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1.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22282049

RESUMO

Altered myeloid inflammation and lymphopenia are hallmarks of severe infections, including with SARS-CoV-2. Here, we identified a gene program, defined by correlation with EN-RAGE (S100A12) gene expression, which was up-regulated in airway and blood myeloid cells from COVID-19 patients. The EN-RAGE program was expressed in 7 cohorts and observed in patients with both COVID-19 and acute respiratory distress syndrome (ARDS) from other causes. This program was associated with greater clinical severity and predicted future mechanical ventilation and death. EN-RAGE+ myeloid cells express features consistent with suppressor cell functionality, with low HLA-DR and high PD-L1 surface expression and higher expression of T cell-suppressive genes. Sustained EN-RAGE signature expression in airway and blood myeloid cells correlated with clinical severity and increasing expression of T cell exhaustion markers, such as PD-1. IL-6 treatment of monocytes in vitro upregulated many of the severity-associated genes in the EN-RAGE gene program, along with potential mediators of T cell suppression, such as IL-10. Blockade of IL-6 signaling by tocilizumab in a placebo-controlled clinical trial led to a rapid normalization of ENRAGE and T cell gene expression. This identifies IL-6 as a key driver of myeloid dysregulation associated with worse clinical outcomes in COVID-19 patients and provides insights into shared pathophysiological mechanisms in non-COVID-19 ARDS.

