Bioinformatics prediction and experimental verification of key biomarkers for diabetic kidney disease based on transcriptome sequencing in mice

Bioinformatic analyses reveal lysosomal-associated protein transmembrane 5 as a potential therapeutic target in lipotoxicity-induced injury in diabetic kidney disease

Emerging data have revealed that damage to tubular epithelial cell is a driving force in the progression of diabetic kidney disease (DKD). However, the specific mechanisms by which lipotoxicity contributes to the injury of these cells, thereby influencing the development of DKD, are yet to be fully understood. Here, we analyzed the GSE 30529 microarray datasets of human tubulointerstitial tissue samples from the Gene Expression Omnibus database (GEO). Concurrently, we conducted RNA-sequencing on palmitic acid (PA)-treated human renal proximal tubule epithelial cells (HK2 cells). After normalization, the differentially expressed genes (DEGs) were screened by R software and gene ontology (GO) enrichment analysis was conducted, and lysosomal-associated protein transmembrane 5 (LAPTM5) was finally selected. Our findings indicate that the expression of LAPTM5 was obviously increased in DKD patients, and the correlation between LAPTM5, and other clinical parameters of DKD was analyzed using the Spearman correlation analysis. The potential of LAPTM5 as a prognostic biomarker for DKD was further consolidated through receiver operating characteristic (ROC) analysis. To further verify the function of LAPTM5, we established mouse or in vitro systems mimicking DKD. The results showed that a consistent upregulation of LAPTM5, which was also found to be linked with inflammatory mediators within the context of DKD. Additionally, LAPTM5 silencing significantly downregulated mRNA expression of inflammatory factors in PA-treated HK2 cells. These results indicate that LAPTM5 is a potential biomarker and therapeutic treatment target for DKD. This discovery paves the way for future research and development of targeted interventions aimed at mitigating the progression of this prevalent condition.

The Influence of Soy Isoflavones and Soy Isoflavones with Inulin on Kidney Morphology, Fatty Acids, and Associated Parameters in Rats with and without Induced Diabetes Type 2

Diabetes mellitus resulting from hyperglycemia stands as the primary cause of diabetic kidney disease. Emerging evidence suggests that plasma concentrations of soy isoflavones, substances with well-established antidiabetic properties, rise following supplemental inulin administration. The investigation encompassed 36 male Sprague-Dawley (SD) rats segregated into two cohorts: non-diabetic and diabetic, induced with type 2 diabetes (high-fat diet + two intraperitoneal streptozotocin injections). Each cohort was further divided into three subgroups (n = 6): control, isoflavone-treated, and isoflavone plus inulin-treated rats. Tail blood glucose and ketone levels were gauged. Upon termination, blood samples were drawn directly from the heart for urea, creatinine, and HbA1c/HbF analyses. One kidney per rat underwent histological (H-E) and immunohistochemical assessments (anti-AQP1, anti-AQP2, anti-AVPR2, anti-SLC22A2, anti-ACC-alpha, anti-SREBP-1). The remaining kidney underwent fatty acid methyl ester analysis. Results unveiled notable alterations in water intake, body and kidney mass, kidney morphology, fatty acids, AQP2, AVPR2, AcetylCoA, SREBP-1, blood urea, creatinine, and glucose levels in control rats with induced type 2 diabetes. Isoflavone supplementation exhibited favorable effects on plasma urea, plasma urea/creatinine ratio, glycemia, water intake, and kidney mass, morphology, and function in type 2 diabetic rats. Additional inulin supplementation frequently modulated the action of soy isoflavones.

Identification of potential key lipid metabolism-related genes involved in tubular injury in diabetic kidney disease by bioinformatics analysis

AIMS

Accumulating evidences indicate that abnormalities in tubular lipid metabolism play a crucial role in the development of diabetic kidney disease (DKD). We aim to identify novel lipid metabolism-related genes associated with tubular injury in DKD by utilizing bioinformatics approaches.

METHODS

Differentially expressed genes (DEGs) between control and DKD tubular tissue samples were screened from the Gene Expression Omnibus (GEO) database, and then were intersected with lipid metabolism-related genes. Hub genes were further determined by combined weighted gene correlation network analysis (WGCNA) and protein-protein interaction (PPI) network. We performed enrichment analysis, immune analysis, clustering analysis, and constructed networks between hub genes and miRNAs, transcription factors and small molecule drugs. Receiver operating characteristic (ROC) curves were employed to evaluate the diagnostic efficacy of hub genes. We validated the relationships between hub genes and DKD with external datasets and our own clinical samples.

