Dataset Information

Comprehensive analysis of lumbar disc degeneration and autophagy-related candidate genes, pathways, and targeting drugs.

ABSTRACT:

Background

Lumbar disc degeneration (LDD) is an essential pathological mechanism related to low back pain. Current research on spinal surgery focused on the sophisticated mechanisms involved in LDD, and autophagy was regarded as an essential factor in the pathogenesis.

Objectives

Our research aimed to apply a bioinformatics approach to select some candidate genes and signaling pathways in relationship with autophagy and LDD and to figure out potential agents targeting autophagy- and LDD-related genes.

Materials and methods

Text mining was used to find autophagy- and LDD-related genes. The DAVID program was applied in Gene Ontology and pathway analysis after selecting these genes. Several important gene modules were obtained by establishing a network of protein-protein interaction and a functional enrichment analysis. Finally, the selected genes were searched in the drug database to find the agents that target LDD- and autophagy-related genes.

Results

There were 72 genes related to "autophagy" and "LDD." Three significant gene modules (22 genes) were selected by using gene enrichment analysis, which represented 4 signaling pathways targeted by 32 kinds of drugs approved by the Food and Drug Administration (FDA). The interactions between drugs and the genes were also identified.

Conclusion

To conclude, a method was proposed in our research to find candidate genes, pathways, and drugs which were involved in autophagy and LDD. We discovered 22 genes, 4 pathways, and 32 potential agents, which provided a theoretical basis and new direction for clinical and basic research on LDD.

SUBMITTER: Xu WL

PROVIDER: S-EPMC8043061 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The present study aimed to investigate differentially expressed genes (DEGs) in whole blood (WB) obtained from patients with lumbar disc prolapse (LDP) and healthy volunteers. A total of 8 patients with LDP and 8 healthy volunteers were recruited. An Agilent SurePrint G3 human gene expression microarray 8×60 K was used to perform the microarray analyses. R was employed to identify DEGs, which were then subjected to bioinformatics analysis, including a Gene Ontology (GO) analysis, Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis and protein-protein interaction (PPI) network analysis. DEGs in the degenerative annulus fibrosis (AF) and nucleus pulposus (NP) compared with non-degenerative tissues were also identified based on microarray data and the intersections of the three were assessed. Furthermore, reverse transcription-quantitative (RT-q)PCR was performed to confirm the aberrant expression levels of selected DEGs in the WB of all subjects. A total of 161 DEGs between LDP patients and the healthy controls were identified (128 upregulated and 33 downregulated). These DEGs were enriched in 293 biological process, 36 cellular component and 21 molecular function GO terms, as well as in 24 KEGG pathways. The PPI network contained 4 submodules, and Toll-like receptor 4 had the highest degree centrality. A total of 22 DEGs were common to the three groups of DEGs. The RT-qPCR assay confirmed that the expression levels of cytochrome P450 family 27 subfamily A member 1, superoxide dismutase 2, protein disulfide isomerase family A member 4, FKBP prolyl isomerase 11 and ectonucleotide pyrophosphatase/phosphodiesterase 4 were significantly different between the patient group and the volunteer group. In conclusion, several genes were identified as potential biomarkers in WB that should be further explored in future studies to determine their potential application in the clinical treatment and diagnosis of LDP, and the present bioinformatics analysis revealed several GO terms, KEGG pathways and submodules of the PPI network that may be involved in LDP, although the exact mechanisms remain elusive.