Blood Biomarkers to Differentiate Ischemic and Hemorrhagic Strokes

Brain Injury Biomarkers and Applications in Neurological Diseases

ABSTRACT

Neurological diseases are a major health concern, and brain injury is a typical pathological process in various neurological disorders. Different biomarkers in the blood or the cerebrospinal fluid are associated with specific physiological and pathological processes. They are vital in identifying, diagnosing, and treating brain injuries. In this review, we described biomarkers for neuronal cell body injury (neuron-specific enolase, ubiquitin C-terminal hydrolase-L1, αII-spectrin), axonal injury (neurofilament proteins, tau), astrocyte injury (S100β, glial fibrillary acidic protein), demyelination (myelin basic protein), autoantibodies, and other emerging biomarkers (extracellular vesicles, microRNAs). We aimed to summarize the applications of these biomarkers and their related interests and limits in the diagnosis and prognosis for neurological diseases, including traumatic brain injury, status epilepticus, stroke, Alzheimer's disease, and infection. In addition, a reasonable outlook for brain injury biomarkers as ideal detection tools for neurological diseases is presented.

Prehospital identification of intracerebral haemorrhage: a scoping review of early clinical features and portable devices

INTRODUCTION

Prehospital identification of intracerebral haemorrhage (ICH) in suspected stroke cases may enable the initiation of appropriate treatments and facilitate better-informed transport decisions. This scoping review aims to examine the literature to identify early clinical features and portable devices for the detection of ICH in the prehospital setting.

METHODS

Three databases were searched via Ovid (MEDLINE, EMBASE and CENTRAL) from inception to August 2022 using prespecified search strategies. One reviewer screened all titles, abstracts and full-text articles for eligibility, while a second reviewer independently screened 20% of the literature during each screening stage. Data extracted were tabulated to summarise the key findings.

RESULTS

A total of 6803 articles were screened for eligibility, of which 22 studies were included for analysis. Among them, 15 studies reported on early clinical features, while 7 considered portable devices. Associations between age, sex and comorbidities with the presence of ICH varied across studies. However, most studies reported that patients with ICH exhibited more severe neurological deficits (n=6) and higher blood pressure levels (n=11) at onset compared with other stroke and non-stroke diagnoses. Four technologies were identified for ICH detection: microwave imaging technology, volumetric impedance phase shift spectroscopy, transcranial ultrasound and electroencephalography. Microwave and ultrasound imaging techniques showed promise in distinguishing ICH from other diagnoses.

CONCLUSION

This scoping review has identified potential clinical features for the identification of ICH in suspected stroke patients. However, the considerable heterogeneity among the included studies precludes meta-analysis of available data. Moreover, we have explored portable devices to enhance ICH identification. While these devices have shown promise in detecting ICH, further technological development is required to distinguish between stroke subtypes (ICH vs ischaemic stroke) and non-stroke diagnoses.

A comprehensive Exdia TRF-LFIA for simultaneous quantification of GFAP and NT-proBNP in distinguishing ischemic and hemorrhagic stroke

The goal of this study is to create a highly sensitive time-resolved fluorescence lateral flow immunoassay (TRF-LFIA) capable of concurrently measuring glial fibrillary acidic protein (GFAP) and the N-terminal fragment of B-type natriuretic peptide precursor (NT-proBNP). This assay is designed as a diagnostic tool and aims to provide an algorithm for stroke management, specifically for distinguishing between Ischemic stroke (IS) and Hemorrhagic stroke (HS). However, LFIA to quantify simultaneous serum NT-proBNP and GFAP are not yet available. We have developed and validated a novel TRF-LFIA for the simultaneous quantitative detection of NT-proBNP and GFAP. The sensitivity and reproducibility of the immunoassay were significantly improved by employing specific monoclonal antibodies linked to europium nanoparticles (EuNPs) that specifically target NT-proBNP and GFAP. The detection area on the nitrocellulose membrane featured sandwich-style complexes containing two test lines for NT-proBNP and GFAP, and one Control line. The fluorescence intensity of these test lines and control line was measured using an in-house developed Exdia TRF-Plus analyzer. As proof-of-concept, we enrolled patients suspected of having a stroke who were admitted within a specific time frame (6 h). A small amount of clinical specimen (serum) was used. To optimize the LFIA, an EuNPs conjugated antibodies were investigated to improve the detection sensitivity and decrease the background signal as well shorten the detection time. The Exdia TRF-LFIA cartridge offers a wide linear dynamic detection range, rapid detection, high sensitivity, and specificity. The limit of detection was determined to be 98 pg/mL for NT-proBNP and 68 pg/mL for GFAP, with minimal cross-reactivity. There were 200 clinical human serum samples that were used to evaluate this platform with high correlation. By combining the results of NT-proBNP and GFAP, we formulated an algorithm for the clinical assessment of Ischemic Stroke (IS) and Hemorrhagic Stroke (HS). According to our proposed algorithm, the combination of GFAP and NT-proBNP emerged as the most effective biomarker combination for distinguishing between IS and HS. Exdia TRF-LFIA shows great potential as a supplemental method for in vitro diagnostics in the laboratory or in other point-of-care testing (POCT) applications. Its development substantially decreases the diagnosis time for IS and HS. The proposed algorithm not only minimizes treatment delays but also lowers medical costs for patients.

