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|Title:||Hyperacute changes in blood mRNA expression profiles of rats after middle cerebral artery occlusion: Towards a stroke time signature.|
|Authors:||Dagonnier, Marie;Wilson, William John;Favaloro, Jenny Margaret;Rewell, Sarah Susan Jane;Lockett, Linda Jane;Sastra, Stephen Andrew;Jeffreys, Amy Lucienne;Dewey, Helen Margaret;Donnan, Geoffrey Alan;Howells, David William|
|Affiliation:||The Florey Institute of Neuroscience and Mental Health, Melbourne Brain Centre, Austin Health, Heidelberg, Victoria, Australia|
The Commonwealth Scientific and Industrial Research Organisation (CSIRO), Sydney, Australia
School of Medicine, Faculty of Health, University of Tasmania, Hobart, Australia
|Citation:||PloS one 2018; 13(11): e0206321|
|Abstract:||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.|
|Appears in Collections:||Conference presentations|
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