Identification of key genes and upstream regulators in ischemic stroke

Identification of hypoxia- and immune-related biomarkers in patients with ischemic stroke

Background

The immune microenvironment and hypoxia play crucial roles in the pathophysiology of ischemic stroke (IS). Hence, in this study, we aimed to identify hypoxia- and immune-related biomarkers in IS.

Methods

The IS microarray dataset GSE16561 was examined to determine differentially expressed genes (DEGs) utilizing bioinformatics-based analysis. The intersection of hypoxia-related genes and DEGs was conducted to identify differentially expressed hypoxia-related genes (DEHRGs). Then, using weighted correlation network analysis (WGCNA), all of the genes in GSE16561 dataset were examined to create a co-expression network, and module-clinical trait correlations were examined for the purpose of examining the genes linked to immune cells. The immune-related DEHRGs were submitted to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. A protein-protein interaction (PPI) network was constructed by Cytoscape plugin MCODE, in order to extract hub genes. The miRNet was used to predict hub gene-related transcription factors (TFs) and miRNAs. Finally, a diagnostic model was developed by least absolute shrinkage and selection operator (LASSO) logistic regression.

Results

Between the control and IS samples, 4171 DEGs were found. Thereafter, the intersection of hypoxia-related genes and DEGs was conducted to obtain 45 DEHRGs. Ten significantly differentially infiltrated immune cells were found-namely, CD56dim natural killer cells, activated CD8 T cells, activated dendritic cells, activated B cells, central memory CD8 T cells, effector memory CD8 T cells, natural killer cells, gamma delta T cells, plasmacytoid dendritic cells, and neutrophils-between IS and control samples. Subsequently, we identified 27 immune-related DEHRGs through the intersection of DEHRGs and genes in important modules of WGCNA. The immune-related DEHRGs were primarily enriched in response to hypoxia, cellular polysaccharide metabolic process, response to decreased oxygen levels, polysaccharide metabolic process, lipid and atherosclerosis, and HIF-1 signaling pathway H. Using MCODE, FOS, DDIT3, DUSP1, and NFIL3 were found to be hub genes. In the validation cohort and training set, the AUC values of the diagnostic model were 0.9188034 and 0.9395085, respectively.

Conclusion

In brief, we identified and validated four hub genes-FOS, DDIT3, DUSP1, and NFIL3-which might be involved in the pathological development of IS, potentially providing novel perspectives for the diagnosis and treatment of IS.

Identification and validation of platelet-related diagnostic markers and potential drug screening in ischemic stroke by integrating comprehensive bioinformatics analysis and machine learning

Background

Ischemic stroke (IS), caused by blood and oxygen deprivation due to cerebral thrombosis, has links to activated and aggregated platelets. Discovering platelet-related biomarkers, developing diagnostic models, and screening antiplatelet drugs are crucial for IS diagnosis and treatment.

Methods and results

Combining and normalizing GSE16561 and GSE22255 datasets identified 1,753 upregulated and 1,187 downregulated genes. Fifty-one genes in the platelet-related module were isolated using weighted gene co-expression network analysis (WGCNA) and other analyses, including 50 upregulated and one downregulated gene. Subsequent enrichment and network analyses resulted in 25 platelet-associated genes and six diagnostic markers for a risk assessment model. This model's area under the ROC curve outperformed single genes, and in the peripheral blood of the high-risk group, immune infiltration indicated a higher proportion of CD4, resting CD4 memory, and activated CD4 memory T cells, along with a lower proportion of CD8 T cells in comparison to the low-risk group. Utilizing the gene expression matrix and the CMap database, we identified two potential drugs for IS. Finally, a rat MACO/R model was used to validate the diagnostic markers' expression and the drugs' predicted anticoagulant effects.

Conclusion

We identified six IS platelet-related biomarkers (APP, THBS1, F13A1, SRC, PPBP, and VCL) for a robust diagnostic model. The drugs alpha-linolenic acid and ciprofibrate have potential antiplatelet effects in IS. This study advances early IS diagnosis and treatment.

