Background: Distinguishing between stroke subtypes and knowing the time of stroke onset are critical in clinical practice. Thrombolysis and thrombectomy are very effective treatments in selected patients with acute ischemic stroke. Neuroimaging helps decide who should be treated and how they should be treated but is expensive, not always available and can have contraindications. These limitations contribute to the under use of these reperfusion therapies.Aim: An alternative approach in acute stroke diagnosis is to identify blood biomarkers which reflect the body's response to the damage caused by the different types of stroke. Specific blood biomarkers capable of differentiating ischemic from hemorrhagic stroke and mimics, identifying large vessel occlusion and capable of predicting stroke onset time would expedite diagnosis and increase eligibility for reperfusion therapies.Summary of Review: To date, measurements of candidate biomarkers have usually occurred beyond the time window for thrombolysis. Nevertheless, some candidate markers of brain tissue damage, particularly the highly abundant glial structural proteins like GFAP and S100β and the matrix protein MMP-9 offer promising results. Grouping of biomarkers in panels can offer additional specificity and sensitivity for ischemic stroke diagnosis. Unbiased “omics” approaches have great potential for biomarker identification because of greater gene, protein, and metabolite coverage but seem unlikely to be the detection methodology of choice because of their inherent cost.Conclusion: To date, despite the evolution of the techniques used in their evaluation, no individual candidate or multimarker panel has proven to have adequate performance for use in an acute clinical setting where decisions about an individual patient are being made. Timing of biomarker measurement, particularly early when decision making is most important, requires urgent and systematic study.

BackgroundA key treatment for acute ischaemic stroke is thrombolysis (rtPA). However, treatment is not devoid of side effects and patients are carefully selected. AVERT (A Very Early Rehabilitation Trial), a large, ongoing international phase III trial, tests whether starting out of bed activity within 24 hours of stroke onset improves outcome. Patients treated with rtPA can be recruited if the physician allows (447 included to date). This study aimed to identify factors that might influence the inclusion of rtPA treated patients in AVERT.MethodsData from all patients thrombolysed at Austin Health, Australia, between September 2007 and December 2011 were retrospectively extracted from medical records. Factors of interest included: demographic and stroke characteristics, 24 hour clinical response to rtPA treatment, cerebral imaging and process factors (day and time of admission).Results211 patients received rtPA at Austin Health and 50 (24%) were recruited to AVERT (AVERT). Of the 161 patients not recruited, 105 (65%) were eligible, and could potentially have been included (pot-AVERT). There were no significant differences in demographics, Oxfordshire classification or stroke severity (NIHSS) on admission between groups. Size and localization of stroke on imaging and symptomatic intracerebral heamorrhage rate did not differ. Patients included in AVERT showed less change in NIHSS 24 hours post rtPA (median change = 1, IQR (−1,4)) than those in the pot-AVERT group (median change = 3, IQR (0,6)) by the median difference of 2 points (95%CI:0.3; p = 0.03). A higher proportion of rtPA treated AVERT patients were admitted on weekdays (p = 0.04).ConclusionExcluding a possible clinical instability, no significant clinical differences were identified between thrombolysed patients included in AVERT and those who were not. Over 500 AVERT patients will be treated with rtPA at trial end. These results suggest we may be able to generalize findings to other rtPA treated patients beyond the trial population.

Application of acute therapies such as thrombolysis for ischaemic stroke (IS) is constrained because of diagnostic uncertainty and the dynamic nature of stroke biology. To investigate changes in blood proteins after stroke and as a result of thrombolysis treatment we performed label-free quantitative proteomics on serum samples using high-resolution mass spectrometry and long high-performance liquid chromatography gradient (5 hours) combined with a 50-cm column to optimise the peptide separation. We identified (false discovery rate [FDR]: 1%) and quantified a total of 574 protein groups from a total of 92 samples from 30 patients. Ten patients were treated by thrombolysis as part of a randomised placebo-controlled trial and up to 5 samples were collected from each individual at different time points after stroke. We identified 26 proteins differently expressed by treatment group (FDR: 5%) and significant changes of expression over time for 23 proteins (FDR: 10%). Molecules such as fibrinogen and C-reactive protein showed expression profiles with a high-potential clinical utility in the acute stroke setting. Protein expression profiles vary acutely in the blood after stroke and have the potential to allow the construction of a stroke clock and to have an impact on IS treatment decision making.

Stroke evolution is a highly dynamic but variable disease which makes clinical decision making difficult. Biomarker discovery programs intended to aid clinical decision making have however largely ignored the rapidity of stroke evolution. We have used gene array technology to determine blood mRNA expression changes over the first day after stroke in rats. Blood samples were collected from 8 male spontaneously hypertensive rats at 0, 1, 2, 3, 6 and 24h post stroke induction by middle cerebral artery occlusion. RNA was extracted from whole blood stabilized in PAXgene tubes and mRNA expression was detected by oligonucleotide Affymetrix microarray. Using a pairwise comparison model, 1932 genes were identified to vary significantly over time (p≤0.5x10-7) within 24h after stroke. Some of the top20 most changed genes are already known to be relevant to the ischemic stroke physiopathology (e.g. Il-1R, Nos2, Prok2). Cluster analysis showed multiple stereotyped and time dependent profiles of gene expression. Direction and rate of change of expression for some profiles varied dramatically during these 24h. Profiles with potential clinical utility including hyper acute or acute transient upregulation (with expression peaking from 2 to 6h after stroke and normalisation by 24h) were identified. We found that blood gene expression varies rapidly and stereotypically after stroke in rats. Previous researchers have often missed the optimum time for biomarker measurement. Temporally overlapping profiles have the potential to provide a biological “stroke clock” able to tell the clinician how far an individual stroke has evolved.