Autoantibody landscapes in Long COVID with neurological symptoms show heterogeneity without a shared disease signature

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Abstract

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 performed a cross-cohort case-control analysis to detect autoantibodies in cerebrospinal fluid (CSF) and serum from n-LC participants. In the Yale COVID Mind Study cohort, CSF from n-LC participants and pre-pandemic and recovered controls was assessed using mouse brain immunofluorescence and proteome-wide phage immunoprecipitation sequencing (PhIP-Seq), followed by supervised modeling and orthogonal validation assays. In the Epidemiology, Immunology, and Clinical Characteristics of Emerging Infectious Diseases with Pandemic Potential (IDCRP EPICC) cohort, post-COVID sera collected prior to iPhone- or iPad-based cognitive screening were profiled by PhIP-Seq and compared between participants with and without cognitive impairment. RESULTS. CSF immunoreactivity on mouse brain tissue was observed in both n-LC and controls, with similar overall frequencies. PhIP-Seq identified sparse, patient-specific peptide reactivities to nuclear and neuronal proteins in CSF and serum. Supervised models provided limited discrimination between cases and controls. Candidate autoantigens had limited disease specificity on orthogonal testing. EPICC serum autoantibody profiling similarly failed to distinguish individuals with and without cognitive impairment. CONCLUSIONS. Across cohorts and compartments, n-LC was not associated with a shared CNS-directed autoantibody signature using the approaches employed. Observed heterogeneity may reflect biological diversity, although limited statistical power to detect a shared response cannot be excluded. FUNDING. Grants HU00012020067, HU00012120103, HU00011920111, R01NS125693, R01MH125737, and R01AI157488 from the Defense Health Program and NIH.

Authors

Debanjana Chakravarty, Ravi Dandekar, Vishal D. Lashkari, Iris Tilton, Lindsay McAlpine, Jennifer Chiarella, Allison Nelson, Thomas Ngo, PeiXi Chen, Chung-Yu Wang, Aditi Saxena, Bryan Castillo-Rojas, Kelsey Zorn, David R. Tribble, Timothy H. Burgess, Leah H. Rubin, Stephanie A. Richard, Brian K. Agan, Simon D. Pollett, Shelli Farhadian, Serena Spudich, Samuel J. Pleasure, Michael R. Wilson