Identification of immune infiltration and immune-related biomarkers of periprosthetic joint infection
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 data...
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Elsevier
2024-02-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024020930 |
| _version_ | 1797267721719644160 |
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| author | Zhuo Li Zhi-Yuan Li Zulipikaer Maimaiti Fan Yang Jun Fu Li-Bo Hao Ji-Ying Chen Chi Xu |
| author_facet | Zhuo Li Zhi-Yuan Li Zulipikaer Maimaiti Fan Yang Jun Fu Li-Bo Hao Ji-Ying Chen Chi Xu |
| author_sort | Zhuo Li |
| collection | DOAJ |
| description | 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 PJI-related 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. |
| first_indexed | 2024-03-08T03:24:11Z |
| format | Article |
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| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-25T01:21:05Z |
| publishDate | 2024-02-01 |
| publisher | Elsevier |
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| series | Heliyon |
| spelling | doaj.art-2381de525814436a9262c5547e9b9bdf2024-03-09T09:27:04ZengElsevierHeliyon2405-84402024-02-01104e26062Identification of immune infiltration and immune-related biomarkers of periprosthetic joint infectionZhuo Li0Zhi-Yuan Li1Zulipikaer Maimaiti2Fan Yang3Jun Fu4Li-Bo Hao5Ji-Ying Chen6Chi Xu7Medical School of Chinese PLA, Beijing, China; Department of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China; School of Medicine, Nankai University, Tianjin, ChinaMedical School of Chinese PLA, Beijing, China; Department of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, ChinaDepartment of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, ChinaMedical School of Chinese PLA, Beijing, China; Department of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China; School of Medicine, Nankai University, Tianjin, ChinaDepartment of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China; Department of Orthopedics, The Fourth Medical Center, Chinese PLA General Hospital, Beijing, ChinaDepartment of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China; Department of Orthopedics, The Fourth Medical Center, Chinese PLA General Hospital, Beijing, ChinaMedical School of Chinese PLA, Beijing, China; Department of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China; School of Medicine, Nankai University, Tianjin, China; Corresponding author. Department of Orthopedics, General Hospital of People's Liberation Army, Beijing, China.Department of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China; Department of Orthopedics, The Fourth Medical Center, Chinese PLA General Hospital, Beijing, China; Corresponding author. Department of Orthopedics, The First Medical Center, Chinese PLA General Hospital, Beijing, China.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 PJI-related 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.http://www.sciencedirect.com/science/article/pii/S2405844024020930Periprosthetic joint infectionPeriprosthetic tissueBiomarkerImmune infiltrationWGCNA |
| spellingShingle | Zhuo Li Zhi-Yuan Li Zulipikaer Maimaiti Fan Yang Jun Fu Li-Bo Hao Ji-Ying Chen Chi Xu Identification of immune infiltration and immune-related biomarkers of periprosthetic joint infection Heliyon Periprosthetic joint infection Periprosthetic tissue Biomarker Immune infiltration WGCNA |
| title | Identification of immune infiltration and immune-related biomarkers of periprosthetic joint infection |
| title_full | Identification of immune infiltration and immune-related biomarkers of periprosthetic joint infection |
| title_fullStr | Identification of immune infiltration and immune-related biomarkers of periprosthetic joint infection |
| title_full_unstemmed | Identification of immune infiltration and immune-related biomarkers of periprosthetic joint infection |
| title_short | Identification of immune infiltration and immune-related biomarkers of periprosthetic joint infection |
| title_sort | identification of immune infiltration and immune related biomarkers of periprosthetic joint infection |
| topic | Periprosthetic joint infection Periprosthetic tissue Biomarker Immune infiltration WGCNA |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024020930 |
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