Literature DB >> 22627989

Prediction of cardioembolic, arterial, and lacunar causes of cryptogenic stroke by gene expression and infarct location.

Glen C Jickling1, Boryana Stamova, Bradley P Ander, Xinhua Zhan, Dazhi Liu, Shara-Mae Sison, Piero Verro, Frank R Sharp.   

Abstract

BACKGROUND AND
PURPOSE: The cause of ischemic stroke remains unclear, or cryptogenic, in as many as 35% of patients with stroke. Not knowing the cause of stroke restricts optimal implementation of prevention therapy and limits stroke research. We demonstrate how gene expression profiles in blood can be used in conjunction with a measure of infarct location on neuroimaging to predict a probable cause in cryptogenic stroke.
METHODS: The cause of cryptogenic stroke was predicted using previously described profiles of differentially expressed genes characteristic of patients with cardioembolic, arterial, and lacunar stroke. RNA was isolated from peripheral blood of 131 cryptogenic strokes and compared with profiles derived from 149 strokes of known cause. Each sample was run on Affymetrix U133 Plus 2.0 microarrays. Cause of cryptogenic stroke was predicted using gene expression in blood and infarct location.
RESULTS: Cryptogenic strokes were predicted to be 58% cardioembolic, 18% arterial, 12% lacunar, and 12% unclear etiology. Cryptogenic stroke of predicted cardioembolic etiology had more prior myocardial infarction and higher CHA(2)DS(2)-VASc scores compared with stroke of predicted arterial etiology. Predicted lacunar strokes had higher systolic and diastolic blood pressures and lower National Institutes of Health Stroke Scale compared with predicted arterial and cardioembolic strokes. Cryptogenic strokes of unclear predicted etiology were less likely to have a prior transient ischemic attack or ischemic stroke.
CONCLUSIONS: Gene expression in conjunction with a measure of infarct location can predict a probable cause in cryptogenic strokes. Predicted groups require further evaluation to determine whether relevant clinical, imaging, or therapeutic differences exist for each group.

Entities:  

Mesh:

Year:  2012        PMID: 22627989      PMCID: PMC3422649          DOI: 10.1161/STROKEAHA.111.648725

Source DB:  PubMed          Journal:  Stroke        ISSN: 0039-2499            Impact factor:   7.914


  25 in total

1.  Aortogenic embolism is a possible mechanism of cryptogenic stroke.

Authors:  Kazuo Kitagawa
Journal:  Ann Neurol       Date:  2004-04       Impact factor: 10.422

Review 2.  Gene-expression signatures in breast cancer.

Authors:  Christos Sotiriou; Lajos Pusztai
Journal:  N Engl J Med       Date:  2009-02-19       Impact factor: 91.245

Review 3.  Underlying pathology of stroke of unknown cause (cryptogenic stroke).

Authors:  Pierre Amarenco
Journal:  Cerebrovasc Dis       Date:  2009-04-03       Impact factor: 2.762

4.  Epidemiology of ischemic stroke subtypes according to TOAST criteria: incidence, recurrence, and long-term survival in ischemic stroke subtypes: a population-based study.

Authors:  P L Kolominsky-Rabas; M Weber; O Gefeller; B Neundoerfer; P U Heuschmann
Journal:  Stroke       Date:  2001-12-01       Impact factor: 7.914

5.  Ischemic stroke subtypes : a population-based study of functional outcome, survival, and recurrence.

Authors:  G W Petty; R D Brown; J P Whisnant; J D Sicks; W M O'Fallon; D O Wiebers
Journal:  Stroke       Date:  2000-05       Impact factor: 7.914

6.  Profiles of lacunar and nonlacunar stroke.

Authors:  Glen C Jickling; Boryana Stamova; Bradley P Ander; Xinhua Zhan; Yingfang Tian; Dazhi Liu; Huichun Xu; S Claiborne Johnston; Piero Verro; Frank R Sharp
Journal:  Ann Neurol       Date:  2011-07-27       Impact factor: 10.422

