title: Gene expression profiling of blood for the prediction of ischemic stroke.
abstract: OBJECTIVE
  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.
authors.affiliation: Department of Neurology and the MIND Institute, University of California at Davis, Sacramento, Calif 95817, USA. boryana.stamova@ucdmc.ucdavis.edu
authors.forename: Boryana
authors.initials: B
authors.lastname: Stamova
authors.forename: Huichun
authors.initials: H
authors.lastname: Xu
authors.forename: Glen
authors.initials: G
authors.lastname: Jickling
authors.forename: Cheryl
authors.initials: C
authors.lastname: Bushnell
authors.forename: Yingfang
authors.initials: Y
authors.lastname: Tian
authors.forename: Bradley P
authors.initials: BP
authors.lastname: Ander
authors.forename: Xinhua
authors.initials: X
authors.lastname: Zhan
authors.forename: Dazhi
authors.initials: D
authors.lastname: Liu
authors.forename: Renee
authors.initials: R
authors.lastname: Turner
authors.forename: Peter
authors.initials: P
authors.lastname: Adamczyk
authors.forename: Jane C
authors.initials: JC
authors.lastname: Khoury
authors.forename: Arthur
authors.initials: A
authors.lastname: Pancioli
authors.forename: Edward
authors.initials: E
authors.lastname: Jauch
authors.forename: Joseph P
authors.initials: JP
authors.lastname: Broderick
authors.forename: Frank R
authors.initials: FR
authors.lastname: Sharp
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015415:Biomarkers / Q000097:blood; D002545:Brain Ischemia / Q000097:blood / Q000235:genetics*; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D008297:Male; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis; D011237:Predictive Value of Tests; D012307:Risk Factors; D020521:Stroke / Q000097:blood / Q000235:genetics*
chemical_list: D015415:Biomarkers
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