Dachet Fabien, Bagla Shruti, Keren-Aviram Gal, Morton Andrew, Balan Karina, Saadat Laleh, Valyi-Nagy Tibor, Kupsky William, Song Fei, Dratz Edward, Loeb Jeffrey A
1 Department of Neurology and Rehabilitation, University of Illinois at Chicago, Chicago, IL 60612, USA 2 The Centre for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, MI 48201, USA.
2 The Centre for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, MI 48201, USA.
Brain. 2015 Feb;138(Pt 2):356-70. doi: 10.1093/brain/awu350. Epub 2014 Dec 16.
Although epilepsy is associated with a variety of abnormalities, exactly why some brain regions produce seizures and others do not is not known. We developed a method to identify cellular changes in human epileptic neocortex using transcriptional clustering. A paired analysis of high and low spiking tissues recorded in vivo from 15 patients predicted 11 cell-specific changes together with their 'cellular interactome'. These predictions were validated histologically revealing millimetre-sized 'microlesions' together with a global increase in vascularity and microglia. Microlesions were easily identified in deeper cortical layers using the neuronal marker NeuN, showed a marked reduction in neuronal processes, and were associated with nearby activation of MAPK/CREB signalling, a marker of epileptic activity, in superficial layers. Microlesions constitute a common, undiscovered layer-specific abnormality of neuronal connectivity in human neocortex that may be responsible for many 'non-lesional' forms of epilepsy. The transcriptional clustering approach used here could be applied more broadly to predict cellular differences in other brain and complex tissue disorders.
尽管癫痫与多种异常情况相关,但确切地说,为何某些脑区会引发癫痫发作而其他脑区不会,目前尚不清楚。我们开发了一种利用转录聚类来识别人类癫痫新皮质细胞变化的方法。对15名患者体内记录的高放电和低放电组织进行配对分析,预测出11种细胞特异性变化及其“细胞相互作用组”。这些预测通过组织学验证,揭示了毫米级的“微病变”以及血管生成和小胶质细胞的整体增加。使用神经元标记物NeuN在更深的皮质层中很容易识别出微病变,其显示出神经元突起明显减少,并与浅层中癫痫活动的标志物MAPK/CREB信号通路的附近激活有关。微病变构成了人类新皮质中一种常见的、未被发现的神经元连接层特异性异常,可能是许多“非病变性”癫痫形式的原因。这里使用的转录聚类方法可以更广泛地应用于预测其他脑部和复杂组织疾病中的细胞差异。