Potential biomarkers for the diagnosis of stroke

Association between red cell distribution width level and risk of stroke: A systematic review and meta-analysis of prospective studies

BACKGROUND

Red cell distribution width level may have relations with the incidence and prognosis of cerebrovascular diseases. Recent researches have reported that red cell distribution width level was linked to the occurrence of stroke. However, the predicted effect of red cell distribution width in stroke is still disputed. We sought to assess the relationship between red cell distribution width and risk of stroke in this meta-analysis.

METHODS

Relevant studies were picked out from the databases of Embase, PubMed, and Cochrane Library. Hazard ratio with 95% confidence interval was chosen to analyze each trial, which was extracted from results of the highest and lowest red cell distribution width group. Funnel plots, Begg and Egger test were used to assess publication bias in the meta-analysis. Stata(12.0) was utilized to perform statistic analysis in the process.

RESULTS

A total of 6 studies with 5783 patients were included in this meta-analysis. The results showed that red cell distribution width level in patients with stroke was significantly higher than it in those without stroke (HR = 1.34, 95%CI:1.23-1.47, P < .001), in particular ischemic stroke(HR = 1.34,95% confidence interval:1.1-1.54, P < .001). There was no evidence of heterogeneity across the studies (P = .355, I = 5.53%).

CONCLUSIONS

The higher red cell distribution width level was associated with an increased risk of stroke, especially ischemic infarction.

Identification of novel blood biomarker panels to detect ischemic stroke in patients and their responsiveness to therapeutic intervention

The use of blood biomarkers for stroke has been long considered an excellent method to determine the occurrence, timing, subtype, and severity of stroke. In this study, venous blood was obtained from ischemic stroke patients after stroke onset and compared with age and sex-matched controls. We used a multiplex panel of 37 inflammatory molecules, analyzed using Luminex MagPix technology, to identify the changes in plasma proteins after ischemic stroke. We identified eight key molecules that were altered within the blood of stroke patients as compared to controls. Plasma levels of interleukin 6 signal transducer (sIL-6Rβ/gp130), matrix metalloproteinase-2 (MMP-2), osteopontin, sTNF-R1 and sTNF-R2 were significantly higher in stroke patients compared to controls. Interferon-β, interleukin-28, and thymic stromal lymphopoietin (TSLP) were decreased in plasma from stroke patients. No other immunological markers were significantly different between patient groups. When stroke patients were treated with tissue plasminogen activator (t-PA), plasma levels of interferon-α2 significantly increased while interleukin-2 and pentraxin-3 decreased. The discriminatory power of the molecules was evaluated by receiver operating characteristic (ROC) analysis. According to ROC analysis, the best markers for distinguishing stroke occurrence were MMP-2 (AUC = 0.76, sensitivity 62.5%, specificity 88.5%), sTNF-R2 (AUC = 0.75, sensitivity 83.3%, specificity 65.3%) and TSLP (AUC = 0.81, sensitivity 66.7%, specificity 96.2%). Multivariate logistic regression, used to evaluate the combination of proteins, identified a biomarker panel with high specificity and sensitivity (AUC = 0.96, sensitivity 87.5%, specificity 96.2%). These results indicate a novel set of blood biomarkers that could be used in a panel to identify stroke patients and their responsiveness to therapeutic intervention.

Red cell distribution width and neurological scoring systems in acute stroke patients

OBJECTIVES

The purpose of the present study was to evaluate the association between the red blood cell distribution width (RDW) and the Glasgow Coma Scale (GCS), Canadian Neurological Scale (CNS), and National Institutes of Health Stroke Scale (NIHSS) scores in patients who had acute ischemic stroke.

METHODS

This prospective observational cohort study included 88 patients who have had acute ischemic stroke and a control group of 40 patients who were evaluated in the Emergency Department for disorders other than acute ischemic stroke. All subjects had RDW determined, and stroke patients had scoring with the GCS, CNS, and NIHSS scores. The GCS, CNS, and NIHSS scores of the patients were rated as mild, moderate, or severe and compared with RDW.

RESULTS

Stroke patients had significantly higher median RDW than control subjects. The median RDW values were significantly elevated in patients who had more severe rather than milder strokes rated with all three scoring systems (GCS, CNS, and NIHSS). The median RDW values were significantly elevated for patients who had moderate rather than mild strokes rated by GCS and CNS and for patients who had severe rather than mild strokes rated by NIHSS. The area under the receiver operating characteristic curve was 0.760 (95% confidence interval, 0.676-0.844). Separation of stroke patients and control groups was optimal with RDW 14% (sensitivity, 71.6%; specificity, 67.5%; accuracy, 70.3%).

