Type 1 Diabetes Risk in African-Ancestry Participants and Utility of an Ancestry-Specific Genetic Risk Score - Onengut-Gumuscu, Suna; Chen, Wei-Min; Robertson, Catherine C; Bonnie, Jessica K; Farber, Emily; Zhu, Zhennan; Oksenberg, Jorge R; Brant, Steven R; Bridges, Jr, S Louis; Edberg, Jeffrey C; Kimberly, Robert P; Gregersen, Peter K; et al. (Diabetes care, 2019)
Genetic risk scores (GRS) have been developed that differentiate individuals with type 1 diabetes from those with other forms of diabetes and are starting to be used for population screening; however, most studies were conducted in European-ancestry populations. This study identifies novel genetic variants associated with type 1 diabetes risk in African-ancestry participants and develops an African-specific GRS. We generated single nucleotide polymorphism (SNP) data with the ImmunoChip on 1,021 African-ancestry participants with type 1 diabetes and 2,928 control participants. HLA class I and class II alleles were imputed using SNP2HLA. Logistic regression models were used to identify genome-wide significant ( < 5.0 × 10 ) SNPs associated with type 1 diabetes in the African-ancestry samples and validate SNPs associated with risk in known European-ancestry loci ( < 2.79 × 10 ). African-specific (HLA- *03:01-HLA- *02:01) and known European-ancestry HLA haplotypes (HLA- *03:01-HLA- *05:01-HLA- *02:01, HLA- *04:01-HLA- *03:01-HLA- *03:02) were significantly associated with type 1 diabetes risk. Among European-ancestry defined non-HLA risk loci, six risk loci were significantly associated with type 1 diabetes in subjects of African ancestry. An African-specific GRS provided strong prediction of type 1 diabetes risk (area under the curve 0.871), performing significantly better than a European-based GRS and two polygenic risk scores in independent discovery and validation cohorts. Genetic risk of type 1 diabetes includes ancestry-specific, disease-associated variants. The GRS developed here provides improved prediction of type 1 diabetes in African-ancestry subjects and a means to identify groups of individuals who would benefit from immune monitoring for early detection of islet autoimmunity.