<b>Development and Validation of a Type 1 Diabetes Multi-Ancestry Polygenic Score</b>
Version 2 2025-11-25, 16:11
Version 1 2025-11-14, 15:01
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posted on 2025-11-25, 16:11 authored by Aaron J. Deutsch, Andrew S. Bell, Dominika A. Michalek, Adam B. Burkholder, Stella Nam, Raymond J. Kreienkamp, Seth A. Sharp, Alicia Huerta-Chagoya, Ravi Mandla, Ruth Nanjala, Yang Luo, Richard A. Oram, Jose C. Florez, Suna Onengut-Gumuscu, Stephen S. Rich, Maggie C. Y. Ng, Alison A. Motsinger-Reif, Alisa K. Manning, Josep M. Mercader, Miriam S. Udler<p dir="ltr">Polygenic scores strongly predict type 1 diabetes risk, but most scores were developed in European-ancestry populations. In this study, we leveraged 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<sub>EUR</sub> and T1D GRS<sub>AFR</sub>. We also developed an updated score (T1D MAPS2) that combines T1D GRS2<sub>EUR</sub> and T1D MAPS. Among individuals with non-European ancestry, the AUC of T1D MAPS was 0.90, significantly higher than T1D GRS2<sub>EUR</sub> (0.82) and T1D GRS<sub>AFR</sub> (0.82). Among individuals with European ancestry, the AUC of T1D MAPS was slightly lower than T1D GRS2<sub>EUR</sub> (0.89 vs. 0.91). However, T1D MAPS2 performed equivalently to T1D GRS2<sub>EUR</sub> 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.</p>
Funding
AJD is supported by National Institutes of Health (NIH) / National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) K23 DK140643. RJK is supported by NIH/NIDDK T32 DK007699. MCYN, AKM, JMM, and MSU are supported by NIH / National Human Genome Research Institute (NHGRI) U01HG011723. JMM is supported by American Diabetes Association grant #11-22-ICTSPM-16, by the NIH / NIDDK under Award Number R01DK137993 and U01 DK140757, AMP CMD award from RFP 6 from the Foundation for the National Institutes of Health, and a Medical University of Bialystok (MUB) grant from the Ministry of Science and Higher Education (Poland). This work is supported by the Novo Nordisk Foundation (NNF21SA0072102). MSU is supported by Doris Duke Foundation Award 2022063, NIDDK U54DK118612, and NIDDK U01DK140757.
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