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Fox T, Geppert J, Dinnes J, Scandrett K, Bigio J, Sulis G, Hettiarachchi D, Mathangasinghe Y, Weeratunga P, Wickramasinghe D, Bergman H, Buckley BS, Probyn K, Sguassero Y, Davenport C, Cunningham J, Dittrich S, Emperador D, Hooft L, Leeflang MM, McInnes MD, Spijker R, Struyf T, Van den Bruel A, Verbakel JY, Takwoingi Y, Taylor-Phillips S, Deeks JJ. Antibody tests for identification of current and past infection with SARS-CoV-2. Cochrane Database Syst Rev 2022; 11:CD013652. [PMID: 36394900 PMCID: PMC9671206 DOI: 10.1002/14651858.cd013652.pub2] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
BACKGROUND The diagnostic challenges associated with the COVID-19 pandemic resulted in rapid development of diagnostic test methods for detecting SARS-CoV-2 infection. Serology tests to detect the presence of antibodies to SARS-CoV-2 enable detection of past infection and may detect cases of SARS-CoV-2 infection that were missed by earlier diagnostic tests. Understanding the diagnostic accuracy of serology tests for SARS-CoV-2 infection may enable development of effective diagnostic and management pathways, inform public health management decisions and understanding of SARS-CoV-2 epidemiology. OBJECTIVES To assess the accuracy of antibody tests, firstly, to determine if a person presenting in the community, or in primary or secondary care has current SARS-CoV-2 infection according to time after onset of infection and, secondly, to determine if a person has previously been infected with SARS-CoV-2. Sources of heterogeneity investigated included: timing of test, test method, SARS-CoV-2 antigen used, test brand, and reference standard for non-SARS-CoV-2 cases. SEARCH METHODS The COVID-19 Open Access Project living evidence database from the University of Bern (which includes daily updates from PubMed and Embase and preprints from medRxiv and bioRxiv) was searched on 30 September 2020. We included additional publications from the Evidence for Policy and Practice Information and Co-ordinating Centre (EPPI-Centre) 'COVID-19: Living map of the evidence' and the Norwegian Institute of Public Health 'NIPH systematic and living map on COVID-19 evidence'. We did not apply language restrictions. SELECTION CRITERIA We included test accuracy studies of any design that evaluated commercially produced serology tests, targeting IgG, IgM, IgA alone, or in combination. Studies must have provided data for sensitivity, that could be allocated to a predefined time period after onset of symptoms, or after a positive RT-PCR test. Small studies with fewer than 25 SARS-CoV-2 infection cases were excluded. We included any reference standard to define the presence or absence of SARS-CoV-2 (including reverse transcription polymerase chain reaction tests (RT-PCR), clinical diagnostic criteria, and pre-pandemic samples). DATA COLLECTION AND ANALYSIS We use standard screening procedures with three reviewers. Quality assessment (using the QUADAS-2 tool) and numeric study results were extracted independently by two people. Other study characteristics were extracted by one reviewer and checked by a second. We present sensitivity and specificity with 95% confidence intervals (CIs) for each test and, for meta-analysis, we fitted univariate random-effects logistic regression models for sensitivity by eligible time period and for specificity by reference standard group. Heterogeneity was investigated by including indicator variables in the random-effects logistic regression models. We tabulated results by test manufacturer and summarised results for tests that were evaluated in 200 or more samples and that met a modification of UK Medicines and Healthcare products Regulatory Agency (MHRA) target performance criteria. MAIN RESULTS We included 178 separate studies (described in 177 study reports, with 45 as pre-prints) providing 527 test evaluations. The studies included 64,688 samples including 25,724 from people with confirmed SARS-CoV-2; most compared the accuracy of two or more assays (102/178, 57%). Participants with confirmed SARS-CoV-2 infection were most commonly hospital inpatients (78/178, 44%), and pre-pandemic samples were used by 45% (81/178) to estimate specificity. Over two-thirds of studies recruited participants based on known SARS-CoV-2 infection status (123/178, 69%). All studies were conducted prior to the introduction of SARS-CoV-2 vaccines and present data for naturally acquired antibody responses. Seventy-nine