Development and Validation of a Type 1 Diabetes Multi-Ancestry Polygenic Score

Polygenic scores strongly predict type 1 diabetes risk, but most scores were developed in European-ancestry populations. In this study, we leveraged recent multiancestry 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 for European (EUR) and African (AFR) populations: T1D Genetic Risk Score 2 (GRS2EUR) and T1D GRSAFR. We also developed an updated score (T1D MAPS2) that combines T1D GRS2EUR and T1D MAPS. Among individuals with non-European ancestry, the AUC of T1D MAPS was 0.90, significantly higher than T1D GRS2EUR (0.82) and T1D GRSAFR (0.82). Among individuals with European ancestry, the AUC of T1D MAPS was slightly lower than T1D GRS2EUR (0.89 vs. 0.91). However, T1D MAPS2 performed equivalently to T1D GRS2EUR in European ancestry (0.91 vs. 0.91) and performed better in non-European ancestry (0.90 vs. 0.82). Overall, these findings advance the accuracy of type 1 diabetes genetic risk prediction across diverse populations.

Type 1 diabetes polygenic scores are highly predictive of disease risk, but their performance varies based on genetic ancestry. Can we develop a polygenic score that accurately predicts type 1 diabetes risk across diverse populations? Our novel polygenic score performs similar to existing scores in European populations, and it demonstrates superior performance in non-European populations. This polygenic score will improve prediction of type 1 diabetes risk in genetically diverse populations.