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Mayers JR, Varon J, Zhou RR, Daniel-Ivad M, Beaulieu C, Bhosle A, Glasser NR, Lichtenauer FM, Ng J, Vera MP, Huttenhower C, Perrella MA, Clish CB, Zhao SD, Baron RM, Balskus EP. A metabolomics pipeline highlights microbial metabolism in bloodstream infections. Cell 2024; 187:4095-4112.e21. [PMID: 38885650 PMCID: PMC11283678 DOI: 10.1016/j.cell.2024.05.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 04/03/2024] [Accepted: 05/17/2024] [Indexed: 06/20/2024]
Abstract
The growth of antimicrobial resistance (AMR) highlights an urgent need to identify bacterial pathogenic functions that may be targets for clinical intervention. Although severe infections profoundly alter host metabolism, prior studies have largely ignored microbial metabolism in this context. Here, we describe an iterative, comparative metabolomics pipeline to uncover microbial metabolic features in the complex setting of a host and apply it to investigate gram-negative bloodstream infection (BSI) in patients. We find elevated levels of bacterially derived acetylated polyamines during BSI and discover the enzyme responsible for their production (SpeG). Blocking SpeG activity reduces bacterial proliferation and slows pathogenesis. Reduction of SpeG activity also enhances bacterial membrane permeability and increases intracellular antibiotic accumulation, allowing us to overcome AMR in culture and in vivo. This study highlights how tools to study pathogen metabolism in the natural context of infection can reveal and prioritize therapeutic strategies for addressing challenging infections.
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Affiliation(s)
- Jared R Mayers
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA; Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
| | - Jack Varon
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Ruixuan R Zhou
- Department of Statistics, University of Illinois at Urbana Champaign, Champaign, IL 61820, USA
| | - Martin Daniel-Ivad
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Amrisha Bhosle
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Nathaniel R Glasser
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
| | | | - Julie Ng
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Mayra Pinilla Vera
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Curtis Huttenhower
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Mark A Perrella
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Clary B Clish
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Sihai D Zhao
- Department of Statistics, University of Illinois at Urbana Champaign, Champaign, IL 61820, USA; Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana Champaign, Champaign, IL 61820, USA
| | - Rebecca M Baron
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA.
| | - Emily P Balskus
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA; Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA.
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2
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Ma Q, Luo G, Wang F, Li H, Li X, Liu Y, Li Z, Guo Y, Li Y. NK Cell Mitochondrial Membrane Potential-Associated Model Predicts Outcomes in Critically Ill Patients with COVID-19. J Inflamm Res 2024; 17:4361-4372. [PMID: 38983452 PMCID: PMC11232957 DOI: 10.2147/jir.s458749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Accepted: 07/01/2024] [Indexed: 07/11/2024] Open
Abstract
Purpose This study investigated potential predictive models associated with natural killer (NK) cell mitochondrial membrane potential (MMP or ΔΨm) in predicting death among critically ill patients with COVID-19. Patients and Methods We included 97 patients with COVID-19 of different severities attending Peking Union Medical College Hospital from December 2022 to January 2023. Patients were divided into three groups according to oxygen and mechanical ventilation use during specimen collection and were followed for survival and death at 3 months. The lymphocyte subpopulation MMP was detected via flow cytometry. We constructed a joint diagnostic model by integrating identified key indicators and generating receiver operating curves (ROCs) and evaluated its predictive performance for mortality risk in critically ill patients. Results The NK-cell MMP median fluorescence intensity (MFI) was significantly lower in critically ill patients who died from COVID-19 (p<0.0001) and significantly and positively correlated with D-dimer content in critically ill patients (r=0.56, p=0.0023). The random forest model suggested that fibrinogen levels and NK-cell MMP MFI were the most important indicators. Integrating the above predictive models for the ROC yielded an area under the curve of 0.94. Conclusion This study revealed the potential of combining NK-cell MMP with key clinical indicators (D-dimer and fibrinogen levels) to predict death among critically ill patients with COVID-19, which may help in early risk stratification of critically ill patients and improve patient care and clinical outcomes.
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Affiliation(s)
- Qingqing Ma
- Department of Clinical Laboratory, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
- Medical Laboratory Innovation Unit, Chinese Academy of Medical Sciences, Shenyang, People’s Republic of China
| | - Guoju Luo
- Department of Clinical Laboratory, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
| | - Fei Wang
- Department of Clinical Laboratory, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
| | - Haolong Li
- Department of Clinical Laboratory, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
| | - Xiaomeng Li
- Department of Clinical Laboratory, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
- Department of Clinical Laboratory, Peking University People’s Hospital, Beijing, People’s Republic of China
| | - Yongmei Liu
- Department of Clinical Laboratory, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
| | - Zhan Li
- Department of Clinical Laboratory, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
| | - Ye Guo
- Department of Clinical Laboratory, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
| | - Yongzhe Li
- Department of Clinical Laboratory, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
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3
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Hu Y, Xiong Z, Huang P, He W, Zhong M, Zhang D, Tang G. Association of mental disorders with sepsis: a bidirectional Mendelian randomization study. Front Public Health 2024; 12:1327315. [PMID: 38827616 PMCID: PMC11140049 DOI: 10.3389/fpubh.2024.1327315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 05/08/2024] [Indexed: 06/04/2024] Open
Abstract
Background Substantial research evidence supports the correlation between mental disorders and sepsis. Nevertheless, the causal connection between a particular psychological disorder and sepsis remains unclear. Methods For investigating the causal relationships between mental disorders and sepsis, genetic variants correlated with mental disorders, including anorexia nervosa (AN), attention-deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), panic disorder (PD), posttraumatic stress disorder (PTSD), schizophrenia (SCZ), and tourette syndrome (TS), were all extracted from the Psychiatric Genomics Consortium (PGC). The causal estimates and direction between these mental disorders and sepsis were evaluated employing a two-sample bidirectional MR strategy. The inverse variance weighted (IVW) method was the primary approach utilized. Various sensitivity analyses were performed to confirm the validity of the causal effect. Meta-analysis, multivariable MR, and mediation MR were conducted to ensure the credibility and depth of this research. Results The presence of AN was in relation to a greater likelihood of sepsis (OR 1.08, 95% CI 1.02-1.14; p = 0.013). A meta-analysis including validation cohorts supported this observation (OR 1.06, 95% CI 1.02-1.09). None of the investigated mental disorders appeared to be impacted when sepsis was set as the exposure factor. Even after adjusting for confounding factors, AN remained statistically significant (OR 1.08, 95% CI 1.02-1.15; p = 0.013). Mediation analysis indicated N-formylmethionine levels (with a mediated proportion of 7.47%), cystatin D levels (2.97%), ketogluconate Metabolism (17.41%) and N10-formyl-tetrahydrofolate biosynthesis (20.06%) might serve as mediators in the pathogenesis of AN-sepsis. Conclusion At the gene prediction level, two-sample bidirectional MR analysis revealed that mental disorder AN had a causal association with an increased likelihood of sepsis. In addition, N-formylmethionine levels, cystatin D levels, ketogluconate metabolism and N10-formyl-tetrahydrofolate biosynthesis may function as potential mediators in the pathophysiology of AN-sepsis. Our research may contribute to the investigation of novel therapeutic strategies for mental illness and sepsis.
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Affiliation(s)
- Yuanzhi Hu
- Guangzhou University of Chinese Medicine, Guangzhou, China
- The Second Clinical Medical College of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Zihui Xiong
- Guangzhou University of Chinese Medicine, Guangzhou, China
- The Second Clinical Medical College of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Pinge Huang
- Guangzhou University of Chinese Medicine, Guangzhou, China
- The Second Clinical Medical College of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Wan He
- Guangzhou University of Chinese Medicine, Guangzhou, China
- The Second Clinical Medical College of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Minlin Zhong
- Emergency Department of Guangdong Provincial Hospital of Traditional Chinese Medicine, Guangzhou, China
| | - Danqi Zhang
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Guanghua Tang
- Emergency Department of Guangdong Provincial Hospital of Traditional Chinese Medicine, Guangzhou, China
- Guangdong Provincial Key Laboratory of Research on Emergency in TCM, Guangzhou, China
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4
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Diehl-Wiesenecker E, Galtung N, Dickescheid J, Prpic M, Somasundaram R, Kappert K, Bauer W. Blood calprotectin as a biomarker for infection and sepsis - the prospective CASCADE trial. BMC Infect Dis 2024; 24:496. [PMID: 38755564 PMCID: PMC11100246 DOI: 10.1186/s12879-024-09394-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 05/09/2024] [Indexed: 05/18/2024] Open
Abstract
BACKGROUND Early in the host-response to infection, neutrophils release calprotectin, triggering several immune signalling cascades. In acute infection management, identifying infected patients and stratifying these by risk of deterioration into sepsis, are crucial tasks. Recruiting a heterogenous population of patients with suspected infections from the emergency department, early in the care-path, the CASCADE trial aimed to evaluate the accuracy of blood calprotectin for detecting bacterial infections, estimating disease severity, and predicting clinical deterioration. METHODS In a prospective, observational trial from February 2021 to August 2022, 395 patients (n = 194 clinically suspected infection; n = 201 controls) were enrolled. Blood samples were collected at enrolment. The accuracy of calprotectin to identify bacterial infections, and to predict and identify sepsis and mortality was analysed. These endpoints were determined by a panel of experts. RESULTS The Area Under the Receiver Operating Characteristic (AUROC) of calprotectin for detecting bacterial infections was 0.90. For sepsis within 72 h, calprotectin's AUROC was 0.83. For 30-day mortality it was 0.78. In patients with diabetes, calprotectin had an AUROC of 0.94 for identifying bacterial infection. CONCLUSIONS Calprotectin showed notable accuracy for all endpoints. Using calprotectin in the emergency department could improve diagnosis and management of severe infections, in combination with current biomarkers. CLINICAL TRIAL REGISTRATION NUMBER DRKS00020521.
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Affiliation(s)
- Eva Diehl-Wiesenecker
- Department of Emergency Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Benjamin Franklin Campus, Zentrale Notaufnahme und Aufnahmestation, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Noa Galtung
- Department of Emergency Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Benjamin Franklin Campus, Zentrale Notaufnahme und Aufnahmestation, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Johannes Dickescheid
- Department of Emergency Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Benjamin Franklin Campus, Zentrale Notaufnahme und Aufnahmestation, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Monika Prpic
- Institute of Diagnostic Laboratory Medicine, Clinical Chemistry and Pathobiochemistry, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Rajan Somasundaram
- Department of Emergency Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Benjamin Franklin Campus, Zentrale Notaufnahme und Aufnahmestation, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Kai Kappert
- Institute of Diagnostic Laboratory Medicine, Clinical Chemistry and Pathobiochemistry, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
- Labor Berlin - Charité Vivantes GmbH, Berlin, Germany
| | - Wolfgang Bauer
- Department of Emergency Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Benjamin Franklin Campus, Zentrale Notaufnahme und Aufnahmestation, Hindenburgdamm 30, 12203, Berlin, Germany.
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5
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Lodge S, Litton E, Gray N, Ryan M, Millet O, Fear M, Raby E, Currie A, Wood F, Holmes E, Wist J, Nicholson JK. Stratification of Sepsis Patients on Admission into the Intensive Care Unit According to Differential Plasma Metabolic Phenotypes. J Proteome Res 2024; 23:1328-1340. [PMID: 38513133 PMCID: PMC11002934 DOI: 10.1021/acs.jproteome.3c00803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 02/15/2024] [Accepted: 03/07/2024] [Indexed: 03/23/2024]
Abstract
Delayed diagnosis of patients with sepsis or septic shock is associated with increased mortality and morbidity. UPLC-MS and NMR spectroscopy were used to measure panels of lipoproteins, lipids, biogenic amines, amino acids, and tryptophan pathway metabolites in blood plasma samples collected from 152 patients within 48 h of admission into the Intensive Care Unit (ICU) where 62 patients had no sepsis, 71 patients had sepsis, and 19 patients had septic shock. Patients with sepsis or septic shock had higher concentrations of neopterin and lower levels of HDL cholesterol and phospholipid particles in comparison to nonsepsis patients. Septic shock could be differentiated from sepsis patients based on different concentrations of 10 lipids, including significantly lower concentrations of five phosphatidylcholine species, three cholesterol esters, one dihydroceramide, and one phosphatidylethanolamine. The Supramolecular Phospholipid Composite (SPC) was reduced in all ICU patients, while the composite markers of acute phase glycoproteins were increased in the sepsis and septic shock patients within 48 h admission into ICU. We show that the plasma metabolic phenotype obtained within 48 h of ICU admission is diagnostic for the presence of sepsis and that septic shock can be differentiated from sepsis based on the lipid profile.
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Affiliation(s)
- Samantha Lodge
- Australian
National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA6150, Australia
- Center
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Edward Litton
- Intensive
Care Unit, Fiona Stanley Hospital, Murdoch, WA 6150, Australia
- Intensive
Care Unit, St John of God Hospital, Subiaco, WA 6009, Australia
- School
of Medicine, University of Western Australia, Crawley, WA 6009, Australia
| | - Nicola Gray
- Australian
National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA6150, Australia
- Center
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Monique Ryan
- Australian
National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA6150, Australia
- Center
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Oscar Millet
- Precision
Medicine and Metabolism Laboratory, CIC
bioGUNE, Parque Tecnológico
de Bizkaia, Bld. 800, Derio 48160, Spain
| | - Mark Fear
- Burn
Injury Research Unit, School of Biomedical Sciences, University of Western Australia, Perth, WA 6009, Australia
- Fiona
Wood Foundation, Perth, WA 6150, Australia
| | - Edward Raby
- Department
of Infectious Diseases, Fiona Stanley Hospital, Murdoch, WA 6150, Australia
| | - Andrew Currie
- School
of Medical, Molecular & Forensic Sciences, Murdoch University, Perth, WA 6150, Australia
- Centre
for Molecular Medicine & Innovative Therapeutics, Murdoch University, Perth, WA 6150, Australia
- Wesfarmers
Centre for Vaccines and Infectious Diseases, Telethon Kids Institute, University of Western Australia, Perth, WA 6009, Australia
| | - Fiona Wood
- Burn
Injury Research Unit, School of Biomedical Sciences, University of Western Australia, Perth, WA 6009, Australia
- Fiona
Wood Foundation, Perth, WA 6150, Australia
- Burns
service of Western Australia, WA Department
of Health, Murdoch, WA 6150, Australia
| | - Elaine Holmes
- Center
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Institute
of Global Health Innovation, Faculty of Medicine, Imperial College London, Level 1, Faculty Building, South Kensington Campus, London SW7 2NA, U.K.
| | - Julien Wist
- Australian
National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA6150, Australia
- Center
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Chemistry
Department, Universidad del Valle, Cali 76001, Colombia
- Department of Metabolism, Digestion and
Reproduction, Faculty of Medicine, Imperial
College London, Sir Alexander
Fleming Building, South Kensington, London SW7 2AZ, U.K.
| | - Jeremy K. Nicholson
- Australian
National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA6150, Australia
- Department of Metabolism, Digestion and
Reproduction, Faculty of Medicine, Imperial
College London, Sir Alexander
Fleming Building, South Kensington, London SW7 2AZ, U.K.
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6
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Chen J, Si J, Li Q, Zhang W, He J. Unlocking the potential of senescence-related gene signature as a diagnostic and prognostic biomarker in sepsis: insights from meta-analyses, single-cell RNA sequencing, and in vitro experiments. Aging (Albany NY) 2024; 16:3989-4013. [PMID: 38412321 PMCID: PMC10929830 DOI: 10.18632/aging.205574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 01/08/2024] [Indexed: 02/29/2024]
Abstract
Cellular senescence is closely associated with the pathogenesis of sepsis. However, the diagnostic and prognostic value of senescence-related genes remain unclear. In this study, 866 senescence-related genes were collected from CellAge. The training cohort, GSE65682, which included 42 control and 760 sepsis samples, was obtained from the Gene Expression Omnibus (GEO). Feature selection was performed using gene expression difference detection, LASSO analysis, random forest, and Cox regression. TGFBI and MAD1L1 were ultimately selected for inclusion in the multivariate Cox regression model. Clustering based on the expressions of TGFBI and MAD1L1 was significantly associated with sepsis characteristics and prognoses (all P < 0.05). The risk signature served as a reliable prognostic predictor across the GSE65682, GSE95233, and GSE4607 cohorts (pooled hazard ratio = 4.27; 95% confidence interval [CI] = 1.63-11.17). Furthermore, it also served as a robust classifier to distinguish sepsis samples from control cases across 14 cohorts (pooled odds ratio = 5.88; 95% CI = 3.54-9.77). Single-cell RNA sequencing analyses from five healthy controls and four sepsis subjects indicated that the risk signature could reflect the senescence statuses of monocytes and B cells; this finding was then experimentally validated in THP-1 and IM-9 cells in vitro (both P < 0.05). In all, a senescence-related gene signature was developed as a prognostic and diagnostic biomarker for sepsis, providing cut-in points to uncover underlying mechanisms and a promising clinical tool to support precision medicine.
