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Herbert C, Manabe YC, Filippaios A, Lin H, Wang B, Achenbach C, Kheterpal V, Hartin P, Suvarna T, Harman E, Stamegna P, Rao LV, Hafer N, Broach J, Luzuriaga K, Fitzgerald KA, McManus DD, Soni A. Differential Viral Dynamics by Sex and Body Mass Index During Acute SARS-CoV-2 Infection: Results From a Longitudinal Cohort Study. Clin Infect Dis 2024; 78:1185-1193. [PMID: 37972270 PMCID: PMC11093673 DOI: 10.1093/cid/ciad701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 10/25/2023] [Accepted: 11/14/2023] [Indexed: 11/19/2023] Open
Abstract
BACKGROUND There is evidence of an association of severe coroanavirus disease (COVID-19) outcomes with increased body mass index (BMI) and male sex. However, few studies have examined the interaction between sex and BMI on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral dynamics. METHODS Participants conducted RT-PCR testing every 24-48 hours over a 15-day period. Sex and BMI were self-reported, and Ct values from E-gene were used to quantify viral load. Three distinct outcomes were examined using mixed-effects generalized linear models, linear models, and logistic models, respectively: all Ct values (model 1), nadir Ct value (model 2), and strongly detectable infection (at least 1 Ct value ≤28 during their infection) (model 3). An interaction term between BMI and sex was included, and inverse logit transformations were applied to quantify the differences by BMI and sex using marginal predictions. RESULTS In total, 7988 participants enrolled in this study and 439 participants (model 1) and 309 (models 2 and 3) were eligible for these analyses. Among males, increasing BMI was associated with lower Ct values in a dose-response fashion. For participants with BMIs greater than 29 kg/m2, males had significantly lower Ct values and nadir Ct values than females. In total, 67.8% of males and 55.3% of females recorded a strongly detectable infection; increasing proportions of men had Ct values <28 with BMIs of 35 and 40 kg/m2. CONCLUSIONS We observed sex-based dimorphism in relation to BMI and COVID-19 viral load. Further investigation is needed to determine the cause, clinical impact, and transmission implications of this sex-differential effect of BMI on viral load.
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Affiliation(s)
- Carly Herbert
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
- UMass Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
| | - Yukari C Manabe
- Division of Infectious Disease, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Andreas Filippaios
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
| | - Honghuang Lin
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
| | - Biqi Wang
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
| | - Chad Achenbach
- Division of Infectious Disease, Department of Medicine, Havey Institute for Global Health, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | | | - Paul Hartin
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
| | | | | | - Pamela Stamegna
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
| | | | - Nathaniel Hafer
- UMass Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
- Program in Molecular Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
| | - John Broach
- Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
| | - Katherine Luzuriaga
- UMass Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
- Program in Molecular Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
| | - Katherine A Fitzgerald
- Division of Infectious Diseases and Immunology, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
| | - David D McManus
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
- Division of Cardiology, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
| | - Apurv Soni
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
- UMass Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
- Division of Health System Science, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
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O'Connor L, Behar S, Tarrant S, Stamegna P, Pretz C, Wang B, Savage B, Scornavacca T, Shirshac J, Wilkie T, Hyder M, Zai A, Toomey S, Mullen M, Fisher K, Tigas E, Wong S, McManus DD, Alper E, Lindenauer PK, Dickson E, Broach J, Kheterpal V, Soni A. Rationale and Design of Healthy at Home for COPD: an Integrated Remote Patient Monitoring and Virtual Pulmonary Rehabilitation Pilot Study. Res Sq 2024:rs.3.rs-3901309. [PMID: 38746125 PMCID: PMC11092828 DOI: 10.21203/rs.3.rs-3901309/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Chronic Obstructive Pulmonary Disease (COPD) is a common, costly, and morbid condition. Pulmonary rehabilitation, close monitoring, and early intervention during acute exacerbations of symptoms represent a comprehensive approach to improve outcomes, but the optimal means of delivering these services is uncertain. Logistical, financial, and social barriers to providing healthcare through face-to-face encounters, paired with recent developments in technology, have stimulated interest in exploring alternative models of care. The Healthy at Home study seeks to determine the feasibility of a multimodal, digitally enhanced intervention provided to participants with COPD longitudinally over six months. This paper details the recruitment, methods, and analysis plan for the study, which is recruiting 100 participants in its pilot phase. Participants were provided with several integrated services including a smartwatch to track physiological data, a study app to track symptoms and study instruments, access to a mobile integrated health program for acute clinical needs, and a virtual comprehensive pulmonary support service. Participants shared physiologic, demographic, and symptom reports, electronic health records, and claims data with the study team, facilitating a better understanding of their symptoms and potential care needs longitudinally. The Healthy at Home study seeks to develop a comprehensive digital phenotype of COPD by tracking and responding to multiple indices of disease behavior and facilitating early and nuanced responses to changes in participants' health status. This study is registered at Clinicaltrials.gov (NCT06000696).
