Genetic Regulation of Adipose Gene Expression and Cardio-Metabolic Traits

Overview

Journal Am J Hum Genet

Publisher Cell Press

Specialty Genetics

Date 2017 Mar 5

PMID 28257690

Citations 108

Authors

Mete Civelek

Ying Wu

Calvin Pan

Chelsea K Raulerson

Arthur Ko

Aiqing He

Charles Tilford

Niyas K Saleem

Alena Stancakova

Laura J Scott

Christian Fuchsberger

Heather M Stringham

Anne U Jackson

Narisu Narisu

Peter S Chines

Kerrin S Small

Johanna Kuusisto

Brian W Parks

Paivi Pajukanta

Todd Kirchgessner

Francis S Collins

Peter S Gargalovic

Michael Boehnke

Markku Laakso

Karen L Mohlke

Aldons J Lusis

Affiliations

Soon will be listed here.

Abstract

Subcutaneous adipose tissue stores excess lipids and maintains energy balance. We performed expression quantitative trait locus (eQTL) analyses by using abdominal subcutaneous adipose tissue of 770 extensively phenotyped participants of the METSIM study. We identified cis-eQTLs for 12,400 genes at a 1% false-discovery rate. Among an approximately 680 known genome-wide association study (GWAS) loci for cardio-metabolic traits, we identified 140 coincident cis-eQTLs at 109 GWAS loci, including 93 eQTLs not previously described. At 49 of these 140 eQTLs, gene expression was nominally associated (p < 0.05) with levels of the GWAS trait. The size of our dataset enabled identification of five loci associated (p < 5 × 10) with at least five genes located >5 Mb away. These trans-eQTL signals confirmed and extended the previously reported KLF14-mediated network to 55 target genes, validated the CIITA regulation of class II MHC genes, and identified ZNF800 as a candidate master regulator. Finally, we observed similar expression-clinical trait correlations of genes associated with GWAS loci in both humans and a panel of genetically diverse mice. These results provide candidate genes for further investigation of their potential roles in adipose biology and in regulating cardio-metabolic traits.

Citing Articles

Systematic functional characterization of non-coding regulatory SNPs associated with central obesity.

Dong S, Duan Y, Zhu R, Jia Y, Chen J, Huang X Am J Hum Genet. 2025; 112(1):116-134.

PMID: 39753113 PMC: 11739881. DOI: 10.1016/j.ajhg.2024.11.005.

Adipose tissue eQTL meta-analysis highlights the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits.

Brotman S, El-Sayed Moustafa J, Guan L, Broadaway K, Wang D, Jackson A Nat Genet. 2025; 57(1):180-192.

PMID: 39747594 DOI: 10.1038/s41588-024-01982-6.

Exploring genetic signatures of obesity: hub genes and miRNAs unveiled through comprehensive bioinformatic analysis.

Tamkini M, Nourbakhsh M, Movahedi M, Golestani A J Diabetes Metab Disord. 2024; 23(2):2225-2232.

PMID: 39610518 PMC: 11599662. DOI: 10.1007/s40200-024-01490-8.

Genetics of cell-type-specific post-transcriptional gene regulation during human neurogenesis.

Aygun N, Vuong C, Krupa O, Mory J, Le B, Valone J Am J Hum Genet. 2024; 111(9):1877-1898.

PMID: 39168119 PMC: 11393701. DOI: 10.1016/j.ajhg.2024.07.015.

Metaboepigenetic regulation of gene expression in obesity and insulin resistance.

Das S, Comeau M, Langefeld C Metabolomics. 2024; 20(5):91.

PMID: 39096438 DOI: 10.1007/s11306-024-02159-2.

References

Albert F, Kruglyak L . The role of regulatory variation in complex traits and disease. Nat Rev Genet. 2015; 16(4):197-212. DOI: 10.1038/nrg3891. View

Walford G, Gustafsson S, Rybin D, Stancakova A, Chen H, Liu C . Genome-Wide Association Study of the Modified Stumvoll Insulin Sensitivity Index Identifies BCL2 and FAM19A2 as Novel Insulin Sensitivity Loci. Diabetes. 2016; 65(10):3200-11. PMC: 5033262. DOI: 10.2337/db16-0199. View

Soranzo N, Sanna S, Wheeler E, Gieger C, Radke D, Dupuis J . Common variants at 10 genomic loci influence hemoglobin A₁(C) levels via glycemic and nonglycemic pathways. Diabetes. 2010; 59(12):3229-39. PMC: 2992787. DOI: 10.2337/db10-0502. View

