key: cord-0985356-36non3cp
authors: Pereira, Christopher; Harris, Benjamin H L; Di Giovannantonio, Matteo; Rosadas, Carolina; Short, Charlotte-Eve; Quinlan, Rachael; Sureda-Vives, Macià; Fernandez, Natalia; Day-Weber, Isaac; Khan, Maryam; Marchesin, Federica; Katsanovskaja, Ksenia; Parker, Eleanor; Taylor, Graham P; Tedder, Richard S; McClure, Myra O; Dani, Melanie; Fertleman, Michael
title: Antibody response to SARS-CoV-2 infection is not associated with Post-COVID-19 Syndrome in healthcare workers
date: 2021-03-02
journal: J Infect Dis
DOI: 10.1093/infdis/jiab120
sha: 87e5a9c5702145a14d2604dfb180852b36499b8b
doc_id: 985356
cord_uid: 36non3cp

It is currently unknown how Post-COVID-19 Syndrome (PCS) may affect those infected with SARS-CoV-2. This longitudinal study reports on healthcare staff who tested positive for SARS-CoV-2 between March-April 2020 and follows their antibody titres and symptomatology. Over half (n=21/38) had PCS at 7-8 months. There was no statistically significant difference between initial RT-PCR viral titres or serial antibody levels between those who did and did not develop PCS. This study highlights the relative commonality of PCS in healthcare workers and this should be considered in vaccination scheduling and workforce planning to allow adequate frontline staffing numbers.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the ongoing coronavirus disease-19 (COVID-19) pandemic. Disease severity ranges from asymptomatic to fatal. As of November 2020, the pandemic was responsible for 1.2 million deaths worldwide (1). Risk factors for mortality include increased age, male gender, comorbidities, South Asian, Black or minority ethnic (BAME) groups and socio-economic deprivation (2) .

Most work on SARS-CoV-2 has focussed on the immediate presentation and sequelae of COVID-19. However, there is a growing appreciation that symptoms can persist after infection, resulting in Post-COVID-19 Syndrome (PCS), otherwise known as Long-COVID (3, 4) . The National Institute for Health and Care Excellence (NICE) define PCS as 'Signs and symptoms that develop during or following an infection consistent with COVID-19, continue for more than 12 weeks and are not explained by an alternative diagnosis' (4) . The symptoms of PCS include fatigue, headache, anosmia and lower respiratory tract symptoms.

More than five symptoms within a week of diagnosis of SARS-CoV-2 increase the chances of developing PCS (5) .

Although an estimated 60,000 people in the UK have PCS, there is little peer-reviewed data on the subject, and longitudinal observational studies are needed (6) . The unprecedented global reach of the COVID-19 pandemic means that the impact of PCS is profound. Thus, identifying risk factors for developing PCS is crucial for planning rehabilitation.

Antibody response to SARS-CoV-2 may inform on immunity to the virus. Establishing the longevity of antibody response to SARS-CoV-2 could predict re-infection risk, the necessity A c c e p t e d M a n u s c r i p t of vaccination in infected individuals and the need for vaccine boosters. We hypothesised that it may affect the risk of developing PCS.

Antibody response to SARS-CoV-2 infection has been analysed up to 94 (7), 98 (8), 152 (9) and 210 days following symptom onset (10), with antibodies being maintained for at least six months (10) . However, it is established that humoral immunity to other coronaviruses decreases over time (11) . Antibody levels to SARS-CoV-2 were initially higher in patients with greater disease severity (7), before falling to the same level as lower disease severity or asymptomatic patients at 3-4 months (9).

This study of 42 healthcare workers considers potential associations between PCS and (a) initial viral titres and (b) serial antibody levels.

This descriptive study of healthcare workers was conducted at a hospital in North West London. Ethical approval was granted from the hospital review board. All participants gave written informed consent. Serial blood samples were processed and serum stored at -80°C at the local University Communicable Disease Research Tissue Bank (NRES SC/20/0226).

All hospital staff at the hospital who tested positive for SARS-CoV-2, following nasopharyngeal swabs, were eligible to volunteer for the study. Those who tested positive for SARS-CoV-2 were invited by e-mail to take part in the study. Information collected at enrolment included gender, age, job, co-morbidities, regular medications and ethnicity.

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The first serum sample for anti-SARS-CoV2 antibody testing was taken between 27-and-69 days post-symptom onset. Three staff members were asymptomatic, meaning diagnosis date was used instead of symptom onset date. Serum samples were taken at weekly intervals for the first month followed by monthly samples.

