Evidence map›Paper›PMID 40788839›Full record

ArticleAmerican journal of respiratory and critical care medicine2026

Host-Microbe Multiomic Profiling Predicts Mortality in Sepsis.

Natasha Spottiswoode, Lucile P Neyton, Eran Mick, Katrina L Kalantar, Samantha Hao, Emily C Lydon, Rithwik Narendra, Paula Hayakawa Serpa, Saharai Caldera, Antonio Gomez and 8 more

Abstract read
In one paragraph

Article in American journal of respiratory and critical care medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Reply to Liu et al. and Chen et al.American journal of respiratory and critical care medicine · 2026
    Article
  5. Article
  6. Article
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

18 authors.

Natasha SpottiswoodeDepartment of Medicine, Division of Infectious Diseases.
Lucile P NeytonDepartment of Medicine, Division of Pulmonary, Critical Care, Allergy and Sleep Medicine.ORCID 0000-0003-1273-2228
Eran MickDepartment of Medicine, Division of Infectious Diseases.ORCID 0000-0002-7299-808X
Katrina L KalantarChan-Zuckerberg Initiative, Redwood City, California.
Samantha HaoDepartment of Neurology, Stanford University, Palo Alto, California.
Emily C LydonDepartment of Medicine, Division of Infectious Diseases.
Rithwik NarendraDepartment of Medicine, Division of Infectious Diseases.
Paula Hayakawa SerpaDepartment of Medicine, Division of Infectious Diseases.
Saharai CalderaDepartment of Medicine, Division of Infectious Diseases.
Antonio GomezDepartment of Medicine, Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Zuckerberg San Francisco General Hospital, California; and.
Carolyn HendricksonDepartment of Medicine, Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Zuckerberg San Francisco General Hospital, California; and.
Kirsten KangelarisDepartment of Medicine.
Kathleen LiuDepartment of Medicine, Division of Pulmonary, Critical Care, Allergy and Sleep Medicine.
Pratik SinhaDepartment of Critical Care Medicine, Washington University, St. Louis, Missouri.
Joseph L DeRisiDepartment of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, California.
Michael A MatthayDepartment of Medicine, Division of Pulmonary, Critical Care, Allergy and Sleep Medicine.
Carolyn S CalfeeDepartment of Medicine, Division of Pulmonary, Critical Care, Allergy and Sleep Medicine.
Charles R LangelierDepartment of Medicine, Division of Infectious Diseases.

Funding

BIOLOGY OF INFECTIOUS DISEASES TRAINING PROGRAMT32AI007641 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MATTHEW G DORSEY · 2000 to 2026
$6.9M
Precision Medicine in the Acute Respiratory Distress SyndromeR35HL140026 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CALFEE, CAROLYN · 2018 to 2024
$6.8M
Precision Medicine in Sepsis with Critical IllnessR35GM142992 · NIGMS · WASHINGTON UNIVERSITY · PI Pratik Sinha · 2021 to 2026
$2.4M
Integrated Host-Microbe Metagenomics for Sepsis Pathogen Surveillance, Subphenotyping and Outcome PredictionR01AI185511 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Charles Langelier · 2024 to 2026
$2.0M
National Institute of Allergy and Infectious Diseases R01AI185511National Institute of Allergy and Infectious Diseases R35HL140026NHLBI NIH HHS R35 HL140026NHLBI NIH HHS R35HL140026NIAID NIH HHS R01 AI185511NIAID NIH HHS T32 AI007641NIGMS NIH HHS R35 GM142992
6 · The paper itself

Abstract

rationaleSepsis is a leading cause of mortality and involves a dysregulated host response to infection. The host and microbe have historically been considered independently in studies of sepsis, limiting our understanding of key relationships driving mortality.

objectivesWe sought to identify host and microbial factors associated with sepsis mortality and build prognostic classifiers.

methodsWe studied 321 critically ill adults and adjudicated sepsis status. From whole blood collected within 24 hours of admission, we performed transcriptional profiling, and from plasma, we performed proteomic and metagenomic analyses. We evaluated associations between in-hospital mortality and gene expression, protein levels, and microbial metagenomic data and built support vector machine-based prognostic classifiers. MEASUREMENTS AND MAIN

resultsIn patients with sepsis, mortality was associated with increased expression of genes related to neutrophil degranulation, lower expression of genes related to T-cell signaling, and higher IL-8 levels. Mortality was also associated with greater microbial mass and greater bacterial relative dominance. Similar findings were observed in a broader group that also included patients with culture-negative sepsis or indeterminate sepsis status. An integrated host-microbe metagenomic classifier predicted sepsis mortality with an area under the curve (AUC) of 0.79, and a host transcriptomic classifier performed comparably, with an AUC of 0.75. Both performed better (P < 0.05 by paired DeLong tests) that the Acute Physiology, Age, Chronic Health Evaluation III score (AUC of 0.69).

conclusionsTaken together, our findings provide a conceptual advance in the understanding of host and microbial factors associated with mortality in critical illness and demonstrate a new approach to mortality prediction in sepsis.

Indexed as

Hospital MortalitySepsisAdultAgedCritical IllnessFemaleGene Expression ProfilingHumansMaleMetagenomicsMiddle AgedPrognosisProteomicshost responsemetagenomicsmortalitysepsistranscriptomics

Identifiers

PMID40788839
PMCPMC12927001

What OpenQuestion holds

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Registered trials

None linked

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 OpenQuestion graph.