RESULTS

There were 5 of 37 lipid metabolism-related DEGs identified as hub genes. Enrichment analysis demonstrated that lipid metabolism-related DEGs were enriched in pathways such as peroxisome proliferator-activated receptors (PPAR) signaling and pyruvate metabolism. Hub genes had potential regulatory relationships with a variety of miRNAs, transcription factors and small molecule drugs, and had high diagnostic efficacy. Immune infiltration analysis revealed that 13 immune cells were altered in DKD, and hub genes exhibited significant correlations with a variety of immune cells. Through clustering analysis, DKD patients could be classified into 3 immune subtypes and 2 lipid metabolism subtypes, respectively. The tubular expression of hub genes in DKD was further verified by other external datasets, and immunohistochemistry (IHC) staining showed that except ACACB, the other 4 hub genes (LPL, AHR, ME1 and ALOX5) exhibited the same results as the bioinformatics analysis.

CONCLUSION

Our study identified several key lipid metabolism-related genes (LPL, AHR, ME1 and ALOX5) that might be involved in tubular injury in DKD, which provide new insights and perspectives for exploring the pathogenesis and potential therapeutic targets of DKD.

Lipid metabolism disorder in diabetic kidney disease

Diabetic kidney disease (DKD), a significant complication associated with diabetes mellitus, presents limited treatment options. The progression of DKD is marked by substantial lipid disturbances, including alterations in triglycerides, cholesterol, sphingolipids, phospholipids, lipid droplets, and bile acids (BAs). Altered lipid metabolism serves as a crucial pathogenic mechanism in DKD, potentially intertwined with cellular ferroptosis, lipophagy, lipid metabolism reprogramming, and immune modulation of gut microbiota (thus impacting the liver-kidney axis). The elucidation of these mechanisms opens new potential therapeutic pathways for DKD management. This research explores the link between lipid metabolism disruptions and DKD onset.

Integrative ATAC-seq and RNA-seq analysis associated with diabetic nephropathy and identification of novel targets for treatment by dapagliflozin

Dapagliflozin (DAPA) are clinically effective in improving diabetic nephropathy (DN). However, whether and how chromatin accessibility changed by DN responds to DAPA treatment is unclear. Therefore, we performed ATAC-seq, RNA-seq, and weighted gene correlation network analysis to identify the chromatin accessibility, the messenger RNA (mRNA) expression, and the correlation between clinical phenotypes and mRNA expression using kidney from three mouse groups: db/m mice (Controls), db/db mice (case group), and those treated with DAPA (treatment group). RNA-Seq and ATAC-seq conjoint analysis revealed many overlapping pathways and networks suggesting that the transcriptional changes of DN and DAPA intervention largely occured dependently on chromatin remodeling. Specifically, the results showed that some key signal transduction pathways, such as immune dysfunction, glucolipid metabolism, oxidative stress and xenobiotic and endobiotic metabolism, were repeatedly enriched in the analysis of the RNA-seq data alone, as well as combined analysis with ATAC-seq data. Furthermore, we identified some candidate genes (UDP glucuronosyltransferase 1 family, Dock2, Tbc1d10c, etc.) and transcriptional regulators (KLF6 and GFI1) that might be associated with DN and DAPA restoration. These reversed genes and regulators confirmed that pathways related to immune response and metabolism pathways were critically involved in DN progression.

Network pharmacology and molecular dynamic simulation integrated strategy for the screening of active components and mechanisms of phytochemicals from Datura innoxia on Alzheimer and cognitive decline

