Blood-Based Biomarkers Are Associated with Different Ischemic Stroke Mechanisms and Enable Rapid Classification between Cardioembolic and Atherosclerosis Etiologies

Integrative Multi-Omics Analysis for Etiology Classification and Biomarker Discovery in Stroke: Advancing towards Precision Medicine

Recent advancements in high-throughput omics technologies have opened new avenues for investigating stroke at the molecular level and elucidating the intricate interactions among various molecular components. We present a novel approach for multi-omics data integration on knowledge graphs and have applied it to a stroke etiology classification task of 30 stroke patients through the integrative analysis of DNA methylation and mRNA, miRNA, and circRNA. This approach has demonstrated promising performance as compared to other existing single technology approaches.

Inflammation biomarkers in acute ischemic stroke according to different etiologies

BACKGROUND

High throughput technologies provide new opportunities to further investigate the pathophysiology of ischemic strokes. The present cross-sectional study aimed to evaluate potential associations between the etiologic subtypes of ischemic stroke and blood-based proteins.

METHODS

We investigated the associations between ischemic stroke subtypes and a panel of circulating inflammation biomarkers in 364 patients included in the Stroke Cohort Augsburg (SCHANA). Stroke etiologies were categorized according to the TOAST (Trial of Org 10172 in Acute Stroke Treatment) classification. Serum concentrations of 52 biomarkers were measured using the Bio-Plex Pro™ Human Cytokine Screening Panel, ICAM-1 set and VCAM-1 set, plus the Pro™ Human TH17 cytokine sCD40L set and IL31 set (all Bio-Rad, USA). Multivariable linear regression models were used to examine associations. Point estimates were calculated as the mean difference inσ -standardized cytokine levels on the log2 -scale.

RESULTS

Stromal-cell-derived-factor 1 alpha (SDF-1a) showed significantly higher serum levels in cardioembolic compared with large vessel atherosclerotic stroke (β = 0.48; 95% CI 0.22; 0.75; Padj  = 0.036). Significantly lower levels of interleukin-6 (IL-6) (β = -0.53; 95% CI -0.84; -0.23; Padj  = 0.036) and macrophage migration inhibitory factor (MIF) (β = -0.52; 95% CI -0.84; -0.21; Padj  = 0.043) were found in the small vessel versus large vessel stroke subtype.

CONCLUSIONS

Immune dysregulations observed in different stroke subtypes might help uncover pathophysiological mechanisms of the disease. Further studies are needed to validate identified biomarkers in diverse study populations before they can potentially be used in clinical practice to further improve stroke management and patient outcomes.

Sex differences in diagnostic modalities of atherosclerosis in the macrocirculation

Asymptomatic atherosclerosis begins early in life and may progress in a sex-specific manner to become the major cause of cardiovascular morbidity and death. As diagnostic tools to evaluate atherosclerosis in the macrocirculation, we discuss imaging methods (in terms of computed tomography, positron emission tomography, intravascular ultrasound, magnetic resonance imaging, and optical coherence tomography), along with derived scores (Agatston, Gensini, Leaman, Syntax), and also hemodynamic indices of vascular stiffness (including flow-mediated dilation, shear stress, pulse pressure, augmentation index, arterial distensibility), assessment of plaque properties (composition, erosion, rupture), stenosis measures such as fractional flow reserve. Moreover, biomarkers including matrix metalloproteinases, vascular endothelial growth factors and miRNAs, as well as the impact of machine learning support, are described. Special attention is given to age-related aspects and sex-specific characteristics, along with clinical implications. Knowledge gaps are identified and directions for future research formulated.

Advances in Cardiac Workup for Transient Ischemic Attack: Improving Diagnostic Yield and Reducing Recurrent Stroke Risk

Transient ischemic attack (TIA) is a warning sign for an impending stroke, with a 10-20% chance of a stroke occurring within 90 days of the initial event. Current clinical practice for cardiac workup in TIA includes cardiac enzymes, with 12-lead electrocardiogram, transthoracic echocardiography, and 24-hour Holter monitoring. However, the diagnostic yield of these investigations is variable, and there is a need for better diagnostic approaches to increase the detection of cardiac abnormalities in a cost-effective way. This review article examines the latest research on emerging diagnostic tools and strategies and discusses the potential benefits and challenges of using these advanced diagnostic approaches in clinical practice. Novel biomarkers, imaging techniques, and prolonged rhythm monitoring devices have shown great promise in enhancing the diagnostic yield of cardiac workup in TIA patients. Echocardiography, Transcranial Doppler ultrasound, cardiac MRI, and cardiac CT are among the promising diagnostic tools being studied. We conclude the article with a suggested diagnostic algorithm for cardiac workup in TIA. Further research is necessary to enhance their usefulness and to outline future directions for research and clinical practice in this field.

