Post-acute sequelae of COVID-19 (PASC) represent an emerging global crisis. However, quantifiable risk-factors for PASC and their biological associations are poorly resolved. We executed a deep multi-omic, longitudinal investigation of 309 COVID-19 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data, and patient-reported symptoms. We resolved four PASC-anticipating risk factors at the time of initial COVID-19 diagnosis: type 2 diabetes, SARS-CoV-2 RNAemia, Epstein-Barr virus viremia, and specific autoantibodies. In patients with gastrointestinal PASC, SARS-CoV-2-specific and CMV-specific CD8 + T cells exhibited unique dynamics during recovery from COVID-19. Analysis of symptom-associated immunological signatures revealed coordinated immunity polarization into four endotypes exhibiting divergent acute severity and PASC. We find that immunological associations between PASC factors diminish over time leading to distinct convalescent immune states. Detectability of most PASC factors at COVID-19 diagnosis emphasizes the importance of early disease measurements for understanding emergent chronic conditions and suggests PASC treatment strategies.
A better understanding of the metabolic alterations in immune cells during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection may elucidate the wide diversity of clinical symptoms experienced by individuals with coronavirus disease 2019 (COVID-19). Here, we report the metabolic changes associated with the peripheral immune response of 198 individuals with COVID-19 through an integrated analysis of plasma metabolite and protein levels as well as single-cell multiomics analyses from serial blood draws collected during the first week after clinical diagnosis. We document the emergence of rare but metabolically dominant T cell subpopulations and find that increasing disease severity correlates with a bifurcation of monocytes into two metabolically distinct subsets. This integrated analysis reveals a robust interplay between plasma metabolites and cell-type-specific metabolic reprogramming networks that is associated with disease severity and could predict survival.
Human adaptive-like natural killer (NK) cells express low levels of FcεRIγ (FcRγ−/low) and are reported to accumulate during COVID-19 infection; however, the mechanism underlying and regulating FcRγ expression in NK cells has yet to be fully defined. We observed lower FcRγ protein expression in NK cell subsets from lung transplant patients during rapamycin treatment, suggesting a link with reduced mTOR activity. Further, FcRγ−/low NK cell subsets from healthy donors displayed reduced mTOR activity. We discovered that FcRγ upregulation is dependent on cell proliferation progression mediated by IL-2, IL-15, or IL-12, is sensitive to mTOR suppression, and is inhibited by TGFβ or IFNα. Accordingly, the accumulation of adaptive-like FcRγ−/low NK cells in COVID-19 patients corresponded to increased TGFβ and IFNα levels and disease severity. Our results show that an adaptive-like NK cell phenotype is induced by diminished cell proliferation and has an early prognostic value for increased TGFβ and IFNα levels in COVID-19 infection associated with disease severity.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.