Gene expression in peripheral immune cells following cardioembolic stroke is sexually dimorphic

Identification of endoplasmic reticulum stress genes in human stroke based on bioinformatics and machine learning

After ischemic stroke (IS), secondary injury is intimately linked to endoplasmic reticulum (ER) stress and body-brain crosstalk. Nonetheless, the underlying mechanism systemic immune disorder mediated ER stress in human IS remains unknown. In this study, 32 candidate ER stress-related genes (ERSRGs) were identified by overlapping MSigDB ER stress pathway genes and DEGs. Three Key ERSRGs (ATF6, DDIT3 and ERP29) were identified using LASSO, random forest, and SVM-RFE. IS patients with different ERSRGs profile were clustered into two groups using consensus clustering and the difference between 2 group was further explored by GSVA. Through immune cell infiltration deconvolution analysis, and middle cerebral artery occlusion (MCAO) mouse scRNA analysis, we found that the expression of 3 key ERSRGs were closely related with peripheral macrophage cell ER stress in IS and this was further confirmed by RT-qPCR experiment. These ERS genes might be helpful to further accurately regulate the central nervous system and systemic immune response through ER stress and have potential application value in clinical practice in IS.

Atherosclerosis-related biomarker PABPC1 predicts pan-cancer events

BACKGROUND

Atherosclerosis (AS) and tumours are the leading causes of death worldwide and share common risk factors, detection methods and molecular markers. Therefore, searching for serum markers shared by AS and tumours is beneficial to the early diagnosis of patients.

METHODS

The sera of 23 patients with AS-related transient ischaemic attack were screened by serological identification of antigens through recombinant cDNA expression cloning (SEREX), and cDNA clones were identified. Pathway function enrichment analysis was performed on cDNA clones to identify their biological pathways and determine whether they were related to AS or tumours. Subsequently, gene-gene and protein-protein interactions were performed and AS-associated markers would be discovered. The expression of AS biomarkers in human normal organs and pan-cancer tumour tissues were explored. Then, immune infiltration level and tumour mutation burden of various immune cells were evaluated. Survival curves analysis could show the expression of AS markers in pan-cancer.

RESULTS

AS-related sera were screened by SEREX, and 83 cDNA clones with high homology were obtained. Through functional enrichment analysis, it was found that their functions were closely related to AS and tumour functions. After multiple biological information interaction screening and the external cohort validating, poly(A) binding protein cytoplasmic 1 (PABPC1) was found to be a potential AS biomarker. To assess whether PABPC1 was related to pan-cancer, its expression in different tumour pathological stages and ages was screened. Since AS-associated proteins were closely related to cancer immune infiltration, we investigated and found that PABPC1 had the same role in pan-cancer. Finally, analysis of Kaplan-Meier survival curves revealed that high PABPC1 expression in pan-cancer was associated with high risk of death.

CONCLUSIONS

Through the findings of SEREX and bioinformatics pan-cancer analysis, we concluded that PABPC1 might serve as a potential biomarker for the prediction and diagnosis of AS and pan-cancer.

Discovery and validation of molecular patterns and immune characteristics in the peripheral blood of ischemic stroke patients

Background

Stroke is a disease with high morbidity, disability, and mortality. Immune factors play a crucial role in the occurrence of ischemic stroke (IS), but their exact mechanism is not clear. This study aims to identify possible immunological mechanisms by recognizing immune-related biomarkers and evaluating the infiltration pattern of immune cells.

Methods

We downloaded datasets of IS patients from GEO, applied R language to discover differentially expressed genes, and elucidated their biological functions using GO, KEGG analysis, and GSEA analysis. The hub genes were then obtained using two machine learning algorithms (least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE)) and the immune cell infiltration pattern was revealed by CIBERSORT. Gene-drug target networks and mRNA-miRNA-lncRNA regulatory networks were constructed using Cytoscape. Finally, we used RT-qPCR to validate the hub genes and applied logistic regression methods to build diagnostic models validated with ROC curves.

Results

We screened 188 differentially expressed genes whose functional analysis was enriched to multiple immune-related pathways. Six hub genes (ANTXR2, BAZ2B, C5AR1, PDK4, PPIH, and STK3) were identified using LASSO and SVM-RFE. ANTXR2, BAZ2B, C5AR1, PDK4, and STK3 were positively correlated with neutrophils and gamma delta T cells, and negatively correlated with T follicular helper cells and CD8, while PPIH showed the exact opposite trend. Immune infiltration indicated increased activity of monocytes, macrophages M0, neutrophils, and mast cells, and decreased infiltration of T follicular helper cells and CD8 in the IS group. The ceRNA network consisted of 306 miRNA-mRNA interacting pairs and 285 miRNA-lncRNA interacting pairs. RT-qPCR results indicated that the expression levels of BAZ2B, C5AR1, PDK4, and STK3 were significantly increased in patients with IS. Finally, we developed a diagnostic model based on these four genes. The AUC value of the model was verified to be 0.999 in the training set and 0.940 in the validation set.

Conclusion

Our research explored the immune-related gene expression modules and provided a specific basis for further study of immunomodulatory therapy of IS.

ITGAM is a critical gene in ischemic stroke

BACKGROUND

Globally, ischemic stroke (IS) is ranked as the second most prevailing cause of mortality and is considered lethal to human health. This study aimed to identify genes and pathways involved in the onset and progression of IS.

METHODS

GSE16561 and GSE22255 were downloaded from the Gene Expression Omnibus (GEO) database, merged, and subjected to batch effect removal using the ComBat method. The limma package was employed to identify the differentially expressed genes (DEGs), followed by enrichment analysis and protein-protein interaction (PPI) network construction. Afterward, the cytoHubba plugin was utilized to screen the hub genes. Finally, a ROC curve was generated to investigate the diagnostic value of hub genes. Validation analysis through a series of experiments including qPCR, Western blotting, TUNEL, and flow cytometry was performed.

RESULTS

The analysis incorporated 59 IS samples and 44 control samples, revealing 226 DEGs, of which 152 were up-regulated and 74 were down-regulated. These DEGs were revealed to be linked with the inflammatory and immune responses through enrichment analyses. Overall, the ROC analysis revealed the remarkable diagnostic potential of ITGAM and MMP9 for IS. Quantitative assessment of these genes showed significant overexpression in IS patients. ITGAM modulation influenced the secretion of critical inflammatory cytokines, such as IL-1β, IL-6, and TNF-α, and had a distinct impact on neuronal apoptosis.

CONCLUSIONS

The inflammation and immune response were identified as potential pathological mechanisms of IS by bioinformatics and experiments. In addition, ITGAM may be considered a potential therapeutic target for IS.

M6A-related bioinformatics analysis indicates that LRPPRC is an immune marker for ischemic stroke

Ischemic stroke (IS) is a common cerebrovascular disease whose pathogenesis involves a variety of immune molecules, immune channels and immune processes. 6-methyladenosine (m6A) modification regulates a variety of immune metabolic and immunopathological processes, but the role of m6A in IS is not yet understood. We downloaded the data set GSE58294 from the GEO database and screened for m6A-regulated differential expression genes. The RF algorithm was selected to screen the m6A key regulatory genes. Clinical prediction models were constructed and validated based on m6A key regulatory genes. IS patients were grouped according to the expression of m6A key regulatory genes, and immune markers of IS were identified based on immune infiltration characteristics and correlation. Finally, we performed functional enrichment, protein interaction network analysis and molecular prediction of the immune biomarkers. We identified a total of 7 differentially expressed genes in the dataset, namely METTL3, WTAP, YWHAG, TRA2A, YTHDF3, LRPPRC and HNRNPA2B1. The random forest algorithm indicated that all 7 genes were m6A key regulatory genes of IS, and the credibility of the above key regulatory genes was verified by constructing a clinical prediction model. Based on the expression of key regulatory genes, we divided IS patients into 2 groups. Based on the expression of the gene LRPPRC and the correlation of immune infiltration under different subgroups, LRPPRC was identified as an immune biomarker for IS. GO enrichment analyses indicate that LRPPRC is associated with a variety of cellular functions. Protein interaction network analysis and molecular prediction indicated that LRPPRC correlates with a variety of immune proteins, and LRPPRC may serve as a target for IS drug therapy. Our findings suggest that LRPPRC is an immune marker for IS. Further analysis based on LRPPRC could elucidate its role in the immune microenvironment of IS.

Unveiling the role of HIST2H2AC in stroke through single-cell and transcriptome analysis

Stroke is a leading cause of death and disability, and genetic risk factors play a significant role in its development. Unfortunately, effective therapies for stroke are currently limited. Early detection and diagnosis are critical for improving outcomes and developing new treatment strategies. In this study, we aimed to identify potential biomarkers and effective prevention and treatment strategies for stroke by conducting transcriptome and single-cell analyses. Our analysis included screening for biomarkers, functional enrichment analysis, immune infiltration, cell-cell communication, and single-cell metabolism. Through differential expression analysis, enrichment analysis, and protein-protein interaction (PPI) network construction, we identified HIST2H2AC as a potential biomarker for stroke. Our study also highlighted the diagnostic role of HIST2H2AC in stroke, its relationship with immune cells in the stroke environment, and our improved understanding of metabolic pathways after stroke. Overall, our research provided important insights into the pathogenesis of stroke, including potential biomarkers and treatment strategies that can be explored further to improve outcomes for stroke patients.

