Blood-based protein biomarkers for stroke differentiation: A systematic review

MicroRNA-124a promoted the differentiation of bone marrow mesenchymal stem cells into neurons through Notch signal pathway

This study investigated the possible mechanisms of microRNA-124a on the differentiation of bone marrow mesenchymal stem cells (BMSCs) and its underlying mechanism. β-Thiol ethanol induced Notch1 mRNA expression, microRNA-124a inhibitor reduced the effects of β-thiol ethanol on Notch1 mRNA expression in BMSCs. Baicalin induced Hes1 mRNA expression, and microRNA-124a inhibitor reduced the effects of baicalin on Hes1 mRNA expression in BMSCs. Si-Notch1 suppressed Hes1 mRNA expression in BMSCs. Baicalin increased the effects of Notch1 on Hes1 mRNA expression in BMSCs. Si-Notch1 increased cell growth of BMSCs. Baicalin reduced the effects of si-Notch1 on cell growth and the differentiation of BMSCs. We demonstrated that microRNA-124a promoted the differentiation of BMSCs into neurons through Notch/Hes1 signal pathway.

Blood biomarkers for the differentiation between central and peripheral vertigo in the emergency department: a systematic review and meta-analysis

BACKGROUND/INTRODUCTION

In patients with acute vestibular syndrome (AVS), differentiating between stroke and nonstroke causes is challenging in the emergency department (ED). Correct diagnosis of vertigo etiology is essential for early optimum treatment and disposition.

OBJECTIVES

The aim of this systematic review and meta-analysis was to summarize the published evidence on the potential of blood biomarkers in the diagnosis and differentiation of peripheral from central causes of AVS.

METHODS

A literature search was conducted for studies published until January 1, 2023, in PubMed, Ovid Medline, and EMBASE databases analyzing biomarkers for the differentiation between central and peripheral AVS. The Quality Assessment of Diagnostic Accuracy Studies questionnaire 2 was used for quality assessment. Pooled standardized mean difference and 95% confidence intervals were calculated if a biomarker was reported in two or more studies. Heterogeneity among included studies was investigated using the I2 metric.

RESULTS

A total of 17 studies with 859 central and 4844 peripheral causes of acute dizziness or vertigo, and analysis of 61 biomarkers were included. The general laboratory markers creatinine, blood urea nitrogen, albumin, C-reactive protein, glucose, HbA1c, leukocyte counts, and neutrophil counts and the brain-derived biomarkers copeptin, S100 calcium-binding protein β (S100β), and neuron-specific enolase (NSE) significantly differentiated central from peripheral causes of AVS.

CONCLUSIONS

This systematic review and meta-analysis highlights the potential of generalized inflammatory markers and brain-specific blood protein markers of NSE and S100β as diagnostic biomarkers for central from peripheral differentiation in AVS. These results, as a complement to clinical characteristics, provide guidance for future large-scale diagnostic research, in this challenging ED patient population.

Non-coding RNAs versus protein biomarkers to diagnose and differentiate acute stroke: Systematic review and meta-analysis

BACKGROUND

Stroke diagnosis is dependent on lengthy clinical and neuroimaging assessments, while rapid treatment initiation improves clinical outcome. Currently, more sensitive biomarker assays of both non-coding RNA- and protein biomarkers have improved their detectability, which could accelerate stroke diagnosis. This systematic review and meta-analysis compares non-coding RNA- with protein biomarkers for their potential to diagnose and differentiate acute stroke (subtypes) in (pre-)hospital settings.

METHODS

We performed a systematic review and meta-analysis of studies evaluating diagnostic performance of non-coding RNA- and protein biomarkers to differentiate acute ischemic and hemorrhagic stroke, stroke mimics, and (healthy) controls. Quality appraisal of individual studies was assessed using the QUADAS-2 tool while the meta-analysis was performed with the sROC approach and by assessing pooled sensitivity and specificity, diagnostic odds ratios, positive- and negative likelihood ratios, and the Youden Index.

SUMMARY OF REVIEW

112 studies were included in the systematic review and 42 studies in the meta-analysis containing 11627 patients with ischemic strokes, 2110 patients with hemorrhagic strokes, 1393 patients with a stroke mimic, and 5548 healthy controls. Proteins (IL-6 and S100 calcium-binding protein B (S100B)) and microRNAs (miR-30a) have similar performance in ischemic stroke diagnosis. To differentiate between ischemic- or hemorrhagic strokes, glial fibrillary acidic protein (GFAP) levels and autoantibodies to the NR2 peptide (NR2aAb, a cleavage product of NMDA neuroreceptors) were best performing whereas no investigated protein or non-coding RNA biomarkers differentiated stroke from stroke mimics with high diagnostic potential.

CONCLUSIONS

Despite sampling time differences, circulating microRNAs (< 24 h) and proteins (< 4,5 h) perform equally well in ischemic stroke diagnosis. GFAP differentiates stroke subtypes, while a biomarker panel of GFAP and UCH-L1 improved the sensitivity and specificity of UCH-L1 alone to differentiate stroke.

Labeling on a Chip of Cellular Fibronectin and Matrix Metallopeptidase-9 in Human Serum

We present a microfluidic chip for protein labeling in the human serum-based matrix. Serum is a complex sample matrix that contains a variety of proteins, and a matrix is used in many clinical tests. In this study, the device performance was tested using commercial serum samples from healthy donors spiked with the following target proteins: cellular fibronectin (c-Fn) and matrix metallopeptidase 9 (MMP9). The microfluidic molds were fabricated using micro milling on acrylic and using stereolithography (SLA) three-dimensional (3D) printing for an alternative method and comparison. A simple quality control was performed for both fabrication mold methods to inspect the channel height of the chip that plays a critical role in the labeling process. The fabricated microfluidic chip shows a good reproducibility and repeatability of the performance for the optimized channel height of 150 µm. The spiked proteins of c-Fn and MMP9 in the human serum-based matrix, were successfully labeled by the functionalized magnetic nanoparticles (MNPs). The biomarker labeling occurring in the serum was compared using a simple matrix sample: phosphate buffer. The measured signals obtained by using a magnetoresistive (MR) biochip platform showed that the labeling using the proposed microfluidic chip is in good agreement for both matrixes, i.e., the analytical performance (sensitivity) obtained with the serum, near the relevant cutoff values, is within the uncertainty of the measurements obtained with a simple and more controlled matrix: phosphate buffer. This finding is promising for stroke patient stratification where these biomarkers are found at high concentrations in the serum.