percent (141/178) of studies reported sensitivity by week after symptom onset and 66% (117/178) for convalescent phase infection. Studies evaluated enzyme-linked immunosorbent assays (ELISA) (165/527; 31%), chemiluminescent assays (CLIA) (167/527; 32%) or lateral flow assays (LFA) (188/527; 36%). Risk of bias was high because of participant selection (172, 97%); application and interpretation of the index test (35, 20%); weaknesses in the reference standard (38, 21%); and issues related to participant flow and timing (148, 82%). We judged that there were high concerns about the applicability of the evidence related to participants in 170 (96%) studies, and about the applicability of the reference standard in 162 (91%) studies. Average sensitivities for current SARS-CoV-2 infection increased by week after onset for all target antibodies. Average sensitivity for the combination of either IgG or IgM was 41.1% in week one (95% CI 38.1 to 44.2; 103 evaluations; 3881 samples, 1593 cases), 74.9% in week two (95% CI 72.4 to 77.3; 96 evaluations, 3948 samples, 2904 cases) and 88.0% by week three after onset of symptoms (95% CI 86.3 to 89.5; 103 evaluations, 2929 samples, 2571 cases). Average sensitivity during the convalescent phase of infection (up to a maximum of 100 days since onset of symptoms, where reported) was 89.8% for IgG (95% CI 88.5 to 90.9; 253 evaluations, 16,846 samples, 14,183 cases), 92.9% for IgG or IgM combined (95% CI 91.0 to 94.4; 108 evaluations, 3571 samples, 3206 cases) and 94.3% for total antibodies (95% CI 92.8 to 95.5; 58 evaluations, 7063 samples, 6652 cases). Average sensitivities for IgM alone followed a similar pattern but were of a lower test accuracy in every time slot. Average specificities were consistently high and precise, particularly for pre-pandemic samples which provide the least biased estimates of specificity (ranging from 98.6% for IgM to 99.8% for total antibodies). Subgroup analyses suggested small differences in sensitivity and specificity by test technology however heterogeneity in study results, timing of sample collection, and smaller sample numbers in some groups made comparisons difficult. For IgG, CLIAs were the most sensitive (convalescent-phase infection) and specific (pre-pandemic samples) compared to both ELISAs and LFAs (P < 0.001 for differences across test methods). The antigen(s) used (whether from the Spike-protein or nucleocapsid) appeared to have some effect on average sensitivity in the first weeks after onset but there was no clear evidence of an effect during convalescent-phase infection. Investigations of test performance by brand showed considerable variation in sensitivity between tests, and in results between studies evaluating the same test. For tests that were evaluated in 200 or more samples, the lower bound of the 95% CI for sensitivity was 90% or more for only a small number of tests (IgG, n = 5; IgG or IgM, n = 1; total antibodies, n = 4). More test brands met the MHRA minimum criteria for specificity of 98% or above (IgG, n = 16; IgG or IgM, n = 5; total antibodies, n = 7). Seven assays met the specified criteria for both sensitivity and specificity. In a low-prevalence (2%) setting, where antibody testing is used to diagnose COVID-19 in people with symptoms but who have had a negative PCR test, we would anticipate that 1 (1 to 2) case would be missed and 8 (5 to 15) would be falsely positive in 1000 people undergoing IgG or IgM testing in week three after onset of SARS-CoV-2 infection. In a seroprevalence survey, where prevalence of prior infection is 50%, we would anticipate that 51 (46 to 58) cases would be missed and 6 (5 to 7) would be falsely positive in 1000 people having IgG tests during the convalescent phase (21 to 100 days post-symptom onset or post-positive PCR) of SARS-CoV-2 infection. AUTHORS' CONCLUSIONS Some antibody tests could be a useful diagnostic tool for those in whom molecular- or antigen-based tests have failed to detect the SARS-CoV-2 virus, including in those with ongoing symptoms of acute infection (from week three onwards) or those presenting with post-acute sequelae of COVID-19. However, antibody tests have an increasing likelihood of detecting an immune response to infection as time since onset of infection progresses and have demonstrated adequate performance for detection of prior infection for sero-epidemiological purposes. The applicability of results for detection of vaccination-induced antibodies is uncertain.
