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Owens K, Esmaeili S, Schiffer JT. Heterogeneous SARS-CoV-2 kinetics due to variable timing and intensity of immune responses. JCI Insight 2024; 9:e176286. [PMID: 38573774 PMCID: PMC11141931 DOI: 10.1172/jci.insight.176286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 03/27/2024] [Indexed: 04/06/2024] Open
Abstract
The viral kinetics of documented SARS-CoV-2 infections exhibit a high degree of interindividual variability. We identified 6 distinct viral shedding patterns, which differed according to peak viral load, duration, expansion rate, and clearance rate, by clustering data from 768 infections in the National Basketball Association cohort. Omicron variant infections in previously vaccinated individuals generally led to lower cumulative shedding levels of SARS-CoV-2 than other scenarios. We then developed a mechanistic mathematical model that recapitulated 1,510 observed viral trajectories, including viral rebound and cases of reinfection. Lower peak viral loads were explained by a more rapid and sustained transition of susceptible cells to a refractory state during infection as well as by an earlier and more potent late, cytolytic immune response. Our results suggest that viral elimination occurs more rapidly during Omicron infection, following vaccination, and following reinfection due to enhanced innate and acquired immune responses. Because viral load has been linked with COVID-19 severity and transmission risk, our model provides a framework for understanding the wide range of observed SARS-CoV-2 infection outcomes.
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Affiliation(s)
- Katherine Owens
- Fred Hutchinson Cancer Center, Vaccine and Infectious Diseases Division, Seattle, Washington, USA
| | - Shadisadat Esmaeili
- Fred Hutchinson Cancer Center, Vaccine and Infectious Diseases Division, Seattle, Washington, USA
| | - Joshua T. Schiffer
- Fred Hutchinson Cancer Center, Vaccine and Infectious Diseases Division, Seattle, Washington, USA
- University of Washington, Department of Medicine, Seattle, Washington, USA
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Webber E, Bishop S, Drain PK, Dupuis V, Garza L, Gregor C, Hassell L, Ibarra G, Kessler L, Ko L, Lambert A, Lyon V, Rowe C, Singleton M, Thompson M, Warne T, Westbroek W, Adams A. Critical lessons from a pragmatic randomized trial of home-based COVID-19 testing in rural Native American and Latino communities. J Rural Health 2024. [PMID: 38449317 DOI: 10.1111/jrh.12830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 01/25/2024] [Accepted: 02/12/2024] [Indexed: 03/08/2024]
Abstract
PURPOSE Native Americans and Latinos have higher COVID-19 infection and mortality rates and may have limited access to diagnostic testing. Home-based testing may improve access to care in rural and underserved populations. This study tests the effect of community health worker (CHW) support on accessibility, feasibility, and completion of COVID-19 home testing among Native American and Latino adults living on the Flathead Reservation in Montana and in Yakima Valley, Washington. METHODS A two-arm, multisite, pragmatic randomized controlled trial was conducted using block randomization stratified by site and participant age. Active arm participants received CHW assistance with online COVID-19 test kit registration and virtual swabbing support. The passive arm participants received standard-of-care support from the kit vendor. Logistic regression modeled the association between study arm and test completion (primary outcome) and between study arm and test completion with return of valid test results (secondary outcome). Responses to posttest surveys and interviews were summarized using deductive thematic analysis. FINDINGS Overall, 63% of participants (n = 268) completed COVID-19 tests, and 50% completed tests yielding a valid result. Active arm participants had higher odds of test completion (odds ratio: 1.66, 95% confidence interval [1.01, 2.75]). Differences were most pronounced among adults ≥60 years. Participants cited ease of use and not having to leave home as positive aspects, and transportation and mailing issues as negative aspects of home-based testing. CONCLUSIONS CHW support led to higher COVID-19 test completion rates, particularly among older adults. Significant testing barriers included language, educational level, rurality, and test kit issues.
