Association analysis of PTPN1 gene SNP with retinopathy and nephropathy in type 2 diabetes mellitus and development of predictive line graph in Chinese population.
Our research endeavored to formulate a patient-specific prognostic algorithm and elucidate the interconnection between critical genetic polymorphisms at PTPN1 loci and the predisposition to small vessel pathologies in Han Chinese subjects presenting with T2DM. From January 1, 2019, to June 30, 2024, a total of 3,847 patients with T2DM were enrolled in this cross-sectional case-control study. They were grouped into four groups by means of fundus examination and renal function assessment: the T2DM alone group (T2DM group), the T2DM combined with diabetic retinopathy (DR) group (T2DM + DR group), the T2DM combined with diabetic nephropathy (DN) group (T2DM + DN group), and the T2DM combined with DR + DN group (T2DM + DR +DN group). The genotypes of four SNP loci (rs968289, rs6067484, rs2206521, rs754118) of the PTPN1 gene were detected by PCR-RFLP. To evaluate the association between SNP loci and microvascular complications, multivariate logistic regression analysis was employed, followed by LASSO regression for variable selection to develop a nomogram prediction model. The rs968289-GG genotype demonstrated a statistically significant link to the risk of DR (adjusted OR = 1.47, 95%CI: 1.15-1.88, P = 0.002); the rs6067484-CC genotype exhibited a significant relationship with the risk of DN (adjusted OR = 1.58, 95%CI: 1.21-2.06, P < 0.001); The rs2206521-AA genotype significantly correlated with the risk of DR + DN co-morbidity (adjusted OR = 1.69, 95%CI: 1.28-2.24, P < 0.001). The column-line graphical model constructed based on nine independent predictors had AUCs of 0.823 and 0.808 in the training and validation sets, with sensitivity and specificity of 76.4%/78.9% and 74.2%/80.1%, respectively. Significant associations were observed between specific genotypic variants at the PTPN1 gene's rs968289, rs6067484 and rs2206521 loci and microvascular complication risk in Chinese Han T2DM patients. The column-line graph prediction model integrating genetic markers and clinical indicators has good discriminative ability and clinical utility, providing an important tool for individualized risk assessment and precise prevention of diabetic microvascular complications.