Molecular Patterns in Acute Pancreatitis Reflect Generalizable Endotypes of the Host Response to Systemic Injury in Humans.


Journal

Annals of surgery
ISSN: 1528-1140
Titre abrégé: Ann Surg
Pays: United States
ID NLM: 0372354

Informations de publication

Date de publication:
01 02 2022
Historique:
pubmed: 4 6 2020
medline: 19 2 2022
entrez: 4 6 2020
Statut: ppublish

Résumé

Acute Pancreatitis (AP) is sudden onset pancreas inflammation that causes systemic injury with a wide and markedly heterogeneous range of clinical consequences. Here, we hypothesized that this observed clinical diversity corresponds to diversity in molecular subtypes that can be identified in clinical and multiomics data. Observational cohort study. n = 57 for the discovery cohort (clinical, transcriptomics, proteomics, and metabolomics data) and n = 312 for the validation cohort (clinical and metabolomics data). We integrated coincident transcriptomics, proteomics, and metabolomics data at serial time points between admission to hospital and up to 48 hours after recruitment from a cohort of patients presenting with acute pancreatitis. We systematically evaluated 4 different metrics for patient similarity using unbiased mathematical, biological, and clinical measures of internal and external validity.We next compared the AP molecular endotypes with previous descriptions of endotypes in a critically ill population with acute respiratory distress syndrome (ARDS). Our results identify 4 distinct and stable AP molecular endotypes. We validated our findings in a second independent cohort of patients with AP.We observed that 2 endotypes in AP recapitulate disease endotypes previously reported in ARDS. Our results show that molecular endotypes exist in AP and reflect biological patterns that are also present in ARDS, suggesting that generalizable patterns exist in diverse presentations of critical illness.

Sections du résumé

OBJECTIVE
Acute Pancreatitis (AP) is sudden onset pancreas inflammation that causes systemic injury with a wide and markedly heterogeneous range of clinical consequences. Here, we hypothesized that this observed clinical diversity corresponds to diversity in molecular subtypes that can be identified in clinical and multiomics data.
SUMMARY BACKGROUND DATA
Observational cohort study. n = 57 for the discovery cohort (clinical, transcriptomics, proteomics, and metabolomics data) and n = 312 for the validation cohort (clinical and metabolomics data).
METHODS
We integrated coincident transcriptomics, proteomics, and metabolomics data at serial time points between admission to hospital and up to 48 hours after recruitment from a cohort of patients presenting with acute pancreatitis. We systematically evaluated 4 different metrics for patient similarity using unbiased mathematical, biological, and clinical measures of internal and external validity.We next compared the AP molecular endotypes with previous descriptions of endotypes in a critically ill population with acute respiratory distress syndrome (ARDS).
RESULTS
Our results identify 4 distinct and stable AP molecular endotypes. We validated our findings in a second independent cohort of patients with AP.We observed that 2 endotypes in AP recapitulate disease endotypes previously reported in ARDS.
CONCLUSIONS
Our results show that molecular endotypes exist in AP and reflect biological patterns that are also present in ARDS, suggesting that generalizable patterns exist in diverse presentations of critical illness.

Identifiants

pubmed: 32487804
pii: 00000658-202202000-00052
doi: 10.1097/SLA.0000000000003974
doi:

Types de publication

Journal Article Observational Study Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e453-e462

Subventions

Organisme : Medical Research Council
ID : MR/P008887/1
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 103258/Z/13/Z
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 103258/Z/13/A
Pays : United Kingdom

Informations de copyright

Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.

Déclaration de conflit d'intérêts

The authors report no conflicts of interest.

Références

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Auteurs

Lucile P A Neyton (LPA)

Medical Research Council Centre for Inflammation Research, Queen's Medical Research Institute, The University of Edinburgh, Edinburgh, UK.
Division of Genetics and Genomics, The Roslin Institute, The University of Edinburgh, Edinburgh, UK.

Xiaozhong Zheng (X)

Medical Research Council Centre for Inflammation Research, Queen's Medical Research Institute, The University of Edinburgh, Edinburgh, UK.

Christos Skouras (C)

Clinical Surgery, School of Clinical Sciences and Community Health, The University of Edinburgh, Edinburgh, UK.

Andrea Doeschl-Wilson (A)

Division of Genetics and Genomics, The Roslin Institute, The University of Edinburgh, Edinburgh, UK.

Michael U Gutmann (MU)

School of Informatics, The University of Edinburgh, Edinburgh, UK.

Iain Uings (I)

GSK Discovery Partnerships with Academia, Exploratory Discovery, Future Pipeline Discovery, Medicines Research Centre, Stevenage, UK.

Francesco V Rao (FV)

DC Biosciences Limited, James Lindsay Place, Dundee Technopole, Dundee, UK.

Armel Nicolas (A)

DC Biosciences Limited, James Lindsay Place, Dundee Technopole, Dundee, UK.

Craig Marshall (C)

Department of Laboratory Medicine, NHS Lothian, Edinburgh, UK.

Lisa-Marie Wilson (LM)

Department of Laboratory Medicine, NHS Lothian, Edinburgh, UK.

J Kenneth Baillie (JK)

Division of Genetics and Genomics, The Roslin Institute, The University of Edinburgh, Edinburgh, UK.

Damian J Mole (DJ)

Medical Research Council Centre for Inflammation Research, Queen's Medical Research Institute, The University of Edinburgh, Edinburgh, UK.
Clinical Surgery, School of Clinical Sciences and Community Health, The University of Edinburgh, Edinburgh, UK.

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