Correlation Between Serum 25-Hydroxyvitamin D Levels in Albuminuria Progression of Diabetic Kidney Disease and Underlying Mechanisms By Bioinformatics Analysis

The association between vitamin D and the progression of diabetic nephropathy: insights into potential mechanisms

Aims

Vitamin D deficiency (VDD) is prevalent in the population, with inadequate intake, impaired absorption and metabolism as the main causative factors. VDD increases the risk of developing chronic diseases such as type 2 diabetes mellitus (T2DM) and diabetic nephropathy (DN), but the molecular mechanisms underlying this phenomenon are not known. The aim of this study was to investigate the association and potential mechanisms of vitamin D levels with the progression of DN by analyzing general clinical data and using bioinformatics methods.

Methods

The study included 567 diabetes mellitus type 2 (T2DM) patients from the Rocket Force Characteristic Medical Center as the case group and 221 healthy examinees as the normal control group. T2DM patients were categorized into T2DM, early diabetic nephropathy (EDN), and advanced diabetic nephropathy (ADN) based on the progression of diabetic nephropathy. The renal RNA-seq and scRNA-seq data of patients with DN were mined from public databases, and the differential expression of vitamin D-related genes in normal-EDN-ADN was analyzed by bioinformatics method, protein interaction network was constructed, immune infiltration was evaluated, single cell map was drawn, and potential mechanisms of VD and DN interaction were explored.

Results

Chi-square test showed that vitamin D level was significantly negatively correlated with DN progression (p < 0.001). Bioinformatics showed that the expression of vitamin D-related cytochrome P450 family genes was down-regulated, and TLR4 and other related inflammatory genes were abnormally up-regulated with the progression of DN. Vitamin D metabolism disturbance up-regulate "Nf-Kappa B signaling pathway," B cell receptor signaling pathway and other immune regulation and insulin resistance related pathways, and inhibit a variety of metabolic pathways. In addition, vitamin D metabolism disturbance are strongly associated with the development of diabetic cardiomyopathy and several neurological disease complications.

Conclusion

VDD or vitamin D metabolism disturbance is positively associated with the severity of renal injury. The mechanisms may involve abnormal regulation of the immune system by vitamin D metabolism disturbance, metabolic suppression, upregulation of insulin resistance and inflammatory signalling pathways.

Unveiling FOS as a Potential Diagnostic Biomarker and Emetine as a Prospective Therapeutic Agent for Diabetic Nephropathy

Background

Diabetic nephropathy (DN) is one of the primary causes of end-stage renal disease, yet effective therapeutic targets remain elusive. This study aims to identify novel diagnostic biomarkers and potential therapeutic candidates for DN.

Methods

Differentially expressed genes (DEGs) in GSE96804 and GSE142025 were identified and functional enrichment analysis was performed. Diagnostic biomarkers were selected using machine learning algorithms and evaluated by Receiver Operating Characteristic analysis. c-Fos expression was validated in an established DN mouse model. Immune infiltration levels were assessed with Single-Sample Gene Set Enrichment Analysis. Co-expression analysis revealed regulatory relationships involving FOS. cMAP predicted potential therapeutic candidates. Transcriptome sequencing and experiments in RAW264.7 cells was performed to investigate molecular mechanisms of emetine.

Results

In both datasets, we identified 44 upregulated and 74 downregulated DEGs involved in focal adhesion, ECM-receptor interaction, and the PI3K-Akt signaling pathway. FOS emerged as a robust diagnostic marker with decreased expression in DN patients and DN mouse. Co-expression analysis revealed potential regulatory mechanisms of FOS, implicating the MAPK signaling pathway, regulation of cell proliferation and apoptotic signaling pathways. Immune dysregulation was observed in DN patients. Notably, emetine was identified as a potential therapeutic candidate. Transcriptome sequencing and experimental validation demonstrated emetine suppressed M1 macrophage polarization by inhibiting the activation of NF-κB signaling pathway, as well as reducing the expression of Il-18 and Ccl5.

