chip surface provided a useful system to elucidate the structure-function relationships of DGAT and screen DGAT inhibitors.

  8. An Interactive Multiobjective Programming Approach to Combinatorial Data Analysis.

    ERIC Educational Resources Information Center

    Brusco, Michael J.; Stahl, Stephanie

    2001-01-01

    Describes an interactive procedure for multiobjective asymmetric unidimensional seriation problems that uses a dynamic-programming algorithm to generate partially the efficient set of sequences for small to medium-sized problems and a multioperational heuristic to estimate the efficient set for larger problems. Applies the procedure to an…

  9. An Analysis of Students' Dyadic Interaction on a Dictogloss Task.

    ERIC Educational Resources Information Center

    Lim, Wai Lee; Jacobs, George M.

    Using a Vygotskian perspective, this study investigated the possibility of secondary school second language students providing scaffolding for each other's learning during dyadic verbal interaction on a dictogloss task. Participants in the study were 19 English-as-a-Second-Language students from China, Hong Kong, and Korea, who studied at a girl's…

  10. 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.

  11. 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…

  12. Analysis of magnetic field plasma interactions using microparticles as probes.

    PubMed

    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. PMID:26382535

  13. 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…

  14. Analysis of magnetic field plasma interactions using microparticles as probes.

    PubMed

    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.

  15. 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.

  16. Understanding Students' Online Interaction: Analysis of Discussion Board Postings

    ERIC Educational Resources Information Center

    Song, Liyan; McNary, Scot W.

    2011-01-01

    The purpose of this paper was to report on the findings of a study examining students' online interaction patterns. The context of the study was a graduate online class delivered via Blackboard[R]. The primary data for the study came from students' discussion board postings, online learning journals, and course grades. Various data analysis…

  17. Microcanonical Analysis on a System with Long-Range Interactions

    NASA Astrophysics Data System (ADS)

    Hou, Ji-Xuan; Yu, Xu-Chen; Hou, Jing-Min

    2016-09-01

    We study a long-range interacting spin chain placed in a staggered magnetic field using microcanonical approach and obtain the global phase diagram. We find that this model exhibits both first order phase transition and second order phase transition separated by a tricritical point, and temperature jump can be observed in the first order phase transition.

  18. Instructional Interactions of Students with Cognitive Disabilities: Sequential Analysis

    ERIC Educational Resources Information Center

    Kim, Ockjean; Hupp, Susan C.

    2007-01-01

    We studied instructional interactions through semi-structured observation of 13 student- teacher dyads involving elementary students with cognitive disabilities. Special educators' use of directions and responses of differing modes and types was analyzed. Student task-engagement behaviors (i.e., active engage, disruptive, passive on-task,…

  19. 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…

  20. Analysis of adeno-associated virus and HPV interaction.

    PubMed

    Hermonat, Paul L; You, Hong; Chiriva-Internati, C Maurizio; Liu, Yong

    2005-01-01

    It is slowly becoming accepted that adeno-associated virus (AAV) is another significant factor involved in cervical carcinogenesis. However, unlike human papillomavirus (HPV), which is positively associated with cervical cancer, AAV is negatively associated with this cancer. This negative association appears to be through a direct and complex bi-directional interaction between AAV and HPV. Essentially all assays used for studying HPV can be used for studying the AAV-HPV interaction. This is because both viruses are productive in the same tissue, the stratified squamous epithelium (skin). Their relationship can be studied on the level of the complete virus and their complete life cycle using the organotypic epithelial raft culture system, which generates a stratified squamous epithelium. Their relationship can be studied in various other tissue-culture models measuring oncogenic potential. Their interaction can also be studied on the component level, as both protein-protein and protein-DNA interactions are known. Their relationship has even been studied using transgenic animals. The AAV-HPV relationship can be broken down into two halves--AAV-encoded products, which affect HPV biology, and HPV-encoded products, which affect AAV biology. To date, the former are much better studied than the latter. The rep gene and its largest product, Rep78, are responsible for most of AAV's effects upon HPV. This chapter largely focuses on AAV's effect on the HPV life cycle.

