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| ORIGINAL ARTICLE |
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| Year : 2023 | Volume
: 15
| Issue : 1 | Page : 70-75 |
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Analysis of severe acute respiratory syndrome coronavirus 2 antibodies response in COVID-19 patients and health-care workers
Yaminy Pradeep Ingale1, Shirish Sahebrao Chandanwale1, Payal Patel1, Rakesh Kumar Rashmi1, Narendra Chindhu Kale2, Tushar Jalindar Kambale1, Vikram Bhausaheb Vikhe3
1 Department of Pathology, Dr. D Y Patil Medical College, Hospital and Research Centre, Dr. D Y Patil Vidyapeeth, Pune, Maharashtra, India
2 Department of Medicine, PCMC's PGI YCMH, Pune, Maharashtra, India
3 Department of Medicine, Dr. D Y Patil Medical College, Hospital and Dr. D Y Patil Vidyapeeth, Pune, Maharashtra, India
| Date of Submission | 16-Jan-2023 |
| Date of Acceptance | 28-Feb-2023 |
| Date of Web Publication | 31-Mar-2023 |
Correspondence Address:
Narendra Chindhu Kale
I-302, Dwarka Suncrest Phase 3, Near Kapse Lowns, Rahatani, Pune - 411 017, Maharashtra
India
 Source of Support: None, Conflict of Interest: None
DOI: 10.4103/ajprhc.ajprhc_8_23
Background: COVID-19 epidemic causes destructive consequences on human beings and on the global economy. Aim: The purpose of this study was to evaluate the severe acute respiratory syndrome coronavirus 2 antibodies response in COVID-19 patients and health-care providers to them in different categories and with respect to age, sex, and symptoms. Materials and Methods: Analysis of immunoglobulin (Ig) G and total COVID antibodies was done by chemiluminescent microparticle immunoassay (CMIA) and IgM antibodies by rapid card test method in 300 cases. Results: Out of 300 cases, asymptomatic were 29%, mild 26.66%, moderate 17.66%, and severe were 28.33%; percentage of males were higher than females in all. The most common age group involved was 30–40 years (20%). The most common symptom was fever (51.33%), followed by cough (38.66%), and the most common comorbidity was hypertension (16.33%). We observed that severe category had a higher percentage of symptoms as well as comorbidities. Out of 300 cases, 56.66% were IgG positive, and 89.6% were total COVID antibody positive. In rapid IgM antibodies, out of 50 cases, 13 were positive. We observed that IgM was positive mainly in severe cases compared to mild cases, while IgG level was lower in severe cases than those of mild cases. In our study, majority of cases (97 cases) are IgG positive approximately in 8–14 days after onset of symptoms. Conclusion: Quantitative analysis of antibodies is a simple, quick, and cheap method and could play major role in diagnosis and prognosis of COVID-19, and also used to pick up silent carriers (asymptomatic patients) who missed in false-negative reverse transcription polymerase chain reaction in such epidemic.
Keywords: Comorbidities, COVID-19, fever, quantitative
How to cite this article:
Ingale YP, Chandanwale SS, Patel P, Rashmi RK, Kale NC, Kambale TJ, Vikhe VB. Analysis of severe acute respiratory syndrome coronavirus 2 antibodies response in COVID-19 patients and health-care workers. Asian J Pharm Res Health Care 2023;15:70-5 |
How to cite this URL:
Ingale YP, Chandanwale SS, Patel P, Rashmi RK, Kale NC, Kambale TJ, Vikhe VB. Analysis of severe acute respiratory syndrome coronavirus 2 antibodies response in COVID-19 patients and health-care workers. Asian J Pharm Res Health Care [serial online] 2023 [cited 2023 Jun 8];15:70-5. Available from: http://www.ajprhc.com/text.asp?2023/15/1/70/373375 |
| Introduction | |  |
The novel coronavirus was identified as a causative organism of coronavirus disease in Wuhan city, Hubei region, China, in December 2019, and named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).[1],[2]
The World Health Organization (WHO) simplified and labeled the disease as COVID-19. Since then, it has dramatically expanded throughout the world, and the WHO declared it as a global sanitary emergency in January 2020.[3],[4]
An etiological agent was identified from throat samples and was subsequently named as SARS-CoV-2.
