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ABSTRACT: Context
Biological and translational insights from large-scale, array-based genetic studies of fat distribution, a key determinant of metabolic health, have been limited by the difficulty in linking predominantly noncoding variants to specific gene targets. Rare coding variant analyses provide greater confidence that a specific gene is involved, but do not necessarily indicate whether gain or loss of function (LoF) would be of most therapeutic benefit.Objective
This work aimed to identify genes/proteins involved in determining fat distribution.Methods
We combined the power of genome-wide analysis of array-based rare, nonsynonymous variants in 450 562 individuals in the UK Biobank with exome-sequence-based rare LoF gene burden testing in 184 246 individuals.Resul
SUBMITTER: Koprulu M
PROVIDER: S-EPMC8947777 | biostudies-literature | 2022 Mar
REPOSITORIES: biostudies-literature