Literature DB >> 33400782

The Duration, Dynamics, and Determinants of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Antibody Responses in Individual Healthcare Workers.

Sheila F Lumley1,2, Jia Wei3,2, Denise O'Donnell2, Nicole E Stoesser2,4,5, Philippa C Matthews2,4,5, Alison Howarth2, Stephanie B Hatch2, Brian D Marsden2,6, Stuart Cox1, Tim James1, Liam J Peck7, Thomas G Ritter7, Zoe de Toledo7, Richard J Cornall2, E Yvonne Jones2, David I Stuart2, Gavin Screaton2, Daniel Ebner2,8, Sarah Hoosdally2,4,5, Derrick W Crook2,4,5, Christopher P Conlon2, Koen B Pouwels5,9, A Sarah Walker2,4,5, Tim E A Peto2,4,5, Timothy M Walker2,10, Katie Jeffery1, David W Eyre3,4,5,11.   

Abstract

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunoglobulin G (IgG) antibody measurements can be used to estimate the proportion of a population exposed or infected and may be informative about the risk of future infection. Previous estimates of the duration of antibody responses vary.
METHODS: We present 6 months of data from a longitudinal seroprevalence study of 3276 UK healthcare workers (HCWs). Serial measurements of SARS-CoV-2 anti-nucleocapsid and anti-spike IgG were obtained. Interval censored survival analysis was used to investigate the duration of detectable responses. Additionally, Bayesian mixed linear models were used to investigate anti-nucleocapsid waning.
RESULTS: Anti-spike IgG levels remained stably detected after a positive result, for example, in 94% (95% credibility interval [CrI] 91-96%) of HCWs at 180 days. Anti-nucleocapsid IgG levels rose to a peak at 24 (95% CrI 19-31) days post first polymerase chain reaction (PCR)-positive test, before beginning to fall. Considering 452 anti-nucleocapsid seropositive HCWs over a median of 121 days from their maximum positive IgG titer, the mean estimated antibody half-life was 85 (95% CrI 81-90) days. Higher maximum observed anti-nucleocapsid titers were associated with longer estimated antibody half-lives. Increasing age, Asian ethnicity, and prior self-reported symptoms were independently associated with higher maximum anti-nucleocapsid levels and increasing age and a positive PCR test undertaken for symptoms with longer anti-nucleocapsid half-lives.
CONCLUSIONS: SARS-CoV-2 anti-nucleocapsid antibodies wane within months and fall faster in younger adults and those without symptoms. However, anti-spike IgG remains stably detected. Ongoing longitudinal studies are required to track the long-term duration of antibody levels and their association with immunity to SARS-CoV-2 reinfection.
© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America.

Entities:  

Keywords:  COVID-19; SARS-CoV-2; antibody; longitudinal; serology

Mesh:

Substances:

Year:  2021        PMID: 33400782      PMCID: PMC7929225          DOI: 10.1093/cid/ciab004

Source DB:  PubMed          Journal:  Clin Infect Dis        ISSN: 1058-4838            Impact factor:   9.079


Measurable immunoglobulin G (IgG) antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigens develop after many, but not all, SARS-CoV-2 infections [1-4]. Serological responses are typically detectable within 1–3 weeks [5-8]. This allows antibody assays to be used to estimate the proportion of a population exposed or infected. Additionally, although the extent of immunity associated with different antibody titers and other immune responses is yet to be fully determined, it is probable that antibody levels will provide some information about the risk and/or severity of future infection. However, SARS-CoV-2 IgG antibody levels are dynamic over time [9]. This has implications for epidemiological studies; for example, if IgG levels fall below detection thresholds before they are measured, past infections may be underascertained. Similarly, it has implications for estimating population protection if antibodies are a marker for protective immunity. Contrasting data have been made available on the longitudinal trajectory and longevity of antibodies induced by SARS-CoV-2 infection. For example, a US study showed IgG antibody levels to trimerized spike were relatively stable in 121 individuals around 110 days post symptom onset [10]. Similarly, data from 1215 individuals in Iceland suggest that IgG responses to nucleocapsid and the S1 component of spike were sustained for 100–125 days [11]. However, others have noted declines in neutralizing antibodies over similar time periods [12-14]. We have recently undertaken baseline serological testing in a cohort of >10 000 healthcare workers (HCWs) [15]. We now describe serial SARS-CoV-2 antibody measurements, demonstrating quantitative anti-nucleocapsid responses fall over time and vary with age, ethnicity, and previous symptoms, but anti-spike levels antibodies remain stably detected in most individuals.

METHODS

Setting and Participants

Oxford University Hospitals (OUH) offers both symptomatic and asymptomatic SARS-CoV-2 testing programs to staff at its 4 teaching hospitals in Oxfordshire, UK. In total, 12 411 HCWs have undergone serological testing to date; data on HCWs who attended more than once for antibody testing are presented. SARS-CoV-2 polymerase chain reaction (PCR) testing of nasal and oropharyngeal swabs for all symptomatic (new persistent cough, fever ≥37.8°C, anosmia/ageusia) staff was offered from 27 March 2020 onward. Asymptomatic HCWs were invited to participate in voluntary staff testing for SARS-CoV-2 by nasal and oropharyngeal swab PCR and serological testing from 23 April 2020 onward. The cohort, associated methods, and findings from the first test per individual have been previously described [15]. Following initial PCR and antibody testing, asymptomatic HCWs were invited to optionally attend for serological testing up to once every 2 months, with some offered more frequent screening as part of related studies. Asymptomatic staff were also offered optional SARS-CoV-2 PCR tests every 2 weeks.

