Dabbs-Brown Amonae, Liu Chang, Hui Qin, Wilson Peter W F, Zhou Jin J, Gwinn Marta, Sun Yan V
Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, Georgia, United States of America.
Division of Cardiology, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, United States of America.
PLoS Genet. 2025 Sep 2;21(9):e1011470. doi: 10.1371/journal.pgen.1011470. eCollection 2025 Sep.
Type 2 diabetes affects an increasing number of people worldwide. Although genome-wide association studies (GWAS) of type 2 diabetes have identified hundreds of loci, their interactions with other risk factors aren't well understood. We investigated genetic interactions with three sex hormones (total testosterone, bioavailable testosterone, and sex hormone binding globulin (SHBG)) to identify additional type 2 diabetes-related loci that were undetected in traditional GWAS.
The study population consisted of white European UK Biobank participants. Individuals with type 1 diabetes were excluded. We examined sex-stratified interactions of polygenic risk score (PRS) for type 2 diabetes with sex hormone levels. We analyzed sex-stratified, genome-wide SNP × sex hormone interactions, adjusting for age and the top ten principal ancestry components.
We found significant (P < 0.05) interactions for each of the sex hormones with PRS in both men and women, with the most significant being between SHBG and PRS in women (OR 0.88; 95% CI: 0.85-0.90; P = 1.09E-18). We identified 3 SNP × sex hormone interactions in men and 14 in women that achieved genome-wide significance (GWS; P < 5 × 10-8). Applying a 2-degree of freedom test, we identified GWS loci (10 in men and 23 in women) that were not GWS when testing marginal genetic effects alone.
Including interaction terms in GWAS may identify additional risk loci and improve the understanding of genetic architecture for type 2 diabetes. Different genetic interactions with sex hormones in men and women emphasize the importance of sex-stratified analysis in sex differential diseases.
2型糖尿病在全球影响着越来越多的人。尽管2型糖尿病的全基因组关联研究（GWAS）已经确定了数百个基因座，但它们与其他风险因素的相互作用尚未得到很好的理解。我们研究了与三种性激素（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，以识别在传统GWAS中未检测到的其他2型糖尿病相关基因座。
研究人群包括欧洲白人英国生物银行参与者。排除1型糖尿病患者。我们检查了2型糖尿病多基因风险评分（PRS）与性激素水平的性别分层相互作用。我们分析了性别分层的全基因组单核苷酸多态性（SNP）×性激素相互作用，并对年龄和前十个主要祖先成分进行了调整。
我们发现男性和女性中每种性激素与PRS之间均存在显著（P < 0.05）相互作用，其中女性中SHBG与PRS之间的相互作用最为显著（OR 0.88；95%CI：0.85 - 0.90；P = 1.09E - 18）。我们在男性中鉴定出3个SNP×性激素相互作用，在女性中鉴定出14个达到全基因组显著性（GWS；P < 5×10 - 8）的相互作用。应用二自由度检验，我们鉴定出单独测试边际遗传效应时未达到GWS的GWS基因座（男性10个，女性23个）。
在GWAS中纳入相互作用项可能会识别出额外的风险基因座，并增进对2型糖尿病遗传结构的理解。男性和女性与性激素的不同遗传相互作用强调了在性别差异疾病中进行性别分层分析的重要性。
