Early life stress (ELS) is associated with risk of excessive alcohol drinking. However, the genetic mechanisms underlying the susceptibility to excessive alcohol drinking are not well understood. DNA methylation may mediate the influence of ELS on gene function and thereby contribute to alcohol misuse. Furthermore, susceptible genotypes of polymorphisms in interaction with early environment may influence alcohol related behaviors in adulthood. The present thesis comprised of a study of rodents and a study of humans. The former aimed to investigate the effects of ELS, alcohol drinking and housing on the expression of stress and DNA methylation regulatory genes in the hypothalamus and pituitary, and the expression of the Fkbp5 in the mesocorticolimbic system and dorsal striatum. The effects of ELS, alcohol, and housing on the DNA methylation of the promoters of genes of interest and blood corticosterone levels were also examined. Hypothalamic Adra2a expression was lower in alcohol drinking rats exposed to ELS, whereas ELS and ethanol drinking exerted independent effects on the expression of other genes in the hypothalamus and pituitary, however in a manner that depended on the control group used. Single housing associated with differential gene expression suggesting single housing as a confounding factor. Water and ethanol drinking in rats exposed to ELS was associated with higher and lower blood corticosterone, respectively. Brain region-dependent interaction effects between alcohol and ELS were observed on Fkbp5 expression in mesolimbic regions. These results indicate a counter-balancing effect of alcohol drinking to ELS. The study of humans investigated whether environment in interaction with single nucleotide polymorphisms of stress-related genes associate with alcohol use problems in young adults. The functional FKBP5 rs1360780 TT genotype in interaction with poor parent-child relationship was associated with problematic drinking behaviour. Regarding CRHR1, aversive and supportive environment in interaction with the rs1876831 AA genotype were associated with higher and lower alcohol drinking problems, respectively. Altogether, the present thesis deepens the knowledge of underlying genetic mechanisms for ELS-mediated propensity to drink alcohol and presents the novel insight into genetic susceptibility of FKBP5 and CRHR1 to early environment in relation to alcohol drinking problems.

It is widely believed that risks of many complex diseases are determined by genetic susceptibilities, including environmental exposures, and their interaction. Chatterjee and Carroll (2005) have recently developed an efficient retrospective maximum-likelihood method for analysis of case-control studies that exploits an assumption of gene-environment independence and leaves the distribution of the environmental covariates to be completely nonparametric. We generalize the semiparametric maximum-likelihood approach to situations when some of the environmental covariates are measured with error and allow genetic information to be missing on some subjects, e.g., unphased haplotypes. Profile likelihood techniques and an EM algorithm are developed, resulting in a relatively simple procedure for parameter estimation. We prove consistency and derive the resulting asymptotic covariance matrix of parameter estimates when variance of measurement error is known and when it is estimated using replications. The performance of the proposed method is illustrated using simulation studies emphasizing the case when genetic information is in the form of a haplotype and missing data arises from haplotype-phase ambiguity and missing genetic data. Inference is performed via a likelihood-ratio type procedure, one that we show has better small-sample performance thanWald-type inferences. An application of this method is illustrated using a case-control study of an association of calcium intake with early stages of colorectal tumor development.

Gene-environment interactions are an area of increasing interest in complex hu- man diseases. The first step in any study of the interactions between genes and the environment involves identifying genes which influence the trait of interest. In this dissertation, a new method for using the information in complex pedigrees to per- form a joint linkage disequilibrium and linkage mapping of quantitative trait loci is developed. Subsequently, methods are needed to determine the interaction, if any, between these genes and environmental risk factors. Many of these factors, such as weight or age, are continuous and little is known about their distributions. Thus, we introduce a new method for estimating the gene-environment interaction parameters in a logistic regression for the case-control study design. In doing so, we make the assumption that in the underlying population, the distributions of the genetic factors and the environmental covariates are independent. Additionally, we treat the envi- ronmental parameters nonparametricly, utilizing the profile likelihood. Furthermore, the methodology we develop is also general enough to be used on many different types of genetic information, including haplotypes, and can accommodate missing genotype data. The method is also extended to allow analysis in the presence of population stratification or genotype misclassification. We show that the standard errors of pa- rameter estimates using our method are smaller than those found using complete data only. These methods are illustrated using simulations and are applied to a real data set exploring the interaction between genotype and environment in disease risk.

