Pathogen-specific host responses define distinct pneumonia endotypes in the human lung

Read full text
Authors: Nikolay S. Markov, Marcin Możejko, Vijeeth Guggilla, Małgorzata Łazȩcka, Helen K. Donnelly, Alvaro Donayre, Samuel W. Fenske, Alec Peltekian, Bruno Puczko-Szymański, Paulina Szymczak, Adam Izdebski, Lucy Luo
+23 more Karolina J. Senkow, Luisa Cusick, Zhan Yu, Suchitra Swaminathan, Ziyan Lu, Hiam Abdala-Valencia, Duc Phan, Katie Clepp, Luke V. Rasmussen, Anna Pawlowski, Chiagozie O Pickens, Nandita R. Nadig, Theresa Walunas, Robert Tighe, The Neu-Lung Investigators, Luisa Morales‐Nebreda, Catherine A Gao, Richard G. Wunderink, G. R. Scott Budinger, Benjamin D Singer, Alexander V. Misharin, Ewa Szczurek, The NU SCRIPT Study Investigators
Cited by: 1
References: 71

Abstract

Pneumonia is the leading cause of death from infectious disease worldwide. The diagnosis and treatment of patients with pneumonia lag behind other major conditions, relying on syndromic definitions that lack molecular resolution and ignore underlying endotypes. We sought to test the hypothesis that dynamic pathogen-specific host responses in the alveolar space represent distinct pneumonia endotypes linked to different clinical features and outcomes. We prospectively enrolled a cohort of 690 patients (including immunocompromised patients) with known or suspected pneumonia receiving mechanical ventilation in whom the etiology of pneumonia was determined by gold-standard analysis of distal lung fluid obtained by bronchoalveolar lavage (BAL) combined with clinical adjudication. From these patients, we analyzed 792 BAL fluid samples, including 310 serial samples, using flow cytometry (482 patients) and single-cell RNA-sequencing (170 patients; 263 samples, complemented by 9 healthy controls and 25 post-COVID-19 patients, yielding ~2.4 million single cells across 28 cell types), and extracted daily clinical data from the electronic health record (>15,000 patient-days). We used machine learning models to identify pathogen-specific host responses in the transcriptome of alveolar immune cells that were associated with changes in alveolar cell abundance and clinical features. Our results suggest that therapeutic strategies for pneumonia should be individualized to specific host-pathogen interactions.

Fields of Study & Subjects

Single-cell and spatial transcriptomics Pneumonia and Respiratory Infections Respiratory viral infections research

Publication details

Journal / source
bioRxiv (Cold Spring Harbor Laboratory)
Publisher
openRxiv
Publication date
14 May 2026
Language
EN
Document type
Preprint