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Hyperacute changes in blood mRNA expression profiles of rats after middle cerebral artery occlusion: Towards a stroke time signature

Citation

Dagonnier, M and Wilson, WJ and Favaloro, JM and Rewell, SSJ and Lockett, LJ and Sastra, SA and Jeffreys, AL and Dewey, HM and Donnan, GA and Howells, DW, Hyperacute changes in blood mRNA expression profiles of rats after middle cerebral artery occlusion: Towards a stroke time signature, PLOS One, 13, (11) pp. 1-22. ISSN 1932-6203 (2018) [Refereed Article]


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DOI: doi:10.1371/journal.pone.0206321

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.

Item Details

Item Type:Refereed Article
Research Division:Biomedical and Clinical Sciences
Research Group:Neurosciences
Research Field:Neurology and neuromuscular diseases
Objective Division:Health
Objective Group:Clinical health
Objective Field:Diagnosis of human diseases and conditions
UTAS Author:Howells, DW (Professor David Howells)
ID Code:151596
Year Published:2018
Web of Science® Times Cited:4
Deposited By:Medicine
Deposited On:2022-08-02
Last Modified:2022-08-02
Downloads:0

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