Stroke Biomarkers Research Articles

MicroRNA: Relevance to stroke diagnosis, prognosis, and therapy.

Stroke is a life-threatening disease that accounts for a considerable burden of mortality in both developing and developed world. Identification of specific biomarkers for stroke and its outcomes can greatly contribute to improved care of patients. MicroRNAs (miRNAs) are known as novel biomarkers that could be used as diagnostic, prognostic, and therapeutic biomarkers. Various studies have shown that miRNAs have key roles in the pathogenesis of stroke, and its complications and outcomes. In addition, there is evidence showing that mesenchaymal stromal cell-derived exosomes containing miRNAs can be used for monitoring and treatment of various diseases such as stroke. Here, we summarized various aspects of miRNA applications in different stages of stroke.

Von Willebrand Factor: Multimeric Structure and Functional Activity in Patients With Atrial Fibrillation With and Without Oral Anticoagulation.

von Willebrand factor (vWF) is a multimeric glycoprotein present in blood plasma. It is synthesized in megakaryocytes and endothelial cells, secreted into circulation in the form of high-molecular-weight multimers (HMWMs), and cleaved into shorter, less active multimers by ADAMTS13. It is essential for platelet adhesion and aggregation. Previous studies have investigated the relationship between vWF levels and thromboembolic events with little regard to vWF multimeric structure. Patients with atrial fibrillation (AF) exhibit higher plasma vWF and lower ADAMTS13 levels. One hundred seven patients with AF, 51 anticoagulated and 56 nonanticoagulated, were eligible for the study. Plasma samples were analyzed for vWF antigen, vWF activity, and ADAMTS13; vWF multimers were analyzed by Western blot in 1% to 1.3% sodium dodecyl sulfate agarose gel electrophoresis. Patients with AF without oral anticoagulation (OAC) had significantly higher vWF plasma levels (154.00 [75-201] UI/dL) and vWF activity (60.00% [20%-210%]) compared to patients with OAC (133.50 [90-192] UI/dL, P = <.001; 50.00% [20%-160%], P = .02). Both were specially decreased in patients treated with acenocumarin. Patients without OAC also showed lower ADAMTS13 levels and presence of vWF HMWMs. Patients with AF show higher plasma levels and vWF activity. Moreover, treatment with traditional OAC (acenocumarin) significantly reduced vWF levels. Patients without OAC might have an increased risk of thrombotic events showing lower ADAMTS13 and higher vWF levels. Patients with stroke had higher plasma levels, vWF activity, and HMWMs. Our study suggests that increased vWF levels and presence of HMWMs could be related to cerebrovascular disease and may represent useful biomarkers for stroke in AF.

Potential Pathogenesis and Biomarkers of Kidney Cancer-Related Stroke.

BackgroundStroke risk and stroke recurrence are increased in cancer patients, but the pathogenesis and biomarkers of kidney cancer-related stroke (KCS) are generally unclear. The aim of the present research was to investigate the pathogenesis and plasma biomarkers of kidney cancer-related stroke.Material/MethodsA retrospective review was conducted on acute stroke patients with kidney cancer (KC) who were admitted to the hospital between January 2006 and December 2015. A total of 106 patients with KCS (active KC patients with acute stroke but without conventional vascular risks) were identified. In addition, 106 age- and sex-matched patients with KC alone were recruited.ResultsKCS patients had higher plasma D-dimer, cancer antigen (CA) 125, and CEA levels and greater proteinuria levels than did KC patients. Multiple logistic regression analysis showed that the risk of stroke in patients with KC increased independently by 0.8% (odds ratio [OR] 1.008; 95% confidence interval [CI] 1.002, 1.013; p=0.004) with a 1 ng/mL increase in D-dimer levels, by 1.2% (OR 1.012; 95% CI 1.007, 1.018; p=0.000) with a 1 U/mL increase in CA125, by 2.5% (OR 1.025; 95% CI 1.012, 1.038; p=0.000) with a 1 U/mL increase in CEA by 1.4% (OR 1.014; 95% CI 1.005, 1.024; p=0.004) with a 1 mg increase in urine protein in 24 hours.ConclusionsElevated plasma D-dimer, CA125 and CEA levels, and increased urine protein levels might lead to hypercoagulability and then KCS; however, they may also be biomarkers of KCS.

