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In this analysis, guided by an evolutionary framework, we investigate how the human genome as a whole interacts with historical period, age, and physical activity to influence body mass index (BMI). The genomic influence is estimated by (1) heritability or the proportion of variance in BMI explained by genome-wide genotype data, and (2) the random effects(More)
Assortative mating in phenotype in human marriages has been widely observed. Using genome-wide genotype data from the Framingham Heart study (FHS; number of married couples = 989) and Health Retirement Survey (HRS; number of married couples = 3,474), this study investigates genomic assortative mating in human marriages. Two types of genomic marital(More)
This study demonstrates body mass in middle and late adulthood as a consequence of the complex interplay among individuals' genes, lifetime socioeconomic experiences, and the historical context in which they live. Drawing on approximately 9,000 genetic samples from the Health and Retirement Study, we first investigate how socioeconomic status (SES) over the(More)
Recently mixed linear models are used to address the issue of “missing" heritability in traditional Genome-wide association studies (GWAS). The models assume that all single-nucleotide polymorphisms (SNPs) are associated with the phenotypes of interest. However, it is more common that only a small proportion of SNPs have significant effects on the(More)
Using data from the National Longitudinal Study of Adolescent to Adult Health (N = 1,254), the authors investigated whether marriage can foster desistance from delinquency and violence by moderating genetic effects. In contrast to existing gene-environment research that typically focuses on one or a few genetic polymorphisms, they extended a recently(More)
In this paper, we draw attention to one unique and valuable source of big data, genomic data, by demonstrating the opportunities they provide to social scientists. We discuss different types of large-scale genomic data and recent advances in statistical methods and computational infrastructure used to address challenges in managing and analyzing such data.(More)
OBJECTIVE Experience of stressful life events is associated with risk of depression. Yet many exposed individuals do not become depressed. A controversial hypothesis is that genetic factors influence vulnerability to depression following stress. This hypothesis is often tested with a "diathesis-stress" model, in which genes confer excess vulnerability. The(More)
OBJECTIVES We explored how gene-environment correlations can result in endogenous models, how natural experiments can protect against this threat, and if unbiased estimates from natural experiments are generalizable to other contexts. METHODS We compared a natural experiment, the College Roommate Study, which measured genes and behaviors of college(More)
Complex human traits are likely to be affected by many environmental and genetic factors, and the interactions among them. However, previous gene-environment interaction (G×E) studies have typically focused on one or only a few genetic variants at a time. To provide a broader view of G×E, this study examines the relationship between 403 genetic variants(More)
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