BNP on Admission Combined with Imaging Markers of Multimodal CT to Predict the Risk of Cardioembolic Stroke

Background

The aim of the study was to find the potential roles of B-type natriuretic peptide (BNP) and imaging markers on distinguishing cardioembolic (CE) stroke from non-CE stroke, so as to provide useful information for making individualized endovascular treatment (EVT) plan for the patients with acute ischemic stroke (AIS).

Methods

The patients with unilateral anterior circulation large vessel occlusion who underwent EVT between March 2016 and December 2021 were analyzed in this study, retrospectively. The risk factors, laboratory test indicators, imaging parameters, and other factors were compared between the CE group and non-CE group. Logistic regression was used to analyze the risk factors of CE stroke. ROC curves were used to assess the values of different parameters on distinguishing CE stroke from non-CE stroke. The relationships between BNP and imaging parameters were assessed using the Spearman correlation analysis.

Results

160 patients were enrolled in the study and divided into the CE group (n = 66) and non-CE group (n = 94). BNP (odds ratio (OR) = 1.004; 95% CI, 1.001-1.009; p = 0.038), MMR (OR = 0.736; 95% CI, 0.573-0.945; p = 0.016), NIHSS (OR = 1.150; 95% CI, 1.022-1.294; p = 0.020), and AF (OR = 556.968; 95% CI, 51.739-5995.765; p < 0.001) were the independent predictive factors of CE stroke. The area under the curve (AUC) of BNP and mismatch ratio (MMR) were 0.846 (95% CI (0.780-0.898), p < 0.001) and 0.636 (95% CI (0.633-0.779), p < 0.001), respectively. The cut-off value of BNP was 249.23 pg/mL with the sensitivity of 74.24% and the specificity of 82.98%. BNP combined with MMR improved the predictive value for CE stroke. The AUC of the combination was 0.858 with the sensitivity of 84.85% and the specificity of 73.40%. BNP was correlated with 4D CTA collateral score, MMR, clot burden score, final infarct volume, infarct core volume, and ischemic penumbra volume (all, p < 0.05).

Conclusion

BNP on admission combined with MMR is valuable for the risk prediction of CE stroke, which will promote the further screening of the high-risk patients with CE stroke and provide more diagnostic information for clinicians.

Fluid biomarkers in stroke: From animal models to clinical care

Stroke is a leading cause of death and disability worldwide. Stroke prevention, early diagnosis, and efficient acute treatment are priorities to successfully impact stroke death and disability. Fluid biomarkers may improve stroke differential diagnostic, patient stratification for acute treatment, and post-stroke individualized rehabilitation. In the present work, we characterized the use of stroke animal models in fluid biomarker research through a systematic review of PubMed and Scopus databases, followed by a literature review on the translation to the human stroke care setting and future perspectives in the field. We found increasing numbers of publications but with limited translation to the clinic. Animal studies are very heterogeneous, do not account for several human features present in stroke, and, importantly, only a minority of such studies used human cohorts to validate biomarker findings. Clinical studies have found appealing candidates, both protein and circulating nucleic acids, to contribute to a more personalized stroke care pathway. Still, brain tissue complexity and the fact that different brain pathologies share lesion biomarkers make this task challenging due to biomarker low specificity. Moreover, the study design and lack of validation cohorts may have precluded a formal integration of biomarkers in different steps of stroke diagnosis and treatment. To overcome such issues, recent pivotal studies on biomarker dynamics in individual patients are providing added value to diagnosis and anticipating patients' early prognosis. Presently, the most consistent protein biomarkers for stroke diagnosis and short- and long-term prognosis are associated with tissue damage at neuronal (TAU), axonal (NFL), or astroglial (GFAP and S100β) levels. Most promising nucleic acids are microRNAs (miR), due to their stability in plasma and ease of access. Still, clinical validation and standardized quantitation place them a step behind compared protein as stroke biomarkers. Ultimately, the definition of clinically relevant biomarker panels and optimization of fast and sensitive biomarker measurements in the blood, together with their combination with clinical and neuroimaging data, will pave the way toward personalized stroke care.

NR-2 antikor peptid düzeyinin akut iskemik inmede tanı, prognoz ve koma skorları ile ilişkisi var mıdır?

Aim: This study aimed to demonstrate the diagnostic and prognostic value of NR-2 peptides as a biomarker in acute ischemic stroke and to evaluate their correlation with the Glasgow Coma Scale (GCS) and the National Institutes of Health Stroke Scale (NIHSS). Materials and Methods: This is a prospective study evaluating the value of NR-2 peptide levels in the diagnosis and prognosis of acute stroke. The study included 101 patients, who presented to a tertiary healthcare facility and were diagnosed with acute stroke, and 57 healthy controls. In the whole study population, serum NR-2 peptide levels were measured using the ELISA method. Results: The NR-2 peptide level was 6.32 ± 8.30 in the patient group and 3.91 ± 1.64 in the study group. The NR-2 peptide level was significantly higher in the patient group (p = 0.006). No correlation was detected between NR-2 peptide levels and scores in the GCS or NIHSS. The results indicated that NR-2 was a potential biomarker elevated in the early phase of acute stroke, but had no correlation with the prognosis of acute stroke. Conclusion: Although our data shed light on the use of the NR-2 peptide level as a biomarker in the acute phase in patients with stroke, data are insufficient to predict prognosis. We think that larger, multicentre studies with longer follow-up periods are needed.

