Autoantigen profiling reveals a shared post-COVID signature in fully recovered and Long COVID patients.

2023
https://researcherprofiles.org/profile/370097899
36798288
Bodansky A, Wang CY, Saxena A, Mitchell A, Takahashi S, Anglin K, Huang B, Hoh R, Lu S, Goldberg SA, Romero J, Tran B, Kirtikar R, Grebe H, So M, Greenhouse B, Durstenfeld MS, Hsue PY, Hellmuth J, Kelly JD, Martin JN, Anderson MS, Deeks SG, Henrich TJ, DeRisi JL, Peluso MJ
Abstract

Some individuals do not return to baseline health following SARS-CoV-2 infection, leading to a condition known as Long COVID. The underlying pathophysiology of Long COVID remains unknown. Given that autoantibodies have been found to play a role in severity of COVID infection and certain other post-COVID sequelae, their potential role in Long COVID is important to investigate. Here we apply a well-established, unbiased, proteome-wide autoantibody detection technology (PhIP-Seq) to a robustly phenotyped cohort of 121 individuals with Long COVID, 64 individuals with prior COVID-19 who reported full recovery, and 57 pre-COVID controls. While a distinct autoreactive signature was detected which separates individuals with prior COVID infection from those never exposed to COVID, we did not detect patterns of autoreactivity that separate individuals with Long COVID relative to individuals fully recovered from SARS-CoV-2 infection. These data suggest that there are robust alterations in autoreactive antibody profiles due to infection; however, no association of autoreactive antibodies and Long COVID was apparent by this assay.