Uncovering host response in adults with severe community-acquired pneumonia: a proteomics and metabolomics perspective study
- Author:
Zhongshu Kuang
1
Author Information
1. Department of Emergency Medicine, Zhongshan Hospital, Fudan University, Shanghai 200030, China
- Publication Type:Journal Article
- Keywords:
Community-acquired pneumonia;
Proteomics;
Metabolomics;
Machine learning
- From:
World Journal of Emergency Medicine
2025;16(3):248-255
- CountryChina
- Language:English
-
Abstract:
BACKGROUND: Community-acquired pneumonia (CAP) represents a significant public health concern due to its widespread prevalence and substantial healthcare costs. This study was to utilize an integrated proteomic and metabolomic approach to explore the mechanisms involved in severe CAP.
METHODS: We integrated proteomics and metabolomics data to identify potential biomarkers for early diagnosis of severe CAP. Plasma samples were collected from 46 CAP patients (including 27 with severe CAP and 19 with non-severe CAP) and 19 healthy controls upon admission. A comprehensive analysis of the combined proteomics and metabolomics data was then performed to elucidate the key pathological features associated with CAP severity.
RESULTS: The proteomic and metabolic signature was markedly different between CAPs and healthy controls. Pathway analysis of changes revealed complement and coagulation cascades, ribosome, tumor necrosis factor (TNF) signaling pathway and lipid metabolic process as contributors to CAP. Furthermore, alterations in lipid metabolism, including sphingolipids and phosphatidylcholines (PCs), and dysregulation of cadherin binding were observed, potentially contributing to the development of severe CAP. Specifically, within the severe CAP group, sphingosine-1-phosphate (S1P) and apolipoproteins (APOC1 and APOA2) levels were downregulated, while S100P level was significantly upregulated.
CONCLUSION: The combined proteomic and metabolomic analysis may elucidate the complexity of CAP severity and inform the development of improved diagnostic tools.
