The variability in caffeine consumption and inconsistencies among studies linking caffeine to heart disease may be explained by genetic variation. Caffeine antagonizes adenosine receptors with downstream effects on dopamine and serotonin. The objectives of this thesis were to determine whether the DRD2 957C>T or HTR2A 102C>T polymorphisms are associated with caffeine consumption or modify the association between coffee consumption and risk of myocardial infarction (MI). DRD2 genotype was associated with caffeine consumption among non-smokers and CYP1A2 -163C allele carriers. HTR2A genotype was associated with caffeine consumption among non-smokers and subjects with the ADORA2A TT genotype. Neither polymorphism modified the association between coffee consumption and risk of MI; however, a significant coffee x HTR2A interaction was seen among subjects with the CYP1A2 -163C allele. The results suggest caffeine’s reinforcing effects may be mediated by the dopamine and serotonin receptors and implicate serotonin in caffeine’s effect on risk of MI.

The variability in caffeine consumption and inconsistencies among studies linking caffeine to heart disease may be explained by genetic variation. Caffeine antagonizes adenosine receptors with downstream effects on dopamine and serotonin. The objectives of this thesis were to determine whether the DRD2 957C>T or HTR2A 102C>T polymorphisms are associated with caffeine consumption or modify the association between coffee consumption and risk of myocardial infarction (MI). DRD2 genotype was associated with caffeine consumption among non-smokers and CYP1A2 -163C allele carriers. HTR2A genotype was associated with caffeine consumption among non-smokers and subjects with the ADORA2A TT genotype. Neither polymorphism modified the association between coffee consumption and risk of MI; however, a significant coffee x HTR2A interaction was seen among subjects with the CYP1A2 -163C allele. The results suggest caffeine’s reinforcing effects may be mediated by the dopamine and serotonin receptors and implicate serotonin in caffeine’s effect on risk of MI.

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Made available in DSpace on 2014-08-20T13:32:47Z (GMT). No. of bitstreams: 1 dissertacao_liziane_pereira_da_silva.pdf: 573482 bytes, checksum: c057ff271e09c08ae99425d3f04b49da (MD5) Previous issue date: 2013-02-28 / Methylenetetrahydrofolate Reductase (MTHFR) gene polymorphisms are related to low activity of the enzyme increasing homocysteine (Hcy) plasma levels. Hyperhomocysteinemia (HHcy) is a risk factor for several pathological processes including atherosclerosis. The aim of the present study was to evaluate the effect of MTHFR C677T and A1298C polymorphisms and behavioral factors on Hcy levels in 3831 biological samples from 1982 Pelotas Birth Cohort individuals. The Hcy levels were measured in serum samples using chemiluminescence immunoassay. The genotyping was performed by allelic discrimination technique using pre-designed TaqMan® assays in the ABI7500 Fast Real-Time PCR System. The mean levels of Hcy were higher (p<0.001) in homozygous TT variant of MTHFR C677T than in CT and CC genotypes independently of sex, alcohol consumption, smoking and physical activity during leisure time. However it was demonstrated a higher MTHFR 677TT effect in smokers compared to non-smokers, as well as, in alcohol consumers than in non-consumers and in active individuals than in less active ones (p for interaction <0.001, respectively). For the MTHFR A1298C, the Hcy levels were higher in AA genotype than AC and CC genotypes, independently of behavioral factors. Men genotyped as MTHFR 1298AA showed 14% increasing on Hcy levels compared to 4% increase observed in women (p for interaction <0.001). No interactions were demonstrated between this polymorphism and the other behavioral factors analyzed. In conclusion, in young adult from 1982 cohort it was observed an interaction effect between the MTHFR C677T polymorphism and lifestyle on Hcy levels, contributing to an increased risk for cardiovascular chronic diseases in the future. / Os polimorfismos do gene Metilenotetrahidrofolato Redutase (MTHFR) estão relacionados com a baixa atividade da enzima e aumento dos níveis plasmáticos de homocisteína (Hcy). A hiper-homocisteinemia (HHcy) é um fator de risco para vários processos patológicos incluindo a aterosclerose. O objetivo do estudo foi avaliar o efeito do MTHFR C677T e A1298C e fatores comportamentais sobre os níveis de homocisteína em 3.831 amostras biológicas coletadas de indivíduos pertencentes à coorte de nascidos em Pelotas no ano de 1982. Os níveis de homocisteína foram medidos no soro por imunoensaio quimioluminescente. A genotipagem foi realizada pela técnica de discriminação alélica através do uso de sondas pré-desenhadas TaqMan® no equipamento ABI7500 Fast Real-Time PCR System. Os níveis médios de Hcy foram maiores (p <0,001) em indivíduos apresentando a variante MTHFR 677T em homozigose do que em indivíduos com genótipos CT e CC, independentemente de sexo, consumo de álcool, tabagismo e atividade física no lazer. No entanto, foi demonstrado um efeito maior em MTHFR 677TT fumantes em comparação aos não-fumantes, bem como, em consumidores de álcool do que em não-consumidores, e em indivíduos ativos do que em outros menos ativos (p de interação <0,001, respectivamente). Para MTHFR A1298C, os níveis de homocisteína foram maiores no genótipo AA do que nos genótipos AC e CC independente de fatores comportamentais. Homens genotipados como MTHFR 1298AA apresentaram aumento de 14% sobre os níveis de homocisteína em relação ao aumento de 4% observado em mulheres (p de interação <0,001). Não houve interação demonstrada entre este polimorfismo e os outros fatores comportamentais analisados. Em conclusão, em adultos jovens da coorte de 1982 foi observado um efeito de interação entre o polimorfismo MTHFR C677T com estilo de vida na determinação dos níveis de Hcy, contribuindo para um aumento do risco de doenças crônicas cardiovasculares no futuro.

