ABSTRACT
As many as 10-30% of the over 760 million survivors of COVID-19 develop persistent symptoms, of which respiratory symptoms are among the most common. To understand the cellular and molecular basis for respiratory PASC, we combined a machine learning-based analysis of lung computed tomography (CT) with flow cytometry, single-cell RNA-sequencing analysis of bronchoalveolar lavage fluid and nasal curettage samples, and alveolar cytokine profiling in a cohort of thirty-five patients with respiratory symptoms and radiographic abnormalities more than 90 days after infection with COVID-19. CT images from patients with PASC revealed abnormalities involving 73% of the lung, which improved on subsequent imaging. Interstitial abnormalities suggestive of fibrosis on CT were associated with the increased numbers of neutrophils and presence of profibrotic monocyte-derived alveolar macrophages in BAL fluid, reflecting unresolved epithelial injury. Persistent infection with SARS-CoV-2 was identified in six patients and secondary bacterial or viral infections in two others. These findings suggest that despite its heterogenous clinical presentations, respiratory PASC with radiographic abnormalities results from a common pathobiology characterized by the ongoing recruitment of neutrophils and profibrotic monocyte-derived alveolar macrophages driving lung fibrosis with implications for diagnosis and therapy.