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

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; Alison A Motsinger-Reif; Alisa K Manning; Josep M Mercader; Miriam S Udler

doi:10.1101/2025.06.20.25329522

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

medRxiv [Preprint]. 2025 Jun 22:2025.06.20.25329522. doi: 10.1101/2025.06.20.25329522.

Authors

Aaron J Deutsch^{1

2

3

4}, Andrew S Bell⁴, Dominika A Michalek⁵, Adam B Burkholder⁶, Stella Nam^{1

2

3}, Raymond J Kreienkamp^{1

2

3

4

7}, Seth A Sharp^{1

2

3}, Alicia Huerta-Chagoya^{3

1}, Ravi Mandla^{3

1

8

9}, Ruth Nanjala¹⁰, Yang Luo¹⁰, Richard A Oram^{11

12}, Jose C Florez^{1

2

3

4}, Suna Onengut-Gumuscu⁵, Stephen S Rich⁵, Alison A Motsinger-Reif¹³, Alisa K Manning^{3

4

14}, Josep M Mercader^{3

1

4}, Miriam S Udler^{1

2

3

4}

Affiliations

¹ Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
² Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
³ Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁴ Department of Medicine, Harvard Medical School, Boston, MA, USA.
⁵ Department of Genome Sciences, University of Virginia, Charlottesville, VA, USA.
⁶ Office of Environmental Science Cyberinfrastructure, National Institute of Environmental Health Sciences, Durham, NC, USA.
⁷ Division of Endocrinology, Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA.
⁸ Graduate Program in Genomics and Computational Biology, University of Pennsylvania, Philadelphia, PA, USA.
⁹ Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
¹⁰ Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK.
¹¹ University of Exeter College of Medicine and Health, Exeter, UK.
¹² Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK.
¹³ Biostatistics & Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA.
¹⁴ Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA.

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.

Publication types

Preprint