Effect of PEAR1, PTGS1 gene polymorphisms on the recurrence of aspirin-treated patients with ischemic stroke in the Han population of China: A 4-year follow-up study.

Platelet endothelial aggregation receptor 1 (PEAR1) and prostaglandin endoperoxide synthase 1 (PTGS1) polymorphisms can affect laboratory aspirin resistance. However, the impact of genetic polymorphisms on the recurrence of ischemic stroke (IS) patients treated with aspirin is not fully understood. This study aimed to examine the relationship between gene polymorphisms of PEAR1 and PTGS1 and IS recurrence in patients treated with aspirin. Peripheral blood samples were collected from 174 patients with nonrecurrent IS and 34 with recurrent IS after aspirin treatment. Follow-up was performed on all patients. PEAR1 rs12041331 and PTGS1 rs10306114 polymorphisms were determined using the PCR fluorescence probe method. And the correlations of them with the clinical characteristics were examined by multivariable logistic regression analysis. The distribution frequencies of PEAR1 rs12041331 and PTGS1 rs10306114 genotypes were in Hardy-Weinberg equilibrium, and there was no significant difference in the distribution of PEAR1 rs12041331 polymorphism. Compared to the nonrecurrent group, the AA genotype of the PTGS1 polymorphism was more frequent in the recurrent group (59.77% vs 35.29%, P = .003), and the A allele also showed a higher frequency than the G allele in the recurrent group (P = .001). Multivariable logistic regression analysis showed that smoking (OR = 5.228, 95% CI: 1.938-14.102, P = .001), coronary heart disease (OR = 4.754, 95% CI: 1.498-15.089, P = .008), and the polymorphism at PTGS1(A>G) AA/AG + GG (OR = 2.955, 95% CI: 1.320-6.616, P = .008) were independently associated with IS recurrence in Chinese patients. Our findings suggested that PTGS rs10306114 polymorphisms should receive more attention in the use of aspirin in patients with IS.

The causal relationship between sarcopenia-related traits and ischemic stroke: Insights from univariable and multivariable Mendelian randomization analyses.

AIMS: The causal relationship between sarcopenia-related traits and ischemic stroke (IS) remains poorly understood. This study aimed to explore the causal impact of sarcopenia-related traits on IS and to identify key mediators of this association. METHODS: We conducted univariable, multivariable two-sample, and two-step Mendelian randomization (MR) analyses using genome-wide association study (GWAS) data. This included data for appendicular lean mass (ALM), hand grip strength (HGS), and usual walking pace (UWP) from the UK Biobank, and IS data from the MEGASTROKE consortium. Additionally, 21 candidate mediators were analyzed based on their respective GWAS data sets. RESULTS: Each 1-SD increase in genetically proxied ALM was associated with a 7.5% reduction in the risk of IS (95% CI: 0.879-0.974), and this correlation remained after controlling for levels of physical activity and adiposity-related indices. Two-step MR identified that six mediators partially mediated the protective effect of higher ALM on IS, with the most significant being coronary heart disease (CHD, mediating proportion: 39.94%), followed by systolic blood pressure (36.51%), hypertension (23.87%), diastolic blood pressure (15.39%), type-2 diabetes mellitus (T2DM, 12.71%), and low-density lipoprotein cholesterol (7.97%). CONCLUSION: Our study revealed a causal protective effect of higher ALM on IS, independent of physical activity and adiposity-related indices. Moreover, we found that higher ALM could reduce susceptibility to IS partially by lowering the risk of vascular risk factors, including CHD, hypertension, T2DM, and hyperlipidemia. In brief, we elucidated another modifiable factor for IS and implied that maintaining sufficient muscle mass may reduce the risk of such disease.

Integrated analysis of single cell-RNA sequencing and Mendelian randomization identifies lactate dehydrogenase B as a target of melatonin in ischemic stroke.

