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Metabolic Profiling at COVID-19 Onset Shows Disease Severity and Sex-Specific Dysregulation
- Source :
- Frontiers in Immunology, Vol 13 (2022)
- Publication Year :
- 2022
- Publisher :
- Frontiers Media S.A., 2022.
-
Abstract
- Backgroundmetabolic changes through SARS-CoV-2 infection has been reported but not fully comprehended. This metabolic dysregulation affects multiple organs during COVID-19 and its early detection can be used as a prognosis marker of severity. Therefore, we aimed to characterize metabolic and cytokine profile at COVID-19 onset and its relationship with disease severity to identify metabolic profiles predicting disease progression.Material and Methodswe performed a retrospective cross-sectional study in 123 COVID-19 patients which were stratified as asymptomatic/mild, moderate and severe according to the highest COVID-19 severity status, and a group of healthy controls. We performed an untargeted plasma metabolic profiling (gas chromatography and capillary electrophoresis-mass spectrometry (GC and CE-MS)) and cytokine evaluation.ResultsAfter data filtering and identification we observed 105 metabolites dysregulated (66 GC-MS and 40 CE-MS) which shown different expression patterns for each COVID-19 severity status. These metabolites belonged to different metabolic pathways including amino acid, energy, and nitrogen metabolism among others. Severity-specific metabolic dysregulation was observed, as an increased transformation of L-tryptophan into L-kynurenine. Thus, metabolic profiling at hospital admission differentiate between severe and moderate patients in the later phase of worse evolution. Several plasma pro-inflammatory biomarkers showed significant correlation with deregulated metabolites, specially with L-kynurenine and L-tryptophan. Finally, we describe a strong sex-related dysregulation of metabolites, cytokines and chemokines between severe and moderate patients. In conclusion, metabolic profiling of COVID-19 patients at disease onset is a powerful tool to unravel the SARS-CoV-2 molecular pathogenesis.ConclusionsThis technique makes it possible to identify metabolic phenoconversion that predicts disease progression and explains the pronounced pathogenesis differences between sexes.
Details
- Language :
- English
- ISSN :
- 16643224
- Volume :
- 13
- Database :
- Directory of Open Access Journals
- Journal :
- Frontiers in Immunology
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.45cfd5a91e6148f08401ad2ca1f41d52
- Document Type :
- article
- Full Text :
- https://doi.org/10.3389/fimmu.2022.925558