  1. 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 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

  2. Muscle Quality and Myosteatosis: Novel Associations With Mortality Risk: The Age, Gene/Environment Susceptibility (AGES)-Reykjavik Study.

    PubMed

    Reinders, Ilse; Murphy, Rachel A; Brouwer, Ingeborg A; Visser, Marjolein; Launer, Lenore; Siggeirsdottir, Kristin; Eiriksdottir, Gudny; Gudnason, Vilmundur; Jonsson, Palmi V; Lang, Thomas F; Harris, Tamara B

    2016-01-01

    Muscle composition may affect mortality risk, but prior studies have been limited to specific samples or less precise determination of muscle composition. We evaluated associations of thigh muscle composition, determined using computed tomography imaging, and knee extension strength with mortality risk among 4,824 participants aged 76.4 (standard deviation (SD), 5.5) years from the Age, Gene/Environment Susceptibility (AGES)-Reykjavik Study (2002-2006). Cox proportional hazards models were used to estimate hazard ratios. After 8.8 years of follow-up, there were 1,942 deaths. For men, each SD-increment increase in muscle lean area, muscle quality, and strength was associated with lower mortality risk, with decreases ranging between 11% and 22%. Each SD-increment increase in intermuscular adipose tissue and intramuscular adipose tissue was associated with higher mortality risk (hazard ratio (HR) = 1.13 (95% confidence interval (CI): 1.06, 1.22) and HR = 1.23 (95% CI: 1.15, 1.30), respectively). For women, each SD-increment increase in muscle lean area, muscle quality, and strength was associated with lower mortality risk, with decreases ranging between 12% and 19%. Greater intramuscular adipose tissue was associated with an 8% higher mortality risk (HR = 1.08, 95% CI: 1.01, 1.16). This study shows that muscle composition is associated with mortality risk. These results also show the importance of improving muscle strength and area and lowering muscle adipose tissue infiltration.

  3. Temperament and peer problems from early to middle childhood: Gene-environment correlations with negative emotionality and sociability.

    PubMed

    Hasenfratz, Liat; Benish-Weisman, Maya; Steinberg, Tami; Knafo-Noam, Ariel

    2015-11-01

    Based in a transactional framework in which children's own characteristics and the social environment influence each other to produce individual differences in social adjustment, we investigated relationships between children's peer problems and their temperamental characteristics, using a longitudinal and genetically informed study of 939 pairs of Israeli twins followed from early to middle childhood (ages 3, 5, and 6.5). Peer problems were moderately stable within children over time, such that children who appeared to have more peer problems at age 3 tended to have also more peer problems at age 6.5. Children's temperament accounted for 10%-22% of the variance in their peer problems measured at the same age and for 2%-7% of the variance longitudinally. It is important that genetic factors accounted for the association between temperament and peer problems and were in line with a gene-environment correlation process, providing support for the proposal that biologically predisposed characteristics, particularly negative emotionality and sociability, have an influence on children's early experiences of peer problems. The results highlight the need for early and continuous interventions that are specifically tailored to address the interpersonal difficulties of children with particular temperamental profiles.

