Bioinformatics analysis of genes related to iron death in diabetic nephropathy through network and pathway levels based approaches

Transcriptomic analysis reveals zinc-mediated virulence and pathogenicity in multidrug-resistant Acinetobacter baumannii

Acinetobacter baumannii is a gram-negative bacterium well known for its multidrug resistance and connection to nosocomial infections under ESKAPE pathogens. This opportunistic pathogen is ubiquitously associated with nosocomial infections, posing significant threats within healthcare environments. Its critical clinical symptoms, namely, meningitis, urinary tract infections, bloodstream infections, ventilator-associated pneumonia, and pneumonia, catalyze the imperative demand for innovative therapeutic interventions. The proposed research focuses on delineating the role of Zinc, a crucial metallo-binding protein and micronutrient integral to bacterial metabolism and virulence, to enhance understanding of the pathogenicity of A. baumannii. RNA sequencing and subsequent DESeq2 analytical methods were used to identify differential gene expressions influenced by zinc exposure. Exploiting the STRING database for functional enrichment analysis has demonstrated the complex molecular mechanisms underlying the enhancement of pathogenicity prompted by Zinc. Moreover, hub genes like gltB, ribD, AIL77834.1, sdhB, nuoI, acsA_1, acoC, accA, accD were predicted using the cytohubba tool in Cytoscape. This investigation underscores the pivotal role of Zinc in the virulence of A. baumannii elucidates the underlying molecular pathways responsible for its pathogenicity. The research further accentuates the need for innovative therapeutic strategies to combat A. baumannii infections, particularly those induced by multidrug-resistant strains.

The research trends of ferroptosis in diabetes: a bibliometric analysis

Objective

Exploring the mechanism of ferroptosis as a potential avenue for investigating the pathogenesis and therapeutic outlook of diabetes mellitus and its complications has emerged as a focal point within recent years. Herein, we employ a bibliometric approach to delineate the current landscape of ferroptosis research in the context of diabetes mellitus. Our objective is to furnish insights and scholarly references conducive to the advancement of comprehensive investigations and innovations in related domains.

Methods

We included studies on ferroptosis in diabetes, obtained from the Web of Science Core Collection. All publications were transported in plaintext full-record format and were analyzed by CiteSpace 6.2.R4 for bibliometric analysis.

Results

Four hundred and forty-eight records that met the criteria were included. The publications released during the initial 3 years were relatively small, while there was a sudden surge of publications published in 2022 and 2023. Representing 41 countries and 173 institutions, China and Wuhan University led the research on ferroptosis in diabetes. The author with the highest number of published papers is Zhongming Wu, while Dixon SJ is the most frequently cited author. The journal with the highest number of co-citations is Cell. The most common keywords include oxidative stress, cell death, lipid peroxidation, and metabolism. Extracted keywords predominantly focus on NLRP3 inflammatory, diabetic kidney disease, mitochondria, iron overload, and cardiomyopathy.

Conclusion

The escalating recognition of ferroptosis as a potential therapeutic target for deciphering the intricate mechanisms underlying diabetes and its complications is underscored by a noteworthy surge in relevant research publications. This surge has catapulted ferroptosis into the spotlight as a burgeoning and vibrant research focus within the field.

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.

VDR Activation Attenuates Renal Tubular Epithelial Cell Ferroptosis by Regulating Nrf2/HO-1 Signaling Pathway in Diabetic Nephropathy

