Diagnostic and prognostic value of autophagy-related key genes in sepsis and potential correlation with immune cell signatures
Background: Autophagy is involved in the pathophysiological process of sepsis. This study was designed to identify autophagy-related key genes in sepsis, analyze their correlation with immune cell signatures, and search for new diagnostic and prognostic biomarkers.Methods: Whole blood RNA datasets G...
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| Format: | Article |
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Frontiers Media S.A.
2023-08-01
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| Series: | Frontiers in Cell and Developmental Biology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcell.2023.1218379/full |
| _version_ | 1797736134776717312 |
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| author | Li Yang Lin Zhou Fangyi Li Xiaotong Chen Ting Li Zijun Zou Yaowei Zhi Zhijie He |
| author_facet | Li Yang Lin Zhou Fangyi Li Xiaotong Chen Ting Li Zijun Zou Yaowei Zhi Zhijie He |
| author_sort | Li Yang |
| collection | DOAJ |
| description | Background: Autophagy is involved in the pathophysiological process of sepsis. This study was designed to identify autophagy-related key genes in sepsis, analyze their correlation with immune cell signatures, and search for new diagnostic and prognostic biomarkers.Methods: Whole blood RNA datasets GSE65682, GSE134347, and GSE134358 were downloaded and processed. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were used to identify autophagy-related key genes in sepsis. Then, key genes were analyzed by functional enrichment, protein-protein interaction (PPI), transcription factor (TF)-gene and competing endogenous RNA (ceRNA) network analysis. Subsequently, key genes with diagnostic efficiency and prognostic value were identified by receiver operating characteristic (ROC) curves and survival analysis respectively. The signatures of immune cells were estimated using CIBERSORT algorithm. The correlation between significantly different immune cell signatures and key genes was assessed by correlation analysis. Finally, key genes with both diagnostic and prognostic value were verified by RT-qPCR.Results: 14 autophagy-related key genes were identified and their TF-gene and ceRNA regulatory networks were constructed. Among the key genes, 11 genes (ATIC, BCL2, EEF2, EIF2AK3, HSPA8, IKBKB, NLRC4, PARP1, PRKCQ, SH3GLB1, and WIPI1) had diagnostic efficiency (AUC > 0.90) and 5 genes (CAPN2, IKBKB, PRKCQ, SH3GLB1 and WIPI1) were associated with survival prognosis (p-value < 0.05). IKBKB, PRKCQ, SH3GLB1 and WIPI1 had both diagnostic and prognostic value, and their expression were verified by RT-qPCR. Analysis of immune cell signatures showed that the abundance of neutrophil, monocyte, M0 macrophage, gamma delta T cell, activated mast cell and M1 macrophage subtypes increased in the sepsis group, while the abundance of resting NK cell, resting memory CD4+ T cell, CD8+ T cell, naive B cell and resting dendritic cell subtypes decreased. Most of the key genes correlated with the predicted frequencies of CD8+ T cells, resting memory CD4+ T cells, M1 macrophages and naive B cells.Conclusion: We identified autophagy-related key genes with diagnostic and prognostic value in sepsis and discovered associations between key genes and immune cell signatures. This work may provide new directions for the discovery of promising biomarkers for sepsis. |
| first_indexed | 2024-03-12T13:09:11Z |
| format | Article |
| id | doaj.art-472f566975b64677827788b762fbbc54 |
| institution | Directory Open Access Journal |
| issn | 2296-634X |
| language | English |
| last_indexed | 2024-03-12T13:09:11Z |
| publishDate | 2023-08-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Cell and Developmental Biology |
