Identification of a ferroptosis-related gene pair biomarker with immune infiltration landscapes in ischemic stroke: a bioinformatics-based comprehensive study

Bioinformatics Analysis Reveals HIST1H2BH as a Novel Diagnostic Biomarker for Atrial Fibrillation-Related Cardiogenic Thromboembolic Stroke

Atrial fibrillation (AF) is a significant precursor to cerebral embolism. Our study sought to unearth new diagnostic biomarkers for atrial fibrillation-related cerebral embolism (AF-CE) by meticulously examining multiple GEO datasets and meta-analysis. The gene expression omnibus (GEO) database provided RNA sequencing data associated with AF and stroke. We began by pinpointing genes with varied expressions in AF-CE patient blood samples. A meta-analysis was subsequently undertaken using several RNA sequencing datasets to verify these genes. LASSO regression discerned key genes for AF-CE, with their diagnostic prowess verified through ROC curve examination. Active signaling pathways within stroke patients were discerned via GO and KEGG enrichment, with PPI interactions detailing gene interplay. Differential gene analysis revealed an upregulation of sixteen genes and a downregulation of four in stroke patient blood samples. Eight genes showcased varied expression in the meta-analysis. LASSO regression zeroed in on five of these, culminating in HIST1H2BH's identification as a characteristic gene. HIST1H2BH's prowess in predicting AF-CE was confirmed through ROC. Integrin signaling, platelet activation, ECM interactions, and the PI3K-Akt pathway were found active in stroke victims. HIST1H2BH's interaction with the notably upregulated ITGA2B was spotlighted by PPI. Additionally, HIST1H2BH exhibited links with NK cells and eosinophils. HIST1H2BH emerges as an insightful diagnostic beacon for AF-CE. Its presence, post AF, potentially modulates pathways, accentuating platelet activation and consequent thrombus generation, leading to cerebral embolism.

Ferroptosis and endoplasmic reticulum stress in ischemic stroke

Ferroptosis is a form of non-apoptotic programmed cell death, and its mechanisms mainly involve the accumulation of lipid peroxides, imbalance in the amino acid antioxidant system, and disordered iron metabolism. The primary organelle responsible for coordinating external challenges and internal cell demands is the endoplasmic reticulum, and the progression of inflammatory diseases can trigger endoplasmic reticulum stress. Evidence has suggested that ferroptosis may share pathways or interact with endoplasmic reticulum stress in many diseases and plays a role in cell survival. Ferroptosis and endoplasmic reticulum stress may occur after ischemic stroke. However, there are few reports on the interactions of ferroptosis and endoplasmic reticulum stress with ischemic stroke. This review summarized the recent research on the relationships between ferroptosis and endoplasmic reticulum stress and ischemic stroke, aiming to provide a reference for developing treatments for ischemic stroke.

Analysis and identification of oxidative stress-ferroptosis related biomarkers in ischemic stroke

Studies have shown that a series of molecular events caused by oxidative stress is associated with ferroptosis and oxidation after ischemic stroke (IS). Differential analysis was performed to identify differentially expressed mRNA (DEmRNAs) between IS and control groups. Critical module genes were identified using weighted gene co-expression network analysis (WGCNA). DEmRNAs, critical module genes, oxidative stress-related genes (ORGs), and ferroptosis-related genes (FRGs) were crossed to screen for intersection mRNAs. Candidate mRNAs were screened based on the protein-protein interaction (PPI) network and the MCODE plug-in. Biomarkers were identified based on two types of machine learning algorithms, and the intersection was obtained. Functional items and related pathways of the biomarkers were identified using gene set enrichment analysis (GSEA). Finally, single-sample GSEA (ssGSEA) and Wilcoxon tests were used to identify differential immune cells. An miRNA-mRNA-TF network was created. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to verify the expression levels of biomarkers in the IS and control groups. There were 8287 DE mRNAs between the IS and control groups. The genes in the turquoise module were selected as critical module genes for IS. Thirty intersecting mRNAs were screened for overlaps. Seventeen candidate mRNAs were also identified. Four biomarkers (CDKN1A, GPX4, PRDX1, and PRDX6) were identified using two types of machine-learning algorithms. GSEA results indicated that the biomarkers were associated with steroid biosynthesis. Nine types of immune cells (activated B cells and neutrophils) were markedly different between the IS and control groups. We identified 3747 miRNA-mRNA-TF regulatory pairs in the miRNA-mRNA-TF regulatory network, including hsa-miR-4469-CDKN1A-BACH2 and hsa-miR-188-3p-GPX4-ATF2. CDKN1A, PRDX1, and PRDX6 were upregulated in IS samples compared with control samples. This study suggests that four biomarkers (CDKN1A, GPX4, PRDX1, and PRDX6) are significantly associated with IS. This study provides a new reference for the diagnosis and treatment of IS.

Bioinformatics and Integrative Experimental Method to Identifying and Validating Co-Expressed Ferroptosis-Related Genes in OA Articular Cartilage and Synovium

Purpose

Osteoarthritis (OA) is the most common joint disease worldwide and is the primary cause of disability and chronic pain in older adults.Ferroptosis is a type of programmed cell death characterized by aberrant iron metabolism and reactive oxygen species accumulation; however, its role in OA is not known.