Diabetic nephropathy (DN) is a serious microvascular complication of diabetes. Ferroptosis, a new form of cell death, plays a crucial role in the pathogenesis of DN. Renal tubular injury triggered by ferroptosis might be essential in this process. Numerous studies demonstrate that the vitamin D receptor (VDR) exerts beneficial effects by suppressing ferroptosis. However, the underlying mechanism has not been fully elucidated. Thus, they verified the nephroprotective effect of VDR activation and explored the mechanism by which VDR activation suppressed ferroptosis in db/db mice and high glucose-cultured proximal tubular epithelial cells (PTECs). Paricalcitol (PAR) is a VDR agonist that can mitigate kidney injury and prevent renal dysfunction. PAR treatment could inhibit ferroptosis of PTECs through decreasing iron content, increasing glutathione (GSH) levels, reducing malondialdehyde (MDA) generation, decreasing the expression of positive ferroptosis mediator transferrin receptor 1 (TFR-1), and enhancing the expression of negative ferroptosis mediators including ferritin heavy chain (FTH-1), glutathione peroxidase 4 (GPX4), and cystine/glutamate antiporter solute carrier family 7 member 11 (SLC7A11). Mechanistically, VDR activation upregulated the NFE2-related factor 2/heme oxygenase-1 (Nrf2/HO-1) signaling pathway to suppress ferroptosis in PTECs. These findings suggested that VDR activation inhibited ferroptosis of PTECs in DN via modulating the Nrf2/HO-1 signaling pathway.

Silencing KPNA2 Promotes Ferroptosis in Laryngeal Cancer by Activating the FoxO Signaling Pathway

We aim to clarify the specific role of Karyopherin α2 (KPNA2) in the progression of laryngeal cancer, a kind of malignant tumor with a poor curative effect. We performed the bioinformatic analysis to obtain the ferroptosis-related differentially expressed genes. KPNA2 was screened out. Then the CCK-8 assay, wound healing assay, and transwell assay were used to clarify the changes in the proliferation, migration, and invasion abilities of laryngeal cancer cells after silencing KPNA2. The concentrations of iron ions, glutathione, superoxide dismutase, and malondialdehyde were evaluated by the corresponding detection kits. The expression levels of cyclooxygenase 2, Acyl-CoA synthetase long-chain family member 4, glutathione peroxidase 4, forkhead box O (FoxO)1a and FoxO3a were determined by Western Blot. A total of 45 ferroptosis-related differentially expressed genes in laryngeal cancer were obtained, and KPNA2 was selected after bioinformatic analysis. In ferroptosis-induced laryngeal cancer cells, the cell viability, migration rate, invasion ability, and the expression of glutathione peroxidase 4, glutathione, and superoxide dismutase were further decreased and the expression of cyclooxygenase 2, Acyl-CoA synthetase long-chain family member 4, iron ions, and malondialdehyde were further increased after silencing KPNA2. The expression levels of FoxO1a and FoxO3a in laryngeal cancer cells were increased by silencing KPNA2. KPNA2 may be a promising therapeutic target for laryngeal cancer. Down-regulation of KPNA2 can promote ferroptosis in laryngeal cancer by stimulating the FoxO signaling pathway.

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.

Identification and experimental validation of ferroptosis-related gene lactotransferrin in age-related hearing loss

Objective

To reveal the relationship between ARHL and ferroptosis and screen ferroptosis-related genes (FRGs) in ARHL.

Methods

Bioinformatics were used to analyze the hub genes and molecular mechanism of ferroptosis in the aging cochleae. Senescence β-galactosidase staining, iron content detection, and micro malondialdehyde (MDA) assay kits were used to measure β-galactosidase activity, and expression of Fe2+ and MDA, respectively. Fluorescence microscope was used for immunofluorescence assay of hub genes. Western blot was used to verify the expression of hub genes in HEI-OC1 cells, cochlear explants, and cochleae of C57BL/6J mice. Data were expressed as mean ± SD of at least three independent experiments.

Results

The analysis of bioinformatics confirmed that lactotransferrin (LTF) is the hub gene and CEBPA-miR-130b-LTF network is the molecular mechanism for cochlear ferroptosis. Compared with the control group, the experiments proved that the indicators of ferroptosis, including Fe2+, MDA, and LTF were differentially expressed in aging HEI-OC1 cells, aging cochlear explants, and aging cochleae.

Conclusion

These results demonstrate that ferroptosis plays an important role in ARHL, and LTF is a potential therapeutic target for ARHL via regulating cochlear ferroptosis.

Single-cell and transcriptomic analyses reveal the influence of diabetes on ovarian cancer

BACKGROUND

There has been a significant surge in the global prevalence of diabetes mellitus (DM), which increases the susceptibility of individuals to ovarian cancer (OC). However, the relationship between DM and OC remains largely unexplored. The objective of this study is to provide preliminary insights into the shared molecular regulatory mechanisms and potential biomarkers between DM and OC.