Negative regulation of angiogenesis and the MAPK pathway may be a shared biological pathway between IS and epilepsy

Ischemia stroke and epilepsy are two neurological diseases that have significant patient and societal burden, with similar symptoms of neurological deficits. However, the underlying mechanism of their co-morbidity are still unclear. In this study, we performed a combined analysis of six gene expression profiles (GSE58294, GSE22255, GSE143272, GSE88723, GSE163654, and GSE174574) to reveal the common mechanisms of IS and epilepsy. In the mouse datasets, 74 genes were co-upregulated and 7 genes were co-downregulated in the stroke and epilepsy groups. Further analysis revealed that the co-expressed differentially expressed genes (DEGs) were involved in negative regulation of angiogenesis and the MAPK signaling pathway, and this was verified by Gene Set Enrichment Analysis of human datasets and single cell RNA sequence of middle cerebral artery occlusion mice. In addition, combining DEGs of human and mouse, PTGS2, TMCC3, KCNJ2, and GADD45B were identified as cross species conserved hub genes. Meanwhile, molecular docking results revealed that trichostatin A and valproic acid may be potential therapeutic drugs. In conclusion, to our best knowledge, this study conducted the first comorbidity analysis of epilepsy and ischemic stroke to identify the potential common pathogenic mechanisms and drugs. The findings may provide an important reference for the further studies on post-stroke epilepsy.

Construction of a novel circRNA-miRNA-ferroptosis related mRNA network in ischemic stroke

Molecule alterations are important to explore the pathological mechanism of ischemic stroke (IS). Ferroptosis, a newly recognized type of regulated cell death, is related to IS. Identification of the interactions between circular RNA (circRNA), microRNA (miRNA) and ferroptosis related mRNA may be useful to understand the molecular mechanism of IS. The circRNA, miRNA and mRNA transcriptome data in IS, downloaded from the Gene Expression Omnibus (GEO) database, was used for differential expression analysis. Ferroptosis related mRNAs were identified from the FerrDb database, followed by construction of circRNA-miRNA-ferroptosis related mRNA network. Enrichment and protein-protein interaction analysis of mRNAs in circRNA-miRNA-mRNA network was performed, followed by expression validation by reverse transcriptase polymerase chain reaction and online dataset. A total of 694, 41 and 104 differentially expressed circRNAs, miRNAs and mRNAs were respectively identified in IS. Among which, dual specificity phosphatase 1 (DUSP1), nuclear receptor coactivator 4 (NCOA4) and solute carrier family 2 member 3 (SLC2A3) were the only three up-regulated ferroptosis related mRNAs. Moreover, DUSP1, NCOA4 and SLC2A3 were significantly up-regulated in IS after 3, 5 and 24 h of the attack. Based on these three ferroptosis related mRNAs, 4 circRNA-miRNA-ferroptosis related mRNA regulatory relationship pairs were identified in IS, including hsa_circ_0071036/hsa_circ_0039365/hsa_circ_0079347/hsa_circ_0008857-hsa-miR-122-5p-DUSP1, hsa_circ_0067717/hsa_circ_0003956/hsa_circ_0013729-hsa-miR-4446-3p-SLC2A3, hsa_circ_0059347/hsa_circ_0001414/hsa_circ_0049637-hsa-miR-885-3p-SLC2A3, and hsa_circ_0005633/hsa_circ_0004479-hsa-miR-4435-NCOA4. In addition, DUSP1 is involved in the signaling pathway of fluid shear stress and atherosclerosis. Relationship of regulatory action between circRNAs, miRNAs and ferroptosis related mRNAs may be associated with the development of IS.

Investigating the AC079305/DUSP1 Axis as Oxidative Stress-Related Signatures and Immune Infiltration Characteristics in Ischemic Stroke

Background

Oxidative stress (OS) and immune inflammation play complex intersections in the pathophysiology of ischemic stroke (IS). However, a competing endogenous RNA- (ceRNA-) based mechanism linked to the intersections in IS has not been explored. We aimed to identify potential OS-related signatures and analyze immune infiltration characteristics in IS.

Methods

Three datasets (GSE22255, GSE110993, and GSE140275) from the GEO database were extracted. Differentially expressed long noncoding RNAs, microRNAs, and messenger RNAs (DElncRNAs, DEmiRNAs, and DEmRNAs) between IS patients and controls were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were explored. Moreover, a triple ceRNA network was constructed to reveal transcriptional regulation mechanisms. A comprehensive strategy among least absolute shrinkage and selection operator (LASSO) regression, DEmRNAs, uprelated DEmRNAs, and OS-related genes was adopted to select the best signature. Then, we evaluated and verified the discriminant ability of the signature via receiver operating characteristic (ROC) analysis. Immune infiltration characteristics were explored via the CIBERSORT algorithm. Moreover, the best signature was verified via qPCR and western blot methods in rat brain tissues and PC12 cells.

