Unraveling the immunological landscape and gut microbiome in sepsis: a comprehensive approach to diagnosis and prognosisResearch in context
Summary: Background: Comprehensive and in-depth research on the immunophenotype of septic patients remains limited, and effective biomarkers for the diagnosis and treatment of sepsis are urgently needed in clinical practice. Methods: Blood samples from 31 septic patients in the Intensive Care Unit...
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Elsevier
2025-03-01
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| author | Yali Luo Jian Gao Xinliang Su Helian Li Yingcen Li Wenhao Qi Xuling Han Jingxuan Han Yiran Zhao Alin Zhang Yan Zheng Feng Qian Hongyu He |
| author_facet | Yali Luo Jian Gao Xinliang Su Helian Li Yingcen Li Wenhao Qi Xuling Han Jingxuan Han Yiran Zhao Alin Zhang Yan Zheng Feng Qian Hongyu He |
| author_sort | Yali Luo |
| collection | DOAJ |
| description | Summary: Background: Comprehensive and in-depth research on the immunophenotype of septic patients remains limited, and effective biomarkers for the diagnosis and treatment of sepsis are urgently needed in clinical practice. Methods: Blood samples from 31 septic patients in the Intensive Care Unit (ICU), 25 non-septic ICU patients, and 18 healthy controls were analyzed using flow cytometry for deep immunophenotyping. Metagenomic sequencing was performed in 41 fecal samples, including 13 septic patients, 10 non-septic ICU patients, and 18 healthy controls. Immunophenotype shifts were evaluated using differential expression sliding window analysis, and random forest models were developed for sepsis diagnosis or prognosis prediction. Findings: Septic patients exhibited decreased proportions of natural killer (NK) cells and plasmacytoid dendritic cells (pDCs) in CD45+ leukocytes compared with non-septic ICU patients and healthy controls. These changes statistically mediated the association of Bacteroides salyersiae with sepsis, suggesting a potential underlying mechanism. A combined diagnostic model incorporating B.salyersia, NK cells in CD45+ leukocytes, and C-reactive protein (CRP) demonstrated high accuracy in distinguishing sepsis from non-sepsis (area under the receiver operating characteristic curve, AUC = 0.950, 95% CI: 0.811–1.000). Immunophenotyping and disease severity analysis identified an Acute Physiology and Chronic Health Evaluation (APACHE) II score threshold of 21, effectively distinguishing mild (n = 19) from severe (n = 12) sepsis. A prognostic model based on the proportion of total lymphocytes, Helper T (Th) 17 cells, CD4+ effector memory T (TEM) cells, and Th1 cells in CD45+ leukocytes achieved robust outcome prediction (AUC = 0.906, 95% CI: 0.732–1.000), with further accuracy improvement when combined with clinical scores (AUC = 0.938, 95% CI: 0.796–1.000). Interpretation: NK cell subsets within innate immunity exhibit significant diagnostic value for sepsis, particularly when combined with B. salyersiae and CRP. In addition, T cell phenotypes within adaptive immunity are correlated with sepsis severity and may serve as reliable prognostic markers. Funding: This project was supported by the National Key R&D Program of China (2023YFC2307600, 2021YFA1301000), Shanghai Municipal Science and Technology Major Project (2023SHZDZX02, 2017SHZDZX01), Shanghai Municipal Technology Standards Project (23DZ2202600). |
| format | Article |
| id | doaj-art-f6cafe941b1e448394191f783a7d6830 |
| institution | Kabale University |
| issn | 2352-3964 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | EBioMedicine |
| spelling | doaj-art-f6cafe941b1e448394191f783a7d68302025-02-02T05:27:42ZengElsevierEBioMedicine2352-39642025-03-01113105586Unraveling the immunological landscape and gut microbiome in sepsis: a comprehensive approach to diagnosis and prognosisResearch in contextYali Luo0Jian Gao1Xinliang Su2Helian Li3Yingcen Li4Wenhao Qi5Xuling Han6Jingxuan Han7Yiran Zhao8Alin Zhang9Yan Zheng10Feng Qian11Hongyu He12State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, 200433, ChinaState Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, 200433, ChinaState Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, 200433, ChinaState Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, 200433, ChinaState Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, 200433, ChinaState Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, 200433, ChinaState Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, 200433, ChinaState Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, 200433, ChinaState Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, 200433, ChinaState Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, 