MicroRNA: An Emerging Predictive, Diagnostic, Prognostic and Therapeutic Strategy in Ischaemic Stroke

Stroke continues to be the third-leading cause of death and disability worldwide. The limited availability of diagnostic tools approved therapeutics and biomarkers that help monitor disease progression or predict future events remain as the major challenges in the field of stroke medicine. Hence, attempts to discover safe and efficacious therapeutics and reliable biomarkers are of paramount importance. MicroRNAs (miRNAs) are a class of non-coding RNAs that play important roles in regulating gene expression. Since miRNAs also play important roles in key mechanisms associated with the pathogenesis of stroke, including energy failure, inflammation and cell death, it is possible that miRNAs may serve as reliable blood-based markers for risk prediction, diagnosis and prognosis of ischaemic stroke. Discovery of better neurological outcome and smaller cerebral infarcts in animal models of ischaemic stroke treated with miRNA agomirs or antagomirs indicate that miRNAs may also play a cerebrovascular protective role after an ischaemic stroke. Nonetheless, further evidences on the optimum time for treatment and route of administration are required before effective translation of these findings into clinical practice. Bearing these in mind, this paper reviews the current literature discussing the involvement of miRNAs in major pathologies associated with ischaemic stroke and evaluates their value as reliable biomarkers and therapeutics for ischaemic stroke.

Noncoding RNA as Diagnostic and Prognostic Biomarkers in Cerebrovascular Disease

Noncoding RNAs (ncRNAs), such as microRNAs, long noncoding RNAs, and circular RNAs, play an important role in the pathophysiology of cerebrovascular diseases (CVDs). They are effectively detectable in body fluids, potentially suggesting new biomarkers for the early detection and prognosis of CVDs. In this review, the physiological functions of circulating ncRNAs and their potential role as diagnostic and prognostic markers in patients with cerebrovascular diseases are discussed, especially in acute ischemic stroke, subarachnoid hemorrhage, and moyamoya disease.

Circulating Biomarkers in Long-Term Stroke Prognosis: A Scoping Review Focusing on the South African Setting

Cerebrovascular disease, including both ischaemic and haemorrhagic strokes, remains one of the highest causes of global morbidity and mortality. Developing nations, such as South Africa (SA), are affected disproportionately. Early identification of stroke patients at risk of poor clinical prognosis may result in improved outcomes. In addition to conventional neuroimaging, the role of predictive biomarkers has been shown to be important. Little data exist on their applicability within SA. This scoping review aimed to evaluate the currently available data pertaining to blood biomarkers that aid in the long-term prognostication of patients following stroke and its potential application in the South African setting. This scoping review followed a 6-stage process to identify and critically review currently available literature pertaining to prognostic biomarkers in stroke. An initial 1191 articles were identified and, following rigorous review, 41 articles were included for the purposes of the scoping review. A number of potential biomarkers were identified and grouped according to the function or origin of the marker. Although most biomarkers showed great prognostic potential, the cost and availability will likely limit their application within SA. The burden of stroke is increasing worldwide and appears to be affecting developing countries disproportionately. Access to neuroradiological services is not readily available in all settings and the addition of biomarkers to assist in the long-term prognostication of patients following a stroke can be of great clinical value. The cost and availability of many of the reviewed biomarkers will likely hinder their use in the South African setting.

Antiphospholipid antibodies in patients with myocardial infarction with and without obstructive coronary arteries

BACKGROUND

Recent studies demonstrate that prothrombotic antiphospholipid antibodies (aPL) are overrepresented in patients with myocardial infarction (MI) due to coronary artery disease (MICAD). However, it is not known whether aPL differ between the two subsets of MI: MICAD and MI with nonobstructive coronary arteries (MINOCA).

OBJECTIVES

To determine whether aPL are associated with MINOCA or MICAD, or with hypercoagulability as assessed by activated protein C-protein C inhibitor (APC-PCI) complex.

METHODS

Well-characterized patients with MINOCA (n = 98), age- and gender-matched patients with MICAD (n = 99), and healthy controls (n = 100) were included in a cross-sectional case-control study. Autoantibodies (IgA/G/M) targeting cardiolipin and β₂ glycoprotein-I and specific nuclear antigens were analyzed by multiplexed bead technology. The concentration of APC-PCI was determined as a measure of hypercoagulability by an immunofluorometric sandwich assay.

RESULTS

Both prevalence and titers of aPL of the IgG isotype (anti-cardiolipin and/or anti-β₂ glycoprotein-I) were higher in patients with MINOCA and MICAD than in controls. aPL IgG positivity was twice as frequent among patients with MICAD than MINOCA (11% vs. 6%, nonsignificant). We observed no group differences regarding aPL IgA/M or antibodies targeting specific nuclear antigens. Levels of APC-PCI were elevated in aPL IgG-positive compared to aPL IgG-negative MICAD patients.

CONCLUSIONS

aPL IgG, but not IgA/M, are enriched particularly in patients with MICAD but also in patients with MINOCA, as compared to controls. Interestingly, signs of hypercoagulability-measured by increased levels of the APC-PCI complex-were present in aPL IgG-positive MICAD patients, indicating an association with functional disturbances of the coagulation system.