Insights into myopic choroidal neovascularization based on quantitative proteomics analysis of the aqueous humor

BACKGROUND

Previous studies on the biomarkers of pathologic myopia choroidal neovascularization (pmCNV) development merely detected limited types of proteins and provide a meagre illustration of the underlying pathways. Hence, a landscape of protein changes in the aqueous humor (AH) of pmCNV patients is lacking. Here, to explore the potential mechanisms and biomarkers of pmCNV, we analyzed the clinical data and protein profile among atrophic (A) lesions, tractional lesions (T) and neovascular (N) lesions in myopic patients based on the ATN grading system for myopic maculopathy (MM).

RESULTS

After investigating demographic data of our patients, a correlation was found between A and N lesions (R = 0.5753, P < 0.0001). Accordingly, groups were divided into patients without MM, patients with myopic atrophic maculopathy (MAM), and patients with pmCNV (N2a lesion). In proteomics analysis, the increased protein level of GFAP and complement-associated molecules in AH samples of the 3 groups also indicated that MAM and pmCNV shared similar characteristics. The GO enrichment and KEGG pathway analysis were performed, which mapped that differential expressed proteins mainly engaged in JAK-STAT pathway between the pmCNV group and two controls. Furthermore, we identified several potential biomarkers for pmCNV, including FCN3, GFAP, EGFR, SFRP3, PPP2R1A, SLIT2, and CD248.

CONCLUSIONS

Atrophic lesions under pathologic myopic conditions demonstrated similarities to neovascularization development. Potential biomarkers including GFAP were associated with the pathogenesis of pmCNV. In summary, our study provides new insights for further research on pmCNV development.

Mollet I, Mendonça M, Salavisa M, Meira B, Fernandes M, Serrazina F, Cabral G, Ventura R, Sobral‐Pinho A, Beck HC, Vieira HLA, Viana‐Baptista M, Matthiesen R. Proteomics to Identify New Blood Biomarkers for Diagnosing Patients With Acute Stroke

Background Blood biomarkers are a potential tool for early stroke diagnosis. We aimed to perform a pilot and exploratory study on untargeted blood biomarkers in patients with suspected stroke by using mass spectrometry analysis. Methods and Results This was a prospective observational study of consecutive patients with suspected stroke admitted within 6 hours of last being seen well. Blood samples were collected at admission. Patients were divided into 3 groups: ischemic stroke (IS), intracerebral hemorrhage (ICH), and stroke mimics. Quantitative analysis from mass spectrometry data was performed using a supervised approach. Biomarker-based prediction models were developed to differentiate IS from ICH and ICH+stroke mimics. Models were built aiming to minimize misidentification of patients with ICH as having IS. We included 90 patients, one-third within each subgroup. The median age was 71 years (interquartile range, 57-81 years), and 49 participants (54.4%) were women. In quantitative analysis, C3 (complement component 3), ICAM-2 (intercellular adhesion molecule 2), PLGLA (plasminogen like A), STXBP5 (syntaxin-binding protein 5), and IGHV3-64 (immunoglobulin heavy variable 3-64) were the 5 most significantly dysregulated proteins for both comparisons. Biomarker-based models showed 88% sensitivity and 89% negative predictive value for differentiating IS from ICH, and 75% sensitivity and 95% negative predictive value for differentiating IS from ICH+stroke mimics. ICAM-2, STXBP5, PLGLA, C3, and IGHV3-64 displayed the highest importance score in our models, being the most informative for identifying patients with stroke. Conclusions In this proof-of-concept and exploratory study, our biomarker-based prediction models, including ICAM-2, STXBP5, PLGLA, C3, and IGHV3-64, showed 75% to 88% sensitivity for identifying patients with IS, while aiming to minimize misclassification of ICH. Although our methodology provided an internal validation, these results still need validation in other cohorts and with different measurement techniques.

Blood-Based Biomarkers in Intracerebral Hemorrhage

Intracerebral hemorrhage (ICH) is one of the most lethal subtypes of stroke, associated with high morbidity and mortality. Prevention of hematoma growth and perihematomal edema expansion are promising therapeutic targets currently under investigation. Despite recent improvements in the management of ICH, the ideal treatments are still to be determined. Early stratification and triage of ICH patients enable the adjustment of the standard of care in keeping with the personalized medicine principles. In recent years, research efforts have been concentrated on the development and validation of blood-based biomarkers. The benefit of looking for blood candidate markers is obvious because of their acceptance in terms of sample collection by the general population compared to any other body fluid. Given their ease of accessibility in clinical practice, blood-based biomarkers have been widely used as potential diagnostic, predictive, and prognostic markers. This review identifies some relevant and potentially promising blood biomarkers for ICH. These blood-based markers are summarized by their roles in clinical practice. Well-designed and large-scale studies are required to validate the use of all these biomarkers in the future.

Effect of Bypassing the Closest Stroke Center in Patients with Intracerebral Hemorrhage: A Secondary Analysis of the RACECAT Randomized Clinical Trial

Importance

Prehospital transfer protocols are based on rapid access to reperfusion therapies for patients with ischemic stroke. The effect of different protocols among patients receiving a final diagnosis of intracerebral hemorrhage (ICH) is unknown.

Objective

To determine the effect of direct transport to an endovascular treatment (EVT)-capable stroke center vs transport to the nearest local stroke center.

