Hub Genes and Key Pathways of Intervertebral Disc Degeneration: Bioinformatics Analysis and Validation

Zhang, Zhi-wen; Wang, Qiong; Li, Yang; Li, Bang-zhi; Zheng, Liming; He, Chengjian

doi:10.1155/2021/5340449

Cited by 7 publications

(10 citation statements)

References 71 publications

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“…In contrast, KEGG analysis was mainly enriched in the TGF beta signaling pathway, toll-like receiver signaling pathway, TNF signaling pathway, and other pathways. This is essentially the same as the results of the previous study [ 37 , 38 ]. The main pathological changes in IDD are apoptosis of the NPCs and degradation of the extracellular matrix [ 39 , 40 ].…”

Section: Discussionsupporting

confidence: 90%

Identification of SMIM1 and SEZ6L2 as Potential Biomarkers for Genes Associated with Intervertebral Disc Degeneration in Pyroptosis

et al. 2022

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Background. Inflammatory reactions and pyroptosis play an important role in the pathology of intervertebral disc degeneration (IDD). The aim of the present study was to investigate pyroptosis in the nucleus pulposus cells (NPCs) of inflammatory induced IDD by bioinformatic methods and to search for possible diagnostic biomarkers. Methods. Gene expression profiles related to IDD were downloaded from the GEO database to identify differentially expressed genes (DEGs) between inflammation-induced IDD and non-inflammatory intervention samples. Pyroptosis genes were then searched for, and their expression in IDD was analyzed. Weighted gene co-expression network analysis (WGCNA) was then used to search for modules of IDD genes associated with pyroptosis and intersected with DEGs to discover candidate genes that would be diagnostically valuable. A LASSO model was developed to screen for genes that met the requirements, and ROC curves were created to clarify the diagnostic value of the genetic markers. Ultimately, the screened genes were further validated, and their diagnostic value assessed by selecting gene sets from the GEO database. RT-PCR was used to assess the mRNA expression of diagnostic markers in the nucleus pulposus (NP). Pan-cancer analysis was applied to demonstrate the expression and prognostic value of the screened genes in various tumors. Results. A total of 733 DEGs were identified in GSE41883 and GSE27494, which were mainly enriched in transmembrane receptor protein serine/threonine, kinase signaling pathway, response to lipopolysaccharide, and other biological processes, and they were mainly related to TGF beta signaling pathway, toll-like receptor signaling pathway, and TNF signaling pathway. A total of 81 genes related to pyroptosis were identified in the literature, and eight genes related to IDD were identified in the Veen diagram, namely, IL1A, IL1B, NOD2, GBP1, IL6, AK1, EEF2K, and PYCARD. Eleven candidate genes were obtained after locating the intersection of pyroptosis-related module genes and DEGs according to WGCNA analysis. A total of six valid genes were obtained after constructing a machine learning model, and five key genes were finally identified after correlation analysis. GSE23132 and GSE56081 validated the candidate genes, and the final IDD-related diagnostic markers were obtained as SMIM1 and SEZ6L2. RT-PCR results indicated that the mRNA expression of both was significantly elevated in IDD. The pan-cancer analysis demonstrated that SMIM1 and SEZ6L2 have important roles in the expression and prognosis of various tumors. Conclusion. In conclusion, this research identifies SMIM1 and SEZ6L2 as important biomarkers of IDD associated with pyroptosis, which will help to unravel the development and pathogenesis of IDD and determine potential therapeutic targets.

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Section: Discussionsupporting

confidence: 90%

Identification of SMIM1 and SEZ6L2 as Potential Biomarkers for Genes Associated with Intervertebral Disc Degeneration in Pyroptosis

et al. 2022

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“…Zhao et al demonstrated that KIF20A can promote tumor cell proliferation and inhibit apoptosis in vivo and in vitro (37). Likewise, Zhang et al [60] confirmed that the mRNA levels of KIF20A were upregulated in degenerative NP tissue than in healthy NP tissue (38). These findings indicate that KIF20A may be a novel target associated with NP cell degeneration.…”

Section: Discussionmentioning

confidence: 85%

“…Likewise, Zhang et al. [60] confirmed that the mRNA levels of KIF20A were upregulated in degenerative NP tissue than in healthy NP tissue ( 38 ). These findings indicate that KIF20A may be a novel target associated with NP cell degeneration.…”

Section: Discussionmentioning

confidence: 89%

Macrophage polarization regulates intervertebral disc degeneration by modulating cell proliferation, inflammation mediator secretion, and extracellular matrix metabolism

Luo

et al. 2022

Front. Immunol.

