Identification of key genes and pathways in diabetic nephropathy by bioinformatics analysis

Sevoflurane blocks KLF5-mediated transcriptional activation of ITGB2 to inhibit macrophage infiltration in hepatic ischemia/reperfusion injury

BACKGROUND

Sevoflurane (Sevo) preconditioning and postconditioning play a protective role against injury induced by hepatic ischemia/reperfusion (I/R). At the same time, the involvement of macrophage infiltration in this process and the precise mechanisms are unclear. Here, we designed this research to elucidate the protective effects of Sevo against hepatic I/R injury and the molecules involved.

METHODS

The alleviating effect of Sevo on the liver injury was analyzed by liver function analysis, hematoxylin and eosin staining, Masson trichrome staining, terminal deoxynucleotidyl transferase-mediated 2'-deoxyuridine 5'-triphosphate nick end labeling, western blot analysis and an enzyme-linked immunosorbent assay. An in vitro cell model was developed using alpha mouse liver 12 (AML12) cells, and the cell model was treated with oxygen-glucose deprivation and reoxygenation and Sevo. Multiple bioinformatics databases were used to screen transcriptional regulators related to hepatic I/R injury and the targets of Krueppel-like factor 5 (KLF5). KLF5 expression was artificially upregulated alone or with integrin beta-2 (ITGB2) knockdown to substantiate their involvement in Sevo-mediated hepatoprotection.

RESULTS

Sevo protected the liver against I/R injury by reducing cell apoptosis and inflammatory response. KLF5 was upregulated in liver tissues following I/R injury, whereas KLF5 overexpression aggravated macrophage infiltration and liver injury induced by I/R injury. KLF5 bound to the promoter of ITGB2 to enhance ITGB2 transcription. Knockdown of ITGB2 reversed the aggravation of injury caused by KLF5 overexpression in mice and AML12 cells.

CONCLUSIONS

Sevo blocked KLF5-mediated transcriptional activation of ITGB2, thereby inhibiting macrophage infiltration in hepatic I/R injury.

Single-cell transcriptomics reveals the ameliorative effect of rosmarinic acid on diabetic nephropathy-induced kidney injury by modulating oxidative stress and inflammation

Diabetic nephropathy (DN) is a severe complication of diabetes, characterized by changes in kidney structure and function. The natural product rosmarinic acid (RA) has demonstrated therapeutic effects, including anti-inflammation and anti-oxidative-stress, in renal damage or dysfunction. In this study, we characterized the heterogeneity of the cellular response in kidneys to DN-induced injury and RA treatment at single cell levels. Our results demonstrated that RA significantly alleviated renal tubular epithelial injury, particularly in the proximal tubular S1 segment and on glomerular epithelial cells known as podocytes, while attenuating the inflammatory response of macrophages, oxidative stress, and cytotoxicity of natural killer cells. These findings provide a comprehensive understanding of the mechanisms by which RA alleviates kidney damage, oxidative stress, and inflammation, offering valuable guidance for the clinical application of RA in the treatment of DN.

Novel biomarkers related to oxidative stress and immunity in chronic kidney disease

Introduction

The incidence of chronic kidney disease (CKD) has been increasing in recent years, gradually becoming a global health crisis. Due to limited treatment options, novel molecular pathways are urgently required to advance the treatment and diagnosis of CKD.

Materials and methods

The characteristics of differentially expressed genes (DEGs) in CKD patients were analyzed using Gene Expression Omnibus (GEO) database, and genes related to oxidative stress were retrieved from the Genecard database. Subsequently, a comprehensive approach was applied, including immune infiltration analysis, weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis, to identify hub genes among differentially expressed immune-related oxidative stress genes (DEIOSGs). Validation of hub genes was performed using an external data set, and diagnostic potential capability was evaluated through receiver operating curve (ROC) analysis. In animal experiments, the expression of hub genes in CKD was confirmed by inducing a CKD model through a 5/6 nephrectomy procedure. Finally, the relationship between these hub genes and clinical characteristics were assessed using the Nephroseq v5 database.

Results

29 DEIOSGs were identified by comprehensive bioinformatics analysis. PPI analysis screened the hub genes NCF2, S100A9, and SELL. ROC analysis demonstrated excellent diagnostic efficacy. Further validation from other databases and animal experiments confirmed a substantial upregulation in the expression of hub genes in CKD. Additionally, clinical correlation analysis established a clear link between hub gene expression and renal function deterioration.

Conclusions

Our study confirms NCF2, S100A9, and SELL as diagnostic biomarkers associated with immune response and oxidative stress in CKD, suggesting their potential as novel targets for CKD diagnosis and treatment.

METTL3/YTHDF2 m6A axis mediates the progression of diabetic nephropathy through epigenetically suppressing PINK1 and mitophagy

AIMS

This research aimed to investigate the specific mechanism of methyltransferase like 3 (METTL3) in the progression of diabetic kidney disease (DKD).

MATERIALS AND METHODS

The model of diabetic kidney disease was established with HK-2 cells and mice in vitro and in vivo. The N6 methyladenosine (m6A) contents in the cells and tissues were detected with a commercial kit and the m6A levels of PTEN induced putative kinase 1 (PINK2) were detected with a MeRIP kit. The mRNA and protein levels were determined with RT-qPCR and western blot. The ROS, TNF-α, and IL-6 levels were assessed with ELISA. The cell proliferative ability was measured by a CCK-8 assay and cell apoptosis was determined with TUNEL staining. The HE and Masson staining was performed to observe the renal morphology. The RIP assay was conducted to detect the interaction between METTL3/YTHDF2 and PINK1.

RESULTS

The m6A content and METTL3 levels were prominently elevated in diabetic kidney disease. METTL3 silencing promoted the cell growth and the expression of LC3 II, PINK1, and Parkin, while inhibiting the cell apoptosis and the expression of LC3 I and p62 in the high glucose (HG) stimulated HK-2 cells. METTL3 silencing also decreased the ROS, TNF-α, and IL-6 levels in diabetic kidney disease. PINK1 silencing neutralized the function of sh-METTL3 in the HG stimulated HK-2 cells. The HE and Masson staining showed that METTL3 silencing alleviated the kidney injury induced by DKD. METTL3 silencing decreased the m6A levels of PINK1, while increased the mRNA levels of PINK1 which depended on YTHDF2.

CONCLUSIONS

METTL3 silencing could inhibit the progression of diabetic nephropathy in vivo and in vitro by regulating the m6A modification of PINK1, which depends on YTHDF2. Our research lays the theoretical foundation for the precise treatment of diabetic kidney disease and the development of targeted drugs in the future.

Single-Cell Sequencing Reveals the Expression of Immune-Related Genes in Macrophages of Diabetic Kidney Disease

Diabetic kidney disease (DKD) is characterized by macrophage infiltration, which requires further investigation. This study aims to identify immune-related genes (IRGs) in macrophage and explore their potential as therapeutic targets. This study analyzed isolated glomerular cells from three diabetic mice and three control mice. A total of 59 glomeruli from normal kidney samples and 66 from DKD samples were acquired from four kidney transcriptomic profiling datasets. Bioinformatics analysis was conducted using both single-cell RNA (scRNA) and bulk RNA sequencing data to investigate inflammatory responses in DKD. Additionally, the "AUCell" function was used to investigate statistically different gene sets. The significance of each interaction pair was determined by assigning a probability using "CellChat." The study also analyzed the biological diagnostic importance of immune hub genes for DKD and validated the expression of these immune genes in mice models. The top 2000 highly variable genes (HVGs) were identified after data normalization. Subsequently, a total of eight clusters were identified. It is worth mentioning that macrophages showed the highest percentage increase among all cell types in the DKD group. Furthermore, the present study observed significant differences in gene sets related to inflammatory responses and complement pathways. The study also identified several receptor-ligand pairs and co-stimulatory interactions between endothelial cells and macrophages. Notably, SYK, ITGB2, FCER1G, and VAV1 were identified as immunological markers of DKD with promising predictive ability. This study identified distinct cell clusters and four marker genes. SYK, ITGB2, FCER1G, and VAV1 may be important roles. Consequently, the present study extends our understanding regarding IRGs in DKD and provides a foundation for future investigations into the underlying mechanisms.

Complement Cascade Proteins Correlate with Fibrosis and Inflammation in Early-Stage Type 1 Diabetic Kidney Disease in the Ins2Akita Mouse Model

Diabetic kidney disease (DKD) is characterized by histological changes including fibrosis and inflammation. Evidence supports that DKD is mediated by the innate immune system and more specifically by the complement system. Using Ins2Akita T1D diabetic mice, we studied the connection between the complement cascade, inflammation, and fibrosis in early DKD. Data were extracted from a previously published quantitative-mass-spectrometry-based proteomics analysis of kidney glomeruli of 2 (early DKD) and 4 months (moderately advanced DKD)-old Ins2Akita mice and their controls A Spearman rho correlation analysis of complement- versus inflammation- and fibrosis-related protein expression was performed. A cross-omics validation of the correlation analyses' results was performed using public-domain transcriptomics datasets (Nephroseq). Tissue sections from 43 patients with DKD were analyzed using immunofluorescence. Among the differentially expressed proteins, the complement cascade proteins C3, C4B, and IGHM were significantly increased in both early and later stages of DKD. Inflammation-related proteins were mainly upregulated in early DKD, and fibrotic proteins were induced in moderately advanced stages of DKD. The abundance of complement proteins with fibrosis- and inflammation-related proteins was mostly positively correlated in early stages of DKD. This was confirmed in seven additional human and mouse transcriptomics DKD datasets. Moreover, C3 and IGHM mRNA levels were found to be negatively correlated with the estimated glomerular filtration rate (range for C3 rs = -0.58 to -0.842 and range for IGHM rs = -0.6 to -0.74) in these datasets. Immunohistology of human kidney biopsies revealed that C3, C1q, and IGM proteins were induced in patients with DKD and were correlated with fibrosis and inflammation. Our study shows for the first time the potential activation of the complement cascade associated with inflammation-mediated kidney fibrosis in the Ins2Akita T1D mouse model. Our findings could provide new perspectives for the treatment of early DKD as well as support the use of Ins2Akita T1D in pre-clinical studies.

