Genes In Spinal Cord Injury Research Articles

Identification of immune-related hub genes in spinal cord injury

ObjectivesImmune regulation is a pivotal factor in the pathogenesis and repair of spinal cord injury (SCI). This study aims to explore potential immune center genes associated with spinal cord injury.MethodsThe public data set GSE151371 was obtained from the GEO database. The R software package "limma" was used to identify differentially expressed genes (DEGs) in SCI. GO, KEGG and GSEA pathway analyses were performed using the DEGs. The key module genes related to spinal cord injury were selected through WGCNA analysis. Overlapping genes were extracted from WGCNA, DEGs, and immune-related genes. LASSO analysis was employed to identify central genes associated with SCI immunity. Pearson correlation analysis assessed the correlation between hub genes and immune cells in SCI. In addition, we further investigated the hub genes' expression, diagnostic potential, function, and targeted drugs.ResultsWe have identified three immunity-related hub genes (ABHD5, EDNRB, EDN3). Immune infiltration analysis showed that the hub gene was significantly associated with resting NK cells, M2 macrophages, and monocytes in the immune microenvironment of SCI. ROC analysis demonstrated that these hub genes have favorable diagnostic performance for SCI. Functional analysis revealed that ABHD5 is primarily associated with lipid metabolism pathways, while EDN3 and EDNRB are mainly involved in endothelin, downstream GPCR signaling, and ERK signaling transduction. In addition, we identified six potential targeted drugs based on our findings.ConclusionsABHD5, EDNRB, and EDN3 are involved in processes such as SCI progression or repair through immunomodulation and deserve further study.

Identification of Anoikis-Related Genes in Spinal Cord Injury: Bioinformatics and Experimental Validation.

Spinal cord injury (SCI) is a serious disease without effective therapeutic strategies. To identify the potential treatments for SCI, it is extremely important to explore the underlying mechanism. Current studies demonstrate that anoikis might play an important role in SCI. In this study, we aimed to identify the key anoikis-related genes (ARGs) providing therapeutic targets for SCI. The mRNA expression matrix of GSE45006 was downloaded from the Gene Expression Omnibus (GEO) database, and the ARGs were downloaded from the Molecular Signatures Database (MSigDB database). Then, the potential differentially expressed ARGs were identified. Next, correlation analysis, gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) analysis were employed for the differentially expressed ARGs. Moreover, miRNA-gene networks were constructed by the hub ARGs. Finally, RNA expression of the top ten hub ARGs was validated in the SCI cell model and rat SCI model. A total of 27 common differentially expressed ARGs were identified at different time points (1, 3, 7, and 14days) following SCI. The GO and KEGG enrichment analysis of these ARGs indicated several enriched terms related to proliferation, cell cycle, and apoptotic process. The PPI results revealed that most of the ARGs interacted with each other. Ten hub ARGs were further screened, and all the 10 genes were validated in the SCI cell model. In the rat model, only seven genes were validated eventually. We identified 27 differentially expressed ARGs of the SCI through bioinformatic analysis. Seven real hub ARGs (CCND1, FN1, IGF1, MYC, STAT3, TGFB1, and TP53) were identified eventually. These results may expand our understanding of SCI and contribute to the exploration of potential SCI targets.

Temporal profiling and validation of oxidative stress-related genes in spinal cord injury

Oxidative stress (OS) plays a pivotal role in the pathogenesis of spinal cord injury (SCI), yet its underlying mechanisms remain elusive. In this study, we explored the OS phenotype in a rat model of SCI. Subsequently, comprehensive bioinformatic analyses were conducted on microarray data pertaining to SCI (GSE45006). Notably, KEGG enrichment analysis revealed a pronounced enrichment of pivotal pathways, namely MAPK, FoxO, Apoptosis, NF-κB, TNF, HIF-1, and Chemokine across distinct phases of SCI. Furthermore, GO enrichment analysis highlighted the significance of biological processes including response to hypoxia, response to decrease oxygen levels, response to reactive oxygen species, cellular response to oxidative stress, reactive oxygen species metabolic process, and regulation of neuron death in the context of OS following SCI. Notably, our study underscores the prominence of nine genes, namely Itgb1, Itgam, Fn1, Icam1, Cd44, Cxcr4, Ptprc, Tlr4, and Tlr2 as OS key genes in SCI, consistently expressed in both the acute phase (1, 3, 7 days) and sub-acute phase (14 days). Subsequently, the relative mRNA expression of these key genes in different time points (1, 3, 7, 14 days) post-SCI. Finally, leveraging the DsigDB database, we predicted ten potential compounds potentially targeting OS and facilitating the repair of SCI, thus providing novel insights into the mechanisms underlying OS and identifying potential therapeutic targets for SCI.

