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Atreya MR, Huang M, Moore AR, Zheng H, Hasin-Brumshtein Y, Fitzgerald JC, Weiss SL, Cvijanovich NZ, Bigham MT, Jain PN, Schwarz AJ, Lutfi R, Nowak J, Thomas NJ, Quasney M, Dahmer MK, Baines T, Haileselassie B, Lautz AJ, Stanski NL, Standage SW, Kaplan JM, Zingarelli B, Sahay R, Zhang B, Sweeney TE, Khatri P, Sanchez-Pinto LN, Kamaleswaran R. Identification and transcriptomic assessment of latent profile pediatric septic shock phenotypes. Crit Care 2024; 28:246. [PMID: 39014377 PMCID: PMC11253460 DOI: 10.1186/s13054-024-05020-z] [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: 03/10/2024] [Accepted: 07/05/2024] [Indexed: 07/18/2024] Open
Abstract
BACKGROUND Sepsis poses a grave threat, especially among children, but treatments are limited owing to heterogeneity among patients. We sought to test the clinical and biological relevance of pediatric septic shock subclasses identified using reproducible approaches. METHODS We performed latent profile analyses using clinical, laboratory, and biomarker data from a prospective multi-center pediatric septic shock observational cohort to derive phenotypes and trained a support vector machine model to assign phenotypes in an internal validation set. We established the clinical relevance of phenotypes and tested for their interaction with common sepsis treatments on patient outcomes. We conducted transcriptomic analyses to delineate phenotype-specific biology and inferred underlying cell subpopulations. Finally, we compared whether latent profile phenotypes overlapped with established gene-expression endotypes and compared survival among patients based on an integrated subclassification scheme. RESULTS Among 1071 pediatric septic shock patients requiring vasoactive support on day 1 included, we identified two phenotypes which we designated as Phenotype 1 (19.5%) and Phenotype 2 (80.5%). Membership in Phenotype 1 was associated with ~ fourfold adjusted odds of complicated course relative to Phenotype 2. Patients belonging to Phenotype 1 were characterized by relatively higher Angiopoietin-2/Tie-2 ratio, Angiopoietin-2, soluble thrombomodulin (sTM), interleukin 8 (IL-8), and intercellular adhesion molecule 1 (ICAM-1) and lower Tie-2 and Angiopoietin-1 concentrations compared to Phenotype 2. We did not identify significant interactions between phenotypes, common treatments, and clinical outcomes. Transcriptomic analysis revealed overexpression of genes implicated in the innate immune response and driven primarily by developing neutrophils among patients designated as Phenotype 1. There was no statistically significant overlap between established gene-expression endotypes, reflective of the host adaptive response, and the newly derived phenotypes, reflective of the host innate response including microvascular endothelial dysfunction. However, an integrated subclassification scheme demonstrated varying survival probabilities when comparing patient endophenotypes. CONCLUSIONS Our research underscores the reproducibility of latent profile analyses to identify pediatric septic shock phenotypes with high prognostic relevance. Pending validation, an integrated subclassification scheme, reflective of the different facets of the host response, holds promise to inform targeted intervention among those critically ill.
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Affiliation(s)
- Mihir R Atreya
- Division of Critical Care Medicine, MLC2005, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH, 45229, USA.
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45627, USA.
| | - Min Huang
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, USA
| | - Andrew R Moore
- Stanford Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA, USA
| | - Hong Zheng
- Stanford Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA, USA
- Center for Biomedical Informatics Research, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | | | | | - Scott L Weiss
- Nemours Children's Health, Wilmington, DE, 19803, USA
| | | | | | - Parag N Jain
- Texas Children's Hospital, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Adam J Schwarz
- Children's Hospital of Orange County, Orange, CA, 92868, USA
| | - Riad Lutfi
- Riley Hospital for Children, Indianapolis, IN, 46202, USA
| | - Jeffrey Nowak
- Children's Hospital and Clinics of Minnesota, Minneapolis, MN, 55404, USA
| | - Neal J Thomas
- Penn State Hershey Children's Hospital, Hershey, PA, 17033, USA
| | - Michael Quasney
- C.S Mott Children's Hospital, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Mary K Dahmer
- C.S Mott Children's Hospital, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Torrey Baines
- University of Florida Health Children's Hospital, Gainesville, FL, 32610, USA
| | | | - Andrew J Lautz
- Division of Critical Care Medicine, MLC2005, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH, 45229, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45627, USA
| | - Natalja L Stanski
- Division of Critical Care Medicine, MLC2005, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH, 45229, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45627, USA
| | - Stephen W Standage
- Division of Critical Care Medicine, MLC2005, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH, 45229, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45627, USA
| | - Jennifer M Kaplan
- Division of Critical Care Medicine, MLC2005, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH, 45229, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45627, USA
| | - Basilia Zingarelli
- Division of Critical Care Medicine, MLC2005, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH, 45229, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45627, USA
| | - Rashmi Sahay
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
| | - Bin Zhang
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
| | | | - Purvesh Khatri
- Stanford Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA, USA
- Center for Biomedical Informatics Research, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - L Nelson Sanchez-Pinto
- Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
- Department of Health and Biomedical Informatics, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Rishikesan Kamaleswaran
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, 30322, USA
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, 30322, USA
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2
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Gordon AC, Alipanah-Lechner N, Bos LD, Dianti J, Diaz JV, Finfer S, Fujii T, Giamarellos-Bourboulis EJ, Goligher EC, Gong MN, Karakike E, Liu VX, Lumlertgul N, Marshall JC, Menon DK, Meyer NJ, Munroe ES, Myatra SN, Ostermann M, Prescott HC, Randolph AG, Schenck EJ, Seymour CW, Shankar-Hari M, Singer M, Smit MR, Tanaka A, Taccone FS, Thompson BT, Torres LK, van der Poll T, Vincent JL, Calfee CS. From ICU Syndromes to ICU Subphenotypes: Consensus Report and Recommendations for Developing Precision Medicine in the ICU. Am J Respir Crit Care Med 2024; 210:155-166. [PMID: 38687499 PMCID: PMC11273306 DOI: 10.1164/rccm.202311-2086so] [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: 11/14/2023] [Accepted: 04/29/2024] [Indexed: 05/02/2024] Open
Abstract
Critical care uses syndromic definitions to describe patient groups for clinical practice and research. There is growing recognition that a "precision medicine" approach is required and that integrated biologic and physiologic data identify reproducible subpopulations that may respond differently to treatment. This article reviews the current state of the field and considers how to successfully transition to a precision medicine approach. To impact clinical care, identification of subpopulations must do more than differentiate prognosis. It must differentiate response to treatment, ideally by defining subgroups with distinct functional or pathobiological mechanisms (endotypes). There are now multiple examples of reproducible subpopulations of sepsis, acute respiratory distress syndrome, and acute kidney or brain injury described using clinical, physiological, and/or biological data. Many of these subpopulations have demonstrated the potential to define differential treatment response, largely in retrospective studies, and that the same treatment-responsive subpopulations may cross multiple clinical syndromes (treatable traits). To bring about a change in clinical practice, a precision medicine approach must be evaluated in prospective clinical studies requiring novel adaptive trial designs. Several such studies are underway, but there are multiple challenges to be tackled. Such subpopulations must be readily identifiable and be applicable to all critically ill populations around the world. Subdividing clinical syndromes into subpopulations will require large patient numbers. Global collaboration of investigators, clinicians, industry, and patients over many years will therefore be required to transition to a precision medicine approach and ultimately realize treatment advances seen in other medical fields.
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Affiliation(s)
| | - Narges Alipanah-Lechner
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Department of Medicine, University of California, San Francisco, San Francisco, California
| | | | - Jose Dianti
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada
- Departamento de Cuidados Intensivos, Centro de Educación Médica e Investigaciones Clínicas, Buenos Aires, Argentina
| | | | - Simon Finfer
- School of Public Health, Imperial College London, London, United Kingdom
- The George Institute for Global Health, University of New South Wales, Sydney, Australia
| | - Tomoko Fujii
- Jikei University School of Medicine, Jikei University Hospital, Tokyo, Japan
| | | | - Ewan C. Goligher
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Michelle Ng Gong
- Division of Critical Care Medicine and
- Division of Pulmonary Medicine, Department of Medicine and Department of Epidemiology and Population Health, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York
| | - Eleni Karakike
- Second Department of Critical Care Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Vincent X. Liu
- Division of Research, Kaiser Permanente, Oakland, California
| | - Nuttha Lumlertgul
- Excellence Center for Critical Care Nephrology, Division of Nephrology, Faculty of Medicine, King Chulalongkorn Memorial Hospital, Bangkok, Thailand
| | - John C. Marshall
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada
| | - David K. Menon
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Nuala J. Meyer
- Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Elizabeth S. Munroe
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Sheila N. Myatra
- Department of Anaesthesiology, Critical Care and Pain, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Marlies Ostermann
- King’s College London, Guy’s & St Thomas’ Hospital, London, United Kingdom
| | - Hallie C. Prescott
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
- Veterans Affairs Center for Clinical Management Research, Ann Arbor, Michigan
| | - Adrienne G. Randolph
- Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children’s Hospital, Boston, Massachusetts
- Department of Anaesthesia and
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts
| | - Edward J. Schenck
- Division of Pulmonary and Critical Care Medicine, Joan and Sanford I. Weill Department of Medicine, Weill Cornell Medicine, New York, New York
| | - Christopher W. Seymour
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Manu Shankar-Hari
- Centre for Inflammation Research, Institute of Regeneration and Repair, University of Edinburgh, Edinburgh, United Kingdom
| | - Mervyn Singer
- Bloomsbury Institute of Intensive Care Medicine, Division of Medicine, University College London, London, United Kingdom
| | | | - Aiko Tanaka
- Department of Intensive Care, University of Fukui Hospital, Yoshida, Fukui, Japan
- Department of Anesthesiology and Intensive Care Medicine, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Fabio S. Taccone
- Department des Soins Intensifs, Hôpital Universitaire de Bruxelles (HUB), Université Libre de Bruxelles (ULB), Brussels, Belgium; and
| | - B. Taylor Thompson
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Lisa K. Torres
- Division of Pulmonary and Critical Care Medicine, Joan and Sanford I. Weill Department of Medicine, Weill Cornell Medicine, New York, New York
| | - Tom van der Poll
- Center of Experimental and Molecular Medicine, and
- Division of Infectious Diseases, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Jean-Louis Vincent
- Department des Soins Intensifs, Hôpital Universitaire de Bruxelles (HUB), Université Libre de Bruxelles (ULB), Brussels, Belgium; and
| | - Carolyn S. Calfee
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Department of Medicine, University of California, San Francisco, San Francisco, California
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3
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Bodinier M, Peronnet E, Llitjos JF, Kreitmann L, Brengel-Pesce K, Rimmelé T, Fleurie A, Textoris J, Venet F, Maucort-Boulch D, Monneret G. Integrated clustering of multiple immune marker trajectories reveals different immunotypes in severely injured patients. Crit Care 2024; 28:240. [PMID: 39010113 PMCID: PMC11247757 DOI: 10.1186/s13054-024-04990-4] [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: 03/21/2024] [Accepted: 06/14/2024] [Indexed: 07/17/2024] Open
Abstract
BACKGROUND The immune response of critically ill patients, such as those with sepsis, severe trauma, or major surgery, is heterogeneous and dynamic, but its characterization and impact on outcomes are poorly understood. Until now, the primary challenge in advancing our understanding of the disease has been to concurrently address both multiparametric and temporal aspects. METHODS We used a clustering method to identify distinct groups of patients, based on various immune marker trajectories during the first week after admission to ICU. In 339 severely injured patients, we initially longitudinally clustered common biomarkers (both soluble and cellular parameters), whose variations are well-established during the immunosuppressive phase of sepsis. We then applied this multi-trajectory clustering using markers composed of whole blood immune-related mRNA. RESULTS We found that both sets of markers revealed two immunotypes, one of which was associated with worse outcomes, such as increased risk of hospital-acquired infection and mortality, and prolonged hospital stays. This immunotype showed signs of both hyperinflammation and immunosuppression, which persisted over time. CONCLUSION Our study suggest that the immune system of critically ill patients can be characterized by two distinct longitudinal immunotypes, one of which included patients with a persistently dysregulated and impaired immune response. This work confirms the relevance of such methodology to stratify patients and pave the way for further studies using markers indicative of potential immunomodulatory drug targets.
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Affiliation(s)
- Maxime Bodinier
- EA 7426 "Pathophysiology of Injury-Induced Immunosuppression" (Université Claude Bernard Lyon 1 - Hospices Civils de Lyon - bioMérieux), Joint Research Unit HCL-bioMérieux, Immunology Laboratory and Anesthesia and Critical Care Medicine Department, Hospices Civils de Lyon, Edouard Herriot Hospital, 5 place d'Arsonval, 69003, Lyon Cedex 03, France
| | - Estelle Peronnet
- EA 7426 "Pathophysiology of Injury-Induced Immunosuppression" (Université Claude Bernard Lyon 1 - Hospices Civils de Lyon - bioMérieux), Joint Research Unit HCL-bioMérieux, Immunology Laboratory and Anesthesia and Critical Care Medicine Department, Hospices Civils de Lyon, Edouard Herriot Hospital, 5 place d'Arsonval, 69003, Lyon Cedex 03, France
| | - Jean-François Llitjos
- EA 7426 "Pathophysiology of Injury-Induced Immunosuppression" (Université Claude Bernard Lyon 1 - Hospices Civils de Lyon - bioMérieux), Joint Research Unit HCL-bioMérieux, Immunology Laboratory and Anesthesia and Critical Care Medicine Department, Hospices Civils de Lyon, Edouard Herriot Hospital, 5 place d'Arsonval, 69003, Lyon Cedex 03, France
- Anesthesiology and Critical Care Medicine, Edouard Herriot Hospital, Hospices Civils de Lyon, 69003, Lyon, France
| | - Louis Kreitmann
- EA 7426 "Pathophysiology of Injury-Induced Immunosuppression" (Université Claude Bernard Lyon 1 - Hospices Civils de Lyon - bioMérieux), Joint Research Unit HCL-bioMérieux, Immunology Laboratory and Anesthesia and Critical Care Medicine Department, Hospices Civils de Lyon, Edouard Herriot Hospital, 5 place d'Arsonval, 69003, Lyon Cedex 03, France
- Department of Infectious Disease, Faculty of Medicine, Imperial College, London, W12 0NN, UK
| | - Karen Brengel-Pesce
- EA 7426 "Pathophysiology of Injury-Induced Immunosuppression" (Université Claude Bernard Lyon 1 - Hospices Civils de Lyon - bioMérieux), Joint Research Unit HCL-bioMérieux, Immunology Laboratory and Anesthesia and Critical Care Medicine Department, Hospices Civils de Lyon, Edouard Herriot Hospital, 5 place d'Arsonval, 69003, Lyon Cedex 03, France
| | - Thomas Rimmelé
- EA 7426 "Pathophysiology of Injury-Induced Immunosuppression" (Université Claude Bernard Lyon 1 - Hospices Civils de Lyon - bioMérieux), Joint Research Unit HCL-bioMérieux, Immunology Laboratory and Anesthesia and Critical Care Medicine Department, Hospices Civils de Lyon, Edouard Herriot Hospital, 5 place d'Arsonval, 69003, Lyon Cedex 03, France
- Anesthesiology and Critical Care Medicine, Edouard Herriot Hospital, Hospices Civils de Lyon, 69003, Lyon, France
| | - Aurore Fleurie
- EA 7426 "Pathophysiology of Injury-Induced Immunosuppression" (Université Claude Bernard Lyon 1 - Hospices Civils de Lyon - bioMérieux), Joint Research Unit HCL-bioMérieux, Immunology Laboratory and Anesthesia and Critical Care Medicine Department, Hospices Civils de Lyon, Edouard Herriot Hospital, 5 place d'Arsonval, 69003, Lyon Cedex 03, France
| | - Julien Textoris
- EA 7426 "Pathophysiology of Injury-Induced Immunosuppression" (Université Claude Bernard Lyon 1 - Hospices Civils de Lyon - bioMérieux), Joint Research Unit HCL-bioMérieux, Immunology Laboratory and Anesthesia and Critical Care Medicine Department, Hospices Civils de Lyon, Edouard Herriot Hospital, 5 place d'Arsonval, 69003, Lyon Cedex 03, France
- Anesthesiology and Critical Care Medicine, Edouard Herriot Hospital, Hospices Civils de Lyon, 69003, Lyon, France
| | - Fabienne Venet
- EA 7426 "Pathophysiology of Injury-Induced Immunosuppression" (Université Claude Bernard Lyon 1 - Hospices Civils de Lyon - bioMérieux), Joint Research Unit HCL-bioMérieux, Immunology Laboratory and Anesthesia and Critical Care Medicine Department, Hospices Civils de Lyon, Edouard Herriot Hospital, 5 place d'Arsonval, 69003, Lyon Cedex 03, France
- Centre International de Recherche en Infectiologie (CIRI), Inserm U1111, CNRS, UMR5308, Ecole Normale Supérieure de Lyon, Université Claude, Bernard-Lyon 1, Lyon, France
| | - Delphine Maucort-Boulch
- Université Claude Bernard Lyon 1, Université de Lyon, Lyon, France
- Équipe Biostatistique-Santé, Laboratoire de Biométrie Et Biologie Évolutive, CNRS UMR 5558, Villeurbanne, France
- Service de Biostatistique-Bioinformatique, Pôle Santé Publique, Hospices Civils de Lyon, Lyon, France
| | - Guillaume Monneret
- EA 7426 "Pathophysiology of Injury-Induced Immunosuppression" (Université Claude Bernard Lyon 1 - Hospices Civils de Lyon - bioMérieux), Joint Research Unit HCL-bioMérieux, Immunology Laboratory and Anesthesia and Critical Care Medicine Department, Hospices Civils de Lyon, Edouard Herriot Hospital, 5 place d'Arsonval, 69003, Lyon Cedex 03, France.
