A joint view on genetic variants for adiposity differentiates subtypes with distinct metabolic implications

Thomas W Winkler,Zoltán Kutalik,Martina Zimmermann,Simon Höllerer,Ruth Jf Loos,Iris M Heid,Felix Günther

doi:10.1038/s41467-018-04124-9

Abstract

The problem of the genetics of related phenotypes is often addressed by analyzing adjusted-model traits, but such traits warrant cautious interpretation. Here, we adopt a joint view of adiposity traits in ~322,154 subjects (GIANT consortium). We classify 159 signals associated with body mass index (BMI), waist-to-hip ratio (WHR), or WHR adjusted for BMI (WHRadjBMI) at P < 5 × 10−8, into four classes based on the direction of their effects on BMI and WHR. Our classes help differentiate adiposity genetics with respect to anthropometry, fat depots, and metabolic health. Class-specific Mendelian randomization reveals that variants associated with both WHR-decrease and BMI increase are linked to metabolically rather favorable adiposity through beneficial hip fat. Class-specific enrichment analyses implicate digestive systems as a pathway in adiposity genetics. Our results demonstrate that WHRadjBMI variants capture relevant effects of “unexpected fat distribution given the BMI” and that a joint view of the genetics underlying related phenotypes can inform on important biology.

Highlights

The problem of the genetics of related phenotypes is often addressed by analyzing adjustedmodel traits, but such traits warrant cautious interpretation
We found a substantial overlap of waist-to-hip ratio (WHR)-derived variants with body mass index (BMI)- or WHRadjBMI-derived variants, with four being exclusive to the WHR-scan, but no overlap between BMI- and WHRadjBMI-derived variants (Fig. 1, Supplementary Data 1)
Our investigation demonstrated that a classification of genetic adiposity variants based on their co-association with BMI and WHR characterized distinct anthropometry and different modes of fat deposition

Summary

Introduction

The problem of the genetics of related phenotypes is often addressed by analyzing adjustedmodel traits, but such traits warrant cautious interpretation. These adjusted-model traits warrant cautious interpretation: as Aschard and colleagues pointed out, genome scans for traits adjusted for heritable covariates reveal genetic factors for the phenotype Y, and those of the covariate Z to an extent that depends on their correlation[1] We exemplify this issue on adiposity traits that were utilized by Aschard and colleagues[1]: BMI and WHR are correlated and capture two aspects of adiposity, overall fat mass, and fat distribution, respectively. Aschard and colleagues pointed out that some of the WHRadjBMI lead variants were not completely independent of BMI and showed some effect on BMI in the unexpected direction (WHR increasing allele decreased BMI) This is due to the fact that the genetic effect estimate for WHRadjBMI, bWHRadjBMI, is related to the estimate for WHR, bWHR, and the estimate for BMI, bBMI, by bWHRadjBMI = bWHR – r * bBMI, with r being the observational correlation between BMI and WHR in the analyzed study[1]. The joint view helps resolve some of the issues that derive from conducting GWAS on adjusted-model traits

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Methods

Results

Conclusion