SARS-CoV-2-IgG Response and the Role of ACE2 G8790A and ACE I/D Polymorphic Variants as Determinants of Covid-19 Severity-A Genetic Association Study in north Indian Population


 Background: Angiotensin-converting enzyme-II and Angiotensin-converting enzyme are an integral part of Renin-Angiotensin system and mediate SARS-CoV-2 infection and outcome. Here we studied the role of host antibody response to SARS-CoV-2, ACE2 G8790A single nucleotide polymorphism, and ACE insertion/deletion (ACE I/D) as key determinants of Covid-19 severity and outcome. Methods: We evaluated anti-SARS-CoV-2 IgG titers by chemiluminescence. ACE2 G8790A and ACE I/D were analyzed by polymerase chain reaction-restriction fragment length polymorphism method (PCR-RFLP) and PCR respectively. Results: The overall positivity rate for SARS-CoV-2-IgG was 83.72%, but a significantly lower positivity was observed in asymptomatic subjects (66.67%, p < 0.05). Anti-SARS-CoV-2 IgG levels were comparatively higher in subjects who required hospitalization (13.06 ± 14.42 vs 7.37 ± 10.79, p < 0.05). ACE2 G8790A ‘AA’ genotype was significantly higher in subjects who did not require hospitalization (OR=0.40, CI 0.14-0.71, P= 0.007). In addition, the frequency of ACE I/D ‘ID’ genotype was significantly lower in symptomatic as compared to asymptomatic subjects (OR=0.235, CI 0.09-0.56, P=0.001). Conclusion: In summary, the current study shows that serological response to SARS-CoV-2 is more pronounced in symptomatic and severe covid-19 cases. Both ACE2 G8790A ‘AA’ and ACE I/D ‘ID’ genotype were observed to show protective role as far as the severity of covid-19 infection was considered. The study provides preliminary evidence of a genetic link between the analyzed polymorphic variants and covid-19 severity suggesting a subtle way of covid-19 risk stratification and utilization of respective variants as predictive biomarkers.


