Identification and validation of a novel mitochondrion-related gene signature for diagnosis and immune infiltration in sepsis
BackgroundOwing to the complex pathophysiological features and heterogeneity of sepsis, current diagnostic methods are not sufficiently precise or timely, causing a delay in treatment. It has been suggested that mitochondrial dysfunction plays a critical role in sepsis. However, the role and mechani...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-06-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2023.1196306/full |
| _version_ | 1797803811174088704 |
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| author | Shuai Hao Miao Huang Xiaofan Xu Xulin Wang Yuqing Song Wendi Jiang Liqun Huo Jun Gu |
| author_facet | Shuai Hao Miao Huang Xiaofan Xu Xulin Wang Yuqing Song Wendi Jiang Liqun Huo Jun Gu |
| author_sort | Shuai Hao |
| collection | DOAJ |
| description | BackgroundOwing to the complex pathophysiological features and heterogeneity of sepsis, current diagnostic methods are not sufficiently precise or timely, causing a delay in treatment. It has been suggested that mitochondrial dysfunction plays a critical role in sepsis. However, the role and mechanism of mitochondria-related genes in the diagnostic and immune microenvironment of sepsis have not been sufficiently investigated.MethodsMitochondria-related differentially expressed genes (DEGs) were identified between human sepsis and normal samples from GSE65682 dataset. Least absolute shrinkage and selection operator (LASSO) regression and the Support Vector Machine (SVM) analyses were carried out to locate potential diagnostic biomarkers. Gene ontology and gene set enrichment analyses were conducted to identify the key signaling pathways associated with these biomarker genes. Furthermore, correlation of these genes with the proportion of infiltrating immune cells was estimated using CIBERSORT. The expression and diagnostic value of the diagnostic genes were evaluated using GSE9960 and GSE134347 datasets and septic patients. Furthermore, we established an in vitro sepsis model using lipopolysaccharide (1 µg/mL)-stimulated CP-M191 cells. Mitochondrial morphology and function were evaluated in PBMCs from septic patients and CP-M191 cells, respectively.ResultsIn this study, 647 mitochondrion-related DEGs were obtained. Machine learning confirmed six critical mitochondrion-related DEGs, including PID1, CS, CYP1B1, FLVCR1, IFIT2, and MAPK14. We then developed a diagnostic model using the six genes, and receiver operating characteristic (ROC) curves indicated that the novel diagnostic model based on the above six critical genes screened sepsis samples from normal samples with area under the curve (AUC) = 1.000, which was further demonstrated in the GSE9960 and GSE134347 datasets and our cohort. Importantly, we also found that the expression of these genes was associated with different kinds of immune cells. In addition, mitochondrial dysfunction was mainly manifested by the promotion of mitochondrial fragmentation (p<0.05), impaired mitochondrial respiration (p<0.05), decreased mitochondrial membrane potential (p<0.05), and increased reactive oxygen species (ROS) generation (p<0.05) in human sepsis and LPS-simulated in vitro sepsis models.ConclusionWe constructed a novel diagnostic model containing six MRGs, which has the potential to be an innovative tool for the early diagnosis of sepsis. |
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| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-03-13T05:26:40Z |
| publishDate | 2023-06-01 |
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| spelling | doaj.art-a1411c9cd6294ed3bbac3cf975b092292023-06-15T05:45:27ZengFrontiers Media S.A.Frontiers in Immunology1664-32242023-06-011410.3389/fimmu.2023.11963061196306Identification and validation of a novel mitochondrion-related gene signature for diagnosis and immune infiltration in sepsisShuai Hao0Miao Huang1Xiaofan Xu2Xulin Wang3Yuqing Song4Wendi Jiang5Liqun Huo6Jun Gu7Department of General Surgery, Jinling Hospital, Medical School of Nanjing University, Nanjing, ChinaNursing School, Chongqing Medical University, Chongqing, ChinaDepartment of General Surgery, Jinling Hospital, Medical School of Nanjing University, Nanjing, ChinaDepartment of General Surgery, Jinling Hospital, Medical School of Nanjing University, Nanjing, ChinaDepartment of General Surgery, Jinling