METHODS

Multiple datasets from the GEO database were utilized for bioinformatics analysis. Single cell datasets from the GEO database were analysed. Subsequently, immune cell infiltration analysis was performed on mRNA expression data. The intersection of these datasets yielded a set of common genes associated with both OC and DM. Using these overlapping genes and Cytoscape, a protein‒protein interaction (PPI) network was constructed, and 10 core targets were selected. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were then conducted on these core targets. Additionally, advanced bioinformatics analyses were conducted to construct a TF-mRNA-miRNA coregulatory network based on identified core targets. Furthermore, immunohistochemistry staining (IHC) and real-time quantitative PCR (RT-qPCR) were employed for the validation of the expression and biological functions of core proteins, including HSPAA1, HSPA8, SOD1, and transcription factors SREBF2 and GTAT2, in ovarian tumors.

RESULTS

The immune cell infiltration analysis based on mRNA expression data for both DM and OC, as well as analysis using single-cell datasets, reveals significant differences in mononuclear cell levels. By intersecting the single-cell datasets, a total of 119 targets related to mononuclear cells in both OC and DM were identified. PPI network analysis further identified 10 hub genesincludingHSP90AA1, HSPA8, SNRPD2, UBA52, SOD1, RPL13A, RPSA, ITGAM, PPP1CC, and PSMA5, as potential targets of OC and DM. Enrichment analysis indicated that these genes are primarily associated with neutrophil degranulation, GDP-dissociation inhibitor activity, and the IL-17 signaling pathway, suggesting their involvement in the regulation of the tumor microenvironment. Furthermore, the TF-gene and miRNA-gene regulatory networks were validated using NetworkAnalyst. The identified TFs included SREBF2, GATA2, and SRF, while the miRNAs included miR-320a, miR-378a-3p, and miR-26a-5p. Simultaneously, IHC and RT-qPCR reveal differential expression of core targets in ovarian tumors after the onset of diabetes. RT-qPCR further revealed that SREBF2 and GATA2 may influence the expression of core proteins, including HSP90AA1, HSPA8, and SOD1.

CONCLUSION

This study revealed the shared gene interaction network between OC and DM and predicted the TFs and miRNAs associated with core genes in monocytes. Our research findings contribute to identifying potential biological mechanisms underlying the relationship between OC and DM.

Identification and validation of voltage-dependent anion channel 1-related genes and immune cell infiltration in diabetic nephropathy

AIMS/INTRODUCTION

This study investigated the roles of voltage-dependent anion channel 1-related differentially expressed genes (VRDEGs) in diabetic nephropathy (DN).

MATERIALS AND METHODS

We downloaded two datasets from patients with DN, namely, GSE30122 and GSE30529, from the Gene Expression Omnibus database. VRDEGs associated with DN were obtained from the intersection of voltage-dependent anion channel 1-related genes from the GeneCards database, and differentially expressed genes were screened according to group (DN/healthy) in the two datasets. The enriched pathways of the VRDEGs were analyzed. Hub genes were selected using a protein-protein interaction network, and their predictive value was verified through receiver operating characteristic curve analysis. The CIBERSORTx software examined hub genes and immune cell infiltration associations. The protein expression of hub genes was verified through immunohistochemistry in 16-week-old db/db mice for experimentation as a model of type 2 DN. Finally, potential drugs targeting hub genes that inhibit DN development were identified.

RESULTS

A total of 57 VRDEGs were identified. The two datasets showed high expression of the PI3K, Notch, transforming growth factor-β, interleukin-10 and interleukin-17 pathways in DN. Five hub genes (ITGAM, B2M, LYZ, C3 and CASP1) associated with DN were identified and verified. Immunohistochemistry showed that the five hub genes were highly expressed in db/db mice, compared with db/m mice. The infiltration of immune cells was significantly correlated with the five hub genes.

CONCLUSIONS

Five hub genes were significantly correlated with immune cell infiltration and might be crucial to DN development. This study provides insight into the mechanisms involved in the pathogenesis of DN.

