Michalek Dominika A, Tern Courtney, Robertson Catherine C, Chen Wei-Min, Onengut-Gumuscu Suna, Rich Stephen S
Department of Genome Sciences, University of Virginia, Charlottesville, VA, USA.
Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.
medRxiv. 2025 Aug 12:2025.08.07.25333167. doi: 10.1101/2025.08.07.25333167.
AIMS/HYPOTHESIS: Type 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 GRS) utilizing single nucleotide polymorphisms (SNPs) or HLA alleles from four ancestry groups (Admixed African (AFR; T1D GRS), Admixed American (AMR; T1D GRS), European (EUR; T1D GRS), Finnish (FIN; T1D GRS) and across ancestry (ALL; T1D GRS). We assessed the performance of genetic risk scores in each population to determine transferability of constructed scores.
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 GRS models. Generated T1D GRS models were used to predict HLA-focused type 1 diabetes genetic risk across four ancestry groups. Performance of each T1D GRS model was assessed using Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) and compared statistically.
Each T1D GRS 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 GRS from SNPs or HLA alleles were similar and ranged from 0.73 (T1D GRS applied to FIN) to 0.88 (T1D GRS to EUR). The ROC AUC using the combined set of conditionally independent SNPs (T1D GRS) or HLA alleles (T1D GRS) 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/INTERPRETATION: T1D GRS models derived from SNPs performed equivalently to those derived from HLA alleles across ancestries. In addition, T1D GRS and GRS 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 GRS across ancestries.
目的/假设:1型糖尿病的特征是胰腺β细胞被破坏。遗传因素约占总风险的50%,人类白细胞抗原(HLA)区域的变异占该遗传风险的一半,历史研究主要集中在欧洲血统人群。我们利用来自四个祖先群体(非洲裔混血(AFR;1型糖尿病遗传风险评分)、美洲裔混血(AMR;1型糖尿病遗传风险评分)、欧洲(EUR;1型糖尿病遗传风险评分)、芬兰(FIN;1型糖尿病遗传风险评分))以及跨祖先群体(ALL;1型糖尿病遗传风险评分)的单核苷酸多态性(SNP)或HLA等位基因,开发了以HLA为重点的1型糖尿病遗传风险评分(T1D GRS)。我们评估了每个群体中遗传风险评分的表现,以确定构建评分的可转移性。
对HLA区域的41689个样本和13695个SNP进行基因分型,使用HLA TAPAS多民族参考面板推算HLA等位基因。在每个群体组中识别与1型糖尿病相关的条件独立SNP和HLA等位基因,以构建T1D GRS模型。生成的T1D GRS模型用于预测四个祖先群体中以HLA为重点的1型糖尿病遗传风险。使用受试者操作特征(ROC)曲线下面积(AUC)评估每个T1D GRS模型的表现,并进行统计学比较。
每个T1D GRS模型包含不同数量的条件独立HLA区域SNP(AFR,n = 5;AMR,n = 3;EUR,n = 38;FIN,n = 6;ALL,n = 36)和HLA等位基因(AFR,n = 6;AMR,n = 5;EUR,n = 40;FIN,n = 8;ALL,n = 41)。来自SNP或HLA等位基因的T1D GRS的ROC AUC值相似,范围从0.73(应用于FIN的T1D GRS)到0.88(应用于EUR的T1D GRS)。使用条件独立SNP(T1D GRS)或HLA等位基因(T1D GRS)组合集的ROC AUC在所有祖先群体中表现一致良好,SNP的范围为0.82至0.88,HLA等位基因的范围为0.80至0.87。
结论/解读:来自SNP的T1D GRS模型在不同祖先群体中的表现与来自HLA等位基因的模型相当。此外,T1D GRS和GRS模型在应用于不同祖先群体时,ROC AUC值始终较高。需要在更多样化的人群中进行更大规模的研究,以更好地评估T1D GRS在不同祖先群体中的可转移性。