Alzheimer's disease (AD) ranks as the most prevalent neurodegenerative disorder with dementia and it accounts for more than 70% of all cases. Despite extensive reporting on the experimental investigation of Datura innoxia (DI) and its phytochemical components in the treatment of AD, the urgent need for elucidation of the principle of multi-mechanism and multi-level treatment of AD remains. In this research, molecular docking and network pharmacology were used to evaluate active compounds and molecular targets of DI for the treatment of AD. The phytochemical compounds of DI were obtained from the Indian Medicinal Plants, Phytochemistry, and Therapeutics (IMPPAT) as well as the Traditional Chinese Medicine System Pharmacology (TCMSP) databases. The screening includes the 28 most abundant components of DI and the Swiss Target Prediction database was used to predict targets of these compounds. The GeneCards database was used to collect AD-related genes. Both DI and AD targets were imported into a Venn diagram, and the 28 overlapped genes were identified as potential DI anti-AD targets. The results showed that Dinoxin B, Meteloidine, Scopoline, and Tropic acid had no effect on AD-related genes. Furthermore, the GO enrichment analysis indicates that DI influences molecular functions and biological processes such as learning or memory and modulation of chemical synaptic transmission as well as the membrane raft and membrane microdomain. The KEGG pathway analysis revealed that the key pathways implicated in DI's anti-AD actions include serotonergic synapse, IL-17 signaling pathway, and AGE-RAGE signaling pathway in diabetic complications. Based on the STRING and Cytoscape network-analysis platforms, the top ten anti-AD core targets include APP, CASP3, IL6, BACE1, IL1B, ACE, PSEN1, GAPDH, GSK3B and ACHE. The molecular docking and molecular dynamic simulation of the top two molecules against the top three target proteins confirmed the strong binding affinity and stability at the docked site. Overall, our findings pave the path for further research into the development and optimization of potential anti-AD agents from DI.Communicated by Ramaswamy H. Sarma.

Network pharmacology based virtual screening of Flavonoids from Dodonea angustifolia and the molecular mechanism against inflammation

Inflammation is a nonspecific immune response against injury caused by a harmful agent that strives to restore tissue function and homeostasis. Dodonaea angustifolia L.f. (Sapindaceae) is a medium-sized shrub used to treat a variety of diseases in traditional medicine. In the current study, integrated network-pharmacology and molecular docking approaches were used to identify the active constituents, their possible targets, signaling pathways, and anti-inflammatory effects of flavonoids from D.angustifolia. D. angustifolia active ingredients were acquired from the Indian Medicinal Plants, Phytochemistry and Therapeutics (IMPPAT), and Traditional Chinese Medicine System Pharmacology (TCMSP) databases. The screening included the ten most prevalent D. angustifolia components, and the SwissTargetPrediction database was utilized to anticipate the targets of these compounds. Anti-inflammatory genes were found using the GeneCards database. The 175 overlapping genes were discovered as prospective D. angustifolia anti-inflammatory targets. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that the overlapped targets were closely related to the major pathogenic processes linked to inflammation, such as response to organonitrogen compound, protein kinase activity, phosphotransferase activity, pI3k-Akt signaling pathway, metabolic pathways, and chemical carcinogenesis. Compound-target-pathway, and protein-protein interaction networks revealed 6-Methoxykaempferol and 5-Hydroxy-7,8 dimethoxyflavone as key compounds, and AKT1, VEGFA, and EGFR as key targets. Furthermore, molecular docking followed by molecular dynamic (MD) simulation of D. angustifolia active ingredients with core proteins fully complemented the binding affinity of these compounds and indicated stable complexes at the docked site. These findings reveal D. angustifolia 's multi-target, multi-compound, and multi-pathway strategies against inflammation. Our study paved the way for further research into the mechanism for developing D. angustifolia -based natural products as alternative therapies for inflammation.

Single-Cell Transcriptional Landscape Reveals the Regulatory Network and Its Heterogeneity of Renal Mitochondrial Damages in Diabetic Kidney Disease

Diabetic kidney disease (DKD) is one of the common chronic microvascular complications of diabetes in which mitochondrial disorder plays an important role in its pathogenesis. The current study delved into the single-cell level transcriptome heterogeneity of mitochondrial homeostasis in db/db mice, an animal model for study of type 2 diabetes and DKD, with single-cell RNA sequencing (scRNA-Seq) and bulk RNA-seq analyses. From the comprehensive dataset comprising 13 meticulously captured and authenticated renal cell types, an unsupervised cluster analysis of mitochondria-related genes within the descending loop of Henle, collecting duct principal cell, endothelial, B cells and macrophage, showed that they had two types of cell subsets, i.e., health-dominant and DKD-dominant clusters. Pseudotime analysis, cell communication and transcription factors forecast resulted in identification of the hub differentially expressed genes between these two clusters and unveiled that the hierarchical regulatory network of receptor-TF-target genes was triggered by mitochondrial degeneration. Furthermore, the collecting duct principal cells were found to be regulated by the decline of Fzd7, which contributed to the impaired cellular proliferation and development, apoptosis and inactive cell cycle, as well as diminished capacity for material transport. Thereby, both scRNA-Seq and bulk RNA-Seq data from the current study elucidate the heterogeneity of mitochondrial disorders among distinct cell types, particularly in the collecting duct principal cells and B cells during the DKD progression and drug administration, which provide novel insights for better understanding the pathogenesis of DKD.