Indexes of ferroptosis and iron metabolism were associated with the severity of diabetic nephropathy in patients with type 2 diabetes mellitus: a cross-sectional study

Objective

To explore the correlations between diabetic nephropathy (DN) and serum levels of glutathione peroxidase 4 (GPX4), acyl-CoA synthetase long-chain family member 4 (ACSL4), iron, transferrin (Tf), and ferritin in patients with type 2 diabetes mellitus (T2DM).

Methods

According to the urinary albumin excretion rate(UAER) or estimated glomerular filtration rate (eGFR) levels, a total of 123 patients with T2DM were separately divided into normoalbuminuria (NO), microalbuminuria (MI), macroalbuminuria (MA) groups, and G1 (eGFR ≥ 90 mL/min), G2 (eGFR ≤ 60 mL/min to < 90 mL/min), and G3 groups (eGFR< 60 mL/min), with 33 healthy participants as the control (HC). The differences in serum GPX4, ACSL4, iron, Tf, and ferritin levels between groups were compared, and the relationships between these levels were analysed. The independent correlations between UAER or DN severity and serum GPX4, ACSL4, iron, Tf, and ferritin levels were analysed by multiple linear and multinomial logistic regression, respectively.

Results

To the patients with T2DM, with the increase in UAER levels, GPX4, iron, and Tf levels gradually decreased, whereas ACSL4 levels increased, meanwhile with the decrease in eGFR levels, GPX4 and Tf levels gradually decreased, whereas ACSL4 levels increased. UAER were independently and positively correlated with ACSL4 [β = 17.53, 95% confidence interval (CI; 11.94, 23.13)] and negatively correlated with GPX4 [β = -1.633, 95% CI (-2.77, -0.496)] and Tf [β = -52.94, 95% CI (-95.78, -10.11)].The NO and MI groups were considered as reference groups, respectively. The severity of DN was negatively correlated with serum GPX4 [odds ratio (OR) = 0.925 and 0.902, p =0.015 and 0.001], and Tf (OR = 0.109 and 0.119, p =0.043 and 0.034), and positively correlated with ACSL4 (OR = 1.952 and 1.865, both p <0.001) in the MA group.

Conclusion

DN severity was negatively correlated with serum GPX4 and Tf levels and positively correlated with serum ACSL4 levels in patients with T2DM.

An integrated bioinformatics approach to identify key biomarkers in the tubulointerstitium of patients with focal segmental glomerulosclerosis and construction of mRNA-miRNA-lncRNA/circRNA networks

OBJECTIVE

The purpose of this study was to identify potential biomarkers in the tubulointerstitium of focal segmental glomerulosclerosis (FSGS) and comprehensively analyze its mRNA-miRNA-lncRNA/circRNA network.

METHODS

The expression data (GSE108112 and GSE200818) were downloaded from the Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo/). Identification and enrichment analysis of differentially expressed genes (DEGs) were performed. the PPI networks of the DEGs were constructed and classified using the Cytoscape molecular complex detection (MCODE) plugin. Weighted gene coexpression network analysis (WGCNA) was used to identify critical gene modules. Least absolute shrinkage and selection operator regression analysis were used to screen for key biomarkers of the tubulointerstitium in FSGS, and the receiver operating characteristic curve was used to determine their diagnostic accuracy. The screening results were verified by quantitative real-time-PCR (qRT-PCR) and Western blot. The transcription factors (TFs) affecting the hub genes were identified by Cytoscape iRegulon. The mRNA-miRNA-lncRNA/circRNA network for identifying potential biomarkers was based on the starBase database.

RESULTS

A total of 535 DEGs were identified. MCODE obtained eight modules. The green module of WGCNA had the greatest association with the tubulointerstitium in FSGS. PPARG coactivator 1 alpha (PPARGC1A) was screened as a potential tubulointerstitial biomarker for FSGS and verified by qRT-PCR and Western blot. The TFs FOXO4 and FOXO1 had a regulatory effect on PPARGC1A. The ceRNA network yielded 17 miRNAs, 32 lncRNAs, and 50 circRNAs.

