Brendon P Scicluna1, Lonneke A van Vught2, Aeilko H Zwinderman3, Maryse A Wiewel2, Emma E Davenport4, Katie L Burnham4, Peter Nürnberg5, Marcus J Schultz6, Janneke Horn6, Olaf L Cremer7, Marc J Bonten8, Charles J Hinds9, Hector R Wong10, Julian C Knight4, Tom van der Poll11. 1. Center for Experimental Molecular Medicine, Academic Medical Center, Amsterdam, Netherlands; Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, Amsterdam, Netherlands. Electronic address: b.scicluna@amc.uva.nl. 2. Center for Experimental Molecular Medicine, Academic Medical Center, Amsterdam, Netherlands. 3. Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, Amsterdam, Netherlands. 4. Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK. 5. Cologne Center for Genomics, University of Cologne, Cologne, Germany; Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany; Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany. 6. Department of Intensive Care Medicine, Academic Medical Center, Amsterdam, Netherlands. 7. Department of Intensive Care Medicine, University Medical Center Utrecht, Utrecht, Netherlands. 8. Department of Medical Microbiology, University Medical Center Utrecht, Utrecht, Netherlands. 9. William Harvey Research Institute, Barts and The London School of Medicine, Queen Mary University, London, UK. 10. Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center and Cincinnati Children's Research Foundation, Cincinnati, OH, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA. 11. Center for Experimental Molecular Medicine, Academic Medical Center, Amsterdam, Netherlands; Division of Infectious Diseases, Academic Medical Center, Amsterdam, Netherlands.
Abstract
BACKGROUND: Host responses during sepsis are highly heterogeneous, which hampers the identification of patients at high risk of mortality and their selection for targeted therapies. In this study, we aimed to identify biologically relevant molecular endotypes in patients with sepsis. METHODS: This was a prospective observational cohort study that included consecutive patients admitted for sepsis to two intensive care units (ICUs) in the Netherlands between Jan 1, 2011, and July 20, 2012 (discovery and first validation cohorts) and patients admitted with sepsis due to community-acquired pneumonia to 29 ICUs in the UK (second validation cohort). We generated genome-wide blood gene expression profiles from admission samples and analysed them by unsupervised consensus clustering and machine learning. The primary objective of this study was to establish endotypes for patients with sepsis, and assess the association of these endotypes with clinical traits and survival outcomes. We also established candidate biomarkers for the endotypes to allow identification of patient endotypes in clinical practice. FINDINGS: The discovery cohort had 306 patients, the first validation cohort had 216, and the second validation cohort had 265 patients. Four molecular endotypes for sepsis, designated Mars1-4, were identified in the discovery cohort, and were associated with 28-day mortality (log-rank p=0·022). In the discovery cohort, the worst outcome was found for patients classified as having a Mars1 endotype, and at 28 days, 35 (39%) of 90 people with a Mars1 endotype had died (hazard ratio [HR] vs all other endotypes 1·86 [95% CI 1·21-2·86]; p=0·0045), compared with 23 (22%) of 105 people with a Mars2 endotype (HR 0·64 [0·40-1·04]; p=0·061), 16 (23%) of 71 people with a Mars3 endotype (HR 0·71 [0·41-1·22]; p=0·19), and 13 (33%) of 40 patients with a Mars4 endotype (HR 1·13 [0·63-2·04]; p=0·69). Analysis of the net reclassification improvement using a combined clinical and endotype model significantly improved risk prediction to 0·33 (0·09-0·58; p=0·008). A 140-gene expression signature reliably stratified patients with sepsis to the four endotypes in both the first and second validation cohorts. Only Mars1 was consistently significantly associated with 28-day mortality across the cohorts. To facilitate possible clinical use, a biomarker was derived for each endotype; BPGM and TAP2 reliably identified patients with a Mars1 endotype. INTERPRETATION: This study provides a method for the molecular classification of patients with sepsis to four different endotypes upon ICU admission. Detection of sepsis endotypes might assist in providing personalised patient management and in selection for trials. FUNDING: Center for Translational Molecular Medicine, Netherlands.