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Affiliation(s)
- Jia Chen
- Department of Emergency, Panyu Maternal and Child Care Service Centre of Guangzhou, Hexian Memorial Affiliated Hospital of Southern Medical University, Panyu, Guangzhou 511400, Guangdong Province, China
| | - Jinhong Si
- Department of Respiratory Medicine, Panyu Maternal and Child Care Service Centre of Guangzhou, Hexian Memorial Affiliated Hospital of Southern Medical University, Panyu, Guangzhou 511400, Guangdong Province, China
| | - Qiankun Li
- Department of Emergency, Panyu Maternal and Child Care Service Centre of Guangzhou, Hexian Memorial Affiliated Hospital of Southern Medical University, Panyu, Guangzhou 511400, Guangdong Province, China
| | - Weihong Zhang
- Department of Emergency, Panyu Maternal and Child Care Service Centre of Guangzhou, Hexian Memorial Affiliated Hospital of Southern Medical University, Panyu, Guangzhou 511400, Guangdong Province, China
| | - Jiahao He
- Department of Emergency, Panyu Maternal and Child Care Service Centre of Guangzhou, Hexian Memorial Affiliated Hospital of Southern Medical University, Panyu, Guangzhou 511400, Guangdong Province, China
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7
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Pandey S. Sepsis, Management & Advances in Metabolomics. Nanotheranostics 2024; 8:270-284. [PMID: 38577320 PMCID: PMC10988213 DOI: 10.7150/ntno.94071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 02/08/2024] [Indexed: 04/06/2024] Open
Abstract
Though there have been developments in clinical care and management, early and accurate diagnosis and risk stratification are still bottlenecks in septic shock patients. Since septic shock is multifactorial with patient-specific underlying co-morbid conditions, early assessment of sepsis becomes challenging due to variable symptoms and clinical manifestations. Moreover, the treatment strategies are traditionally based on their progression and corresponding clinical symptoms, not personalized. The complex pathophysiology assures that a single biomarker cannot identify, stratify, and describe patients affected by septic shock. Traditional biomarkers like CRP, PCT, and cytokines are not sensitive and specific enough to be used entirely for a patient's diagnosis and prognosis. Thus, the need of the hour is a sensitive and specific biomarker after comprehensive analysis that may facilitate an early diagnosis, prognosis, and drug development. Integration of clinical data with metabolomics would provide means to understand the patient's condition, stratify patients better, and predict the clinical outcome.
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Affiliation(s)
- Swarnima Pandey
- University of Maryland, School of Pharmacy, Department of Pharmaceutical Sciences, Baltimore, MD, USA
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8
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Sha Y, Meng W, Luo G, Zhai X, Tong HHY, Wang Y, Li K. MetDIT: Transforming and Analyzing Clinical Metabolomics Data with Convolutional Neural Networks. Anal Chem 2024. [PMID: 38324756 DOI: 10.1021/acs.analchem.3c04607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Clinical metabolomics is growing as an essential tool for precision medicine. However, classical machine learning algorithms struggle to comprehensively encode and analyze the metabolomics data due to their high dimensionality and complex intercorrelations. This article introduces a new method called MetDIT, designed to analyze intricate metabolomics data effectively using deep convolutional neural networks (CNN). MetDIT comprises two components: TransOmics and NetOmics. Since CNN models have difficulty in processing one-dimensional (1D) sequence data efficiently, we developed TransOmics, a framework that transforms sequence data into two-dimensional (2D) images while maintaining a one-to-one correspondence between the sequences and images. NetOmics, the second component, leverages a CNN architecture to extract more discriminative representations from the transformed samples. To overcome the overfitting due to the small sample size and class imbalance, we introduced a feature augmentation module (FAM) and a loss function to improve the model performance. Furthermore, we systematically optimized the model backbone and image resolution to balance the model parameters and computational costs. To demonstrate the performance of the proposed MetDIT, we conducted extensive experiments using three different clinical metabolomics data sets and achieved better classification performance than classical machine learning methods used in metabolomics, including Random Forest, SVM, XGBoost, and LightGBM. The source code is available at the GitHub repository at https://github.com/Li-OmicsLab/MetDIT, and the WebApp can be found at http://metdit.bioinformatics.vip/.
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Affiliation(s)
- Yuyang Sha
- Center for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macau SR 999708, China
| | - Weiyu Meng
- Center for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macau SR 999708, China
| | - Gang Luo
- Center for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macau SR 999708, China
| | - Xiaobing Zhai
- Center for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macau SR 999708, China
| | - Henry H Y Tong
- Center for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macau SR 999708, China
| | - Yuefei Wang
- National Key Laboratory of Chinese Medicine Modernization, State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
- Haihe Laboratory of Modern Chinese Medicine, Tianjin 301617, China
| | - Kefeng Li
- Center for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macau SR 999708, China
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9
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Meng W, Pan H, Sha Y, Zhai X, Xing A, Lingampelly SS, Sripathi SR, Wang Y, Li K. Metabolic Connectome and Its Role in the Prediction, Diagnosis, and Treatment of Complex Diseases. Metabolites 2024; 14:93. [PMID: 38392985 PMCID: PMC10890086 DOI: 10.3390/metabo14020093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 01/17/2024] [Accepted: 01/25/2024] [Indexed: 02/25/2024] Open
Abstract
The interconnectivity of advanced biological systems is essential for their proper functioning. In modern connectomics, biological entities such as proteins, genes, RNA, DNA, and metabolites are often represented as nodes, while the physical, biochemical, or functional interactions between them are represented as edges. Among these entities, metabolites are particularly significant as they exhibit a closer relationship to an organism's phenotype compared to genes or proteins. Moreover, the metabolome has the ability to amplify small proteomic and transcriptomic changes, even those from minor genomic changes. Metabolic networks, which consist of complex systems comprising hundreds of metabolites and their interactions, play a critical role in biological research by mediating energy conversion and chemical reactions within cells. This review provides an introduction to common metabolic network models and their construction methods. It also explores the diverse applications of metabolic networks in elucidating disease mechanisms, predicting and diagnosing diseases, and facilitating drug development. Additionally, it discusses potential future directions for research in metabolic networks. Ultimately, this review serves as a valuable reference for researchers interested in metabolic network modeling, analysis, and their applications.
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Affiliation(s)
- Weiyu Meng
- Center for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macau SAR 999078, China
| | - Hongxin Pan
- Center for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macau SAR 999078, China
| | - Yuyang Sha
- Center for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macau SAR 999078, China
| | - Xiaobing Zhai
- Center for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macau SAR 999078, China
| | - Abao Xing
- Center for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macau SAR 999078, China
| | | | - Srinivasa R Sripathi
- Henderson Ocular Stem Cell Laboratory, Retina Foundation of the Southwest, Dallas, TX 75231, USA
| | - Yuefei Wang
- National Key Laboratory of Chinese Medicine Modernization, State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
- Haihe Laboratory of Modern Chinese Medicine, Tianjin 301617, China
| | - Kefeng Li
- Center for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macau SAR 999078, China
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10
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Johansson PI, Henriksen HH, Karvelsson ST, Rolfsson Ó, Schønemann-Lund M, Bestle MH, McGarrity S. LASSO regression shows histidine and sphingosine 1 phosphate are linked to both sepsis mortality and endothelial damage. Eur J Med Res 2024; 29:71. [PMID: 38245777 PMCID: PMC10799523 DOI: 10.1186/s40001-023-01612-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 12/21/2023] [Indexed: 01/22/2024] Open
Abstract
Sepsis is a major cause of death worldwide, with a mortality rate that has remained stubbornly high. The current gold standard of risk stratifying sepsis patients provides limited mechanistic insight for therapeutic targeting. An improved ability to predict sepsis mortality and to understand the risk factors would allow better treatment targeting. Sepsis causes metabolic dysregulation in patients; therefore, metabolomics offers a promising tool to study sepsis. It is also known that that in sepsis endothelial cells affecting their function regarding blood clotting and vascular permeability. We integrated metabolomics data from patients admitted to an intensive care unit for sepsis, with commonly collected clinical features of their cases and two measures of endothelial function relevant to blood vessel function, platelet endothelial cell adhesion molecule and soluble thrombomodulin concentrations in plasma. We used least absolute shrinkage and selection operator penalized regression, and pathway enrichment analysis to identify features most able to predict 30-day survival. The features important to sepsis survival include carnitines, and amino acids. Endothelial proteins in plasma also predict 30-day mortality and the levels of these proteins also correlate with a somewhat overlapping set of metabolites. Overall metabolic dysregulation, particularly in endothelial cells, may be a contributory factor to sepsis response. By exploring sepsis metabolomics data in conjunction with clinical features and endothelial proteins we have gained a better understanding of sepsis risk factors.
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Affiliation(s)
- Pär I Johansson
- CAG Center for Endotheliomics, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Hanne H Henriksen
- CAG Center for Endotheliomics, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | | | - Óttar Rolfsson
- Biomedical Center, University of Iceland, Reykjavik, Iceland
| | - Martin Schønemann-Lund
- Department of Anaesthesiology and Intensive Care, Copenhagen University Hospital - North Zealand, Hillerod, Denmark
| | - Morten H Bestle
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Anaesthesiology and Intensive Care, Copenhagen University Hospital - North Zealand, Hillerod, Denmark
| | - Sarah McGarrity
- Biomedical Center, University of Iceland, Reykjavik, Iceland.
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11
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de Nooijer AH, Pickkers P, Netea MG, Kox M. Inflammatory biomarkers to predict the prognosis of acute bacterial and viral infections. J Crit Care 2023; 78:154360. [PMID: 37343422 DOI: 10.1016/j.jcrc.2023.154360] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 06/07/2023] [Indexed: 06/23/2023]
Abstract
Mortality in acute infections is mostly associated with sepsis, defined as 'life-threatening organ dysfunction caused by a dysregulated host response to infection'. It remains challenging to identify the patients with increased mortality risk due to the high heterogeneity in the dysregulated host immune response and disease progression. Biomarkers reflecting different pathways involved in the inflammatory response might improve prediction of mortality risk (prognostic enrichment) among patients with acute infections by reducing heterogeneity of the host response, as well as suggest novel strategies for patient stratification and treatment (predictive enrichment) through precision medicine approaches. The predictive value of inflammatory biomarkers has been extensively investigated in bacterial infections and the recent COVID-19 pandemic caused an increased interest in inflammatory biomarkers in this viral infection. However, limited research investigated whether the prognostic potential of these biomarkers differs between bacterial and viral infections. In this narrative review, we provide an overview of the value of various inflammatory biomarkers for the prediction of mortality in bacterial and viral infections.
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Affiliation(s)
- Aline H de Nooijer
- Department of Internal Medicine, Radboud University Medical Center, 6500 HB Nijmegen, the Netherlands; Department of Intensive Care Medicine, Radboud University Medical Center, 6500 HB Nijmegen, the Netherlands; Radboud University Medical Center for Infectious Diseases, Radboud University Medical Center, 6500 HB Nijmegen, the Netherlands
| | - Peter Pickkers
- Department of Intensive Care Medicine, Radboud University Medical Center, 6500 HB Nijmegen, the Netherlands; Radboud University Medical Center for Infectious Diseases, Radboud University Medical Center, 6500 HB Nijmegen, the Netherlands
| | - Mihai G Netea
- Department of Internal Medicine, Radboud University Medical Center, 6500 HB Nijmegen, the Netherlands; Radboud University Medical Center for Infectious Diseases, Radboud University Medical Center, 6500 HB Nijmegen, the Netherlands; Department of Immunology and Metabolism, Life & Medical Sciences Institute, University of Bonn, 53115 Bonn, Germany
| | - Matthijs Kox
- Department of Intensive Care Medicine, Radboud University Medical Center, 6500 HB Nijmegen, the Netherlands; Radboud University Medical Center for Infectious Diseases, Radboud University Medical Center, 6500 HB Nijmegen, the Netherlands.
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12
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Mayers JR, Varon J, Zhou RR, Daniel-Ivad M, Beaulieu C, Bholse A, Glasser NR, Lichtenauer FM, Ng J, Vera MP, Huttenhower C, Perrella MA, Clish CB, Zhao SD, Baron RM, Balskus EP. Identification and targeting of microbial putrescine acetylation in bloodstream infections. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.21.558834. [PMID: 37790300 PMCID: PMC10542159 DOI: 10.1101/2023.09.21.558834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
The growth of antimicrobial resistance (AMR) has highlighted an urgent need to identify bacterial pathogenic functions that may be targets for clinical intervention. Although severe bacterial infections profoundly alter host metabolism, prior studies have largely ignored alterations in microbial metabolism in this context. Performing metabolomics on patient and mouse plasma samples, we identify elevated levels of bacterially-derived N-acetylputrescine during gram-negative bloodstream infections (BSI), with higher levels associated with worse clinical outcomes. We discover that SpeG is the bacterial enzyme responsible for acetylating putrescine and show that blocking its activity reduces bacterial proliferation and slows pathogenesis. Reduction of SpeG activity enhances bacterial membrane permeability and results in increased intracellular accumulation of antibiotics, allowing us to overcome AMR of clinical isolates both in culture and in vivo. This study highlights how studying pathogen metabolism in the natural context of infection can reveal new therapeutic strategies for addressing challenging infections.
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Affiliation(s)
- Jared R. Mayers
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA 02115
- Harvard Medical School, Boston, MA, USA 02115
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA 02138
| | - Jack Varon
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA 02115
- Harvard Medical School, Boston, MA, USA 02115
| | - Ruixuan R. Zhou
- Department of Statistics, University of Illinois at Urbana Champaign, Champaign, IL, USA 61820
| | - Martin Daniel-Ivad
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA 02138
- Broad Institute of MIT and Harvard, Cambridge, MA, USA 02142
| | | | - Amrisha Bholse
- Broad Institute of MIT and Harvard, Cambridge, MA, USA 02142
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA 02115
| | - Nathaniel R. Glasser
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA 02138
| | | | - Julie Ng
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA 02115
- Harvard Medical School, Boston, MA, USA 02115
| | - Mayra Pinilla Vera
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA 02115
| | - Curtis Huttenhower
- Broad Institute of MIT and Harvard, Cambridge, MA, USA 02142
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA 02115
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Mark A. Perrella
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA 02115
- Harvard Medical School, Boston, MA, USA 02115
| | - Clary B. Clish
- Broad Institute of MIT and Harvard, Cambridge, MA, USA 02142
| | - Sihai D. Zhao
- Department of Statistics, University of Illinois at Urbana Champaign, Champaign, IL, USA 61820
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana Champaign, Champaign, IL, USA 61820
| | - Rebecca M. Baron
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA 02115
- Harvard Medical School, Boston, MA, USA 02115
| | - Emily P. Balskus
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA 02138
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA, USA 02138
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13
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Feng S, Cui N, Zhao W, Zhao H, Wang C, Zheng J, Zhu T, Chen J, Jiang H, Su Q. Prognostic biomarkers for sepsis mortality based on the literature and LC-MS-based metabolomics of sepsis patients. Am J Transl Res 2023; 15:5757-5768. [PMID: 37854200 PMCID: PMC10579003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 06/29/2023] [Indexed: 10/20/2023]
Abstract
OBJECTIVES The management of sepsis, a potentially lethal overreaction to infection, is limited by the lack of prognostic tools to guide its treatment. Our aim is to identify a novel metabolic biomarker panel for predicting sepsis mortality based on a literature review and liquid chromatography-mass spectrometry (LC-MS)-based metabolomics. METHODS In the literature, we found metabolomics biomarkers reported to predict sepsis mortality. We determined the classifications, reported frequency, and KEGG pathway enrichment of these markers. Using serum samples from 20 sepsis survivors and 20 non-survivors within 28 days after admission to the intensive care unit (ICU), we performed LC-MS-based metabolomics. Based on the literature review and metabolomics, a prognostic biomarker panel for sepsis was identified and its area under the curve (AUC) values was assessed. RESULTS Kynurenate, caffeine, and lysoPC 22:4 were selected as a prognostic biomarker panel for sepsis. The panel had an area under the curve (AUC) of 0.885 (95% CI, 0.694-1) evaluated by linear support vector machine (SVM) and 0.849 (0.699-1) by random forest (RF), which was higher than that of the Sequential Organ Failure Assessment (SOFA). A combination of kynurenate, caffeine, and lysoPC 22:4 and SOFA provided the best discriminating performance, with AUCs of 0.961 (0.878-1) for SVM and 0.916 (0.774-1) for RF. CONCLUSIONS The prognostic biomarker panel consisting of kynurenate, caffeine, and lysoPC 22:4 may aid in the identification of sepsis patients at a high risk of death, leading to personalized therapy in clinical practice that will improve sepsis survival.
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Affiliation(s)
- Shi Feng
- Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang UniversityHangzhou 310003, Zhejiang, China
- Key Laboratory of Nephropathy, Zhejiang UniversityHangzhou 310003, Zhejiang, China
- Institute of Nephropathy, Zhejiang UniversityHangzhou 310003, Zhejiang, China
- Zhejiang Clinical Research Center of Kidney and Urinary System Disease, Zhejiang UniversityHangzhou 310003, Zhejiang, China
| | - Nannan Cui
- Department of ICU, The First Affiliated Hospital, Zhejiang UniversityHangzhou 310003, Zhejiang, China
| | - Wenjun Zhao
- Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang UniversityHangzhou 310003, Zhejiang, China
- Key Laboratory of Nephropathy, Zhejiang UniversityHangzhou 310003, Zhejiang, China
- Institute of Nephropathy, Zhejiang UniversityHangzhou 310003, Zhejiang, China
- Zhejiang Clinical Research Center of Kidney and Urinary System Disease, Zhejiang UniversityHangzhou 310003, Zhejiang, China
| | - Haige Zhao
- Department of Cardiothoracic Surgery, The First Affiliated Hospital, School of Medicine, Zhejiang UniversityHangzhou 310003, Zhejiang, China
| | - Cuili Wang
- Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang UniversityHangzhou 310003, Zhejiang, China
- Key Laboratory of Nephropathy, Zhejiang UniversityHangzhou 310003, Zhejiang, China
- Institute of Nephropathy, Zhejiang UniversityHangzhou 310003, Zhejiang, China
- Zhejiang Clinical Research Center of Kidney and Urinary System Disease, Zhejiang UniversityHangzhou 310003, Zhejiang, China
| | - Junnan Zheng
- Department of ICU, The First Affiliated Hospital, Zhejiang UniversityHangzhou 310003, Zhejiang, China
| | - Tingting Zhu
- Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang UniversityHangzhou 310003, Zhejiang, China
- Key Laboratory of Nephropathy, Zhejiang UniversityHangzhou 310003, Zhejiang, China
- Institute of Nephropathy, Zhejiang UniversityHangzhou 310003, Zhejiang, China
- Zhejiang Clinical Research Center of Kidney and Urinary System Disease, Zhejiang UniversityHangzhou 310003, Zhejiang, China
| | - Jianghua Chen
- Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang UniversityHangzhou 310003, Zhejiang, China
- Key Laboratory of Nephropathy, Zhejiang UniversityHangzhou 310003, Zhejiang, China
- Institute of Nephropathy, Zhejiang UniversityHangzhou 310003, Zhejiang, China
- Zhejiang Clinical Research Center of Kidney and Urinary System Disease, Zhejiang UniversityHangzhou 310003, Zhejiang, China
| | - Hong Jiang
- Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang UniversityHangzhou 310003, Zhejiang, China
- Key Laboratory of Nephropathy, Zhejiang UniversityHangzhou 310003, Zhejiang, China
- Institute of Nephropathy, Zhejiang UniversityHangzhou 310003, Zhejiang, China
- Zhejiang Clinical Research Center of Kidney and Urinary System Disease, Zhejiang UniversityHangzhou 310003, Zhejiang, China
| | - Qun Su
- Department of ICU, The First Affiliated Hospital, Zhejiang UniversityHangzhou 310003, Zhejiang, China
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14
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Sinha S, Kumar S, Narwaria M, Singh A, Haque M. Severe Acute Bronchial Asthma with Sepsis: Determining the Status of Biomarkers in the Diagnosis of the Disease. Diagnostics (Basel) 2023; 13:2691. [PMID: 37627950 PMCID: PMC10453001 DOI: 10.3390/diagnostics13162691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 08/04/2023] [Accepted: 08/15/2023] [Indexed: 08/27/2023] Open
Abstract
Bronchial asthma is a widely prevalent illness that substantially impacts an individual's health standard worldwide and has a significant financial impact on society. Global guidelines for managing asthma do not recommend the routine use of antimicrobial agents because most episodes of the condition are linked to viral respiratory tract infections (RTI), and bacterial infection appears to have an insignificant impact. However, antibiotics are recommended when there is a high-grade fever, a consolidation on the chest radiograph, and purulent sputum that contains polymorphs rather than eosinophils. Managing acute bronchial asthma with sepsis, specifically the choice of whether or not to initiate antimicrobial treatment, remains difficult since there are currently no practical clinical or radiological markers that allow for a simple distinction between viral and bacterial infections. Researchers found that serum procalcitonin (PCT) values can efficiently and safely minimize antibiotic usage in individuals with severe acute asthma. Again, the clinical manifestations of acute asthma and bacterial RTI are similar, as are frequently used test values, like C-reactive protein (CRP) and white blood cell (WBC) count, making it harder for doctors to differentiate between viral and bacterial infections in asthma patients. The role and scope of each biomarker have not been precisely defined yet, although they have all been established to aid healthcare professionals in their diagnostics and treatment strategies.