Potential Biomarkers for Post-Stroke Cognitive Impairment: A Systematic Review and Meta-Analysis

Stroke is a primary debilitating disease in adults, occurring in 15 million individuals each year and causing high mortality and disability rates. The latest estimate revealed that stroke is currently the second leading cause of death worldwide. Post-stroke cognitive impairment (PSCI), one of the major complications after stroke, is frequently underdiagnosed. However, stroke has been reported to increase the risk of cognitive impairment by at least five to eight times. In recent decades, peripheral blood molecular biomarkers for stroke have emerged as diagnostic, prognostic, and therapeutic targets. In this study, we aimed to evaluate some blood-derived proteins for stroke, especially related to brain damage and cognitive impairments, by conducting a systematic review and meta-analysis and discussing the possibility of these proteins as biomarkers for PSCI. Articles published before 26 July 2021 were searched in PubMed, Embase, the Web of Science, and the Cochrane Library to identify all relevant studies reporting blood biomarkers in patients with stroke. Among 1820 articles, 40 were finally identified for this study. We meta-analyzed eight peripheral biomarker candidates: homocysteine (Hcy), high-density lipoprotein cholesterol (HDL-C), C-reactive protein (CRP), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), triglyceride (TG), uric acid, and glycated hemoglobin (HbA1c). The Hcy, CRP, TC, and LDL-C levels were significantly higher in patients with PSCI than in the non-PSCI group; however, the HDL-C, TG, uric acid, and HbA1c levels were not different between the two groups. Based on our findings, we suggest the Hcy, CRP, TC, and LDL-C as possible biomarkers in patients with post-stroke cognitive impairment. Thus, certain blood proteins could be suggested as effective biomarkers for PSCI.

Metabolomic Profiles of Men and Women Ischemic Stroke Patients

Background: Stroke is known to affect both men and women; however, incidence and outcomes differ between them. Therefore, the discovery of novel, sex-specific, blood-based biomarkers for acute ischemic stroke (AIS) patients has the potential to enhance the understanding of the etiology of this deadly disease in the content of sex. The objective of this study was to identify serum metabolites associated with male and female AIS patients. Methods: Metabolites were measured with the use of untargeted, reverse-phase ultra-performance liquid chromatography-tandem mass spectrometry quantification from blood specimens collected from AIS patients. Samples were collected from 36 patients comprising each of 18 men and women with matched controls. Metabolic pathway analysis and principal component analysis (PCA) was used to differentiate metabolite profiles for male and female AIS patients from the control, while logistic regression was used to determine differences in metabolites between male and female AIS patients. Results: In female AIS patients, 14 distinct altered metabolic pathways and 49 corresponding metabolites were identified, while 39 metabolites and 5 metabolic pathways were identified in male patients. Metabolites that are predictive of ischemic stroke in female patients were 1-(1-enyl-palmitoyl)-2-arachidonoyl-GPC (P-16:0/20:4) (AUC = 0.914, 0.765–1.000), 1-(1-enyl-palmitoyl)-2-palmitoyl-GPC (P-16:0/16:0) (AUC = 0.840, 0.656–1.000), and 5,6-dihydrouracil (P-16:0/20:2) (AUC = 0.815, 0.601–1.000). Significant metabolites that were predictive of stroke in male patients were 5alpha-androstan-3alpha,17beta-diol disulfate (AUC = 0.951, 0.857–1.000), alpha-hydroxyisocaproate (AUC = 0.938, 0.832–1.000), threonate (AUC = 0.877, 0.716–1.000), and bilirubin (AUC = 0.817, 0.746–1.000). Conclusions: In the current study, the untargeted serum metabolomics platform identified multiple pathways and metabolites associated with male and female AIS patients. Further research is necessary to characterize how these metabolites are associated with the pathophysiology in male and female AIS patients.

Timely and Blood-Based Multiplex Molecular Profiling of Acute Stroke

Stroke is a leading cause of death and disability in the world. To address such a problem, early diagnosis and tailored acute treatment represent one of the major priorities in acute stroke care. Since the efficacy of reperfusion treatments is highly time-dependent, there is a critical need to optimize procedures for faster and more precise diagnosis. We provide a concise review of the most relevant and well-documented blood-protein biomarkers that exhibit greater potential for translational to clinical practice in stroke differential diagnosis and to differentiate ischemic stroke from hemorrhagic stroke, followed by an overview of the most recent point-of-care technological approaches to address this problem. The integration of fluid-based biomarker profiling, using point-of-care biosensors with demographic, clinical, and neuroimaging parameters in multi-dimensional clinical decision-making algorithms, will be the next step in personalized stroke care.

Development and Validation of a LASSO Prediction Model for Better Identification of Ischemic Stroke: A Case-Control Study in China

Background

Timely diagnosis of ischemic stroke (IS) in the acute phase is extremely vital to achieve proper treatment and good prognosis. In this study, we developed a novel prediction model based on the easily obtained information at initial inspection to assist in the early identification of IS.

Methods

A total of 627 patients with IS and other intracranial hemorrhagic diseases from March 2017 to June 2018 were retrospectively enrolled in the derivation cohort. Based on their demographic information and initial laboratory examination results, the prediction model was constructed. The least absolute shrinkage and selection operator algorithm was used to select the important variables to form a laboratory panel. Combined with the demographic variables, multivariate logistic regression was performed for modeling, and the model was encapsulated within a visual and operable smartphone application. The performance of the model was evaluated on an independent validation cohort, formed by 304 prospectively enrolled patients from June 2018 to May 2019, by means of the area under the curve (AUC) and calibration.

Results

The prediction model showed good discrimination (AUC = 0.916, cut-off = 0.577), calibration, and clinical availability. The performance was reconfirmed in the more complex emergency department. It was encapsulated as the Stroke Diagnosis Aid app for smartphones. The user can obtain the identification result by entering the values of the variables in the graphical user interface of the application.

Conclusion

The prediction model based on laboratory and demographic variables could serve as a favorable supplementary tool to facilitate complex, time-critical acute stroke identification.