To assess symptoms of PCS, participants were followed-up with a questionnaire which was completed between 7-8 months following symptom onset. The authors felt this represented enough time to have recovered from the initial viral infection, so clearly differentiating PCS from ongoing symptomatic COVID-19.

A diagnosis of PCS was made using the NICE definition, with screening questions based on the most commonly reported symptoms in the NICE guidelines (4). These included: breathlessness, cough, chest tightness/pain, palpitations, fatigue, fever, pain, cognitive impairment, headache, sleep disturbance, peripheral neuropathic symptoms, dizziness, delirium, abdominal pain, diarrhoea, anorexia/reduced appetite, joint/muscle pain, depression, anxiety, tinnitus, earache, sore throat, dizziness, loss of appetite, anosmia and rashes.

Diagnostic testing for SARS-CoV-2 was undertaken by Micropathology (University of Warwick) using the same method as described by Harris et al (12) . Samples were analysed within a day of testing and viral RNA was extracted via the Maxwell® HT 96 NA kit of the KingFisher FLEX platform (Thermo Fisher Scientific Inc).

A c c e p t e d M a n u s c r i p t As outlined in the US Centers for Disease Control and Prevention recommendations for SARS-CoV-2 testing (13), specific primers and probes were used for the reversetranscriptase (RT) PCR work. The primer and probe sequences are detailed here https://www.cdc.gov/coronavirus/2019-ncov/lab/rt-pcr-panel-primer-probes.html (13) . The probe anneals to a specific target sequence located between the forward and reverse primers. RT-PCR was performed on a Roche LightCycler 480. The cycles used were: RT (50°C for 10 minutes) and polymerase activation (95°C for 2 minutes), followed by PCR (45 cycles of 95°C for 5 seconds and 55°C for 20 seconds). Results were expressed as Cycle threshold (Ct) values. The internal control used was the DNA from the baculovirus, Adoxophyes orana granulovirus. This was added to the samples at a fixed concentration, meaning its amplification in each sample should be the same (Ct~33). If the internal control failed (i.e. no amplification was seen) or amplification was delayed (Ct >37) the sample was retested.

Antibody testing for SARS-CoV-2 was undertaken using the 'in-house' double antigen binding assay ELISA (Imperial Hybrid DABA; Imperial College London, London, UK). This detects total antibodies against the SARS-CoV-2 receptor binding domain (anti-RBD) and has a specificity of 100% (95% CI 99.6-100%) and a sensitivity of 98·9% (96·8-99·8%) (14) .

As described by Rosadas et al (14) , the Imperial Hybrid DABA uses S1 antigen and enzymelabelled RBD in the solid and fluid phase respectively. As the Hybrid DABA detects total immunoglobulin, confounding seroconversion from IgM to IgG is avoided.

A c c e p t e d M a n u s c r i p t Assay cut-off was calculated from Receiver Operating Characteristic Curve analysis. Serum reactivity was normalised by using the binding ratio, the ratio of optical density (OD) values generated in a sample to the cut-off OD value. Antibody positive samples were determined by a binding ratio of ≥1.

Samples with a binding ratio >20 were diluted further and retested using the Imperial Hybrid DABA, to correct for a loss of linearity when the binding ratio exceeded 20. This was necessary in only a minority of samples (29/291). To quantify the antibody level in each sample, an indicative value called Arbitrary Unitage (AU) was calculated from the standard curve using a method previously described by Tedder et al (15) .

Analyses were carried out using Python software, version 3.7. A two-sided Mann-Whitney-Wilcoxon test was used for the comparison of the Ct values and antibody levels between the Non-Post-COVID-19 Syndrome (NPCS) and PCS groups. Fisher's exact test (two-tailed) was used to compare the likelihood of men vs women having PCS and BAME vs non-BAME having PCS. Spearman rank correlation coefficient was used to correlate Ct values and Hybrid DABA antibody binding ratios.

A total of 42 staff members enrolled into the study (36 female). All staff were RT-PCR positive for SARS-CoV-2 and were either asymptomatic (n=3) or symptomatic but not requiring hospitalisation (n=39). The average age was 43 years (range 23-67) and 37% (n=14) were from a BAME group. Full demographic information is detailed in Table 1 , excluding the A c c e p t e d M a n u s c r i p t four staff members who did not complete the PCS questionnaire. Staff were diagnosed between 21/03/20-05/05/20 with symptom onset ranging from 16/03/20-28/04/20.