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Affiliation(s)
- Tilly Fox
- Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, UK
| | - Julia Geppert
- Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, 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
| | - Katie Scandrett
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Jacob Bigio
- Research Institute of the McGill University Health Centre, Montreal, Canada
- McGill International TB Centre, Montreal, Canada
| | - Giorgia Sulis
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada
| | - Dineshani Hettiarachchi
- Department of Anatomy Genetics and Biomedical Informatics, Faculty of Medicine, University of Colombo, Colombo, Sri Lanka
| | - Yasith Mathangasinghe
- Department of Anatomy Genetics and Biomedical Informatics, Faculty of Medicine, University of Colombo, Colombo, Sri Lanka
- Australian Regenerative Medicine Institute, Monash University, Clayton, Australia
| | - Praveen Weeratunga
- Department of Clinical Medicine, Faculty of Medicine, University of Colombo, Colombo, Sri Lanka
| | | | | | - Brian S Buckley
- Cochrane Response, Cochrane, London, UK
- Department of Surgery, University of the Philippines, Manila, Philippines
| | | | | | - 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
| | - Jane Cunningham
- Global Malaria Programme, World Health Organization, Geneva, Switzerland
| | | | | | - Lotty Hooft
- Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht , Netherlands
| | - Mariska Mg Leeflang
- Epidemiology and Data Science, Amsterdam UMC location University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Public Health, Amsterdam, Netherlands
| | | | - 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
| | - Thomas Struyf
- Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium
| | - Ann Van den Bruel
- Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium
| | - Jan Y Verbakel
- Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium
| | - 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
| | - Sian Taylor-Phillips
- Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - 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
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Tollånes MC, Jenum PA, Kierkegaard H, Abildsnes E, Bævre-Jensen RM, Breivik AC, Sandberg S. Evaluation of 32 rapid tests for detection of antibodies against SARS-CoV-2. Clin Chim Acta 2021; 519:133-139. [PMID: 33930425 PMCID: PMC8078036 DOI: 10.1016/j.cca.2021.04.016] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 04/23/2021] [Accepted: 04/23/2021] [Indexed: 12/16/2022]
Abstract
AIMS To evaluate the analytical performance of 32 rapid tests for detection of antibodies against coronavirus SARS-CoV-2. MATERIALS AND METHODS We used at total of 262 serum samples (197 pre-pandemic and 65 convalescent COVID-19), and three criteria to evaluate the rapid tests under standardized and optimal conditions: (i) Immunoglobulin G (IgG) specificity "good" if lower limit of the 95% confidence interval was ≥ 97.0%, "acceptable" if point estimate was ≥ 97.0%, otherwise "not acceptable". (ii) IgG sensitivity "good" if point estimate was ≥ 90.0%, "acceptable" if ≥ 85.0%, otherwise "not acceptable". (iii) User-friendliness "not acceptable" if complicated to perform or difficult to read result, otherwise "good". We also included partial evaluations of three automated immunoassay systems. RESULTS Sensitivity and specificity varied considerably; IgG specificity between 90.9% (85.9-94.2) and 100% (97.7-100.0), and IgG sensitivity between 53.8% (41.9-65.4) and 98.5% (91.0-100.0). Combining our evaluation criteria, none of the 28 rapid tests that detected IgG had an overall performance considered "good", seven tests were considered "acceptable", while 21 tests were considered "not acceptable". Four tests detected only total antibodies and were not given an overall evaluation. IgG sensitivity and/or specificity of the automated immunoassays did not exceed that of many rapid tests. CONCLUSION When prevalence is low, the most important analytical property is a test's IgG specificity, which must be high to minimize false positive results. Out of 32 rapid tests, none had a performance classified as "good", but seven were classified as "acceptable".
