Role of serum β2-microglobulin, glycosylated hemoglobin, and vascular endothelial growth factor levels in diabetic nephropathy

Study of the relationship between the level of proinflammatory cytokines and β2-microglobulin with indicators of changes in the functional status of the kidneys in diabetic nepropathy to determine the degrees of chronic renal failure

OBJECTIVE

Aim: The purpose of this study is to analyze the correlations of pro-inflammatory cytokines and β2-microglobulin with indicators of changes in the functional state of kidneys in patients with diabetic nephropathy, to determine different degrees of chronic renal failure.

PATIENTS AND METHODS

Materials and Methods: 80 patients with type 1 and type 2 diabetes, complicated by diabetic nephropathy, at different levels of the functional state of the kidneys were examined.

RESULTS

Results: It has been shown that the level of tumor necrosis factor α (TNFα) in the blood of patients with diabetic nephropathy (DN) is increased already with sufficient kidney function, decreases with chronic renal failure (CRF) of the I degree and reaches maximum values with CRF of the II and III degrees. Which indicates the degree of progression of fibroplastic and sclerotic processes in the kidneys with DN. The level of interleukin-1α (IL-1α) in the blood of patients with DN begins to decrease with sufficient kidney function, increases with CRF of the II degree, but remains below the values of the control group and is minimal in patients with CRF of the III degree, which reflects a decrease in the intensity of the acute-phase inflammatory process in the development of CRF.

CONCLUSION

Conclusions: The development and progression of CRF is accompanied by an increase in the excretion of β2-microglobulin in the urine in parallel with changes in the cytokine profile in the blood.

A semantic segmentation method to analyze retinal vascular parameters of diabetic nephropathy

Introduction

By using spectral domain optical coherence tomography (SD-OCT) to measure retinal blood vessels. The correlation between the changes of retinal vascular structure and the degree of diabetic nephropathy is analyzed with a full-pixel Semantic segmentation method.

Methods

A total of 120 patients with diabetic nephropathy who were treated in the nephrology department of Quzhou People's Hospital from March 2023 to March 2024 were selected and divided into three groups according to the urinary albumin creatinine ratio (UACR). The groups included simple diabetes group (UACR < 30 mg/g), microalbuminuria group (30 mg/g ≤ UACR <300 mg/g) and macroalbuminuria group (UACR ≥300 mg/g). SD-OCT was used to scan the arteries and veins in the superior temporal area B of the retina. The semantic segmentation method built into the SD-eye software was used to automatically identify the morphology and structure of the vessels and calculate the parameters of arteriovenous vessels. The parameters of arteriovenous vessels are as follows: outer diameter of the retinal artery (RAOD); inner diameter of the retinal artery (RALD); arterial wall thickness (AWT); arterial wall to lumen ratio (AWLR); cross sectional area of arterial wall (AWCSA); retinal vein outer diameter (RVOD); retinal vein inner diameter (RVLD); vein wall thickness (VWT); vein wall to lumen ratio (VWLR); cross sectional area of vein wall (VWCSA). Statistical analysis software was used to compare and analyze the parameters of retinal arteriovenous vessels of the three groups.

Results

The study revealed statistically significant differences in RAOD and RALD among the three groups (p < 0.05) with the RAOD and RALD of the macroalbuminuria group and microalbuminuria group being lower than those of the simple diabetes group. Conversely, there were no significant differences in AWT, AWLR and AWCSA among the three groups (p > 0.05). Additionally, the differences in RVOD and RVLD among the three groups were found to be statistically significant (p < 0.05) with the RVOD and RVLD of the simple diabetes group being lower than those of the microalbuminuria group and macroalbuminuria group. No significant differences were observed in VWT and VWL among the groups. Additionally, RVOD and RVLD were weakly associated with UACR (R = 0.247, p = 0.007; R = 0.210, p = 0.021). Full-pixel semantic segmentation method combined with OCT images is a new retinal vascular scanning technology, which can be used as a new method for early diagnosis of diabetic nephropathy. The structural changes of retinal vessels can be used to predict the severity of diabetic nephropathy during the development of diabetic nephropathy.

Serum VEGF as a predictive marker of glycemic control and diabetic nephropathy in Chinese older adults with type 2 diabetes mellitus

Objectives

Recent researches have demonstrated good correlation between vascular endothelial growth factor (VEGF) and diabetic nephropathy (DN); however, this relationship seems less clear-cut when VEGF was measured in blood samples. We tended to explore the possible association between serum VEGF and glycemic control and diabetic nephropathy severity in Chinese older adults with type 2 diabetes mellitus (T2DM).

Materials and methods

This study retrospectively enrolled 595 older T2DM adults at random. Participants were clinically grouped across the urine albumin-to-creatinine ratio (UACR) and the HbA1c tertiles by genders. Linear regressions were performed for the correlation of VEGF with HbA1c and UACR and binary logistic regressions for the odds of DN after adjusting for confounders. The receiver operating characteristic (ROC) curves were conducted for the predictive value of VEGF for DN.

Results

Both males and females with DN exhibited higher VEGF levels than non-DN (P < 0.001). Furthermore, a positive correlation of VEGF with UACR and HbA1c was presented regardless of adjusting confounding factors (P < 0.001). Serum VEGF level and fasting plasma glucose (FPG) were independent risk factors of DN in older adults of both genders (P < 0.05), while the risk prediction of DN by HbA1c only reflected in female patients (P < 0.05). The ROC curve of VEGF for DN had the area under curve (AUC) of 0.819 for males and 0.793 for females, indicating the clinical value of serum VEGF as a predictive biomarker.

Conclusions

Serum VEGF was strongly associated with UACR and HbA1c in both genders, and could be regarded as a predictive biomarker for glycemic control and diabetic nephropathy in older adults with T2DM.

Bioinformatics led discovery of biomarkers related to immune infiltration in diabetes nephropathy

BACKGROUND

The leading cause of end-stage renal disease is diabetic nephropathy (DN). A key factor in DN is immune cell infiltration (ICI). It has been shown that immune-related genes play a significant role in inflammation and immune cell recruitment. However, neither the underlying mechanisms nor immune-related biomarkers have been identified in DNs. Using bioinformatics, this study investigated biomarkers associated with immunity in DN.

METHODS

Using bioinformatic methods, this study aimed to identify biomarkers and immune infiltration associated with DN. Gene expression profiles (GSE30528, GSE47183, and GSE104948) were selected from the Gene Expression Omnibus database. First, we identified 23 differentially expressed immune-related genes and 7 signature genes, LYZ, CCL5, ALB, IGF1, CXCL2, NR4A2, and RBP4. Subsequently, protein-protein interaction networks were created, and functional enrichment analysis and genome enrichment analysis were performed using the gene ontology and Kyoto Encyclopedia of Genes and Genome databases. In the R software, the ConsensusClusterPlus package identified 2 different immune modes (cluster A and cluster B) following the consistent clustering method. The infiltration of immune cells between the 2 clusters was analyzed by applying the CIBERSORT method. And preliminarily verified the characteristic genes through in vitro experiments.

RESULTS

In this study, the samples of diabetes nephropathy were classified based on immune related genes, and the Hub genes LYZ, CCL5, ALB, IGF1, CXCL2, NR4A2 and RBP4 related to immune infiltration of diabetes nephropathy were obtained through the analysis of gene expression differences between different subtypes.

CONCLUSIONS

This study was based on bioinformatics technology to analyze the biomarkers of immune related genes in diabetes nephropathy. To analyze the pathogenesis of diabetes nephropathy at the RNA level, and ultimately provide guidance for disease diagnosis, treatment, and prognosis.