Extension of Type 2 Diabetes Genetic Clustering to Populations of non-European Ancestry

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Abstract In the United States, populations of non-predominantly European ancestry, such as African Americans and Hispanic-Latinos, are disproportionately afflicted with type 2 diabetes (T2D) and T2D-related complications, but are also traditionally under-represented in medical research, particularly genetic studies. There are appreciated, but as yet unexplained, differences in T2D clinical characteristics between populations; for example, at a given body mass index, individuals of Asian ancestry having a higher prevalence of T2D and increased visceral adiposity compared to individuals of European ancestry. Furthermore, several important T2D loci have been identified in non-European populations, such as SLC16A11, which is common in Latin Americans and essentially absent from individuals of European ancestry. We recently performed cluster analysis of T2D-associated genetic variants and T2D-related traits, resulting in five groupings of T2D genetic loci based on the T2D genetic-variant-trait associations (Udler et al, PLoS Medicine 2018). The clusters were readily interpretable: two related to mechanisms of insulin deficiency and three related to mechanisms of insulin resistance. These analyses, however, were restricted to studies in populations of European ancestry due to data availability at the time, but newer genetic studies and datasets are now accessible. We would like to extend the cluster analysis to groups of non-European ancestry in order to elucidate genetic mechanism of disease and generate results that are more widely translatable. In Aim 1 we will perform phenotypically informed cluster analysis of T2D genetic variants using study populations of non- European ancestry (African, East Asian, Hispanic/Latino, and South Asian) to identify T2D mechanistic pathways. In Aim 2, we will utilize the genetic clusters generated in Aim 1 to construct cluster-specific polygenetic scores in individuals of non- European ancestry from validation cohorts (Mass General Brigham Biobank, UK Biobanks, and All of Us) to determine which clinical characteristics are associated with each cluster-specific polygenic score. The goal of Aim 2 is thus to use the genetic clusters to inform T2D subclassification. Finally, in Aim 3, we will investigate whether the relative disease burden conferred by these genetic clusters differs among ancestral populations. The overarching objectives of this R03 are to improve understanding of T2D pathophysiology, translate genomic discoveries to useful applications for patient care, and advance T2D genetics research in populations traditionally under-represented in biomedical research. This proposal will provide necessary preliminary data for a future R01 study aimed at investigating the physiology of individuals with high burden for T2D genetic pathways and support more diverse representation in future research.