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      Test concordance and diagnostic accuracy of three serological assays for detection of anti-SARS-CoV-2 antibody: result from a population-based sero-epidemiological study in Delhi

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          Abstract

          Background

          Several methodological tests are available to detect SARS-CoV-2 antibody. Tests are mostly used in the aid of diagnosis or for serological assessment. No tests are fully confirmatory and have variable level of diagnostic ability. We aimed at assessing agreement with three serological tests: quantitative anti receptor binding domain ELISA (Q-RBD), qualitative ELISA (WANTAI SARS-CoV-2 Ab) and qualitative chemiluminescence assay (CLIA).

          Methods

          This study was a part of a large population based sero-epidemiological cohort study. Participants aged 1 year or older were included from 25 randomly selected clusters each in Delhi urban (urban resettlement colony of South Delhi district) and Delhi rural (villages in Faridabad district, Haryana). Three type of tests were applied to all the baseline blood samples. Result of the three tests were evaluated by estimating the total agreement and kappa value.

          Results

          Total 3491 blood samples collected from March to September, 2021, out of which 1700 (48.7%) from urban and 1791 (51.3%) from rural. Overall 44.1% of participants were male. The proportion of sero-positivity were 78.1%, 75.2% and 31.8% by Wantai, QRBD and CLIA tests respectively. The total agreement between Wantai and QRBD was 94.5%, 53.1% between Wantai and CLIA, and 56.8% between QRBD and CLIA. The kappa value between these three tests were 0.84 (95% CI 0.80–0.87), 0.22 (95% CI 0.19–0.24) and 0.26 (95% CI 0.23–0.28).

          Conclusions

          There was strong concordance between Wantai and QRBD test. Agreement between CLIA with other two tests was low. Wantai and QRBD tests measuring the antibody to same S protein can be used with high agreement based on the relevant scenario.

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          Most cited references10

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          Structural and functional properties of SARS-CoV-2 spike protein: potential antivirus drug development for COVID-19

          Coronavirus disease 2019 is a newly emerging infectious disease currently spreading across the world. It is caused by a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The spike (S) protein of SARS-CoV-2, which plays a key role in the receptor recognition and cell membrane fusion process, is composed of two subunits, S1 and S2. The S1 subunit contains a receptor-binding domain that recognizes and binds to the host receptor angiotensin-converting enzyme 2, while the S2 subunit mediates viral cell membrane fusion by forming a six-helical bundle via the two-heptad repeat domain. In this review, we highlight recent research advance in the structure, function and development of antivirus drugs targeting the S protein.
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            Evaluation of Nucleocapsid and Spike Protein-Based Enzyme-Linked Immunosorbent Assays for Detecting Antibodies against SARS-CoV-2

            At present, PCR-based nucleic acid detection cannot meet the demands for coronavirus infectious disease (COVID-19) diagnosis. Two hundred fourteen confirmed COVID-19 patients who were hospitalized in the General Hospital of Central Theater Command of the People’s Liberation Army between 18 January and 26 February 2020 were recruited. Two enzyme-linked immunosorbent assay (ELISA) kits based on recombinant severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid protein (rN) and spike protein (rS) were used for detecting IgM and IgG antibodies, and their diagnostic feasibility was evaluated.
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              Serum IgA, IgM, and IgG responses in COVID-19