Key Genes in Olfactory Disorder in Experimental Autoimmune Encephalomyelitis Identified by Transcriptomic Analysis of the Olfactory Bulbs

Experimental autoimmune encephalomyelitis (EAE) is an animal model of multiple sclerosis that shows demyelination in the central nervous system and functional deficits, including olfactory impairment. However, the genes related to olfactory impairment in EAE are unknown. We evaluated hub genes of the olfactory bulb in EAE mice. Differentially expressed genes (cut-offs, fold change > 2 and adjusted p < 0.05) and their related pathways in olfactory bulbs were subjected to gene ontology (GO) pathway analysis, gene set enrichment analysis (GSEA). Protein-protein interactions with selected genes were evaluated using the Search Tool for the Retrieval of Interacting Genes/Proteins. Gene regulatory networks (GRNs) which were constructed at the post-transcriptional level, including the genes-transcription factors (TFs) and gene-microRNAs (miRNAs) interaction networks. Twelve hub genes were found, three of which (Ctss, Itgb2, and Tlr2) were validated by RT-qPCR to be related to GO pathways such as immune response and regulation of immune response. GSEA showed that neuron-related genes-including Atp6v1g2, Egr1, and Gap43-and their pathways were significantly downregulated. GRNs analysis of six genes (Ctss, Itgb2, Tlr2, Atp6v1g2, Egr1, and Gap43) revealed 37 TFs and 84 miRNAs were identified as potential regulators of six genes, indicating significant interaction among six genes, TFs, and miRNAs. Collectively, these results suggest that transcriptomic analysis of the olfactory bulb of EAE mice can provide insight into olfactory dysfunction and reveal therapeutic targets for olfactory impairment.

Notoginsenoside R1 ameliorates the inflammation induced by amyloid‑β by suppressing SphK1‑mediated NF‑κB activation in PC12 cells

Alzheimer's disease (AD) is the most common type of age‑related dementia, and causes progressive memory degradation, neuronal loss and brain atrophy. The pathological hallmarks of AD consist of amyloid‑β (Aβ) plaque accumulation and abnormal neurofibrillary tangles. Amyloid fibrils are constructed from Aβ peptides, which are recognized to assemble into toxic oligomers and exert cytotoxicity. The fibrillar Aβ‑protein fragment 25‑35 (Aβ25‑35) induces local inflammation, thereby exacerbating neuronal apoptosis. Notoginsenoside R1 (NGR1), one of the primary bioactive ingredients isolated from Panax notoginseng, exhibits effective anti‑inflammatory and anti‑oxidative activities. However, NGR1 pharmacotherapies targeting Aβ‑induced inflammation and cell injury cascade remain to be elucidated. The present study investigated the effect and mechanism of NGR1 in Aβ25‑35‑treated PC12 cells. NGR1 doses between 250 and 1,000 µg/ml significantly increased cell viability suppressed by 20 µM Aβ25‑35 peptide treatment. Notably, the present study demonstrated that Aβ25‑35 peptide‑induced sphingosine kinase 1 (SphK1) signaling activation was reduced after NGR1 treatment, further inhibiting the downstream NF‑κB inflammatory signaling pathway. In addition, administration of SphK1 inhibitor II (SKI‑II), a SphK1 inhibitor, also significantly reduced Aβ25‑35 peptide‑induced apoptosis and the ratio of NF‑κB p‑p65/p65. Furthermore, SphK1 knockdown in PC12 cells using small interfering RNA alleviated Aβ‑induced cell apoptosis and inflammation, suggesting a pivotal role of SphK1 signaling in the anti‑inflammatory effect of NGR1. In summary, NGR1 alleviated inflammation and apoptosis stimulated by Aβ25‑35 by inhibiting the SphK1/NF‑κB signaling pathway and may be a promising agent for future AD treatment.

Identification of driver genes in lupus nephritis based on comprehensive bioinformatics and machine learning

Background

Lupus nephritis (LN) is a common and severe glomerulonephritis that often occurs as an organ manifestation of systemic lupus erythematosus (SLE). However, the complex pathological mechanisms associated with LN have hindered the progress of targeted therapies.

Methods

We analyzed glomerular tissues from 133 patients with LN and 51 normal controls using data obtained from the GEO database. Differentially expressed genes (DEGs) were identified and subjected to enrichment analysis. Weighted gene co-expression network analysis (WGCNA) was utilized to identify key gene modules. The least absolute shrinkage and selection operator (LASSO) and random forest were used to identify hub genes. We also analyzed immune cell infiltration using CIBERSORT. Additionally, we investigated the relationships between hub genes and clinicopathological features, as well as examined the distribution and expression of hub genes in the kidney.

Results

A total of 270 DEGs were identified in LN. Using weighted gene co-expression network analysis (WGCNA), we clustered these DEGs into 14 modules. Among them, the turquoise module displayed a significant correlation with LN (cor=0.88, p<0.0001). Machine learning techniques identified four hub genes, namely CD53 (AUC=0.995), TGFBI (AUC=0.997), MS4A6A (AUC=0.994), and HERC6 (AUC=0.999), which are involved in inflammation response and immune activation. CIBERSORT analysis suggested that these hub genes may contribute to immune cell infiltration. Furthermore, these hub genes exhibited strong correlations with the classification, renal function, and proteinuria of LN. Interestingly, the highest hub gene expression score was observed in macrophages.

Conclusion

CD53, TGFBI, MS4A6A, and HERC6 have emerged as promising candidate driver genes for LN. These hub genes hold the potential to offer valuable insights into the molecular diagnosis and treatment of LN.

Identification of ferroptosis-related genes as potential diagnostic biomarkers for diabetic nephropathy based on bioinformatics

Objective: This study investigated to probe ferroptosis-related diagnostic biomarkers and underlying molecular mechanisms in Diabetic nephropathy (DN). Methods: GSE30122 and GSE1009 from GEO database were used as training and verification sets, respectively, to screen differentially expressed ferroptosis-related genes (FRGs). These genes were further analyzed using GO, KEGG, and GSEA methods, and screened with PPI, LASSO, and SVM-RFE to identify ferroptosis-related diagnostic biomarkers for DN. A diagnostic model was established using the Glm function and verified with ROC curve. The relationship between these biomarkers and immune cell was analyzed, and qRT-PCR and Western blot were used to detect the expression of these biomarkers in kidney tissues and identify the effect of TP53 on DN development. Results: Fifty one differentially expressed FRGs were enriched in bioprocesses such as p53 signaling pathway, oxidative stress and chemical stress response, and mTOR signaling pathway. TP53, RB1, NF2, RRM2, PRDX1, and CDC25A were identified as ferroptosis-related diagnostic biomarkers for DN. TP53 showed the most differential expression. ROC analysis showed that AUC values of TP53, RB1, NF2, RRM2, PRDX1, and CDC25A were 0.751, 0.705, 0.725, 0.882, 0.691, and 0.675, respectively. The AUC value of DN diagnosis model was 0.939 in training set and 1.000 in verification set. qRT-PCR results confirmed significant differences in these six biomarkers between DN and normal kidney tissue (p < 0.05), and correlation analysis showed that five biomarkers were significantly correlated with infiltrating immune cells (p < 0.05). Furthermore, western blots showed that TP53 promotes apoptosis through PI3K-AKT signaling in DN. Conclusion: TP53, RB1, NF2, RRM2, PRDX1, and CDC25A have potential as diagnostic biomarkers for DN. The diagnostic model containing the above six biomarkers performs well in the diagnosis of DN. Five of the six biomarkers are strongly associated with several infiltrating immune cells. TP53 may play an essential role in the development of DN.

