Association of gene coding variation and resting metabolic rate in a multi-ethnic sample of children and adults

BMC Obes. 2017 Apr 5;4:12. doi: 10.1186/s40608-017-0145-5. eCollection 2017.

Abstract

Background: Resting metabolic rates (RMR) vary across individuals. Understanding the determinants of RMR could provide biological insight into obesity and its metabolic consequences such as type 2 diabetes and cardiovascular diseases.

Methods: The present study measured RMR using reference standard indirect calorimetry and evaluated genetic variations from an exome array in a sample of children and adults (N = 262) predominantly of African and European ancestry with a wide range of ages (10 - 67 years old) and body mass indices (BMI; 16.9 - 56.3 kg/m2 for adults, 15.1 - 40.6 kg/m2 for children).

Results: Single variant analysis for RMR identified suggestive loci on chromosomes 15 (rs74010762, TRPM1, p-value = 2.7 × 10-6), 1 (rs2358728 and rs2358729, SH3D21, p-values < 5.8x10-5), 17 (AX-82990792, DHX33, 5.5 × 10-5) and 5 (rs115795863 and rs35433829, C5orf33 and RANBP3L, p-values < 8.2 × 10-5). To evaluate the effect of low frequency variations with RMR, we performed gene-based association tests. Our most significant locus was SH3D21 (p-value 2.01 × 10-4), which also contained suggestive results from single-variant analyses. A further investigation of all variants within the reported genes for all obesity-related loci from the GWAS catalog found nominal evidence for association of body mass index (BMI- kg/m2)-associated loci with RMR, with the most significant p-value at rs35433754 (TNKS, p-value = 0.0017).

Conclusions: These nominal associations were robust to adjustment for BMI. The most significant variants were also evaluated using phenome-wide association to evaluate pleiotropy, and genetically predicted gene expression using the summary statistics implicated loci related to in obesity and body composition. These results merit further examination in larger cohorts of children and adults.

Keywords: Gene-based analysis; Genetic variants; Obesity; Predicted gene expression; Resting metabolic rate.