Introduction
Severe acute respiratory syndrome (SARS) caused by Novel coronavirus (CoV) generally recognized as 'COVID-19' by the World Health Organization (WHO) broke out at the beginning of December 2019 in Wuhan City, Hubei Province, China [1]. This strain most often affects the respiratory system of humans besides the gastrointestinal system [2,3]. Most infected individuals experience mild to moderate symptoms usually after less than a week of infection, such as high body temperature in addition to respiratory symptoms such as cough, sore throat, nasal congestion, fatigue, and headache. Some people preferentially with underlying co-morbidities may develop severe symptoms like pneumonia or acute respiratory distress syndrome as observed on computed tomography [4][5][6]. Prominent signs of pneumonia include decreased oxygen saturation, blood gas deviations, changes visible through chest Xrays including ground glass abnormalities, patchy consolidation, and alveolar exudates indicating tissue deterioration [7]. Lymphopenia appears to be common and in ammatory markers like C-reactive protein (CRP), D-dimers, ferritin, lactate dehydrogenase (LDH), and IL-6 are most often elevated [8,9]. SARS is a highly contagious menace and is supposed to spread rapidly via droplet particles. The droplet particles containing SARS-CoV-2 may arise through sneezing or coughing which may infect healthy individuals in close contact with the patient [10][11][12][13]. Because of rapid outspread, the World Health Organization (WHO) declared it a Public Health Emergency of International concern on 30th January 2020, followed by declaring it as a Global Pandemic on 11th March 2020, nearly 3 months after its rst appearance.
According to the latest updates of WHO, this disease has affected 223 countries or territories and currently, the number of cases reported globally exceeds 180 million with almost 4 million worldwide deaths [14].
The pathological mechanisms involved in the interaction of SARS-CoV-2 are of key signi cance for infection and viral replication. The interaction of SARS-CoV-2 with the host cells is mediated by ACE 2 receptor present on epithelial cells of the respiratory tract, most of the organs of the gastrointestinal tract, lymph nodes, arterial and venous endothelial cells, and arterial smooth muscle cells [15]. This interaction has already been expounded in detail suggesting ACE 2 to be the key determinant of SARS-CoV-2 infection. Various studies have reported signi cant differences in the frequency of ACE 2 variant (rs2285666/G8790A) in covid-19 infected sub-populations. This variant has been reported to have a mean frequency of 0.6 in Indian population as compared to 0.2 in Europeans and 0.55 in East Asians. Srivastawa et al 2020 revealed a signi cantly higher (P < 0.0001) frequency of this variant among Indian populations in comparison to European or Afro-American populations [16]. G8790A polymorphism has already been reported to carry a potential risk for hypertension, coronary artery diseases, and type II diabetes which translates its possible role as a predisposing factor associated with covid-19 related comorbidities. This variant is located at the beginning of intron 2, thereby may play a possible role in the splicing process which may inturn alter the expression level of ACE 2. Asselta et al 2020 reported G8790A 'A' allele to increase the expression of ACE 2 protein [17]. A study carried out in the Indian sub-continent showed a strong correlation of G8790A 'AA' genotype with the lower infection rate and lower case fatality rate (CFR) [16]. ACE 2 is a component of RAAS and works in coordination with angiotensin I converting enzyme (ACE) which converts angiotensin I to angiotensin II, a potent vasoactive peptide. Besides G8790A polymorphism, an important Insertion Deletion polymorphism (rs4646994) of the ACE gene bears potential implication in covid- 19 [18]. ACE gene is located on chromosome 17q23.3 and rs4646994 involves the presence or absence of a 287 base pair sequence in intron-16 of the gene. Various evidence suggest that D allele or DD genotype could elevate blood pressure, risk of CVD, atherosclerosis, diabetic nephropathy and coronary heart disease [19]. ACE ID and G8790A polymorphisms are probably in linkage disequilibrium and DD/GG combination of these polymorphisms have been reported to confer a signi cative increased risk of developing hypertension [20]. A meta-analysis conducted by Y.li et al reported a signi cant association between the ACE ID "D" allele in Chinese population. The relation between ACE ID polymorphism and various disease states is con icting, as many studies have failed to associate these variants with co-morbidities like coronary artery diseases, hypertension and diabetes [21][22][23].
The synergistic role of ACE2 and ACE cannot be neglected in covid-19 pandemic as these are the important components of the host reception platform for SARS-CoV-2 virus [24]. Because of the fact that the above mentioned co-morbidities play crucial role in deciding the fate of covid-19 infection coupled with a remarkable role of ACE and ACE2 in these disease states, we assessed the role of ACEI/D and G8790A ACE2 polymorphisms as risk factors for severity of covid-19 infection [25].

Subject selection and recruitment
The current study was conducted in the Department of Immunology and Molecular Medicine, in collaboration with the department of General Medicine, Sher-i-Kashmir Institute of Medical sciences, Srinagar (SKIMS), between December 2020 and June 2021. The ethical approval was granted by the institutional ethics committee vide approval number 14/2020. A total of 127 post covid-19 RT con rmed negative subjects who visited the department to check their IgG levels for plasma donation were recruited.
The participants were verbally informed about the nature of the study and its possible outcome and a written consent was taken as directed by the ethical committee of the institute. A detailed questionnaire was completed for each patient that included information on age, gender, blood group, dwelling, occupation, smoking, source of infection, symptoms besides other clinical parameters as depicted in Table 1. vials and stored at -20°C until processing. Serum was used for estimation of IgG levels and whole blood was used for molecular analysis.

Estimation of anti covid-19 IgG antibodies
Anti covid-19 IgG kits were procured from Beckman Couter, USA and serological IgG levels were estimated by using chemiluminescence unicell DXI 800.

Statistical analysis
Statistical analysis was performed using the software SPSS 23.0 (IMB SPSS Statistics 23) and Graph Pad Prism (Version 7.05, La Jolia, California, USA). Categorical variables were compared using Pearson's Chi square test/Fisher's exact test as appropriate. Continuous variables were compared using 'Student's unpaired t-test'; where the data was not normally distributed, an appropriate non-parametric test like Mann-Whitney U-test was used. Spearman correlation coe cient was used for correlation between the variables. All reported P values were based on two-tailed tests. P-value of less than 0.05 (< 0.05) was considered statistically signi cant for all tests.

