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  1. Home
  3. Multi-omics Landscapes Reveal Heterogeneity In Long Covid Patients Characterized With Enhanced Neutrophil Activity.
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  3. Multi-omics Landscapes Reveal Heterogeneity In Long Covid Patients Characterized With Enhanced Neutrophil Activity.

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Multi-omics landscapes reveal heterogeneity in long COVID patients characterized with enhanced neutrophil activity.

Ke Lin1, Jianpeng Cai1, Jingxin Guo1,2,3

  • 1Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.

Journal of Translational Medicine
|August 12, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

Omicron variant causes long COVID, with a subgroup exhibiting neutrophil activation linked to inflammation and psychiatric symptoms. A 5-gene signature identifies this long COVID subtype.

Keywords:
Long COVIDNeutrophil degranulationOmicronProteomeTranscriptome

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Area of Science:

  • Immunology
  • Genomics
  • Proteomics
  • Infectious Disease Epidemiology

Background:

  • The Omicron variant's rapid spread has led to a significant number of individuals experiencing persistent symptoms, known as long COVID.
  • The underlying molecular and immune mechanisms driving long COVID, particularly in the context of the Omicron variant, remain poorly understood due to patient heterogeneity.

Purpose of the Study:

  • To investigate the molecular and immune profiles of individuals with long COVID following Omicron infection.
  • To identify potential biomarkers and patient subgroups within the long COVID population.
  • To explore the heterogeneity in long COVID pathogenesis.

Main Methods:

  • Recruited 66 participants: 22 healthy controls, 22 with long COVID (LC), and 22 without long COVID (NLC) 6 months post-Omicron infection.
  • Assessed plasma neutralizing antibody titers, SARS-CoV-2 viral load, and performed transcriptomic and proteomic profiling.
  • Utilized machine learning for data analysis and identification of distinct patient subgroups.

    • Main Results:

    • No residual SARS-CoV-2 or significant differences in neutralizing antibody titers were observed between LC and NLC groups at 6 months.
    • Transcriptomic and proteomic analyses stratified long COVID patients into neutrophil function upregulated (NU-LC) and downregulated (ND-LC) subgroups.
    • The NU-LC subgroup showed higher neutrophil counts and degranulation function, identifiable by 5 gene markers (ABCA13, CEACAM6, CRISP3, CTSG, BPI), with recovery by 12 months.

    Conclusions:

    • Long COVID exhibits heterogeneity, with a distinct subgroup characterized by neutrophil activation.
    • Neutrophil activation in long COVID may be associated with psychiatric symptoms and heightened inflammation.
    • A 5-gene signature serves as a potent discriminator for this neutrophil-activated long COVID subgroup, aiding therapeutic targeting and epidemiological studies.