Harnessing the power of polygenic risk scores to predict type 2 diabetes and its subtypes in a high-risk population of British Pakistanis and Bangladeshis in a routine healthcare setting

Abstract

Background: Type 2 diabetes is a heterogeneous condition highly prevalent in British Pakistanis and Bangladeshis (BPB). The Genes & Health (G&H) cohort offers means to explore genetic determinants of disease in BPBs, combining genetic and lifelong health record data. Methods: We assessed whether common genetic loci associated with type 2 diabetes in European-ancestry individuals (EUR) replicate in G&H. We constructed a type 2 diabetes polygenic risk score (PRS) and combined it with a clinical risk instrument (QDiabetes) to build a novel, integrated risk tool (IRT). We compared IRT performance using net reclassification index (NRI) versus QDiabetes alone. We assessed the ability of the PRS to predict type 2 diabetes following gestational diabetes (GDM). We compared PRS distribution between type 2 diabetes subgroups identified by clinical features at diagnosis. Findings: Accounting for power, we replicated fewer loci associated with type 2 diabetes in G&H (n = 76/338, 22%) than would be expected if all EUR-ascertained loci were transferable (n = 95, 28%) (binomial p value = 0.01). In 13,648 patients free from type 2 diabetes followed up for 10 years, NRI was 3.2% for IRT versus QDiabetes (95% confidence interval 2.0 - 4.4%). IRT performance was best in reclassification of young adults deemed low risk by QDiabetes as high risk. PRS was independently associated with progression to type 2 diabetes after GDM (p = 0.028). Mean type 2 diabetes PRS differed between phenotypically-defined type 2 diabetes subgroups (p = 0.002). Interpretation: The type 2 diabetes PRS has broad potential clinical application in BPB, improving identification of type 2 diabetes risk (especially in the young), and characterisation of type 2 diabetes subgroups at diagnosis. Funding: Wellcome Trust, MRC, NIHR, and others. Full funding disclosed within.