Laboratory Assays

Serology for SARS-CoV-2 IgG to nucleocapsid protein was performed using the Abbott Architect i2000 chemiluminescent microparticle immunoassay (CMIA; Abbott, Maidenhead, UK). Antibody levels ≥1.40 manufacturer’s arbitrary units were considered positive, 0.50–1.39 equivocal (following Abbott Diagnostics Product Information Letter PI1060–2020) and <0.5 negative. Anti-trimeric-spike IgG levels were measured using an enzyme-linked immunosorbent assay (ELISA) developed by the University of Oxford [2], using net-normalized signal cutoff of ≥8 million units to determine antibody presence and defining 4.0–7.9 million units as equivocal [16]. Details on PCR assays are provided in the Supplementary Data.

Statistical Methods

For anti-nucleocapsid antibodies, individuals with ≥1 positive antibody result (titer ≥1.40) and ≥2 antibody results were classified as showing rising titers only, falling or stable titers only, or both. Those with only one measurement could not be classified and were excluded. In those with falling/stable titers we estimated the duration of antibody responses following the maximum observed result using Bayesian linear mixed models and their association with age, gender, ethnicity, previous self-reported symptoms, and PCR results (allowing correlated random intercept and slope terms, see Supplementary Data for details and Supplementary Table 1). We assumed antibody levels fell exponentially and so modeled log2 transformed antibody levels over time (observed data and fitted models demonstrated close congruence, Supplementary Data). The incidence of coronavirus disease 2019 (COVID-19) in our hospital fell after a peak in March and April 2020 [15], such that reexposure of HCWs during the study was uncommon; we therefore had insufficient data to study boosting of antibody responses. We additionally modeled the antibody trajectory from a first positive PCR test using a similar approach but allowing for nonlinear effects of time rather than assuming an exponential decline. It was not possible to model anti-spike IgG titers over time in those with a positive result as most positive readings were above the upper limit of quantification of the assay (9 million units). Therefore, we considered changes in binary results for both anti-spike and anti-nucleocapsid using Bayesian interval censored regression to estimate the proportion of individuals remaining antibody positive (as opposed to equivocal or negative) at varying times following their maximum antibody result (Supplementary Data).

Ethics

Deidentified data from staff testing were obtained from the Infections in Oxfordshire Research Database (IORD), which has generic Research Ethics Committee, Health Research Authority, and Confidentiality Advisory Group approvals (19/SC/0403, 19/CAG/0144).

RESULTS

A total of 3276 HCWs provided ≥2 samples for serological testing between 23 April and 20 October 2020 (3217 had anti-nucleocapsid results [Table 1], 3123 anti-spike results, 3064 had both) (Figure 1, Supplementary Table 2). For both assays the median (interquartile range [IQR]) [range] number of samples tested was 2 (2–2) [2-8], and time from the first to last sample was 124 (95–144) [3-174] days.
Table 1.

Baseline Cohort Demographics for 3217 HCWs and 452 HCWs With ≥1 Positive SARS-CoV-2 Anti-Nucleocapsid IgG Result and ≥1 Subsequent Follow-up Sample

CharacteristicWhole Cohort, n (%) or Median (IQR) [Range]452 HCWs With a Positive Antibody Result and ≥1 Subsequent Sample, n (%) or Median (IQR) [Range]
Age
 Age, y39 (29–50) [16–76]41 (29–50) [17–69]
Gender
 Female2542 (79)340 (75)
 Male673 (21)112 (25)
 Not disclosed2 (<1)
Self-reported ethnicity
 White2473 (77)302 (67)
 Black90 (3)25 (6)
 Asian440 (14)89 (20)
 Other214 (7)36 (8)
COVID-19-like symptoms between 01 February 2020 and testing
 Yes898 (28)274 (61)
 No2319 (72)178 (39)
Previous positive SARS-CoV-2 PCR
 Symptomatic128 (4)95 (21)
 Asymptomatic117 (4)59 (13)
 None2972 (92)298 (66)

Abbreviations: COVID-19, coronavirus disease 2019; HCW, healthcare worker; IgG; immunoglobulin G; IQR, interquartile range; PCR, polymerase chain reaction; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.

Figure 1.

SARS-CoV-2 antibody trajectory cohorts. Abbreviations: IgG, immunoglobulin G; PCR, polymerase chain reaction; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.

Baseline Cohort Demographics for 3217 HCWs and 452 HCWs With ≥1 Positive SARS-CoV-2 Anti-Nucleocapsid IgG Result and ≥1 Subsequent Follow-up Sample Abbreviations: COVID-19, coronavirus disease 2019; HCW, healthcare worker; IgG; immunoglobulin G; IQR, interquartile range; PCR, polymerase chain reaction; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2. SARS-CoV-2 antibody trajectory cohorts. Abbreviations: IgG, immunoglobulin G; PCR, polymerase chain reaction; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2. Observed IgG antibody trajectories are shown in Figure 2. In sum, 522/3217 (16%) HCWs had ≥1 sample with detected anti-nucleocapsid antibodies (Figure 2A, 2B), and another 90 (3%) had ≥1 sample with an equivocal titer (Figure 2C). Antibody titers in those with consistently negative results were broadly stable (Figure 2D), whereas falls were observed in 438/466 (94%) initially anti-nucleocapsid antibody positive individuals and in 61/83 (73%) with an initial equivocal titer (Figure 2A, 2C). Also, 560/3123 (18%) HCWs had a positive anti-spike IgG (Figure 2E, 2F) and 209 (7%) an equivocal result. Among 457 HCWs with an initially positive anti-spike titer, 362 (79%) had a final titer that remained above the upper limit of quantification, and 49 (11%) had a fall in titer (Figure 2E).
Figure 2.