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4
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Burnham KL, Milind N, Lee W, Kwok AJ, Cano-Gamez K, Mi Y, Geoghegan CG, Zhang P, McKechnie S, Soranzo N, Hinds CJ, Knight JC, Davenport EE. eQTLs identify regulatory networks and drivers of variation in the individual response to sepsis. CELL GENOMICS 2024; 4:100587. [PMID: 38897207 PMCID: PMC11293594 DOI: 10.1016/j.xgen.2024.100587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 03/27/2024] [Accepted: 05/28/2024] [Indexed: 06/21/2024]
Abstract
Sepsis is a clinical syndrome of life-threatening organ dysfunction caused by a dysregulated response to infection, for which disease heterogeneity is a major obstacle to developing targeted treatments. We have previously identified gene-expression-based patient subgroups (sepsis response signatures [SRS]) informative for outcome and underlying pathophysiology. Here, we aimed to investigate the role of genetic variation in determining the host transcriptomic response and to delineate regulatory networks underlying SRS. Using genotyping and RNA-sequencing data on 638 adult sepsis patients, we report 16,049 independent expression (eQTLs) and 32 co-expression module (modQTLs) quantitative trait loci in this disease context. We identified significant interactions between SRS and genotype for 1,578 SNP-gene pairs and combined transcription factor (TF) binding site information (SNP2TFBS) and predicted regulon activity (DoRothEA) to identify candidate upstream regulators. Overall, these approaches identified putative mechanistic links between host genetic variation, cell subtypes, and the individual transcriptomic response to infection.
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Affiliation(s)
- Katie L Burnham
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Nikhil Milind
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK; University of Cambridge, Cambridge, UK
| | - Wanseon Lee
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Andrew J Kwok
- Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Kiki Cano-Gamez
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK; Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Yuxin Mi
- Centre for Human Genetics, University of Oxford, Oxford, UK
| | | | - Ping Zhang
- Centre for Human Genetics, University of Oxford, Oxford, UK; Chinese Academy of Medical Science Oxford Institute, University of Oxford, Oxford, UK
| | | | - Nicole Soranzo
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Charles J Hinds
- Centre for Translational Medicine & Therapeutics, William Harvey Research Institute, Faculty of Medicine & Dentistry, Queen Mary University of London, London, UK
| | - Julian C Knight
- Centre for Human Genetics, University of Oxford, Oxford, UK; Chinese Academy of Medical Science Oxford Institute, University of Oxford, Oxford, UK.
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5
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Chenoweth JG, Brandsma J, Striegel DA, Genzor P, Chiyka E, Blair PW, Krishnan S, Dogbe E, Boakye I, Fogel GB, Tsalik EL, Woods CW, Owusu-Ofori A, Oppong C, Oduro G, Vantha T, Letizia AG, Beckett CG, Schully KL, Clark DV. Sepsis endotypes identified by host gene expression across global cohorts. COMMUNICATIONS MEDICINE 2024; 4:120. [PMID: 38890515 PMCID: PMC11189468 DOI: 10.1038/s43856-024-00542-7] [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: 05/19/2023] [Accepted: 06/04/2024] [Indexed: 06/20/2024] Open
Abstract
BACKGROUND Sepsis from infection is a global health priority and clinical trials have failed to deliver effective therapeutic interventions. To address complicating heterogeneity in sepsis pathobiology, and improve outcomes, promising precision medicine approaches are helping identify disease endotypes, however, they require a more complete definition of sepsis subgroups. METHODS Here, we use RNA sequencing from peripheral blood to interrogate the host response to sepsis from participants in a global observational study carried out in West Africa, Southeast Asia, and North America (N = 494). RESULTS We identify four sepsis subtypes differentiated by 28-day mortality. A low mortality immunocompetent group is specified by features that describe the adaptive immune system. In contrast, the three high mortality groups show elevated clinical severity consistent with multiple organ dysfunction. The immunosuppressed group members show signs of a dysfunctional immune response, the acute-inflammation group is set apart by molecular features of the innate immune response, while the immunometabolic group is characterized by metabolic pathways such as heme biosynthesis. CONCLUSIONS Our analysis reveals details of molecular endotypes in sepsis that support immunotherapeutic interventions and identifies biomarkers that predict outcomes in these groups.
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Affiliation(s)
- Josh G Chenoweth
- Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO), The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA.
| | - Joost Brandsma
- Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO), The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA
| | - Deborah A Striegel
- Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO), The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA
| | - Pavol Genzor
- Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO), The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA
| | - Elizabeth Chiyka
- Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO), The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA
| | - Paul W Blair
- Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO), The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA
| | - Subramaniam Krishnan
- Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO), The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA
| | - Elliot Dogbe
- Laboratory Services Directorate, KATH, Kumasi, Ghana
| | - Isaac Boakye
- Research and Development Unit, KATH, Kumasi, Ghana
| | | | - Ephraim L Tsalik
- Center for Infectious Disease Diagnostics and Innovation, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
- Danaher Diagnostics, Washington, DC., USA
| | - Christopher W Woods
- Center for Infectious Disease Diagnostics and Innovation, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Alex Owusu-Ofori
- Laboratory Services Directorate, KATH, Kumasi, Ghana
- Department of Clinical Microbiology, Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana
| | - Chris Oppong
- Accident and Emergency Department, KATH, Kumasi, Ghana
| | - George Oduro
- Accident and Emergency Department, KATH, Kumasi, Ghana
| | - Te Vantha
- Takeo Provincial Referral Hospital, Takeo, Cambodia
| | - Andrew G Letizia
- Naval Medical Research Unit EURAFCENT Ghana detachment, Accra, Ghana
| | - Charmagne G Beckett
- Naval Medical Research Command Infectious Diseases Directorate, Silver Spring, MD, USA
| | - Kevin L Schully
- Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO), Biological Defense Research Directorate, Naval Medical Research Command-Frederick, Ft. Detrick, Maryland, MD, USA
| | - Danielle V Clark
- Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO), The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA
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6
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Jariyasakoolroj T, Chattipakorn SC, Chattipakorn N. Potential biomarkers used for risk estimation of pediatric sepsis-associated organ dysfunction and immune dysregulation. Pediatr Res 2024:10.1038/s41390-024-03289-y. [PMID: 38834784 DOI: 10.1038/s41390-024-03289-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 04/03/2024] [Accepted: 05/11/2024] [Indexed: 06/06/2024]
Abstract
Pediatric sepsis is a serious issue globally and is a significant cause of illness and death among infants and children. Refractory septic shock and multiple organ dysfunction syndrome are the primary causes of mortality in children with sepsis. However, there is incomplete understanding of mechanistic insight of sepsis associated organ dysfunction. Biomarkers present during the body's response to infection-related inflammation can be used for screening, diagnosis, risk stratification/prognostication, and/or guidance in treatment decision-making. Research on biomarkers in children with sepsis can provide information about the risk of poor outcomes and sepsis-related organ dysfunction. This review focuses on clinically used biomarkers associated with immune dysregulation and organ dysfunction in pediatric sepsis, which could be useful for developing precision medicine strategies in pediatric sepsis management in the future. IMPACT: Sepsis is a complex syndrome with diverse clinical presentations, where organ dysfunction is a key factor in morbidity and mortality. Early detection of organ complications is vital in sepsis management, and potential biomarkers offer promise for precision medicine in pediatric cases. Well-designed studies are needed to identify phase-specific biomarkers and improve outcomes through more precise management.
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Affiliation(s)
- Theerapon Jariyasakoolroj
- Division of Pediatric Critical Care Medicine, Department of Pediatrics, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
| | - Siriporn C Chattipakorn
- Cardiac Electrophysiology Research and Training Center, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
- Center of Excellence in Cardiac Electrophysiology Research, Chiang Mai University, Chiang Mai, Thailand
- Department of Oral Biology and Diagnostic Sciences, Faculty of Dentistry, Chiang Mai University, Chiang Mai, Thailand
| | - Nipon Chattipakorn
- Cardiac Electrophysiology Research and Training Center, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
- Center of Excellence in Cardiac Electrophysiology Research, Chiang Mai University, Chiang Mai, Thailand.
- Cardiac Electrophysiology Unit, Department of Physiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
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7
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Stevens J, Tezel O, Bonnefil V, Hapstack M, Atreya MR. Biological basis of critical illness subclasses: from the bedside to the bench and back again. Crit Care 2024; 28:186. [PMID: 38812006 PMCID: PMC11137966 DOI: 10.1186/s13054-024-04959-3] [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: 03/09/2024] [Accepted: 05/17/2024] [Indexed: 05/31/2024] Open
Abstract
Critical illness syndromes including sepsis, acute respiratory distress syndrome, and acute kidney injury (AKI) are associated with high in-hospital mortality and long-term adverse health outcomes among survivors. Despite advancements in care, clinical and biological heterogeneity among patients continues to hamper identification of efficacious therapies. Precision medicine offers hope by identifying patient subclasses based on clinical, laboratory, biomarker and 'omic' data and potentially facilitating better alignment of interventions. Within the previous two decades, numerous studies have made strides in identifying gene-expression based endotypes and clinico-biomarker based phenotypes among critically ill patients associated with differential outcomes and responses to treatment. In this state-of-the-art review, we summarize the biological similarities and differences across the various subclassification schemes among critically ill patients. In addition, we highlight current translational gaps, the need for advanced scientific tools, human-relevant disease models, to gain a comprehensive understanding of the molecular mechanisms underlying critical illness subclasses.
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Affiliation(s)
- Joseph Stevens
- Division of Immunobiology, Graduate Program, College of Medicine, University of Cincinnati, Cincinnati, OH, 45267, USA
| | - Oğuzhan Tezel
- Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
| | - Valentina Bonnefil
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45627, USA
| | - Matthew Hapstack
- Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
| | - Mihir R Atreya
- Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA.
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45627, USA.
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8
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Abstract
Sepsis syndromes have been recognized since antiquity yet still pose significant challenges to modern medicine. One of the biggest challenges lies in the heterogeneity of triggers and its protean clinical manifestations, as well as its rapidly progressive and lethal nature. Thus, there is a critical need for biomarkers that can quickly and accurately detect sepsis onset and predict treatment response. In this review, we will briefly describe the current consensus definitions of sepsis and the ideal features of a biomarker. We will then delve into currently available and in-development markers of pathogens, hosts, and their interactions that together comprise the sepsis syndrome.
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Affiliation(s)
- Maya Cohen
- Division of Pulmonary, Critical Care, and Sleep Medicine, Alpert/Brown Medical School, Providence, RI, USA
| | - Debasree Banerjee
- Division of Pulmonary, Critical Care, and Sleep Medicine, Alpert/Brown Medical School, Providence, RI, USA
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9
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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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10
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Marin MJ, van Wijk XMR, Chambliss AB. Advances in sepsis biomarkers. Adv Clin Chem 2024; 119:117-166. [PMID: 38514209 DOI: 10.1016/bs.acc.2024.02.003] [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] [Indexed: 03/23/2024]
Abstract
Sepsis, a dysregulated host immune response to an infectious agent, significantly increases morbidity and mortality for hospitalized patients worldwide. This chapter reviews (1) the basic principles of infectious diseases, pathophysiology and current definition of sepsis, (2) established sepsis biomarkers such lactate, procalcitonin and C-reactive protein, (3) novel, newly regulatory-cleared/approved biomarkers, such as assays that evaluate white blood cell properties and immune response molecules, and (4) emerging biomarkers and biomarker panels to highlight future directions and opportunities in the diagnosis and management of sepsis.
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Affiliation(s)
- Maximo J Marin
- Department of Pathology, Immunology & Laboratory Medicine, University of Florida, Gainesville, Florida, USA
| | | | - Allison B Chambliss
- Department of Pathology & Laboratory Medicine, University of California Los Angeles, Los Angeles, California, USA
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11
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Liu D, Langston JC, Prabhakarpandian B, Kiani MF, Kilpatrick LE. The critical role of neutrophil-endothelial cell interactions in sepsis: new synergistic approaches employing organ-on-chip, omics, immune cell phenotyping and in silico modeling to identify new therapeutics. Front Cell Infect Microbiol 2024; 13:1274842. [PMID: 38259971 PMCID: PMC10800980 DOI: 10.3389/fcimb.2023.1274842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 12/18/2023] [Indexed: 01/24/2024] Open
Abstract
Sepsis is a global health concern accounting for more than 1 in 5 deaths worldwide. Sepsis is now defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Sepsis can develop from bacterial (gram negative or gram positive), fungal or viral (such as COVID) infections. However, therapeutics developed in animal models and traditional in vitro sepsis models have had little success in clinical trials, as these models have failed to fully replicate the underlying pathophysiology and heterogeneity of the disease. The current understanding is that the host response to sepsis is highly diverse among patients, and this heterogeneity impacts immune function and response to infection. Phenotyping immune function and classifying sepsis patients into specific endotypes is needed to develop a personalized treatment approach. Neutrophil-endothelium interactions play a critical role in sepsis progression, and increased neutrophil influx and endothelial barrier disruption have important roles in the early course of organ damage. Understanding the mechanism of neutrophil-endothelium interactions and how immune function impacts this interaction can help us better manage the disease and lead to the discovery of new diagnostic and prognosis tools for effective treatments. In this review, we will discuss the latest research exploring how in silico modeling of a synergistic combination of new organ-on-chip models incorporating human cells/tissue, omics analysis and clinical data from sepsis patients will allow us to identify relevant signaling pathways and characterize specific immune phenotypes in patients. Emerging technologies such as machine learning can then be leveraged to identify druggable therapeutic targets and relate them to immune phenotypes and underlying infectious agents. This synergistic approach can lead to the development of new therapeutics and the identification of FDA approved drugs that can be repurposed for the treatment of sepsis.