Human-to-human virus transmission occurs through the respiratory route; aerosols, droplets, fomites, and close contact. Despite intensive containment efforts, there is rapid international spread, and SARS-COV-2 virus has recently emerged as a cause of human pandemic. It is evaluated that approximately 80% of all infections remain unregistered as all these patients are either asymptomatic or having only mild symptoms.[5] In asymptomatic and patients with mild symptoms, the viral loads are similar.
Currently, reverse transcription polymerase chain reaction (RT-PCR) is the main test to diagnose SARS-CoV-2 infection. The sample required for that is from the nasal or pharyngeal swabs and bronchoalveolar lavage. Along with RT-PCR, high-resolution computed tomography (HRCT) scan and laboratory parameters are essential to conclude the diagnosis as for therapeutic purpose.[6]
RT-PCR from the upper respiratory swabs can be falsely negative due to quality, timing of swabs, and low viral load in the nasal and pharyngeal swabs compared to sputum. The chances of positive RT-PCR test decrease with the time since the onset of symptoms.[7]
It may be considered a potent diagnostic tool to complement RT-PCR-based diagnosis.
Infection status, disease progression in COVID-19 patients, and antibody status in health-care providers can be used to make educated decisions about quarantine, social distancing, need of personal protective equipment, and desire to do duties with COVID-19 patients in elective setting.
Currently, antibody response against SARS-CoV-2 is under investigation and is not yet fully defined. Serological surveys for SARS-CoV2 are being conducted across the globe to understand the antibody response.
Protein S is the coronavirus proteins which carry receptor-binding domain for the legend on host cell membrane. It also has epitopes, which are recognized by T- and B-lymphocytes, which motivate the production of neutralizing antibodies.[8] Multiple evidences suggest that humoral response, mainly antibodies against S proteins, block virus attachment to angiotensin-converting enzyme-2 receptor bearing cells like type 2 pneumocytes, in the lungs and mucous membranes of the nose and mouth.
The researcher all over the world used antibody tests to calculate the extent of SARS-CoV-2 virus infection in the population, which is very important because in many areas, standard protocols of testing are not followed; because of that, mild symptomatic patients or asymptomatic patients may be missed.
SARS CoV-2, SARS, and Middle East Respiratory Syndrome (MERS) all share the same genetic and epidemiological features.[9],[10]
Hence, the method of antibody generation against SARS-CoV-2 might be the same.
The presence of immunoglobulin (Ig) M and IgG antibodies could provide the information about the time course of virus infection.[11],[12] Normally, IgM appears after 3–6 days, following a SARS infection, and IgG appears approximately after 8 days.
The aim of our study was to evaluate age, sex, and symptoms and IgG, IgM antibodies, and total COVID antibodies response in COVID-19 patients and health-care providers to them in different categories.
Here, we analyzed the detection of IgG antibodies by chemiluminescent immunoassay (CLIA) and IgM antibodies by rapid card test in COVID-19 patients and health-care providers to them.
| Materials and Methods | | |
This was a cross-sectional prospective study which was carried out at a tertiary care hospital, Pune. A total of 300 individuals were included, having confirmed COVID-19-positive report and health-care providers to them underwent serological testing for the presence or absence of IgG, total COVID antibodies, and IgM antibodies in our tertiary care hospital. This study was approved by the Ethical Committee of our college on September 4, 2020; ref no is DYPV/EC/521/2020.
Inclusion criteria
The study included patients positive for SARS-CoV-2 by RT-PCR, irrespective of age and sex, and all health-care providers to them, irrespective of age and sex.
Exclusion criteria
The study excluded COVID-19 patients diagnosed by RT-PCR, in whom antibody testing was done.
We collected all data of patients such as age, sex, symptoms, date of admission, onset of symptoms, status of vaccination, and comorbidities.
We categorized all patients into asymptomatic, mild, moderate, and severe cases. The mild cases are with fever, body ache, loss of smell and taste, and headache. The moderate cases are with mild symptoms with breathlessness, low SpO2, and bilateral ground-glass opacities on HRCT, but can monitor on oxygen in ward. The severe cases are which required intensive care unit and ventilator support. All close contacts and health-care workers were included in asymptomatic cases.
The 2cc blood will be collected in a sterile vacutainer with a disposable syringe using disposable personal protective equipment. The IgM antibody in serum was done on a rapid kit of SD Biosensor Company. Sensitivity of this kit is 99.03%, and specificity is 98.65%.