  4. 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

  5. How resonance assists hydrogen bonding interactions: an energy decomposition analysis.

    PubMed

    Beck, John Frederick; Mo, Yirong

    2007-01-15

    Block-localized wave function (BLW) method, which is a variant of the ab initio valence bond (VB) theory, was employed to explore the nature of resonance-assisted hydrogen bonds (RAHBs) and to investigate the mechanism of synergistic interplay between pi delocalization and hydrogen-bonding interactions. We examined the dimers of formic acid, formamide, 4-pyrimidinone, 2-pyridinone, 2-hydroxpyridine, and 2-hydroxycyclopenta-2,4-dien-1-one. In addition, we studied the interactions in beta-diketone enols with a simplified model, namely the hydrogen bonds of 3-hydroxypropenal with both ethenol and formaldehyde. The intermolecular interaction energies, either with or without the involvement of pi resonance, were decomposed into the Hitler-London energy (DeltaEHL), polarization energy (DeltaEpol), charge transfer energy (DeltaECT), and electron correlation energy (DeltaEcor) terms. This allows for the examination of the character of hydrogen bonds and the impact of pi conjugation on hydrogen bonding interactions. Although it has been proposed that resonance-assisted hydrogen bonds are accompanied with an increasing of covalency character, our analyses showed that the enhanced interactions mostly originate from the classical dipole-dipole (i.e., electrostatic) attraction, as resonance redistributes the electron density and increases the dipole moments in monomers. The covalency of hydrogen bonds, however, changes very little. This disputes the belief that RAHB is primarily covalent in nature. Accordingly, we recommend the term "resonance-assisted binding (RAB)" instead of "resonance-assisted hydrogen bonding (RHAB)" to highlight the electrostatic, which is a long-range effect, rather than the electron transfer nature of the enhanced stabilization in RAHBs. PMID:17143867

  6. An application of fragment interaction analysis based on local MP2

    NASA Astrophysics Data System (ADS)

    Ishikawa, Takeshi; Mochizuki, Yuji; Amari, Shinji; Nakano, Tatsuya; Tanaka, Shigenori; Tanaka, Kiyoshi

    2008-09-01

    We have developed a method named 'fragment interaction analysis based on local MP2' (abbreviated as FILM). This method enables us to decompose the interaction energy associated with dispersion interactions into contributions of localized occupied orbitals. In this study, the basis set dependence of the results derived from FILM was examined. The results suggested that the individual ratio of pair correlation energies of selected orbital pairs to the total dispersion interaction was almost independent of the basis set size. As an illustrative example, detailed analysis was performed on the human immunodeficiency virus type 1 protease complexed with lopinavir molecule.

  7. Inter-helical interactions in membrane proteins: analysis based on the local backbone geometry and the side chain interactions.

    PubMed

    Jha, Anupam Nath; Vishveshwara, Saraswathi

    2009-06-01

    The availability of a significant number of the structures of helical membrane proteins has prompted us to investigate the mode of helix-helix packing. In the present study, we have considered a dataset of alpha-helical membrane proteins representing structures solved from all the known superfamilies. We have described the geometry of all the helical residues in terms of local coordinate axis at the backbone level. Significant inter-helical interactions have been considered as contacts by weighing the number of atom-atom contacts, including all the side-chain atoms. Such a definition of local axis and the contact criterion has allowed us to investigate the inter-helical interaction in a systematic and quantitative manner. We show that a single parameter (designated as alpha), which is derived from the parameters representing the mutual orientation of local axes, is able to accurately capture the details of helix-helix interaction. The analysis has been carried out by dividing the dataset into parallel, anti-parallel, and perpendicular orientation of helices. The study indicates that a specific range of alpha value is preferred for interactions among the anti-parallel helices. Such a preference is also seen among interacting residues of parallel helices, however to a lesser extent. No such preference is seen in the case of perpendicular helices, the contacts that arise mainly due to the interaction of surface helices with the end of the trans-membrane helices. The study supports the prevailing view that the anti-parallel helices are well packed. However, the interactions between helices of parallel orientation are non-trivial. The packing in alpha-helical membrane proteins, which is systematically and rigorously investigated in this study, may prove to be useful in modeling of helical membrane proteins.