Electrochemical impedimetric detection of stroke biomarker NT-proBNP using disposable screen-printed gold electrodes

Abstract Stroke is the second top leading cause of death globally. It is caused by an abrupt interruption of blood flow to the brain. In that course, brain natriuretic peptide (BNP) and its derivative N-terminal pro b-type natriuretic peptide (NT-proBNP), neurohormones produced mainly by the heart ventricles in response to excessive stretching of cardiomyocytes (heart muscle cells), are proven to be good biomarkers for heart failure diagnosis. Moreover, there is growing clinical interest of the use of NT-proBNP for stroke diagnosis and prognosis because it is significantly associated with cardioembolic stroke and secondary stroke reoccurrence, with sensitivity &gt;90% and specificity &gt;80%. However, in diagnostic settings, there is still a need to address the encountered analytical problems, particularly assay specificity and set up. In this study, a novel approach for NT-proBNP detection is demonstrated using an electrochemical immunoassay method. A label-free impedimetry immunosensor for stroke biomarker was developed using modified disposable screen-printed gold electrodes (SPGE) hosting specific anti-NT-proBNP capture antibody. The performance of our immunosensor was studied in the presence of NT-proBNP in both buffered and mock (porcine) plasma samples. A linear relation between the relative total resistance (ΔRtot) responses and the NT-proBNP concentrations in buffer was observed in a range from 0.1 to 5 ng mL-1 with a correlation coefficient (R2) of 0.94656. Overall, the biosensor has demonstrated the capability to quantitate NT-proBNP and differentiate such concentrations in a low concentration range, especially among 0, 0.1, 0.5, 1, and 3 ng mL-1 in plasma samples within 25 min. This range is valuable not only for classifying cardioembolic stroke (higher or equal to 0.5 ng mL-1), but also predicting the risk of secondary stroke reoccurrence (higher than 0.255 ng mL-1). Our biosensor has the potential to be used as an easy-to-use point-of-care test that is both accurate and affordable.

LO62: Systolic blood pressure is a strong predictive marker for TIA and mild stroke in younger patients

Introduction: Age and systolic blood pressure (SBP) are important predictors of Acute Cerebrovascular Syndrome (ACVS). Yet, the effect of SBP is confounded by age, making its independent contribution to ACVS risk difficult to quantify. Here we use logistic regression to explore the role of SBP in younger and older ED patients. Methods: Data comprised 1019 ED patients (ACVS 70%, 30% non-ACVS) enrolled during a 28-month period of an ongoing prospective, observational, multi-site stroke biomarker study (SpecTRA). We used logistic regression to examine the effects of age, sex, and the age:SBP interaction as predictive markers of the diagnosis of ACVS. Results: Participants (53% male) ranged in age from 18 to 97 years (Q1=58, median=70, Q3=80). SBP ranged from 84 to 248 mmHg (Q1=137, median=154, Q3=174). In our initial regression model, age, sex, SBP and the age:SBP interaction were all significant (p&amp;lt;0.01). Using cubic regression splines for age, sbp and their interaction yields the same conclusion (p&amp;lt;0.01). To better understand the role of SBP in younger vs. older patients, we stratified the sample at the median age (70 years of age). In the younger group (n=510), participants were 55% male, 60% ACVS, and had SBP ranging from 91 to 236 mmHg (Q1=133, median=148, Q3=165). In the older group (n=509), participants were 51% male, 82% ACVS and had SBP ranging from 84 to 248 mmHg (Q1=143, median=159, Q3=179), a shift of approximately 10 mmHg between the groups. The logistic regression model was then fit separately to each group without the age:SBP interaction term. In the younger group, we found SBP to be highly significant (p&amp;lt;0.001), with an odds-ratio (OR) of 1.18 per 10 mmHg (95% CI: 1.10-1.29). In the older group, we found that SBP was not significant (p=0.91), with an OR of 1.00 per 10 mmHg (95% CI: 0.91-1.08). Age and sex were also significant risk factors in the younger group (each p&amp;lt;0.01), though not in the older group (both p&amp;gt;0.07). Conclusion: Our findings suggest that for ED patients suspected of ACVS, SBP is a clinically relevant predictor for younger patients, with higher SBP associated with an increased risk of ACVS, regardless of patient age and sex. SBP does not appear to be a strong predictor for patients over 70. ED physicians can leverage this finding by attributing greater importance to elevated SBP in younger patients than older patients when working toward a clinical suspicion of ACVS.

