Jain Vardhmaan, Dabbs-Brown Amonae, Liu Chang, Hui Qin, Mehta Anurag, Wilson Peter W F, Quyyumi Arshed A, Sun Yan V
Division of Cardiology Emory University School of Medicine Atlanta GA USA.
Department of Epidemiology Emory University Rollins School of Public Health Atlanta GA USA.
J Am Heart Assoc. 2024 Dec 17;13(24):e034132. doi: 10.1161/JAHA.123.034132. Epub 2024 Dec 14.
Although sex differences in coronary artery disease (CAD) risk have been observed, little is known about the role of sex hormones in CAD genetics. Accounting for sex hormone levels may help identify CAD-risk loci and extend our knowledge of its genetic architecture.
A total of 365 662 individuals of European ancestry enrolled in the UK Biobank were considered. Genetic interaction of total testosterone, bioavailable testosterone, and SHBG (sex hormone-binding globulin) were evaluated. Gene-environment interactions in millions of samples software was used to conduct sex-stratified genome-wide interaction analysis with prevalent CAD as the outcome. Participant age at enrollment and principal components 1 to 10 were adjusted as covariates. We identified 45 loci in men and 8 loci in women that reached genome-wide significance ( < 5 × 10) for CAD. Ten of the loci identified (5 loci in both men and women) were through joint effects and would not have been picked up using a traditional genome-wide association study. Two of the joint effect loci in women were independently identified with significant single nucleotide polymorphism-total testosterone interactions.
This genome-wide gene-sex hormone interaction study identified genomic-risk loci that may contribute to the differential CAD risk between men and women, which otherwise would not have been discovered in a traditional genome-wide association study solely including marginal genetic effects.
尽管已观察到冠状动脉疾病(CAD)风险存在性别差异,但关于性激素在CAD遗传学中的作用知之甚少。考虑性激素水平可能有助于识别CAD风险位点,并扩展我们对其遗传结构的认识。
纳入了英国生物银行中365662名欧洲血统的个体。评估了总睾酮、生物可利用睾酮和性激素结合球蛋白(SHBG)的基因相互作用。使用数百万样本软件中的基因-环境相互作用进行以CAD患病率为结局的性别分层全基因组相互作用分析。将入组时的参与者年龄和主成分1至10作为协变量进行调整。我们在男性中鉴定出45个位点,在女性中鉴定出8个位点,这些位点在CAD方面达到全基因组显著性(<5×10)。所鉴定的10个位点(男性和女性各5个位点)是通过联合效应鉴定出来的,使用传统的全基因组关联研究无法发现这些位点。女性中的两个联合效应位点是通过显著的单核苷酸多态性-总睾酮相互作用独立鉴定出来的。
这项全基因组基因-性激素相互作用研究鉴定出了可能导致男性和女性CAD风险差异的基因组风险位点,而仅包括边际遗传效应的传统全基因组关联研究则无法发现这些位点。