Neutralising SARS-CoV-2 RBD-specific antibodies persist for at least six months independently of symptoms in adults.

Background: In spring 2020, at the beginning of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in Europe, we set up an assay system for large-scale testing of virus-specific and neutralising antibodies including their longevity.
Methods: We analysed the sera of 1655 adult employees for SARS-CoV-2-specific antibodies using the S1 subunit of the spike protein of SARS-CoV-2. Sera containing S1-reactive antibodies were further evaluated for receptor-binding domain (RBD)- and nucleocapsid protein (NCP)-specific antibodies in relation to the neutralisation test (NT) results at three time points over six months.
Results: We detect immunoglobulin G (IgG) and/or IgA antibodies reactive to the S1 protein in 10.15% (n = 168) of the participants. In total, 0.97% (n = 16) are positive for S1-IgG, 0.91% (n = 15) were S1-IgG- borderline and 8.28% (n = 137) exhibit only S1-IgA antibodies. Of the 168 S1-reactive sera, 8.33% (n = 14) have detectable RBD-specific antibodies and 6.55% (n = 11) NCP-specific antibodies. The latter correlates with NTs (kappa coefficient = 0.8660) but start to decline after 3 months. RBD-specific antibodies correlate most closely with the NT (kappa = 0.9448) and only these antibodies are stable for up to six months. All participants with virus-neutralising antibodies report symptoms, of which anosmia and/or dysgeusia correlate most closely with the detection of virus-neutralising antibodies. Conclusions: RBD-specific antibodies are most reliably detected post-infection, independent of the number/severity of symptoms, and correlate with neutralising antibodies at least for six months. They thus qualify best for large-scale seroepidemiological evaluation of both antibody reactivity and virus neutralisation.

Introduction

The ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has led to dramatic restrictions in public life worldwide to mitigate the anticipated epidemic peak[1]. At the early stage of the pandemic, data were missing to estimate the actual number of infected individuals, including asymptomatic/oligosymptomatic cases that were left unreported due to the limitations in the polymerase chain reaction (PCR) testing capacity and strategy that was initially confined to the fulfilment of case definitions. It was, therefore, difficult to assess the actual risk of infection for employers with respect to shared workspaces and staff in contact with customers. Where possible, employers facilitated employees’ work in home office mode with the intention to reduce the number of social contacts and consequently, the risk of infection[2].

In order to estimate past infections irrespective of symptoms and a preceding PCR test, specific and sensitive serological antibody tests, including neutralising assays, are necessary tools[3].

Several validated serological formats are now in use, based on enzyme-linked immunosorbent assays (ELISA) and chemiluminescence targeting different SARS-CoV-2 antigens[4]. The target antigens are the spike (S) protein with its receptor-binding domain (RBD), and the nucleocapsid protein (NCP). These antigens have been shown to induce robust antibody responses in infected individuals[5,6]. Another important question has emerged as to whether the detected antibodies also indicate protection against reinfection. In this regard, neutralising antibodies are likely to be considered as correlate of protection as they can lead to virus inactivation[6]. Along these lines, it is still unclear which test would prove most appropriate to describe transmission patterns and to determine immunity upon virus contact in overall, as well as in defined populations (in contrast to individual analysis/neutralisation tests [NTs]).

The goal of the current study was to analyse the seroprevalence of SARS-CoV-2-specific antibodies at the beginning of the pandemic and over several months in a representative cohort of employees from a large Austrian company. Therefore, several assays were included to identify the most accurate test for large-scale seroepidemiological analysis. The participants were included irrespective of a previous history of COVID-19 or experienced symptoms. The accumulated basic demographic data (gender, age, household size) and information on respiratory tract infections and symptoms, medical risk factors and travel history were analysed in context with the SARS-CoV-2-specific antibody test results. Employees with virus-reactive antibodies at the initial blood draw at the beginning of April 2020 were invited for follow-up blood draws at 3 and 6 months after study onset to analyse the persistence of the detected antibody levels. At 6 months, also participants without detectable virus-reactive antibodies at the initial blood draw were asked for a follow-up blood draw in order to detect seroconversion and to assess the development of seroprevalence in the overall study population over the last months.

Here, we show that RBD-specific antibodies are most reliably detected post-infection independently of the number/severity of symptoms and correlate with neutralising antibodies at least for 6 months.