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Affiliation(s)
- Susmita Sinha
- Department of Physiology, Khulna City Medical College and Hospital, 33 KDA Avenue, Hotel Royal Crossing, Khulna Sadar, Khulna 9100, Bangladesh
| | - Santosh Kumar
- Department of Periodontology, Karnavati School of Dentistry, Karnavati University, Gandhinagar 382422, Gujarat, India
| | - Mahendra Narwaria
- Asian Bariatrics Plus Hospital, V Wing-Mondeal Business Park, SG Highways, Ahmedabad 380054, Gujarat, India
| | - Arya Singh
- Asian Bariatrics Plus Hospital, V Wing-Mondeal Business Park, SG Highways, Ahmedabad 380054, Gujarat, India
| | - Mainul Haque
- The Unit of Pharmacology, Faculty of Medicine and Defence Health, Universiti Pertahanan Nasional Malaysia, Kuala Lumpur 57000, Malaysia
- Department of Scientific Research Center (KSRC), Karnavati School of Dentistry, Karnavati University, Gandhinagar 382422, Gujarat, India
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15
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Lavigne A, Géhin T, Gilquin B, Jousseaume V, Veillerot M, Botella C, Chevalier C, Jamois C, Chevolot Y, Phaner-Goutorbe M, Yeromonahos C. Effect of Silane Monolayers and Nanoporous Silicon Surfaces on the Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Detection of Sepsis Metabolites Biomarkers Mixed in Solution. ACS OMEGA 2023; 8:28898-28909. [PMID: 37576693 PMCID: PMC10413469 DOI: 10.1021/acsomega.3c04266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 07/07/2023] [Indexed: 08/15/2023]
Abstract
Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-ToF MS) is a promising strategy for clinical diagnosis based on metabolite detection. However, several bottlenecks (such as the lack of reproducibility in analysis, the presence of an important background in low-mass range, and the lack of organic matrix for some molecules) prevent its transfer to clinical cases. These limitations can be addressed by using nanoporous silicon surfaces chemically functionalized with silane monolayers. In the present study, sepsis metabolite biomarkers were used to investigate the effects of silane monolayers and porous silicon substrates on MALDI-ToF MS analysis (signal-to-noise value (S/N), relative standard deviation of the S/N of triplicate samples (STDmean), and intra-substrates uniformity). Also, the impact of the physicochemical properties of metabolites, with different isoelectric points and hydrophobic-hydrophilic balances, was assessed. Four different silane molecules, with various alkyl chain lengths and head-group charges, were self-assembled in monolayers on plane and porous silicon surfaces. Their surface coverage and conformity were investigated by X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (ToF-SIMS). The seven metabolites detected on the stainless-steel target plate (lysophosphatidylcholine, caffeine, phenylalanine, creatinine, valine, arginine, and glycerophosphocholine) are also detected on the silanized and bare, plane and porous silicon surfaces. Moreover, two metabolites, glycine and alanine, which are not detected on the stainless-steel target plate, are detected on all silanized surfaces, except glycine which is not detected on CH3 short-modified porous silicon and on the bare plane silicon substrate. In addition, whatever the metabolites (except phenylalanine and valine), at least one of the silicon surfaces allows to increase the S/N value in comparison with the stainless-steel target plate. Also, the heterogeneity of matrix crystallization features is linked to the STDmean which is poor on the NH3+ monolayer on plane substrate and better on the NH3+ monolayer on porous substrate, for most of the metabolites. Nevertheless, matrix crystallization features are not sufficient to systematically get high STDmean and uniformity in MALDI-ToF MS analysis. Indeed, the physicochemical properties of metabolites and surfaces, limitations in metabolite extraction from the pores, and improvement in metabolite desorption due to the pores are shown to significantly impact MS analysis. In particular, in the case of the most hydrophobic metabolites studied, the highest S/N values and the best STDmean and uniformity (the lowest values) are reached by using porous substrates, while in the case of the most hydrophilic metabolites studied, plane substrates demonstrated the highest S/N and the lowest STDmean. No clear trend of surface chemistry was evidenced.
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Affiliation(s)
- Antonin Lavigne
- Univ
Lyon, Ecole Centrale de Lyon, CNRS, INSA Lyon, Université Claude
Bernard Lyon 1, CPE Lyon, INL, UMR5270, 69134 Ecully Cedex, France
| | - Thomas Géhin
- Univ
Lyon, CNRS, Ecole Centrale de Lyon, INSA Lyon, Université Claude
Bernard Lyon 1, CPE Lyon, INL, UMR5270, 69134 Ecully Cedex, France
| | - Benoît Gilquin
- Univ
Grenoble Alpes, CEA, LETI, F-38000 Grenoble, France
| | | | - Marc Veillerot
- Univ
Grenoble Alpes, CEA, LETI, F-38000 Grenoble, France
| | - Claude Botella
- Univ
Lyon, CNRS, Ecole Centrale de Lyon, INSA Lyon, Université Claude
Bernard Lyon 1, CPE Lyon, INL, UMR5270, 69134 Ecully Cedex, France
| | - Céline Chevalier
- Univ
Lyon, INSA Lyon, CNRS, Ecole Centrale de Lyon, Université Claude
Bernard Lyon 1, CPE Lyon, INL, UMR5270, 69621 Villeurbanne Cedex, France
| | - Cécile Jamois
- Univ
Lyon, INSA Lyon, CNRS, Ecole Centrale de Lyon, Université Claude
Bernard Lyon 1, CPE Lyon, INL, UMR5270, 69621 Villeurbanne Cedex, France
| | - Yann Chevolot
- Univ
Lyon, CNRS, Ecole Centrale de Lyon, INSA Lyon, Université Claude
Bernard Lyon 1, CPE Lyon, INL, UMR5270, 69134 Ecully Cedex, France
| | - Magali Phaner-Goutorbe
- Univ
Lyon, Ecole Centrale de Lyon, CNRS, INSA Lyon, Université Claude
Bernard Lyon 1, CPE Lyon, INL, UMR5270, 69134 Ecully Cedex, France
| | - Christelle Yeromonahos
- Univ
Lyon, Ecole Centrale de Lyon, CNRS, INSA Lyon, Université Claude
Bernard Lyon 1, CPE Lyon, INL, UMR5270, 69134 Ecully Cedex, France
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16
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Pandey S, Siddiqui MA, Azim A, Sinha N. Metabolic fingerprint of patients showing responsiveness to treatment of septic shock in intensive care unit. MAGMA (NEW YORK, N.Y.) 2023; 36:659-669. [PMID: 36449125 DOI: 10.1007/s10334-022-01049-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 11/11/2022] [Accepted: 11/14/2022] [Indexed: 06/17/2023]
Abstract
OBJECTIVE An early metabolic signature associated with the responsiveness to treatment can be useful in the better management of septic shock patients. This would help clinicians in designing personalized treatment protocols for patients showing non-responsiveness to treatment. METHODS We analyzed the serum on Day 1 (n = 60), Day 3 (n = 47), and Day 5 (n = 26) of patients with septic shock under treatment using NMR-based metabolomics. Partial least square discriminant analysis (PLS-DA) was performed to generate the list of metabolites that can be identified as potential disease biomarkers having statistical significance (that is, metabolites that had a VIP score > 1, and p value < 0.05, False discovery rate (FDR) < 0.05). RESULTS Common significant metabolites amongst the three time points were obtained that distinguished the patients being responsive (R) and non-responsive (NR) to treatments, namely 3 hydroxybutyrate, lactate, and phenylalanine which were lower, whereas glutamate and choline higher in patients showing responsiveness. DISCUSSION The study gave these metabolic signatures identifying patients' responsiveness to treatment. The results of the study will aid in the development of targeted therapy for ICU patients.
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Affiliation(s)
- Swarnima Pandey
- Centre of Biomedical Research, SGPGIMS Campus, Raebareli Road, Lucknow, 226014, India
| | - Mohd Adnan Siddiqui
- Centre of Biomedical Research, SGPGIMS Campus, Raebareli Road, Lucknow, 226014, India
| | - Afzal Azim
- Department of Critical Care Medicine, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Rae Bareli Road, Lucknow, Uttar Pradesh, 226014, India
| | - Neeraj Sinha
- Centre of Biomedical Research, SGPGIMS Campus, Raebareli Road, Lucknow, 226014, India.
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17
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den Hartog I, Karu N, Zwep LB, Voorn GP, van de Garde EM, Hankemeier T, van Hasselt JC. Differential metabolic host response to pathogens associated with community-acquired pneumonia. Metabol Open 2023; 18:100239. [PMID: 37025095 PMCID: PMC10070890 DOI: 10.1016/j.metop.2023.100239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 03/20/2023] [Indexed: 03/30/2023] Open
Abstract
Background Metabolic changes induced by the host immune response to pathogens found in patients with community-acquired pneumonia (CAP) may provide insight into its pathogenesis. In this study, we characterized differences in the host metabolic response to common CAP-associated pathogens. Method Targeted metabolomic profiling was performed on serum samples obtained from hospitalized CAP patients (n = 119) at admission. We quantified 347 unique metabolites across multiple biochemical classes, including amines, acylcarnitines, and signaling lipids. We evaluated if unique associations between metabolite levels and specific CAP-associated pathogens could be identified. Results Several acylcarnitines were found to be elevated in C. burnetii and herpes simplex virus and lowered in M. pneumoniae as compared to other pathogens. Phenylalanine and kynurenine were found elevated in L. pneumophila as compared to other pathogens. S-methylcysteine was elevated in patients with M. pneumoniae, and these patients also showed lowered cortisol levels in comparison to almost all other pathogens. For the herpes simplex virus, we observed a unique elevation of eicosanoids and several amines. Many lysophosphatidylcholines showed an altered profile in C. burnetii versus S. pneumoniae, L. pneumophila, and respiratory syncytial virus. Finally, phosphatidylcholines were negatively affected by the influenza virus in comparison to S. pneumoniae. Conclusions In this exploratory analysis, metabolites from different biochemical classes were found to be altered in serum samples from patients with different CAP-associated pathogens, which may be used for hypothesis generation in studies on differences in pathogen host response and pathogenesis of CAP.
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Affiliation(s)
- Ilona den Hartog
- Division of Systems Pharmacology & Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Leiden, the Netherlands
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Leiden, the Netherlands
| | - Naama Karu
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Leiden, the Netherlands
| | - Laura B. Zwep
- Division of Systems Pharmacology & Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Leiden, the Netherlands
| | - G. Paul Voorn
- Department of Medical Microbiology and Immunology, St. Antonius Hospital, Nieuwegein, the Netherlands
| | - Ewoudt M.W. van de Garde
- Division of Pharmacoepidemiology and Clinical Pharmacology, Department of Pharmaceutical Sciences, Utrecht University, Utrecht, the Netherlands
- Department of Clinical Pharmacy, St. Antonius Hospital, Nieuwegein, the Netherlands
| | - Thomas Hankemeier
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Leiden, the Netherlands
| | - J.G. Coen van Hasselt
- Division of Systems Pharmacology & Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Leiden, the Netherlands
- Corresponding author.
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Gillen A, Catherine Archer D. Epidemiology of Colic: Current Knowledge and Future Directions. Vet Clin North Am Equine Pract 2023:S0749-0739(23)00017-2. [PMID: 37268523 DOI: 10.1016/j.cveq.2023.03.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/04/2023] Open
Abstract
Epidemiologic studies are essential for the generation of evidence-based, preventive health care strategies. This includes ways to minimize colic risk and assist informed decision making concerning diagnosis, treatment, and likely outcomes. It is important to consider that colic is not a simple "disease" but is a syndrome of abdominal pain that encompasses multiple different disease processes, and which is multifactorial in nature. This review focuses on prevention and diagnosis of colic, including specific forms of colic, communications with owners/carers concerning colic risk and management, and areas of future research.
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Affiliation(s)
- Alexandra Gillen
- Department of Equine Clinical Science, School of Veterinary Sciences, Leahurst Campus, University of Liverpool, Leahurst, Neston, Wirral CH64 7TE, United Kingdom
| | - Debra Catherine Archer
- Department of Equine Clinical Science, School of Veterinary Sciences, Leahurst Campus, University of Liverpool, Leahurst, Neston, Wirral CH64 7TE, United Kingdom.
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19
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Lavigne A, Gilquin B, Géhin T, Jousseaume V, Veillerot M, Chevolot Y, Phaner-Goutorbe M, Yeromonahos C. Effects of Silane Monolayers on Lysophosphatidylcholine (LysoPC) Detection by Desorption Ionization on Silicon Mass Spectrometry (DIOS-MS) in Solution and Plasma. ACS APPLIED MATERIALS & INTERFACES 2023; 15:18685-18693. [PMID: 37014887 DOI: 10.1021/acsami.3c01181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Desorption ionization on silicon mass spectrometry (DIOS-MS) enables high throughput analysis of low-molecular-weight biomolecules. However, detection of metabolite biomarkers in complex fluids such as plasma requires sample pretreatment, limiting clinical application. Here, we show that porous silicon, chemically modified using monolayers of n-propyldimethylmethoxysilane molecules, is a good candidate for fingerprinting lysophosphatidylcholine (lysoPC) in plasma, without sample pretreatment, for DIOS-MS-based diagnosis (e.g., sepsis). Results were correlated to lysoPC molecule location inside/outside the pores, determined by time-of-flight secondary ion mass spectrometry profiling, and to physicochemical properties.
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Affiliation(s)
- Antonin Lavigne
- CNRS, INSA Lyon, Université Claude Bernard Lyon 1, CPE Lyon, INL, UMR5270, Univ Lyon, Ecole Centrale de Lyon, 69134 Ecully Cedex, France
| | - Benoît Gilquin
- CEA, LETI, Clinatec, Univ. Grenoble Alpes, 38000 Grenoble, France
| | - Thomas Géhin
- INSA Lyon, Université Claude Bernard Lyon 1, CPE Lyon, INL, UMR5270, Univ Lyon, CNRS, Ecole Centrale de Lyon, 69134 Ecully Cedex, France
| | | | - Marc Veillerot
- CEA, LETI, Univ Grenoble Alpes, F-38000 Grenoble, France
| | - Yann Chevolot
- INSA Lyon, Université Claude Bernard Lyon 1, CPE Lyon, INL, UMR5270, Univ Lyon, CNRS, Ecole Centrale de Lyon, 69134 Ecully Cedex, France
| | - Magali Phaner-Goutorbe
- CNRS, INSA Lyon, Université Claude Bernard Lyon 1, CPE Lyon, INL, UMR5270, Univ Lyon, Ecole Centrale de Lyon, 69134 Ecully Cedex, France
| | - Christelle Yeromonahos
- CNRS, INSA Lyon, Université Claude Bernard Lyon 1, CPE Lyon, INL, UMR5270, Univ Lyon, Ecole Centrale de Lyon, 69134 Ecully Cedex, France
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20
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Vanderhaeghen T, Timmermans S, Eggermont M, Watts D, Vandewalle J, Wallaeys C, Nuyttens L, De Temmerman J, Hochepied T, Dewaele S, Berghe JV, Sanders N, Wielockx B, Beyaert R, Libert C. The impact of hepatocyte-specific deletion of hypoxia-inducible factors on the development of polymicrobial sepsis with focus on GR and PPARα function. Front Immunol 2023; 14:1124011. [PMID: 37006237 PMCID: PMC10060827 DOI: 10.3389/fimmu.2023.1124011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 02/27/2023] [Indexed: 03/18/2023] Open
Abstract
IntroductionPolymicrobial sepsis causes acute anorexia (loss of appetite), leading to lipolysis in white adipose tissue and proteolysis in muscle, and thus release of free fatty acids (FFAs), glycerol and gluconeogenic amino acids. Since hepatic peroxisome proliferator-activated receptor alpha (PPARα) and glucocorticoid receptor (GR) quickly lose function in sepsis, these metabolites accumulate (causing toxicity) and fail to yield energy-rich molecules such as ketone bodies (KBs) and glucose. The mechanism of PPARα and GR dysfunction is not known.Methods & resultsWe investigated the hypothesis that hypoxia and/or activation of hypoxia inducible factors (HIFs) might play a role in these issues with PPARα and GR. After cecal ligation and puncture (CLP) in mice, leading to lethal polymicrobial sepsis, bulk liver RNA sequencing illustrated the induction of the genes encoding HIF1α and HIF2α, and an enrichment of HIF-dependent gene signatures. Therefore, we generated hepatocyte-specific knock-out mice for HIF1α, HIF2α or both, and a new HRE-luciferase reporter mouse line. After CLP, these HRE-luciferase reporter mice show signals in several tissues, including the liver. Hydrodynamic injection of an HRE-luciferase reporter plasmid also led to (liver-specific) signals in hypoxia and CLP. Despite these encouraging data, however, hepatocyte-specific HIF1α and/or HIF2α knock-out mice suggest that survival after CLP was not dependent on the hepatocyte-specific presence of HIF proteins, which was supported by measuring blood levels of glucose, FFAs, and KBs. The HIF proteins were also irrelevant in the CLP-induced glucocorticoid resistance, but we found indications that the absence of HIF1α in hepatocytes causes less inactivation of PPARα transcriptional function.ConclusionWe conclude that HIF1α and HIF2α are activated in hepatocytes in sepsis, but their contribution to the mechanisms leading to lethality are minimal.