Ultra-High-Resolution IonStar Strategy Enhancing Accuracy and Precision of MS1-Based Proteomics and an Extensive Comparison with State-of-the-Art SWATH-MS in Large-Cohort Quantification

Quantitative proteomics in large cohorts is highly valuable for clinical/pharmaceutical investigations but often suffers from severely compromised reliability, accuracy, and reproducibility. Here, we describe an ultra-high-resolution IonStar method achieving reproducible protein measurement in large cohorts while minimizing the ratio compression problem, by taking advantage of the exceptional selectivity of ultra-high-resolution (UHR)-MS1 detection (240k_FWHM@m/z = 200). Using mixed-proteome benchmark sets reflecting large-cohort analysis with technical or biological replicates (N = 56), we comprehensively compared the quantitative performances of UHR-IonStar vs a state-of-the-art SWATH-MS method, each with their own optimal analytical platforms. We confirmed a cutting-edge micro-liquid chromatography (LC)/Triple-TOF with Spectronaut outperforms nano-LC/Orbitrap for SWATH-MS, which was then meticulously developed/optimized to maximize sensitivity, reproducibility, and proteome coverage. While the two methods with distinct principles (i.e., MS1- vs MS2-based) showed similar depth-of-analysis (∼6700-7000 missing-data-free proteins quantified, 1% protein-false discovery rate (FDR) for entire set, 2 unique peptides/protein) and good accuracy/precision in quantifying high-abundance proteins, UHR-IonStar achieved substantially superior quantitative accuracy, precision, and reproducibility for lower-abundance proteins (a category that includes most regulatory proteins), as well as much-improved sensitivity/selectivity for discovering significantly altered proteins. Furthermore, compared to SWATH-MS, UHR-IonStar showed markedly higher accuracy for a single analysis of each sample across a large set, which is an inadequately investigated albeit critical parameter for large-cohort analysis. Finally, we compared UHR-IonStar vs SWATH-MS in measuring the time courses of altered proteins in paclitaxel-treated cells (N = 36), where dysregulated biological pathways have been very well established. UHR-IonStar discovered substantially more well-recognized biological processes/pathways induced by paclitaxel. Additionally, UHR-IonStar showed markedly superior ability than SWATH-MS in accurately depicting the time courses of well known to be paclitaxel-induced biomarkers. In summary, UHR-IonStar represents a reliable, robust, and cost-effective solution for large-cohort proteomic quantification with excellent accuracy and precision.

Acute Stroke Biomarkers: Are We There Yet?

Background: Distinguishing between stroke subtypes and knowing the time of stroke onset are critical in clinical practice. Thrombolysis and thrombectomy are very effective treatments in selected patients with acute ischemic stroke. Neuroimaging helps decide who should be treated and how they should be treated but is expensive, not always available and can have contraindications. These limitations contribute to the under use of these reperfusion therapies.

Aim: An alternative approach in acute stroke diagnosis is to identify blood biomarkers which reflect the body's response to the damage caused by the different types of stroke. Specific blood biomarkers capable of differentiating ischemic from hemorrhagic stroke and mimics, identifying large vessel occlusion and capable of predicting stroke onset time would expedite diagnosis and increase eligibility for reperfusion therapies.

Summary of Review: To date, measurements of candidate biomarkers have usually occurred beyond the time window for thrombolysis. Nevertheless, some candidate markers of brain tissue damage, particularly the highly abundant glial structural proteins like GFAP and S100β and the matrix protein MMP-9 offer promising results. Grouping of biomarkers in panels can offer additional specificity and sensitivity for ischemic stroke diagnosis. Unbiased “omics” approaches have great potential for biomarker identification because of greater gene, protein, and metabolite coverage but seem unlikely to be the detection methodology of choice because of their inherent cost.

Conclusion: To date, despite the evolution of the techniques used in their evaluation, no individual candidate or multimarker panel has proven to have adequate performance for use in an acute clinical setting where decisions about an individual patient are being made. Timing of biomarker measurement, particularly early when decision making is most important, requires urgent and systematic study.

iTRAQ-based Quantitative Proteomic Analysis of Dural Tissues Reveals Upregulated Haptoglobin to be a Potential Biomarker of Moyamoya Disease

Background:

Moyamoya Disease (MMD) is a rare cerebrovascular disease with a high rate of disability and mortality. Immune reactions have been implicated in the pathogenesis of MMD, however, the underlying mechanism is still unclear.

Objective:

To identify proteins related to MMD specially involved in the immunogenesis, we performed a proteomic study.

Methods:

In this work, dural tissues or plasma from 98 patients with MMD, 17 disease controls without MMD, and 12 healthy donors were included. Proteomic profiles of dural tissues from 4 MMD and 4 disease controls were analyzed by an isobaric tag for relative and absolute quantitation (iTRAQ)- based proteomics. The immune-related proteins were explored by bioinformatics and the key MMDrelated proteins were verified by western blot, multiple reaction monitoring methods, enzyme-linked immunosorbent assay, and tissue microarray.

Results:

1,120 proteins were identified, and 82 MMD-related proteins were found with more than 1.5 fold difference compared with those in the control samples. Gene Ontology analysis showed that 29 proteins were immune-related. In particular, Haptoglobin (HP) was up-regulated in dural tissue and plasma of MMD samples compared to the controls, and its up-regulation was found to be sex- and MMD Suzuki grade dependent. Through Receiver Operating Characteristic (ROC) analysis, HP can well discriminate MMD and healthy donors with the Area Under the Curve (AUC) of 0.953.

Conclusion:

We identified the biggest protein database of the dura mater. 29 out of 82 differentially expressed proteins in MMD are involved in the immune process. Of which, HP was up-regulated in dural tissue and plasma of MMD, with sex- and MMD Suzuki grade-dependence. HP might be a potential biomarker of MMD.

