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Publications

Journal Article Epublish

PubMed: 42548383 DOI: 10.1016/j.chpulm.2026.100256

Community-Acquired Pneumonia: Disease Course Prediction With a 5-Gene Signature.

CHEST Pulm 4(2):100256

Authors: Holger Kirsten, Sebastian Weis, Peter Ahnert, Martin Witzenrath, Brendon P Scicluna, Knut Krohn, Michael Rade, Friedemann Horn, Catharina Bertram, Kristin Reiche, Dennis Löffler, Conny Blumert, Stefan Jenner, Kai Sohn, Geraldine Nouailles, Michael Kiehntopf, Petra Creutz, Maciej Rosolowski, Markus Loeffler, Norbert Suttorp, Markus Scholz, Michael Bauer

Affiliations

  • Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig University, Leipzig, Germany.
  • German Center for Lung Research (DZL), Associated Partner PROGRESS, Universität Leipzig, Leipzig, Germany.
  • Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI), Dresden/Leipzig, Germany.
  • Department of Anesthesiology and Intensive Care Medicine, Jena University Hospital, Friedrich-Schiller-University Jena, Jena, Germany.
  • Institute for Infectious Disease and Infection Control, Jena University Hospital, Friedrich-Schiller-University Jena, Jena, Germany.
  • Leibniz Institute for Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute, Jena, Germany.
  • Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Infectious Diseases, Respiratory Medicine and Critical Care, Berlin, Germany.
  • German Center for Lung Research (DZL), Partner Site Charité, Berlin, Germany.
  • Centre for Molecular Medicine and Biobanking, University of Malta, Msida, Malta.
  • Department of Applied Biomedical Science, Faculty of Health Sciences, Mater Dei hospital, University of Malta, Msida, Malta.
  • Core Unit DNA Technologies, Medical Faculty, Leipzig University, Leipzig, Germany.
  • Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany.
  • Fraunhofer Institute for Interfacial Engineering and Biotechnology, Stuttgart, Germany.
  • Department of Clinical Chemistry and Laboratory Medicine, Jena University Hospital, Friedrich-Schiller-University Jena, Jena, Germany.
  • Integrated Biobank Jena (IBBJ), Jena University Hospital, Friedrich-Schiller-University Jena, Jena, Germany.

Abstract

BACKGROUND

Clinical decision-making for patients with community-acquired pneumonia (CAP) at risk of organ dysfunction and death is currently guided by clinical evaluation and scores. Every fifth patient with CAP requires admission to the ICU, with a subsequent high mortality; delayed admission to the ICU increases this risk.

RESEARCH QUESTION

Can a transcriptomic signature improve identification of at-risk patients compared with conventional scores and metrics?

STUDY DESIGN AND METHODS

Time-course transcriptomic data were obtained from blood samples taken from 455 participants in 41 centers enrolled in the Progression of Community-Acquired Pneumonia in the Hospital (PROGRESS) trial, a prospective observational cohort study of hospitalized patients with CAP who did not initially require organ support. Discovery (n = 240) and validation (n = 215) cohorts were randomly assigned. Transcriptome data were analyzed for association with a severe CAP course, defined as a composite of requirement for ICU admission or 28-day mortality. Predictive performance of the gene expression profiles was compared against clinical scores and serum markers, and validated in publicly available transcriptomic data sets.

RESULTS

A 5-gene signature consisting of SIGLEC14, TNFSF14, YOD1, CLEC4A, and KLRB1 (STYCK) was identified and validated to predict clinical deterioration with subsequent ICU admission or 28-day mortality (AUC discovery, 0.82; 95% CI, 0.71-0.90; P = 0.00000065; AUC validation, 0.81; 95% CI, 0.70-0.90; P = 0.0000013). The signature outperformed clinical scores in predicting severe CAP and improved prediction when added to the Sequential Organ Failure Assessment score (AUC SOFA, 0.70 vs AUC SOFA+STYCK, 0.83; P = .0002). Prognostic value was confirmed in 6 of 17 publicly available sepsis cohorts, particularly those with low case fatality.

INTERPRETATION

We identified a 5-gene transcriptomic signature that, taken soon after hospital admission, was shown to predict disease course of hospitalized patients with CAP. STYCK was superior to conventional, currently used scores and clinical metrics in predicting this deterioration and improved, if added to the Sequential Organ Failure Assessment, its performance.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov; No.: NCT02782013; URL: www.clinicaltrials.gov.

MeSH

Genes, Mortality, Pneumonia, Prospective Studies, Gene Expression, Community-Acquired Pneumonia