Login / Signup

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

Chih-Yi HoJia-In LeeShu-Pin HuangSzu-Chia ChenJiun-Hung Geng
Published in: Nutrients (2023)
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.
Keyphrases
  • genome wide
  • genome wide association study
  • metabolic syndrome
  • copy number
  • dna methylation
  • big data
  • healthcare
  • south africa
  • insulin resistance
  • risk assessment
  • machine learning
  • young adults
  • single cell