Comprehensive analysis of immune cell landscapes revealed that immune cell ratio eosinophil/B.cell.memory is predictive of survival in sepsis
Abstract Background Immune dysregulation is a feature of sepsis. However, a comprehensive analysis of the immune landscapes in septic patients has not been conducted. Objectives This study aims to explore the abundance ratios of immune cells in sepsis and investigate their clinical value. Methods Se...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-12-01
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| Series: | European Journal of Medical Research |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40001-023-01506-8 |
| _version_ | 1797398072257413120 |
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| author | Lei Wang Guoan Zhang Wenjie Sun Yan Zhang Yi Tian Xiaohui Yang Yingfu Liu |
| author_facet | Lei Wang Guoan Zhang Wenjie Sun Yan Zhang Yi Tian Xiaohui Yang Yingfu Liu |
| author_sort | Lei Wang |
| collection | DOAJ |
| description | Abstract Background Immune dysregulation is a feature of sepsis. However, a comprehensive analysis of the immune landscapes in septic patients has not been conducted. Objectives This study aims to explore the abundance ratios of immune cells in sepsis and investigate their clinical value. Methods Sepsis transcriptome data sets were downloaded from the NCBI GEO database. The immunedeconv R package was employed to analyze the abundance of immune cells in sepsis patients and calculate the ratios of different immune cell types. Differential analysis of immune cell ratios was performed using the t test. The Spearman rank correlation coefficient was utilized to find the relationships between immune cell abundance and pathways. The prognostic significance of immune cell ratios for patient survival probability was assessed using the log-rank test. In addition, differential gene expression was performed using the limma package, and gene co-expression analysis was executed using the WGCNA package. Results We found significant changes in immune cell ratios between sepsis patients and healthy controls. Some of these ratios were associated with 28-day survival. Certain pathways showed significant correlations with immune cell ratios. Notably, six immune cell ratios demonstrated discriminative ability for patients with systemic inflammatory response syndrome (SIRS), bacterial sepsis, and viral sepsis, with an Area Under the Curve (AUC) larger than 0.84. Patients with a high eosinophil/B.cell.memory ratio exhibited poor survival outcomes. A total of 774 differential genes were identified in sepsis patients with a high eosinophil/B.cell.memory ratio compared to those with a low ratio. These genes were organized into seven co-expression modules associated with relevant pathways, including interferon signaling, T-cell receptor signaling, and specific granule pathways. Conclusions Immune cell ratios eosinophil/B.cell.memory and NK.cell.activated/NK.cell.resting in sepsis patients can be utilized for disease subtyping, prognosis, and diagnosis. The proposed cell ratios may have higher prognostic values than the neutrophil-to-lymphocyte ratio (NLR). |
| first_indexed | 2024-03-09T01:20:23Z |
| format | Article |
| id | doaj.art-5264b9183b3b4a33a8dd267a476a9efa |
| institution | Directory Open Access Journal |
| issn | 2047-783X |
| language | English |
| last_indexed | 2024-03-09T01:20:23Z |
| publishDate | 2023-12-01 |
| publisher | BMC |
| record_format | Article |
| series | European Journal of Medical Research |
| spelling | doaj.art-5264b9183b3b4a33a8dd267a476a9efa2023-12-10T12:12:09ZengBMCEuropean Journal of Medical Research2047-783X2023-12-0128111310.1186/s40001-023-01506-8Comprehensive analysis of immune cell landscapes revealed that immune cell ratio eosinophil/B.cell.memory is predictive of survival in sepsisLei Wang0Guoan Zhang1Wenjie Sun2Yan Zhang3Yi Tian4Xiaohui Yang5Yingfu Liu6Microbiology and Immunology Department, Cangzhou Medical CollegeScience and Technology Experiment Center, Cangzhou Medical CollegeScience and Technology Experiment Center, Cangzhou Medical CollegeScience and Technology Experiment Center, Cangzhou Medical