Repurposing large health insurance claims data to estimate genetic and environmental contributions in 560 phenotypes

We analysed a large health insurance dataset to assess the genetic and environmental contributions of 560 disease-related phenotypes in 56,396 twin pairs and 724,513 sibling pairs out of 44,859,462 individuals that live in the United States. We estimated the contribution of environmental risk factors (socioeconomic status (SES), air pollution and climate) in each phenotype. Mean heritability ( h 2 = 0.311) and shared environmental variance ( c 2 = 0.088) were higher than variance attributed to specific environmental factors such as zip-code-level SES (var SES = 0.002), daily air quality (var AQI = 0.0004), and average temperature (var temp = 0.001) overall, as well as for individual phenotypes. We found significant heritability and shared environment for a number of comorbidities ( h 2 = 0.433, c 2 = 0.241) and average monthly cost ( h 2 = 0.290, c 2 = 0.302). All results are available using our Claims Analysis of Twin Correlation and Heritability (CaTCH) web application. Analysis of a health insurance dataset comprising more than 44 million individuals allows for the estimation of genetic and environmental contributions in 560 phenotypes by using twins and sibling pairs.