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Soni A, Herbert C, Lin H, Yan Y, Pretz C, Stamegna P, Wang B, Orwig T, Wright C, Tarrant S, Behar S, Suvarna T, Schrader S, Harman E, Nowak C, Kheterpal V, Rao LV, Cashman L, Orvek E, Ayturk D, Gibson L, Zai A, Wong S, Lazar P, Wang Z, Filippaios A, Barton B, Achenbach CJ, Murphy RL, Robinson ML, Manabe YC, Pandey S, Colubri A, O'Connor L, Lemon SC, Fahey N, Luzuriaga KL, Hafer N, Roth K, Lowe T, Stenzel T, Heetderks W, Broach J, McManus DD. Performance of Rapid Antigen Tests to Detect Symptomatic and Asymptomatic SARS-CoV-2 Infection : A Prospective Cohort Study. Ann Intern Med 2023; 176:975-982. [PMID: 37399548 PMCID: PMC10321467 DOI: 10.7326/m23-0385] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/05/2023] Open
Abstract
BACKGROUND The performance of rapid antigen tests (Ag-RDTs) for screening asymptomatic and symptomatic persons for SARS-CoV-2 is not well established. OBJECTIVE To evaluate the performance of Ag-RDTs for detection of SARS-CoV-2 among symptomatic and asymptomatic participants. DESIGN This prospective cohort study enrolled participants between October 2021 and January 2022. Participants completed Ag-RDTs and reverse transcriptase polymerase chain reaction (RT-PCR) testing for SARS-CoV-2 every 48 hours for 15 days. SETTING Participants were enrolled digitally throughout the mainland United States. They self-collected anterior nasal swabs for Ag-RDTs and RT-PCR testing. Nasal swabs for RT-PCR were shipped to a central laboratory, whereas Ag-RDTs were done at home. PARTICIPANTS Of 7361 participants in the study, 5353 who were asymptomatic and negative for SARS-CoV-2 on study day 1 were eligible. In total, 154 participants had at least 1 positive RT-PCR result. MEASUREMENTS The sensitivity of Ag-RDTs was measured on the basis of testing once (same-day), twice (after 48 hours), and thrice (after a total of 96 hours). The analysis was repeated for different days past index PCR positivity (DPIPPs) to approximate real-world scenarios where testing initiation may not always coincide with DPIPP 0. Results were stratified by symptom status. RESULTS Among 154 participants who tested positive for SARS-CoV-2, 97 were asymptomatic and 57 had symptoms at infection onset. Serial testing with Ag-RDTs twice 48 hours apart resulted in an aggregated sensitivity of 93.4% (95% CI, 90.4% to 95.9%) among symptomatic participants on DPIPPs 0 to 6. When singleton positive results were excluded, the aggregated sensitivity on DPIPPs 0 to 6 for 2-time serial testing among asymptomatic participants was lower at 62.7% (CI, 57.0% to 70.5%), but it improved to 79.0% (CI, 70.1% to 87.4%) with testing 3 times at 48-hour intervals. LIMITATION Participants tested every 48 hours; therefore, these data cannot support conclusions about serial testing intervals shorter than 48 hours. CONCLUSION The performance of Ag-RDTs was optimized when asymptomatic participants tested 3 times at 48-hour intervals and when symptomatic participants tested 2 times separated by 48 hours. PRIMARY FUNDING SOURCE National Institutes of Health RADx Tech program.
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Affiliation(s)
- Apurv Soni
- Program in Digital Medicine, Department of Medicine; Division of Health Systems Science, Department of Medicine; and Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (A.S.)
| | - Carly Herbert
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., C.P., P.S., T.O., C.W., S.T., S.B., A.F., S.P.)
| | - Honghuang Lin
- Program in Digital Medicine and Division of Health Systems Science, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (H.L., B.W.)
| | - Yi Yan
- Office of In Vitro Diagnostics, Office of Product Evaluation and Quality, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland (Y.Y., K.R., T.L.)
| | - Caitlin Pretz
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., C.P., P.S., T.O., C.W., S.T., S.B., A.F., S.P.)
| | - Pamela Stamegna
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., C.P., P.S., T.O., C.W., S.T., S.B., A.F., S.P.)
| | - Biqi Wang
- Program in Digital Medicine and Division of Health Systems Science, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (H.L., B.W.)
| | - Taylor Orwig
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., C.P., P.S., T.O., C.W., S.T., S.B., A.F., S.P.)
| | - Colton Wright
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., C.P., P.S., T.O., C.W., S.T., S.B., A.F., S.P.)
| | - Seanan Tarrant
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., C.P., P.S., T.O., C.W., S.T., S.B., A.F., S.P.)
| | - Stephanie Behar
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., C.P., P.S., T.O., C.W., S.T., S.B., A.F., S.P.)
| | - Thejas Suvarna
- CareEvolution, Ann Arbor, Michigan (T.S., S.S., E.H., C.N., V.K.)
| | - Summer Schrader
- CareEvolution, Ann Arbor, Michigan (T.S., S.S., E.H., C.N., V.K.)
| | - Emma Harman
- CareEvolution, Ann Arbor, Michigan (T.S., S.S., E.H., C.N., V.K.)
| | - Chris Nowak
- CareEvolution, Ann Arbor, Michigan (T.S., S.S., E.H., C.N., V.K.)
| | - Vik Kheterpal
- CareEvolution, Ann Arbor, Michigan (T.S., S.S., E.H., C.N., V.K.)
| | - Lokinendi V Rao
- Quest Diagnostics, Marlborough, Massachusetts (L.V.R., L.C.)
| | - Lisa Cashman
- Quest Diagnostics, Marlborough, Massachusetts (L.V.R., L.C.)
| | - Elizabeth Orvek
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (E.O., D.A., A.Z., S.W., P.L., B.B., S.C.L.)
| | - Didem Ayturk
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (E.O., D.A., A.Z., S.W., P.L., B.B., S.C.L.)
| | - Laura Gibson
- Division of Infectious Diseases and Immunology, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (L.G.)
| | - Adrian Zai
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (E.O., D.A., A.Z., S.W., P.L., B.B., S.C.L.)