SARS-CoV-2 anti-nucleocapsid (A–D) and anti-spike (E–H) IgG antibody trajectories. Panels A and B show anti-nucleocapsid trajectories for HCWs with a positive result (≥1.40 arbitrary units) at some time. A, Those whose first measurement was positive (n = 466, only data from 100 randomly sampled individuals is shown to assist visualization). B, Remainder (n = 56) in whom seroconversion was observed. C, Those with a maximum titer that was equivocal (0.50–1.39, n = 90). D, Results from HCWs with a maximum titer that was negative (<0.50, n = 2605, 100 randomly sampled individuals are shown). Dashed and dotted lines indicate the thresholds for a positive and equivocal result; note the different y-axis scales in panels A and B vs panels C and D. Similarly, panels E–H show anti-spike trajectories in million net normalized units for individuals who start positive (≥8 million units, n = 457), seroconvert (n = 103), have a maximum equivocal result (4.0–7.9 million units, n = 209, 100 shown), and only negative results (<4 million units, n = 2354, 100 shown). Anti-spike assay values above the upper limited of quantification, ie, >9 million, are plotted as 9 million. Abbreviations: HCW, healthcare worker; IgG, immunoglobulin G; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.

SARS-CoV-2 anti-nucleocapsid (A–D) and anti-spike (E–H) IgG antibody trajectories. Panels A and B show anti-nucleocapsid trajectories for HCWs with a positive result (≥1.40 arbitrary units) at some time. A, Those whose first measurement was positive (n = 466, only data from 100 randomly sampled individuals is shown to assist visualization). B, Remainder (n = 56) in whom seroconversion was observed. C, Those with a maximum titer that was equivocal (0.50–1.39, n = 90). D, Results from HCWs with a maximum titer that was negative (<0.50, n = 2605, 100 randomly sampled individuals are shown). Dashed and dotted lines indicate the thresholds for a positive and equivocal result; note the different y-axis scales in panels A and B vs panels C and D. Similarly, panels E–H show anti-spike trajectories in million net normalized units for individuals who start positive (≥8 million units, n = 457), seroconvert (n = 103), have a maximum equivocal result (4.0–7.9 million units, n = 209, 100 shown), and only negative results (<4 million units, n = 2354, 100 shown). Anti-spike assay values above the upper limited of quantification, ie, >9 million, are plotted as 9 million. Abbreviations: HCW, healthcare worker; IgG, immunoglobulin G; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.

Anti-Nucleocapsid IgG Trajectories After a Positive Antibody Result

Among 522 individuals with ≥1 anti-nucleocapsid IgG-positive sample, 70 (13%) seroconverted with rising titers only and so were excluded from analyses of the duration of response following a peak IgG result (39/70 had a PCR test and are included in a separate analysis below). In the remaining 452 (87%), the median (IQR) [range] number of samples tested was 2 (2–3) [2-5], and time from the first to last sample was 121 (83–143) [4-171] days. Only 3/120 (3%) of individuals with ≥3 measurements had a final titer above the minimum observed; that is, potential evidence of boosting and titer increases were all <5%. The median (IQR) age was 41 (29–50) years, and 75% of participants were female (Table 1). The most common self-reported ethnic groups were White (302, 67%) and Asian (89, 20%; predominately south Asian and Filipino). In addition, 274 (61%) recalled self-identified COVID-19-like symptoms between 1 February 2020 and testing; 95 (21%) had a positive SARS-CoV-2 PCR following symptomatic testing, and 59 (13%) a positive PCR during asymptomatic screening. It is likely that many of the remainder were infected prior to widespread availability of testing. The first positive PCR in each individual was prior to or on the day of their maximum antibody titer in all but 5/154 (3%, tested 3–17 days later). Using a Bayesian statistical model, the trajectory of anti-nucleocapsid IgG levels following the maximum measured titer in each individual is shown in Figure 3A. The estimated mean antibody half-life was 85 (95% CrI 81–90) days and estimated mean maximum antibody level 4.3 (95% CrI 4.1–4.4) arbitrary units. The mean trajectory crossed the diagnostic threshold of 1.40, switching from a positive to equivocal result at 137 (95% CrI 127–148) days. IgG half-lives and maximum titers varied between individuals (Figure 3B, 3C). Higher maximum observed anti-nucleocapsid levels correlated with longer IgG half-lives, that is, slower rates of decline over time (Figure 3D; Spearman rank R2 = .65, P < .0001). Findings were similar in a sensitivity analysis investigating the impact of starting with each individual’s maximum result on half-life estimates (see Supplementary Data).
Figure 3.

SARS-CoV-2 anti-nucleocapsid IgG antibody trajectories in 452 SARS-CoV-2 seropositive HCWs. A, Overall mean trajectory of anti-nucleocapsid IgG antibody levels from the maximum observed level (ie, model fixed effect). Posterior mean and 95% CrI are shown as a solid line and shaded area. Dashed line represents the diagnostic threshold of 1.40 arbitrary units. B, Estimated anti-nucleocapsid IgG half-life with 95% CrI by days for all participants, ranked by its value. Solid horizontal line indicates the overall mean. CrIs exceeding 500 days are truncated at 500 days. C, Estimated maximum anti-nucleocapsid IgG antibody level with 95% CrI for all participants, ranked by its value. Solid horizontal line indicates the overall mean. D, Comparison of maximum observed anti-nucleocapsid IgG antibody level and the estimated anti-nucleocapsid IgG half-life per individual. Abbreviations: CrI, credibility interval; HCW, healthcare worker; IgG, immunoglobulin G; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.

