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目的 评估中国成人2型糖尿病(type 2 diabetes mellitus, T2DM)多基因风险评分(polygenic risk score, PRS)联合传统危险因素对T2DM发病风险的预测能力。方法 利用“中国成人慢性病与营养监测(2015)”项目数据开展病例对照研究，其中包含2041例T2DM患者和1149例健康对照者。提取冻存白细胞DNA,并采用Illumina Asian Screening Array芯片对其进行基因分型检测以获得研究对象遗传信息。分别基于东亚人群和多种族全基因组关联研究(genome-wide association study, GWAS)数据构建PRS并进行预测性能比较。利用向前逐步法筛选T2DM相关风险因素，并联合预测性能更优的PRS构建回归模型，基于受试者工作曲线(receiver operation curve, ROC)评估比较单一模型与联合变量模型对T2DM发病风险的预测性能。结果 相较于基于东亚人群GWAS构建的PRS,基于多种族GWAS构建的PRS能为本研究人群的T2DM风险提供更可靠的遗传风险分层，且与空腹血糖/糖化血红蛋白存在正向关联。除遗传因素外，T2DM与多项传统危险因素显著相关，包括血脂指标、血压、城乡分布、教育水平及饮酒状况。单纯传统危险因素和单纯T2DM患者的PRS对T2DM预测能力的ROC曲线下面积(area under the curve, AUC)分别为0.656和0.666,而两者联合分析显示模型性能显著提升，AUC增至0.724。结论 根据覆盖广泛遗传信息的多种族GWAS构建的PRS与传统危险因素结合，可显著提升中国成人T2DM风险预测效能。
Abstract：OBJECTIVE To evaluate the predictive ability of a polygenic risk score(PRS) combined with traditional risk factors for type 2 diabetes mellitus(T2DM) in Chinese adults.METHODS Using data from the “China Adult Chronic Disease and Nutrition Surveillance(2015)” project, we conducted a case-control study comprising 2041 people with T2DM and 1149 healthy adults of same age as control group. Total DNA was extracted from cryopreserved leukocyte samples separated from blood, and genotyping was performed using the Illumina ASA platform. Two PRS models were constructed based on East Asian-specific and trans-ancestry genome-wide association study(GWAS) summary statistics, and their predictive performance was compared. T2DM-related risk factors were selected using forward stepwise regression. The better-performing PRS was then integrated with traditional risk factors into a combined prediction model. The receiver operation curve(ROC) was used to evaluate and compare the predictive performance of models containing traditional factors alone, PRS alone, and the combined model.RESULTS Our analysis revealed that the trans-ancestry GWAS-derived PRS provided more reliable genetic stratification for T2DM risk in this population compared to an East Asian model. Beyond genetic factors, multivariable analysis confirmed significant associations between T2DM incidence and several traditional risk factors, including lipid profiles, blood pressure, urban-rural distribution, education, and drinking status. While models containing only traditional risk factors or PRS alone showed moderate predictive capability(area under the curve(AUC)=0.656 and 0.666, respectively), their integration significantly enhanced performance, elevating the AUC to 0.724.CONCLUSION These findings demonstrate that incorporating a PRS derived from a trans-ancestry GWAS covering extensive SNPs alongside conventional risk factors substantially improves T2DM risk prediction in Chinese adults.
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基本信息:
DOI：10.19813/j.cnki.weishengyanjiu.2026.03.002
中图分类号:R587.1
引用信息:
[1]欧玲玲,卓勤,韩超,等.多基因风险评分联合传统危险因素评估中国成人2型糖尿病的发病风险[J].卫生研究,2026,55(03):365-374.DOI:10.19813/j.cnki.weishengyanjiu.2026.03.002.
基金信息:
国家财政项目(No.102393220020070000013)
2026-05-21
2026-05-21