AIMS: Despite the success of single-cell RNA sequencing in identifying cellular heterogeneity in ischemic stroke, clarifying the mechanisms underlying these associations of differently expressed genes remains challenging. Several studies that integrate gene expression and gene expression quantitative trait loci (eQTLs) with genome wide-association study (GWAS) data to determine their causal role have been proposed. METHODS: Here, we combined Mendelian randomization (MR) framework and single cell (sc) RNA sequencing to study how differently expressed genes (DEGs) mediating the effect of gene expression on ischemic stroke. The hub gene was further validated in the in vitro model. RESULTS: We identified 2339 DEGs in 10 cell clusters. Among these DEGs, 58 genes were associated with the risk of ischemic stroke. After external validation with eQTL dataset, lactate dehydrogenase B (LDHB) is identified to be positively associated with ischemic stroke. The expression of LDHB has also been validated in sc RNA-seq with dominant expression in microglia and astrocytes, and melatonin is able to reduce the LDHB expression and activity in vitro ischemic models. CONCLUSION: Our study identifies LDHB as a novel biomarker for ischemic stroke via combining the sc RNA-seq and MR analysis.

Genetically predicted type 2 diabetes mellitus mediates the causal association between plasma uric acid and ischemic stroke.

OBJECTIVE: This study conducts a systematic investigation into the causal relationships between plasma uric acid levels and subtypes of ischemic stroke (IS), as well as the extent to which Type 2 diabetes mellitus (T2DM) mediates this relationship. BACKGROUND: There is a known association between Uric acid and IS but whether they have a causal relationship remains unclear. This study aims to determine whether a genetic predisposition to uric acid is causally linked to IS, including three subtypes, and to determine the mediating role of T2DM. METHODS: Bidirectional Mendelian randomization (MR) analyses was initially used to explore the causal relationship between uric acid and three subtypes of IS. Two-step MR methods were then used to investigate the role of T2DM in mediating the effect of uric acid and IS with its subtypes. RESULTS: A primary analysis showed uric acid had a markedly causal association with IS (IVW, OR 1.23; 95 % CI, 1.13 - 1.34; p = 6.39 × 10-9), and two subtypes of IS, Large-vessel atherosclerotic stroke LAS (IVW, OR 1.25; 95 % CI, 1.03 - 1.53; p = 0.026) and small vessel stroke (SVS) (IVW, OR 1.20; 95 % CI, 1.00 - 1.43; p = 0.049), but not with cardioembolic stroke (CES)(IVW, OR 1.00; 95 % CI, 0.87 - 1.15; p = 0.993). Two-step MR results showed that T2DM mediated the association between uric acid and LAS and SVS, accounting for 13.85 % (p = 0.025) and 13.57 % (p = 0.028), respectively. CONCLUSIONS: The study suggests that genetic predisposition to uric acid is linked to a greater risk of IS, especially LAS and SVS. T2DM might mediate a significant proportion of the associations between uric acid and LAS as well as SVS.

Bayesian colocalization of GWAS and eQTL signals reveals cell type-specific genes and regulatory variants for susceptibility to subtypes of ischemic stroke.

A colocalization analysis of genome-wide association study (GWAS) signals and expression quantitative trait loci (eQTL) was conducted to pinpoint target genes and their regulatory nucleotide variants for subtypes of ischemic stroke. We utilized GWAS data from prominent meta-analysis consortia (MEGASTROKE and GIGASTROKE) and single-cell eQTL data in brain and blood tissues to enhance accuracy and minimize noise inherent in bulk RNA-seq. Employing Bayesian colocalization methods, we identified ten shared loci between GWAS and eQTL signals, targeting five eGenes. Specifically, RAPH1 and ICA1L were discovered for small vessel stroke (SVS), whereas SCYL3, CAV1, and CAV2 were for cardioembolic stroke (CS). However, no findings have been made for large artery stroke. The exploration and subsequent functional analysis of causal variants within the colocalized regions revealed their regulatory roles, particularly as enhancer variants (e.g., rs144505847 and rs72932755 targeting ICA1L; rs629234 targeting SCYL3; rs3807989 targeting CAV1 and CAV2). Notably, our study unveiled that all eQTL for CS were identified in oligodendrocytes, while those for SVS were across excitatory neurons, astrocytes, and oligodendrocyte precursor cells. This underscores the heterogeneous tissue-specific genetic factors by subtypes of ischemic stroke. The study emphasizes the need for intensive research efforts to discover causative genes and variants, unravelling the cell type-specific genetic architecture of ischemic stroke subtypes. This knowledge is crucial for advancing our understanding of the underlying pathophysiology and paving the way for precision neurology applications.

Exploring the "gene-metabolite" network of ischemic stroke with blood stasis and toxin syndrome by integrated transcriptomics and metabolomics strategy.