The Genetic Cross-Talk between Periodontitis and Chronic Kidney Failure Revealed by Transcriptomic Analysis

Periodontitis and chronic kidney failure (CKF) are potentially related to each other. This bioinformatics analysis aimed at the identification of potential cross-talk genes and related pathways between periodontitis and CKF. Based on NCBI Gene Expression Omnibus (GEO), datasets GSE10334, GSE16134, and GSE23586 were extracted for periodontitis. A differential expression analysis (p < 0.05, |log2(FC)| > 0.5) was performed to assess deregulated genes (DEGs). CKF-related genes were extracted from DisGeNET and examined regarding their overlap with periodontitis-related DEGs. Cytoscape was used to construct and analyze a protein-protein interaction (PPI) network. Based on Cytoscape plugin MCODE and a LASSO regression analysis, the potential hub cross-talk genes were identified. Finally, a complex PPI of the hub genes was constructed. A total of 489 DEGs for periodontitis were revealed. With the 805 CKF-related genes, an overlap of 47 cross-talk genes was found. The PPI network of the potential cross-talk genes was composed of 1081 nodes and 1191 edges. The analysis with MCODE resulted in 10 potential hub genes, while the LASSO regression resulted in 22. Finally, five hub cross-talk genes, CCL5, FCGR3B, MMP-9, SAA1, and SELL, were identified. Those genes were significantly upregulated in diseased samples compared to controls (p ≤ 0.01). Furthermore, ROC analysis showed a high predictive value of those genes (AUC ≥ 73.44%). Potentially relevant processes and pathways were primarily related to inflammation, metabolism, and cardiovascular issues. In conclusion, five hub cross-talk genes, i.e., CCL5, FCGR3B, MMP-9, SAA1, and SELL, could be involved in the interplay between periodontitis and CKF, whereby primarily inflammation, metabolic, and vascular issues appear to be of relevance.

Integrated Analysis of Single-Cell RNA-Seq and Bulk RNA-Seq Combined with Multiple Machine Learning Identified a Novel Immune Signature in Diabetic Nephropathy

Background

Increasing evidence suggests that immune modulation contributes to the pathogenesis and progression of diabetic nephropathy (DN). However, the role of immune modulation in DN has not been elucidated. The purpose of this study was to search for potential immune-related therapeutic targets and molecular mechanisms of DN.

Methods

Gene expression datasets were obtained from the Gene Expression Omnibus (GEO) database. A total of 1793 immune-related genes were acquired from the Immunology Database and Analysis Portal (ImmPort). Weighted gene co-expression network analysis (WGCNA) was performed for GSE142025, and the red and turquoise co-expression modules were found to be key for DN progression. We utilized four machine learning algorithms, namely, random forest (RF), support vector machine (SVM), adaptive boosting (AdaBoost), and k-nearest neighbor (KNN), to evaluate the diagnostic value of hub genes. Immune infiltration patterns were analyzed using the CIBERSORT algorithm, and the correlation between immune cell type abundance and hub gene expression was also investigated.

Results

A total of 77 immune-related genes of advanced DN were selected for subsequent analyzes. Functional enrichment analysis showed that the regulation of cytokine-cytokine receptor interactions and immune cell function play a corresponding role in the progression of DN. The final 10 hub genes were identified through multiple datasets. In addition, the expression levels of the identified hub genes were corroborated through a rat model. The RF model exhibited the highest AUC. CIBERSORT analysis and single-cell sequencing analysis revealed changes in immune infiltration patterns between control subjects and DN patients. Several potential drugs to reverse the altered hub genes were identified through the Drug-Gene Interaction database (DGIdb).

Conclusion

This pioneering work provided a novel immunological perspective on the progression of DN, identifying key immune-related genes and potential drug targets, thus stimulating future mechanistic research and therapeutic target identification for DN.

The characteristics of extrachromosomal circular DNA in patients with end-stage renal disease

BACKGROUND

End-stage renal disease (ESRD) is the final stage of chronic kidney disease (CKD). In addition to the structurally intact chromosome genomic DNA, there is a double-stranded circular DNA called extrachromosomal circular DNA (eccDNA), which is thought to be involved in the epigenetic regulation of human disease. However, the features of eccDNA in ESRD patients are barely known. In this study, we identified eccDNA from ESRD patients and healthy people, as well as revealed the characteristics of eccDNA in patients with ESRD.

METHODS

Using the high-throughput Circle-Sequencing technique, we examined the eccDNA in peripheral blood mononuclear cells (PBMCs) from healthy people (NC) (n = 12) and ESRD patients (n = 16). We analyzed the length distribution, genome elements, and motifs feature of eccDNA in ESRD patients. Then, after identifying the specific eccDNA in ESRD patients, we explored the potential functions of the target genes of the specific eccDNA. Finally, we investigated the probable hub eccDNA using algorithms.

RESULTS

In total, 14,431 and 11,324 eccDNAs were found in the ESRD and NC groups, respectively, with sizes ranging from 0.01 kb to 60 kb at most. Additionally, the ESRD group had a greater distribution of eccDNA on chromosomes 4, 11, 13, and 20. In two groups, we also discovered several motifs of specific eccDNAs. Furthermore, we identified 13,715 specific eccDNAs in the ESRD group and 10,585 specific eccDNAs in the NC group, both of which were largely annotated as mRNA catalog. Pathway studies using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) showed that the specific eccDNA in ESRD was markedly enriched in cell junction and communication pathways. Furthermore, we identified potentially 20 hub eccDNA-targeting genes from all ESRD-specific eccDNA-targeting genes. Also, we found that 39 eccDNA-targeting genes were associated with ESRD, and some of these eccDNAs may be related to the pathogenesis of ESRD.

CONCLUSIONS

Our findings revealed the characteristics of eccDNA in ESRD patients and discovered potentially hub and ESRD-relevant eccDNA-targeting genes, suggesting a novel probable mechanism of ESRD.

Landscape and Construction of a Novel N6-methyladenosine-related LncRNAs in Cervical Cancer

Cervical cancer is a crucial clinical problem with high mortality. Despite much research in therapy, the prognosis of patients with cervical cancer is still not ideal. The data on cervical cancer were downloaded from The Cancer Genome Atlas (TCGA) portal. R language was used to screen out the N6-methyladenosine (m6A)-related lncRNAs (long non-coding RNA). A consensus clustering algorithm was performed to identify m6A-related lncRNAs in cervical cancer; 10 m6A-related lncRNAs showing a significant association with survival were filtrated through a gradually univariate Cox regression model, least absolute shrinkage and selection operator (LASSO) algorithm, and multivariate Cox regression preliminarily. Furthermore, we conducted Kaplan-Meier curves, receiver operating curve (ROC) analyses, and proportional hazards model to quantify the underlying character of the m6A-related model in the prevision of cervical cancer patients. Gene set enrichment analysis (GSEA) was used to explore several pathways significantly. Finally, cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) was applied to estimate the immune cell infiltration in the profiling. In the present study, 10 m6A-related lncRNAs make up our prediction model. This prediction model can do duty for an independent predictive biomolecular element. Subsequently, we then found that the model was still valid in further validation of the training group and the test group. Our signature was correlated with immune cell infiltration and partial signaling pathway. These lncRNAs played a no negligible biomolecular role in contributing to the prognosis of cervical cancer.

Network pharmacology analysis combined with experimental validation to explore the therapeutic mechanism of Schisandra Chinensis Mixture on diabetic nephropathy

ETHNOPHARMACOLOGICAL RELEVANCE

Diabetic nephropathy (DN) is one of the most common and serious microvascular complications of Diabetes mellitus (DM). The inflammatory response plays a critical role in DN. Schisandra Chinensis Mixture (SM) has shown promising clinical efficacy in the treatment of DN while the pharmacological mechanisms are still unclear.

AIM OF THE STUDY

In this study, a network pharmacology approach and bioinformatic analysis were adopted to predict the pharmacological mechanisms of SM in DN therapy. Based on the predicted results, molecular docking and in vivo experiments were used for verification.

MATERIALS AND METHODS

In this study, the candidate bioactive ingredients of SM were obtained via Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and supplementing according to the literature. SM putative targets and the verified targets were acquired from TCMSP and SiwssTartgetPrediction Database. DN-related target genes were collected from GeneCards, OMIM, DisGeNET databases, and microarray data analysis. Biological function and pathway analysis were performed to further explore the pharmacological mechanisms of SM in DN therapy. The protein-protein interaction (PPI) network was established to screen the hub gene. The Receiver Operating Characteristic (ROC) analysis and the molecular docking simulations were performed to validate the potential target-drug interactions. The fingerprint spectrum of multi-components of the SM was characterized by UPLC-MS/MS. The signaling pathways associated with inflammation and hub genes were partially validated in SD rats.

RESULTS

A total of 36 bioactive ingredients were contained, and 666 component-related targets were screened from SM, of which 50 intersected with DN targets and were considered potential therapeutic targets. GO analyses revealed that the 50 intersection targets were mainly enriched in the inflammatory response, positive regulation of angiogenesis, and positive regulation of phosphatidylinositol 3-kinase(PI3K) signaling. KEGG analyses indicated that the PI3K-Akt signaling pathway was considered as the most important pathway for SM antagonism to the occurrence and development of DN, with the highest target count enrichment. PPI network results showed that the top 15 protein targets in degree value, VEGFA, JAK2, CSF1R, NOS3, CCR2, CCR5, TLR7, FYN, BTK, LCK, PLAT, NOS2, TEK, MMP1 and MCL1, were identified as hub genes. The results of ROC analysis showed that VEGFA and NOS3 were valuable in the diagnosis of DN. The molecular docking confirmed that the core bioactive ingredients had well-binding affinity for VEGFA and NOS3. The in vivo experiments confirmed that SM significantly inhibited the over-release of inflammatory cytokines such as interleukin (IL)-6 and tumor necrosis factor receptor (TNF)-α in DN rats, while regulating the PI3K-AKT and VEGFA-NOS3 signaling pathways.

CONCLUSION

This study revealed the multi-component, multi-target and multi-pathway characteristics of SM therapeutic DN. SM inhibited the inflammatory response and improved renal pathological damage in DN rats, which was related to the regulation of the PI3K-Akt and VEGFA-NOS3 signaling pathways.

