Jul 2026· Journal of Immunology· Vol 215· 0 citations
TL;DR
Meta-analysis of publicly available Olink® data from Long COVID cohorts identified a conserved 60-protein Long COVID Signature (LCS) score revealing multi-compartment immune activation involving monocyte, neutrophil, and T/NK cell modules that may help direct future proteomic biomarker endpoints for Long COVID clinical trials.
Abstract
Post Acute Sequelae of COVID-19 (PASC), also called Long COVID, is an infection-associated chronic syndrome. Despite proposed viral persistence mechanisms, no therapeutic benefit was observed in randomized placebo-controlled trials of nirmatrelvir/ritonavir (NMV/r) in adults with Long COVID, including the Selective Trial of Paxlovid for PASC (STOP-PASC). This systems immunology analysis aimed to characterize immune profiles of participants during clinical trial intervention, identify biomarkers associated with patient-reported outcomes, and investigate potential mechanisms underlying Long COVID.
We performed comprehensive immunological profiling of 152 STOP-PASC trial participants using plasma proteomics (Olink® Explore HT 5400 panel), autoantigen arrays, viral serology, and microclot assays at baseline, day 15, and week 10. We assessed associations between immune features and patient-reported outcomes. We also conducted meta-analysis of nine independent Long COVID proteomics cohorts (n = 590 total samples) to identify conserved inflammatory signatures.
NMV/r treatment at day 15 compared with baseline induced transient changes in plasma proteins that normalized by week 10, primarily impacting myeloid cell/monocyte, lysosome, and complement activation pathways. Cardiovascular symptoms were negatively associated with SARS-CoV-2 antibody levels at baseline. No widespread differences in autoantibody profiles, Epstein-Barr virus (EBV) reactivation, or microclotting were observed between STOP-PASC Long COVID participants, pre-pandemic controls, and individuals without Long COVID. Meta-analysis of publicly available Olink® data from Long COVID cohorts identified a conserved 60-protein Long COVID Signature (LCS) score revealing multi-compartment immune activation involving monocyte, neutrophil, and T/NK cell modules.
These findings advance our understanding of Long COVID immunology and may help direct future proteomic biomarker endpoints for Long COVID clinical trials.
Pfizer
Computational and Systems Immunology (COMP)
BACKGROUND
Although antigenemia is associated with poor outcomes in respiratory viral infections, the underlying mechanisms driving viral bloodstream dissemination remain not fully understood. Herein, we aimed to characterise SARS-CoV-2 nucleocapsid (N)-antigenemia kinetics in patients with severe COVID-19. We also sou...
W. Mouton, K. Saker, Priscille Franc et al.· EBioMedicine· 0 citations
BACKGROUND
Post-acute sequelae of SARS-CoV-2 infection, more commonly known as long COVID, has emerged as a major health problem. The pathogenesis of long COVID is unknown, but among the leading hypotheses is viral persistence. We aimed to investigate whether the use of the SARS-CoV-2 antiviral nirmatrelvir-ritonavir i...
L. Baden, N. Shah, Sean T. H. Liu et al.· Lancet. Infectious Diseases...· 0 citations
BACKGROUND
Neurological Long COVID (n-LC) includes persistent cognitive and autonomic symptoms after SARS-CoV-2 infection. Prior studies of post-COVID conditions have described diverse humoral autoreactivity. It remains unclear whether n-LC is associated with a consistent CNS-directed humoral signature.
METHODS
We pe...
D. Chakravarty, R. Dandekar, Vishal D. Lashkari et al.· JCI Insight· 0 citations
PAS and PACVS exhibit substantial clinical and immunological overlap, including GPCR-directed autoreactivity and altered receptor-reactive T-cell responses, which suggest overlapping pathophysiological mechanisms.
J. Dinser, M. Anft, L. Wiemers et al.· medRxiv· 0 citations
The emergence of Post-COVID sequelae (PCS) represents a global challenge. However, understanding of biological mechanisms and the definition of quantifiable risk factors remains limited. This study employed machine learning-based classification to explore the potential of proteomics in identifying associations with ind...
Sepehr Golriz Khatami, Rieke Baumkötter, T. Köck et al.· Molecular & Cellular Proteom...· 0 citations
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