CollegeMicrobiology and Immunology Department, Cangzhou Medical CollegeScience and Technology Experiment Center, Cangzhou Medical CollegeUniversity Nanobody Application Technology Research and Development Center of Hebei ProvinceAbstract Background Immune dysregulation is a feature of sepsis. However, a comprehensive analysis of the immune landscapes in septic patients has not been conducted. Objectives This study aims to explore the abundance ratios of immune cells in sepsis and investigate their clinical value. Methods Sepsis transcriptome data sets were downloaded from the NCBI GEO database. The immunedeconv R package was employed to analyze the abundance of immune cells in sepsis patients and calculate the ratios of different immune cell types. Differential analysis of immune cell ratios was performed using the t test. The Spearman rank correlation coefficient was utilized to find the relationships between immune cell abundance and pathways. The prognostic significance of immune cell ratios for patient survival probability was assessed using the log-rank test. In addition, differential gene expression was performed using the limma package, and gene co-expression analysis was executed using the WGCNA package. Results We found significant changes in immune cell ratios between sepsis patients and healthy controls. Some of these ratios were associated with 28-day survival. Certain pathways showed significant correlations with immune cell ratios. Notably, six immune cell ratios demonstrated discriminative ability for patients with systemic inflammatory response syndrome (SIRS), bacterial sepsis, and viral sepsis, with an Area Under the Curve (AUC) larger than 0.84. Patients with a high eosinophil/B.cell.memory ratio exhibited poor survival outcomes. A total of 774 differential genes were identified in sepsis patients with a high eosinophil/B.cell.memory ratio compared to those with a low ratio. These genes were organized into seven co-expression modules associated with relevant pathways, including interferon signaling, T-cell receptor signaling, and specific granule pathways. Conclusions Immune cell ratios eosinophil/B.cell.memory and NK.cell.activated/NK.cell.resting in sepsis patients can be utilized for disease subtyping, prognosis, and diagnosis. The proposed cell ratios may have higher prognostic values than the neutrophil-to-lymphocyte ratio (NLR).https://doi.org/10.1186/s40001-023-01506-8Septic shockAcute respiratory distress syndrome (ARDS)InfluenzaReceiver operating characteristic (ROC)Intensive care unit (ICU) |
| spellingShingle | Lei Wang Guoan Zhang Wenjie Sun Yan Zhang Yi Tian Xiaohui Yang Yingfu Liu Comprehensive analysis of immune cell landscapes revealed that immune cell ratio eosinophil/B.cell.memory is predictive of survival in sepsis European Journal of Medical Research Septic shock Acute respiratory distress syndrome (ARDS) Influenza Receiver operating characteristic (ROC) Intensive care unit (ICU) |
| title | Comprehensive analysis of immune cell landscapes revealed that immune cell ratio eosinophil/B.cell.memory is predictive of survival in sepsis |
| title_full | Comprehensive analysis of immune cell landscapes revealed that immune cell ratio eosinophil/B.cell.memory is predictive of survival in sepsis |
| title_fullStr | Comprehensive analysis of immune cell landscapes revealed that immune cell ratio eosinophil/B.cell.memory is predictive of survival in sepsis |
| title_full_unstemmed | Comprehensive analysis of immune cell landscapes revealed that immune cell ratio eosinophil/B.cell.memory is predictive of survival in sepsis |
| title_short | Comprehensive analysis of immune cell landscapes revealed that immune cell ratio eosinophil/B.cell.memory is predictive of survival in sepsis |
| title_sort | comprehensive analysis of immune cell landscapes revealed that immune cell ratio eosinophil b cell memory is predictive of survival in sepsis |
| topic | Septic shock Acute respiratory distress syndrome (ARDS) Influenza Receiver operating characteristic (ROC) Intensive care unit (ICU) |
| url | https://doi.org/10.1186/s40001-023-01506-8 |
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