Therapeutic modulation of V Set and Ig domain-containing 4 (VSIG4) signaling in immune and inflammatory diseases

Inflammation is the result of acute and chronic stresses, caused by emotional or physical trauma, or nutritional or environmental pollutants, and brings serious harm to human life and health. As an important cellular component of the innate immune barrier, the macrophage plays a key role in maintaining tissue homeostasis and promoting tissue repair by controlling infection and resolving inflammation. Several studies suggest that V Set and Ig domain-containing 4 is specifically expressed in tissue macrophages and is associated with a variety of inflammatory diseases. In this paper, we mainly summarize the recent research on V Set and Ig domain-containing 4 structures, functions, function and roles in acute and chronic inflammatory diseases, and provide a novel therapeutic avenue for the treatment of inflammatory diseases, including nervous system, urinary, respiratory and metabolic diseases.

Silencing circ_0080425 alleviates high-glucose-induced endothelial cell dysfunction in diabetic nephropathy by targeting miR-140-3p/FN1 axis

BACKGROUND

Hsa_circ_0080425 (circ_0080425) is newly identified to correlate with the progression of diabetic nephropathy (DN). However, its role and mechanism in DN process is not very clear.

METHODS

Cell counting kit-8 assay, flow cytometry, scratch wound assay, and western blotting were performed to measure endothelial cell dysfunction. Expression of circ_0080425, microRNA (miR)-140-3p and fibronectin 1 (FN1) were determined by quantitative real-time PCR and western blotting. The direct interaction was confirmed by dual-luciferase reporter assay.

RESULTS

High-glucose (HG) treatment could induce inhibition of cell proliferation, cell cycle entrance and wound healing rate in human umbilical vein endothelial cells (HRGEC), and enhancement of apoptosis rate. Circ_0080425 expression was upregulated by HG, and exhausting circ_0080425 could attenuate HG-induced above effects in HRGEC. MiR-140-3p was sponged by circ_0080425, and its inhibitor reversed the regulation of circ_0080425 knockdown on HG-induced HRGEC injury. FN1 was targeted by miR-140-3p, and its overexpression also restored the inhibitory effect of miR-140-3p on HC-induced HRGEC injury.

CONCLUSION

Circ_0080425 expression might contribute to HG-induced endothelial cell injury, and circ_0080425/miR-140-3p/FN1 axis was a potential therapeutic approach to interfere DN process.

Integrative analyses of biomarkers and pathways for diabetic nephropathy

Background: Diabetic nephropathy (DN) is a widespread diabetic complication and a major cause of terminal kidney disease. There is no doubt that DN is a chronic disease that imposes substantial health and economic burdens on the world's populations. By now, several important and exciting advances have been made in research on etiopathogenesis. Therefore, the genetic mechanisms underlying these effects remain unknown. Methods: The GSE30122, GSE30528, and GSE30529 microarray datasets were downloaded from the Gene Expression Omnibus database (GEO). Analyses of differentially expressed genes (DEGs), enrichment of gene ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were performed. Protein-protein interaction (PPI) network construction was completed by the STRING database. Hub genes were identified by Cytoscape software, and common hub genes were identified by taking intersection sets. The diagnostic value of common hub genes was then predicted in the GSE30529 and GSE30528 datasets. Further analysis was carried out on the modules to identify transcription factors and miRNA networks. As well, a comparative toxicogenomics database was used to assess interactions between potential key genes and diseases associated upstream of DN. Results: Samples from 19 DNs and 50 normal controls were identified in the GSE30122 dataset. 86 upregulated genes and 34 downregulated genes (a total of 120 DEGs). GO analysis showed significant enrichment in humoral immune response, protein activation cascade, complement activation, extracellular matrix, glycosaminoglycan binding, and antigen binding. KEGG analysis showed significant enrichment in complement and coagulation cascades, phagosomes, the Rap1 signaling pathway, the PI3K-Akt signaling pathway, and infection. GSEA was mainly enriched in the TYROBP causal network, the inflammatory response pathway, chemokine receptor binding, the interferon signaling pathway, ECM receptor interaction, and the integrin 1 pathway. Meanwhile, mRNA-miRNA and mRNA-TF networks were constructed for common hub genes. Nine pivotal genes were identified by taking the intersection. After validating the expression differences and diagnostic values of the GSE30528 and GSE30529 datasets, eight pivotal genes (TYROBP, ITGB2, CD53, IL10RA, LAPTM5, CD48, C1QA, and IRF8) were finally identified as having diagnostic values. Conclusion: Pathway enrichment analysis scores provide insight into the genetic phenotype and may propose molecular mechanisms of DN. The target genes TYROBP, ITGB2, CD53, IL10RA, LAPTM5, CD48, C1QA, and IRF8 are promising new targets for DN. SPI1, HIF1A, STAT1, KLF5, RUNX1, MBD1, SP1, and WT1 may be involved in the regulatory mechanisms of DN development. Our study may provide a potential biomarker or therapeutic locus for the study of DN.

Early renal structural changes and potential biomarkers in diabetic nephropathy

Diabetic nephropathy is one of the most serious microvascular complications of diabetes mellitus, with increasing prevalence and mortality. Currently, renal function is assessed clinically using albumin excretion rate and glomerular filtration rate. But before the appearance of micro-albumin, the glomerular structure has been severely damaged. Glomerular filtration rate based on serum creatinine is a certain underestimate of renal status. Early diagnosis of diabetic nephropathy has an important role in improving kidney function and delaying disease progression with drugs. There is an urgent need for biomarkers that can characterize the structural changes associated with the kidney. In this review, we focus on the early glomerular and tubular structural alterations, with a detailed description of the glomerular injury markers SMAD1 and Podocalyxin, and the tubular injury markers NGAL, Netrin-1, and L-FABP in the context of diabetic nephropathy. We have summarized the currently studied protein markers and performed bioprocess analysis. Also, a brief review of proteomic and scRNA-seq method in the search of diabetic nephropathy.

Integrative transcriptome analysis reveals TEKT2 and PIAS2 involvement in diabetic nephropathy

Cell heterogeneity has impeded the accurate interpretation of the bulk transcriptome data from patients with diabetic nephropathy (DN). We performed an analysis by integrating bulk and single-cell transcriptome datasets to uncover novel mechanisms leading to DN, especially in the podocytes. Microdissected glomeruli and tubules transcriptome datasets were selected from Gene Expression Omnibus (GEO). Then the consistency between datasets was evaluated. The analysis of the bulk dataset and single-nucleus RNA dataset was integrated to reveal the cell type-specific responses to DN. The candidate genes were validated in kidney tissues from DN patients and diabetic mice. We compared 4 glomerular and 4 tubular datasets and found considerable discrepancies among datasets regarding the deferentially expressed genes (DEGs), involved signaling pathways, and the hallmark enrichment profiles. Deconvolution of the bulk data revealed that the variations in cell-type proportion contributed greatly to this discrepancy. The integrative analysis uncovered that the dysregulation of spermatogenesis-related genes, including TEKT2 and PIAS2, was involved in the development of DN. Importantly, the mRNA level of TEKT2 was negatively correlated with the mRNA levels of NPHS1 (r = -.66, p < .0001) and NPHS2 (r = -.85, p < .0001) in human diabetic glomeruli. Immunostaining confirmed that the expression of TEKT2 and PIAS2 were up-regulated in podocytes of DN patients and diabetic mice. Knocking down TEKT2 resisted high glucose-induced cytoskeletal remodeling and down-regulation of NPHS1 protein in the cultured podocyte. In conclusion, the integrative strategy can help us efficiently use the publicly available transcriptomics resources. Using this approach and combining it with classical research methods, we identified TEKT2 and PIAS2, two spermatogenesis-related genes involved in the pathogenesis of DN. Furthermore, TEKT2 is involved in this pathogenesis by regulating the podocyte cytoskeleton.

Ameliorative Effects of Camel Milk and Its Exosomes on Diabetic Nephropathy in Rats

Contradictory results were obtained regarding the effects of extracellular vesicles such as exosomes (EXOs) on diabetes and diabetic nephropathy (DN). Some studies showed that EXOs, including milk EXOs, were involved in the pathogenesis of DN, whereas other studies revealed ameliorative effects. Compared to other animals, camel milk had unique components that lower blood glucose levels. However, little is known regarding the effect of camel milk and its EXOs on DN. Thus, the present study was conducted to evaluate this effect on a rat model of DN induced by streptozotocin. Treatment with camel milk and/or its EXOs ameliorated DN as evidenced by (1) reduced levels of kidney function parameters (urea, creatinine, retinol-binding protein (RBP), and urinary proteins), (2) restored redox balance (decreased lipid peroxide malondialdehyde (MDA) and increased the activity of antioxidants enzymes superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPx)), (3) downregulated expression of DN-related genes (transforming growth factor-beta 1 (TGFβ1), intercellular adhesion molecules 1 (ICAM1), and transformation specific 1 (ETS1), integrin subunit beta 2 (ITGβ2), tissue inhibitors of matrix metalloproteinase 2 (TIMP2), and kidney injury molecule-1 (KIM1)), and (4) decreased renal damage histological score. These results concluded that the treatment with camel milk and/or its EXOs could ameliorate DN with a better effect for the combined therapy.