Hospital, Medical School of Nanjing University, Nanjing, ChinaDepartment of General Surgery, Jinling Hospital, Medical School of Nanjing University, Nanjing, ChinaDepartment of General Surgery, Jinling Hospital, Medical School of Nanjing University, Nanjing, ChinaDepartment of General Surgery, Jinling Hospital, Medical School of Nanjing University, Nanjing, ChinaBackgroundOwing to the complex pathophysiological features and heterogeneity of sepsis, current diagnostic methods are not sufficiently precise or timely, causing a delay in treatment. It has been suggested that mitochondrial dysfunction plays a critical role in sepsis. However, the role and mechanism of mitochondria-related genes in the diagnostic and immune microenvironment of sepsis have not been sufficiently investigated.MethodsMitochondria-related differentially expressed genes (DEGs) were identified between human sepsis and normal samples from GSE65682 dataset. Least absolute shrinkage and selection operator (LASSO) regression and the Support Vector Machine (SVM) analyses were carried out to locate potential diagnostic biomarkers. Gene ontology and gene set enrichment analyses were conducted to identify the key signaling pathways associated with these biomarker genes. Furthermore, correlation of these genes with the proportion of infiltrating immune cells was estimated using CIBERSORT. The expression and diagnostic value of the diagnostic genes were evaluated using GSE9960 and GSE134347 datasets and septic patients. Furthermore, we established an in vitro sepsis model using lipopolysaccharide (1 µg/mL)-stimulated CP-M191 cells. Mitochondrial morphology and function were evaluated in PBMCs from septic patients and CP-M191 cells, respectively.ResultsIn this study, 647 mitochondrion-related DEGs were obtained. Machine learning confirmed six critical mitochondrion-related DEGs, including PID1, CS, CYP1B1, FLVCR1, IFIT2, and MAPK14. We then developed a diagnostic model using the six genes, and receiver operating characteristic (ROC) curves indicated that the novel diagnostic model based on the above six critical genes screened sepsis samples from normal samples with area under the curve (AUC) = 1.000, which was further demonstrated in the GSE9960 and GSE134347 datasets and our cohort. Importantly, we also found that the expression of these genes was associated with different kinds of immune cells. In addition, mitochondrial dysfunction was mainly manifested by the promotion of mitochondrial fragmentation (p<0.05), impaired mitochondrial respiration (p<0.05), decreased mitochondrial membrane potential (p<0.05), and increased reactive oxygen species (ROS) generation (p<0.05) in human sepsis and LPS-simulated in vitro sepsis models.ConclusionWe constructed a novel diagnostic model containing six MRGs, which has the potential to be an innovative tool for the early diagnosis of sepsis.https://www.frontiersin.org/articles/10.3389/fimmu.2023.1196306/fullsepsisimmune infiltrationmitochondriondiagnostic biomarkersbioinformatics |
| spellingShingle | Shuai Hao Miao Huang Xiaofan Xu Xulin Wang Yuqing Song Wendi Jiang Liqun Huo Jun Gu Identification and validation of a novel mitochondrion-related gene signature for diagnosis and immune infiltration in sepsis Frontiers in Immunology sepsis immune infiltration mitochondrion diagnostic biomarkers bioinformatics |
| title | Identification and validation of a novel mitochondrion-related gene signature for diagnosis and immune infiltration in sepsis |
| title_full | Identification and validation of a novel mitochondrion-related gene signature for diagnosis and immune infiltration in sepsis |
| title_fullStr | Identification and validation of a novel mitochondrion-related gene signature for diagnosis and immune infiltration in sepsis |
| title_full_unstemmed | Identification and validation of a novel mitochondrion-related gene signature for diagnosis and immune infiltration in sepsis |
| title_short | Identification and validation of a novel mitochondrion-related gene signature for diagnosis and immune infiltration in sepsis |
| title_sort | identification and validation of a novel mitochondrion related gene signature for diagnosis and immune infiltration in sepsis |
| topic | sepsis immune infiltration mitochondrion diagnostic biomarkers bioinformatics |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2023.1196306/full |
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