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Purpose:
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Post-acute infection syndromes (PAIS) may develop following acute viral disease. Infection with SARS-CoV-2 can result in the development of persistent sequelae comprising a PAIS designated as ?post-acute sequelae of COVID-19? (PASC) or ?Long COVID?. Individuals with Long COVID frequently report unremitting fatigue, post-exertional malaise, and a variety of cognitive and autonomic dysfunctions; however, the biological processes associated with the development and persistence of these symptoms are unclear. Here, 267 individuals with and without Long COVID were enrolled in a cross-sectional study that included multi-dimensional immune phenotyping and unbiased machine-learning methods to identify immunological features associated with Long COVID. Marked differences were noted in circulating myeloid and lymphocyte populations relative to matched controls, as well as evidence of exaggerated humoral responses directed against SARS-CoV-2 among participants with Long COVID. Further, higher antibody responses directed against non-SARS-CoV-2 viral pathogens were observed among individuals with Long COVID, particularly Epstein-Barr virus. Levels of soluble immune mediators and hormones varied among groups, with cortisol levels being lower among participants with Long COVID relative to matched controls. Integration of immune phenotyping data into unbiased machine learning models identified key features most strongly associated with Long COVID status. Collectively, these findings may help guide future studies into the pathobiology of Long COVID and aid in developing relevant biomarkers. |
