Diagnostic blood RNA profiles for human acute spinal cord injury
Nikos Kyritsis, Abel Torres-Espín, Patrick G Schupp, J Russell Huie, Austin Chou, Xuan Duong-Fernandez, Leigh H Thomas, Rachel E Tsolinas, Debra D Hemmerle, Lisa U Pascual, Vineeta Singh, Jonathan Z Pan, Jason F Talbott, William D Whetstone, John F Burke, Anthony M DiGiorgio, Philip R Weinstein, Geoffrey T Manley, Sanjay S Dhall, Adam R Ferguson, Michael C Oldham, Jacqueline C Bresnahan, Michael S Beattie
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.