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Lipidomic signatures of ventilator-associated pneumonia in COVID-19 ARDS patients: A new frontier for diagnostic biomarkers - 09/05/26

Doi : 10.1016/j.rmr.2025.12.056 
A. Kassa-Sombo a, C. Verney a, b, , A. Pasquet b, J. Vaidie b, c, D. Brea a, V. Vasseur a, A. Cezard a, A. Lefevre d, C. David a, E. Piver e, L. Nadal-Desbarats d, f, P. Emond f, H. Blasco d, f, M. Si-Tahar a, A. Guillon a, b
a Research Center for Respiratory Diseases, Inserm Ua University of Tours, Tours, France 
b Intensive Care Unit, Tours University Hospital, Bd Tonnellé, Tours Cedex, France 
c Intensive Care Unit, Limoges University Hospital, Avenue Martin Luther King, Limoges Cedex, France 
d Imaging Brain & Neuropsychiatry iBraiN, Inserm U, Team Neurogenomic and Neuronal PathoPhysiology, University of Tours, Tours, France 
e Morphogenesis and Antigenicity of HIV and Hepatitis Viruses, Inserm U University of Tours, Tours, France 
f Metabolomic and Biochemical Analysis Facility, US ASB, Inserm, University of Tours, Tours, France 

Corresponding author.

Resumen

Background

Ventilator-associated pneumonia (VAP) is a significant complication in mechanically ventilated patients. Paradoxically, it lacks precise diagnostic criteria, making the identification of a reliable diagnostic indicator an unmet medical need [1] . Lipids are critical regulators of innate lung defense [2] . The aim of the study was to identify lipid alterations specific to VAP in tracheal aspirates of patients with ARDS.

Methods

Tracheal aspirates samples from ventilated patients were collected longitudinally from patients with COVID-19-related ARDS. Tracheal aspirates sampled at the day of VAP diagnosis were used to assess VAP specific lipidome and were compared with matched controls (patients without VAP). Lipid detection was performed using ultra-high-performance liquid chromatography with high resolution mass spectrometry. The statistical analysis included: unsupervised multivariate methods, partial least squares discriminant analysis (PLS-DA), orthogonal partial least squares discriminant analysis (OPLS-DA), and the area under the receiver operating characteristic (AUROC) curve to assess classification performance. The Benjamini-Hochberg adjusted p-value was used to control the false discovery rate.

Results

We studied 39 patients (26 VAP and 13 control patients). The characteristics of VAP and control patients were similar, including biological markers such as neutrophils, CRP, and PCT. The lipid signature, composed of 272 lipids, differed between VAP and control patients ( p = 0.003). Phosphatidylcholines were the most represented with 17 significantly upregulated and 6 downregulated lipids. OPLSDA identified 8 best candidates as VAP biomarkers with sphingomyelin (34: 1) and phosphatidylcholine (O-34: 1) presenting the best scores (AUROC = 0.85 [0.71–0.95] and 0.83 [0.66–0.94], respectively). Combinations of several lipid biomarkers did not improve the prediction accuracy. During ARDS, lung lipidome mostly resulted in breakdown product of host-pathogen interactions (surfactant and pulmonary cells).

Conclusion

We investigated VAP-specific lipids in tracheal aspirate and identified significant alterations in lipidomic profiles, likely driven by active infection dynamic and the breakdown of surfactant and pulmonary cells. Among the potential VAP biomarker candidates in COVID-19 ARDS, sphingomyelin (34: 1) and phosphatidylcholine (O-34: 1) demonstrated predictive performance for VAP that surpassed all previously tested biomarkers [3] Fig. 1 .

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© 2025  Publicado por Elsevier Masson SAS.
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