Multiple genotype\u2013phenotype association study reveals intronic variant pair on SIDT2 associated with metabolic syndrome in a Korean population

Sanghoon Moon,Young Lee,Juyoung Lee,Sungho Won

doi:10.1186/s40246-018-0180-4

Sanghoon Moon, Young Lee + Show 2 more

Open Access

https://doi.org/10.1186/s40246-018-0180-4

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Abstract

BackgroundMetabolic syndrome is a risk factor for type 2 diabetes and cardiovascular disease. We identified common genetic variants that alter the risk for metabolic syndrome in the Korean population. To isolate these variants, we conducted a multiple-genotype and multiple-phenotype genome-wide association analysis using the family-based quasi-likelihood score (MFQLS) test. For this analysis, we used 7211 and 2838 genotyped study subjects for discovery and replication, respectively. We also performed a multiple-genotype and multiple-phenotype analysis of a gene-based single-nucleotide polymorphism (SNP) set.ResultsWe found an association between metabolic syndrome and an intronic SNP pair, rs7107152 and rs1242229, in SIDT2 gene at 11q23.3. Both SNPs correlate with the expression of SIDT2 and TAGLN, whose products promote insulin secretion and lipid metabolism, respectively. This SNP pair showed statistical significance at the replication stage.ConclusionsOur findings provide insight into an underlying mechanism that contributes to metabolic syndrome.

Highlights

Metabolic syndrome is a cluster of metabolic risk factors for cardiovascular disease and type 2 diabetes that are attributable to both genetic and environmental factors [1,2,3]
From the joint analysis of a single genotype and multiple phenotypes, we found that three single-nucleotide polymorphism (SNP) pairs in the respective genes SID1 transmembrane family member 2 (SIDT2), UBASH3B, and CUX2 were significant in the multi-SNP–multi-trait analysis but not significant in the single-SNP–multi-trait analysis
We considered six quantitative components of metabolic syndrome: systolic blood pressure (SBP), diastolic blood pressure (DBP), high-density lipoprotein (HDL), fasting plasma glucose (FPG), triglyceride, and waist circumference

Summary

Introduction

Metabolic syndrome is a cluster of metabolic risk factors for cardiovascular disease and type 2 diabetes that are attributable to both genetic and environmental factors [1,2,3]. Moon et al Human Genomics (2018) 12:48 tests and mitigates the multiple testing issues, resulting in increased statistical power [13, 14] This approach identifies genetic variants that have pleiotropic effects for metabolic syndrome and other diseases. We identified common genetic variants that alter the risk for metabolic syndrome in the Korean population. To isolate these variants, we conducted a multiple-genotype and multiple-phenotype genome-wide association analysis using the family-based quasi-likelihood score (MFQLS) test. We conducted a multiple-genotype and multiple-phenotype genome-wide association analysis using the family-based quasi-likelihood score (MFQLS) test For this analysis, we used 7211 and 2838 genotyped study subjects for discovery and replication, respectively. We performed a multiple-genotype and multiple-phenotype analysis of a gene-based single-nucleotide polymorphism (SNP) set

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