key: cord-0970543-mcrmcfr6
authors: Pradenas, Edwards; Trinité, Benjamin; Urrea, Víctor; Marfil, Silvia; Ávila-Nieto, Carlos; de la Concepción, María Luisa Rodríguez; Tarrés-Freixas, Ferran; Pérez-Yanes, Silvia; Rovirosa, Carla; Ainsua-Enrich, Erola; Rodon, Jordi; Vergara-Alert, Júlia; Segalés, Joaquim; Guallar, Victor; Valencia, Alfonso; Izquierdo-Useros, Nuria; Paredes, Roger; Mateu, Lourdes; Chamorro, Anna; Massanella, Marta; Carrillo, Jorge; Clotet, Bonaventura; Blanco, Julià
title: Stable neutralizing antibody levels six months after mild and severe COVID-19 episode
date: 2020-11-24
journal: bioRxiv
DOI: 10.1101/2020.11.22.389056
sha: e9283f9a2fafdd6b599cdc209c70f46cda1acbf9
doc_id: 970543
cord_uid: mcrmcfr6

Understanding mid-term kinetics of immunity to SARS-CoV-2 is the cornerstone for public health control of the pandemic and vaccine development. However, current evidence is rather based on limited measurements, thus losing sight of the temporal pattern of these changes1–6. In this longitudinal analysis, conducted on a prospective cohort of COVID-19 patients followed up to 242 days, we found that individuals with mild or asymptomatic infection experienced an insignificant decay in neutralizing activity that persisted six months after symptom onset or diagnosis. Hospitalized individuals showed higher neutralizing titers, which decreased following a two-phase pattern, with an initial rapid decline that significantly slowed after day 80. Despite this initial decay, neutralizing activity at six months remained higher among hospitalized individuals. The slow decline in neutralizing activity at mid-term contrasted with the steep slope of antibody titers change, reinforcing the hypothesis that the quality of immune response evolves over the post-convalescent stage4,5.

Understanding mid-term kinetics of immunity to SARS-CoV-2 is the cornerstone for public health control of the pandemic and vaccine development. However, current evidence is rather based on limited measurements, losing sight of the temporal pattern of these changes [1] [2] [3] [4] [5] [6] . In this longitudinal analysis, conducted on a prospective cohort of COVID-19 patients followed up to 242 days, we found that individuals with mild or asymptomatic infection experienced an insignificant decay in neutralizing activity that persisted six months after symptom onset or diagnosis.

Hospitalized individuals showed higher neutralizing titers, which decreased following a two-phase pattern, with an initial rapid decline that significantly slowed after day 80. Despite this initial decay, neutralizing activity at six months remained higher among hospitalized individuals. The slow decline in neutralizing activity at mid-term contrasted with the steep slope of antibody titers change, reinforcing the hypothesis that the quality of immune response evolves over the post-convalescent stage 4,5 .

Our analysis included 210 patients with RT-PCR-confirmed SARS-CoV-2 infection, recruited during the first and second waves of the COVID-19 epidemic in Catalonia (North-East Spain). Of them, 106 (50.5%) had a mild or asymptomatic infection, and 104 (49.5%) required hospitalization because of respiratory compromise (Table 1) . We collected samples periodically throughout a maximum follow-up period of 242 days ( Figure S1 , Supplementary Information). Most study participants developed a neutralizing humoral response against SARS-CoV-2 HIV-based pseudoviruses, that was confirmed using infectious viruses. However, in line with trends reported elsewhere 2,3 , mildly affected or asymptomatic individuals developed a 10-fold lower maximal neutralization titer than those who required hospitalization when the full dataset was analyzed (p<0.0001, Mann-Whitney test; Fig. 1a ). The higher number of determinations obtained from hospitalized individuals during the acute phase permitted the clear observation of a sharp initial response (Fig. 1b-c) , also reported in previous analyses of the early response [7] [8] [9] [10] [11] . This was visible for individuals recruited during both the first (March-June 2020) and the second (July-October 2020) waves of COVID-19 pandemic in Catalonia. A longitudinal analysis fitted to a four-parameter logistic model of increase defined a 30-day sharpening phase after symptom onset, irrespective of the wave in which hospital admission occurred. Half maximal neutralization activity was achieved on day 10 (95% confidence interval, CI 8-11); 80% maximal response, which corresponded to 3.97 logs (i.e., 9,333 reciprocal dilution), was achieved on day 14 (Fig. 1d ). Based on this finding, we assumed no significant differences between the two waves regarding early neutralizing response and we decided to set day 30 after symptom onset as a starting point for the longitudinal analysis of immune response at the mid-term.

While the early humoral response after SARS-CoV-2 infection has been thoroughly described [7] [8] [9] [10] [11] , current data on the decay of antibody levels beyond the convalescent stage depict a heterogeneous scenario with limited information on the neutralizing activity throughout the follow-up period 1-3 . Various authors have recently suggested more complex kinetics of neutralizing activity decay, with clonotype-, epitope-, or subjectspecific patterns that evolve in terms of potency and resistance to epitope mutations 4, 5, 12 .

The longitudinal modeling of the neutralizing activity at mid-term in our cohort revealed a nearly flat slope (i.e., not significantly different from 0, with half-life 2134 days) in individuals with asymptomatic infection or mild disease (Fig. 2a) . Conversely, the decrease of neutralizing activity in hospitalized individuals showed a two-phase pattern, with a rapid decay (half-life 31 days) until day 80 that slowed down to a flat slope (halflife 753 days) from that time point on (Fig. 2b) . Complementary data on the binding affinity and B-cell clone abundance at the same time points would provide a more comprehensive picture to explain this divergent trend.

