key: cord-0932918-k67208js
authors: Mallon, P W G; Tinago, W; Garcia Leon, A; McCann, K; Kenny, G; McGettrick, P; Green, S; Inzitari, R; Cotter, A G; Feeney, E R; Savinelli, S; Doran, P
title: Dynamic change and clinical relevance of post-infectious SARS-CoV-2 antibody responses
date: 2021-03-26
journal: Open Forum Infect Dis
DOI: 10.1093/ofid/ofab122
sha: d155e80499d46773c493705155557cb2bddc02fa
doc_id: 932918
cord_uid: k67208js

BACKGROUND: Although reports suggest that most individuals with COVID-19 develop detectable antibodies post infection, the kinetics, durability, and relative differences between IgM and IgG responses beyond the first few weeks after symptom onset remain poorly understood. METHODS: Within a large, well-phenotyped, diverse, prospective cohort of subjects with and without SARS-CoV-2 PCR-confirmed infection and historical controls derived from cohorts with high prevalence of viral coinfections and samples taken during prior flu seasons, we measured SARS-CoV-2 serological responses (both IgG and IgM) using commercially available assays. We calculated sensitivity and specificity, relationship with disease severity and mapped the kinetics of antibody responses over time using generalised additive models. RESULTS: We analysed 1,001 samples from 752 subjects, 327 with confirmed SARS-CoV-2 (29.7% with severe disease) spanning a period of 90 days from symptom onset. Sensitivity was lower (44.1-47.1%) early (<10 days) after symptom onset but increased to >80% after 10 days. IgM positivity increased earlier than IgG-targeted assays but positivity peaked between day 32 and 38 post onset of symptoms and declined thereafter, a dynamic that was confirmed when antibody levels were analysed, with more rapid decline observed with IgM. Early (<10 days) IgM but not IgG levels were significantly higher in those who subsequently developed severe disease (signal / cut-off 4.20 (0.75-17.93) versus 1.07 (0.21-5.46), P=0.048). CONCLUSIONS: This study suggests that post-infectious antibody responses in those with confirmed COVID-19 begin to decline relatively early post infection and suggests a potential role for higher IgM levels early in infection predicting subsequent disease severity

A c c e p t e d M a n u s c r i p t 4

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of COVID-19 was first identified in December 2019 in Wuhan, China before rapidly becoming pandemic. Over and above the significant proportion of asymptomatic cases, the majority of symptomatic COVID-19 cases are mild. However, up to 20% of infections progress to severe disease, as classified by the World Health Organisation (WHO),[1] with comorbidities, male sex and older age associated with poorer outcomes. [2] It remains unclear to what extent infection with SARS-CoV-2 confers post-infectious immunity, either through humoral (antibody-mediated) or cellular (T-cell mediated) mechanisms.

Emerging data suggest that many individuals, particularly with severe COVID-19, mount detectable anti-SARS-CoV-2 IgG responses within two weeks after infection, [3] with many factors influencing antibody responses including age, disease severity and time from onset of symptoms, with variable intensity and durability of serologic responses reported. [4, 5] Serology plays important roles in the diagnosis of many infections, both at an individual and population level, with early IgM responses used to detect recent infections and more persistent memory IgG responses used to estimate seroprevalence. However, given the uncertainties surrounding development and persistence of antibody responses to SARS-CoV-2, [6] the role of serology in diagnosis or surveillance of COVID-19 remains to be fully clarified.

A number of commercial anti-SARS-CoV-2 serological assays report high sensitivity and specificity.

However, their validation in real-world settings, taking into account the range of factors that affect serologic responses, including cross-reactivity against other chronic infections, has been limited. [7] A c c e p t e d M a n u s c r i p t 5 Although several studies have compared commercially available serological assays in COVID-19, many have small sample sizes [8] or lack non-SARS-CoV-2 infected controls. [7, 9] Additionally, inclusion of uninfected controls defined as not detected on SARS-CoV-2 PCR [10] raises the potential for false positive antibody tests to be misinterpreted in those with previous infection, particularly where detailed clinical information is lacking. Many other studies either have limited data on disease severity [11, 12] , or have over-representation of hospitalized patients with severe disease. In one systematic review only 4 of 40 studies included non-hospitalised patients, [13] which limits the generalisability of some observations, such as associations between higher antibody titres and disease severity. [14] In one of the largest studies to date, analysing 976 pre-pandemic blood samples and 536 blood samples from patients with SARS-CoV-2 infection, severity data was only available for 29%.