CONCLUSION

In stroke patients who have symptoms <24 hours, the RDW may be useful in predicting the severity and functional outcomes of the stroke.

Aortic Stiffness Is Related to the Ischemic Brain Injury Biomarker N-Methyl-D-aspartate Receptor Antibody Levels in Aortic Valve Replacement

Background. Aortic stiffness changes the flow pattern of circulating blood causing microvascular damage to different end-organ tissues, such as brain cells. The relationship between aortic stiffness measured by pulse wave velocity (PWV) and serum ischemic brain injury biomarker N-methyl-D-aspartate receptor antibody (NR2Ab) levels in aortic valve replacement has not been assessed. Methods. Patients undergoing aortic valve replacement (AVR) for aortic stenosis (AS) had their PWV and NR2Ab serum levels measured preoperatively. We analyzed PWV and NR2Ab in two ways: (1) as continuous variables using the actual value and (2) as dichotomous variables (PWV-norm and PWV-high groups) and (NR2Ab-low and NR2Ab-high groups). Results. Fifty-six patients (71 ± 8.4 years) were included in this study. The NR2Ab level (ng/mL) was significantly higher in the PWV-high group (n = 21) than in PWV-norm group (n = 35; median 1.8 ± 1.2 versus 1.2 ± 0.7, resp., P = 0.003). NR2Ab level was positively associated with PWV and negatively associated with male gender. Multiple regression revealed PWV independently related to NR2Ab level, and PWV cut-off was associated with a 7.23 times increase in the likelihood of having high NR2Ab (>1.8 ng/mL). Conclusion. Higher PWV in patients with surgical aortic stenosis is associated with higher levels of the ischemic brain biomarker NR2Ab.

High-sensitivity C-reactive protein, lipoprotein-related phospholipase A2, and acute ischemic stroke

BACKGROUND

Serum biomarkers may be useful for early diagnosis of acute ischemic stroke, exclusion of other diseases that may mimic stroke, and prediction of infarct volume. We evaluated serum high-sensitivity C-reactive protein (hs-CRP) and lipoprotein-related phospholipase A2 (Lp-PLA2) in patients who had acute ischemic stroke.

METHODS

In 200 patients who presented to an emergency service (acute ischemic stroke, 102 patients; control with no stroke, 98 patients), stroke patients were evaluated with the Canadian neurological scale and diffusion-weighted magnetic resonance imaging, and all patients were evaluated with the Glasgow coma scale and their serum hs-CRP level and Lp-PLA2 activity were assessed. The volume of stroke lesions was calculated from magnetic resonance images.

RESULTS

Patients who had stroke had higher mean serum hs-CRP level (stroke, 7±6 mg/dL; control, mean ± standard deviation 1±1 mg/dL; P≤0.001) and Lp-PLA2 activity (stroke, mean ± standard deviation 113±86 nmol/min/mL; control, mean ± standard deviation 103±50 nmol/min/mL; P≤0.001) than control patients who did not have stroke. The mean hs-CRP level and Lp-PLA2 activity were higher in patients who had greater stroke severity (lower Canadian neurological scale score) and were higher in patients who had larger volume strokes.

CONCLUSION

Higher hs-CRP level and Lp-PLA2 activity are significantly associated with more severe neurologic impairment and larger infarct size in patients who have acute ischemic stroke. These biomarkers may be useful for rapid diagnosis and prediction of ischemic tissue volume in the early stage of ischemic stroke. These findings may be important for health care facilities that have limited access to emergency computed tomography scanning for the diagnosis of stroke.

Ischemic stroke biomarkers in blood

Ischemic stroke is a leading cause of adult disability and mortality. With over 15 million strokes occurring every year in the world, methods to better identify patients at risk for stroke are needed, as are methods to improve patient diagnosis and prognosis when stroke occurs. Use of blood-based biomarkers is one method that has been evaluated to predict risk of stroke, diagnose stroke and its causes, predict stroke severity and outcome, and guide prevention therapy. Markers that have been identified include a variety of proteins, nucleic acids and lipids that relate to stroke pathophysiology. The role of blood biomarkers in ischemic stroke is still being defined, and further study is needed to develop blood biomarkers for clinical stroke use. In this review, the authors provide a summary of biomarkers that have been divided by their potential clinical application.