SARS-CoV-2 anti-nucleocapsid IgG antibody trajectories in 452 SARS-CoV-2 seropositive HCWs. A, Overall mean trajectory of anti-nucleocapsid IgG antibody levels from the maximum observed level (ie, model fixed effect). Posterior mean and 95% CrI are shown as a solid line and shaded area. Dashed line represents the diagnostic threshold of 1.40 arbitrary units. B, Estimated anti-nucleocapsid IgG half-life with 95% CrI by days for all participants, ranked by its value. Solid horizontal line indicates the overall mean. CrIs exceeding 500 days are truncated at 500 days. C, Estimated maximum anti-nucleocapsid IgG antibody level with 95% CrI for all participants, ranked by its value. Solid horizontal line indicates the overall mean. D, Comparison of maximum observed anti-nucleocapsid IgG antibody level and the estimated anti-nucleocapsid IgG half-life per individual. Abbreviations: CrI, credibility interval; HCW, healthcare worker; IgG, immunoglobulin G; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.

Effect of Demographics and Other Covariates on Anti-Nucleocapsid Trajectories

Within this cohort of HCWs of working age, age, self-reported ethnicity, prior symptoms compatible with COVID-19, and a positive SARS-CoV-2 PCR were independently associated with changes in anti-nucleocapsid trajectories (Table 2, Supplementary Figure 1–5, Supplementary Table 3). Increasing age was independently associated with higher maximum anti-nucleocapsid levels and a longer half-life, .17 (95% CrI .07–.25) arbitrary units and 3.40 (1.79–4.62) days per 10 years, respectively (Table 2, Supplementary Figure 5). HCWs of Asian ethnicity had higher maximum anti-nucleocapsid levels with adjusted increases of 0.54 (0.18–0.95) arbitrary units compared to White HCWs, with marginal evidence for longer half-lives, by 6.28 (−0.44 to 14.8) days. Within the limits of the power of the study, there was no strong statistical evidence that antibody trajectories varied in other ethnic groups.
Table 2.

Univariable and Multivariable Models of Determinants of SARS-CoV-2 Anti-Nucleocapsid Antibody Trajectories

Univariable ModelMultivariable Model
Posterior Mean95% CrIPosterior Mean95% CrI
Baseline modelMaximum antibody level (intercept)4.264.074.443.333.023.67
Antibody level half-life85.3881.1790.0169.9463.7477.19
Gender modelMaximum antibody level (intercept): Female4.244.044.46
Antibody level half-life: Female84.8880.1490.25
Change in intercept: Male.03−.40.47−.05−.34.25
Change in half-life: Male1.95−8.2613.12−.40−5.665.30
Age modelMaximum antibody level (intercept): 41 years (median)3.823.564.10
Antibody level half-life: 41 years (median)75.2769.7181.46
Change in intercept: per 10-year older.21.10.30.17.07.25
Change in half-life: per 10-year older4.072.525.173.401.794.62
Ethnicity modelMaximum antibody level (intercept): White4.033.824.24
Antibody level half-life: White81.4876.6986.66
Change in intercept: Black.48−.301.37.37−.211.03
Change in intercept: Asian.83.321.34.54.18.95
Change in intercept: Other.59−.101.37.44−.071.00
Change in half-life: Black7.03−11.4131.132.63−6.9215.03
Change in half-life: Asian14.641.5429.296.28−.4414.76
Change in half-life: Other14.85−3.1238.268.24−1.1320.55
Prior symptom modelMaximum antibody level (intercept): No3.903.644.16
Antibody level half-life: No83.5777.3890.61
Change in intercept: Yes.60.24.96.40.12.69
Change in half-life: Yes2.85−5.9911.59.26−4.525.19
PCR modelMaximum antibody level (intercept): No4.093.874.32
Antibody level half-life: No80.2375.4885.28
Change in intercept: Positive (symptomatic).65.171.16.30−.04.67
Change in intercept: Positive (asymptomatic).23−.31.81.14−.24.55
Change in half-life: Positive (symptomatic)19.607.2235.669.562.3519.09
Change in half-life: Positive (asymptomatic)13.49−.3130.376.45−.8615.85

Posterior mean and 95% credibility intervals for the maximum antibody level (model intercept) and antibody half-life (model slope) are shown. See Supplementary Table 3 for other model parameters and statistical analysis quality metrics.

Abbreviations: CrI, credibility interval; PCR, polymerase chain reaction; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.

Univariable and Multivariable Models of Determinants of SARS-CoV-2 Anti-Nucleocapsid Antibody Trajectories Posterior mean and 95% credibility intervals for the maximum antibody level (model intercept) and antibody half-life (model slope) are shown. See Supplementary Table 3 for other model parameters and statistical analysis quality metrics. Abbreviations: CrI, credibility interval; PCR, polymerase chain reaction; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2. Prior self-reported symptoms were associated with a higher starting maximum anti-nucleocapsid levels (adjusted increase .40 [95% CrI .12–.69]) but not changes in half-lives. There was moderate evidence that a positive PCR result undertaken for symptoms, independently increased the starting maximum level by .30 (−.04 to .67) arbitrary units, and half-life by 9.56 (2.35–19.09) days compared to those with no positive PCR. We observed no effect of gender on either maximum level or antibody half-life.

Anti-Nucleocapsid Trajectories Following a Positive PCR Test

In total, 245 of the 3217 HCWs with ≥2 anti-nucleocapsid samples had a positive PCR test. And 114/128 (89%) symptomatic HCW seroconverted (maximum IgG titer ≥1.40), including 11/12 (92%) who required hospital treatment, all other infections were mild. 79/117 (68%) identified through asymptomatic screening seroconverted. In the 52 individuals not showing evidence of seroconversion, all but 1 (98%) had ≥1 antibody test ≥14 days after their PCR-positive test, and in 29 (56%) this was before 90 days. PCR cycle threshold values were lower in individuals who seroconverted (Supplementary Table 4). Data from PCR-positive individuals who seroconverted were used to model antibody trajectories relative to a first positive PCR test. Antibody levels rose to a peak at 24 (95% CrI 19–31) days post-first positive PCR test, before beginning to fall (Supplementary Figure 6). Comparing with the antibody trajectory estimated in the main analysis, the estimated rates of waning were consistent between the 2 models. Antibody trajectories were similar in those being tested following symptoms or during asymptomatic screening (Figure 4).
Figure 4.

