Abstract: BACKGROUND: Lactylation plays an important role in spinal cord injury by regulating the immune microenvironment, but its key biomarkers and mechanisms have not been clarified. The present study aims to systematically analyze the association between abnormal lactate metabolism and spinal cord injury based on multiple databases, including the GEO database, and the integration of multiregional spinal cord injury data (covering both European and Asian populations). By mining the regulatory network of lactation-related genes, we can reveal the new mechanism of metabolism-immunity interaction and predict the target drugs, which will provide a theoretical basis for the development of therapeutic strategies.
OBJECTIVE: To screen core biomarkers related to lactylation in spinal cord injury, to analyze their regulatory mechanisms, and to predict potential active components of traditional Chinese medicine.
METHODS: The study integrated three spinal cord injury datasets (GSE45006, GSE114426, and GSE2599, containing 30 spinal cord injury and 10 normal samples) and validation set (GSE151371, 58 samples) from the GEO database (maintained by NCBI, which contains global public gene expression profiles), combined with the MSigDB database (developed by the Broad Institute for gene function annotation) of 395 lactate-related genes, and screened the core genes by differential expression analysis, weighted gene co-expression network, and machine learning algorithms (LASSO, XGBoost, and Random Forest). Sample data from a total of 815 376 samples from the Integrated Epidemiological Unit (IEU) database (a repository developed and maintained by the MRC Integrated Epidemiological Unit for storing and sharing genome-wide association study (GWAS) data) and Mendelian randomization analyses were used to validate causal association between lactate metabolism and spinal cord injury, followed by immune infiltration analysis. The target components were also predicted from ITCM and HERB TCM database (constructed by the Chinese Academy of Sciences, covering active ingredients of traditional medicines).
RESULTS AND CONCLUSION: SLC16A7 and ACACA were identified as core lactylation genes associated with spinal cord injury, and their expression was significantly associated with M2 macrophage and T cell infiltration. Mendelian randomization analysis showed that lactate [odds ratio (OR)=1.89, 95% confidence interval (CI): 0.99-3.62] and lactate dehydrogenase (OR=0.34, 95% CI: 0.16-0.74) were significantly causally associated with spinal cord injury (P < 0.05), while SLC16A7 and ACACA were risk factors for spinal cord injury (OR > 1.00). Molecular docking identified quercetin, estradiol and ginseng saponin as active ingredients, which were stable in binding to their targets and met the criteria for drug-like properties. These findings indicate that SLC16A7 and ACACA are biomarkers associated with lactylation in spinal cord injury, and herbal medicines and their active ingredients targeting these genes have potential therapeutic values. To conclude, this study reveals the regulatory role of lactation modification in spinal cord injury based on international standardized databases and European cohort-led multi-omics data. Its methodological framework (e.g., multi-omics integration, Mendelian randomization for causal inference) provides an important reference for biomedical research in China: on the one hand, it promotes cross-ethnic data sharing and validation to make up for the lack of regional samples; on the other hand, it opens up a new pathway for drug development in the treatment of spinal cord injury with the combination of Chinese and Western medicines by tapping into the mechanism of interactions between Chinese herbal medicine’s active ingredients and their targets, which can advance the localization of precision medicine practices..

Key words: lactylation, spinal cord injury, biomarkers, immune infiltration, Mendelian randomization