Leveraging the clinical, genetic, and molecular heterogeneity of type 2 diabetes to improve screening and treatment strategies (360G-Wellcome-339320_Z_25_Z)

Type 2 diabetes (T2D) affects over half a billion people globally, but its causes, symptoms, and outcomes vary widely between individuals and populations. South Asian populations in particular develop T2D at a younger age and lower body weight, and have higher risks of complications – yet they remain underrepresented in research. I aim to better understand variations in T2D diagnoses in South and Southeast Asian (SSEA) populations by applying ‘soft’ clustering methods. These methods describe how individuals can belong to a mixture of disease subtypes, rather than assigning them to single disease categories – better reflecting the real-world complexity of T2D. I will use clinical, genetic, and molecular data from SSEA cohorts to explore how these subtypes relate to disease progression, complications, and response to treatments like metformin. I will also investigate how genetic risk scores and molecular markers can help improve our understanding of disease causes and progression. Ultimately, I aim to develop evidence that will help doctors choose the most appropriate treatments for SSEA patients with T2D. By reflecting the real-world complexity of T2D more accurately, my research aims to make diabetes care more personalised, effective, and equitable – in a disadvantaged community that is not well represented in medical research.