The Role of the Epidermal Growth Factor Receptor in Diabetic Kidney Disease

Network medicine based approach for identifying the type 2 diabetes, osteoarthritis and triple negative breast cancer interactome: Finding the hub of hub genes

The increasing prevalence of multi-morbidities, particularly the incidence of breast cancer in diabetic/osteoarthritic patients emphasize on the need for exploring the underlying molecular mechanisms resulting in carcinogenesis. To address this, present study employed a systems biology approach to identify switch genes pivotal to the crosstalk between diseased states resulting in multi-morbid conditions. Hub genes previously reported for type 2 diabetes mellitus (T2DM), osteoarthritis (OA), and triple negative breast cancer (TNBC), were extracted from published literature and fed into an integrated bioinformatics analyses pipeline. Thirty-one hub genes common to all three diseases were identified. Functional enrichment analyses showed these were mainly enriched for immune and metabolism associated terms including advanced glycation end products (AGE) pathways, cancer pathways, particularly breast neoplasm, immune system signalling and adipose tissue. The T2DM-OA-TNBC interactome was subjected to protein-protein interaction network analyses to identify meta hub/clustered genes. These were prioritized and wired into a three disease signalling map presenting the enriched molecular crosstalk on T2DM-OA-TNBC axes to gain insight into the molecular mechanisms underlying disease-disease interactions. Deciphering the molecular bases for the intertwined metabolic and immune states may potentiate the discovery of biomarkers critical for identifying and targeting the immuno-metabolic origin of disease.

Identification of key immune-related genes and potential therapeutic drugs in diabetic nephropathy based on machine learning algorithms

BACKGROUND

Diabetic nephropathy (DN) is a major contributor to chronic kidney disease. This study aims to identify immune biomarkers and potential therapeutic drugs in DN.

METHODS

We analyzed two DN microarray datasets (GSE96804 and GSE30528) for differentially expressed genes (DEGs) using the Limma package, overlapping them with immune-related genes from ImmPort and InnateDB. LASSO regression, SVM-RFE, and random forest analysis identified four hub genes (EGF, PLTP, RGS2, PTGDS) as proficient predictors of DN. The model achieved an AUC of 0.995 and was validated on GSE142025. Single-cell RNA data (GSE183276) revealed increased hub gene expression in epithelial cells. CIBERSORT analysis showed differences in immune cell proportions between DN patients and controls, with the hub genes correlating positively with neutrophil infiltration. Molecular docking identified potential drugs: cysteamine, eltrombopag, and DMSO. And qPCR and western blot assays were used to confirm the expressions of the four hub genes.

RESULTS

Analysis found 95 and 88 distinctively expressed immune genes in the two DN datasets, with 14 consistently differentially expressed immune-related genes. After machine learning algorithms, EGF, PLTP, RGS2, PTGDS were identified as the immune-related hub genes associated with DN. In addition, the mRNA and protein levels of them were obviously elevated in HK-2 cells treated with glucose for 24 h, as well as their mRNA expressions in kidney tissues of mice with DN.

CONCLUSION

This study identified 4 hub immune-related genes (EGF, PLTP, RGS2, PTGDS), as well as their expression profiles and the correlation with immune cell infiltration in DN.

Adiponectin mRNA Conjugated with Lipid Nanoparticles Specifically Targets the Pathogenesis of Type 2 Diabetes

Type 2 diabetes (T2D) is a widespread health condition both in the United States and around the world, with insulin resistance playing a critical role in its development. Effective treatment strategies are essential for managing T2D and mitigating associated risks. Adiponectin (APN), secreted by adipocytes, exhibits an inverse correlation with obesity-related adiposity, and its levels are negatively associated with insulin resistance and body mass index. This study aimed to enhance endogenous APN levels in a diet-induced obese (DIO) mouse model using lipid nanoparticles (LNP) as safe delivery agents for APN mRNA conjugates. The results indicate that APN-mRNA-LNP administration successfully induced APN synthesis in various tissues, including muscle, liver, kidney, pancreas, and adipose cells. This induction was associated with several positive outcomes, such as preventing diet-induced body weight gain, improving hyperglycemia by promoting Glut-4 expression, alleviating diabetic nephropathy symptoms by blocking the EGFR pathway, and reducing pro-inflammatory cytokine production. In addition, the treatment demonstrated enhanced insulin sensitivity by activating DGKd and inhibiting PKCε. This resulted in reactivation of insulin receptors in insulin target tissues and stimulation of insulin secretion from pancreatic beta cells. The findings of the present study highlight the potential of APN-mRNA-LNP-based nucleic acid therapy as a treatment for type 2 diabetes, offering a comprehensive approach to addressing its complexities.

Identification of Senescence-Associated Biomarkers in Diabetic Glomerulopathy Using Integrated Bioinformatics Analysis

Background

Cellular senescence is thought to play a significant role in the onset and development of diabetic nephropathy. The goal of this study was to explore potential biomarkers associated with diabetic glomerulopathy from the perspective of senescence.