BACKGROUND: Host responses during sepsis are highly heterogeneous, which hampers the identification of patients at high risk of mortality and their selection for targeted therapies. In this study, we aimed to identify biologically relevant molecular endotypes in patients with sepsis. METHODS: This was a prospective observational cohort study that included consecutive patients admitted for sepsis to two intensive care units (ICUs) in the Netherlands between Jan 1, 2011, and July 20, 2012 (discovery and first validation cohorts) and patients admitted with sepsis due to community-acquired pneumonia to 29 ICUs in the UK (second validation cohort). We generated genome-wide blood gene expression profiles from admission samples and analysed them by unsupervised consensus clustering and machine learning. The primary objective of this study was to establish endotypes for patients with sepsis, and assess the association of these endotypes with clinical traits and survival outcomes. We also established candidate biomarkers for the endotypes to allow identification of patient endotypes in clinical practice. FINDINGS: The discovery cohort had 306 patients, the first validation cohort had 216, and the second validation cohort had 265 patients. Four molecular endotypes for sepsis, designated Mars1-4, were identified in the discovery cohort, and were associated with 28-day mortality (log-rank p=0·022). In the discovery cohort, the worst outcome was found for patients classified as having a Mars1 endotype, and at 28 days, 35 (39%) of 90 people with a Mars1 endotype had died (hazard ratio [HR] vs all other endotypes 1·86 [95% CI 1·21-2·86]; p=0·0045), compared with 23 (22%) of 105 people with a Mars2 endotype (HR 0·64 [0·40-1·04]; p=0·061), 16 (23%) of 71 people with a Mars3 endotype (HR 0·71 [0·41-1·22]; p=0·19), and 13 (33%) of 40 patients with a Mars4 endotype (HR 1·13 [0·63-2·04]; p=0·69). Analysis of the net reclassification improvement using a combined clinical and endotype model significantly improved risk prediction to 0·33 (0·09-0·58; p=0·008). A 140-gene expression signature reliably stratified patients with sepsis to the four endotypes in both the first and second validation cohorts. Only Mars1 was consistently significantly associated with 28-day mortality across the cohorts. To facilitate possible clinical use, a biomarker was derived for each endotype; BPGM and TAP2 reliably identified patients with a Mars1 endotype. INTERPRETATION: This study provides a method for the molecular classification of patients with sepsis to four different endotypes upon ICU admission. Detection of sepsis endotypes might assist in providing personalised patient management and in selection for trials. FUNDING: Center for Translational Molecular Medicine, Netherlands.
Authors: Christopher W Seymour; Jason N Kennedy; Shu Wang; Chung-Chou H Chang; Corrine F Elliott; Zhongying Xu; Scott Berry; Gilles Clermont; Gregory Cooper; Hernando Gomez; David T Huang; John A Kellum; Qi Mi; Steven M Opal; Victor Talisa; Tom van der Poll; Shyam Visweswaran; Yoram Vodovotz; Jeremy C Weiss; Donald M Yealy; Sachin Yende; Derek C Angus Journal: JAMA Date: 2019-05-28 Impact factor: 56.272
Authors: Carolyn S Calfee; Kevin L Delucchi; Pratik Sinha; Michael A Matthay; Jonathan Hackett; Manu Shankar-Hari; Cliona McDowell; John G Laffey; Cecilia M O'Kane; Daniel F McAuley Journal: Lancet Respir Med Date: 2018-08-02 Impact factor: 30.700
Authors: Michael D Maile; Matthew J Sigakis; Kathleen A Stringer; Elizabeth S Jewell; Milo C Engoren Journal: J Crit Care Date: 2020-01-14 Impact factor: 3.425
Authors: Robert P Dickson; Marcus J Schultz; Tom van der Poll; Laura R Schouten; Nicole R Falkowski; Jenna E Luth; Michael W Sjoding; Christopher A Brown; Rishi Chanderraj; Gary B Huffnagle; Lieuwe D J Bos Journal: Am J Respir Crit Care Med Date: 2020-03-01 Impact factor: 21.405