The landscape of immune cell infiltration in the glomerulus of diabetic nephropathy: evidence based on bioinformatics

Background

Increasing evidence suggests that immune cell infiltration contributes to the pathogenesis and progression of diabetic nephropathy (DN). We aim to unveil the immune infiltration pattern in the glomerulus of DN and provide potential targets for immunotherapy.

Methods

Infiltrating percentage of 22 types of immune cell in the glomerulus tissues were estimated by the CIBERSORT algorithm based on three transcriptome datasets mined from the GEO database. Differentially expressed genes (DEGs) were identified by the “limma” package. Then immune-related DEGs were identified by intersecting DEGs with immune-related genes (downloaded from Immport database). The protein–protein interactions of Immune-related DEGs were explored using the STRING database and visualized by Cytoscape. The enrichment analyses for KEGG pathways and GO terms were carried out by the gene set enrichment analysis (GSEA) method.

Results

11 types of immune cell were revealed to be significantly altered in the glomerulus tissues of DN (Up: B cells memory, T cells gamma delta, NK cells activated, Macrophages.M1, Macrophages M2, Dendritic cells resting, Mast cells resting; Down: B cells naive, NK cells resting, Mast cells activated, Neutrophils). Several pathways related to immune, autophagy and metabolic process were significantly activated. Moreover, 6 hub genes with a medium to strong correlation with renal function (eGFR) were identified (SERPINA3, LTF, C3, PTGDS, EGF and ALB).

Conclusion

In the glomerulus of DN, the immune infiltration pattern changed significantly. A complicated and tightly regulated network of immune cells exists in the pathological of DN. The hub genes identified here will facilitate the development of immunotherapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12882-022-02906-4.

Identification of Hub Genes Involved in Tubulointerstitial Injury in Diabetic Nephropathy by Bioinformatics Analysis and Experiment Verification

Diabetic nephropathy (DN) is the most important cause of end-stage renal disease with a poorer prognosis and high economic burdens of medical treatments. It is of great research value and clinical significance to explore potential gene targets of renal tubulointerstitial lesions in DN. To properly identify key genes associated with tubulointerstitial injury of DN, we initially performed a weighted gene coexpression network analysis of the dataset to screen out two nonconserved gene modules (dark orange and dark red). The regulation of oxidative stress-induced intrinsic apoptotic signaling pathway, PI3K-Akt signaling pathway, p38MAPK cascade, and Th1 and Th2 cell differentiation were primarily included in Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of these two modules. Next, 199 differentially expressed genes (DEGs) were identified via the limma package. Then, the GO annotation and KEGG pathways of the DEGs were primarily enriched in extracellular matrix (ECM) organization, epithelial cell migration, cell adhesion molecules (CAMs), NF-kappa B signaling pathway, and ECM-receptor interaction. Gene set enrichment analysis showed that in the DN group, the interaction of ECM-receptor, CAMs, the interaction of cytokine-cytokine receptor, and complement and coagulation cascade pathways were significantly activated. Eleven key genes, including ALB, ANXA1, ANXA2, C3, CCL2, CLU, EGF, FOS, PLG, TIMP1, and VCAM1, were selected by constructing a protein-protein interaction network, and expression validation, ECM-related pathways, and glomerular filtration rate correlation analysis were performed in the validated dataset. The upregulated expression of hub genes ANXA2 and FOS was verified by real-time quantitative PCR in HK-2 cells treated with high glucose. This study revealed potential regulatory mechanisms of renal tubulointerstitial damage and highlighted the crucial role of extracellular matrix in DN, which may promote the identification of new biomarkers and therapeutic targets.

Mesenchymal stem cells derived extracellular vesicles: A promising nanomedicine for drug delivery system

An ideal drug delivery system should selectively deliver incorporated therapeutics to the target site, escape from immune cells recognition and degradation, and act controlled release of incorporated therapeutics in the site targeted. Extracellular vesicles (EVs) have gained great attention for their potential application as a drug delivery system in nanomedicine. EVs such as exosomes are membrane-bound vesicles that contribute to intracellular communication by transferring various biomolecules including RNAs, proteins, and lipids. EVs derived from mesenchymal stem cells (MSCs-EVs) have several advantages such as low immunogenicity, high biocompatibility, and stability against conventional synthetic carriers, opening new avenues for delivering theaputic agents to target cells. To obtain modified MSCs-EVs, several loading methods are used to incorporate different therapeutic agents including proteins, RNAs, and chemotherapeutic drugs into MSCs-EVs. In addition, modification of MSCs-EVs surface may improve their potential in targeted therapies. Modified MSCs-EVs have been shown to improve many diseases including, cancer, cardiovascular diseases, and diabetes mellitus. While land greatly potential, the application of MSCs-EVs as a drug-delivery system has been hampered by several challenges. Clinical translation of modified-EVs needs further scrutiny. In this review, we discuss the biogenesis and production of EVs along with the loading and modification methods of MSCs-EVs. We also describe numerous MSCs-EVs based delivery studies with a focus on advantages and challenges when using them as a drug delivery system.

Establishment of a Nomogram Model for Predicting Cardiovascular and Cerebrovascular Events in Diabetic Nephropathy Patients Receiving Maintenance Hemodialysis

Objective. The objective of this study is to explore the risk factors of cardiovascular and cerebrovascular events (CCE) in patients with diabetic nephropathy (DN) receiving maintenance hemodialysis, and to establish a nomogram model on this basis. Method. 144 patients with DN receiving maintenance hemodialysis from February 2020 to February 2021 were selected and followed up for 12 months. They were divided into the occurrence and nonoccurrence groups according to whether CCE occurred. The multivariate logistic regression analysis was used to analyze the influencing factors of CCE, and a predictive nomogram model was established. The receiver operating characteristic (ROC) curve was drawn to evaluate the predictive effect of the nomogram model. The Hosmer-Lemeshow method was used to test the calibration degree. Results. Among the patients, 63 patients (43.75%) encountered CCE. Multivariate logistic regression analysis showed that age >60 years old, history of CCE, dialysis age >12 months, systolic blood pressure >140 mmHg, blood phosphorus level >1.5 mmol/L, triglyceride (TG) level >2.30 mmol/l, adiponectin (ADPN) level <5 mg/L, high-sensitivity-C-reactive protein (hs-CRP) level >10 mg/L, hemoglobin (Hb) level <120 g/L, serum creatinine (SCr) level >720 μmol/L, and albumin (ALB) level <40 g/L were independent risk factors for CCE. Based on the above independent risk factors, a nomogram model of CCE was created. ROC curve analysis showed that the area under curve for predicting CCE was 0.881 (95% CI: 0.833~0.919), indicating that the nomogram model had great predictive effect. The Hosmer-Lemeshow method showed that the calibration curve was in good agreement with the standard curve. Conclusion. Age, history of CCE, dialysis age, systolic blood pressure and serum phosphorus, and TG, ADPN, hs-CRP, Hb, SCr, and ALB levels are all influencing factors for the occurrence of CCE in patients with DN receiving maintenance hemodialysis, and the nomogram model has a great predictive effect on CCE.

Identification of key differential genes in intimal hyperplasia induced by left carotid artery ligation

Background

Intimal hyperplasia is a common pathological process of restenosis following angioplasty, atherosclerosis, pulmonary hypertension, vein graft stenosis, and other proliferative diseases. This study aims to screen for potential novel gene targets and mechanisms related to vascular intimal hyperplasia through an integrated microarray analysis of the Gene Expression Omnibus Database (GEO) database.

Material and Methods

The gene expression profile of the GSE56143 dataset was downloaded from the Gene Expression Omnibus database. Functional enrichment analysis, protein-protein interaction (PPI) network analysis, and the transcription factor (TF)-target gene regulatory network were used to reveal the biological functions of differential genes (DEGs). Furthermore, the expression levels of the top 10 key DEGs were verified at the mRNA and protein level in the carotid artery 7 days after ligation.

Results

A total of 373 DEGs (199 upregulated DEGs and 174 downregulated DEGs) were screened. These DEGs were significantly enriched in biological processes, including immune system process, cell adhesion, and several pathways, which were mainly associated with cell adhesion molecules and the regulation of the actin cytoskeleton. The top 10 key DEGs (Ptprc, Fn1, Tyrobp, Emr1, Itgb2, Itgax, CD44, Ctss, Ly86, and Aif1) acted as key genes in the PPI network. The verification of these key DEGs at the mRNA and protein levels was consistent with the results of the above-mentioned bioinformatics analysis.

Conclusion

The present study identified key genes and pathways involved in intimal hyperplasia induced by carotid artery ligation. These results improved our understanding of the mechanisms underlying the development of intimal hyperplasia and provided candidate targets.