H-FABP: A new biomarker to differentiate between CT-positive and CT-negative patients with mild traumatic brain injury

The majority of patients with mild traumatic brain injury (mTBI) will have normal Glasgow coma scale (GCS) of 15. Furthermore, only 5%–8% of them will be CT-positive for an mTBI. Having a useful biomarker would help clinicians evaluate a patient’s risk of developing intracranial lesions. The S100B protein is currently the most studied and promising biomarker for this purpose. Heart fatty-acid binding protein (H-FABP) has been highlighted in brain injury models and investigated as a biomarker for stroke and severe TBI, for example. Here, we evaluate the performances of S100B and H-FABP for differentiating between CT-positive and CT-negative patients. A total of 261 patients with a GCS score of 15 and at least one clinical symptom of mTBI were recruited at three different European sites. Blood samples from 172 of them were collected ≤ 6 h after trauma. Patients underwent a CT scan and were dichotomised into CT-positive and CT-negative groups for statistical analyses. H-FABP and S100B levels were measured using commercial kits, and their capacities to detect all CT-positive scans were evaluated, with sensitivity set to 100%. For patients recruited ≤ 6 h after trauma, the CT-positive group demonstrated significantly higher levels of both H-FABP (p = 0.004) and S100B (p = 0.003) than the CT-negative group. At 100% sensitivity, specificity reached 6% (95% CI 2.8–10.7) for S100B and 29% (95% CI 21.4–37.1) for H-FABP. Similar results were obtained when including all the patients recruited, i.e. hospital arrival within 24 h of trauma onset. H-FABP out-performed S100B and thus seems to be an interesting protein for detecting all CT-positive mTBI patients with a GCS score of 15 and at least one clinical symptom.

The metal and metalloprotein profile of human plasma as biomarkers for stroke diagnosis

Stroke, a major cause of disability and mortality, affects someone in the United States every 40s. Stroke biomarkers, including those that could be used as a blood test for diagnosis of stroke, have been particularly elusive. We performed a double blind study to identify human plasma biomarkers for the diagnosis of stroke, including acute ischemic stroke (AIS) and intracerebral hemorrhage (ICH). We utilized a three-track approach based on the total metal profile, the metal cofactor levels among metalloproteins, and the identification of stroke-related metalloproteins. The study included 14 case-control pairs of AIS and 23 case-control pairs of ICH. Controls were matched to cases based on gender, ethnicity, and age (±5 years). AIS cases were statistically higher from their respective controls for protein bound co-factors Se and Cd, while unique correlations of metal cofactor concentrations among metalloproteins were identified between Pb-W, Sr-W, Pb-V, and Cu-V. ICH cases were statistically higher from their respective controls for Se and Co cofactors, whereas Cd and Pb were statistically lower. Unique correlations between metal cofactors for ICH cases were identified between Pb-W, Sr-W, Pb-V, and Cu-V. Stroke-related metalloproteins were identified, including calpain-15, protein-activated inward rectifier potassium channel 1, tau-tubulin kinase 1, and voltage-dependent L-type calcium channel subunit beta-3. Linear discriminant analysis (LDA) was able to classify patients between stroke cases or controls with 93% accuracy as well as classify patients with one of the four stroke groups with 85% accuracy. Additionally, this study found utmost importance in vanadium (V) and tungsten (W) correlations for both bound and total metal concentrations, suggestive of binding to transferrin or inhibition of oxidoreductases. Future work in stroke patients will seek to quantify varying selenoproteins, including selenoprotein P and glutathione peroxidase and identified zinc finger tissue leakage proteins, and further explore the role of trace metal fluctuations with transferrin.

