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Sci Rep . Metabolomic profile of severe COVID-19 and a signature predictive of progression towards severe disease status: a prospective cohort stud

tetano

Editor, Senior Moderator
Sci Rep


. 2025 Feb 10;15(1):4963.
doi: 10.1038/s41598-025-87288-x. Metabolomic profile of severe COVID-19 and a signature predictive of progression towards severe disease status: a prospective cohort study (METCOVID)

Roger Mallol[SUP] #[/SUP][SUP] 1 [/SUP], Alexander Rombauts[SUP] #[/SUP][SUP] 2 [/SUP], Gabriela Abelenda-Alonso[SUP] 3 4 [/SUP], Carlota Gudiol[SUP] 3 5 4 6 [/SUP], Marc Balsalobre[SUP] 7 [/SUP], Jordi Carratalà[SUP] 3 5 4 [/SUP]



Affiliations
Abstract

Profound metabolomic alterations occur during COVID-19. Early identification of the subset of hospitalised COVID-19 patients at risk of developing severe disease is critical for optimal resource utilization and prompt treatment. This work explores the metabolomic profile of hospitalised adult COVID-19 patients with severe disease, and establishes a predictive signature for disease progression. Within 48 hours of admission, serum samples were collected from 148 hospitalised patients for nuclear magnetic resonance (NMR) spectroscopy. Lipoprotein profiling was performed using the [SUP]1[/SUP]H-NMR-based Liposcale test, while low molecular weight metabolites were analysed using one-dimensional Carr-Purcell-Meiboom-Gill pulse spectroscopy and an adaptation of the Dolphin method for lipophilic extracts. Severe COVID-19, per WHO's Clinical Progression Scale, was characterized by altered lipoprotein distribution, elevated signals of glyc-A and glyc-B, a shift towards a catabolic state with elevated levels of branched-chain amino acids, and accumulation of ketone bodies. Furthermore, COVID-19 patients initially presenting with moderate disease but progressing to severe stages exhibited a distinct metabolic signature. Our multivariate model demonstrated a cross-validated AUC of 0.82 and 72% predictive accuracy for severity progression. NMR spectroscopy-based metabolomic profiling enables the identification of moderate COVID-19 patients at risk of disease progression, aiding in resource allocation and early intervention.

Keywords: COVID-19; Metabolomics; NMR; Prognosis; SARS-CoV-2; Severity; Spectroscopy.

 
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