Genetics of Multisystem Aging

The present study aims to address how gene-environment interactions across lifestyle, socioeconomic and health-related factors predict levels and rates of declines across diverse domains of health, including multiple measures of cognitive function, functional ability, chronic diseases, and wellbeing. First, we will assess and characterize individual patterns of change across health domains. Second, we will search for common and specific sources of senescent change over time across health domains. Third, we will assess how genetic liabilities for medical traits and environmental exposures determine broad and specific sources of variation in intra- and inter-individual change across health domains. We will use phenotypic data from all the waves of the Health and Retirement Study (HRS) (1992–2024) covering the following domains: 1) demographic and socioeconomic variables, 2) lifestyle behaviors 3) cognitive function, 4) functional ability, 5) chronic diseases, and 6) wellbeing. We will use genetic data from the Health and Retirement Study (HRS) to compute polygenic risk scores (PRS) across socioeconomic and health domains, using Genomic Structural Equation Modelling (Genomic SEM) to integrate the most recent and large GWAS summary data available from published meta-analyses and biobanks. To analyze the data, we will fit univariate LGCM models for each individual indicator embedded into health domains 3 to 5. We will specify up to three latent factors: a) an intercept factor, representing levels, b) a linear change factor, and c) a quadratic change factor. Secondly, we will fit a series of multivariate LGCM models. We will start fitting an unconstrained associative LGCM to estimate correlations among the factors of levels and slopes across health indicators, identifying clusters of health indicators with shared underlying change processes. Thirdly, we will expand the multivariate LGCM models to include additive and non-additive exogenous covariates, covering genetic and environmental exposures and their interaction.

The present study aims to uncover how health-related genetic factors and environmental exposures interact, shaping heterogeneous trajectories of health in old age. We investigate pathways of aging across diverse domains of health, including multiple measures of cognitive function, functional ability, chronic diseases, and well-being, identifying common and specific sources of senescent change across health-related outcomes. A better understanding of genetic and environmental determinants of health trajectories is key to promoting health and well-being in old age.