[15] Lastly, although SARS-CoV-2 serological responses are dynamic, not all studies either report or account for time since symptom onset; in a recent Cochrane systematic review, 19

of 57 included studies did not stratify by time since symptom onset. [16] The same review found very little data beyond 35 days post onset of symptoms.

To address these data gaps, we aimed to compare several different commercial SARS-CoV-2 serological assays in demographically, clinically diverse and well phenotyped clinical cohorts, to define the dynamic change in qualitative and quantitative antibody responses over time since symptom onset, and delineate the relative role of IgM versus IgG antibodies in relation to onset and severity of infection in clinical samples from individuals with and without COVID-19 infection.

A c c e p t e d M a n u s c r i p t between the 26th of March 2020 and the 10th of July 2020 with available biobanked samples. In addition, as controls, we included subjects with plasma samples biobanked prior to 2020 from the AIID Cohort and another longitudinal study of subjects with and without HIV infection, [17] including samples specifically taken during previous flu seasons from 2016 to 2019, as outlined in national statistics. [18, 19] 

All subjects provide written, informed consent and the study was reviewed and approved in line with A c c e p t e d M a n u s c r i p t 8

Continuous and categorical variables are summarised using median with interquartile range (IQR) and frequency/percentage respectively. Sensitivity and specificity along with their binomial exact 95% confidence intervals (CI) were used to describe the performance characteristics of the assays.

Sensitivity was calculated based on samples from subjects who tested detected on SARS-CoV-2 PCR (SARS-CoV-2 Pos). Specificity was derived for two distinct groups (i) samples from subjects who presented for hospital care during the 2020 pandemic but who tested 'not detected' on SARS-CoV-2 PCR (SARS-CoV-2 Neg) and (ii) historical controls-subjects (Controls Pre-2020) that included subjects with and without chronic infections such as HIV and hepatitis C as well as subjects with biobanked serum samples taken during prior flu seasons between 2016 and 2019.

Within the SARS-CoV-2 Pos group, assay sensitivity was also evaluated at different time periods after date of symptom onset; 0-10, 11-21, 21-42 and >42 days. We used scatter plots with superimposed curves fitted using generalised additive mixed models (GAMM), with either a Gaussian or binomial link function and time since symptom onset fitted as a spline, to depict the non-linear relationship between time from symptom onset with either (i) quantitative antibody levels or (ii) seropositivity rate as dependent variables respectively. GAMM models were fitted using the mgcv package in R and incorporated individual participants as a random effect and also included an autocorrelation error structure. We compared quantitative antibody responses (COI for Elecsys or S/CO for Abbott IgG and IgM assays, referred to as antibody 'levels') and positivity rate for the first two time periods post symptoms onset (0-10 and 11-21 days) between subjects categorised into severe and nonsevere maximal disease stage attained using the Wilcoxon rank sum test and the chi-square test respectively.

A c c e p t e d M a n u s c r i p t 9 Overall sensitivity and specificity were compared between assays using the McNemar's chi-square test as previously described. [20, 21] . Overall concordance between the assays was evaluated using the Cohen's Kappa and percentage agreement. Cross-reactivity was assessed in the Controls Pre-2020 group in samples from subjects with and without known chronic viral infections (HIV, hepatitis C or B) and samples from the 2016-2019 flu seasons. All analyses were conducted using Stata 15 (College Station, Tx) and R version 4.0.2.