RNA as a stroke biomarker

A biomarker to aid in the diagnosis of ischemic stroke and its causes would be of value in acute clinical practice. It could have applications to aid in acute stroke treatment decisions for tissue plasminogen activator and/or the triage to endovascular therapy. A stroke biomarker may also be useful to identify stroke etiology and guide stroke prevention treatments. This review provides an overview of RNA as a novel biomarker for the diagnosis and assessment of ischemic stroke. Topics addressed include RNA to identify acute ischemic stroke; RNA to identify transient ischemic attack; RNA to predict large vessel, cardioembolic and small vessel cause of stroke; and RNA to predict risk of tissue plasminogen activator related hemorrhagic transformation. Emerging methods to measure RNA as a point-of-care assay include microfluidics sorting and electrochemical sensors.

MicroRNAs regulating cluster of differentiation 46 (CD46) in cardioembolic and non-cardioembolic stroke.

Ischemic stroke is a major cause of mortality and morbidity globally. Among the ischemic stroke subtypes, cardioembolic stroke is with poor functional outcome (Modified Rankin score ≥ 2). Early diagnosis of cardioembolic stroke will prove beneficial. This study examined the microRNAs targeting cluster of differentiation 46 (CD46), a potential biomarker for cardioembolic stroke. CD46 mRNA level was shown to be differentially expressed (p < 0.001) between cardioembolic stroke (median = 1.32) and non-cardioembolic stroke subtypes (large artery stroke median = 5.05; small vessel stroke median = 6.45). Bioinformatic search showed that miR-19a, -20a, -185 and -374b were found to target CD46 mRNA and further verified by luciferase reporter assay. The levels of miRNAs targeting CD46 were significantly reduced (p < 0.05) in non-cardioembolic stroke patients (large artery stroke median: miR-19a = 0.63, miR-20a = 0.42, miR-185 = 0.32, miR-374b = 0.27; small artery stroke median: miR-19a = 0.07, miR-20a = 0.06, miR-185 = 0.07, miR-374b = 0.05) as compared to cardioembolic stroke patients (median: miR-19a = 2.69, miR-20a = 1.36, miR-185 = 1.05, miR-374b = 1.23). ROC curve showed that the miRNAs could distinguish cardioembolic stroke from non-cardioembolic stroke with better AUC value as compared to CD46. Endogenous expression of CD46 in Human Umbilical Vein Endothelial Cells (HUVECs) were found to be regulated by miR-19a and miR-20a. Thus implicating that miR-19a and -20a may play a role in pathogenesis of cardioembolic stroke, possibly via the endothelial cells.

Genome-Wide Analysis of the Circulating miRNome After Cerebral Ischemia Reveals a Reperfusion-Induced MicroRNA Cluster.

Circulating microRNAs (miRNAs) are emerging biomarkers for stroke because of their high stability in the bloodstream and association with pathophysiologic conditions. However, the circulating whole-genome miRNAs (miRNome) has not been characterized comprehensively in the acute phase of stroke. We profiled the circulating miRNome in mouse models of acute ischemic and hemorrhagic stroke by next-generation sequencing. Stroke models were compared with sham-operated and naive mice to identify deregulated circulating miRNAs. Top-ranked miRNAs were validated and further characterized by quantitative reverse transcription polymerase chain reaction. We discovered 24 circulating miRNAs with an altered abundance in the circulation 3 hours after ischemia, whereas the circulating miRNome was not altered after intracerebral hemorrhage compared with sham-operated mice. Among the upregulated miRNAs in ischemia, the top-listed miR-1264/1298/448 cluster was strongly dependent on reperfusion in different ischemia models. A time course experiment revealed that the miR-1264/1298/448 cluster peaked in the circulation around 3 hours after reperfusion and gradually decreased thereafter. Alteration of the miRNome in the circulation is associated with cerebral ischemia/reperfusion, but not hemorrhage, suggesting a potential to serve as biomarkers for reperfusion in the acute phase. The pathophysiological role of reperfusion-inducible miR-1264/1298/448 cluster, which is located on chromosome X within the introns of the serotonin receptor HTR2C, requires further investigation.

