使用多基因风险评分对2型糖尿病进行通路洞察和预测建模。

Pathway insights and predictive modeling for type 2 diabetes using polygenic risk scores.

作者信息

Liao Wen-Ling, Yang Jai-Sing, Liu Ting-Yuan, Lu Hsing-Fang, Chang Ya-Wen, Tsai Fuu-Jen

机构信息

Graduate Institute of Integrated Medicine, College of Chinese Medicine, China Medical University, Taichung, 40402, Taiwan.

Center for Personalized Medicine, Department of Medical Research,, China Medical University Hospital, Taichung, 40447, Taiwan.

出版信息

Sci Rep. 2025 Aug 7;15(1):28956. doi: 10.1038/s41598-025-13391-8.

DOI:10.1038/s41598-025-13391-8

PMID:40775498

Abstract

Type 2 diabetes (T2D) poses a significant global health burden. We developed a polygenic risk score (PRS) model based on genome-wide association study (GWAS) findings and integrated it with clinical data to predict T2D risk. This study analyzed electronic medical records from a major medical center in Taiwan, comprising 315,424 T2D cases and 141,484 controls. Fourteen genome-wide significant SNPs were identified and used to construct the T2D PRS. The integrated predictive model showed high accuracy (AUROC 0.842) and was validated in the Taiwan Biobank. A risk score ranging from 0 to 19 was established for clinical use. Phenome-wide association study (PheWAS) revealed links between PRSs and T2D-related complications, such as diabetic retinopathy and hypertension. Pathway analysis highlighted biological processes including IL-15 production and WNT/β-catenin signaling. Our findings support the use of PRSs in personalized T2D risk assessment and early prevention strategies.

摘要

2型糖尿病（T2D）给全球健康带来了重大负担。我们基于全基因组关联研究（GWAS）结果开发了一种多基因风险评分（PRS）模型，并将其与临床数据相结合以预测T2D风险。本研究分析了台湾一家大型医疗中心的电子病历，其中包括315424例T2D病例和141484例对照。识别出14个全基因组显著的单核苷酸多态性（SNP），并用于构建T2D的PRS。该综合预测模型显示出高准确性（曲线下面积为0.842），并在台湾生物银行中得到验证。建立了一个范围从0到19的风险评分供临床使用。全表型组关联研究（PheWAS）揭示了PRS与T2D相关并发症（如糖尿病视网膜病变和高血压）之间的联系。通路分析突出了包括白细胞介素-15产生和WNT/β-连环蛋白信号传导在内的生物学过程。我们的研究结果支持在个性化T2D风险评估和早期预防策略中使用PRS。