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The Omics Landscape of Long COVID—A Comprehensive Systematic Review to Advance Biomarker, Target and Drug Discovery

  • Amsterdam Leukodystrophy Center
  • Amsterdam UMC
  • Haaglanden Medisch Centrum
  • Leiden University
  • Boston Children's Hospital
  • Harvard University
  • Broad Institute of MIT and Harvard
  • Massachusetts Institute of Technology
  • Assiut University

Research output: Contribution to journal › Review article › Academic › peer-review

149 Downloads (Pure)

Abstract

An estimated 10% of coronavirus disease (COVID-19) survivors suffer from persisting symptoms referred to as long COVID (LC), a condition for which approved treatment options are still lacking. This systematic review (PROSPERO: CRD42024499281) aimed to explore the pathophysiological mechanisms underlying LC and potential treatable traits across symptom-based phenotypes. We included studies with primary data, written in English, focusing on omics analyses of human samples from LC patients with persistent symptoms of at least 3 months. Our search in PubMed and Embase, conducted on January 8, 2024, identified 642 studies, of which 29 met the inclusion criteria after full-text assessment. The risk of bias was evaluated using the Joanna Briggs Institute appraisal tool. The synthesis of omics data, including genomics, transcriptomics, proteomics, metabolomics, and metagenomics, revealed common findings associated with fatigue, cardiovascular, pulmonary, neurological, and gastrointestinal phenotypes. Key findings included mitochondrial dysfunction, dysregulated microRNAs associated with pulmonary dysfunction, tissue impairment, blood–brain barrier disruption, coagulopathy, vascular dysfunction, microbiome disturbances, microbial-derived metabolite production and persistent inflammation. Limitations include cross-study heterogeneity and variability in sampling methods. Our review emphasizes the complexity of LC and the need for further longitudinal omics-integrated studies to advance the development of biomarkers and targeted treatments.
Original languageEnglish
Pages (from-to)932-948
Number of pages17
JournalAllergy: European Journal of Allergy and Clinical Immunology
Volume80
Issue number4
Early online date2025
DOIs
Publication statusPublished - Apr 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • long COVID
  • multi-omics
  • phenotypes
  • post-acute sequelae of COVID-19
  • post-viral condition

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