Background: Traumatic brain injury (TBI) has increased in rank among traumatic injuries worldwide. Traumatic brain injury is a serious obstacle given that its complex pathology represents a long-term process. Recently, systems biology strategies such as metabolomics to investigate the multifactorial nature of TBI have facilitated attempts to find biomarkers and probe molecular pathways for its diagnosis and therapy.
Methods:This study included a group of 20 rats with controlled cortical impact and a group of 20 sham rats. We utilized mNSS tests to investigate neurological metabolic impairments on day 1 and day 3. Furthermore, we applied metabolomics and bioinformatics to determine the metabolic perturbation caused by TBI during the acute period in the hippocampus tissue of controlled cortical impact (CCI) rats. Notably, TBI-protein-metabolite subnetworks identified from a database were assessed for associations between metabolites and TBI by the dysregulation of related enzymes and transporters.
Results:Our results identified 7 and 8 biomarkers on day 1 and day 3, respectively.Additionally, related pathway disorders showed effects on arginine and proline metabolism as well as taurine and hypotaurine metabolism on day 3 in acute TBI.Furthermore, according to metabolite-protein database searches, 25 metaboliteprotein pairs were established as causally associated with TBI. Further, bioinformation indicated that these TBI-associated proteins mainly take part in 5′-nucleotidase activity and carboxylic acid transmembrane transport. In addition, interweaved networks were constructed to show that the development of TBI might be affected by metabolite-related proteins and their protein pathways.
Conclusion:The overall results show that acute TBI is susceptible to metabolic disorders, and the joint metabolite-protein network analysis provides a favorable prediction of TBI pathogenesis mechanisms in the brain. The signatures in the hippocampus might be promising for the development of biomarkers and pathways relevant to acute TBI and could further guide testable predictions of the underlying mechanism of TBI.