Evidence map›Paper›PMID 39636373›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2024

Untargeted metabolomics and lipidomics in COVID-19 patient plasma reveals disease severity biomarkers.

Jinchun Sun, Megan Peters, Li-Rong Yu, Vikrant Vijay, Mallikarjun Bidarimath, Mona Agrawal, Armando S Flores-Torres, Amanda M Green, Keith Burkhart, Jessica Oliphant and 2 more

Abstract read
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In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Review
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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

12 authors.

Jinchun SunDivision of Systems Biology, National Center for Toxicological Research, United States Food and Drug Administration, 3900 NCTR Road, Jefferson, AR, 72079, USA. Jinchun.Sun@fda.hhs.gov.
Megan PetersDivision of Systems Biology, National Center for Toxicological Research, United States Food and Drug Administration, 3900 NCTR Road, Jefferson, AR, 72079, USA.
Li-Rong YuDivision of Systems Biology, National Center for Toxicological Research, United States Food and Drug Administration, 3900 NCTR Road, Jefferson, AR, 72079, USA.
Vikrant VijayDivision of Systems Biology, National Center for Toxicological Research, United States Food and Drug Administration, 3900 NCTR Road, Jefferson, AR, 72079, USA.
Mallikarjun BidarimathDivision of Systems Biology, National Center for Toxicological Research, United States Food and Drug Administration, 3900 NCTR Road, Jefferson, AR, 72079, USA.
Mona AgrawalDepartment of Pediatrics, University of Tennessee Health Science Center, Memphis, USA.
Armando S Flores-TorresDepartment of Pediatrics, University of Tennessee Health Science Center, Memphis, USA.
Amanda M GreenDepartment of Pediatrics, University of Tennessee Health Science Center, Memphis, USA.
Keith BurkhartOffice of Translational Sciences, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, USA.
Jessica OliphantDivision of Systems Biology, National Center for Toxicological Research, United States Food and Drug Administration, 3900 NCTR Road, Jefferson, AR, 72079, USA.
Heather S SmallwoodDepartment of Pediatrics, University of Tennessee Health Science Center, Memphis, USA.
Richard D BegerDivision of Systems Biology, National Center for Toxicological Research, United States Food and Drug Administration, 3900 NCTR Road, Jefferson, AR, 72079, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCoronavirus disease 2019 (COVID-19) has widely varying clinical severity. Currently, no single marker or panel of markers is considered standard of care for prediction of COVID-19 disease progression. The goal of this study is to gain mechanistic insights at the molecular level and to discover predictive biomarkers of severity of infection and outcomes among COVID-19 patients.

methodThis cohort study (n = 76) included participants aged 16-78 years who tested positive for SARS-CoV-2 and enrolled in Memphis, TN between August 2020 to July 2022. Clinical outcomes were classified as Non-severe (n = 39) or Severe (n = 37). LC/HRMS-based untargeted metabolomics/lipidomics was conducted to examine the difference in plasma metabolome and lipidome between the two groups.

resultsMetabolomics data indicated that the kynurenine pathway was activated in Severe participants. Significant increases in short chain acylcarnitines, and short and medium chain acylcarnitines containing OH-FA chain in Severe vs. Non-severe group, which indicates that (1) the energy pathway switched to FA β-oxidation to maintain the host energy homeostasis and to provide energy for virus proliferation; (2) ROS status was aggravated in Severe vs. Non-severe group. Based on PLS-DA and correlation analysis to severity score, IL-6, and creatine, a biomarker panel containing glucose (pro-inflammation), ceramide and S1P (inflammation related), 4-hydroxybutyric acid (oxidative stress related), testosterone sulfate (immune related), and creatine (kidney function), was discovered. This novel biomarker panel plus IL-6 with an AUC of 0.945 provides a better indication of COVID-19 clinical outcomes than that of IL-6 alone or the three clinical biomarker panel (IL-6, glucose and creatine) with AUCs of 0.875 or 0.892.

Indexed as

BiomarkersCOVID-19LipidomicsMetabolomicsSARS-CoV-2Severity of Illness IndexAdolescentAdultAgedCohort StudiesFemaleHumansMaleMiddle AgedYoung AdultBiomarkersClinical outcomesCoronavirus disease 2019 (COVID-19)MetabolomicsRisk factorsSeverity plasma biomarkers

Identifiers

PMID39636373

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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.