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Affiliation(s)
- Mette C. Tollånes
- Norwegian Organization for Quality Improvement of Laboratory Examinations, Haraldsplass Deaconess Hospital, Bergen, Norway,Department of Global Public Health and Primary Care, University of Bergen, Norway,Corresponding author.at: Norwegian Organization for Quality Improvement of Laboratory Examinations (Noklus), Haraldsplass Deaconess Hospital, P.O. Box 6165, N-5892 Bergen, Norway
| | - Pål A. Jenum
- Norwegian Organization for Quality Improvement of Laboratory Examinations, Haraldsplass Deaconess Hospital, Bergen, Norway
| | | | | | | | - Anne C. Breivik
- Norwegian Organization for Quality Improvement of Laboratory Examinations, Haraldsplass Deaconess Hospital, Bergen, Norway
| | - Sverre Sandberg
- Norwegian Organization for Quality Improvement of Laboratory Examinations, Haraldsplass Deaconess Hospital, Bergen, Norway,Department of Global Public Health and Primary Care, University of Bergen, Norway,Department of Medical Biochemistry and Pharmacology, Haukeland University Hospital, Bergen, Norway
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Kruse RL, Huang Y, Lee A, Zhu X, Shrestha R, Laeyendecker O, Littlefield K, Pekosz A, Bloch EM, Tobian AAR, Wang ZZ. A hemagglutination-based, semi-quantitative test for point-of-care determination of SARS-CoV-2 antibody levels. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021. [PMID: 33972952 DOI: 10.1101/2021.05.01.21256452] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Serologic, point-of-care tests to detect antibodies against SARS-CoV-2 are an important tool in the COVID-19 pandemic. The majority of current point-of-care antibody tests developed for SARS-CoV-2 rely on lateral flow assays, but these do not offer quantitative information. To address this, we developed a new method of COVID-19 antibody testing employing hemagglutination tested on a dry card, similar to that which is already available for rapid typing of ABO blood groups. A fusion protein linking red blood cells (RBCs) to the receptor-binding domain (RBD) of SARS-CoV-2 spike protein was placed on the card. 200 COVID-19 patient and 200 control plasma samples were reconstituted with O-negative RBCs to form whole blood and added to the dried protein, followed by a stirring step and a tilting step, 3-minute incubation, and a second tilting step. The sensitivity for the hemagglutination test, Euroimmun IgG ELISA test and RBD-based CoronaChek lateral flow assay was 87.0%, 86.5%, and 84.5%, respectively, using samples obtained from recovered COVID-19 individuals. Testing pre-pandemic samples, the hemagglutination test had a specificity of 95.5%, compared to 97.3% and 98.9% for the ELISA and CoronaChek, respectively. A distribution of agglutination strengths was observed in COVID-19 convalescent plasma samples, with the highest agglutination score (4) exhibiting significantly higher neutralizing antibody titers than weak positives (2) (p<0.0001). Strong agglutinations were observed within 1 minute of testing, and this shorter assay time also increased specificity to 98.5%. In conclusion, we developed a novel rapid, point-of-care RBC agglutination test for the detection of SARS-CoV-2 antibodies that can yield semi-quantitative information on neutralizing antibody titer in patients. The five-minute test may find use in determination of serostatus prior to vaccination, post-vaccination surveillance and travel screening.
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Baker OR, Grabowski MK, Galiwango RM, Nalumansi A, Serwanga J, Clarke W, Hsieh YH, Rothman RE, Fernandez RE, Serwadda D, Kagaayi J, Lutalo T, Reynolds SJ, Kaleebu P, Quinn TC, Laeyendecker O. Differential Performance of CoronaCHEK SARS-CoV-2 Lateral Flow Antibody Assay by Geographic Origin of Samples. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.04.12.21255284. [PMID: 33880484 PMCID: PMC8057252 DOI: 10.1101/2021.04.12.21255284] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Background We assessed the performance of CoronaCHEK lateral flow assay on samples from Uganda and Baltimore to determine the impact of geographic origin on assay performance. Methods Serum samples from SARS-CoV-2 PCR+ individuals (Uganda: 78 samples from 78 individuals and Baltimore: 266 samples from 38 individuals) and from pre-pandemic individuals (Uganda 1077 and Baltimore 532) were evaluated. Prevalence ratios (PR) were calculated to identify factors associated with a false-positive test. Results After first positive PCR in Ugandan samples the sensitivity was: 45% (95% CI 24,68) at 0-7 days; 79% (95%CI 64,91) 8-14 days; and 76% (95%CI 50,93) >15 days. In samples from Baltimore, sensitivity was: 39% (95% CI 30, 49) 0-7 days; 86% (95% CI 79,92) 8-14 days; and 100% (95% CI 89,100) 15 days post positive PCR. The specificity of 96.5% (95% CI 97.5,95.2) in Ugandan samples was significantly lower than samples from Baltimore 99.3% (95% CI 98.1,99.8), p<0.01. In Ugandan samples, individuals with a false positive result were more likely to be male (PR 2.04, 95% CI 1.03,3.69) or individuals who had a fever more than a month prior to sample acquisition (PR 2.87, 95% CI 1.12,7.35). Conclusions Sensitivity of the CoronaCHEK was similar in samples from Uganda and Baltimore. The specificity was significantly lower in Ugandan samples than in Baltimore samples. False positive results in Ugandan samples appear to correlate with a recent history of a febrile illness, potentially indicative of a cross-reactive immune response in individuals from East Africa.