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Macrophage infiltration and polarization have been increasingly observed in intervertebral disc (IVD) degeneration (IDD). However, their biological roles in IDD are still unrevealed. We harvested conditioned media (CM) derived from a spectrum of macrophages induced from THP-1 cells, and examined how they affect nucleus pulposus cells (NPCs) in vitro, by studying cell proliferation, extracellular matrix (ECM) synthesis, and pro-inflammation expression; and in vivo by injection CM in a rat IDD model. Then, high-throughput sequencing was used to detect differentially expressed genes (DEGs). Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) networks were used to further analysis. Higher CCR7+ (M1 marker) and CD206+ (M2 marker) cell counts were found in the degenerated human IVD tissues as compared with the control. Furthermore, the cell co-culture model showed M1CM attenuated NPC proliferation, downregulated the expression of ECM anabolic genes encoding aggrecan and collagen IIα1, upregulated the expression of ECM catabolic genes encoding MMP-13, and inflammation-related genes encoding IL-1β, IL-6, and IL-12, while M2CM showed contrasting trends. In IDD model, higher histological scores and lower disc height index were found following M1CM treatment, while M2CM exhibited opposite results. M1CM injection decreased ECM anabolic and increased ECM catabolic, as well as the upregulation of inflammation-related genes after 8 weeks treatment, while M2CM slowed down these trends. Finally, a total of 637 upregulated and 655 downregulated genes were detected in M1CM treated NPCs, and 975 upregulated genes and 930 downregulated genes in the M2CM groups. The top 30 GO terms were shown and the most significant KEGG pathway was cell cycle in both groups. Based on the PPI analysis, the five most significant hub genes were PLK1, KIF20A, RRM2, CDC20, and UBE2C in the M1CM groups and RRM2, CCNB1, CDC20, PLK1, and UBE2C in the M2CM groups. In conclusion, macrophage polarization exhibited diverse roles in IDD progression, with M1CM exacerbating cell proliferation suppression and IVD degeneration, while M2CM attenuated IDD development. These findings may facilitate the further elucidation of the role of macrophage polarization in IDD, and provide novel insights into the therapeutic potential of macrophages.

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“…Khan et al (22) showed that the 3-phosphoinositol-dependent protein kinase (PDK) can promote chondrocyte apoptosis in OA through the p38 MAPK signaling pathway (23,24), while Yang et al (25) found DUal-specificity phosphatase (DUSP) overexpression in OA inhibited the activation of MAPK signaling and the expression of the OA-associated matrix. Zhang et al (26) revealed the JAK/STAT signaling pathway was regulated by significantly upregulated by proinflammatory cytokine gene expression, while MMP-13 expression in the IL-1treated human chondrosarcoma cell lines induced JAK2 and STAT1/STAT2 activation and MMP-13 gene expression which was blocked by the pan-tyrosine kinase inhibitor AG490 (27)(28)(29)(30). However, it was also found that treatment of this chondrocyte line with IL-1 also activated p38-MAPK.…”

Section: Discussionmentioning

confidence: 98%

Screening and identification of osteoarthritis related differential genes and construction of a risk prognosis model based on bioinformatics analysis

You¹,

Liu²,

Tan³

2022

Ann Transl Med

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Background: Searching for the production mechanism of synovial lesions helps to find precise therapeutic targets and improve prognosis. The previous identification and screening of differential genes in osteoarthritis (OA) pathogenesis were well combined to further build a risk prognosis model of OA, which is beneficial to the diagnosis and treatment of patients with OA. Methods:The synovia-related chip data sets GSE82107, GSE12021, GSE55457, and GSE55235 were downloaded from the public database of Gene Expression Omnibus (GEO), and 40 cases of synovial tissues of OA and 36 cases of normal synovial tissues were included. R software was used to screen differentially expressed genes (DEGs), Gene Ontology (GO) functional enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The STRING online analysis tool and Cytoscape software were used to further screen key genes, and a prognostic model of OA susceptibility risk was constructed. Results:The results showed 1,921 differential genes, including 762 upregulated genes and 1,159 downregulated genes, which were mainly involved cell growth, cell adhesion, skeletal muscle growth, iron ion binding, ubiquitin protein ligase binding, and hormone receptor binding. Co-acquisition based on 10 key target genes of the protein interaction network, containing CTNNB1, GSK3B, STAT1, RHOC, HDAC9, PSEN1, KDM5C, BACE1, JAK3, and CUL1. The area under the concentration-time curve (AUC) was used to evaluate the prognostic model of OA risk, and the curve results showed that the prognostic model had high accuracy and validity (AUC =0.690).Conclusions: Bioinformatics analysis was applied to screen out the DEG profiles of OA. This may provide functional predictions to provide new ideas for treatment of the disease and may be a biological marker for its diagnosis and a potential target for treatment. The construction of the risk and prognosis model is beneficial to the risk assessment of rehabilitation function recovery of patients with OA, the evaluation of the severity of the disease and the subsequent treatment guidance.

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Hub Genes and Key Pathways of Intervertebral Disc Degeneration: Bioinformatics Analysis and Validation

Cited by 7 publications

References 71 publications

Identification of SMIM1 and SEZ6L2 as Potential Biomarkers for Genes Associated with Intervertebral Disc Degeneration in Pyroptosis

Identification of SMIM1 and SEZ6L2 as Potential Biomarkers for Genes Associated with Intervertebral Disc Degeneration in Pyroptosis

Macrophage polarization regulates intervertebral disc degeneration by modulating cell proliferation, inflammation mediator secretion, and extracellular matrix metabolism

Screening and identification of osteoarthritis related differential genes and construction of a risk prognosis model based on bioinformatics analysis

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