Family-based and genome-wide association studies (GWAS) of alcohol dependence (AD) have reported numerous associated variants. The clinical validity of these variants for predicting AD compared to family history has not yet been reported. These studies aim to explore the aggregate impact of multiple genetic variants with small effect sizes on risk prediction in order to provide a clinical interpretation of genetic contributions to AD. Data simulations showed that given AD’s prevalence and heritability, a risk prediction model incorporating all genetic contributions would have an area under the receiver operating characteristic curve (AUC) approaching 0.80, which is often a target AUC for screening. Adding additional environmental factors could increase the AUC to 0.95. Using the Collaborative Study on the Genetics of Alcoholism (COGA) and the Study of Addiction: Genes and Environment (SAGE) GWAS samples, we used several different sources to capture genetic information associated with AD in discovery samples, and then tested genetic sum scores created based on this information for predictive accuracy in validation samples. Scores were assessed separately for single nucleotide polymorphisms (SNPs) associated in candidate gene studies and in GWAS analyses. Candidate gene sum scores did not exhibit significant predictive accuracy, but SNPs meeting less stringent p-value thresholds in GWAS analyses did, ranging from mean estimates of 0.549 for SNPs meeting p<0.01 to 0.565 for SNPs meeting p<0.50. Variants associated with subtypes of AD showed that there is similarly modest and significant predictive ability for an externalizing subtype. Scores created based on all individual SNP effects in aggregate across the entire genome accounted for 0.46%-0.57% of the variance in AD symptom count, and have AUCs of 0.527 to 0.549. Additional covariates and environmental factors that are correlated with AD increased the AUC to 0.865. Family history was a better classifier of case-control status than genetic sum scores, with an AUC of 0.686 in COGA and 0.614 in SAGE. This project suggests that SNPs from candidate gene studies and genome-wide association studies currently have limited clinical validity, but there is potential for enhanced predictive ability with better detection of genetic factors contributing to AD.

Atualmente, um dos problemas mais importantes da Genética é a identificação de genes associados com doenças complexas. Um delineamento adequado para esta finalidade corresponde à coleta de dados de famílias e plataformas de marcadores moleculares do tipo SNP (do inglês, Single Nucleotide Polimorphism). Estas plataformas representam pontos de referência estrategicamente dispostos ao longo do genoma dos indivíduos e são de alta dimensão. A análise destes dados traz desafios analíticos como o problema de múltiplos testes e a seleção de variáveis preditoras. Nesta tese, propõe-se um critério para discriminar as variáveis preditoras genéticas em efeitos devidos ao componente aleatório poligênico e ao componente residual, sob a estrutura de um modelo linear misto. Também, considerando que o efeito individual das variáveis preditoras é esperado ser pequeno, é sugerido um método para encontrar subconjuntos ordenados destas variáveis e estudar o seu efeito simultâneo sobre a variável resposta em estudo. Neste contexto, utiliza-se a teoria associada ao Gráfico da Variável Adicionada em modelos mistos. As propostas são validadas por meio de um estudo de simulação, o qual é baseado em estruturas de famílias envolvidas no Projeto ``Corações de Baependi\" (InCor/USP), cujo objetivo é identificar genes associados a fatores de risco cardiovascular na população brasileira. Para a implementação dos procedimentos, usa-se o programa R e na geração das variáveis preditoras genéticas adota-se o aplicativo SimPed. / Recently, one of the most important problems in genetics is the identification of genes associated with complex diseases. A useful design for this proposal corresponds to collect data from extended families and molecular markers platforms SNPs (Single Nucleotide polymorphism). These platforms represent points of reference strategically placed along the genome of the individuals and are high dimensional. Analysis of these data brings analytical challenges as the problem of multiple testing and selection of predictive variables. In this thesis, we propose a criterion for discriminating predictors of genetic effects due to random polygenic component and the residual component, under the framework of a linear mixed model. Also, considering that the individual effects of predictor variables is expected to be small, it is suggested a method for finding ordered subsets of these variables and study their simultaneous effect on the response variable under study. In this context, is used the theory of the added variable plot under a mixed model framework. The proposals are validated through a simulation study, which is based on structures of families involved in the Project `` Baependi Heart Study (FAPESP Process 2007/58150-7), whose objective is to identify genes associated with cardiovascular risk factors in the Brazilian population. This proposal is implemented by using the R statistical environment and for the simulation of genetic predictors is adopted the SimPed application.

