23 With the identification of a large number of genetic loci associated with human fat 24 distribution and its importance for metabolic health, the question arises as to what 25 the genetic drivers for discrete fat depot expansion might be. To date most studies 26 have focussed on conventional anthropometric measures such as waist-to-hip ratio 27 (WHR) adjusted for body mass index. We searched for genetic loci determining 28 discrete fat depots mass size using an exome-wide approach in 3 large cohorts.29 Here we report an exome-wide analysis of non-synonymous genetic variants in 30 17,212 participants in which regional fat masses were quantified using dual-energy 31 X-ray absorptiometry. The missense variant CCDC92 S70C, previously associated with 32 WHR, is associated specifically with reduced visceral and increased leg fat masses.33 Allele-specific expression analysis shows that the deleterious minor allele carrying 34 transcript also has a constitutively higher expression. In addition, we identify two 35 variants associated with the transcriptionally distinct fat depot arm fat (SPATA20 K422R 36 and UQCC1 R51Q ). SPATA20 K422R , a rare novel locus with a large effect size specific 37 to arm, and UQCC1 R51Q , a common variant exome-wide significant in arm but 38 showing similar trends in other subcutaneous fat depots. In terms of the 39 understanding of human fat distribution, these findings suggest distinct regulation of 40 discrete fat depot expansion.
42Author summary 43 Human fat storing tissues are heterogeneous and comprise functionally and 44 structurally distinct regional fat depots, the relative size of which appear to have 45 significant implications for health. Whilst it is known that inter-individual differences in 46 fat distribution have genetic drivers, studies to date have focussed on crude 3 47 anthropometric approximations of region fat masses rather than precise measures.48 Here we describe an exome-wide analysis of a large collection of men and women 49 who have undergone body scanning using dual-energy X-ray absorptiometry (DXA) 50 to better define regional fat masses and identify new genetic drivers for human fat 51 distribution. With this approach we identify three gene regions associated with 52 distinct fat depots which can help to explain the variation in fat distribution between 53 people and may lead to a better understanding of the depot specific fat 54 tissue expansion.4 56 57 58 Beyond associations with chronic disease and overall obesity, as defined by body-59 mass index (BMI), it is becoming increasingly apparent that there is an even stronger 60 relationship between body fat distribution and cardio-metabolic disease [1, 2]. For 61 example, Yusuf et al. [1] showed that waist-to-hip ratio (WHR) is a stronger predict of 62 myocardial infarction than BMI. To date, the overwhelming majority genome and 63 exome-wide association studies on fat distribution have focussed on waist and hip 64 circumference and WHR [3, 4]. While these measures are easy and cheap to obtain 65 on a large sca...