| | - Steven Wong
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (E.O., D.A., A.Z., S.W., P.L., B.B., S.C.L.)
| | - Peter Lazar
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (E.O., D.A., A.Z., S.W., P.L., B.B., S.C.L.)
| | - Ziyue Wang
- Division of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (Z.W.)
| | - Andreas Filippaios
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., C.P., P.S., T.O., C.W., S.T., S.B., A.F., S.P.)
| | - Bruce Barton
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (E.O., D.A., A.Z., S.W., P.L., B.B., S.C.L.)
| | - Chad J Achenbach
- Division of Infectious Diseases, Department of Medicine, Havey Institute for Global Health, Feinberg School of Medicine, Northwestern University, Chicago, Illinois (C.J.A., R.L.M.)
| | - Robert L Murphy
- Division of Infectious Diseases, Department of Medicine, Havey Institute for Global Health, Feinberg School of Medicine, Northwestern University, Chicago, Illinois (C.J.A., R.L.M.)
| | - Matthew L Robinson
- Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland (M.L.R., Y.C.M.)
| | - Yukari C Manabe
- Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland (M.L.R., Y.C.M.)
| | - Shishir Pandey
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., C.P., P.S., T.O., C.W., S.T., S.B., A.F., S.P.)
| | - Andres Colubri
- Department of Microbiology and Physiological Systems, University of Massachusetts Chan Medical School, Worcester, Massachusetts (A.C.)
| | - Laurel O'Connor
- Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (L.O., J.B.)
| | - Stephenie C Lemon
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (E.O., D.A., A.Z., S.W., P.L., B.B., S.C.L.)
| | - Nisha Fahey
- Program in Digital Medicine, Department of Medicine; Department of Population and Quantitative Health Sciences; and Department of Pediatrics, University of Massachusetts Chan Medical School, Worcester, Massachusetts (N.F.)
| | - Katherine L Luzuriaga
- University of Massachusetts Center for Clinical and Translational Science and Program in Molecular Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (K.L.L., N.H.)
| | - Nathaniel Hafer
- University of Massachusetts Center for Clinical and Translational Science and Program in Molecular Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (K.L.L., N.H.)
| | - Kristian Roth
- Office of In Vitro Diagnostics, Office of Product Evaluation and Quality, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland (Y.Y., K.R., T.L.)
| | - Toby Lowe
- Office of In Vitro Diagnostics, Office of Product Evaluation and Quality, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland (Y.Y., K.R., T.L.)
| | - Timothy Stenzel
- Division of Microbiology, Office of In Vitro Diagnostics, Office of Product Evaluation and Quality, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland (T.S.)
| | - William Heetderks
- National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland (W.H.)
| | - John Broach
- Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (L.O., J.B.)
| | - David D McManus
- Program in Digital Medicine, Division of Health Systems Science, and Division of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (D.D.M.)
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Soni A, Herbert C, Pretz C, Stamegna P, Filippaios A, Shi Q, Suvarna T, Harman E, Schrader S, Nowak C, Schramm E, Kheterpal V, Behar S, Tarrant S, Ferranto J, Hafer N, Robinson M, Achenbach C, Murphy RL, Manabe YC, Gibson L, Barton B, O’Connor L, Fahey N, Orvek E, Lazar P, Ayturk D, Wong S, Zai A, Cashman L, Rao LV, Luzuriaga K, Lemon S, Blodgett A, Trippe E, Barcus M, Goldberg B, Roth K, Stenzel T, Heetderks W, Broach J, McManus D. Design and implementation of a digital site-less clinical study of serial rapid antigen testing to identify asymptomatic SARS-CoV-2 infection. J Clin Transl Sci 2023; 7:e120. [PMID: 37313378 PMCID: PMC10260333 DOI: 10.1017/cts.2023.540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 04/05/2023] [Accepted: 04/27/2023] [Indexed: 06/15/2023] Open
Abstract
Background Rapid antigen detection tests (Ag-RDT) for SARS-CoV-2 with emergency use authorization generally include a condition of authorization to evaluate the test's performance in asymptomatic individuals when used serially. We aim to describe a novel study design that was used to generate regulatory-quality data to evaluate the serial use of Ag-RDT in detecting SARS-CoV-2 virus among asymptomatic individuals. Methods This prospective cohort study used a siteless, digital approach to assess longitudinal performance of Ag-RDT. Individuals over 2 years old from across the USA with no reported COVID-19 symptoms in the 14 days prior to study enrollment were eligible to enroll in this study. Participants throughout the mainland USA were enrolled through a digital platform between October 18, 2021 and February 15, 2022. Participants were asked to test using Ag-RDT and molecular comparators every 48 hours for 15 days. Enrollment demographics, geographic distribution, and SARS-CoV-2 infection rates are reported. Key Results A total of 7361 participants enrolled in the study, and 492 participants tested positive for SARS-CoV-2, including 154 who were asymptomatic and tested negative to start the study. This exceeded the initial enrollment goals of 60 positive participants. We enrolled participants from 44 US states, and geographic distribution of participants shifted in accordance with the changing COVID-19 prevalence nationwide. Conclusions The digital site-less approach employed in the "Test Us At Home" study enabled rapid, efficient, and rigorous evaluation of rapid diagnostics for COVID-19 and can be adapted across research disciplines to optimize study enrollment and accessibility.
