Weill Institute for Neurosciences, Brain and Spinal Injury Center, University of California, San Francisco, San Francisco, CA.
Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA.
J Exp Med. 2021 Mar 1;218(3). doi: 10.1084/jem.20201795.
Diagnosis of spinal cord injury (SCI) severity at the ultra-acute stage is of great importance for emergency clinical care of patients as well as for potential enrollment into clinical trials. The lack of a diagnostic biomarker for SCI has played a major role in the poor results of clinical trials. We analyzed global gene expression in peripheral white blood cells during the acute injury phase and identified 197 genes whose expression changed after SCI compared with healthy and trauma controls and in direct relation to SCI severity. Unsupervised coexpression network analysis identified several gene modules that predicted injury severity (AIS grades) with an overall accuracy of 72.7% and included signatures of immune cell subtypes. Specifically, for complete SCIs (AIS A), ROC analysis showed impressive specificity and sensitivity (AUC: 0.865). Similar precision was also shown for AIS D SCIs (AUC: 0.938). Our findings indicate that global transcriptomic changes in peripheral blood cells have diagnostic and potentially prognostic value for SCI severity.
脊髓损伤 (SCI) 在超急性阶段的严重程度诊断对于患者的紧急临床护理以及潜在的临床试验入组都非常重要。缺乏 SCI 的诊断生物标志物是临床试验结果不佳的主要原因。我们分析了急性损伤阶段外周血白细胞中的全球基因表达,发现了 197 个基因,这些基因的表达在 SCI 后与健康和创伤对照组相比发生了变化,并且与 SCI 严重程度直接相关。无监督的共表达网络分析确定了几个基因模块,这些模块可以预测损伤严重程度 (AIS 等级),整体准确率为 72.7%,并包含免疫细胞亚型的特征。具体来说,对于完全性 SCI (AIS A),ROC 分析显示出令人印象深刻的特异性和敏感性 (AUC:0.865)。对于 AIS D SCI,也显示出了类似的精度 (AUC:0.938)。我们的研究结果表明,外周血细胞的全转录组变化对 SCI 严重程度具有诊断和潜在的预后价值。