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Sex differences in global metabolomic profiles of COVID-19 patients, 2022, Diaz Escarcega et al

Discussion in 'Epidemics (including Covid-19, not Long Covid)' started by Andy, May 16, 2022.

  1. Andy

    Andy Committee Member

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    21,963
    Location:
    Hampshire, UK
    Abstract

    Coronavirus disease (COVID-19), caused by SARS-CoV-2, leads to symptoms ranging from asymptomatic disease to death. Although males are more susceptible to severe symptoms and higher mortality due to COVID-19, patient sex has rarely been examined. Sex-associated metabolic changes may implicate novel biomarkers and therapeutic targets to treat COVID-19. Here, using serum samples, we performed global metabolomic analyses of uninfected and SARS-CoV-2-positive male and female patients with severe COVID-19. Key metabolic pathways that demonstrated robust sex differences in COVID-19 groups, but not in controls, involved lipid metabolism, pentose pathway, bile acid metabolism, and microbiome-related metabolism of aromatic amino acids, including tryptophan and tyrosine. Unsupervised statistical analysis showed a profound sexual dimorphism in correlations between patient-specific clinical parameters and their global metabolic profiles. Identification of sex-specific metabolic changes in severe COVID-19 patients is an important knowledge source for researchers striving for development of potential sex-associated biomarkers and druggable targets for COVID-19 patients.

    Open access, https://www.nature.com/articles/s41419-022-04861-2
     
    alex3619, Trish and Peter Trewhitt like this.
  2. Trish

    Trish Moderator Staff Member

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    52,340
    Location:
    UK
    ???
     
    alktipping likes this.
  3. CRG

    CRG Senior Member (Voting Rights)

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    1,857
    Location:
    UK
    alktipping likes this.
  4. Midnattsol

    Midnattsol Moderator Staff Member

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    3,605
    "Unsupervised" would mean that when performing the analysis the program does not know what group a sample belongs to. They've used both supervised and unsupervised methods in this paper.
     
    alktipping, Trish and Mij like this.

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