Polygenic risk scores predict diabetes complications and their response to intensive blood pressure and glucose control
Journal Diabetologia
Summary
A multi-polygenic risk score (multiPRS) model was developed to predict diabetes complications and the efficacy of intensive blood pressure and glucose control treatments.
Study Design
Interventions
Study Type
Outcomes
Duration and Size
Study Population
Geography
Methodology
This study developed a multi-polygenic risk score (multiPRS) model integrating 10 weighted polygenic risk scores (wPRS) from genome-wide association studies. The model was validated using the ADVANCE trial (n=4098) and the UK Biobank dataset (n=17,604). Logistic regression was applied to predict microvascular and macrovascular outcomes in type 2 diabetes patients. Predictive performance was assessed through C-statistics and external validation.
Interventions
The study assessed the impact of intensive blood pressure and glucose control therapy on high-risk individuals identified by the multiPRS model. The ADVANCE trial intervention included perindopril-indapamide for blood pressure control and gliclazide MR-based glucose control targeting HbA1c ≤6.5%. Treatment effects were stratified based on polygenic risk classification.
Key Findings
The multiPRS model effectively stratified patients based on their risk of diabetes complications. Individuals in the highest genetic risk third benefited the most from intensive therapy, showing a 47% reduction in cardiovascular death with combined intensive treatment. The model achieved an area under the receiver operating characteristic curve (AUC) of 0.67 for major cardiovascular events and 0.72 for cardiovascular death.
Comparison with other Studies
The study "Polygenic Risk Scores Predict Diabetes Complications and Their Response to Intensive Blood Pressure and Glucose Control" by Lu et al. (2021) demonstrates that polygenic risk scores (PRS) can effectively identify individuals with diabetes who are at varying risks for complications and who may benefit differently from intensive therapies. This aligns with findings from other research. For instance, a study published in Scientific Reports in 2023 highlighted the clinical relevance of PRS in predicting type 2 diabetes and its complications, suggesting that incorporating PRS into clinical practice could enhance personalized treatment strategies. citeturn0search4 Similarly, research available on medRxiv in 2019 indicated that a novel polygenic prediction model could stratify individuals with diabetes into low and high-risk categories for complications, thereby improving the targeting of intensive therapies. citeturn0search6 Furthermore, a 2023 study in the European Journal of Preventive Cardiology examined the interaction between type 2 diabetes polygenic risk and physical activity, finding that the beneficial effects of physical activity on cardiovascular outcomes diminished among those with high genetic risk for type 2 diabetes. citeturn0search13 Collectively, these studies underscore the potential of PRS to refine risk assessment and guide personalized interventions in diabetes management.
Journal Reference
Lu J, Bi X, Wang H, et al. Polygenic risk scores predict diabetes complications and their response to intensive blood pressure and glucose control. Diabetologia. 2021;64(12):2691-2703. doi:10.1007/s00125-021-05491-7.