Methods

Patients and samples

We included 1655 serum samples of employees working for a large company in Vienna. While half of the staff continuously worked on-site with frequent client contacts, the other half worked from home at the beginning of this trial followed by a weekly rotation between home office and on-site work after the lockdown period in Austria. The blood samples were taken at the medical centre of the company between 2nd and 17th April 2020 and sent in for further analysis (to the Institute of Specific Prophylaxis and Tropical Medicine at the Medical University of Vienna). Three months later, 156 of 168 participants with detectable S1-specific antibodies at the first blood draw came for a follow-up blood draw. Six months after the first blood draw 1292 of all 1655 participants participated in a follow-up blood draw, including 139 participants of those 168 that had detectable antibodies at the initial blood draw. The employees gave informed consent to SARS-CoV-2 serological testing and answered a questionnaire covering demographic data and their medical history, including current medications. Symptoms such as coughing, dyspnoea, thoracic pain, sore throat, rhinitis, elevated body temperature, fever, shivers, limb pain, weakness, headache, dysgeusia and/or anosmia, and gastrointestinal symptoms as described for COVID-19 were recorded, in addition to medical risk factors including those predisposing for a severe course of COVID-19. The risk factors were defined according to the Austrian Ministry of Social Affairs, Health, Care and Consumer Protection (chronic lung/respiratory disease, chronic cardiovascular disease, active cancer, immunosuppression and immunosuppressive drugs, chronic kidney disease, chronic liver disease with liver failure, diabetes, and arterial hypertension).

The ethics committee of the Medical University of Vienna approved this monocentric study (EK 1438/2020, EK 1746/2020).

Testing for SARS-CoV-2-specific antibodies

The SARS-CoV-2-specific antibody levels were measured with four different serological assays.

First, all sera were tested for SARS-CoV-2-specific immunoglobin (Ig) A and IgG antibodies using a commercial ELISA kit (Euroimmune®, Euroimmun Medizinische Labordiagnostika, Lübeck, Germany) according to the manufacturer’s instructions. The antigen used in this semi-quantitative assay is the S1 domain of the SARS-CoV-2 S protein. The sera were diluted 1:101 before incubation. Results with a ratio below 0.8 were interpreted as negative, ratios between 0.8 and 1.1 as borderline and above 1.1 as positive, whereby ratios were calculated as optical density values of the control or patient sample divided by the optical density values of the calibrator. Samples within the borderline range and with ratios close to the cut-off of 0.8 or 1.1 (value from 0.7 to 1.2) were repeated in two independent tests and the geometric mean was used for the final result. Therefore, samples that were positive for S1-specific IgG, regardless of their S1-specific IgA result, were regarded as “IgG-positive”, those with borderline values for S1-specific IgG after two repetitions, regardless of their IgA result, as “IgG-borderline” and those negative for S1-specific IgG but IgA-positive or IgA-borderline as “IgA-positive or -borderline” samples. No valid interpretation is currently possible in the case of isolated positive IgA findings. Samples negative for IgG and IgA were considered as “IgG- and IgA-negative”.

Second, all positive and borderline samples were further evaluated for antibodies against the RBD of the S protein and NCP. The RBD-specific antibodies were determined using a commercial available ELISA for IgM and total antibodies (ab) (Beijing Wantai Biological Pharmacy Enterprise, Beijing, China) as described in the manufacturer’s instructions, leading to borderline results when the ratio was between 0.9 and 1.1. Samples within the borderline range and with ratios close to the cut-off of 0.9 or 1.1 (i.e., between 0.8 and 1.2) were repeated in two independent tests and the geometric mean was used for the final result. NCP-specific IgG antibodies were tested by ELISA (Euroimmune®, Euroimmun Medizinische Labordiagnostika, Lübeck, Germany) applying the same criteria for calculating the results as for the S1 ELISA following the manufacturer´s instructions. In addition, we measured total NCP-specific antibodies in an automated sandwich electrochemiluminescence assay (Elecsys®, Roche Diagnostics, Mannheim, Germany; on a Cobas e 801). Results with a cut-off index of ≥1 were regarded as positive.

Finally, all IgG-positive sera and those with high IgA levels (Euroimmune ratio > 4) as well as a random sample (n = 20) of the seronegative sera were also tested/confirmed by a live virus-neutralising assay to evaluate the rate of functional antibodies. The SARS-CoV-2 NTs were done in cooperation with Takeda (Vienna, Austria).