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Affiliation(s)
- Apurv Soni
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Division of Health System Science, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Carly Herbert
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Caitlin Pretz
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Pamela Stamegna
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Andreas Filippaios
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Qiming Shi
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Division of Health System Science, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
- University of Massachusetts Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | | | | | | | | | | | | | - Stephanie Behar
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Seanan Tarrant
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Julia Ferranto
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Nathaniel Hafer
- University of Massachusetts Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Matthew Robinson
- Division of Infectious Disease, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Chad Achenbach
- Division of Infectious Disease, Department of Medicine, Havey Institute for Global Health, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Robert L. Murphy
- Division of Infectious Disease, Department of Medicine, Havey Institute for Global Health, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Yukari C. Manabe
- Division of Infectious Disease, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Laura Gibson
- Division of Infectious Disease, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Bruce Barton
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Laurel O’Connor
- Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Nisha Fahey
- Department of Pediatrics, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Elizabeth Orvek
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Peter Lazar
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Didem Ayturk
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Steven Wong
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Adrian Zai
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | | | | | - Katherine Luzuriaga
- University of Massachusetts Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Stephenie Lemon
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Allison Blodgett
- University of Massachusetts Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Elizabeth Trippe
- Division of Microbiology, OHT7 Office of Product Evaluation and Quality, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA
| | - Mary Barcus
- Division of Microbiology, OHT7 Office of Product Evaluation and Quality, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA
| | - Brittany Goldberg
- Division of Microbiology, OHT7 Office of Product Evaluation and Quality, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA
| | - Kristian Roth
- Division of Microbiology, OHT7 Office of Product Evaluation and Quality, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA
| | - Timothy Stenzel
- OHT7 Office of Product Evaluation and Quality, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA
| | - William Heetderks
- National Institute of Biomedical Imaging and Bioengineering, NIH, Via Contract with Kelly Services, Bethesda, MD, USA
| | - John Broach
- Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - David McManus
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Division of Health System Science, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Division of Cardiology, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
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Herbert C, Wang B, Lin H, Hafer N, Pretz C, Stamegna P, Tarrant S, Hartin P, Ferranto J, Behar S, Wright C, Orwig T, Suvarna T, Harman E, Schrader S, Nowak C, Kheterpal V, Orvek E, Wong S, Zai A, Barton B, Gerber B, Lemon SC, Filippaios A, D'Amore K, Gibson L, Greene S, Howard-Wilson S, Colubri A, Achenbach C, Murphy R, Heetderks W, Manabe YC, O'Connor L, Fahey N, Luzuriaga K, Broach J, McManus DD, Soni A. Performance of Rapid Antigen Tests Based on Symptom Onset and Close Contact Exposure: A secondary analysis from the Test Us At Home prospective cohort study. medRxiv 2023:2023.02.21.23286239. [PMID: 36865199 PMCID: PMC9980261 DOI: 10.1101/2023.02.21.23286239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/02/2023]
Abstract
Background The performance of rapid antigen tests for SARS-CoV-2 (Ag-RDT) in temporal relation to symptom onset or exposure is unknown, as is the impact of vaccination on this relationship. Objective To evaluate the performance of Ag-RDT compared with RT-PCR based on day after symptom onset or exposure in order to decide on 'when to test'. Design Setting and Participants The Test Us at Home study was a longitudinal cohort study that enrolled participants over 2 years old across the United States between October 18, 2021 and February 4, 2022. All participants were asked to conduct Ag-RDT and RT-PCR testing every 48 hours over a 15-day period. Participants with one or more symptoms during the study period were included in the Day Post Symptom Onset (DPSO) analyses, while those who reported a COVID-19 exposure were included in the Day Post Exposure (DPE) analysis. Exposure Participants were asked to self-report any symptoms or known exposures to SARS-CoV-2 every 48-hours, immediately prior to conducting Ag-RDT and RT-PCR testing. The first day a participant reported one or more symptoms was termed DPSO 0, and the day of exposure was DPE 0. Vaccination status was self-reported. Main Outcome and Measures Results of Ag-RDT were self-reported (positive, negative, or invalid) and RT-PCR results were analyzed by a central laboratory. Percent positivity of SARS-CoV-2 and sensitivity of Ag-RDT and RT-PCR by DPSO and DPE were stratified by vaccination status and calculated with 95% confidence intervals. Results A total of 7,361 participants enrolled in the study. Among them, 2,086 (28.3%) and 546 (7.4%) participants were eligible for the DPSO and DPE analyses, respectively. Unvaccinated participants were nearly twice as likely to test positive for SARS-CoV-2 than vaccinated participants in event of symptoms (PCR+: 27.6% vs 10.1%) or exposure (PCR+: 43.8% vs. 22.2%). The highest proportion of vaccinated and unvaccinated individuals tested positive on DPSO 2 and DPE 5-8. Performance of RT-PCR and Ag-RDT did not differ by vaccination status. Ag-RDT detected 78.0% (95% Confidence Interval: 72.56-82.61) of PCR-confirmed infections by DPSO 4. For exposed participants, Ag-RDT detected 84.9% (95% CI: 75.0-91.4) of PCR-confirmed infections by day five post-exposure (DPE 5). Conclusions and Relevance Performance of Ag-RDT and RT-PCR was highest on DPSO 0-2 and DPE 5 and did not differ by vaccination status. These data suggests that serial testing remains integral to enhancing the performance of Ag-RDT.