Conclusion

In conclusion, our study identified FOS as a promising diagnostic biomarker and emetine as a potential therapeutic candidate for DN. These findings enhance our understanding of DN pathogenesis and present novel prospects for therapeutic strategies.

Identification of key biomarkers of the glomerulus in focal segmental glomerulosclerosis and their relationship with immune cell infiltration based on WGCNA and the LASSO algorithm

OBJECTIVE

The aim of our study was to identify key biomarkers of glomeruli in focal glomerulosclerosis (FSGS) and analyze their relationship with the infiltration of immune cells.

METHODS

The expression profiles (GSE108109 and GSE200828) were obtained from the GEO database. The differentially expressed genes (DEGs) were filtered and analyzed by gene set enrichment analysis (GSEA). MCODE module was constructed. Weighted gene coexpression network analysis (WGCNA) was performed to obtain the core gene modules. Least absolute shrinkage and selection operator (LASSO) regression was applied to identify key genes. ROC curves were employed to explore their diagnostic accuracy. Transcription factor prediction of the key biomarkers was performed using the Cytoscape plugin IRegulon. The analysis of the infiltration of 28 immune cells and their correlation with the key biomarkers were performed.

RESULTS

A total of 1474 DEGs were identified. Their functions were mostly related to immune-related diseases and signaling pathways. MCODE identified five modules. The turquoise module of WGCNA had significant relevance to the glomerulus in FSGS. TGFB1 and NOTCH1 were identified as potential key glomerular biomarkers in FSGS. Eighteen transcription factors were obtained from the two hub genes. Immune infiltration showed significant correlations with T cells. The results of immune cell infiltration and their relationship with key biomarkers implied that NOTCH1 and TGFB1 were enhanced in immune-related pathways.

CONCLUSION

TGFB1 and NOTCH1 may be strongly correlated with the pathogenesis of the glomerulus in FSGS and are new candidate key biomarkers. T-cell infiltration plays an essential role in the FSGS lesion process.

Identification of a copper metabolism-related gene signature for predicting prognosis and immune response in glioma

BACKGROUND

Gliomas are highly refractory intracranial cancers characterized by genetic and transcriptional heterogeneity. However, therapeutic options are limited. In the last years, copper-induced cell death is becoming a prospective treatment strategy for gliomas and other solid tumors, but copper metabolism-related genes associated with cancer development remain unclear.

METHODS

We first collected gene expression data from The Cancer Genome Atlas (TCGA) to identify significantly differentially expressed copper metabolism-related genes in gliomas. Using these genes, we performed COX regression and Least Absolute Shrinkage and Selection Operator (LASSO) regression to construct the prognostic model. The prognostic value of the model was further validated by CGGA testing set. Subsequently, functional analyses were carried out, including gene set enrichment analysis (GSEA), immune infiltration analysis, and mutation analysis. Finally, the expression levels of these genes were verified by immunohistochemical analysis.

RESULTS

The prognostic model consisted of 7 genes: CDK1, LOXL2, LOXL3, NFE2L2, SLC31A1, SUMF1 and FDX1. According to this prognosis model, glioma patients could be split into the high-risk group or low-risk group, and the low-risk group showed significantly better prognostic survival (p < 0.001). Moreover, the high-risk group had higher levels of immune cell infiltration, immune checkpoint genes expression, and higher tumor mutational burden (TMB), which indicates that they might benefit more from immunotherapy. Finally, we confirmed the expression level of FDX1, SUMF1, and SLC31A1 protein as significantly different in glioblastoma, lower-grade glioma, and non-tumor brain tissues by immunohistochemical analysis, and the high expression of FDX1 and SLC31A1 protein was related to poor survival in glioma patients.

CONCLUSIONS

Our study could contribute to the prognosis prediction and decision-making in patients with gliomas.

