Identification of immune infiltration and immune-related biomarkers of periprosthetic joint infection

被引：0

作者：

Li, Zhuo ^{[1
,2
,3
,5
]}

Li, Zhi-Yuan ^{[1
,2
]}

Maimaiti, Zulipikaer ^{[2
,6
]}

Yang, Fan ^{[1
,2
,3
]}

Fu, Jun ^{[2
,4
]}

Hao, Li -Bo ^{[2
,4
]}

Chen, Ji-Ying ^{[1
,2
,3
,7
]}

Xu, Chi ^{[2
,4
]}

机构：

[1] Med Sch Chinese PLA, Beijing, Peoples R China

[2] Chinese Peoples Liberat Army Gen Hosp, Med Ctr 1, Dept Orthoped, Beijing, Peoples R China

[3] Nankai Univ, Sch Med, Tianjin, Peoples R China

[4] Chinese Peoples Liberat Army Gen Hosp, Med Ctr 4, Dept Orthoped, Beijing, Peoples R China

[5] Shandong First Med Univ, Shandong Prov Hosp, Dept Joint Surg, Jinan, Shandong, Peoples R China

[6] Capital Med Univ, Beijing Luhe Hosp, Dept Orthoped, Beijing, Peoples R China

[7] Gen Hosp PLA Peoples Liberat Army, Dept Orthoped, Beijing, Peoples R China

来源：

HELIYON | 2024年 / 10卷 / 04期

基金：

中国国家自然科学基金;

关键词：

Periprosthetic joint infection; Periprosthetic tissue; Biomarker; Immune infiltration; WGCNA; ENDOTHELIAL GLYCOCALYX; MAST-CELLS; INTEGRIN; ARTHROPLASTY; EXPRESSION; HIP; RECRUITMENT; SYNDECAN-1; ADHESION; SEPSIS;

D O I：

10.1016/j.heliyon.2024.e26062

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Background: The immune response associated with periprosthetic joint infection (PJI) is an emerging but relatively unexplored topic. The aim of this study was to investigate immune cell infiltration in periprosthetic tissues and identify potential immune-related biomarkers. Methods: The GSE7103 dataset from the GEO database was selected as the data source. Differentially expressed genes (DEGs) and significant modular genes in weighted correlation network analysis (WGCNA) were identified. Functional enrichment analysis and transcription factor prediction were performed on the overlapping genes. Next, immune-related genes from the ImmPort database were matched. The protein-protein interaction (PPI) analysis was performed to identify hub genes. CIBERSORTx was used to evaluate the immune cell infiltration pattern. Spearman correlation analysis was used to evaluate the relationship between hub genes and immune cells. Results: A total of 667 DEGs were identified between PJI and control samples, and 1847 PJIrelated module genes were obtained in WGCNA. Enrichment analysis revealed that the common genes were mainly enriched in immune and host defense-related terms. TFEC, SPI1, and TWIST2 were the top three transcription factors. Three hub genes, SDC1, MMP9, and IGF1, were identified in the immune-related PPI network. Higher levels of plasma cells, CD4+ memory resting T cells, follicular helper T cells, resting mast cells, and neutrophils were found in the PJI group, while levels of M0 macrophages were lower. Notably, the expression of all three hub genes correlated with the infiltration levels of seven types of immune cells. Conclusion: The present study revealed immune infiltration signatures in the periprosthetic tissues of PJI patients. SDC1, MMP9, and IGF1 were potential immune-related biomarkers for PJI.

引用

页数：12