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Affiliation(s)
- Tineke Vanderhaeghen
- Flanders Institute for Biotechnology (VIB) Center for Inflammation Research, Ghent, Belgium
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
| | - Steven Timmermans
- Flanders Institute for Biotechnology (VIB) Center for Inflammation Research, Ghent, Belgium
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
| | - Melanie Eggermont
- Flanders Institute for Biotechnology (VIB) Center for Inflammation Research, Ghent, Belgium
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
| | - Deepika Watts
- Department of Clinical Pathobiochemistry, Institute for Clinical Chemistry and Laboratory Medicine, Technische Universität Dresden, Dresden, Germany
- Deutsche Forschungsgemeinschaft (DFG) Research Centre and Cluster of Excellence for Regenerative Therapies Dresden, Technische Universität Dresden, Dresden, Germany
| | - Jolien Vandewalle
- Flanders Institute for Biotechnology (VIB) Center for Inflammation Research, Ghent, Belgium
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
| | - Charlotte Wallaeys
- Flanders Institute for Biotechnology (VIB) Center for Inflammation Research, Ghent, Belgium
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
| | - Louise Nuyttens
- Flanders Institute for Biotechnology (VIB) Center for Inflammation Research, Ghent, Belgium
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
| | - Joyca De Temmerman
- Department of Nutrition, Genetics, and Ethology, Faculty of Veterinary Medicine, Ghent University, Ghent, Belgium
- Department of Pathology, Bacteriology, and Avian Diseases, Faculty of Veterinary Medicine, Ghent University, Ghent, Belgium
| | - Tino Hochepied
- Flanders Institute for Biotechnology (VIB) Center for Inflammation Research, Ghent, Belgium
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
| | - Sylviane Dewaele
- Flanders Institute for Biotechnology (VIB) Center for Inflammation Research, Ghent, Belgium
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
| | - Joke Vanden Berghe
- Flanders Institute for Biotechnology (VIB) Center for Inflammation Research, Ghent, Belgium
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
| | - Niek Sanders
- Department of Nutrition, Genetics, and Ethology, Faculty of Veterinary Medicine, Ghent University, Ghent, Belgium
- Department of Pathology, Bacteriology, and Avian Diseases, Faculty of Veterinary Medicine, Ghent University, Ghent, Belgium
| | - Ben Wielockx
- Department of Clinical Pathobiochemistry, Institute for Clinical Chemistry and Laboratory Medicine, Technische Universität Dresden, Dresden, Germany
- Deutsche Forschungsgemeinschaft (DFG) Research Centre and Cluster of Excellence for Regenerative Therapies Dresden, Technische Universität Dresden, Dresden, Germany
| | - Rudi Beyaert
- Flanders Institute for Biotechnology (VIB) Center for Inflammation Research, Ghent, Belgium
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
| | - Claude Libert
- Flanders Institute for Biotechnology (VIB) Center for Inflammation Research, Ghent, Belgium
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
- *Correspondence: Claude Libert,
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21
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He S, Zhao C, Guo Y, Zhao J, Xu X, Hu Y, Lian B, Ye H, Wang N, Luo L, Liu Q. Alterations in the gut microbiome and metabolome profiles of septic mice treated with Shen FuHuang formula. Front Microbiol 2023; 14:1111962. [PMID: 36970673 PMCID: PMC10030955 DOI: 10.3389/fmicb.2023.1111962] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 02/20/2023] [Indexed: 03/10/2023] Open
Abstract
Sepsis has a high mortality rate, and treating sepsis remains a significant challenge worldwide. In former studies, our group found that traditional Chinese medicine, Shen FuHuang formula (SFH), is a promising medicine in treating coronavirus disease 2019 (COVID-19) patients with the septic syndrome. However, the underlying mechanisms remain elusive. In the present study, we first investigated the therapeutic effects of SFH on septic mice. To investigate the mechanisms of SFH-treated sepsis, we identified the gut microbiome profile and exploited untargeted metabolomics analyses. The results demonstrated that SFH significantly enhanced the mice’s 7-day survival rate and hindered the release of inflammatory mediators, i.e., TNF-α, IL-6, and IL-1β. 16S rDNA sequencing further deciphered that SFH decreased the proportion of Campylobacterota and Proteobacteria at the phylum level. LEfSe analysis revealed that the treatment of SFH enriched Blautia while decreased Escherichia_Shigella. Furthermore, serum untargeted metabolomics analysis indicated that SFH could regulate the glucagon signaling pathway, PPAR signaling pathway, galactose metabolism, and pyrimidine metabolism. Finally, we found the relative abundance of Bacteroides, Lachnospiraceae_NK4A136_group, Escherichia_Shigella, Blautia, Ruminococcus, and Prevotella were closely related to the enrichment of the metabolic signaling pathways, including L-tryptophan, uracil, glucuronic acid, protocatechuic acid, and gamma-Glutamylcysteine. In conclusion, our study demonstrated that SFH alleviated sepsis by suppressing the inflammatory response and hence reduced mortality. The mechanism of SFH for treating sepsis may be ascribed to the enrichment of beneficial gut flora and modulation in glucagon signaling pathway, PPAR signaling pathway, galactose metabolism, and pyrimidine metabolism. To sum up, these findings provide a new scientific perspective for the clinical application of SFH in treating sepsis.
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Affiliation(s)
- Shasha He
- Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China
- Beijing Institute of Chinese Medicine, Beijing, China
- Beijing Key Laboratory of Basic Research with Traditional Chinese Medicine on Infectious Diseases, Beijing, China
| | - Chunxia Zhao
- Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China
- Beijing Institute of Chinese Medicine, Beijing, China
- Beijing Key Laboratory of Basic Research with Traditional Chinese Medicine on Infectious Diseases, Beijing, China
| | - Yuhong Guo
- Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China
- Beijing Institute of Chinese Medicine, Beijing, China
- Beijing Key Laboratory of Basic Research with Traditional Chinese Medicine on Infectious Diseases, Beijing, China
| | - Jingxia Zhao
- Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China
- Beijing Institute of Chinese Medicine, Beijing, China
- Beijing Key Laboratory of Basic Research with Traditional Chinese Medicine on Infectious Diseases, Beijing, China
| | - Xiaolong Xu
- Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China
- Beijing Institute of Chinese Medicine, Beijing, China
- Beijing Key Laboratory of Basic Research with Traditional Chinese Medicine on Infectious Diseases, Beijing, China
| | - Yahui Hu
- Beijing Institute of Chinese Medicine, Beijing, China
- Beijing Key Laboratory of Basic Research with Traditional Chinese Medicine on Infectious Diseases, Beijing, China
- Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Bo Lian
- Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Haoran Ye
- Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China
- Beijing Institute of Chinese Medicine, Beijing, China
- Beijing Key Laboratory of Basic Research with Traditional Chinese Medicine on Infectious Diseases, Beijing, China
| | - Ning Wang
- Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China
- Beijing Institute of Chinese Medicine, Beijing, China
| | - Lianxiang Luo
- The Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang, Guangdong, China
- Lianxiang Luo,
| | - Qingquan Liu
- Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China
- Beijing Institute of Chinese Medicine, Beijing, China
- Beijing Key Laboratory of Basic Research with Traditional Chinese Medicine on Infectious Diseases, Beijing, China
- *Correspondence: Qingquan Liu,
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22
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Chen ZH, Zhang WY, Ye H, Guo YQ, Zhang K, Fang XM. A signature of immune-related genes correlating with clinical prognosis and immune microenvironment in sepsis. BMC Bioinformatics 2023; 24:20. [PMID: 36650470 PMCID: PMC9843880 DOI: 10.1186/s12859-023-05134-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 01/02/2023] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Immune-related genes (IRGs) remain poorly understood in their function in the onset and progression of sepsis. METHODS GSE65682 was obtained from the Gene Expression Omnibus database. The IRGs associated with survival were screened for subsequent modeling using univariate Cox regression analysis and least absolute shrinkage and selection operator in the training cohort. Then, we assessed the reliability of the 7 IRGs signature's independent predictive value in the training and validation cohorts following the creation of a signature applying multivariable Cox regression analysis. After that, we utilized the E-MTAB-4451 external dataset in order to do an independent validation of the prognostic signature. Finally, the CIBERSORT algorithm and single-sample gene set enrichment analysis was utilized to investigate and characterize the properties of the immune microenvironment. RESULTS Based on 7 IRGs signature, patients could be separated into low-risk and high-risk groups. Patients in the low-risk group had a remarkably increased 28-day survival compared to those in the high-risk group (P < 0.001). In multivariable Cox regression analyses, the risk score calculated by this signature was an independent predictor of 28-day survival (P < 0.001). The signature's predictive ability was confirmed by receiver operating characteristic curve analysis with the area under the curve reaching 0.876 (95% confidence interval 0.793-0.946). Moreover, both the validation set and the external dataset demonstrated that the signature had strong clinical prediction performance. In addition, patients in the high-risk group were characterized by a decreased neutrophil count and by reduced inflammation-promoting function. CONCLUSION We developed a 7 IRGs signature as a novel prognostic marker for predicting sepsis patients' 28-day survival, indicating possibilities for individualized reasonable resource distribution of intensive care unit.
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Affiliation(s)
- Zhong-Hua Chen
- grid.13402.340000 0004 1759 700XDepartment of Anesthesiology and Intensive Care, The First Affiliated Hospital, School of Medicine, Zhejiang University, QingChun Road 79, Hangzhou, 310003 China ,grid.415644.60000 0004 1798 6662Department of Anesthesiology, Shaoxing People’s Hospital, Shaoxing, China
| | - Wen-Yuan Zhang
- grid.13402.340000 0004 1759 700XDepartment of Anesthesiology and Intensive Care, The First Affiliated Hospital, School of Medicine, Zhejiang University, QingChun Road 79, Hangzhou, 310003 China
| | - Hui Ye
- grid.13402.340000 0004 1759 700XDepartment of Anesthesiology and Intensive Care, The First Affiliated Hospital, School of Medicine, Zhejiang University, QingChun Road 79, Hangzhou, 310003 China
| | - Yu-Qian Guo
- grid.13402.340000 0004 1759 700XDepartment of Anesthesiology and Intensive Care, The First Affiliated Hospital, School of Medicine, Zhejiang University, QingChun Road 79, Hangzhou, 310003 China
| | - Kai Zhang
- grid.13402.340000 0004 1759 700XDepartment of Anesthesiology and Intensive Care, The First Affiliated Hospital, School of Medicine, Zhejiang University, QingChun Road 79, Hangzhou, 310003 China
| | - Xiang-Ming Fang
- grid.13402.340000 0004 1759 700XDepartment of Anesthesiology and Intensive Care, The First Affiliated Hospital, School of Medicine, Zhejiang University, QingChun Road 79, Hangzhou, 310003 China
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23
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Distinct subsets of neutrophils crosstalk with cytokines and metabolites in patients with sepsis. iScience 2023; 26:105948. [PMID: 36756375 PMCID: PMC9900520 DOI: 10.1016/j.isci.2023.105948] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 11/04/2022] [Accepted: 01/05/2023] [Indexed: 01/09/2023] Open
Abstract
Sepsis is a life-threatening condition caused by a dysregulated host response to infection. Despite continued efforts to understand the pathophysiology of sepsis, no effective therapies are currently available. While singular components of the aberrant immune response have been investigated, comprehensive studies linking different data layers are lacking. Using an integrated systems immunology approach, we evaluated neutrophil phenotypes and concomitant changes in cytokines and metabolites in patients with sepsis. Our findings identify differentially expressed mature and immature neutrophil subsets in patients with sepsis. These subsets correlate with various proteins, metabolites, and lipids, including pentraxin-3, angiopoietin-2, and lysophosphatidylcholines, in patients with sepsis. These results enabled the construction of a statistical model based on weighted multi-omics linear regression analysis for sepsis biomarker identification. These findings could help inform early patient stratification and treatment options, and facilitate further mechanistic studies targeting the trifecta of surface marker expression, cytokines, and metabolites.
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24
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Xie Y, Zhuang D, Chen H, Zou S, Chen W, Chen Y. 28-day sepsis mortality prediction model from combined serial interleukin-6, lactate, and procalcitonin measurements: a retrospective cohort study. Eur J Clin Microbiol Infect Dis 2023; 42:77-85. [PMID: 36383295 PMCID: PMC9816294 DOI: 10.1007/s10096-022-04517-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 10/24/2022] [Indexed: 11/17/2022]
Abstract
Sepsis is a global medical issue owing to its unacceptably high mortality rate. Therefore, an effective approach to predicting patient outcomes is critically needed. We aimed to search for a novel 28-day sepsis mortality prediction model based on serial interleukin-6 (IL-6), lactate (LAC), and procalcitonin (PCT) measurements. We enrolled 367 septic patients based on Sepsis-3 (Third International Consensus Definitions for Sepsis and Septic Shock). Serum IL-6, LAC, and PCT levels were measured serially. Results collected within 24 and 48-72 h of admission were marked as D1 and D3 (e.g., IL-6D1/D3), respectively; the IL-6, LAC, and PCT clearance (IL-6c, LACc, PCTc) at D3 were calculated. Data were split into training and validation cohorts (7:3). Logistic regression analyses were used to select variables to develop models and choose the best one according to the Akaike information criterion (AIC). Receiver operating characteristic curves (ROC), calibration plots, and decision curve analysis (DCA) were used to test model performance. A nomogram was used to validate the model. There were 314 (85.56%) survivors and 53 (14.44%) non-survivors. Logistic regression analyses showed that IL-6D1, IL-6D3, PCTD1, PCTD3, and LACcD3 could be used to develop the best prediction model. The areas under the curves (AUC) of the training (0.849, 95% CI: 0.787-0.911) and validation cohorts (0.828, 95% CI: 0.727-0.929), calibration plot, and the DCA showed that the model performed well. Thus, the predictive value of the risk nomogram was verified. Combining IL-6D1, IL-6D3, PCTD1, PCTD3, and LACcD3 may create an accurate prediction model for 28-day sepsis mortality. Multiple-center research with a larger quantity of data is necessary to determine its clinical utility.
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Affiliation(s)
- Yinjing Xie
- Department of Medical Laboratory, Shenzhen People's Hospital, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of South University of Science and Technology, Shenzhen, 518020, Guangdong, China
| | - Dehua Zhuang
- Department of Medical Laboratory, Shenzhen People's Hospital, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of South University of Science and Technology, Shenzhen, 518020, Guangdong, China
| | - Huaisheng Chen
- Department of Critical Care Medicine, Shenzhen People's Hospital, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of South University of Science and Technology, Shenzhen, 518020, Guangdong, China
| | - Shiqing Zou
- Department of Medical Laboratory, Shenzhen People's Hospital, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of South University of Science and Technology, Shenzhen, 518020, Guangdong, China
| | - Weibu Chen
- Department of Medical Laboratory, Shenzhen People's Hospital, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of South University of Science and Technology, Shenzhen, 518020, Guangdong, China.
| | - Yue Chen
- Department of Medical Laboratory, Shenzhen People's Hospital, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of South University of Science and Technology, Shenzhen, 518020, Guangdong, China.
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25
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Komorowski M, Green A, Tatham KC, Seymour C, Antcliffe D. Sepsis biomarkers and diagnostic tools with a focus on machine learning. EBioMedicine 2022; 86:104394. [PMID: 36470834 PMCID: PMC9783125 DOI: 10.1016/j.ebiom.2022.104394] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 11/16/2022] [Accepted: 11/18/2022] [Indexed: 12/04/2022] Open
Abstract
Over the last years, there have been advances in the use of data-driven techniques to improve the definition, early recognition, subtypes characterisation, prognostication and treatment personalisation of sepsis. Some of those involve the discovery or evaluation of biomarkers or digital signatures of sepsis or sepsis sub-phenotypes. It is hoped that their identification may improve timeliness and accuracy of diagnosis, suggest physiological pathways and therapeutic targets, inform targeted recruitment into clinical trials, and optimise clinical management. Given the complexities of the sepsis response, panels of biomarkers or models combining biomarkers and clinical data are necessary, as well as specific data analysis methods, which broadly fall under the scope of machine learning. This narrative review gives a brief overview of the main machine learning techniques (mainly in the realms of supervised and unsupervised methods) and published applications that have been used to create sepsis diagnostic tools and identify biomarkers.
