• Seth Tigchelaar, Rishab Gupta, Casey P Shannon, Femke Streijger, Sunita Sinha, Stephane Flibotte, Michael A Rizzuto, John Street, Scott Paquette, Tamir Ailon, Raphaele Charest-Morin, Nicolas Dea, Charles Fisher, Marcel F Dvorak, Sanjay Dhall, Jean-Marc Mac-Thiong, Stefan Parent, Christopher Bailey, Sean Christie, Kendall Van Keuren-Jensen, Corey Nislow, and Brian K Kwon.
• 1International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, British Columbia, Canada.
• J. Neurotrauma. 2019 Aug 1; 36 (15): 2358-2371.

AbstractSpinal cord injury (SCI) is a devastating condition with variability in injury mechanisms and neurologic recovery. Spinal cord impairment after SCI is measured and classified by a widely accepted standard neurological examination. In the very acute stages post-injury, however, this examination is extremely challenging (and often impossible) to conduct and has modest prognostic value in terms of neurological recovery. The lack of objective tools to classify injury severity and predict outcome is a barrier for clinical trials and thwarts development of therapies for those with SCI. Biological markers (biomarkers) represent a promising, complementary approach to these challenges because they represent an unbiased approach to classify injury severity and predict neurological outcome. Identification of a suitable panel of molecular biomarkers would comprise a fundamental shift in how patients with acute SCI are evaluated, stratified, and treated in clinical trials. MicroRNA are attractive biomarker candidates in neurological disorders for several reasons, including their stability in biological fluids, their conservation between humans and model mammals, and their tissue specificity. In this study, we used next-generation sequencing to identify microRNA associated with injury severity within the cerebrospinal fluid (CSF) and serum of human patients with acute SCI. The CSF and serum samples were obtained 1-5 days post-injury from 39 patients with acute SCI (24 American Spinal Injury Association Impairment Scale [AIS] A, 8 AIS B, 7 AIS C) and from five non-SCI controls. We identified a severity-dependent pattern of change in microRNA expression in CSF and identified a set of microRNA that are diagnostic of baseline AIS classification and prognostic of neurological outcome six months post-injury. The data presented here provide a comprehensive description of the CSF and serum microRNA expression changes that occur after acute human SCI. This data set reveals microRNA candidates that warrant further evaluation as biomarkers of injury severity after SCI and as key regulators in other neurological disorders.

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