Uncovering the multivariate genetic architecture of frailty with genomic structural equation modeling.

Abstract

Frailty is a multifaceted clinical state associated with accelerated aging and adverse health outcomes. Informed etiological models of frailty hold promise for producing widespread health improvements across the aging population. Frailty is currently measured using aggregate scores, which obscure etiological pathways that are only relevant to subcomponents of frailty. Here we perform a multivariate genome-wide association study of the latent genetic architecture between 30 frailty deficits, which identifies 408 genomic risk loci. Our model includes a general factor of genetic overlap across all deficits, plus six new factors indexing a shared genetic signal across specific groups of deficits. We demonstrate the added clinical and etiological value of the six factors, including predicting frailty in external datasets, highlighting divergent genetic correlations with clinically relevant outcomes and uncovering unique underlying biology linked to aging. We show that nuanced models of frailty are key to understanding its causes and how it relates to worse health.