Nanotechnology in the diagnosis and treatment of stroke

Increasing developments in the field of nanotechnology have ignited its use in stroke diagnosis and treatment. The benefits of structural modification, ease of synthesis, and biocompatibility support the use of nanomaterials in the clinic. The pathophysiology of stroke is complex, involving different brain regions; hence, therapeutic agents are required to be delivered to specific regions. Nanoparticles (NPs) can be engineered to help improve the delivery and release of therapeutic agents in a localized manner, especially in the penumbra. This contributes not only to therapy, but also to neurosurgery and neuroimaging. Nanomaterials also offer high efficacy with few adverse effects. In this review, we provide a concise summary of the caveats associated with nanotechnology with respect to stroke therapy and diagnosis.

Blood Biomarkers for Detection of Brain Injury in COVID-19 Patients

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus attacks multiple organs of coronavirus disease 2019 (COVID-19) patients, including the brain. There are worldwide descriptions of neurological deficits in COVID-19 patients. Central nervous system (CNS) symptoms can be present early in the course of the disease. As many as 55% of hospitalized COVID-19 patients have been reported to have neurological disturbances three months after infection by SARS-CoV-2. The mutability of the SARS-COV-2 virus and its potential to directly affect the CNS highlight the urgency of developing technology to diagnose, manage, and treat brain injury in COVID-19 patients. The pathobiology of CNS infection by SARS-CoV-2 and the associated neurological sequelae of this infection remain poorly understood. In this review, we outline the rationale for the use of blood biomarkers (BBs) for diagnosis of brain injury in COVID-19 patients, the research needed to incorporate their use into clinical practice, and the improvements in patient management and outcomes that can result. BBs of brain injury could potentially provide tools for detection of brain injury in COVID-19 patients. Elevations of BBs have been reported in cerebrospinal fluid (CSF) and blood of COVID-19 patients. BB proteins have been analyzed in CSF to detect CNS involvement in patients with infectious diseases, including human immunodeficiency virus and tuberculous meningitis. BBs are approved by the U.S. Food and Drug Administration for diagnosis of mild versus moderate traumatic brain injury and have identified brain injury after stroke, cardiac arrest, hypoxia, and epilepsy. BBs, integrated with other diagnostic tools, could enhance understanding of viral mechanisms of brain injury, predict severity of neurological deficits, guide triage of patients and assignment to appropriate medical pathways, and assess efficacy of therapeutic interventions in COVID-19 patients.

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

Stroke is a top leading cause of death, which occurs due to interference in the blood flow of the brain. Ischemic stroke (blockage) accounts for most cases (87%) and is further subtyped into cardioembolic, atherosclerosis, lacunar, other causes, and cryptogenic strokes. The main value of subtyping ischemic stroke patients is for a better therapeutic decision-making process. The current classification methods are complex and time-consuming (hours to days). Specific blood-based biomarker measurements have promising potential to improve ischemic stroke mechanism classification. Over the past decades, the hypothesis that different blood-based biomarkers are associated with different ischemic stroke mechanisms is increasingly investigated. This review presents the recent studies that investigated blood-based biomarker characteristics differentiation between ischemic stroke mechanisms. Different blood-based biomarkers are specifically discussed (b-type natriuretic peptide, d-dimer, c-reactive protein, tumor necrosis factor-α, interleukin-6, interleukin-1β, neutrophil-lymphocyte ratio, total cholesterol, triglycerides, low-density lipoprotein, high-density lipoprotein and apolipoprotein A), as well as the different cut-off values that may be useful in specific classifications for cardioembolic and atherosclerosis etiologies. Lastly, the structure of a point-of-care biosensor device is presented, as a measuring tool on-site. The information presented in this review will hopefully contribute to the major efforts to improve the care for stroke patients.

B-Type Natriuretic Peptide as a Significant Brain Biomarker for Stroke Triaging Using a Bedside Point-of-Care Monitoring Biosensor

Stroke is a widespread condition that causes 7 million deaths globally. Survivors suffer from a range of disabilities that affect their everyday life. It is a complex condition and there is a need to monitor the different signals that are associated with it. Stroke patients need to be rapidly diagnosed in the emergency department in order to allow the admission of the time-limited treatment of tissue plasminogen activator (tPA). Stroke diagnostics show the use of sophisticated technologies; however, they still contain limitations. The hidden information and technological advancements behind the utilization of biomarkers for stroke triaging are significant. Stroke biomarkers can revolutionize the way stroke patients are diagnosed, monitored, and how they recover. Different biomarkers indicate different cascades and exhibit unique expression patterns which are connected to certain pathologies in the human body. Over the past decades, B-type natriuretic peptide (BNP) and its derivative N-terminal fragment (NT-proBNP) have been increasingly investigated and highlighted as significant cardiovascular biomarkers. This work reviews the recent studies that have reported on the usefulness of BNP and NT-proBNP for stroke triaging. Their classification association is also presented, with increased mortality in stroke, correlation with cardioembolic stroke, and an indication of a second stroke recurrence. Moreover, recent scientific efforts conducted for the technological advancement of a bedside point-of-care (POC) device for BNP and NT-proBNP measurements are discussed. The conclusions presented in this review may hopefully assist in the major efforts that are currently being conducted in order to improve the care of stroke patients.

Blood biomarkers for the diagnosis and differentiation of stroke: A systematic review and meta-analysis

Background

Correct diagnosis of stroke and its subtypes is pivotal in early stages for optimum treatment.

Aims

The aim of this systematic review and meta-analysis is to summarize the published evidence on the potential of blood biomarkers in the diagnosis and differentiation of stroke subtypes.

Methods

A literature search was conducted for papers published until 20 April 2020 in PubMed, EMBASE, Cochrane Library, TRIP, and Google Scholar databases to search for eligible studies investigating the role of blood biomarkers in diagnosing stroke. Quality assessment was done using modified Quality Assessment of Diagnostic Accuracy Studies questionnaire. Pooled standardized mean difference and 95% confidence intervals were calculated. Presence of heterogeneity among the included studies was investigated using the Cochran's Q statistic and I2 metric tests. If I2 was < 50% then a fixed-effect model was applied else a random-effect model was applied. Risk of bias was assessed using funnel plots and between-study heterogeneity was assessed using meta-regression and sensitivity analyses. Entire statistical analysis was conducted in STATA version 13.0.