Design, Setting, and Participants

This was a prespecified secondary analysis of RACECAT, a multicenter, population-based, cluster-randomized clinical trial conducted from March 2017 to June 2020 in Catalonia, Spain. Patients were evaluated by a blinded end point assessment. All consecutive patients suspected of experiencing a large vessel occlusion stroke (Rapid Arterial Occlusion Evaluation Scale [RACE] score in the field >4 on a scale of 0 to 9, with lower to higher stroke severity) with final diagnosis of ICH were included. A total of 1401 patients were enrolled in RACECAT with suspicion of large vessel occlusion stroke. The current analysis was conducted in October 2022.

Intervention

Direct transport to an EVT-capable stroke center (n = 137) or to the closest local stroke center (n = 165).

Main Outcomes and Measures

The primary outcome was tested using cumulative ordinal logistic regression to estimate the common odds ratio (OR) and 95% CI of the shift analysis of disability at 90 days as assessed by the modified Rankin Scale (mRS) score (range, 0 [no symptoms] to 6 [death]) in the intention-to-treat population. Secondary outcomes, included 90-day mortality, death or severe functional dependency, early neurological deterioration, early mortality, ICH volume and enlargement, rate of neurosurgical treatment, rate of clinical complications during initial transport, and rate of adverse events until day 5.

Results

Of 1401 patients enrolled, 1099 were excluded from this analysis (32 rejected informed consent, 920 had ischemic stroke, 29 had transient ischemic attack, 12 had subarachnoid hemorrhage, and 106 had stroke mimic). Thus, 302 patients were included (204 [67.5%] men; mean [SD] age 71.7 [12.8] years; and median [IQR] RACE score, 7 [6-8]). For the primary outcome, direct transfer to an EVT-capable stroke center (mean [SD] mRS score, 4.93 [1.38]) resulted in worse functional outcome at 90 days compared with transfer to the nearest local stroke center (mean [SD] mRS score, 4.66 [1.39]; adjusted common OR, 0.63; 95% CI, 0.41-0.96). Direct transfer to an EVT-capable stroke center also suggested potentially higher 90-day mortality compared with transfer to the nearest local stroke center (67 of 137 [48.9%] vs 62 of 165 [37.6%]; adjusted hazard ratio, 1.40; 95% CI, 0.99-1.99). The rates of medical complications during the initial transfer (30 of 137 [22.6%] vs 9 of 165 patients [5.6%]; adjusted OR, 5.29; 95% CI, 2.38-11.73) and in-hospital pneumonia (49 of 137 patients [35.8%] vs 29 of 165 patients [17.6%]; OR, 2.61; 95% CI, 1.53-4.44) were higher in the EVT-capable stroke center group.

Conclusions and Relevance

In this secondary analysis of the RACECAT randomized clinical trial, bypassing the closest stroke center resulted in reduced chances of functional independence at 90 days for patients who received a final diagnosis of ICH.

Trial Registration

ClinicalTrials.gov Identifier: NCT02795962.

Prospective collection of blood plasma samples to identify potential biomarkers for the prehospital stroke diagnosis (ProGrEss-Bio): study protocol for a multicenter prospective observational study

Introduction

Intravenous thrombolysis (IVT) and mechanical thrombectomy (MT) are well-established, evidence-based, time-critical therapies that reduce morbidity and mortality in acute ischemic stroke (AIS) patients. The exclusion of intracerebral hemorrhage (ICH) is mandatory and has been performed by cerebral imaging to date. Mobile stroke units (MSUs) have been shown to improve functional outcomes by bringing cerebral imaging and IVT directly to the patient, but they have limited coverage. Blood biomarkers clearly distinguishing between AIS, ICH, and stroke mimics (SM) could provide an alternative to cerebral imaging if concentration changes are detectable in the hyperacute phase after stroke with high diagnostic accuracy. In this study, we will take blood samples in a prehospital setting to evaluate potential biomarkers. The study was registered in the German Clinical Trials Register (https://drks.de/search/de) with the identifier DRKS00023063.

Methods and analysis

We plan a prospective, observational study involving 300 patients with suspected stroke and symptom onset of ≤4.5 h before the collection of biomarkers. Study participants will be recruited from three sites in Berlin, Germany during MSU deployments. The focus of the study is the collection of blood samples from participants at the prehospital scene and from participants with AIS or ICH at a second-time point. All samples will be analyzed using targeted and untargeted analytical approaches. Study-related information about participants, including medical information and discharge diagnoses from the subsequent treating hospital, will be collected and documented in an electronic case report form (eCRF).

Discussion

This study will evaluate whether a single blood biomarker or a combination of biomarkers can distinguish patients with AIS and ICH from patients with stroke and SM in the early phase after symptom onset in the prehospital setting. In addition, the kinetics of blood biomarkers in AIS and ICH patients will be investigated. Our goal is to evaluate new ways to reliably diagnose stroke in the prehospital setting and thus accelerate the application of evidence-based therapies to stroke patients.

Modeling the potential efficiency of a blood biomarker-based tool to guide pre-hospital thrombolytic therapy in stroke patients

OBJECTIVES

Stroke treatment with intravenous tissue-type plasminogen activator (tPA) is effective and efficient, but as its benefits are highly time dependent, it is essential to treat the patient promptly after symptom onset. This study evaluates the cost-effectiveness of a blood biomarker test to differentiate ischemic and hemorrhagic stroke to guide pre-hospital treatment with tPA in patients with suspected stroke, compared with standard hospital management. The standard care for patients suffering stroke consists mainly in diagnosis, treatment, hospitalization and monitoring.