CONCLUSIONS

PPARGC1A may be a potential biomarker in the tubulointerstitium of FSGS. The ceRNA network contributes to the comprehensive elucidation of the mechanisms of tubulointerstitial lesions in FSGS.

Ferroptosis: new insight into the mechanisms of diabetic nephropathy and retinopathy

Diabetic nephropathy (DN) and diabetic retinopathy (DR) are the most serious and common diabetes-associated complications. DN and DR are all highly prevalent and dangerous global diseases, but the underlying mechanism remains to be elucidated. Ferroptosis, a relatively recently described type of cell death, has been confirmed to be involved in the occurrence and development of various diabetic complications. The disturbance of cellular iron metabolism directly triggers ferroptosis, and abnormal iron metabolism is closely related to diabetes. However, the molecular mechanism underlying the role of ferroptosis in DN and DR is still unclear, and needs further study. In this review article, we summarize and evaluate the mechanism of ferroptosis and its role and progress in DN and DR, it provides new ideas for the diagnosis and treatment of DN and DR.

LncRNA NEAT1: A novel regulator associated with the inflammatory response in acute respiratory distress syndrome

BACKGROUND

Acute respiratory distress syndrome (ARDS) is a life-threatening condition with an unfavorable prognosis. As the pathogenesis of ARDS remains unclear, we aimed to identify the core genes associated with ARDS and the mechanisms by which competing endogenous RNAs (ceRNAs) regulate the disease's progression.

METHODS

Three mRNA microarray datasets (GSE17355, GSE48787, and GSE130936), derived from the Gene Expression Omnibus (GEO) database, were selected. Common differentially expressed genes (DEGs) related to acute lung injury (ALI) were identified and subjected to enrichment analysis. Then, hub genes were figured out through the protein-protein interaction (PPI) network and functional analysis, and targeted miRNAs and lncRNAs were predicted. Finally, the ceRNA networks associated with ALI were constructed and validated experimentally.

RESULTS

A total of 155 upregulated and 93 downregulated DEGs were identified in the three datasets. The TNF signaling pathway and IL-17 signaling pathway were the most enriched pathways. Then, eleven DEGs enriched in the IL-17 signaling pathway were selected as the hub genes. Three miRNAs (mmu-mir-155-5p, mmu-mir-21a-5p, and mmu-mir-122-5p), which were located in the lung tissue and predicted to bind the hub genes at the same time, and two lncRNAs (Neat1 and Tug1), which have binding sites for the aforementioned miRNAs, were filtered. With qPCR verification, we identified a ceRNA network composed of NEAT1, miR-21-5p, MMP9, and CXCL5. NEAT1 knockdown promoted the migration and reduced the expression of pro-inflammatory factor and reactive oxygen species (ROS) in lung epithelial cells. We eventually confirmed that NEAT1/miR-21-5p/CXCL5/MMP9 played a pivotal role in regulating the inflammatory response in ALI.

CONCLUSION

The IL-17 signaling pathway is of great importance in the pathogenesis of ARDS. NEAT1/miR-21-5p is involved in the inflammation of ALI by regulating CXCL5 and MMP9.

Identifying C1QB, ITGAM, and ITGB2 as potential diagnostic candidate genes for diabetic nephropathy using bioinformatics analysis

Background

Diabetic nephropathy (DN), the most intractable complication in diabetes patients, can lead to proteinuria and progressive reduction of glomerular filtration rate (GFR), which seriously affects the quality of life of patients and is associated with high mortality. However, the lack of accurate key candidate genes makes diagnosis of DN very difficult. This study aimed to identify new potential candidate genes for DN using bioinformatics, and elucidated the mechanism of DN at the cellular transcriptional level.