  8. Numerical analysis of kinematic soil-pile interaction

    SciTech Connect

    Castelli, Francesco; Maugeri, Michele; Mylonakis, George

    2008-07-08

    In the present study, the response of singles pile to kinematic seismic loading is investigated using the computer program SAP2000. The objectives of the study are: (1) to develop a numerical model that can realistically simulate kinematic soil-structure interaction for piles accounting for discontinuity conditions at the pile-soil interface, energy dissipation and wave propagation; (2) to use the model for evaluating kinematic interaction effects on pile response as function of input ground motion; and (3) to present a case study in which theoretical predictions are compared with results obtained from other formulations. To evaluate the effects of kinematic loading, the responses of both the free-field soil (with no piles) and the pile were compared. Time history and static pushover analyses were conducted to estimate the displacement and kinematic pile bending under seismic loadings.

  9. Analysis of Coupled Reaction-Diffusion Equations for RNA Interactions

    PubMed Central

    Hohn, Maryann E.; Li, Bo; Yang, Weihua

    2015-01-01

    We consider a system of coupled reaction-diffusion equations that models the interaction between multiple types of chemical species, particularly the interaction between one messenger RNA and different types of non-coding microRNAs in biological cells. We construct various modeling systems with different levels of complexity for the reaction, nonlinear diffusion, and coupled reaction and diffusion of the RNA interactions, respectively, with the most complex one being the full coupled reaction-diffusion equations. The simplest system consists of ordinary differential equations (ODE) modeling the chemical reaction. We present a derivation of this system using the chemical master equation and the mean-field approximation, and prove the existence, uniqueness, and linear stability of equilibrium solution of the ODE system. Next, we consider a single, nonlinear diffusion equation for one species that results from the slow diffusion of the others. Using variational techniques, we prove the existence and uniqueness of solution to a boundary-value problem of this nonlinear diffusion equation. Finally, we consider the full system of reaction-diffusion equations, both steady-state and time-dependent. We use the monotone method to construct iteratively upper and lower solutions and show that their respective limits are solutions to the reaction-diffusion system. For the time-dependent system of reaction-diffusion equations, we obtain the existence and uniqueness of global solutions. We also obtain some asymptotic properties of such solutions. PMID:25601722

  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. PMID:24014400

  11. Head Motion Modeling for Human Behavior Analysis in Dyadic Interaction

    PubMed Central

    Xiao, Bo; Georgiou, Panayiotis; Baucom, Brian; Narayanan, Shrikanth S.

    2015-01-01

    This paper presents a computational study of head motion in human interaction, notably of its role in conveying interlocutors’ behavioral characteristics. Head motion is physically complex and carries rich information; current modeling approaches based on visual signals, however, are still limited in their ability to adequately capture these important properties. Guided by the methodology of kinesics, we propose a data driven approach to identify typical head motion patterns. The approach follows the steps of first segmenting motion events, then parametrically representing the motion by linear predictive features, and finally generalizing the motion types using Gaussian mixture models. The proposed approach is experimentally validated using video recordings of communication sessions from real couples involved in a couples therapy study. In particular we use the head motion model to classify binarized expert judgments of the interactants’ specific behavioral characteristics where entrainment in head motion is hypothesized to play a role: Acceptance, Blame, Positive, and Negative behavior. We achieve accuracies in the range of 60% to 70% for the various experimental settings and conditions. In addition, we describe a measure of motion similarity between the interaction partners based on the proposed model. We show that the relative change of head motion similarity during the interaction significantly correlates with the expert judgments of the interactants’ behavioral characteristics. These findings demonstrate the effectiveness of the proposed head motion model, and underscore the promise of analyzing human behavioral characteristics through signal processing methods. PMID:26557047

  12. In vivo analysis of human nucleoporin repeat domain interactions

    PubMed Central

    Xu, Songli; Powers, Maureen A.

