Identification of a potential novel biomarker in intervertebral disk degeneration by bioinformatics analysis and experimental validation - Yang, Zhao; Yuan, Zhen-Zhen; Ma, Xin-Long (Frontiers in Immunology, 2023)
Background: Intervertebral disc degeneration (IVDD) is one of the most common health problems all over the world. However, the early diagnosis of IVDD is still restricted. The purpose of this study is to identify and validate the key characteristic gene of IVDD and analyze its correlation with immune cell infiltration. Methods: 3 IVDD-related gene expression profiles were downloaded from the GEO database to screen for differentially expressed genes (DEGs). GO and GSEA were conducted to explore the biological functions. 2 machine learning algorithms were used to identify characteristic genes, which were tested to further find the key characteristic gene. The ROC curve was performed to estimate the clinical diagnostic value of key characteristic gene. The excised human intervertebral discs were obtained, and the normal nucleus pulposus (NP) and degenerative NP were carefully separated and cultured in vitro. The expression of key characteristic gene was validated by qRT-PCR. Finally, the Correlation was investigated between key characteristic gene and immune cells infiltration. Results: A total of 5 DEGs, including 3 up-regulated genes and 2 down-regulated genes, were screened between IVDD and control samples. GO Enrichment Analysis showed that DEGs were enriched to 4 items in BP, 6 items in CC, and 13 items in MF. They mainly included regulation of ion transmembrane transport, transporter complex and channel activity, etc. GSEA suggested that cell cycle, DNA replication, graft versus host disease and nucleotide excision repair were enriched in control samples, while complement and coagulation cascades, FC gamma R mediated phagocytosis, neuroactive ligand receptor interaction, NOD-like receptor signaling pathway, gap junctions, etc. were enriched in IVDD samples. Furthermore, ZNF542P was identified and tested as key characteristic gene in IVDD samples through machine learning algorithms and showed a good diagnostic value. The results of qRT-PCR showed that compared with normal NP cells, the expression of ZNF542P gene was decreased in degenerated NP cells. Finally, we found that the expression of ZNF542P was positively related to the proportions of γδT cells. Conclusion: ZNF542P is a potential biomarker in the early diagnosis of IVDD and may influence IVDD by regulating the infiltration of γδT cells.