Abstract

Introduction: Long-term pulmonary dysfunction (L-TPD) is one of the most critical manifestations of long-COVID. This lung affection has been associated with disease severity during the acute phase and the presence of previous comorbidities, however, the clinical manifestations, the concomitant consequences and the molecular pathways supporting this clinical condition remain unknown. The aim of this study was to identify and characterize L-TPD in patients with long-COVID and elucidate the main pathways and long-term consequences attributed to this condition by analyzing clinical parameters and functional tests supported by machine learning and serum proteome profiling. Methods: Patients with L-TPD were classified according to the results of their computer-tomography (CT) scan and diffusing capacity of the lungs for carbon monoxide adjusted for hemoglobin (DLCOc) tests at 4 and 12-months post-infection. Results: Regarding the acute phase, our data showed that L-TPD was favored in elderly patients with hypertension or insulin resistance, supported by pathways associated with vascular inflammation and chemotaxis of phagocytes, according to computer proteomics. Then, at 4-months post-infection, clinical and functional tests revealed that L-TPD patients exhibited a restrictive lung condition, impaired aerobic capacity and reduced muscular strength. At this time point, high circulating levels of platelets and CXCL9, and an inhibited FCgamma-receptor-mediated-phagocytosis due to reduced FcγRIII (CD16) expression in CD14+ monocytes was observed in patients with L-TPD. Finally, 1-year post infection, patients with L-TPD worsened metabolic syndrome and augmented body mass index in comparison with other patient groups. Discussion: Overall, our data demonstrated that CT scan and DLCOc identified patients with L-TPD after COVID-19. This condition was associated with vascular inflammation and impair phagocytosis of virus-antibody immune complexes by reduced FcγRIII expression. In addition, we conclude that COVID-19 survivors required a personalized follow-up and adequate intervention to reduce long-term sequelae and the appearance of further metabolic diseases.The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The study was supported by the Agencia Nacional de Investigación y Desarrollo (ANID) ANID/COVID1005 and ANID/ACT210085), Chilean Government. GL declares funding for research by the American Academy of Sleep Medicine (AASM, 254-FP-21). EN-L, SS, CC, RQ, and BA were funded by Fondecyt Regular 1211480 and COVID-19 Genomics Network (C19-GenoNet) ANID/ACT210085. Flow Cytometer was funded by EQM150061 (FONDEQUIP-ANID). UW was funded by Fondecyt Regular 1200459. DG-C has received financial support from Instituto de Salud Carlos III (Miguel Servet 2020: CP20/00041) co-funded by the European Union. CIBERES (CB07/06/2008) is an initiative of the Instituto de Salud Carlos III. MB and EN-L are funded by ANID/ATE220034. MH was supported by CLA-023023-2 FISAR

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Last time updated on 23/07/2025

This paper was published in Repositorio Universidad Mayor.

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