A research model combining a disease and syndrome can provide new ideas for the treatment of ischemic stroke. In the field of traditional Chinese medicine, blood stasis and toxin (BST) syndrome is considered an important syndrome seen in patients with ischemic stroke (IS). However, the biological basis of IS-BST syndrome is currently not well understood. Therefore, this study aimed to explore the biological mechanism of IS-BST syndrome. This study is divided into two parts: (1) establishment of an animal model of ischemic stroke disease and an animal model of BST syndrome in ischemic stroke; (2) use of omics methods to identify differentially expressed genes and metabolites in the models. We used middle cerebral artery occlusion (MCAO) surgery to establish the disease model, and utilized carrageenan combined with active dry yeast and MCAO surgery to construct the IS-BST syndrome model. Next, we used transcriptomics and metabolomics methods to explore the differential genes and metabolites in the disease model and IS-BST syndrome model. It is found that the IS-BST syndrome model exhibited more prominent characteristics of IS disease and syndrome features. Both the disease model and the IS-BST syndrome model share some common biological processes, such as thrombus formation, inflammatory response, purine metabolism, sphingolipid metabolism, and so on. Results of the "gene-metabolite" network revealed that the IS-BST syndrome model exhibited more pronounced features of complement-coagulation cascade reactions and amino acid metabolism disorders. Additionally, the "F2 (thrombin)-NMDAR/glutamate" pathway was coupled with the formation process of the blood stasis and toxin syndrome. This study reveals the intricate mechanism of IS-BST syndrome, offering a successful model for investigating the combination of disease and syndrome.

Microglial CMPK2 promotes neuroinflammation and brain injury after ischemic stroke.

Neuroinflammation plays a significant role in ischemic injury, which can be promoted by oxidized mitochondrial DNA (Ox-mtDNA). Cytidine/uridine monophosphate kinase 2 (CMPK2) regulates mtDNA replication, but its role in neuroinflammation and ischemic injury remains unknown. Here, we report that CMPK2 expression is upregulated in monocytes/macrophages and microglia post-stroke in humans and mice, respectively. Microglia/macrophage CMPK2 knockdown using the Cre recombination-dependent adeno-associated virus suppresses the inflammatory responses in the brain, reduces infarcts, and improves neurological outcomes in ischemic CX3CR1Cre/ERT2 mice. Mechanistically, CMPK2 knockdown limits newly synthesized mtDNA and Ox-mtDNA formation and subsequently blocks NLRP3 inflammasome activation in microglia/macrophages. Nordihydroguaiaretic acid (NDGA), as a CMPK2 inhibitor, is discovered to reduce neuroinflammation and ischemic injury in mice and prevent the inflammatory responses in primary human monocytes from ischemic patients. Thus, these findings identify CMPK2 as a promising therapeutic target for ischemic stroke and other brain disorders associated with neuroinflammation.

A combined observational and Mendelian randomization investigation reveals NMR-measured analytes to be risk factors of major cardiovascular diseases.

Dyslipidaemias is the leading risk factor of several major cardiovascular diseases (CVDs), but there is still a lack of sufficient evidence supporting a causal role of lipoprotein subspecies in CVDs. In this study, we comprehensively investigated several lipoproteins and their subspecies, as well as other metabolites, in relation to coronary heart disease (CHD), heart failure (HF) and ischemic stroke (IS) longitudinally and by Mendelian randomization (MR) leveraging NMR-measured metabolomic data from 118,012 UK Biobank participants. We found that 123, 110 and 36 analytes were longitudinally associated with myocardial infarction, HF and IS (FDR < 0.05), respectively, and 25 of those were associated with all three outcomes. MR analysis suggested that genetically predicted levels of 70, 58 and 7 analytes were associated with CHD, HF and IS (FDR < 0.05), respectively. Two analytes, ApoB/ApoA1 and M-HDL-C were associated with all three CVD outcomes in the MR analyses, and the results for M-HDL-C were concordant in both observational and MR analyses. Our results implied that the apoB/apoA1 ratio and cholesterol in medium size HDL were particularly of importance to understand the shared pathophysiology of CHD, HF and IS and thus should be further investigated for the prevention of all three CVDs.

[Mechanism and compatibility efficacy of Astragali Radix-Chuanxiong Rhizoma drug pair in treating ischemic stroke based on network regulation].