              Currently, detecting SARS-CoV-2 RNAs is a standard approach for COVID-19 diagnosis. However, there is an urgent need for reliable and rapid serological diagnostic methods to screen SARS-CoV-2-infected people including those who do not have overt symptoms. Most emerging studies described serological tests based on detection of SARS-CoV-2-specific IgM and IgG. 1–4 Although detection of SARS-CoV-2-specific IgA in serum has been reported in few papers, 5,6 analyses of IgA levels in a larger number of COVID-19 patients are still lacking. This study enrolled a total of 87 confirmed COVID-19 patients (Supplementary Table 1) who were admitted to the First Affiliated Hospital of USTC Hospital or the First Affiliated Hospital of Anhui Medical University between January 26, and Mar 5, 2020. Their blood samples were collected during routine clinical testing. All enrolled cases were confirmed with SARS-CoV-2 infection by use of a standard RT-qPCR assay on throat swab samples from the respiratory tract. For all of the enrolled patients, the date of illness onset, clinical classifications of severity, RNA testing results during the hospitalization period, and the personal demographic information were obtained from the clinical records. Highly purified receptor-binding domain (RBD) of the SARS-CoV-2 spike protein (Supplementary Fig. 1) was expressed in human 293F cells and used to make a set of chemical luminescence kits for detecting the presence of RBD-specific IgA, IgM, and IgG, respectively. To evaluate the diagnostic power of the these kits, 216 sera from 87 SARS-CoV-2-infected patients and a total of 483 control sera including 330 healthy sera, 138 “interfering” sera of other-type patients and 15 sera from once-suspected pneumonia cases were tested. The detected signals relative light units (RLU), for each of isotype of the RBD-specific antibodies, were plotted (Fig. 1a–c). The RBD-specific IgA, IgM, and IgG kits showed diagnostic sensitivities of 98.6%, 96.8%, and 96.8%, and specificities of 98.1%, 92.3%, and 99.8%, respectively (Supplementary Fig. 2a–c). The sensitivities, specificities, and overall agreements of the RBD-specific IgA, IgM, or IgG kit and their combinations are also summarized in Supplementary Table 2. When combining the RBD IgA and IgG kits, the sensitivity, specificity, and overall agreement elevated to 99.1%, 100%, and 99.7%, respectively. This is better than those when IgM and IgG kits are combined using our data or the previous data shown by others. 1–4 Fig. 1 Analysis of SARS-CoV-2 RBD-specific IgA, IgM, and IgG antibodies in 87 COVID-19 patients. Testing results of RBD-specific IgA (a), IgM (b), and IgG (c) kits using 330 healthy sera, 138 sera from other-type of patients who may interfere with the test, 15 sera of once-suspected pneumonia patients, and 216 sera of 87 qPCR-confirmed COVID-19 patients. RLU relative light units. Black bar indicates median values. The dotted line indicates the cut-off value for detecting of each isotypes of antibodies. d Sensitivity of RBD-specific IgA, IgM, and IgG detection in serum samples obtained at different periods after illness onset. The kinetics of anti-RBD IgA, IgM, and IgG levels in sera of COVID-19 patients at different time windows was analyzed (e). The median values of RLU were plotted for each isotype of three antibodies. Bars indicate median with interquartile ranges. f–h Serum antibody levels in healthy and three distinct severity groups of COVID-19 patients were analyzed. Healthy: 330 sera; Mild: 7 sera; Moderate: 44 sera; and Severe: 21 sera. The critically ill patients were included into the severe group. Only the data of serum antibody levels at 16–25 days after illness onset of COVID-19 patients were used In order to investigate the seroconversion during COVID-19 pathogenesis, all the data from 216 sera samples were divided into six groups according to the time windows of collection after illness onset (Fig. 1d). At 4–10 days after symptom onset, the IgA kit exhibited the highest positive diagnostic rate as 88.2% (15/17), while IgM and IgG kit showed detection rates of 76.4% (13/17) and 64.7% (11/17), respectively. The 2 sera diagnosed as negative in the 4–10 days group by IgA kit were collected at the 4th day after illness onset, all other sera includes 2 at the 6th day, 3 at the 7th day, 1 at the 8th day, 6 at the 9th day, and 3 at 10th day after illness onset were tested as positive. In the group of 11–41 days after symptom onset, both RBD IgA and IgG kit showed the same positive diagnostic rate of 99.5% (198/199). In contrast, IgM kit somehow showed a relatively lower positive diagnostic rate as 98.5% (196/199). These results suggest that including IgA in a test provides better diagnostic outcome in early stages. Overall, the medium seroconversion time for IgA, IgM, and IgG are 4–6, 4–6, and 5–10 days post symptom onset, respectively, if tested with the RBD-kits described in this study. While it generally follows a typical seroconversion and immunoglobulin class switching time course, our kits provides an early diagnosis solution due to high sensitivities. To better understand the trends of antibody levels in all of the 87 COVID-19 patients (some of them contributed multiple samples), we plotted the median RLU reading according the time windows when sera were collected (Fig. 1e). IgA detection shows the highest sensitivity during about 4–25 days after illness onset. The median RLU of RBD-specific IgA reached the peak during 16–20 days after illness onset, and then began to decline but remained at relatively high reading until 31–41 days. The median RLU of RBD-specific IgG was the lowest in early disease stages but raised at 15 days post illness onset, the IgG reached its peak during 21–25 days after illness onset, and stayed at a relatively high reading until 31–41 days, suggesting that IgG is powerful for diagnostics at later stages. Although IgM reached its peak at early stages, the RLU reading was lower than that of IgA or IgG. We further divided the 87 patients into three severity groups based on established clinical classifications. Consistent with a previous report, 7 we found that COVID-19 severity is correlated positively with age in our cohort (Supplementary Fig. 3). Patients with severe symptoms were significantly older (median age of 62.5) than those patients with moderate (median age of 46) and mild symptoms (median age of 30), as expected. We used the data of antibody levels at the period of 16–25 days after illness onset, when all of the three isotypes reached or were near their peaks (Fig. 1e). If there were more than one data points, the average value was taken. Serum IgM and IgG levels in moderate and severe COVID-19 patients were significantly higher than mild cases, while no significant difference was observed between severe and moderate patients (Fig. 1g, h). However, we found that IgA levels in severe cases were significantly higher than those mild or moderate cases (Fig. 1f). The molecular mechanism of this observation warrants future studies. There are some limitations in this study at the current form. We used 216 serum samples from 87 confirmed COVID-19 patients in this study, and serum samples were not available every day for each patient. The earliest serum was collected at the 4th day, and last one was at the 41th day after self-reported illness onset. There are only 17 cases of serum samples collected within the first 10 days after illness onset; which consequently influenced the accuracy. Similarly, there were only 23 cases of serum samples taken after 30 days post illness onset, hampering an analysis of long-term antibody levels in recovered patients. We are currently following up some of the 87 convalescent COVID-19 patients who are willing to participate in further study. Nevertheless, this study provide valuable information regarding COVID-19 serological testing and seroconversion responses, especially for IgA antibodies. Supplementary information Supplemental materials
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                Author and article information

