Construction of a metabolic-immune model for predicting the risk of diabetic nephropathy and study of gut microbiota.

Abstract

Aims: This study conducts a comprehensive analysis of the relative impact of risk factors for diabetic nephropathy (DN) during disease progression, with a particular emphasis on the role of gut microbiota. We developed multiple predictive models trying to enhance the early identification of high-risk patients in clinical practice.

Materials and methods: We collected data from type 2 diabetes mellitus patients, categorizing them by renal function for comparison. Logistic regression identified risk factors for DN, and we developed nomogram and random forest risk prediction models. Finally, we analyzed the correlations among these factors.

Results: Compared to patients with diabetes alone, those with DN have a longer disease duration, characterized by abdominal obesity, hypertension, chronic inflammation, activation of the complement system, and declining renal function, along with a significant reduction in Bifidobacterium and Enterobacterium. Patients with macroalbuminuria exhibit a higher male prevalence, as well as elevated blood pressure and lipid levels, and poorer renal function. Increased waist-to-hip ratio, systolic blood pressure, urea, neutrophil-to-lymphocyte ratio, and complement C3, along with decreased Enterobacterium and albumin, have been identified as significant risk factors for DN. The nomogram model developed based on these findings demonstrates good predictive capacity. And the establishment of the random forest model further underscores the importance of the aforementioned indicators. Additionally, significant correlations were observed among obesity, inflammation, blood pressure, lipid levels, and gut microbiota.

Conclusions: Dysbiosis, metabolic disorders, and chronic inflammation play key roles in the progression of DN and may serve as new targets for future prevention and treatment strategies.