BACKGROUND: Genes influencing resting metabolic rate (RMR) and respiratory quotient (RQ) represent candidate genes for obesity, type 2 diabetes, and the metabolic syndrome because of the involvement of these traits in energy balance and substrate oxidation. OBJECTIVE: We conducted a genome-wide scan for quantitative trait loci (QTL) contributing to the variability in RMR and RQ. DESIGN: Regression-based and variance components-based genome-wide autosomal scans on RMR and RQ phenotypes, obtained from indirect calorimetry, were performed in 169 families ascertained via an obese proband or from the general population. RESULTS: We found evidence for linkage to RMR on chromosomes 3q26.1 (lod = 2.74), 1q21.2 (2.44), and 22q12.3 (1.33). QTL influencing RQ were found on chromosomes 12q13 (1.65) and 14q22 (1.83) when the analyses were performed in all families. Considerable locus heterogeneity within this population was suggested because most of the families were unlinked to any one quantitative trait locus. Significant associations between traits and linked microsatellites were detected within the linked, informative subsets. CONCLUSIONS: We found several new QTL for energy metabolism, but the QTL on 1q may be a replication of the one reported in Pima Indians. All 3 RMR linkages overlapped regions previously linked to the metabolic syndrome or its components, and the significant association between RMR and the metabolic syndrome in the present cohort reinforces this relation. We conclude that considerable locus heterogeneity exists even within populations, which should be taken into account when considering candidate gene studies of energy metabolism phenotypes and other complex traits.
BACKGROUND: Genes influencing resting metabolic rate (RMR) and respiratory quotient (RQ) represent candidate genes for obesity, type 2 diabetes, and the metabolic syndrome because of the involvement of these traits in energy balance and substrate oxidation. OBJECTIVE: We conducted a genome-wide scan for quantitative trait loci (QTL) contributing to the variability in RMR and RQ. DESIGN: Regression-based and variance components-based genome-wide autosomal scans on RMR and RQ phenotypes, obtained from indirect calorimetry, were performed in 169 families ascertained via an obese proband or from the general population. RESULTS: We found evidence for linkage to RMR on chromosomes 3q26.1 (lod = 2.74), 1q21.2 (2.44), and 22q12.3 (1.33). QTL influencing RQ were found on chromosomes 12q13 (1.65) and 14q22 (1.83) when the analyses were performed in all families. Considerable locus heterogeneity within this population was suggested because most of the families were unlinked to any one quantitative trait locus. Significant associations between traits and linked microsatellites were detected within the linked, informative subsets. CONCLUSIONS: We found several new QTL for energy metabolism, but the QTL on 1q may be a replication of the one reported in Pima Indians. All 3 RMR linkages overlapped regions previously linked to the metabolic syndrome or its components, and the significant association between RMR and the metabolic syndrome in the present cohort reinforces this relation. We conclude that considerable locus heterogeneity exists even within populations, which should be taken into account when considering candidate gene studies of energy metabolism phenotypes and other complex traits.
Authors: Gregory J Tranah; Ernest T Lam; Shana M Katzman; Michael A Nalls; Yiqiang Zhao; Daniel S Evans; Jennifer S Yokoyama; Ludmila Pawlikowska; Pui-Yan Kwok; Sean Mooney; Stephen Kritchevsky; Bret H Goodpaster; Anne B Newman; Tamara B Harris; Todd M Manini; Steven R Cummings Journal: Biochim Biophys Acta Date: 2012-05-31
Authors: Claudia H T Tam; Vincent K L Lam; Wing-Yee So; Ronald C W Ma; Juliana C N Chan; Maggie C Y Ng Journal: BMC Genet Date: 2010-02-24 Impact factor: 2.797
Authors: Madaniah Zakari; Musaad Alsahly; Lauren G Koch; Steven L Britton; Laxmansa C Katwa; Robert M Lust Journal: Front Cardiovasc Med Date: 2018-11-27
Authors: Paolo Piaggi; Çiğdem Köroğlu; Anup K Nair; Jeff Sutherland; Yunhua L Muller; Pankaj Kumar; Wen-Chi Hsueh; Sayuko Kobes; Alan R Shuldiner; Hye In Kim; Nehal Gosalia; Cristopher V Van Hout; Marcus Jones; William C Knowler; Jonathan Krakoff; Robert L Hanson; Clifton Bogardus; Leslie J Baier Journal: J Clin Endocrinol Metab Date: 2020-11-01 Impact factor: 5.958