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Affiliation(s)
- Dan Liu
- Department of Bioengineering, Temple University, Philadelphia, PA, United States
| | - Jordan C. Langston
- Department of Bioengineering, Temple University, Philadelphia, PA, United States
| | | | - Mohammad F. Kiani
- Department of Bioengineering, Temple University, Philadelphia, PA, United States
- Department of Mechanical Engineering, Temple University, Philadelphia, PA, United States
- Department of Radiation Oncology, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, United States
| | - Laurie E. Kilpatrick
- Center for Inflammation and Lung Research, Department of Microbiology, Immunology and Inflammation, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, United States
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12
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Aldewereld Z, Horvat C, Carcillo JA, Clermont G. EMERGENCE OF A TECHNOLOGY-DEPENDENT PHENOTYPE OF PEDIATRIC SEPSIS IN A LARGE CHILDREN'S HOSPITAL. Shock 2024; 61:76-82. [PMID: 38010054 PMCID: PMC10842625 DOI: 10.1097/shk.0000000000002264] [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] [Indexed: 11/29/2023]
Abstract
ABSTRACT Objective: To investigate whether pediatric sepsis phenotypes are stable in time. Methods: Retrospective cohort study examining children with suspected sepsis admitted to a Pediatric Intensive Care Unit at a large freestanding children's hospital during two distinct periods: 2010-2014 (early cohort) and 2018-2020 (late cohort). K-means consensus clustering was used to derive types separately in the cohorts. Variables included ensured representation of all organ systems. Results: One thousand ninety-one subjects were in the early cohort and 737 subjects in the late cohort. Clustering analysis yielded four phenotypes in the early cohort and five in the late cohort. Four types were in both: type A (34% of early cohort, 25% of late cohort), mild sepsis, with minimal organ dysfunction and low mortality; type B (25%, 22%), primary respiratory failure; type C (25%, 18%), liver dysfunction, coagulopathy, and higher measures of systemic inflammation; type D (16%, 17%), severe multiorgan dysfunction, with high degrees of cardiorespiratory support, renal dysfunction, and highest mortality. Type E was only detected in the late cohort (19%) and was notable for respiratory failure less severe than B or D, mild hypothermia, and high proportion of diagnoses and technological dependence associated with medical complexity. Despite low mortality, this type had the longest PICU length of stay. Conclusions: This single center study identified four pediatric sepsis phenotypes in an earlier epoch but five in a later epoch, with the new type having a large proportion of characteristics associated with medical complexity, particularly technology dependence. Personalized sepsis therapies need to account for this expanding patient population.
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Affiliation(s)
- Zachary Aldewereld
- Division of Pediatric Critical Care Medicine, Department of Critical Care Medicine, and Division of Pediatric Infectious Diseases, Department of Pediatrics, University of Pittsburgh, UPMC Children’s Hospital of Pittsburgh, Pittsburgh, PA, United States
| | - Christopher Horvat
- Division of Pediatric Critical Care Medicine, Department of Critical Care Medicine, and Division of Division of Health Informatics, Department of Pediatrics, University of Pittsburgh, UPMC Children’s Hospital of Pittsburgh, Pittsburgh, PA, United States
| | - Joseph A Carcillo
- Division of Pediatric Critical Care Medicine, Department of Critical Care Medicine, University of Pittsburgh, UPMC Children’s Hospital of Pittsburgh, Pittsburgh, PA, United States
| | - Gilles Clermont
- Department of Critical Care Medicine, and Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, United States
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13
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Levine AR, Calfee CS. Subphenotypes of Acute Respiratory Distress Syndrome: Advancing Towards Precision Medicine. Tuberc Respir Dis (Seoul) 2024; 87:1-11. [PMID: 37675452 PMCID: PMC10758309 DOI: 10.4046/trd.2023.0104] [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: 07/26/2023] [Revised: 08/25/2023] [Accepted: 09/06/2023] [Indexed: 09/08/2023] Open
Abstract
Acute respiratory distress syndrome (ARDS) is a common cause of severe hypoxemia defined by the acute onset of bilateral non-cardiogenic pulmonary edema. The diagnosis is made by defined consensus criteria. Supportive care, including prevention of further injury to the lungs, is the only treatment that conclusively improves outcomes. The inability to find more advanced therapies is due, in part, to the highly sensitive but relatively non-specific current syndromic consensus criteria, combining a heterogenous population of patients under the umbrella of ARDS. With few effective therapies, the morality rate remains 30% to 40%. Many subphenotypes of ARDS have been proposed to cluster patients with shared combinations of observable or measurable traits. Subphenotyping patients is a strategy to overcome heterogeneity to advance clinical research and eventually identify treatable traits. Subphenotypes of ARDS have been proposed based on radiographic patterns, protein biomarkers, transcriptomics, and/or machine-based clustering of clinical and biological variables. Some of these strategies have been reproducible across patient cohorts, but at present all have practical limitations to their implementation. Furthermore, there is no agreement on which strategy is the most appropriate. This review will discuss the current strategies for subphenotyping patients with ARDS, including the strengths and limitations, and the future directions of ARDS subphenotyping.
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Affiliation(s)
- Andrea R. Levine
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Carolyn S. Calfee
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
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14
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Atreya MR, Banerjee S, Lautz AJ, Alder MN, Varisco BM, Wong HR, Muszynski JA, Hall MW, Sanchez-Pinto LN, Kamaleswaran R. Machine learning-driven identification of the gene-expression signature associated with a persistent multiple organ dysfunction trajectory in critical illness. EBioMedicine 2024; 99:104938. [PMID: 38142638 PMCID: PMC10788426 DOI: 10.1016/j.ebiom.2023.104938] [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: 09/20/2023] [Revised: 12/08/2023] [Accepted: 12/12/2023] [Indexed: 12/26/2023] Open
Abstract
BACKGROUND Multiple organ dysfunction syndrome (MODS) disproportionately drives morbidity and mortality among critically ill patients. However, we lack a comprehensive understanding of its pathobiology. Identification of genes associated with a persistent MODS trajectory may shed light on underlying biology and allow for accurate prediction of those at-risk. METHODS Secondary analyses of publicly available gene-expression datasets. Supervised machine learning (ML) was used to identify a parsimonious set of genes associated with a persistent MODS trajectory in a training set of pediatric septic shock. We optimized model parameters and tested risk-prediction capabilities in independent validation and test datasets, respectively. We compared model performance relative to an established gene-set predictive of sepsis mortality. FINDINGS Patients with a persistent MODS trajectory had 568 differentially expressed genes and characterized by a dysregulated innate immune response. Supervised ML identified 111 genes associated with the outcome of interest on repeated cross-validation, with an AUROC of 0.87 (95% CI: 0.85-0.88) in the training set. The optimized model, limited to 20 genes, achieved AUROCs ranging from 0.74 to 0.79 in the validation and test sets to predict those with persistent MODS, regardless of host age and cause of organ dysfunction. Our classifier demonstrated reproducibility in identifying those with persistent MODS in comparison with a published gene-set predictive of sepsis mortality. INTERPRETATION We demonstrate the utility of supervised ML driven identification of the genes associated with persistent MODS. Pending validation in enriched cohorts with a high burden of organ dysfunction, such an approach may inform targeted delivery of interventions among at-risk patients. FUNDING H.R.W.'s NIHR35GM126943 award supported the work detailed in this manuscript. Upon his death, the award was transferred to M.N.A. M.R.A., N.S.P, and R.K were supported by NIHR21GM151703. R.K. was supported by R01GM139967.
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Affiliation(s)
- Mihir R Atreya
- Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center and Cincinnati Children's Research Foundation, Cincinnati, 45229, OH, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45267, USA.
| | - Shayantan Banerjee
- Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, 600 036, India
| | - Andrew J Lautz
- Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center and Cincinnati Children's Research Foundation, Cincinnati, 45229, OH, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45267, USA
| | - Matthew N Alder
- Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center and Cincinnati Children's Research Foundation, Cincinnati, 45229, OH, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45267, USA
| | - Brian M Varisco
- Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center and Cincinnati Children's Research Foundation, Cincinnati, 45229, OH, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45267, USA
| | - Hector R Wong
- Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center and Cincinnati Children's Research Foundation, Cincinnati, 45229, OH, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45267, USA
| | - Jennifer A Muszynski
- Division of Critical Care Medicine, Nationwide Children's Hospital, Columbus, 43205, OH, USA; Department of Pediatrics, Ohio State University, Columbus, 43205, OH, USA
| | - Mark W Hall
- Division of Critical Care Medicine, Nationwide Children's Hospital, Columbus, 43205, OH, USA; Department of Pediatrics, Ohio State University, Columbus, 43205, OH, USA
| | - L Nelson Sanchez-Pinto
- Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, 60611, IL, USA; Department of Health and Biomedical Informatics, Northwestern University Feinberg School of Medicine, Chicago, 60611, IL, USA
| | - Rishikesan Kamaleswaran
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, 30322, GA, United States; Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, 30322, GA, United States
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15
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Yang JO, Zinter MS, Pellegrini M, Wong MY, Gala K, Markovic D, Nadel B, Peng K, Do N, Mangul S, Nadkarni VM, Karlsberg A, Deshpande D, Butte MJ, Asaro L, Agus M, Sapru A. Whole blood transcriptomics identifies subclasses of pediatric septic shock. Crit Care 2023; 27:486. [PMID: 38066613 PMCID: PMC10709863 DOI: 10.1186/s13054-023-04689-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 10/14/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Sepsis is a highly heterogeneous syndrome, which has hindered the development of effective therapies. This has prompted investigators to develop a precision medicine approach aimed at identifying biologically homogenous subgroups of patients with septic shock and critical illnesses. Transcriptomic analysis can identify subclasses derived from differences in underlying pathophysiological processes that may provide the basis for new targeted therapies. The goal of this study was to elucidate pathophysiological pathways and identify pediatric septic shock subclasses based on whole blood RNA expression profiles. METHODS The subjects were critically ill children with cardiopulmonary failure who were a part of a prospective randomized insulin titration trial to treat hyperglycemia. Genome-wide expression profiling was conducted using RNA sequencing from whole blood samples obtained from 46 children with septic shock and 52 mechanically ventilated noninfected controls without shock. Patients with septic shock were allocated to subclasses based on hierarchical clustering of gene expression profiles, and we then compared clinical characteristics, plasma inflammatory markers, cell compositions using GEDIT, and immune repertoires using Imrep between the two subclasses. RESULTS Patients with septic shock depicted alterations in innate and adaptive immune pathways. Among patients with septic shock, we identified two subtypes based on gene expression patterns. Compared with Subclass 2, Subclass 1 was characterized by upregulation of innate immunity pathways and downregulation of adaptive immunity pathways. Subclass 1 had significantly worse clinical outcomes despite the two classes having similar illness severity on initial clinical presentation. Subclass 1 had elevated levels of plasma inflammatory cytokines and endothelial injury biomarkers and demonstrated decreased percentages of CD4 T cells and B cells and less diverse T cell receptor repertoires. CONCLUSIONS Two subclasses of pediatric septic shock patients were discovered through genome-wide expression profiling based on whole blood RNA sequencing with major biological and clinical differences. Trial Registration This is a secondary analysis of data generated as part of the observational CAF-PINT ancillary of the HALF-PINT study (NCT01565941). Registered March 29, 2012.
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Affiliation(s)
- Jamie O Yang
- UCLA Department of Internal Medicine, David Geffen School of Medicine, Los Angeles, CA, USA
| | - Matt S Zinter
- UCSF Department of Pediatrics, San Francisco, CA, USA
| | - Matteo Pellegrini
- UCLA Department of Molecular, Cell, and Developmental Biology, Los Angeles, CA, USA
| | - Man Yee Wong
- Division of Pediatric Critical Care, UCLA Department of Pediatrics, UCLA Mattel Children's Hospital, Los Angeles, CA, USA
| | - Kinisha Gala
- Division of Pediatric Critical Care, UCLA Department of Pediatrics, UCLA Mattel Children's Hospital, Los Angeles, CA, USA
| | - Daniela Markovic
- UCLA Department of Medicine Statistics Core, Los Angeles, CA, USA
| | - Brian Nadel
- USC Department of Clinical Pharmacy, USC Alfred E Mann School of Pharmacy and Pharmaceutical Sciences, Los Angeles, CA, USA
| | - Kerui Peng
- USC Department of Clinical Pharmacy, USC Alfred E Mann School of Pharmacy and Pharmaceutical Sciences, Los Angeles, CA, USA
| | - Nguyen Do
- Division of Pediatric Critical Care, UCLA Department of Pediatrics, UCLA Mattel Children's Hospital, Los Angeles, CA, USA
| | - Serghei Mangul
- USC Department of Clinical Pharmacy, USC Alfred E Mann School of Pharmacy and Pharmaceutical Sciences, Los Angeles, CA, USA
- Department of Quantitative and Computational Biology, USC Dornsife College of Letters, Arts and Sciences, Los Angeles, CA, USA
| | - Vinay M Nadkarni
- Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Aaron Karlsberg
- USC Department of Clinical Pharmacy, USC Alfred E Mann School of Pharmacy and Pharmaceutical Sciences, Los Angeles, CA, USA
| | - Dhrithi Deshpande
- USC Department of Clinical Pharmacy, USC Alfred E Mann School of Pharmacy and Pharmaceutical Sciences, Los Angeles, CA, USA
| | - Manish J Butte
- Division of Immunology, Allergy, and Rheumatology, UCLA Department of Pediatrics, Los Angeles, CA, USA
| | - Lisa Asaro
- Department of Pediatrics, Division of Medical Critical Care, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michael Agus
- Department of Pediatrics, Division of Medical Critical Care, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Anil Sapru
- Division of Pediatric Critical Care, UCLA Department of Pediatrics, UCLA Mattel Children's Hospital, Los Angeles, CA, USA.
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16
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Bode C, Weis S, Sauer A, Wendel-Garcia P, David S. Targeting the host response in sepsis: current approaches and future evidence. Crit Care 2023; 27:478. [PMID: 38057824 PMCID: PMC10698949 DOI: 10.1186/s13054-023-04762-6] [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: 09/13/2023] [Accepted: 11/28/2023] [Indexed: 12/08/2023] Open
Abstract
Sepsis, a dysregulated host response to infection characterized by organ failure, is one of the leading causes of death worldwide. Disbalances of the immune response play an important role in its pathophysiology. Patients may develop simultaneously or concomitantly states of systemic or local hyperinflammation and immunosuppression. Although a variety of effective immunomodulatory treatments are generally available, attempts to inhibit or stimulate the immune system in sepsis have failed so far to improve patients' outcome. The underlying reason is likely multifaceted including failure to identify responders to a specific immune intervention and the complex pathophysiology of organ dysfunction that is not exclusively caused by immunopathology but also includes dysfunction of the coagulation system, parenchymal organs, and the endothelium. Increasing evidence suggests that stratification of the heterogeneous population of septic patients with consideration of their host response might led to treatments that are more effective. The purpose of this review is to provide an overview of current studies aimed at optimizing the many facets of host response and to discuss future perspectives for precision medicine approaches in sepsis.
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Affiliation(s)
- Christian Bode
- Department of Anesthesiology and Intensive Care Medicine, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.
| | - Sebastian Weis
- Institute for Infectious Disease and Infection Control, University Hospital Jena, Friedrich-Schiller University Jena, Jena, Germany
- Department of Anesthesiology and Intensive Care Medicine, University Hospital Jena, Friedrich-Schiller University Jena, Jena, Germany
- Leibniz Institute for Natural Product Research and Infection Biology, Hans-Knöll Institute-HKI, Jena, Germany
| | - Andrea Sauer
- Department of Anesthesiology and Intensive Care Medicine, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Pedro Wendel-Garcia
- Institute of Intensive Care Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Sascha David
- Institute of Intensive Care Medicine, University Hospital Zurich, Zurich, Switzerland
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17
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Atreya MR, Huang M, Moore AR, Zheng H, Hasin-Brumshtein Y, Fitzgerald JC, Weiss SL, Cvijanovich NZ, Bigham MT, Jain PN, Schwarz AJ, Lutfi R, Nowak J, Thomas NJ, Quasney M, Dahmer MK, Baines T, Haileselassie B, Lautz AJ, Stanski NL, Standage SW, Kaplan JM, Zingarelli B, Sweeney TE, Khatri P, Sanchez-Pinto LN, Kamaleswaran R. Derivation, validation, and transcriptomic assessment of pediatric septic shock phenotypes identified through latent profile analyses: Results from a prospective multi-center observational cohort. RESEARCH SQUARE 2023:rs.3.rs-3692289. [PMID: 38105983 PMCID: PMC10723552 DOI: 10.21203/rs.3.rs-3692289/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Background Sepsis poses a grave threat, especially among children, but treatments are limited due to clinical and biological heterogeneity among patients. Thus, there is an urgent need for precise subclassification of patients to guide therapeutic interventions. Methods We used clinical, laboratory, and biomarker data from a prospective multi-center pediatric septic shock cohort to derive phenotypes using latent profile analyses. Thereafter, we trained a support vector machine model to assign phenotypes in a hold-out validation set. We tested interactions between phenotypes and common sepsis therapies on clinical outcomes and conducted transcriptomic analyses to better understand the phenotype-specific biology. Finally, we compared whether newly identified phenotypes overlapped with established gene-expression endotypes and tested the utility of an integrated subclassification scheme. Findings Among 1,071 patients included, we identified two phenotypes which we named 'inflamed' (19.5%) and an 'uninflamed' phenotype (80.5%). The 'inflamed' phenotype had an over 4-fold risk of 28-day mortality relative to those 'uninflamed'. Transcriptomic analysis revealed overexpression of genes implicated in the innate immune response and suggested an overabundance of developing neutrophils, pro-T/NK cells, and NK cells among those 'inflamed'. There was no significant overlap between endotypes and phenotypes. However, an integrated subclassification scheme demonstrated varying survival probabilities when comparing endophenotypes. Interpretation Our research underscores the reproducibility of latent profile analyses to identify clinical and biologically informative pediatric septic shock phenotypes with high prognostic relevance. Pending validation, an integrated subclassification scheme, reflective of the different facets of the host response, holds promise to inform targeted intervention among those critically ill.