Identification of Ferroptotic Genes in Spinal Cord Injury at Different Time Points: Bioinformatics and Experimental Validation.

Programmed cell death (PCD) is an important pathologic process after spinal cord injury (SCI). As a new type of PCD, ferroptosis is involved in the secondary SCI. However, the underlying molecular mechanism remains unclear. In this study, we validated ferroptotic phenotype in an animal model of SCI. Then, the bioinformatic analyses performed on a microarray data of SCI (GSE45006). KEGG analysis suggested that the pathways of mTOR, HIF-1, VEGF, and protein process in endoplasmic reticulum were involved in SCI-induced ferroptosis. GO analysis revealed that oxidative stress, amide metabolic process, cation transport, and cytokine production were essential biological processes in ferroptosis after SCI. We highlighted five genes including ATF-3, XBP-1, HMOX-1, DDIT-3, and CHAC-1 as ferroptotic key gene in SCI. These results contribute to exploring the ferroptotic mechanism underlying the secondary SCI and providing potential targets for clinical treatment.

CRISPR gRNA phenotypic screening in zebrafish reveals pro-regenerative genes in spinal cord injury.

Zebrafish exhibit robust regeneration following spinal cord injury, promoted by macrophages that control post-injury inflammation. However, the mechanistic basis of how macrophages regulate regeneration is poorly understood. To address this gap in understanding, we conducted a rapid in vivo phenotypic screen for macrophage-related genes that promote regeneration after spinal injury. We used acute injection of synthetic RNA Oligo CRISPR guide RNAs (sCrRNAs) that were pre-screened for high activity in vivo. Pre-screening of over 350 sCrRNAs allowed us to rapidly identify highly active sCrRNAs (up to half, abbreviated as haCRs) and to effectively target 30 potentially macrophage-related genes. Disruption of 10 of these genes impaired axonal regeneration following spinal cord injury. We selected 5 genes for further analysis and generated stable mutants using haCRs. Four of these mutants (tgfb1a, tgfb3, tnfa, sparc) retained the acute haCR phenotype, validating the approach. Mechanistically, tgfb1a haCR-injected and stable mutant zebrafish fail to resolve post-injury inflammation, indicated by prolonged presence of neutrophils and increased levels of il1b expression. Inhibition of Il-1β rescues the impaired axon regeneration in the tgfb1a mutant. Hence, our rapid and scalable screening approach has identified functional regulators of spinal cord regeneration, but can be applied to any biological function of interest.

Analysis of the potential pathways and target genes in spinal cord injury using bioinformatics methods

Spinal cord injury (SCI) remains to be the most devastating type of trauma for patients because of long lasting disability and limited response to the acute drug administration and efforts at rehabilitation. With the purpose to identify potential targets for SCI treatment and to gain more insights into the mechanisms of SCI, the microarray data of GSE2270, including 119 raphe magnus (RM) samples and 125 sensorimotor cortex (SMTC) samples, was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened in RM group and SMTC group compared with their corresponding controls, respectively. A protein–protein interaction (PPI) network was constructed based on the common DEGs identified in both RM group and SMTC group. Gene ontology (GO) and pathway enrichment analyses of the overlapping DEGs were performed. Furthermore, the common DEGs enriched in each pathway were analyzed to identify significant regulatory elements. Totally, 173 overlapping DEGs (130 up-regulated and 43 down-regulated) were identified in both RM and SMTC samples. These overlapping DEGs were enriched in different GO terms. Pathway enrichment analysis revealed that DEGs were mainly related to inflammation and immunity. CD68 molecule (CD68) was a hub protein in the PPI network. Moreover, the regulatory network showed that ras-related C3 botulinum toxin substrate 2 (RAC2), CD44 molecule (CD44), and actin related protein 2/3 complex (ARPC1B) were hub genes. RAC2, CD44, and ARPC1B may be significantly involved in the pathogenesis of SCI by participating significant pathways such as extracellular matrix-receptor signaling pathway and Toll-like receptor signaling pathway.

