Variants in KCNQ1 are associated with susceptibility to type 2 diabetes mellitus

Abstract

We carried out a multistage genome-wide association study of type 2 diabetes mellitus in Japanese individuals, with a total of 1,612 cases and 1,424 controls and 100,000 SNPs. The most significant association was obtained with SNPs in KCNQ1, and dense mapping within the gene revealed that rs2237892 in intron 15 showed the lowest Pvalue (6.7 x 10(-13), odds ratio (OR) = 1.49). The association of KCNQ1 with type 2 diabetes was replicated in populations of Korean, Chinese and European ancestry as well as in two independent Japanese populations, and meta-analysis with a total of 19,930 individuals (9,569 cases and 10,361 controls) yielded a P value of 1.7 x 10(-42) (OR = 1.40; 95% CI = 1.34-1.47) for rs2237892. Among control subjects, the risk allele of this polymorphism was associated with impairment of insulin secretion according to the homeostasis model assessment of beta-cell function or the corrected insulin response. Our data thus implicate KCNQ1 as a diabetes susceptibility gene in groups of different ancestries.

Efficiency of trans-ethnic genome-wide meta-analysis and fine-mapping

“…The KCNQ1 association with Type 2 diabetes (T2D) is a classic example where the initial discovery was made in East Asians and subsequently validated in Caucasians, as the risk alleles of the associated singlenucleotide polymorphisms (SNPs) were at higher frequencies in East Asian populations than in Europeans. 10,11 The next phase in genomewide studies will be to meta-analyze as many of the available GWAS as possible, to increase sample sizes for locating the smaller effects that will be generally present in most human populations, as well as to leverage on the differential allele frequency spectrum to identify loci like KCNQ1. However, this means such meta-analyses will take place across genetically diverse populations, which presents additional challenges owing to the use of tagging SNPs in GWAS.…”

The pursuit of genome-wide association studies: where are we now?

“…Interestingly, both studies also found KCNQ1 to be associated with the trait; this is because the gene was also associated with type-2 diabetes (T2D). 37,38 This finding further revealed the pleiotropic effect of gene or genetic locus influences on multiple traits. Prolongation of the QT interval increases the risk of ventricular arrhythmias and sudden cardiac death, and this index also predicts cardiovascular mortality among healthy individuals.…”

“…The finding of differences in association with risk alleles in different populations is not limited to PD, as the finding of association of KCNQ1 with T2D in the Japanese but not in the European population illustrates the same scenario. 37,38 The success of finding novel Parkinson's risk alleles is at least attributed to the well-powered GWAS where both the studies have genotyped a much larger sample size of several thousands in the initial screening and have also achieved robust replication, compared with the earlier GWAS of PD.…”

Association between type 2 diabetes genetic susceptibility loci and visceral and subcutaneous fat area as determined by computed tomography

“…Risk alleles refer to the type 2 diabetesassociated alleles, according to previous reports. [26][27][28][29][30][31][32][33] Multiple linear regression analyses were performed to test the independent effects of the risk alleles on BMI, VFA and SFA by taking into account the effects of other variables (i.e., age and gender) that were assumed to be independent of the effect of each SNP. The values of BMI, VFA and SFA were logarithmically transformed before multiple linear regression analysis.…”

“…We selected 23 SNPs identified as susceptibility loci for type 2 diabetes by GWAS [26][27][28][29][30][31][32][33] and constructed Invader probes (Third Wave Technologies, Madison, WI, USA) for the following SNPs: notch 2 (NOTCH2) rs10923931, thyroid adenoma-associated (THADA) rs7578597, peroxisome proliferator-activated receptor g (PPARG) rs1801282, ADAM metallopeptidase with thrombospondin type 1 motif, 9 (ADAMTS9) rs4607103, insulinlike growth factor 2 mRNA-binding protein 2 (IGF2BP2) rs1470579, vascular endothelial growth factor A (VEGFA) rs9472138, JAZF zinc finger 1 (JAZF1) rs864745, cyclin-dependent kinase inhibitor 2A and cyclin-dependent kinase inhibitor 2B (CDKN2A/CDKN2B) rs564398 and rs10811661, hematopoietically expressed homeobox (HHEX) rs1111875 and rs5015480, transcription factor 7-like 2 (TCF7L2) rs7901695, potassium voltage-gated channel, KQT-like subfamily, member 1 (KCNQ1) rs2237892, potassium inwardly-rectifying channel, subfamily J, member 11 (KCNJ11) rs5215 and rs5219, exostosin 2 (EXT2) rs1113132, rs11037909, and rs3740878, melatonin receptor 1B (MTNR1B) rs10830963, dermcidin (DCD) rs1153188, tetraspanin 8/leucine-rich repeat containing G protein-coupled receptor 5 (TSPAN8/LGR5) rs7961581, and FTO rs8050136 and rs9939609. The SNPs were genotyped using Invader assays as previously described.…”