Comprehensive analysis of a pyroptosis-related gene signature of clinical and biological values in spinal cord injury

Pingping Zhang; Jianping Zhang; Wenjuan Kou; Guangjin Gu; Yaning Zhang; Weihan Shi; Pengcheng Chu; Dachuan Liang; Guangwei Sun; Jun Shang

doi:10.3389/fneur.2023.1141939

Comprehensive analysis of a pyroptosis-related gene signature of clinical and biological values in spinal cord injury

Front Neurol. 2023 May 19:14:1141939. doi: 10.3389/fneur.2023.1141939. eCollection 2023.

Authors

Pingping Zhang^#¹, Jianping Zhang^#², Wenjuan Kou^#^{3

4}, Guangjin Gu^#², Yaning Zhang¹, Weihan Shi¹, Pengcheng Chu¹, Dachuan Liang⁵, Guangwei Sun¹, Jun Shang^{1

2}

Affiliations

¹ Department of Orthopedics, Seventh Affiliated Hospital of Shanxi Medical University, Linfen People's Hospital, Linfen, Shanxi, China.
² Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, China.
³ School of Pharmaceutical Sciences and Research Center of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
⁴ Department of Disinfection Monitoring, Yongji Disease Control and Prevention Center, Yongji, Shanxi, China.
⁵ Department of Scientific Research Management, Shanxi Medical College Seventh Affiliated Hospital, Linfen People's Hospital, Linfen, Shanxi, China.

^# Contributed equally.

Abstract

Background: Since some of the clinical examinations are not suitable for patients with severe spinal cord injury (SCI), blood biomarkers have been reported to reflect the severity of SCI. The objective of this study was to screen out the potential biomarkers associated with the diagnosis of SCI by bioinformatics analysis.

Methods: The microarray expression profiles of SCI were obtained from the Gene Expression Omnibus (GEO) database. Core genes correlated to pyroptosis were obtained by crossing the differential genes, and module genes were obtained by WGCNA analysis and lasso regression. The immune infiltration analysis and GSEA analysis revealed the essential effect of immune cells in the progression of SCI. In addition, the accuracy of the biomarkers in diagnosing SCI was subsequently evaluated and verified using the receiver operating characteristic curve (ROC) and qRT-PCR.

Results: A total of 423 DEGs were identified, among which 319 genes were upregulated and 104 genes were downregulated. Based on the WGCNA analysis, six potential biomarkers were screened out, including LIN7A, FCGR1A, FGD4, GPR27, BLOC1S1, and GALNT4. The results of ROC curves demonstrated the accurate value of biomarkers related to SCI. The immune infiltration analysis and GSEA analysis revealed the essential effect of immune cells in the progression of SCI, including macrophages, natural killer cells, and neutrophils. The qRT-PCR results verified that FGD4, FCAR1A, LIN7A, BLOC1S1, and GPR27 were significantly upregulated in SCI patients.

Conclusion: In this study, we identified and verified five immune pyroptosis-related hub genes by WGCNA and biological experiments. It is expected that the five identified potential biomarkers in peripheral white blood cells may provide a novel strategy for early diagnosis.

Keywords: bioinformatics analysis; biomarkers; clinical examination; immune infiltration; peripheral blood; spinal cord injury.

Grants and funding

We acknowledge funding from the Youth Project of Shanxi Basic Research Program (202103021223016), the Key Medical Research Projects in Shanxi Province (2020XM51), and the Scientific Research Fund of Linfen People's Hospital (T20210512135).