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1.
Preprint in English | bioRxiv | ID: ppbiorxiv-485922

ABSTRACT

Over two years into the COVID-19 pandemic, the human immune response to SARS-CoV-2 during the active disease phase has been extensively studied. However, the long-term impact after recovery, which is critical to advance our understanding SARS-CoV-2 and COVID-19-associated long-term complications, remains largely unknown. Herein, we characterized multi-omic single-cell profiles of circulating immune cells in the peripheral blood of 100 patients, including covenlesent COVID-19 and sero-negative controls. The reduced frequencies of both short-lived monocytes and long-lived regulatory T (Treg) cells are significantly associated with the patients recovered from severe COVID-19. Consistently, sc-RNA seq analysis reveals seven heterogeneous clusters of monocytes (M0-M6) and ten Treg clusters (T0-T9) featuring distinct molecular signatures and associated with COVID-19 severity. Asymptomatic patients contain the most abundant clusters of monocyte and Treg expressing high CD74 or IFN-responsive genes. In contrast, the patients recovered from a severe disease have shown two dominant inflammatory monocyte clusters with S100 family genes: S100A8 & A9 with high HLA-I whereas S100A4 & A6 with high HLA-II genes, a specific non-classical monocyte cluster with distinct IFITM family genes, and a unique TGF-{beta} high Treg Cluster. The outpatients and seronegative controls share most of the monocyte and Treg clusters patterns with high expression of HLA genes. Surprisingly, while presumably short-ived monocytes appear to have sustained alterations over 4 months, the decreased frequencies of long-lived Tregs (high HLA-DRA and S100A6) in the outpatients restore over the tested convalescent time (>= 4 months). Collectively, our study identifies sustained and dynamically altered monocytes and Treg clusters with distinct molecular signatures after recovery, associated with COVID-19 severity.

2.
Preprint in English | bioRxiv | ID: ppbiorxiv-407031

ABSTRACT

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes the coronavirus disease 2019 (COVID-19) with innate and adaptive immune response triggered in such patients by viral antigens. Both convalescent plasma and engineered high affinity human monoclonal antibodies have shown therapeutic potential to treat COVID-19. Whether additional antiviral soluble factors exist in peripheral blood remain understudied. Herein, we detected circulating exosomes that express the SARS-CoV-2 viral entry receptor angiotensin-converting enzyme 2 (ACE2) in plasma of both healthy donors and convalescent COVID-19 patients. We demonstrated that exosomal ACE2 competes with cellular ACE2 for neutralization of SARS-CoV-2 infection. ACE2-expressing (ACE2+) exosomes blocked the binding of the viral spike (S) protein RBD to ACE2+ cells in a dose dependent manner, which was 400- to 700-fold more potent than that of vesicle-free recombinant human ACE2 extracellular domain protein (rhACE2). As a consequence, exosomal ACE2 prevented SARS-CoV-2 pseudotype virus tethering and infection of human host cells at a 50-150 fold higher efficacy than rhACE2. A similar antiviral activity of exosomal ACE2 was further demonstrated to block wild-type live SARS-CoV-2 infection. Of note, depletion of ACE2+ exosomes from COVID-19 patient plasma impaired the ability to block SARS-CoV-2 RBD binding to host cells. Our data demonstrate that ACE2+ exosomes can serve as a decoy therapeutic and a possible innate antiviral mechanism to block SARS-CoV-2 infection.

3.
Griffin M Weber; Chuan Hong; Nathan P Palmer; Paul Avillach; Shawn N Murphy; Alba Gutiérrez-Sacristán; Zongqi Xia; Arnaud Serret-Larmande; Antoine Neuraz; Gilbert S. Omenn; Shyam Visweswaran; Jeffrey G Klann; Andrew M South; Ne Hooi Will Loh; Mario Cannataro; Brett K Beaulieu-Jones; Riccardo Bellazzi; Giuseppe Agapito; Mario Alessiani; Bruce J Aronow; Douglas S Bell; Antonio Bellasi; Vincent Benoit; Michele Beraghi; Martin Boeker; John Booth; Silvano Bosari; Florence T Bourgeois; Nicholas W Brown; Mauro Bucalo; Luca Chiovato; Lorenzo Chiudinelli; Arianna Dagliati; Batsal Devkota; Scott L DuVall; Robert W Follett; Thomas Ganslandt; Noelia García Barrio; Tobias Gradinger; Romain Griffier; David A Hanauer; John H Holmes; Petar Horki; Kenneth M Huling; Richard W Issitt; Vianney Jouhet; Mark S Keller; Detlef Kraska; Molei Liu; Yuan Luo; Kristine E Lynch; Alberto Malovini; Kenneth D Mandl; Chengsheng Mao; Anupama Maram; Michael E Matheny; Thomas Maulhardt; Maria Mazzitelli; Marianna Milano; Jason H Moore; Jeffrey S Morris; Michele Morris; Danielle L Mowery; Thomas P Naughton; Kee Yuan Ngiam; James B Norman; Lav P Patel; Miguel Pedrera Jimenez; Rachel B Ramoni; Emily R Schriver; Luigia Scudeller; Neil J Sebire; Pablo Serrano Balazote; Anastasia Spiridou; Amelia LM Tan; Byorn W.L. Tan; Valentina Tibollo; Carlo Torti; Enrico M Trecarichi; Michele Vitacca; Alberto Zambelli; Chiara Zucco; - The Consortium for Clinical Characterization of COVID-19 by EHR (4CE); Isaac S Kohane; Tianxi Cai; Gabriel A Brat.
Preprint in English | medRxiv | ID: ppmedrxiv-20247684

ABSTRACT

ObjectivesTo perform an international comparison of the trajectory of laboratory values among hospitalized patients with COVID-19 who develop severe disease and identify optimal timing of laboratory value collection to predict severity across hospitals and regions. DesignRetrospective cohort study. SettingThe Consortium for Clinical Characterization of COVID-19 by EHR (4CE), an international multi-site data-sharing collaborative of 342 hospitals in the US and in Europe. ParticipantsPatients hospitalized with COVID-19, admitted before or after PCR-confirmed result for SARS-CoV-2. Primary and secondary outcome measuresPatients were categorized as "ever-severe" or "never-severe" using the validated 4CE severity criteria. Eighteen laboratory tests associated with poor COVID-19-related outcomes were evaluated for predictive accuracy by area under the curve (AUC), compared between the severity categories. Subgroup analysis was performed to validate a subset of laboratory values as predictive of severity against a published algorithm. A subset of laboratory values (CRP, albumin, LDH, neutrophil count, D-dimer, and procalcitonin) was compared between North American and European sites for severity prediction. ResultsOf 36,447 patients with COVID-19, 19,953 (43.7%) were categorized as ever-severe. Most patients (78.7%) were 50 years of age or older and male (60.5%). Longitudinal trajectories of CRP, albumin, LDH, neutrophil count, D-dimer, and procalcitonin showed association with disease severity. Significant differences of laboratory values at admission were found between the two groups. With the exception of D-dimer, predictive discrimination of laboratory values did not improve after admission. Sub-group analysis using age, D-dimer, CRP, and lymphocyte count as predictive of severity at admission showed similar discrimination to a published algorithm (AUC=0.88 and 0.91, respectively). Both models deteriorated in predictive accuracy as the disease progressed. On average, no difference in severity prediction was found between North American and European sites. ConclusionsLaboratory test values at admission can be used to predict severity in patients with COVID-19. Prediction models show consistency across international sites highlighting the potential generalizability of these models.

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