2.
- IMPACC group; Al Ozonoff; Joanna Schaenman; Naresh Doni Jayavelu; Carly E. Milliren; Carolyn S. Calfee; Charles B. Cairns; Monica Kraft; Lindsey R. Baden; Albert C. Shaw; Florian Krammer; Harm Van Bakel; Denise Esserman; Shanshan Liu; Ana Fernandez Sesma; Viviana Simon; David A. Hafler; Ruth R. Montgomery; Steven H. Kleinstein; Ofer Levy; Christian Bime; Elias K. Haddad; David J. Erle; Bali Pulendran; Kari C. Nadeau; Mark M. Davis; Catherine L. Hough; William B. Messer; Nelson I. Agudelo Higuita; Jordan P. Metcalf; Mark A. Atkinson; Scott C. Brakenridge; David B. Corry; Farrah Kheradmand; Lauren I. R. Ehrlich; Esther Melamed; Grace A. McComsey; Rafick Sekaly; Joann Diray-Arce; Bjoern Peters; Alison D. Augustine; Elaine F. Reed; Kerry McEnaney; Brenda Barton; Claudia Lentucci; Mehmet Saluvan; Ana C. Chang; Annmarie Hoch; Marisa Albert; Tanzia Shaheen; Alvin Kho; Sanya Thomas; Jing Chen; Maimouna D. Murphy; Mitchell Cooney; Scott Presnell; Leying Guan; Jeremy Gygi; Shrikant Pawar; Anderson Brito; Zain Khalil; James A. Overton; Randi Vita; Kerstin Westendorf; Cole Maguire; Slim Fourati; Ramin Salehi-Rad; Aleksandra Leligdowicz; Michael Matthay; Jonathan Singer; Kirsten N. Kangelaris; Carolyn M. Hendrickson; Matthew F. Krummel; Charles R. Langelier; Prescott G. Woodruff; Debra L. Powell; James N. Kim; Brent Simmons; I.Michael Goonewardene; Cecilia M. Smith; Mark Martens; Jarrod Mosier; Hiroki Kimura; Amy Sherman; Stephen Walsh; Nicolas Issa; Charles Dela Cruz; Shelli Farhadian; Akiko Iwasaki; Albert I. Ko; Evan J. Anderson; Aneesh Mehta; Jonathan E. Sevransky; Sharon Chinthrajah; Neera Ahuja; Angela Rogers; Maja Artandi; Sarah A.R. Siegel; Zhengchun Lu; Douglas A. Drevets; Brent R. Brown; Matthew L. Anderson; Faheem W. Guirgis; Rama V. Thyagarajan; Justin Rousseau; Dennis Wylie; Johanna Busch; Saurin Gandhi; Todd A. Triplett; George Yendewa; Olivia Giddings; Tatyana Vaysman; Bernard Khor; Adeeb Rahman; Daniel Stadlbauer; Jayeeta Dutta; Hui Xie; Seunghee Kim-Schulze; Ana Silvia Gonzalez-Reiche; Adriana van de Guchte; Holden T. Maecker; Keith Farrugia; Zenab Khan; Joanna Schaenman; Elaine F. Reed; Ramin Salehi-Rad; David Elashoff; Jenny Brook; Estefania Ramires-Sanchez; Megan Llamas; Adreanne Rivera; Claudia Perdomo; Dawn C. Ward; Clara E. Magyar; Jennifer Fulcher; Yumiko Abe-Jones; Saurabh Asthana; Alexander Beagle; Sharvari Bhide; Sidney A. Carrillo; Suzanna Chak; Rajani Ghale; Ana Gonzales; Alejandra Jauregui; Norman Jones; Tasha Lea; Deanna Lee; Raphael Lota; Jeff Milush; Viet Nguyen; Logan Pierce; Priya Prasad; Arjun Rao; Bushra Samad; Cole Shaw; Austin Sigman; Pratik Sinha; Alyssa Ward; Andrew - Willmore; Jenny Zhan; Sadeed Rashid; Nicklaus Rodriguez; Kevin Tang; Luz Torres Altamirano; Legna Betancourt; Cindy Curiel; Nicole Sutter; Maria Tercero Paz; Gayelan Tietje-Ulrich; Carolyn Leroux; Jennifer Connors; Mariana Bernui; Michele Kutzler; Carolyn Edwards; Edward Lee; Edward Lin; Brett Croen; Nicholas Semenza; Brandon Rogowski; Nataliya Melnyk; Kyra Woloszczuk; Gina Cusimano; Matthew Bell; Sara Furukawa; Renee McLin; Pamela Marrero; Julie Sheidy; George P. Tegos; Crystal Nagle; Nathan Mege; Kristen Ulring; Vicki Seyfert-Margolis; Michelle Conway; Dave Francisco; Allyson Molzahn; Heidi Erickson; Connie Cathleen Wilson; Ron Schunk; Trina Hughes; Bianca Sierra; Kinga K. Smolen; Michael Desjardins; Simon van Haren; Xhoi Mitre; Jessica Cauley; Xiofang Li; Alexandra Tong; Bethany Evans; Christina Montesano; Jose Humberto Licona; Jonathan Krauss; Jun Bai Park Chang; Natalie Izaguirre; Omkar Chaudhary; Andreas Coppi; John Fournier; Subhasis Mohanty; M. Catherine Muenker; Allison Nelson; Khadir Raddassi; Michael Rainone; William Ruff; Syim Salahuddin; Wade L. Schulz; Pavithra Vijayakumar; Haowei Wang; Elsio Wunder Jr.; H. Patrick Young; Yujiao Zhao; Miti Saksena; Deena Altman; Erna Kojic; Komal Srivastava; Lily Q. Eaker; Maria Carolina Bermudez; Katherine F. Beach; Levy A. Sominsky; Arman Azad; Juan Manuel Carreno; Gagandeep Singh; Ariel Raskin; Johnstone Tcheou; Dominika Bielak; Hisaaki Kawabata; Lubbertus CF Mulder; Giulio Kleiner; Laurel Bristow; Laila Hussaini; Kieffer Hellmeister; Hady Samaha; Andrew Cheng; Christine Spainhour; Erin M. Scherer; Brandi Johnson; Amer Bechnak; Caroline R. Ciric; Lauren Hewitt; Bernadine Panganiban; Chistopher Huerta; Jacob Usher; Erin Carter; Nina Mcnair; Susan Pereira Ribeiro; Alexandra S. Lee; Evan Do; Andrea Fernandes; Monali Manohar; Thomas Hagan; Catherine Blish; Hena Naz Din; Jonasel Roque; Samuel S. Yang; Amanda E. Brunton; Peter E. Sullivan; Matthew Strnad; Zoe L. Lyski; Felicity J. Coulter; John L. Booth; Lauren A. Sinko; Lyle Moldawer; Brittany Borrensen; Brittney Roth-Manning; Li-Zhen Song; Ebony Nelson; Megan Lewis-Smith; Jacob Smith; Pablo Guaman Tipan; Nadia Siles; Sam Bazzi; Janelle Geltman; Kerin Hurley; Giovanni Gabriele; Scott Sieg; Matthew C. Altman; Patrice M. Becker; Nadine Rouphael.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22273396