Results

11 DEmRNAs were identified totally. Enrichment analysis showed that the DEmRNAs were primarily concentrated in MAPK-associated biological processes and immune or inflammation-involved pathways. DUSP1 was identified as the best signature with an area under the ROC curve of 73.5% (95%CI = 57.02-89.98, sensitivity = 95%, and specificity = 60%) in GSE22255 and 100.0% (95%CI = 100.00-100.00, sensitivity = 100%, and specificity = 100%) in GSE140275. Importantly, we also identified the AC079305/DUSP1 axis in the ceRNA network. Immune infiltration showed that resting mast cells infiltrate less in IS patients compared with controls. And DUSP1 was negatively correlated with resting mast cells (r = −0.703, P < 0.01), whereas it was positively correlated with neutrophils (r = 0.339, P < 0.05). Both in vivo and in vitro models confirmed the upregulated expression of DUSP1 and the downregulated expression of miR-429.

Conclusion

This study identified the ceRNA-based AC079305/DUSP1 axis as a promising OS-related signature for IS. Immune infiltrating cells, especially mast cells, may exert a pivotal role in IS progression. Pharmacological agents targeting signatures, their receptors, or mast cells may shed a novel light on therapeutic targets for IS.

Prediction of Mechanosensitive Genes in Vascular Endothelial Cells Under High Wall Shear Stress

Objective: The vulnerability of atherosclerotic plaques is among the leading cause of ischemic stroke. High wall shear stress (WSS) promotes the instability of atherosclerotic plaques by directly imparting mechanical stimuli, but the specific mechanisms remain unclear. We speculate that modulation of mechanosensitive genes may play a vital role in accelerating the development of plaques. The purpose of this study was to find mechanosensitive genes in vascular endothelial cells (ECs) through combining microarray data with bioinformatics technology and further explore the underlying dynamics–related mechanisms that cause the progression and destabilization of atherosclerotic plaques.

Methods: Microarray data sets for human vascular ECs under high and normal WSS were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified through the R language. The performance of enrichment analysis and protein–protein interaction (PPI) network presented the biological function and signaling pathways of the DEGs. Hub genes were identified based on the PPI network and validated by GEO data sets. Predicted transcription factor (TF) genes and miRNAs interaction with potential mechanosensitive genes were identified by NetworkAnalyst.

Results: A total of 260 DEGs, 121 upregulated and 139 downregulated genes, were screened between high and normal WSS from GSE23289. A total of 10 hub genes and four cluster modules were filtered out based on the PPI network. The enrichment analysis showed that the biological functions of the hub genes were mainly involved in responses to unfolded protein and topologically incorrect protein, and t to endoplasmic reticulum stress. The significant pathways associated with the hub genes were those of protein processing in the endoplasmic reticulum, antigen processing, and presentation. Three out of the 10 hub genes, namely, activated transcription factor 3 (ATF3), heat shock protein family A (Hsp70) member 6 (HSPA6), and dual specificity phosphatase 1 (DUSP1, also known as CL100, HVH1, MKP-1, PTPN10), were verified in GSE13712. The expression of DUSP1 was higher in the senescent cell under high WSS than that of the young cell. The TF–miRNA–mechanosensitive gene coregulatory network was constructed.

Conclusion: In this work, we identified three hub genes, ATF3, HSPA6, and DUSP1, as the potential mechanosensitive genes in the human blood vessels. DUSP1 was confirmed to be associated with the senescence of vascular ECs. Therefore, these three mechanosensitive genes may have emerged as potential novel targets for the prediction and prevention of ischemic stroke. Furthermore, the TF–miRNA–mechanosensitive genes coregulatory network reveals an underlying regulatory mechanism and the pathways to control disease progression.

Identification of Dysregulated Mechanisms and Potential Biomarkers in Ischemic Stroke Onset

Objective

Ischemic stroke (IS) is a major cause of severe disability. This study aimed to identify potential biomarkers closely related to IS diagnosis and treatment.

Methods

Profiles of gene expression were obtained from datasets GSE16561, GSE22255, GSE112801 and GSE110993. Differentially expressed mRNAs between IS and controls were then subjected to weighted gene co-expression network analysis as well as multiscale embedded gene co-expression network analysis. The intersection of the two sets of module genes was subjected to analyses of functional enrichment and of microRNAs (miRNAs) regulation. Then, the area under receiver operating characteristic curves (AUC) was calculated to assess the ability of genes to discriminate IS patients from controls. IS diagnostic signatures were constructed using least absolute shrinkage and selection operator regression.

