Document Type

Article

Publication Date

1-1-2023

Keywords

JGM, Humans, COVID-19, SARS-CoV-2, Plasma, Nucleic Acids, Lipids

JAX Source

Front Immunol. 2023;14:1221493.

ISSN

1664-3224

PMID

37705971

DOI

https://doi.org/10.3389/fimmu.2023.1221493

Grant

This study is supported in part by the Department of Science and Technology of Shaanxi Province (Grant No. 2020ZDXM2-SF- 02) (CZ and BS) and operational funds from The First Affiliated Hospital of Xi’an Jiaotong University (CZ and BS).

Abstract

BACKGROUND: COVID-19 is a highly infectious respiratory disease that can manifest in various clinical presentations. Although many studies have reported the lipidomic signature of COVID-19, the molecular changes in asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected individuals remain elusive.

METHODS: This study combined a comprehensive lipidomic analysis of 220 plasma samples from 166 subjects: 62 healthy controls, 16 asymptomatic infections, and 88 COVID-19 patients. We quantified 732 lipids separately in this cohort. We performed a difference analysis, validated with machine learning models, and also performed GO and KEGG pathway enrichment analysis using differential lipids from different control groups.

RESULTS: We found 175 differentially expressed lipids associated with SASR-CoV-2 infection, disease severity, and viral persistence in patients with COVID-19. PC (O-20:1/20:1), PC (O-20:1/20:0), and PC (O-18:0/18:1) better distinguished asymptomatic infected individuals from normal individuals. Furthermore, some patients tested positive for SARS-CoV-2 nucleic acid by RT-PCR but did not become negative for a longer period of time (≥60 days, designated here as long-term nucleic acid test positive, LTNP), whereas other patients became negative for viral nucleic acid in a shorter period of time (≤45 days, designated as short-term nucleic acid test positive, STNP). We have found that TG (14:1/14:1/18:2) and FFA (4:0) were differentially expressed in LTNP and STNP.

CONCLUSION: In summary, the integration of lipid information can help us discover novel biomarkers to identify asymptomatic individuals and further deepen our understanding of the molecular pathogenesis of COVID-19.

Comments

This is an open-access article distributed under the terms of the Creative Commons Attribution License(CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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