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Affiliation(s)
- Mihir R Atreya
- Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45627, USA
| | - Min Huang
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, USA
| | - Andrew R Moore
- Stanford Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA
| | - Hong Zheng
- Stanford Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA
- Center for Biomedical Informatics Research, Department of Medicine, Stanford University School of Medicine, Stanford, 94305, CA
| | | | | | - Scott L Weiss
- Nemours Children's Health, Wilmington, DE, 19803, USA
| | | | | | - Parag N Jain
- Texas Children's Hospital, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Adam J Schwarz
- Children's Hospital of Orange County, Orange, CA, 92868, USA
| | - Riad Lutfi
- Riley Hospital for Children, Indianapolis, IN, 46202, USA
| | - Jeffrey Nowak
- Children's Hospital and Clinics of Minnesota, Minneapolis, MN, 55404, USA
| | - Neal J Thomas
- Penn State Hershey Children's Hospital, Hershey, PA, 17033, USA
| | - Michael Quasney
- C.S Mott Children's Hospital, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Mary K Dahmer
- C.S Mott Children's Hospital, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Torrey Baines
- University of Florida Health Shands Children's Hospital, Gainesville, FL, 32610, USA
| | | | - Andrew J Lautz
- Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45627, USA
| | - Natalja L Stanski
- Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45627, USA
| | - Stephen W Standage
- Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45627, USA
| | - Jennifer M Kaplan
- Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45627, USA
| | - Basilia Zingarelli
- Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45627, USA
| | | | - Purvesh Khatri
- Stanford Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA
- Center for Biomedical Informatics Research, Department of Medicine, Stanford University School of Medicine, Stanford, 94305, CA
| | - L Nelson Sanchez-Pinto
- Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, 60611, IL, USA
- Department of Health and Biomedical Informatics, Northwestern University Feinberg School of Medicine, Chicago, 60611, IL, USA
| | - Rishikesan Kamaleswaran
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, 30322, GA, USA
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, 30322, GA, USA
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18
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Liu Z, Qiu E, Yang B, Zeng Y. Uncovering hub genes in sepsis through bioinformatics analysis. Medicine (Baltimore) 2023; 102:e36237. [PMID: 38050254 PMCID: PMC10695588 DOI: 10.1097/md.0000000000036237] [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: 07/07/2023] [Accepted: 10/31/2023] [Indexed: 12/06/2023] Open
Abstract
In-depth studies on the mechanisms of pathogenesis of sepsis and diagnostic biomarkers in the early stages may be the key to developing individualized and effective treatment strategies. This study aimed to identify sepsis-related hub genes and evaluate their diagnostic reliability. The gene expression profiles of GSE4607 and GSE131761 were obtained from the Gene Expression Omnibus. Differentially co-expressed genes between the sepsis and control groups were screened. Single-sample gene set enrichment analysis and gene set variation analysis were performed to investigate the biological functions of the hub genes. A receiver operating characteristic curve was used to evaluate diagnostic value. Datasets GSE154918 and GSE185263 were used as external validation datasets to verify the reliability of the hub genes. Four differentially co-expressed genes, FAM89A, FFAR3, G0S2, and FGF13, were extracted using a weighted gene co-expression network analysis and differential gene expression analysis methods. These 4 genes were upregulated in the sepsis group and were distinct from those in the controls. Moreover, the receiver operating characteristic curves of the 4 genes exhibited considerable diagnostic value in discriminating septic blood samples from those of the non-septic control group. The reliability and consistency of these 4 genes were externally validated. Single-sample gene set enrichment analysis and gene set variation analysis analyses indicated that the 4 hub genes were significantly correlated with the regulation of immunity and metabolism in sepsis. The identified FAM89A, FFAR3, G0S2, and FGF13 genes may help elucidate the molecular mechanisms underlying sepsis and drive the introduction of new biomarkers to advance diagnosis and treatment.
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Affiliation(s)
- Zhao Liu
- Department of Critical Care Medicine, Zhuzhou Central Hospital, Zhuzhou, China
| | - Eryue Qiu
- Department of Trauma Center, Zhuzhou Central Hospital, Zhuzhou, China
| | - Bihui Yang
- Department of Hematology, Zhuzhou Central Hospital, Zhuzhou, China
| | - Yiqian Zeng
- Department of Trauma Center, Zhuzhou Central Hospital, Zhuzhou, China
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19
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Wheelwright J, Halstead ES, Knehans A, Bonavia AS. Ex Vivo Endotoxin Stimulation of Blood for Predicting Survival in Patients With Sepsis: A Systematic Review. CHEST CRITICAL CARE 2023; 1:100029. [PMID: 38148988 PMCID: PMC10751038 DOI: 10.1016/j.chstcc.2023.100029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/28/2023]
Abstract
BACKGROUND Sepsis is a syndrome characterized by host immune dysfunction, with the extent of immunoparalysis differing among patients. Lipopolysaccharide (LPS) is used commonly to assess the immune function of critically ill patients with sepsis. However, the reliability of this ex vivo diagnostic test in predicting clinical outcomes remains uncertain. RESEARCH QUESTION Does LPS-induced tumor necrosis factor (TNF) production from the blood of patients with sepsis predict mortality? Secondary outcomes included ICU and hospital stay durations, nosocomial infection rate, and organ recovery rate. STUDY DESIGN AND METHODS Human sepsis studies from various databases through April 2023 were evaluated. Inclusion criteria encompassed LPS-stimulated blood assays, English language, and reported clinical outcomes. Bias risk was evaluated using the Newcastle-Ottawa scale (NOS). Relationships between TNF production and mortality were analyzed at sepsis onset and during established sepsis, alongside secondary outcomes. RESULTS Of 11,580 studies, 17 studies (14 adult and three pediatric) were selected for analysis. Although 15 studies were evaluated as moderate to high quality using the NOS, it is important to note that some of these studies also had identifiable biases, such as unclear methods of participant recruitment. Nine studies detailed survival outcomes associated with LPS-induced TNF production at sepsis onset, whereas five studies explored TNF production's relationship with mortality during established sepsis. Trends suggested that lower LPS-induced TNF production correlated with higher mortality. However, heterogeneity in methodologies, especially the LPS assay protocol, hindered definitive conclusions. Publication bias was highlighted using funnel plot analysis. Concerning secondary outcomes, diminished TNF production might signify worsening organ dysfunction, although the link between cytokine production and nosocomial infection varied among studies. INTERPRETATION For functional immune profiling in sepsis, streamlined research methodologies are essential. This entails organizing cohorts based on microbial sources of sepsis, establishing standardized definitions of immunoparalysis, using consistent types and dosages of immune stimulants, adhering to uniform blood incubation conditions, and adopting consistent clinical outcomes.
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Affiliation(s)
- Jonathan Wheelwright
- Division of Critical Care Medicine (J. W. and A. S. B.), Department of Anesthesiology and Perioperative Medicine, the Division of Critical Care (E. S. H.), Department of Pediatrics, Penn State Health, and the Penn State College of Medicine (A. K.), Hershey, PA
| | - E Scott Halstead
- Division of Critical Care Medicine (J. W. and A. S. B.), Department of Anesthesiology and Perioperative Medicine, the Division of Critical Care (E. S. H.), Department of Pediatrics, Penn State Health, and the Penn State College of Medicine (A. K.), Hershey, PA
| | - Amy Knehans
- Division of Critical Care Medicine (J. W. and A. S. B.), Department of Anesthesiology and Perioperative Medicine, the Division of Critical Care (E. S. H.), Department of Pediatrics, Penn State Health, and the Penn State College of Medicine (A. K.), Hershey, PA
| | - Anthony S Bonavia
- Division of Critical Care Medicine (J. W. and A. S. B.), Department of Anesthesiology and Perioperative Medicine, the Division of Critical Care (E. S. H.), Department of Pediatrics, Penn State Health, and the Penn State College of Medicine (A. K.), Hershey, PA
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20
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Wang W, Wang H, Sun T. N 6-methyladenosine modification: Regulatory mechanisms and therapeutic potential in sepsis. Biomed Pharmacother 2023; 168:115719. [PMID: 37839108 DOI: 10.1016/j.biopha.2023.115719] [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: 09/01/2023] [Revised: 10/10/2023] [Accepted: 10/11/2023] [Indexed: 10/17/2023] Open
Abstract
Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection and is characterized by multiple biological and clinical features. N6-methyladenosine (m6A) modification is the most common type of RNA modifications in eukaryotes and plays an important regulatory role in various biological processes. Recently, m6A modification has been found to be involved in the regulation of immune responses in sepsis. In addition, several studies have shown that m6A modification is involved in sepsis-induced multiple organ dysfunctions, including cardiovascular dysfunction, acute lung injury (ALI), acute kidney injury (AKI) and etc. Considering the complex pathogenesis of sepsis and the lack of specific therapeutic drugs, m6A modification may be the important bond in the pathophysiological process of sepsis and even therapeutic targets. This review systematically highlights the recent advances regarding the roles of m6A modification in sepsis and sheds light on their use as treatment targets for sepsis.
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Affiliation(s)
- Wei Wang
- Department of Pediatrics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, China
| | - Huaili Wang
- Department of Pediatrics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, China.
| | - Tongwen Sun
- General ICU, The First Affiliated Hospital of Zhengzhou University, Henan Key Laboratory of Critical Care Medicine, Zhengzhou Key Laboratory of Sepsis, Henan Engineering Research Center for Critical Care Medicine, Zhengzhou, Henan, China.
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21
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Moreira AG, Arora T, Arya S, Winter C, Valadie CT, Kwinta P. Leveraging transcriptomics to develop bronchopulmonary dysplasia endotypes: a concept paper. Respir Res 2023; 24:284. [PMID: 37968635 PMCID: PMC10648631 DOI: 10.1186/s12931-023-02596-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Accepted: 11/07/2023] [Indexed: 11/17/2023] Open
Abstract
IMPACT Bronchopulmonary dysplasia has multiple definitions that are currently based on phenotypic characteristics. Using an unsupervised machine learning approach, we created BPD subclasses (e.g., endotypes) by clustering whole microarray data. T helper 17 cell differentiation was the most significant pathway differentiating the BPD endotypes. INTRODUCTION Bronchopulmonary dysplasia (BPD) is the most common complication of extreme prematurity. Discovery of BPD endotypes in an unbiased format, derived from the peripheral blood transcriptome, may uncover patterns underpinning this complex lung disease. METHODS An unsupervised agglomerative hierarchical clustering approach applied to genome-wide expression of profiling from 62 children at day of life five was used to identify BPD endotypes. To identify which genes were differentially expressed across the BPD endotypes, we formulated a linear model based on least-squares minimization with empirical Bayes statistics. RESULTS Four BPD endotypes (A, B,C,D) were identified using 7,319 differentially expressed genes. Across BPD endotypes, 5,850 genes had a p value < 0.05 after multiple comparison testing. Endotype A consisted of neonates with a higher gestational age and birthweight. Endotypes B-D included neonates between 25 and 26 weeks and a birthweight range of 640 to 940 g. Endotype D appeared to have a protective role against BPD compared to Endotypes B and C (36% vs. 62% vs. 60%, respectively). The most significant pathway focused on T helper 17 cell differentiation. CONCLUSION Bioinformatic analyses can help identify BPD endotypes that associate with clinical definitions of BPD.
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Affiliation(s)
- Alvaro G Moreira
- Department of Pediatrics, Division of Neonatology, University of Texas Health San Antonio, San Antonio, TX, USA.
| | - Tanima Arora
- Department of Pediatrics, Division of Neonatology, University of Texas Health San Antonio, San Antonio, TX, USA
| | - Shreyas Arya
- Division of Neonatology, Dayton Children's Hospital, Cincinnati, OH, USA
| | - Caitlyn Winter
- Department of Pediatrics, Division of Neonatology, University of Texas Health San Antonio, San Antonio, TX, USA
| | - Charles T Valadie
- Department of Pediatrics, Division of Neonatology, University of Texas Health San Antonio, San Antonio, TX, USA
| | - Przemko Kwinta
- Neonatal Intensive Care Unit, Department of Pediatrics, Jagiellonian University Medical College, Kraków, Poland
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22
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Sinha P, Kerchberger VE, Willmore A, Chambers J, Zhuo H, Abbott J, Jones C, Wickersham N, Wu N, Neyton L, Langelier CR, Mick E, He J, Jauregui A, Churpek MM, Gomez AD, Hendrickson CM, Kangelaris KN, Sarma A, Leligdowicz A, Delucchi KL, Liu KD, Russell JA, Matthay MA, Walley KR, Ware LB, Calfee CS. Identifying molecular phenotypes in sepsis: an analysis of two prospective observational cohorts and secondary analysis of two randomised controlled trials. THE LANCET. RESPIRATORY MEDICINE 2023; 11:965-974. [PMID: 37633303 PMCID: PMC10841178 DOI: 10.1016/s2213-2600(23)00237-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 06/17/2023] [Accepted: 06/20/2023] [Indexed: 08/28/2023]
Abstract
BACKGROUND In sepsis and acute respiratory distress syndrome (ARDS), heterogeneity has contributed to difficulty identifying effective pharmacotherapies. In ARDS, two molecular phenotypes (hypoinflammatory and hyperinflammatory) have consistently been identified, with divergent outcomes and treatment responses. In this study, we sought to derive molecular phenotypes in critically ill adults with sepsis, determine their overlap with previous ARDS phenotypes, and evaluate whether they respond differently to treatment in completed sepsis trials. METHODS We used clinical data and plasma biomarkers from two prospective sepsis cohorts, the Validating Acute Lung Injury biomarkers for Diagnosis (VALID) study (N=1140) and the Early Assessment of Renal and Lung Injury (EARLI) study (N=818), in latent class analysis (LCA) to identify the optimal number of classes in each cohort independently. We used validated models trained to classify ARDS phenotypes to evaluate concordance of sepsis and ARDS phenotypes. We applied these models retrospectively to the previously published Prospective Recombinant Human Activated Protein C Worldwide Evaluation in Severe Sepsis and Septic Shock (PROWESS-SHOCK) trial and Vasopressin and Septic Shock Trial (VASST) to assign phenotypes and evaluate heterogeneity of treatment effect. FINDINGS A two-class model best fit both VALID and EARLI (p<0·0001). In VALID, 804 (70·5%) of the 1140 patients were classified as hypoinflammatory and 336 (29·5%) as hyperinflammatory; in EARLI, 530 (64·8%) of 818 were hypoinflammatory and 288 (35·2%) hyperinflammatory. We observed higher plasma pro-inflammatory cytokines, more vasopressor use, more bacteraemia, lower protein C, and higher mortality in the hyperinflammatory than in the hypoinflammatory phenotype (p<0·0001 for all). Classifier models indicated strong concordance between sepsis phenotypes and previously identified ARDS phenotypes (area under the curve 0·87-0·96, depending on the model). Findings were similar excluding participants with both sepsis and ARDS. In PROWESS-SHOCK, 1142 (68·0%) of 1680 patients had the hypoinflammatory phenotype and 538 (32·0%) had the hyperinflammatory phenotype, and response to activated protein C differed by phenotype (p=0·0043). In VASST, phenotype proportions were similar to other cohorts; however, no treatment interaction with the type of vasopressor was observed (p=0·72). INTERPRETATION Molecular phenotypes previously identified in ARDS are also identifiable in multiple sepsis cohorts and respond differently to activated protein C. Molecular phenotypes could represent a treatable trait in critical illness beyond the patient's syndromic diagnosis. FUNDING US National Institutes of Health.
