ArticleTherapeutic advances in endocrinology and metabolism2023
Assessing the prediction of type 2 diabetes risk using polygenic and clinical risk scores in South Asian study populations.
Article in Therapeutic advances in endocrinology and metabolism, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 11 citations in OpenAlex.
- Type 2 Diabetes Causally Reduces Circulating Vitamin D Levels: A Multi-Ancestry Mendelian Randomization Study.Nutrients · 2026Article
- Identification of lipid quantitative trait loci linked with cardiometabolic disease in Asian Indians and Europeans: A genome-wide association study and Mendelian randomization.PLoS medicine · 2026Observational
- Article
- Plasminogen activator inhibitor-1, vaspin, and dietary inflammatory index in relation to cardiometabolic health in diabetic women.Frontiers in nutrition · 2026Article
- Predictive Models for Type 2 Diabetes Mellitus in Han Chinese with Insights into Cross-Population Applicability and Demographic Specific Risk Factors.Diabetes & metabolism journal · 2025Article
- Unmasking heterogeneity in type 2 diabetes: the clinical relevance of phenotyping in the era of precision medicine.Acta diabetologica · 2025Article
- Clinical use of polygenic scores in type 2 diabetes: challenges and possibilities.Diabetologia · 2025Review
- Excess of rare noncoding variants in several type 2 diabetes candidate genes among Asian Indian families.Communications medicine · 2025Article
- Article
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Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
Abstract
Background: Genome-wide polygenic risk scores (PRS) have shown high specificity and sensitivity in predicting type 2 diabetes (T2D) risk in Europeans. However, the PRS-driven information and its clinical significance in non-Europeans are underrepresented. We examined the predictive efficacy and transferability of PRS models using variant information derived from genome-wide studies of Asian Indians (AIs) (PRS Methods: Weighted PRS models were constructed and analyzed on 4602 individuals from the Asian Indian Diabetes Heart Study/Sikh Diabetes Study (AIDHS/SDS) as discovery/training and test/validation datasets. The results were further replicated in 9372 South Asian individuals from UK Biobank (UKBB). We also assessed the performance of each PRS model by combining data of the clinical risk score (CRS). Results: Both genetic models (PRS Conclusion: Our data suggest the need for extending genetic and clinical studies in varied ethnic groups to exploit the full clinical potential of PRS as a risk prediction tool in diverse study populations.
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