Single-Nucleus Transcriptional Profiling of Chronic Kidney Disease after Cisplatin Nephrotoxicity

Cisplatin induces both acute and chronic nephrotoxicity during chemotherapy in patients with cancer. Presented here is the first study of single-nucleus RNA sequencing (snRNA-seq) of cisplatin-induced nephrotoxicity. Repeated low-dose cisplatin treatment (RLDC) led to decreases in renal function and kidney weight in mice at 9 weeks. The kidneys of these mice showed tubular degeneration and dilation. snRNA-seq identified 16 cell types and 17 cell clusters in these kidneys. Cluster-by-cluster comparison demonstrated cell type-specific changes in gene expression and identified a unique proximal tubule (PT) injury/repair cluster that co-expressed the injury marker kidney injury molecule-1 (Kim1) and the proliferation marker Ki-67. Compared with control, post-RLDC kidneys had 424 differentially expressed genes in PT cells, including tubular transporters and cytochrome P450 enzymes involved in lipid metabolism. snRNA-seq also revealed transcriptional changes in potential PT injury markers (Krt222, Eda2r, Ltbp2, and Masp1) and repair marker (Bex4). RLDC induced inflammation and proinflammatory cytokines (RelB, TNF-α, Il7, Ccl2, and Cxcl2) and the expression of fibrosis markers (fibronectin, collagen I, connective tissue growth factor, vimentin, and α-smooth muscle actin). Together, these results provide new insights into RLDC-induced transcriptional changes at the single-cell level that may contribute to the development of chronic kidney problems in patients with cancer after cisplatin chemotherapy.

Genome-wide Analysis Reflects Novel 5-Hydroxymethylcytosines Implicated in Diabetic Nephropathy and the Biomarker Potential

AIM

Diabetic nephropathy (DN) has become the most common cause of end-stage renal disease (ESRD) in most countries. Elucidating novel epigenetic contributors to DN can not only enhance our understanding of this complex disorder, but also lay the foundation for developing more effective monitoring tools and preventive interventions in the future, thus contributing to our ultimate goal of improving patient care.

METHODS

The 5hmC-Seal, a highly selective, chemical labeling technique, was used to profile genome-wide 5-hydroxymethylcytosines (5hmC), a stable cytosine modification type marking gene activation, in circulating cell-free DNA (cfDNA) samples from a cohort of patients recruited at Zhongnan Hospital, including T2D patients with nephropathy (DN, n = 12), T2D patients with non-DN vascular complications (non-DN, n = 29), and T2D patients without any complication (controls, n = 14). Differentially analysis was performed to find DN-associated 5hmC features, followed by the exploration of biomarker potential of 5hmC in cfDNA for DN using a machine learning approach.

RESULTS

Genome-wide analyses of 5hmC in cfDNA detected 427 and 336 differential 5hmC modifications associated with DN, compared with non-DN individuals and controls, and suggested relevant pathways such as NOD-like receptor signaling pathway and tyrosine metabolism. Our exploration using a machine learning approach revealed an exploratory model comprised of ten 5hmC genes showing the possibility to distinguish DN from non-DN individuals or controls.

CONCLUSION

Genome-wide analysis suggests the possibility of exploiting novel 5hmC in patient-derived cfDNA as a non-invasive tool for monitoring DN in high risk T2D patients in the future.

Identification of Type 2 Diabetes Based on a Ten-Gene Biomarker Prediction Model Constructed Using a Support Vector Machine Algorithm

Background

Type 2 diabetes is a major health concern worldwide. The present study is aimed at discovering effective biomarkers for an efficient diagnosis of type 2 diabetes.

Methods

Differentially expressed genes (DEGs) between type 2 diabetes patients and normal controls were identified by analyses of integrated microarray data obtained from the Gene Expression Omnibus database using the Limma package. Functional analysis of genes was performed using the R software package clusterProfiler. Analyses of protein-protein interaction (PPI) performed using Cytoscape with the CytoHubba plugin were used to determine the most sensitive diagnostic gene biomarkers for type 2 diabetes in our study. The support vector machine (SVM) classification model was used to validate the gene biomarkers used for the diagnosis of type 2 diabetes.

Results

GSE164416 dataset analysis revealed 499 genes that were differentially expressed between type 2 diabetes patients and normal controls, and these DEGs were found to be enriched in the regulation of the immune effector pathway, type 1 diabetes mellitus, and fatty acid degradation. PPI analysis data showed that five MCODE clusters could be considered as clinically significant modules and that 10 genes (IL1B, ITGB2, ITGAX, COL1A1, CSF1, CXCL12, SPP1, FN1, C3, and MMP2) were identified as “real” hub genes in the PPI network using algorithms such as Degree, MNC, and Closeness. The sensitivity and specificity of the SVM model for identifying patients with type 2 diabetes were 100%, with an area under the curve of 1 in the training as well as the validation dataset.

Conclusion

Our results indicate that the SVM-based model developed by us can facilitate accurate diagnosis of type 2 diabetes.

Detection of molecular signatures and pathways shared by Alzheimer's disease and type 2 diabetes

Alzheimer's disease (AD) and type 2 diabetes (T2D) are common in the general elderly population, conferring heavy individual, social, and economic stresses on families and society. Accumulating evidence indicates T2D to be a risk factor for AD. However, the underlying mechanisms for this association are largely unknown. This study aimed to identify the shared molecular signatures between AD and T2D through integrated analysis of temporal cortex gene expression data. Gene Ontology (GO) and pathway enrichment analysis, protein over-representation analysis, protein-protein interaction, DEG-transcription factor interactions, DEG-microRNA interactions, protein-drug interactions, gene-disease association analysis, and protein subcellular localization analysis of the common DEGs were performed. We identified 16 common DEGs between the two datasets, which were mainly enriched in the biological processes of apoptosis, autophagy, inflammation, and hemostasis. We also identified five hub proteins encoded by the DEGs, five central regulatory transcription factors, and six microRNAs. Protein-drug interaction analysis showed C1QB to be associated with different drugs. Gene-disease association analysis revealed that hub genes, SFN and ITGB2, were actively engaged in other diseases. Collectively, these findings provide new insights into shared molecular mechanisms between AD and T2D and provide novel candidate targets for therapeutic intervention.

E26 transformation-specific 1 is implicated in the inhibition of osteogenic differentiation induced by chronic high glucose by directly regulating Runx2 expression

Chronic high glucose (HG) plays a crucial role in the pathogenesis of diabetes-induced osteoporosis by inhibiting the differentiation and proliferation of osteoblasts. This study aims to examine the role of E26 transformation-specific 1 (ETS1) in the inhibition of osteoblast differentiation and proliferation caused by chronic HG, as well as the underlying mechanism. Chronic HG treatment downregulated ETS1 expression and inhibited differentiation and proliferation of MC3T3-E1 cells. Downregulation of ETS1 expression inhibited the differentiation and proliferation of MC3T3-E1 cells under normal glucose conditions, and ETS1 overexpression attenuated the damage to cells exposed to chronic HG. In addition, ETS1 overexpression reversed the decrease in runt-related transcription factor 2 (Runx2) expression in MC3T3-E1 cells treated with chronic HG. Using chromatin immunoprecipitation (ChIP) and luciferase reporter assays, we confirmed that ETS1 directly bound to and increased the activity of the Runx2 promoter. In summary, our study suggested that ETS1 was involved in the inhibitory effect of chronic HG on osteogenic differentiation and proliferation and may be a potential therapeutic target for diabetes-induced osteoporosis.

Urinary complement proteins and risk of end-stage renal disease: quantitative urinary proteomics in patients with type 2 diabetes and biopsy-proven diabetic nephropathy

PURPOSE

To investigate the association between urinary complement proteins and renal outcome in biopsy-proven diabetic nephropathy (DN).

METHODS

Untargeted proteomic and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional analyses and targeted proteomic analysis using parallel reaction-monitoring (PRM)-mass spectrometry was performed to determine the abundance of urinary complement proteins in healthy controls, type 2 diabetes mellitus (T2DM) patients, and patients with T2DM and biopsy-proven DN. The abundance of each urinary complement protein was individually included in Cox proportional hazards models for predicting progression to end-stage renal disease (ESRD).

RESULTS

Untargeted proteomic and functional analysis using the KEGG showed that differentially expressed urinary proteins were primarily associated with the complement and coagulation cascades. Subsequent urinary complement proteins quantification using PRM showed that urinary abundances of C3, C9, and complement factor H (CFAH) correlated negatively with annual estimated glomerular filtration rate (eGFR) decline, while urinary abundances of C5, decay-accelerating factor (DAF), and CD59 correlated positively with annual rate of eGFR decline. Furthermore, higher urinary abundance of CFAH and lower urinary abundance of DAF were independently associated with greater risk of progression to ESRD. Urinary abundance of CFAH and DAF had a larger area under the curve (AUC) than that of eGFR, proteinuria, or any pathological parameter. Moreover, the model that included CFAH or DAF had a larger AUC than that with only clinical or pathological parameters.

CONCLUSION

Urinary abundance of complement proteins was significantly associated with ESRD in patients with T2DM and biopsy-proven DN, indicating that therapeutically targeting the complement pathway may alleviate progression of DN.

Mesenchymal stem cells-derived exosomes for drug delivery

Exosomes are extracellular vesicles secreted by various cells, mainly composed of lipid bilayers without organelles. In recent years, an increasing number of researchers have focused on the use of exosomes for drug delivery. Targeted drug delivery in the body is a promising method for treating many refractory diseases such as tumors and Alzheimer's disease (AD). Finding a suitable drug delivery carrier in the body has become a popular research today. In various drug delivery studies, the exosomes secreted by mesenchymal stem cells (MSC-EXOs) have been broadly researched due to their immune properties, tumor-homing properties, and elastic properties. While MSC-EXOs have apparent advantages, some unresolved problems also exist. This article reviews the studies on MSC-EXOs for drug delivery, summarizes the characteristics of MSC-EXOs, and introduces the primary production and purification methods and drug loading methods to provide solutions for existing problems and suggestions for future studies.

