Heterogeneity in phenotype, disease progression and drug response in type 2 diabetes

A new analysis of patients newly diagnosed with diabetes uses a data dimenionality reduction approach to understand how phenotypic variation drives diseaese onset, clinical outcomes and responses to glycemic-lowering medications. Type 2 diabetes (T2D) is a complex chronic disease characterized by considerable phenotypic heterogeneity. In this study, we applied a reverse graph embedding method to routinely collected data from 23,137 Scottish patients with newly diagnosed diabetes to visualize this heterogeneity and used partitioned diabetes polygenic risk scores to gain insight into the underlying biological processes. Overlaying risk of progression to outcomes of insulin requirement, chronic kidney disease, referable diabetic retinopathy and major adverse cardiovascular events, we show how these risks differ by patient phenotype. For example, patients at risk of retinopathy are phenotypically different from those at risk of cardiovascular events. We replicated our findings in the UK Biobank and the ADOPT clinical trial, also showing that the pattern of diabetes drug monotherapy response differs for different drugs. Overall, our analysis highlights how, in a European population, underlying phenotypic variation drives T2D onset and affects subsequent diabetes outcomes and drug response, demonstrating the need to incorporate these factors into personalized treatment approaches for the management of T2D.

Automated summary

An analysis of newly diagnosed diabetes patients reveals the impact of phenotypic variation on disease onset, clinical outcomes, and drug response. The study shows that patients with different phenotypes have varying risks of diabetic complications and respond differently to different drugs. These findings are important for personalized treatment of diabetes.