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Affiliation(s)
- Matthieu Komorowski
- Division of Anaesthetics, Pain Medicine, and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, SW7 2AZ, United Kingdom,Corresponding author.
| | - Ashleigh Green
- Division of Anaesthetics, Pain Medicine, and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, SW7 2AZ, United Kingdom
| | - Kate C. Tatham
- Division of Anaesthetics, Pain Medicine, and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, SW7 2AZ, United Kingdom,Anaesthetics, Perioperative Medicine and Pain Department, Royal Marsden NHS Foundation Trust, 203 Fulham Rd, London, SW3 6JJ, United Kingdom
| | - Christopher Seymour
- Department of Critical Care Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - David Antcliffe
- Division of Anaesthetics, Pain Medicine, and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, SW7 2AZ, United Kingdom
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26
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Ding W, Xu S, Zhou B, Zhou R, Liu P, Hui X, Long Y, Su L. Dynamic Plasma Lipidomic Analysis Revealed Cholesterol Ester and Amides Associated with Sepsis Development in Critically Ill Patients after Cardiovascular Surgery with Cardiopulmonary Bypass. J Pers Med 2022; 12:jpm12111838. [PMID: 36579569 PMCID: PMC9693300 DOI: 10.3390/jpm12111838] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 10/25/2022] [Accepted: 10/28/2022] [Indexed: 11/06/2022] Open
Abstract
Background: Sepsis in patients after cardiovascular surgery with cardiopulmonary bypass (CPB) has a high rate of mortality. We sought to determine whether changes in lipidomics can predict sepsis after cardiac surgery. Methods: We used high-performance liquid chromatography coupled to tandem mass spectrometry to explore global lipidome changes in samples from a prospective case-control cohort (30 sepsis vs. 30 nonsepsis) hospitalized with cardiovascular surgery. All patients were sampled before and within 48−72 h after surgery. A bioinformatic pipeline was applied to acquire reliable features and MS/MS-driven identifications. Furthermore, a multiple-step machine learning framework was performed for signature discovery and performance evaluation. Results: Compared with preoperative samples, 94 features were upregulated and 282 features were downregulated in the postoperative samples of the sepsis group, and 73 features were upregulated and 265 features were downregulated in the postoperative samples of the nonsepsis group. “Autophagy”, “pathogenic Escherichia coli infection” and “glycosylphosphatidylinositol-anchor biosynthesis” pathways were significantly enriched in the pathway enrichment analysis. A multistep machine learning framework further confirmed that two cholesterol esters, CE (18:0) and CE (16:0), were significantly decreased in the sepsis group (p < 0.05). In addition, oleamide and stearamide were increased significantly in the postoperative sepsis group (p < 0.001). Conclusions: This study revealed characteristic lipidomic changes in the plasma of septic patients before and after cardiac surgery with CPB. We discovered two cholesterol esters and two amides from peripheral blood that could be promising signatures for sepsis within a dynamic detection between the preoperative and postoperative groups.
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Affiliation(s)
- Wenyan Ding
- Department of Critical Care Medicine, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Shaohang Xu
- Deepxomics Co., Ltd., Shenzhen 518000, China
| | - Baojin Zhou
- Deepxomics Co., Ltd., Shenzhen 518000, China
| | - Ruo Zhou
- Deepxomics Co., Ltd., Shenzhen 518000, China
| | - Peng Liu
- Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Xiangyi Hui
- Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Yun Long
- Department of Critical Care Medicine, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, China
- Correspondence: (Y.L.); (L.S.)
| | - Longxiang Su
- State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, China
- Correspondence: (Y.L.); (L.S.)
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27
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Njunge JM, Tickell K, Diallo AH, Sayeem Bin Shahid ASM, Gazi MA, Saleem A, Kazi Z, Ali S, Tigoi C, Mupere E, Lancioni CL, Yoshioka E, Chisti MJ, Mburu M, Ngari M, Ngao N, Gichuki B, Omer E, Gumbi W, Singa B, Bandsma R, Ahmed T, Voskuijl W, Williams TN, Macharia A, Makale J, Mitchel A, Williams J, Gogain J, Janjic N, Mandal R, Wishart DS, Wu H, Xia L, Routledge M, Gong YY, Espinosa C, Aghaeepour N, Liu J, Houpt E, Lawley TD, Browne H, Shao Y, Rwigi D, Kariuki K, Kaburu T, Uhlig HH, Gartner L, Jones K, Koulman A, Walson J, Berkley J. The Childhood Acute Illness and Nutrition (CHAIN) network nested case-cohort study protocol: a multi-omics approach to understanding mortality among children in sub-Saharan Africa and South Asia. Gates Open Res 2022; 6:77. [PMID: 36415883 PMCID: PMC9646488 DOI: 10.12688/gatesopenres.13635.2] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/06/2022] [Indexed: 08/10/2023] Open
Abstract
Introduction: Many acutely ill children in low- and middle-income settings have a high risk of mortality both during and after hospitalisation despite guideline-based care. Understanding the biological mechanisms underpinning mortality may suggest optimal pathways to target for interventions to further reduce mortality. The Childhood Acute Illness and Nutrition (CHAIN) Network ( www.chainnnetwork.org) Nested Case-Cohort Study (CNCC) aims to investigate biological mechanisms leading to inpatient and post-discharge mortality through an integrated multi-omic approach. Methods and analysis; The CNCC comprises a subset of participants from the CHAIN cohort (1278/3101 hospitalised participants, including 350 children who died and 658 survivors, and 270/1140 well community children of similar age and household location) from nine sites in six countries across sub-Saharan Africa and South Asia. Systemic proteome, metabolome, lipidome, lipopolysaccharides, haemoglobin variants, toxins, pathogens, intestinal microbiome and biomarkers of enteropathy will be determined. Computational systems biology analysis will include machine learning and multivariate predictive modelling with stacked generalization approaches accounting for the different characteristics of each biological modality. This systems approach is anticipated to yield mechanistic insights, show interactions and behaviours of the components of biological entities, and help develop interventions to reduce mortality among acutely ill children. Ethics and dissemination. The CHAIN Network cohort and CNCC was approved by institutional review boards of all partner sites. Results will be published in open access, peer reviewed scientific journals and presented to academic and policy stakeholders. Data will be made publicly available, including uploading to recognised omics databases. Trial registration NCT03208725.
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Affiliation(s)
- James M. Njunge
- The Childhood Acute Illness and Nutrition Network, Nairobi, Kenya
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Kirkby Tickell
- Global Health and Epidemiology, University of Washington, Seattle, Seattle, USA
| | - Abdoulaye Hama Diallo
- Department of Public Health, Faculty of Health Sciences, University of Ouagadougou, Ouagadougou, Burkina Faso
| | | | - Md. Amran Gazi
- Nutrition and Clinical Services Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | - Ali Saleem
- Department of Pediatrics and Child Health, Aga Khan University Hospital, Karachi, Karachi, Pakistan
| | - Zaubina Kazi
- Department of Pediatrics and Child Health, Aga Khan University Hospital, Karachi, Karachi, Pakistan
| | - Syed Ali
- Department of Pediatrics and Child Health, Aga Khan University Hospital, Karachi, Karachi, Pakistan
| | - Caroline Tigoi
- The Childhood Acute Illness and Nutrition Network, Nairobi, Kenya
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Ezekiel Mupere
- Department of Paediatrics and Child Health, College of Health Sciences, Makerere University, Kampala, Uganda
| | | | - Emily Yoshioka
- Global Health and Epidemiology, University of Washington, Seattle, Seattle, USA
| | - Mohammod Jobayer Chisti
- Nutrition and Clinical Services Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | - Moses Mburu
- The Childhood Acute Illness and Nutrition Network, Nairobi, Kenya
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Moses Ngari
- The Childhood Acute Illness and Nutrition Network, Nairobi, Kenya
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Narshion Ngao
- The Childhood Acute Illness and Nutrition Network, Nairobi, Kenya
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Bonface Gichuki
- The Childhood Acute Illness and Nutrition Network, Nairobi, Kenya
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Elisha Omer
- The Childhood Acute Illness and Nutrition Network, Nairobi, Kenya
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Wilson Gumbi
- The Childhood Acute Illness and Nutrition Network, Nairobi, Kenya
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Benson Singa
- Kenya Medical Research Institute, Nairobi, Kenya
| | - Robert Bandsma
- Centre for Global Child Health, The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Biomedical Sciences, University of Malawi College of Medicine, Blantyre, Malawi
| | - Tahmeed Ahmed
- Nutrition and Clinical Services Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | - Wieger Voskuijl
- Amsterdam UMC location, University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Centre for Global Child Health & Emma Children’s Hospital, Amsterdam, The Netherlands
| | - Thomas N. Williams
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
- Institute of Global Health Innovation, Department of Surgery and Cancer, Imperial College London, London, UK
| | - Alex Macharia
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | | | | | | | | | | | - Rupasri Mandal
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - David S. Wishart
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - Hang Wu
- School of Food Science and Nutrition, University of Leeds, Leeds, UK
| | - Lei Xia
- School of Food Science and Nutrition, University of Leeds, Leeds, UK
| | - Michael Routledge
- School of Food Science and Nutrition, University of Leeds, Leeds, UK
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, China
| | - Yun Yun Gong
- School of Food Science and Nutrition, University of Leeds, Leeds, UK
| | - Camilo Espinosa
- Departments of Anesthesiology, Pain, and Perioperative Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Nima Aghaeepour
- Departments of Anesthesiology, Pain, and Perioperative Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Jie Liu
- Division of Infectious Diseases and International Health, University of Virginia, Charlottesville, Virginia, USA
| | - Eric Houpt
- Division of Infectious Diseases and International Health, University of Virginia, Charlottesville, Virginia, USA
| | | | | | - Yan Shao
- Wellcome Sanger Institute, Hinxton, UK
| | - Doreen Rwigi
- The Centre for Microbiology Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - Kevin Kariuki
- The Centre for Microbiology Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - Timothy Kaburu
- The Centre for Microbiology Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - Holm H. Uhlig
- Translational Gastroenterology Unit, John Radcliffe Hospital, University of Oxford, Oxford, UK
- Department of Paediatrics and Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Lisa Gartner
- Translational Gastroenterology Unit, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Kelsey Jones
- Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK
- Gastroenterology Department, Great Ormond Street Hospital for Children, London, UK
| | - Albert Koulman
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
- NIHR BRC Nutritional Biomarker Laboratory, University of Cambridge, Cambridge, UK
| | - Judd Walson
- Global Health and Epidemiology, University of Washington, Seattle, Seattle, USA
| | - James Berkley
- The Childhood Acute Illness and Nutrition Network, Nairobi, Kenya
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
- Center for Tropical Medicine and Global Health, University of Oxford, Oxford, UK
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Wang Y, Feng S. A prediction model for 30-day mortality of sepsis patients based on intravenous fluids and electrolytes. Medicine (Baltimore) 2022; 101:e30578. [PMID: 36181047 PMCID: PMC9524964 DOI: 10.1097/md.0000000000030578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
To establish a prediction model for the 30-day mortality in sepsis patients. The data of 1185 sepsis patients were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) and all participants were randomly divided into the training set (n = 829) and the testing set (n = 356). The model was established in the training set and verified in the testing set. After standardization of the data, age, gender, input, output, and variables with statistical difference between the survival group and the death group in the training set were involved in the extreme gradient boosting (XGBoost) model. Subgroup analysis was performed concerning age and gender in the testing set. In the XGBoost model with variables related to intravenous (IV) fluid management and electrolytes for the 30-day mortality of sepsis patients, the area under the curve (AUC) was 0.868 (95% confidence interval [CI]: 0.867-0.869) in the training set and 0.781 (95% CI: 0.779-0.782) in the testing set. The sensitivity was 0.815 (95% CI: 0.774-0.857) in the training set and 0.755 (95% CI: 0.686-0.825) in the testing set. The specificity was 0.761 (95% CI: 0.723-0.798) in the training set, and 0.737 (95% CI: 0.677-0.797) in the testing set. In the XGBoost forest model without variables related to IV fluid management and electrolytes for the 30-day mortality of sepsis patients, in the training set, the AUC was 0.830 (95% CI: 0.829-0.831), the sensitivity was 0.717 (95% CI: 0.669-0.765), the specificity was 0.797 (95% CI: 0.762-0.833), and the accuracy was 0.765 (95% CI: 0.736-0.794). In the testing set, the AUC was 0.751 (95% CI: 0.750-0.753), the sensitivity was 0.612 (95% CI: 0.533-0.691), the specificity was 0.756 (95% CI: 0.698-0.814), and the accuracy was 0.697(95% CI: 0.649-0.744). The prediction model including variables associated with IV fluids and electrolytes had good predictive value for the 30-day mortality of sepsis patients.
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Affiliation(s)
- Yan Wang
- Department of Critical Care Medicine, The Second Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Songqiao Feng
- Department of Critical Care Medicine, The Second Affiliated Hospital of Dalian Medical University, Dalian, China
- *Correspondence: Songqiao Feng, Department of Critical Care Medicine, The Second Affiliated Hospital of Dalian Medical University, Dalian 116023, China (e-mail: )
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29
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Li K, Tong HHY, Chen Y, Sun Y, Wang J. The emerging roles of next-generation metabolomics in critical care nutrition. Crit Rev Food Sci Nutr 2022; 64:1213-1224. [PMID: 36004623 DOI: 10.1080/10408398.2022.2113761] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Critical illness leads to millions of deaths worldwide each year, with a significant surge due to the COVID-19 pandemic. Patients with critical illness are frequently associated with systemic metabolic disorders and malnutrition. The idea of intervention for critically ill patients through enteral and parenteral nutrition has been paid more and more attention gradually. However, current nutritional therapies focus on evidence-based practice, and there have been lacking holistic approaches for nutritional support assessment. Metabolomics is a well-established omics technique in system biology that enables comprehensive profiling of metabolites in a biological system and thus provides the underlying information expressed and modulated by all other omics layers. In recent years, with the development of high-resolution and accurate mass spectrometry, metabolomics entered a new "generation", promoting its broader applications in critical care nutrition. In this review, we first described the technological development and milestones of next-generation metabolomics in the past 20 years. We then discussed the emerging roles of next-generation metabolomics in advancing our understanding of critical care nutrition, such as nutritional deficiency risk evaluation, metabolic mechanisms of nutritional therapies, and novel nutrition target identification.
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Affiliation(s)
- Kefeng Li
- Department of Critical Care Medicine, Yantai Yuhuangding Hospital Affiliated with Medical College of Qingdao University, Yantai, Shandong, China
- Faculty of Health Sciences and Sports, Macao Polytechnic University, Macao SAR, China
- School of Medicine, University of California, San Diego, California, USA
| | - Henry Hoi Yee Tong
- Faculty of Health Sciences and Sports, Macao Polytechnic University, Macao SAR, China
| | - Yuwei Chen
- The Second Clinical Medical College, Binzhou Medical University, Binzhou, Shandong, China
| | - Yizhu Sun
- Department of Critical Care Medicine, Yantai Yuhuangding Hospital Affiliated with Medical College of Qingdao University, Yantai, Shandong, China
| | - Jing Wang
- Department of Critical Care Medicine, Yantai Yuhuangding Hospital Affiliated with Medical College of Qingdao University, Yantai, Shandong, China
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30
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Njunge JM, Tickell K, Diallo AH, Sayeem Bin Shahid ASM, Gazi MA, Saleem A, Kazi Z, Ali S, Tigoi C, Mupere E, Lancioni CL, Yoshioka E, Chisti MJ, Mburu M, Ngari M, Ngao N, Gichuki B, Omer E, Gumbi W, Singa B, Bandsma R, Ahmed T, Voskuijl W, Williams TN, Macharia A, Makale J, Mitchel A, Williams J, Gogain J, Janjic N, Mandal R, Wishart DS, Wu H, Xia L, Routledge M, Gong YY, Espinosa C, Aghaeepour N, Liu J, Houpt E, Lawley TD, Browne H, Shao Y, Rwigi D, Kariuki K, Kaburu T, Uhlig HH, Gartner L, Jones K, Koulman A, Walson J, Berkley J. The Childhood Acute Illness and Nutrition (CHAIN) network nested case-cohort study protocol: a multi-omics approach to understanding mortality among children in sub-Saharan Africa and South Asia. Gates Open Res 2022; 6:77. [PMID: 36415883 PMCID: PMC9646488 DOI: 10.12688/gatesopenres.13635.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/01/2022] [Indexed: 02/15/2024] Open
Abstract
Introduction: Many acutely ill children in low- and middle-income settings have a high risk of mortality both during and after hospitalisation despite guideline-based care. Understanding the biological mechanisms underpinning mortality may suggest optimal pathways to target for interventions to further reduce mortality. The Childhood Acute Illness and Nutrition (CHAIN) Network ( www.chainnnetwork.org) Nested Case-Cohort Study (CNCC) aims to investigate biological mechanisms leading to inpatient and post-discharge mortality through an integrated multi-omic approach. Methods and analysis; The CNCC comprises a subset of participants from the CHAIN cohort (1278/3101 hospitalised participants, including 350 children who died and 658 survivors, and 270/1140 well community children of similar age and household location) from nine sites in six countries across sub-Saharan Africa and South Asia. Systemic proteome, metabolome, lipidome, lipopolysaccharides, haemoglobin variants, toxins, pathogens, intestinal microbiome and biomarkers of enteropathy will be determined. Computational systems biology analysis will include machine learning and multivariate predictive modelling with stacked generalization approaches accounting for the different characteristics of each biological modality. This systems approach is anticipated to yield mechanistic insights, show interactions and behaviours of the components of biological entities, and help develop interventions to reduce mortality among acutely ill children. Ethics and dissemination. The CHAIN Network cohort and CNCC was approved by institutional review boards of all partner sites. Results will be published in open access, peer reviewed scientific journals and presented to academic and policy stakeholders. Data will be made publicly available, including uploading to recognised omics databases. Trial registration NCT03208725.