Study subjects
Data from all the covid-19 patients was obtained from their personal interviews and clinical examinations which included their age, gender, blood group, dwelling, occupation, source of infection, covid-19 symptoms present or not, hospitalization required or not, history of vaccination, underlying diseases, and smoking (

Analysis of SARS-CoV-2 IgG levels vs clinicopathological and demographic features
SARS-CoV-2 IgG levels were compared between different subgroups by running a bivariate analysis depicted in Table 1. A signi cant association was observed with smoking history, dwelling, hospitalization required and age. The mean (SD) of IgG levels in non smokers vs smokers was 9.89 ± 12.64 vs 1.54 ± 2.36 (p = 0.01) which was statistically signi cant. Urban dwellers had higher IgG levels (P = 0.01) with a mean (SD) of 12.16 ± 15.62 as compared to 6.50 ± 7.49 in rural group. Patients aged above 35 had signi cantly higher IgG levels as compared to younger patients (p = 0.01). IgG levels were higher in covid-19 patients who required hospitalization as compared to those who did not require hospitalization (p = 0.01).

Analysis of Resolution-time vs clinico pathological and demographic features
Resolution-time of covid-19 infection for each patient was calculated as the time interval (No. of days) between the date of RT-PCR positive con rmation and date of covid-19 RT-PCR negative con rmation. The mean resolution-time for covid-19 infection in our study cohort was 12.53 with a standard deviation of 4.95. Resolution-time revealed a signi cant association with age and history of H1N1 vaccination, while as association with other parameters was statistically insigni cant. Subjects aged above 35 years presented with a mean resolution-time of 13.76 days as compared to 11.78 days in the younger age group (P = 0.03). Patients who were previously vaccinated for H1N1 had a mean resolution-time of 11.13 ± 3.34 in comparison to 13.24 ± 5.47 in patients who were not previously vaccinated (p = 0.03) ( Table 2).

Correlation analysis between IgG levels, age and resolution-time
Correlation analysis revealed a signi cant positive correlation between age & IgG levels (Fig. 1). No signi cant correlation was observed between resolution-time and IgG levels (Fig. 2), and between Age and resolution time (Fig. 3).

Genotyping of ACE2 G8790A and ACE I/D polymorphisms
Regarding the genotypic frequencies, the results obtained for ACE2 G8790A polymorphism were 55.12% (GG), 0.78% (GA) and 44.09% (AA) ( Table 3). Statistical analysis of G8790A revealed a signi cant association of this variant with severity of covid-19 infection (Table 4). AA genotype was observed to be protective as compared to GG genotype (OR 0.40 (CI -0.141-0.717) P = 0.007). Analysis of G8790A on the basis of symptoms revealed no signi cant association (Table 4).   combined genotype showed an odds ratio of 3.50 and was prevalent in symptomatic covid-19 subjects (Table 6).