Abstract 182: Thermal Imaging as a Diagnostic Biomarker in Acute Ischemic Stroke

Purpose: With highly portable mobile infrared cameras thermal imaging during acute stroke triage has become possible. The purpose of this pilot study was to evaluate the pattern of superficial facial skin temperature in patients with acute proximal arterial occlusion of the anterior circulation compared to non-ischemic controls. We hypothesize, that temperature dysregulation in stroke with associated thermal pattern may be used to predict presence of proximal vessel occlusion. Methods: In 46 patients suffering from acute occlusion in the anterior circulation (ICA: 17, M1-MCA: 13, M2-MCA: 16) infrared thermal imaging of the face was performed before endovascular treatment. Asymmetric temperature patterns were evaluated visually. Quantitative temperature values were obtained from regions of interest (ROIs) placed symmetrically on the left and right half of on the facial thermal image. Presence and side of vessel occlusion was correlated with temperature measurements. Results: Regional facial asymmetric temperature was readily visible at 0.5°C. Temperature differences ranged from 0.5 to 1.5° C in stroke patients, and &lt;0.5°C in controls. In 16 of 17 patients with ICA occlusion, facial asymmetric temperature was detected (in 13 lower temperatures on ipsilateral side, in 3 on the contralateral side). In 11 of 13 patients with M1-MCA occlusion, facial asymmetric temperature was detected (in 8 lower temperatures on the contralateral side, 3 on the ipsilateral side). In 15 of 16 patients with an occlusion of M2-segment, asymmetric temperature pattern was apparent, however no clear trend with regard. In 16 of 20 controls, no asymmetric temperature pattern &gt;0.5°C was observed. Conclusion: Thermal imaging could serve as a fast point-of-care test to detect asymmetrical pattern in facial temperature as a predictor of proximal vessel occlusion in stroke. However, the current method is prone to imaging artifacts and reliability of detected asymmetry is moderate.

Abstract WP434: Serum MicroRNA Panel as a Candidate Biomarker of Carotid Plaque Rupture and Stroke

Introduction: Atherosclerotic plaque vulnerability and subsequent rupture are mediated by alterations in miRNAs that promote inflammation and fibrous cap thinning, leading to an acute ischemic stroke. Release of these miRNAs from the plaque tissue into the circulation may provide a miRNA profile that serves as a biomarker panel to identify the vulnerable patient at greatest risk of plaque rupture. Methods: Using RNA-Seq methodology, serum microRNA content was compared between patients undergoing carotid endarterectomy (CEA) for 2 distinct clinical phenotypes: patients without previous neurological events but high-grade carotid stenosis (asymptomatic, n=5), and patients with an acute neurological event within 5 days of the CEA (urgent, n=7). Differential expression of miRNAs was performed using the R statistical software and the DESeq2 package. Results: A total of 695 miRNAs detected in sera on RNA-Seq, 54 were significantly different between the asymptomatic and urgent groups. 22 miRNAs were decreased and 32 were increased in the serum of urgent patient’s compared to asymptomatic patients (adjusted p-value &lt; 0.05). Of these miRNAs, miR-21, miR-486, miR-23b, miR-27b, and let-7f were selected for validation as a biomarker panel based on a prior association with vascular disease. A pilot study (n= 6 asymptomatic and 6 urgent) measuring these miRNAs demonstrated that while miR-486 was detectable in all samples and exhibited a 9.4-fold increase (p &lt; 0.10) in the urgent group, the other miRNAs were only detected in a fraction of the samples (33 - 75%). Furthermore, miR-486 alone did not exhibit characteristics of a good indicator of ischemic stroke. A score normalizing the expression of miR-486 to the mean expression of the detectable miRNAs from this panel, did yield a promising C-statistic (0.97 ± 0.08, p &lt; 0.01), suggesting its potential as an indicator of an acute ischemic event. Conclusion: Carotid plaque rupture resulting in an acute ischemic event is associated with alterations in the profile of circulating miRNAs and these may be useful as biomarkers of ischemic stroke. Our pilot data suggest that the development of a score based on a panel of circulating miRNAs may allow for the diagnosis of patients experiencing plaque rupture and an acute ischemic stroke.

