Metabolomic profile of severe COVID-19 and a signature predictive of progression towards severe disease status: a prospective cohort study (METCOVID)

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.

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Publication Details

Journal
Scientific Reports
Published
2025-02-10
DOI
https://doi.org/10.1038/s41598-025-87288-x
Citations
3
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
2.42

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article

Metabolomic profile of severe COVID-19 and a signature predictive of progression towards severe disease status: a prospective cohort study (METCOVID)

Roger Mallol, María D. Balsalobre, Jordi Carratalà, Gabriela Abelenda-Alonso et al.
3 citations
Scientific Reports
Metabolomics and Mass Spectrometry Studies
2.42
article

Metabolomic profile of severe COVID-19 and a signature predictive of progression towards severe disease status: a prospective cohort study (METCOVID)

Roger Mallol, María D. Balsalobre, Jordi Carratalà, Gabriela Abelenda-Alonso, Carlota Gudiol, Alexander Rombauts
article en
3 citations

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.

Scientific ReportsVol. 15(1)
Instituto de Salud Carlos III (ES), Bellvitge University Hospital (ES), Institut d'Investigació Biomédica de Bellvitge (ES), Centro de Investigación Biomédica en Red (ES), Institut Universitari d'Investigació en Atenció Primària Jordi Gol (ES), Universitat Ramon Llull (ES), Universitat de Barcelona (ES)
Centres de Recerca de Catalunya, Generalitat de Catalunya, Instituto de Salud Carlos III, Departament de Salut, Generalitat de Catalunya, European Social Fund
Openalex Percentile: Top 13%
Metabolomics and Mass Spectrometry Studies
2.42
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