Comparison of SARS-CoV-2 anti-nucleocapsid IgG antibody levels following a positive PCR test and the maximum IgG level per individual in those with a positive PCR test. A, Those with a positive PCR undertaken for symptoms; B, those with a positive PCR for asymptomatic screening. The x-axis value for the model starting from the maximum IgG level is aligned to the maximum point from the model starting with a positive PCR test. Model starting from a positive PCR is fitted with a 5-knot spline (3 interior knots at t = 10, t = 30, and t = 50, locations chosen based on model fit). Abbreviations: IgG, immunoglobulin G; PCR, polymerase chain reaction; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.

Comparison of SARS-CoV-2 anti-nucleocapsid IgG antibody levels following a positive PCR test and the maximum IgG level per individual in those with a positive PCR test. A, Those with a positive PCR undertaken for symptoms; B, those with a positive PCR for asymptomatic screening. The x-axis value for the model starting from the maximum IgG level is aligned to the maximum point from the model starting with a positive PCR test. Model starting from a positive PCR is fitted with a 5-knot spline (3 interior knots at t = 10, t = 30, and t = 50, locations chosen based on model fit). Abbreviations: IgG, immunoglobulin G; PCR, polymerase chain reaction; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.

Anti-Spike Trajectories

To enable comparison with anti-spike results and to facilitate comparison with studies reporting only categorical antibody results, we considered the proportion of seropositive individuals remaining antibody-positive (as opposed to equivocal or negative) when observed at varying time intervals (Figure 5A, 5C) and using an interval censored survival analysis approach (Figure 5B, 5D). Consistent with the model in Figure 4, the median time remaining anti-nucleocapsid IgG-positive was 166 (95% CrI 139–214) days. In contrast, anti-spike IgG levels remained above positive threshold in most seropositive HCWs for the duration of the study (Figure 5C, 5D), by 180 days post maximum anti-spike IgG level an estimated 94% (95% CrI 91–96%) remained positive.
Figure 5.

Proportion of HCWs remaining anti-nucleocapsid IgG (A–B) and anti-spike IgG (C–D) antibody positive by days following their maximum antibody level. Panels A and C show the observed proportion in 30-day intervals with binomial 95% confidence intervals. Number of individuals tested and the number of individuals remaining antibody positive is shown at the base of each bar. Panels B and D show the results of Bayesian interval censored survival analyses, the posterior mean and 95% credibility interval are shown. Abbreviations: HCW, healthcare worker; IgG, immunoglobulin G; PCR, polymerase chain reaction.

Proportion of HCWs remaining anti-nucleocapsid IgG (A–B) and anti-spike IgG (C–D) antibody positive by days following their maximum antibody level. Panels A and C show the observed proportion in 30-day intervals with binomial 95% confidence intervals. Number of individuals tested and the number of individuals remaining antibody positive is shown at the base of each bar. Panels B and D show the results of Bayesian interval censored survival analyses, the posterior mean and 95% credibility interval are shown. Abbreviations: HCW, healthcare worker; IgG, immunoglobulin G; PCR, polymerase chain reaction.

DISCUSSION

Most epidemiological outbreak models assume that SARS-CoV-2 infection leads to the development of postinfection immunity for a defined duration. Here we show contrasting antibody trajectories in 608 symptomatic and asymptomatic HCWs seropositive for anti-nucleocapsid and/or anti-spike antibodies followed for a median of 4 months from their maximum IgG titer. We show anti-nucleocapsid IgG levels wane with an estimated half-life of 85 (95% CrI 81–90) days. We observed variation between individuals; higher maximum observed anti-nucleocapsid titers were associated with longer half-lives. Increasing age, Asian ethnicity, and prior self-reported symptoms were independently associated with higher maximum anti-nucleocapsid levels, and increasing age and a positive PCR test undertaken for symptoms with longer antibody half-lives. In contrast, although we could not quantitively follow titers of anti-spike IgG, levels remained stably above the threshold for a positive result in 94% at 180 days post maximum titer. IgG waning and reinfection within a year is reported for seasonal coronaviruses [17], whereas IgG remains detectable against SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV) 1–3 years later [18]. The differences we observe in SARS-CoV-2 antibody trajectories may be antigen and/or assay dependent; for example, stable anti-spike antibodies with waning of anti-nucleocapsid IgG using the same Abbott platform as in our study was also seen in an earlier smaller study, but total anti-nucleocapsid antibodies assayed using a Roche platform remained stable [14]. To some extent these findings are conditional on assay cutoffs which can be tuned to prioritise sensitivity or specificity, with inherently more specific assays having potential to also be set more sensitively, resulting in apparently longer durations of detectable antibody responses. For anti-nucleocapsid, we observe higher IgG titers with longer durability occurring after symptomatic PCR-positive infection, consistent with data from Long et al, where 40% of asymptomatic individuals and 13% of the symptomatic group became negative for IgG in the early convalescent phase [19] and consistent with emerging coronaviruses, where antibody titers remained detectable longer after more severe illness [18], waning more rapidly after asymptomatic infection. Relatively short-term anti-nucleocapsid IgG responses have 2 epidemiological consequences. First, antibody waning may lead to under-ascertainment of previous infections within the current pandemic, particularly in younger individuals following asymptomatic/mild infection. Additionally, IgG testing is unlikely to determine whether SARS-CoV-2 has circulated historically, for example, in a particular geographic region. Older age (within this cohort of working age HCWs, up to 69 years) was associated with higher maximum observed anti-nucleocapsid IgG titers and longer half-lives, with similar findings associated with Asian ethnicity (many of the Asian HCWs in our study came to work in the UK healthcare system as adults). It is possible to hypothesize that this could arise from boosting of cross-reactive anti-nucleocapsid antibodies from prior exposure, for example, to a previously circulating or geographically restricted human coronavirus. However, anti-nucleocapsid cross-reactivity between endemic coronaviruses and other epidemic coronaviruses, SARS-CoV and MERS-CoV, is uncommon [18, 20].

