Regional fat depot masses are influenced by protein-coding gene variants

Abstract

With the identification of a large number of genetic loci associated with human fat distribution and its importance for metabolic health, the question arises as to what the genetic drivers for discrete fat depot expansion might be. To date most studies have focussed on conventional anthropometric measures such as waist-to-hip ratio (WHR) adjusted for body mass index. We searched for genetic loci determining discrete fat depots mass size using an exome-wide approach in 3 large cohorts. Here we report an exome-wide analysis of non-synonymous genetic variants in 17,212 participants in which regional fat masses were quantified using dual-energy X-ray absorptiometry. The missense variant CCDC92S70C, previously associated with WHR, is associated specifically with reduced visceral and increased leg fat masses. Allele-specific expression analysis shows that the deleterious minor allele carrying transcript also has a constitutively higher expression. In addition, we identify two variants associated with the transcriptionally distinct fat depot arm fat (SPATA20K422R and UQCC1R51Q). SPATA20K422R, a rare novel locus with a large effect size specific to arm, and UQCC1R51Q, a common variant exome-wide significant in arm but showing similar trends in other subcutaneous fat depots. In terms of the understanding of human fat distribution, these findings suggest distinct regulation of discrete fat depot expansion. Author summaryHuman fat storing tissues are heterogeneous and comprise functionally and structurally distinct regional fat depots, the relative size of which appear to have significant implications for health. Whilst it is known that inter-individual differences in fat distribution have genetic drivers, studies to date have focussed on crude anthropometric approximations of region fat masses rather than precise measures. Here we describe an exome-wide analysis of a large collection of men and women who have undergone body scanning using dual-energy X-ray absorptiometry (DXA) to better define regional fat masses and identify new genetic drivers for human fat distribution. With this approach we identify three gene regions associated with distinct fat depots which can help to explain the variation in fat distribution between people and may lead to a better understanding of the depot specific fat tissue expansion.