Coulet P, Gautheron D . Coupled reaction of immobilized aspartate aminotransferase and malate dehydrogenase. A plausible model for the cellular behaviour of these enzymes. Biochim Biophys Acta. 1985; 829(1):58-68. DOI: 10.1016/0167-4838(85)90068-8. View

Willer C, Schmidt E, Sengupta S, Peloso G, Gustafsson S, Kanoni S . Discovery and refinement of loci associated with lipid levels. Nat Genet. 2013; 45(11):1274-1283. PMC: 3838666. DOI: 10.1038/ng.2797. View

Grundberg E, Small K, Hedman A, Nica A, Buil A, Keildson S . Mapping cis- and trans-regulatory effects across multiple tissues in twins. Nat Genet. 2012; 44(10):1084-9. PMC: 3784328. DOI: 10.1038/ng.2394. View

Kooner J, Saleheen D, Sim X, Sehmi J, Zhang W, Frossard P . Genome-wide association study in individuals of South Asian ancestry identifies six new type 2 diabetes susceptibility loci. Nat Genet. 2011; 43(10):984-9. PMC: 3773920. DOI: 10.1038/ng.921. View

Yang J, Zaitlen N, Goddard M, Visscher P, Price A . Advantages and pitfalls in the application of mixed-model association methods. Nat Genet. 2014; 46(2):100-6. PMC: 3989144. DOI: 10.1038/ng.2876. View

Edwards S, Beesley J, French J, Dunning A . Beyond GWASs: illuminating the dark road from association to function. Am J Hum Genet. 2013; 93(5):779-97. PMC: 3824120. DOI: 10.1016/j.ajhg.2013.10.012. View

10.

Yang J, Benyamin B, McEvoy B, Gordon S, Henders A, Nyholt D . Common SNPs explain a large proportion of the heritability for human height. Nat Genet. 2010; 42(7):565-9. PMC: 3232052. DOI: 10.1038/ng.608. View

11.

Nikpay M, Goel A, Won H, Hall L, Willenborg C, Kanoni S . A comprehensive 1,000 Genomes-based genome-wide association meta-analysis of coronary artery disease. Nat Genet. 2015; 47(10):1121-1130. PMC: 4589895. DOI: 10.1038/ng.3396. View

12.

Brown M, Bonomi L, Ungerleider N, Zina J, Kimura F, Mukherjee A . Follistatin and follistatin like-3 differentially regulate adiposity and glucose homeostasis. Obesity (Silver Spring). 2011; 19(10):1940-9. PMC: 3179827. DOI: 10.1038/oby.2011.97. View

13.

Orozco L, Bennett B, Farber C, Ghazalpour A, Pan C, Che N . Unraveling inflammatory responses using systems genetics and gene-environment interactions in macrophages. Cell. 2012; 151(3):658-70. PMC: 3513387. DOI: 10.1016/j.cell.2012.08.043. View

14.

Zhang X, Johnson A, Hendricks A, Hwang S, Tanriverdi K, Ganesh S . Genetic associations with expression for genes implicated in GWAS studies for atherosclerotic cardiovascular disease and blood phenotypes. Hum Mol Genet. 2013; 23(3):782-95. PMC: 3900869. DOI: 10.1093/hmg/ddt461. View

15.

Matsuda M, DeFronzo R . Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care. 1999; 22(9):1462-70. DOI: 10.2337/diacare.22.9.1462. View

16.

Zhong H, Beaulaurier J, Lum P, Molony C, Yang X, MacNeil D . Liver and adipose expression associated SNPs are enriched for association to type 2 diabetes. PLoS Genet. 2010; 6(5):e1000932. PMC: 2865508. DOI: 10.1371/journal.pgen.1000932. View

17.

Lippert C, Listgarten J, Liu Y, Kadie C, Davidson R, Heckerman D . FaST linear mixed models for genome-wide association studies. Nat Methods. 2011; 8(10):833-5. DOI: 10.1038/nmeth.1681. View

18.

Guernsey D, Jiang H, Campagna D, Evans S, Ferguson M, Kellogg M . Mutations in mitochondrial carrier family gene SLC25A38 cause nonsyndromic autosomal recessive congenital sideroblastic anemia. Nat Genet. 2009; 41(6):651-3. DOI: 10.1038/ng.359. View

19.

Krzywinski M, Schein J, Birol I, Connors J, Gascoyne R, Horsman D . Circos: an information aesthetic for comparative genomics. Genome Res. 2009; 19(9):1639-45. PMC: 2752132. DOI: 10.1101/gr.092759.109. View

20.

Emilsson V, Thorleifsson G, Zhang B, Leonardson A, Zink F, Zhu J . Genetics of gene expression and its effect on disease. Nature. 2008; 452(7186):423-8. DOI: 10.1038/nature06758. View