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Affiliation(s)
- Owen R. Baker
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Baltimore, MD, USA
| | - M. Kate Grabowski
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Rakai Health Sciences Program, Kalisizo, Uganda
| | | | | | - Jennifer Serwanga
- Uganda Virus Research Institute, Entebbe, Uganda
- Medical Research Council, Uganda Virus Research Institute and London School of hygiene and Tropical Medicine Uganda Research Unit
| | - William Clarke
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yu-Hsiang Hsieh
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | | | | | - David Serwadda
- Rakai Health Sciences Program, Kalisizo, Uganda
- Makerere University School of Public Health, Kampala, Uganda
| | | | - Tom Lutalo
- Rakai Health Sciences Program, Kalisizo, Uganda
- Uganda Virus Research Institute, Entebbe, Uganda
| | - Steven J. Reynolds
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Baltimore, MD, USA
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Rakai Health Sciences Program, Kalisizo, Uganda
| | - Pontiano Kaleebu
- Uganda Virus Research Institute, Entebbe, Uganda
- Medical Research Council, Uganda Virus Research Institute and London School of hygiene and Tropical Medicine Uganda Research Unit
| | - Thomas C. Quinn
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Baltimore, MD, USA
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Oliver Laeyendecker
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Baltimore, MD, USA
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
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5
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Moshe M, Daunt A, Flower B, Simmons B, Brown JC, Frise R, Penn R, Kugathasan R, Petersen C, Stockmann H, Ashby D, Riley S, Atchison C, Taylor GP, Satkunarajah S, Naar L, Klaber R, Badhan A, Rosadas C, Marchesin F, Fernandez N, Sureda-Vives M, Cheeseman H, O'Hara J, Shattock R, Fontana G, Pallett SJC, Rayment M, Jones R, Moore LSP, Ashrafian H, Cherapanov P, Tedder R, McClure M, Ward H, Darzi A, Elliott P, Cooke GS, Barclay WS. SARS-CoV-2 lateral flow assays for possible use in national covid-19 seroprevalence surveys (React 2): diagnostic accuracy study. BMJ 2021; 372:n423. [PMID: 33653694 PMCID: PMC7921617 DOI: 10.1136/bmj.n423] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
OBJECTIVE To evaluate the performance of new lateral flow immunoassays (LFIAs) suitable for use in a national coronavirus disease 2019 (covid-19) seroprevalence programme (real time assessment of community transmission 2-React 2). DESIGN Diagnostic accuracy study. SETTING Laboratory analyses were performed in the United Kingdom at Imperial College, London and university facilities in London. Research clinics for finger prick sampling were run in two affiliated NHS trusts. PARTICIPANTS Sensitivity analyses were performed on sera stored from 320 previous participants in the React 2 programme with confirmed previous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Specificity analyses were performed on 1000 prepandemic serum samples. 100 new participants with confirmed previous SARS-CoV-2 infection attended study clinics for finger prick testing. INTERVENTIONS Laboratory sensitivity and specificity analyses were performed for seven LFIAs on a minimum of 200 serum samples from participants with confirmed SARS-CoV-2 infection and 500 prepandemic serum samples, respectively. Three LFIAs were found to have a laboratory sensitivity superior to the finger prick sensitivity of the LFIA currently used in React 2 seroprevalence studies (84%). These LFIAs were then further evaluated through finger prick testing on participants with confirmed previous SARS-CoV-2 infection: two LFIAs (Surescreen, Panbio) were evaluated in clinics in June-July 2020 and the