Landscape of Metabolic Fingerprinting for Diagnosis and Risk Stratification of Sepsis
BackgroundSepsis and septic shock, a subset of sepsis with higher risk stratification, are hallmarked by high mortality rates and necessitated early and accurate biomarkers.MethodsUntargeted metabolomic analysis was performed to compare the metabolic features between the sepsis and control systemic...
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| Format: | Article |
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Frontiers Media S.A.
2022-05-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2022.883628/full |
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| author | Geng Lu Jiawei Zhou Ting Yang Jin Li Xinrui Jiang Wenjun Zhang Shuangshuang Gu Jun Wang |
| author_facet | Geng Lu Jiawei Zhou Ting Yang Jin Li Xinrui Jiang Wenjun Zhang Shuangshuang Gu Jun Wang |
| author_sort | Geng Lu |
| collection | DOAJ |
| description | BackgroundSepsis and septic shock, a subset of sepsis with higher risk stratification, are hallmarked by high mortality rates and necessitated early and accurate biomarkers.MethodsUntargeted metabolomic analysis was performed to compare the metabolic features between the sepsis and control systemic inflammatory response syndrome (SIRS) groups in discovery cohort, and potential metabolic biomarkers were selected and quantified using multiple reaction monitoring based target metabolite detection method.ResultsDifferentially expressed metabolites including 46 metabolites in positive electrospray ionization (ESI) ion mode, 22 metabolites in negative ESI ion mode, and 4 metabolites with dual mode between sepsis and SIRS were identified and revealed. Metabolites 5-Oxoproline, L-Kynurenine and Leukotriene D4 were selected based on least absolute shrinkage and selection operator regularization logistic regression and differential expressed between sepsis and septic shock group in the training and test cohorts. Respective risk scores for sepsis and septic shock based on a 3-metabolite fingerprint classifier were established to distinguish sepsis from SIRS, septic shock from sepsis. Significant relationship between developed sepsis risk scores, septic shock risk scores and Sequential (sepsis-related) Organ Failure Assessment (SOFA), procalcitonin (PCT) and lactic acid were observed.ConclusionsCollectively, our findings demonstrated that the characteristics of plasma metabolites not only manifest phenotypic variation in sepsis onset and risk stratification of sepsis but also enable individualized treatment and improve current therapeutic strategies. |
| first_indexed | 2024-04-14T04:49:03Z |
| format | Article |
| id | doaj.art-3b4ae55da4da47ad972081d016e7ea12 |
| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-04-14T04:49:03Z |
| publishDate | 2022-05-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Immunology |
| spelling | doaj.art-3b4ae55da4da47ad972081d016e7ea122022-12-22T02:11:21ZengFrontiers Media S.A.Frontiers in Immunology1664-32242022-05-011310.3389/fimmu.2022.883628883628Landscape of Metabolic Fingerprinting for Diagnosis and Risk Stratification of SepsisGeng Lu0Jiawei Zhou1Ting Yang2Jin Li3Xinrui Jiang4Wenjun Zhang5Shuangshuang Gu6Jun Wang7Department of Emergency, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, ChinaDepartment of Emergency, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, ChinaDepartment of Pharmacy, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, ChinaDepartment of Emergency, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, ChinaDepartment of Emergency, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, ChinaDepartments of Laboratory Medicine, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, ChinaDepartment of Emergency, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, ChinaDepartment of Emergency, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, ChinaBackgroundSepsis and septic shock, a subset of sepsis with higher risk stratification, are hallmarked by high mortality rates and necessitated early and accurate biomarkers.MethodsUntargeted metabolomic analysis was performed to compare the metabolic features between the sepsis and control systemic inflammatory response syndrome (SIRS) groups in discovery cohort, and potential metabolic biomarkers were selected and quantified using multiple reaction monitoring based target metabolite detection method.ResultsDifferentially expressed metabolites including 46 metabolites in positive electrospray ionization (ESI) ion mode, 22 metabolites in negative ESI ion mode, and 4 metabolites with dual mode between sepsis and SIRS were identified and revealed. Metabolites 5-Oxoproline, L-Kynurenine and Leukotriene D4 were selected based on least absolute shrinkage and selection operator regularization logistic regression and differential expressed between sepsis and septic shock group in the training and test cohorts. Respective risk scores for sepsis and septic shock based on a 3-metabolite fingerprint classifier were established to distinguish sepsis from SIRS, septic shock from sepsis. Significant relationship between developed sepsis risk scores, septic shock risk scores and Sequential (sepsis-related) Organ Failure Assessment (SOFA), procalcitonin (PCT) and lactic acid were observed.ConclusionsCollectively, our findings demonstrated that the characteristics of plasma metabolites not only manifest phenotypic variation in sepsis onset and risk stratification of sepsis but also enable individualized treatment and improve current therapeutic strategies.https://www.frontiersin.org/articles/10.3389/fimmu.2022.883628/fullsepsisseptic shockbiomarkersmetabolomicsrisk score |
| spellingShingle | Geng Lu Jiawei Zhou Ting Yang Jin Li Xinrui Jiang Wenjun Zhang Shuangshuang Gu Jun Wang Landscape of Metabolic Fingerprinting for Diagnosis and Risk Stratification of Sepsis Frontiers in Immunology sepsis septic shock biomarkers metabolomics risk score |
| title | Landscape of Metabolic Fingerprinting for Diagnosis and Risk Stratification of Sepsis |
| title_full | Landscape of Metabolic Fingerprinting for Diagnosis and Risk Stratification of Sepsis |
| title_fullStr | Landscape of Metabolic Fingerprinting for Diagnosis and Risk Stratification of Sepsis |
| title_full_unstemmed | Landscape of Metabolic Fingerprinting for Diagnosis and Risk Stratification of Sepsis |
| title_short | Landscape of Metabolic Fingerprinting for Diagnosis and Risk Stratification of Sepsis |
| title_sort | landscape of metabolic fingerprinting for diagnosis and risk stratification of sepsis |
| topic | sepsis septic shock biomarkers metabolomics risk score |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2022.883628/full |
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