Genome-Wide Association Study of the Metabolic Syndrome in UK Biobank

Metab Syndr Relat Disord. 2019 Dec;17(10):505-511. doi: 10.1089/met.2019.0070. Epub 2019 Oct 7.


Background: The metabolic syndrome (MetS) is a description of a clustering of cardiometabolic risk factors in the same individual. Previous genome-wide association studies (GWASs) have identified 29 independent genetic loci linked to MetS as a binary trait. This study used data from UK biobank to search for additional loci. Methods: Using data from 291,107 individuals in the UK biobank, a GWAS was performed versus the binary trait MetS (harmonized NCEP criteria). Results: In a GWAS of MetS (binary) we found 93 independent loci with P < 5 × 10-8, of which 80 were not identified in previous GWASs of MetS. However, the majority of those loci have previously been associated with one or more of the five MetS components. Of particular interest are the genes being related to MetS (binary) in this study, but not to any of the MetS components in past studies, such as WDR48, KLF14, NAADL1, GADD45G, and OR5R1, as well as the two loci that have been associated with all five MetS components in past studies, SNX10 and C5orf67. A pathway analysis of the 93 independent loci showed the immune system, transportation of small molecules, and metabolism to be enriched. Conclusion: This GWAS of the MetS in UK biobank identified several new loci being associated with MetS. Most of those have previously been found to be associated with different components of MetS, but several loci were found not previously linked to cardiometabolic disease.

Keywords: GWAS; UK biobank; gene; genetics; metabolic syndrome.

MeSH terms

  • Adult
  • Aged
  • Biological Specimen Banks / statistics & numerical data*
  • Female
  • Genetic Loci*
  • Genetic Predisposition to Disease
  • Genome-Wide Association Study*
  • Humans
  • Male
  • Metabolic Syndrome / epidemiology*
  • Metabolic Syndrome / genetics*
  • Middle Aged
  • Polymorphism, Single Nucleotide
  • Risk Factors
  • United Kingdom / epidemiology