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Affiliation(s)
- Pratik Sinha
- Division of Clinical and Translational Research, Division of Critical Care, Department of Anesthesiology, Washington University School of Medicine, Saint Louis, MO, USA.
| | - V Eric Kerchberger
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Andrew Willmore
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Julia Chambers
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Hanjing Zhuo
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Jason Abbott
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Chayse Jones
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Nancy Wickersham
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nelson Wu
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Lucile Neyton
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Charles R Langelier
- Division of Infectious Diseases, Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Eran Mick
- Division of Infectious Diseases, Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - June He
- Division of Clinical and Translational Research, Division of Critical Care, Department of Anesthesiology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Alejandra Jauregui
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Matthew M Churpek
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Antonio D Gomez
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA, USA
| | | | - Kirsten N Kangelaris
- Division of Hospital Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Aartik Sarma
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Aleksandra Leligdowicz
- Department of Medicine, Division of Critical Care Medicine, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Kevin L Delucchi
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA
| | - Kathleen D Liu
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Division of Nephrology, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - James A Russell
- Division of Critical Care Medicine, St Paul's Hospital, University of British Columbia, Vancouver, BC, Canada; Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, Canada
| | - Michael A Matthay
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Department of Anesthesia, University of California San Francisco, San Francisco, CA, USA
| | - Keith R Walley
- Division of Critical Care Medicine, St Paul's Hospital, University of British Columbia, Vancouver, BC, Canada; Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, Canada
| | - Lorraine B Ware
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Carolyn S Calfee
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Department of Anesthesia, University of California San Francisco, San Francisco, CA, USA
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23
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Zhang WY, Chen ZH, An XX, Li H, Zhang HL, Wu SJ, Guo YQ, Zhang K, Zeng CL, Fang XM. Analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in pediatric sepsis by integrating bioinformatics and machine learning. World J Pediatr 2023; 19:1094-1103. [PMID: 37115484 PMCID: PMC10533616 DOI: 10.1007/s12519-023-00717-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 03/10/2023] [Indexed: 04/29/2023]
Abstract
BACKGROUND Pediatric sepsis is a complicated condition characterized by life-threatening organ failure resulting from a dysregulated host response to infection in children. It is associated with high rates of morbidity and mortality, and rapid detection and administration of antimicrobials have been emphasized. The objective of this study was to evaluate the diagnostic biomarkers of pediatric sepsis and the function of immune cell infiltration in the development of this illness. METHODS Three gene expression datasets were available from the Gene Expression Omnibus collection. First, the differentially expressed genes (DEGs) were found with the use of the R program, and then gene set enrichment analysis was carried out. Subsequently, the DEGs were combined with the major module genes chosen using the weighted gene co-expression network. The hub genes were identified by the use of three machine-learning algorithms: random forest, support vector machine-recursive feature elimination, and least absolute shrinkage and selection operator. The receiver operating characteristic curve and nomogram model were used to verify the discrimination and efficacy of the hub genes. In addition, the inflammatory and immune status of pediatric sepsis was assessed using cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT). The relationship between the diagnostic markers and infiltrating immune cells was further studied. RESULTS Overall, after overlapping key module genes and DEGs, we detected 402 overlapping genes. As pediatric sepsis diagnostic indicators, CYSTM1 (AUC = 0.988), MMP8 (AUC = 0.973), and CD177 (AUC = 0.986) were investigated and demonstrated statistically significant differences (P < 0.05) and diagnostic efficacy in the validation set. As indicated by the immune cell infiltration analysis, multiple immune cells may be involved in the development of pediatric sepsis. Additionally, all diagnostic characteristics may correlate with immune cells to varying degrees. CONCLUSIONS The candidate hub genes (CD177, CYSTM1, and MMP8) were identified, and the nomogram was constructed for pediatric sepsis diagnosis. Our study could provide potential peripheral blood diagnostic candidate genes for pediatric sepsis patients.
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Affiliation(s)
- Wen-Yuan Zhang
- Department of Anesthesiology and Intensive Care, School of Medicine, The First Affiliated Hospital, Zhejiang University, QingChun Road 79, Hangzhou, 310003, China
| | - Zhong-Hua Chen
- Department of Anesthesiology and Intensive Care, School of Medicine, The First Affiliated Hospital, Zhejiang University, QingChun Road 79, Hangzhou, 310003, China
- Department of Anesthesiology, Shaoxing People's Hospital (Shaoxing Hospital, Zhejiang University School of Medicine), Shaoxing, 312000, China
| | | | - Hui Li
- Department of Anesthesiology and Intensive Care, School of Medicine, The First Affiliated Hospital, Zhejiang University, QingChun Road 79, Hangzhou, 310003, China
| | - Hua-Lin Zhang
- Department of Anesthesiology and Intensive Care, School of Medicine, The First Affiliated Hospital, Zhejiang University, QingChun Road 79, Hangzhou, 310003, China
| | - Shui-Jing Wu
- Department of Anesthesiology and Intensive Care, School of Medicine, The First Affiliated Hospital, Zhejiang University, QingChun Road 79, Hangzhou, 310003, China
| | - Yu-Qian Guo
- Department of Anesthesiology and Intensive Care, School of Medicine, The First Affiliated Hospital, Zhejiang University, QingChun Road 79, Hangzhou, 310003, China
| | - Kai Zhang
- Department of Anesthesiology and Intensive Care, School of Medicine, The First Affiliated Hospital, Zhejiang University, QingChun Road 79, Hangzhou, 310003, China
| | - Cong-Li Zeng
- Department of Anesthesiology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Xiang-Ming Fang
- Department of Anesthesiology and Intensive Care, School of Medicine, The First Affiliated Hospital, Zhejiang University, QingChun Road 79, Hangzhou, 310003, China.
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24
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Sanchez-Pinto LN, Bhavani SV, Atreya MR, Sinha P. Leveraging Data Science and Novel Technologies to Develop and Implement Precision Medicine Strategies in Critical Care. Crit Care Clin 2023; 39:627-646. [PMID: 37704331 DOI: 10.1016/j.ccc.2023.03.002] [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] [Indexed: 09/15/2023]
Abstract
Precision medicine aims to identify treatments that are most likely to result in favorable outcomes for subgroups of patients with similar clinical and biological characteristics. The gaps for the development and implementation of precision medicine strategies in the critical care setting are many, but the advent of data science and multi-omics approaches, combined with the rich data ecosystem in the intensive care unit, offer unprecedented opportunities to realize the promise of precision critical care. In this article, the authors review the data-driven and technology-based approaches being leveraged to discover and implement precision medicine strategies in the critical care setting.
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Affiliation(s)
- Lazaro N Sanchez-Pinto
- Department of Pediatrics, Northwestern University Feinberg School of Medicine, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA; Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA.
| | | | - Mihir R Atreya
- Division of Critical Care Medicine, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, 3333 Burnet Avenue, Cincinnati, OH 45229, USA
| | - Pratik Sinha
- Division of Clinical and Translational Research, Department of Anesthesia, Washington University School of Medicine, 1 Barnes Jewish Hospital Plaza, St. Louis, MO 63110, USA; Division of Critical Care, Department of Anesthesia, Washington University School of Medicine, 1 Barnes Jewish Hospital Plaza, St. Louis, MO 63110, USA
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25
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Abstract
BACKGROUND Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection, with extremely high mortality. Notably, sepsis is a heterogeneous syndrome characterized by a vast, multidimensional array of clinical and biologic features, which has hindered advances in the therapeutic field beyond the current standards. DATA SOURCES We used PubMed to search the subject-related medical literature by searching for the following single and/or combination keywords: sepsis, heterogeneity, personalized treatment, host response, infection, epidemiology, mortality, incidence, age, children, sex, comorbidities, gene susceptibility, infection sites, bacteria, fungi, virus, host response, organ dysfunction and management. RESULTS We found that host factors (age, biological sex, comorbidities, and genetics), infection etiology, host response dysregulation and multiple organ dysfunctions can all result in different disease manifestations, progression, and response to treatment, which make it difficult to effectively treat and manage sepsis patients. CONCLUSIONS Herein, we have summarized contributing factors to sepsis heterogeneity, including host factors, infection etiology, host response dysregulation, and multiple organ dysfunctions, from the key elements of pathogenesis of sepsis. An in-depth understanding of the factors that contribute to the heterogeneity of sepsis will help clinicians understand the complexity of sepsis and enable researchers to conduct more personalized clinical studies for homogenous patients.
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Affiliation(s)
- Wei Wang
- Department of Pediatrics, ShengJing Hospital of China Medical University, No. 36, SanHao Street, Shenyang City, Liaoning Province, 110004, China
| | - Chun-Feng Liu
- Department of Pediatrics, ShengJing Hospital of China Medical University, No. 36, SanHao Street, Shenyang City, Liaoning Province, 110004, China.
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26
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Wang H, Huang J, Guo C, Wu J, Zhang L, Ren X, Gan L. Molecular subtypes based on N6-methyladenosine RNA methylation demonstrate the heterogeneity of immune and biological functions in pediatric septic shock. Heliyon 2023; 9:e20714. [PMID: 37842565 PMCID: PMC10568115 DOI: 10.1016/j.heliyon.2023.e20714] [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] [Received: 05/05/2023] [Revised: 09/17/2023] [Accepted: 10/04/2023] [Indexed: 10/17/2023] Open
Abstract
Introduction Septic shock in children is a highly heterogeneous syndrome involving different immune states and biological processes. We used a bioinformatics approach to explore the relationship between N6-methyladenosine (m6A) methylation and septic shock in children. Methods A gene expression dataset including information on 98 children with septic shock was selected. To construct and evaluate a risk prediction model, machine learning was used to screen marker m6A regulators. Based on differentially expressed m6A regulators, molecular subtypes for paediatric septic shock were constructed. Subsequently, the differences in the m6Ascore, heterogeneity of immune cell infiltration, and heterogeneity of biological functions between the different subtypes were analyzed. Finally, real-time quantitative PCR (RT-qPCR) was performed to validate the expression of the marker m6A regulators. Results Fifteen differentially expressed m6A regulators were identified. Six marker m6A regulators, including LRPPRC, ELAVL1, RBM15, CBLL1, FTO, and RBM15B, were screened using the random forest method. The risk prediction model for paediatric septic shock constructed using m6A markers had strong consistency and high clinical practicability. Two subtypes of paediatric septic shock have been identified based on the differential expression pattern of m6A regulators. Significant differences were observed in RNA epigenetics, immune statuses, and biological processes between the two m6A subtypes. Differentially expressed genes between the two subtypes were enriched in cell number homeostasis, redox responses, and innate immune system responses. Finally, the six marker m6A regulators were verified in additional samples. Conclusions Based on the heterogeneity of m6A methylation-regulated genes, two different subtypes of septic shock in children with different RNA epigenetics, immune statuses, and biological processes were identified, revealing the heterogeneity of the disease largely attributable to differential m6A methylation. The findings will help explore and establish appropriate individualized treatments.
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Affiliation(s)
- Huabin Wang
- Department of Neonatal Intensive Care Unit, Affiliated Hospital of Jining Medical University, Jining Medical University, Jining 272000, China
- Postdoctoral Mobile Station of Shandong University of Traditional Chinese Medicine, Jinan 250000, China
- Department of Pediatrics, Affiliated Hospital of Jining Medical University, Jining Medical University, Jining 272000, China
| | - Junbin Huang
- Division of Hematology/Oncology, Department of Pediatrics, the Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, 518107, China
| | - Cheng Guo
- Department of Neonatal Intensive Care Unit, Affiliated Hospital of Jining Medical University, Jining Medical University, Jining 272000, China
- Department of Pediatrics, Affiliated Hospital of Jining Medical University, Jining Medical University, Jining 272000, China
| | - Jingfang Wu
- Department of Pediatrics, Affiliated Hospital of Jining Medical University, Jining Medical University, Jining 272000, China
- Department of Pediatric Intensive Care Unit, Affiliated Hospital of Jining Medical University, Jining Medical University, Jining 272000, China
| | - Liyuan Zhang
- Department of Pediatrics, Affiliated Hospital of Jining Medical University, Jining Medical University, Jining 272000, China
- Department of Pediatric Intensive Care Unit, Affiliated Hospital of Jining Medical University, Jining Medical University, Jining 272000, China
| | - Xueyun Ren
- Department of Neonatal Intensive Care Unit, Affiliated Hospital of Jining Medical University, Jining Medical University, Jining 272000, China
- Department of Pediatrics, Affiliated Hospital of Jining Medical University, Jining Medical University, Jining 272000, China
| | - Lijun Gan
- Department of Cardiology, Affiliated Hospital of Jining Medical University, Jining Medical University, Jining 272000, China
- Jining Key Laboratory for Diagnosis and Treatment of Cardiovascular Diseases, Jining 272000, China
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Yang JO, Zinter MS, Pellegrini M, Wong MY, Gala K, Markovic D, Nadel B, Peng K, Do N, Mangul S, Nadkarni VM, Karlsberg A, Deshpande D, Butte MJ, Asaro L, Agus M, Sapru A. Whole Blood Transcriptomics Identifies Subclasses of Pediatric Septic Shock. RESEARCH SQUARE 2023:rs.3.rs-3267057. [PMID: 37693502 PMCID: PMC10491329 DOI: 10.21203/rs.3.rs-3267057/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Background Sepsis is a highly heterogeneous syndrome, that has hindered the development of effective therapies. This has prompted investigators to develop a precision medicine approach aimed at identifying biologically homogenous subgroups of patients with septic shock and critical illnesses. Transcriptomic analysis can identify subclasses derived from differences in underlying pathophysiological processes that may provide the basis for new targeted therapies. The goal of this study was to elucidate pathophysiological pathways and identify pediatric septic shock subclasses based on whole blood RNA expression profiles. Methods The subjects were critically ill children with cardiopulmonary failure who were a part of a prospective randomized insulin titration trial to treat hyperglycemia. Genome-wide expression profiling was conducted using RNA-sequencing from whole blood samples obtained from 46 children with septic shock and 52 mechanically ventilated noninfected controls without shock. Patients with septic shock were allocated to subclasses based on hierarchical clustering of gene expression profiles, and we then compared clinical characteristics, plasma inflammatory markers, cell compositions using GEDIT, and immune repertoires using Imrep between the two subclasses. Results Patients with septic shock depicted alterations in innate and adaptive immune pathways. Among patients with septic shock, we identified two subtypes based on gene expression patterns. Compared with Subclass 2, Subclass 1 was characterized by upregulation of innate immunity pathways and downregulation of adaptive immunity pathways. Subclass 1 had significantly worse clinical outcomes despite the two classes having similar illness severity on initial clinical presentation. Subclass 1 had elevated levels of plasma inflammatory cytokines and endothelial injury biomarkers and demonstrated decreased percentages of CD4 T cells and B cells, and less diverse T-Cell receptor repertoires. Conclusions Two subclasses of pediatric septic shock patients were discovered through genome-wide expression profiling based on whole blood RNA sequencing with major biological and clinical differences. Trial Registration This is a secondary analysis of data generated as part of the observational CAF PINT ancillary of the HALF PINT study (NCT01565941). Registered 29 March 2012.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Nguyen Do
- University of California, Los Angeles
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28
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de Almeida RJ, de Lima Hirata AH, de Jesus Rocha LA, de Arruda Motta MD, Varela P, Martins L, Pesquero JB, Camacho CP. Similar hypothyroid and sepsis circulating mRNA expression could be useful as a biomarker in onthyroidal illness syndrome: a pilot study. ARCHIVES OF ENDOCRINOLOGY AND METABOLISM 2023; 67:e000625. [PMID: 37249456 PMCID: PMC10665055 DOI: 10.20945/2359-3997000000625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 12/20/2022] [Indexed: 05/31/2023]
Abstract
Objective Based on hypothetical hypothyroidism and nonthyroidal illness syndrome (NTIS) gene expression similarities, we decided to compare the patterns of expression of both as models of NTIS. The concordant profile between them may enlighten new biomarkers for NTIS challenging scenarios. Materials and methods We used Ion Proton System next-generation sequencing to build the hypothyroidism transcriptome. We selected two databanks in GEO2 platform datasets to find the differentially expressed genes (DEGs) in adults and children with sepsis. The ROC curve was constructed to calculate the area under the curve (AUC). The AUC, chi-square, sensitivity, specificity, accuracy, kappa and likelihood were calculated. We performed Cox regression and Kaplan-Meier analyses for the survival analysis. Results Concerning hypothyroidism DEGs, 70.42% were shared with sepsis survivors and 61.94% with sepsis nonsurvivors. Some of them were mitochondrial gene types (mitGenes), and 95 and 88 were related to sepsis survivors and nonsurvivors, respectively. BLOC1S1, ROMO1, SLIRP and TIMM8B mitGenes showed the capability to distinguish sepsis survivors and nonsurvivors. Conclusion We matched our hypothyroidism DEGs with those in adults and children with sepsis. Additionally, we observed different patterns of hypothyroid-related genes among sepsis survivors and nonsurvivors. Finally, we demonstrated that ROMO1, SLIRP and TIMM8B could be predictive biomarkers in children´s sepsis.
