Patients with type 2 diabetes often respond differently to glucose-lowering medications, reflecting both clinical and genetic heterogeneity. At EASD 2025, researchers presented analyses assessing the impact of aetiological variation using partitioned polygenic risk scores (pPRS) on treatment response.

The study included 34,201 patients from the Tayside & Fife region, with 10,811 having genotyping data. Six drug classes were evaluated: metformin, sulfonylureas, DPP4 inhibitors, thiazolidinediones, SGLT2 inhibitors, and GLP-1 receptor agonists. Glycaemic response was measured by change in HbA1c after 12 months and the proportion achieving HbA1c below 58 mmol/mol.

Clinical variables, including baseline HbA1c, body mass index, liver and kidney function, and gender, were strong predictors of drug response. Importantly, specific pPRS were linked to drug-specific responses: Beta-cell function scores predicted sulfonylurea response, bilirubin scores predicted DPP4 inhibitor response, and lipodystrophy scores predicted metformin response.

These findings suggest that integrating genetic risk scores with clinical predictors could enhance individualized therapy selection, pending further validation in larger and diverse populations.