| spelling | doaj.art-472f566975b64677827788b762fbbc542023-08-28T08:20:06ZengFrontiers Media S.A.Frontiers in Cell and Developmental Biology2296-634X2023-08-011110.3389/fcell.2023.12183791218379Diagnostic and prognostic value of autophagy-related key genes in sepsis and potential correlation with immune cell signaturesLi Yang0Lin Zhou1Fangyi Li2Xiaotong Chen3Ting Li4Zijun Zou5Yaowei Zhi6Zhijie He7Department of Critical Care Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, ChinaDepartment of Critical Care Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, ChinaDepartment of Critical Care Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, ChinaDepartment of Health Management Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, ChinaDepartment of Critical Care Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, ChinaDepartment of Critical Care Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, ChinaDepartment of Critical Care Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, ChinaDepartment of Critical Care Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, ChinaBackground: Autophagy is involved in the pathophysiological process of sepsis. This study was designed to identify autophagy-related key genes in sepsis, analyze their correlation with immune cell signatures, and search for new diagnostic and prognostic biomarkers.Methods: Whole blood RNA datasets GSE65682, GSE134347, and GSE134358 were downloaded and processed. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were used to identify autophagy-related key genes in sepsis. Then, key genes were analyzed by functional enrichment, protein-protein interaction (PPI), transcription factor (TF)-gene and competing endogenous RNA (ceRNA) network analysis. Subsequently, key genes with diagnostic efficiency and prognostic value were identified by receiver operating characteristic (ROC) curves and survival analysis respectively. The signatures of immune cells were estimated using CIBERSORT algorithm. The correlation between significantly different immune cell signatures and key genes was assessed by correlation analysis. Finally, key genes with both diagnostic and prognostic value were verified by RT-qPCR.Results: 14 autophagy-related key genes were identified and their TF-gene and ceRNA regulatory networks were constructed. Among the key genes, 11 genes (ATIC, BCL2, EEF2, EIF2AK3, HSPA8, IKBKB, NLRC4, PARP1, PRKCQ, SH3GLB1, and WIPI1) had diagnostic efficiency (AUC > 0.90) and 5 genes (CAPN2, IKBKB, PRKCQ, SH3GLB1 and WIPI1) were associated with survival prognosis (p-value < 0.05). IKBKB, PRKCQ, SH3GLB1 and WIPI1 had both diagnostic and prognostic value, and their expression were verified by RT-qPCR. Analysis of immune cell signatures showed that the abundance of neutrophil, monocyte, M0 macrophage, gamma delta T cell, activated mast cell and M1 macrophage subtypes increased in the sepsis group, while the abundance of resting NK cell, resting memory CD4+ T cell, CD8+ T cell, naive B cell and resting dendritic cell subtypes decreased. Most of the key genes correlated with the predicted frequencies of CD8+ T cells, resting memory CD4+ T cells, M1 macrophages and naive B cells.Conclusion: We identified autophagy-related key genes with diagnostic and prognostic value in sepsis and discovered associations between key genes and immune cell signatures. This work may provide new directions for the discovery of promising biomarkers for sepsis.https://www.frontiersin.org/articles/10.3389/fcell.2023.1218379/fullsepsisautophagyimmune cell signaturesbioinformatics analysisdiagnosticprognostic |
| spellingShingle | Li Yang Lin Zhou Fangyi Li Xiaotong Chen Ting Li Zijun Zou Yaowei Zhi Zhijie He Diagnostic and prognostic value of autophagy-related key genes in sepsis and potential correlation with immune cell signatures Frontiers in Cell and Developmental Biology sepsis autophagy immune cell signatures bioinformatics analysis diagnostic prognostic |
| title | Diagnostic and prognostic value of autophagy-related key genes in sepsis and potential correlation with immune cell signatures |
| title_full | Diagnostic and prognostic value of autophagy-related key genes in sepsis and potential correlation with immune cell signatures |
| title_fullStr | Diagnostic and prognostic value of autophagy-related key genes in sepsis and potential correlation with immune cell signatures |
| title_full_unstemmed | Diagnostic and prognostic value of autophagy-related key genes in sepsis and potential correlation with immune cell signatures |
| title_short | Diagnostic and prognostic value of autophagy-related key genes in sepsis and potential correlation with immune cell signatures |
| title_sort | diagnostic and prognostic value of autophagy related key genes in sepsis and potential correlation with immune cell signatures |
| topic | sepsis autophagy immune cell signatures bioinformatics analysis diagnostic prognostic |
| url | https://www.frontiersin.org/articles/10.3389/fcell.2023.1218379/full |
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