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Affiliation(s)
- James M. Njunge
- The Childhood Acute Illness and Nutrition Network, Nairobi, Kenya
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Kirkby Tickell
- Global Health and Epidemiology, University of Washington, Seattle, Seattle, USA
| | - Abdoulaye Hama Diallo
- Department of Public Health, Faculty of Health Sciences, University of Ouagadougou, Ouagadougou, Burkina Faso
| | | | - Md. Amran Gazi
- Nutrition and Clinical Services Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | - Ali Saleem
- Department of Pediatrics and Child Health, Aga Khan University Hospital, Karachi, Karachi, Pakistan
| | - Zaubina Kazi
- Department of Pediatrics and Child Health, Aga Khan University Hospital, Karachi, Karachi, Pakistan
| | - Syed Ali
- Department of Pediatrics and Child Health, Aga Khan University Hospital, Karachi, Karachi, Pakistan
| | - Caroline Tigoi
- The Childhood Acute Illness and Nutrition Network, Nairobi, Kenya
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Ezekiel Mupere
- Department of Paediatrics and Child Health, College of Health Sciences, Makerere University, Kampala, Uganda
| | | | - Emily Yoshioka
- Global Health and Epidemiology, University of Washington, Seattle, Seattle, USA
| | - Mohammod Jobayer Chisti
- Nutrition and Clinical Services Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | - Moses Mburu
- The Childhood Acute Illness and Nutrition Network, Nairobi, Kenya
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Moses Ngari
- The Childhood Acute Illness and Nutrition Network, Nairobi, Kenya
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Narshion Ngao
- The Childhood Acute Illness and Nutrition Network, Nairobi, Kenya
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Bonface Gichuki
- The Childhood Acute Illness and Nutrition Network, Nairobi, Kenya
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Elisha Omer
- The Childhood Acute Illness and Nutrition Network, Nairobi, Kenya
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Wilson Gumbi
- The Childhood Acute Illness and Nutrition Network, Nairobi, Kenya
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Benson Singa
- Kenya Medical Research Institute, Nairobi, Kenya
| | - Robert Bandsma
- Centre for Global Child Health, The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Biomedical Sciences, University of Malawi College of Medicine, Blantyre, Malawi
| | - Tahmeed Ahmed
- Nutrition and Clinical Services Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | - Wieger Voskuijl
- Amsterdam UMC location, University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Centre for Global Child Health & Emma Children’s Hospital, Amsterdam, The Netherlands
| | - Thomas N. Williams
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
- Institute of Global Health Innovation, Department of Surgery and Cancer, Imperial College London, London, UK
| | - Alex Macharia
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | | | | | | | | | | | - Rupasri Mandal
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - David S. Wishart
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - Hang Wu
- School of Food Science and Nutrition, University of Leeds, Leeds, UK
| | - Lei Xia
- School of Food Science and Nutrition, University of Leeds, Leeds, UK
| | - Michael Routledge
- School of Food Science and Nutrition, University of Leeds, Leeds, UK
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, China
| | - Yun Yun Gong
- School of Food Science and Nutrition, University of Leeds, Leeds, UK
| | - Camilo Espinosa
- Departments of Anesthesiology, Pain, and Perioperative Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Nima Aghaeepour
- Departments of Anesthesiology, Pain, and Perioperative Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Jie Liu
- Division of Infectious Diseases and International Health, University of Virginia, Charlottesville, Virginia, USA
| | - Eric Houpt
- Division of Infectious Diseases and International Health, University of Virginia, Charlottesville, Virginia, USA
| | | | | | - Yan Shao
- Wellcome Sanger Institute, Hinxton, UK
| | - Doreen Rwigi
- The Centre for Microbiology Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - Kevin Kariuki
- The Centre for Microbiology Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - Timothy Kaburu
- The Centre for Microbiology Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - Holm H. Uhlig
- Translational Gastroenterology Unit, John Radcliffe Hospital, University of Oxford, Oxford, UK
- Department of Paediatrics and Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Lisa Gartner
- Translational Gastroenterology Unit, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Kelsey Jones
- Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK
- Gastroenterology Department, Great Ormond Street Hospital for Children, London, UK
| | - Albert Koulman
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
- NIHR BRC Nutritional Biomarker Laboratory, University of Cambridge, Cambridge, UK
| | - Judd Walson
- Global Health and Epidemiology, University of Washington, Seattle, Seattle, USA
| | - James Berkley
- The Childhood Acute Illness and Nutrition Network, Nairobi, Kenya
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
- Center for Tropical Medicine and Global Health, University of Oxford, Oxford, UK
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31
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Pang LX, Cai WW, Chen L, Fu J, Xia CX, Li JY, Li Q. The Diagnostic Value of Mitochondrial Mass of Peripheral T Lymphocytes in Early Sepsis. Front Public Health 2022; 10:928306. [PMID: 35910903 PMCID: PMC9330378 DOI: 10.3389/fpubh.2022.928306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 06/15/2022] [Indexed: 11/13/2022] Open
Abstract
Background Studies have shown that lymphocyte dysfunction can occur during the early stages of sepsis and that cell dysfunction is associated with mitochondrial dysfunction. Therefore, quantifying the mitochondrial function of lymphocytes in patients with sepsis could be valuable for the early diagnosis of sepsis. Methods Seventy-nine patients hospitalized from September 2020 to September 2021 with Sepsis-3 were retrospectively analyzed and subsequently compared with those without sepsis. Results Univariate analysis showed statistical differences between the data of the two groups regarding age, neutrophil/lymphocyte, procalcitonin (PCT), C-reactive protein, total bilirubin, serum creatinine, type B natriuretic peptide, albumin, prothrombin time, activated partial thromboplastin time, lactic acid, single-cell mitochondrial mass (SCMM)-CD3, SCMM-CD4, SCMM-CD8, and Acute Physiology and Chronic Health Evaluation II score (P < 0.05). Multivariate logistic regression analysis performed on the indicators mentioned above demonstrated a statistical difference in PCT, lactic acid, SCMM-CD4, and SCMM-CD8 levels between the two groups (P < 0.05). The receiver operating characteristic curves of five models were subsequently compared [area under the curve: 0.740 (PCT) vs. 0.933 (SCMM-CD4) vs. 0.881 (SCMM-CD8) vs. 0.961 (PCT + SCMM-CD4) vs. 0.915 (PCT+SCMM-CD8), P < 0.001]. Conclusion SCMM-CD4 was shown to be a better diagnostic biomarker of early sepsis when compared with the traditional biomarker, PCT. Furthermore, the value of the combination of PCT and SCMM-CD4 in the diagnosis of early sepsis was better than that of SCMM-CD4 alone.
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Affiliation(s)
- Ling-Xiao Pang
- Emergency and Critical Care Center, Department of Emergency Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, China
| | - Wen-Wei Cai
- Emergency and Critical Care Center, Department of Emergency Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, China
| | - Lue Chen
- Emergency and Critical Care Center, Department of Emergency Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, China
| | - Jin Fu
- Graduate School of Clinical Medicine, Bengbu Medical College, Bengbu, China
| | - Chun-Xiao Xia
- Zhejiang Chinese Medical University, Hangzhou, China
| | - Jia-Yan Li
- Zhejiang Chinese Medical University, Hangzhou, China
| | - Qian Li
- Emergency and Critical Care Center, Department of Emergency Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, China
- *Correspondence: Qian Li
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32
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Zhang J, Luo W, Miao C, Zhong J. Hypercatabolism and Anti-catabolic Therapies in the Persistent Inflammation, Immunosuppression, and Catabolism Syndrome. Front Nutr 2022; 9:941097. [PMID: 35911117 PMCID: PMC9326442 DOI: 10.3389/fnut.2022.941097] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 06/21/2022] [Indexed: 12/06/2022] Open
Abstract
Owing to the development of intensive care units, many patients survive their initial insults but progress to chronic critical illness (CCI). Patients with CCI are characterized by prolonged hospitalization, poor outcomes, and significant long-term mortality. Some of these patients get into a state of persistent low-grade inflammation, suppressed immunity, and ongoing catabolism, which was defined as persistent inflammation, immunosuppression, and catabolism syndrome (PICS) in 2012. Over the past few years, some progress has been made in the treatment of PICS. However, most of the existing studies are about the role of persistent inflammation and suppressed immunity in PICS. As one of the hallmarks of PICS, hypercatabolism has received little research attention. In this review, we explore the potential pathophysiological changes and molecular mechanisms of hypercatabolism and its role in PICS. In addition, we summarize current therapies for improving the hypercatabolic status and recommendations for patients with PICS.
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Affiliation(s)
- Jinlin Zhang
- Department of Anesthesiology, Zhongshan Hospital Fudan University, Shanghai, China
| | - Wenchen Luo
- Department of Anesthesiology, Zhongshan Hospital Fudan University, Shanghai, China
| | - Changhong Miao
- Department of Anesthesiology, Zhongshan Hospital Fudan University, Shanghai, China
| | - Jing Zhong
- Department of Anesthesiology, Zhongshan Hospital Fudan University, Shanghai, China
- Fudan Zhangjiang Institute, Shanghai, China
- Department of Anesthesiology, Zhongshan Wusong Hospital, Fudan University, Shanghai, China
- Shanghai Key Laboratory of Perioperative Stress and Protection, Shanghai, China
- *Correspondence: Jing Zhong,
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33
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Fibroblast Growth Factor 19 Improves LPS-Induced Lipid Disorder and Organ Injury by Regulating Metabolomic Characteristics in Mice. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2022; 2022:9673512. [PMID: 35847588 PMCID: PMC9279090 DOI: 10.1155/2022/9673512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 05/31/2022] [Accepted: 06/07/2022] [Indexed: 11/17/2022]
Abstract
Sepsis is extremely heterogeneous pathology characterized by complex metabolic changes. Fibroblast growth factor 19 (FGF19) is a well-known intestine-derived inhibitor of bile acid biosynthesis. However, it is largely unknown about the roles of FGF19 in improving sepsis-associated metabolic disorder and organ injury. In the present study, mice were intravenously injected recombinant human FGF19 daily for 7 days followed by lipopolysaccharide (LPS) administration. At 24 hours after LPS stimuli, sera were collected for metabolomic analysis. Ingenuity pathway analysis (IPA) network based on differential metabolites (DMs) was conducted. Here, metabolomic analysis revealed that FGF19 pretreatment reversed the increase of LPS-induced fatty acids. IPA network indicated that altered linoleic acid (LA) and gamma-linolenic acid (GLA) were involved in the regulation of oxidative stress and mitochondrial function and were closely related to reactive oxygen species (ROS) generation. Further investigation proved that FGF19 pretreatment decreased serum malondialdehyde (MDA) levels and increased serum catalase (CAT) levels. In livers, FGF19 suppressed the expression of inducible NO synthase (iNOS) and enhanced the expression of nuclear factor erythroid 2-related factor 2 (NRF2) and hemeoxygenase-1 (HO-1). Finally, FGF19 pretreatment protected mice against LPS-induced liver, ileum, and kidney injury. Taken together, FGF19 alleviates LPS-induced organ injury associated with improved serum LA and GLA levels and oxidative stress, suggesting that FGF19 might be a promising target for metabolic therapy for sepsis.
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Severe COVID-19 Is Characterised by Perturbations in Plasma Amines Correlated with Immune Response Markers, and Linked to Inflammation and Oxidative Stress. Metabolites 2022; 12:metabo12070618. [PMID: 35888742 PMCID: PMC9321395 DOI: 10.3390/metabo12070618] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 06/25/2022] [Accepted: 06/26/2022] [Indexed: 02/01/2023] Open
Abstract
The COVID-19 pandemic raised a need to characterise the biochemical response to SARS-CoV-2 infection and find biological markers to identify therapeutic targets. In support of these aims, we applied a range of LC-MS platforms to analyse over 100 plasma samples from patients with varying COVID-19 severity and with detailed clinical information on inflammatory responses (>30 immune markers). The first publication in a series reports the results of quantitative LC-MS/MS profiling of 56 amino acids and derivatives. A comparison between samples taken from ICU and ward patients revealed a notable increase in ten post-translationally modified amino acids that correlated with markers indicative of an excessive immune response: TNF-alpha, neutrophils, markers for macrophage, and leukocyte activation. Severe patients also had increased kynurenine, positively correlated with CRP and cytokines that induce its production. ICU and ward patients with high IL-6 showed decreased levels of 22 immune-supporting and anti-oxidative amino acids and derivatives (e.g., glutathione, GABA). These negatively correlated with CRP and IL-6 and positively correlated with markers indicative of adaptive immune activation. Including corresponding alterations in convalescing ward patients, the overall metabolic picture of severe COVID-19 reflected enhanced metabolic demands to maintain cell proliferation and redox balance, alongside increased inflammation and oxidative stress.
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Han X, Wang J, Gu H, Guo H, Cai Y, Liao X, Jiang M. Predictive value of serum bile acids as metabolite biomarkers for liver cirrhosis: a systematic review and meta-analysis. Metabolomics 2022; 18:43. [PMID: 35759044 DOI: 10.1007/s11306-022-01890-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 04/19/2022] [Indexed: 12/01/2022]
Abstract
INTRODUCTION A large number of studies have explored the potential biomarkers for detecting liver cirrhosis in an early stage, yet consistent conclusions are still warranted. OBJECTIVES To conduct a review and a meta-analysis of the existing studies that test the serum level of bile acids in cirrhosis as the potential biomarkers to predict cirrhosis. METHODS Six databases had been searched from inception date to April 12, 2021. Screening and selection of the records were based on the inclusion criteria. The risk of bias was assessed with the Newcastle-Ottawa quality assessment scale (NOS). Mean difference (MD) and confidence intervals 95% (95% CI) were calculated by using the random effect model for the concentrations of bile acids in the meta-analysis, and I2 statistic was used to measure studies heterogeneity. This study was registered on PROSPERO. RESULTS A total of 1583 records were identified and 31 studies with 2679 participants (1263 in the cirrhosis group, 1416 in the healthy control group) were included. The quality of included studies was generally high, with 25 studies (80.6%) rated over 7 stars. A total of 45 bile acids or their ratios in included studies were extracted. 36 increased in the cirrhosis group compared with those of the healthy controls by a qualitative summary, 5 decreased and 4 presented with mixing results. The result of meta-analysis among 12 studies showed that 13 bile acids increased, among which four primary conjugated bile acids showed the most significant elevation in the cirrhosis group: GCDCA (MD = 11.38 μmol/L, 95% CI 8.21-14.55, P < 0.0001), GCA (MD = 5.72 μmol/L, 95% CI 3.47-7.97, P < 0.0001), TCDCA (MD = 3.57 μmol/L, 95% CI 2.64-4.49, P < 0.0001) and TCA (MD = 2.14 μmol/L, 95% CI 1.56-2.72, P < 0.0001). No significant differences were found between the two groups in terms of DCA (MD = - 0.1 μmol/L, 95% CI - 0.18 to - 0.01, P < 0.0001) and LCA (MD = - 0.01 μmol/L, 95% CI - 0.01 to - 0.02, P < 0.0001), UDCA (MD = - 0.14 μmol/L, 95% CI - 0.04 to - 0.32, P < 0.0001), and TLCA (MD = 0 μmol/L, 95% CI 0-0.01, P < 0.0001). Subgroup analysis in patients with hepatitis B cirrhosis showed similar results. CONCLUSION Altered serum bile acids profile seems to be associated with cirrhosis. Some specific bile acids (GCA, GCDCA, TCA, and TCDCA) may increase with the development of cirrhosis, which possibly underlay their potential role as predictive biomarkers for cirrhosis. Yet this predictive value still needs further investigation and validation in larger prospective cohort studies.
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Affiliation(s)
- Xu Han
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, No. 16 Nanxiaojie, Dongzhimennei, Beijing, 100700, China
| | - Juan Wang
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, No. 16 Nanxiaojie, Dongzhimennei, Beijing, 100700, China
| | - Hao Gu
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, No. 16 Nanxiaojie, Dongzhimennei, Beijing, 100700, China
| | - Hongtao Guo
- Department of Rheumatology and Immunology, The First Affiliated Hospital of Henan University of CM, Zhengzhou, China
| | - Yili Cai
- Ningbo First Hospital, Ningbo, China
| | - Xing Liao
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, No. 16 Nanxiaojie, Dongzhimennei, Beijing, 100700, China.
| | - Miao Jiang
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, No. 16 Nanxiaojie, Dongzhimennei, Beijing, 100700, China.
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Hussain H, Vutipongsatorn K, Jiménez B, Antcliffe DB. Patient Stratification in Sepsis: Using Metabolomics to Detect Clinical Phenotypes, Sub-Phenotypes and Therapeutic Response. Metabolites 2022; 12:metabo12050376. [PMID: 35629881 PMCID: PMC9145582 DOI: 10.3390/metabo12050376] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Revised: 04/01/2022] [Accepted: 04/12/2022] [Indexed: 11/16/2022] Open
Abstract
Infections are common and need minimal treatment; however, occasionally, due to inappropriate immune response, they can develop into a life-threatening condition known as sepsis. Sepsis is a global concern with high morbidity and mortality. There has been little advancement in the treatment of sepsis, outside of antibiotics and supportive measures. Some of the difficulty in identifying novel therapies is the heterogeneity of the condition. Metabolic phenotyping has great potential for gaining understanding of this heterogeneity and how the metabolic fingerprints of patients with sepsis differ based on survival, organ dysfunction, disease severity, type of infection, treatment or causative organism. Moreover, metabolomics offers potential for patient stratification as metabolic profiles obtained from analytical platforms can reflect human individuality and phenotypic variation. This article reviews the most relevant metabolomic studies in sepsis and aims to provide an overview of the metabolic derangements in sepsis and how metabolic phenotyping has been used to identify sub-groups of patients with this condition. Finally, we consider the new avenues that metabolomics could open, exploring novel phenotypes and untangling the heterogeneity of sepsis, by looking at advances made in the field with other -omics technologies.
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Affiliation(s)
- Humma Hussain
- Division of Anaesthetics, Pain Medicine and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK; (H.H.); (K.V.)
| | - Kritchai Vutipongsatorn
- Division of Anaesthetics, Pain Medicine and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK; (H.H.); (K.V.)
| | - Beatriz Jiménez
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, UK;
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, UK
| | - David B. Antcliffe
- Division of Anaesthetics, Pain Medicine and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK; (H.H.); (K.V.)
