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September 10, 2025Scientific ReportsOpen Access

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

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Authors

WLWen-Ling LiaoJYJai‐Sing YangTLTing-Yuan Liu

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Overview

Analysis reveals high accuracy of polygenic risk scores in predicting type 2 diabetes, suggesting personalized prevention strategies.

Key Points

  • The integrated predictive model achieved high accuracy with an AUROC of 0.842, indicating its effectiveness in predicting type 2 diabetes risk.
  • Fourteen genome-wide significant SNPs were identified and used to construct the polygenic risk score model, demonstrating a robust genetic basis for prediction.
  • Electronic medical records from 315,424 cases and 141,484 controls were analyzed to enrich the dataset and validate the findings.
  • The study supports using polygenic risk scores for early prevention strategies and personalized risk assessment in type 2 diabetes.

Cite This Study

Liao et al. (2025) studied this question.

synapsesocial.com/papers/68c1bd2a54b1d3bfb60ee006https://doi.org/10.1038/s41598-025-13391-8
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