Evidence map›Paper›PMID 35446921›Full record

ArticlePLoS pathogens2022

Profiling metabolites and lipoproteins in COMETA, an Italian cohort of COVID-19 patients.

Veronica Ghini, Gaia Meoni, Lorenzo Pelagatti, Tommaso Celli, Francesca Veneziani, Fabrizia Petrucci, Vieri Vannucchi, Laura Bertini, Claudio Luchinat, Giancarlo Landini and 1 more

Open access · goldAbstract read
In one paragraph

Article in PLoS pathogens, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
4.0field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

37 citing papers in PubMed, 47 citations in OpenAlex.

  1. Trial
  2. Recent Trends in Metabolomics by NMR Spectroscopy.Angewandte Chemie (International ed. in English) · 2026
    Review
  3. MTHFR allele and one-carbon metabolic profile predict severity of COVID-19.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 1 country.

Veronica GhiniDepartment of Chemistry, University of Florence, Sesto Fiorentino, Italy.
Gaia MeoniDepartment of Chemistry, University of Florence, Sesto Fiorentino, Italy.
Lorenzo PelagattiInternal Medicine, Santa Maria Nuova Hospital, Florence, Italy.
Tommaso CelliInternal Medicine, Santa Maria Nuova Hospital, Florence, Italy.
Francesca VenezianiLaboratory of Clinical Pathology, Santa Maria Nuova Hospital, Florence, Italy.
Fabrizia PetrucciLaboratory of Clinical Pathology, Santa Maria Nuova Hospital, Florence, Italy.
Vieri VannucchiInternal Medicine, Santa Maria Nuova Hospital, Florence, Italy.
Laura BertiniInternal Medicine, Santa Maria Nuova Hospital, Florence, Italy.
Claudio LuchinatDepartment of Chemistry, University of Florence, Sesto Fiorentino, Italy.
Giancarlo LandiniInternal Medicine, Santa Maria Nuova Hospital, Florence, Italy.
Paola TuranoDepartment of Chemistry, University of Florence, Sesto Fiorentino, Italy.ORCID 0000-0002-7683-8614
Santa Maria Nuova Hospital · ITInteruniversity Consortium for Magnetic Resonance · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolomics and lipidomics have been used in several studies to define the biochemical alterations induced by COVID-19 in comparison with healthy controls. Those studies highlighted the presence of a strong signature, attributable to both metabolites and lipoproteins/lipids. Here, 1H NMR spectra were acquired on EDTA-plasma from three groups of subjects: i) hospitalized COVID-19 positive patients (≤21 days from the first positive nasopharyngeal swab); ii) hospitalized COVID-19 positive patients (>21 days from the first positive nasopharyngeal swab); iii) subjects after 2-6 months from SARS-CoV-2 eradication. A Random Forest model built using the EDTA-plasma spectra of COVID-19 patients ≤21 days and Post COVID-19 subjects, provided a high discrimination accuracy (93.6%), indicating both the presence of a strong fingerprint of the acute infection and the substantial metabolic healing of Post COVID-19 subjects. The differences originate from significant alterations in the concentrations of 16 metabolites and 74 lipoprotein components. The model was then used to predict the spectra of COVID-19>21 days subjects. In this group, the metabolite levels are closer to those of the Post COVID-19 subjects than to those of the COVID-19≤21 days; the opposite occurs for the lipoproteins. Within the acute phase patients, characteristic trends in metabolite levels are observed as a function of the disease severity. The metabolites found altered in COVID-19≤21 days patients with respect to Post COVID-19 individuals overlap with acute infection biomarkers identified previously in comparison with healthy subjects. Along the trajectory towards healing, the metabolome reverts back to the "healthy" state faster than the lipoproteome.

Indexed as

COVID-19Edetic AcidHumansLipoproteinsMetabolomicsSARS-CoV-2Edetic AcidLipoproteins

Identifiers

PMID35446921
PMCPMC9022834
OpenAlexW4224286328

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.