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Affiliation(s)
- Eliza Webber
- Center for American Indian and Rural Health Equity, Montana State University, Bozeman, Montana, USA
| | - Sonia Bishop
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Paul K Drain
- Department of Global Health, University of Washington, Seattle, Washington, USA
- Department of Medicine, University of Washington, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Virgil Dupuis
- Extension Office, Salish Kootenai College, Pablo, Montana, USA
| | - Lorenzo Garza
- Family and Community Engagement, Sunnyside School District, Sunnyside, Washington, USA
| | - Charlie Gregor
- Institute of Translational Health Sciences, University of Washington, Seattle, Washington, USA
| | - Laurie Hassell
- Institute of Translational Health Sciences, University of Washington, Seattle, Washington, USA
| | - Geno Ibarra
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Larry Kessler
- Institute of Translational Health Sciences, University of Washington, Seattle, Washington, USA
| | - Linda Ko
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
- Institute of Translational Health Sciences, University of Washington, Seattle, Washington, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, Washington, USA
| | - Alison Lambert
- Department of Medicine, University of Washington, Seattle, Washington, USA
- Institute of Translational Health Sciences, University of Washington, Seattle, Washington, USA
- Providence Medical Research Center, Providence Health Care, Spokane, Washington, USA
| | - Victoria Lyon
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Carly Rowe
- Institute of Translational Health Sciences, University of Washington, Seattle, Washington, USA
| | - Michael Singleton
- Institute of Translational Health Sciences, University of Washington, Seattle, Washington, USA
| | - Matthew Thompson
- Institute of Translational Health Sciences, University of Washington, Seattle, Washington, USA
- Department of Family Medicine, University of Washington, Seattle, Washington, USA
| | - Teresa Warne
- Center for American Indian and Rural Health Equity, Montana State University, Bozeman, Montana, USA
| | - Wendy Westbroek
- Extension Office, Salish Kootenai College, Pablo, Montana, USA
| | - Alexandra Adams
- Center for American Indian and Rural Health Equity, Montana State University, Bozeman, Montana, USA
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Owens K, Esmaeili-Wellman S, Schiffer JT. Heterogeneous SARS-CoV-2 kinetics due to variable timing and intensity of immune responses. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.08.20.23294350. [PMID: 37662228 PMCID: PMC10473815 DOI: 10.1101/2023.08.20.23294350] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
The viral kinetics of documented SARS-CoV-2 infections exhibit a high degree of inter-individual variability. We identified six distinct viral shedding patterns, which differed according to peak viral load, duration, expansion rate and clearance rate, by clustering data from 768 infections in the National Basketball Association cohort. Omicron variant infections in previously vaccinated individuals generally led to lower cumulative shedding levels of SARS-CoV-2 than other scenarios. We then developed a mechanistic mathematical model that recapitulated 1510 observed viral trajectories, including viral rebound and cases of reinfection. Lower peak viral loads were explained by a more rapid and sustained transition of susceptible cells to a refractory state during infection, as well as an earlier and more potent late, cytolytic immune response. Our results suggest that viral elimination occurs more rapidly during omicron infection, following vaccination, and following re-infection due to enhanced innate and acquired immune responses. Because viral load has been linked with COVID-19 severity and transmission risk, our model provides a framework for understanding the wide range of observed SARS-CoV-2 infection outcomes.
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Affiliation(s)
- Katherine Owens
- Fred Hutchinson Cancer Center, Vaccine and Infectious Diseases Division
| | | | - Joshua T Schiffer
- Fred Hutchinson Cancer Center, Vaccine and Infectious Diseases Division
- University of Washington, Department of Medicine
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Lim FY, Kim SY, Kulkarni KN, Blazevic RL, Kimball LE, Lea HG, Haack AJ, Gower MS, Stevens-Ayers T, Starita LM, Boeckh M, Schiffer JT, Hyrien O, Theberge AB, Waghmare A. Longitudinal home self-collection of capillary blood using homeRNA correlates interferon and innate viral defense pathways with SARS-CoV-2 viral clearance. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.01.24.23284913. [PMID: 37034678 PMCID: PMC10081427 DOI: 10.1101/2023.01.24.23284913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/13/2023]
Abstract
Blood transcriptional profiling is a powerful tool to evaluate immune responses to infection; however, blood collection via traditional phlebotomy remains a barrier to precise characterization of the immune response in dynamic infections (e.g., respiratory viruses). Here we present an at-home self-collection methodology, homeRNA, to study the host transcriptional response during acute SARS-CoV-2 infections. This method uniquely enables high frequency measurement of the host immune kinetics in non-hospitalized adults during the acute and most dynamic stage of their infection. COVID-19+ and healthy participants self-collected blood every other day for two weeks with daily nasal swabs and symptom surveys to track viral load kinetics and symptom burden, respectively. While healthy uninfected participants showed remarkably stable immune kinetics with no significant dynamic genes, COVID-19+ participants, on the contrary, depicted a robust response with over 418 dynamic genes associated with interferon and innate viral defense pathways. When stratified by vaccination status, we detected distinct response signatures between unvaccinated and breakthrough (vaccinated) infection subgroups; unvaccinated individuals portrayed a response repertoire characterized by higher innate antiviral responses, interferon signaling, and cytotoxic lymphocyte responses while breakthrough infections portrayed lower levels of interferon signaling and enhanced early cell-mediated response. Leveraging cross-platform longitudinal sampling (nasal swabs and blood), we observed that IFI27, a key viral response gene, tracked closely with SARS-CoV-2 viral clearance in individual participants. Taken together, these results demonstrate that at-home sampling can capture key host antiviral responses and facilitate frequent longitudinal sampling to detect transient host immune kinetics during dynamic immune states.