Mechanisms of Hypoxia-Induced Pulmonary Arterial Stiffening in Mice Revealed by a Functional Genetics Assay of Structural, Functional, and Transcriptomic Data

Hypoxia adversely affects the pulmonary circulation of mammals, including vasoconstriction leading to elevated pulmonary arterial pressures. The clinical importance of changes in the structure and function of the large, elastic pulmonary arteries is gaining increased attention, particularly regarding impact in multiple chronic cardiopulmonary conditions. We establish a multi-disciplinary workflow to understand better transcriptional, microstructural, and functional changes of the pulmonary artery in response to sustained hypoxia and how these changes inter-relate. We exposed adult male C57BL/6J mice to normoxic or hypoxic (FiO₂ 10%) conditions. Excised pulmonary arteries were profiled transcriptionally using single cell RNA sequencing, imaged with multiphoton microscopy to determine microstructural features under in vivo relevant multiaxial loading, and phenotyped biomechanically to quantify associated changes in material stiffness and vasoactive capacity. Pulmonary arteries of hypoxic mice exhibited an increased material stiffness that was likely due to collagen remodeling rather than excessive deposition (fibrosis), a change in smooth muscle cell phenotype reflected by decreased contractility and altered orientation aligning these cells in the same direction as the remodeled collagen fibers, endothelial proliferation likely representing endothelial-to-mesenchymal transitioning, and a network of cell-type specific transcriptomic changes that drove these changes. These many changes resulted in a system-level increase in pulmonary arterial pulse wave velocity, which may drive a positive feedback loop exacerbating all changes. These findings demonstrate the power of a multi-scale genetic-functional assay. They also highlight the need for systems-level analyses to determine which of the many changes are clinically significant and may be potential therapeutic targets.

Exploring the Molecular Mechanism of Liuwei Dihuang Pills for Treating Diabetic Nephropathy by Combined Network Pharmacology and Molecular Docking

BACKGROUND

Diabetic nephropathy (DN) is a common and serious complication of diabetes, but without a satisfactory treatment strategy till now. Liuwei Dihuang pills (LDP), an effective Chinese medicinal formula, has been used to treat DN for more than 1000 years. However, its underlying mechanism of action is still vague.

METHODS

Active compounds and corresponding targets of LDP were predicted from the TCMSP database. DN disease targets were extracted from the OMIM, GeneCards, TTD, DisGeNET, and DrugBank databases. Subsequently, the "herbal-compound-target" network and protein-protein interaction (PPI) network were constructed and analyzed via the STRING web platform and Cytoscape software. GO functional and KEGG pathway enrichment analyses were carried out on the Metascape web platform. Molecular docking utilized AutoDock Vina and PyMOL software.

RESULTS

41 active components and 186 corresponding targets of LDP were screened out. 131 common targets of LDP and DN were acquired. Quercetin, kaempferol, beta-sitosterol, diosgenin, and stigmasterol could be defined as five crucial compounds. JUN, MAPK8, AKT1, EGF, TP53, VEGFA, MMP9, MAPK1, and TNF might be the nine key targets. The enrichment analysis showed that common targets were mainly associated with inflammation reaction, oxidative stress, immune regulation, and cell apoptosis. AGE-RAGE and IL-17 were the suggested two significant signal pathways. Molecular docking revealed that the nine key targets could closely bind to their corresponding active compounds.

CONCLUSION

The present study fully reveals the multicompound's and multitarget's characteristics of LDP in DN treatment. Furthermore, this study provides valuable evidence for further scientific research of the pharmacological mechanisms and broader clinical application.

ets1 associates with KMT5A to participate in high glucose-mediated EndMT via upregulation of PFN2 expression in diabetic nephropathy

Background

Diabetic nephropathy (DN) is currently the leading cause of end-stage renal disease globally. The endothelial-to-mesenchymal transition (EndMT) of glomerular endothelial cells has been reported to play a crucial role in DN. As a specific form of epithelial-to-mesenchymal transition, EndMT and epithelial-to-mesenchymal transition may exhibit mutual modulators. Profilin 2 (PFN2) has been reported to participate in epithelial-to-mesenchymal transition. Moreover, ETS proto-oncogene 1 (ets1) and lysine methyltransferase 5A (KMT5A) have been reported to contribute to high glucose-mediated endothelial injury and epithelial-to-mesenchymal transition. In this study, we hypothesize ets1 associates with KMT5A to modulate PFN2 transcription, thus participating in high glucose-mediated EndMT in glomerular endothelial cells.

Methods

Immunohistochemistry (IHC) was performed to detect protein levels in the kidney tissues and/or aorta tissues of human subjects and rats. Western blot, qPCR and immunofluorescence were performed using human umbilical vein endothelial cells (HUVECs). Chromatin immunoprecipitation (ChIP) assays and dual luciferase assays were performed to assess transcriptional activity. The difference between the groups was compared by two-tailed unpaired t-tests or one-way ANOVAs.

Results

Our data indicated that vimentin, αSMA, S100A4 and PFN2 levels were increased, and CD31 levels were reduced in glomerular endothelial cells of DN patients and rats. Our cell experiments showed that high glucose induced EndMT by augmenting PFN2 expression in HUVECs. Moreover, high glucose increased ets1 expression. si-ets1 suppressed high glucose-induced PFN2 levels and EndMT. ets1 overexpression-mediated EndMT was reversed by si-PFN2. Furthermore, ets1 was determined to associate with KMT5A. High glucose attenuated KMT5A levels and histone H4 lysine 20 methylation (H4K20me1), one of the downstream targets of KMT5A. KMT5A upregulation suppressed high glucose-induced PFN2 levels and EndMT. sh-KMT5A-mediated EndMT was counteracted by si-PFN2. Furthermore, H4K20me1 and ets1 occupied the PFN2 promoter region. sh-KMT5A cooperated with ets1 overexpression to activate PFN2 promoter activity. Our in vivo study demonstrated that KMT5A was reduced, while ets1 was augmented, in glomerular endothelial cells of DN patients and rats.

Conclusions

The present study indicated that ets1 cooperated with KMT5A to transcribe PFN2, thus contributing to hyperglycemia-induced EndMT in the glomerular endothelial cells of DN patients and rats.

Trial registration ChiCTR, ChiCTR2000029425. 2020/1/31, http://www.chictr.org.cn/showproj.aspx?proj=48548

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-021-00339-7.

Identification of Lumican and Fibromodulin as Hub Genes Associated with Accumulation of Extracellular Matrix in Diabetic Nephropathy

INTRODUCTION

Diabetic nephropathy (DN) remains a major cause of end-stage renal disease. The development of novel biomarkers and early diagnosis of DN are of great clinical importance. The goal of this study was to identify hub genes with diagnostic potential for DN by weighted gene co-expression network analysis (WGCNA).

METHODS

Gene Expression Omnibus database was searched for microarray data including distinct types of CKD. Gene co-expression network was constructed, and modules specific for DN were identified by WGCNA. Gene ontology (GO) analysis was performed, and the hub genes were screened out within the selected gene modules. In addition, cross-validation was performed in an independent dataset and in samples of renal biopsies with DN and other types of glomerular diseases.

RESULTS

Dataset GSE99339 was selected, and a total of 179 microdissected glomeruli samples were analyzed, including DN, normal control, and 7 groups of other glomerular diseases. Twenty-three modules of the total 10,947 genes were grouped by WGCNA, and a module was specifically correlated with DN (r = 0.54, p = 9e-15). GO analysis showed that module genes were mainly enriched in the accumulation of extracellular matrix (ECM). LUM, ELN, FBLN1, MMP2, FBLN5, and FMOD were identified as hub genes. Cross verification showed LUM and FMOD were higher in the DN group and were negatively correlated with estimated glomerular filtration rate (eGFR). In renal biopsies, expression levels of LUM and FMOD were higher in DN than IgA nephropathy, membranous nephropathy, and normal controls.

CONCLUSION

By using WGCNA approach, we identified LUM and FMOD related to ECM accumulation and were specific for DN. These 2 genes may represent potential candidate diagnostic biomarkers of DN.

Exome Chip Analyses and Genetic Risk for IgA Nephropathy among Han Chinese

BACKGROUND AND OBJECTIVES

IgA nephropathy is the most common form of primary GN worldwide. The evidence of geographic and ethnic differences, as well as familial aggregation of the disease, supports a strong genetic contribution to IgA nephropathy. Evidence for genetic factors in IgA nephropathy comes also from genome-wide association patient-control studies. However, few studies have systematically evaluated the contribution of coding variation in IgA nephropathy.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

We performed a two-stage exome chip-based association study in 13,242 samples, including 3363 patients with IgA nephropathy and 9879 healthy controls of Han Chinese ancestry. Common variant functional annotation, gene-based low-frequency variants analysis, differential mRNA expression, and gene network integration were also explored.

RESULTS

We identified three non-HLA gene regions (FBXL21, CCR6, and STAT3) and one HLA gene region (GABBR1) with suggestive significance (Pmeta <5×10-5) in single-variant associations. These novel non-HLA variants were annotated as expression-associated single-nucleotide polymorphisms and were located in enhancer regions enriched in histone marks H3K4me1 in primary B cells. Gene-based low-frequency variants analysis suggests CFB as another potential susceptibility gene. Further combined expression and network integration suggested that the five novel susceptibility genes, TGFBI, CCR6, STAT3, GABBR1, and CFB, were involved in IgA nephropathy.