SARS-CoV-2 neutralisation assay

SARS-CoV-2 neutralisation (NT) testing was done similar as previously described[7]. Briefly, Vero cells (ATCC CCL-81) sourced from the European Collection of Authenticated Cell Cultures (84113001) were cultured in TC-Vero medium supplemented with 5% fetal calf serum, l-glutamine (2 mM), nonessential amino acids (1x), sodium pyruvate (1 mM), gentamicin sulfate (100 mg/ml), and sodium bicarbonate (7.5%). SARS-CoV-2 strain BetaCoV/Germany/BavPat1/2020 was kindly provided by the Institute of Virology at Charité Universitätsmedizin, Berlin, Germany. For the SARS-CoV-2 neutralisation assays, samples were serially diluted 1:2 and incubated with 100 tissue culture infectious dose 50% (TCID50) of SARS-CoV-2 per well. The samples were subsequently applied onto Vero cells seeded in tissue culture plates and incubated for 5 to 7 days, after which the cells were evaluated for the presence of a cytopathic effect and the SARS-CoV-2 neutralisation titre (NT50), i.e., the reciprocal sample dilution resulting in 50% virus neutralisation, was determined using the Spearman-Kärber formula and reported as 1:X. Cut-off values varied between 1:3 and 1:7.7 NT50 between the assay runs, depending on sample-predilution and level of sample cytotoxicity.

Statistical evaluation

For sample size considerations, we expected to compile data sets from ~800 employees continuing to work on-site with client contacts and some 700 home office workers. Based on the numbers of notified SARS-CoV-2 PCR-positive individuals in Vienna and an estimated number of 10% unreported cases, it was assumed that ~1% of the population had already had contact with the virus prior to the blood draw. Presuming that these figures would also apply to the employees included in the study, the effect size expressed as an odds ratio of 3 at a two-sided level of significance of 5% resulted in a statistical power of 77% to compare employees on-site and in home office (Fisher′s exact probability test).

The data were evaluated for the two groups (working on-site and from home) and the subgroups stratified for age (15 to 25 years, 25 to 50 and above the age of 50). Seropositivity as a dependent variable was evaluated in a general linear model for binominal counts (see supplementary materials for more details). The primary predictor variable was defined according to the current workplace (home office or continuing to work with client contacts). Age, the number of household contacts, and the presence of underlying disease served as co-variables. To assess the relationship between various symptoms and seropositivity, a stepwise procedure was applied entering all mentioned covariates in one step and including symptoms in further steps with a significance level of 5% for inclusion and 10% for exclusion. The analyses were done using SPSS 26 (IBM Corp., New York, NY, USA) and the graphics were prepared with GraphPad Prism 7 (Graphpad Software, Inc., San Diego, CA, USA) or Excel (Microsoft Excel 2010, Microsoft Corporation, Redmond, WA, USA).

For changes in seroprevalence between the first blood draw and 6 months later, we calculated the ratio of new positives compared to new negatives applying the Chi² McNemar test and the difference in prevalences.

Table 1

Demographic data by general characteristics and brief medical history.

Demographic data		All participants(n = 1655)		n	%	SEM
Gender	Female			886	53.53%	(±1.23)
	Male			769	46.46%	(±1.23)
Age group	Young	15–25 a	Mean age = 22.40 (±0.15)	226	13.66%
			Home office	63	27.88%	(±3.08)
			No home office	146	64.60%	(±2.99)
			Not specified	7	3.10%	(±1.16)
	Medium	25–50 a	Mean age =  37.80 (±0.23)	1031	62.30%
			Home office	555	53.83%	(±1.55)
			No home office	409	39.67%	(±1.55)
			Not specified	3	0.29%	(±0.17)
	Older	>50 a	Mean age =  54.75 (±0.18)	395	23.87%
			Home office	248	62.78%	(±2.43)
			No home office	123	31.13%	(±2.44)
			Not specified	1	0.25%	(±0.25)
		Not specified		3	0.18%
Home office		No		778	47.01%	(±1.23)
		Yes		866	52.33%	(±1.23)
		Not Specified		11	0.66%	(±0.20)
Residence		Vienna		1115	67.37%	(±1.15)
		Outside Vienna		531	32.08%	(±1.15)
		Not specified		9	0.54%	(±0.18)
Children (≤15a) living in same houshold		No		1184	71.54%	(±1.11)
		Yes		463	27.98%	(±1.10)
		Not specified		8	0.48%	(±0.17)
Travelling in the last 3 months		No		806	48.76%	(±1.23)
		Yes		822	49.61%	(±1.23)
		Not specified		27	1.63%	(±0.31)
Use of public transport		No		510	30.82%	(±1.14)
		Yes		446	26.95%	(±1.10)
		Not specified		699	42.24%	(±1.22)
Social contacts during lockdown		No		104	6.28%	(±0.60)
		Yes		1016	61.39%	(±1.20)
		Not specified		535	32.33%	(±1.15)
Known contact with COVID-19 infected patients		No		1617	97.70%	(±0.37)
		Yes		36	2.17%	(±0.36)
		Not specified		2	0.12%	(±0.09)
Previously tested for COVID-19		No		1630	98.49%	(±0.30)
		Yes		19	1.15%	(±0.26)
			Positive	3	15.79%	(±0.13)
			Negative	5	26.32%	(±0.10)
			Not specified	11	57.89%	(±0.20)
		Not specified		6	0.36%	(±0.15)
Symptoms in the last 3 months		No		956	57.76%	(±1.21)
		Yes		696	42.05%	(±1.21)
		Not specified		3	0,18%	(±0.10)
Personal risk factors / medical history		No		1257	75.95%	(±0.88)
		Yes		391	23.62%	(±0.87)
		Not specified		7	0.42%	(±0.16)
Use of medication		No		1246	75.29%	(±1.06)
		Yes		403	24.35%	(±1.06)
		Not Specified		6	0.36%	(±0.15)

These data were analysed from the received questionnaires.