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Soni A, Herbert C, Lin H, Yan Y, Pretz C, Stamegna P, Wang B, Orwig T, Wright C, Tarrant S, Behar S, Suvarna T, Schrader S, Harman E, Nowak C, Kheterpal V, Rao LV, Cashman L, Orvek E, Ayturk D, Gibson L, Zai A, Wong S, Lazar P, Wang Z, Filippaios A, Barton B, Achenbach CJ, Murphy RL, Robinson M, Manabe YC, Pandey S, Colubri A, Oâ Connor L, Lemon SC, Fahey N, Luzuriaga KL, Hafer N, Roth K, Lowe T, Stenzel T, Heetderks W, Broach J, McManus DD. Performance of Rapid Antigen Tests to Detect Symptomatic and Asymptomatic SARS-CoV-2 Infection. medRxiv 2023:2022.08.05.22278466. [PMID: 35982680 PMCID: PMC9387089 DOI: 10.1101/2022.08.05.22278466] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Background Performance of rapid antigen tests for SARS-CoV-2 (Ag-RDT) varies over the course of an infection, and their performance in screening for SARS-CoV-2 is not well established. We aimed to evaluate performance of Ag-RDT for detection of SARS-CoV-2 for symptomatic and asymptomatic participants. Methods Participants >2 years old across the United States enrolled in the study between October 2021 and February 2022. Participants completed Ag-RDT and molecular testing (RT-PCR) for SARS-CoV-2 every 48 hours for 15 days. This analysis was limited to participants who were asymptomatic and tested negative on their first day of study participation. Onset of infection was defined as the day of first positive RT-PCR result. Sensitivity of Ag-RDT was measured based on testing once, twice (after 48-hours), and thrice (after 96 hours). Analysis was repeated for different Days Post Index PCR Positivity (DPIPP) and stratified based on symptom-status. Results In total, 5,609 of 7,361 participants were eligible for this analysis. Among 154 participants who tested positive for SARS-CoV-2, 97 were asymptomatic and 57 had symptoms at infection onset. Serial testing with Ag-RDT twice 48-hours apart resulted in an aggregated sensitivity of 93.4% (95% CI: 89.1-96.1%) among symptomatic participants on DPIPP 0-6. Excluding singleton positives, aggregated sensitivity on DPIPP 0-6 for two-time serial-testing among asymptomatic participants was lower at 62.7% (54.7-70.0%) but improved to 79.0% (71.0-85.3%) with testing three times at 48-hour intervals. Discussion Performance of Ag-RDT was optimized when asymptomatic participants tested three-times at 48-hour intervals and when symptomatic participants tested two-times separated by 48-hours.
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Soni A, Herbert C, Pretz C, Stamegna P, Filippaios A, Shi Q, Suvarna T, Harman E, Schrader S, Nowak C, Schramm E, Kheterpal V, Behar S, Tarrant S, Ferranto J, Hafer N, Robinson M, Achenbach C, Murphy RL, Manabe YC, Gibson L, Barton B, O'Connor L, Fahey N, Orvek E, Lazar P, Ayturk D, Wong S, Zai A, Cashman L, Rao LV, Luzuriaga K, Lemon S, Blodgett A, Trippe E, Barcus M, Goldberg B, Roth K, Stenzel T, Heetderks W, Broach J, McManus D. Finding a Needle in a Haystack: Design and Implementation of a Digital Site-less Clinical Study of Serial Rapid Antigen Testing to Identify Asymptomatic SARS-CoV-2 Infection. medRxiv 2023:2022.08.04.22278274. [PMID: 35982663 PMCID: PMC9387154 DOI: 10.1101/2022.08.04.22278274] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Background Rapid antigen tests (Ag-RDT) for SARS-CoV-2 with Emergency Use Authorization generally include a condition of authorization to evaluate the test's performance in asymptomatic individuals when used serially. Objective To describe a novel study design to generate regulatory-quality data to evaluate serial use of Ag-RDT in detecting SARS-CoV-2 virus among asymptomatic individuals. Design Prospective cohort study using a decentralized approach. Participants were asked to test using Ag-RDT and molecular comparators every 48 hours for 15 days. Setting Participants throughout the mainland United States were enrolled through a digital platform between October 18, 2021 and February 15, 2022. Ag-RDTs were completed at home, and molecular comparators were shipped to a central laboratory. Participants Individuals over 2 years old from across the U.S. with no reported COVID-19 symptoms in the 14 days prior to study enrollment were eligible to enroll in this study. Measurements Enrollment demographics, geographic distribution, and SARS-CoV-2 infection rates are reported. Key Results A total of 7,361 participants enrolled in the study, and 492 participants tested positive for SARS-CoV-2, including 154 who were asymptomatic and tested negative to start the study. This exceeded the initial enrollment goals of 60 positive participants. We enrolled participants from 44 U.S. states, and geographic distribution of participants shifted in accordance with the changing COVID-19 prevalence nationwide. Limitations New, complex workflows required significant operational and data team support. Conclusions: The digital site-less approach employed in the 'Test Us At Home' study enabled rapid, efficient, and rigorous evaluation of rapid diagnostics for COVID-19, and can be adapted across research disciplines to optimize study enrollment and accessibility.