PA2G4/EBP1 ubiquitination by PRKN/PARKIN promotes mitophagy protecting neuron death in cerebral ischemia

Cerebral ischemia induces massive mitochondrial damage, leading to neuronal death. The elimination of damaged mitochondria via mitophagy is critical for neuroprotection. Here we show that the level of PA2G4/EBP1 (proliferation-associated 2G4) was notably increased early during transient middle cerebral artery occlusion and prevented neuronal death by eliciting cerebral ischemia-reperfusion (IR)-induced mitophagy. Neuron-specific knockout of Pa2g4 increased infarct volume and aggravated neuron loss with impaired mitophagy and was rescued by introduction of adeno-associated virus serotype 2 expressing PA2G4/EBP1. We determined that PA2G4/EBP1 is ubiquitinated on lysine 376 by PRKN/PARKIN on the damaged mitochondria and interacts with receptor protein SQSTM1/p62 for mitophagy induction. Thus, our study suggests that PA2G4/EBP1 ubiquitination following cerebral IR-injury promotes mitophagy induction, which may be implicated in neuroprotection.Abbreviations: AAV: adeno-associated virus; ACTB: actin beta; BNIP3L/NIX: BCL2 interacting protein 3 like; CA1: Cornu Ammonis 1; CASP3: caspase 3; CCCP: carbonyl cyanide m-chlorophenyl hydrazone; DMSO: dimethyl sulfoxide; PA2G4/EBP1: proliferation-associated 2G4; FUNDC1: FUN14 domain containing 1; IB: immunoblotting; ICC: immunocytochemistry; IHC: immunohistochemistry; IP: immunoprecipitation; MCAO: middle cerebral artery occlusion; MEF: mouse embryonic fibroblast; OGD: oxygen-glucose deprivation; PRKN/PARKIN: parkin RBR E3 ubiquitin protein ligase; PINK1: PTEN induced kinase 1; RBFOX3/NeuN: RNA binding fox-1 homolog 3; SQSTM1/p62: sequestosome 1; TIMM23: translocase of inner mitochondrial membrane 23; TOMM20: translocase of outer mitochondrial membrane 20; TUBB: tubulin beta class I; WT: wild-type.

Hypoxia and Activation of Neutrophil Degranulation-Related Genes in the Peripheral Blood of COVID-19 Patients

Severe COVID-19 is characterized by systematic hyper-inflammation and subsequent damage to various organs. Therefore, it is critical to trace this cascade of hyper-inflammation. Blood transcriptome has been routinely utilized in the interrogation of host immune response in COVID-19 and other infectious conditions. In this study, consensus gene dysregulation in the blood was obtained from 13 independent transcriptome studies on COVID-19. Among the up-regulated genes, the most prominent functional categories were neutrophil degranulation and cell cycle, which is clearly different from the classical activation of interferon signaling pathway in seasonal flu. As for the potential upstream causal factors of the atypical gene dysregulation, systemic hypoxia was further examined because it is much more widely reported in COVID-19 than that in seasonal flu. It was found that both physiological and pathological hypoxia can induce activation of neutrophil degranulation-related genes in the blood. Furthermore, COVID-19 patients with different requirement for oxygen intervention showed distinctive levels of gene expression related to neutrophil degranulation in the whole blood, which was validated in isolated neutrophils. Thus, activation of neutrophil degranulation-related genes in the blood of COVID-19 could be partially attributed to hypoxia. Interestingly, similar pattern was also observed in H1N1 infection (the cause of Spanish flu) and several other severe respiratory viral infections. As for the molecular mechanism, both HIF-dependent and HIF-independent pathways have been examined. Since the activation of neutrophil degranulation-related genes is highly correlated with disease severity in COVID-19, early detection of hypoxia and active intervention may prevent further activation of neutrophil degranulation-related genes and other harmful downstream hyper-inflammation. This common mechanism is applicable to current and future pandemic as well as the severe form of common respiratory infection.

Investigating the ID3/SLC22A4 as immune-related signatures in ischemic stroke

BACKGROUND

Ischemic stroke (IS) is a fearful disease that can cause a variety of immune events. Nevertheless, precise immune-related mechanisms have yet to be systematically elucidated. This study aimed to identify immune-related signatures using machine learning and to validate them with animal experiments and single cell analysis.

METHODS

In this study, we screened 24 differentially expressed genes (DEGs) while identifying immune-related signatures that may play a key role in IS development through a comprehensive strategy between least absolute shrinkage and selection operation (LASSO) regression, support vector machine (SVM) and immune-related genes. In addition, we explored immune infiltration using the CIBERSORT algorithm. Finally, we performed validation in mouse brain tissue and single cell analysis.

RESULTS

We identified 24 DEGs for follow-up analysis. ID3 and SLC22A4 were finally identified as the better immune-related signatures through a comprehensive strategy among DEGs, LASSO, SVM and immune-related genes. RT-qPCR, western blot, and immunofluorescence revealed a significant decrease in ID3 and a significant increase in SLC22A4 in the middle cerebral artery occlusion group. Single cell analysis revealed that ID3 was mainly concentrated in endothelial_2 cells and SLC22A4 in astrocytes in the MCAO group. A CIBERSORT finds significantly altered levels of immune infiltration in IS patients.

CONCLUSIONS

This study focused on immune-related signatures after stroke and ID3 and SLC22A4 may be new therapeutic targets to promote functional recovery after stroke. Furthermore, the association of ID3 and SLC22A4 with immune cells may be a new direction for post-stroke immunotherapy.

Integrative Analysis of Machine Learning and Molecule Docking Simulations for Ischemic Stroke Diagnosis and Therapy

Due to the narrow therapeutic window and high mortality of ischemic stroke, it is of great significance to investigate its diagnosis and therapy. We employed weighted gene coexpression network analysis (WGCNA) to ascertain gene modules related to stroke and used the maSigPro R package to seek the time-dependent genes in the progression of stroke. Three machine learning algorithms were further employed to identify the feature genes of stroke. A nomogram model was built and applied to evaluate the stroke patients. We analyzed single-cell RNA sequencing (scRNA-seq) data to discern microglia subclusters in ischemic stroke. The RNA velocity, pseudo time, and gene set enrichment analysis (GSEA) were performed to investigate the relationship of microglia subclusters. Connectivity map (CMap) analysis and molecule docking were used to screen a therapeutic agent for stroke. A nomogram model based on the feature genes showed a clinical net benefit and enabled an accurate evaluation of stroke patients. The RNA velocity and pseudo time analysis showed that microglia subcluster 0 would develop toward subcluster 2 within 24 h from stroke onset. The GSEA showed that the function of microglia subcluster 0 was opposite to that of subcluster 2. AZ_628, which screened from CMap analysis, was found to have lower binding energy with Mmp12, Lgals3, Fam20c, Capg, Pkm2, Sdc4, and Itga5 in microglia subcluster 2 and maybe a therapeutic agent for the poor development of microglia subcluster 2 after stroke. Our study presents a nomogram model for stroke diagnosis and provides a potential molecule agent for stroke therapy.

Aging-related genes revealed Neuroinflammatory mechanisms in ischemic stroke by bioinformatics

Ischemic stroke (IS) is a leading cause of disability, morbidity, and mortality globally. Aging affects immune function and contributes to poor outcomes of IS in elderly individuals. However, little is known about how aging-related genes (ARGs) are involved in IS. In this study, the relationship between ARGs and IS immune microenvironment biomarkers was explored by bioinformatics. Two IS microarray datasets (GSE22255, GSE16561) from human blood samples were analyzed and 502 ARGs were identified, from which 29 differentially expressed ARGs were selected. Functional analysis revealed that 7 of these ARGs (IL1B, FOS, JUN, CXCL5, PTGS2, TNFAIP3 and TLR4) were involved in five top enriched pathways (IL-17 signaling pathway, TNF signaling pathway, Rheumatoid arthritis, NF-kappa B signaling pathway and Pertussis) related to immune responses and inflammation. Five hub DE-ARGs (IL2RB, FOS, IL7R, ALDH2 and BIRC2) were identified using machine learning algorithms, and their association with immune-related characteristics was confirmed by additional tests. Single-cell sequencing dataset GSE129788 was retrieved to analyze aging molecular-related features, which was in accordance with microarray datasets. Clustering analysis revealed two subtypes of IS, which were distinguished by their differential expression of genes related to the NF-kappa B signaling pathway. These findings highlight the importance of ARGs in regulating immune responses in IS and suggest potential prevention and treatment strategies as well as guidelines for future research.

Sexual dimorphism in peripheral blood cell characteristics linked to recanalization success of endovascular thrombectomy in acute ischemic stroke

Endovascular thrombectomy (EVT) success to treat acute ischemic stroke varies with factors like stroke etiology and clot composition, which can differ between sexes. We studied if sex-specific blood cell characteristics (BCCs) are related to recanalization success. We analyzed electronic health records of 333 EVT patients from a single intervention center, and extracted 71 BCCs from the Sapphire flow cytometry analyzer. Through Sparse Partial Least Squares Discriminant Analysis, incorporating cross-validation and stability selection, we identified BCCs associated with successful recanalization (TICI 3) in both sexes. Stroke etiology was considered, while controlling for cardiovascular risk factors. Of the patients, successful recanalization was achieved in 51% of women and 49% of men. 21 of the 71 BCCs showed significant differences between sexes  (pFDR-corrected < 0.05). The female-focused recanalization model had lower error rates than both combined [t(192.4) = 5.9, p < 0.001] and male-only models [t(182.6) = - 15.6, p < 0.001]. In women, successful recanalization and cardioembolism were associated with a higher number of reticulocytes, while unsuccessful recanalization and large artery atherosclerosis (LAA) as cause of stroke were associated with a higher mean corpuscular hemoglobin concentration. In men, unsuccessful recanalization and LAA as cause of stroke were associated with a higher coefficient of variance of lymphocyte complexity of the intracellular structure. Sex-specific BCCs related to recanalization success varied and were linked to stroke etiology. This enhanced understanding may facilitate personalized treatment for acute ischemic stroke.

Identification of disulfidptosis-related genes and analysis of immune infiltration characteristics in ischemic strokes

Immune infiltration plays a pivotal role in the pathogenesis of ischemic stroke. A novel form of cell death known as disulfidptosis has emerged in recent studies. However, there is currently a lack of research investigating the regulatory mechanism of disulfidptosis-related genes in immune infiltration during ischemic stroke. Using machine learning methods, we identified candidate key disulfidptosis-related genes (DRGs). Subsequently, we performed an analysis of immune cell infiltration to investigate the dysregulation of immune cells in the context of ischemic stroke. We assessed their diagnostic value by employing receiver operating characteristic (ROC) curves. To gain further insights, we conducted functional enrichment analyses to elucidate the signaling pathways associated with these seven DRGs. We identified two distinct subclusters based on the expression patterns of these seven DRGs. The unique roles of these subclusters were further evaluated through KEGG analysis and immune infiltration studies. Furthermore, we validated the expression profiles of these seven DRGs using both single-cell datasets and external datasets. Lastly, molecular docking was performed to explore potential drugs for the treatment of ischemic stroke. We identified seven DRGs. The seven DRGs are related to immune cells. Additionally, these seven DRGs also demonstrate potential diagnostic value in ischemic stroke. Functional enrichment analysis highlighted pathways such as platelet aggregation and platelet activation. Two subclusters related to disulfidptosis were defined, and functional enrichment analysis of their differentially expressed genes (DEGs) primarily involved pathways like cytokine-cytokine receptor interaction. Single-cell analysis indicated that these seven DRGs were primarily distributed among immune cell types. Molecular docking results suggested that genistein might be a potential therapeutic drug. This study has opened up new avenues for exploring the causes of ischemic stroke and developing potential therapeutic targets.

Identification of key biomarkers in ischemic stroke: single-cell sequencing and weighted co-expression network analysis

PURPOSE

At present, there is a lack of accurate early diagnostic markers for ischemic stroke.

METHODS

By using dimensionality reduction cluster analysis, differential expression analysis, weighted co-expression network analysis, protein-protein interaction network analysis, cell heterogeneity and key pathogenic genes were identified in ischemic stroke. Immunomicroenvironment analysis was used to explore the immune landscape and immune associations of key genes in ischemic stroke. The analysis platform we use is R software (version 4.0.5). PCR experiments were used to verify the expression of key genes.

RESULTS

Single cell sequencing data in ischemic stroke can be annotated as fibroblast cells, pre-B cell CD34, neutrophils cells, bone marrow (BM), keratinocytes, macrophage, neurons and mesenchymal stem cells (MSC). By the intersection of differential expression analysis and WGCNA analysis, 385 genes were obtained. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that these genes were highly correlated with multiple functions and pathways. Protein-protein interaction network analysis revealed that MRPS11 and MRPS12 were key genes, both of which were down-regulated in ischemic stroke. The Pseudo-time series analysis found that the expression of MRPS12 decreased gradually with the differentiation of pre-B cell CD34 cells in ischemic stroke, suggesting that the downregulation of MRPS12 expression may play an important role in ischemic stroke. At last, PCR showed that MRPS11 and MRPS12 were significantly down-regulated in peripheral blood of patients with ischemic stroke.

CONCLUSIONS

Our study provides a reference for the study of pathogenesis and key targets of ischemic stroke.

Identification of hypoxia-related genes and exploration of their relationship with immune cells in ischemic stroke

Ischemic stroke (IS) is a major threat to human health, and it is the second leading cause of long-term disability and death in the world. Impaired cerebral perfusion leads to acute hypoxia and glucose deficiency, which in turn induces a stroke cascade response that ultimately leads to cell death. Screening and identifying hypoxia-related genes (HRGs) and therapeutic targets is important for neuroprotection before and during brain recanalization to protect against injury and extend the time window to further improve functional outcomes before pharmacological and mechanical thrombolysis. First, we downloaded the GSE16561 and GSE58294 datasets from the NCBI GEO database. Bioinformatics analysis of the GSE16561 dataset using the limma package identified differentially expressed genes (DEGs) in ischemic stroke using adj. p. values < 0.05 and a fold change of 0.5 as thresholds. The Molecular Signature database and Genecards database were pooled to obtain hypoxia-related genes. 19 HRGs associated with ischemic stroke were obtained after taking the intersection. LASSO regression and multivariate logistic regression were applied to identify critical biomarkers with independent diagnostic values. ROC curves were constructed to validate their diagnostic efficacy. We used CIBERSORT to analyze the differences in the immune microenvironment between IS patients and controls. Finally, we investigated the correlation between HRGs and infiltrating immune cells to understand molecular immune mechanisms better. Our study analyzed the role of HRGs in ischemic stroke. Nineteen hypoxia-related genes were obtained. Enrichment analysis showed that 19 HRGs were involved in response to hypoxia, HIF-1 signaling pathway, autophagy, autophagy of mitochondrion, and AMPK signaling pathway. Because of the good diagnostic properties of SLC2A3, we further investigated the function of SLC2A3 and found that it is closely related to immunity. We have also explored the relevance of other critical genes to immune cells. Our findings suggest that hypoxia-related genes play a crucial role in the diversity and complexity of the IS immune microenvironment. Exploring the association between hypoxia-related critical genes and immune cells provides innovative insights into the therapeutic targets for ischemic stroke.

Identification and cross-validation of autophagy-related genes in cardioembolic stroke

Objective

Cardioembolic stroke (CE stroke, also known as cardiogenic cerebral embolism, CCE) has the highest recurrence rate and fatality rate among all subtypes of ischemic stroke, the pathogenesis of which was unclear. Autophagy plays an essential role in the development of CE stroke. We aim to identify the potential autophagy-related molecular markers of CE stroke and uncover the potential therapeutic targets through bioinformatics analysis.

Methods

The mRNA expression profile dataset GSE58294 was obtained from the GEO database. The potential autophagy-related differentially expressed (DE) genes of CE stroke were screened by R software. Protein-protein interactions (PPIs), correlation analysis, and gene ontology (GO) enrichment analysis were applied to the autophagy-related DE genes. GSE66724, GSE41177, and GSE22255 were introduced for the verification of the autophagy-related DE genes in CE stroke, and the differences in values were re-calculated by Student's t-test.

Results

A total of 41 autophagy-related DE genes (37 upregulated genes and four downregulated genes) were identified between 23 cardioembolic stroke patients (≤3 h, prior to treatment) and 23 healthy controls. The KEGG and GO enrichment analysis of autophagy-related DE genes indicated several enriched terms related to autophagy, apoptosis, and ER stress. The PPI results demonstrated the interactions between these autophagy-related genes. Moreover, several hub genes, especially for CE stroke, were identified and re-calculated by Student's t-test.

Conclusion

We identified 41 potential autophagy-related genes associated with CE stroke through bioinformatics analysis. SERPINA1, WDFY3, ERN1, RHEB, and BCL2L1 were identified as the most significant DE genes that may affect the development of CE stroke by regulating autophagy. CXCR4 was identified as a hub gene of all types of strokes. ARNT, MAPK1, ATG12, ATG16L2, ATG2B, and BECN1 were identified as particular hub genes for CE stroke. These results may provide insight into the role of autophagy in CE stroke and contribute to the discovery of potential therapeutic targets for CE stroke treatment.

Sex differences in the inflammatory response to stroke

Ischemic stroke is a leading cause of morbidity and mortality and disproportionally affects women, in part due to their higher longevity. Older women have poorer outcomes after stroke with high rates of cognitive deficits, depression, and reduced quality of life. Post-stroke inflammatory responses are also sexually dimorphic and drive differences in infarct size and recovery. Factors that influence sex-specific immune responses can be both intrinsic and extrinsic. Differences in gonadal hormone exposure, sex chromosome compliment, and environmental/social factors can drive changes in transcriptional and metabolic profiles. In addition, how these variables interact, changes across the lifespan. After the onset of ischemic injury, necrosis and apoptosis occur, which activate microglia and other glial cells within the central nervous system, promoting the release of cytokines and chemokines and neuroinflammation. Cells involved in innate and adaptive immune responses also have dual functions after stroke as they can enhance inflammation acutely, but also contribute to suppression of the inflammatory cascade and later repair. In this review, we provide an overview of the current literature on sex-specific inflammatory responses to ischemic stroke. Understanding these differences is critical to identifying therapeutic options for both men and women.

Integration of Mendelian randomisation and systems biology models to identify novel blood-based biomarkers for stroke

Stroke is the second largest cause of mortality in the world. Genome-wide association studies (GWAS) have identified some genetic variants associated with stroke risk, but their putative functional causal genes are unknown. Hence, we aimed to identify putative functional causal gene biomarkers of stroke risk. We used a summary-based Mendelian randomisation (SMR) approach to identify the pleiotropic associations of genetically regulated traits (i.e., gene expression and DNA methylation) with stroke risk. Using SMR approach, we integrated cis-expression quantitative loci (cis-eQTLs) and cis-methylation quantitative loci (cis-mQTLs) data with GWAS summary statistics of stroke. We also utilised heterogeneity in dependent instruments (HEIDI) test to distinguish pleiotropy from linkage from the observed associations identified through SMR analysis. Our integrative SMR analyses and HEIDI test revealed 45 candidate biomarker genes (FDR < 0.05; P_HEIDI>0.01) that were pleiotropically or potentially causally associated with stroke risk. Of those candidate biomarker genes, 10 genes (HTRA1, PMF1, FBN2, C9orf84, COL4A1, BAG4, NEK6, SH2B3, SH3PXD2A, ACAD10) were differentially expressed in genome-wide blood transcriptomics data from stroke and healthy individuals (FDR<0.05). Functional enrichment analysis of the identified candidate biomarker genes revealed gene ontologies and pathways involved in stroke, including "cell aging", "metal ion binding" and "oxidative damage". Based on the evidence of genetically regulated expression of genes through SMR and directly measured expression of genes in blood, our integrative analysis suggests ten genes as blood biomarkers of stroke risk. Furthermore, our study provides a better understanding of the influence of DNA methylation on the expression of genes linked to stroke risk.

GAS6-AS1, a long noncoding RNA, functions as a key candidate gene in atrial fibrillation related stroke determined by ceRNA network analysis and WGCNA

BACKGROUND

Stroke attributable to atrial fibrillation (AF related stroke, AFST) accounts for 13 ~ 26% of ischemic stroke. It has been found that AFST patients have a higher risk of disability and mortality than those without AF. Additionally, it's still a great challenge to treat AFST patients because its exact mechanism at the molecular level remains unclear. Thus, it's vital to investigate the mechanism of AFST and search for molecular targets of treatment. Long non-coding RNAs (lncRNAs) are related to the pathogenesis of various diseases. However, the role of lncRNAs in AFST remains unclear. In this study, AFST-related lncRNAs are explored using competing endogenous RNA (ceRNA) network analysis and weighted gene co-expression network analysis (WGCNA).

METHODS

GSE66724 and GSE58294 datasets were downloaded from GEO database. After data preprocessing and probe reannotation, differentially expressed lncRNAs (DELs) and differentially expressed mRNAs (DEMs) between AFST and AF samples were explored. Then, functional enrichment analysis and protein-protein interaction (PPI) network analysis of the DEMs were performed. At the meantime, ceRNA network analysis and WGCNA were performed to identify hub lncRNAs. The hub lncRNAs identified both by ceRNA network analysis and WGCNA were further validated by Comparative Toxicogenomics Database (CTD).

RESULTS

In all, 19 DELs and 317 DEMs were identified between the AFST and AF samples. Functional enrichment analysis suggested that the DEMs associated with AFST were mainly enriched in the activation of the immune response. Two lncRNAs which overlapped between the three lncRNAs identified by the ceRNA network analysis and the 28 lncRNAs identified by the WGCNA were screened as hub lncRNAs for further validation. Finally, lncRNA GAS6-AS1 turned out to be associated with AFST by CTD validation.

CONCLUSION

These findings suggested that low expression of GAS6-AS1 might exert an essential role in AFST through downregulating its downstream target mRNAs GOLGA8A and BACH2, and GAS6-AS1 might be a potential target for AFST therapy.

Integrated bioinformatics analysis identifies shared immune changes between ischemic stroke and COVID 19

Although COVID-19 is primarily a respiratory disease, its neurological complications, such as ischemic stroke (IS), have aroused growing concerns and reports. However, the molecular mechanisms that underlie IS and COVID-19 are not well understood. Therefore, we implemented transcriptomic analysis from eight GEO datasets consist of 1191 samples to detect common pathways and molecular biomarkers in IS and COVID-19 that help understand the linkage between them. Differentially expressed genes (DEGs) were detected for IS and COVID-19 separately for finding shared mechanisms and we found that immune-related pathways were outlined with statistical significance. JAK2, which was identified as a hub gene, was supposed to be a potential therapeutic gene targets during the immunological process of COVID-19 and IS. Besides, we found a decrease in the proportion of CD8+ T and T helper 2 cells in the peripheral circulation of both COVID and IS patients, and NCR3 expression was significantly correlated with this change. In conclusion, we demonstrated that transcriptomic analyses reported in this study could make a deeper understanding of the common mechanism and might be promising for effective therapeutic for IS and COVID-19.

Monocyte, neutrophil, and whole blood transcriptome dynamics following ischemic stroke

BACKGROUND

After ischemic stroke (IS), peripheral leukocytes infiltrate the damaged region and modulate the response to injury. Peripheral blood cells display distinctive gene expression signatures post-IS and these transcriptional programs reflect changes in immune responses to IS. Dissecting the temporal dynamics of gene expression after IS improves our understanding of immune and clotting responses at the molecular and cellular level that are involved in acute brain injury and may assist with time-targeted, cell-specific therapy.

METHODS

The transcriptomic profiles from peripheral monocytes, neutrophils, and whole blood from 38 ischemic stroke patients and 18 controls were analyzed with RNA-seq as a function of time and etiology after stroke. Differential expression analyses were performed at 0-24 h, 24-48 h, and >48 h following stroke.

RESULTS

Unique patterns of temporal gene expression and pathways were distinguished for monocytes, neutrophils, and whole blood with enrichment of interleukin signaling pathways for different time points and stroke etiologies. Compared to control subjects, gene expression was generally upregulated in neutrophils and generally downregulated in monocytes over all times for cardioembolic, large vessel, and small vessel strokes. Self-organizing maps identified gene clusters with similar trajectories of gene expression over time for different stroke causes and sample types. Weighted Gene Co-expression Network Analyses identified modules of co-expressed genes that significantly varied with time after stroke and included hub genes of immunoglobulin genes in whole blood.

CONCLUSIONS

Altogether, the identified genes and pathways are critical for understanding how the immune and clotting systems change over time after stroke. This study identifies potential time- and cell-specific biomarkers and treatment targets.

C1QC, VSIG4, and CFD as Potential Peripheral Blood Biomarkers in Atrial Fibrillation-Related Cardioembolic Stroke

Atrial fibrillation (AF) is a major risk factor for ischemic stroke. We aimed to identify novel potential biomarkers with diagnostic value in patients with atrial fibrillation-related cardioembolic stroke (AF-CE).Publicly available gene expression profiles related to AF, cardioembolic stroke (CE), and large artery atherosclerosis (LAA) were downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified and then functionally annotated. The support vector machine recursive feature elimination (SVM-RFE) and least absolute shrinkage and selection operator (LASSO) regression analysis were conducted to identify potential diagnostic AF-CE biomarkers. Furthermore, the results were validated by using external data sets, and discriminability was measured by the area under the ROC curve (AUC). In order to verify the predictive results, the blood samples of 13 healthy controls, 20 patients with CE, and 20 patients with LAA stroke were acquired for RT-qPCR, and the correlation between biomarkers and clinical features was further explored. Lastly, a nomogram and the companion website were developed to predict the CE-risk rate. Three feature genes (C1QC, VSIG4, and CFD) were selected and validated in the training and the external datasets. The qRT-PCR evaluation showed that the levels of blood biomarkers (C1QC, VSIG4, and CFD) in patients with AF-CE can be used to differentiate patients with AF-CE from normal controls (P < 0.05) and can effectively discriminate AF-CE from LAA stroke (P < 0.05). Immune cell infiltration analysis revealed that three feature genes were correlated with immune system such as neutrophils. Clinical impact curve, calibration curves, ROC, and DCAs of the nomogram indicate that the nomogram had good performance. Our findings showed that C1QC, VSIG4, and CFD can potentially serve as diagnostic blood biomarkers of AF-CE; novel nomogram and the companion website can help clinicians to identify high-risk individuals, thus helping to guide treatment decisions for stroke patients.

Comparison of ischemic stroke diagnosis models based on machine learning

Background

The incidence, prevalence, and mortality of ischemic stroke (IS) continue to rise, resulting in a serious global disease burden. The prediction models have a great value in the early prediction and diagnosis of IS.

Methods

The R software was used to screen the differentially expressed genes (DEGs) of IS and control samples in the datasets GSE16561, GSE58294, and GSE37587 and analyze DEGs for enrichment analysis. The feature genes of IS were obtained by several machine learning algorithms, including the least absolute shrinkage and selector operation (LASSO) logistic regression, the support vector machine-recursive feature elimination (SVM-RFE), and the Random Forest (RF). The IS diagnostic models were constructed based on transcriptomics by machine learning and artificial neural network (ANN).

Results

A total of 69 DEGs, mainly involved in immune and inflammatory responses, were identified. The pathways enriched in the IS group were complement and coagulation cascades, lysosome, PPAR signaling pathway, regulation of autophagy, and toll-like receptor signaling pathway. The feature genes selected by LASSO, SVM-RFE, and RF were 17, 10, and 12, respectively. The area under the curve (AUC) of the LASSO model in the training dataset, GSE22255, and GSE195442 was 0.969, 0.890, and 1.000. The AUC of the SVM-RFE model was 0.957, 0.805, and 1.000, respectively. The AUC of the RF model was 0.947, 0.935, and 1.000, respectively. The models have good sensitivity, specificity, and accuracy. The AUC of the LASSO+ANN, SVM-RFE+ANN, and RF+ANN models was 1.000, 0.995, and 0.997, respectively, in the training dataset. However, the AUC of LASSO+ANN, SVM-RFE+ANN, and RF+ANN models was 0.688, 0.605, and 0.619, respectively, in the GSE22255 dataset. The AUC of the LASSO+ANN and RF+ANN models was 0.740 and 0.630, respectively, in the GSE195442 dataset. In the training dataset, the sensitivity, specificity, and accuracy of the LASSO+ANN model were 1.000, 1.000, and 1.000, respectively; of the SVM-RFE+ANN model were 0.946, 0.982, and 0.964, respectively; and of the RF+ANN model were 0.964, 1.000, and 0.982, respectively. In the test datasets, the sensitivity was very satisfactory; however, the specificity and accuracy were not good.

Conclusion

The LASSO, SVM-RFE, and RF models have good prediction abilities. However, the ANN model is efficient at classifying positive samples and is unsuitable at classifying negative samples.

Gene expression changes implicate specific peripheral immune responses to Deep and Lobar Intracerebral Hemorrhages in humans

The peripheral immune system response to Intracerebral Hemorrhage (ICH) may differ with ICH in different brain locations. Thus, we investigated peripheral blood mRNA expression of Deep ICH, Lobar ICH, and vascular risk factor-matched control subjects (n = 59). Deep ICH subjects usually had hypertension. Some Lobar ICH subjects had cerebral amyloid angiopathy (CAA). Genes and gene networks in Deep ICH and Lobar ICH were compared to controls. We found 774 differentially expressed genes (DEGs) and 2 co-expressed gene modules associated with Deep ICH, and 441 DEGs and 5 modules associated with Lobar ICH. Pathway enrichment showed some common immune/inflammatory responses between locations including Autophagy, T Cell Receptor, Inflammasome, and Neuroinflammation Signaling. Th2, Interferon, GP6, and BEX2 Signaling were unique to Deep ICH. Necroptosis Signaling, Protein Ubiquitination, Amyloid Processing, and various RNA Processing terms were unique to Lobar ICH. Finding amyloid processing pathways in blood of Lobar ICH patients suggests peripheral immune cells may participate in processes leading to perivascular/vascular amyloid in CAA vessels and/or are involved in its removal. This study identifies distinct peripheral blood transcriptome architectures in Deep and Lobar ICH, emphasizes the need for considering location in ICH studies/clinical trials, and presents potential location-specific treatment targets.

Identification of immune characteristic landscapes related to autophagy in ischemic stroke

Ischemic stroke (IS) is a common and grievous nervous system disease. Both autophagy activation and immune response after cerebral ischemia play important roles in the development of IS. Many studies have revealed a close interplay between autophagy and immunity. However, little is known about how autophagy influences the immune characteristics of IS. Hence, the study aims to systematically explore the role of autophagy and its impact on immune characteristics in IS. We first compared the expression differences of autophagy genes in a training set and identified 20 dysregulated autophagy genes between healthy and IS samples. An autophagy-related classifier composed of seven genes was further established and could well distinguish healthy and IS samples. Then, the association between autophagy and immune characteristics, including infiltrating immunocytes, activity of immune reactions, and HLA gene expression, was investigated. The results showed that autophagy closely correlated with immune characteristics, such as NAMPT and ARNT significantly related to infiltrating immunocytes; PPP1R15A and CASP3 significantly related to activity of immune reactions; and NAMPT and ATG16L2 significantly related to HLA genes. Next, two distinct autophagy expression patterns were identified by unsupervised clustering analysis, and diverse immune characteristics were discovered between them. A total of 5481 autophagy phenotype-related genes were obtained between two expression patterns, and their biological functions revealed that these genes were involved in immune-related biological pathways. Finally, five dysregulated autophagy genes (FOS, MAP1LC3B, ERO1L, ARNT, and PPP1R15A) were proved between IS and healthy samples using another two validation sets. Our results illustrated that autophagy had a dramatic effect on the immunity of IS and provided a novel sight into understanding the pathogenesis of IS.

Transcriptomic analysis identifies shared biological foundations between ischemic stroke and Alzheimer's disease

AIM

Alzheimer's disease (AD) and ischemic stroke (IS), two major neurological diseases, are suggested to be associated in clinical and pathophysiological levels. Previous studies have provided some insights into the possible genetic mechanisms behind the correlation between AD and IS, but this issue is still not clear. We implemented transcriptomic analysis to detect common hub genes and pathways to help promote the understanding of this issue.

MATERIALS AND METHODS

Four gene expression profiling datasets (GSE16561, GSE58294, GSE63060, and GSE63061) of peripheral whole blood, which contain 108 IS samples, 284 AD samples, and 285 matched controls, were employed to detect differentially expressed genes (DEGs) for AD and IS, which were further analyzed for shared biological pathways, candidate drugs, and transcription factors. Protein-protein interaction (PPI) network and drug-target interaction analysis were applied to identify hub genes and drug targets, respectively. Result verification was done with other independent datasets (GSE37587, GSE46480, and GSE140829). The difference in proportions of various immune cells in the peripheral blood of AD and IS patients were evaluated using CIBERSORT.

RESULTS

We identified 74 DEGs and 18 biological processes with statistical significance shared by AD and IS, 9 of which were immune-related pathways. Five hub genes scored high in the topological analysis of the PPI network, and we also found eight drug target genes and candidate drugs which were associated with AD and IS. As for immunological changes, an increase in the proportion of M0 macrophages was found in the peripheral circulation of both AD and IS patients, and SOD1 expression was significantly correlated with this change.

CONCLUSION

Collectively, the common DEGs and shared pathways found in this study suggest a potential shared etiology between AD and IS, behind which immune system, particularly the M0 macrophage elevation, might have important roles. While, the shared hub genes, potential therapeutic gene targets and drugs reported in this study provide promising treatment strategies for AD and IS.

Ferroptosis-related differentially expressed genes serve as new biomarkers in ischemic stroke and identification of therapeutic drugs

Background

Iron is an essential nutrient element, and iron metabolism is related to many diseases. Ferroptosis is an iron-dependent form of regulated cell death associated with ischemic stroke (IS). Hence, this study intended to discover and validate the possible ferroptosis-related genes involved in IS.

Materials and methods

GSE16561, GSE37587, and GSE58294 were retrieved from the GEO database. Using R software, we identified ferroptosis-related differentially expressed genes (DEGs) in IS. Protein-protein interactions (PPIs) and enrichment analyses were conducted. The ROC curve was plotted to explore the diagnostic significance of those identified genes. The consistent clustering method was used to classify the IS samples. The level of immune cell infiltration of different subtypes was evaluated by ssGSEA and CIBERSORT algorithm. Validation was conducted in the test sets GSE37587 and GSE58294.

Results

Twenty-one ferroptosis-related DEGs were detected in IS vs. the normal controls. Enrichment analysis shows that the 21 DEGs are involved in monocarboxylic acid metabolism, iron ion response, and ferroptosis. Moreover, their expression levels were pertinent to the age and gender of IS patients. The ROC analysis demonstrated remarkable diagnostic values of LAMP2, TSC22D3, SLC38A1, and RPL8 for IS. Transcription factors and targeting miRNAs of the 21 DEGs were determined. Vandetanib, FERRIC CITRATE, etc., were confirmed as potential therapeutic drugs for IS. Using 11 hub genes, IS patients were categorized into C1 and C2 subtypes. The two subtypes significantly differed between immune cell infiltration, checkpoints, and HLA genes. The 272 DEGs were identified from two subtypes and their biological functions were explored. Verification was performed in the GSE37587 and GSE58294 datasets.

Conclusion

Our findings indicate that ferroptosis plays a critical role in the diversity and complexity of the IS immune microenvironment.

Sexual dimorphism in immune cell responses following stroke

Recent bodies of work in regard to stroke have revealed significant sex differences in terms of risk and outcome. While differences in sex hormones have been the focus of earlier research, the reasons for these differences are much more complex and require further identification. This review covers differences in sex related immune responses with a focus on differences in immune cell composition and function. While females are more susceptible to immune related diseases, they seem to have better outcomes from stroke at the experimental level with reduced pro-inflammatory responses. However, at the clinical level, the picture is much more complex with worse neurological outcomes from stroke. While the use of exogenous sex steroids can replicate some of these findings, it is apparent that many other factors are involved in the modulation of immune responses. As a result, more research is needed to better understand these differences and identify appropriate interventions and risk modification.

Integrated Microarray Analysis to Identify Genes and Small-Molecule Drugs Associated with Stroke Progression

Several blood biomarkers are now considered increasingly important for stratifying risk, monitoring disease progression, and evaluating the response to therapy in ischemic stroke. The purpose of the present study was to identify the key genes associated with ischemic stroke progression and elucidate the potential therapeutic small molecules. Microarray datasets related to stroke for GSE58294, GSE22255, and GSE16561 were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were filtered using the Limma package. DAVID was then searched to perform gene ontology (GO) and pathway enrichment analyses. Based on the DEGs, a protein-protein interaction (PPI) network was developed using Cytoscape, and MCODE was applied to conduct module analysis. Finally, to identify the potential drugs for ischemic stroke, the connectivity map (CMap) database was used. Sixty DEGs were identified after analyzing the three datasets. The GO data analysis revealed that the DEGs were significantly associated with biological processes, including positive regulation of programmed cell death, protein localization in organelles, and positive regulation of apoptosis. KEGG analysis showed that the DEGs were particularly enriched in the Fc epsilon RI signaling pathway, MAPK signaling pathway, and Huntington’s disease. We selected five DEGs with high connectivity (CYBB, SYK, DUSP1, TNF, and SP1) that significantly predicted stroke progression. In addition, CMap prediction showed ten small molecules that could be used as adjuvants when treating ischemic stroke. The outcomes of the present study indicated that the five genes mentioned above can be considered potential targets for developing new medications that can modify the ischemic stroke process, and mycophenolic acid was the most promising small molecule to treat ischemic stroke.

Experimental verification and validation of immune biomarkers based on chromatin regulators in ischemic stroke

Ischemic stroke (IS) is a disease characterized by rapid progression and high mortality and disability rates. Its pathophysiological process is inseparable from immune dysfunction. Recently, chromatin regulators (CRs) have been described as a class of enzymes that can recognize, form, and maintain the epigenetic state of an organism, and are closely associated with immune regulation. Nevertheless, the role of CR-related genes in IS has not been fully elucidated. In this study, seven CR-related immune biomarkers in the GSE58294 and GSE22255 datasets were identified by combining differential gene expression analysis, weighted correlation network analysis, and single sample gene set enrichment analysis. After experimental validation using quantitative polymerase chain reaction, four genes (DPF2, LMNB1, MLLT3, and JAK2) were screened as candidate immune biomarkers. These four biomarkers demonstrated good predictive power in the clinical risk model (area under the curve, 0.775). Molecular docking simulations revealed that mevastatin, WP1066, cladribine, trichostatin A, mequitazine, and zuclomiphene may be potential immunomodulatory drugs for IS. Overall, the results of this study contribute to the identification of CR-related immune therapeutics target in IS and provide an important reference for further research.

Differential Regulation of the Immune System in Peripheral Blood Following Ischemic Stroke

Method

108 IS samples and 47 matched controls were obtained from the GEO database. Immune-related genes (IRGs) and their associated drugs were collected from the ImmPort and PharmGBK databases, respectively. Random forest (RF) regression and least absolute shrinkage and selection operator (LASSO) logistic regression were applied to identify immune-related genetic biomarkers (IRGBs) of IS, and accuracy was verified using neural network models. Finally, proportion changes of various immune cells in peripheral blood of IS patients were evaluated using CIBERSORT and xCell and correlation analyses were performed between IRGBs and differentially distributed immune cells.

Results

A total of 537 genes were differentially expressed between IS and control samples. Four immune-related differential expressed genes identified by regression analysis presented strong predictive power (AUC = 0.909) which we suggeseted them as immune-related genetic biomarkers (IRGBs). We also demonstrated six immune-related genes targeted by known drugs. In addition, post-IS immune system presented an increase in the proportion of innate immune cells and a decrease in adaptive immune cells in the peripheral circulation, and IRGBs showing significance were associated with this process.

Conclusion

The study identified CARD11, ICAM2, VIM, and CD19 as immune-related genetic biomarkers of IS. Six immune-related DEGs targeted by known drugs were found and provide new candidate drug targets for modulating the post-IS immune system. The innate immune cells and adaptive immune cells are diversified in the post-IS immune system, and IRGBs might play important role during this process.

The Construction and Analysis of Immune Infiltration and Competing Endogenous RNA Network in Acute Ischemic Stroke

Acute ischemic stroke (AIS) is a common neurological disease that seriously endangers both the physical and mental health of human. After AIS, activated immune cells are recruited to the stroke site, where inflammatory mediators are released locally, and severe immune inflammatory reactions occur within a short time, which affects the progress and prognosis of IS. Circular RNA (circRNA) is a type of non-coding RNA (ncRNA) with a closed-loop structure and high stability. Studies have found that circRNA can affect the course of IS. However, there is no report on ceRNA’s pathogenesis in AIS that is mediated by circRNA. In this study, the CIBERSORT algorithm was used to analyze the distribution of immune cells in patients with AIS. mRNA dataset was downloaded from the GEO database, and the weighted gene co-expression network analysis (WGCNA) method was used to construct weighted gene co-expression to determine 668 target genes, using GO, KEGG enrichment analysis, construction of protein-protein interaction (PPI) network analysis, and molecular complex detection (MCODE) plug-in analysis. The results showed that the biological function of the target gene was in line with the activation and immune regulation of neutrophils; signal pathways were mostly enriched in immune inflammation-related pathways. A Venn diagram was used to obtain 52 intersection genes between target genes and disease genes. By analyzing the correlation between the intersection genes and immune cells, we found that the top 5 hub genes were TOM1, STAT3, RAB3D, MDM2, and FOS, which were all significantly positively correlated with neutrophils and significantly negatively correlated with eosinophils. A total of 52 intersection genes and the related circRNA and miRNA were used as input for Cytoscape software to construct a circRNA-mediated ceRNA competition endogenous network, where a total of 18 circRNAs were found. Further analysis of the correlation between circRNA and immune cells found that 4 circRNAs are positively correlated with neutrophils. Therefore, we speculate that there may be a regulatory relationship between circRNA-mediated ceRNA and the immune mechanism in AIS. This study has important guiding significance for the progress, outcome of AIS, and the development of new medicine.

Sex-Specific Immune Responses in Stroke

In both acute and chronic diseases, functional differences in host immune responses arise from a multitude of intrinsic and extrinsic factors. Two of the most important factors affecting the immune response are biological sex and aging. Ischemic stroke is a debilitating disease that predominately affects older individuals. Epidemiological studies have shown that older women have poorer functional outcomes compared with men, in part due to the older age at which they experience their first stroke and the increased comorbidities seen with aging. The immune response also differs in men and women, which could lead to altered inflammatory events that contribute to sex differences in poststroke recovery. Intrinsic factors including host genetics and chromosomal sex play a crucial role both in shaping the host immune system and in the neuroimmune response to brain injury. Ischemic stroke leads to altered intracellular communication between astrocytes, neurons, and resident immune cells in the central nervous system. Increased production of cytokines and chemokines orchestrate the infiltration of peripheral immune cells and promote neuroinflammation. To maintain immunosurveillance, the host immune and central nervous system are highly regulated by a diverse population of immune cells which are strategically distributed within the neurovascular unit and become activated with injury. In this review, we provide a comprehensive overview of sex-specific host immune responses in ischemic stroke.

Sex-Associated Differences in Neurovascular Dysfunction During Ischemic Stroke

Neurovascular units (NVUs) are basic functional units in the central nervous system and include neurons, astrocytes and vascular compartments. Ischemic stroke triggers not only neuronal damage, but also dissonance of intercellular crosstalk within the NVU. Stroke is sexually dimorphic, but the sex-associated differences involved in stroke-induced neurovascular dysfunction are studied in a limited extend. Preclinical studies have found that in rodent models of stroke, females have less neuronal loss, stronger repairing potential of astrocytes and more stable vascular conjunction; these properties are highly related to the cerebroprotective effects of female hormones. However, in humans, these research findings may be applicable only to premenopausal stroke patients. Women who have had a stroke usually have poorer outcomes compared to men, and because stoke is age-related, hormone replacement therapy for postmenopausal women may exacerbate stroke symptoms, which contradicts the findings of most preclinical studies. This stark contrast between clinical and laboratory findings suggests that understanding of neurovascular differences between the sexes is limited. Actually, apart from gonadal hormones, differences in neuroinflammation as well as genetics and epigenetics promote the sexual dimorphism of NVU functions. In this review, we summarize the confirmed sex-associated differences in NVUs during ischemic stroke and the possible contributing mechanisms. We also describe the gap between clinical and preclinical studies in terms of sexual dimorphism.

Identification of Genes Linking Natural Killer Cells to Apoptosis in Acute Myocardial Infarction and Ischemic Stroke

Natural killer (NK) cells are a type of innate lymphoid cell that are involved in the progression of acute myocardial infarction and ischemic stroke. Although multiple forms of programmed cell death are known to play important roles in these diseases, the correlation between NK cells and apoptosis-related genes during acute myocardial infarction and ischemic stroke remains unclear. In this study, we explored the distinct patterns of NK cell infiltration and apoptosis during the pathological progression of acute myocardial infarction and ischemic stroke using mRNA expression microarrays from the Gene Expression Omnibus database. Since the abundance of NK cells correlated positively with apoptosis in both diseases, we further examined the correlation between NK cell abundance and the expression of apoptosis-related genes. Interestingly, APAF1 and IRAK3 expression correlated negatively with NK cell abundance in both acute myocardial infarction and ischemic stroke, whereas ATM, CAPN1, IL1B, IL1R1, PRKACA, PRKACB, and TNFRSF1A correlated negatively with NK cell abundance in acute myocardial infarction. Together, these findings suggest that these apoptosis-related genes may play important roles in the mechanisms underlying the patterns of NK cell abundance and apoptosis in acute myocardial infarction and ischemic stroke. Our study, therefore, provides novel insights for the further elucidation of the pathogenic mechanism of ischemic injury in both the heart and the brain, as well as potential useful therapeutic targets.

Comprehensive Analysis of Hub Genes Associated With Competing Endogenous RNA Networks in Stroke Using Bioinformatics Analysis

Background: Acute ischemic stroke (AIS) is the second leading cause of death and the third leading cause of disability worldwide. Long noncoding RNAs (lncRNAs) are promising biomarkers for the early diagnosis of AIS and closely participate in the mechanism of stroke onset. However, studies focusing on lncRNAs functioning as microRNA (miRNA) sponges to regulate the mRNA expression are rare and superficial. Methods: In this study, we systematically analyzed the expression profiles of lncRNA, mRNA (GSE58294), and miRNA (GSE110993) from the GEO database. Gene ontology (GO) analysis was performed to reveal the functions of differentially expressed genes (DEGs), and we used weighted gene co-expression network analysis (WGCNA) to investigate the relationships between clinical features and expression profiles and the co-expression of miRNA and lncRNA. Finally, we constructed a lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network with selected DEGs using bioinformatics methods and obtained ROC curves to assess the diagnostic efficacy of differentially expressed lncRNAs (DElncRNAs) and differentially expressed mRNAs (DEmRNAs) in our network. The GSE22255 dataset was used to confirm the diagnostic value of candidate genes. Results: In total, 199 DElncRNAs, 2068 DEmRNAs, and 96 differentially expressed miRNAs were detected. The GO analysis revealed that DEmRNAs primarily participate in neutrophil activation, neutrophil degranulation, vacuolar transport, and lysosomal transport. WGCNA screened out 16 lncRNAs and 195 mRNAs from DEGs, and only eight DElncRNAs maintained an area under the curve higher than 0.9. By investigating the relationships between lncRNAs and mRNAs, a ceRNA network containing three lncRNAs, three miRNAs, and seven mRNAs was constructed. GSE22255 confirmed that RP1-193H18.2 is more advantageous for diagnosing stroke, whereas no mRNA showed realistic diagnostic efficacy. Conclusion: The ceRNA network may broaden our understanding of AIS pathology, and the candidate lncRNA from the ceRNA network is assumed to be a promising therapeutic target and diagnostic biomarker for AIS.

Computational drug repositioning for ischemic stroke: neuroprotective drug discovery

Background: A comprehensive approach to drug repositioning will be required to overcome translational hurdles and identify more neuroprotective drugs. Results & methods: Gene Set Enrichment Analysis was applied to identify related pathways and enriched genes. Candidate genes were optimized using ToppGene, ToppGenet and pBRIT. From the perspective of the local structures, gene-domain-substructure-drug relationships were constructed. Using the MCODE algorithm and K-means clustering, 31 functional subnetworks were obtained, and 252 drugs with proposed neuroprotective function were identified. Using computational analysis, 72 substructures with different scores were found to correspond to neuroprotective functions. The protective effects of benidipine and barnidipine were confirmed in vitro. Conclusion: The authors' research has great potential to discover more neuroprotective drugs and obtain more information regarding mechanisms of action and functional substructures.

Preclinical Stroke Research and Translational Failure: A Bird's Eye View on Preventable Variables

Despite achieving remarkable success in understanding the cellular, molecular and pathophysiological aspects of stroke, translation from preclinical research has always remained an area of debate. Although thousands of experimental compounds have been reported to be neuro-protective, their failures in clinical setting have left the researchers and stakeholders in doldrums. Though the failures described have been excruciating, they also give us a chance to refocus on the shortcomings. For better translational value, evidences from preclinical studies should be robust and reliable. Preclinical study design has a plethora of variables affecting the study outcome. Hence, this review focusses on the factors to be considered for a well-planned preclinical study while adhering to guidelines with emphasis on the study design, commonly used animal models, their limitations with special attention on various preventable attritions including comorbidities, aged animals, time of dosing, outcome measures and physiological variables along with the concept of multicentric preclinical randomized controlled trials. Here, we provide an overview of a panorama of practical aspects, which could be implemented, so that a well-defined preclinical study would result in a neuro-protectant with better translational value.

Genome-Wide Detection of m6A-Associated Genetic Polymorphisms Associated with Ischemic Stroke

N⁶-Methyladenosine (m⁶A) methylation is the most abundant post-transcription modification in eukaryotes and plays a vital role in many pathological conditions including cerebral ischemia-reperfusion injury and vascular inflammation. Moreover, recent studies have reported that single-nucleotide polymorphisms (SNPs) can affect the m⁶A modification. Therefore, we investigated the relationship between m⁶A-SNPs and ischemic stroke (IS) risk through integrative analysis of an IS genome-wide association study and m⁶A-SNP list from the m6AVar database. Next, we performed eQTL and differential expression analysis to support these IS-associated m⁶A-SNPs. Finally, using the identified polymorphisms, a PPI network was constructed using the STRING database, and GO and pathway enrichment analyses were performed using the DAVID online tool. Accordingly, we identified 305 IS-associated SNPs that could affect m⁶A methylation. Next, 158 of these SNPs were determined to have eQTL signals on local genes. We further identified 84 local genes (containing a total of 87 SNPs) that were differentially expressed in IS patients. Finally, we identified several biological processes and pathways related to IS pathogenesis, such as "leukocyte migration" and "focal adhesion." In summary, our study detected dozens of m⁶A-SNPs as critical functional polymorphisms and novel genetic biomarkers for IS susceptibility and provided a new means of elucidating the biological mechanism underlying IS development.

Sex Difference of Ribosome in Stroke-Induced Peripheral Immunosuppression by Integrated Bioinformatics Analysis

Ischemic stroke (IS) greatly threatens human health resulting in high mortality and substantial loss of function. Recent studies have shown that the outcome of IS has sex specific, but its mechanism is still unclear. This study is aimed at identifying the sexually dimorphic to peripheral immune response in IS progression, predicting potential prognostic biomarkers that can lead to sex-specific outcome, and revealing potential treatment targets. Gene expression dataset GSE37587, including 68 peripheral whole blood samples which were collected within 24 hours from known onset of symptom and again at 24-48 hours after onset (20 women and 14 men), was downloaded from the Gene Expression Omnibus (GEO) datasets. First, using Bioconductor R package, two kinds of differentially expressed genes (DEGs) (nonsex-specific- and sex-specific-DEGs) were screened by follow-up (24-48 hours) vs. baseline (24 hours). 30 nonsex-specific DEGs (1 upregulated and 29 downregulated), 79 female-specific DEGs (25 upregulated and 54 downregulated), and none of male-specific DEGs were obtained finally. Second, bioinformatics analysis of female-specific DEGs was performed. Gene Ontology (GO) functional annotation analysis shows that DEGs were mainly enriched in translational initiation, cytosolic ribosome, and structural constituent of ribosome. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis shows that the top 6 enrichment pathways are ribosome, nuclear factor-­kappa B (NF-kappa B) signaling pathway, apoptosis, mineral absorption, nonalcoholic fatty liver disease, and pertussis. Three functional modules were clustered in the protein–protein interaction (PPI) network of DEGs. The top 10 key genes of the PPI network constructed were selected, including RPS14, RPS15A, RPS24, FAU, RPL27, RPL31, RPL34, RPL35A, RSL24D1, and EEF1B2. Sex difference of ribosome in stroke-induced peripheral immunosuppression may be the potential mechanism of sex disparities in outcome after IS, and women are more likely to have stroke-induced immunosuppression. RPS14, RPS15A, RPS24, FAU, RPL27, RPL31, RPL34, RPL35A, RSL24D1, and EEF1B2 may be novel prognostic biomarkers and potential therapeutic targets for IS.

Microarray Profiling Reveals Distinct Circulating miRNAs in Aged Male and Female Mice Subjected to Post-stroke Social Isolation

Social isolation (SI) increases ischemic injury and significantly delays recovery after experimental stroke. Changes in circulating microRNAs (miRNAs) have been implicated in several neurological disorders, including stroke. However, potential biomarkers to elucidate the mechanisms that underlie the detrimental effects of post-stroke isolation are unknown. Aged C57BL/6 male and female mice (18-20 months) were subjected to a 60-min middle cerebral artery occlusion followed by reperfusion and were assigned to either isolation (SI) or continued pair housing (PH) immediately after stroke. On day 15, mice were sacrificed, and plasma samples were collected for miRNAome analysis. Top candidate miRNAs and their biological functions were identified using integrated bioinformatics. The miRNAome analysis revealed a total of 21 differentially expressed miRNAs across both sexes with fold change of 3 or higher. Within the female cohort, miR-206-3p, -376a-3p, -34b-5p, -133a-5p, -466f, and -671-3p were highly altered relative to the PH housing condition. Similarly in males, miR-376c-3p, -181d-5p, -712-5p, -186-5p, -21a-3p, -30d-3p, -495-3p, -669c-5p, -335-5p, -429-3p, -31-3p, and -217-5p were identified. Following Kyoto Encyclopedia of Genes and Genomes analysis, the identified miRNAs effected distinct subset of pathways within sexes. Interactional network analysis revealed miR-495-3p (male) and miR-34b-5p (female) as pivotal nodes that targeted the largest subset of genes. We identified several sex-specific miRNAs as candidate biomarkers for post-stroke SI in aged male and female mice. Additionally, these results suggest that there is potential to use plasma-based circulating miRNAs as a source of novel biomarkers to identify biological pathways involved in post-stroke SI.

Identification of common and divergent gene expression signatures in patients with venous and arterial thrombosis using data from public repositories

Cardiovascular disease (CVD) and venous thromboembolism (VTE) figure among the main causes of morbidity and mortality in modern societies. Although associated with distinct pathogenic mechanisms, epidemiological, experimental and clinical trial data suggest that the mechanisms responsible for arterial and venous thrombosis are at least partially overlapped. Herein we aimed to explore shared and discordant pathways involved in the pathogenesis of VTE and CVD at the transcriptomic level and to validate the results in independent cohorts. Five public datasets of gene expression data from VTE and CVD (myocardial infarction, peripheral arterial occlusive disease and stroke) patients were analyzed using an integrative bioinformatic strategy. A machine/statistical learning method was used to derive classifiers for the discrimination of VTE and CVD, and tested in independent datasets. Two sets of genes that were commonly (n = 472) or divergently (n = 124) expressed in CVD and VTE were identified. Genes and pathways associated with innate immune function were over-represented in both conditions, along with pathways associated with complement and hemostasis. Pathways associated with neutrophil activation and with IL-1 signaling were also enriched in CVD compared to VTE. The gene expression signature of VTE more closely resembled the pattern of cardioembolic stroke than the patterns of acute myocardial infarction, ischemic stroke and peripheral arterial occlusive disease. Classifiers derived from these gene lists accurately discriminated patients with VTE and CVD from independent cohorts. In conclusion, our results add a new set of data at the transcriptomic level for future studies between arterial and venous thrombosis.

Ctnnb1 transcriptional upregulation compensates for Mdm2/p53-mediated β-catenin degradation in neutrophils following cardioembolic stroke

BACKGROUND

A better understanding of the mechanism(s) underlying cardioembolic stroke can promote recovery and reduce the risk of recurrent embolisms.

