Longitudinal multiomic signatures of ARDS and sepsis inflammatory phenotypes identify pathways associated with mortality

BACKGROUNDCritically ill patients with acute respiratory distress syndrome (ARDS) and sepsis exhibit distinct inflammatory phenotypes with divergent clinical outcomes, but the underlying molecular mechanisms remain poorly understood. These phenotypes, derived from clinical data and protein biomarkers, were associated with metabolic differences in a pilot study.METHODSWe performed integrative multiomics analysis of blood samples from 160 patients with ARDS in the ROSE trial, randomly selecting 80 patients from each latent class analysis-defined inflammatory phenotype (hyperinflammatory and hypoinflammatory) with phenotype probability greater than 0.9. Untargeted plasma metabolomics and whole-blood transcriptomics at day 0 and day 2 were analyzed using multimodal factor analysis (MEFISTO). The primary outcome was 90-day mortality, with validation in an independent critically ill sepsis cohort (EARLI).RESULTSMultiomics integration revealed 4 molecular signatures associated with mortality: (a) enhanced innate immune activation coupled with increased glycolysis (associated with hyperinflammatory phenotype), (b) hepatic dysfunction and immune dysfunction paired with impaired fatty acid β-oxidation (associated with hyperinflammatory phenotype), (c) interferon program suppression coupled with altered mitochondrial respiration (associated with hyperinflammatory phenotype), and (d) redox impairment and cell proliferation pathways (not associated with inflammatory phenotype). These signatures persisted through day 2 of trial enrollment. Within-phenotype analysis revealed distinct mortality-associated pathways in each group. All molecular signatures were validated in the independent EARLI cohort.CONCLUSIONInflammatory phenotypes of ARDS reflect distinct underlying biological processes with both phenotype-specific and phenotype-independent pathways influencing patient outcomes, all characterized by mitochondrial dysfunction. These findings suggest potential therapeutic targets for precise treatment strategies in critical illness.FUNDINGNIH National Heart, Lung, and Blood Institute and National Institute of General Medical Sciences.

Authors

Institutions

Publication Details

Journal
Journal of Clinical Investigation
Published
2025-12-02
DOI
https://doi.org/10.1172/jci196290
Citations
1
Primary Topic
Sepsis Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
1.35

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Longitudinal multiomic signatures of ARDS and sepsis inflammatory phenotypes identify pathways associated with mortality

Charles Langelier, Carolyn Leroux, Lucile Neyton, Carolyn M. Hendrickson et al.
1 citations
Journal of Clinical Investigation
Sepsis Diagnosis and Treatment
1.35
article

Longitudinal multiomic signatures of ARDS and sepsis inflammatory phenotypes identify pathways associated with mortality

Charles Langelier, Carolyn Leroux, Lucile Neyton, Carolyn M. Hendrickson, Kathleen A. Stringer, Sidney Carrillo, Narges Alipanah, Olivia S. Chao, Liam Magee, Chelsea Lin, Andrew Willmore, Pratik Sinha, Michael A. Matthay, Carolyn S. Calfee, Deanna Lee, Kathleen D. Liu, Natasha Spottiswoode, Angela J. Rogers, Aartik Sarma, Melanie Weingart, Kirsten N. Kangelaris, Suzanna Chak, Kathryn Sullivan, Emma Schmiege, Hanjing Zhuo, Taarini Hariharan, Angelika Ringor, Kim Bardillon
article en
1 citations

Abstract

BACKGROUNDCritically ill patients with acute respiratory distress syndrome (ARDS) and sepsis exhibit distinct inflammatory phenotypes with divergent clinical outcomes, but the underlying molecular mechanisms remain poorly understood. These phenotypes, derived from clinical data and protein biomarkers, were associated with metabolic differences in a pilot study.METHODSWe performed integrative multiomics analysis of blood samples from 160 patients with ARDS in the ROSE trial, randomly selecting 80 patients from each latent class analysis-defined inflammatory phenotype (hyperinflammatory and hypoinflammatory) with phenotype probability greater than 0.9. Untargeted plasma metabolomics and whole-blood transcriptomics at day 0 and day 2 were analyzed using multimodal factor analysis (MEFISTO). The primary outcome was 90-day mortality, with validation in an independent critically ill sepsis cohort (EARLI).RESULTSMultiomics integration revealed 4 molecular signatures associated with mortality: (a) enhanced innate immune activation coupled with increased glycolysis (associated with hyperinflammatory phenotype), (b) hepatic dysfunction and immune dysfunction paired with impaired fatty acid β-oxidation (associated with hyperinflammatory phenotype), (c) interferon program suppression coupled with altered mitochondrial respiration (associated with hyperinflammatory phenotype), and (d) redox impairment and cell proliferation pathways (not associated with inflammatory phenotype). These signatures persisted through day 2 of trial enrollment. Within-phenotype analysis revealed distinct mortality-associated pathways in each group. All molecular signatures were validated in the independent EARLI cohort.CONCLUSIONInflammatory phenotypes of ARDS reflect distinct underlying biological processes with both phenotype-specific and phenotype-independent pathways influencing patient outcomes, all characterized by mitochondrial dysfunction. These findings suggest potential therapeutic targets for precise treatment strategies in critical illness.FUNDINGNIH National Heart, Lung, and Blood Institute and National Institute of General Medical Sciences.

Journal of Clinical InvestigationVol. 136(3)
San Francisco General Hospital (US), University of California, San Francisco (US), American Association of Colleges of Pharmacy (US), Washington University in St. Louis (US), University of Michigan (US), Pulmonary and Allergy Associates (US), Stanford Medicine (US), Pulmonary and Critical Care Associates (US), Institute for Social Research (NO), University of San Francisco (US), Stanford University (US)
China Scholarship Council, National Institutes of Health, National Heart, Lung, and Blood Institute, National Institute of General Medical Sciences
Openalex Percentile: Top 14%
Sepsis Diagnosis and Treatment
1.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.