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.

Inhibition of Oxidative Stress: An Important Molecular Mechanism of Chinese Herbal Medicine (Astragalus membranaceus, Carthamus tinctorius L., Radix Salvia Miltiorrhizae, etc.) in the Treatment of Ischemic Stroke by Regulating the Antioxidant System

Ischemic stroke is a severe cerebrovascular disease with high mortality and morbidity. Traditional Chinese medicine (TCM) has been utilized for thousands of years in China and is becoming increasingly popular all over the world, especially for the treatments of ischemic stroke. More and more evidences have implicated that oxidative stress has been closely related with ischemic stroke. This review will concentrate on the evidence of the action mechanism of Chinese herbal medicine and its active ingredient in preventing ischemic stroke by modulating redox signaling and oxidative stress pathways and providing references for clinical treatment and scientific research applications.

Association of Interleukin-6-174G/C Polymorphism With Ischemic Stroke: An Updated Meta-Analysis

Background: Although numerous epidemiological studies have investigated the association between −174G/C(rs1800795) polymorphism in the interleukin-6 (IL-6) gene-stimulatory region and the risk of ischemic stroke (IS), they failed to reach a unified conclusion. The true relationship between −174G/C(rs1800795) polymorphism and IS remains controversial and unclear. Therefore, in this meta-analysis, we aimed to analyze more precisely the association between −174G/C(rs1800795) single-nucleotide polymorphism (SNP) of IL-6 gene and IS in a larger pooled population.

Methods: A comprehensive literature search was performed in PubMed, Web of Science, and the Cochrane Central Register of Controlled Trials until June 30, 2021. A fixed or random-effects model was utilized based on heterogeneity between studies. The odds ratios (ORs) and 95% confidence intervals (Cis) were calculated in the models of allele comparison (G vs. C), homozygote comparison (GG vs. CC) and (GC vs. CC), dominant (GG vs. GC + CC), hyper dominant (GG + CC vs. GC), and recessive (GG + GC vs. CC) to determine the strength of associations.

Results: This meta-analysis included 13 case-control studies in 35 articles with 5,548 individuals. Overall, no significant associations between IL-6 −174G/C(rs1800795) and IS were identified (G vs. C:OR [95% CI] = 0.99 [0.81, 1.21], P = 0.91; GG + CC vs. GC:0.97 [0.85, 1.11], P = 0.66; GG vs. GC + CC: 1.01 [0.81, 1.25], P = 0.94; GC vs. CC: OR [95% CI] = 1.01 [0.68, 1.5], P = 0.96; GG vs. CC:0.93 [0.57, 1.51], P = 0.76; GG + GC vs. CC:0.97 [0.64, 1.47], P = 0.89). In the subgroup analyses by ethnicity or HWE P-value, there was a statistically significant association between IL-6 −174G/C(rs1800795) polymorphisms and IS in the alleles model; (G vs. C: LogOR [95% CI] = 0.14 [−0.16,.45], P = 0.00), homozygote model (GG vs. CC: LogOR [95% CI] = 0.18 [−0.58,.95], P = 0.00) and (GC vs. CC: LogOR [95% CI] = 0.2 [−0.46,.85], P = 0.00), dominant model (GG vs. GC + CC: OR [95% CI] = 0.02 [−0.72, 0.77], P = 0.00), and recessive model (GG + GC vs. CC: OR [95% CI]= −0.17 [−0.86,.52], P = 0.00) of the European population and in the dominant model (GG vs. GC + CC: OR [95% CI] = −0.13 [−0.51, 0.24]) of the Asian population. No statistical significance was identified in both six models of HWE p ≥ 0.2 group (both P ≥ 0.05).

Conclusion: This meta-analysis revealed no correlation between IL-6 −174G/C(rs1800795) polymorphism and IS, whereas the subgroup analysis indicated that the relationship between IL-6 −174G/C(rs1800795) polymorphism and IS susceptibility varied significantly according to ethnicity and geography.

