Integrated multi-omics characterization across clinically relevant subgroups of long COVID

Area of Science:

• Immunology
• Genomics
• Metabolomics
• Proteomics

Background:

• Post-acute sequelae of COVID-19 (PASC), commonly known as long COVID, affects a significant number of patients after SARS-CoV-2 infection.
• The heterogeneity of long COVID symptoms and underlying mechanisms presents a challenge for diagnosis and treatment.

Purpose of the Study:

• To investigate the distinct pathophysiological mechanisms and multi-omics signatures of different long COVID subgroups.
• To identify potential biomarkers for diagnosing and understanding the heterogeneity of long COVID.

Main Methods:

• Integrative multi-omics analyses including transcriptomics, proteomics, and metabolomics.
• Characterization of distinct molecular profiles for various long COVID subgroups, such as Multisystemic, Neurological, Cardio cerebral, Musculoskeletal + Systemic, and Cardiopulmonary.
• Identification of general and serum-specific protein biomarkers associated with long COVID and its subgroups.

Main Results:

• Long COVID patients exhibit elevated MAPK pathway activation, which is downregulated in recovered patients.
• Distinct multi-omics signatures were identified for each long COVID subgroup, revealing specific metabolic and signaling pathway alterations.
• Several potential biomarkers, including ABHD17A, CSNK1D, PSME4, SYVN1, CRH, FPGT, CBX6, and RBBP4, were identified for general and subgroup-specific diagnosis.

Conclusions:

• The study provides a shared and distinct pathophysiological explanation for PASC, highlighting its complex and heterogeneous nature.
• The identified multi-omics signatures and biomarkers offer a foundation for future diagnostic tools and targeted therapeutic interventions for long COVID.