Results

A total of 40 studies including patients with 5001 ischemic strokes, 756 intracerebral hemorrhage, 554 stroke mimics, and 1774 healthy control subjects analyzing 25 biomarkers (within 24 h after symptoms onset/after the event) were included in our meta-analysis; 67.5% of studies had moderate evidence of quality. Brain natriuretic peptide, matrix metalloproteinase-9, and D-dimer significantly differentiated ischemic stroke from intracerebral hemorrhage, stroke mimics, and health control subjects ( p < 0.05). Glial fibrillary acidic protein successfully differentiated ischemic stroke from intracerebral hemorrhage (standardized mean difference −1.04; 95% confidence interval −1.46 to −0.63) within 6 h. No studies were found to conduct a meta-analysis of blood biomarkers differentiating transient ischemic attack from healthy controls and stroke mimics.

Conclusion

This meta-analysis highlights the potential of brain natriuretic peptide, matrix metalloproteinase-9, D-dimer, and glial fibrillary acidic protein as diagnostic biomarkers for stroke within 24 h. Results of our meta-analysis might serve as a platform for conducting further targeted proteomics studies and phase-III clinical trials. PROSPERO Registration ID: CRD42019139659.

Metabolome Changes in Cerebral Ischemia

Cerebral ischemia is caused by perturbations in blood flow to the brain that trigger sequential and complex metabolic and cellular pathologies. This leads to brain tissue damage, including neuronal cell death and cerebral infarction, manifesting clinically as ischemic stroke, which is the cause of considerable morbidity and mortality worldwide. To analyze the underlying biological mechanisms and identify potential biomarkers of ischemic stroke, various in vitro and in vivo experimental models have been established investigating different molecular aspects, such as genes, microRNAs, and proteins. Yet, the metabolic and cellular pathologies of ischemic brain injury remain not fully elucidated, and the relationships among various pathological mechanisms are difficult to establish due to the heterogeneity and complexity of the disease. Metabolome-based techniques can provide clues about the cellular pathologic status of a condition as metabolic disturbances can represent an endpoint in biological phenomena. A number of investigations have analyzed metabolic changes in samples from cerebral ischemia patients and from various in vivo and in vitro models. We previously analyzed levels of amino acids and organic acids, as well as polyamine distribution in an in vivo rat model, and identified relationships between metabolic changes and cellular functions through bioinformatics tools. This review focuses on the metabolic and cellular changes in cerebral ischemia that offer a deeper understanding of the pathology underlying ischemic strokes and contribute to the development of new diagnostic and therapeutic approaches.

A scoping review of pre-hospital technology to assist ambulance personnel with patient diagnosis or stratification during the emergency assessment of suspected stroke

BACKGROUND

Pre-hospital identification of key subgroups within the suspected stroke population could reduce delays to emergency treatment. We aimed to identify and describe technology with existing proof of concept for diagnosis or stratification of patients in the pre-hospital setting.

METHODS

A systematic electronic search of published literature (from 01/01/2000 to 06/06/2019) was conducted in five bibliographic databases. Two reviewers independently assessed eligibility of studies or study protocols describing diagnostic/stratification tests (portable imaging/biomarkers) or technology facilitating diagnosis/stratification (telemedicine) used by ambulance personnel during the assessment of suspected stroke. Eligible descriptions required use of tests or technology during the actual assessment of suspected stroke to provide information directly to ambulance personnel in the pre-hospital setting. Due to study, intervention and setting heterogeneity there was no attempt at meta-analysis.

RESULTS

2887 articles were screened for eligibility, 19 of which were retained. Blood biomarker studies (n = 2) were protocols of prospective diagnostic accuracy studies, one examining purines and the other a panel of known and novel biomarkers for identifying stroke sub-types (versus mimic). No data were yet available on diagnostic accuracy or patient health outcomes. Portable imaging studies (n = 2) reported that an infrared screening device for detecting haemorrhages yielded moderate sensitivity and poor specificity in a small study, whilst a dry-EEG study to detect large vessel occlusion in ischaemic stroke has not yet reported results. Fifteen evaluations of pre-hospital telemedicine were identified (12 observational and 3 controlled comparisons) which all involved transmission of stroke assessment data from the pre-hospital setting to the hospital. Diagnosis was generally comparable with hospital diagnosis and most telemedicine systems reduced time-to-treatment; however, it is unknown whether this time saving translated into more favourable clinical outcomes. Telemedicine systems were deemed acceptable by clinicians.

CONCLUSIONS

Pre-hospital technologies to identify clinically important subgroups amongst the suspected stroke population are in development but insufficient evidence precludes recommendations about routine use in the pre-hospital setting. Multi-centre diagnostic accuracy studies and clinical utility trials combining promising technologies are warranted.

Proteomics Analysis of Brain Tissue in a Rat Model of Ischemic Stroke in the Acute Phase

Background: Stroke is a leading health issue, with high morbidity and mortality rates worldwide. Of all strokes, approximately 80% of cases are ischemic stroke (IS). However, the underlying mechanisms of the occurrence of acute IS remain poorly understood because of heterogeneous and multiple factors. More potential biomarkers are urgently needed to reveal the deeper pathogenesis of IS.

Methods: We identified potential biomarkers in rat brain tissues of IS using an iTRAQ labeling approach coupled with LC-MS/MS. Furthermore, bioinformatrics analyses including GO, KEGG, DAVID, and Cytoscape were used to present proteomic profiles and to explore the disease mechanisms. Additionally, Western blotting for target proteins was conducted for further verification.