- Correspondence:
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Pathak E, Atri N, Mishra R. Single-Cell Transcriptome Analysis Reveals the Role of Pancreatic Secretome in COVID-19 Associated Multi-organ Dysfunctions. Interdiscip Sci 2022; 14:863-878. [PMID: 35394619 PMCID: PMC8990272 DOI: 10.1007/s12539-022-00513-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 03/16/2022] [Accepted: 03/17/2022] [Indexed: 01/09/2023]
Abstract
The SARS-CoV-2 infection affects the lungs, heart, kidney, intestine, olfactory epithelia, liver, and pancreas and brings forward multi-organ dysfunctions (MODs). However, mechanistic details of SARS-CoV-2-induced MODs are unclear. Here, we have investigated the role of pancreatic secretory proteins to mechanistically link COVID-19 with MODs using single-cell transcriptome analysis. Secretory proteins were identified using the Human Protein Atlas. Gene ontology, pathway, and disease enrichment analyses were used to highlight the role of upregulated pancreatic secretory proteins (secretome). We show that SARS-CoV-2 infection shifts the expression profile of pancreatic endocrine cells to acinar and ductal cell-specific profiles, resulting in increased expression of acinar and ductal cell-specific genes. Among all the secretory proteins, the upregulated expression of IL1B, AGT, ALB, SPP1, CRP, SERPINA1, C3, TFRC, TNFSF10, and MIF was mainly associated with disease of diverse organs. Extensive literature and experimental evidence are used to validate the association of the upregulated pancreatic secretome with the coagulation cascade, complement activation, renin-angiotensinogen system dysregulation, endothelial cell injury and thrombosis, immune system dysregulation, and fibrosis. Our finding suggests the influence of an upregulated secretome on multi-organ systems such as nervous, cardiovascular, immune, digestive, and urogenital systems. Our study provides evidence that an upregulated pancreatic secretome is a possible cause of SARS-CoV-2-induced MODs. This finding may have a significant impact on the clinical setting regarding the prevention of SARS-CoV-2-induced MODs.
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Affiliation(s)
- Ekta Pathak
- Banaras Hindu University, Varanasi, Uttar Pradesh, 221005, India.
| | - Neelam Atri
- Bioinformatics Department, MMV, Institute of Science, Banaras Hindu University, Varanasi, 221005, India
- Department of Botany, MMV, Institute of Science, Banaras Hindu University, Varanasi, 221005, India
| | - Rajeev Mishra
- Bioinformatics Department, MMV, Institute of Science, Banaras Hindu University, Varanasi, 221005, India.
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Vandewalle J, Libert C. Sepsis: a failing starvation response. Trends Endocrinol Metab 2022; 33:292-304. [PMID: 35181202 DOI: 10.1016/j.tem.2022.01.006] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 01/12/2022] [Accepted: 01/18/2022] [Indexed: 12/22/2022]
Abstract
Sepsis is involved in ~ 20% of annual global deaths. Despite decades of research, the current management of sepsis remains supportive rather than curative. Clinical trials in sepsis have mainly been focused on targeting the inflammatory pathway, but without success. Recent data indicate that metabolic dysregulation takes place in sepsis, and targeting metabolic pathways might hold much promise for the management of sepsis. Sepsis yields a strong starvation response, including the release of high-energy metabolites such as lactate and free fatty acids. However, the activity of two major transcription factors, GR and PPARα, is downregulated in hepatocytes, leading to the accumulation and toxicity of metabolites that, moreover, fail to be transformed into useful molecules such as glucose and ketones. We review the literature and suggest mechanisms and potential therapeutic targets that might prevent or revert the fatal metabolic dysregulation in sepsis.
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Affiliation(s)
- Jolien Vandewalle
- Center for Inflammation Research, Vlaams Instituut voor Biotechnologie (VIB), Ghent, Belgium; Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
| | - Claude Libert
- Center for Inflammation Research, Vlaams Instituut voor Biotechnologie (VIB), Ghent, Belgium; Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium.
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Wen B, Njunge JM, Bourdon C, Gonzales GB, Gichuki BM, Lee D, Wishart DS, Ngari M, Chimwezi E, Thitiri J, Mwalekwa L, Voskuijl W, Berkley JA, Bandsma RHJ. Systemic inflammation and metabolic disturbances underlie inpatient mortality among ill children with severe malnutrition. SCIENCE ADVANCES 2022; 8:eabj6779. [PMID: 35171682 PMCID: PMC8849276 DOI: 10.1126/sciadv.abj6779] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 12/23/2021] [Indexed: 06/14/2023]
Abstract
Children admitted to hospital with an acute illness and concurrent severe malnutrition [complicated severe malnutrition (CSM)] have a high risk of dying. The biological processes underlying their mortality are poorly understood. In this case-control study nested within a multicenter randomized controlled trial among children with CSM in Kenya and Malawi, we found that blood metabolomic and proteomic profiles robustly differentiated children who died (n = 92) from those who survived (n = 92). Fatalities were characterized by increased energetic substrates (tricarboxylic acid cycle metabolites), microbial metabolites (e.g., propionate and isobutyrate), acute phase proteins (e.g., calprotectin and C-reactive protein), and inflammatory markers (e.g., interleukin-8 and tumor necrosis factor-α). These perturbations indicated disruptions in mitochondria-related bioenergetic pathways and sepsis-like responses. This study identified specific biomolecular disturbances associated with CSM mortality, revealing that systemic inflammation and bioenergetic deficits are targetable pathophysiological processes for improving survival of this vulnerable population.
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Affiliation(s)
- Bijun Wen
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Canada
- Department of Translational medicine, Hospital for Sick Children, Toronto, Canada
| | - James M. Njunge
- The Childhood Acute Illness & Nutrition Network, Nairobi, Kenya
- KEMRI/Wellcome Trust Research Programme, Kilifi, Kenya
| | - Celine Bourdon
- Department of Translational medicine, Hospital for Sick Children, Toronto, Canada
- The Childhood Acute Illness & Nutrition Network, Nairobi, Kenya
| | - Gerard Bryan Gonzales
- Nutrition, Metabolism and Genomics Group, Division of Human Nutrition and Health, Wageningen University & Research, Wageningen, Netherlands
| | - Bonface M. Gichuki
- The Childhood Acute Illness & Nutrition Network, Nairobi, Kenya
- KEMRI/Wellcome Trust Research Programme, Kilifi, Kenya
| | - Dorothy Lee
- Department of Translational medicine, Hospital for Sick Children, Toronto, Canada
| | | | - Moses Ngari
- The Childhood Acute Illness & Nutrition Network, Nairobi, Kenya
- KEMRI/Wellcome Trust Research Programme, Kilifi, Kenya
| | | | - Johnstone Thitiri
- The Childhood Acute Illness & Nutrition Network, Nairobi, Kenya
- KEMRI/Wellcome Trust Research Programme, Kilifi, Kenya
| | - Laura Mwalekwa
- KEMRI/Wellcome Trust Research Programme, Kilifi, Kenya
- Department of Paediatrics, Coast General Hospital, Mombasa, Kenya
| | - Wieger Voskuijl
- The Childhood Acute Illness & Nutrition Network, Nairobi, Kenya
- Department of Global Health, Amsterdam Institute for Global Health and Development, Amsterdam University Medical Centres, Amsterdam, Netherlands
- Department of Pediatrics, the College of Medicine, University of Malawi, Blantyre, Malawi
| | - James A. Berkley
- The Childhood Acute Illness & Nutrition Network, Nairobi, Kenya
- KEMRI/Wellcome Trust Research Programme, Kilifi, Kenya
- Centre for Tropical Medicine & Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Robert HJ Bandsma
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Canada
- Department of Translational medicine, Hospital for Sick Children, Toronto, Canada
- The Childhood Acute Illness & Nutrition Network, Nairobi, Kenya
- Department of Pediatrics, the College of Medicine, University of Malawi, Blantyre, Malawi
- Department of Biomedical Sciences, the College of Medicine, University of Malawi, Blantyre, Malawi
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Jia H, Liu C, Li D, Huang Q, Liu D, Zhang Y, Ye C, Zhou D, Wang Y, Tan Y, Li K, Lin F, Zhang H, Lin J, Xu Y, Liu J, Zeng Q, Hong J, Chen G, Zhang H, Zheng L, Deng X, Ke C, Gao Y, Fan J, Di B, Liang H. Metabolomic analyses reveal new stage-specific features of COVID-19. Eur Respir J 2022; 59:2100284. [PMID: 34289974 PMCID: PMC8311281 DOI: 10.1183/13993003.00284-2021] [Citation(s) in RCA: 53] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Accepted: 06/28/2021] [Indexed: 01/10/2023]
Abstract
The current pandemic of coronavirus disease 2019 (COVID-19) has affected >160 million individuals to date, and has caused millions of deaths worldwide, at least in part due to the unclarified pathophysiology of this disease. Identifying the underlying molecular mechanisms of COVID-19 is critical to overcome this pandemic. Metabolites mirror the disease progression of an individual and can provide extensive insights into their pathophysiological significance at each stage of disease. We provide a comprehensive view of metabolic characterisation of sera from COVID-19 patients at all stages using untargeted and targeted metabolomic analysis. As compared with the healthy controls, we observed different alteration patterns of circulating metabolites from the mild, severe and recovery stages, in both the discovery cohort and the validation cohort, which suggests that metabolic reprogramming of glucose metabolism and the urea cycle are potential pathological mechanisms for COVID-19 progression. Our findings suggest that targeting glucose metabolism and the urea cycle may be a viable approach to fight COVID-19 at various stages along the disease course.
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Affiliation(s)
- Hongling Jia
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
- Dept of Medical Biochemistry and Molecular Biology, School of Medicine, Jinan University, Guangzhou, China
- These authors contributed equally to this study
| | - Chaowu Liu
- Guangdong Institute of Microbiology, Guangdong Academy of Sciences, State Key Laboratory of Applied Microbiology Southern China, Guangzhou, China
- These authors contributed equally to this study
| | - Dantong Li
- Clinical Data Center, Guangdong Provincial People's Hospital/Guangdong Academy of Medical Sciences, Guangzhou, China
- These authors contributed equally to this study
| | - Qingsheng Huang
- Clinical Data Center, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- These authors contributed equally to this study
| | - Dong Liu
- Big Data and Machine Learning Laboratory, Chongqing University of Technology, Chongqing, China
- These authors contributed equally to this study
| | - Ying Zhang
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
- These authors contributed equally to this study
| | - Chang Ye
- Clinical Data Center, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Di Zhou
- Metabo-Profile Biotechnology (Shanghai) Co. Ltd, Shanghai, China
| | - Yang Wang
- Metabo-Profile Biotechnology (Shanghai) Co. Ltd, Shanghai, China
| | - Yanlian Tan
- Dept of Medical Biochemistry and Molecular Biology, School of Medicine, Jinan University, Guangzhou, China
| | - Kuibiao Li
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Fangqin Lin
- Clinical Data Center, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Haiqing Zhang
- Dept of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jingchao Lin
- Metabo-Profile Biotechnology (Shanghai) Co. Ltd, Shanghai, China
| | - Yang Xu
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Jingwen Liu
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Qing Zeng
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Jian Hong
- Dept of Pathophysiology, School of Medicine, Jinan University, Guangzhou, China
| | - Guobing Chen
- Institute of Geriatric Immunology, Dept of Microbiology and Immunology, School of Medicine, Dept of Neurology, Affiliated Huaqiao Hospital, Jinan University, Guangzhou, China
| | - Hao Zhang
- Institute of Precision Cancer Medicine and Pathology, School of Medicine, Jinan University, Guangzhou, China
| | - Lingling Zheng
- Clinical Data Center, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Xilong Deng
- Institute of Infectious Diseases, Guangzhou Eighth People's Hospital, Guangzhou, China
| | - Changwen Ke
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Yunfei Gao
- Zhuhai Precision Medical Center, Zhuhai People's Hospital (Zhuhai Hospital Affiliated with Jinan University), Jinan University, Zhuhai, China
- The Biomedical Translational Research Institute, Jinan University Faculty of Medical Science, Jinan University, Guangzhou, China
- Yunfei Gao, Jun Fan, Biao Di and Huiying Liang are joint lead authors
| | - Jun Fan
- Dept of Medical Biochemistry and Molecular Biology, School of Medicine, Jinan University, Guangzhou, China
- Yunfei Gao, Jun Fan, Biao Di and Huiying Liang are joint lead authors
| | - Biao Di
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
- Yunfei Gao, Jun Fan, Biao Di and Huiying Liang are joint lead authors
| | - Huiying Liang
- Clinical Data Center, Guangdong Provincial People's Hospital/Guangdong Academy of Medical Sciences, Guangzhou, China
- Yunfei Gao, Jun Fan, Biao Di and Huiying Liang are joint lead authors
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Han X, Wang J, Gu H, Liao X, Jiang M. Predictive value of liver cirrhosis using metabolite biomarkers of bile acid in the blood: A protocol for systematic review and meta-analysis. Medicine (Baltimore) 2022; 101:e28529. [PMID: 35089190 PMCID: PMC8797474 DOI: 10.1097/md.0000000000028529] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Accepted: 12/21/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Previous studies have indicated that the changes of bile acids are associated with liver cirrhosis. The objective of our study is to perform a systematic review to explore the relationship between bile acids and the pathologic process of cirrhosis, and to find minimally invasive, accurate and reliable potential biomarkers for predicting cirrhosis. METHODS EMBASE, the Cochrane Library, PubMed, Web of Science, WanFang Data and Chinese National Knowledge Infrastructure (CNKI) will be searched, using the search strategy of liver cirrhosis, bile acids and metabolomic. The screening process will be conducted strictly based on inclusion and exclusion criteria. Clinical studies based on human including randomized controlled trial, cohort study and case control study will be included without restriction of time. Cochrane collaboration's tool for assessing risk of bias and Newcastle-Ottawa Scale (NOS) will be applied to assess the risk of bias to randomized controlled trial and observational study, respectively. The bile acids and their concentrate which are different between liver cirrhosis and control group will be the mainly outcome. A qualitative analysis will be performed to profile the trajectory change of bile acids, then the meta-analysis will be done for quantitative analysis. RESULTS The bile acids profile of liver cirrhosis that has potential predictive value for cirrhosis will be identified. CONCLUSION The conclusion of this systematic review will finding potential biomarkers for predicting cirrhosis. ETHICS AND DISSEMINATION This systematic review is based on published researches, so there is no ethical approval required. We intend to disseminate our findings in a peer-reviewed journal.
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Jennaro TS, Viglianti EM, Ingraham NE, Jones AE, Stringer KA, Puskarich MA. Serum Levels of Acylcarnitines and Amino Acids Are Associated with Liberation from Organ Support in Patients with Septic Shock. J Clin Med 2022; 11:jcm11030627. [PMID: 35160078 PMCID: PMC8836990 DOI: 10.3390/jcm11030627] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 01/12/2022] [Accepted: 01/24/2022] [Indexed: 12/23/2022] Open
Abstract
Sepsis-induced metabolic dysfunction is associated with mortality, but the signatures that differentiate variable clinical outcomes among survivors are unknown. Our aim was to determine the relationship between host metabolism and chronic critical illness (CCI) in patients with septic shock. We analyzed metabolomics data from mechanically ventilated patients with vasopressor-dependent septic shock from the placebo arm of a recently completed clinical trial. Baseline serum metabolites were measured by liquid chromatography-mass spectrometry and 1H-nuclear magnetic resonance. We conducted a time-to-event analysis censored at 28 days. Specifically, we determined the relationship between metabolites and time to extubation and freedom from vasopressors using a competing risk survival model, with death as a competing risk. We also compared metabolite concentrations between CCI patients, defined as intensive care unit level of care ≥ 14 days, and those with rapid recovery. Elevations in two acylcarnitines and four amino acids were related to the freedom from organ support (subdistributional hazard ratio < 1 and false discovery rate < 0.05). Proline, glycine, glutamine, and methionine were also elevated in patients who developed CCI. Our work highlights the need for further testing of metabolomics to identify patients at risk of CCI and to elucidate potential mechanisms that contribute to its etiology.
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Affiliation(s)
- Theodore S. Jennaro
- Department of Clinical Pharmacy and the NMR Metabolomics Laboratory, College of Pharmacy, University of Michigan, Ann Arbor, MI 48109, USA; (T.S.J.); (K.A.S.)
| | - Elizabeth M. Viglianti
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, School of Medicine, University of Michigan, Ann Arbor, MI 48109, USA;
| | - Nicholas E. Ingraham
- Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine, Department of Internal Medicine, School of Medicine, University of Minnesota, Minneapolis, MN 55455, USA;
| | - Alan E. Jones
- Department of Emergency Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA;
| | - Kathleen A. Stringer
- Department of Clinical Pharmacy and the NMR Metabolomics Laboratory, College of Pharmacy, University of Michigan, Ann Arbor, MI 48109, USA; (T.S.J.); (K.A.S.)
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, School of Medicine, University of Michigan, Ann Arbor, MI 48109, USA;
- Michigan Center for Integrative Research in Critical Care (MCIRCC), University of Michigan, Ann Arbor, MI 48109, USA
| | - Michael A. Puskarich
- Department of Emergency Medicine, School of Medicine, University of Minnesota, Minneapolis, MN 55415, USA
- Department of Emergency Medicine, Hennepin County Medical Center, Minneapolis, MN 55415, USA
- Correspondence:
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Guedes GV, Minicucci MF, Tanni SE. The supplementation of L-carnitine in septic shock patients: Systematic review and meta-analysis. Clinics (Sao Paulo) 2022; 77:100124. [PMID: 36327640 PMCID: PMC9636543 DOI: 10.1016/j.clinsp.2022.100124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 09/30/2022] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Sepsis and septic shock are severe and difficult-to-treat conditions with high lethality. There is interest in identifying new adjunct therapies that are effective in reducing mortality. In this context, L-carnitine has been investigated in trials as a potentially beneficial drug. Therefore, the aim of this systematic review was to assess the clinical evidence to support the use of L-carnitine in septic shock patients to reduce the risk of mortality. The objective of this review was to evaluate the effect of L-carnitine compared to placebo or Usual Care (UC) on the mortality rate in hospitalized adult septic shock patients. METHODS The authors exclusively included randomized clinical trials that compared the use of L-carnitine versus placebo in adult (> 18 years old) septic shock patients. The outcome was a mortality rate of 28 days. This systematic review and meta-analysis were performed following the PRISMA guidelines and registered in PROSPERO with the ID CRD42020180499. RESULTS Following the initial search, 4007 citations were identified, with 2701 remaining after duplicate removal. Eight citations were selected for body text reading, and two were selected for inclusion. The studies enrolled 275 patients, with 186 in the carnitine arm and 89 in the placebo arm. The effect of L-carnitine uses in septic shock patients showed a difference risk of -0.03 (95% Confidence Interval: -0.15-0.10, I2 = 77%, p = 0.69) compared to placebo/in mortality rate with low quality of evidence. CONCLUSIONS There is low-quality evidence that the use of L-carnitine has no significant effect on reducing 28-day mortality in septic shock patients.
