Bioinformatics analysis and experimental validation of key genes associated with lumbar disc degeneration and biomechanics

Abstract

Background: Lumbar disc degeneration (LDD) is an important pathological basis for the development of degenerative diseases of the lumbar spine. Most clinical patients have low back pain as their main symptom. The deterioration of the biomechanical environment is an important cause of LDD. Although there is a large amount of basic research on LDD, there are fewer reports that correlate biomechanical mechanisms with basic research. Our research aims to identify 304 key genes involved in LDD due to biomechanical deterioration, using a bioinformatics approach. We focus on SMAD3, CAV1, SMAD7, TGFB1 as hub genes, and screen for 30 potential target drugs, offering novel insights into LDD pathology and treatment options.

Methods: The Gene Cards, GenCLip3, OMIM and Drugbank databases were explored to obtain genes associated with biomechanics and LDD, followed by making veen plots to obtain both co-expressed genes. GO enrichment analysis and KEGG pathway analysis of the co-expressed genes were obtained using the DAVID online platform and visualised via a free online website. Protein interaction networks (PPI) were obtained through the STRING platform and visualised through Cytoscape 3.9.0. These genes were predicted for downstream interaction networks using the STITCH platform. Then, the GSE56081 dataset was used to validate the key genes. RT-PCR was used to detect mRNA expression of core genes in the degenerated nucleus pulposus (NP) samples and western bolt was used for protein expression. Lastly, the obtained hub genes were searched in the drug database (DGIdb) to find relevant drug candidates.

Results: From the perspective of biomechanics-induced LDD, we obtained a total of 304 genes, the GO functional enrichment and KEGG pathway enrichment analysis showed that the functions of these genes are mostly related to inflammation and apoptosis. The PPI network was constructed and four Hub genes were obtained through the plug-in of Cytoscape software, namely SMAD3, CAV1, SMAD7 and TGFB1. The analysis of key genes revealed that biomechanical involvement in LDD may be related to the TGF-β signaling pathway. Validation of the GSE56081 dataset revealed that SMAD3 and TGFB1 were highly expressed in degenerating NP samples. RT-PCR results showed that the mRNA expression of SMAD3 and TGFB1 was significantly increased in the severe degeneration group; Western blot results also showed that the protein expression of TGFB1 and P-SMAD3 was significantly increased. In addition, we identified 30 potential drugs.

Conclusion: This study presented a new approach to investigate the correlation between biomechanical mechanisms and LDD. The deterioration of the biomechanical environment may cause LDD through the TGF-β signaling pathway. TGFB1 and SMAD3 are important core targets. The important genes, pathways and drugs obtained in this study provided a new basis and direction for the study, diagnosis and treatment of LDD.

Keywords: Bioinformatics; Biomechanics; Genes; Lumbar disc degeneration; Targeted drugs.

Fig. 1

Venn map of A (Disc degeneration) and B (Biomechanics) targets. A total of 304 targets are shared between these two groups.

Fig. 2

GO Functional enrichment histogram related to Biomechanics and LDD. This represents the top ten GO enrichment results, categorized as BP (Biological Process), CC (Cellular Component), and MF (Molecular Function).

Fig. 3

Bubble diagram of KEGG pathway enrichment. A total of 304 genes are associated with various pathways including the tumor necrosis factor signaling pathway, cytokine-cytokine receptor interaction, osteoclast differentiation, the PI3K-Akt signaling pathway, and rheumatoid arthritis.

Fig. 4

PPI network from the 304 genes. PPI network of the 304 genes obtained from STRING and Cytoscape software.

Fig. 5

Network diagram of the 3 clusters. (A) Cluster1 incluede 7 density and 21 nodes; (B) Cluster2 incluede 5 density and 10 nodes; (C) Cluster3 incluede 11 density and 22 nodes.

Fig. 6

Ranked display of the top 11 core genes. (A) Construction of network among 4 hub genes; (B) Coexpression analysis of 4 hub genes.

Fig. 7

Targetable four hub genes (SMAD3, CAV1, SMAD7 and TGFB1) subnetworks. (A) Downstream interaction network for SMAD3; (B) Downstream interaction network for CAV1; (C) Downstream interaction network for SMAD7; (D) Downstream interaction network for TGFB1.

Fig. 8

Validation violin map of hub genes in GSE56081. CAV1 and SMAD7 exhibit no significant differences between the NC (Normal Control) and IDD (Intervertebral Disc Degeneration) groups. TGFB1 and SMAD3 have been identified as crucial targets for IDD.

Fig. 9

Relative mRNA expressions of TGFB1 and SMAD3 in NPS. (A) The mRNA expression of TGFB1 in mild degeneration (MD) and severe degeneration (SD); (B) The mRNA expression of SMAD3 in MD and SD. *p < 0.05 (compared with MD).

Fig. 10

Protein expression of TGFB1 and P-SMAD3. (A) Western blot was employed to measure the relative expressions of TGFB1, p-SMAD3 and SMAD3 in MD and SD; (B) The relative expression of TGFB1; (C) The relative expression of p-SMAD3; (D) The relative expression of SMAD3. *p < 0.05 (compared with MD).

Fig. 11

Overall experiment flowchart. This is a summary of the entire experiment, including a simple flowchart from data collection to analysis to validation.