Abstract

In recent years, evidence has accumulated with regard to the ubiquity of pleiotropy across the genome, and shared genetic etiology is thought to play a large role in the widespread comorbidity among psychiatric disorders and risk factors. Recent methods investigate pleiotropy by estimating genetic correlation from genome-wide association summary statistics. More comprehensive estimates can be derived from the known relatedness between genetic relatives. Analysis of extended twin pedigree data allows for the estimation of genetic correlation for additive and non-additive genetic effects, as well as a shared household effect. Here we conduct a series of bivariate genetic analyses in extended twin pedigree data on lifetime major depressive disorder (MDD) and three indicators of lifestyle, namely smoking behavior, physical inactivity, and obesity, decomposing phenotypic variance and covariance into genetic and environmental components. We analyze lifetime MDD and lifestyle data in a large multigenerational dataset of 19,496 individuals by variance component analysis in the ‘Mendel’ software. We find genetic correlations for MDD and smoking behavior (rG = 0.249), physical inactivity (rG = 0.161), body-mass index (rG = 0.081), and obesity (rG = 0.155), which were primarily driven by additive genetic effects. These outcomes provide evidence in favor of a shared genetic etiology between MDD and the lifestyle factors.

Highlights

  • It is widely observed that multiple complex human traits tend to co-occur at the population-level

  • Evidence has accumulated with regard to the ubiquity of pleiotropy across the genome [5,6,7], and shared genetic etiology is thought to play a large role in the widespread comorbidity among psychiatric disorders [8,9]

  • We find genetic correlations, but environmental correlations of nearly zero. These findings suggest that insomuch as the associations between lifetime major depressive disorder (MDD) and lifestyle are explained by causal effects, they reflect a partially shared genetic etiology

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Summary

Introduction

It is widely observed that multiple complex human traits tend to co-occur at the population-level. Complex traits can have partly similar etiological processes, either environmental or genetic. The latter is defined as genetic pleiotropy [4], where one or multiple genes affect multiple traits, so that if the gene is segregating it causes simultaneous variation in the traits it affects. Evidence has accumulated with regard to the ubiquity of pleiotropy across the genome [5,6,7], and shared genetic etiology is thought to play a large role in the widespread comorbidity among psychiatric disorders [8,9]. Understanding genetic pleiotropy benefits our understanding of disease etiology, elucidating the relations among disorders as a function of sharing common genetic variant risk, as well as clarifying which traits and disorders are more distinct from one another [10]

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