IgG antibodies were done on SARS-CoV-2 IgG by chemiluminescent microparticle immunoassay (CMIA) on ARCHITECT i system. SARS-CoV-2 total antibody was done by sandwich chemiluminescent immunoassay based on LOCI Technology by Siemens Company.
IgG antibodies and total COVID antibodies were done in all 300 cases, while IgM rapid antibody was done in only 50 cases.
Testing will be done according to the instructions provided with antibody test kit. Results will be read as per the instructions given with the test kit. Test results will be correlated with the symptoms.
The data entry was done in Microsoft Excel spreadsheet. Categorical variable was expressed in terms of frequency and percentages, and continuous variables in terms of mean and standard deviation.
| Results | | |
The present study included a total of 300 hospitalized patients with confirmed COVID-19 report and health-care providers who work with COVID patients.
Out of them, 190 (63.33%) patients were male, 110 (36.66%) were female. The most common age group involved was 31–40 years (60 cases, 20%), followed by 21–30 years (58 cases, 19.33%) [Table 1].
We categorized them into four categories – asymptomatic (90 cases, 30%), mild (71 cases, 23.7%), moderate (54 cases, 18%), and severe (85 cases, 28.33 cases). The percentage of males was higher in that of the females in all categories [Table 1].
In our study, most of the patients were presented with fever (154 cases, 51.33%), cough (116 cases, 38.66%), breathlessness (84 cases, 28%), and weakness (45 cases, 15%). Patients presented with breathlessness were mainly of moderate and severe categories [Table 2].
Out of 300 cases, 94 patients were having comorbidities. The most common comorbidities were hypertension (49 cases, 16.33%), diabetes (37 cases, 12.33%), chronic kidney disease (6 cases, 2%), and ischemic heart disease (2 cases, 0.66%). From our findings, we observed that the severe category had higher percentages of symptoms as well as comorbidities [Table 3].
We also analyzed the quantitative IgG antibodies and SARS-CoV-2 total antibody in all four categories as well as health-care workers. We did rapid IgM antibodies in 50 cases. We found that out of 300 patients, 170 (56.66%) cases were IgG positive, and 130 (43.33%) were IgG negative, while 269 (89.6%) cases were positive, and 31 cases were negative (10.4%) for SARS-CoV-2 total antibody. SARS-CoV-2 total antibody-positive results may be due to the past or present infection with non-SARS-CoV-2 coronavirus strains such as coronavirus HKV1, NL63, OC43, or 229E, and negative results do not preclude acute SARS-CoV-2 infection.
SARS-CoV-2 IgG antibody was positive in 27 (72.9%) cases in asymptomatic category, 46 (64.8%) cases in mild category, 37 (68.5%) cases in moderate category, 56 (65.9%) cases in severe category, and 4 (7.5%) cases positive in health-care workers [Table 4]. High titer of IgG was found in mild and asymptomatic cases compared to severe cases.
The results of SARS-CoV-2 total antibody show increased titer in severe category compared to other categories. In health-care workers also, the titer was extremely high due to vaccination, as the SARS-CoV-2 total antibodies are increased after vaccination [Table 4].
In rapid IgM antibodies, out of 50 cases, 13 were positive, and 37 were negative. We observed that IgM was positive mainly in severe cases compared to mild cases, while IgG level was lower in severe cases than those of mild cases.
We analyzed IgG antibody levels in relation to days of onset of symptoms. We found that IgG positive titer was detected roughly after 8–14 days after disease onset. In our study, majority of cases (97 cases) were IgG positive after 8–14 days after onset of symptoms [Table 5]. | Table 5: Distribution of IgG-positive cases in relation to days of onset of symptoms
Click here to view |
| Discussion | | |
The novel coronavirus (SARS-CoV-2) is a new virus accountable for COVID-19 global pandemic all over the world.
Here, we studied the antibody responses in different categories of COVID-19 patients of different severity, which give the information about the development of immune responses in that different category. Furthermore, we identified asymptomatic or mildly symptomatic health-care providers who may have acquired SARS-CoV-2 infection while treating the COVID-19 patients. Such asymptomatic cases have low viral load, but still disseminating virus, and may be responsible for causing silent epidemics.