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Affiliation(s)
- Robson José de Almeida
- Laboratório de Inovação Molecular e Biotecnologia, Programa de Pós-graduação em Medicina, Universidade Nove de Julho (Uninove), São Paulo, SP, Brasil
| | - Andréa Harumy de Lima Hirata
- Laboratório de Inovação Molecular e Biotecnologia, Programa de Pós-graduação em Medicina, Universidade Nove de Julho (Uninove), São Paulo, SP, Brasil
| | - Luiz Antônio de Jesus Rocha
- Laboratório de Inovação Molecular e Biotecnologia, Programa de Pós-graduação em Medicina, Universidade Nove de Julho (Uninove), São Paulo, SP, Brasil
- Centro e Laboratório de Doenças da Tireoide de Endocrinologia Molecular e Translacional, Divisão de Endocrinologia, Departamento de Medicina, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, SP, Brasil
| | - Miriam Duarte de Arruda Motta
- Laboratório de Inovação Molecular e Biotecnologia, Programa de Pós-graduação em Medicina, Universidade Nove de Julho (Uninove), São Paulo, SP, Brasil
| | - Patricia Varela
- McKusick-Nathans Institute of Genetic Medicine - Johns Hopkins University School of Medicine, Baltimore, MD
- Centro de Pesquisa e Diagnóstico Molecular de Doenças Genéticas, Departamento de Biofísica, Universidade Federal de São Paulo, São Paulo, SP, Brasil
| | - Leonardo Martins
- Centro de Pesquisa e Diagnóstico Molecular de Doenças Genéticas, Departamento de Biofísica, Universidade Federal de São Paulo, São Paulo, SP, Brasil
| | - João Bosco Pesquero
- Centro de Pesquisa e Diagnóstico Molecular de Doenças Genéticas, Departamento de Biofísica, Universidade Federal de São Paulo, São Paulo, SP, Brasil
| | - Cléber P Camacho
- Laboratório de Inovação Molecular e Biotecnologia, Programa de Pós-graduação em Medicina, Universidade Nove de Julho (Uninove), São Paulo, SP, Brasil
- Centro e Laboratório de Doenças da Tireoide de Endocrinologia Molecular e Translacional, Divisão de Endocrinologia, Departamento de Medicina, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, SP, Brasil,
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29
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Garduno A, Cusack R, Leone M, Einav S, Martin-Loeches I. Multi-Omics Endotypes in ICU Sepsis-Induced Immunosuppression. Microorganisms 2023; 11:1119. [PMID: 37317092 DOI: 10.3390/microorganisms11051119] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Revised: 04/03/2023] [Accepted: 04/21/2023] [Indexed: 06/16/2023] Open
Abstract
It is evident that the admission of some patients with sepsis and septic shock to hospitals is occurring late in their illness, which has contributed to the increase in poor outcomes and high fatalities worldwide across age groups. The current diagnostic and monitoring procedure relies on an inaccurate and often delayed identification by the clinician, who then decides the treatment upon interaction with the patient. Initiation of sepsis is accompanied by immune system paralysis following "cytokine storm". The unique immunological response of each patient is important to define in terms of subtyping for therapy. The immune system becomes activated in sepsis to produce interleukins, and endothelial cells express higher levels of adhesion molecules. The proportions of circulating immune cells change, reducing regulatory cells and increasing memory cells and killer cells, having long-term effects on the phenotype of CD8 T cells, HLA-DR, and dysregulation of microRNA. The current narrative review seeks to highlight the potential application of multi-omics data integration and immunological profiling at the single-cell level to define endotypes in sepsis and septic shock. The review will consider the parallels and immunoregulatory axis between cancer and immunosuppression, sepsis-induced cardiomyopathy, and endothelial damage. Second, the added value of transcriptomic-driven endotypes will be assessed through inferring regulatory interactions in recent clinical trials and studies reporting gene modular features that inform continuous metrics measuring clinical response in ICU, which can support the use of immunomodulating agents.
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Affiliation(s)
- Alexis Garduno
- Department of Clinical Medicine, Trinity College, University of Dublin, D02 PN40 Dublin, Ireland
| | - Rachael Cusack
- Department of Intensive Care Medicine, St. James's Hospital, James's Street, D08 NHY1 Dublin, Ireland
| | - Marc Leone
- Department of Anesthesia, Intensive Care and Trauma Center, Nord University Hospital, Aix Marseille University, APHM, 13015 Marseille, France
| | - Sharon Einav
- General Intensive Care Unit, Shaare Zedek Medical Center, Jerusalem 23456, Israel
- Faculty of Medicine, Hebrew University, Jerusalem 23456, Israel
| | - Ignacio Martin-Loeches
- Department of Clinical Medicine, Trinity College, University of Dublin, D02 PN40 Dublin, Ireland
- Department of Intensive Care Medicine, St. James's Hospital, James's Street, D08 NHY1 Dublin, Ireland
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Kwok AJ, Allcock A, Ferreira RC, Cano-Gamez E, Smee M, Burnham KL, Zurke YX, McKechnie S, Mentzer AJ, Monaco C, Udalova IA, Hinds CJ, Todd JA, Davenport EE, Knight JC. Neutrophils and emergency granulopoiesis drive immune suppression and an extreme response endotype during sepsis. Nat Immunol 2023; 24:767-779. [PMID: 37095375 DOI: 10.1038/s41590-023-01490-5] [Citation(s) in RCA: 58] [Impact Index Per Article: 58.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Accepted: 03/13/2023] [Indexed: 04/26/2023]
Abstract
Sepsis arises from diverse and incompletely understood dysregulated host response processes following infection that leads to life-threatening organ dysfunction. Here we showed that neutrophils and emergency granulopoiesis drove a maladaptive response during sepsis. We generated a whole-blood single-cell multiomic atlas (272,993 cells, n = 39 individuals) of the sepsis immune response that identified populations of immunosuppressive mature and immature neutrophils. In co-culture, CD66b+ sepsis neutrophils inhibited proliferation and activation of CD4+ T cells. Single-cell multiomic mapping of circulating hematopoietic stem and progenitor cells (HSPCs) (29,366 cells, n = 27) indicated altered granulopoiesis in patients with sepsis. These features were enriched in a patient subset with poor outcome and a specific sepsis response signature that displayed higher frequencies of IL1R2+ immature neutrophils, epigenetic and transcriptomic signatures of emergency granulopoiesis in HSPCs and STAT3-mediated gene regulation across different infectious etiologies and syndromes. Our findings offer potential therapeutic targets and opportunities for stratified medicine in severe infection.
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Affiliation(s)
- Andrew J Kwok
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Alice Allcock
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Ricardo C Ferreira
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Eddie Cano-Gamez
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Madeleine Smee
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Katie L Burnham
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | | | - Stuart McKechnie
- John Radcliffe Hospital, Oxford Universities Hospitals NHS Foundation Trust, Oxford, UK
| | - Alexander J Mentzer
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- John Radcliffe Hospital, Oxford Universities Hospitals NHS Foundation Trust, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Claudia Monaco
- Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK
| | - Irina A Udalova
- Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK
| | - Charles J Hinds
- William Harvey Research Institute, Faculty of Medicine and Dentistry, Queen Mary University, London, UK
| | - John A Todd
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Emma E Davenport
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Julian C Knight
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- John Radcliffe Hospital, Oxford Universities Hospitals NHS Foundation Trust, Oxford, UK.
- NIHR Oxford Biomedical Research Centre, Oxford, UK.
- Chinese Academy of Medical Science Oxford Institute, University of Oxford, Oxford, UK.
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31
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Bongers KS, Chanderraj R, Woods RJ, McDonald RA, Adame MD, Falkowski NR, Brown CA, Baker JM, Winner KM, Fergle DJ, Hinkle KJ, Standke AK, Vendrov KC, Young VB, Stringer KA, Sjoding MW, Dickson RP. The Gut Microbiome Modulates Body Temperature Both in Sepsis and Health. Am J Respir Crit Care Med 2023; 207:1030-1041. [PMID: 36378114 PMCID: PMC10112447 DOI: 10.1164/rccm.202201-0161oc] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Accepted: 11/15/2022] [Indexed: 11/16/2022] Open
Abstract
Rationale: Among patients with sepsis, variation in temperature trajectories predicts clinical outcomes. In healthy individuals, normal body temperature is variable and has decreased consistently since the 1860s. The biologic underpinnings of this temperature variation in disease and health are unknown. Objectives: To establish and interrogate the role of the gut microbiome in calibrating body temperature. Methods: We performed a series of translational analyses and experiments to determine whether and how variation in gut microbiota explains variation in body temperature in sepsis and in health. We studied patient temperature trajectories using electronic medical record data. We characterized gut microbiota in hospitalized patients using 16S ribosomal RNA gene sequencing. We modeled sepsis using intraperitoneal LPS in mice and modulated the microbiome using antibiotics, germ-free, and gnotobiotic animals. Measurements and Main Results: Consistent with prior work, we identified four temperature trajectories in patients hospitalized with sepsis that predicted clinical outcomes. In a separate cohort of 116 hospitalized patients, we found that the composition of patients' gut microbiota at admission predicted their temperature trajectories. Compared with conventional mice, germ-free mice had reduced temperature loss during experimental sepsis. Among conventional mice, heterogeneity of temperature response in sepsis was strongly explained by variation in gut microbiota. Healthy germ-free and antibiotic-treated mice both had lower basal body temperatures compared with control animals. The Lachnospiraceae family was consistently associated with temperature trajectories in hospitalized patients, experimental sepsis, and antibiotic-treated mice. Conclusions: The gut microbiome is a key modulator of body temperature variation in both health and critical illness and is thus a major, understudied target for modulating physiologic heterogeneity in sepsis.
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Affiliation(s)
| | - Rishi Chanderraj
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan Health System, Ann Arbor, Michigan
- Medicine Service, Infectious Diseases Section, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, Michigan
| | - Robert J. Woods
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan Health System, Ann Arbor, Michigan
- Medicine Service, Infectious Diseases Section, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, Michigan
- Center for Computational Medicine and Bioinformatics and
| | | | - Mark D. Adame
- Division of Pulmonary and Critical Care Medicine and
| | | | - Christopher A. Brown
- Division of Pulmonary and Critical Care Medicine and
- Institute for Research on Innovation and Science, Institute for Social Research
| | - Jennifer M. Baker
- Division of Pulmonary and Critical Care Medicine and
- Department of Microbiology and Immunology, Medical School
| | - Katherine M. Winner
- Division of Pulmonary and Critical Care Medicine and
- Department of Microbiology and Immunology, Medical School
| | | | | | - Alexandra K. Standke
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan Health System, Ann Arbor, Michigan
| | - Kimberly C. Vendrov
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan Health System, Ann Arbor, Michigan
| | - Vincent B. Young
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan Health System, Ann Arbor, Michigan
- Department of Microbiology and Immunology, Medical School
| | - Kathleen A. Stringer
- Division of Pulmonary and Critical Care Medicine and
- Department of Clinical Pharmacy, College of Pharmacy, and
- Weil Institute for Critical Care Research & Innovation, Ann Arbor, Michigan
| | - Michael W. Sjoding
- Division of Pulmonary and Critical Care Medicine and
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, Michigan; and
- Weil Institute for Critical Care Research & Innovation, Ann Arbor, Michigan
| | - Robert P. Dickson
- Division of Pulmonary and Critical Care Medicine and
- Department of Microbiology and Immunology, Medical School
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, Michigan; and
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32
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Dahmer M, Jennings A, Parker M, Sanchez-Pinto LN, Thompson A, Traube C, Zimmerman JJ. Pediatric Critical Care in the Twenty-first Century and Beyond. Crit Care Clin 2023; 39:407-425. [PMID: 36898782 DOI: 10.1016/j.ccc.2022.09.013] [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: 11/16/2022]
Abstract
Pediatric critical care addresses prevention, diagnosis, and treatment of organ dysfunction in the setting of increasingly complex patients, therapies, and environments. Soon burgeoning data science will enable all aspects of intensive care: driving facilitated diagnostics, empowering a learning health-care environment, promoting continuous advancement of care, and informing the continuum of critical care outside the intensive care unit preceding and following critical illness/injury. Although novel technology will progressively objectify personalized critical care, humanism, practiced at the bedside, defines the essence of pediatric critical care now and in the future.
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Affiliation(s)
- Mary Dahmer
- Division of Critical Care, Department of Pediatrics, University of Michigan, 1500 East Medical Center Drive, F6790/5243, Ann Arbor, MI, USA
| | - Aimee Jennings
- Division of Critical Care Medicine, Advanced Practice, FA.2.112, Seattle Children's Hospital, 4800 Sandpoint Way Northeast, Seattle, WA 98105, USA
| | - Margaret Parker
- Department of Pediatrics, Stony Brook University, 7762 Bloomfield Road, Easton, MD 21601, USA
| | - Lazaro N Sanchez-Pinto
- Department of Pediatrics, Ann and Robert H Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, 225 East Chicago Avenue, Box 73, Chicago, IL 60611-2605, USA
| | - Ann Thompson
- Department of Critical Care Medicine, University of Pittsburgh, 3550 Terrace Street, Pittsburgh, PA 15261, USA
| | - Chani Traube
- Department of Pediatrics, Weill Cornell Medicine, 525 East 68th Street, Box 225, New York, NY 10065, USA
| | - Jerry J Zimmerman
- Department of Pediatrics, FA.2.300B Seattle Children's Hospital, 4800 Sandpoint Way Northeast, Seattle, WA 98105, USA; Pediatric Critical Care Medicine, Seattle Children's Hospital, Harborview Medical Center, University of Washington, School of Medicine, FA.2.300B, Seattle Children's Hospital, 4800 Sand Point Way Northeast, Seattle, WA 98105, USA.
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Parra-Llorca A, Pinilla-Gonzlez A, Torrejón-Rodríguez L, Lara-Cantón I, Kuligowski J, Collado MC, Gormaz M, Aguar M, Vento M, Serna E, Cernada M. Effects of Sepsis on Immune Response, Microbiome and Oxidative Metabolism in Preterm Infants. CHILDREN (BASEL, SWITZERLAND) 2023; 10:children10030602. [PMID: 36980160 PMCID: PMC10046958 DOI: 10.3390/children10030602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 03/03/2023] [Accepted: 03/16/2023] [Indexed: 03/30/2023]
Abstract
This is a narrative review about the mechanisms involved in bacterial sepsis in preterm infants, which is an illness with a high incidence, morbidity, and mortality. The role of the innate immune response and its relationship with oxidative stress in the pathogenesis are described as well as their potential implementation as early biomarkers. Moreover, we address the impact that all the mechanisms triggered by sepsis have on the dysbiosis and the changes on neonatal microbiota.
