Evidence map›Paper›PMID 41571837›Full record

ArticleScientific reports2026

A proteomics and redox proteomics approach to understanding ARDS heterogeneity.

Thomas E Forshaw, Kirtikar Shukla, Hanzhi Wu, Susan Sergeant, Jingyun Lee, Allen W Tsang, Peter E Morris, Kevin W Gibbs, D Clark Files, Cristina M Furdui

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Thomas E ForshawDepartment of Internal Medicine, Section on Molecular Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA.
Kirtikar ShuklaDepartment of Internal Medicine, Section on Molecular Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA.
Hanzhi WuDepartment of Internal Medicine, Section on Molecular Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA.
Susan SergeantDepartment of Biochemistry, Wake Forest University School of Medicine, Winston- Salem, NC, USA.
Jingyun LeeDepartment of Internal Medicine, Section on Molecular Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA.
Allen W TsangDepartment of Internal Medicine, Section on Molecular Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA.
Peter E MorrisDepartment of Internal Medicine, Section of Pulmonary, Critical Care, Allergy, and Immunologic Diseases, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
Kevin W GibbsDepartment of Internal Medicine, Section of Pulmonary, Critical Care, Allergy, and Immunologic Diseases, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
D Clark FilesDepartment of Internal Medicine, Section of Pulmonary, Critical Care, Allergy, and Immunologic Diseases, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
Cristina M FurduiDepartment of Internal Medicine, Section on Molecular Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA. cristina.furdui@advocatehealth.org.

Funding

Tumor Tissue CoreP30CA012197 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI Ruben A. Mesa · 1985 to 2026
$55.4M
CTSA UM1 Program at Wake ForestUM1TR004929 · NCATS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI Jamy D Ard, KRISTIE L FOLEY · 2024 to 2026
$11.9M
NCATS NIH HHS UM1 TR004929NCI NIH HHS P30 CA012197
6 · The paper itself

Abstract

Acute Respiratory Distress Syndrome (ARDS) is a severe and heterogeneous critical illness characterized by systemic inflammation, lung injury, and profound hypoxemia. To investigate the temporal evolution of molecular features underlying ARDS heterogeneity, we applied advanced proteomics and redox proteomics to matched plasma and bronchoalveolar lavage (BAL) fluid samples collected longitudinally from 16 intensive care unit (ICU) ARDS patients during hospitalization. Exploratory, data-driven hierarchical clustering (Ward method) identified three distinct molecular patterns across patients represented as Groups A, B, and C. This framework was associated with illness severity at study enrollment (Group A profiling patients with more severe illness at enrollment), demonstrated temporal stability across sampling timepoints, and revealed molecular features associated with clinical improvement during hospitalization. Key pathways distinguishing the molecular patterns and consistent with prior findings included the production and detoxification of reactive oxygen species (ROS), Liver X receptor–Retinoid X receptor (LXR/RXR) activation and 24-dehydrocholesterol reductase (DHCR24) signaling, interleukin-12 (IL-12) signaling and production in macrophages, and neutrophil degranulation. Although plasma proteomic profiles were generally consistent with findings in BAL fluid, BAL fluid data were more mechanistically informative and enabled clearer and more consistent interrogation of ARDS molecular heterogeneity. The results highlight the potential value of lung–focused, temporal studies to improve patient stratification and guide future therapeutic strategies. However, the modest cohort size and exploratory nature of this study necessitate cautious interpretation of pathway-level inferences. Future longitudinal studies in larger, independent ARDS cohorts will be required to validate these molecular groups and assess their clinical relevance.

Indexed as

ProteomeProteomicsRespiratory Distress SyndromeBronchoalveolar Lavage FluidFemaleHumansMaleMiddle AgedOxidation-ReductionReactive Oxygen SpeciesProteomeReactive Oxygen Species

Identifiers

PMID41571837
PMCPMC12901994

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.