The detection of antibodies allowed for serological diagnosis in COVID-19 patients and the pattern of the responses in consistent with acute viral infection.[12] In coronavirus epidemic, the identification of IgM and IgG antibodies authorized for serological diagnosis.[13]
There are several detection methods available in the market. SARS-CoV-2 antibody testing is a rapid and sensitive method of diagnosis of COVID-19.[14] In the present study, we used CMIA method for IgG detection, sandwich chemiluminescent immunoassay based on LOCI Technology for SARS-CoV-2 total antibody, and for IgM, we used a rapid kit of SD Biosensor Company.
In our study, males (63.33%) were commonly affected than females in all categories, which is comparable with Hou et al.'s[15] study, in which 50.6% of males were affected. While in Solbach et al.'s[16] and Jia et al.'s[17] studies, females (56.8% and 57.8%, respectively) were more affected than males.
The most common age group suffered was 31–40 years (20%), which is comparable with Jia et al.'s study.[17] In Solbach et al.'s[16] study, mainly 50–59 years (28.8%) group was suffered commonly.
The most common presentation in our study was fever (51.33%), followed by cough (38.6%). Hou et al[15] also get the same finding in his study with fever (77.8%), cough (45%), Jia et al[17] get fever (61.4%), cough (47.37%), and Al-Mughales et al[18] also get fever (73.9%), cough (60.9%) which are comparable with our study.
The most common comorbidity was hypertension (16.3%), followed by diabetes (12.3%), which is similar with Hou et al.'s[15] study with hypertension (41.4%) and diabetes (18.6%).
The level of IgG and total COVID antibodies were analyzed prospectively in COVID-19 patients with different categories and health-care workers, while IgM was done in 50 cases. In our study, IgG-positive cases were 56.6%, while 89.6% of cases were total COVID antibody positive. Category wise, 72.9% asymptomatic, 64.8% mild category, 68.5% moderate category, and 55.9% severe category were IgG positive, while 7.5% of health-care workers were IgG positive. In Hou et al.'s[15] study, IgG-positive percentage was 90.6%, 92.7%, and 88% in mild, moderate, and critical category, respectively.
We observed that the levels of IgG were mainly increased in mild and asymptomatic category compared to moderate and severe one, which is comparable with Hou et al.'s[15] study.
After SARS-CoV infection, the antibodies production against the virus is consistent in most of the patients. Within 3 days after infection, IgM antibodies can be detected, which is the first line of defense of humoral immunity. IgG antibody can be detected after that, and it gives a longtime protection.[19]
In our study, majority of cases (97 cases) are IgG positive roughly in 8–14 days after onset of symptoms, which is comparable with Long et al.'s[20] study, who got 115 cases positive roughly in 8–14 days; whereas in Solbach et al.'s[16] study, in majority of cases (30 cases), IgG detection is commonly seen in 20–28 days after onset of symptoms.
SARS-CoV-2 is beta coronavirus. It shows many similar characteristics with SARS virus and MERS. There are many other studies done on these other coronaviruses, and knowledge obtained from these all studies can give awareness in antibody responses which occur after SARS-CoV infection.[9],[21]
In our study, IgM antibody was generated in 1 week after onset of symptoms and reached its peak level in 2–3 weeks, after that the level is decreased. IgG level increased immediately, but slowly with respect to IgM levels, and remains at high level for 2–3 months, which is comparable with Hou et al.'s[15] study.
Therefore, the antibody levels could give information with regard to serological convention over disease course, as IgM antibody detection specifies the recent exposure of SARS-CoV-2, while IgG antibody detection specifies earlier virus exposure.
IgG and/or IgM antibodies positivity rate was not markedly different in different categories such as mild, moderate, and severe. The quantitative investigations of both antibodies of SARS-CoV-2 show IgM were higher and IgG were lower levels in severe disease category patients, when compared with mild and moderate categories, which might be due to high viral load or severity of the disease and or low immunity in them. In mild category, IgG level was sustained at high level till patients were in recovery stage of infection.
| Conclusion | | |
In our study, we found that antibodies against SARS-CoV-2 vary remarkably among COVID-19 patients with different categories and outcomes. Quantitative analysis of antibodies is a simple, quick, and cheap method and could play major role in diagnosis and prognosis of COVID-19, and also used to pick up silent carriers (asymptomatic patients) who missed in false-negative RT-PCR in such epidemic.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]
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