METHODS

A Markov model was built with four health states according to the modified Rankin scale, in adult patients with suspected moderate to severe stroke (NIHSS 4-22) within 4.5 hours after symptom onset. A Spanish Health System perspective was used. The time horizon was 15 years. Quality-adjusted life-years (QALYs) and life-years gained (LYGs) were used as a measure of effectiveness. Short- and long-term direct health costs were included. Costs were expressed in Euros (2022). A discount rate of 3% was used. Probabilistic sensitivity analysis and several one-way sensitivity analyses were conducted.

RESULTS

The use of a blood-test biomarker compared with standard care was associated with more QALYs (4.87 vs. 4.77), more LYGs (7.18 vs. 7.07), and greater costs (12,807€ vs. 12,713€). The ICER was 881€/QALY. Probabilistic sensitivity analysis showed that the biomarker test was cost-effective in 82% of iterations using a threshold of 24,000€/QALY.

CONCLUSIONS

The use of a blood biomarker test to guide pre-hospital thrombolysis is cost-effective compared with standard hospital care in patients with ischemic stroke.

A-Tuning Ensemble Machine Learning Technique for Cerebral Stroke Prediction

A cerebral stroke is a medical problem that occurs when the blood flowing to a section of the brain is suddenly cut off, causing damage to the brain. Brain cells gradually die because of interruptions in blood supply and other nutrients to the brain, resulting in disabilities, depending on the affected region. Early recognition and detection of symptoms can aid in the rapid treatment of strokes and result in better health by reducing the severity of a stroke episode. In this paper, the Random Forest (RF), Extreme Gradient Boosting (XGBoost), and light gradient-boosting machine (LightGBM) were used as machine learning (ML) algorithms for predicting the likelihood of a cerebral stroke by applying an open-access stroke prediction dataset. The stroke prediction dataset was pre-processed by handling missing values using the KNN imputer technique, eliminating outliers, applying the one-hot encoding method, and normalizing the features with different ranges of values. After data splitting, synthetic minority oversampling (SMO) was applied to balance the stroke samples and no-stroke classes. Furthermore, to fine-tune the hyper-parameters of the ML algorithm, we employed a random search technique that could achieve the best parameter values. After applying the tuning process, we stacked the parameters to a tuning ensemble RXLM that was analyzed and compared with traditional classifiers. The performance metrics after tuning the hyper-parameters achieved promising results with all ML algorithms.

Development and validation of a clinical nomogram for differentiating hemorrhagic and ischemic stroke prehospital

OBJECTIVES

The early detection and identification of stroke are essential to the prognosis of patients with suspected stroke symptoms out-of-hospital. We aimed to develop a risk prediction model based on the FAST score to identify the different types of strokes early for emergency medical services (EMS).

METHODS

This retrospective observational study enrolled 394 stroke patients at a single center from January 2020 to December 2021. Demographic data, clinical characteristics, and stroke risk factors with patients were collected from the EMS record database. Univariate and multivariate logistic regression analysis was used to identify the independent risk predictors. The nomogram was developed based on the independent predictors, in which the discriminative value and calibration of the nomogram were verified by the receiver operator characteristic (ROC) curve and calibration plots.

RESULTS

A total of 31.90% (88/276) of patients were diagnosed with hemorrhagic stroke in the training set, while 36.40% (43/118) in the validation set. The nomogram was developed based on the multivariate analysis, including age, systolic blood pressure, hypertension, vomiting, arm weakness, and slurred speech. The area under the curve (AUC) of the ROC with nomogram was 0.796 (95% CI: 0.740-0.852, P < 0.001) and 0.808 (95% CI:0.728-0.887, P < 0.001) in the training set and validation set, respectively. In addition, the AUC with the nomogram was superior to the FAST score in both two sets. The calibration curve showed a good agreement with the nomogram and the decision curves analysis also demonstrated that the nomogram had a wider range of threshold probabilities than the FAST score in the prediction risk of hemorrhagic stroke.

CONCLUSIONS

This novel noninvasive clinical nomogram shows a good performance in differentiating hemorrhagic and ischemic stroke for EMS staff prehospital. Moreover, all of the variables of nomogram are acquired in clinical practice easily and inexpensively out-of-hospital.

Rapid Activation of Neuroinflammation in Stroke: Plasma and Extracellular Vesicles Obtained on a Mobile Stroke Unit

BACKGROUND

Neuroinflammation is ubiquitous in acute stroke and worsens outcome. However, the precise timing of the inflammatory response is unknown, hindering the design of acute anti-inflammatory therapeutic interventions. We sought to identify the onset of the neuroinflammatory cascade using a mobile stroke unit.

METHODS

The study is a proof-of-concept, cohort investigation of ultra-early blood- and extracellular vesicle-derived markers of neuroinflammation and outcome in acute stroke. Blood was obtained, prehospital, on an mobile stroke unit. Outcomes were biomarker concentrations, modified Rankin Scale score, and National Institutes of Health Stroke Scale score.