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Affiliation(s)
- Fang Yun Lim
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center; Seattle, Washington, U.S.A
- Department of Chemistry, University of Washington; Seattle, Washington, U.S.A
| | - Soo-Young Kim
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center; Seattle, Washington, U.S.A
| | - Karisma N. Kulkarni
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center; Seattle, Washington, U.S.A
| | - Rachel L. Blazevic
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center; Seattle, Washington, U.S.A
| | - Louise E. Kimball
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center; Seattle, Washington, U.S.A
| | - Hannah G. Lea
- Department of Chemistry, University of Washington; Seattle, Washington, U.S.A
| | - Amanda J. Haack
- Department of Chemistry, University of Washington; Seattle, Washington, U.S.A
| | - Maia. S. Gower
- Department of Chemistry, University of Washington; Seattle, Washington, U.S.A
| | - Terry Stevens-Ayers
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center; Seattle, Washington, U.S.A
| | - Lea M. Starita
- Brotman Baty Institute, University of Washington, Seattle
- Department of Genome Sciences, University of Washington, Seattle
| | - Michael Boeckh
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center; Seattle, Washington, U.S.A
- Department of Medicine, University of Washington; Seattle, Washington, U.S.A
| | - Joshua T. Schiffer
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center; Seattle, Washington, U.S.A
- Department of Medicine, University of Washington; Seattle, Washington, U.S.A
| | - Ollivier Hyrien
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center; Seattle, Washington, U.S.A
| | - Ashleigh B. Theberge
- Department of Chemistry, University of Washington; Seattle, Washington, U.S.A
- Department of Urology, University of Washington; Seattle, Washington, U.S.A
| | - Alpana Waghmare
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center; Seattle, Washington, U.S.A
- Department of Pediatrics, University of Washington; Seattle, Washington, U.S.A
- Seattle Children’s Research Institute; Seattle, Washington, U.S.A
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Stankiewicz Karita HC, Dong TQ, Johnston C, Neuzil KM, Paasche-Orlow MK, Kissinger PJ, Bershteyn A, Thorpe LE, Deming M, Kottkamp A, Laufer M, Landovitz RJ, Luk A, Hoffman R, Roychoudhury P, Magaret CA, Greninger AL, Huang ML, Jerome KR, Wener M, Celum C, Chu HY, Baeten JM, Wald A, Barnabas RV, Brown ER. Trajectory of Viral RNA Load Among Persons With Incident SARS-CoV-2 G614 Infection (Wuhan Strain) in Association With COVID-19 Symptom Onset and Severity. JAMA Netw Open 2022; 5:e2142796. [PMID: 35006245 PMCID: PMC8749477 DOI: 10.1001/jamanetworkopen.2021.42796] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
IMPORTANCE The SARS-CoV-2 viral trajectory has not been well characterized in incident infections. These data are needed to inform natural history, prevention practices, and therapeutic development. OBJECTIVE To characterize early SARS-CoV-2 viral RNA load (hereafter referred to as viral load) in individuals with incident infections in association with COVID-19 symptom onset and severity. DESIGN, SETTING, AND PARTICIPANTS This prospective cohort study was a secondary data analysis of a remotely conducted study that enrolled 829 asymptomatic community-based participants recently exposed (<96 hours) to persons with SARS-CoV-2 from 41 US states from March 31 to August 21, 2020. Two cohorts were studied: (1) participants who were SARS-CoV-2 negative at baseline and tested positive during study follow-up, and (2) participants who had 2 or more positive swabs during follow-up, regardless of the initial (baseline) swab result. Participants collected daily midturbinate swab samples for SARS-CoV-2 RNA detection and maintained symptom diaries for 14 days. EXPOSURE Laboratory-confirmed SARS-CoV-2 infection. MAIN OUTCOMES AND MEASURES The observed SARS-CoV-2 viral load among incident infections was summarized, and piecewise linear mixed-effects models were used to estimate the characteristics of viral trajectories in association with COVID-19 symptom onset and severity. RESULTS A total of 97 participants (55 women [57%]; median age, 37 years [IQR, 27-52 years]) developed incident infections during follow-up. Forty-two participants (43%) had viral shedding for 1 day (median peak viral load cycle threshold [Ct] value, 38.5 [95% CI, 38.3-39.0]), 18 (19%) for 2 to 6 days (median Ct value, 36.7 [95% CI, 30.2-38.1]), and 31 (32%) for 7 days or more (median Ct value, 18.3 [95% CI, 17.4-22.0]). The cycle threshold value has an inverse association with viral load. Six participants (6%) had 1 to 6 days of