Methods

To identify ferroptosis markers co-expressed in articular cartilage and synovium samples from patients with OA, in silico analysis was performed.Signature genes were analyzed and the results were evaluated using a ROC curve prediction model.The biological function, correlation between Signature genes, immune cell infiltration, and ceRNA network analyses were performed. Signature genes and ferroptosis phenotypes were verified through in vivo animal experiments and clinical samples. The expression levels of non-coding RNAs in samples from patients with OA were determined using qRT-PCR. ceRNA network analysis results were confirmed using dual-luciferase assays.

Results

JUN, ATF3, and CDKN1A were identified as OA- and ferroptosis-associated signature genes. GSEA analysis demonstrated an enrichment of these genes in immune and inflammatory responses, and amino acid metabolism. The CIBERSORT algorithm showed a negative correlation between T cells and these signature genes in the cartilage, and a positive correlation in the synovium. Moreover, RP5-894D12.5 and FAM95B1 regulated the expression of JUN, ATF3, and CDKN1A by competitively binding to miR-1972, miR-665, and miR-181a-2-3p. In vivo, GPX4 was downregulated in both OA cartilage and synovium; however, GPX4 and GSH were downregulated, while ferrous ions were upregulated in patient OA cartilage and synovium samples, indicating that ferroptosis was involved in the pathogenesis of OA. Furthermore, JUN, ATF3, and CDKN1A expression was downregulated in both mouse and human OA synovial and cartilage tissues. qRT-PCR demonstrated that miR-1972, RP5-894D12.5, and FAM95B1 were differentially expressed in OA tissues. Targeted interactions between miR-1972 and JUN, and a ceRNA regulatory mechanism between RP5-894D12.5, miR-1972, and JUN were confirmed by dual-luciferase assays.

Conclusion

This study identified JUN, ATF3, and CDKN1A as possible diagnostic biomarkers and therapeutic targets for joint synovitis and OA. Furthermore, our finding indicated that RP5-894D12.5/miR-1972/JUN was a potential ceRNA regulatory axis in OA, providing an insight into the connection between ferroptosis and OA.

Integrated analysis of circRNA-associated ceRNA network in ischemic stroke

Introduction: Stroke, of which ischemic stroke (IS) is the major type, is the second leading cause of disability and death worldwide. Circular RNAs (circRNAs) are reported to play important role in the physiology and pathology of IS. CircRNAs often act as competing endogenous RNA (ceRNA) to regulate gene expression by acting as miRNA sponges. However, whole transcriptome-wide screenings of circRNA-mediated ceRNA networks associated with IS are still lacking. In the present study, we constructed a circRNA-miRNA-mRNA ceRNA network by whole transcriptome-wide analysis. Methods: CircRNAs, miRNAs and mRNAs expression profiles were downloaded from the Gene Expression Omnibus (GEO) datasets. We identified differentially expressed (DE) circRNAs, miRNAs, and mRNAs in IS patients. StarBase and CircBank databases were used to predict the miRNA targets of DEcircRNAs, and mirDIP database was used to predict the mRNA targets of DEmiRNAs. CircRNA-miRNA pairs and miRNA-mRNA pairs were established. Then, we identified hub genes via protein-protein interaction analysis and constructed a core ceRNA sub-network. Results: In total, 276 DEcircRNAs, 43 DEmiRNAs, and 1926 DEmRNAs were explored. The ceRNA network included 69 circRNAs, 24 miRNAs, and 92 mRNAs. The core ceRNA subnetwork included hsa_circ_0011474, hsa_circ_0023110, CDKN1A, FHL2, RPS2, CDK19, KAT6A, CBX1, BRD4, and ZFHX3. Discussion: In conclusion, we established a novel hsa_circ_0011474 - hsa-miR-20a-5p/hsa-miR-17-5p - CDKN1A ceRNA regulatory axis associated with IS. Our findings provide new insights into the pathogenesis of IS and offer promising diagnostic and predictive biomarkers.

Competing endogenous RNA network analysis of the molecular mechanisms of ischemic stroke

BACKGROUND

Ischemic stroke (IS) is a serious neurological disease that largely results in long-term disability and death. Extensive evidence has indicated that the activation of inflammation and ferroptosis significantly contribute to the development of IS pathology. However, the underlying molecular mechanism remains unclear. In this study, we aimed to identify potential biomarkers associated with IS through the construction of a competing endogenous RNA (ceRNA) network and to investigate the possible inflammatory and ferroptosis-related molecular mechanisms.