third LFIA (AbC-19) in September 2020. A spike protein enzyme linked immunoassay and hybrid double antigen binding assay were used as laboratory reference standards. MAIN OUTCOME MEASURES The accuracy of LFIAs in detecting immunoglobulin G (IgG) antibodies to SARS-CoV-2 compared with two reference standards. RESULTS The sensitivity and specificity of seven new LFIAs that were analysed using sera varied from 69% to 100%, and from 98.6% to 100%, respectively (compared with the two reference standards). Sensitivity on finger prick testing was 77% (95% confidence interval 61.4% to 88.2%) for Panbio, 86% (72.7% to 94.8%) for Surescreen, and 69% (53.8% to 81.3%) for AbC-19 compared with the reference standards. Sensitivity for sera from matched clinical samples performed on AbC-19 was significantly higher with serum than finger prick at 92% (80.0% to 97.7%, P=0.01). Antibody titres varied considerably among cohorts. The numbers of positive samples identified by finger prick in the lowest antibody titre quarter varied among LFIAs. CONCLUSIONS One new LFIA was identified with clinical performance suitable for potential inclusion in seroprevalence studies. However, none of the LFIAs tested had clearly superior performance to the LFIA currently used in React 2 seroprevalence surveys, and none showed sufficient sensitivity and specificity to be considered for routine clinical use.
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Affiliation(s)
- Maya Moshe
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
| | - Anna Daunt
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
- Imperial College Healthcare NHS Trust, St Mary's Hospital, London, UK
| | - Barnaby Flower
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
- Imperial College Healthcare NHS Trust, St Mary's Hospital, London, UK
| | - Bryony Simmons
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
| | - Jonathan C Brown
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
| | - Rebecca Frise
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
| | - Rebecca Penn
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
| | - Ruthiran Kugathasan
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
| | - Claire Petersen
- Imperial College Healthcare NHS Trust, St Mary's Hospital, London, UK
| | - Helen Stockmann
- Imperial College Healthcare NHS Trust, St Mary's Hospital, London, UK
| | - Deborah Ashby
- School of Public Health, Imperial College London, St Mary's Hospital, London, UK
| | - Steven Riley
- School of Public Health, Imperial College London, St Mary's Hospital, London, UK
| | - Christina Atchison
- School of Public Health, Imperial College London, St Mary's Hospital, London, UK
| | - Graham P Taylor
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
| | - Sutha Satkunarajah
- Institute for Global Health Innovation, Imperial College London, London, UK
| | - Lenny Naar
- Institute for Global Health Innovation, Imperial College London, London, UK
| | - Robert Klaber
- Imperial College Healthcare NHS Trust, St Mary's Hospital, London, UK
| | - Anjna Badhan
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
| | - Carolina Rosadas
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
| | - Federica Marchesin
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
| | - Natalia Fernandez
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
| | - Macià Sureda-Vives
- Synthetic Biology Group, London Institute of Medical Sciences, Imperial College London, London, UK
| | - Hannah Cheeseman
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
| | - Jessica O'Hara
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
| | - Robin Shattock
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
| | - Gianluca Fontana
- Institute for Global Health Innovation, Imperial College London, London, UK
| | - Scott J C Pallett