Atualmente, um dos problemas mais importantes da Genética é a identificação de genes associados com doenças complexas. Um delineamento adequado para esta finalidade corresponde à coleta de dados de famílias e plataformas de marcadores moleculares do tipo SNP (do inglês, Single Nucleotide Polimorphism). Estas plataformas representam pontos de referência estrategicamente dispostos ao longo do genoma dos indivíduos e são de alta dimensão. A análise destes dados traz desafios analíticos como o problema de múltiplos testes e a seleção de variáveis preditoras. Nesta tese, propõe-se um critério para discriminar as variáveis preditoras genéticas em efeitos devidos ao componente aleatório poligênico e ao componente residual, sob a estrutura de um modelo linear misto. Também, considerando que o efeito individual das variáveis preditoras é esperado ser pequeno, é sugerido um método para encontrar subconjuntos ordenados destas variáveis e estudar o seu efeito simultâneo sobre a variável resposta em estudo. Neste contexto, utiliza-se a teoria associada ao Gráfico da Variável Adicionada em modelos mistos. As propostas são validadas por meio de um estudo de simulação, o qual é baseado em estruturas de famílias envolvidas no Projeto ``Corações de Baependi\" (InCor/USP), cujo objetivo é identificar genes associados a fatores de risco cardiovascular na população brasileira. Para a implementação dos procedimentos, usa-se o programa R e na geração das variáveis preditoras genéticas adota-se o aplicativo SimPed. / Recently, one of the most important problems in genetics is the identification of genes associated with complex diseases. A useful design for this proposal corresponds to collect data from extended families and molecular markers platforms SNPs (Single Nucleotide polymorphism). These platforms represent points of reference strategically placed along the genome of the individuals and are high dimensional. Analysis of these data brings analytical challenges as the problem of multiple testing and selection of predictive variables. In this thesis, we propose a criterion for discriminating predictors of genetic effects due to random polygenic component and the residual component, under the framework of a linear mixed model. Also, considering that the individual effects of predictor variables is expected to be small, it is suggested a method for finding ordered subsets of these variables and study their simultaneous effect on the response variable under study. In this context, is used the theory of the added variable plot under a mixed model framework. The proposals are validated through a simulation study, which is based on structures of families involved in the Project `` Baependi Heart Study (FAPESP Process 2007/58150-7), whose objective is to identify genes associated with cardiovascular risk factors in the Brazilian population. This proposal is implemented by using the R statistical environment and for the simulation of genetic predictors is adopted the SimPed application.

Durante el ciclo de la vida, los individuos se ven expuestos a distintos factores tanto exógenos como endógenos, con diversas consecuencias sobre el comportamiento y el bienestar de los mismos. Entender la forma en que dichos factores afectan desenlaces de interés tanto a nivel individual como agregado, permite formular políticas públicas que mitiguen o potencien los efectos encontrados. En esta tesis analizo como factores socio-económicos, ambientales y genéticos afectan las decisiones de consumo y los niveles de salud de los individuos. En el primer capítulo de esta tesis, evalúo el efecto de una asignación gratuita de agua otorgada a hogares de bajos niveles socio-económicos en la ciudad de Bogotá (Colombia). Específicamente, evalúo el efecto de la asignación sobre las decisiones de consumo de agua de los individuos, encontrando que gracias a la intervención, los hogares incrementan su consumo de agua, al tiempo que experimentan una disminución en la factura del agua. Este resultado sugiere que la asignación funciona como una transferencia en efectivo. Adicionalmente, encuentro un incremento en el porcentaje de hogares que poseen un lavamanos; de esta forma el subsidio genera un incremento en el consumo de bienes durables relacionados con el consumo de agua. Finalmente, encuentro que entre la población más vulnerable, hay una disminución en la prevalencia de diarrea en menores de cinco años. En el segundo capítulo, analizo como la asociación entre variantes genéticas relacionadas con la obesidad y el índice de masa corporal (IMC) varía a lo largo del ciclo de la vida en varias cohortes poblacionales en Estados Unidos. Para tal fin empleo puntuaciones poligénicas, índices que resumen el riesgo genético de las personas hacia un elevado IMC. Encuentro que el efecto de las puntuaciones poligénicas del IMC sobre el IMC aumenta significativamente a medida que los adolescentes pasan a la edad adulta. Sin embargo, este no es el caso de las personas mayores de 55 años, cuya influencia genética en el IMC es notablemente estable a medida que avanzan hacia la vejez. Finalmente, en el último capítulo, evalúo el efecto que tienen los niveles de lluvia sobre medidas objetivas de salud mental en un país en vías de desarrollo. Usando un modelo de efectos y datos colombianos, encuentro que incrementos en los niveles de lluvia generan incrementos en el número de intentos de suicidios, en el número de personas tratadas por problemas de salud relacionados con el estrés y en el número de personas tratadas por depresión. A su vez encuentro una relación positiva entre niveles de lluvia y desempleo. Entre la población trabajadora, encuentro que incrementos en los niveles de lluvia únicamente afecta a los trabajadores del sector formal. Este resultado sugiere que los trabajadores del sector informal continúan trabajando aún bajo condiciones climáticas adversas.