RESULTS

Forty-one adults were analyzed, including 15 patients treated on the mobile stroke unit between August 2021 and April 2022, and 26 healthy controls to establish biomarker reference levels. Median patient age was 74 (range, 36-97) years, 60% were female, and 80% White. Ten (67%) were diagnosed as stroke, with 8 (53%) confirmed and 2 likely transient ischemic attack or stroke averted by thrombolysis; 5 were stroke mimics. For strokes, median initial National Institutes of Health Stroke Scale score was 11 (range, 4-19) and 6 (75%) received tPA (tissue-type plasminogen activator). Blood was obtained a median of 58 (range, 36-133) minutes after symptom onset. Within 36 minutes after stroke, plasma IL-6 (interleukin-6), neurofilament light chain, UCH-L1 (ubiquitin C-terminal hydrolase L1), and GFAP (glial fibrillary acidic protein) were elevated by as much as 10 times normal. In EVs, MMP-9 (matrix metalloproteinase-9), CXCL4 (chemokine (C-X-C motif) ligand 4), CRP (C-reactive protein), IL-6, OPN (osteopontin), and PECAM1 (platelet and endothelial cell adhesion molecule 1) were elevated. Inflammatory markers increased rapidly in the first 2 hours and continued rising for 24 hours.

CONCLUSIONS

The neuroinflammatory cascade was found to be activated within 36 to 133 minutes after stroke and progresses rapidly. This is earlier than observed previously in humans and suggests injury from neuroinflammation occurs faster than had been surmised. These findings could inform development of acute immunomodulatory stroke therapies and lead to new diagnostic tools and improved outcomes.

Diagnostic performance of Glial Fibrillary Acidic Protein and Prehospital Stroke Scale for identification of stroke and stroke subtypes in an unselected patient cohort with symptom onset < 4.5 h

INTRODUCTION

Rapid identification and treatment of stroke is crucial for the outcome of the patient. We aimed to determine the performance of glial fibrillary acidic protein (GFAP) independently and in combination with the Prehospital Stroke Score (PreSS) for identification and differentiation of acute stroke within 4.5 h after symptom onset.

PATIENTS AND METHODS

Clinical data and serum samples were collected from the Treat-Norwegian Acute Stroke Prehospital Project (Treat-NASPP). Patients with suspected stroke and symptoms lasting ≤ 4.5 h had blood samples collected and were evaluated with the National Institutes of Health Stroke Scale prospectively. In this sub study, NIHSS was retrospectively translated into PreSS and GFAP was measured using the sensitive single molecule array (SIMOA).

RESULTS

A total of 299 patients with suspected stroke were recruited from Treat-NASPP and included in this study (44% acute ischemic stroke (AIS), 10% intracranial hemorrhage (ICrH), 7% transient ischemic attack (TIA), and 38% stroke mimics). ICrH was identified with a cross-fold validated area under the receiver-operating characteristic curve (AUC) of 0.73 (95% CI 0.62-0.84). A decision tree with PreSS and GFAP combined, first identified patients with a low probability of stroke. Subsequently, GFAP detected patients with ICrH with a 25.0% sensitivity (95% CI 11.5-43.4) and 100.0% specificity (95% CI 98.6-100.0). Lastly, patients with large-vessel occlusion (LVO) were detected with a 55.6% sensitivity (95% CI 35.3-74.5) and 82.4% specificity (95% CI 77.3-86.7).

CONCLUSION

In unselected patients with suspected stroke, GFAP alone identified ICrH. Combined in a decision tree, GFAP and PreSS identified subgroups with high proportions of stroke mimics, ICrH, LVO, and AIS (non-LVO strokes).

Differential Diagnostic Value of Machine Learning-Based Models for Embolic Stroke

Cancer-associated thrombosis (CAT) and atrial fibrillation (AF)-related stroke are two subtypes of acute embolic stroke with distinct lesion patterns on diffusion weighted imaging (DWI). This pilot study aimed to evaluate the feasibility and performance of DWI-based machine learning models for differentiating between CAT and AF-related stroke. Patients with CAT and AF-related stroke were enrolled. In this pilot study with a small sample size, DWI images were augmented by flipping and/or contrast shifting to build convolutional neural network (CNN) predicative models. DWI images from 29 patients, including 9 patients with CAT and 20 with AF-related stroke, were analyzed. Training and testing accuracies of the DWI-based CNN model were 87.1% and 78.6%, respectively. Training and testing accuracies were 95.2% and 85.7%, respectively, for the second CNN model that combined DWI images with demographic/clinical characteristics. There were no significant differences in sensitivity, specificity, accuracy, and AUC between two CNN models (all P = n.s.).The DWI-based CNN model using data augmentation may be useful for differentiating CAT from AF-related stroke.

Machine learning-based identification of the novel circRNAs circERBB2 and circCHST12 as potential biomarkers of intracerebral hemorrhage

BACKGROUND

The roles and potential diagnostic value of circRNAs in intracerebral hemorrhage (ICH) remain elusive.

METHODS

This study aims to investigate the expression profiles of circRNAs by RNA sequencing and RT-PCR in a discovery cohort and an independent validation cohort. Bioinformatics analysis was performed to identify the potential functions of circRNA host genes. Machine learning classification models were used to assess circRNAs as potential biomarkers of ICH.

