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Bioinformatic analysis and identification of macrophage polarization-related genes in intervertebral disc degeneration.
Liu, Lei; Peng, Shengxin; Shi, Bin; Yu, Gongchang; Liang, Yuanhao; Zhang, Yixiang; Xiao, Wenshan; Xu, Rui.
Afiliación
  • Liu L; Academy of Medical Engineering and Translational Medicine, Tianjin University Tianjin, China.
  • Peng S; Department of Painology, The First Affiliated Hospital of Shandong First Medical University Jinan, Shandong, China.
  • Shi B; School of Rehabilitation Medicine of Binzhou Medical University Yantai, Shandong, China.
  • Yu G; Neck-Shoulder and Lumbocrural Pain Hospital of Shandong First Medical University Jinan, Shandong, China.
  • Liang Y; Neck-Shoulder and Lumbocrural Pain Hospital of Shandong First Medical University Jinan, Shandong, China.
  • Zhang Y; Weifang Medical University Weifang, Shandong, China.
  • Xiao W; Weifang Medical University Weifang, Shandong, China.
  • Xu R; Shandong First Medical University Jinan, Shandong, China.
Am J Transl Res ; 16(5): 1891-1906, 2024.
Article en En | MEDLINE | ID: mdl-38883390
ABSTRACT

BACKGROUND:

The relationship between macrophage polarization-related genes (MPRGs) and intervertebral disc degeneration (IDD) is unclear. The purpose of this study was to identify biomarkers associated with IDD.

METHODS:

Three transcriptome sequencing datasets, GSE124272, GSE70362 and GSE56081 were included in this study. Differential expressed genes (DEGs) were obtained by overlapping DEGs1 from the GSE124272 and DEGs2 from the GSE70362. The key module genes associated with the score of MPRGs were identified by weighted gene co-expression network analysis (WGCNA) in GSE12472. Differentially expressed (DE)-MPRGs were acquired by overlapping key module genes and DEGs. Candidate genes were obtained by SVM-RFE algorithm. Biomarkers were obtained by expression level analysis. In addition, immune analysis, enrichment analysis and construction of a ceRNA network were completed. The blood samples from 9 IDD patients (IDD group) and 9 healthy individuals (Control group) were used to verify the expression levels of these biomarkers through RT-qPCR.

RESULTS:

A sum of 39 DEGs were obtained by overlapping DEGs1 and DEGs2, and 1,633 key module genes were obtained by WGCNA. 9 DE-MPRGs were obtained by overlapping DEGs and key module genes, and ST6GALNAC2, SMIM3, and IFITM2 were identified as biomarkers. These biomarkers were enriched in KEGG_RIBOSOME pathway. Check-point, Cytolytic_activity, T_cell_co-stimulation, Neutrophils, Th2_cells and TIL differed between IDD and control groups. Some relationships such as SMIM3-hsa-miR-107-LINC02381 were identified in the network. Moreover, the functional analysis results of biomarkers showed that FITM2 and SMIM3 could predict IDD and nociceptive pain. The RT-qPCR showed that ST6GALNAC2 and IFITM2 were significantly expressed in IDD group in contrast to the control group.

CONCLUSION:

The macrophage polarization related biomarkers (ST6GALNAC2, SMIM3 and IFITM2) were associated with IDD, among which IFITM2 could be considered as a key gene for IDD. This may provide a new direction for the biological treatment and mechanism research into IDD.
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Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Am J Transl Res Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Am J Transl Res Año: 2024 Tipo del documento: Article País de afiliación: China