- Chelsea and Westminster NHS Foundation Trust, London, UK
- Centre of Defence Pathology, Royal Centre for Defence Medicine, Queen Elizabeth Hospital, Birmingham, UK
| | | | - Rachael Jones
- Chelsea and Westminster NHS Foundation Trust, London, UK
| | - Luke S P Moore
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
- Chelsea and Westminster NHS Foundation Trust, London, UK
| | - Hutan Ashrafian
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Peter Cherapanov
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
- Chromatin Structure and Mobile DNA Laboratory, Francis Crick Institute, London, UK
| | - Richard Tedder
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
| | - Myra McClure
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
| | - Helen Ward
- School of Public Health, Imperial College London, St Mary's Hospital, London, UK
| | - Ara Darzi
- Institute for Global Health Innovation, Imperial College London, London, UK
| | - Paul Elliott
- Imperial College Healthcare NHS Trust, St Mary's Hospital, London, UK
- School of Public Health, Imperial College London, St Mary's Hospital, London, UK
- National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Chemical and Radiation Threats and Hazards, Imperial College London, London, UK
| | - Graham S Cooke
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
| | - Wendy S Barclay
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, Praed Street, London W2 1NY, UK
- Imperial College Healthcare NHS Trust, St Mary's Hospital, London, UK
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Heaney CD, Pisanic N, Randad PR, Kruczynski K, Howard T, Zhu X, Littlefield K, Patel EU, Shrestha R, Laeyendecker O, Shoham S, Sullivan D, Gebo K, Hanley D, Redd AD, Quinn TC, Casadevall A, Zenilman JM, Pekosz A, Bloch EM, Tobian AAR. Comparative performance of multiplex salivary and commercially available serologic assays to detect SARS-CoV-2 IgG and neutralization titers. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.01.28.21250717. [PMID: 33532806 PMCID: PMC7852272 DOI: 10.1101/2021.01.28.21250717] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Oral fluid (hereafter saliva) offers a non-invasive sampling method for the detection of SARS-CoV-2 antibodies. However, data comparing performance of salivary tests against commercially-available serologic and neutralizing antibody (nAb) assays are lacking. This study compared the performance of a multiplex salivary SARS-CoV-2 IgG assay targeting antibodies to nucleocapsid (N), receptor binding domain (RBD) and spike (S) antigens to three commercially-available SARS-CoV-2 serology enzyme immunoassays (EIAs) (Ortho Vitros, Euroimmun, and BioRad) and nAb. Paired saliva and plasma samples were collected from 101 eligible COVID-19 convalescent plasma (CCP) donors >14 days since PCR+ confirmed diagnosis. Concordance was evaluated using positive (PPA) and negative (NPA) percent agreement, overall percent agreement (PA), and Cohen kappa coefficient. The range between salivary and plasma EIAs for SARS-CoV-2-specific N was PPA: 54.4-92.1% and NPA: 69.2-91.7%, for RBD was PPA: 89.9-100% and NPA: 50.0-84.6%, and for S was PPA: 50.6-96.6% and NPA: 50.0-100%. Compared to a plasma nAb assay, the multiplex salivary assay PPA ranged from 62.3% (N) and 98.6% (RBD) and NPA ranged from 18.8% (RBD) to 96.9% (S). Combinations of N, RBD, and S and a summary algorithmic index of all three (N/RBD/S) in saliva produced ranges of PPA: 87.6-98.9% and NPA: 50-91.7% with the three EIAs and ranges of PPA: 88.4-98.6% and NPA: 21.9-34.4% with the nAb assay. A multiplex salivary SARS-CoV-2 IgG assay demonstrated comparable performance to three commercially-available plasma EIAs and a nAb assay, and may be a viable alternative to assist in screening CCP donors and monitoring population-based seroprevalence and vaccine antibody response.
