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| Humoral response to SARS-COV-2 in COVID-19-recovered patients and correlation with various factors |
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Tulika Chandra1, D Himanshu2, Pradeep Kumar Maurya1, Mallika Agarwal3, Saurabh Pandey4
1 Department of Transfusion Medicine, King George's M.U, Lucknow, Uttar Pradesh, India
2 Department of Medicine, King George's M.U, Lucknow, Uttar Pradesh, India
3 Era Medical College, Lucknow, Uttar Pradesh, India
4 Department of Internal Medicine, King George's M.U, Lucknow, Uttar Pradesh, India
Click here for correspondence address and email
| Date of Submission | 20-May-2021 |
| Date of Decision | 09-Jun-2021 |
| Date of Acceptance | 12-Jun-2021 |
| Date of Web Publication | 04-Jun-2022 |
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 Abstract | | |
CONTEXT: On exposure to SARS-CoV-2 in participants anti-SARS-CoV-2 antibodies are expected to appear as a humoral response. Furthermore, various factors affect their expression.
AIMS: The aim of this study is to investigate the humoral response of COVID-19-recovered participants and correlation with duration of disease, duration of COVID positive to date of test, occupation, blood group, age group, weight, gender, and symptoms of anti-SARS-CoV-2 antibodies.
SETTINGS AND DESIGN: This prospective observational study was conducted at the Department of Transfusion Medicine, at a tertiary care center in North India.
METHODS: Seventy-two participants were tested for anti-SARS-CoV-2 antibodies on chemiluminescent microparticle immunoassay postgetting COVID negative.
STATISTICAL ANALYSIS: The data were analyzed using Kruskal–Wallis and Mann–Whitney test. To correlate variables such as duration of disease, duration of COVID positive to date of test of immunoglobulin G (IgG), occupation, blood group, weight, gender, symptoms, and age group Chi-square test were used.
RESULTS: The correlation of anti-SARS-CoV-2 antibodies with a duration of disease (P > 0.05), duration of COVID positive to date of test of IgG (P > 0.05), occupation (P > 0.05), blood group (P > 0.05), weight (P > 0.05), gender (P > 0.05), and symptoms (P > 0.05) is insignificant and whereas significant correlation with age group (P < 0.05) seen.
CONCLUSIONS: A significant correlation was seen in anti-SARS-COV-2 antibodies and age group. Higher antibody levels were seen in participants of the upper extreme age group (50–60 years).
Keywords: Anti-SARS-CoV-2, COVID-19, humoral response
How to cite this URL:
Chandra T, Himanshu D, Maurya PK, Agarwal M, Pandey S. Humoral response to SARS-COV-2 in COVID-19-recovered patients and correlation with various factors. Asian J Transfus Sci [Epub ahead of print] [cited 2023 Mar 24]. Available from: https://www.ajts.org/preprintarticle.asp?id=346000 |
| Introduction | |  |
In 2019, SARS-CoV-2 was first reported and later declared a pandemic. Quarantine, screening of cases that had symptoms lead to reduced transmission, and early diagnosis and severity will help in epidemic impact.[1],[2],[3] As infection is novel to humans, so screening of the population for antibodies will help in the extent of infection.[4] COVID-19-recovered population expresses anti-SARS-CoV-2 antibodies (immunoglobulin G [IgG] and neutralizing antibodies) usually after 2 weeks of recovery.[5],[6] However, titer of IgG and neutralizing antibodies start to wane after 2–3 months. Prior infection with the other SARS-CoV also showed no long-lasting immune protection.[7],[8]
| Methods | | |
This prospective observational study was conducted at the Department of Transfusion Medicine, at a tertiary care center in North India during the COVID pandemic, and the study was conducted over a 6-month duration from April 2020 to September 2020.
Patients who had recovered from COVID were recruited in the study as per the guidelines laid down by the Drug and Cosmetic Act and the Indian Council of Medical Research and were screened for the SARS-CoV-2 antibodies. All participants were screened only after 14 days of being COVID negative or 28 days after being diagnosed COVID positive if COVID-negative report was not available. Some of the participants were screened for the antibodies more than once with a minimum interval of 2 weeks. All the individuals were between the age group of 18–60 years. Only nulliparous female participants were included in the study.
A total of 72 participants tested for COVID IgG on the 15th–29th day after being COVID negative were recruited in the study as a sample. Anti-SARS-COV-2 antibodies were detected using commercially available SARS-COV-2 chemiluminescent microparticle immunoassay, qualitative detection of IgG antibodies to SARS-COV-2 in human serum, and plasma on the ARCHITECT i System. The default result unit for the SARS-CoV-2 IgG assay cutoff was 1.4 index (S/C) so a result more than and equal to 1.4 was taken as positive for IgG antibodies.
The study was approved by the Institutional Ethics Committee before enrollment of the individuals. Participants were recruited after written informed consent.
Statistical analysis
Data were analyzed using the appropriate statistical procedures and SPSS software version-23. Continuous variables were expressed as mean, Kruskal–Wallis, and Mann‒Whitney tests were used for continuous variables and Chi-square tests were used for categorical variables for comparisons between groups. P ≤ 0.05 was considered statistically significant.
| Results | | |
Plasma donors tested for COVID IgG on the 15th–29th day after being COVID Negative were 72.
The highest COVID IgG levels (4.71) were seen when the duration from recovery was more than 28 days, whereas the lowest values were seen (4.30) between 8 and 13 days.
The highest COVID IgG levels (4.47) were seen after 1 month to 2 months after being diagnosed as COVID positive, whereas the lowest (4.16) levels were observed between 15 and 29 days [Table 1]. | Table 2: Association of OD status with the duration of coronavirus disease positive to date of test of IgG
Click here to view |
Nonhealth workers showed the highest levels of antibody (4.66) as compared to students who showed the lowest levels of IgG [Table 3].