200433, ChinaState Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, 200433, China; Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, 200438, China; Corresponding author. State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, 200433, China.State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, 200433, China; Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, 200438, China; Corresponding author. State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, 200433, China.Department of Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China; Corresponding author.Summary: Background: Comprehensive and in-depth research on the immunophenotype of septic patients remains limited, and effective biomarkers for the diagnosis and treatment of sepsis are urgently needed in clinical practice. Methods: Blood samples from 31 septic patients in the Intensive Care Unit (ICU), 25 non-septic ICU patients, and 18 healthy controls were analyzed using flow cytometry for deep immunophenotyping. Metagenomic sequencing was performed in 41 fecal samples, including 13 septic patients, 10 non-septic ICU patients, and 18 healthy controls. Immunophenotype shifts were evaluated using differential expression sliding window analysis, and random forest models were developed for sepsis diagnosis or prognosis prediction. Findings: Septic patients exhibited decreased proportions of natural killer (NK) cells and plasmacytoid dendritic cells (pDCs) in CD45+ leukocytes compared with non-septic ICU patients and healthy controls. These changes statistically mediated the association of Bacteroides salyersiae with sepsis, suggesting a potential underlying mechanism. A combined diagnostic model incorporating B.salyersia, NK cells in CD45+ leukocytes, and C-reactive protein (CRP) demonstrated high accuracy in distinguishing sepsis from non-sepsis (area under the receiver operating characteristic curve, AUC = 0.950, 95% CI: 0.811–1.000). Immunophenotyping and disease severity analysis identified an Acute Physiology and Chronic Health Evaluation (APACHE) II score threshold of 21, effectively distinguishing mild (n = 19) from severe (n = 12) sepsis. A prognostic model based on the proportion of total lymphocytes, Helper T (Th) 17 cells, CD4+ effector memory T (TEM) cells, and Th1 cells in CD45+ leukocytes achieved robust outcome prediction (AUC = 0.906, 95% CI: 0.732–1.000), with further accuracy improvement when combined with clinical scores (AUC = 0.938, 95% CI: 0.796–1.000). Interpretation: NK cell subsets within innate immunity exhibit significant diagnostic value for sepsis, particularly when combined with B. salyersiae and CRP. In addition, T cell phenotypes within adaptive immunity are correlated with sepsis severity and may serve as reliable prognostic markers. Funding: This project was supported by the National Key R&D Program of China (2023YFC2307600, 2021YFA1301000), Shanghai Municipal Science and Technology Major Project (2023SHZDZX02, 2017SHZDZX01), Shanghai Municipal Technology Standards Project (23DZ2202600).http://www.sciencedirect.com/science/article/pii/S2352396425000301SepsisImmunophenotypeGut microbiomeDiagnosisPrognosis |
| spellingShingle | Yali Luo Jian Gao Xinliang Su Helian Li Yingcen Li Wenhao Qi Xuling Han Jingxuan Han Yiran Zhao Alin Zhang Yan Zheng Feng Qian Hongyu He Unraveling the immunological landscape and gut microbiome in sepsis: a comprehensive approach to diagnosis and prognosisResearch in context EBioMedicine Sepsis Immunophenotype Gut microbiome Diagnosis Prognosis |
| title | Unraveling the immunological landscape and gut microbiome in sepsis: a comprehensive approach to diagnosis and prognosisResearch in context |
| title_full | Unraveling the immunological landscape and gut microbiome in sepsis: a comprehensive approach to diagnosis and prognosisResearch in context |
| title_fullStr | Unraveling the immunological landscape and gut microbiome in sepsis: a comprehensive approach to diagnosis and prognosisResearch in context |
| title_full_unstemmed | Unraveling the immunological landscape and gut microbiome in sepsis: a comprehensive approach to diagnosis and prognosisResearch in context |
| title_short | Unraveling the immunological landscape and gut microbiome in sepsis: a comprehensive approach to diagnosis and prognosisResearch in context |
| title_sort | unraveling the immunological landscape and gut microbiome in sepsis a comprehensive approach to diagnosis and prognosisresearch in context |
| topic | Sepsis Immunophenotype Gut microbiome Diagnosis Prognosis |
| url | http://www.sciencedirect.com/science/article/pii/S2352396425000301 |
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