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Affiliation(s)
- Christopher D. Heaney
- Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Nora Pisanic
- Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Pranay R. Randad
- Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Kate Kruczynski
- Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Tyrone Howard
- Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Xianming Zhu
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kirsten Littlefield
- Department of Molecular Microbiology and Immunology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Eshan U. Patel
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ruchee Shrestha
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Oliver Laeyendecker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Baltimore MD
| | - Shmuel Shoham
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - David Sullivan
- Department of Molecular Microbiology and Immunology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kelly Gebo
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniel Hanley
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Andrew D. Redd
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Baltimore MD
| | - Thomas C. Quinn
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Baltimore MD
| | - Arturo Casadevall
- Department of Molecular Microbiology and Immunology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Jonathan M. Zenilman
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Andrew Pekosz
- Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
- Department of Molecular Microbiology and Immunology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Evan M. Bloch
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Aaron A. R. Tobian
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Galipeau Y, Greig M, Liu G, Driedger M, Langlois MA. Humoral Responses and Serological Assays in SARS-CoV-2 Infections. Front Immunol 2020; 11:610688. [PMID: 33391281 PMCID: PMC7775512 DOI: 10.3389/fimmu.2020.610688] [Citation(s) in RCA: 156] [Impact Index Per Article: 39.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Accepted: 11/23/2020] [Indexed: 12/14/2022] Open
Abstract
In December 2019, the novel betacoronavirus Severe Acute Respiratory Disease Coronavirus 2 (SARS-CoV-2) was first detected in Wuhan, China. SARS-CoV-2 has since become a pandemic virus resulting in hundreds of thousands of deaths and deep socioeconomic implications worldwide. In recent months, efforts have been directed towards detecting, tracking, and better understanding human humoral responses to SARS-CoV-2 infection. It has become critical to develop robust and reliable serological assays to characterize the abundance, neutralization efficiency, and duration of antibodies in virus-exposed individuals. Here we review the latest knowledge on humoral immune responses to SARS-CoV-2 infection, along with the benefits and limitations of currently available commercial and laboratory-based serological assays. We also highlight important serological considerations, such as antibody expression levels, stability and neutralization dynamics, as well as cross-reactivity and possible immunological back-boosting by seasonal coronaviruses. The ability to accurately detect, measure and characterize the various antibodies specific to SARS-CoV-2 is necessary for vaccine development, manage risk and exposure for healthcare and at-risk workers, and for monitoring reinfections with genetic variants and new strains of the virus. Having a thorough understanding of the benefits and cautions of standardized serological testing at a community level remains critically important in the design and implementation of future vaccination campaigns, epidemiological models of immunity, and public health measures that rely heavily on up-to-date knowledge of transmission dynamics.
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Affiliation(s)
- Yannick Galipeau
- Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, ON, Canada
| | - Matthew Greig
- Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, ON, Canada
| | - George Liu
- Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, ON, Canada
| | | | - Marc-André Langlois
- Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, ON, Canada
- uOttawa Center for Infection, Immunity and Inflammation (CI3), Ottawa, ON, Canada
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Woldemeskel BA, Kwaa AK, Garliss CC, Laeyendecker O, Ray SC, Blankson JN. Healthy donor T cell responses to common cold coronaviruses and SARS-CoV-2. J Clin Invest 2020; 130:6631-6638. [PMID: 32966269 PMCID: PMC7685719 DOI: 10.1172/jci143120] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Accepted: 09/09/2020] [Indexed: 12/13/2022] Open
Abstract
BACKGROUNDT cell responses to the common cold coronaviruses have not been well characterized. Preexisting T cell immunity to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been reported, and a recent study suggested that this immunity was due to cross-recognition of the novel coronavirus by T cells specific for the common cold coronaviruses.METHODSWe used the enzyme-linked immunospot (ELISPOT) assay to characterize the T cell responses against peptide pools derived from the spike protein of 3 common cold coronaviruses (HCoV-229E, HCoV-NL63, and HCoV-OC43) and SARS-CoV-2 in 21 healthy donors (HDs) who were seronegative for SARS-CoV-2 and had no known exposure to the virus. An in vitro expansion culture assay was also used to analyze memory T cell responses.RESULTSWe found responses to the spike protein of the 3 common cold coronaviruses in many of the donors. We then focused on HCoV-NL63 and detected broad T cell responses to the spike protein and identified 22 targeted peptides. Interestingly, only 1 study participant had a significant response to SARS-CoV-2 spike or nucleocapsid protein in the ELISPOT assay. In vitro expansion studies suggested that T cells specific for the HCoV-NL63 spike protein in this individual could also recognize SARS-CoV-2 spike protein peptide pools.CONCLUSIONHDs have circulating T cells specific for the spike proteins of HCoV-NL63, HCoV-229E, and HCoV-OC43. T cell responses to SARS-CoV-2 spike and nucleocapsid proteins were present in only 1 participant and were potentially the result of cross-recognition by T cells specific for the common cold coronaviruses. Further studies are needed to determine whether this cross-recognition influences coronavirus disease 2019 (COVID-19) outcomes.
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Affiliation(s)
- Bezawit A. Woldemeskel
- Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Abena K. Kwaa
- Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Caroline C. Garliss
- Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Oliver Laeyendecker
- Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), NIH, Baltimore, Maryland, USA
| | - Stuart C. Ray
- Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Joel N. Blankson
- Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
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