Yu Chenglong, Zhou Zhen, Neumann Johannes T, Lin Tian, Robb Catherine, Fransquet Peter, McNeil John J, Wray Naomi R, Zoungas Sophia, Lacaze Paul
School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
Department of Cardiology, University Heart & Vascular Center (UHZ), Hamburg, Germany.
Diabetes Obes Metab. 2025 Sep;27(9):5259-5268. doi: 10.1111/dom.16579. Epub 2025 Jul 2.
The utility of a polygenic score (PGS) for type 2 diabetes (T2D) has been demonstrated in the general adult population. However, while previous studies have included older adults within broader age ranges, the performance of PGS specifically in older individuals aged ≥70 years remains unclear. We aimed to evaluate the predictive utility of a PGS in an older cohort.
We derived a PGS in 12 174 Australian participants aged ≥70 years from the ASPREE trial, with a median follow-up of 4.6 years. T2D was defined by self-report, commencement of glucose-lowering medication, or a fasting plasma glucose of ≥7.0 mmol/L. Multivariable logistic and Cox models examined associations between the PGS and baseline and incident T2D, adjusting for clinical risk factors. Risk prediction was evaluated using area under the curve (AUC), C-index, and net reclassification improvement (NRI).
At baseline, 1150 (9.4%) participants had prevalent T2D. During follow-up, an additional 590 (4.8%) developed incident T2D. Per standard deviation, the PGS was significantly associated with baseline (odds ratio: 2.39 [95% CI: 2.19-2.61]) and incident (hazard ratio: 1.55 [1.40-1.71]) T2D. The PGS improved prediction over the clinical risk factors, increasing the AUC from 0.70 to 0.79, and C-index from 0.67 to 0.71 (both p < 0.001). Adding the PGS to a clinical risk model resulted in NRI of 0.63 [0.57-0.71] for baseline T2D and 0.42 [0.30-0.51] for incident T2D within 5 years.
The PGS significantly enhances T2D risk prediction in older adults, supporting its potential as a clinical tool for risk stratification.
多基因评分（PGS）对2型糖尿病（T2D）的预测效用已在一般成年人群中得到证实。然而，尽管先前的研究纳入了年龄范围更广的老年人，但PGS在年龄≥70岁的老年人中的表现仍不明确。我们旨在评估PGS在老年队列中的预测效用。
我们从ASPREE试验中12174名年龄≥70岁的澳大利亚参与者中得出PGS，中位随访时间为4.6年。T2D通过自我报告、开始使用降糖药物或空腹血糖≥7.0 mmol/L来定义。多变量逻辑回归和Cox模型检验了PGS与基线和新发T2D之间的关联，并对临床风险因素进行了调整。使用曲线下面积（AUC）、C指数和净重新分类改善（NRI）评估风险预测。
在基线时，1150名（9.4%）参与者患有T2D。在随访期间，又有590名（4.8%）发生了新发T2D。每增加一个标准差，PGS与基线T2D（优势比：2.39 [95% CI：2.19 - 2.61]）和新发T2D（风险比：1.55 [1.40 - 1.71]）显著相关。PGS比临床风险因素改善了预测效果，使AUC从0.70提高到0.79，C指数从0.67提高到0.71（均p < 0.001）。将PGS添加到临床风险模型中，基线T2D的NRI为0.63 [0.57 - 0.71]，5年内新发T2D的NRI为0.42 [0.30 - 0.51]。
PGS显著提高了老年人T2D风险预测能力，支持其作为风险分层临床工具的潜力。
