Proteomic and bioinformatic discovery of biomarkers for diabetic nephropathy

Evaluation of microalbuminuria in type-2 diabetes mellitus under oral hypoglycemic agents: Association with age, sex, BMI, and renal clearance

Background

Diabetes mellitus (DM) is increasing drastically and affecting the individuals globally, especially in the low- and middle-income countries like India. The poor glycaemic control results in micro-vascular and macro-vascular complications, leading to dysfunction of multiple organs. This study aimed to evaluate the association between the risk factors and microalbuminuria levels among patients with type 2 DM on oral hypoglycaemic agents.

Materials and Methods

Hundred type 2 DM patients fulfilling the inclusion and exclusion criteria were selected by convenient random sampling. Demographic details, biochemical markers, and anti-diabetic medication details were collected. The findings were analyzed statistically using Chi-square test and one-way analysis of variance (ANOVA) with SPSS software 21.0.

Results

Among the different combination therapies, 59% were commonly using metformin and teneligliptin. There was a significant association noted between microalbuminuria and risk factors like age, duration of disease, body mass index (BMI) (25.5 ± 2.9), fasting blood sugar (151 ± 53.2 mg/dL), post prandial blood sugar (227.01 ± 70.9 mg/dL), blood urea (24.42 ± 9.3 mg/dL), and serum creatinine (1.5 ± 0.2 mg/dL) (P < 0.001). One-way ANOVA showed statistical significance between microalbuminuria and the different treatment groups (P < 0.0001).

Conclusion

Microalbuminuria was associated with age, duration of diabetes, glycaemic control, and BMI. In contrast, there was no significant difference noted between the genders and microalbuminuria. Microalbuminuria is an early indication of nephropathy in diabetes patients. The early identification of the risk factors is important, and it is always recommended to screen for microalbuminuria in all the diabetic patients for early detection and prevention of diabetic nephropathy and their associated complications.

Investigating HMGB1 as a potential serum biomarker for early diabetic nephropathy monitoring by quantitative proteomics

Current diagnostic methods for diabetic nephropathy (DN) lack precision, especially in early stages and monitoring progression. This study aims to find potential biomarkers for DN progression and evaluate their accuracy. Using serum samples from healthy controls (NC), diabetic patients (DM), early-medium stage DN (DN-EM), and late-stage DN (DN-L), researchers employed quantitative proteomics and Mfuzz clustering analysis revealed 15 proteins showing increased expression during DN progression, hinting at their biomarker potential. Combining Mfuzz clustering with weighted gene co-expression network analysis (WGCNA) highlighted five candidates (HMGB1, CD44, FBLN1, PTPRG, and ADAMTSL4). HMGB1 emerged as a promising biomarker, closely correlated with renal function changes. Experimental validation supported HMGB1's upregulation under high glucose conditions, reinforcing its potential as an early detection biomarker for DN. This research advances DN understanding and identifies five potential biomarkers, notably HMGB1, as a promising early monitoring target. These findings set the stage for future clinical diagnostic applications in DN.