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Affiliation(s)
- Gabriel Voltani Guedes
- Faculdade de Medicina de Botucatu, Universidade Estadual Paulista (UNESP), Botucatu, SP, Brazil.
| | - Marcos Ferreira Minicucci
- Internal Medicine Department, Faculdade de Medicina de Botucatu, Universidade Estadual Paulista (UNESP), Botucatu, SP, Brazil
| | - Suzana Erico Tanni
- Internal Medicine Department, Faculdade de Medicina de Botucatu, Universidade Estadual Paulista (UNESP), Botucatu, SP, Brazil
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Pike DP, McGuffee RM, Geerling E, Albert CJ, Hoft DF, Shashaty MGS, Meyer NJ, Pinto AK, Ford DA. Plasmalogen Loss in Sepsis and SARS-CoV-2 Infection. Front Cell Dev Biol 2022; 10:912880. [PMID: 35784479 PMCID: PMC9242022 DOI: 10.3389/fcell.2022.912880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 05/23/2022] [Indexed: 11/13/2022] Open
Abstract
Plasmalogens are plasma-borne antioxidant phospholipid species that provide protection as cellular lipid components during cellular oxidative stress. In this study we investigated plasma plasmalogen levels in human sepsis as well as in rodent models of infection. In humans, levels of multiple plasmenylethanolamine molecular species were decreased in septic patient plasma compared to control subject plasma as well as an age-aligned control subject cohort. Additionally, lysoplasmenylcholine levels were significantly decreased in septic patients compared to the control cohorts. In contrast, plasma diacyl phosphatidylethanolamine and phosphatidylcholine levels were elevated in septic patients. Lipid changes were also determined in rats subjected to cecal slurry sepsis. Plasma plasmenylcholine, plasmenylethanolamine, and lysoplasmenylcholine levels were decreased while diacyl phosphatidylethanolamine levels were increased in septic rats compared to control treated rats. Kidney levels of lysoplasmenylcholine as well as plasmenylethanolamine molecular species were decreased in septic rats. Interestingly, liver plasmenylcholine and plasmenylethanolamine levels were increased in septic rats. Since COVID-19 is associated with sepsis-like acute respiratory distress syndrome and oxidative stress, plasmalogen levels were also determined in a mouse model of COVID-19 (intranasal inoculation of K18 mice with SARS-CoV-2). 3 days following infection, lung infection was confirmed as well as cytokine expression in the lung. Multiple molecular species of lung plasmenylcholine and plasmenylethanolamine were decreased in infected mice. In contrast, the predominant lung phospholipid, dipalmitoyl phosphatidylcholine, was not decreased following SARS-CoV-2 infection. Additionally total plasmenylcholine levels were decreased in the plasma of SARS-CoV-2 infected mice. Collectively, these data demonstrate the loss of plasmalogens during both sepsis and SARS-CoV-2 infection. This study also indicates plasma plasmalogens should be considered in future studies as biomarkers of infection and as prognostic indicators for sepsis and COVID-19 outcomes.
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Affiliation(s)
- Daniel P Pike
- Edward A. Doisy Department of Biochemistry and Molecular Biology, Saint Louis University School of Medicine, St. Louis, MO, United States.,Center for Cardiovascular Research, Saint Louis University School of Medicine, St. Louis, MO, United States
| | - Reagan M McGuffee
- Edward A. Doisy Department of Biochemistry and Molecular Biology, Saint Louis University School of Medicine, St. Louis, MO, United States.,Center for Cardiovascular Research, Saint Louis University School of Medicine, St. Louis, MO, United States
| | - Elizabeth Geerling
- Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine, St. Louis, MO, United States
| | - Carolyn J Albert
- Edward A. Doisy Department of Biochemistry and Molecular Biology, Saint Louis University School of Medicine, St. Louis, MO, United States.,Center for Cardiovascular Research, Saint Louis University School of Medicine, St. Louis, MO, United States
| | - Daniel F Hoft
- Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine, St. Louis, MO, United States.,Department of Internal Medicine, Division of Infectious Diseases, Allergy and Immunology, Saint Louis University School of Medicine, St. Louis, MO, United States
| | - Michael G S Shashaty
- Pulmonary, Allergy, and Critical Care Division, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States.,Center for Translational Lung Biology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Nuala J Meyer
- Pulmonary, Allergy, and Critical Care Division, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States.,Center for Translational Lung Biology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Amelia K Pinto
- Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine, St. Louis, MO, United States
| | - David A Ford
- Edward A. Doisy Department of Biochemistry and Molecular Biology, Saint Louis University School of Medicine, St. Louis, MO, United States.,Center for Cardiovascular Research, Saint Louis University School of Medicine, St. Louis, MO, United States
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45
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Trongtrakul K, Thonusin C, Pothirat C, Chattipakorn SC, Chattipakorn N. Past Experiences for Future Applications of Metabolomics in Critically Ill Patients with Sepsis and Septic Shocks. Metabolites 2021; 12:metabo12010001. [PMID: 35050123 PMCID: PMC8779293 DOI: 10.3390/metabo12010001] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 12/16/2021] [Accepted: 12/18/2021] [Indexed: 12/17/2022] Open
Abstract
A disruption of several metabolic pathways in critically ill patients with sepsis indicates that metabolomics might be used as a more precise tool for sepsis and septic shock when compared with the conventional biomarkers. This article provides information regarding metabolomics studies in sepsis and septic shock patients. It has been shown that a variety of metabolomic pathways are altered in sepsis and septic shock, including amino acid metabolism, fatty acid oxidation, phospholipid metabolism, glycolysis, and tricarboxylic acid cycle. Based upon this comprehensive review, here, we demonstrate that metabolomics is about to change the world of sepsis biomarkers, not only for its utilization in sepsis diagnosis, but also for prognosticating and monitoring the therapeutic response. Additionally, the future direction regarding the establishment of studies integrating metabolomics with other molecular modalities and studies identifying the relationships between metabolomic profiles and clinical characteristics to address clinical application are discussed in this article. All of the information from this review indicates the important impact of metabolomics as a tool for diagnosis, monitoring therapeutic response, and prognostic assessment of sepsis and septic shock. These findings also encourage further clinical investigations to warrant its use in routine clinical settings.
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Affiliation(s)
- Konlawij Trongtrakul
- Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; (K.T.); (C.P.)
| | - Chanisa Thonusin
- Metabolomics Unit, Cardiac Electrophysiology Research and Training Center, Chiang Mai University, Chiang Mai 50200, Thailand;
- Center of Excellence in Cardiac Electrophysiology Research, Chiang Mai University, Chiang Mai 50200, Thailand
- Cardiac Electrophysiology Unit, Department of Physiology, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand
- Correspondence: (C.T.); (N.C.)
| | - Chaicharn Pothirat
- Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; (K.T.); (C.P.)
| | - Siriporn C. Chattipakorn
- Metabolomics Unit, Cardiac Electrophysiology Research and Training Center, Chiang Mai University, Chiang Mai 50200, Thailand;
- Center of Excellence in Cardiac Electrophysiology Research, Chiang Mai University, Chiang Mai 50200, Thailand
- Department of Oral Biology and Diagnostic Sciences, Faculty of Dentistry, Chiang Mai University, Chiang Mai 50200, Thailand
| | - Nipon Chattipakorn
- Metabolomics Unit, Cardiac Electrophysiology Research and Training Center, Chiang Mai University, Chiang Mai 50200, Thailand;
- Center of Excellence in Cardiac Electrophysiology Research, Chiang Mai University, Chiang Mai 50200, Thailand
- Cardiac Electrophysiology Unit, Department of Physiology, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand
- Correspondence: (C.T.); (N.C.)
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46
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Smith BJ, Silva-Costa LC, Martins-de-Souza D. Human disease biomarker panels through systems biology. Biophys Rev 2021; 13:1179-1190. [PMID: 35059036 PMCID: PMC8724340 DOI: 10.1007/s12551-021-00849-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 10/01/2021] [Indexed: 12/23/2022] Open
Abstract
As more uses for biomarkers are sought after for an increasing number of disease targets, single-target biomarkers are slowly giving way for biomarker panels. These panels incorporate various sources of biomolecular and clinical data to guarantee a higher robustness and power of separation for a clinical test. Multifactorial diseases such as psychiatric disorders show great potential for clinical use, assisting medical professionals during the analysis of risk and predisposition, disease diagnosis and prognosis, and treatment applicability and efficacy. More specific tests are also being developed to assist in ruling out, distinguishing between, and confirming suspicions of multifactorial diseases, as well as to predict which therapy option may be the best option for a given patient's biochemical profile. As more complex datasets are entering the field, involving multi-omic approaches, systems biology has stepped in to facilitate the discovery and validation steps during biomarker panel generation. Filtering biomolecules and clinical data, pre-validating and cross-validating potential biomarkers, generating final biomarker panels, and testing the robustness and applicability of those panels are all beginning to rely on machine learning and systems biology and research in this area will only benefit from advances in these approaches.
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Affiliation(s)
- Bradley J. Smith
- Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil
| | - Licia C. Silva-Costa
- Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil
| | - Daniel Martins-de-Souza
- Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil
- Instituto Nacional de Biomarcadores Em Neuropsiquiatria (INBION), Conselho Nacional de Desenvolvimento Científico E Tecnológico, Sao Paulo, Brazil
- Experimental Medicine Research Cluster (EMRC), University of Campinas, Campinas, Brazil
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Liu T, Feng S, Zhang Y, Wang C. Commentary: Plasma Metabolic Profiling of Pediatric Sepsis in a Chinese Cohort. Front Cell Dev Biol 2021; 9:766357. [PMID: 34778274 PMCID: PMC8581402 DOI: 10.3389/fcell.2021.766357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2021] [Accepted: 09/28/2021] [Indexed: 11/13/2022] Open
Affiliation(s)
- Tiantian Liu
- Department of Critical Care Medicine, Shanghai Children's Hospital, Shanghai Jiao Tong University, Shanghai, China.,Institute of Pediatric Critical Care, Shanghai Jiao Tong University, Shanghai, China
| | - Shuyun Feng
- Department of Critical Care Medicine, Shanghai Children's Hospital, Shanghai Jiao Tong University, Shanghai, China.,Institute of Pediatric Critical Care, Shanghai Jiao Tong University, Shanghai, China
| | - Yucai Zhang
- Department of Critical Care Medicine, Shanghai Children's Hospital, Shanghai Jiao Tong University, Shanghai, China.,Institute of Pediatric Critical Care, Shanghai Jiao Tong University, Shanghai, China.,Institute of Pediatric Infection, Immunity, and Critical Care Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Chunxia Wang
- Department of Critical Care Medicine, Shanghai Children's Hospital, Shanghai Jiao Tong University, Shanghai, China.,Institute of Pediatric Critical Care, Shanghai Jiao Tong University, Shanghai, China.,Institute of Pediatric Infection, Immunity, and Critical Care Medicine, Shanghai Jiao Tong University, Shanghai, China.,Clinical Research Unit, Shanghai Children's Hospital, Shanghai Jiao Tong University, Shanghai, China
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48
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An analysis of urine and serum amino acids in critically ill patients upon admission by means of targeted LC-MS/MS: a preliminary study. Sci Rep 2021; 11:19977. [PMID: 34620961 PMCID: PMC8497565 DOI: 10.1038/s41598-021-99482-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 09/27/2021] [Indexed: 12/12/2022] Open
Abstract
Sepsis, defined as a dysregulated host response to infection, causes the interruption of homeostasis resulting in metabolic changes. An examination of patient metabolites, such as amino acids, during the early stage of sepsis may facilitate diagnosing and assessing the severity of the sepsis. The aim of this study was to compare patterns of urine and serum amino acids relative to sepsis, septic shock and survival. Urine and serum samples were obtained from healthy volunteers (n = 15) once or patients (n = 15) within 24 h of a diagnosis of sepsis or septic shock. Concentrations of 25 amino acids were measured in urine and serum samples with liquid chromatography-electrospray mass spectrometry. On admission in the whole cohort, AAA, ABA, mHis, APA, Gly-Pro and tPro concentrations were significantly lower in the serum than in the urine and Arg, Gly, His, hPro, Leu, Ile, Lys, Orn, Phe, Sarc, Thr, Tyr, Asn and Gln were significantly higher in the serum than in the urine. The urine Gly-Pro concentration was significantly higher in septic shock than in sepsis. The serum Cit concentration was significantly lower in septic shock than in sepsis. The urine ABA, mHis and Gly-Pro, and serum Arg, hPro and Orn concentrations were over two-fold higher in the septic group compared to the control group. Urine and serum amino acids measured in septic patients on admission to the ICU may shed light on a patient’s metabolic condition during sepsis or septic shock.
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49
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Liu Y, Wang J, Guan X, Yu D, Huangfu M, Dou T, Zhou L, Wang L, Liu G, Li X, Zhai Z, Han M, Liu H, Chen X. Mogroside V reduce OVA-induced pulmonary inflammation based on lung and serum metabolomics. PHYTOMEDICINE : INTERNATIONAL JOURNAL OF PHYTOTHERAPY AND PHYTOPHARMACOLOGY 2021; 91:153682. [PMID: 34483017 DOI: 10.1016/j.phymed.2021.153682] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 07/15/2021] [Accepted: 07/16/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Mogroside V, the main ingredient of Siraitia grosvenorii, has been proved to have therapeutic effects on pulmonary diseases. The specific mechanism still remains to be clarified, which hinders the potence of its medicinal value. PURPOSE Serum and lung metabolomics based on LC-MS analysis were applied to explore the mechanism of mogroside V against lung inflammation. METHOD In this study, balb/c mice were divided into control, model, mogeoside V and SH groups. We evaluated the protective effects of mogroside V on lung inflammation in asthmatic mice. Suhuang Zhike Jiaonang was used as positive drug. Metabolic profiles of serum and lung samples of mice in control, model and mogroside V groups were analyzed by LC-MS. RESULTS Administration of mogroside V effectively relieved the expression of biochemical cytokines and lung inflammatory infiltration of asthmatic mice caused by ovalbumin (OVA). And visceral index of mice treated with mogroside V was close to control group. These results indicated that mogroside V ameliorated OVA-induced lung inflammation. LC-MS based metabolomics analysis demonstrated 6 main pathways in asthmatic mice including Vitamin B6 metabolism, Taurine and hypotaurine metabolism, Ascorbate and aldarate metabolism, Histidine metabolism, Pentose and glucuronate interconversions, Citrate cycle (TCA cycle) were regulated after using mogroside V. CONCLUSION The study firstly elucidates the metabolic pathways regulated by mogroside V on lung inflammation through metabolomics, providing a theoretical basis for more sufficient utilization and compatibility of mogroside V.
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Affiliation(s)
- Yisa Liu
- Department of Pharmacy, Guilin Medical University, Guilin 541199, PR China
| | - Juan Wang
- Guangxi Key Laboratory of Molecular Medicine in Liver Injury and Repair, Guilin Medical University, 541001 PR China; Faculty of Basic Medicine, Guilin Medical University, Huan Cheng North 2nd Road No. 109, Guilin 541004, PR China
| | - Xiao Guan
- Department of Pharmacy, Guilin Medical University, Guilin 541199, PR China; Xiangya Hospital, Central South University, Changsha 410008, PR China
| | - Dan Yu
- Department of Pharmacy, Guilin Medical University, Guilin 541199, PR China
| | - Mengjie Huangfu
- Department of Pharmacy, Guilin Medical University, Guilin 541199, PR China
| | - Tong Dou
- Department of Pharmacy, Guilin Medical University, Guilin 541199, PR China
| | - Luwei Zhou
- Department of Pharmacy, Guilin Medical University, Guilin 541199, PR China
| | - Lin Wang
- Department of Pharmacy, Guilin Medical University, Guilin 541199, PR China; Science and Technology Department, Guilin Medical University, Guilin 541199, PR China
| | - Guoxiang Liu
- Department of Pharmacy, Guilin Medical University, Guilin 541199, PR China
| | - Xiaojuan Li
- Department of Pharmacy, Guilin Medical University, Guilin 541199, PR China
| | - Zhaokun Zhai
- Department of Pharmacy, Guilin Medical University, Guilin 541199, PR China
| | - Mengjie Han
- Department of Pharmacy, Guilin Medical University, Guilin 541199, PR China
| | - Haiping Liu
- Department of Pharmacy, Guilin Medical University, Guilin 541199, PR China
| | - Xu Chen
- Department of Pharmacy, Guilin Medical University, Guilin 541199, PR China.
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50
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Luo S, Gou L, Liu S, Cao X. Efficacy and safety of Shenfu injection in the treatment of sepsis: A protocol for systematic review and meta-analysis. Medicine (Baltimore) 2021; 100:e27196. [PMID: 34664847 PMCID: PMC8448001 DOI: 10.1097/md.0000000000027196] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 08/25/2021] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Sepsis is a syndrome of infection-induced systemic inflammatory response. Conventional treatment combined with Shenfu injection (SFI) has been previously validated clinical effective in alleviating inflammatory response in patients with septic shock. However, evidence-based medical evidence is scant. Herein, we designed the protocol of a proposed study based on the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines, aiming to systematically evaluate the efficacy and safety of SFI in patients with sepsis. METHODS Eligible studies reporting the efficacy and safety of SFI in the treatment of sepsis published before August 2021 will be searched from online databases, including the PubMed, Web of Science, EMBASE, Ovid, the Cochrane Library, Wanfang Database, China National Knowledge Infrastructure, and China Biology Medicine Disc. The literature selection process will be reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines. After data extraction and methodological quality evaluation, Stata 12.0 software will be used to synthesize the data through fixed/random effects of meta-analysis models. RESULTS The results of this meta-analysis will be submitted to a peer-reviewed journal for publication. CONCLUSION This study will provide reliable evidence-based basis for the clinical application of SFI in the treatment of sepsis. OSF REGISTRATION NUMBER DOI 10.17605/OSF.IO/KCMDQ.
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Affiliation(s)
- Shu Luo
- Emergency Department, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan Province, China
| | - Lianping Gou
- General Medical Department, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan Province, China
| | - Shiping Liu
- General Medical Department, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan Province, China
| | - Xiaoping Cao
- Emergency Department, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan Province, China
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