Identification of diagnostic markers related to oxidative stress and inflammatory response in diabetic kidney disease by machine learning algorithms: Evidence from human transcriptomic data and mouse experiments

INTRODUCTION

Diabetic kidney disease (DKD) is a long-term complication of diabetes and causes renal microvascular disease. It is also one of the main causes of end-stage renal disease (ESRD), which has a complex pathophysiological process. Timely prevention and treatment are of great significance for delaying DKD. This study aimed to use bioinformatics analysis to find key diagnostic markers that could be possible therapeutic targets for DKD.

METHODS

We downloaded DKD datasets from the Gene Expression Omnibus (GEO) database. Overexpression enrichment analysis (ORA) was used to explore the underlying biological processes in DKD. Algorithms such as WGCNA, LASSO, RF, and SVM_RFE were used to screen DKD diagnostic markers. The reliability and practicability of the the diagnostic model were evaluated by the calibration curve, ROC curve, and DCA curve. GSEA analysis and correlation analysis were used to explore the biological processes and significance of candidate markers. Finally, we constructed a mouse model of DKD and diabetes mellitus (DM), and we further verified the reliability of the markers through experiments such as PCR, immunohistochemistry, renal pathological staining, and ELISA.

RESULTS

Biological processes, such as immune activation, T-cell activation, and cell adhesion were found to be enriched in DKD. Based on differentially expressed oxidative stress and inflammatory response-related genes (DEOIGs), we divided DKD patients into C1 and C2 subtypes. Four potential diagnostic markers for DKD, including tenascin C, peroxidasin, tissue inhibitor metalloproteinases 1, and tropomyosin (TNC, PXDN, TIMP1, and TPM1, respectively) were identified using multiple bioinformatics analyses. Further enrichment analysis found that four diagnostic markers were closely related to various immune cells and played an important role in the immune microenvironment of DKD. In addition, the results of the mouse experiment were consistent with the bioinformatics analysis, further confirming the reliability of the four markers.

CONCLUSION

In conclusion, we identified four reliable and potential diagnostic markers through a comprehensive and systematic bioinformatics analysis and experimental validation, which could serve as potential therapeutic targets for DKD. We performed a preliminary examination of the biological processes involved in DKD pathogenesis and provide a novel idea for DKD diagnosis and treatment.

Dapagliflozin Ameliorates Renal Tubular Ferroptosis in Diabetes via SLC40A1 Stabilization

Tubular injury has been shown to play a critical role in the morbidity of diabetic kidney disease (DKD); ferroptosis often occurs in tubules during renal disease development. This study was aimed at evaluating the inhibitory effects and potential mechanism of dapagliflozin (DAPA) against diabetic-related ferroptosis in the kidney. C57BL/6 mice were fed a high-fat diet (HFD) for 12 weeks, administered a small dose of streptozocin (STZ) for three consecutive days by intraperitoneal injection, and then orally administered dapagliflozin (10 mg/kg/day) for 8 weeks. Mouse blood and urine samples were collected, and their renal cortices were harvested for subsequent investigations. The effects of DAPA were also evaluated in HK-2 cells subjected to simulated diabetic conditions through excess glucose or palmitic acid (PA) administration. DAPA significantly ameliorated tubular injury independently of glycemic control in diabetic model mice. In vivo and in vitro investigations showed that dapagliflozin ameliorated tubular injury by inhibiting ferroptosis. Docking experiments demonstrated that dapagliflozin and SLC40A1 could bind with each other and may consequently reduce ubiquitination degradation. In conclusion, in this study, the tubular protective effects of DAPA, irrespective of glycemic control, were observed in a diabetic mouse model. DAPA ameliorated ferroptosis during diabetic tubular injury via SLC40A1 stabilization, and this may be the mechanism underlying its action. To the best of our knowledge, this is the first study to investigate the ferroptosis inhibitory effects of DAPA in the treatment of DKD.