Genetic and home chaos influences in early childhood have been independently associated with externalizing problems, characterized by inattentive, hyperactive, and aggressive behaviors. However, the Behavioral Genetics approach indicates that genetic and environmental influences, although independently effective, interact to produce behavior throughout development. Thus, this thesis uses two samples, the Early Growth and Development study (EGDS), n= 564, and the Avon Longitudinal Study of Parents and Children (ALSPAC), n= 8,952, and two genetically-sensitive approaches, a parent-child adoption approach and a polygenic scoring approach, to examine how genetic influences and home chaos interact in early childhood (age 3-4) to predict externalizing problems later in childhood (age 7). Results indicate that, although home chaos is correlated with later externalizing problems, the effect is reduced in the context of earlier externalizing, possibly suggesting that home chaos is most salient for concurrent, not later, externalizing problems. In addition, genetic influences were not predictive of externalizing problems in either study, nor was the interaction of home chaos and genetic influences. This pattern of results suggests that, although home chaos may be an important factor for concurrent externalizing problems, other factors, e.g., parenting style and prenatal risk, may be more salient than home chaos, especially in interaction with genetic effects. Further, failure to find genetic influence in this thesis suggest that accounting for the broad scope of genetic influences on complex traits like externalizing and the specific genetic risk for individual externalizing phenotypes is important in attempts to find genetic influence and interaction.

Schizophrenia is a severe psychiatric disorder associated with cognitive impairments. Polygenic risk for schizophrenia (SCZ-PGR) has been associated with poor performance in cognitive tasks, both in patients and in healthy individuals. It has also been suggested that schizophrenia is associated with accelerated aging. This study examines the association between SCZ-PGR and accelerated non-pathological cognitive aging by performing longitudinal analyses using linear mixed-effects models. We hypothesize that higher SCZ-PGR is associated with accelerated rate of cognitive decline in healthy elderly. The study sample consist of 1746 Caucasian individuals with genetic data. Their performance in general cognition, episodic memory, semantic memory and visuospatial memory was tested over 25 years. SCZ-PGR was significantly associated with poor cognitive function but was not associated with cognitive decline over time with any of the cognitive domains. Our results indicate that genetics of schizophrenia may not be associated with rate of cognitive aging. / Schizofreni är en svår psykiatrisk sjukdom som är associerad med kognitiv nedsättning. Polygenetisk risk för schizofreni (SCZ-PGR) har associerats med sämre resultat på kognitiva test, både hos schizofrenipatienter och friska individer. Det har även föreslagits att schizofreni är associerad med accelererat åldrande. Denna studie avser undersöka associationen mellan SCZPGR och accelererad icke-patologisk kognitivt åldrande genom att genomföra longitudinella analyser i lineära mixade-effekt-modeller. Vår hypotes är att högre SCZ-PGR är associerad med accelererad kognitivt åldrande hos friska. I denna studie ingår 1746 deltagare, där deltagarnas kognitiva förmåga testades under 25 år. Vi analyserade deras SCZ-PGR i relation till generell kognitiv förmåga, episodminne, semantiskt minne och visuo-spatialt minne, samt associationen mellan SCZ-PGR och förändringen av dessa variabler över tid. SCZ-PGR var signifikant associerad med sämre kognitiv förmåga, men inte med kognitiv försämring över tid. Dessa resultat indikerar att gener relaterade till schizofreni inte är associerade till kognitivt åldrande.

<p>Complex traits are influenced by genetic and environmental factors and their interactions. Most common human disorders such as cardiovascular, metabolic, autoimmune, and neurological diseases are complex. Understanding their genetic architecture and etiology is an important step to prevent, diagnose and treat these conditions. Genome Wide Association Studies (GWAS) have emerged as a powerful and widely used tool that can be used to explore and identify the genetic variants associated with complex traits. In this dissertation, we present some of the downstream applications of GWAS studies to analyze and understand the genetic risk and etiology of complex traits and provide important insights into the genetic architecture and background of several complex phenotypes. First, we examined whether prevalence of complex disorders around the world correlates to Polygenic Risk Scores (PRS). To do so, we determined the average PRS of 14 such complex disorders across 24 world populations using results of GWAS studies. We found variation in risk across populations and significant correlation was obtained between average disease risk and prevalence for seven of the studied disorders. Further exploring the power of PRS- based calculations, we performed a PRS - based phenome wide association study (PheWAS) for Tourette Syndrome (TS) and identified 57 phenotypic outcomes significantly associated with TS PRS. The strongest associations were found between TS PRS and mental health factors. Cross- disorder comparisons of phenotypic associations with genetic risk for other childhood-onset disorders (e.g.: attention deficit hyperactivity disorder [ADHD], autism spectrum disorder [ASD], and obsessive-compulsive disorder [OCD]) indicated an overlap in associations between TS and these disorders. Furthermore, we performed a sex specific PheWAS that highlighted differences in associations of complex disorders with TS PRS in males and females. Finally, we used large- scale GWAS results to identify causal associations between different biological markers (proteins, metabolites, and microbes) and subcortical brain structure volumes using Mendelian Randomization (MR) analysis. We identified eleven proteins and six metabolites to be significantly associated with subcortical brain volume structures. Enrichment analysis indicated that the associated proteins were enriched for proteolytic functions and regulation of apoptotic pathways. Overall, our work demonstrates the power of GWAS studies to help disentangle the genetic basis of complex diseases and also provides important insights into the etiology of the studied complex traits. </p>

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