Based on the association network of "drug pair-disease", the effect characteristics of Astragali Radix-Chuanxiong Rhizoma drug pair in the treatment of ischemic stroke(IS) with Qi deficiency and blood stasis and the matching mechanism of the two were explored. Through Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP) and SwissTargetPrediction Database, the effective chemical components of the drug pair were screened, and the candidate targets were predicted. Databa-ses such as GeneCards, DrugBank, Online Mendelian Inheritance in Man(OMIM), and Therapeutic Target Database(TTD) were searched to obtain gene targets related to IS. Through STRING and Cytoscape 3.9.1 software, the protein-protein interaction(PPI) network was constructed by using the interaction information of disease syndrome-related genes and candidate targets of drug pairs, and the core targets were screened according to the network topological feature values. Based on the Metascape platform and DAVID database, the biomolecular interaction information was integrated to analyze the Kyoto Encyclopedia of Genes and Genomes(KEGG) and mine biological functions, so as to further explore the mechanism of action and compatibility characteristics of Astragali Radix-Chuan-xiong Rhizoma. The results showed that the candidate biological process was mainly involved in the regulation of functional modules such as immune, blood circulation, neurotransmitter, and oxidative stress, and it was enriched in lipid and atherosclerosis, calcium signaling pathway, and platelet activation. Astragali Radix and Chuanxiong Rhizoma have their own characteristics. Astragali Radix has a regulatory response to growth factors while maintaining the body's immune balance, while Chuanxiong Rhizoma mainly improves the circulatory system and participates in hormone metabolism, so as to indicate the compatibility mechanism of Astragali Radix-Chuanxiong Rhizoma drug pair for multi-target and multi-pathway synergistic treatment of IS. Through further experimental verification, it was found that the Astragali Radix-Chuanxiong Rhizoma drug pair could significantly down-regulate the expression of key targets including TLR4, NF-κB, IL-1ß, F2R, PLCß1, and MYLK. This study preliminarily reveals that the Astragali Radix-Chuanxiong Rhizoma drug pair may play the three replenishing effects of promoting blood circulation, benefiting Qi, and clearing collaterals by correcting immune di-sorders, blood circulation disorders, and inflammation, which provide support for the clinical research on the subsequent improvement of Qi deficiency and blood stasis in the treatment of IS and provide a new idea for the analysis of modern biological connotation of the compatibility of seven emotions of traditional Chinese medicine.

Associations Between Genetically Predicted Iron Status and Cardiovascular Disease Risk: A Mendelian Randomization Study.

BACKGROUND: Mendelian randomization (MR) studies suggest a causal effect of iron status on cardiovascular disease (CVD) risk, but it is unknown if these associations are confounded by pleiotropic effects of the instrumental variables on CVD risk factors. We aimed to investigate the effect of iron status on CVD risk controlling for CVD risk factors. METHODS AND RESULTS: Iron biomarker instrumental variables (total iron-binding capacity [n=208 422], transferrin saturation [n=198 516], serum iron [n=236 612], ferritin [n=257 953]) were selected from a European genome-wide association study meta-analysis. We performed 2-sample univariate MR of each iron trait on CVD outcomes (all-cause ischemic stroke, cardioembolic ischemic stroke, large-artery ischemic stroke, small-vessel ischemic stroke, and coronary heart disease) from MEGASTROKE (n=440 328) and CARDIoGRAMplusC4D (Coronary Artery Disease Genome Wide Replication and Meta-Analysis Plus the Coronary Artery Disease Genetics) (n=183 305). We then implemented multivariate MR conditioning on 7 CVD risk factors from independent European samples to evaluate their potential confounding or mediating effects on the observed iron-CVD associations. With univariate MR analyses, we found higher genetically predicted iron status to be associated with a greater risk of cardioembolic ischemic stroke (transferrin saturation: odds ratio, 1.17 [95% CI, 1.03-1.33]; serum iron: odds ratio, 1.21 [95% CI, 1.02-1.44]; total iron-binding capacity: odds ratio, 0.81 [95% CI, 0.69-0.94]). The detrimental effects of iron status on cardioembolic ischemic stroke risk remained unaffected when adjusting for CVD risk factors (all P<0.05). Additionally, we found diastolic blood pressure to mediate between 7.1 and 8.8% of the total effect of iron status on cardioembolic ischemic stroke incidence. Univariate MR initially suggested a protective effect of iron status on large-artery stroke and coronary heart disease, but controlling for CVD factors using multivariate MR substantially diminished these associations (all P>0.05). CONCLUSIONS: Higher iron status was associated with a greater risk of cardioembolic ischemic stroke independent of CVD risk factors, and this effect was partly mediated by diastolic blood pressure. These findings support a role of iron status as a modifiable risk factor for cardioembolic ischemic stroke.