viral shedding with censored duration. The peak mean (SD) viral load was observed on day 3 of shedding (Ct value, 33.8 [95% CI, 31.9-35.6]). Based on the statistical models fitted to 129 participants (60 men [47%]; median age, 38 years [IQR, 25-54 years]) with 2 or more SARS-CoV-2-positive swab samples, persons reporting moderate or severe symptoms tended to have a higher peak mean viral load than those who were asymptomatic (Ct value, 23.3 [95% CI, 22.6-24.0] vs 30.7 [95% CI, 29.8-31.4]). Mild symptoms generally started within 1 day of peak viral load, and moderate or severe symptoms 2 days after peak viral load. All 535 sequenced samples detected the G614 variant (Wuhan strain). CONCLUSIONS AND RELEVANCE This cohort study suggests that having incident SARS-CoV-2 G614 infection was associated with a rapid viral load peak followed by slower decay. COVID-19 symptom onset generally coincided with peak viral load, which correlated positively with symptom severity. This longitudinal evaluation of the SARS-CoV-2 G614 with frequent molecular testing serves as a reference for comparing emergent viral lineages to inform clinical trial designs and public health strategies to contain the spread of the virus.
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Affiliation(s)
| | - Tracy Q. Dong
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Christine Johnston
- Division of Allergy and Infectious Diseases, University of Washington, Seattle
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle
| | - Kathleen M. Neuzil
- Department of Medicine, University of Maryland School of Medicine, Baltimore
| | - Michael K. Paasche-Orlow
- Department of Medicine, Boston University School of Medicine, Boston, Massachusetts
- Department of Medicine, Boston Medical Center, Boston, Massachusetts
| | | | - Anna Bershteyn
- Department of Population Health, New York University Grossman School of Medicine, New York
| | - Lorna E. Thorpe
- Department of Population Health, New York University Grossman School of Medicine, New York
| | - Meagan Deming
- Department of Medicine, University of Maryland School of Medicine, Baltimore
| | - Angelica Kottkamp
- Department of Medicine, New York University Grossman School of Medicine, New York
| | - Miriam Laufer
- Department of Medicine, University of Maryland School of Medicine, Baltimore
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore
| | | | - Alfred Luk
- Department of Medicine, Tulane University, New Orleans, Louisiana
| | - Risa Hoffman
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore
| | - Pavitra Roychoudhury
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle
| | - Craig A. Magaret
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle
| | - Alexander L. Greninger
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle
| | - Meei-Li Huang
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Keith R. Jerome
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle
| | - Mark Wener
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle
- Division of Rheumatology, University of Washington, Seattle
| | - Connie Celum
- Division of Allergy and Infectious Diseases, University of Washington, Seattle
- Department of Global Health, University of Washington, Seattle
- Department of Epidemiology, University of Washington, Seattle
| | - Helen Y. Chu
- Division of Allergy and Infectious Diseases, University of Washington, Seattle
- Department of Global Health, University of Washington, Seattle
- Department of Epidemiology, University of Washington, Seattle
| | - Jared M. Baeten
- Division of Allergy and Infectious Diseases, University of Washington, Seattle
- Department of Global Health, University of Washington, Seattle
- Department of Epidemiology, University of Washington, Seattle
| | - Anna Wald
- Division of Allergy and Infectious Diseases, University of Washington, Seattle
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle
- Department of Epidemiology, University of Washington, Seattle
| | - Ruanne V. Barnabas
- Division of Allergy and Infectious Diseases, University of Washington, Seattle
- Department of Global Health, University of Washington, Seattle
- Department of Epidemiology, University of Washington, Seattle
| | - Elizabeth R. Brown
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
- Department of Biostatistics, University of Washington, Seattle
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
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Jenner AL, Aogo RA, Alfonso S, Crowe V, Deng X, Smith AP, Morel PA, Davis CL, Smith AM, Craig M. COVID-19 virtual patient cohort suggests immune mechanisms driving disease outcomes. PLoS Pathog 2021; 17:e1009753. [PMID: 34260666 PMCID: PMC8312984 DOI: 10.1371/journal.ppat.1009753] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 07/26/2021] [Accepted: 06/24/2021] [Indexed: 12/11/2022] Open
Abstract
To understand the diversity of immune responses to SARS-CoV-2 and distinguish features that predispose individuals to severe COVID-19, we developed a mechanistic, within-host mathematical model and virtual patient cohort. Our results suggest that virtual patients with low production rates of infected cell derived IFN subsequently experienced highly inflammatory disease phenotypes, compared to those with early and robust IFN responses. In these in silico patients, the maximum concentration of IL-6 was also a major predictor of CD8+ T cell depletion. Our analyses predicted that individuals with severe COVID-19 also have accelerated monocyte-to-macrophage differentiation mediated by increased IL-6 and reduced type I IFN signalling. Together, these findings suggest biomarkers driving the development of severe COVID-19 and support early interventions aimed at reducing inflammation.
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Affiliation(s)
- Adrianne L. Jenner
- Sainte-Justine University Hospital Research Centre, Montréal, Québec, Canada
- Department of Mathematics and Statistics, Université de Montréal, Montréal, Québec, Canada
| | - Rosemary A. Aogo
- Department of Pediatrics, University of Tennessee Health Science Center, Memphis, Tennessee, United States of America
| | - Sofia Alfonso
- Department of Physiology, McGill University, Montréal, Québec, Canada
| | - Vivienne Crowe
- Department of Mathematics and Statistics, Concordia University, Montréal, Québec, Canada
| | - Xiaoyan Deng
- Sainte-Justine University Hospital Research Centre, Montréal, Québec, Canada
- Department of Mathematics and Statistics, Université de Montréal, Montréal, Québec, Canada
| | - Amanda P. Smith
- Department of Pediatrics, University of Tennessee Health Science Center, Memphis, Tennessee, United States of America
| | - Penelope A. Morel
- Department of Immunology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Courtney L. Davis
- Natural Science Division, Pepperdine University, Malibu, California, United States of America
| | - Amber M. Smith
- Department of Pediatrics, University of Tennessee Health Science Center, Memphis, Tennessee, United States of America
| | - Morgan Craig
- Sainte-Justine University Hospital Research Centre, Montréal, Québec, Canada
- Department of Mathematics and Statistics, Université de Montréal, Montréal, Québec, Canada
- Department of Physiology, McGill University, Montréal, Québec, Canada
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Jenner AL, Aogo RA, Alfonso S, Crowe V, Smith AP, Morel PA, Davis CL, Smith AM, Craig M. COVID-19 virtual patient cohort reveals immune mechanisms driving disease outcomes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.01.05.425420. [PMID: 33442689 PMCID: PMC7805446 DOI: 10.1101/2021.01.05.425420] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
To understand the diversity of immune responses to SARS-CoV-2 and distinguish features that predispose individuals to severe COVID-19, we developed a mechanistic, within-host mathematical model and virtual patient cohort. Our results indicate that virtual patients with low production rates of infected cell derived IFN subsequently experienced highly inflammatory disease phenotypes, compared to those with early and robust IFN responses. In these in silico patients, the maximum concentration of IL-6 was also a major predictor of CD8 + T cell depletion. Our analyses predicted that individuals with severe COVID-19 also have accelerated monocyte-to-macrophage differentiation that was mediated by increased IL-6 and reduced type I IFN signalling. Together, these findings identify biomarkers driving the development of severe COVID-19 and support early interventions aimed at reducing inflammation. AUTHOR SUMMARY Understanding of how the immune system responds to SARS-CoV-2 infections is critical for improving diagnostic and treatment approaches. Identifying which immune mechanisms lead to divergent outcomes can be clinically difficult, and experimental models and longitudinal data are only beginning to emerge. In response, we developed a mechanistic, mathematical and computational model of the immunopathology of COVID-19 calibrated to and validated against a broad set of experimental and clinical immunological data. To study the drivers of severe COVID-19, we used our model to expand a cohort of virtual patients, each with realistic disease dynamics. Our results identify key processes that regulate the immune response to SARS-CoV-2 infection in virtual patients and suggest viable therapeutic targets, underlining the importance of a rational approach to studying novel pathogens using intra-host models.