RESUMO

BackgroundBetter understanding of the association between characteristics of patients hospitalized with coronavirus disease 2019 (COVID-19) and outcome is needed to further improve upon patient management. MethodsImmunophenotyping Assessment in a COVID-19 Cohort (IMPACC) is a prospective, observational study of 1,164 patients from 20 hospitals across the United States. Disease severity was assessed using a 7-point ordinal scale based on degree of respiratory illness. Patients were prospectively surveyed for 1 year after discharge for post-acute sequalae of COVID-19 (PASC) through quarterly surveys. Demographics, comorbidities, radiographic findings, clinical laboratory values, SARS-CoV-2 PCR and serology were captured over a 28-day period. Multivariable logistic regression was performed. FindingsThe median age was 59 years (interquartile range [IQR] 20); 711 (61%) were men; overall mortality was 14%, and 228 (20%) required invasive mechanical ventilation. Unsupervised clustering of ordinal score over time revealed distinct disease course trajectories. Risk factors associated with prolonged hospitalization or death by day 28 included age [≥] 65 years (odds ratio [OR], 2.01; 95% CI 1.28-3.17), Hispanic ethnicity (OR, 1.71; 95% CI 1.13-2.57), elevated baseline creatinine (OR 2.80; 95% CI 1.63-4.80) or troponin (OR 1.89; 95% 1.03-3.47), baseline lymphopenia (OR 2.19; 95% CI 1.61-2.97), presence of infiltrate by chest imaging (OR 3.16; 95% CI 1.96-5.10), and high SARS-CoV2 viral load (OR 1.53; 95% CI 1.17-2.00). Fatal cases had the lowest ratio of SARS-CoV-2 antibody to viral load levels compared to other trajectories over time (p=0.001). 589 survivors (51%) completed at least one survey at follow-up with 305 (52%) having at least one symptom consistent with PASC, most commonly dyspnea (56% among symptomatic patients). Female sex was the only associated risk factor for PASC. InterpretationIntegration of PCR cycle threshold, and antibody values with demographics, comorbidities, and laboratory/radiographic findings identified risk factors for 28-day outcome severity, though only female sex was associated with PASC. Longitudinal clinical phenotyping offers important insights, and provides a framework for immunophenotyping for acute and long COVID-19. FundingNIH RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSWe did a systematic search of the PubMed database from January 1st, 2020 until April 24th, 2022 using the search terms: "hospitalized" AND "SARS-CoV-2" OR "COVID-19" AND "Pro-spective" AND "Antibody" OR "PCR" OR "long term follow up" and applying the following filters: "Multicenter Study" AND "Observational Study". No language restrictions were applied. While clinical, laboratory, and radiographic features associated with severe COVID-19 in hospitalized adults have been described, description of the kinetics of SARS-CoV-2 specific assays available to clinicians (e.g. PCR and binding antibody) and their integration with other variables is scarce for both short and long term follow up. The current literature is comprised of several studies with small sample size, cross-sectional design with laboratory data typically only recorded at a single point in time (e.g., on admission), limited clinical characteristics, variable duration of follow up, single-center setting, retrospective analyses, kinetics of either PCR or antibody testing but not both, and outcomes such as death or, mechanical ventilation that do not allow delineation of variations in clinical course. Added value of this studyIn our large longitudinal multicenter cohort, the description of outcome severity, was not limited to survival versus death, but encompassed a clinical trajectory approach leveraging longitudinal data based on time in hospital, disease severity by ordinal scale based on degree of respiratory illness, and presence or absence of limitations at discharge. Fatal COVID-19 cases had the lowest ratio of antibody to viral load levels over time as compared to non-fatal cases. Integration of PCR cycle threshold and antibody values with demographics, baseline comorbidities, and laboratory/radiographic findings identified additional risk factors for outcome severity over the first 28 days. However, female sex was the only variable associated with persistence of symptoms over time. Persistence of symptoms was not associated with clinical trajectory over the first 28 days, nor with antibody/viral loads from the acute phase. Implications of all the available evidenceThe described calculated ratio (binding IgG/PCR Ct value) is unique compared to other studies, reflecting host pathogen interactions and representing an accessible approach for patient risk stratification. Integration of SARS-CoV-2 viral load and binding antibody kinetics with other laboratory as well as clinical characteristics in hospitalized COVID-19 patients can identify patients likely to have the most severe short-term outcomes, but is not predictive of symptom persistence at one year post-discharge.