RESULTS

A total of 125 and 284 differentially expressed circRNAs (fold change > 1.5 and FDR < 0.05) were found between ICH patients and healthy controls in the discovery and validation cohorts, respectively. Nine circRNAs were consistently altered in ICH patients compared to healthy controls. The combination of the novel circERBB2 and circCHST12 in ICH patients and healthy controls showed an area under the curve of 0.917 (95% CI: 0.869-0.965), with a sensitivity of 87.5% and a specificity of 82%. In combination with ICH risk factors, circRNAs improved the performance in discriminating ICH patients from healthy controls. Together with hsa_circ_0005505, two novel circRNAs for differentiating between patients with ICH and healthy controls showed an AUC of 0.946 (95% CI: 0.910-0.982), with a sensitivity of 89.1% and a specificity of 86%.

CONCLUSION

We provided a transcriptome-wide overview of aberrantly expressed circRNAs in ICH patients and identified hsa_circ_0005505 and novel circERBB2 and circCHST12 as potential biomarkers for diagnosing ICH.

CCL5 Levels Predict Stroke Volume Growth in Acute Ischemic Stroke and Significantly Diminish in Hemorrhagic Stroke Patients

Stroke remains an important health challenge. Here, we study whether circulating chemokine (C-C motif) ligand 5 (CCL5) levels may predict clinical outcomes for stroke patients. A total of 100 consecutive stroke patients (36 acute ischemic and 64 hemorrhagic) were admitted to the stroke unit. Clinical history data and monitoring parameters were recorded. Blood serum was collected at days 0, 1, and hospital discharge to measure CCL5 levels by ELISA. Infarct or hemorrhagic volume, neurological severity (NIHSS), and functional prognosis (mRankin scale) were measured as clinical outcomes. CCL5 levels were lower in patients with hemorrhagic stroke than in patients with acute ischemic stroke. No differences were found between females and males in both types of stroke. Ischemic stroke patients whose infarct volume grew had lower CCL5 levels at day 0. Levels of CCL5 in ischemic and hemorrhagic patients were not associated with more severe symptoms/worse prognosis (NIHSS > 3; mRankin > 2) at admission or at 3 months. CCL5 could be used as a diagnostic marker to distinguish between ischemic and hemorrhagic strokes. Furthermore, CCL5 levels could predict the infarct volume outcomes in ischemic patients.

Neurovascular Unit-Derived Extracellular Vesicles: From Their Physiopathological Roles to Their Clinical Applications in Acute Brain Injuries

Extracellular vesicles (EVs) form a heterogeneous group of membrane-enclosed structures secreted by all cell types. EVs export encapsulated materials composed of proteins, lipids, and nucleic acids, making them a key mediator in cell–cell communication. In the context of the neurovascular unit (NVU), a tightly interacting multicellular brain complex, EVs play a role in intercellular communication and in maintaining NVU functionality. In addition, NVU-derived EVs can also impact peripheral tissues by crossing the blood–brain barrier (BBB) to reach the blood stream. As such, EVs have been shown to be involved in the physiopathology of numerous neurological diseases. The presence of NVU-released EVs in the systemic circulation offers an opportunity to discover new diagnostic and prognostic markers for those diseases. This review outlines the most recent studies reporting the role of NVU-derived EVs in physiological and pathological mechanisms of the NVU, focusing on neuroinflammation and neurodegenerative diseases. Then, the clinical application of EVs-containing molecules as biomarkers in acute brain injuries, such as stroke and traumatic brain injuries (TBI), is discussed.

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.

Stroke Risk Prediction with Machine Learning Techniques

A stroke is caused when blood flow to a part of the brain is stopped abruptly. Without the blood supply, the brain cells gradually die, and disability occurs depending on the area of the brain affected. Early recognition of symptoms can significantly carry valuable information for the prediction of stroke and promoting a healthy life. In this research work, with the aid of machine learning (ML), several models are developed and evaluated to design a robust framework for the long-term risk prediction of stroke occurrence. The main contribution of this study is a stacking method that achieves a high performance that is validated by various metrics, such as AUC, precision, recall, F-measure and accuracy. The experiment results showed that the stacking classification outperforms the other methods, with an AUC of 98.9%, F-measure, precision and recall of 97.4% and an accuracy of 98%.

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.

A Combined Clinical and Serum Biomarker-Based Approach May Allow Early Differentiation Between Patients With Minor Stroke and Transient Ischemic Attack as Well as Mid-term Prognostication

Background: Early differentiation between transient ischemic attack (TIA) and minor ischemic stroke (MIS) impacts on the patient's individual diagnostic work-up and treatment. Furthermore, estimations regarding persisting impairments after MIS are essential to guide rehabilitation programs. This study evaluated a combined clinical- and serum biomarker-based approach for the differentiation between TIA and MIS as well as the mid-term prognostication of the functional outcome, which is applicable within the first 24 h after symptom onset. Methods: Prospectively collected data were used for a retrospective analysis including the neurological deficit at admission (National Institutes of Health Stroke Scale, NIHSS) and the following serum biomarkers covering different pathophysiological aspects of stroke: Coagulation (fibrinogen, antithrombin), inflammation (C reactive protein), neuronal damage in the cellular [neuron specific enolase], and the extracellular compartment [matrix metalloproteinase-9, hyaluronic acid]. Further, cerebral magnetic resonance imaging was performed at baseline and day 7, while functional outcome was evaluated with the modified Rankin Scale (mRS) after 3, 6, and 12 months. Results: Based on data from 96 patients (age 64 ± 14 years), 23 TIA patients (NIHSS 0.6 ± 1.1) were compared with 73 MIS patients (NIHSS 2.4 ± 2.0). In a binary logistic regression analysis, the combination of NIHSS and serum biomarkers differentiated MIS from TIA with a sensitivity of 91.8% and a specificity of 60.9% [area under the curve (AUC) 0.84]. In patients with NIHSS 0 at admission, this panel resulted in a still acceptable sensitivity of 81.3% (specificity 71.4%, AUC 0.69) for the differentiation between MIS (n = 16) and TIA (n = 14). By adding age, remarkable sensitivities of 98.4, 100, and 98.2% for the prediction of an excellent outcome (mRS 0 or 1) were achieved with respect to time points investigated within the 1-year follow-up. However, the specificity was moderate and decreased over time (83.3, 70, 58.3%; AUC 0.96, 0.92, 0.91). Conclusion: This pilot study provides evidence that the NIHSS combined with selected serum biomarkers covering pathophysiological aspects of stroke may represent a useful tool to differentiate between MIS and TIA within 24 h after symptom onset. Further, this approach may accurately predict the mid-term outcome in minor stroke patients, which might help to allocate rehabilitative resources.

