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Dataset Information

Identification of female-specific genetic variants for metabolic syndrome and its component traits to improve the prediction of metabolic syndrome in females.


ABSTRACT:

Background

Metabolic syndrome (MetS), defined as a cluster of metabolic risk factors including dyslipidemia, insulin-resistance, and elevated blood pressure, has been known as partly heritable. MetS effects the lives of many people worldwide, yet females have been reported to be more vulnerable to this cluster of risks.

Methods

To elucidate genetic variants underlying MetS specifically in females, we performed a genome-wide association study (GWAS) for MetS as well as its component traits in a total of 9932 Korean female subjects (including 2276 MetS cases and 1692 controls). To facilitate the prediction of MetS in females, we calculated a genetic risk score (GRS) combining 14 SNPs detected in our GWA analyses specific for MetS.

Results

GWA analyses identified 14 mode

SUBMITTER: Kong S 

PROVIDER: S-EPMC6555714 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature