Biomarker For Ischemic Stroke Research Articles

Bioinformatics strategies to identify differences in molecular biomarkers for ischemic stroke and myocardial infarction.

Ischemic strokes (ISs) are commonly treated by intravenous thrombolysis using a recombinant tissue plasminogen activator; however, successful treatment can only occur within 3 hours after the stroke. Therefore, it is crucial to determine the causes and underlying molecular mechanisms, identify molecular biomarkers for early diagnosis, and develop precise preventive treatments for strokes. We aimed to clarify the differences in gene expression, molecular mechanisms, and drug prediction approaches between IS and myocardial infarction (MI) using comprehensive bioinformatics analysis. The pathogenesis of these diseases was explored to provide directions for future clinical research. The IS (GSE58294 and GSE16561) and MI (GSE60993 and GSE141512) datasets were downloaded from the Gene Expression Omnibus database. IS and MI transcriptome data were analyzed using bioinformatics methods, and the differentially expressed genes (DEGs) were screened. A protein-protein interaction network was constructed using the STRING database and visualized using Cytoscape, and the candidate genes with high confidence scores were identified using Degree, MCC, EPC, and DMNC in the cytoHubba plug-in. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the DEGs were performed using the database annotation, visualization, and integrated discovery database. Network Analyst 3.0 was used to construct transcription factor (TF) - gene and microRNA (miRNA) - gene regulatory networks of the identified candidate genes. The DrugBank 5.0 database was used to identify gene-drug interactions. After bioinformatics analysis of IS and MI microarray data, 115 and 44 DEGS were obtained in IS and MI, respectively. Moreover, 8 hub genes, 2 miRNAs, and 3 TFs for IS and 8 hub genes, 13 miRNAs, and 2 TFs for MI were screened. The molecular pathology between IS and MI presented differences in terms of GO and KEGG enrichment pathways, TFs, miRNAs, and drugs. These findings provide possible directions for the diagnosis of IS and MI in the future.

Identification of Serum Biomarkers of Ischemic Stroke in a Hypertensive Population Based on Metabolomics and Lipidomics.

Hypertensive individuals are at a high risk of stroke, and thus, prevention of stroke in hypertensive patients is essential. Metabolomics and lipidomics can be used to identify diagnostic biomarkers and conduct early assessments of stroke risk in hypertensive populations. In this study, serum samples were collected from 30 hypertensive ischemic stroke (IS), 30 matched hypertensive and 30 matched healthy participants. Metabolomics and lipidomics analyses were conducted via liquid chromatography-tandem mass spectrometry, and the data were analyzed using multivariate and univariate statistical methods. A random forest algorithm and binary logistic regression were used to screen the biomarkers and establish diagnostic model. We detected 21 differential metabolites and 38 differential lipids between the hypertensive IS and healthy group. Moreover, we found 18 differential metabolites and 31 differential lipids between the hypertensive IS and hypertension group. In particular, the following seven metabolites or lipids distinguished the hypertensive IS from the healthy group: 4-hydroxyphenylpyruvic acid, cafestol, phosphatidylethanolamine (PE) (18:0p/18:2), PE (16:0e/20:4), (O-acyI)-1-hydroxy fatty acid (36:3), PE (16:0p/20:3) and PE (18:1p/18:2) (rep). The following seven biomarkers distinguished the hypertensive IS from the hypertension group: diglyceride (DG) (20:1/18:2), PE (18:0p/18:2), PE (16:0e/22:5), phosphatidylcholine (40:7), dimethylphosphatidylethanolamine (50:3), DG (18:1/18:2), and 4-hydroxyphenylpyruvic acid. The aforementioned panels had good diagnostic and predictive ability for hypertensive IS. Our study determines the metabolomic and lipidomic profiles of hypertensive IS patients and thereby identifies potential biomarkers of the presence of IS in hypertensive populations.

MicroRNAs as Potential Biomarkers of Post-Traumatic Epileptogenesis: A Systematic Review.

Structural or post-traumatic epilepsy often develops after brain tissue damage caused by traumatic brain injury, stroke, infectious diseases of the brain, etc. Most often, between the initiating event and epilepsy, there is a period without seizures-a latent period. At this time, the process of restructuring of neural networks begins, leading to the formation of epileptiform activity, called epileptogenesis. The prediction of the development of the epileptogenic process is currently an urgent and difficult task. MicroRNAs are inexpensive and minimally invasive biomarkers of biological and pathological processes. The aim of this study is to evaluate the predictive ability of microRNAs to detect the risk of epileptogenesis. In this study, we conducted a systematic search on the MDPI, PubMed, ScienceDirect, and Web of Science platforms. We analyzed publications that studied the aberrant expression of circulating microRNAs in epilepsy, traumatic brain injury, and ischemic stroke in order to search for microRNAs-potential biomarkers for predicting epileptogenesis. Thus, 31 manuscripts examining biomarkers of epilepsy, 19 manuscripts examining biomarkers of traumatic brain injury, and 48 manuscripts examining biomarkers of ischemic stroke based on circulating miRNAs were analyzed. Three miRNAs were studied: miR-21, miR-181a, and miR-155. The findings showed that miR-21 and miR-155 are associated with cell proliferation and apoptosis, and miR-181a is associated with protein modifications. These miRNAs are not strictly specific, but they are involved in processes that may be indirectly associated with epileptogenesis. Also, these microRNAs may be of interest when they are studied in a cohort with each other and with other microRNAs. To further study the microRNA-based biomarkers of epileptogenesis, many factors must be taken into account: the time of sampling, the type of biological fluid, and other nuances. Currently, there is a need for more in-depth and prolonged studies of epileptogenesis.

БИОМАРКЕРЫ КРОВИ – ПРЕДИКТОРЫ РАЗВИТИЯ ИШЕМИЧЕСКОГО ИНСУЛЬТА: НОВЫЙ ВЗГЛЯД НА ИЗВЕСТНЫЕ МОЛЕКУЛЫ

Abstract. The number of strokes and deaths from stroke is increasing every year in the world, with ischemic stroke (IS) accounting for about 80% of cases. The purpose of this review is to analyze the results of studies evaluating the significance of measuring various biomarkers in predicting the risk of developing IS. To date, studies are actively exploring the prospects of a number of inflammatory (C-reactive protein, fibrinogen, pro-inflammatory cytokines, etc.), hemodynamic, cardiac, and metabolic biomarkers that can be used to improve the accuracy of IS risk stratification. Currently, it is difficult to isolate the screening biomarker that is the most diagnostically significant for assessing the risk of stroke. Thus, according to a number of studies and meta-analyses, highly sensitive C-reactive protein is a diagnostically significant biomarker of IS. The role of highly sensitive troponin I and natriuretic peptide in diagnosing the risk of IS requires further study. Evaluation of triglyceride-glucose index, apolipoprotein B, apolipoprotein A1, asymmetric dimethylarginine, uric acid seems promising. However, their possible role in the reclassification of asymptomatic patients in addition to the existing scales based on traditional risk factors remains to be elucidated

Neutrophil-to-lymphocyte ratio and its changes predict the 3-month outcome and mortality in acute ischemic stroke patients after intravenous thrombolysis.

The neutrophil-to-lymphocyte ratio (NLR) has been demonstrated as a prognostic inflammatory biomarker in ischemic stroke. The study aimed to investigate the association of NLR and its dynamic change with long-term outcome and mortality in acute ischemic stroke (AIS) patients who received intravenous thrombolysis (IVT). From a prospective cohort, AIS patients receiving IVT (alteplase, 0.9mg/kg) with complete NLR data were retrospectively screened. Based on 3-month modified Rankin scale score (mRS), patients were classified into good group (mRS 0-1) and poor outcome group (mRS 2-6), or survival group (mRS 0-5) and death group (mRS 6). Multivariate logistic regression analysis and receiver operating curve were used to identify prognostic factors and their predictive powers. A total of 259 eligible patients were enrolled in our study. Logistic regression analysis showed that NLR at 24h (adjusted odds ratio [aOR] 1.182), 12 days (aOR 1.218) after IVT was independent predictors of 3-month outcome with the AUC of 0.815, 0.820, respectively, whereas NLR at 24h (aOR 1.17), 12 days (aOR 1.252) after IVT and percentage changes of NLR between admission and 24h after IVT (aOR 1.214), and between admission and 12 days after IVT (aOR 1.233) were independent predictors of 3-month mortality with the AUCs of 0.86, 0.902, 0.814, and 0.855, respectively. The comprehensive report suggests that NLR and its dynamic changes are associated with 3-month outcome and mortality in AIS patients after IVT with good predictive powers.

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

At present, there is a lack of accurate early diagnostic markers for ischemic stroke. 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. 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. Our study provides a reference for the study of pathogenesis and key targets of ischemic stroke.

A potential relationship between MMP-9 rs2250889 and ischemic stroke susceptibility.

Ischemic stroke (IS), a serious cerebrovascular disease, greatly affects people's health and life. Genetic factors are indispensable for the occurrence of IS. As a biomarker for IS, the MMP-9 gene is widely involved in the pathophysiological process of IS. This study attempts to find out the relationship between MMP-9 polymorphisms and IS susceptibility. A total of 700 IS patients and 700 healthy controls were recruited. The single nucleotide polymorphism (SNP) markers of the MMP-9 gene were genotyped by the MassARRAY analyzer. Multifactor dimensionality reduction (MDR) was applied to generate SNP-SNP interaction. Furthermore, the relationship between genetic variations (allele and genotype) of the MMP-9 gene and IS susceptibility was analyzed by calculating odds ratios (ORs) and 95% confidence intervals (CIs). Our results demonstrated that rs2250889 could significantly increase the susceptibility to IS in the codominant, dominant, overdominant, and log-additive models (p < 0.05). Further stratification analysis showed that compared with the control group, rs2250889 was associated with IS risk in different case groups (age, female, smoking, and non-drinking) (p < 0.05). Based on MDR analysis, rs2250889 was the best model for predicting IS risk (cross-validation consistency: 10/10, OR = 1.56 (1.26-1.94), p < 0.001). Our study preliminarily confirmed that SNP rs2250889 was significantly associated with susceptibility to IS.

The identification of sex-specific biomarkers in peripheral blood mononuclear cells from elderly individuals with ischemic stroke.

The aim of this study was to identify sex-specific biomarkers for ischemic stroke (IS) prophylaxis in elderly individuals. The GSE22255 dataset for elderly individuals with IS was retrieved from the gene expression omnibus database. Thereafter, gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, as well as gene set enrichment analysis (GSEA). Furthermore, protein-protein interactions (PPIs) were explored using the STRING database, and to screen central genes from the Cytoscape PPI network, corresponding to peripheral blood samples from elderly individuals, we used the molecular complex detection plug-in and cytoHubba. Moreover, a Venn diagram was used to visualize the key genes common among elderly women and men with IS. Statistical analysis was also performed, and receiver operating characteristic (ROC) curves were constructed to evaluate the specificity and sensitivity of the prediction of IS in the elderly. Compared with the healthy controls, in elderly women with IS, 511 biological process (BP) terms, 16 molecular function (MF) terms, and 34 KEGG terms were significantly enriched, whereas in the elderly men with IS, 681 BP terms, 12 MF terms, and 44 KEGG terms were enriched. The GSEA revealed 99 and 140 significantly enriched gene sets in elderly women and men with IS, respectively. Furthermore, in the PPI network, 10 hub genes for each sex with high specificity and sensitivity were identified using ROC curves. Ten genes for each sex with significant differential expression were also identified in individuals with IS. The novel sex-specific gene targets may be promising diagnostic or prognostic markers and potential therapeutic targets for IS in the elderly.

Circulating Extracellular-Vesicle-Incorporated MicroRNAs as Potential Biomarkers for Ischemic Stroke in Patients With Cancer.

This study aimed to evaluate whether extracellular-vesicle-incorporated microRNAs (miRNAs) are potential biomarkers for cancer-related stroke. This cohort study compared patients with active cancer who had embolic stroke of unknown sources (cancer-stroke group) with patients with only cancer, patients with only stroke, and healthy individuals (control groups). The expression profiles of miRNAs encapsulated in plasma exosomes and microvesicles were evaluated using microarray and validated using quantitative real-time polymerase chain reaction. The XENO-QTM miRNA assay technology was used to determine the absolute copy numbers of individual miRNAs in an external validation cohort. This study recruited 220 patients, of which 45 had cancer-stroke, 76 were healthy controls, 39 were cancer controls, and 60 were stroke controls. Three miRNAs (miR-205-5p, miR-645, and miR-646) were specifically incorporated into microvesicles in patients with cancer-related stroke, cancer controls, and stroke controls. The area under the receiver operating characteristic curves of these three miRNAs were 0.7692-0.8510 for the differentiation of patients with cancer-stroke from cancer-controls and 0.8077-0.8846 for the differentiation of patients with cancer-stroke from stroke controls. The levels of several miRNAs were elevated in the plasma exosomes of patients with cancer, but were lower than those in plasma microvesicles. An in vivo study showed that systemic injection of miR-205-5p promoted the development of arterial thrombosis and elevation of D-dimer levels. Stroke due to cancer-related coagulopathy was associated with deregulated expression of miRNAs, particularly microvesicle-incorporated miR-205-5p, miR-645, and miR-646. Further prospective studies of extracellular-vesicle-incorporated miRNAs are required to confirm the diagnostic role of miRNAs in patients with stroke and to screen the roles of miRNAs in patients with cancer.

Association between PAI-1 Polymorphisms and Ischemic Stroke in a South Korean Case-Control Cohort.

Stroke is the second leading cause of death in the world. Approximately 80% of strokes are ischemic in origin. Many risk factors have been linked to stroke, including an increased level of plasminogen activator inhibitor-1 (PAI-1). PAI-1 levels increase and remain elevated in blood during the acute phase of ischemic stroke, which can impair fibrinolytic activity, leading to coronary artery disease and arterial thrombotic disorders. Here, we present a case-control study of 574 stroke patients and 425 controls seen for routine health examination or treatment for nonspecific dizziness, nonorganic headache, or anxiety for positive family history of stroke at the Bundang Medical Center in South Korea. Polymorphisms in PAI-1 were identified by polymerase chain reaction/restriction fragment length polymorphism analysis using genomic DNA. Specifically, three variations (-675 4G>5G, 10692T>C, and 12068G>A) were linked to a higher overall prevalence of stroke as well as a higher prevalence of certain stroke subtypes. Haplotype analyses also revealed combinations of these variations (-844G>A, -675 4G>5G, 43G>A, 9785A>G, 10692T>C, 11053T>G, and 12068G>A) that were significantly associated with a higher prevalence of ischemic stroke. To the best of our knowledge, this is the first strong evidence that polymorphic sites in PAI-1 promoter and 3'-UTR regions are associated with higher ischemic stroke risk. Furthermore, the PAI-1 genotypes and haplotypes identified here have potential as clinical biomarkers of ischemic stroke and could improve the prognosis and future management of stroke patients.

Common clinical blood and urine biomarkers for ischemic stroke: an Estonian Electronic Health Records database study

BackgroundIschemic stroke (IS) is a major health risk without generally usable effective measures of primary prevention. Early warning signals that are easy to detect and widely available can save lives. Estonia has one nation-wide Electronic Health Record (EHR) database for the storage of medical information of patients from hospitals and primary care providers.MethodsWe extracted structured and unstructured data from the EHRs of participants of the Estonian Biobank (EstBB) and evaluated different formats of input data to understand how this continuously growing dataset should be prepared for best prediction. The utility of the EHR database for finding blood- and urine-based biomarkers for IS was demonstrated by applying different analytical and machine learning (ML) methods.ResultsSeveral early trends in common clinical laboratory parameter changes (set of red blood indices, lymphocyte/neutrophil ratio, etc.) were established for IS prediction. The developed ML models predicted the future occurrence of IS with very high accuracy and Random Forests was proved as the most applicable method to EHR data.ConclusionsWe conclude that the EHR database and the risk factors uncovered are valuable resources in screening the population for risk of IS as well as constructing disease risk scores and refining prediction models for IS by ML.

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.

The prognostic value of caveolin-1 levels in ischemic stroke patients after mechanical thrombectomy.

The impact of serum caveolin-1 (Cav-1) on clinical outcomes in patients after mechanical thrombectomy (MT) is unclear. We aimed to investigate the association between serum cav-1 levels and the 3-month functional outcome. We prospectively enrolled and analyzed patients with an anterior circulation large vessel occlusion who underwent MT. Serum cav-1 concentrations were tested after admission. The primary outcome was a 90-day modified Rankin Scale score of 3-6. Of the 237 recruited patients (mean age, 69.7 ± 12.1years; 152 male), 131 (55.3%) experienced a 90-day poor outcome. After adjustment for demographic characteristics and other covariates, patients with higher serum Cav-1 levels had a reduced risk of poor outcome at 3months (Per 1-standard deviation increase; odd ratios [OR], 0.59; 95% confidence interval [CI], 0.39 - 0.89, P = 0.013). Elevated Cav-1 concentrations (Per 1-standard deviation increase; OR, 0.59; 95% CI, 0.40 - 0.88, P = 0.011) were significantly associated with a favorable shift in modified Rankin Scale score distribution. Similar results were confirmed when the Cav-1 levels were analyzed as a categorical variable. Furthermore, the restricted cubic spline showed a linear association between Cav-1 levels and 90-day poor outcome (P = 0.032 for linearity). Increased serum Cav-1 levels were associated with improved prognosis at 3months in ischemic stroke patients after MT, suggesting that Cav-1 may be a potential prognostic biomarker for ischemic stroke after reperfusion therapy.

Experimental verification and comprehensive analysis of m7G methylation regulators in the subcluster classification of ischemic stroke.

Background: Ischemic stroke (IS) is a fatal cerebrovascular disease involving several pathological mechanisms. Modification of 7-methylguanosine (m7G) has multiple regulatory functions. However, the expression pattern and mechanism of m7G in IS remain unknown. Herein, we aimed to explore the effect of m7G modification on IS. Methods: We screened significantly different m7G-regulated genes in Gene Expression Omnibus datasets, GSE58294 and GSE22255. The random forest (RF) algorithm was selected to identify key m7G-regulated genes that were subsequently validated using the middle cerebral artery occlusion (MCAO) model and quantitative polymerase chain reaction (qPCR). A risk model was subsequently generated using key m7G-regulated genes. Then, "ConsensusClusterPlus" package was used to distinguish different m7G clusters of patients with IS. Simultaneously, between two m7G clusters, differentially expressed genes (DEGs) and immune infiltration differences were also explored. Finally, we investigated functional enrichment and the mRNA-miRNA-transcription factor network of DEGs. Results: RF and qPCR confirmed that EIF3D, CYFIP2, NCBP2, DCPS, and NUDT1 were key m7G-related genes in IS that could accurately predict clinical risk (area under the curve = 0.967). NCBP2 was the most significantly associated gene with immune infiltration. Based on the expression profiles of these key m7G-related genes, the IS group could be divided into two clusters. According to the single-sample gene set enrichment analysis algorithm, four types of immune cells (immature dendritic cells, macrophages, natural killer T cells, and TH1 cells) were significantly different in the two m7G clusters. The functional enrichment of 282 DEGs between the two clusters was mainly concentrated in the "regulation of apoptotic signaling pathway," "cellular response to DNA damage stimulus," "adaptive immune system," and "pyroptosis." The miR-214-LTF-FOXJ1 axis may be a key regulatory pathway for IS. Conclusion: Our findings suggest that EIF3D, CYFIP2, NCBP2, DCPS, and NUDT1 may serve as potential diagnostic biomarkers for IS and that the m7G clusters developed by these genes provide more evidence for the regulation of m7G in IS.

Circulating microRNAs as diagnostic biomarkers for ischemic stroke: evidence from comprehensive analysis and real-world validation.

Ischemic stroke (IS) is the majority of strokes which remain the second leading cause of deaths in the last two decades. Circulating microRNAs (miRNAs) have been suggested as potential diagnostic and therapeutic tools for IS by previous studies analyzing their differential expression. However, inconclusive and controversial conclusions of these results have to be addressed. In this study, comprehensive analysis and real-world validation were performed to assess the associations between circulating miRNAs and IS. 29 studies with 112 miRNAs were extracted after manual selection and filtering, 12 differentially expressed miRNAs were obtained from our results of meta-analysis. These miRNAs were evaluated in 20 IS patients, compared to 20 healthy subjects. 4 miRNAs (hsa-let-7e-5p, hsa-miR-124-3p, hsa-miR-17-5p, hsa-miR-185-5p) exhibited the significant expression level in IS patient plasma samples. Pathway and biological process enrichment analysis for the target genes of the 4 validated miRNAs identified cellular senescence and neuroinflammation as key post-IS response pathways. The results of our analyses closely correlated with the pathogenesis and implicated pathways observed in IS subjects suggested by the literature, which may provide aid in the development of circulating diagnostic or therapeutic targets for IS patients.

Diagnostic model constructed by nine inflammation-related genes for diagnosing ischemic stroke and reflecting the condition of immune-related cells.

Ischemic cerebral infarction is the most common type of stroke with high rates of mortality, disability, and recurrence. However, the known diagnostic biomarkers and therapeutic targets for ischemic stroke (IS) are limited. In the current study, we aimed to identify novel inflammation-related biomarkers for IS using machine learning analysis and to explore their relationship with the levels of immune-related cells in whole blood samples. Gene expression profiles of healthy controls and patients with IS were download from the Gene Expression Omnibus. Analysis of differentially expressed genes (DEGs) was performed in healthy controls and patients with IS. Single-sample gene set enrichment analysis was performed to calculate inflammation scores, and weighted gene co-expression network analysis was used to analyze genes in significant modules associated with inflammation scores. Key DEGs in significant modules were then analyzed using LASSO regression analysis for constructing a diagnostic model. The effectiveness and specificity of the diagnostic model was verified in healthy controls and patients with IS and with cerebral hemorrhage (CH) using qRT-PCR. The relationship between diagnostic score and the levels of immune-related cells in whole blood were analyzed using Pearson correlations. A total of 831 DEGs were identified. Both chronic and acute inflammation scores were higher in patients with IS, while 54 DEGs were also clustered in the gene modules associated with chronic and acute inflammation scores. Among them, a total of 9 genes were selected to construct a diagnostic model. Interestingly, RT-qPCR showed that the diagnostic model had better diagnostic value for IS but not for CH. The levels of lymphocytes were lower in blood of patients with IS, while the levels of monocytes and neutrophils were increased. The diagnostic score of the model was negatively associated with the levels of lymphocytes and positively associated with levels of monocytes and neutrophils. Taken together, the diagnostic model constructed using the inflammation-related genes TNFSF10, ID1, PAQR8, OSR2, PDK4, PEX11B, TNIP1, FFAR2, and JUN exhibited high and specific diagnostic value for IS and reflected the condition of lymphocytes, monocytes, and neutrophils in the blood. The diagnostic model may contribute to the diagnosis of IS.

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

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

Multi-omics research strategies in ischemic stroke: A multidimensional perspective.

Ischemic stroke (IS) is a multifactorial and heterogeneous neurological disorder with high rate of death and long-term impairment. Despite years of studies, there are still no stroke biomarkers for clinical practice, and the molecular mechanisms of stroke remain largely unclear. The high-throughput omics approach provides new avenues for discovering biomarkers of IS and explaining its pathological mechanisms. However, single-omics approaches only provide a limited understanding of the biological pathways of diseases. The integration of multiple omics data means the simultaneous analysis of thousands of genes, RNAs, proteins and metabolites, revealing networks of interactions between multiple molecular levels. Integrated analysis of multi-omics approaches will provide helpful insights into stroke pathogenesis, therapeutic target identification and biomarker discovery. Here, we consider advances in genomics, transcriptomics, proteomics and metabolomics and outline their use in discovering the biomarkers and pathological mechanisms of IS. We then delineate strategies for achieving integration at the multi-omics level and discuss how integrative omics and systems biology can contribute to our understanding and management of IS.

Biological Properties and Clinical Significance of Lipoprotein-Associated Phospholipase A2 in Ischemic Stroke.

Ischemic stroke, which occurs following blockage of the blood supply to the brain, is a leading cause of death worldwide. Its main cause is atherosclerosis, a disease of the arteries characterized by the deposition of plaques of fatty material on the inner artery walls. Multiple proteins involved in the inflammation response have been identified as diagnosing biomarkers of ischemic stroke. One of these is lipoprotein-associated phospholipase A2 (Lp-PLA2), an enzyme that can hydrolyze circulating oxidized phospholipids, generating proinflammatory lysophosphatidylcholine and promoting the development of atherosclerosis. In the last two decades, a number of studies have revealed that both the concentration and the activity of Lp-PLA2 are independent biomarkers of ischemic stroke. The US Food and Drug Administration (FDA) has approved two tests to determine Lp-PLA2 mass and activity for predicting stroke. In this review, we summarize the biological properties of Lp-PLA2, the detection sensitivity and limitations of Lp-PLA2 measurement, the clinical significance and association of Lp-PLA2 in ischemic stroke, and the prospects of therapeutic inhibition of Lp-PLA2 as an intervention and treatment.

Characterization of the Retinal Microvasculature and FAZ Changes in Ischemic Stroke and Its Different Types.

PurposeThis study aimed to assess morphological changes in the retinal microvasculature and foveal avascular zone (FAZ) in patients with ischemic stroke and its different subtypes.MethodsThirty-three patients with ischemic stroke (14 with nonlacunar infarction and 19 with lacunar infarction) and 27 control participants were enrolled in this study. Based on optical coherence tomography angiography (OCTA), three vascular parameters, including vascular area density, vascular fractal dimension (VFD), and vascular orientation distribution (VOD), and four FAZ-related parameters, including FAZ area, FAZ axis ratio (FAR), FAZ circularity (FC), and FAZ roundness, in the superficial capillary plexus (SCP) and deep capillary plexus (DCP) were extracted and analyzed.ResultsLogistic regression results showed that worse best-corrected visual acuity (odds ratio [OR], 0.21), higher FAR (OR, 2.77) and lower FC (OR, 0.36) of the DCP were associated with ischemic stroke. Furthermore, lower VOD of the SCP was significantly associated with lacunar infarction compared with nonlacunar infarction.ConclusionsOur study shows that the FAR and FC of the DCP may be potential biomarkers of ischemic stroke. Moreover, we demonstrated that OCT showed specific damage patterns in retinal microvascular and macular morphology in different subtypes of ischemic stroke.Translational RelevanceThis work lays the foundation for the pathophysiological characteristics of cerebrovascular diseases assisted by retinal imaging and artificial intelligence.