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Affiliation(s)
- Anna Parra-Llorca
- Division of Neonatology, University and Polytechnic Hospital La Fe (HULAFE), 46026 Valencia, Spain
- Neonatal Research Group, Health Research Institute La Fe (IISLAFE), 46026 Valencia, Spain
| | - Alejandro Pinilla-Gonzlez
- Division of Neonatology, University and Polytechnic Hospital La Fe (HULAFE), 46026 Valencia, Spain
- Neonatal Research Group, Health Research Institute La Fe (IISLAFE), 46026 Valencia, Spain
| | - Laura Torrejón-Rodríguez
- Division of Neonatology, University and Polytechnic Hospital La Fe (HULAFE), 46026 Valencia, Spain
- Neonatal Research Group, Health Research Institute La Fe (IISLAFE), 46026 Valencia, Spain
| | - Inmaculada Lara-Cantón
- Division of Neonatology, University and Polytechnic Hospital La Fe (HULAFE), 46026 Valencia, Spain
- Neonatal Research Group, Health Research Institute La Fe (IISLAFE), 46026 Valencia, Spain
| | - Julia Kuligowski
- Neonatal Research Group, Health Research Institute La Fe (IISLAFE), 46026 Valencia, Spain
| | - María Carmen Collado
- Department of Biotechnology, Institute of Agrochemistry and Food Technology, National Research Council (IATA-CSIC), 46980 Valencia, Spain
| | - María Gormaz
- Division of Neonatology, University and Polytechnic Hospital La Fe (HULAFE), 46026 Valencia, Spain
- Neonatal Research Group, Health Research Institute La Fe (IISLAFE), 46026 Valencia, Spain
| | - Marta Aguar
- Division of Neonatology, University and Polytechnic Hospital La Fe (HULAFE), 46026 Valencia, Spain
- Neonatal Research Group, Health Research Institute La Fe (IISLAFE), 46026 Valencia, Spain
| | - Máximo Vento
- Division of Neonatology, University and Polytechnic Hospital La Fe (HULAFE), 46026 Valencia, Spain
- Neonatal Research Group, Health Research Institute La Fe (IISLAFE), 46026 Valencia, Spain
| | - Eva Serna
- Department of Physiology, University of Valencia, 46010 Valencia, Spain
| | - María Cernada
- Division of Neonatology, University and Polytechnic Hospital La Fe (HULAFE), 46026 Valencia, Spain
- Neonatal Research Group, Health Research Institute La Fe (IISLAFE), 46026 Valencia, Spain
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Tsakiroglou M, Evans A, Pirmohamed M. Leveraging transcriptomics for precision diagnosis: Lessons learned from cancer and sepsis. Front Genet 2023; 14:1100352. [PMID: 36968610 PMCID: PMC10036914 DOI: 10.3389/fgene.2023.1100352] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 02/20/2023] [Indexed: 03/12/2023] Open
Abstract
Diagnostics require precision and predictive ability to be clinically useful. Integration of multi-omic with clinical data is crucial to our understanding of disease pathogenesis and diagnosis. However, interpretation of overwhelming amounts of information at the individual level requires sophisticated computational tools for extraction of clinically meaningful outputs. Moreover, evolution of technical and analytical methods often outpaces standardisation strategies. RNA is the most dynamic component of all -omics technologies carrying an abundance of regulatory information that is least harnessed for use in clinical diagnostics. Gene expression-based tests capture genetic and non-genetic heterogeneity and have been implemented in certain diseases. For example patients with early breast cancer are spared toxic unnecessary treatments with scores based on the expression of a set of genes (e.g., Oncotype DX). The ability of transcriptomics to portray the transcriptional status at a moment in time has also been used in diagnosis of dynamic diseases such as sepsis. Gene expression profiles identify endotypes in sepsis patients with prognostic value and a potential to discriminate between viral and bacterial infection. The application of transcriptomics for patient stratification in clinical environments and clinical trials thus holds promise. In this review, we discuss the current clinical application in the fields of cancer and infection. We use these paradigms to highlight the impediments in identifying useful diagnostic and prognostic biomarkers and propose approaches to overcome them and aid efforts towards clinical implementation.
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Affiliation(s)
- Maria Tsakiroglou
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
- *Correspondence: Maria Tsakiroglou,
| | - Anthony Evans
- Computational Biology Facility, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
| | - Munir Pirmohamed
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
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35
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Affiliation(s)
- Jerry J Zimmerman
- Pediatric Critical Care Medicine, Seattle Children's Hospital, Harborview Medical Center, Department of Pediatrics, University of Washington, School of Medicine, Seattle, WA
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Babu S, Sreedhar R, Munaf M, Gadhinglajkar SV. Sepsis in the Pediatric Cardiac Intensive Care Unit: An Updated Review. J Cardiothorac Vasc Anesth 2023; 37:1000-1012. [PMID: 36922317 DOI: 10.1053/j.jvca.2023.02.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Revised: 01/25/2023] [Accepted: 02/06/2023] [Indexed: 02/13/2023]
Abstract
Sepsis remains among the most common causes of mortality in children with congenital heart disease (CHD). Extensive literature is available regarding managing sepsis in pediatric patients without CHD. Because the cardiovascular pathophysiology of children with CHD differs entirely from their typical peers, the available diagnosis and management recommendations for sepsis cannot be implemented directly in children with CHD. This review discusses the risk factors, etiopathogenesis, available diagnostic tools, resuscitation protocols, and anesthetic management of pediatric patients suffering from various congenital cardiac lesions. Further research should focus on establishing a standard guideline for managing children with CHD with sepsis and septic shock admitted to the intensive care unit.
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Affiliation(s)
- Saravana Babu
- Division of Cardiothoracic and Vascular Anesthesia, Sree Chitra Tirunal institute for medical sciences and technology, Trivandrum, India.
| | - Rupa Sreedhar
- Division of Cardiothoracic and Vascular Anesthesia, Sree Chitra Tirunal institute for medical sciences and technology, Trivandrum, India
| | - Mamatha Munaf
- Division of Cardiothoracic and Vascular Anesthesia, Sree Chitra Tirunal institute for medical sciences and technology, Trivandrum, India
| | - Shrinivas V Gadhinglajkar
- Division of Cardiothoracic and Vascular Anesthesia, Sree Chitra Tirunal institute for medical sciences and technology, Trivandrum, India
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Kneyber MCJ, Khemani RG, Bhalla A, Blokpoel RGT, Cruces P, Dahmer MK, Emeriaud G, Grunwell J, Ilia S, Katira BH, Lopez-Fernandez YM, Rajapreyar P, Sanchez-Pinto LN, Rimensberger PC. Understanding clinical and biological heterogeneity to advance precision medicine in paediatric acute respiratory distress syndrome. THE LANCET. RESPIRATORY MEDICINE 2023; 11:197-212. [PMID: 36566767 PMCID: PMC10880453 DOI: 10.1016/s2213-2600(22)00483-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 10/14/2022] [Accepted: 11/15/2022] [Indexed: 12/24/2022]
Abstract
Paediatric acute respiratory distress syndrome (PARDS) is a heterogeneous clinical syndrome that is associated with high rates of mortality and long-term morbidity. Factors that distinguish PARDS from adult acute respiratory distress syndrome (ARDS) include changes in developmental stage and lung maturation with age, precipitating factors, and comorbidities. No specific treatment is available for PARDS and management is largely supportive, but methods to identify patients who would benefit from specific ventilation strategies or ancillary treatments, such as prone positioning, are needed. Understanding of the clinical and biological heterogeneity of PARDS, and of differences in clinical features and clinical course, pathobiology, response to treatment, and outcomes between PARDS and adult ARDS, will be key to the development of novel preventive and therapeutic strategies and a precision medicine approach to care. Studies in which clinical, biomarker, and transcriptomic data, as well as informatics, are used to unpack the biological and phenotypic heterogeneity of PARDS, and implementation of methods to better identify patients with PARDS, including methods to rapidly identify subphenotypes and endotypes at the point of care, will drive progress on the path to precision medicine.
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Affiliation(s)
- Martin C J Kneyber
- Department of Paediatrics, Division of Paediatric Critical Care Medicine, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Groningen, Netherlands; Critical Care, Anaesthesiology, Peri-operative and Emergency Medicine, University of Groningen, Groningen, Netherlands.
| | - Robinder G Khemani
- Department of Anesthesiology and Critical Care Medicine, Children's Hospital Los Angeles, Los Angeles, CA, USA; Department of Paediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Anoopindar Bhalla
- Department of Anesthesiology and Critical Care Medicine, Children's Hospital Los Angeles, Los Angeles, CA, USA; Department of Paediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Robert G T Blokpoel
- Department of Paediatrics, Division of Paediatric Critical Care Medicine, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Pablo Cruces
- Facultad de Ciencias de la Vida, Universidad Andres Bello, Santiago, Chile
| | - Mary K Dahmer
- Department of Pediatrics, Division of Critical Care, University of Michigan, Ann Arbor, MI, USA
| | - Guillaume Emeriaud
- Department of Pediatrics, CHU Sainte Justine, Université de Montréal, Montreal, QC, Canada
| | - Jocelyn Grunwell
- Department of Pediatrics, Division of Critical Care, Emory University, Atlanta, GA, USA
| | - Stavroula Ilia
- Pediatric Intensive Care Unit, University Hospital, School of Medicine, University of Crete, Heraklion, Crete, Greece
| | - Bhushan H Katira
- Department of Pediatrics, Division of Critical Care Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Yolanda M Lopez-Fernandez
- Pediatric Intensive Care Unit, Department of Pediatrics, Cruces University Hospital, Biocruces-Bizkaia Health Research Institute, Bizkaia, Spain
| | - Prakadeshwari Rajapreyar
- Department of Pediatrics (Critical Care), Medical College of Wisconsin and Children's Wisconsin, Milwaukee, WI, USA
| | - L Nelson Sanchez-Pinto
- Department of Pediatrics (Critical Care), Northwestern University Feinberg School of Medicine and Ann & Robert H Lurie Children's Hospital of Chicago, Chicago, IL, USA
| | - Peter C Rimensberger
- Division of Neonatology and Paediatric Intensive Care, Department of Paediatrics, University Hospital of Geneva, University of Geneva, Geneva, Switzerland
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Qin Y, Caldino Bohn RI, Sriram A, Kernan KF, Carcillo JA, Kim S, Park HJ. Refining empiric subgroups of pediatric sepsis using machine-learning techniques on observational data. Front Pediatr 2023; 11:1035576. [PMID: 36793336 PMCID: PMC9923004 DOI: 10.3389/fped.2023.1035576] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 01/05/2023] [Indexed: 01/31/2023] Open
Abstract
Sepsis contributes to 1 of every 5 deaths globally with 3 million per year occurring in children. To improve clinical outcomes in pediatric sepsis, it is critical to avoid "one-size-fits-all" approaches and to employ a precision medicine approach. To advance a precision medicine approach to pediatric sepsis treatments, this review provides a summary of two phenotyping strategies, empiric and machine-learning-based phenotyping based on multifaceted data underlying the complex pediatric sepsis pathobiology. Although empiric and machine-learning-based phenotypes help clinicians accelerate the diagnosis and treatments, neither empiric nor machine-learning-based phenotypes fully encapsulate all aspects of pediatric sepsis heterogeneity. To facilitate accurate delineations of pediatric sepsis phenotypes for precision medicine approach, methodological steps and challenges are further highlighted.
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Affiliation(s)
- Yidi Qin
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States
| | - Rebecca I. Caldino Bohn
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States
| | - Aditya Sriram
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States
| | - Kate F. Kernan
- Division of Pediatric Critical Care Medicine, Department of Critical Care Medicine, UPMC Children’s Hospital of Pittsburgh, Pittsburgh, PA, United States
| | - Joseph A. Carcillo
- Division of Pediatric Critical Care Medicine, Department of Critical Care Medicine, UPMC Children’s Hospital of Pittsburgh, Pittsburgh, PA, United States
| | - Soyeon Kim
- Division of Pediatric Pulmonary Medicine, UPMC Children’s Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Pediatrics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Hyun Jung Park
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States
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Abstract
Heterogeneity in sepsis and acute respiratory distress syndrome (ARDS) is increasingly being recognized as one of the principal barriers to finding efficacious targeted therapies. The advent of multiple high-throughput biological data ("omics"), coupled with the widespread access to increased computational power, has led to the emergence of phenotyping in critical care. Phenotyping aims to use a multitude of data to identify homogenous subgroups within an otherwise heterogenous population. Increasingly, phenotyping schemas are being applied to sepsis and ARDS to increase understanding of these clinical conditions and identify potential therapies. Here we present a selective review of the biological phenotyping schemas applied to sepsis and ARDS. Further, we outline some of the challenges involved in translating these conceptual findings to bedside clinical decision-making tools.
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Affiliation(s)
- Pratik Sinha
- Division of Clinical & Translational Research and Division of Critical Care, Department of Anesthesia, Washington University, St. Louis, Missouri, USA;
| | - Nuala J Meyer
- Division of Pulmonary, Allergy, and Critical Care Medicine; Center for Translational Lung Biology; and Lung Biology Institute, University of Pennsylvania Perelman School of Medicine; Philadelphia, Pennsylvania, USA
| | - Carolyn S Calfee
- Division of Pulmonary, Critical Care, Allergy & Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, California, USA
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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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Fiorino C, Liu Y, Henao R, Ko ER, Burke TW, Ginsburg GS, McClain MT, Woods CW, Tsalik EL. Host Gene Expression to Predict Sepsis Progression. Crit Care Med 2022; 50:1748-1756. [PMID: 36178298 PMCID: PMC9671818 DOI: 10.1097/ccm.0000000000005675] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
OBJECTIVES Sepsis causes significant mortality. However, most patients who die of sepsis do not present with severe infection, hampering efforts to deliver early, aggressive therapy. It is also known that the host gene expression response to infection precedes clinical illness. This study seeks to develop transcriptomic models to predict progression to sepsis or shock within 72 hours of hospitalization and to validate previously identified transcriptomic signatures in the prediction of 28-day mortality. DESIGN Retrospective differential gene expression analysis and predictive modeling using RNA sequencing data. PATIENTS Two hundred seventy-seven patients enrolled at four large academic medical centers; all with clinically adjudicated infection were considered for inclusion in this study. MEASUREMENTS AND MAIN RESULTS Sepsis progression was defined as an increase in Sepsis 3 category within 72 hours. Transcriptomic data were generated using RNAseq of whole blood. Least absolute shrinkage and selection operator modeling was used to identify predictive signatures for various measures of disease progression. Four previously identified gene signatures were tested for their ability to predict 28-day mortality. There were no significant differentially expressed genes in 136 subjects with worsened Sepsis 3 category compared with 141 nonprogressor controls. There were 1,178 differentially expressed genes identified when sepsis progression was defined as ICU admission or 28-day mortality. A model based on these genes predicted progression with an area under the curve of 0.71. Validation of previously identified gene signatures to predict sepsis mortality revealed area under the receiver operating characteristic values of 0.70-0.75 and no significant difference between signatures. CONCLUSIONS Host gene expression was unable to predict sepsis progression when defined by an increase in Sepsis-3 category, suggesting this definition is not a useful framework for transcriptomic prediction methods. However, there was a differential response when progression was defined as ICU admission or death. Validation of previously described signatures predicted 28-day mortality with insufficient accuracy to offer meaningful clinical utility.
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Affiliation(s)
- Cassandra Fiorino
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Yiling Liu
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Ricardo Henao
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA
| | - Emily R. Ko
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
- Duke Regional Hospital, Durham, NC, USA
| | - Thomas W. Burke
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Geoffrey S. Ginsburg
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Micah T. McClain
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
- Medical Service, Durham Veterans Affairs Health Care System, Durham, NC, USA
| | - Christopher W. Woods
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
- Medical Service, Durham Veterans Affairs Health Care System, Durham, NC, USA
| | - Ephraim L. Tsalik
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
- Emergency Medicine Service, Durham Veterans Affairs Health Care System, Durham, NC, USA
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
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42
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Assessment of Infection Progression per Host Gene Expression. Crit Care Med 2022; 50:1834-1837. [PMID: 36394402 DOI: 10.1097/ccm.0000000000005677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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43
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Identification of novel potential molecular targets associated with pediatric septic shock by integrated bioinformatics analysis and validation of in vitro septic shock model. JOURNAL OF SURGERY AND MEDICINE 2022. [DOI: 10.28982/josam.7461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Background/Aim: Sepsis is a major cause of morbidity, mortality, and healthcare utilization among children all over the world. Sepsis, characterized as life-threatening organ failure, results from a dysregulated host response to infection. When combined with critically low blood pressure, it causes septic shock, resulting in high mortality rates. The aim of this study was to perform a bioinformatic analysis of gene expression profiles to predict septic shock risk.