Abstract WP209: Plasma Brain Natriuretic Peptide Should be a Predictor for 3-Month Mortality in Non-Cardioembolic Stroke

Background: Plasma brain natriuretic peptide (BNP) is primarily released from the ventricular myocardium and is a biomarker of cardioembolic stroke. Previous studies have shown that elevated plasma BNP level predicts short and long term mortality in cardioembolic stroke. However, the relationship between BNP and mortality in non-cardioembolic stroke has not been fully examined. The present study tested the hypothesis that admission plasma BNP level can serve as a marker of 3-month mortality in non-cardioembolic stroke. Methods: From a prospective stroke registry, we examined acute non-cardioembolic stroke patients within 7 days after symptom onset who measured plasma BNP on admission from September 2014 to March 2016. We divided all patients into the non-survivors and the survivors within 3 month of non-cardioembolic stroke, and compared clinical characteristics between the two groups. The factors associated with 3-month mortality were investigated by multivariate logistic regression analysis. Results: Three hundred and one patients (198 males, 71 [61-80] years old) were enrolled in the study. Thirteen patients (3.8%) died within 3 month of non-cardioembolic stroke. There were no significant differences in male (61.5% vs. 66.0%, P=0.769), age (71 years old vs. 68 years old, P=0.450), hypertension (61.5% vs. 65.6%, P=0.771), diabetes (15.4% vs. 28.7%, P=0.525), dyslipidemia (30.8% vs. 43.4%, P=0.409), and smoking (61.5% vs. 50.0%, P=0.573) between the non-survivors and the survivors. The NIHSS score was significantly higher in the non-survivors than in the survivors (15 vs. 2, P&lt;0.001). The plasma BNP was significantly higher in the group of non-survivors than in the group of survivors (85 pg/ml vs. 31 pg/ml, p =0.005). A cut off plasma BNP level of 65.0 pg/ml could predict death within 3 month of non-cardioembolic stroke. Multivariate logistic regression analysis showed that a plasma BNP level of &gt;65.0 pg/ml (odds ratio [OR] 6.49; 95% confidence interval [CI], 1.79-23.56, P=0.04) was independently associated with 3-month mortality in non-cardioembolic stroke. Conclusions: A high plasma BNP level on admission should be a predictor for 3-month mortality in non-cadioembolic stroke.

Abstract 67: Blood Biomarkers for Prediction of Cardiac Complications in the Stroke Unit

Introduction: Cardiac complications such as acute coronary syndrome (ACS) or acute congestive heart failure (ACHF) account for 2-6%of mortality after stroke. Early detection of the patients at the highest risk to suffer from cardiac complications could be of interest to indicate a closer monitoring or therapeutic measures. We aimed to test whether a panel of blood biomarkers could predict the development of cardiac complications during stroke unit admission. Methods: The StrokeChip was a prospective, observational study, conducted at six Hospitals in Catalonia. Patients with suspected stroke were enrolled at Emergency Departments. Blood samples were obtained within the first six hours after symptom onset to measure a 21-biomarker panel. In-hospital development of cardiac complications (ACS and ACHF) was recorded. The association between the measured biomarkers and the development of complications was assessed by logistic regression analysis. Results: From August-2012 to December-2013, 941 out of 1308 patients enrolled were ischemic strokes. Cardiac complications were developed by 25 patients, including 19 ACHF and six cases of ACS. Due to the small number of ACS, just ACHF were further analyzed. Patients with ACHF had higher baseline levels of D-dimer, endostatin, VAP-1, NT-proBNP, FasL and vWF, and lower levels of IGFBP-3. After logistic regression analysis, NT-proBNP [OR=3.56(1.17-10.84)], FasL [OR=4.94(1.60-15.26)], VAP-1 [OR=6.56(2.21-19.46)] and IGFBP-3 [OR=0.21(0.07-0.67)] were independently associated with ACHF after adjustment by clinical predictors such as stroke severity, previous disability or history of coronary disease. Addition of the biomarker panel over clinical predictors resulted in improved accuracy (AUC from 0.808 to 0.925, p=0.05). Conclusions: Baseline measurement of blood biomarkers in acute stroke could be useful to predict the development of cardiac complications during stroke unit admission.

