Abstract
OBJECTIVE: Polygenic scores strongly predict type 1 diabetes risk, but most scores were developed in European-ancestry populations. In this study, we developed a multi-ancestry polygenic score to accurately predict type 1 diabetes risk across diverse populations. RESEARCH DESIGN AND METHODS: We used recent multi-ancestry genome-wide association studies to create a type 1 diabetes multi-ancestry polygenic score (T1D MAPS). We trained the score in the Mass General Brigham (MGB) Biobank (372 individuals with type 1 diabetes) and tested the score in the All of Us program (86 individuals with type 1 diabetes). We evaluated the area under the receiver operating characteristic curve (AUC), and we compared the AUC to two published single-ancestry scores: T1D GRS2(EUR) and T1D GRS(AFR). We also developed an updated score (T1D MAPS2) that combines T1D GRS2(EUR) and T1D MAPS. RESULTS: Among individuals with non-European ancestry, the AUC of T1D MAPS was 0.90, significantly higher than T1D GRS2(EUR) (0.82, P = 0.04) and T1D GRS(AFR) (0.82, P = 0.007). Among individuals with European ancestry, the AUC of T1D MAPS was slightly lower than T1D GRS2(EUR) (0.89 vs. 0.91, P = 0.02). However, T1D MAPS2 performed equivalently to T1D GRS2(EUR) in European ancestry (0.91 vs. 0.91, P = 0.45) while still performing better in non-European ancestry (0.90 vs. 0.82, P = 0.04). CONCLUSIONS: A novel polygenic score improves type 1 diabetes risk prediction in non-European ancestry while maintaining high predictive power in European ancestry. These findings advance the accuracy of type 1 diabetes genetic risk prediction across diverse populations.