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Soni A, Herbert C, Filippaios A, Broach J, Colubri A, Fahey N, Woods K, Nanavati J, Wright C, Orwig T, Gilliam K, Kheterpal V, Suvarna T, Nowak C, Schrader S, Lin H, O'Connor L, Pretz C, Ayturk D, Orvek E, Flahive J, Lazar P, Shi Q, Achenbach C, Murphy R, Robinson M, Gibson L, Stamegna P, Hafer N, Luzuriaga K, Barton B, Heetderks W, Manabe YC, McManus D. Comparison of Rapid Antigen Tests' Performance Between Delta and Omicron Variants of SARS-CoV-2 : A Secondary Analysis From a Serial Home Self-testing Study. Ann Intern Med 2022; 175:1685-1692. [PMID: 36215709 PMCID: PMC9578286 DOI: 10.7326/m22-0760] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND It is important to document the performance of rapid antigen tests (Ag-RDTs) in detecting SARS-CoV-2 variants. OBJECTIVE To compare the performance of Ag-RDTs in detecting the Delta (B.1.617.2) and Omicron (B.1.1.529) variants of SARS-CoV-2. DESIGN Secondary analysis of a prospective cohort study that enrolled participants between 18 October 2021 and 24 January 2022. Participants did Ag-RDTs and collected samples for reverse transcriptase polymerase chain reaction (RT-PCR) testing every 48 hours for 15 days. SETTING The parent study enrolled participants throughout the mainland United States through a digital platform. All participants self-collected anterior nasal swabs for rapid antigen testing and RT-PCR testing. All Ag-RDTs were completed at home, whereas nasal swabs for RT-PCR were shipped to a central laboratory. PARTICIPANTS Of 7349 participants enrolled in the parent study, 5779 asymptomatic persons who tested negative for SARS-CoV-2 on day 1 of the study were eligible for this substudy. MEASUREMENTS Sensitivity of Ag-RDTs on the same day as the first positive (index) RT-PCR result and 48 hours after the first positive RT-PCR result. RESULTS A total of 207 participants were positive on RT-PCR (58 Delta, 149 Omicron). Differences in sensitivity between variants were not statistically significant (same day: Delta, 15.5% [95% CI, 6.2% to 24.8%] vs. Omicron, 22.1% [CI, 15.5% to 28.8%]; at 48 hours: Delta, 44.8% [CI, 32.0% to 57.6%] vs. Omicron, 49.7% [CI, 41.6% to 57.6%]). Among 109 participants who had RT-PCR-positive results for 48 hours, rapid antigen sensitivity did not differ significantly between Delta- and Omicron-infected participants (48-hour sensitivity: Delta, 81.5% [CI, 66.8% to 96.1%] vs. Omicron, 78.0% [CI, 69.1% to 87.0%]). Only 7.2% of the 69 participants with RT-PCR-positive results for shorter than 48 hours tested positive by Ag-RDT within 1 week; those with Delta infections remained consistently negative on Ag-RDTs. LIMITATION A testing frequency of 48 hours does not allow a finer temporal resolution of the analysis of test performance, and the results of Ag-RDTs are based on self-report. CONCLUSION The performance of Ag-RDTs in persons infected with the SARS-CoV-2 Omicron variant is not inferior to that in persons with Delta infections. Serial testing improved the sensitivity of Ag-RDTs for both variants. The performance of rapid antigen testing varies on the basis of duration of RT-PCR positivity. PRIMARY FUNDING SOURCE National Heart, Lung, and Blood Institute of the National Institutes of Health.
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Affiliation(s)
- Apurv Soni
- Program in Digital Medicine and Division of Clinical Informatics, Department of Medicine, and Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (A.S.)
| | - Carly Herbert
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.)
| | - Andreas Filippaios
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.)
| | - John Broach
- Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (J.B., L.O.)
| | - Andres Colubri
- Department of Microbiology and Physiological Systems, University of Massachusetts Chan Medical School, Worcester, Massachusetts (A.C.)
| | - Nisha Fahey
- Program in Digital Medicine, Department of Medicine, Department of Population and Quantitative Health Sciences, and Department of Pediatrics, University of Massachusetts Chan Medical School, Worcester, Massachusetts (N.F.)
| | - Kelsey Woods
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.)
| | - Janvi Nanavati
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.)
| | - Colton Wright
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.)
| | - Taylor Orwig
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.)
| | - Karen Gilliam
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.)
| | - Vik Kheterpal
- CareEvolution, Ann Arbor, Michigan (V.K., T.S., C.N., S.S.)
| | - Thejas Suvarna
- CareEvolution, Ann Arbor, Michigan (V.K., T.S., C.N., S.S.)
| | - Chris Nowak
- CareEvolution, Ann Arbor, Michigan (V.K., T.S., C.N., S.S.)
| | | | - Honghuang Lin
- Program in Digital Medicine and Division of Clinical Informatics, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (H.L.)
| | - Laurel O'Connor
- Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (J.B., L.O.)
| | - Caitlin Pretz
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.)
| | - Didem Ayturk
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (D.A., E.O., J.F., P.L., B.B.)
| | - Elizabeth Orvek
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (D.A., E.O., J.F., P.L., B.B.)
| | - Julie Flahive
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (D.A., E.O., J.F., P.L., B.B.)
| | - Peter Lazar
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (D.A., E.O., J.F., P.L., B.B.)
| | - Qiming Shi
- Program in Digital Medicine, Department of Medicine, Department of Population and Quantitative Health Sciences, and University of Massachusetts Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, Massachusetts (Q.S.)
| | - Chad Achenbach
- Division of Infectious Disease, Department of Medicine, Havey Institute for Global Health, Feinberg School of Medicine, Northwestern University, Chicago, Illinois (C.A., R.M.)
| | - Robert Murphy
- Division of Infectious Disease, Department of Medicine, Havey Institute for Global Health, Feinberg School of Medicine, Northwestern University, Chicago, Illinois (C.A., R.M.)
| | - Matthew Robinson
- Division of Infectious Disease, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland (M.R., Y.C.M.)
| | - Laura Gibson
- Department of Pediatrics and Division of Infectious Disease, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (L.G.)
| | - Pamela Stamegna
- University of Massachusetts Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, Massachusetts (P.S., N.H.)
| | - Nathaniel Hafer
- University of Massachusetts Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, Massachusetts (P.S., N.H.)
| | - Katherine Luzuriaga
- University of Massachusetts Center for Clinical and Translational Science and Program in Molecular Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (K.L.)
| | - Bruce Barton
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (D.A., E.O., J.F., P.L., B.B.)
| | - William Heetderks
- National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland (W.H.)
| | - Yukari C Manabe
- Division of Infectious Disease, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland (M.R., Y.C.M.)
| | - David McManus
- Program in Digital Medicine and Division of Cardiology, Department of Medicine, and Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (D.M.)
