A Genome-Wide Association Study of Metabolic Syndrome in the Taiwanese Population

Abstract

The purpose of this study was to investigate genetic factors associated with metabolic syndrome (MetS) by conducting a large-scale genome-wide association study (GWAS) in Taiwan, addressing the limited data on Asian populations compared to Western populations. Using data from the Taiwan Biobank, comprehensive clinical and genetic information from 107,230 Taiwanese individuals was analyzed. Genotyping data from the TWB1.0 and TWB2.0 chips, including over 650,000 single nucleotide polymorphisms (SNPs), were utilized. Genotype imputation using the 1000 Genomes Project was performed, resulting in more than 9 million SNPs. MetS was defined based on a modified version of the Adult Treatment Panel III criteria. Among all participants (mean age: 50 years), 23% met the MetS definition. GWAS analysis identified 549 SNPs significantly associated with MetS, collectively mapping to 10 genomic risk loci. Notable risk loci included rs1004558, rs3812316, rs326, rs4486200, rs2954038, rs10830963, rs662799, rs62033400, rs183130, and rs34342646. Gene-set analysis revealed 22 associated genes: CETP, LPL, APOA5, SIK3, ZPR1, APOC1, BUD13, MLXIPL, TOMM40, GCK, YKT6, RPS6KB1, FTO, VMP1, TUBD1, BCL7B, C19orf80 (ANGPTL8), SIDT2, SENP7, PAFAH1B2, DOCK6, and FOXA2. This study identified genomic risk loci for MetS in a large Taiwanese population through a comprehensive GWAS approach. These associations provide novel insights into the genetic basis of MetS and hold promise for the potential discovery of clinical biomarkers.

Keywords: GWAS; Taiwan biobank; diabetes mellitus; high-density lipoprotein cholesterol; hypertension; metabolic syndrome; single nucleotide polymorphism; triglyceride; waist circumference.

Figure 1

The Manhattan (upper panel) and Q–Q (lower panel) plots of genome-wide association study for metabolic syndrome. The Manhattan and Q–Q plots depict the genetic association results of metabolic syndrome phenotypes in a Taiwanese population. The Manhattan plot shows an observed p-value (on a -10 log-scale) for each single nucleotide polymorphism in relation to the chromosomal position. The green and red lines in the Manhattan plot represent genome-wide significance with a p-value of 5 × 10⁻⁸ and suggested significance with a p-value of 1 × 10⁻⁵, respectively. The Q-Q plot shows the observed p-value versus the expected p-value (on a -10 log-scale). The dotted line in the Q-Q plot represents the diagonal line (expected distribution line). Each point on the Q-Q plot corresponds to a specific quantile of the expected distribution (x-axis) and its corresponding observed p-value from the analysis (y-axis). Points aligning with the diagonal line indicate that observed p-values match the expected distribution, signifying appropriate calibration of the statistical test. Points above the diagonal line represent observed p-values that surpass what’s expected by chance under the null hypothesis. This suggests potential true associations or systematic biases in the data or analysis. The Manhattan plot in the present study reveals significant loci clustering on chromosomes 7, 8, 11, 16, and 19. The Q–Q plot exhibits a notable deviation from the expected null distribution, indicating an increased occurrence of lower p-values beyond chance alone.

Figure 2

The Manhattan plot of the gene-based test as computed by MAGMA based on genome-wide association study for metabolic syndrome summary statistics. The Manhattan plots display the gene-based test computed by MAGMA using summary statistics from genome-wide association study for metabolic syndrome in a Taiwanese population. The color dots show an observed p-value (on a -10 log-scale) for each gene in relation to the chromosomal position. The line on the plot represents gene-based significance with a p-value of 3.27 × 10⁻⁶.

Figure 3

Significant pathways (with a false discovery rate (FDR) of <0.05) that were associated with metabolic syndrome. The red dotted line represents that the threshold of the p-value after the Bonferroni correction.

Figure 4

An overview of the mechanisms related to MetS, linking our genetic associations to signal pathways.