3.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22274628

RESUMO

IntroductionThe COVID-19 pandemic brought an urgent need to discover novel effective therapeutics for patients hospitalized with severe COVID-19. The ISPY COVID trial was designed and implemented in early 2020 to evaluate investigational agents rapidly and simultaneously on a phase 2 adaptive platform. This manuscript outlines the design, rationale, implementation, and challenges of the ISPY COVID trial during the first phase of trial activity from April 2020 until December 2021. Methods and analysisThe ISPY COVID Trial is a multi-center open label phase 2 platform trial in the United States designed to evaluate therapeutics that may have a large effect on improving outcomes from severe COVID-19. The ISPY COVID Trial network includes academic and community hospitals with significant geographic diversity across the country. Enrolled patients are randomized to receive one of up to four investigational agents or a control and are evaluated for a family of two primary outcomes--time to recovery and mortality. The statistical design uses a Bayesian model with "stopping" and "graduation" criteria designed to efficiently discard ineffective therapies and graduate promising agents for definitive efficacy trials. Each investigational agent arm enrolls to a maximum of 125 patients per arm and is compared to concurrent controls. As of December 2021, 11 investigational agent arms had been activated, and 8 arms were complete. Enrollment and adaptation of the trial design is ongoing. Ethics and disseminationISPY COVID operates under a central institutional review board via Wake Forest School of Medicine IRB00066805. Data generated from this trial will be reported in peer reviewed medical journals. Trial registration numberClinicaltrials.gov registration number NCT04488081 Strengths and limitations of this studyO_LIThe ISPY COVID Trial was developed in early 2020 to rapidly and simultaneously evaluate therapeutics for severe COVID-19 on an adaptive open label phase 2 platform C_LIO_LIThe ISPY COVID Adaptive Platform Trial Network is an academic-industry partnership that includes academic and community hospitals spanning a wide geographic area across the United States C_LIO_LIOf December 2021, 11 investigational agent arms have been activated on the ISPY COVID Trial Platform C_LIO_LIThe ISPY COVID Trial was designed to identify therapeutic agents with a large clinical effect for further testing in definitive efficacy trials--limitations to this approach include the risk of a type 2 error C_LI

4.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-489942

RESUMO

In the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, considerable focus has been placed on a model of viral entry into host epithelial populations, with a separate focus upon the responding immune system dysfunction that exacerbates or causes disease. We developed a precision-cut lung slice model to investigate very early host-viral pathogenesis and found that SARS-CoV-2 had a rapid and specific tropism for myeloid populations in the human lung. Infection of alveolar macrophages was partially dependent upon their expression of ACE2, and the infections were productive for amplifying virus, both findings which were in contrast with their neutralization of another pandemic virus, Influenza A virus (IAV). Compared to IAV, SARS-CoV-2 was extremely poor at inducing interferon-stimulated genes in infected myeloid cells, providing a window of opportunity for modest titers to amplify within these cells. Endotracheal aspirate samples from humans with the acute respiratory distress syndrome (ARDS) from COVID-19 confirmed the lung slice findings, revealing a persistent myeloid depot. In the early phase of SARS-CoV-2 infection, myeloid cells may provide a safe harbor for the virus with minimal immune stimulatory cues being generated, resulting in effective viral colonization and quenching of the immune system.