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Affiliation(s)
- Adrianne L. Jenner
- CHU Sainte-Justine Research Centre, Montréal, Québec, Canada
- Department of Mathematics and Statistics, Université de Montréal, Montréal, Québec, Canada
| | - Rosemary A. Aogo
- Department of Pediatrics, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Sofia Alfonso
- Department of Physiology, McGill University, Montréal, Québec, Canada
| | - Vivienne Crowe
- Department of Mathematics and Statistics, Concordia University, Montréal, Québec, Canada
| | - Amanda P. Smith
- Department of Pediatrics, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Penelope A. Morel
- Department of Immunology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Courtney L. Davis
- Natural Science Division, Pepperdine University, Malibu, California, USA
| | - Amber M. Smith
- Department of Pediatrics, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Morgan Craig
- CHU Sainte-Justine Research Centre, Montréal, Québec, Canada
- Department of Mathematics and Statistics, Université de Montréal, Montréal, Québec, Canada
- Department of Physiology, McGill University, Montréal, Québec, Canada
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8
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Abdollahi A, shakoori A, Khoshnevis H, Arabzadeh M, Dehghan Manshadi SA, Mohammadnejad E, Ghasemi D, Safari Aboksari M, Alizadeh S, Mehrtash V, Eftekhar-javadi A, Safaei M. Comparison of Patient-collected and Lab Technician-collected Nasopharyngeal and Oropharyngeal Swabs for Detection of COVID-19 by RT-PCR. IRANIAN JOURNAL OF PATHOLOGY 2020; 15:313-319. [PMID: 32944044 PMCID: PMC7477688 DOI: 10.30699/ijp.2020.127312.2387] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Accepted: 06/08/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND & OBJECTIVE A simple approach to prevent close contact in healthcare settings during the COVID-19 outbreak is to train patients to collect their own nasopharyngeal and oropharyngeal swabs and deliver them to medical laboratories to have them processed. The aim of our study was to compare lab technician- with patient- collected oropharyngeal and nasopharyngeal samples for detection of the coronavirus disease 2019 (COVID 19) using rapid real-time polymerase chain reaction (rRT-PCR). METHODS Fifty adult patients with flu-like symptoms and radiologic findings compatible with atypical pneumonia who were admitted to the infectious diseases ward of Imam Khomeini Hospital Complex, Tehran, Iran, with a clinical diagnosis of COVID-19 from February 28 to April 27 of 2020 were randomly selected and entered in our study. Two sets of naso- and oropharyngeal swabs were collected, one set by a lab technician and the other by the patients, and the COVID-19 rRT-PCR test was performed. RESULTS Of 50 selected cases, in seven patients all collected naso- and oropharyngeal swabs tested positive, and in 22 patients all samples tested negative for COVID-19 in rRT-PCR. Discrepancies between rRT-PCR results of lab technician- and patient-collected swabs were observed in 12 nasopharyngeal and 13 oropharyngeal specimens. Positive lab technician-collected and negative patient-collected samples were observed in 10 and 5 nasopharyngeal and oropharyngeal specimens, respectively. Negative lab technician-collected and positive patient-collected samples were observed in two and seven nasopharyngeal and oropharyngeal specimens, respectively. The overall percentage of agreement among both nasopharyngeal and oropharyngeal swabs taken by a lab technician and patients was 76% with a kappa value of 0.49 (P=0.001). CONCLUSION Based on our findings, lab technician-collected naso- and oropharyngeal swabs cannot be replaced by patient-collected ones with regard to COVID-19 rRT-PCR.
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Affiliation(s)
- Alireza Abdollahi
- Department of Pathology, Imam Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
| | - Abbas shakoori
- Medical Genetic Ward, Imam Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
| | - Hoda Khoshnevis
- Supervisor of Genetic Ward, Imam Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Arabzadeh
- Laboratory Senior Technical Associate of Genetic Ward, Imam Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyed Ali Dehghan Manshadi
- Department of Infectious Diseases and Tropical Medicine, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Esmaeil Mohammadnejad
- Department of Medical-Surgical Nursing, School of Nursing and Midwifery, Tehran University of Medical Sciences, Tehran, Iran
| | - Dorsa Ghasemi
- Department of Pathology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Maryam Safari Aboksari
- Department of Pathology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Shaban Alizadeh
- Hematology Department, Allied medical school, Tehran University of Medical Sciences, Tehran, Iran
| | - Vahid Mehrtash
- Department of Pathology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Arezoo Eftekhar-javadi
- Department of Pathology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Masoomeh Safaei
- Department of Pathology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
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Deeks JJ, Dinnes J, Takwoingi Y, Davenport C, Spijker R, Taylor-Phillips S, Adriano A, Beese S, Dretzke J, Ferrante di Ruffano L, Harris IM, Price MJ, Dittrich S, Emperador D, Hooft L, Leeflang MM, Van den Bruel A. Antibody tests for identification of current and past infection with SARS-CoV-2. Cochrane Database Syst Rev 2020; 6:CD013652. [PMID: 32584464 PMCID: PMC7387103 DOI: 10.1002/14651858.cd013652] [Citation(s) in RCA: 432] [Impact Index Per Article: 108.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and resulting COVID-19 pandemic present important diagnostic challenges. Several diagnostic strategies are available to identify current infection, rule out infection, identify people in need of care escalation, or to test for past infection and immune response. Serology tests to detect the presence of antibodies to SARS-CoV-2 aim to identify previous SARS-CoV-2 infection, and may help to confirm the presence of current infection. OBJECTIVES To assess the diagnostic accuracy of antibody tests to determine if a person presenting in the community or in primary or secondary care has SARS-CoV-2 infection, or has previously had SARS-CoV-2 infection, and the accuracy of antibody tests for use in seroprevalence surveys. SEARCH METHODS We undertook electronic searches in the Cochrane COVID-19 Study Register and the COVID-19 Living Evidence Database from the University of Bern, which is updated daily with published articles from PubMed and Embase and with preprints from medRxiv and bioRxiv. In addition, we checked repositories of COVID-19 publications. We did not apply any language restrictions. We conducted searches for this review iteration up to 27 April 2020. SELECTION CRITERIA We included test accuracy studies of any design that evaluated antibody tests (including enzyme-linked immunosorbent assays, chemiluminescence immunoassays, and lateral flow assays) in people suspected of current or previous SARS-CoV-2 infection, or where tests were used to screen for infection. We also included studies of people either known to have, or not to have SARS-CoV-2 infection. We included all reference standards to define the presence or absence of SARS-CoV-2 (including reverse transcription polymerase chain reaction tests (RT-PCR) and clinical diagnostic criteria). DATA COLLECTION AND ANALYSIS We assessed possible bias and applicability of the studies using the QUADAS-2 tool. We extracted 2x2 contingency table data and present sensitivity and specificity for each antibody (or combination of antibodies) using paired forest plots. We pooled data using random-effects logistic regression where appropriate, stratifying by time since post-symptom onset. We tabulated available data by test manufacturer. We have presented uncertainty in estimates of sensitivity and specificity using 95% confidence intervals (CIs). MAIN RESULTS We included 57 publications reporting on a total of 54 study cohorts with 15,976 samples, of which 8526 were from cases of SARS-CoV-2 infection. Studies were conducted in Asia (n = 38), Europe (n = 15), and the USA and China (n = 1). We identified data from 25 commercial tests and numerous in-house assays, a small fraction of the 279 antibody assays listed by the Foundation for Innovative Diagnostics. More than half (n = 28) of the studies included were only available as preprints. We had concerns about risk of bias and applicability. Common issues were use of multi-group designs (n = 29), inclusion of only COVID-19 cases (n = 19), lack of blinding of the index test (n = 49) and reference standard (n = 29), differential verification (n = 22), and the lack of clarity about participant numbers, characteristics and study exclusions (n = 47). Most studies (n = 44) only included people hospitalised due to suspected or confirmed COVID-19 infection. There were no studies exclusively in asymptomatic participants. Two-thirds of the studies (n = 33) defined COVID-19 cases based on RT-PCR results alone, ignoring the potential for false-negative RT-PCR results. We observed evidence of selective publication of study findings through omission of the identity of