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Association of Gene Coding Variation and Resting Metabolic Rate in a Multi-ethnic Sample of Children and Adults

Overview
Journal BMC Obes
Publisher Biomed Central
Date 2017 Apr 19
PMID 28417008
Citations 5
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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 ( = 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/m for adults, 15.1 - 40.6 kg/m2 for children).

Results: Single variant analysis for RMR identified suggestive loci on chromosomes 15 (rs74010762, , -value = 2.7 × 10-6), 1 (rs2358728 and rs2358729, , -values < 5.8x10-5), 17 (AX-82990792, , 5.5 × 10-5) and 5 (rs115795863 and rs35433829, and , -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 (-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/m)-associated loci with RMR, with the most significant -value at rs35433754 (, -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.

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References
1.
Shefer G, Marcus Y, Stern N . Is obesity a brain disease?. Neurosci Biobehav Rev. 2013; 37(10 Pt 2):2489-503. DOI: 10.1016/j.neubiorev.2013.07.015. View

2.
Nakamura M, Sanuki R, Yasuma T, Onishi A, Nishiguchi K, Koike C . TRPM1 mutations are associated with the complete form of congenital stationary night blindness. Mol Vis. 2010; 16:425-37. PMC: 2838739. View

3.
Price A, Patterson N, Plenge R, Weinblatt M, Shadick N, Reich D . Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006; 38(8):904-9. DOI: 10.1038/ng1847. View

4.
Bosch D, Boonstra F, de Leeuw N, Pfundt R, Nillesen W, de Ligt J . Novel genetic causes for cerebral visual impairment. Eur J Hum Genet. 2015; 24(5):660-5. PMC: 4930090. DOI: 10.1038/ejhg.2015.186. View

5.
Csernus K, Pauler G, Erhardt E, Lanyi E, Molnar D . Effects of energy expenditure gene polymorphisms on obesity-related traits in obese children. Obes Res Clin Pract. 2014; 9(2):133-40. DOI: 10.1016/j.orcp.2014.06.001. View