Limitations

The assays we used could only measure quantitative trajectories for anti-nucleocapsid IgG, further studies, for example, using multiple serum dilutions, are required to quantify anti-spike IgG over time. We therefore cannot say whether the longer duration of positive anti-spike responses is due to slower waning or higher initial levels relative to assay cut-offs. Another limitation of our study was that our cohort of individuals consisted of adults of working age (17–69 years); further longitudinal studies will be required to investigate younger and older age groups. The small numbers of self-reported Black (n = 25) and other (n = 36) ethnicities reduced/limited power to detect an association between these ethnicities and antibody trajectories. We also do not account for mediators, for example, socioeconomic inequalities, that may link ethnicity to antibody responses in the absence of a direct causal relationship. Due to many of our staff developing symptoms before widespread SARS-CoV-2 PCR testing was available, only 34% of the anti-nucleocapsid-positive cohort had a documented positive PCR, and as a proportion of the cohort were asymptomatic throughout, we modeled time from maximum positive antibody test rather than time from first positive PCR or time from symptom onset in our main analysis of antibody durability. However, under an exponential assumption, half-lives can be estimated from any measurements taken after a maximum; we excluded individuals with only evidence of rising titers to avoid underestimating half-lives. Furthermore, data from those that were PCR positive were consistent with this analysis (Figure 4). Multiple different assays are in use globally to characterize antibody responses to SARS-CoV-2. Here we study only 2; however, other antibody classes and targets, and aspects of immunity, including the innate and cellular responses, are important in conferring postinfection immunity [21]. When comparing longitudinal studies of antibody durability, care must be taken, as the various assays have not yet been cross-calibrated, and implications for protective immunity are not fully understood.

Implications

It is widely recognized that pathogen-specific IgG levels decline after the acute phase of an infection. After the initial humoral response in which short-lived plasmablasts secrete high titers of antibody, long-lived plasma cells and memory B cells then contribute to longer-term antibody-mediated protection [22]. Although declines in IgG titers are expected, understanding the assay-dependent rate of decline, whether and when titers fall below assay positive cutoffs, and how these titers relate to protection from subsequent asymptomatic and symptomatic reinfection is crucial. Serological testing also helps quantify the extent of infection in populations, informing epidemiological models and public health strategies. However, waning antibody levels may lead to underestimated exposure due to loss of seropositivity. For example, using the anti-nucleocapsid assay, an estimated 33% of individuals seroreverted (ie, fell below the positive cutoff for the Abbott assay) within 3 months of IgG detection and an estimated 53% of individuals by 6 months (Figure 5B). Therefore, depending on the assay used, seroepidemiological surveys performed several months into this pandemic may have underestimated prior exposure, especially in younger adults who lose detectable antibody faster. Our findings contrast with the repeated cross-sectional REACT2 study [23], which reported greater reductions over time at a population level in the proportion of adults ≥65 years testing antibody-positive and more sustained responses in those 18–24 years. Nearly all HCWs in our study were <65 years; other differences may arise from study design, the assay used, and the potential for new infections predominantly in younger people [24] to replace others who had seroreverted, supporting population-level seroprevalence (in our study each individual was followed up separately).

Future Work

Antibody dynamics have significant implications for the course and management of pandemics. Durability of immunity postinfection and postvaccination will dictate the overall course of the pandemic. Further work is required to determine how prior infection and/or vaccination impacts the probability of future infection and severity of subsequent disease, determine the antibody-based correlates of this protection, and therefore the ability of serological tests to identify those who are immune. Longitudinal cohorts with baseline immunology are required to determine immune correlates of protection, to determine whether measurement of the current antibody status is enough to infer whether an individual have functional immunity or not, whether waning IgG titers are representative of waning immune protection, or whether protection remains even after an individual seroreverts.

CONCLUSION

We demonstrate that the half-life of SARS-CoV-2 anti-nucleocapsid IgG antibody responses in a cohort of adult HCWs is 85 days and varies between individuals by age, ethnicity, and prior symptom history. In contrast, anti-spike IgG responses were sustained in most HCWs up to 180 days. The extent and duration of immunity to SARS-CoV-2 infection following COVID-19 and its association with antibody titers remains a key question to be answered.

Supplementary Data

Supplementary materials are available at Clinical Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author. Click here for additional data file. Click here for additional data file.
  20 in total

1.  Clinical and immunological assessment of asymptomatic SARS-CoV-2 infections.

Authors:  Quan-Xin Long; Xiao-Jun Tang; Qiu-Lin Shi; Qin Li; Hai-Jun Deng; Jun Yuan; Jie-Li Hu; Wei Xu; Yong Zhang; Fa-Jin Lv; Kun Su; Fan Zhang; Jiang Gong; Bo Wu; Xia-Mao Liu; Jin-Jing Li; Jing-Fu Qiu; Juan Chen; Ai-Long Huang
Journal:  Nat Med       Date:  2020-06-18       Impact factor: 53.440

2.  COVID-19 and the Path to Immunity.

Authors:  David S Stephens; M Juliana McElrath
Journal:  JAMA       Date:  2020-10-06       Impact factor: 56.272

