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GENOME-WIDE INTERACTION WITH SELECTED TYPE 2 DIABETES LOCI REVEALS NOVEL LOCI FOR TYPE 2 DIABETES IN AFRICAN AMERICANS.

Citation
Keaton, J. M., et al. “Genome-Wide Interaction With Selected Type 2 Diabetes Loci Reveals Novel Loci For Type 2 Diabetes In African Americans.”. Pacific Symposium On Biocomputing. Pacific Symposium On Biocomputing, pp. 242-253.
Center UCSD-UCLA
Author Jacob M Keaton, Jacklyn N Hellwege, Maggie C Y Ng, Nicholette D Palmer, James S Pankow, Myriam Fornage, James G Wilson, Adolfo Correa, Laura J Rasmussen-Torvik, Jerome I Rotter, Yii-Der I Chen, Kent D Taylor, Stephen S Rich, Lynne E Wagenknecht, Barry I Freedman, Donald W Bowden
Abstract

Type 2 diabetes (T2D) is the result of metabolic defects in insulin secretion and insulin sensitivity, yet most T2D loci identified to date influence insulin secretion. We hypothesized that T2D loci, particularly those affecting insulin sensitivity, can be identified through interaction with known T2D loci implicated in insulin secretion. To test this hypothesis, single nucleotide polymorphisms (SNPs) nominally associated with acute insulin response to glucose (AIRg), a dynamic measure of first-phase insulin secretion, and previously associated with T2D in genome-wide association studies (GWAS) were identified in African Americans from the Insulin Resistance Atherosclerosis Family Study (IRASFS; n=492 subjects). These SNPs were tested for interaction, individually and jointly as a genetic risk score (GRS), using GWAS data from five cohorts (ARIC, CARDIA, JHS, MESA, WFSM; n=2,725 cases, 4,167 controls) with T2D as the outcome. In single variant analyses, suggestively significant (Pinteraction < 5×10-6) interactions were observed at several loci including DGKB (rs978989), CDK18 (rs12126276), CXCL12 (rs7921850), HCN1 (rs6895191), FAM98A (rs1900780), and MGMT (rs568530). Notable beta-cell GRS interactions included two SNPs at the DGKB locus (rs6976381; rs6962498). These data support the hypothesis that additional genetic factors contributing to T2D risk can be identified by interactions with insulin secretion loci.

Year of Publication
2017
Journal
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Volume
22
Number of Pages
242-253
Date Published
12/2017
ISSN Number
2335-6936
DOI
10.1142/9789813207813_0024
Alternate Journal
Pac Symp Biocomput
PMID
27896979
PMCID
PMC5146756
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