Background: Obesity is now considered to be a global epidemic and gene-environment interaction studies are crucial to understanding the genetic architecture of this disease. The objectives of this research were to (1) review the current evidence of gene-environment interactions in the field of obesity, (2) examine the interactions between obesity predisposing gene variants and physical activity using precise physical activity data and (3) analyze a novel gene-environment interaction between obesity predisposing gene variants and multiple pregnancies. Methods: The data for the gene-environment interaction analyses were collected from the EpiDREAM study: a prospective cohort including participants of six ethnic backgrounds from 21 countries worldwide. A subset of 17 423 participants with complete genotype and phenotype information was included in the analysis. Obesity predisposing single nucleotide polymorphisms were analyzed independently and as a genetic risk score. General linear models were used to analyze all main effects and interactions. Results: Physical activity interacted with FTO rs9939609 to modulate BMI (Pinteraction=0.032) and BAI (Pinteraction=3.26 x 10-4). Increased physical activity attenuated the impact of FTO on obesity. Four SNPs displayed significant associations with physical activity: NTRK2 rs1211166 (P=0.015), BDNF rs6265 (P=0.007), BDNF rs1401635 P=0.003) and NPC1 rs1805081 (P=3.52 x 10-4). Multiple pregnancies was significantly associated with BMI (Pinteraction=1.17 x 10-5) BAI (Pinteraction=3.47 x 10-7) and also interacted with FTO rs9939609 to modulate BMI (Pinteraction=0.014). The impact of FTO on BMI was accentuated by multiple pregnancies in the EpiDREAM cohort. Discussion: Both physical activity and parity have a significant impact on obesity measures and these effects appear to be relevant on a global scale. Our results confirm the physical activity x FTO interaction in a multi-ethnic context and indicate that parity may also interact with FTO polymorphisms. / Thesis / Master of Science (MSc)

Background: Obesity is a multifactorial disease caused by the interplay of environmental and genetic risk factors. With the prevalence of obesity more than doubling since 1980, this disease has become a global epidemic. The objectives of this research were to (1) review the current evidence of gene-environment interactions (GEI) in the field of obesity, (2) investigate novel GEI involving sedentary behaviour, sleep duration and alcohol consumption, (3) assess GEI using a cumulative environmental risk score, and (4) provide an overview of methodological weaknesses in GEI studies and provide suggestions for future directions. Methods: The data for the gene-environment interaction analyses were collected from the EpiDREAM study: a cohort study including participants of six ethnic backgrounds from 17 countries worldwide. A subset of 17 423 participants with complete genotype and phenotype information was included in the analysis. Twenty-three obesity predisposing single nucleotide polymorphisms (SNPs) were analyzed independently and as a genetic risk score (GRS). Linear regression models were used to analyze these interactions. Results: Heritability, monogenic and polygenic obesity studies provide converging evidence that obesity-predisposing genes interact with a variety of environmental exposures including physical activity and diet patterns. In the EpiDREAM cohort, we found that increased sedentary time did not interact with obesity predisposing SNPs or the GRS to modulate BMI. The interaction between sedentary time and physical activity was also not significant. We observed a U-shaped association between sleep duration and BMI and sleep duration did not appear to moderate the impact of the obesity predisposing SNPs or the GRS. However, we did observe an alcohol x FTO rs1421085 interaction, whereby increased alcohol consumption attenuated the impact of FTO rs1421085 variation on BMI. We also found that the combined effect of several environmental risk factors significantly modified the effect of FTO rs3751812 on BMI. Specifically, we found that the effect of the FTO rs3751812 SNP on BMI was over two times greater among those in the highest quartile of environmental risk compared to those in the lowest quartile. The GRS did not interact with any of the exposures tested. Discussion: Our results indicate that sedentary behaviour did not moderate the impact of obesity predisposing genes, while alcohol consumption decreased the impact of variation in FTO rs3751812 on BMI. We also observed that variation in FTO rs3751812 interacted with a cumulative environmental risk score to moderate BMI. The growing body of GEI evidence has provided a deeper understanding of obesity aetiology and may have tremendous applications in the emerging field of personalized medicine and individualized lifestyle recommendations. Although the number of gene-environment interaction analyses has increased rapidly across multiple disciplines, addressing methodological concerns such as statistical modeling, confounding, biological assumptions and measurement precision will be necessary to fully exploit the potential of the GEI field. With the development of new methodological and measurement techniques such as hypothesis-free genome wide interaction studies and deep phenotyping, it may be possible to translate the information from GEI studies into public health policy and personalized medicine for obesity and other complex human diseases. / Thesis / Doctor of Philosophy (PhD)

