No abstract

Stroke is the fifth leading cause of death and the most frequent cause of disability worldwide. Currently, stroke diagnosis is based on neuroimaging; therefore, the lack of a rapid tool to diagnose stroke is still a major concern. In addition, therapeutic approaches to combat ischemic stroke are still scarce, since the only approved therapies are directed toward restoring blood flow to the affected brain area. However, due to the reduced time window during which these therapies are effective, few patients benefit from them; therefore, alternative treatments are urgently needed to reduce stroke brain damage in order to improve patients’ outcome. The inflammatory response triggered after the ischemic event plays an important role in the progression of stroke; consequently, the study of inflammatory molecules in the acute phase of stroke has attracted increasing interest in recent decades. Here, we provide an overview of the inflammatory processes occurring during ischemic stroke, as well as the potential for these inflammatory molecules to become stroke biomarkers and the possibility that these candidates will become interesting neuroprotective therapeutic targets to be blocked or stimulated in order to modulate inflammation after stroke.

Background and Purpose: Outcome prognostication in ischemic stroke patients remains challenging due to limited predictive properties of existing models. Blood-based biomarkers might provide additional information to established prognostic factors. We intended to identify the most promising prognostic biomarkers in ischemic stroke, their incremental prognostic value, and whether their predictive value differs among etiologies. Methods: We searched MEDLINE (Ovid) and Institute for Scientific Information Web of Knowledge for articles reporting the predictive performance of blood-based biomarkers measured up to 7 days after ischemic stroke and reporting functional outcome or death at least 7 days after stroke. This work updates a previous systematic review (up to January 2007), follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement and was registered (International Prospective Register of Systematic Reviews PROSPERO 2018; https://www.crd.york.ac.uk/PROSPERO /; Unique identifier: CRD42018094671). Results: Two hundred ninety-one articles published between January 2007 and August 2018 comprising 257 different biomarkers met inclusion criteria. Median sample size was 232 (interquartile range, 110–455); 260 (89%) articles reported regression analyses with 78% adjusting for stroke severity, 82% for age, 67% for both, and 9% for none of them; 37% investigated discrimination, 5% calibration, and 11% reclassification. Including publications from a previous systematic review (1960–January 2007), natriuretic peptides, copeptin, procalcitonin, mannose-binding lectin, adipocyte fatty acid–binding protein, and cortisol were the biomarkers most consistently associated with poor outcome in higher-quality studies showing an incremental value over established prognostic factors. Other biomarkers were less consistently associated with poor outcome or were reported in lower quality studies. High heterogeneity among studies precluded the performance of a meta-analysis. Conclusions: The number of reports on prognostic blood-based biomarkers in ischemic stroke increased 3.5-fold in the period January 2007 to August 2018. Although sample size increased, methodological flaws are still common. Natriuretic peptides and markers of inflammation, atherogenesis, and stress response are the most promising prognostic biomarkers among identified studies.

No abstract

Stroke remains a leading cause of death and disability worldwide. Despite continuous advances, the identification of key molecular signatures in the hyper-acute phase of ischemic stroke is still a primary interest for translational research on stroke diagnosis, prognosis, and treatment. Data integration from high-throughput -omics techniques has become crucial to unraveling key interactions among different molecular elements in complex biological contexts, such as ischemic stroke. Thus, we used advanced data integration methods for a multi-level joint analysis of transcriptomics and proteomics datasets obtained from mouse brains at 2 h after cerebral ischemia. By modeling net-like correlation structures, we identified an integrated network of genes and proteins that are differentially expressed at a very early stage after stroke. We validated 10 of these deregulated elements in acute stroke, and changes in their expression pattern over time after cerebral ischemia were described. Of these, CLDN20, GADD45G, RGS2, BAG5, and CTNND2 were next evaluated as blood biomarkers of cerebral ischemia in mice and human blood samples, which were obtained from stroke patients and patients presenting stroke-mimicking conditions. Our findings indicate that CTNND2 levels in blood might potentially be useful for distinguishing ischemic strokes from stroke-mimicking conditions in the hyper-acute phase of the disease. Furthermore, circulating GADD45G content within the first 6 h after stroke could also play a key role in predicting poor outcomes in stroke patients. For the first time, we have used an integrative biostatistical approach to elucidate key molecules in the initial stages of stroke pathophysiology and highlight new notable molecules that might be further considered as blood biomarkers of ischemic stroke.

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.

Although preclinical models do not seem suitable to characterize CCL23, it might be a novel promising biomarker for the early diagnosis of cerebral lesions and might facilitate the prediction of stroke patient outcome.

Cerebral ischemia entails rapid tissue damage in the affected brain area causing devastating neurological dysfunction. How each component of the neurovascular unit contributes or responds to the ischemic insult in the context of the human brain has not been solved yet. Thus, the analysis of the proteome is a straightforward approach to unraveling these cell proteotypes. In this study, post-mortem brain slices from ischemic stroke patients were obtained corresponding to infarcted (IC) and contralateral (CL) areas. By means of laser microdissection, neurons and blood brain barrier structures (BBB) were isolated and analyzed using label-free quantification. MS data are available via ProteomeXchange with identifier PXD003519. Ninety proteins were identified only in neurons, 260 proteins only in the BBB and 261 proteins in both cell types. Bioinformatics analyses revealed that repair processes, mainly related to synaptic plasticity, are outlined in microdissected neurons, with nonexclusive important functions found in the BBB. A total of 30 proteins showing < 0.05 and fold-change> 2 between IC and CL areas were considered meaningful in this study: 13 in neurons, 14 in the BBB and 3 in both cell types. Twelve of these proteins were selected as candidates and analyzed by immunohistofluorescence in independent brains. The MS findings were completely verified for neuronal SAHH2 and SRSF1 whereas the presence in both cell types of GABT and EAA2 was only validated in neurons. In addition, SAHH2 showed its potential as a prognostic biomarker of neurological improvement when analyzed early in the plasma of ischemic stroke patients. Therefore, the quantitative proteomes of neurons and the BBB (or proteotypes) after human brain ischemia presented here contribute to increasing the knowledge regarding the molecular mechanisms of ischemic stroke pathology and highlight new proteins that might represent putative biomarkers of brain ischemia or therapeutic targets.