Introduction – Animal studies suggested that NFKB1, SOCS3 and IKBKB genes could be involved in the association between overnutrition and obesity. This study aims to investigate interactions involving these genes and nutrition affecting obesity-related phenotypes. Methods – We used multifactor dimensionality reduction (MDR) and penalized logistic regression (PLR) to better detect gene/environment interactions in data from the Toronto Nutrigenomics and Health Study (n=1639) using dichotomized body mass index (BMI) and waist circumference (WC) as obesity-related phenotypes. Exposure variables included genotypes on 54 single nucleotide polymorphisms, dietary factors and ethnicity. Results – MDR identified interactions between SOCS3 rs6501199 and rs4969172, and IKBKB rs3747811 affecting BMI in whites; SOCS3 rs6501199 and NFKB1 rs1609798 affecting WC in whites; and SOCS3 rs4436839 and IKBKB rs3747811 affecting WC in South Asians. PLR found a main effect of SOCS3 rs12944581 on BMI among South Asians. Conclusion – MDR and PLR gave different results, but support some results from previous studies.

Genetic association studies have successfully identified many genetic markers associated with complex human diseases and related quantitative traits. However, for most complex diseases and quantitative traits, all associated genetic markers identified to date only explain a small proportion of heritability. Thus, exploring the unexplained heritability in these traits will help us discover novel genetic determinants for these traits and better understand disease etiology and pathophysiology. Due to limited sample size, a single cohort study may not have sufficient power to identify novel genetic association with a small effect size, and meta-analysis approaches have been proposed and applied to combine results from multiple cohorts in large consortia, increasing the sample size and statistical power. Rare genetic variants and gene by environment interaction may both play a role in genetic association studies. In this dissertation, we develop statistical methods in meta-analysis, rare genetic variants analysis and gene by environment interaction analysis, conduct extensive simulation studies, and apply these methods in real data examples. First, we develop a method of moments estimator for the between-study covariance matrix in random effects model multivariate meta-analysis. Our estimator is the first such estimator in matrix form, and holds the invariance property to linear transformations. It has similar performance with existing methods in simulation studies and real data analysis. Next, we extend the Sequence Kernel Association Test (SKAT), a rare genetic variants analysis approach for unrelated individuals, to be applicable in family samples for quantitative traits. The extension is necessary, as the original test has inflated type I error when directly applied to related individuals, and selecting an unrelated subset from family samples reduces the sample size and power. Finally, we derive methods for rare genetic variants analysis in detecting gene by environment interaction on quantitative traits, in the context of univariate test on the interaction term parameter. We develop statistical tests in the settings of both burden test and SKAT, for both unrelated and related individuals. Our methods are relevant to genetic association studies, and we hope that they can facilitate research in this field and beyond.

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Alcohol dependence (AD) is a serious and common public health problem that contributes to great societal, medical, and legal costs. It has taken work from multiple disciplines, including developmental psychology, genetic epidemiology, and molecular genetics, to achieve our current understanding of environmental and genetic risk factors for AD as well as its variable developmental trajectories. Nevertheless, there is still much to be learned in order to improve treatment outcomes. One approach to augmenting our understanding of this disorder is through genetically informative study designs that either examine risk in aggregate or assess specific susceptibility variants. In this dissertation, we utilize both study designs and provide support for the idea that they are both important and useful approaches to continue to pursue.

Background: The aim of the present article is to explore interaction and correlation effects between familial depression liability and selected adverse (separation and traumatic) events in predicting the first onset of a major depressive episode (MDE) in a 10-year prospective longitudinal community survey. Methods: Analyses are based on 1982 subjects (14 to 24 years at baseline) without baseline MDE who participated during the whole study period and for whom diagnostic information about psychopathology in both parents was available. The offspring’s familial depression liability was determined by aggregating information on parental depressive symptoms obtained from family history data and direct interviews with parents. Data were assessed with the Munich-Composite International Diagnostic Interview according to its DSM-IV algorithms. Results: Adverse events predicted a substantially increased incidence of MDE among respondents with familial liability but not in those without familial liability. There was a significant interaction between familial liability and traumatic events with the strongest effect for the number of severe traumatic events (risk difference = 11.3%; 95% confidence interval = 3.55–19.15). Associations with familial liability were most pronounced for separation events. Conclusions: Adverse events are particularly pathogenic in individuals with familial liability. The involvement of interactions and correlations between familial liability and adversity might depend on type, severity, and number of events. Both processes are suggested to be concomitant rather than exclusive.