Results

A total of 234 common co-expression network genes were found to be potentially associated with IS. Enrichment analysis found that these genes were mainly associated with inflammation and immune response. The aberrantly expressed miRNAs (hsa-miR-651-5p, hsa-miR-138-5p, hsa-miR-9-3p and hsa-miR-374a-3p) in IS had regulatory effects on IS-related genes and were involved in brain-related diseases. We used the criterion AUC > 0.7 to screen out 23 hub genes from IS-related genes in the GSE16561 and GSE22255 datasets. We obtained an 8-gene signature (ADCY4, DUSP1, ATP5F1, DCTN5, EIF3G, ELAVL1, EXOSC7 and PPIE) from the training set of GSE16561 dataset, which we confirmed in the validation set of GSE16561 dataset and in the GSE22255 dataset. The genes in this signature were highly accurate for diagnosing IS. In addition, the 8-gene signature significantly correlated with infiltration by immune cells.

Conclusion

These findings provide new clues to molecular mechanisms and treatment targets in IS. The genes in the signature may be candidate markers and potential gene targets for treatments.

High-Density Lipoprotein Carries Markers That Track With Recovery From Stroke

RATIONALE

Prospective cohort studies question the value of HDL-C (high-density lipoprotein cholesterol) for stroke risk prediction.

OBJECTIVE

Investigate the relationship between long-term functional recovery and HDL proteome and function.

METHODS AND RESULTS

Changes in HDL protein composition and function (cholesterol efflux capacity) in patients after acute ischemic stroke at 2 time points (24 hours, 35 patients; 96 hours, 20 patients) and in 35 control subjects were measured. The recovery from stroke was assessed by 3 months, the National Institutes of Health Stroke Scale and modified Rankin scale scores. When compared with control subject after adjustments for sex and HDL-C levels, 12 proteins some of which participate in acute phase response and platelet activation (APMAP [adipocyte plasma membrane-associated protein], GPLD1 [phosphate inositol-glycan specific phospholipase D], APOE [apolipoprotein E], IHH [Indian hedgehog protein], ITIH4 [inter-alpha-trypsin inhibitor chain H4], SAA2 [serum amyloid A2], APOA4 [apolipoprotein A-IV], CLU [clusterin], ANTRX2 [anthrax toxin receptor 2], PON1 [serum paraoxonase/arylesterase], SERPINA1 [alpha-1-antitrypsin], and APOF [apolipoprotein F]) were significantly (adjusted P<0.05) altered in stroke HDL at 96 hours. The first 8 of these proteins were also significantly altered at 24 hours. Consistent with inflammatory remodeling, cholesterol efflux capacity was reduced by 32% (P<0.001) at both time points. Baseline stroke severity adjusted regression model showed that changes within 96-hour poststroke in APOF, APOL1, APMAP, APOC4 (apolipoprotein C4), APOM (apolipoprotein M), PCYOX1 (prenylcysteine oxidase 1), PON1, and APOE correlate with stroke recovery scores (R2=0.38-0.73, adjusted P<0.05). APOF (R2=0.73) and APOL1 (R2=0.60) continued to significantly correlate with recovery scores after accounting for tPA (tissue-type plasminogen activator) treatment.

CONCLUSIONS

Changes in HDL proteins during early acute phase of stroke associate with recovery. Monitoring HDL proteins may provide clinical biomarkers that inform on stroke recuperation.

Long noncoding RNA ZNF800 suppresses proliferation and migration of vascular smooth muscle cells by upregulating PTEN and inhibiting AKT/mTOR/HIF-1α signaling

BACKGROUND AND AIMS

Long noncoding RNAs (lncRNAs) have recently been implicated in many biological and disease processes, but the exact mechanism of their involvement in atherosclerosis is unclear. The aberrant proliferation and migration of vascular smooth muscle cells (VSMCs) is a major contributor to the development of atherosclerotic lesions. This study aimed to investigate the potential effects of lncRNA ZNF800, a previously uncharacterized lncRNA, on VSMC proliferation and migration.

METHODS

The expression of lncRNA ZNF800 in atherosclerotic plaque tissues was detected using reverse transcription-quantitative PCR (RT-qPCR), while the role and mechanism of lncRNA ZNF800 in proliferation and migration of VSMCs were investigated by CCK8 assay, transwell assay, scratch wound assay, RT-qPCR and Western blot.