Association of Natriuretic Peptide With Adverse Outcomes and Disease Severity After Intracerebral Hemorrhage: A Systematic Review

Background: Over the past decade, many studies have reported the association of brain natriuretic peptide (BNP) and N-terminal pro-brain natriuretic peptide (NT-proBNP) with clinical outcome of intracerebral hemorrhage (ICH). However, a broad consensus has not been reached. Objective: To evaluate the role of BNP/NT-proBNP levels in prognosis and disease severity assessment in patients with ICH. Methods: A systematic literature search was conducted utilizing PubMed, Embase, Web of Science and the Cochrane Library databases up to July 23, 2021. Studies that explored the association between BNP/NT-proBNP level and clinical outcome or disease severity in ICH patients were eligible. Outcome measures were all-cause mortality, poor functional outcome, adverse cardiac events and markers of disease severity. Results: Ten studies, involving 1,373 patients with ICH, met the inclusion criteria. Nine studies focused on clinical outcomes (five all-cause mortality, five functional outcomes, and one adverse cardiac event) and seven on disease severity. In terms of prognosis, all five studies showed an association between elevated BNP/NT-proBNP level and increased risk of all-cause mortality in ICH patients. Four of the five studies reported poor functional outcomes in patients with higher BNP/NT-proBNP levels and one study associated higher BNP/NT-proBNP levels with increased risk of adverse cardiac events. Moreover, two studies identified an additional predictive ability of BNP/NT-proBNP level beyond that of pre-existing prognostic variables. In terms of disease severity, five studies (71%) reported that BNP/NT-proBNP level correlated positively with hematoma volume in addition to ICH and GCS scores. Conclusion: Elevated BNP/NT-proBNP level is associated with increased risk of all-cause mortality, poor functional outcome, adverse cardiac events and disease severity in patients with ICH. Thus, BNP/NT-proBNP level is a promising prognostic indicator for ICH and also an effective marker of disease severity. Current evidence remains limited by the small number and high heterogeneity of included studies. Further appropriately designed, large-scale studies are required to confirm the current findings.

[Time is Brain - Preclinical Emergency Care for Acute Ischemic Stroke]

Stroke is one of the most common neurological emergencies and requires rapid detection and treatment (time is brain). There is still insufficient knowledge about stroke warning signs. It is therefore of crucial importance that trained personnel in the preclinical setting recognize the relevant warning symptoms and collect the necessary information to quickly refer the patient to the appropriate additional care structure. For this purpose, training of the emergency medical services (EMS) and the correct triage are of particular importance. The on-site assessment of a patient with a suspected stroke by EMS should include airway, breathing, vital functions, a basic neurological examination, blood glucose testing and cardiac monitoring.Patients with suspected acute ischemic stroke should be brought to the nearest hospital with a stroke unit, ideally connected with a tertiary stroke centre. From there, once the primary diagnosis has been carried out and appropriate therapy initiated, the patient can be transferred to a thrombectomy center if necessary. To improve supply times, teleradiological networking plays a major role both between clinics of different levels of care and in communication between pre- and intra-hospital care providers. Also, the use of mobile stroke units can improve preclinical stroke care and reduce delays in access to intravenous thrombolytic therapy and mechanical thrombectomy. The identification of preclinical biomarkers could also save time.

Basal IL-6 and S100b levels are associated with infarct volume

OBJECTIVES

The study of biomarkers related to the infarct volume of acute ischaemic stroke (AIS) is a valuable clinical strategy. We conducted a prospective study to evaluate the relationship between a wide panel of biomarkers involved in different biochemical pathways and lesion volume.

MATERIALS & METHODS

We studied 332 patients with AIS. Infarct volume was calculated from diffusion weighted imaging (DWI). Blood samples were drawn within 24 h of symptom onset to test a panel of biomarkers that included high-sensitivity C-reactive protein (hs-CRP), IL-6, neuron-specific enolase (NSE), N-terminal pro-B-type natriuretic peptide (NT-ProBNP), S100b, troponin and IL-10.