RESULTS

We identified 178 differentially expressed target messenger RNAs (DETmRNAs) associated with IS. As revealed through enrichment analysis, the DEmRNAs were mainly enriched in the inflammatory signaling pathways and also related to ferroptosis mechanism. The CIBERSORT algorithm showed immune infiltration landscapes in which the naïve B cells, naïve T cells, and monocytes had statistically different numbers in the cerebral infarction group compared with the control group. A ceRNA network was constructed in this study involving 44 long non-coding RNAs (lncRNAs), 15 microRNAs (miRNAs), and 160 messenger RNAs (mRNAs). We used the receiver operating characteristic (ROC) analysis to identify three miRNAs (miR-103a-3p, miR-140-3p, and miR-17-5p), one mRNA (TLR4), and one lncRNA (NEAT1) as the potential key biomarkers of the ceRNA network. The key mRNA and lncRNA were shown to be highly related to the ferroptosis mechanism of IS. The expression of these key biomarkers was also further validated by a method of quantitative real-time polymerase chain reaction in SH-SY5Y cells, and the validated results were consistent with the findings predicted by bioinformatics.

CONCLUSION

Our results suggest that the ceRNA network may exert an important role in the inflammatory and ferroptosis molecular mechanisms of IS, providing new insight into therapeutic IS targets.

Emerging roles of ferroptosis in cardiovascular diseases

The mechanism of cardiovascular diseases (CVDs) is complex and threatens human health. Cardiomyocyte death is an important participant in the pathophysiological basis of CVDs. Ferroptosis is a new type of iron-dependent programmed cell death caused by excessive accumulation of iron-dependent lipid peroxides and reactive oxygen species (ROS) and abnormal iron metabolism. Ferroptosis differs from other known cell death pathways, such as apoptosis, necrosis, necroptosis, autophagy and pyroptosis. Several compounds have been shown to induce or inhibit ferroptosis by regulating related key factors or signalling pathways. Recent studies have confirmed that ferroptosis is associated with the development of diverse CVDs and may be a potential therapeutic drug target for CVDs. In this review, we summarize the characteristics and related mechanisms of ferroptosis and focus on its role in CVDs, with the goal of inspiring novel treatment strategies.

New Insights into the Regulatory Role of Ferroptosis in Ankylosing Spondylitis via Consensus Clustering of Ferroptosis-Related Genes and Weighted Gene Co-Expression Network Analysis

Background: The pathogenesis of ankylosing spondylitis (AS) remains undetermined. Ferroptosis is a newly discovered form of regulated cell death involved in multiple autoimmune diseases. Currently, there are no reports on the connection between ferroptosis and AS. Methods: AS samples from the Gene Expression Omnibus were divided into two subgroups using consensus clustering of ferroptosis-related genes (FRGs). Weighted gene co-expression network analysis (WGCNA) of the intergroup differentially expressed genes (DEGs) and protein–protein interaction (PPI) analysis of the key module were used to screen out hub genes. A multifactor regulatory network was then constructed based on hub genes. Results: The 52 AS patients in dataset GSE73754 were divided into cluster 1 (n = 24) and cluster 2 (n = 28). DEGs were mainly enriched in pathways related to mitochondria, ubiquitin, and neurodegeneration. Candidate hub genes, screened by PPI and WGCNA, were intersected. Subsequently, 12 overlapping genes were identified as definitive hub genes. A multifactor interaction network with 45 nodes and 150 edges was generated, comprising the 12 hub genes and 32 non-coding RNAs. Conclusions: AS can be divided into two subtypes according to FRG expression. Ferroptosis might play a regulatory role in AS. Tailoring treatment according to the ferroptosis status of AS patients can be a promising direction.

Eucommia ulmoides Oliver-Tribulus terrestris L. Drug Pair Regulates Ferroptosis by Mediating the Neurovascular-Related Ligand-Receptor Interaction Pathway- A Potential Drug Pair for Treatment Hypertension and Prevention Ischemic Stroke

Background

In this study, we used the network pharmacology approach to explore the potential disease targets of the Eucommia ulmoides Oliver (EUO)-Tribulus terrestris L. (TT) drug pair in the treatment of hypertension-associated neurovascular lesions and IS via the ferroptosis pathway.

Methods

We used the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform to search for the key active compounds and targets of the drug pair. Based on the GeneCards database, the relevant targets for the drug pair were obtained. Then, we performed the molecular docking of the screened core active ingredients and proteins using the DAVID database and the R AutoDock Vina software. Based on the GSE22255 dataset, these screened target proteins were used to build random forest (RF) and support vector machine (SVM) models. Finally, a new IS nomogram prediction model was constructed and evaluated.

Results

There were 36 active compounds in the EUO-TT drug pair. CHRM1, NR3C1, ADRB2, and OPRD1 proteins of the neuroactive ligand-receptor interaction pathway interacted with the proteins related to the ferroptosis pathway. Molecular docking experiments identified 12 active ingredients of the drug pair that may tightly bind to those target proteins. We constructed a visual IS nomogram prediction model using four genes (CHRM1, NR3C1, ADRB2, and OPRD1). The calibration curve, DCA, and clinical impact curves all indicated that the nomogram model is clinically applicable and diagnostically capable. CHRM1, NR3C1, ADRB2, and OPRD1, the target genes of the four effective components of the EUO-TT drug pair, were considered as risk markers for IS.

Conclusions

The active ingredients of EUO-TT drug pair may act on proteins associated with the neuroactive ligand-receptor interaction pathway to regulate ferroptosis in vascular neurons cells, ultimately affecting the onset and progression of hypertension.