Methods: Four datasets related to pediatric septic shock were retrieved from the Gene Expression Omnibus (GEO) database for a total of 240 patients and 83 controls. GEO2R tools based on R were used to find differentially expressed genes (DEGs). The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used to examine the functional enrichment of DEGs. STRING was used to create a protein–protein interaction (PPI) network. After separately analyzing the four datasets, commonly affected genes were removed using the Venny program. Finally, human umbilical vein endothelial cells (HUVECs) were stimulated with supernatants of lipopolysaccharide (LPS)-stimulated RAW267.4 macrophage cells and expression of selected genes was confirmed by real-time reverse-transcriptase polymerase chain reaction (qRT-PCR) and used to construct an in vitro septic shock model.
Results: Seven-hundred seventy-one common differentially expressed genes in the four groups were found. Of these, 433 genes showed increased expression, while 338 had reduced expression. In the DAVID analysis results, DEGs up-regulated according to gene ontology results were enriched in the regulation of innate and adaptive immune responses, complement receptor-mediated signaling, and cytokine secretion processes. Down-regulated DEGs were significantly enriched in the regulation of immune response, T-cell activation, antigen processing, and presentation and integral component of plasma membrane processes. According to The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), Cystoscape Molecular Complex Detection (MCODE), nine down-regulated genes in the center of the PPI network, ZAP70, ITK, LAT, PRKCQ, LCK, IL2RB, FYN, CD8A, CD247 and four up-regulated genes, MMP9, TIMP1, LCN2, HGF, were associated with septic shock. Expressions of FYN and MMP9 genes in the in vitro septic shock model were consistent with the bioinformatic results.
Conclusion: Comparative bioinformatics analysis of data from four different septic shock studies was performed. As a result, molecular processes and important signal networks and 13 genes that we think will play a role in the development and risk prediction of septic shock are proposed.
Methods: Four datasets related to Pediatric septic shock were retrieved from the Gene Expression Omnibus (GEO) database for a total of 240 patients and 83 controls. GEO2R tools based on R were used to find differentially expressed genes (DEGs). DAVID was used to examine the functional enrichment of DEGs. STRING was used to create a protein-protein interaction (PPI) network. After separately analyzing the four datasets, commonly affected genes were removed using the Venny program. Finally, HUVECs were stimulated with supernatants of LPS-stimulated RAW267.4 macrophage cells and expression of selected genes was confirmed by qRT-PCR, constructing an in vitro septic shock model.
Results: There were 771 common differentially expressed genes in the 4 groups. Of these, 433 genes showed increased expression, while 338 had reducing expression. In the DAVID analysis results, DEGs upregulated by gene ontology were enriched in the regulation of innate and adaptive immune responses, complement receptor-mediated signaling, and cytokine secretion processes. Downregulated DEGs are significantly enriched in the regulation of immune response, T cell activation, antigen processing, and presentation and integral component of plasma membrane processes. According to STRING, cystoscape MCODE, and cytohubba analysis, 9 downregulated genes in the center of the PPI network, ZAP70, ITK, LAT, PRKCQ, LCK, IL2RB, FYN, CD8A, CD247, and 4 upregulated genes, MMP9, TIMP1, LCN2, HGF, were associated with septic shock. Expressions of FYN and MMP9 genes in the in vitro septic shock model were consistent with bioinformatic results.
Conclusion: Important signaling networks and 13 genes potentially indicating molecular processes for the incidence, development, and risk prediction in septic shock were found using bioinformatic analysis of gene expression profiles.
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Zhou W, Zhang C, Zhuang Z, Zhang J, Zhong C. Identification of two robust subclasses of sepsis with both prognostic and therapeutic values based on machine learning analysis. Front Immunol 2022; 13:1040286. [PMID: 36505503 PMCID: PMC9732458 DOI: 10.3389/fimmu.2022.1040286] [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] [Received: 09/09/2022] [Accepted: 11/07/2022] [Indexed: 11/27/2022] Open
Abstract
Background Sepsis is a heterogeneous syndrome with high morbidity and mortality. Optimal and effective classifications are in urgent need and to be developed. Methods and results A total of 1,936 patients (sepsis samples, n=1,692; normal samples, n=244) in 7 discovery datasets were included to conduct weighted gene co-expression network analysis (WGCNA) to filter out candidate genes related to sepsis. Then, two subtypes of sepsis were classified in the training sepsis set (n=1,692), the Adaptive and Inflammatory, using K-means clustering analysis on 90 sepsis-related features. We validated these subtypes using 617 samples in 5 independent datasets and the merged 5 sets. Cibersort method revealed the Adaptive subtype was related to high infiltration levels of T cells and natural killer (NK) cells and a better clinical outcome. Immune features were validated by single-cell RNA sequencing (scRNA-seq) analysis. The Inflammatory subtype was associated with high infiltration of macrophages and a disadvantageous prognosis. Based on functional analysis, upregulation of the Toll-like receptor signaling pathway was obtained in Inflammatory subtype and NK cell-mediated cytotoxicity and T cell receptor signaling pathway were upregulated in Adaptive group. To quantify the cluster findings, a scoring system, called, risk score, was established using four datasets (n=980) in the discovery cohorts based on least absolute shrinkage and selection operator (LASSO) and logistic regression and validated in external sets (n=760). Multivariate logistic regression analysis revealed the risk score was an independent predictor of outcomes of sepsis patients (OR [odds ratio], 2.752, 95% confidence interval [CI], 2.234-3.389, P<0.001), when adjusted by age and gender. In addition, the validation sets confirmed the performance (OR, 1.638, 95% CI, 1.309-2.048, P<0.001). Finally, nomograms demonstrated great discriminatory potential than that of risk score, age and gender (training set: AUC=0.682, 95% CI, 0.643-0.719; validation set: AUC=0.624, 95% CI, 0.576-0.664). Decision curve analysis (DCA) demonstrated that the nomograms were clinically useful and had better discriminative performance to recognize patients at high risk than the age, gender and risk score, respectively. Conclusions In-depth analysis of a comprehensive landscape of the transcriptome characteristics of sepsis might contribute to personalized treatments and prediction of clinical outcomes.
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Affiliation(s)
- Wei Zhou
- Department of Anesthesiology, Huzhou Central Hospital, The Affiliated Huzhou Hospital, Zhejiang University School of Medicine, Huzhou, Zhejiang, China
| | - Chunyu Zhang
- Department of Neurosurgery, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China,Department of Neurosurgery, Shanghai East Hospital, Nanjing Medical University, Nanjing, China
| | - Zhongwei Zhuang
- Department of Neurosurgery, Shanghai East Hospital, Nanjing Medical University, Nanjing, China
| | - Jing Zhang
- Department of Neurosurgery, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China,Institute for Advanced Study, Tongji University, Shanghai, China,*Correspondence: Jing Zhang, ; Chunlong Zhong,
| | - Chunlong Zhong
- Department of Neurosurgery, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China,Department of Neurosurgery, Shanghai East Hospital, Nanjing Medical University, Nanjing, China,*Correspondence: Jing Zhang, ; Chunlong Zhong,
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Clustering ICU patients with sepsis based on the patterns of their circulating biomarkers: A secondary analysis of the CAPTAIN prospective multicenter cohort study. PLoS One 2022; 17:e0267517. [PMID: 36301921 PMCID: PMC9612564 DOI: 10.1371/journal.pone.0267517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 10/11/2022] [Indexed: 01/24/2023] Open
Abstract
BACKGROUND Although sepsis is a life-threatening condition, its heterogeneous presentation likely explains the negative results of most trials on adjunctive therapy. This study in patients with sepsis aimed to identify subgroups with similar immune profiles and their clinical and outcome correlates. METHODS A secondary analysis used data of a prospective multicenter cohort that included patients with early assessment of sepsis. They were described using Predisposition, Insult, Response, Organ failure sepsis (PIRO) staging system. Thirty-eight circulating biomarkers (27 proteins, 11 mRNAs) were assessed at sepsis diagnosis, and their patterns were determined through principal component analysis (PCA). Hierarchical clustering was used to group the patients and k-means algorithm was applied to assess the internal validity of the clusters. RESULTS Two hundred and three patients were assessed, of median age 64.5 [52.0-77.0] years and SAPS2 score 55 [49-61] points. Five main patterns of biomarkers and six clusters of patients (including 42%, 21%, 17%, 9%, 5% and 5% of the patients) were evidenced. Clusters were distinguished according to the certainty of the causal infection, inflammation, use of organ support, pro- and anti-inflammatory activity, and adaptive profile markers. CONCLUSIONS In this cohort of patients with suspected sepsis, we individualized clusters which may be described with criteria used to stage sepsis. As these clusters are based on the patterns of circulating biomarkers, whether they might help to predict treatment responsiveness should be addressed in further studies. TRIAL REGISTRATION The CAPTAIN study was registered on clinicaltrials.gov on June 22, 2011, # NCT01378169.
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46
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Moreira A, Jain P. Genomics and Pediatric Sepsis. Pediatr Ann 2022; 51:e387-e389. [PMID: 36215090 DOI: 10.3928/19382359-20220803-04] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/13/2023]
Abstract
Sepsis is a clinical syndrome manifested by a dysregulation of the immune system triggered by an infection. The severity of illness is variable, which can include mild symptoms with no organ dysfunction to severe symptoms and multiorgan failure, eventually leading to death. Advances in bioinformatics have elucidated distinct sepsis endotypes and have allowed for a better understanding of the pathophysiologic mechanisms. As we learn more about these sepsis endotypes, more precise therapies will emerge for use as adjuncts to antibiotics. [Pediatr Ann. 2022;51(10):e387-e389.].
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Molecular Framework of Mouse Endothelial Cell Dysfunction during Inflammation: A Proteomics Approach. Int J Mol Sci 2022; 23:ijms23158399. [PMID: 35955534 PMCID: PMC9369400 DOI: 10.3390/ijms23158399] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 07/18/2022] [Accepted: 07/25/2022] [Indexed: 02/01/2023] Open
Abstract
A key aspect of cytokine-induced changes as observed in sepsis is the dysregulated activation of endothelial cells (ECs), initiating a cascade of inflammatory signaling leading to leukocyte adhesion/migration and organ damage. The therapeutic targeting of ECs has been hampered by concerns regarding organ-specific EC heterogeneity and their response to inflammation. Using in vitro and in silico analysis, we present a comprehensive analysis of the proteomic changes in mouse lung, liver and kidney ECs following exposure to a clinically relevant cocktail of proinflammatory cytokines. Mouse lung, liver and kidney ECs were incubated with TNF-α/IL-1β/IFN-γ for 4 or 24 h to model the cytokine-induced changes. Quantitative label-free global proteomics and bioinformatic analysis performed on the ECs provide a molecular framework for the EC response to inflammatory stimuli over time and organ-specific differences. Gene Ontology and PANTHER analysis suggest why some organs are more susceptible to inflammation early on, and show that, as inflammation progresses, some protein expression patterns become more uniform while additional organ-specific proteins are expressed. These findings provide an in-depth understanding of the molecular changes involved in the EC response to inflammation and can support the development of drugs targeting ECs within different organs. Data are available via ProteomeXchange (identifier PXD031804).
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48
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Prout A, Meert KL. Research in Pediatric Intensive Care. Pediatr Clin North Am 2022; 69:607-620. [PMID: 35667764 DOI: 10.1016/j.pcl.2022.01.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Many important clinical questions remain unanswered in the practice of pediatric intensive care due to the lack of high-quality evidence. Although challenges exist in conducting research in pediatric intensive care units, identification of research priorities, interdisciplinary collaborations, innovative trial designs, and the use of common datasets and outcome measures helps to bring new knowledge to our field. The topic of "Research in PICUs" is extremely broad; therefore, this review focuses on a few common themes receiving increased attention in the literature, including research agendas, core outcome sets, precision medicine, and novel clinical trial strategies.
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Affiliation(s)
- Andrew Prout
- Division of Pediatric Critical Care Medicine, Discipline of Pediatrics, Children's Hospital of Michigan, Floor Carls Building, 3901 Beaubien Boulevard, Detroit, MI, 48201, USA; Central Michigan University, Mt. Pleasant, MI, USA.
| | - Kathleen L Meert
- Central Michigan University, Mt. Pleasant, MI, USA; Discipline of Pediatrics, Children's Hospital of Michigan, Detroit, MI, USA; Children's Hospital of Michigan, Suite H-07, 3901 Beaubien Boulevard, Detroit, MI 48201, USA
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Abstract
Research and practice in critical care medicine have long been defined by syndromes, which, despite being clinically recognizable entities, are, in fact, loose amalgams of heterogeneous states that may respond differently to therapy. Mounting translational evidence-supported by research on respiratory failure due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection-suggests that the current syndrome-based framework of critical illness should be reconsidered. Here we discuss recent findings from basic science and clinical research in critical care and explore how these might inform a new conceptual model of critical illness. De-emphasizing syndromes, we focus on the underlying biological changes that underpin critical illness states and that may be amenable to treatment. We hypothesize that such an approach will accelerate critical care research, leading to a richer understanding of the pathobiology of critical illness and of the key determinants of patient outcomes. This, in turn, will support the design of more effective clinical trials and inform a more precise and more effective practice at the bedside.
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Aldewereld ZT, Zhang LA, Urbano A, Parker RS, Swigon D, Banerjee I, Gómez H, Clermont G. Identification of Clinical Phenotypes in Septic Patients Presenting With Hypotension or Elevated Lactate. Front Med (Lausanne) 2022; 9:794423. [PMID: 35665340 PMCID: PMC9160971 DOI: 10.3389/fmed.2022.794423] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 04/28/2022] [Indexed: 01/13/2023] Open
Abstract
Introduction Targeted therapies for sepsis have failed to show benefit due to high variability among subjects. We sought to demonstrate different phenotypes of septic shock based solely on clinical features and show that these relate to outcome. Methods A retrospective analysis was performed of a 1,023-subject cohort with early septic shock from the ProCESS trial. Twenty-three clinical variables at baseline were analyzed using hierarchical clustering, with consensus clustering used to identify and validate the ideal number of clusters in a derivation cohort of 642 subjects from 20 hospitals. Clusters were visualized using heatmaps over 0, 6, 24, and 72 h. Clinical outcomes were 14-day all-cause mortality and organ failure pattern. Cluster robustness was confirmed in a validation cohort of 381 subjects from 11 hospitals. Results Five phenotypes were identified, each with unique organ failure patterns that persisted in time. By enrollment criteria, all patients had shock. The two high-risk phenotypes were characterized by distinct multi-organ failure patterns and cytokine signatures, with the highest mortality group characterized most notably by liver dysfunction and coagulopathy while the other group exhibited primarily respiratory failure, neurologic dysfunction, and renal dysfunction. The moderate risk phenotype was that of respiratory failure, while low-risk phenotypes did not have a high degree of additional organ failure. Conclusions Sepsis phenotypes with distinct biochemical abnormalities may be identified by clinical characteristics alone and likely provide an opportunity for early clinical actionability and prognosis.
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Affiliation(s)
- Zachary T. Aldewereld
- UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA, United States,Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, United States,Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, United States,*Correspondence: Zachary T. Aldewereld
| | - Li Ang Zhang
- Department of Chemical and Petroleum Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Alisa Urbano
- Department of Chemical and Petroleum Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Robert S. Parker
- Department of Chemical and Petroleum Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - David Swigon
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, United States
| | - Ipsita Banerjee
- Department of Chemical and Petroleum Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Hernando Gómez
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Gilles Clermont
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, United States,Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, United States
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