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Differential abundance of lipids and metabolites related to SARS-CoV-2 infection and susceptibility

Albóniga et al., Scientific Reports, doi:10.1038/s41598-023-40999-5
Sep 2023  
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Plasma metabolomic analysis showing significantly lower threonic acid levels for severe and mild COVID-19 cases compared with moderate cases.
Threonic acid is a metabolite of vitamin C. The expected relationship in non-linear and depends on many factors, however higher vitamin C supports higher threonic acid levels. The results are consistent with a potential relationship between low vitamin C levels and COVID-19 severity:
In mild cases, low viral loads/inflammation may result in lower conversion of vitamin C to threonic acid.
In moderate cases, conversion of vitamin C to threonic acid may increase.
In severe COVID-19, extensive inflammation and oxidative stress may deplete vitamin C and threonic acid levels. Alternatively, low vitamin C levels may increase risk of COVID-19 severity. In either case, the results suggest that supplementation of vitamin C may be beneficial.
Albóniga et al., 13 Sep 2023, Spain, peer-reviewed, 13 authors.
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Differential abundance of lipids and metabolites related to SARS-CoV-2 infection and susceptibility
Oihane E Albóniga, Elena Moreno, Javier Martínez-Sanz, Pilar Vizcarra, Raquel Ron, Jorge Díaz-Álvarez, Marta Rosas, Matilde Sánchez-Conde, Juan Carlos Galán, Santiago Angulo, Santiago Moreno, Coral Barbas, Sergio Serrano-Villar
Scientific Reports, doi:10.1038/s41598-023-40999-5
The mechanisms driving SARS-CoV-2 susceptibility remain poorly understood, especially the factors determining why unvaccinated individuals remain uninfected despite high-risk exposures. To understand lipid and metabolite profiles related with COVID-19 susceptibility and disease progression. We collected samples from an exceptional group of unvaccinated healthcare workers heavily exposed to SARS-CoV-2 but not infected ('non-susceptible') and subjects who became infected during the follow-up ('susceptible'), including non-hospitalized and hospitalized patients with different disease severity providing samples at early disease stages. Then, we analyzed their plasma metabolomic profiles using mass spectrometry coupled with liquid and gas chromatography. We show specific lipids profiles and metabolites that could explain SARS-CoV-2 susceptibility and COVID-19 severity. More importantly, non-susceptible individuals show a unique lipidomic pattern characterized by the upregulation of most lipids, especially ceramides and sphingomyelin, which could be interpreted as markers of low susceptibility to SARS-CoV-2 infection. This study strengthens the findings of other researchers about the importance of studying lipid profiles as relevant markers of SARS-CoV-2 pathogenesis. Why some unvaccinated individuals with repeated high-risk exposures to SARS-CoV-2 did not show evidence of COVID-19 during the first pandemic waves? Among the possible explanations, host factors have been shown drive SARS-CoV-2 susceptibility and COVID-19 disease severity 1 . Consequently, omics studies, including metabolomic profiling, have gained attention to elucidate biochemical pathways affected by SARS-CoV-2 infection 2-4 . Metabolic profiles can be obtained by mass spectrometry (MS) coupled with different separation techniques, such as liquid chromatography (LC-MS), gas chromatography (GC-MS), or capillary electrophoresis (CE-MS). These techniques allow the identification of different types of molecules, such as amino acids, lipids, and glycoproteins 5 . Since it is not possible to analyze the vast amount of metabolites present in plasma samples using only one technique, the combination of these complementary techniques provides a broader picture of the metabolic pathways and their metabolites under selected conditions. The COVID-19 pandemic has generated a considerable economic and societal impact 6 including long-term effects 7,8 due to Long COVID conditions 9 . Abnormal immune responses to SARS-CoV-2 characterized by impaired macrophage, neutrophil, and dendritic functions or decreased IFN-ɣ production appear to explain adverse clinical outcomes [10] [11] [12] . Furthermore, several comorbidities such as immunosuppression, diabetes, pulmonary disease, or cardiovascular disease negatively affect disease progression 13, 14 . Lipidomics and metabolomics
Competing interests The authors declare no competing interests. Additional information Supplementary Information The online version contains supplementary material available at https:// doi. org/ 10. 1038/ s41598-023-40999-5. Correspondence and requests for materials should be addressed to S.S.-V. Reprints and permissions information is available at Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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