    2013-01-01

    The nuclear pore complex (NPC), assembled from ∼30 proteins termed nucleoporins (Nups), mediates selective nucleocytoplasmic trafficking. A subset of nucleoporins bear a domain with multiple phenylalanine–glycine (FG) motifs. As binding sites for transport receptors, FG Nups are critical in translocation through the NPC. Certain FG Nups are believed to associate via low-affinity, cohesive interactions to form the permeability barrier of the pore, although the form and composition of this functional barrier are debated. We used green fluorescent protein–Nup98/HoxA9 constructs with various numbers of repeats and also substituted FG domains from other nucleoporins for the Nup98 domain to directly compare cohesive interactions in live cells by fluorescence recovery after photobleaching (FRAP). We find that cohesion is a function of both number and type of FG repeats. Glycine–leucine–FG (GLFG) repeat domains are the most cohesive. FG domains from several human nucleoporins showed no interactions in this assay; however, Nup214, with numerous VFG motifs, displayed measurable cohesion by FRAP. The cohesive nature of a human nucleoporin did not necessarily correlate with that of its yeast orthologue. The Nup98 GLFG domain also functions in pore targeting through binding to Nup93, positioning the GLFG domain in the center of the NPC and supporting a role for this nucleoporin in the permeability barrier. PMID:23427268

  13. Graphics Flutter Analysis Methods, an interactive computing system at Lockheed-California Company

    NASA Technical Reports Server (NTRS)

    Radovcich, N. A.

    1975-01-01

    An interactive computer graphics system, Graphics Flutter Analysis Methods (GFAM), was developed to complement FAMAS, a matrix-oriented batch computing system, and other computer programs in performing complex numerical calculations using a fully integrated data management system. GFAM has many of the matrix operation capabilities found in FAMAS, but on a smaller scale, and is utilized when the analysis requires a high degree of interaction between the engineer and computer, and schedule constraints exclude the use of batch entry programs. Applications of GFAM to a variety of preliminary design, development design, and project modification programs suggest that interactive flutter analysis using matrix representations is a feasible and cost effective computing tool.

  14. Assessing group interaction with social language network analysis.

    SciTech Connect

    Pennebaker, James; Scholand, Andrew Joseph; Tausczik, Yla R.

    2010-04-01

    In this paper we discuss a new methodology, social language network analysis (SLNA), that combines tools from social language processing and network analysis to assess socially situated working relationships within a group. Specifically, SLNA aims to identify and characterize the nature of working relationships by processing artifacts generated with computer-mediated communication systems, such as instant message texts or emails. Because social language processing is able to identify psychological, social, and emotional processes that individuals are not able to fully mask, social language network analysis can clarify and highlight complex interdependencies between group members, even when these relationships are latent or unrecognized.

  15. Assessing Group Interaction with Social Language Network Analysis

    NASA Astrophysics Data System (ADS)

    Scholand, Andrew J.; Tausczik, Yla R.; Pennebaker, James W.

    In this paper we discuss a new methodology, social language network analysis (SLNA), that combines tools from social language processing and network analysis to assess socially situated working relationships within a group. Specifically, SLNA aims to identify and characterize the nature of working relationships by processing artifacts generated with computer-mediated communication systems, such as instant message texts or emails. Because social language processing is able to identify psychological, social, and emotional processes that individuals are not able to fully mask, social language network analysis can clarify and highlight complex interdependencies between group members, even when these relationships are latent or unrecognized.

