SynthesisThe lancet. Diabetes & endocrinology2026
Multi-ancestry polygenic risk scores for the prediction of type 2 diabetes and complications in diverse ancestries.
Synthesis in The lancet. Diabetes & endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A multiancestry polygenic risk score improves stratification in patients with hypertrophic cardiomyopathy.Nature cardiovascular research · 2026Pooled it
- Multi-ancestry polygenic risk scores: toward equitable prediction of type 2 diabetes and its complications.Acta diabetologica · 2026Article
- Variant-specific contributions of CYP21A2 and CYP11B1 to the clinical and hormonal heterogeneity of polyendocrine metabolic ovarian syndrome phenotypes.Molecular biology reports · 2026Article
- Incorporating polygenic risk scores and social determinants of health across populations: Considerations and best practices in research.American journal of human genetics · 2026Review
- Statistical uncertainty explains the poor agreement in polygenic scoring for type 2 diabetes.medRxiv : the preprint server for health sciences · 2026Article
- Genomic landscape of Mexican patients with maturity onset diabetes of the young: beyond mutations in MODY-known genes.Frontiers in endocrinology · 2026Article
- Improving performance of polygenic risk scores for hypertension across two ancestry groups.PloS one · 2026Article
- Evaluation of functional annotation-informed and ancestry-specific polygenic risk scores for ischemic stroke.Frontiers in bioinformatics · 2026Article
- Improving type 2 diabetes polygenic risk scores by incorporating rare, low-frequency, and population-specific variants.medRxiv : the preprint server for health sciences · 2025Article
- Improving performance of polygenic risk scores for hypertension across two ancestry groups.medRxiv : the preprint server for health sciences · 2025Article
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40 authors.
Funding
Abstract
backgroundPolygenic risk scores (PRSs) improve prediction of the development of type 2 diabetes over the use of clinical risk factors alone; however, they perform poorly in populations of non-European ancestry, limiting their global clinical utility. We aimed to deliver comprehensive and rigorously tested multi-ancestry PRSs for prediction in type 2 diabetes.
methodsWe conducted meta-analyses using data from type 2 diabetes genome-wide association studies (GWAS) across cohorts from five major global ancestries: European, African or African American, Admixed American, South Asian, and East Asian. We used summary statistics from the GWAS to construct single-ancestry PRSs (using the continuous-shrinkage PRS-CS method) and multi-ancestry PRSs (using the PRS-CSx method), and constructed ancestry-specific linkage disequilibrium panels to model pairwise correlations between single-nucleotide polymorphisms in GWAS during PRS construction. Models were validated for association with type 2 diabetes in at least four independent cohorts per ancestry. The effect sizes of PRSs were estimated as the odds ratio (OR) per SD of the PRS, and ORs for individuals at the 90th, 95th, and 97·5th PRS percentiles were compared with the IQR as a reference. We also tested our PRS models for prediction of diabetes incidence with or without additional clinical factors, as well as microvascular complications and comorbidities.
findingsOur analysis used data from 409 959 individuals with type 2 diabetes and 1 983 345 controls: respectively, 359 819 and 1 825 729 indivduals were included in the GWAS dataset, with 10 992 and 31 792 individuals in the training dataset and 39 148 and 125 824 individuals in the validation dataset. The best predictive performance for the single-ancestry PRSs was in European (incremental AUC 0·07-0·14) and East Asian (0·02-0·16) ancestries, whereas prediction was poorer for African or African American (0·02-0·03), Admixed American (0·02-0·04), and South Asian (0·02-0·04) ancestries, correlating with sample sizes in the GWAS. Compared with single-ancestry PRSs, our multi-ancestry PRSs showed higher effect sizes and smaller 95% CIs across all ancestries: OR per SD 1·73 (95% CI 1·67-1·80) in African or African American, 2·82 (2·67-2·97) in Admixed American, 2·45 (2·36-2·54) in East Asian, 2·36 (2·32-2·41) in European, and 2·23 (2·05-2·42) in South Asian ancestries. Individuals in the 97·5th PRS percentile had a 3-7 times increased risk of type 2 diabetes compared with those in the IQR (OR 3·43 [95% CI 2·80-4·21] in African or African American, 7·47 [5·64-9·89] in Admixed American, 6·62 [5·58-7·85] in East Asian, 6·25 [5·72-6·82] in European, and 4·50 [2·70-7·53] in South Asian ancestries). These PRSs were also associated with earlier onset of type 2 diabetes, higher risk of developing microvascular complications, and provide additional predictive value beyond clinical factors. In individuals with type 2 diabetes, the association between multi-ancestry PRSs and risk of microvascular complications and comorbidity was studied in populations of African, Admixed American, and European ancestries and was significant in all three ancestry groups for diabetic retinopathy (ORs per SD 1·28-1·57), diabetic nephropathy (1·25-1·58), proliferative diabetic retinopathy (1·39-2·08), and end-stage diabetic nephropathy (1·44-1·87); PRS was associated with coronary artery disease in the Admixed American ancestry group only (1·16 [95% CI 1·08-1·25]).
interpretationThese validated, publicly available PRSs can improve risk stratification for type 2 diabetes onset and complications across diverse ancestries, supporting their further evaluation in clinical settings.
fundingThe National Human Genome Research Institute of the US National Institutes of Health.
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