Retraction Note to: Analyzing time-series microarray data reveals key genes in spinal cord injury.

Although many scholars have utilized high-throughput microarrays to delineate gene expression patterns after spinal cord injury (SCI), no study has evaluated gene changes in raphe magnus (RM) and somatomotor cortex (SMTC), two areas in brain primarily affected by SCI. In present study, we aimed to analyze the differentially expressed genes (DEGs) of RM and SMTC between SCI model and sham injured control at 4, 24 h, 7, 14, 28 days, and 3 months using microarray dataset GSE2270 downloaded from gene expression omnibus and unpaired significance analysis of microarray method. Protein–protein interaction (PPI) network was constructed for DEGs at crucial time points and significant biological functions were enriched using DAVID. The results indicated that more DEGs were identified at 14 days in RM and at 4 h/3 months in SMTC after SCI. In the PPI network for DEGs at 14 days in RM, interleukin 6, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), FBJ murine osteosarcoma viral oncogene homolog (FOS), tumor necrosis factor, and nuclear receptor subfamily 3, group C, member 1 (glucocorticoid receptor) were the top 5 hub genes; In the PPI network for DEGs at 3 months in SMTC, the top 5 hub genes were ubiquitin B, Ras‐related C3 botulinum toxin substrate 1 (rho family, small GTP binding protein Rac1), FOS, Janus kinase 2 and vascular endothelial growth factor A. Hedgehog and Wnt signaling pathways were the top 2 significant pathways in RM. These hub DEGs and pathways may be underlying therapeutic targets for SCI.

Gene sequence analysis and screening of feature genes in spinal cord injury.

The aim of the present study was to screen for feature genes associated with spinal cord injury (SCI), in order to identify the underlying pathogenic mechanisms. Differentially expressed genes were screened for using pre‑processing data. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed to analyze and identify the genes involved in pathways associated with SCI. Subsequently, Gene Ontology enrichment analysis and Uniprot tissue analysis were used to screen out genes specifically expressed in spinal cord tissue. In addition, a protein‑protein interaction network was used to demonstrate possible associations among SCI‑associated feature genes. Finally, a link was identified between feature genes and SCI by analyzing protein domains in coding areas of the three feature genes. The cytochrome c oxidase subunit Va, adenosine triphosphate (ATP) synthase, H+ transporting, mitochondrial F1 complex, α subunit 1 and cardiac muscle and mitochondrial β‑F1‑ATPase may be downregulated in SCI, resulting in destruction of the mitochondrial electron transport chain and membrane‑bound enzyme complexes/ion transporters, thus, affecting the normal function of nerves. The three screened feature genes have the potential to become candidate target molecules to monitor, diagnose and treat SCI and may be beneficial for the early diagnosis and therapeutic control of the condition.

RETRACTED ARTICLE: Analyzing time-series microarray data reveals key genes in spinal cord injury

Although many scholars have utilized high-throughput microarrays to delineate gene expression patterns after spinal cord injury (SCI), no study has evaluated gene changes in raphe magnus (RM) and somatomotor cortex (SMTC), two areas in brain primarily affected by SCI. In present study, we aimed to analyze the differentially expressed genes (DEGs) of RM and SMTC between SCI model and sham injured control at 4, 24 h, 7, 14, 28 days, and 3 months using microarray dataset GSE2270 downloaded from gene expression omnibus and unpaired significance analysis of microarray method. Protein-protein interaction (PPI) network was constructed for DEGs at crucial time points and significant biological functions were enriched using DAVID. The results indicated that more DEGs were identified at 14 days in RM and at 4 h/3 months in SMTC after SCI. In the PPI network for DEGs at 14 days in RM, interleukin 6, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), FBJ murine osteosarcoma viral oncogene homolog (FOS), tumor necrosis factor, and nuclear receptor subfamily 3, group C, member 1 (glucocorticoid receptor) were the top 5 hub genes; In the PPI network for DEGs at 3 months in SMTC, the top 5 hub genes were ubiquitin B, Ras-related C3 botulinum toxin substrate 1 (rho family, small GTP binding protein Rac1), FOS, Janus kinase 2 and vascular endothelial growth factor A. Hedgehog and Wnt signaling pathways were the top 2 significant pathways in RM. These hub DEGs and pathways may be underlying therapeutic targets for SCI.

