The coronavirus disease 2019 (Covid-19), which caused respiratory problems in many
patients worldwide, led to more than 5 million deaths by the end of 2021. Experienced
symptoms vary from mild to severe illness. Understanding the infection severity to reach
a better prognosis could be useful to the clinics, and one study area to fulfill one
piece of this biological puzzle is metabolomics. The metabolite profile and/or levels
being monitored can help predict phenotype properties. Therefore, this study evaluated
plasma metabolomes of 110 individual samples, 57 from control patients and 53 from
recent positive cases of Covid-19 (IgM 98% reagent), representing mild to severe
symptoms, before any clinical intervention. Polar metabolites from plasma samples were
analyzed by quantitative
1
H NMR. Glycerol, 3-aminoisobutyrate, formate, and
glucuronate levels showed alterations in Covid-19 patients compared to those in the
control group (Tukey’s HSD
p
-value cutoff = 0.05), affecting the
lactate, phenylalanine, tyrosine, and tryptophan biosynthesis and
d
-glutamine,
d
-glutamate, and glycerolipid metabolisms. These metabolic alterations show
that SARS-CoV-2 infection led to disturbance in the energetic system, supporting the
viral replication and corroborating with the severe clinical conditions of patients. Six
polar metabolites (glycerol, acetate, 3-aminoisobutyrate, formate, glucuronate, and
lactate) were revealed by PLS-DA and predicted by ROC curves and ANOVA to be potential
prognostic metabolite panels for Covid-19 and considered clinically relevant for
predicting infection severity due to their straight roles in the lipid and energy
metabolism. Thus, metabolomics from samples of Covid-19 patients is a powerful tool for
a better understanding of the disease mechanism of action and metabolic consequences of
the infection in the human body and may corroborate allowing clinicians to intervene
quickly according to the needs of Covid-19 patients.