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

Abstract

Aims/hypothesisType 1 diabetes is characterized by the destruction of pancreatic beta cells. Genetic factors account for ~50% of the total risk, with variants in the Human Leukocyte Antigen (HLA) region contributing to half of this genetic risk, with research historically focused on populations of European ancestry. We developed HLA-focused type 1 diabetes genetic risk scores (T1D GRSHLA) utilizing single nucleotide polymorphisms (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), Finnish (FIN; T1D GRSHLA-FIN) and across ancestry (ALL; T1D GRSHLA-ALL). We assessed the performance of genetic risk scores in each population to determine transferability of constructed scores. MethodsA 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. Performance of each T1D GRSHLA model was assessed using Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) and compared statistically. ResultsEach 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 of 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 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, ranging from 0.82 to 0.88 for SNPs, and 0.80 to 0.87 for HLA alleles. Conclusions/interpretationT1D 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. Research in ContextO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LIThe HLA region harbors 50% of the genetic risk in type 1 diabetes. C_LIO_LIThe majority of the type 1 diabetes genetic risk scores (T1D GRS) used in the field were developed based on European ancestry data. C_LI What is the key question?O_LIShould genetic risk scores for type 1 diabetes be derived separately for each population, or can a score derived from multiple ancestries effectively capture the complexity of the HLA region and predict the risk of type 1 diabetes across diverse groups? C_LI What are the new findings?O_LIT1D GRSHLA derived from SNPs performed equivalently to T1D GRSHLA derived from HLA alleles across ancestries. C_LIO_LIT1D GRSHLA derived from combined ancestry (ALL) data performed equivalent to, or better than, ancestry-specific T1D GRSHLA models developed for each ancestry group. C_LI How might this impact on clinical practice in the foreseeable future?O_LIThe implementation of a single T1D GRSHLA-SNP-ALL constructed from multiple ancestral populations can be a useful tool for population screening aiming to identify individuals at risk for type 1 diabetes for intervention and prevention. C_LI