3.  Antibody Detection and Dynamic Characteristics in Patients With Coronavirus Disease 2019.

Authors:  Fei Xiang; Xiaorong Wang; Xinliang He; Zhenghong Peng; Bohan Yang; Jianchu Zhang; Qiong Zhou; Hong Ye; Yanling Ma; Hui Li; Xiaoshan Wei; Pengcheng Cai; Wan-Li Ma
Journal:  Clin Infect Dis       Date:  2020-11-05       Impact factor: 9.079

4.  Longitudinal Monitoring of SARS-CoV-2 IgM and IgG Seropositivity to Detect COVID-19.

Authors:  Raymond T Suhandynata; Melissa A Hoffman; Michael J Kelner; Ronald W McLawhon; Sharon L Reed; Robert L Fitzgerald
Journal:  J Appl Lab Med       Date:  2020-09-01

5.  SARS-CoV-2-IgG response is different in COVID-19 outpatients and asymptomatic contact persons.

Authors:  Nele Wellinghausen; Dietmar Plonné; Meike Voss; Ralitsa Ivanova; Reinhard Frodl; Susanne Deininger
Journal:  J Clin Virol       Date:  2020-07-06       Impact factor: 3.168

6.  Temporal profiles of viral load in posterior oropharyngeal saliva samples and serum antibody responses during infection by SARS-CoV-2: an observational cohort study.

Authors:  Kelvin Kai-Wang To; Owen Tak-Yin Tsang; Wai-Shing Leung; Anthony Raymond Tam; Tak-Chiu Wu; David Christopher Lung; Cyril Chik-Yan Yip; Jian-Piao Cai; Jacky Man-Chun Chan; Thomas Shiu-Hong Chik; Daphne Pui-Ling Lau; Chris Yau-Chung Choi; Lin-Lei Chen; Wan-Mui Chan; Kwok-Hung Chan; Jonathan Daniel Ip; Anthony Chin-Ki Ng; Rosana Wing-Shan Poon; Cui-Ting Luo; Vincent Chi-Chung Cheng; Jasper Fuk-Woo Chan; Ivan Fan-Ngai Hung; Zhiwei Chen; Honglin Chen; Kwok-Yung Yuen
Journal:  Lancet Infect Dis       Date:  2020-03-23       Impact factor: 25.071

7.  Community prevalence of SARS-CoV-2 in England from April to November, 2020: results from the ONS Coronavirus Infection Survey.

Authors:  Koen B Pouwels; Thomas House; Emma Pritchard; Julie V Robotham; Paul J Birrell; Andrew Gelman; Karina-Doris Vihta; Nikola Bowers; Ian Boreham; Heledd Thomas; James Lewis; Iain Bell; John I Bell; John N Newton; Jeremy Farrar; Ian Diamond; Pete Benton; Ann Sarah Walker
Journal:  Lancet Public Health       Date:  2020-12-10

8.  A systematic review of antibody mediated immunity to coronaviruses: kinetics, correlates of protection, and association with severity.

Authors:  Angkana T Huang; Bernardo Garcia-Carreras; Matt D T Hitchings; Bingyi Yang; Leah C Katzelnick; Susan M Rattigan; Brooke A Borgert; Carlos A Moreno; Benjamin D Solomon; Luke Trimmer-Smith; Veronique Etienne; Isabel Rodriguez-Barraquer; Justin Lessler; Henrik Salje; Donald S Burke; Amy Wesolowski; Derek A T Cummings
Journal:  Nat Commun       Date:  2020-09-17       Impact factor: 14.919

9.  Humoral Immune Response to SARS-CoV-2 in Iceland.

Authors:  Daniel F Gudbjartsson; Gudmundur L Norddahl; Pall Melsted; Kristbjorg Gunnarsdottir; Hilma Holm; Elias Eythorsson; Asgeir O Arnthorsson; Dadi Helgason; Kristbjorg Bjarnadottir; Ragnar F Ingvarsson; Brynja Thorsteinsdottir; Steinunn Kristjansdottir; Kolbrun Birgisdottir; Anna M Kristinsdottir; Martin I Sigurdsson; Gudny A Arnadottir; Erna V Ivarsdottir; Margret Andresdottir; Frosti Jonsson; Arna B Agustsdottir; Jonas Berglund; Berglind Eiriksdottir; Run Fridriksdottir; Elisabet E Gardarsdottir; Magnus Gottfredsson; Olafia S Gretarsdottir; Steinunn Gudmundsdottir; Kjartan R Gudmundsson; Thora R Gunnarsdottir; Arnaldur Gylfason; Agnar Helgason; Brynjar O Jensson; Aslaug Jonasdottir; Hakon Jonsson; Thordur Kristjansson; Karl G Kristinsson; Droplaug N Magnusdottir; Olafur T Magnusson; Lovisa B Olafsdottir; Solvi Rognvaldsson; Louise le Roux; Gudrun Sigmundsdottir; Asgeir Sigurdsson; Gardar Sveinbjornsson; Kristin E Sveinsdottir; Maney Sveinsdottir; Emil A Thorarensen; Bjarni Thorbjornsson; Marianna Thordardottir; Jona Saemundsdottir; S Hjortur Kristjansson; Kamilla S Josefsdottir; Gisli Masson; Gudmundur Georgsson; Mar Kristjansson; Alma Moller; Runolfur Palsson; Thorolfur Gudnason; Unnur Thorsteinsdottir; Ingileif Jonsdottir; Patrick Sulem; Kari Stefansson
Journal:  N Engl J Med       Date:  2020-09-01       Impact factor: 91.245

10.  Robust neutralizing antibodies to SARS-CoV-2 infection persist for months.

Authors:  Ania Wajnberg; Fatima Amanat; Adolfo Firpo; Deena R Altman; Mark J Bailey; Mayce Mansour; Meagan McMahon; Philip Meade; Damodara Rao Mendu; Kimberly Muellers; Daniel Stadlbauer; Kimberly Stone; Shirin Strohmeier; Viviana Simon; Judith Aberg; David L Reich; Florian Krammer; Carlos Cordon-Cardo
Journal:  Science       Date:  2020-10-28       Impact factor: 47.728

View more
  101 in total

1.  Longitudinal evaluation of laboratory-based serological assays for SARS-CoV-2 antibody detection.

Authors:  K A Bond; E Williams; S Nicholson; S Lim; D Johnson; B Cox; M Putland; E Gardiner; E Tippett; M Graham; F Mordant; M Catton; S R Lewin; K Subbarao; B P Howden; D A Williamson
Journal:  Pathology       Date:  2021-07-20       Impact factor: 5.306

2.  Prevalence and predictors of anti-SARS-CoV-2 serology in a highly vulnerable population of Rio de Janeiro: A population-based serosurvey.

