Pleiotropic genes for metabolic syndrome and inflammation
File(s)
Accepted version
Author(s)
Type
Journal Article
Abstract
Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factors, genetic variants exist that influence MetS and inflammatory markers forming a predisposing MetS genetic network. To test this hypothesis a staged approach was undertaken. (a) We analyzed 17 metabolic and inflammatory traits in more than 85,500 participants from 14 large epidemiological studies within the Cross Consortia Pleiotropy Group. Individuals classified with MetS (NCEP definition), versus those without, showed on average significantly different levels for most inflammatory markers studied. (b) Paired average correlations between 8 metabolic traits and 9 inflammatory markers from the same studies as above, estimated with two methods, and factor analyses on large simulated data, helped in identifying 8 combinations of traits for follow-up in meta-analyses, out of 130,305 possible combinations between metabolic traits and inflammatory markers studied. (c) We performed correlated meta-analyses for 8 metabolic traits and 6 inflammatory markers by using existing GWAS published genetic summary results, with about 2.5 million SNPs from twelve predominantly largest GWAS consortia. These analyses yielded 130 unique SNPs/genes with pleiotropic associations (a SNP/gene associating at least one metabolic trait and one inflammatory marker). Of them twenty-five variants (seven loci newly reported) are proposed as MetS candidates. They map to genes MACF1, KIAA0754, GCKR, GRB14, COBLL1, LOC646736-IRS1, SLC39A8, NELFE, SKIV2L, STK19, TFAP2B, BAZ1B, BCL7B, TBL2, MLXIPL, LPL, TRIB1, ATXN2, HECTD4, PTPN11, ZNF664, PDXDC1, FTO, MC4R and TOMM40. Based on large data evidence, we conclude that inflammation is a feature of MetS and several gene variants show pleiotropic genetic associations across phenotypes and might explain a part of MetS correlated genetic architecture. These findings warrant further functional investigation.
Date Issued
2014-05-09
Date Acceptance
2014-04-26
Citation
Molecular Genetics and Metabolism, 2014, 112 (4), pp.317-338
ISSN
1096-7206
Publisher
Elsevier
Start Page
317
End Page
338
Journal / Book Title
Molecular Genetics and Metabolism
Volume
112
Issue
4
Copyright Statement
© 2014 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Subjects
Science & Technology
Life Sciences & Biomedicine
Endocrinology & Metabolism
Genetics & Heredity
Medicine, Research & Experimental
Research & Experimental Medicine
Metabolic syndrome
Inflammatory markers
Pleiotropic associations
Meta-analysis
Regulome
GENOME-WIDE ASSOCIATION
DENSITY-LIPOPROTEIN CHOLESTEROL
CORONARY-ARTERY-DISEASE
DIABETES SUSCEPTIBILITY LOCI
C-REACTIVE PROTEIN
NF-KAPPA-B
INSULIN-RESISTANCE
BLOOD-PRESSURE
CARDIOVASCULAR-DISEASE
CIRCULATING ADIPONECTIN
Biomarkers
Computational Biology
Gene Regulatory Networks
Genetic Pleiotropy
Genetic Predisposition to Disease
Genome-Wide Association Study
Humans
Inflammation
Meta-Analysis as Topic
Metabolic Syndrome X
Phenotype
Quantitative Trait, Heritable
Cross Consortia Pleiotropy Group
Cohorts for Heart and
Aging Research in Genetic Epidemiology
Genetic Investigation of Anthropometric Traits Consortium
Global Lipids Genetics Consortium
Meta-Analyses of Glucose
Insulin-related traits Consortium
Global BPgen Consortium
ADIPOGen Consortium
Women's Genome Health Study
Howard University Family Study
1103 Clinical Sciences
Publication Status
Published