Mitochondrial repair as potential pharmacological target in cerebral ischemia

Cerebral ischemia and its consequences like transient ischemic attack, aneurysm and stroke are the common and devastating conditions which remain the leading cause of mortality after coronary heart disease in developed countries and are the greatest cause of disability, leaving 50% of survivors permanently disabled. Despite recognition of risk factors and mechanisms involved in the pathology of the disease, treatment of ischemic disorders is limited to thrombolytic drugs like recombinant tissue plasminogen activator (rt-PA) and clinical rendition of the neuroprotective agents have not been so successful. Recent studies evidenced the role of mitochondrial dysfunction in neuronal damage that occurred after cerebral ischemia. This review article will focus on the various fundamental mechanisms responsible for neuronal damage because of mitochondrial dysfunction including cell signaling pathways, autophagy, apoptosis/necrosis, generation of reactive oxygen species, calcium overload, the opening of membrane permeability transition pore (mPTP), mitochondrial dynamics and biogenesis. Recent studies have concerned the significant role of mitochondrial biogenesis in mitochondrial repair and transfer of healthy mitochondria from astrocytes to the damaged neurons, providing neuroprotection and neural recovery following ischemia. Novel and influential studies have evidenced the significant role of mitochondria transfer and mitochondrial transplantation in reviving cell energy and in replacement of impaired or dysfunctional mitochondria with healthy mitochondria after ischemic episode. This review article will focus on recent advances in mitochondrial interventions and exogenous therapeutic modalities like mitochondria transfer technique, employment of stem cells, mitochondrial transplantation, miRNA inhibition and mitochondrial-targeted Sirtuin1 activator for designing novel and promising treatment for cerebral ischemia induced pathological states.

DGAT2-MOGAT2 SNPs and Gene-Environment Interactions on Serum Lipid Profiles and the Risk of Ischemic Stroke

Background: The genetic susceptibility to ischemic stroke (IS) is still not well-understood. Recent genome-wide association studies (GWASes) found that several single nucleotide polymorphisms (SNPs) in the Diacylglycerol acyltransferase 2 gene (DGAT2) and monoacylglycerol O-acyltransferase 2 (MOGAT2) cluster were associated with serum lipid levels. However, the association between the DGAT2-MOGAT2 SNPs and serum lipid phenotypes has not yet been verified in the Chinese people. Therefore, the present study was to determine the DGAT2-MOGAT2 SNPs and gene-environment interactions on serum lipid profiles and the risk of IS. Methods: Genotyping of 5 SNPs (DGAT2 rs11236530, DGAT2 rs3060, MOGAT2 rs600626, MOGAT2 rs609379, and MOGAT2 rs10899104) in 544 IS patients and 561 healthy controls was performed by the next-generation sequencing technologies. The association between genotypes and serum lipid data was determined by analysis of covariance, and a corrected P-value was adopted after Bonferroni correction. Unconditional logistic regression analysis was performed to assess the association between genotypes and the risk of IS after adjustment of potential confounders. Results: The rs11236530A allele was associated with increased risk of IS (CA/AA vs. CC, OR = 1.45, 95%CI = 1.12-1.88, P = 0.0044), whereas the rs600626G-rs609379A-rs10899104G haplotype was associated with decreased risk of IS (adjusted OR = 0.67, 95% CI = 0.48-0.93, P = 0.018). The rs11236530A allele carriers had lower high-density lipoprotein cholesterol (HDL-C) concentrations than the rs11236530A allele non-carriers (P < 0.001). The interactions of rs11236530-smoking, rs3060-smoking and rs10899104-smoking influenced serum apolipoprotein B levels, whereas the interactions of rs11236530- and rs3060-alcohol affected serum HDL-C levels (P _I < 0.004-0.001). The interaction of rs600626G-rs609379A-rs10899104G-alcohol (OR = 0.41, 95% CI = 0.22-0.76) and rs600626G-rs609379C-rs10899104T-alcohol (OR = 0.12, 95% CI = 0.04-0.36) decreased the risk of IS (P _I < 0.0001). Conclusions: The rs11236530A allele was associated with decreased serum HDL-C levels in controls and increased risk of IS in patient group. The rs600626G-rs609379A-rs10899104G haplotype, the rs600626G-rs 609379A-rs10899104G-alcohol and rs600626G-rs609379C-rs10899104T-alcohol interactions were associated with decreased risk of IS. The rs11236530 SNP may be a genetic marker for IS in our study populations.

Carotid intima media thickness measurements coupled with stroke severity strongly predict short-term outcome in patients with acute ischemic stroke: a machine learning study

