Nogo-A Is a Potential Prognostic Marker for Spinal Cord Injury.

Abstract

Objective Spinal cord injury (SCI) has become prevalent worldwide in recent years, and its prognosis is poor and the pathological mechanism has not been fully elucidated. Nogo-A is one of the isoforms of the neurite outgrowth inhibitory protein reticulon 4. The purpose of this study was to determine whether Nogo-A could be used as a marker for predicting the prognosis of SCI. Methods We screened eligible SCI patients and controls based on inclusion and exclusion criteria. We also collected baseline clinical information and peripheral venous blood of the enrolled population. Participants' baseline serum Nogo-A levels were measured by enzyme-linked immunosorbent assay (ELISA). The American Spinal Injury Association (ASIA) scale was used to evaluate the prognosis of SCI patients after 3 months. Results Baseline clinical information (age; gender; smoking; drinking; SBP, systolic blood pressure; DBP, diastolic blood pressure; fasting blood glucose; WBC, white blood cells; CRP, C-reactive protein) of SCI patients and controls were not statistically significant academic differences (p > 0.05). The baseline serum Nogo-A levels of SCI patients and controls were 192.7 ± 13.9 ng/ml and 263.1 ± 22.4 ng/ml, respectively, and there was a statistically significant difference between the two groups (p < 0.05). We divided SCI patients into 4 groups according to their baseline serum Nogo-A quartile levels and analyzed their relationship with ASIA scores. The trend test results showed that with the increase of Nogo-A level, the ASIA sensation score and ASIA motor score were significantly decreased (p < 0.001). Multivariate regression analysis showed that serum Nogo-A levels remained a potential cause affecting the prognosis of SCI after adjusting for confounding factors in multiple models. Conclusions Serum Nogo-A levels were significantly elevated in SCI patients. Moreover, elevated Nogo-A levels often indicate poor prognosis and can be used as a marker to predict the prognosis of SCI.