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. 2025 Jul 2.
doi: 10.1164/rccm.202502-0325OC. Online ahead of print.

The Plasma Proteome in Community-acquired Pneumonia: Pathophysiology, Outcome and 10-Year Risk

Affiliations

The Plasma Proteome in Community-acquired Pneumonia: Pathophysiology, Outcome and 10-Year Risk

Erik H A Michels et al. Am J Respir Crit Care Med. .

Abstract

Rationale: Community-acquired pneumonia (CAP) represents a significant health burden.

Objectives: We aimed to map the plasma proteome in patients with CAP and associate protein abundance with pathophysiology, tissue source, and outcome.

Methods: We measured the plasma proteome of CAP patients upon admission to a general ward using Olink technology (derivation cohort). Additional Olink measurements were performed in CAP patients admitted to the intensive care unit (ICU) and SARS-CoV-2 pneumonia patients across care settings (validation cohorts).

Measurements and main results: Of 2676 proteins analysed in 93 ward-CAP patients and 21 healthy controls, 904 (33.8%) were higher in CAP, 396 (14.8%) lower, and 1376 (51.4%) not different. More abundant proteins were associated with innate immune and mitosis pathways, and mainly originated from lung and cardiac tissue. 131 proteins associated with time to clinical stability (TCS), of which 124 (primarily related to monocyte/macrophage and RNA processing) were connected with a long TCS. Most TCS-associated proteins were differentially abundant in non-survivors versus survivors amongst 88 ICU-CAP (1.4- to 3.5-fold higher) and 305 SARS-CoV-2 pneumonia patients (1.16- to 1.35-fold lower or 1.14- to 2.65-fold higher; all p<0.05). In the general population (UK Biobank), 115 of 124 (92.7%) proteins correlated with long TCS were associated with an increased risk of pneumonia during a 10-year follow-up, while 6 of 7 (85.7%) proteins correlated with shorter TCS were associated with a lower risk of pneumonia.

Conclusions: This now publicly available CAP plasma proteome provides information on pathophysiological mechanisms and tissue involvement, and may support development of personalised therapies.

Keywords: biomarkers; clinical stability; long-term development; pneumonia; proteomics.

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