Acute ischemic stroke (IS) is one of the leading causes of morbidity, functional disability and mortality worldwide. The objective was to evaluate IS risk factors and imaging variables as predictors of short-term disability and mortality in IS. Consecutive 106 IS patients were enrolled. We examined the accuracy of IS severity using the National Institutes of Health Stroke Scale (NIHSS), carotid intima-media thickness (cIMT) and carotid stenosis (both assessed using ultrasonography with doppler) predicting IS outcome assessed with the modified Rankin scale (mRS) three months after hospital admission. Poor prognosis (mRS ≥ 3) at three months was predicted by carotid stenosis (≥ 50%), type 2 diabetes mellitus and NIHSS with an accuracy of 85.2% (sensitivity: 90.2%; specificity: 81.8%). The mRS score at three months was strongly predicted by NIHSS (β = 0.709, p < 0.001). Short-term mortality was strongly predicted using a neural network model with cIMT (≥ 1.0 mm versus < 1.0 mm), NIHSS and age, yielding an area under the receiving operator characteristic curve of 0.977 and an accuracy of 94.7% (sensitivity: 100.0%; specificity: 90.9%). High NIHSS (≥ 15) and cIMT (≥ 1.0 mm) increased the probability of dying with hazard ratios of 7.62 and 3.23, respectively. Baseline NIHSS was significantly predicted by the combined effects of age, large artery atherosclerosis stroke, sex, cIMT, body mass index, and smoking. In conclusion, high values of cIMT and NIHSS at admission strongly predict short-term functional impairment as well as mortality three months after IS, underscoring the importance of those measurements to predict clinical IS outcome.

Neutrophil to lymphocyte ratio and adverse clinical outcomes in patients with ischemic stroke

Background

Neutrophils and lymphocytes mediate differential inflammatory responses after ischemic stroke and have different effects on patients’ clinical outcomes. Several studies have used the neutrophil to lymphocyte ratio (NLR) as a prognostic indicator for ischemic stroke; however, some limitations remain.

Methods

We derived data from the Third China National Stroke Registry. The NLR is defined as neutrophil count/lymphocyte count. Patients included in the study were classified into four groups by NLR quartiles. Odds ratios (ORs) of adverse clinical outcomes were calculated with the lowest quartile group as the reference category. We plotted receiver operating characteristic (ROC) curves of NLR for adverse clinical outcomes and calculated area under the curve (AUC) values and cutoff values. Under different TOAST classifications, medians of NLR and ORs of adverse clinical outcomes were also calculated. Furthermore, interaction tests between NLR and etiology were performed.

Results

A total of 13,018 patients were enrolled. At both 3- and 12-month follow-ups, higher quartile groups were associated with increased risks of death and poor functional outcomes, even after adjustments. For death, the cutoff values of NLR were 3.872 at 3-month follow-up and 3.180 at 12-month follow-up. For poor functional outcomes, the cutoff value of NLR was 2.846 at both 3- and 12-month follow-ups. The association between NLR and stroke recurrence was significant only at 3-month follow-up before adjustments. There was no correlation between NLR and hemorrhagic transformation during hospitalization. Under different TOAST classifications, the medians of NLR were different; conversely, the correlations of NLR with adverse clinical outcomes had no differences.

Conclusions

High level of NLR within the first 24 h after admission was associated with increased risks of both short- and long-term adverse clinical outcomes in patients with ischemic stroke, regardless of etiology.

Immune-inflammatory, coagulation, adhesion, and imaging biomarkers combined in machine learning models improve the prediction of death 1 year after ischemic stroke

Some clinical, imaging, and laboratory biomarkers have been identified as predictors of prognosis of acute ischemic stroke (IS). The aim of this study was to evaluate the prognostic validity of a combination of clinical, imaging, and laboratory biomarkers in predicting 1-year mortality of IS. We evaluated 103 patients with IS within 24 h of their hospital admission and assessed demographic data, IS severity using the National Institutes of Health Stroke Scale (NIHSS), carotid intima-media thickness (cIMT), and degree of stenosis, as well as laboratory variables including immune-inflammatory, coagulation, and endothelial dysfunction biomarkers. The IS patients were categorized as survivors and non-survivors 1 year after admission. Non-survivors showed higher NIHSS and cIMT values, lower antithrombin, Protein C, platelet counts, and albumin, and higher Factor VIII, von Willebrand Factor (vWF), white blood cells, tumor necrosis factor (TNF)-α, interleukin (IL)-10, high-sensitivity C-reactive protein (hsCRP), and vascular cellular adhesion molecule 1 (VCAM-1) than survivors. Neural network models separated non-survivors from survivors using NIHSS, cIMT, age, IL-6, TNF-α, hsCRP, Protein C, Protein S, vWF, and platelet endothelial cell adhesion molecule 1 (PECAM-1) with an area under the receiving operating characteristics curve (AUC/ROC) of 0.975, cross-validated accuracy of 93.3%, sensitivity of 100% and specificity of 85.7%. In conclusion, imaging, immune-inflammatory, and coagulation biomarkers add predictive information to the NIHSS clinical score and these biomarkers in combination may act as predictors of 1-year mortality after IS. An early prediction of IS outcome is important for personalized therapeutic strategies that may improve the outcome of IS.