Methods

The microarray dataset GSE30529 was downloaded from the Gene Expression Omnibus Database (GEO), and the differentially expressed genes (DEGs) were screened by R software. We used Gene Ontology (GO), gene set enrichment analysis (GSEA), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to identify the signal pathways and genes. Protein-protein interaction (PPI) networks were constructed using the STRING database. The GSE30122 dataset was selected as the validation set. Receiver operating characteristic (ROC) curves were applied to evaluate the predictive value of genes. An area under curve (AUC) greater than 0.85 was considered to be of high diagnostic value. Several online databases were used to predict miRNAs and transcription factors (TFs) capable of binding hub genes. Cytoscape was used for constructing a miRNA-mRNA-TF network. The online database 'nephroseq' predicted the correlation between genes and kidney function. The serum level of creatinine, BUN, and albumin, and the urinary protein/creatinine ratio of the DN rat model were detected. The expression of hub genes was further verified through qPCR. Data were analyzed statistically using Student's t-test by the 'ggpubr' package.

Results

A total of 463 DEGs were identified from GSE30529. According to enrichment analysis, DEGs were mainly enriched in the immune response, coagulation cascades, and cytokine signaling pathways. Twenty hub genes with the highest connectivity and several gene cluster modules were ensured using Cytoscape. Five high diagnostic hub genes were selected and verified by GSE30122. The MiRNA-mRNA-TF network suggested a potential RNA regulatory relationship. Hub gene expression was positively correlated with kidney injury. The level of serum creatinine and BUN in the DN group was higher than in the control group (unpaired t test, t = 3.391, df = 4, p = 0.0275, r = 0.861). Meanwhile, the DN group had a higher urinary protein/creatinine ratio (unpaired t test, t = 17.23, df = 16, p < 0.001, r = 0.974). QPCR results showed that the potential candidate genes for DN diagnosis included C1QB, ITGAM, and ITGB2.

Conclusions

We identified C1QB, ITGAM and ITGB2 as potential candidate genes for DN diagnosis and therapy and provided insight into the mechanisms of DN development at transcriptome level. We further completed the construction of miRNA-mRNA-TF network to propose potential RNA regulatory pathways adjusting disease progression in DN.

Identification and characterization of the ferroptosis-related ceRNA network in irreversible pulpitis

Background

The role of ferroptosis in irreversible pulpitis (IP) remains unclear. The competing endogenous RNA (ceRNA) theory that has been widely investigated is rarely used studied in IP. Hub lncRNAs selected from a ceRNA network may provide a novel hypothesis for the interaction of ferroptosis and IP.

Methods

Differentially expressed genes (DEGs) were intersected with 484 ferroptosis markers to identify differentially expressed ferroptosis-related genes (DE-FRGs). Functional analysis and protein-protein interaction (PPI) networks were constructed to reveal the functions of DE-FRGs. Then, coexpression analyses were conducted between DE-FRGs and DElncRNAs to define ferroptosis-related DElncRNAs (FR-DElncRNAs). Predictions of DE-FRG- and FR-DElncRNA-related miRNAs were obtained, and members of both groups were selected. Additionally, two ceRNA networks consisting of FR-DElncRNAs, miRNAs and DE-FRGs from upregulated and downregulated groups were built. Finally, the hub lncRNAs of the ceRNA networks were used for immuno-infiltration analysis and qPCR verification.

Results

According to the results of PCA and clustering analysis, 5 inflamed and 5 healthy pulp tissue samples were selected for analysis. The intersection of DEGs with 484 ferroptosis marker genes identified 72 DE-FRGs. The response to stimulus, cellular process, signaling, localization, and biological regulation pathways related to DE-FRGs were enriched. In total, 161 downregulated and 40 upregulated FR-DElncRNAs were chosen by coexpression analysis for further investigation. The MultimiR package and starBase were used to predict miRNAs of DE-FRGs and FR-DElncRNAs, respectively. The upregulated ceRNA network contained 2 FR-DElncRNAs (↑), 19 miRNAs (↓) and 22 DE-FRGs (↑). The downregulated network contained 44 FR-DElncRNAs (↓), 251 miRNAs (↑) and 10 DE-FRGs (↓). Six hub lncRNAs were identified based on the MCC method (LUCAT1 and AC106897.1 ↑; LINC00943, AL583810.1, AC068888.1, and AC125257.1↓). In addition, strong relationships between hub lncRNAs and immune cells were shown by immune infiltration analysis. Finally, validated by qPCR assays of the pulp tissue of IP patients, the expression levels in clinical samples were consistent with the microarray data.

