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Review

The role of multi-omics in the diagnosis of COVID-19 and the prediction of new therapeutic targets

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Pages 1101-1110 | Received 23 May 2022, Accepted 18 Jun 2022, Published online: 08 Jul 2022
 

ABSTRACT

The global pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus causing COVID-19, has led to more than 170 million confirmed cases in 223 countries and regions, claiming 3,872,457 lives. Some patients with COVID-19 have mild clinical symptoms despite severe respiratory failure, which greatly increases the difficulty of diagnosis and treatment. It is therefore necessary to identify biological characteristics of SARS-CoV-2, screen novel diagnostic and prognostic biomarkers, as well as to explore potential therapeutic targets for COVID-19. In this comprehensive review, we discuss the current published literature on COVID-19. We find that the comprehensive application of genomics, transcriptomics, proteomics and metabolomics is becoming increasingly important in the treatment of COVID-19. Multi-omics analysis platforms are expected to revolutionize the diagnosis and classification of COVID-19. This review aims to provide a reference for diagnosis, surveillance and clinical decision making related to COVID-19.

Highlights

  • Comprehensive application of Genomics, Transcriptomic, Proteomics and Metabolomics is important in the treatment of COVID-19.

  • Multi-omics analysis platforms support the diagnosis, surveillance and clinical decisions about COVID-19.

  • The long-term clinical value is early detection and prevention of a COVID-10 outbreak.

Acknowledgments

The reference materials were supported by the Shandong Cancer Hospital affiliated to Shandong University and the Harbin Medical University Cancer Hospital.

Data availability statement

Data sharing is not applicable to this article as no new data were created or analysed in this study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.