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Profiles of lacunar and nonlacunar stroke.

ABSTRACT: OBJECTIVE:Determining which small deep infarcts (SDIs) are of lacunar, arterial, or cardioembolic etiology is challenging, but important in delivering optimal stroke prevention therapy. We sought to distinguish lacunar from nonlacunar causes of SDIs using a gene expression profile. METHODS:A total of 184 ischemic strokes were analyzed. Lacunar stroke was defined as a lacunar syndrome with infarction <15mm in a region supplied by penetrating arteries. RNA from blood was processed on whole genome microarrays. Genes differentially expressed between lacunar (n = 30) and nonlacunar strokes (n = 86) were identified (false discovery rate ? 0.05, fold change >|1.5|) and used to develop a prediction model. The model was evaluated by cross-validation and in a second test cohort (n = 36). The etiology of SDIs of unclear cause (SDIs ? 15mm or SDIs with potential embolic source) (n = 32) was predicted using the derived model. RESULTS:A 41-gene profile discriminated lacunar from nonlacunar stroke with >90% sensitivity and specificity. Of the 32 SDIs of unclear cause, 15 were predicted to be lacunar, and 17 were predicted to be nonlacunar. The identified profile represents differences in immune response between lacunar and nonlacunar stroke. INTERPRETATION:Profiles of differentially expressed genes can distinguish lacunar from nonlacunar stroke. SDIs of unclear cause were frequently predicted to be of nonlacunar etiology, suggesting that comprehensive workup of SDIs is important to identify potential cardioembolic and arterial causes. Further study is required to evaluate the gene profile in an independent cohort and determine the clinical and treatment implications of SDIs of predicted nonlacunar etiology.

SUBMITTER: Jickling GC

PROVIDER: S-EPMC3201749 | biostudies-literature | 2011 Sep

REPOSITORIES: biostudies-literature

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Profiles of lacunar and nonlacunar stroke.

Jickling Glen C GC Stamova Boryana B Ander Bradley P BP Zhan Xinhua X Tian Yingfang Y Liu Dazhi D Xu Huichun H Johnston S Claiborne SC Verro Piero P Sharp Frank R FR

Annals of neurology 20110727 3

<h4>Objective</h4>Determining which small deep infarcts (SDIs) are of lacunar, arterial, or cardioembolic etiology is challenging, but important in delivering optimal stroke prevention therapy. We sought to distinguish lacunar from nonlacunar causes of SDIs using a gene expression profile.<h4>Methods</h4>A total of 184 ischemic strokes were analyzed. Lacunar stroke was defined as a lacunar syndrome with infarction <15mm in a region supplied by penetrating arteries. RNA from blood was processed o ...[more]

PMID: 21796664

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Project description:Neuroinflammation is believed to be involved in the pathophysiological mechanisms of silent brain infarcts (SBI). However, the immunological profile of SBI has been scarcely investigated. In the context of a national research project named SILENCE, aimed at investigating clinical, biochemical and pathogenic features of SBI, we have measured the plasma profile of some inflammatory-related molecules in SBI patients (n?=?21), patients with recent lacunar infarcts (LI, n?=?28) and healthy controls (n?=?31), consecutively enrolled in four Italian centres. A panel of chemokines (MIG, CTACK, IL16, SDF1a, MCP1), growth factors (SCF, SCGFb, HGF, IL3), immunoglobulin-type adhesion molecules (ICAM1, VCAM1), proinflammatory cytokines (IL18, INFa2, MIF, IL12p40), cell surface receptors on T-cells (IL2Ra), and inductors of apoptosis (TRAIL) was assessed in plasma samples by Luminex xMAP™ technology. Immunological parameters were compared using non-parametric statistics and performance to distinguish SBI and LI was evaluated by receiver operating characteristic (ROC) analysis. Plasma levels of ICAM1 were significantly higher in both SBI and LI patients as compared to controls (SBI?LI>Ctrl). A different trend was observed for IL16 (SBI<LI>Ctrl), SCF (LI<SBI>Ctrl) and SCGFb (SBI>LI<Ctrl). SBI subjects had significantly increased levels of MIG when compared to controls (LI?SBI>Ctrl) and IL18 when compared to LI patients (Ctrl?SBI>LI). All the other immunological markers did not significantly differ among groups. According to ROC analysis, the best predictor for SBI condition was the chemokine MIG (AUC?=?0.84, sensitivity 86%, specificity 77%), while SCF had the best performance in distinguishing LI patients (AUC?=?0.84, sensitivity 86%, specificity 68%). These results confirm the involvement of inflammatory processes in cerebrovascular disorders, particularly in SBI, a very common age-related condition. The differences in plasma profile of inflammatory molecules may underlie different pathological mechanisms in SBI and LI patients.

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Profiles of lacunar and nonlacunar stroke.

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Profiles of lacunar and nonlacunar stroke.

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