Donors with blood group B-positive showed the highest antibody levels, whereas the A-negative blood group had the minimum IgG antibody levels[Table 4].
A significant correlation was seen between the age group and plasma IgG levels. It was highest in the age group of 50–60 years and minimum in the young age group of 18–29 years [Table 5].
The highest IgG levels were seen in donors with a weight of more than 120 kg, while the minimum was seen in donors weighing between 50 and 59 kg [Table 6].
Males had higher antibody levels as compared to females [Table 7].
There was no significant correlation between symptoms during COVID and antibody levels [Table 8].  | Table 8: Association of antibody levels with symptoms of coronavirus disease
Click here to view |
| Discussion | | |
In our study, highest COVID IgG levels (4.71) were seen, when the duration of the disease was more than 28 days, whereas the lowest values were seen (4.30), when the disease lasted between 8 and 13 days. In addition, it was observed that COVID IgG levels were highest when 1 month to 2 months had elapsed after being diagnosed as COVID positive, whereas the lowest IgG levels were observed between 15 and 29 days of COVID diagnosis. In all of the cases, the ideal time for testing for COVID IgG antibodies seemed to be 14 days after recovery. However, anti-N IgG was showing peaks in 7–14 days to test in abbot, but other tests were showing low antibody detection rate and antibody levels with a shorter duration of antibody testing. Naaber et al. concluded that different viral proteins can elicit immune response earlier and at high levels as compared to others.[9] In another study, peak was seen 10–15 days after onset of disease (median = 30; range: 14–78 days).[10]
Association between blood group antigen and viral infections has been noticed previously in a study by Cooling.[11] In our study, the highest mean was 9.15 of COVID IgG with blood group B+. In another study, it had been observed that blood group A is at higher risk of getting infection, whereas O blood group shows a protective effect. Furthermore, higher amounts of antibodies were formed by A blood group patients, but O was the least antibody producer.[10] In our study, B + blood group patients had the highest protective effects and A − were most susceptible. The difference may be due to demographic and epidemiological variables.
No significant correlation with the gender with COVID IgG was seen which correlated with other studies A significant correlation in patient's age group of 50–60 years with the highest level of COVID IgG antibodies was seen in our study which was unlike the study of Naaber et al. where no correlation was seen.[9] In another study, high humoral response was seen with patients who are acutely ill males of the older age group which correlated with our findings.
We also found that higher antibodies were seen with a higher weight of donors. Similar results were reported where patients with a higher weight of more than 90 kg or overweight/obese had a higher titer of antibody.[10]
We did not find a significant correlation between symptoms of COVID or duration of symptoms with antibody levels. In contrast to our study, Naaber et al. said that patients with the higher symptom score had a higher rate of getting positive and high levels of antibody with one specific brand of the antibody testing kit targeting a specific antigen. At the same time, results were insignificant with other antibody testing kits targeting another antigen. However, the conclusion was that symptomatic patients had a better immune response in comparison to the asymptomatic one against the viral protein.[9] In another study, despite no severe symptoms of the disease, patients had shown intensified and prolonged humoral-mediated immune response.
| Conclusions | | |
The result of this study has come out with the conclusion that there is a significant association between anti-SARS-COV-2 antibodies and age group. A higher amount of anti-SARS-CoV-2 antibodies were seen in plasma and serum of participants of the upper extreme age group (50–60 years).
Acknowledgment
We will like to acknowledge the technical and paramedical staff of the Department of Transfusion Medicine of KGMU for their hard work which made this study possible.
Financial support and sponsorship
This study was financially supported by KGMU Administration.
Conflicts of interest
There are no conflicts of interest.
| References | | |
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| 6. | Marklund E, Leach S, Axelsson H, Nyström K, Norder H, Bemark M, et al. Serum-IgG responses to SARS-CoV-2 after mild and severe COVID-19 infection and analysis of IgG non-responders. PLoS One 2020;15:e0241104. |
| 7. | Madewell ZJ, Yang Y, Ira M. Longini Jr., Halloran ME, Dean NE. NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. medRxiv 2020;1:1-13. |
| 8. | Liu W, Fontanet A, Zhang PH, Zhan L, Xin ZT, Baril L, et al. Two-year prospective study of the humoral immune response of patients with severe acute respiratory syndrome. J Infect Dis 2006;193:792-5. |
| 9. | Naaber P, Hunt K, Pesukova J, Haljasmägi L, Rumm P, Peterson P, et al. Evaluation of SARS-CoV-2 IgG antibody response in PCR positive patients: Comparison of nine tests in relation to clinical data. PLoS One 2020;15:e0237548. |
| 10. | Wendel S, Fontão-Wendel R, Fachini R, Candelaria G, Scuracchio P, Achkar R, Brito M, et al. A longitudinal study of convalescent plasma (CCP) donors and correlation of ABO group, initial neutralizing antibodies (nAb ) and body mass index (BMI) with nAb and anti-nucleocapsid (NP) SARS-CoV-2 antibody kinetics: Proposals for better quality of CCP collections. Transfusion. 2021 M-1460. doi: 10. 1111/trf. 16323. E 2021 F 19. P 33604884; PP. https://orcid.org/0000-0002-1941-7733; Vol. 0. 2020. 20.05.2021.. |
| 11. | Cooling L. Blood groups in infection and host susceptibility. Clin Microbiol Rev 2015;28:801-70. |
Correspondence Address:
Tulika Chandra,
Department of Transfusion Medicine, King George's M.U, Lucknow, Uttar Pradesh
India
 Source of Support: None, Conflict of Interest: None DOI: 10.4103/ajts.ajts_56_21
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8] |
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