7.  Interatrial septal abnormalities and stroke: a meta-analysis of case-control studies.

Authors:  J R Overell; I Bone; K R Lees
Journal:  Neurology       Date:  2000-10-24       Impact factor: 9.910

8.  Frequency and mechanisms of stroke recurrence after cryptogenic stroke.

Authors:  Oh Young Bang; Phil Hyu Lee; Sung Yeol Joo; Jin Soo Lee; In Soo Joo; Kyoon Huh
Journal:  Ann Neurol       Date:  2003-08       Impact factor: 10.422

9.  Intermittent atrial fibrillation may account for a large proportion of otherwise cryptogenic stroke: a study of 30-day cardiac event monitors.

Authors:  Lucas Elijovich; S Andrew Josephson; Gordon L Fung; Wade S Smith
Journal:  J Stroke Cerebrovasc Dis       Date:  2009 May-Jun       Impact factor: 2.136

10.  New approach to stroke subtyping: the A-S-C-O (phenotypic) classification of stroke.

Authors:  P Amarenco; J Bogousslavsky; L R Caplan; G A Donnan; M G Hennerici
Journal:  Cerebrovasc Dis       Date:  2009-04-03       Impact factor: 2.762

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  37 in total

Review 1.  All's well that transcribes well: non-coding RNAs and post-stroke brain damage.

Authors:  Raghu Vemuganti
Journal:  Neurochem Int       Date:  2013-08-15       Impact factor: 3.921

Review 2.  Application of proteomics to cerebrovascular disease.

Authors:  Mingming Ning; Mary Lopez; Jing Cao; Ferdinando S Buonanno; Eng H Lo
Journal:  Electrophoresis       Date:  2012-12       Impact factor: 3.535

Review 3.  [Current indications for left atrial appendage occlusion].

Authors:  Clemens Jilek; Thorsten Lewalter
Journal:  Herzschrittmacherther Elektrophysiol       Date:  2017-10-25

4.  Insertable cardiac monitors for detection of atrial fibrillation after cryptogenic stroke: a meta-analysis.

Authors:  Yue Lu; Shan-Shan Diao; Shuang-Jiao Huang; Jie-Ji Zhao; Meng-Fan Ye; Fei-Rong Yao; Yan Kong; Zhuan Xu
Journal:  Neurol Sci       Date:  2021-02-02       Impact factor: 3.307

5.  Altered Expression of Long Noncoding RNAs in Blood After Ischemic Stroke and Proximity to Putative Stroke Risk Loci.

Authors:  Cheryl Dykstra-Aiello; Glen C Jickling; Bradley P Ander; Natasha Shroff; Xinhua Zhan; DaZhi Liu; Heather Hull; Miles Orantia; Boryana S Stamova; Frank R Sharp
Journal:  Stroke       Date:  2016-11-10       Impact factor: 7.914

6.  Stroke: Predicting stroke cause using imaging and RNA profiling.

Authors:  Katie Kingwell
Journal:  Nat Rev Neurol       Date:  2012-05-07       Impact factor: 42.937

7.  Biomarker panels in ischemic stroke.

Authors:  Glen C Jickling; Frank R Sharp
Journal:  Stroke       Date:  2015-02-05       Impact factor: 7.914

Review 8.  Whole genome expression of cellular response to stroke.

Authors:  Frank R Sharp; Glen C Jickling
Journal:  Stroke       Date:  2013-06       Impact factor: 7.914

Review 9.  Cryptogenic stroke: how to define it? How to treat it?

Authors:  Ava L Liberman; Shyam Prabhakaran
Journal:  Curr Cardiol Rep       Date:  2013-12       Impact factor: 2.931

Review 10.  RNA expression studies in stroke: what can they tell us about stroke mechanism?

Authors:  Sarina Falcione; Joseph Kamtchum-Tatuene; Gina Sykes; Glen C Jickling
Journal:  Curr Opin Neurol       Date:  2020-02       Impact factor: 5.710

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