A total of 752 subjects provided 1,001 samples for analysis. The (Table 1) . Compared to the SARS-CoV-2 Neg group, the SARS-CoV-2 Pos group were more likely to be diabetic, have an underlying malignancy and less likely to smoke. Although the majority of the SARS-CoV-2 Pos and SARS-CoV-2 Neg groups were admitted to hospital (71.8% and A c c e p t e d M a n u s c r i p t 10 79.9% respectively), within the SARS-CoV-2 Pos group, most (58%) experienced only mild disease, 12% moderate and 30% severe disease severity respectively.

Overall, the sensitivity for all four assays was relatively low, ranging from 74.3% to 77.1% (Table 2) , with no significant difference in sensitivity between assays (Supplementary table 1). In contrast, all three IgG-targeted assays and the IgM assay were highly specific, ranging from 92.7% to 100% ( Table 2 ).

The sensitivity of the three IgG-targeted assays increased considerably with time after onset of COVID-19 symptoms; 44.1% to 47.1% in samples collected ≤10 days post symptom onset increasing to a maximum sensitivity ranging from 86.5% to 90.5% in samples collected at >42 days post symptom onset, with no significant differences between the three assay ( Figure 1, Table 3 ). In contrast, the Abbott IgM assay sensitivity increased from a low of 57.6% in the early (≤10 days) period to a high of 89.0% at 11-21 days post symptom onset, but notably decline to 68.5% >42 days post symptom onset (Figure 1 ). 

Within the SARS-CoV-2 Neg group, 9 (4.02% overall) returned a positive result on the Elecsys assay, of which 8 (3.57% overall) were also positive on both Abbott IgG assays. Detailed clinical review of these 9 subjects revealed that the majority had a clinical presentation suggestive of COVID-19 despite having a negative SARS-CoV-2 PCR; six presented with an influenza-like illness, two with a systemic inflammatory response, four had history of close contact with a confirmed COVID-19 case and one was diagnosed with a viral myocarditis (Supplementary table 4 Although overall assay sensitivity for all four assays was less than 80%, sensitivity was lower early after symptom onset and increased to levels consistently above 80% after day 11 and maintained beyond day 42 for all but the Abbott IgM assay, which decreased notably after day 42 to 68.5% (Table 3) . These data are in keeping with previous studies and metanalyses that demonstrated lower assay sensitivity early after onset of symptoms [7, 11, 13, 16] and other studies that demonstrated high sensitivity in samples taken more than 2 weeks after symptom onset. [9, 15] Data on IgM responses are lacking and limited to relatively small studies, [4, 22] with one study (N=74) showing overall sensitivity of 70% in samples taken at least three weeks post exposure to SARS-CoV-2, [4] similar to that seen in the later time periods of our analysis (>42 days) when the proportion with positive IgM was notably reduced.

To our knowledge this is the first study to map dynamic changes in antibody levels against date of symptom onset within a large, diverse cohort. Consistent across all three IgG-targeted assays, A c c e p t e d M a n u s c r i p t 14 antibody levels peaked just over five weeks after symptom onset and decreased thereafter. The dynamics of IgM titres followed an earlier peak and more rapid subsequent decline, which is biologically plausible. The declines in antibody levels observed across all assays support earlier data from a small cohort that demonstrated loss of both antibody levels and neutralising antibody responses in the early convalescent period [4] and suggest the potential for waning of post-infectious immune responses that may explain the recent increase in reported reinfections with SARS-CoV-

In our analysis, significantly higher IgM levels early in infection (before day 10), but not levels of the other antibodies tested, were observed in subjects who developed severe COVID-19. This is in contrast to a previous smaller study that showed higher IgG levels (but not IgM) in subjects with severe compared to asymptomatic SARS-CoV-2 infection, however this previous study did not include as heterogeneous a study population as our analysis. Interestingly, the only other study to report on kinetics of IgM and IgG early into infection (N=23, 11 with moderate and 12 with severe infection) also demonstrated higher early IgM but not IgG levels in more severe disease.

[22] These data, confirmed within our large, diverse population suggest a potential role for early measurement of IgM in identifying those presenting with symptoms who are at greater risk of developing severe COVID-19.