The questionnaire response rate was 90% (38/42). Of those participants who completed the questionnaire, 55% (21/38) reported at least one ongoing symptom. The commonest was fatigue (57%), followed by loss of smell (29%), breathlessness (24%) and difficulty concentrating (24%). In the 21 staff members with PCS, 38% had 1, 29% had 2 and 33% had ≥3 ongoing symptoms. Sixteen percent reported they were no longer able to participate in a sport or recreational activity because of their ongoing symptoms. A higher percentage of BAME individuals developed PCS (10/14), although this was not statistically significant (p=0.181). Women appeared more likely to develop PCS (63% vs. 17%), but again this was not statistically significant (p=0.07) and only six people in the study were male.

Antibody response over time is shown in Figure 1A . Five staff members (12%) elected to stop donating samples before six months. Excluding these participants, serum samples were taken for a mean of 205 days post-symptom onset (range 177-231 days), with a mean of seven sequential samples taken per person.

Of the 37 staff members who continued giving serum samples, 89% had detectable antibodies at six months. Of those whose antibody levels were negative at six months, three people were initially seropositive and then became seronegative, whilst one person never developed detectable antibodies. There was no significant correlation between Ct values (which indicate viral load) and antibody response over time.

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There was no statistically significant difference in Ct values for RT-PCR for SARS-CoV-2 between the PCS and NPCS groups at diagnosis, as shown in Figure 1B 3-38.7) . Similarly, there was no statistically significant difference in serial antibody binding ratios between the PCS and NPCS groups ( Figure 1C ). At month two, the median antibody binding ratios for PCS were 3.14 (IQR 1.8-6.8) and 4.7 for NPCS (IQR 2.1-8.2) whilst at month eight the median antibody binding ratios for PCS were 4.5 (IQR 1.3-8.4) and 3.2 for NPCS (IQR 1. 5-12.7 ).

This study shows that, in a cohort of SARS-Cov-2 infected healthcare workers who did not require hospitalisation, antibody levels were detectable for 89% of tested staff for at least six months from symptom onset (n=33/37). This is in line with a study on a larger cohort (10) . Of the four subjects who were seronegative at six months, three started seropositive and became seronegative and one never developed antibodies. One of the staff who was initially antibody seropositive and later became seronegative was asymptomatic and on immunosuppressants. The other three staff who were seronegative at six months were symptomatic at time of diagnosis. This is the first study to examine the relationship between initial viral titres and antibody measurements with development of PCS. Our results show that PCS rates are high amongst healthcare workers (55%) at 7-8 months. This is higher than studies with shorter follow up times, where rates of PCS fell to 2.3% at >12 weeks (5) .

A c c e p t e d M a n u s c r i p t In our study, neither initial viral titres at diagnosis nor serial antibody measurements up to 8 months from symptom onset provided differentiation between NPCS and PCS groups. This was unexpected, as it suggests that prolonged effects are not directly related to the severity of the initial infection or the host response to the virus.

Our study had certain limitations which include the small group size (resulting in wide confidence limits on the measured values) and the fact that PCS information was collected only once, therefore our results should be interpreted with caution. It is possible that some participants had PCS symptoms that had resolved by the time of the questionnaire, potentially underestimating the scale of PCS. Completing the questionnaire after 7-8 months may have resulted in recall bias for the initial symptoms patients developed. It is noteworthy that a diagnosis of PCS was made based on self-reported symptoms, the most common of which was relatively non-specific (fatigue). There was no comparison with an uninfected group of healthcare workers and no investigations were undertaken to identify alternative causes. Finally, we only comment on the humoral response whilst it is likely non-B cell responses also play a role in physiological defences.

These findings highlight the high incidence of symptoms consistent with PCS amongst healthcare workers. They should be considered by those involved in workforce planning and vaccination scheduling in order to minimise the impacts of PCS on the welfare of healthcare workers and the provision of health care. The lack of difference in a) viral load and b) serial antibody reactivity between staff with and without PCS suggests that this is a complex disease process. Our knowledge of PCS remains in its infancy, with an urgent need to understand its aetiology and treatment.

A c c e p t e d M a n u s c r i p t 

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The authors would like to thank all participants who agreed to take part in this study. We would like to thank those involved in recruitment and sample processing, including Vasileios Pastarmatzis, Scott Lister, Jelyne Jesusa, Paul Andrew Tiamzon, Andy Taylor, Ronan Calvez and Mohamed Zuhair.

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