ArticleScientific reports2025
Pathway insights and predictive modeling for type 2 diabetes using polygenic risk scores.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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