Methods

Datasets about human glomerular biopsy samples related to diabetic nephropathy were systematically obtained from the Gene Expression Omnibus database. Hub senescence-associated genes were investigated by differential gene analysis and Least Absolute Shrinkage and Selection Operator analysis. Cluster analysis was employed to identify senescence molecular subtypes. A single-cell dataset was used to validate the above findings and further evaluate the senescence environment. The relationship between these genes and the glomerular filtration rate was explored based on the Nephroseq database. These gene expressions have also been explored in various kidney diseases.

Results

Twelve representative senescence-associated genes (VEGFA, IQGAP2, JUN, PLAT, ETS2, ANG, MMP14, VEGFC, SERPINE2, CXCR2, PTGES, and EGF) were finally identified. Biological changes in immune inflammatory response, cell cycle regulation, metabolic regulation, and immune microenvironment have been observed across different molecular subtypes. The above results were also validated based on single-cell analysis. Additionally, we also identified several significantly altered cell communication pathways, including COLLAGEN, PTN, LAMININ, SPP1, and VEGF. Finally, almost all these genes could well predict the occurrence of diabetic glomerulopathy based on receiver operating characteristic analysis and are associated with the glomerular filtration rate. These genes are differently expressed in various kidney diseases.

Conclusion

The present study identified potential senescence-associated biomarkers and further explored the heterogeneity of diabetic glomerulopathy that might provide new insights into the diagnosis, assessment, management, and personalized treatment of DN.

Exploring the possible mechanism(s) underlying the nephroprotective effect of Zhenwu Decoction in diabetic kidney disease: An integrated analysis

BACKGROUND

Diabetic kidney disease (DKD) is one of the major chronic microvascular complications of diabetes and the main cause of end-stage renal failure. Zhenwu Decoction (ZWD), an ancient classic herbal formula in Chinese medicine, has been clinically used for the treatment of kidney disease in China for many years. However, there is currently limited research investigating the application of ZWD in the treatment of DKD and the underlying chemical and biochemical mechanisms involved. Therefore, in the present study, we aimed to identify active components in ZWD and unravel the possible mechanism(s) of action for ZWD in treating DKD.

METHODS

The protective effect of ZWD against DKD was evaluated utilizing an in vitro model of diabetic renal proximal tubulopathy. The major chemical components from ZWD were identified by LC-MS/MS. Drug targets were predicted by submitting the SMILES (Simplified Molecular Input Line Entry System) of the compounds to SEA (Similarity Ensemble Approach) search server and SwissTargetPrediction. The differentially expressed genes (DEGs) of the disease were collected and integrated from GeneCards. The constructions of "Compounds-potential targets interaction" (CTI) network and Protein-Protein Interaction (PPI) network, as well as topology analysis were conducted by Cytoscape. Gene Ontology (GO) enrichment and Metacore pathway enrichment analysis were also performed. Lastly, molecular docking and experimental studies were adopted to validate the core target and identify an active component(s) of ZWD.

RESULTS

We demonstrated that the ZWD extract could significantly rescue the palmitic acid (PA) and high glucose-induced apoptotic cell death in HK-2 cells, and the cytoprotection was accompanied by decreases in the extent of reactive oxygen species (ROS) production, mitochondrial membrane depolarization and ATP depletion. Fifty-seven compounds in the aqueous extract of ZWD were identified by LC-MS. The results of PPI analysis showed that top hub genes involved epidermal growth factor receptor (EGFR), Signal Transducer and Activator of Transcription 3 (STAT3), Serine/Threonine Kinase 1 (AKT1), Vascular Endothelial Growth Factor A (VEGFA) and Fibroblast Growth Factor 2 (FGF2). Pathway enrichment analysis revealed the involvement of S1P1 receptor signaling and EGFR pathways. The results of molecular docking analysis showed that albiflorin has a high binding affinity to EGFR. Albiflorin could also exert protective effects in an HK-2 cell model of DKD, which may be related to the inhibition of the high glucose/high lipid-induced EGFR and Akt phosphorylation.

CONCLUSION

ZWD has been shown to be effective in ameliorating cell death in an experimental model of DKD. The beneficial effect of ZWD against DKD was associated with the interactions between the active ingredients and the hub genes, such as EGFR, STAT3, AKT1, and VEGF-A. Albiflorin may be one of the active components responsible for the nephroprotective effect in ZWD.

Hippo signaling in acute kidney injury to chronic kidney disease transition: current understandings and future targets

Acute kidney injury (AKI)-to-chronic kidney disease (CKD) transition is a slow but persistent progression toward end-stage kidney disease. Earlier reports have shown that Hippo components, such as Yes-associated protein (YAP) and its homolog TAZ (Transcriptional coactivator with PDZ-binding motif), regulate inflammation and fibrogenesis during the AKI-to-CKD transition. Notably, the roles and mechanisms of Hippo components vary during AKI, AKI-to-CKD transition, and CKD. Hence, it is important to understand these roles in detail. This review addresses the potential of Hippo regulators or components as future therapeutic targets for halting the AKI-to-CKD transition.