Establishment of Quantitative Severity Evaluation Model for Spinal Cord Injury by Metabolomic Fingerprinting

Spinal cord injury (SCI) is a devastating event with a limited hope for recovery and represents an enormous public health issue. It is crucial to understand the disturbances in the metabolic network after SCI to identify injury mechanisms and opportunities for treatment intervention. Through plasma 1H-nuclear magnetic resonance (NMR) screening, we identified 15 metabolites that made up an “Eigen-metabolome” capable of distinguishing rats with severe SCI from healthy control rats. Forty enzymes regulated these 15 metabolites in the metabolic network. We also found that 16 metabolites regulated by 130 enzymes in the metabolic network impacted neurobehavioral recovery. Using the Eigen-metabolome, we established a linear discrimination model to cluster rats with severe and mild SCI and control rats into separate groups and identify the interactive relationships between metabolic biomarkers in the global metabolic network. We identified 10 clusters in the global metabolic network and defined them as distinct metabolic disturbance domains of SCI. Metabolic paths such as retinal, glycerophospholipid, arachidonic acid metabolism; NAD–NADPH conversion process, tyrosine metabolism, and cadaverine and putrescine metabolism were included. In summary, we presented a novel interdisciplinary method that integrates metabolomics and global metabolic network analysis to visualize metabolic network disturbances after SCI. Our study demonstrated the systems biological study paradigm that integration of 1H-NMR, metabolomics, and global metabolic network analysis is useful to visualize complex metabolic disturbances after severe SCI. Furthermore, our findings may provide a new quantitative injury severity evaluation model for clinical use.

脊髓损伤（Spinal cord injury, SCI）是一类康复希望渺茫的灾难性事件，亦是重大公共卫生问题。明确脊髓损伤后代谢网络的紊乱特征，对于揭示损伤机制、探寻治疗干预方向至关重要。本研究通过血浆1H-核磁共振（1H-nuclear magnetic resonance, NMR）筛查，鉴定出15种代谢物，共同构成可区分重度脊髓损伤大鼠与健康对照大鼠的“特征代谢组（Eigen-metabolome）”。该代谢网络中共有40种酶调控这15种代谢物。同时本研究发现，代谢网络中由130种酶调控的16种代谢物，可对神经行为恢复产生影响。基于该特征代谢组，本研究构建了线性判别模型，可将重度、轻度脊髓损伤大鼠与对照大鼠划分为不同组别，并揭示全局代谢网络中代谢生物标志物间的相互作用关系。本研究在全局代谢网络中鉴定出10个聚类模块，并将其定义为脊髓损伤特有的代谢紊乱域，涵盖视黄醛代谢、甘油磷脂代谢、花生四烯酸代谢；NAD-NADPH转化过程、酪氨酸代谢，以及尸胺和腐胺代谢等多条代谢通路。综上，本研究提出了一种整合代谢组学与全局代谢网络分析的新型跨学科方法，可用于可视化脊髓损伤后的代谢网络紊乱情况。本研究证实，整合1H-NMR、代谢组学与全局代谢网络分析的系统生物学研究范式，可有效可视化重度脊髓损伤后复杂的代谢紊乱状态。此外，本研究结果可为临床提供一种全新的损伤严重程度量化评估模型。