Despoina Manousaki, Dominika A Michalek, Hui-Qi Qu, Lauric A Ferrat, Aaron J Deutsch
Type 1 diabetes is highly influenced by genetic risk factors, especially variation in the HLA genes. Polygenic scores can strongly predict type 1 diabetes risk by integrating variants across the genome. Most polygenic scores perform best in European-ancestry populations, due to low representation of other ancestry groups in existing studies, as well as substantial variation in HLA alleles across the globe. However, recent multi-ancestry genome-wide association studies have broadened our understanding of type 1 diabetes genetic risk, and advanced computational techniques can accurately capture HLA alleles at high resolution. This article will review novel approaches to develop type 1 diabetes polygenic scores that demonstrate high predictive power across diverse populations.