RESULTS

The median lesion volume was 2.5 cc (IQR: 0.6-15.3). Patients with previous atrial fibrillation, cardioembolic aetiology and total anterior circulation infarct TACI classification had higher lesion volumes than those without them. Patients with previous recent TIA had smaller ischaemic lesions than those without it. Age and NIHSS were significantly correlated with lesion volume. In a linear regression analysis adjusted by aetiology, S100b and IL-6 emerged as the only biomarkers independently associated with infarct volume. In contrast, previous recent TIA and small-vessel disease were inversely related to infarct volume.

CONCLUSIONS

The correlation between the two blood marker levels and ischaemic lesion volume would support the use of these biomarkers as a surrogate endpoint in AIS, especially in centres without DWI 24/7 but these could not substitute basic neuroimaging. Our findings should be further explored in larger, preferably multicentre studies.

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.

Ultra-Early Differential Diagnosis of Acute Cerebral Ischemia and Hemorrhagic Stroke by Measuring the Prehospital Release Rate of GFAP

BACKGROUND

Plasma glial fibrillary acidic protein (GFAP) and tau are promising markers for differentiating acute cerebral ischemia (ACI) and hemorrhagic stroke (HS), but their prehospital dynamics and usefulness are unknown.

METHODS

We performed ultra-sensitivite single-molecule array (Simoa®) measurements of plasma GFAP and total tau in a stroke code patient cohort with cardinal stroke symptoms [National Institutes of Health Stroke Scale (NIHSS) ≥3]. Sequential sampling included 2 ultra-early samples, and a follow-up sample on the next morning.

RESULTS

We included 272 cases (203 ACI, 60 HS, and 9 stroke mimics). Median (IQR) last-known-well to sampling time was 53 (35-90) minutes for initial prehospital samples, 90 (67-130) minutes for secondary acute samples, and 21 (16-24) hours for next morning samples. Plasma GFAP was significantly higher in patients with HS than ACI (P < 0.001 for <1 hour and <3 hour prehospital samples, and <3 hour secondary samples), while total tau showed no intergroup difference. The prehospital GFAP release rate (pg/mL/minute) occurring between the 2 very early samples was significantly higher in patients with HS than ACI [2.4 (0.6-14.1)] versus 0.3 (-0.3-0.9) pg/mL/minute, P < 0.001. For cases with <3 hour prehospital sampling (ACI n = 178, HS n = 59), a combined rule (prehospital GFAP >410 pg/mL, or prehospital GFAP 90-410 pg/mL together with GFAP release >0.6 pg/mL/minute) enabled ruling out HS with high certainty (NPV 98.4%) in 68% of patients with ACI (sensitivity for HS 96.6%, specificity 68%, PPV 50%).

CONCLUSIONS

In comparison to single-point measurement, monitoring the prehospital GFAP release rate improves ultra-early differentiation of stroke subtypes. With serial measurement GFAP has potential to improve future prehospital stroke diagnostics .

Blood-Based Biomarkers: A Forgotten Friend of Hyperacute Ischemic Stroke

Ischemic stroke (IS) is the second leading cause of death worldwide. Multimodal neuroimaging techniques that have significantly facilitated the diagnosis of hyperacute IS are not widely used in underdeveloped areas and community hospitals owing to drawbacks such as high cost and lack of trained operators. Moreover, these methods do not have sufficient resolution to detect changes in the brain at the cellular and molecular levels after IS onset. In contrast, blood-based biomarkers can reflect molecular and biochemical alterations in both normal and pathophysiologic processes including angiogenesis, metabolism, inflammation, oxidative stress, coagulation, thrombosis, glial activation, and neuronal and vascular injury, and can thus provide information complementary to findings from routine examinations and neuroimaging that is useful for diagnosis. In this review, we summarize the current state of knowledge on blood-based biomarkers of hyperacute IS including those associated with neuronal injury, glial activation, inflammation and oxidative stress, vascular injury and angiogenesis, coagulation and thrombosis, and metabolism as well as genetic and genomic biomarkers. Meanwhile, the blood sampling time of the biomarkers which are cited and summarized in the review is within 6 h after the onset of IS. Additionally, we also discuss the diagnostic and prognostic value of blood-based biomarkers in stroke patients, and future directions for their clinical application and development.

Proteomic Characterization of the Dynamics of Ischemic Stroke in Mice

Novel therapies and biomarkers are needed for the treatment of acute ischemic stroke (AIS). This study aimed to provide comprehensive insights into the dynamic proteome changes and underlying molecular mechanisms post-ischemic stroke. TMT-coupled proteomic analysis was conducted on mouse brain cortex tissue from five time points up to 4 weeks poststroke in the distal hypoxic-middle cerebral artery occlusion (DH-MCAO) model. We found that nearly half of the detected proteome was altered following stroke, but only ∼8.6% of the changes were at relatively large scales. Clustering on the changed proteome defined four distinct expression patterns characterized by temporal and quantitative changes in innate and adaptive immune response pathways and cytoskeletal and neuronal remodeling. Further analysis on a subset of 309 “top hits”, which temporally responded to stroke with relatively large and sustained changes, revealed that they were mostly secreted proteins, highly correlated to different cortical cytokines, and thereby potential pharmacodynamic biomarker candidates for inflammation-targeting therapies. Closer examination of the top enriched neurophysiologic pathways identified 57 proteins potentially associated with poststroke recovery. Altogether, our study generated a rich dataset with candidate proteins worthy of further validation as biomarkers and/or therapeutic targets for stroke. The proteomics data are available in the PRIDE Archive with identifier PXD025077.