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. 2025 Oct 2.
doi: 10.1007/s00125-025-06563-8. Online ahead of print.

HLA-focused type 1 diabetes genetic risk prediction in populations of diverse ancestry

Dominika A Michalek  1 , Courtney Tern  1   2 , Catherine C Robertson  1   3 , Wei-Min Chen  1 , Suna Onengut-Gumuscu #  1 , Stephen S Rich #  4
Affiliations

HLA-focused type 1 diabetes genetic risk prediction in populations of diverse ancestry

Dominika A Michalek et al. Diabetologia. .

Abstract

Aims/hypothesis: Type 1 diabetes is characterised by the destruction of pancreatic beta cells. Genetic factors account for approximately 50% of the total risk, with variants in the HLA region contributing to half of this genetic risk. Research has historically focused on populations of European ancestry. We developed HLA-focused type 1 diabetes genetic risk scores (T1D GRSHLA) using SNPs or HLA alleles from four ancestry groups (admixed African [AFR; T1D GRSHLA-AFR], admixed American [AMR; T1D GRSHLA-AMR], European [EUR; T1D GRSHLA-EUR] and Finnish [FIN; T1D GRSHLA-FIN]). We also developed an across-ancestry GRS (ALL; T1D GRSHLA-ALL). We assessed the performance of the GRS in each population to determine the transferability of constructed scores.

Methods: A total of 41,689 samples and 13,695 SNPs in the HLA region were genotyped, with HLA alleles imputed using the HLA-TAPAS multi-ethnic reference panel. Conditionally independent SNPs and HLA alleles associated with type 1 diabetes were identified in each population group to construct T1D GRSHLA models. Generated T1D GRSHLA models were used to predict HLA-focused type 1 diabetes genetic risk across four ancestry groups. The performance of each T1D GRSHLA model was assessed using receiver operating characteristic (ROC) AUCs, and compared statistically.

Results: Each T1D GRSHLA model included a different number of conditionally independent HLA-region SNPs (AFR, n=5; AMR, n=3; EUR, n=38; FIN, n=6; ALL, n=36) and HLA alleles (AFR, n=6; AMR, n=5; EUR, n=40; FIN, n=8; ALL, n=41). The ROC AUC values for the T1D GRSHLA from SNPs or HLA alleles were similar, and ranged from 0.73 (T1D GRSHLA-allele-AMR applied to FIN) to 0.88 (T1D GRSHLA-allele-EUR applied to EUR). The ROC AUC using the combined set of conditionally independent SNPs (T1D GRSHLA-SNP-ALL) or HLA alleles (T1D GRSHLA-allele-ALL) performed uniformly well across all ancestry groups, with values ranging from 0.82 to 0.88 for SNPs and 0.80 to 0.87 for HLA alleles.

Conclusions/interpretation: T1D GRSHLA models derived from SNPs performed equivalently to those derived from HLA alleles across ancestries. In addition, T1D GRSHLA-SNP-ALL and GRSHLA-allele-ALL models had consistently high ROC AUC values when applied across ancestry groups. Larger studies in more diverse populations are needed to better assess the transferability of T1D GRSHLA across ancestries.

Keywords: Genetic risk score; HLA; Multi-ancestry; Transferability; Type 1 diabetes.

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Conflict of interest statement

Acknowledgements: The authors express their gratitude to the investigators and groups who collected and provided biological samples or data for this study, as well as to the participants whose contributions made this research possible. Data availability: Summary statistics are available in dbGaP ( https://dbgap.ncbi.nlm.nih.gov/home ) under accession number pha002468.v2.p1, and the Accelerating Medicines Partnership Common Metabolic Diseases (AMP CMD) Knowledge Portal ( https://hugeamp.org/ ). Code availability: Code used to generate results is available at https://github.com/damichalek/T1DGC_GRS_HLA . Funding: Research reported in this publication was supported by National Institutes of Health grants U01 DK062418, DP3 DK085678, R01 DK122586 and U01 HG011723, a grant from the Leona M. and Harry B. Helmsley Charitable Trust (grant number 2204-05134), and grants from the JDRF, now known as Breakthrough T1D (grant numbers 1-2001-916 and 9-2011-530). Authors’ relationships and activities: SSR has received consulting and lecture fees from Sanofi. The University of Virginia has received research support for SSR from Sanofi and from the Leona M. and Harry B. Helmsley Charitable Trust. The remaining authors declare that there are no relationships or activities that might bias, or be perceived to bias, their work. Contribution statement: SSR and SO-G conceptualised, designed the study and contributed to data acquisition. DAM, CT, CCR and W-MC conducted statistical analysis. DAM, W-MC, SSR and SO-G were involved in data interpretation. DAM, SSR and SO-G drafted the manuscript. All authors contributed to the editing and critical revision of the manuscript. All authors read and approved the final version to be published. SSR is responsible for the integrity of the work as a whole.

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