Genome-wide association study of metabolic syndrome in Korean populations.
Seung-Won OhJong-Eun LeeEunsoon ShinHyuktae KwonEun Kyung ChoeSu-Yeon ChoiHwanseok RheeSeung Ho ChoiPublished in: PloS one (2020)
Metabolic syndrome (MetS) which is caused by obesity and insulin resistance, is well known for its predictive capability for the risk of type 2 diabetes mellitus and cardiovascular disease. The development of MetS is associated with multiple genetic factors, environmental factors and lifestyle. We performed a genome-wide association study to identify single-nucleotide polymorphism (SNP) related to MetS in large Korean population based samples of 1,362 subjects with MetS and 6,061 controls using the Axiom® Korean Biobank Array 1.0. We replicated the data in another sample including 502 subjects with MetS and 1,751 controls. After adjusting for age and sex, rs662799 located in the APOA5 gene were significantly associated with MetS. 15 SNPs in GCKR, C2orf16, APOA5, ZPR1, and BUD13 were associated with high triglyceride (TG). 14 SNPs in APOA5, ALDH1A2, LIPC, HERPUD1, and CETP, and 2 SNPs in MTNR1B were associated with low high density lipoprotein cholesterol (HDL-C) and high fasting blood glucose respectively. Among these SNPs, 6 TG SNPs: rs1260326, rs1260333, rs1919127, rs964184, rs2075295 and rs1558861 and 11 HDL-C SNPs: rs4775041, rs10468017, rs1800588, rs72786786, rs173539, rs247616, rs247617, rs3764261, rs4783961, rs708272, and rs7499892 were first discovered in Koreans. Additional research is needed to confirm these 17 novel SNPs in Korean population.
Keyphrases
- metabolic syndrome
- insulin resistance
- genome wide
- cardiovascular disease
- blood glucose
- type diabetes
- adipose tissue
- coronary artery disease
- genome wide association study
- weight loss
- machine learning
- high resolution
- high fat diet
- cardiovascular events
- single cell
- high throughput
- big data
- high density
- genome wide association