METHODS

Peripheral blood mononuclear cell (PBMC) gene expression datasets from cardioembolic patients and healthy controls were obtained from the Gene Expression Omnibus (GEO) database (GSE58294). The Limma software package was utilized to identify differentially-expressed genes (DEGs). Protein-protein interaction (PPI) analysis of the DEGs was performed using STRING. A weighted gene co-expression network analysis (WGCNA) was used to build a gene co-expression network. In vitro experiments assessed the effects on neutrophils exposed to oxygen and glucose-deprived (OGD) cortical neurons. An in vivo murine model of thromboembolic stroke was constructed through thrombin injection to examine effects on circulating neutrophils. Mechanistic in vitro studies were conducted using the proteasome inhibitor MG132, the p53-Mdm2 binding inhibitor Nutlin-3a, Mdm2 small-interfering RNA (siRNA), and Ctnnb1 siRNA.

RESULTS

DEG analysis identified 44 upregulated and 66 downregulated genes in cardioembolic stroke PBMCs. PPI analysis of these DEGs yielded one eight-node protein module with β-catenin (CTNNB1) as the central hub protein. Integration of the DEGs with WGCNA-derived hub genes revealed the key hub DEGs CTNNB1 and mouse double minute 2 (MDM2). Follow-up experiments revealed Mdm2, p53, and phospho-β-catenin upregulation in neutrophils exposed to OGD neurons in vitro and following thromboembolic stroke in vivo. Mechanistic studies revealed that neutrophils transcriptionally upregulate Ctnnb1 expression to compensate for Mdm2/p53-mediated β-catenin degradation induced by exposure to OGD neurons, thereby promoting neutrophil survival.

CONCLUSION

Compensatory Ctnnb1 transcriptional upregulation in neutrophils induced by ischemic neuron exposure may be involved in promoting neutrophil survival following cardioembolic stroke.

Insight into atrial fibrillation through analysis of the coding transcriptome in humans

Atrial fibrillation is the most common sustained cardiac arrhythmia in humans, and its prevalence continues to increase because of the aging of the world population. Much still needs to be learned about the molecular pathways involved in the development and the persistence of the disease. Analysis of the transcriptome of cardiac tissue has provided valuable insight into diverse aspects of atrial remodeling, in particular concerning electrical remodeling-related to ion channels-and structural remodeling identified by dysregulation of processes linked to inflammation, fibrosis, oxidative stress, and thrombogenesis. The huge amount of data produced by these studies now represents a valuable source for the identification of novel potential therapeutic targets. In addition, the shift from cardiac tissue to peripheral blood as a substrate for transcriptome analysis revealed this strategy as a promising tool for improved diagnosis and therefore better patient care.

Genetic Etiology Shared by Multiple Sclerosis and Ischemic Stroke

Although dramatic progress has been achieved in the understanding and treatment of multiple sclerosis (MS) and ischemic stroke (IS), more precise and instructive support is required for further research. Recent large-scale genome-wide association studies (GWASs) have already revealed risk variants for IS and MS, but the common genetic etiology between MS and IS remains an unresolved issue. This research was designed to overlapping genes between MS and IS and unmask their transcriptional features. We designed a three-section analysis process. Firstly, we computed gene-based analyses of MS GWAS and IS GWAS data sets by VGEAS2. Secondly, overlapping genes of significance were identified in a meta-analysis using the Fisher’s procedure. Finally, we performed gene expression analyses to confirm transcriptional changes. We identified 24 shared genes with Bonferroni correction (P_combined < 2.31E-04), and five (FOXP1, CAMK2G, CLEC2D, LBH, and SLC2A4RG) had significant expression differences in MS and IS gene expression omnibus data sets. These meaningful shared genes between IS and MS shed light on the underlying genetic etiologies shared by the diseases. Our results provide a basis for in-depth genomic studies of associations between MS and IS.

SERPINA1 gene expression in whole blood links the rs6647 variant G allele to an increased risk of large artery atherosclerotic stroke

The rs6647 variant G allele in SERPINA1 gene was reported to be associated with the risk of large artery atherosclerotic stroke (LAS), however, the mechanism remains unclear. Here, we performed a functional annotation of the rs6647 variant by using the software HaploReg version 4.1 (HaploReg v4.1). Next, the expression quantitative trait loci (eQTLs) analysis of multiple datasets was conducted for determining the association between the rs6647 and SERPINA1 expression in various tissues. Then, a case-control gene expression analysis was done using two independent ischemic stroke (IS) gene expression datasets. Finally, SERPINA1 expression in whole blood samples from 8 LAS patients and 14 healthy persons were compared. The functional annotation suggested that the rs6647 regulates gene expression in multiple human tissues especially in brain and blood. The eQTLs analysis revealed a significant association of the rs6647 G allele with increased expression of SERPINA1 gene only in whole blood. Compared with the controls, there was an increased expression of SERPINA1 gene in whole blood in both IS patients and LAS patients. SERPINA1 gene expression in whole blood bridges the rs6647 variant G allele with increased LAS risk, providing new insights into the mechanisms underlying role of the rs6647 in determining LAS risk.

Identification of Co-expressed Genes Between Atrial Fibrillation and Stroke

Atrial fibrillation (AF) increases the risk of ischemic stroke and systemic arterial embolism. However, the risk factors or predictors of stroke in AF patients have not been clarified. Therefore, it is necessary to find effective diagnostic and therapeutic targets. Two datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differently expressed genes (DEGs) were identified between samples of atrial fibrillation without stroke and atrial fibrillation with stroke. Enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) by Gene Set Enrichment Analysis (GSEA), construction and analysis of protein-protein interaction (PPI) network and significant module, and the receiver operator characteristic (ROC) curve analysis were performed. A total of 524 DEGs were common to both datasets. Analysis of KEGG pathways indicated that the top canonical pathways associated with DEGs were ubiquitin-mediated proteolysis, endocytosis, spliceosome, and so on. Ten hub genes (SMURF2, CDC42, UBE3A, RBBP6, CDC5L, NEDD4L, UBE2D2, UBE2B, UBE2I, and MAPK1) were identified from the PPI network and were significantly associated with a diagnosis of atrial fibrillation and stroke (AFST). In summary, a total of 524 DEGs and 10 hub genes were identified between samples of atrial fibrillation without stroke and atrial fibrillation with stroke. These genes may serve as the target of early diagnosis or treatment of AF complicated by stroke.

Virtual Screening of the Multi-pathway and Multi-gene Regulatory Molecular Mechanism of Dachengqi Decoction in the Treatment of Stroke Based on Network Pharmacology

BACKGROUND

Stroke is ranked second among diseases that cause mortality worldwide. Owing to its complicated pathogenesis, no satisfactory treatment strategies for stroke are available. Dachengqi decoction (DCQD), a traditional Chinese herbal medicine, has been widely used in China for a long time, as it has a good effect on stroke. However, the molecular mechanism underlying this effect of DCQD is unclear.

OBJECTIVE

In the present study, we aimed to reveal and explore the multi-pathway and multi-gene regulatory molecular mechanism of Dachengqi decoction in the treatment of stroke.

METHODS

In this study, a network pharmacology method, in combination with oral bioavailability prediction and drug-likeness evaluation, was employed to predict the active ingredients of DCQD. The target genes of the active components and the traced pathways related to these target genes were predicted. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using clusterProfiler software package on the R platform and ClueGo+CluePedia plug-ins. Finally, the key DCQD targets were verified using the Gene Expression Omnibus (GEO) dataset.

RESULTS AND DISCUSSION

According to the ADME model, 52 active components were screened from 296 active components of DCQD. After prediction and screening, 215 stroke-related targets were obtained and analyzed via GO and KEGG analyses. GO analysis showed that DCQD targets were mainly involved in the regulation of oxidative stress, lipid metabolism, inflammation, and other biological processes. KEGG pathway analysis further revealed pathways involved in stroke, such as arachidonic acid metabolic, HIF-1 signaling pathway, estrogen signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway, platelet activation pathway, VEGF signaling pathway, and cAMP signaling pathway. Network analysis revealed that DCQD might be involved in the regulation of lipid metabolism, blood pressure, inflammation, angiogenesis, neuroprotection, platelet aggregation, apoptosis, and oxidation in stroke treatment. GEO dataset analysis showed that DCQD's therapeutic effects might be exerted via the bidirectional regulation principle.

CONCLUSION

Based on the methods of network pharmacology and GEO analysis, it was found that, during stroke treatment, DCQD regulates and controls multiple genes and multiple pathways in a synergistic manner, providing a new strategy for stroke treatment.

Establishing molecular signatures of stroke focusing on omic approaches: a narrative review

Stroke or 'brain attack' is considered to be the major cause of mortality and morbidity worldwide after myocardial infraction. Inspite of the years of research and clinical practice, the pathogenesis of stroke still remains incompletely understood. Omics approaches not only enable the description of a huge number of molecular platforms but also have a potential to recognize new factors associated with various complex disorders including stroke. The most significant development among all other omics technologies over the recent years has been seen by genomics which is a powerful tool for exploring the genetic architecture of stroke. Genomics has decisively established itself in stroke research and by now wealth of data has been generated providing new insights into the physiology and pathophysiology of stroke. However, the efficacy of genomic data is restricted to risk prediction only. Omics approaches not only enable the description of a huge number of molecular platforms but also have a potential to recognize new factors associated with various complex disorders including stroke. The data generated by omics technologies enables clinicians to provide detailed insight into the makeup of stroke in individual patients, which will further help in developing diagnostic procedures to direct therapies. Present review has been compiled with an aim to understand the potential of integrated omics approach to help in characterization of mechanisms leading to stroke, to predict the patient risk of getting stroke by analyzing signature biomarkers and to develop targeted therapeutic strategies.