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Comprehensive analysis of senescence-related genes and immune infiltration in intervertebral disc degeneration: a meta-data approach utilizing bulk and single-cell RNA sequencing data.
Deng, Ya-Jun; Wang, Xin-Gang; Li, Zhi; Wang, Bo; Li, Jie; Ma, Jun; Xue, Xiong; Tian, Xin; Liu, Quan-Cheng; Liu, Jia-Yuan; Zhang, Ying; Yuan, Bin.
Afiliação
  • Deng YJ; Department of Spine Surgery, Xi'an Daxing Hospital, Yanan University, Xi'an, China.
  • Wang XG; Department of Spine Surgery, Xi'an Daxing Hospital, Yanan University, Xi'an, China.
  • Li Z; Department of Spine Surgery, Xi'an Daxing Hospital, Yanan University, Xi'an, China.
  • Wang B; Department of Spine Surgery, Xi'an Daxing Hospital, Yanan University, Xi'an, China.
  • Li J; Department of Spine Surgery, Xi'an Daxing Hospital, Yanan University, Xi'an, China.
  • Ma J; Department of Spine Surgery, Xi'an Daxing Hospital, Yanan University, Xi'an, China.
  • Xue X; Department of Spine Surgery, Xi'an Daxing Hospital, Yanan University, Xi'an, China.
  • Tian X; Department of Spine Surgery, Xi'an Daxing Hospital, Yanan University, Xi'an, China.
  • Liu QC; Department of Spine Surgery, Xi'an Daxing Hospital, Yanan University, Xi'an, China.
  • Liu JY; Department of Spine Surgery, Xi'an Daxing Hospital, Yanan University, Xi'an, China.
  • Zhang Y; Department of Spine Surgery, Xi'an Daxing Hospital, Yanan University, Xi'an, China.
  • Yuan B; Department of Spine Surgery, Xi'an Daxing Hospital, Yanan University, Xi'an, China.
Front Mol Biosci ; 10: 1296782, 2023.
Article em En | MEDLINE | ID: mdl-38187091
ABSTRACT

Objectives:

This study aims to identify the key senescence genes and potential regulatory mechanisms that contribute to the etiology of intervertebral disc degeneration (IDD).

Method:

We analyzed GSE34095 and GSE70362 datasets, identifying key senescence-related differentially expressed genes (DEGs) in IDD using lasso regression. Risk scores classified patients into high- and low-risk groups. We compared pathways, functions, and immune infiltration between these groups. Diagnostic ability was assessed using ROC curves and a nomogram predicted IDD incidence. In single-cell dataset GSE165722, we evaluated expression of key senescence-related DEGs.

Results:

We identified 12 key senescence-related DEGs distinguishing high- and low-risk IDD patients. Enrichment analysis revealed cellular stress response, apoptotic signaling pathway, and protein kinase activation differences. Immune cell analysis showed elevated eosinophils in low-risk group and increased effector memory CD8 T, central memory CD4 T, myeloid-derived suppressor, natural killer, monocyte, Type 1 T helper, plasmacytoid dendritic, and natural killer T cells in high-risk group. A nomogram using AUC >0.75 genes (CXCL8, MAP4K4, MINK1, and TNIK) predicted IDD incidence with good diagnostic power. High senescence scores were observed in neutrophils.

Conclusion:

Our diagnostic model, based on key senescence-related DEGs and immune cell infiltration, offers new insights into IDD pathogenesis and immunotherapy strategies.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article