Department of Neurology and the MIND Institute, University of California at Davis, Sacramento, CA 95817, USA.
Ann Neurol. 2010 Nov;68(5):681-92. doi: 10.1002/ana.22187.
The cause of stroke remains unknown or cryptogenic in many patients. We sought to determine whether gene expression signatures in blood can distinguish between cardioembolic and large-vessel causes of stroke, and whether these profiles can predict stroke etiology in the cryptogenic group.
A total of 194 samples from 76 acute ischemic stroke patients were analyzed. RNA was isolated from blood and run on Affymetrix U133 Plus2.0 microarrays. Genes that distinguish large-vessel from cardioembolic stroke were determined at 3, 5, and 24 hours following stroke onset. Predictors were evaluated using cross-validation and a separate set of patients with known stroke subtype. The cause of cryptogenic stroke was predicted based on a model developed from strokes of known cause and identified predictors.
A 40-gene profile differentiated cardioembolic stroke from large-vessel stroke with >95% sensitivity and specificity. A separate 37-gene profile differentiated cardioembolic stroke due to atrial fibrillation from nonatrial fibrillation causes with >90% sensitivity and specificity. The identified genes elucidate differences in inflammation between stroke subtypes. When applied to patients with cryptogenic stroke, 17% are predicted to be large-vessel and 41% to be cardioembolic stroke. Of the cryptogenic strokes predicted to be cardioembolic, 27% were predicted to have atrial fibrillation.
Gene expression signatures distinguish cardioembolic from large-vessel causes of ischemic stroke. These gene profiles may add valuable diagnostic information in the management of patients with stroke of unknown etiology though they need to be validated in future independent, large studies.
许多患者的中风病因仍然未知或为隐源性的。我们旨在确定血液中的基因表达谱是否可以区分心源性栓塞和大血管病变引起的中风,以及这些特征是否可以预测隐源性中风患者的病因。
共分析了 76 例急性缺血性中风患者的 194 个样本。从血液中分离 RNA 并在 Affymetrix U133 Plus2.0 微阵列上运行。在中风发作后 3、5 和 24 小时确定区分大血管和心源性栓塞性中风的基因。使用交叉验证和一组已知中风亚型的患者来评估预测因子。根据已知病因和识别出的预测因子建立的模型来预测隐源性中风的病因。
一个 40 基因的特征可以区分心源性栓塞性中风和大血管性中风,具有>95%的敏感性和特异性。另一个独立的 37 基因特征可以区分房颤引起的心源性栓塞性中风和非房颤性中风,具有>90%的敏感性和特异性。鉴定出的基因阐明了中风亚型之间炎症的差异。当应用于隐源性中风患者时,17%的患者被预测为大血管性中风,41%的患者被预测为心源性栓塞性中风。在预测为心源性栓塞的隐源性中风中,27%的患者被预测为房颤。
基因表达谱可以区分心源性栓塞和缺血性中风的大血管病因。这些基因谱可能会在未知病因中风患者的管理中提供有价值的诊断信息,尽管它们需要在未来的独立、大型研究中进行验证。