Related Experiment Video
Updated: Sep 8, 2025

A High-Throughput Multiplexed Screening for Type 1 Diabetes, Celiac Diseases, and COVID-19
Published on: July 5, 2022
HLA-focused type 1 diabetes genetic risk prediction in populations of diverse ancestry
Dominika A Michalek1, Courtney Tern1,2, Catherine C Robertson1,3
1Department of Genome Sciences, University of Virginia, Charlottesville, VA, USA.
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 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.
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. Performance of each T1D GRSHLA model was assessed using Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) 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 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/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.
More Related Videos
06:50A High-Throughput Electrochemiluminescence 7-Plex Assay Simultaneously Screening for Type 1 Diabetes and Multiple Autoimmune Diseases
Published on: May 29, 2020
09:52Generation of High Quality Chromatin Immunoprecipitation DNA Template for High-throughput Sequencing ChIP-seq
Published on: April 19, 2013
Related Concept Videos
Genome-wide Association Studies-GWAS
GWAS does not require the identification of the target gene involved in...
Diabetes Mellitus: Overview and Type I Subtype
Type 1 diabetes is an autoimmune disease in which the immune system mistakenly attacks and destroys the insulin-producing beta cells in the pancreas. As a result, the body is unable to produce sufficient insulin, and individuals with...
Diabetes Mellitus: Type 2 and Gestational
Human Genetics
The complex relationship between genetics and psychology is observable through common biological components such...
Genetic Lingo
Diabetes: Symptoms, Diagnosis, and Complications