Genetic Variants Associated with Supernormal Coronary Arteries

与冠状动脉异常增生相关的基因变异

阅读:3

Abstract

AIMS: Genetic and medical insights from studies on cardioprotective phenotypes aid the development of novel therapeutics. This study identified genetic variants associated with supernormal coronary arteries using genome-wide association study data and the corresponding genes based on expression quantitative trait loci (eQTL). METHODS: Study participants were selected from two Korean cohorts according to inclusion criteria that included males with high cardiovascular risk (Framingham risk score ≥ 14, 10-year risk ≥ 16%) but with normal coronary arteries (supernormal group) or coronary artery disease (control group). After screening 12,309 individuals, males meeting the supernormal phenotype (n=72) and age-matched controls (n=94) were enrolled. Genetic variants associated with the supernormal phenotype were identified using Firth's logistic regression, and eQTL was used to evaluate whether the identified variants influence the expression of particular genes in human tissues. RESULTS: Approximately 5 million autosomal variants were tested for association with the supernormal phenotype, and 10 independent loci suggestive of supernormal coronary arteries (p<5.0×10(-5)) were identified. The lead variants were seven intergenic single-nucleotide polymorphisms (SNPs), including one near PBX1, and three intronic SNPs, including one in PPFIA4. Of these variants or their proxies, rs9630089, rs6427989, and rs4984694 were associated with expression levels of SLIT1 and ARHGAP19, PPFIA4, and METTL26 in human tissues, respectively. These eQTL results supported their potential biological relevance. CONCLUSIONS: This study identified genetic variants and eQTL genes associated with supernormal coronary arteries. These results suggest candidate genes representing potential therapeutic targets for coronary artery disease.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。