Authors:  Lara E Coelho; Paula M Luz; Débora C Pires; Emilia M Jalil; Hugo Perazzo; Thiago S Torres; Sandra W Cardoso; Eduardo M Peixoto; Sandro Nazer; Eduardo Massad; Mariângela F Silveira; Fernando C Barros; Ana T R Vasconcelos; Carlos A M Costa; Rodrigo T Amancio; Daniel A M Villela; Tiago Pereira; Guilherme T Goedert; Cleber V B D Santos; Nadia C P Rodrigues; Beatriz Grinsztejn; Valdilea G Veloso; Claudio J Struchiner
Journal:  Lancet Reg Health Am       Date:  2022-07-30

3.  Longitudinal assessment of SARS-CoV-2 IgG seroconversionamong front-line healthcare workers during the first wave of the Covid-19 pandemic at a tertiary-care hospital in Chile.

Authors:  Mirentxu Iruretagoyena; Macarena R Vial; Maria Spencer-Sandino; Pablo Gaete; Anne Peters; Iris Delgado; Inia Perez; Claudia Calderon; Lorena Porte; Paulette Legarraga; Alicia Anderson; Ximena Aguilera; Pablo Vial; Thomas Weitzel; Jose M Munita
Journal:  BMC Infect Dis       Date:  2021-05-26       Impact factor: 3.090

4.  Disparities of SARS-CoV-2 Nucleoprotein-Specific IgG in Healthcare Workers in East London, UK.

Authors:  Naheed Choudhry; Kate Drysdale; Carla Usai; Dean Leighton; Vinay Sonagara; Ruaridh Buchanan; Manreet Nijjar; Sherine Thomas; Mark Hopkins; Teresa Cutino-Moguel; Upkar S Gill; Graham R Foster; Patrick T Kennedy
Journal:  Front Med (Lausanne)       Date:  2021-04-27

5.  Prevalence of IgG antibodies induced by the SARS-COV-2 virus in asymptomatic adults in Nuevo Leon, Mexico.

Authors:  Edgar P Rodríguez-Vidales; Denise Garza-Carrillo; José J Pérez-Trujillo; Olivia A Robles-Rodríguez; Ana María Salinas-Martínez; Roberto Montes de Oca-Luna; Consuelo Treviño-Garza; Manuel E De la O-Cavazos
Journal:  J Med Virol       Date:  2021-06-16       Impact factor: 20.693

6.  Determinants of IgG antibodies kinetics after severe and critical COVID-19.

Authors:  Julien De Greef; Anaïs Scohy; Francis Zech; Frank Aboubakar; Charles Pilette; Ludovic Gerard; Lucie Pothen; Halil Yildiz; Leïla Belkhir; Jean Cyr Yombi
Journal:  J Med Virol       Date:  2021-05-12       Impact factor: 20.693

7.  kinetics of anti-SARS-CoV-2 antibodies over time. Results of 10 month follow up in over 300 seropositive Health Care Workers.

Authors:  Jose F Varona; Rodrigo Madurga; Francisco Peñalver; Elena Abarca; Cristina Almirall; Marta Cruz; Enrique Ramos; Jose María Castellano-Vazquez
Journal:  Eur J Intern Med       Date:  2021-05-25       Impact factor: 7.749

8.  Quantitative SARS-CoV-2 anti-spike responses to Pfizer-BioNTech and Oxford-AstraZeneca vaccines by previous infection status.

Authors:  David W Eyre; Sheila F Lumley; Jia Wei; Stuart Cox; Tim James; Anita Justice; Gerald Jesuthasan; Denise O'Donnell; Alison Howarth; Stephanie B Hatch; Brian D Marsden; E Yvonne Jones; David I Stuart; Daniel Ebner; Sarah Hoosdally; Derrick W Crook; Tim Ea Peto; Timothy M Walker; Nicole E Stoesser; Philippa C Matthews; Koen B Pouwels; A Sarah Walker; Katie Jeffery
Journal:  Clin Microbiol Infect       Date:  2021-06-07       Impact factor: 8.067

9.  Antibody Responses One Year after Mild SARS-CoV-2 Infection.

Authors:  Pyoeng Gyun Choe; Kye Hyung Kim; Chang Kyung Kang; Hyeon Jeong Suh; EunKyo Kang; Sun Young Lee; Nam Joong Kim; Jongyoun Yi; Wan Beom Park; Myoung Don Oh
Journal:  J Korean Med Sci       Date:  2021-05-31       Impact factor: 2.153

10.  A three-phase population based sero-epidemiological study: Assessing the trend in prevalence of SARS-CoV-2 during COVID-19 pandemic in Jordan.

Authors:  Saverio Bellizzi; Lora Alsawalha; Sami Sheikh Ali; Ghazi Sharkas; Nazeema Muthu; Mahmoud Ghazo; Wail Hayajneh; Maria Cristina Profili; Nathir M Obeidat
Journal:  One Health       Date:  2021-07-10
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.