Explore potential plasma biomarkers of acute respiratory distress syndrome (ARDS) using GC-MS metabolomics analysis

Abstract

Objectives: The aim of this study was to analyse the metabolomics of patients with acute respiratory distress syndrome (ARDS) for the identification of metabolic markers with potential diagnostic and prognostic value.

Methods: The enrolled subjects included adult patients with ARDS that met the Berlin definition and healthy controls matched based on age, gender, and body mass index (BMI). Plasma samples were collected from 37 patients with ARDS and 28 healthy controls. The plasma metabolites were detected with gas chromatography-mass spectrometry (GC-MS), and the relevant metabolic pathways were predicted using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.

Results: A total of 222 metabolites were identified in our study, of which 128 were significantly altered in patients with ARDS compared with healthy controls. Phenylalanine, aspartic acid, and carbamic acid levels were significantly different between all groups of patients with ARDS classified from mild to severe. Furthermore, four metabolites, ornithine, caprylic acid, azetidine, and iminodiacetic acid, could serve as biomarkers to potentially predict the severity of ARDS. We discovered 92 pathways that were significantly different between ARDS and control groups, including 57 pathways linked to metabolism.

Conclusions: Plasma metabolomics may improve our understanding of ARDS biology. Specific products related to hypoxia may serve as early biomarkers for ARDS prediction, while the metabolites with significant correlations with partial pressure of arterial oxygen (PaO₂)/percentage of inspired oxygen (FiO₂) may play a role in determining ARDS severity. This study suggests that metabolomic analysis in patients at risk of ARDS or those with early ARDS may provide new insight into disease pathogenesis or prognosis.

Keywords: Acute respiratory distress syndrome/ARDS; Clinical research design; Gas chromatography–mass spectrometry/GC–MS; Metabolomics.