SES health gradients in late life: testing models of gene-environment interplay in an international twin consortium

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Inequalities in health outcomes are targeted by Healthy People 2020 as a public health priority. The social stratification of health is well documented, pervasive, and of growing concern because it appears to be increasing over time. Reducing these social class disparities will require greater understanding of how social class impacts health than we currently have. While most research focuses on individual-level socioeconomic status—defined as social status that accrues to occupational classification, education, and income—new research has begun to focus on the macro-economic environment. Further, although both genetic (G) and environmental (E) factors are known to contribute to the SES-health gradient, the mechanisms by which the two sets of factors combine to influence health outcomes (i.e., GE interplay) are poorly understood. Models of GE interplay differ in their environmental focus (disease-triggering effects of toxic environments vs. health- promoting benefits of favorable environments) and the expected genetic contribution to disease (maximized in adverse environments, in favorable environments, or at both extremes) Understanding whether high-SES preferentially promotes good health among a genetically selected subset of individuals (i.e., social enhancement), whether low-SES triggers poor health among a genetically vulnerable subset of individuals (i.e., diathesis-stress), or both, is essential for translating research in this area into effective prevention strategies. The consortium on Interplay of Genes and Environments across Multiple Studies (IGEMS) with 16 existing longitudinal twin studies in the U.S., Sweden, Denmark, Finland, and Australia is poised to evaluate these models. IGEMS includes more than 52,000 individual twins, with over 7000 identical twin pairs for within-pair difference models, and over 12,600 dizygotic twin pairs with nearly 4000 opposite sex pairs for sex-difference models. The sample spans a wide age range (15 to 103 years at intake) and includes a set of well-characterized longitudinal phenotypes, including harmonized measures of physical health (e.g., subjective health, chronic disease indicators, body mass index, lung function, blood pressure, activities of daily living, and grip strength), cognitive health (verbal ability, spatial ability, memory, and processing speed), and emotional health (depression, loneliness) as well as measures of multiple facets of SES (e.g., occupation, education, financial strain). In addition, a large subset of IGEMS participants has genome wide genotyping from which we have computed polygenic risk scores (PRS). We will use co-twin control/within pair models, quantitative genetic moderation, sex-limitation models, and PRS analyses to investigate specific mechanisms of the SES-health gradient at the individual level as well as the country and historical cohort level (e.g., country-level indices of social inequality). The proposed study reflects an innovative vision by the investigators who—rather than addressing the research questions through new data collection—successfully created a collaboration among 16 large international studies with relevant phenotypes, making this study highly cost-effective and efficient.