abstract: The present study utilized longitudinal data from a high-risk community sample (n=254, 52.8% female, 47.2% children of alcoholics, 74% non-Hispanic Caucasian) to test questions concerning the effects of genetic risk, parental knowledge, and peer substance use on emerging adult substance use disorders (SUDs). Specifically, this study examined whether parental knowledge and peer substance use mediated the effects of parent alcohol use disorder (AUD) and genetic risk for behavioral undercontrol on SUD. The current study also examined whether genetic risk moderated effects of parental knowledge and peer substance use on risk for SUD. Finally, this study examined these questions over and above a genetic "control" which explained a large proportion of variance in the outcome, thereby providing a stricter test of environmental influences. Analyses were performed in a path analysis framework. To test these research questions, the current study employed two polygenic risk scores. The first, a theory-based score, was formed using single-nucleotide polymorphisms (SNPs) from receptor systems implicated in the amplification of positive effects in the presence of new/exciting stimuli and/or pleasure derived from using substances. The second, an empirically-based score, was formed using a data-driven approach that explained a large amount of variance in SUDs. Together, these scores allowed the present study to test explanations for the relations among parent AUD, parental knowledge, peer substance use, and SUDs. Results of the current study found that having parents with less knowledge or an AUD conferred greater risk for SUDs, but only for those at higher genetic risk for behavioral undercontrol. The current study replicated research findings suggesting that peer substance use mediated the effect of parental AUD on SUD. However, it adds to this literature by suggesting that some mechanism other than increased behavioral undercontrol explains relations among parental AUD, peer substance use, and emerging adult SUD. Taken together, these findings indicate that children of parents with AUDs comprise a particularly risky group, although likelihood of SUD within this group is not uniform. These findings also suggest that some of the most important environmental risk factors for SUDs exert effects that vary across level of genetic propensity. / Dissertation/Thesis / Doctoral Dissertation Psychology 2015

Risk-taking behavior (RTB) is defined as behavior involving the probability of reward with concurrent probability of some negative outcome. Peer influence is among the most robust predictors of RTB, such that greater peer influence, particularly deviant or delinquent peer influence, is associated with increased RTB. Evidence suggests that those with genetic predispositions for RTB may also be more susceptible to peer influence as a function of genotype. Given that genetic polymorphisms within the dopaminergic system have evidenced associations with various forms of RTB and delinquent peer affiliation, it is possible that these genes may interact with peer influence to predict increased RTB, a process called gene × environment interaction (G×E). We expected that those genetically at risk would take more risks in the presence of a peer than alone. To test this effect, five polymorphisms within the dopaminergic system were genotyped in a sample of 85 undergraduate students. Participants completed a behavioral risk task alone and in the presence of a peer providing "risky" feedback. No significant G×Es were identified for any of the dependent variables. However, participants took significantly more risks in the presence of a risky peer than when taking risks alone. These results suggest that G×E may not be a relevant process for peer-influenced RTB during late adolescence. It is possible that G×E is a relevant process during early adolescence, while gene-environment correlation (rGE) is the dominant process during late adolescence. Future research would benefit from testing whether these genes are relevant to G×E in early adolescence, as well as to rGE during late adolescence.

No description available.

Measurement error is an important issue in studies of environmental epidemiology. We considered the effects of measurement error in environmental covariates in several important settings affecting current public health research. Throughout this dissertation, we investigate the impacts of measurement error and consider statistical methodology to fix that error.

Introduction: There is evidence to suggest that common genetic polymorphisms can modify the effect of environmental risk factors on colorectal neoplasia. Methods: Data on 1430 individuals were obtained from two chemoprevention trials, the Wheat Bran Fiber Trial (WBF) (1) and the Effects of Ursodeoxycholic Acid on Adenomatous Polyp Recurrence Trial (URSO) (2). Data were analyzed to test for gene-environment interactions between allelic variation in PPAR-γ (Pro12Ala, C1431T), body mass index (BMI) and waist circumference, and the biochemical biomarkers of metabolic syndrome. Simulated data were then used to determine if the sample size required to formally test the relationship between gene-exposure interactions could be reduced by using a genetically enriched study population. For this simulation aspect of the work, an established gene-drug interaction (i.e.: flavin monooxygenase 3 (FMO3) and sulindac) was used as a model system. Results: There was a borderline significant interaction between BMI and PPAR-γ for the Pro12Ala genotype (p(inter)=0.11) and significant interactions between BMI and the C1431T genotype (p(inter)=0.09). Results from the recursive partition model identified BMI (p = 0.007) and baseline fasting glucose levels (p =0.033) as significant predictors of colorectal adenoma recurrence for carriers of Ala12 and waist circumference as a significant predictor for the Pro12Pro12 carriers (p=0.002). Results from the simulated studies indicated that using genetically pre-screened and enriched populations can result in a 50% savings in the number of subjects required to test the candidate gene-drug interaction. Conclusions: These findings provide evidence that the effect of allelic variation in PPAR-γ on colorectal adenoma recurrence is modified by BMI and that component traits of metabolic syndrome differentially affect the risk of colorectal adenoma recurrence depending on genotype. In addition, using genotype as an inclusion criterion in future studies of adenoma recurrence will result in a smaller sample size required to test gene-environment interactions.