tests (n = 5). We observed substantial heterogeneity in sensitivities of IgA, IgM and IgG antibodies, or combinations thereof, for results aggregated across different time periods post-symptom onset (range 0% to 100% for all target antibodies). We thus based the main results of the review on the 38 studies that stratified results by time since symptom onset. The numbers of individuals contributing data within each study each week are small and are usually not based on tracking the same groups of patients over time. Pooled results for IgG, IgM, IgA, total antibodies and IgG/IgM all showed low sensitivity during the first week since onset of symptoms (all less than 30.1%), rising in the second week and reaching their highest values in the third week. The combination of IgG/IgM had a sensitivity of 30.1% (95% CI 21.4 to 40.7) for 1 to 7 days, 72.2% (95% CI 63.5 to 79.5) for 8 to 14 days, 91.4% (95% CI 87.0 to 94.4) for 15 to 21 days. Estimates of accuracy beyond three weeks are based on smaller sample sizes and fewer studies. For 21 to 35 days, pooled sensitivities for IgG/IgM were 96.0% (95% CI 90.6 to 98.3). There are insufficient studies to estimate sensitivity of tests beyond 35 days post-symptom onset. Summary specificities (provided in 35 studies) exceeded 98% for all target antibodies with confidence intervals no more than 2 percentage points wide. False-positive results were more common where COVID-19 had been suspected and ruled out, but numbers were small and the difference was within the range expected by chance. Assuming a prevalence of 50%, a value considered possible in healthcare workers who have suffered respiratory symptoms, we would anticipate that 43 (28 to 65) would be missed and 7 (3 to 14) would be falsely positive in 1000 people undergoing IgG/IgM testing at days 15 to 21 post-symptom onset. At a prevalence of 20%, a likely value in surveys in high-risk settings, 17 (11 to 26) would be missed per 1000 people tested and 10 (5 to 22) would be falsely positive. At a lower prevalence of 5%, a likely value in national surveys, 4 (3 to 7) would be missed per 1000 tested, and 12 (6 to 27) would be falsely positive. Analyses showed small differences in sensitivity between assay type, but methodological concerns and sparse data prevent comparisons between test brands. AUTHORS' CONCLUSIONS The sensitivity of antibody tests is too low in the first week since symptom onset to have a primary role for the diagnosis of COVID-19, but they may still have a role complementing other testing in individuals presenting later, when RT-PCR tests are negative, or are not done. Antibody tests are likely to have a useful role for detecting previous SARS-CoV-2 infection if used 15 or more days after the onset of symptoms. However, the duration of antibody rises is currently unknown, and we found very little data beyond 35 days post-symptom onset. We are therefore uncertain about the utility of these tests for seroprevalence surveys for public health management purposes. Concerns about high risk of bias and applicability make it likely that the accuracy of tests when used in clinical care will be lower than reported in the included studies. Sensitivity has mainly been evaluated in hospitalised patients, so it is unclear whether the tests are able to detect lower antibody levels likely seen with milder and asymptomatic COVID-19 disease. The design, execution and reporting of studies of the accuracy of COVID-19 tests requires considerable improvement. Studies must report data on sensitivity disaggregated by time since onset of symptoms. COVID-19-positive cases who are RT-PCR-negative should be included as well as those confirmed RT-PCR, in accordance with the World Health Organization (WHO) and China National Health Commission of the People's Republic of China (CDC) case definitions. We were only able to obtain data from a small proportion of available tests, and action is needed to ensure that all results of test evaluations are available in the public domain to prevent selective reporting. This is a fast-moving field and we plan ongoing updates of this living systematic review.
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Affiliation(s)
- Jonathan J Deeks
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK
| | - Jacqueline Dinnes
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK
| | - Yemisi Takwoingi
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK
| | - Clare Davenport
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK
| | - René Spijker
- Medical Library, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health, Amsterdam, Netherlands
- Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Sian Taylor-Phillips
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK
| | - Ada Adriano
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Sophie Beese
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Janine Dretzke
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Lavinia Ferrante di Ruffano
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Isobel M Harris
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Malcolm J Price
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK
| | | | | | - Lotty Hooft
- Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Mariska Mg Leeflang
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
- Biomarker and Test Evaluation Programme (BiTE), Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Ann Van den Bruel
- Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium
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