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Soni A, Herbert C, Filippaios A, Broach J, Colubri A, Fahey N, Woods K, Nanavati J, Wright C, Orwig T, Gilliam K, Kheterpal V, Suvarna T, Nowak C, Schrader S, Lin H, O'Connor L, Pretz C, Ayturk D, Orvek E, Flahive J, Lazar P, Shi Q, Achenbach C, Murphy R, Robinson M, Gibson L, Stamegna P, Hafer N, Luzuriaga K, Barton B, Heetderks W, Manabe YC, McManus D. Comparison of Rapid Antigen Tests' Performance between Delta (B.1.61.7; AY.X) and Omicron (B.1.1.529; BA1) Variants of SARS-CoV-2: Secondary Analysis from a Serial Home Self-Testing Study. medRxiv 2022. [PMID: 35262091 DOI: 10.1101/2022.02.27.22271090] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Background There is a need to understand the performance of rapid antigen tests (Ag-RDT) for detection of the Delta (B.1.61.7; AY.X) and Omicron (B.1.1.529; BA1) SARS-CoV-2 variants. Methods Participants without any symptoms were enrolled from October 18, 2021 to January 24, 2022 and performed Ag-RDT and RT-PCR tests every 48 hours for 15 days. This study represents a non-pre-specified analysis in which we sought to determine if sensitivity of Ag-RDT differed in participants with Delta compared to Omicron variant. Participants who were positive on RT-PCR on the first day of the testing period were excluded. Delta and Omicron variants were defined based on sequencing and date of first RT-PCR positive result (RT-PCR+). Comparison of Ag-RDT performance between the variants was based on sensitivity, defined as proportion of participants with Ag-RDT+ results in relation to their first RT-PCR+ result, for different duration of testing with rapid Ag-RDT. Subsample analysis was performed based on the result of participants' second RT-PCR test within 48 hours of the first RT-PCR+ test. Results From the 7,349 participants enrolled in the parent study, 5,506 met the eligibility criteria for this analysis. A total of 153 participants were RT-PCR+ (61 Delta, 92 Omicron); among this group, 36 (23.5%) tested Ag-RDT+ on the same day, and 84 (54.9%) tested Ag-RDT+ within 48 hours as first RT-PCR+. The differences in sensitivity between variants were not statistically significant (same-day: Delta 16.4% [95% CI: 8.2-28.1] vs Omicron 28.2% [95% CI: 19.4-38.6]; and 48-hours: Delta 45.9% [33.1-59.2] vs. Omicron 60.9% [50.1-70.9]). This trend continued among the 86 participants who had consecutive RT-PCR+ result (48-hour sensitivity: Delta 79.3% [60.3-92.1] vs. Omicron: 89.5% [78.5-96.0]). Conversely, the 38 participants who had an isolated RT-PCR+ remained consistently negative on Ag-RDT, regardless of the variant. Conclusions The performance of Ag-RDT is not inferior among individuals infected with the SARS-CoV-2 Omicron variant as compared to the Delta variant. The improvement in sensitivity of Ag-RDT noted with serial testing is consistent between Delta and Omicron variant. Performance of Ag-RDT varies based on duration of RT-PCR+ results and more studies are needed to understand the clinical and public health significance of individuals who are RT-PCR+ for less than 48 hours.
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Lazaro E, Kadie C, Stamegna P, Zhang SC, Gourdain P, Lai NY, Zhang M, Martinez SA, Heckerman D, Le Gall S. Variable HIV peptide stability in human cytosol is critical to epitope presentation and immune escape. J Clin Invest 2011; 121:2480-92. [PMID: 21555856 DOI: 10.1172/jci44932] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2010] [Accepted: 03/16/2011] [Indexed: 11/17/2022] Open
Abstract
Induction of virus-specific CD8⁺ T cell responses is critical for the success of vaccines against chronic viral infections. Despite the large number of potential MHC-I-restricted epitopes located in viral proteins, MHC-I-restricted epitope generation is inefficient, and factors defining the production and presentation of MHC-I-restricted viral epitopes are poorly understood. Here, we have demonstrated that the half-lives of HIV-derived peptides in cytosol from primary human cells were highly variable and sequence dependent, and significantly affected the efficiency of cell recognition by CD8⁺ T cells. Furthermore, multiple clinical isolates of HLA-associated HIV epitope variants displayed reduced half-lives relative to consensus sequence. This decreased cytosolic peptide stability diminished epitope presentation and CTL recognition, illustrating a mechanism of immune escape. Chaperone complexes including Hsp90 and histone deacetylase HDAC6 enhanced peptide stability by transient protection from peptidase degradation. Based on empirical results with 166 peptides, we developed a computational approach utilizing a sequence-based algorithm to estimate the cytosolic stability of antigenic peptides. Our results identify sequence motifs able to alter the amount of peptide available for loading onto MHC-I, suggesting potential new strategies to modulate epitope production from vaccine immunogens.