Molecular markers and mechanisms of stroke: RNA studies of blood in animals and humans

Whole genome expression microarrays can be used to study gene expression in blood, which comes in part from leukocytes, immature platelets, and red blood cells. Since these cells are important in the pathogenesis of stroke, RNA provides an index of these cellular responses to stroke. Our studies in rats have shown specific gene expression changes 24  hours after ischemic stroke, hemorrhage, status epilepticus, hypoxia, hypoglycemia, global ischemia, and following brief focal ischemia that simulated transient ischemic attacks in humans. Human studies show gene expression changes following ischemic stroke. These gene profiles predict a second cohort with >90% sensitivity and specificity. Gene profiles for ischemic stroke caused by large-vessel atherosclerosis and cardioembolism have been described that predict a second cohort with >85% sensitivity and specificity. Atherosclerotic genes were associated with clotting, platelets, and monocytes, and cardioembolic genes were associated with inflammation, infection, and neutrophils. These gene profiles predicted the cause of stroke in 58% of cryptogenic patients. These studies will provide diagnostic, prognostic, and therapeutic markers, and will advance our understanding of stroke in humans. New techniques to measure all coding and noncoding RNAs along with alternatively spliced transcripts will markedly advance molecular studies of human stroke.

Blood biomarkers of ischemic stroke

This review provides a summary of the protein and RNA biomarkers that have been studied for the diagnosis and assessment of ischemic stroke. Many of the biomarkers identified relate to the pathophysiology of ischemic stroke, including ischemia of CNS tissue, acute thrombosis and inflammatory response. These biomarkers are summarized by their intended clinical application in ischemic stroke including diagnosis, prediction of stroke severity and outcome, and stratification of patients for stroke therapy. Among the biomarkers discussed are recent whole genome studies using RNA expression profiles to diagnose ischemic stroke and stroke etiology. Though many candidate blood based biomarkers for ischemic stroke have been identified, none are currently used in clinical practice. With further well designed study and careful validation, the development of blood biomarkers to improve the care of patients with ischemic stroke may be achieved.

Gene expression profiling of blood for the prediction of ischemic stroke

BACKGROUND AND PURPOSE

A blood-based biomarker of acute ischemic stroke would be of significant value in clinical practice. This study aimed to (1) replicate in a larger cohort our previous study using gene expression profiling to predict ischemic stroke; and (2) refine prediction of ischemic stroke by including control groups relevant to ischemic stroke.

METHODS

Patients with ischemic stroke (n=70, 199 samples) were compared with control subjects who were healthy (n=38), had vascular risk factors (n=52), and who had myocardial infarction (n=17). Whole blood was drawn ≤3 hours, 5 hours, and 24 hours after stroke onset and from control subjects. RNA was processed on whole genome microarrays. Genes differentially expressed in ischemic stroke were identified and analyzed for predictive ability to discriminate stroke from control subjects.

RESULTS

The 29 probe sets previously reported predicted a new set of ischemic strokes with 93.5% sensitivity and 89.5% specificity. Sixty- and 46-probe sets differentiated control groups from 3-hour and 24-hour ischemic stroke samples, respectively. A 97-probe set correctly classified 86% of ischemic strokes (3 hour+24 hour), 84% of healthy subjects, 96% of vascular risk factor subjects, and 75% with myocardial infarction.

CONCLUSIONS

This study replicated our previously reported gene expression profile in a larger cohort and identified additional genes that discriminate ischemic stroke from relevant control groups. This multigene approach shows potential for a point-of-care test in acute ischemic stroke.

Advances in genomic analysis of stroke: what have we learned and where are we headed?

As a result of technological advances, the genomic analysis of stroke has shifted from candidate gene association studies to genome-wide association studies (GWAS). Agnostic GWAS evaluate up to 90% of common genetic variation in a single experiment, creating an improved framework for identifying novel genetic leads for biochemical and cellular mechanisms underlying stroke. Given the ubiquity of the GWAS approach, it has become essential for stroke researchers and clinicians to be able to interpret GWAS results. Thus, we review the basic elements of design, methods, presentation, and interpretation of GWAS in the context of stroke research. In 8 recent stroke GWAS reports, no single locus has been identified in 2 GWAS at a genome-wide level of significance. Additionally, no significant association signal between stroke and a locus with previous evidence from candidate gene studies of stroke has been identified yet. Some caveats of the approach and future directions for stroke genomics are discussed, including the use of intermediate phenotypes, Mendelian randomization, phenomics, and deep resequencing. Intelligent, appropriately powered, multidisciplinary studies incorporating knowledge from clinical medicine, epidemiology, genetics, and molecular biology will be required to fully characterize the genomic contributors to stroke.