Conclusion

Two ceRNA networks were comprehensively constructed, and 6 hub lncRNAs were identified. These genes provide novel insights into the relationship between ferroptosis and IP. Intriguingly, the LINC00943/hsa-miR-29a-3p/PDK4 axis was deemed to be the key node in this network.

Emerging Role of Ferroptosis in Diabetic Kidney Disease: Molecular Mechanisms and Therapeutic Opportunities

Diabetic kidney disease (DKD) is one of the most common and severe microvascular complications of diabetes mellitus (DM), and has become the leading cause of end-stage renal disease (ESRD) worldwide. Although the exact pathogenic mechanism of DKD is still unclear, programmed cell death has been demonstrated to participate in the occurrence and development of diabetic kidney injury, including ferroptosis. Ferroptosis, an iron-dependent form of cell death driven by lipid peroxidation, has been identified to play a vital role in the development and therapeutic responses of a variety of kidney diseases, such as acute kidney injury (AKI), renal cell carcinoma and DKD. In the past two years, ferroptosis has been well investigated in DKD patients and animal models, but the specific mechanisms and therapeutic effects have not been fully revealed. Herein, we reviewed the regulatory mechanisms of ferroptosis, summarized the recent findings associated with the involvement of ferroptosis in DKD, and discussed the potential of ferroptosis as a promising target for DKD treatment, thereby providing a valuable reference for basic study and clinical therapy of DKD.

IncRNA XIST Promotes Cardiac Fibrosis in Mice with Diabetic Nephropathy via Sponging miR-106a-5p to Target RUNX1

Diabetic nephropathy (DN) accompanied by cardiac fibrosis (CF) increases the mortality rate among people with diabetes. This study sought to explore the molecular mechanism of long non-coding RNA X inactive specific transcript (lncRNA XIST) in CF in DN mice. The animal model of DN was established by streptozocin (STZ). The levels of lncRNA XIST, microRNA (miR)-106a-5p, and RUNX family transcription factor 1 (RUNX1) were determined by quantitative real-time polymerase chain reaction (qRT-PCR), followed by biochemical analysis, hematoxylin & eosin and Masson staining, echocardiography, and quantification of collagen I, collagen III, α-smooth muscle actin (α-SMA), and transforming growth factor-β1 (TGF-β1) levels through qRT-PCR and Western blot assay. The subcellular localization of lncRNA XIST was analyzed by nuclear/cytoplasmic fractionation assay and the bindings of miR-106a-5p to lncRNA XIST and RUNX1 were confirmed by RNA immunoprecipitation and dual-luciferase assays. Functional rescue experiments were performed to validate the role of miR-106a-5p/RUNX1 in CF in DN mice. lncRNA XIST and RUNX1 were elevated while miR-106a-5p was decreased in STZ mice. lncRNA XIST inhibition reduced myocardial injury and collagen deposition, along with decreased levels of fasting blood glucose, serum creatinine, blood urea nitrogen, and urinary microalbumin, collagen I, collagen III, α-SMA, and TGF-β1. lncRNA XIST competitively bound to miR-106a-5p to promote RUNX1 transcription. miR-106a-5p downregulation or RUXN1 upregulation reversed the protective role of lncRNA XIST inhibition in STZ mice. lncRNA XIST competitively bound to miR-106a-5p to promote RUNX1 transcription, thereby aggravating renal dysfunction and CF in DN mice.

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.

HIF-1α promotes paraquat induced acute lung injury and implicates a role NF-κB and Rac2 activity