Results: We identified 4,578 proteins using the iTRAQ-based proteomics method. Of these proteins, 282 differentiated proteins, comprising 73 upregulated and 209 downregulated proteins, were observed. Further bioinformatics analysis suggested that the candidate proteins were mainly involved in energy liberation, intracellular protein transport, and synaptic plasticity regulation during the acute period. KEGG pathway enrichment analysis indicated a series of representative pathological pathways, including energy metabolite, long-term potentiation (LTP), and neurodegenerative disease-related pathways. Moreover, Western blotting confirmed the associated candidate proteins, which refer to oxidative responses and synaptic plasticity.

Conclusions: Our findings highlight the identification of candidate protein biomarkers and provide insight into the biological processes involved in acute IS.

Plasma Levels of Retinol Binding Protein 4 Relate to Large VLDL and Small LDL Particles in Subjects with and without Type 2 Diabetes

Background: Retinol binding protein 4 (RBP4) carries retinol in plasma, but is also considered an adipokine, as it is implicated in insulin resistance in mice. Plasma RBP4 correlates with total cholesterol, low density lipoprotein (LDL)-cholesterol and triglycerides, and may confer increased cardiovascular risk. However, controversy exists about circulating RPB4 levels in type 2 diabetes mellitus (T2DM) and obesity. Here, we analyzed the relationships of RBP4 and retinol with lipoprotein subfractions in subjects with and without T2DM. Methods: Fasting plasma RBP4 (enzyme-linked immunosorbent assay) and retinol (high performance liquid chromatography) were assayed in 41 T2DM subjects and 37 non-diabetic subjects. Lipoprotein subfractions (NMR spectroscopy) were measured in 36 T2DM subjects and 27 non-diabetic subjects. Physical interaction of RBP4 with lipoproteins was assessed by fast protein liquid chromatography (FPLC). Results: Plasma RBP4 and retinol were strongly correlated (r = 0.881, p < 0.001). RBP4, retinol and the RBP4/retinol ratio were not different between T2DM and non-diabetic subjects (all p > 0.12), and were unrelated to body mass index. Notably, RBP4 and retinol were elevated in subjects with metabolic syndrome (p < 0.05), which was attributable to an association with elevated triglycerides (p = 0.013). Large VLDL, total LDL and small LDL were increased in T2DM subjects (p = 0.035 to 0.003). Taking all subjects together, RBP4 correlated with total cholesterol, non-HDL cholesterol, LDL cholesterol, triglycerides and apolipoprotein B in univariate analysis (p < 0.001 for each). Age-, sex- and diabetes status-adjusted multivariable linear regression analysis revealed that RBP4 was independently associated with large VLDL (β = 0.444, p = 0.005) and small LDL particles (β = 0.539, p < 0.001). Its relationship with large VLDL remained after further adjustment for retinol. RBP4 did not co-elute with VLDL nor LDL particles in FPLC analyses. Conclusions: Plasma RBP4 levels are related to but do not physically interact with large VLDL and small LDL particles. Elevated RBP4 may contribute to a proatherogenic plasma lipoprotein profile.

Multiparameter Optimization of Two Common Proteomics Quantification Methods for Quantifying Low-Abundance Proteins

Quantitative proteomics has been extensively applied in the screening of differentially regulated proteins in various research areas for decades, but its sensitivity and accuracy have been a bottleneck for many applications. Every step in the proteomics workflow can potentially affect the quantification of low-abundance proteins, but a systematic evaluation of their effects has not been done yet. In this work, to improve the sensitivity and accuracy of label-free quantification and tandem mass tags (TMT) labeling in quantifying low-abundance proteins, multiparameter optimization was carried out using a complex 2-proteome artificial sample mixture for a series of steps from sample preparation to data analysis, including the desalting of peptides, peptide injection amount for LC-MS/MS, MS1 resolution, the length of LC-MS/MS gradient, AGC targets, ion accumulation time, MS2 resolution, precursor coisolation threshold, data analysis software, statistical calculation methods, and protein fold changes, and the best settings for each parameter were defined. The suitable cutoffs for detecting low-abundance proteins with at least 1.5-fold and 2-fold changes were identified for label-free and TMT methods, respectively. The use of optimized parameters will significantly improve the overall performance of quantitative proteomics in quantifying low-abundance proteins and thus promote its application in other research areas.

Proteomic Analysis of Cerebral Cortex Extracts from Sus scrofa with Induced Hemorrhagic Stroke

Cerebrovascular diseases, including stroke and micro stroke, are the main causes of death in contemporary society. Hemorrhagic stroke is the fast emerging defficiency in the brain function resulting from disturbance of blood supply to the brain caused by the rapture of blood vessels (Lopez et al. in Proteomics Clin Appl 6:190-200, 2012). The influence of a model hemorrhagic stroke on white pigs with the change in the protein profile of their cortical samples 24 h and 2 months after the stroke was examined using mass-spectrometric analysis. Different proteins (n = 30) were identified, and their content was elevated. These proteins are involved in the mechanisms of neuroprotection, including compensation of oxidative stress (TXN, SNCA, PRDX6, ENO1), prevention of unwanted protein aggregation and apoptosis (PTMA, SNCA, SNCB), release of neurotransmitters (GAPDH, PEBP1) and assembly of the cytoskeleton (ACTA2, PTMA, TUBA4A, TUBA1D), etc. Also, a group of seven Ras family proteins involved in the regulation of cell proliferation and differentiation was found in the samples taken 24 h following the stroke. The relative concentrations of most of the proteins in the samples taken 2 months after the stroke demonstrate intermediate values between the control sample and the sample taken in 24 h, indicating the extinction of change in the protein profile with time. During the first 24 h after the stroke, there is an increase in protein fractions participating in exocytosis, synaptic plasticity/signaling, and support of neurotransmitter transport. Such shift in the weight of protein functional clusters can be attributed to activation of compensatory mechanisms in the body focused on neuroprotection.