Predictive model of declining glomerular filtration rate in type 2 diabetes mellitus with poorly glycemic control: Integration of RAAS and TGFB polymorphisms with clinical risk factors in the Jambi Malay population

Abstract

Background: Diabetic kidney disease (DKD) is a major complication of type 2 diabetes mellitus (T2DM) and a leading cause of end-stage renal disease worldwide. Despite optimal glycemic and blood pressure control, many patients experience renal decline, suggesting a role for genetic factors. Objective: To develop a predictive model integrating clinical and genetic parameters to identify individuals at risk of declining glomerular filtration rate (GFR) among Malay Jambi patients with poorly controlled T2DM. Methods: A cross-sectional study of 62 patients was conducted using ACE rs4343 and TGFB1 rs1800470 genotyping by Tetra-ARMS PCR. Declining renal function was defined as eGFR <60 mL/min/1.73 m² (KDIGO 2024). Logistic regression and ROC analyses assessed model performance. Results: Older age and higher blood pressure were associated with reduced GFR. The TGFB1 rs1800470 TT and ACE rs4343 AG genotypes significantly increased the risk of renal decline (adjusted OR 7.79 and 5.98, respectively; p < 0.05). The integrated clinical–genetic model achieved the highest discrimination (AUC = 0.859; sensitivity 78.9%; specificity 88.4%). Conclusion: Integrating ACE and TGFB1 genotypes with clinical factors enhances DKD risk prediction and supports early genotype-informed interventions. This approach strengthens population-specific precision nephrology in Indonesia and provides a foundation for future polygenic risk model development.