Plasma metabolomic and lipidomic alterations associated with COVID-19

  1. Di Wu
  2. Ting Shu
  3. Xiaobo Yang
  4. Jian-Xin Song
  5. Mingliang Zhang
  6. Chengye Yao
  7. Wen Liu
  8. Muhan Huang
  9. Yuan Yu
  10. Qingyu Yang
  11. Tingju Zhu
  12. Jiqian Xu
  13. Jingfang Mu
  14. Yaxin Wang
  15. Hong Wang
  16. Tang Tang
  17. Yujie Ren
  18. Yongran Wu
  19. Shu-Hai Lin
  20. Yang Qiu
  21. Ding-Yu Zhang
  22. You Shang
  23. Xi Zhou

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Abstract

The pandemic of the coronavirus disease 2019 (COVID-19) has become a global public health crisis. The symptoms of COVID-19 range from mild to severe, but the physiological changes associated with COVID-19 are barely understood. In this study, we performed targeted metabolomic and lipidomic analyses of plasma from a cohort of patients with COVID-19 who had experienced different symptoms. We found that metabolite and lipid alterations exhibit apparent correlation with the course of disease in these patients, indicating that the development of COVID-19 affected their whole-body metabolism. In particular, malic acid of the TCA cycle and carbamoyl phosphate of the urea cycle result in altered energy metabolism and hepatic dysfunction, respectively. It should be noted that carbamoyl phosphate is profoundly down-regulated in patients who died compared with patients with mild symptoms. And, more importantly, guanosine monophosphate (GMP), which is mediated not only by GMP synthase but also by CD39 and CD73, is significantly changed between healthy subjects and patients with COVID-19, as well as between the mild and fatal cases. In addition, dyslipidemia was observed in patients with COVID-19. Overall, the disturbed metabolic patterns have been found to align with the progress and severity of COVID-19. This work provides valuable knowledge about plasma biomarkers associated with COVID-19 and potential therapeutic targets, as well as an important resource for further studies of the pathogenesis of COVID-19.

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    SciScore for 10.1101/2020.04.05.20053819: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethics and Human Subjects: All work performed in this study was approved by the Wuhan Jinyintan Hospital Ethics Committee and written informed consent was obtained from patients.
    Consent: Ethics and Human Subjects: All work performed in this study was approved by the Wuhan Jinyintan Hospital Ethics Committee and written informed consent was obtained from patients.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Metabolite structure analysis referred to some existing mass spectrometry public databases, mainly including massbank (http://www.massbank.jp/), knapsack (http://kanaya.naist.jp/knapsack/)
    massbank
    suggested: (MassBank, RRID:SCR_015535)
    HMDB (http://www.hmdb.ca/), and Metlin (http://metlin.scripps.edu/index.php).
    HMDB
    suggested: (HMDB, RRID:SCR_007712)
    Metlin
    suggested: (METLIN, RRID:SCR_010500)
    To maximize identification of differences in metabolic profiles between groups, the orthogonal projection to latent structure discriminant analysis (OPLS-DA) model was applied using the MetaboAnalyst online tool (https://www.metaboanalyst.ca/).
    MetaboAnalyst
    suggested: (MetaboAnalyst, RRID:SCR_015539)
    KEGG) database (http://www.genome.jp/kegg/) to analyze the KEGG pathway enrichment to identify highly enriched metabolic pathways in differential metabolites or lipids.
    KEGG
    suggested: (KEGG, RRID:SCR_012773)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1093/nsr/nwaa086
  3. Version published to 10.1101/2020.04.05.20053819v3 on medRxiv
  4. Version published to 10.1101/2020.04.05.20053819v2 on medRxiv
  5. Version published to 10.1101/2020.04.05.20053819v1 on medRxiv