Bioinformatics analysis of ferroptosis in spinal cord injury

Abstract

Ferroptosis plays a key role in aggravating the progression of spinal cord injury (SCI), but the specific mechanism remains unknown. In this study, we constructed a rat model of T10 SCI using a modified Allen method. We identified 48, 44, and 27 ferroptosis genes that were differentially expressed at 1, 3, and 7 days after SCI induction. Compared with the sham group and other SCI subgroups, the subgroup at 1 day after SCI showed increased expression of the ferroptosis marker acyl-CoA synthetase long-chain family member 4 and the oxidative stress marker malondialdehyde in the injured spinal cord while glutathione in the injured spinal cord was lower. These findings with our bioinformatics results suggested that 1 day after SCI was the important period of ferroptosis progression. Bioinformatics analysis identified the following top ten hub ferroptosis genes in the subgroup at 1 day after SCI: STAT3, JUN, TLR4, ATF3, HMOX1, MAPK1, MAPK9, PTGS2, VEGFA, and RELA. Real-time polymerase chain reaction on rat spinal cord tissue confirmed that STAT3, JUN, TLR4, ATF3, HMOX1, PTGS2, and RELA mRNA levels were up-regulated and VEGFA, MAPK1 and MAPK9 mRNA levels were down-regulated. Ten potential compounds were predicted using the DSigDB database as potential drugs or molecules targeting ferroptosis to repair SCI. We also constructed a ferroptosis-related mRNA-miRNA-lncRNA network in SCI that included 66 lncRNAs, 10 miRNAs, and 12 genes. Our results help further the understanding of the mechanism underlying ferroptosis in SCI.

Keywords

• bioinformatics; drug; ferroptosis; gene ontology enrichment analysis; gene-mirna network; kyoto encyclopedia of genes and genomes pathway; mrna-mirna-lncrna network; progression; spinal cord injury