Chronic inflammation, neutrophil activity, and autoreactivity splits long COVID

Post-acute sequelae of COVID-19 (PASC) has heterogenous presentation and complex etiology. Here the authors profile peripheral blood of patients with PASC and analyze by machine-learning to identify immune and serology features that allow the stratification of PASC into inflammatory and non-inflammatory types for better diagnosis and therapy-planning. While immunologic correlates of COVID-19 have been widely reported, their associations with post-acute sequelae of COVID-19 (PASC) remain less clear. Due to the wide array of PASC presentations, understanding if specific disease features associate with discrete immune processes and therapeutic opportunities is important. Here we profile patients in the recovery phase of COVID-19 via proteomics screening and machine learning to find signatures of ongoing antiviral B cell development, immune-mediated fibrosis, and markers of cell death in PASC patients but not in controls with uncomplicated recovery. Plasma and immune cell profiling further allow the stratification of PASC into inflammatory and non-inflammatory types. Inflammatory PASC, identifiable through a refined set of 12 blood markers, displays evidence of ongoing neutrophil activity, B cell memory alterations, and building autoreactivity more than a year post COVID-19. Our work thus helps refine PASC categorization to aid in both therapeutic targeting and epidemiological investigation of PASC.