Table 2

S1-reactive IgA and IgG antibody results according to age group.

Age group	IgG & IgA negative	IgG positive	IgG borderline	IgA borderline/positive
15–25	196 (86.73%)	4 (1.77%)	2 (0.88%)	24 (10.62%)
25–50	920 (89.23%)	7 (0.68%)	12 (1.16%)	92 (8.92%)
>50	369 (93.42)	5 (1.27%)	1 (0.25%)	20 (5.06%)
not specified	2	0	0	1

Antibodies were measured in sera from the initial blood draw at day 0. S1 subunit of spike protein (S1).

Table 3

Likelihood for seropositivity according to independent variables (predictors) such as home office, known contact to COVID-19 patients, children <15 years of age within the same household, residence in Vienna or outside, age group (comparison to the young 15–25 years old) and symptoms.

Predictor	Odds ratio	95% confidence interval	p-value
Home office (yes/no)	1.91	1.21–3.01	0.005
Known contact to COVID-19 patients	1.27	0.35–4.59	0.719
Children < 15 years in the same household	1.04	0.65–1.64	0.882
Residence in Vienna (y/n)	1.32	0.86–2.03	0.197
Age group 15–24	1.00
Age group 25–50	0.56	0.32–0.99	0.046
Age group >50	0.38	0.19–0.77	0.007
Any symptom	1.19	0.80–1.77	0.397
Anosmia/dysgeusia	22.48	7.75–65.22	<0.001

Table 4

Overall prevalence of COVID-19 like symptoms in participants without and with neutralising antibodies in participants with neutralising antibodies evaluated in sera from the initial blood draw (day 0).

	NT neg/not done	NT pos
Symptoms	n (%)	n (%)	Prevalence	p-value
Cough	341 (20.8%)	4 (30.8%)	1.2%	0.489
Fever/elevated body temp.	214 (13.0%)	7 (53.8%)	3.2%	0.001
Sore throat	205 (12.5%)	6 (46.2%)	2.8%	0.003
Rhinitis	212 (12.9%)	4 (30.8%)	1.9%	0.078
Body aches	55 (3.3%)	1 (7.7%)	1.8%	0.362
Faintness	68 (4.1%)	3 (23.1%)	4.2%	0.016
Headache	55 (3.3%)	2 (15.4%)	3.5%	0.071
Common cold	87 (5.3%)	1 (7.7%)	1.1%	0.510
Shivers	19 (1.2%)	1 (7.7%)	5.0%	0.147
Dyspnea	27 (1.6%)	2 (15.4%)	6.9%	0.021
Thoracical pain	14 (0.9%)	1 (7.7%)	6.7%	0.112
Gastrointestinal symptoms	24 (1.5%)	2 (15.4%)	7.7%	0.017
Anosmia/dysgeusia	6 (0.4%)	9 (69.2%)	60.0%	<0.001
Other	23 (1.4%)	1 (7.7%)	4.2%	0.174
Any symptom	669 (40.7%)	13 (100.0%)	1.9%	<0.001

Neutralising test (NT).

Bold values refer to significant results (p-value < 0.05)

Table 5

Changes in the seroprevalence between day 0 and 6 months.

Test	Ratio	p-value (against day 0)	Neg → pos (%neg)	Pos → neg (%pos)	Difference of prevalence (%)
S1-specific IgG	1.56	0.212	2.0	55.2	0.7
S1-specific IgA	0.33	<0.001	2.6	70.8	−4.8
RBD-specific IgM	2.88	0.012	1.8	53.3	1.2
RBD-specific total antibodies	>54	<0.001	2.1	0.0	2.1
NCP-specific IgG	3.00	0.014	1.6	50.0	1.1

Changes are indicated by the ratio of newly positives to those that became negative; and the proportion of negatives that became positive (neg → pos) as well as the proportion of positives that became negative (pos → neg) and difference of prevalences of positives at month 6 and day 0; p-value assessed by Chi² McNemar. S1 subunit of spike protein (S1), receptor-binding domain (RBD), nucleocapsid (NCP).