Bayesian Variable Selection for Gene Expression Modeling With Regulatory Motif Binding Sites in Neuroinflammatory Events

Multiple transcription factors (TFs) coordinately control transcriptional regulation of genes in eukaryotes. Although numerous computational methods focus on the identification of individual TF-binding sites (TFBSs), very few consider the interdependence among these sites. In this article, we studied the relationship between TFBSs and microarray gene expression levels using both family-wise and memberspecific motifs, under various combination of regression models with Bayesian variable selection, as well as motif scoring and sharing conditions, in order to account for the coordination complexity of transcription regulation. We proposed a three-step approach to model the relationship. In the first step, we preprocessed microarray data and used p-values and expression ratios to preselect upregulated and downregulated genes. The second step aimed to identify and score individual TFBSs within DNA sequence of each gene. A method based on the degree of similarity and the number of TFBSs was employed to calculate the score of each TFBS in each gene sequence. In the last step, linear regression and probit regression were used to build a predictive model of gene expression outcomes using these TFBSs as predictors. Given a certain number of predictors to be used, a full search of all possible predictor sets is usually combinatorially prohibitive. Therefore, this article considered the Bayesian variable selection for prediction using either of the regression models. The Bayesian variable selection has been applied in the context of gene selection, missing value estimation, and regulatory motif identification. In our modeling, the regressor was approximated as a linear combination of the TFBSs and a Gibbs sampler was employed to find the strongest TFBSs. We applied these regression models with the Bayesian variable selection on spinal cord injury gene expression data set. These TFs demonstrated intricate regulatory roles either as a family or as individual members in neuroinflammatory events. Our analysis can be applied to create plausible hypotheses for combinatorial regulation by TFBSs and avoiding false-positive candidates in the modeling process at the same time. Such a systematic approach provides the possibility to dissect transcription regulation, from a more comprehensive perspective, through which phenotypical events at cellular and tissue levels are moved forward by molecular events at gene transcription and translation levels.

The experimental study of hypoxia-inducible factor-1α and its target genes in spinal cord injury

Animal model of compressive spinal cord injury (SCI), reverse transcription-polymerase chain reaction (RT-PCR), in situ hybridization (ISH), immunohistochemistry (IHC) and enzymehistochemistry (EHC) were used to test the hypothesis that hypoxia-inducible factor-1alpha (HIF-1alpha) and the target genes activated by HIF-1alpha are involved in cell hypoxia tolerance and tissue vascularity to help injured tissue to go through the stress disease. To determine whether HIF-1alpha and its target genes associated with hypoxia tolerance and neovascularization take part in the pathophysiological procedure of SCI in rats. Yunnan University, China. Random-bred adult male Sprague-Dawley (SD) rats weighing 250+/-50 g were prepared for compressive SCI models. After receiving compressive injury at T(10), rats were sacrificed at different times from 6 h to 1 week after injury. The injured cords were removed, and HIF-1alpha and its target genes were assayed by RT-PCR, ISH, IHC and EHC. The data were statistically analyzed. An increase in HIF-1alpha mRNA expression was observed 12 h postinjury, reached a maximum at 3 days, and reduced gradually thereafter. HIF-1alpha protein expressed earlier than HIF-1alpha mRNA. Additionally, two glycolytic enzymes and vascular endothelial growth factor (VEGF), which are regulated by HIF-1alpha, also increased after an interval postinjury, and their expression patterns shared a same trend with that of HIF-1alpha protein. The findings suggested that the most important hypoxic regulatory factor HIF-1alpha was upregulated in involved cells by activating the transcription and increasing protein stability, and subsequently activated the expression of HIF-1alpha target genes, including glycolytic enzymes and VEGF in SCI. Combined with the pathologic observation, it suggested that overexpression of HIF-1alpha and its target genes might take part in hypoxia tolerance and vascularity of the injured spinal cord.