Causal effects of immune cell surface antigens and functional outcome after ischemic stroke: a Mendelian randomization study.

Objective: While observational studies link immune cells with post-stroke functional outcome, the underlying immune mechanisms are not well understood. Immune cell surface antigens are actively involved in the biological behavior of immune cells, investigating immune cell surface antigens could deepen our comprehension of their role and biological processes in stroke recovery. Therefore, we aimed to investigate the immunological basis of stroke outcome by exploring the causal relationship between immune cell surface antigens and functional outcome after ischemic stroke in a Mendelian randomization study. Methods: Genetic variants related to immune cell surface antigens and post-stroke functional outcome were selected for two-sample Mendelian randomization (MR) analysis. 389 fluorescence intensities (MFIs) with surface antigens were included. Inverse variance weighted (IVW) modeling was used as the primary MR method to estimate the causal effect of exposure on the outcome, followed by several alternative methods and sensitivity analyses. Additional analysis of the association between immune cell surface antigens and risk of ischemic stroke for assessment of collider bias. Results: We found that suggestive associations between CD20 on switched memory B cell (OR = 1.16, 95% CI: 1.01-1.34, p = 0.036) and PDL-1 on monocyte (OR = 1.32, 95% CI: 1.04-1.66, p = 0.022) and poor post-stroke functional outcome, whereas CD25 on CD39+ resting Treg (OR = 0.77, 95% CI: 0.62-0.96, p = 0.017) was suggestively associated with good post-stroke functional outcome. Conclusion: The elevated CD20 on switched memory B cell, PDL-1 on monocyte, and CD25 on CD39+ resting Treg may be novel biomarkers and potential causal factors influencing post-stroke functional outcome.

Knockdown of lncRNA AU020206 could inhibit microglia apoptosis in ischemic stroke.

The diagnostic biomarkers associated with ischemic stroke (IS) that may have clinical utility remain elucidated. Thus, the potential functional lncRNAs in IS were explored. The Gene Expression Omnibus database provided the transcriptome profile of IS for download. WGCNA analysis and integrated bioinformatics were used to find genes that were differentially expressed (DEGs). The Starbase database created the lncRNA-based ceRNA network. In order to investigate the molecular mechanism and involved pathways of DEGs in IS, functional enrichment analysis was carried out. Using qRT-PCR, lncRNAs identified as putative IS biomarkers were confirmed to be expressed in a permanent middle cerebral artery occlusion (MCAO) model. Using the annexin V/PI apoptosis test, the amount of apoptosis in oxygen-glucose deprivation (OGD) cells was measured. A total of 1600 common differentially expressed - protein-coding RNA (DE-pcRNAs) and 26 DE-lncRNAs were identified. The results of enrichment analysis indicate that the cytokine may be regulated by common DE-pcRNAs and are vital in the progress of IS. A lncRNAs-mediated ceRNA network including lncRNAs AU020206, Brip1os, F630028O10Rik and 9530082P21Rik was constructed. The expression of these lncRNAs was significantly increased in MCAO model. Knockdown of lncRNA AU020206 inhibited microglia apoptosis in OGD cell model. We constructed a lncRNAs-mediated ceRNA network and found that lncRNA AU020206 inhibited microglia apoptosis in OGD cell model. These findings provided further evidence for the diagnosis and a novel avenue for targeted therapy of IS.

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.

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.

ATF3 is a neuron-specific biomarker for spinal cord injury and ischaemic stroke.