RESULTS

We found that lncRNA ZNF800 was significantly more abundant in atherosclerotic plaque tissues, and substantially suppressed the proliferation and migration of VSMCs. LncRNA ZNF800 had no effect on phosphatase and tensin homolog deleted on chromosome 10 (PTEN) mRNA expression but dramatically increased the levels of PTEN protein. Enhanced lncRNA ZNF800 expression inhibited the activity of the AKT/mTOR/HIF-1α signaling pathway, downregulated the expression of vascular endothelial growth factor α (VEGF-α) and matrix metalloproteinase 1 (MMP1), and suppressed VSMC proliferation and migration. These inhibitory effects of lncRNA ZNF800 were abolished by knockdown of PTEN. The inhibitory effects of lncRNA ZNF800 on cell proliferation and migration and the expression of VEGF-α and MMP1 were exacerbated by HIF-1α knockdown in VSMCs.

CONCLUSIONS

These findings demonstrated that lncRNA ZNF800 suppressed VSMC proliferation and migration by interacting with PTEN through a mechanism involving AKT/mTOR/HIF-1α signaling. Therefore, it may play a key atheroprotective role and represent a potential therapeutic target for atherosclerosis-related diseases.

Identification of candidate genes in ischemic cardiomyopathy by gene expression omnibus database

BACKGROUND

Ischemic cardiomyopathy (ICM) is one of the most usual causes of death worldwide. This study aimed to find the candidate gene for ICM.

METHODS

We studied differentially expressed genes (DEGs) in ICM compared to healthy control. According to these DEGs, we carried out the functional annotation, protein-protein interaction (PPI) network and transcriptional regulatory network constructions. The expression of selected candidate genes were confirmed using a published dataset and Quantitative real time polymerase chain reaction (qRT-PCR).

RESULTS

From three Gene Expression Omnibus (GEO) datasets, we acquired 1081 DEGs (578 up-regulated and 503 down-regulated genes) between ICM and healthy control. The functional annotation analysis revealed that cardiac muscle contraction, hypertrophic cardiomyopathy, arrhythmogenic right ventricular cardiomyopathy and dilated cardiomyopathy were significantly enriched pathways in ICM. SNRPB, BLM, RRS1, CDK2, BCL6, BCL2L1, FKBP5, IPO7, TUBB4B and ATP1A1 were considered the hub proteins. PALLD, THBS4, ATP1A1, NFASC, FKBP5, ECM2 and BCL2L1 were top six transcription factors (TFs) with the most downstream genes. The expression of 6 DEGs (MYH6, THBS4, BCL6, BLM, IPO7 and SERPINA3) were consistent with our integration analysis and GSE116250 validation results.

CONCLUSIONS

The candidate DEGs and TFs may be related to the ICM process. This study provided novel perspective for understanding mechanism and exploiting new therapeutic means for ICM.

Identification of key genes and upstream regulators in ischemic stroke

INTRODUCTION

Ischemic stroke (IS) causes severe neurological impairments and physical disabilities and has a high economic burden. Our study aims to identify the key genes and upstream regulators in IS by integrated microarray analysis.

METHODS

An integrated analysis of microarray studies of IS was performed to identify the differentially expressed genes (DEGs) in IS compared to normal control. Based on these DEGs, we performed the functional annotation and transcriptional regulatory network constructions. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to verify the expression of DEGs.

RESULTS

From two Gene Expression Omnibus datasets obtained, we obtained 1526 DEGs (534 up-regulated and 992 down-regulated genes) between IS and normal control. The results of functional annotation showed that Oxidative phosphorylation and Alzheimer's disease were significantly enriched pathways in IS. Top four transcription factors (TFs) with the most downstream genes including PAX4, POU2F1, ELK1, and NKX2-5. The expression of six genes (ID3, ICAM2, DCTPP1, ANTXR2, DUSP1, and RGS2) was detected by qRT-PCR. Except for DUSP1 and RGS2, the other four genes in qRT-PCR played the same pattern with that in our integrated analysis.

CONCLUSIONS

The dysregulation of these six genes may involve with the process of ischemic stroke (IS). Four TFs (PAX4, POU2F1, ELK1 and NKX2-5) were concluded to play a role in IS. Our finding provided clues for exploring mechanism and developing novel diagnostic and therapeutic strategies for IS.