5.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-484467

RESUMO

Many studies have provided insights into the immune response to COVID-19; however, little is known about the immunological changes and immune signaling occurring during COVID-19 resolution. Individual heterogeneity and variable disease resolution timelines obscure unifying immune characteristics. Here, we collected and profiled >200 longitudinal peripheral blood samples from patients hospitalized with COVID-19, with other respiratory infections, and healthy individuals, using mass cytometry to measure immune cells and signaling states at single cell resolution. COVID-19 patients showed a unique immune composition and an early, coordinated and elevated immune cell signaling profile, which correlated with early hospital discharge. Intra-patient time course analysis tied to clinically relevant events of recovery revealed a conserved set of immunological processes that accompany, and are unique to, disease resolution and discharge. This immunological process, together with additional changes in CD4 regulatory T cells and basophils, accompanies recovery from respiratory failure and is associated with better clinical outcomes at the time of admission. Our work elucidates the biological timeline of immune recovery from COVID-19 and provides insights into the fundamental processes of COVID-19 resolution in hospitalized patients.

6.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-434529

RESUMO

Type I interferon (IFN-I) neutralizing autoantibodies have been found in some critical COVID-19 patients; however, their prevalence and longitudinal dynamics across the disease severity scale, and functional effects on circulating leukocytes remain unknown. Here, in 284 COVID-19 patients, we found IFN-I autoantibodies in 19% of critical, 6% of severe and none of the moderate cases. Longitudinal profiling of over 600,000 peripheral blood mononuclear cells using multiplexed single-cell epitope and transcriptome sequencing from 54 COVID-19 patients, 15 non-COVID-19 patients and 11 non-hospitalized healthy controls, revealed a lack of IFN-I stimulated gene (ISG-I) response in myeloid cells from critical cases, including those producing anti-IFN-I autoantibodies. Moreover, surface protein analysis showed an inverse correlation of the inhibitory receptor LAIR-1 with ISG-I expression response early in the disease course. This aberrant ISG-I response in critical patients with and without IFN-I autoantibodies, supports a unifying model for disease pathogenesis involving ISG-I suppression via convergent mechanisms.

7.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21253487

RESUMO

Secondary bacterial infections, including ventilator-associated pneumonia (VAP), lead to worse clinical outcomes and increased mortality following viral respiratory infections including in patients with coronavirus disease 2019 (COVID-19). Using a combination of tracheal aspirate bulk and single-cell RNA sequencing we assessed lower respiratory tract immune responses and microbiome dynamics in 23 COVID-19 patients, 10 of whom developed VAP, and eight critically ill uninfected controls. At a median of three days (range: 2-4 days) before VAP onset we observed a transcriptional signature of bacterial infection. At a median of 15 days prior to VAP onset (range: 8-38 days), we observed a striking impairment in immune signaling in COVID-19 patients who developed VAP. Longitudinal metatranscriptomic analysis revealed disruption of lung microbiome community composition in patients with VAP, providing a connection between dysregulated immune signaling and outgrowth of opportunistic pathogens. These findings suggest that COVID-19 patients who develop VAP have impaired antibacterial immune defense detectable weeks before secondary infection onset.

8.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20248552

RESUMO

We performed comparative lower respiratory tract transcriptional profiling of 52 critically ill patients with ARDS from COVID-19 or other etiologies, or without ARDS. We found no evidence of cytokine storm but instead observed complex host response dysregulation driven by genes with non-canonical roles in inflammation and immunity that were predicted to be modulated by dexamethasone. Compared to other viral ARDS, COVID-19 was characterized by impaired interferon-stimulated gene expression.

9.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20105171

RESUMO

We studied the host transcriptional response to SARS-CoV-2 by performing metagenomic sequencing of upper airway samples in 238 patients with COVID-19, other viral or non-viral acute respiratory illnesses (ARIs). Compared to other viral ARIs, COVID-19 was characterized by a diminished innate immune response, with reduced expression of genes involved in toll-like receptor and interleukin signaling, chemokine binding, neutrophil degranulation and interactions with lymphoid cells. Patients with COVID-19 also exhibited significantly reduced proportions of neutrophils and macrophages, and increased proportions of goblet, dendritic and B-cells, compared to other viral ARIs. Using machine learning, we built 26-, 10- and 3-gene classifiers that differentiated COVID-19 from other acute respiratory illnesses with AUCs of 0.980, 0.950 and 0.871, respectively. Classifier performance was stable at low viral loads, suggesting utility in settings where direct detection of viral nucleic acid may be unsuccessful. Taken together, our results illuminate unique aspects of the host transcriptional response to SARS-CoV-2 in comparison to other respiratory viruses and demonstrate the feasibility of COVID-19 diagnostics based on patient gene expression.

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