Advances in Understanding Long COVID: Pathophysiological Mechanisms and the Role of Omics Technologies in Biomarker Identification
- PMID: 40531392
- PMCID: PMC12436531
- DOI: 10.1007/s40291-025-00792-8
Advances in Understanding Long COVID: Pathophysiological Mechanisms and the Role of Omics Technologies in Biomarker Identification
Abstract
Long coronavirus disease (COVID) is a multisystem condition that affects a significant proportion of individuals following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, with persistent symptoms ranging from fatigue and cognitive dysfunction to cardiovascular disorders. It is estimated that 30-60% of infected individuals experience symptoms lasting more than 12 weeks. Despite advances in understanding acute infection, the pathophysiological mechanisms underlying long COVID remain unclear. Current hypotheses suggest that viral persistence, immune dysfunction, and metabolic alterations play central roles. Omics approaches, including metabolomics, proteomics, and lipidomics, have played a crucial role in investigating molecular changes, identifying biomarkers, and refining therapeutic strategies. This review discusses recent advances in understanding long COVID, addressing its mechanisms, risk factors, the impact of viral variants, and the role of vaccination, with an emphasis on the importance of omics technologies in elucidating this condition.
© 2025. The Author(s).
Conflict of interest statement
Declarations. Conflict of interest: The authors (M.D.d.S., T.S.d.S., C.G.M., M.C.M.V., A.K.B.T., L.F.L., S.M.B., R.D., and M.A.M) declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Author contributions: Conceptualization, M.D.d.S., T.S.d.S., C.G.M., M.C.M.V., A.K.B.T., L.F.L., S.M.B., R.D., and M.A.M.; methodology, M.D.d.S., T.S.d.S., C.G.M., M.C.M.V., A.K.B.T., L.F.L., S.M.B., R.D., and M.A.M.; writing—original draft preparation, M.D.d.S., T.S.d.S., C.G.M., M.C.M.V., A.K.B.T., L.F.L., S.M.B., R.D. and M.A.M.; writing—review and editing, M.D.d.S., T.S.d.S., C.G.M., M.C.M.V., A.K.B.T., L.F.L., S.M.B., R.D., and M.A.M. All authors have read and agreed to the published version of the manuscript. Funding: Open access funding provided by FCT|FCCN (b-on). This work was supported by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) (Process No. 200177/2022-2). Ethics approval: Not applicable. Consent (participation and publication): Not applicable. Data availability: Data sharing is not applicable to this article, as no datasets were generated or analyzed during the current study. Code availability: Not applicable.
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