                Contributors
                doctormisra@gmail.com
                Journal
                BMC Infect Dis
                BMC Infect Dis
                BMC Infectious Diseases
                BioMed Central (London )
                1471-2334
                7 December 2022
                7 December 2022
                2022
                : 22
                : 915
                Affiliations
                [1 ]GRID grid.413618.9, ISNI 0000 0004 1767 6103, Centre for Community Medicine, , All India Institute of Medical Sciences, ; New Delhi, 110029 India
                [2 ]GRID grid.413618.9, ISNI 0000 0004 1767 6103, All India Institute of Medical Sciences, ; New Delhi, 110029 India
                [3 ]GRID grid.417256.3, WHO Country Office, World Health Organization, ; New Delhi, India
                [4 ]GRID grid.413618.9, ISNI 0000 0004 1767 6103, Department of Reproductive Biology, , All India Institute of Medical Sciences, ; New Delhi, 110029 India
                [5 ]GRID grid.464764.3, ISNI 0000 0004 1763 2258, Translational Health Science and Technology Institute, ; Faridabad, 121001 India
                [6 ]GRID grid.413618.9, ISNI 0000 0004 1767 6103, Department of Laboratory Medicine, , All India Institute of Medical Sciences, ; New Delhi, 110029 India
                [7 ]GRID grid.417256.3, WHO, ; New Delhi, India
                Author information
                https://orcid.org/0000-0002-2019-1524
                Article
                7805
                10.1186/s12879-022-07805-5
                9730588
                36476336
                2035a2fa-531b-46e4-9f5a-9f2c07fed05d
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 2 June 2022
                : 26 October 2022
                Funding
                Funded by: WHO Country Office, New Delhi 110016, India
                Award ID: Ref No: 2020/1085497, Purchase Order: 202630166
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Infectious disease & Microbiology
                concordance,serology,serum,antibody,sars-cov-2
                Infectious disease & Microbiology
                concordance, serology, serum, antibody, sars-cov-2

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