CONCLUSIONS

Five novel gene regions with suggestive significance for IgA nephropathy were identified and shed new light for further mechanism investigation.

Mesenchymal Stem Cell-Derived Exosomes Carry MicroRNA-125a to Protect Against Diabetic Nephropathy by Targeting Histone Deacetylase 1 and Downregulating Endothelin-1

BACKGROUND

Mesenchymal stem cell (MSC)-derived exosomes have seen great advances in human disease control in a minimally invasive manner. This research aimed to explore the function of MSC-derived exosomes in diabetic nephropathy (DN) progression and the molecules involved.

METHODS

A rat model with DN and rat glomerular mesangial cell (GMC) models treated with high glucose (HG) were established, which were treated with exosomes from adipose-derived-MSCs (adMSCs). The levels of blood glucose, serum creatinine, and urinary protein, the urine albumin-to-creatinine ratio (UACR), kidney weight/body weight, and mesangial hyperplasia and kidney fibrosis in rats were determined. The expression of interleukin-6 (IL-6), collagen I (Col. I), fibronectin (FN), Bax and Bcl-2 in HG-treated GMCs was assessed. The microRNA (miRNA) carried by adMSC-exosomes was identified, and the implicated down-stream molecules were analyzed.

RESULTS

adMSC-derived exosomes decreased levels of blood glucose, serum creatinine, 24-h urinary protein, UACR and kidney weight/body weight, and they suppressed mesangial hyperplasia and kidney fibrosis in DN rats. The exosomes also suppressed levels of IL6, Col. I and FN in HG-treated GMCs and promoted cell apoptosis. miR-125a was at least partially responsible for the above protective events mediated by adMSC-exosomes. miR-125a directly bound to histone deacetylase 1 (HDAC1), while HDAC1 further regulated endothelin-1 (ET-1) activation. Up-regulation of HDAC1 blocked the functions of adMSC-exosomal miR-125a.

CONCLUSION

This study suggested that adMSC-derived exosomes inhibit DN progression and alleviate the symptoms by carrying miR-125a, during which HDAC1 and ET-1 were inhibited. This study may provide novel effects into DN treatment.

VSIG4 Induces Epithelial-Mesenchymal Transition of Renal Tubular Cells under High-Glucose Conditions

High glucose-mediated tubular injury contributes to the development and progression of diabetic nephropathy through renal tubulointerstitial fibrosis. V-set immunoglobulin-domain-containing 4 (VSIG4), a B7 family-related protein, is a complement receptor. Although the role of epithelial–mesenchymal transition (EMT) has been reported in several diseases, little is known about its relationship with VSIG4 under diabetic conditions. This study aimed to investigate the role of VSIG4 in human tubule cells stimulated by high glucose (HG, 55 mM). HG upregulated both mRNA and protein levels of VSIG4 in proximal tubule cells (HK-2 cells) and Madin Darby Canine Kidney cells. These upregulations were accompanied by increased expression of mesenchymal markers such as fibronectin, N-cadherin, matrix metalloproteinase 9, and vimentin, and by decreased expression of the epithelial marker, E-cadherin. The siRNA-mediated inhibition of VSIG4 in HK-2 cells restored the dysregulation of EMT in cells. Interestingly, VSIG4 inhibition did not affect the expression of transforming growth factor (TGF)-β, whereas inhibition of TGF-β reduced VSIG4 expression, subsequently suppressing fibrosis markers. These findings suggest that VSIG4 plays an important role in mediating renal tubular EMT through the downstream action of HG-induced TGF-β activation.

Bioinformatic Reconstruction and Analysis of Gene Networks Related to Glucose Variability in Diabetes and Its Complications

Glucose variability (GV) has been recognized recently as a promoter of complications and therapeutic targets in diabetes. The aim of this study was to reconstruct and analyze gene networks related to GV in diabetes and its complications. For network analysis, we used the ANDSystem that provides automatic network reconstruction and analysis based on text mining. The network of GV consisted of 37 genes/proteins associated with both hyperglycemia and hypoglycemia. Cardiovascular system, pancreas, adipose and muscle tissues, gastrointestinal tract, and kidney were recognized as the loci with the highest expression of GV-related genes. According to Gene Ontology enrichment analysis, these genes are associated with insulin secretion, glucose metabolism, glycogen biosynthesis, gluconeogenesis, MAPK and JAK-STAT cascades, protein kinase B signaling, cell proliferation, nitric oxide biosynthesis, etc. GV-related genes were found to occupy central positions in the networks of diabetes complications (cardiovascular disease, diabetic nephropathy, retinopathy, and neuropathy) and were associated with response to hypoxia. Gene prioritization analysis identified new gene candidates (THBS1, FN1, HSP90AA1, EGFR, MAPK1, STAT3, TP53, EGF, GSK3B, and PTEN) potentially involved in GV. The results expand the understanding of the molecular mechanisms of the GV phenomenon in diabetes and provide molecular markers and therapeutic targets for future research.

Bioinformatics analysis reveals novel hub gene pathways associated with IgA nephropathy

BACKGROUND

Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulopathy worldwide. However, the molecular events underlying IgAN remain to be fully elucidated. This study aimed to identify novel biomarkers of IgAN through bioinformatics analysis and elucidate the possible molecular mechanism.

METHODS

Based on the microarray datasets GSE93798 and GSE37460 downloaded from the Gene Expression Omnibus database, the differentially expressed genes (DEGs) between IgAN samples and normal controls were identified. Using the DEGs, we further performed a series of functional enrichment analyses. Protein-protein interaction (PPI) networks of the DEGs were constructed using the STRING online search tool and were visualized using Cytoscape. Next, hub genes were identified and the most important module among the DEGs, Biological Networks Gene Ontology tool (BiNGO), was used to elucidate the molecular mechanism of IgAN.

RESULTS

In total, 148 DEGs were identified, comprising 53 upregulated genes and 95 downregulated genes. Gene Ontology (GO) analysis indicated that the DEGs for IgAN were mainly enriched in extracellular exosome, region and space, fibroblast growth factor stimulus, inflammatory response, and innate immunity. Module analysis showed that genes in the top 1 significant module of the PPI network were mainly associated with innate immune response, integrin-mediated signaling pathway and inflammatory response. The top 10 hub genes were constructed in the PPI network, which could well distinguish the IgAN and control group in monocyte and tissue samples. We finally identified the integrin subunit beta 2 (ITGB2) and Fc fragment of IgE receptor Ig (FCER1G) genes that may play important roles in the development of IgAN.

CONCLUSIONS

We identified key genes along with the pathways that were most closely related to IgAN initiation and progression. Our results provide a more detailed molecular mechanism for the development of IgAN and novel candidate gene targets of IgAN.

Complexities of the glomerular basement membrane

The glomerular basement membrane (GBM) is a key component of the glomerular capillary wall and is essential for kidney filtration. The major components of the GBM include laminins, type IV collagen, nidogens and heparan sulfate proteoglycans. In addition, the GBM harbours a number of other structural and regulatory components and provides a reservoir for growth factors. New technologies have improved our ability to study the composition and assembly of basement membranes. We now know that the GBM is a complex macromolecular structure that undergoes key transitions during glomerular development. Defects in GBM components are associated with a range of hereditary human diseases such as Alport syndrome, which is caused by defects in the genes COL4A3, COL4A4 and COL4A5, and Pierson syndrome, which is caused by variants in LAMB2. In addition, the GBM is affected by acquired autoimmune disorders and metabolic diseases such as diabetes mellitus. Current treatments for diseases associated with GBM involvement aim to reduce intraglomerular pressure and to treat the underlying cause where possible. As our understanding about the maintenance and turnover of the GBM improves, therapies to replace GBM components or to stimulate GBM repair could translate into new therapies for patients with GBM-associated disease.

Differential expression of parietal epithelial cell and podocyte extracellular matrix proteins in focal segmental glomerulosclerosis and diabetic nephropathy

In healthy glomeruli, parietal epithelial cell (PEC)-derived extracellular matrix (ECM) proteins include laminin-β1, perlecan, and collagen type IV-α2 and podocyte-specific ECM proteins include laminin-β2, agrin, and collagen type IV-α4. This study aimed to define individual ECM protein isoform expression by PECs in both experimental and human focal segmental glomerulosclerosis (FSGS) and diabetic nephropathy (DN) and to determine if changes were CD44 dependent. In experimental FSGS induced with a cytotoxic podocyte antibody and in the BTBR ob/ob mouse model of DN, PEC-derived protein staining was significantly increased in PECs. Dual staining also showed de novo expression of the podocyte-specific ECM proteins laminin-β2 and agrin in PECs. Similar findings were observed in biopsies from patients with FSGS and DN. Increases in individual ECM proteins colocalized with CD44 in PECs in disease. To determine the role of CD44, FSGS was induced in CD44-/- and CD44+/+ mice. PEC staining for perlecan, collagen type IV-α2, laminin-β2, and agrin were significantly lower in diseased CD44-/- mice compared with diseased CD44+/+ mice. These results show that in experimental and human FSGS and DN, PECs typically in an activated state, produce both PEC-derived and podocyte-specific ECM protein isoforms, and that the majority of these changes were dependent on CD44.