Our results add to the body of data showing the high specificity of the serological assays tested. In particular, we showed little cross-reactivity with historical samples from populations with high prevalence of common viral co-infections as well as those taken during previous outbreaks of reported community influenza-like illnesses in Ireland. Of note, when we analysed cases of positive antibody responses in subjects hospitalised but not detected by SARS-CoV-2 PCR we identified a A c c e p t e d M a n u s c r i p t 15 majority that presented with symptoms consistent with COVID-19 where no alternative diagnosis was established. This suggests an additional clinical use for serological testing in aiding clinical diagnosis in these circumstances.

Our study has limitations. The AIID Cohort is a prospective, observational cohort but biobanking is not conducted at set timepoints. This results in a spread of results over time that makes analyses less conventional and potentially more difficult to interpret but does enable modelling over time from subjects with SARS-CoV-2 infection from a variety of sources and can provide insights into pathogenesis that may not be readily apparent from conventional studies with fixed sampling. There were some differences in characteristics between those with and without SARS-CoV-2 in terms of sampling time, reflected in the choice of SARS-CoV-2 negative population from predominantly hospital admitted cases while SARS-CoV-2 positive cases were recruited from both hospital and outpatient clinics. Although we measured serological responses, we do not have data on corresponding functional immunity, important when interpreting the clinical relevance of the observed decline in antibody levels. We chose to model kinetics in all those with positive SARS-CoV-2 infection to provide overall population kinetics in a symptomatic population. However, although the majority of our cohort presented with mild SARS-CoV-2 infection, we did not examine individuals who were asymptomatic but SARS-CoV-2 positive, in which some reports suggest serological responses may be lower again to what we observed [24] . Although we analysed historical samples, we did not have data on confirmed influenza in these subjects nor did we routinely test the SARS-CoV2 Pos and Neg groups for other co-infections. Lastly, we used SARS-CoV-2 diagnosed by PCR as our reference for diagnosis but acknowledge that no test has perfect characteristics as a 'gold standard'.

A c c e p t e d M a n u s c r i p t 16 Despite these limitations, this study, one of the largest and most detailed analyses of the performance and kinetics of anti-SARS-CoV-2 antibody responses, suggests higher, early IgM responses in those who develop more severe COVID-19. The early decline in antibody levels, as early as five weeks post symptom onset, contribute to an increasing concern that post-infectious immunity to SARS-CoV-2 infection may be time limited.

M a n u s c r i p t 

The authors wish to thank all study participants and their families for their participation and support in the conduct of the All Ireland Infectious Diseases Cohort Study. M a n u s c r i p t 26 The proportion of individuals with SARS-CoV-2 PCR-detected diagnosis of COVID-19 with positive antibody responses was higher after 10 days from symptom onset for all assays. Ab; antibody. CI, confidence interval.

Mallon has received honoraria and/or travel grants from Gilead Sciences

Willard Tinago -no conflicts declared

Kathleen McCann -no conflicts declared

Grace Kenny -no conflicts declared

Padraig McGettrick -no conflicts declared

Sandra Green -no conflicts declared

Rosanna Inzitiari -no conflicts declared

Aoife Cotter -no conflicts declared

Stefano Savinelli -no conflicts declared

Eoin R Feeney has received honoraria and/or travel grants from Gilead Sciences

Peter Doran -no conflicts declared. References: 1. WHO. (World Health Organisation) Clinical Management of COVID-19 Interim Guidance

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When measured in all available samples, sensitivity for all assays was lower than specificity. SAR-CoV-2; severe acute respiratory syndrome coronavirus 19. Ab; antibody. CI, confidence interval. * IgM was only measured in the control samples from prior flu-seasons (n=116) and data were available for 150 of 152 samples for each of the other three assays

M a n u s c r i p t 20 We compared antibody levels taken early after symptom onset (<10 days or between 11-22 days) in those who developed severe and non-severe disease. We found higher IgM in those with severe disease (d) an effect not seen with any of the IgG targeted assays (a-c). Log; logarithmic