Validating a Predictive Model of Acute Advanced Imaging Biomarkers in Ischemic Stroke

Advanced imaging to identify tissue pathophysiology may provide more accurate prognostication than the clinical measures used currently in stroke. This study aimed to derive and validate a predictive model for functional outcome based on acute clinical and advanced imaging measures. A database of prospectively collected sub-4.5 hour patients with ischemic stroke being assessed for thrombolysis from 5 centers who had computed tomographic perfusion and computed tomographic angiography before a treatment decision was assessed. Individual variable cut points were derived from a classification and regression tree analysis. The optimal cut points for each assessment variable were then used in a backward logic regression to predict modified Rankin scale (mRS) score of 0 to 1 and 5 to 6. The variables remaining in the models were then assessed using a receiver operating characteristic curve analysis. Overall, 1519 patients were included in the study, 635 in the derivation cohort and 884 in the validation cohort. The model was highly accurate at predicting mRS score of 0 to 1 in all patients considered for thrombolysis therapy (area under the curve [AUC] 0.91), those who were treated (AUC 0.88) and those with recanalization (AUC 0.89). Next, the model was highly accurate at predicting mRS score of 5 to 6 in all patients considered for thrombolysis therapy (AUC 0.91), those who were treated (0.89) and those with recanalization (AUC 0.91). The odds ratio of thrombolysed patients who met the model criteria achieving mRS score of 0 to 1 was 17.89 (4.59-36.35, P<0.001) and for mRS score of 5 to 6 was 8.23 (2.57-26.97, P<0.001). This study has derived and validated a highly accurate model at predicting patient outcome after ischemic stroke.

Soluble lectin-like oxidized low-density lipoprotein receptor-1 as a novel biomarker for large-artery atherosclerotic stroke

ABSTRACTBackground: Serum soluble lectin-like oxidized low-density lipoprotein receptor-1 (sLOX-1) has been shown associated with the progression of atherosclerosis in endothelial cells. We sought to assess whether the baseline serum sLOX-1 levels are correlated with the presence and short-term functional outcome of large-artery atherosclerotic (LAA) stroke. Methods: The study recruited 241 subjects, including 148 consecutive patients with acute ischemic stroke with the subtype of LAA and 93 non-stroke controls. Clinical and laboratory data, including serum concentration of sLOX-1, were collected within 24 h of admission, and the severity of LAA stroke patients was evaluated by National Institutes of Health Stroke Scale score. And functional outcome was assessed by modified Rankin Scale three months after stroke. The association between sLOX-1 level and the functional outcome at three months was analyzed by multiple logistic regression models. Results: Serum levels of sLOX-1 in the LAA stroke patients were significantly higher as compared to normal controls (2.48 ± 0.93 ng/ml vs. 2.22 ± 0.79 ng/ml in the controls, t = 2.301, p = 0.022). The levels of serum sLOX-1 in patients with good outcome were significantly lower than those with poor outcome (2.39 ± 0.94 ng/ml vs. 2.77 ± 0.84 ng/ml, p = 0.032). After adjusting for potential confounders, sLOX-1 was still an independent predictor for the function outcome with an adjusted OR of 3.39 (95% CI, 1.61–7.11, p = 0.001). Conclusions: The serum sLOX-1 level was higher in patients with LAA stroke, and it was an independent predictor of functional outcome in patients with LAA ischemic stroke.

Assessed and Emerging Biomarkers in Stroke and Training-Mediated Stroke Recovery: State of the Art.

Since the increasing update of the biomolecular scientific literature, biomarkers in stroke have reached an outstanding and remarkable revision in the very recent years. Besides the diagnostic and prognostic role of some inflammatory markers, many further molecules and biological factors have been added to the list, including tissue derived cytokines, growth factor-like molecules, hormones, and microRNAs. The literatures on brain derived growth factor and other neuroimmune mediators, bone-skeletal muscle biomarkers, cellular and immunity biomarkers, and the role of microRNAs in stroke recovery were reviewed. To date, biomarkers represent a possible challenge in the diagnostic and prognostic evaluation of stroke onset, pathogenesis, and recovery. Many molecules are still under investigation and may become promising and encouraging biomarkers. Experimental and clinical research should increase this list and promote new discoveries in this field, to improve stroke diagnosis and treatment.