Paraquat (PQ) is a bipyridine herbicide and oral exposure is the main way of PQ exposure with a very high mortality. At present, it is believed that large number of oxygen free radicals are generated and cause lipid peroxidation of tissue and organ cell membranes after PQ is absorbed. PQ exposure could cause multiple organ dysfunction, among which acute lung injury is the most common and most serious. However, its specific mechanism is still unclear. In this study, the C57BL/6J mouse (alveolar epithelial cell-specific knockout HIF-1α) model of acute lung injury (40 mg/kg PQ) at several time pointes and a model of acute type II alveolar epithelial cell (A549, 800 μM PQ) injury constructed. The oxidative stress (ROS, MDA) and inflammatory response (IL-1β, IL-6, TNF-α) were significantly inhibited in the alveolar epithelial cell-specific knockout of HIF-1α mice and siRNA technology to inhibit HIF-1α in alveolar epithelial cells. Further proteomic analysis showed that the expression of Rac2 protein, which is closely related to oxidative stress, was significantly increased after PQ exposure. And the inhibition of Rac2 expression in vitro significantly alleviated PQ-induced oxidative stress and inflammatory response. The expression of Rac2 protein was regulated by HIF-1α. The above suggests that HIF-1α may promote oxidative stress and inflammatory response in alveolar epithelial cells by regulating the expression of Rac2, and then participate in the promotion of PQ exposure-induced acute lung injury.

Identification of ferroptosis-related genes and pathways in diabetic kidney disease using bioinformatics analysis

Diabetic kidney disease (DKD) is a major public health issue because of its refractory nature. Ferroptosis is a newly coined programmed cell death characterized by the accumulation of lipid reactive oxygen species (ROS). However, the prognostic and diagnostic value of ferroptosis-related genes (FRGs) and their biological mechanisms in DKD remain elusive. The gene expression profiles GSE96804, GSE30566, GSE99339 and GSE30528 were obtained and analyzed. We constructed a reliable prognostic model for DKD consisting of eight FRGs (SKIL, RASA1, YTHDC2, SON, MRPL11, HSD17B14, DUSP1 and FOS). The receiver operating characteristic (ROC) curves showed that the ferroptosis-related model had predictive power with an area under the curve (AUC) of 0.818. Gene functional enrichment analysis showed significant differences between the DKD and normal groups, and ferroptosis played an important role in DKD. Consensus clustering analysis showed four different ferroptosis types, and the risk score of type four was significantly higher than that of other groups. Immune infiltration analysis indicated that the expression of macrophages M2 increased significantly, while that of neutrophils and mast cells activated decreased significantly in the high-risk group. Our study identified and validated the molecular mechanisms of ferroptosis in DKD. FRGs could serve as credible diagnostic biomarkers and therapeutic targets for DKD.

Identification of Genes Reveals the Mechanism of Cell Ferroptosis in Diabetic Nephropathy

Aims/Introduction: Diabetic nephropathy (DN) is one of the main complications of diabetes. Genomics may reveal the essential pathogenesis of DN. We analyzed datasets to search for key genes to explore pathological mechanisms of DN.

Materials and Methods: In this study, weighted gene co-expression network analysis (WGCNA) was used to divide the differential expression genes (DEGs) from GSE142025 into different modules, and enrichment pathway analysis was conducted for each module to find key genes related to cell death pathway. Then, verification was carried out through network and histopathology. Finally, the regulatory mechanisms of key gene expression, including transcription factors (TFs), miRNA and E3 ligases related to ubiquitination, were predicted through website prediction and then miRNA results were validated using GSE51674 dataset.

Results: The results of WGCNA and enrichment pathway analysis indicated that ferroptosis had significantly occurred in advanced DN (AND) group. Analysis of DEGs indicated that the occurrence and development of ferroptosis are mainly through ALOX15-mediated lipid metabolism pathway, which was found in all intrinsic cells of the glomerulus detected by IHC and IF staining. Moreover, network predictions were used for searching ALOX15-related TFs and ubiquitination. Meanwhile, the network predictions combining with other dataset furtherly discovered miRNAs which regulated ALOX15 expression. This study showed that the levels of mmu-miR-142-3p increased in DN mice kidney tissues, compared with the NC group.

Conclusion: Ferroptosis existed in glomerular intrinsic cells of ADN group and its potential key candidate gene was ALOX15 which may be regulated by miR-142 and miRNA-650, TFs (CREBBP, EP300, HDAC1, MTA1, SPI1, STAT6) and E3 ligases related to ubiquitination (PML, ZMIZ1, MARCHF1, MARCHF3, MARCHF8, MARCHF11).