Abstrakt

Biomarkers screening and related functions identification for spinal cord injury based on guilt-by-association

Chun Shan Zheng, Hui Qin Sun, Xiao Mei Dong, Ping Li, Fuqiang Wang

Objective: The aim was to research Spinal Cord Injury (SCI) related genes and functions for postoperative recovery and complications and prevention.

Methods: E-GEOD-18179 was used to screen Differently Expressed Genes (DEGs) between SCI samples and controls. Adjacency matrix was constructed as gene co-expression network. Sub-network was identified based on spearman correlation coefficient. Assortativity coefficient was calculated to represent the relationship among nodes. Gene Ontology (GO) functional enrichment was processed and guilt-byassociation was undertaken.

Results: Total 129 DEGs were obtained and Adjacency matrix with 129 × 129 genes was constructed. There into, TYROBP and MIA were with weight of 0.9695. Total 129 genes were enriched in 127 GO terms, such as molecular function and catalytic activity. K terms and related AUC values were obtained. The guilt-by-association node degrees AUCs were generated. In addition, the optimal list genes were obtained, such as JUN and PTK2B. Finally, optimal GO terms were obtained, such as regulation of signal transduction, positive regulation of macromolecule metabolic process and cellular component organization.

Conclusion: Screened genes including JUN, PTK2B, CCND1 and ADAM8 might be potential genes for SCI postoperative recovery and complications and prevention.