Discussion
The pathological mechanisms involved in the interaction of SARS-CoV-2 are of key signi cance for infection and viral replication. Whilst a well-regulated immune response is essential in controlling SARS-CoV-2 infection, the ability of this virus to disrupt the normal immune responses leads to an uncontrolled immune modulation. In this study, we hypothesized that SARS-CoV-2 IgG level, ACE2 G8790A and ACE I/D polymorphism may impact the SARS-CoV-2 infection and its outcomes. We observed a signi cant association of SARS-CoV-2 IgG levels with smoking history, dwelling and age, with comparatively higher levels in non smokers, urban and those aged above 35 years. An interesting observation was that SARS-CoV-2 IgG levels were comparatively higher in subjects who had conspicuous complications coupled with need for hospitalization suggesting that SARS-CoV-2 IgG levels might be helpful in evaluating the course of disease and predicting the prognosis as also suggested by Wu et al., 2019 [26]. Correlation analysis of SARS-CoV-2 IgG levels with the resolution-time revealed insigni cant statistical results. However, resolution-time as a dependent variable showed signi cant association with age and H1N1 vaccination. Subjects aged more than 35 years showed a mean resolution-time of 13.76 which was signi cantly higher than younger sub group (P < 0.05). In addition, subjects who had vaccinated themselves against H1N1 presented with a lower resolution-time (p < 0.05) suggesting that previous vaccination against H1N1 may cross protect against SARS-CoV-2 infection. Several studies have evaluated immune responses in H1N1 and SARS-CoV-2 co-infected models and have revealed some important considerations. Zhang et al., revealed that simultaneous or sequential co-infection by SARS-CoV-2 and H1N1 caused more severe disease than infection by either virus in hamsters although prior H1N1 infection lowered SARS-CoV-2 pulmonary viral load [27]. In an experimental model, Bao et al., reported that co-vaccination effectively protected K18-hACE2 mice against both H1N1 and SARS-CoV-2 infection [28]. A case report from an In uenza-like illness surveillance site in Egypt reported rapid resolution of SARS-CoV-2 and H1N1 co-infection in a 21-year-old woman and her family without treatment [29]. Thus, exploring the cross-protective role of neutralizing antibodies combined with co-vaccination strategies may hold promise against different variants of SARS virus as also suggested by persistence of lower resolution-time in H1N1 vaccinated subgroup in our study and may be an effective tool in developing more e cacious vaccines to support and succor the management of covid-19 pandemic.
Role of ACE2 G8790A and ACE ID Polymorphisms in SARS-CoV-2 SARS-Cov-2 infection is mediated by its binding with ACE2 receptor, a membrane exopeptidase, present on the host cells. Apparently, it seems concurring that the extent of ACE2 expression may determine the severity of this infection. Various studies have correlated ACE2 expression and its polymorphisms with covid-19 severity and most importantly ACE2 is overexpressed in men suggesting a higher sensitivity against the adverse effects of covid-19 infection [30,31]. Various studies have investigated the potential for ACE2 polymorphisms to explain population-based differences in Covid-19 severity [30,32]. In current study, frequency of G8790A GG genotype was observed to be considerably higher in subjects who required hospitalization suggesting GG genotype to be a potential genetic risk which could be predicative of disease severity. Carriers of G8790A GG genotype had higher anti covid-19 IgG titers as compared to those who carried AA genotype; however the results were statistically insigni cant. In addition, no signi cant difference in the resolution-time of covid-19 infection was observed between the carriers of GG and AA genotypes. G8790A is located at the beginning of intron 2 and may play a possible role in splicing process which may in turn alter the expression level of ACE 2 [20,33]. AA genotype has been observed to be associated with higher expression of ACE2. A study reported A/A genotype to increase the expression level of ACE2 by almost 50% in comparison to the G/G genotype [22]. This variant has been extensively studied as a potential risk factor for hypertension, type-2 diabetes, and coronary artery disease [22,23,34]. Contrary to these reports, a study carried out in Indian sub continent showed a strong association of G8790A 'A' allele with lower infection rate and lower CFR thus highlighting its protective role which holds true for the current study as we observed an odds ratio of 0 recovered patients offsets the possibility to observe reported association of ACEI/D DD variant with increased mortality. Based on the close proximity of ACE2 G8790A and ACE ID; these polymorphisms being in linkage disequilibrium, we further carried out their combined genotypic distribution, however the results were statistically insigni cant.
In conclusion the aforementioned results suggest that ACE G8790A GG genotype carries a signi cant risk for covid-19 severity whereas ACE I/D heterozygous genotype bears protective role. The study provides preliminary evidence of a genetic link between the mentioned variants and COVID-19 suggesting a subtle way of COVID-19 risk strati cation and utilization of respective variants as predictive biomarkers. In addition, we report a signi cant association of anti SARS-CoV-2 IgG levels with covid-19 severity. At an individual level, risk strati cation involving ACE I/D and ACE2 G8790A combined with status of SARS-CoV-2 IgG titers might be helpful in evaluating the course of disease, predicting the prognosis and may be an effective tool in improving patient outcomes, management of covid-19 and related complications. Correlation analysis between anti SARS-CoV-2 IgG levels and age at recruitment Correlation analysis between anti SARS-CoV-2 IgG levels and resolution-time