BACKGROUND: Although many molecules have been investigated as biomarkers for spinal cord injury (SCI) or ischemic stroke, none of them are specifically induced in central nervous system (CNS) neurons following injuries with low baseline expression. However, neuronal injury constitutes a major pathology associated with SCI or stroke and strongly correlates with neurological outcomes. Biomarkers characterized by low baseline expression and specific induction in neurons post-injury are likely to better correlate with injury severity and recovery, demonstrating higher sensitivity and specificity for CNS injuries compared to non-neuronal markers or pan-neuronal markers with constitutive expressions. METHODS: In animal studies, young adult wildtype and global Atf3 knockout mice underwent unilateral cervical 5 (C5) SCI or permanent distal middle cerebral artery occlusion (pMCAO). Gene expression was assessed using RNA-sequencing and qRT-PCR, while protein expression was detected through immunostaining. Serum ATF3 levels in animal models and clinical human samples were measured using commercially available enzyme-linked immune-sorbent assay (ELISA) kits. RESULTS: Activating transcription factor 3 (ATF3), a molecular marker for injured dorsal root ganglion sensory neurons in the peripheral nervous system, was not expressed in spinal cord or cortex of naïve mice but was induced specifically in neurons of the spinal cord or cortex within 1 day after SCI or ischemic stroke, respectively. Additionally, ATF3 protein levels in mouse blood significantly increased 1 day after SCI or ischemic stroke. Importantly, ATF3 protein levels in human serum were elevated in clinical patients within 24 hours after SCI or ischemic stroke. Moreover, Atf3 knockout mice, compared to the wildtype mice, exhibited worse neurological outcomes and larger damage regions after SCI or ischemic stroke, indicating that ATF3 has a neuroprotective function. CONCLUSIONS: ATF3 is an easily measurable, neuron-specific biomarker for clinical SCI and ischemic stroke, with neuroprotective properties. HIGHLIGHTS: ATF3 was induced specifically in neurons of the spinal cord or cortex within 1 day after SCI or ischemic stroke, respectively. Serum ATF3 protein levels are elevated in clinical patients within 24 hours after SCI or ischemic stroke. ATF3 exhibits neuroprotective properties, as evidenced by the worse neurological outcomes and larger damage regions observed in Atf3 knockout mice compared to wildtype mice following SCI or ischemic stroke.

Transcriptomic Analysis of Extracellular Vesicles in the Search for Novel Plasma and Thrombus Biomarkers of Ischemic Stroke Etiologies.

Accurate etiologic diagnosis provides an appropriate secondary prevention and better prognosis in ischemic stroke (IS) patients; still, 45% of IS are cryptogenic, urging us to enhance diagnostic precision. We have studied the transcriptomic content of plasma extracellular vesicles (EVs) (n = 21) to identify potential biomarkers of IS etiologies. The proteins encoded by the selected genes were measured in the sera of IS patients (n = 114) and in hypertensive patients with (n = 78) and without atrial fibrillation (AF) (n = 20). IGFBP-2, the most promising candidate, was studied using immunohistochemistry in the IS thrombi (n = 23) and atrium of AF patients (n = 13). In vitro, the IGFBP-2 blockade was analyzed using thromboelastometry and endothelial cell cultures. We identified 745 differentially expressed genes among EVs of cardioembolic, atherothrombotic, and ESUS groups. From these, IGFBP-2 (cutoff > 247.6 ng/mL) emerged as a potential circulating biomarker of embolic IS [OR = 8.70 (1.84-41.13) p = 0.003], which was increased in patients with AF vs. controls (p < 0.001) and was augmented in cardioembolic vs. atherothrombotic thrombi (p < 0.01). Ex vivo, the blockage of IGFBP-2 reduced clot firmness (p < 0.01) and lysis time (p < 0.001) and in vitro, diminished endothelial permeability (p < 0.05) and transmigration (p = 0.06). IGFBP-2 could be a biomarker of embolic IS and a new therapeutic target involved in clot formation and endothelial dysfunction.

Brain-Derived Exosomal CircRNAs in Plasma Serve as Diagnostic Biomarkers for Acute Ischemic Stroke.