However, our findings support the hypothesis of Gaebler et al., who suggested that the accumulation of IgG somatic mutations-and subsequent production of antibodies with increased neutralizing potency-allow the maintenance of neutralizing activity levels, despite the decline in specific antibody titers 5 . Of note, our follow-up period encompassed two waves of the COVID-19 outbreak in our country. Individuals infected during the first wave were likely to be exposed to high viral pressure in their environment, potentially favoring further virus exposure that may also contribute to boosting humoral responses, adding to the mechanism proposed by Gaebler et al 5 .

Our analysis is limited by the reduced sample size, particularly in the mild/asymptomatic subgroup, for which we failed to identify a two-phase pattern decay of neutralizing activity. Despite the limited sample size, the availability of multiple measures along the follow-up period allowed us to provide a longitudinal perspective on neutralizing activity, and antibody titer behavior. This analysis supplements current evidence regarding midterm immunity against SARS-CoV-2, based on two-or three-point measurements [3] [4] [5] . Our longitudinal analysis confirmed the slow decay and mid-term maintenance of neutralizing activity observed in other cohorts with a 5-to-11% prevalence of hospitalized patients 3, 5 .

In this regard, the two-phase behavioral pattern of neutralizing activity observed in hospitalized individuals suggests that the rapid decay reported in previous characterizations 1 might be due to the abundance of individuals in this early phase.

Furthermore, apparent inconsistencies found between the declines of neutralizing activity and IgG titers reinforce the idea proposed by other authors that the behavior of antibody titers may not mirror the neutralizing activity 4 . Taken together, current evidence on immunity to SARS-CoV-2 infection suggests stability of neutralizing activity, pointing towards an optimistic scenario for the establishment of infection-or vaccine-mediated herd immunity. Still, long-term data available on other human coronaviruses show waning of antibodies 1-to-2 years after infection 15, 16 , with uncertainty regarding the immune response behavior in the context of vaccine-mediated immunity 17 . The continuity of our prospective cohort of individuals recovered from SARS-CoV-2 infection will provide novel insights into the long-term kinetics of the immune response.

The study was approved by the Hospital Ethics Committee Board from Hospital Universitari Germans Trias i Pujol, HUGTiP (reference PI-20-122 and PI-20-217) and all participants provided written informed consent before inclusion. 

The humoral response against SARS-CoV-2 was evaluated using an in-house sandwich-ELISA. The following SARS-CoV-2 antigens were purchased from Sino Biological 

Continuous variables were described using medians and the interquartile range (IQR, defined by the 25 th and 75 th percentiles), whereas categorical factors were reported as percentages over available data. Quantitative variables between severity groups were compared using the Mann-Whitney test, and percentages using the chi-squared test.

Kinetics of neutralizing activity and antibody titers were estimated from symptom onset-or serological diagnosis in asymptomatic individuals-and modeled using mixedeffects models and in two steps. First, a 4-parameter logistic function was adjusted for the first 30 days after diagnosis using non-linear mixed models. Mid-term decay was analyzed using a piecewise regression with two decline slopes for data beyond 30 days, with a breakpoint at 80 days. For the latter analysis, linear mixed-effect models with random intercepts and slopes were used, and different breakpoints were tested; the one with the best adjustment was chosen. For the longitudinal analysis of neutralizing activity, patients were grouped into two severity groups according to the WHO progression scale as proposed elsewhere 21 : asymptomatic or mild (levels 1-3), and hospitalized (levels [4] [5] [6] [7] [8] [9] [10] . Differences between the two severity groups were assessed using the likelihood ratio Fig 1. Neutralizing activity among study participants. a, Maximal neutralization titer of 210 individuals recruited, according to disease severity (light and dark blue for mild/asymptomatic and hospitalized individuals, respectively). Boxes show the median and the interquartile range, and bars the 10 th and 90 th percentiles. Distributions were compared using the Mann-Whitney test. Individual values are ranked for comparative purposes. b and c, Longitudinal dot plot of neutralizing activity among hospitalized individuals admitted during the first (b) and second (c) waves of the COVID-19 epidemic in our area; filled (b) and empty (c) blue dots show the early (i.e., 30 days after diagnosis) increasing phase. d, Magnification of the early phase for individuals admitted during the first (filled symbols) and second (empty symbols) waves. No differences between waves were observed. The solid line shows the non-linear fit (mixed-model estimate) for the whole dataset (125 samples, 55 individuals analyzed). Two samples from late seroconverters (one from each wave, grey dots) were excluded from the analysis. Figure 1a ; Mann-Whitney test for comparative analysis) and modeled data as dotted lines (likelihood ratio test for comparative analysis). d, Frequency of long-term neutralizers (i.e., individuals with mean neutralizing activity >250 in the 135-242 days period) in each severity subgroup (Chi square test p value is shown). anti-S2. c, anti-nucleoprotein. d, overall neutralizing activity in the same set of samples. All analyses were performed on a subset of individuals with largest follow-up (n=14 for mild/asymptomatic in light blue and n=14 for hospitalized in dark blue; total no. of samples 94). Solid orange lines show the linear mixed model estimate for the period beyond day 30. Kinetics of antibody decay (panels a-c) were calculated excluding timepoints preceding the maximal values for each patient. Kinetics of neutralizing antibodies excluded samples preceding day 30 (as in Fig 2a/b ). All excluded values are shown but grayed out. 

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