Molecular Links and Biomarkers of Stroke, Vascular Dementia, and Alzheimer's Disease.

Stroke is a very common neurological disease, and it occurs when the blood supply to part of the brain is interrupted and the subsequent shortage of oxygen and nutrients causes damage to the brain tissue. Stroke is the second leading cause of death and the third leading cause of disability-adjusted life years. The occurrence of stroke increases with age, but anyone at any age can suffer a stroke. Stroke can be broadly classified in two major clinical types: ischemic stroke (IS) and hemorrhagic stroke. Research also revealed that stroke, vascular dementia (VaD), and Alzheimer's disease (AD) increase with a number of modifiable factors, and most strokes can be prevented and/or controlled through pharmacological or surgical interventions and lifestyle changes. The pathophysiology of stroke, VaD, and AD is complex, and recent molecular and postmortem brain studies have revealed that multiple cellular changes have been implicated, including inflammatory responses, microRNA alterations, and marked changes in brain proteins. These molecular and cellular changes provide new information for developing therapeutic strategies for stroke and related vascular disorders treatment. IS is the major risk factor for VaD and AD. This chapter summarizes the (1) links among stroke-VaD-AD; (2) updates the latest developments of research in identifying protein biomarkers in peripheral and central nervous system tissues; and (3) critically evaluates miRNA profile and function in human blood samples, animal, and postmortem brains.

Where Are the Stroke Markers?

Stroke is a leading cause of preventable death and is a major cause of productivity impairment. On average, a stroke occurs every 40 seconds in the US, and someone will die of a stroke every 4 minutes. In 2016, it is estimated that in the US alone, 795000 people will suffer a new or recurrent stroke (ischemic or hemorrhagic). Of these, 610000 of these will be first events, and 185000 recurrent (1). Biomarkers are tests providing insight as to a physiologic state, either of the entire patient (e.g., cholesterol), or to a specific system (e.g., cardiac troponin). Usually monitored by blood testing, biomarkers provide rapid, noninvasive, relatively inexpensive, and objective measures of the presence of disease. Alternatively, in certain settings (e.g., the acute care environment), their greatest utility may be in confirming the absence of disease. Why would we need a stroke biomarker? We have excellent radiographic imaging-based diagnostics that can deliver fantastic, real-time, 3-dimensional images. And now, with the advent of the mobile computed tomography (CT), images can be obtained before the patient even reaches the hospital, where even more detailed images are obtainable with MRI. So the question remains, isn't this enough? The answer is no. Because, despite the current imaging-dominated climate for evaluation of suspected acute stroke, early diagnosis and treatment still require critical life-threatening decisions to be made without any objective input. Although this is the art of medicine, it is clearly not optimal. Pictures simply do not provide adequate objective data of pathologic events in the time that it is needed. We don't have a lot of treatment options to reverse the symptoms of acute stroke. One of the most effective is thrombolytics. By dissolving clots in the setting of an acute ischemic stroke, thrombolytics potentially restore blocked circulation, thus markedly reducing morbidity and …

Optimised Selection of Stroke Biomarker Based on Svm and Information Theory

With the development of molecular biology and gene-engineering technology, gene diagnosis has been an emerging approach for modern life sciences. Biological marker, recognized as the hot topic in the molecular and gene fields, has important values in early diagnosis, malignant tumor stage, treatment and therapeutic efficacy evaluation. So far, the researcher has not found any effective way to predict and distinguish different type of stroke. In this paper, we aim to optimize stroke biomarker and figure out effective stroke detection index based on SVM (support vector machine) and information theory. Through mutual information analysis and principal component analysis to complete the selection of biomarkers and then we use SVM to verify our model. According to the testing data of patients provided by Xuanwu Hospital, we explore the significant markers of the stroke through data analysis. Our model can predict stroke well. Then discuss the effects of each biomarker on the incidence of stroke.