Analysis of Type 1 Diabetes Polygenic Scores in Atypical Forms of Diabetes

Massachusetts General Hospital, Boston MA

Investigators

Linked publications, trials & patents

Abstract

PROJECT SUMMARY/ABSTRACT Diabetes is traditionally classified as type 1 diabetes (T1D) or type 2 diabetes (T2D). T1D is caused by autoimmune destruction of beta cells and insulin deficiency, while T2D is characterized by increased body mass and insulin resistance. However, some atypical forms of diabetes are not easily classified as T1D or T2D, and they share overlapping features with both conditions. In this project, we propose to use genetic information to enhance the diagnosis of atypical forms of diabetes. In particular, we will use polygenic scores, a promising tool that combines the effects of multiple variants across the genome to predict the risk of disease. T1D polygenic scores have been validated to predict the onset of T1D in children and to help discriminate between T1D and T2D in adults. Here, we will apply T1D polygenic scores in novel contexts. In Aim 1, we will examine ketosis-prone diabetes, which phenotypically resembles T2D but nevertheless involves ketoacidosis. In Aim 2, we will investigate latent autoimmune diabetes in adults, which phenotypically resembles T1D but presents later in life and has slower progression compared to classic, childhood-onset T1D. Finally, in Aim 3, we will study immune checkpoint inhibitor-induced diabetes, in which individuals treated with immune checkpoint inhibitors develop variable phenotypes and may or may not require insulin. In each of these aims, we will implement T1D polygenic scores to better characterize disease heterogeneity and to identify diabetes subtypes with distinct clinical outcomes. By using ancestry-specific and multi-ancestry polygenic scores, we will ensure that diverse populations are well-represented. This is particularly important because most existing polygenic scores have been developed in populations with European ancestry, whereas certain atypical forms of diabetes are more common in other populations. The proposed project will provide advanced training in computational biology and statistical genetics. The research setting represents an ideal environment for junior investigators, combining the world-class clinical expertise of Massachusetts General Hospital with the innovative computational resources of the Broad Institute. This project will provide a foundation for the candidate to apply for a career development award and ultimately to become an independent physician scientist.