  16. Taylor Dispersion Analysis as a promising tool for assessment of peptide-peptide interactions.

    PubMed

    Høgstedt, Ulrich B; Schwach, Grégoire; van de Weert, Marco; Østergaard, Jesper

    2016-10-10

    Protein-protein and peptide-peptide (self-)interactions are of key importance in understanding the physiochemical behavior of proteins and peptides in solution. However, due to the small size of peptide molecules, characterization of these interactions is more challenging than for proteins. In this work, we show that protein-protein and peptide-peptide interactions can advantageously be investigated by measurement of the diffusion coefficient using Taylor Dispersion Analysis. Through comparison to Dynamic Light Scattering it was shown that Taylor Dispersion Analysis is well suited for the characterization of protein-protein interactions of solutions of α-lactalbumin and human serum albumin. The peptide-peptide interactions of three selected peptides were then investigated in a concentration range spanning from 0.5mg/ml up to 80mg/ml using Taylor Dispersion Analysis. The peptide-peptide interactions determination indicated that multibody interactions significantly affect the PPIs at concentration levels above 25mg/ml for the two charged peptides. Relative viscosity measurements, performed using the capillary based setup applied for Taylor Dispersion Analysis, showed that the viscosity of the peptide solutions increased with concentration. Our results indicate that a viscosity difference between run buffer and sample in Taylor Dispersion Analysis may result in overestimation of the measured diffusion coefficient. Thus, Taylor Dispersion Analysis provides a practical, but as yet primarily qualitative, approach to assessment of the colloidal stability of both peptide and protein formulations.

  17. Liminality in language use: some thoughts on interactional analysis from a dialogical perspective.

    PubMed

    Murakami, Kyoko

    2010-03-01

    This essay traces my engagement with Michèle Grossen's ideas of a dialogical perspective on interaction analysis (Grossen Integrative Psychological and Behavioral Science, 1-22, 2009) and highlights a process account of self in interaction. Firstly I draw on Turner's concept of liminality with respect to the transformative, temporal significance in interaction. Secondly I explored further the conversation analytic concepts such as formulation and reformulation as a viable analytical tool for a dialogical perspective. Lastly, I addressed the issue of interaction in institutional settings, in particular with interactional asymmetries of interaction, whilst relativising the I-position dialogical perspective. I explore insights from social anthropology as well as revisiting conversation analysis and discursive psychology, concluding that a promising direction would be sought through a cross-fertilisation between dialogism and other sibling perspectives concerning language use, communication, social action and discourse- and narrative-based analyses.

  18. Collisional interactions between self-interacting nonrelativistic boson stars: Effective potential analysis and numerical simulations

    NASA Astrophysics Data System (ADS)

    Cotner, Eric

    2016-09-01

    Scalar particles are a common prediction of many beyond the Standard Model theories. If they are light and cold enough, there is a possibility they may form Bose-Einstein condensates, which will then become gravitationally bound. These boson stars are solitonic solutions to the Einstein-Klein-Gordon equations but may be approximated in the nonrelativistic regime with a coupled Schrödinger-Poisson system. General properties of single soliton states are derived, including the possibility of quartic self-interactions. Binary collisions between two solitons are then studied, and the effects of different mass ratios, relative phases, self-couplings, and separation distances are characterized, leading to an easy conceptual understanding of how these parameters affect the collision outcome in terms of conservation of energy. Applications to dark matter are discussed.

  19. GIANT: a computer code for General Interactive ANalysis of Trajectories

    SciTech Connect

    Jaeger, J.; Lee, M.; Servranckx, R.; Shoaee, H.

    1985-04-01

    Many model-driven diagnostic and correction procedures have been developed at SLAC for the on-line computer controlled operation of SPEAR, PEP, the LINAC, and the Electron Damping Ring. In order to facilitate future applications and enhancements, these procedures are being collected into a single program, GIANT. The program allows interactive diagnosis as well as performance optimization of any beam transport line or circular machine. The test systems for GIANT are those of the SLC project. The organization of this program and some of the recent applications of the procedures will be described in this paper.

  20. Analysis of interaction phenomena between liquid jets and materials [preprint

    SciTech Connect

    Kang, S-W.; Reitter, T.; Carlson, G.

    1995-04-01

    The interaction phenomena of high-velocity liquid jets impinging on a material surface have been investigated theoretically and experimentally to understand the physics of material removal by jet-machining processes. Experiments were performed to delineate conditions under which liquid jet impacts will cause mass removal and to determine optimum jet-cutting conditions. Theoretical analyses have also been carried out to study the effects of multiple jet-droplet impacts on a target surface as a material deformation mechanism. The calculated target response and spallation behavior following droplet impacts and their physical implications are also discussed.