Acute ischemic stroke (AIS), commonly known as stroke, is a debilitating condition characterized by the interruption of blood flow to the brain, resulting in tissue damage and neurological deficits. Early diagnosis is crucial for effective intervention and management, as timely treatment can significantly improve patient outcomes. Therefore, novel methods for the early diagnosis of AIS are urgently needed. Several studies have shown that bioactive molecules contained in extracellular vesicles, especially circRNAs, could be ideal markers for the diagnosis of many diseases. However, studies on the effects of exosomes and their circRNAs on the development and prognosis of AIS have not been reported extensively. Therefore, we explored the feasibility of using circRNAs in plasma brain-derived exosomes as biomarkers for AIS. By high-throughput sequencing, we first identified 358 dysregulated circRNAs (including 23 significantly upregulated circRNAs and 335 significantly downregulated circRNAs) in the plasma brain-derived exosomes of the brain infarct patient group compared to those of the noninfarct control group. Five upregulated circRNAs (hsa_circ_0007290, hsa_circ_0049637, hsa_circ_0000607, hsa_circ_0004808, and hsa_circ_0000097) were selected for further validation via Real-Time Quantitative Reverse Transcription PCR (qRT‒PCR) in a larger cohort based on the exclusion criteria of log2FC > 1, p < 0.05 and measurable expression. We found that the expression levels of hsa_circ_0007290, hsa_circ_0049637, hsa_circ_0000607, hsa_circ_0004808 and hsa_circ_0000097 were significantly upregulated in AIS patients and could serve as potential biomarkers for AIS with high specificity and sensitivity. Moreover, the expression levels of hsa_circ_0007290, hsa_circ_0049637, hsa_circ_0000607, hsa_circ_0004808 and hsa_circ_0000097 were also found to be positively correlated with National Institutes of Health Stroke Scale (NISS) and modified Rankin scale (mRS) scores, which indicated that the presence of these circRNAs in plasma brain-derived exosomes could also determine the progression of AIS.

Machine learning identifies novel coagulation genes as diagnostic and immunological biomarkers in ischemic stroke.

BACKGROUND: Coagulation system is currently known associated with the development of ischemic stroke (IS). Thus, the current study is designed to identify diagnostic value of coagulation genes (CGs) in IS and to explore their role in the immune microenvironment of IS. METHODS: Aberrant expressed CGs in IS were input into unsupervised consensus clustering to classify IS subtypes. Meanwhile, key CGs involved in IS were further selected by weighted gene co-expression network analysis (WGCNA) and machine learning methods, including random forest (RF), support vector machine (SVM), generalized linear model (GLM) and extreme-gradient boosting (XGB). The diagnostic performance of key CGs were evaluated by receiver operating characteristic (ROC) curves. At last, quantitative PCR (qPCR) was performed to validate the expressions of key CGs in IS. RESULTS: IS patients were classified into two subtypes with different immune microenvironments by aberrant expressed CGs. Further WGCNA, machine learning methods and ROC curves identified ACTN1, F5, TLN1, JMJD1C and WAS as potential diagnostic biomarkers of IS. In addition, their expressions were significantly correlated with macrophages, neutrophils and/or T cells. GSEA also revealed that those biomarkers may regulate IS via immune and inflammation. Moreover, qPCR verified the expressions of ACTN1, F5 and JMJD1C in IS. CONCLUSIONS: The current study identified ACTN1, F5 and JMJD1C as novel coagulation-related biomarkers associated with IS immune microenvironment, which enriches our knowledge of coagulation-mediated pathogenesis of IS and sheds light on next-step in vivo and in vitro experiments to elucidate the relevant molecular mechanisms.

Molecular subtype identification of cerebral ischemic stroke based on ferroptosis-related genes.

Cerebral ischemic stroke (CIS) has the characteristics of a high incidence, disability, and mortality rate. Here, we aimed to explore the potential pathogenic mechanisms of ferroptosis-related genes (FRGs) in CIS. Three microarray datasets from the Gene Expression Omnibus (GEO) database were utilized to analyze differentially expressed genes (DEGs) between CIS and normal controls. FRGs were obtained from a literature report and the FerrDb database. Weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network were used to screen hub genes. The receiver operating characteristic (ROC) curve was adopted to evaluate the diagnostic value of key genes in CIS, followed by analysis of immune microenvironment, transcription factor (TF) regulatory network, drug prediction, and molecular docking. In total, 128 CIS samples were divided into 2 subgroups after clustering analysis. Compared with cluster A, 1560 DEGs were identified in cluster B. After the construction of the WGCNA and PPI network, 5 hub genes, including MAPK3, WAS, DNAJC5, PRKCD, and GRB2, were identified for CIS. Interestingly, MAPK3 was a FRG that differentially expressed between cluster A and cluster B. The expression levels of 5 hub genes were all specifically highly in cluster A subtype. It is noted that neutrophils were the most positively correlated with all 5 real hub genes. PRKCD was one of the target genes of FASUDIL. In conclusion, five real hub genes were identified as potential diagnostic markers, which can distinguish the two subtypes well.