A multi-ancestry genome-wide association study in type 1 diabetes

Author:

Michalek Dominika A12ORCID,Tern Courtney12,Zhou Wei345678,Robertson Catherine C12,Farber Emily12,Campolieto Paul12,Chen Wei-Min1292,Onengut-Gumuscu Suna1292,Rich Stephen S1292

Affiliation:

1. Center for Public Health Genomics , , 1330 Jefferson Park Avenue, Charlottesville, VA 22908 , United States

2. University of Virginia , , 1330 Jefferson Park Avenue, Charlottesville, VA 22908 , United States

3. Analytic and Translational Genetics Unit , Department of Medicine, , 185 Cambridge Street, Boston, MA 02114 , United States

4. Massachusetts General Hospital , Department of Medicine, , 185 Cambridge Street, Boston, MA 02114 , United States

5. Stanley Center for Psychiatric Research , , 415 Main Street, Cambridge, MA 02142 , United States

6. Broad Institute of MIT and Harvard , , 415 Main Street, Cambridge, MA 02142 , United States

7. Program in Medical and Population Genetics , , 185 Cambridge Street, Boston, MA 02114 , United States

8. Broad Institute of Harvard and MIT , , 185 Cambridge Street, Boston, MA 02114 , United States

9. Department of Public Health Sciences , , 1330 Jefferson Park Avenue, Charlottesville, VA 22908 , United States

Abstract

Abstract Type 1 diabetes (T1D) is an autoimmune disease caused by destruction of the pancreatic β-cells. Genome-wide association (GWAS) and fine mapping studies have been conducted mainly in European ancestry (EUR) populations. We performed a multi-ancestry GWAS to identify SNPs and HLA alleles associated with T1D risk and age at onset. EUR families (N = 3223), and unrelated individuals of African (AFR, N = 891) and admixed (Hispanic/Latino) ancestry (AMR, N = 308) were genotyped using the Illumina HumanCoreExome BeadArray, with imputation to the TOPMed reference panel. The Multi-Ethnic HLA reference panel was utilized to impute HLA alleles and amino acid residues. Logistic mixed models (T1D risk) and frailty models (age at onset) were used for analysis. In GWAS meta-analysis, seven loci were associated with T1D risk at genome-wide significance: PTPN22, HLA-DQA1, IL2RA, RNLS, INS, IKZF4-RPS26-ERBB3, and SH2B3, with four associated with T1D age at onset (PTPN22, HLA-DQB1, INS, and ERBB3). AFR and AMR meta-analysis revealed NRP1 as associated with T1D risk and age at onset, although NRP1 variants were not associated in EUR ancestry. In contrast, the PTPN22 variant was significantly associated with risk only in EUR ancestry. HLA alleles and haplotypes most significantly associated with T1D risk in AFR and AMR ancestry differed from that seen in EUR ancestry; in addition, the HLA-DRB1*08:02-DQA1*04:01-DQB1*04:02 haplotype was ‘protective’ in AMR while HLA-DRB1*08:01-DQA1*04:01-DQB1*04:02 haplotype was ‘risk’ in EUR ancestry, differing only at HLA-DRB1*08. These results suggest that much larger sample sizes in non-EUR populations are required to capture novel loci associated with T1D risk.

Funder

National Institute of Diabetes and Digestive and Kidney Diseases

NIDDK

Juvenile Diabetes Research Foundation

Leona M. and Harry B. Helmsley Charitable Trust

National Human Genome Research Institute

Publisher

Oxford University Press (OUP)

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