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Affiliation(s)
- Estibaliz Lazaro
- Ragon Institute of MGH, MIT and Harvard, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02129, USA
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Lazaro E, Godfrey SB, Stamegna P, Ogbechie T, Kerrigan C, Zhang M, Walker BD, Le Gall S. Differential HIV epitope processing in monocytes and CD4 T cells affects cytotoxic T lymphocyte recognition. J Infect Dis 2009; 200:236-43. [PMID: 19505257 PMCID: PMC3724235 DOI: 10.1086/599837] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
Abstract
The ability of cytotoxic T lymphocytes (CTLs) to clear virus-infected cells is dependent on the presentation of viral peptides processed intracellularly and displayed by major histocompatibility complex class I. Most CTL functional assays use exogenously added peptides, a practice that does not account for the kinetics and quantity of antigenic peptides produced by infectable cells. Here, we examined the relative ability of 2 major human immunodeficiency virus-infectable cell subsets-CD4 T lymphocytes and monocytes-to produce antigenic peptides, using cytosol as a source of peptidases and mass spectrometry to define the degradation products. We show clear subset-specific differences in the kinetics of peptide production and the ability of the peptides produced to sensitize cells for lysis by CTLs, with primary CD4 T lymphocytes having significantly lower proteolytic activity than monocytes. These differences in epitope processing by cell subsets may affect the efficiency of CTL-mediated clearance of infected subsets and contribute to the establishment of chronic infection.
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Affiliation(s)
- Estibaliz Lazaro
- Ragon Institute of MGH, MIT and Harvard (formerly Partners AIDS Research Center), Massachusetts General Hospital, Harvard Medical School, CNY 149 13 street, Boston, MA 02129
| | - Sasha Blue Godfrey
- Ragon Institute of MGH, MIT and Harvard (formerly Partners AIDS Research Center), Massachusetts General Hospital, Harvard Medical School, CNY 149 13 street, Boston, MA 02129
| | - Pamela Stamegna
- Ragon Institute of MGH, MIT and Harvard (formerly Partners AIDS Research Center), Massachusetts General Hospital, Harvard Medical School, CNY 149 13 street, Boston, MA 02129
| | - Tobi Ogbechie
- Ragon Institute of MGH, MIT and Harvard (formerly Partners AIDS Research Center), Massachusetts General Hospital, Harvard Medical School, CNY 149 13 street, Boston, MA 02129
| | - Christopher Kerrigan
- Ragon Institute of MGH, MIT and Harvard (formerly Partners AIDS Research Center), Massachusetts General Hospital, Harvard Medical School, CNY 149 13 street, Boston, MA 02129
| | - Mei Zhang
- Ragon Institute of MGH, MIT and Harvard (formerly Partners AIDS Research Center), Massachusetts General Hospital, Harvard Medical School, CNY 149 13 street, Boston, MA 02129
| | - Bruce D. Walker
- Ragon Institute of MGH, MIT and Harvard (formerly Partners AIDS Research Center), Massachusetts General Hospital, Harvard Medical School, CNY 149 13 street, Boston, MA 02129
- Howard Hughes Medical Institute, 4000 Jones Bridge Road, Chevy Chase, MD 20815-6789
| | - Sylvie Le Gall
- Ragon Institute of MGH, MIT and Harvard (formerly Partners AIDS Research Center), Massachusetts General Hospital, Harvard Medical School, CNY 149 13 street, Boston, MA 02129
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Le Gall S, Stamegna P, Walker BD. Portable flanking sequences modulate CTL epitope processing. J Clin Invest 2008; 117:3563-75. [PMID: 17975674 DOI: 10.1172/jci32047] [Citation(s) in RCA: 82] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2007] [Accepted: 09/05/2007] [Indexed: 02/05/2023] Open
Abstract
Peptide presentation is critical for immune recognition of pathogen-infected cells by CD8+ T lymphocytes. Although a limited number of immunodominant peptide epitopes are consistently observed in diseases such as HIV-1 infection, the relationship between immunodominance and antigen processing in humans is largely unknown. Here, we have demonstrated that endogenous processing and presentation of a human immunodominant HIV-1 epitope is more efficient than that of a subdominant epitope. Furthermore, we have shown that the regions flanking the immunodominant epitope constitute a portable motif that increases the production and antigenicity of otherwise subdominant epitopes. We used a novel in vitro degradation assay involving cytosolic extracts as well as endogenous intracellular processing assays to examine 2 well-characterized HIV-1 Gag overlapping epitopes presented by the same HLA class I allele, one of which is consistently immunodominant and the other subdominant in infected persons. The kinetics and products of degradation of HIV-1 Gag favored the production of peptides encompassing the immunodominant epitope and destruction of the subdominant one. Notably, cytosolic digestion experiments revealed flanking residues proximal to the immunodominant epitope that increased the production and antigenicity of otherwise subdominant epitopes. Furthermore, specific point mutations in these portable flanking sequences modulated the production and antigenicity of epitopes. Such portable epitope processing determinants provide what we believe is a novel approach to optimizing CTL responses elicited by vaccine vectors.
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Affiliation(s)
- Sylvie Le Gall
- Partners AIDS Research Center and Howard Hughes Medical Institute, Massachusetts General Hospital (MGH), Harvard Medical School, Boston, Massachusetts 02129, USA.
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Lazaro E, Godfrey SB, Stamegna P, Ho J, Walker B, Gall SL. Su.40. Differential Antigen Processing Activities of PBMC Subsets Targeted by HIV Modulate HIV Epitope Production. Clin Immunol 2008. [DOI: 10.1016/j.clim.2008.03.391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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