Article Clinical course impacts early kinetics,magnitude, and amplitude of SARS-CoV-2 neutralizing antibodies beyond 1 year after infection Graphical abstract Authors Edwards Pradenas, Benjamin Trinité, Vı́ctor Urrea, ..., Marta Massanella, Bonaventura Clotet, Julià Blanco Non- Hypothetical reinfection risk Hospitalized according to neutralizing n=190 antibody titers Correspondence neutralizing response jblanco@irsicaixa.es SARS-CoV-2 In brief 100 200 300 400 500 Pradenas and Trinité et al. analyze the Time from symptom onset (days) kinetics of neutralizing antibodies in response to natural SARS-CoV-2 WH1 ALPHA BETA DELTA infection and evaluate the long-term Hospitalized (beyond 1 year) stability and breadth of n=142 the neutralizing response before neutralizing response subsequent vaccination. SARS-CoV-2 100 200 300 400 500 Time from symptom onset (days) Non-neutralizers Low neutralizers High neutralizers Highlights d Long-term persistence (>12 months) of neutralizing antibodies against SARS-CoV-2 d Severity of infection determines the magnitude and quality of neutralizing response d Vaccination boosts neutralizing response to natural infection Pradenas et al., 2022, Cell Reports Medicine 3, 100523 February 15, 2022 ª 2022 The Author(s). https://doi.org/10.1016/j.xcrm.2022.100523 ll ll OPEN ACCESS Article Clinical course impacts early kinetics, magnitude, and amplitude of SARS-CoV-2 neutralizing antibodies beyond 1 year after infection Edwards Pradenas,1,9 Benjamin Trinité,1,9 Vı́ctor Urrea,1 Silvia Marfil,1 Ferran Tarrés-Freixas,1 Raquel Ortiz,1 Carla Rovirosa,1 Jordi Rodon,2 Júlia Vergara-Alert,2 Joaquim Segalés,3,4 Victor Guallar,5,6 Alfonso Valencia,5,6 Nuria Izquierdo-Useros,1 Marc Noguera-Julian,1 Jorge Carrillo,1 Roger Paredes,1,7 Lourdes Mateu,7 Anna Chamorro,7 Ruth Toledo,7 Marta Massanella,1 Bonaventura Clotet,1,7,8 and Julià Blanco1,8,10,* 1IrsiCaixa AIDS Research Institute, Germans Trias i Pujol Research Institute (IGTP), Can Ruti Campus, UAB, Hospital Germans Trias i Pujol, Ctra. de Canyet s/n. 2a Planta Maternal, 08916 Badalona, Catalonia, Spain 2IRTA Centre de Recerca en Sanitat Animal (CReSA, IRTA-UAB), Campus de la UAB, 08193 Bellaterra, Catalonia, Spain 3UAB, Centre de Recerca en Sanitat Animal (IRTA-UAB), Campus de la UAB, 08193 Bellaterra, Catalonia, Spain 4Departament de Sanitat i Anatomia Animals, Facultat de Veterinària, UAB, 08193, Bellaterra, Catalonia, Spain 5Barcelona Supercomputing Center, 08034 Barcelona, Catalonia, Spain 6Catalan Institution for Research and Advanced Studies (ICREA), 08010 Barcelona, Catalonia, Spain 7Infectious Diseases Department, Fight against AIDS Foundation (FLS), Germans Trias i Pujol Hospital, 08916 Badalona, Catalonia, Spain 8University of Vic–Central University of Catalonia (UVic-UCC), 08500 Vic, Catalonia, Spain 9These authors contributed equally 10Lead contact *Correspondence: jblanco@irsicaixa.es https://doi.org/10.1016/j.xcrm.2022.100523 SUMMARY To understand the determinants of long-term immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the concurrent impact of vaccination and emerging variants, we follow a prospective cohort of 332 patients with coronavirus disease 2019 (COVID-19) over more than a year after symptom onset. We evaluate plasma-neutralizing activity using HIV-based pseudoviruses expressing the spike of different SARS-CoV-2 variants and analyze them longitudinally using mixed-effects models. Long- term neutralizing activity is stable beyond 1 year after infection in mild/asymptomatic and hospitalized participants. However, longitudinal models suggest that hospitalized individuals generate both short- and long-lived memory B cells, while the responses of non-hospitalized individuals are dominated by long-lived B cells. In both groups, vaccination boosts responses to natural infection. Long-term (>300 days from infec- tion) responses in unvaccinated participants show a reduced efficacy against beta, but not alpha nor delta, variants. Multivariate analysis identifies the severity of primary infection as an independent determinant of higher magnitude and lower relative cross-neutralization activity of long-term neutralizing responses. INTRODUCTION and epidemiological studies on SARS-CoV-2 indicate that neutralizing antibodies can serve as surrogate markers of pro- Immune responses to severe acute respiratory syndrome coro- tection,5–7 as they do for other viral infections.8,9 navirus 2 (SARS-CoV-2) infection involve an undefined balance Given the relevance of antibodies, the early (1–3 months) and of innate and adaptive pathways1 resulting in the development mid-term (3–12 months) humoral responses after SARS-CoV-2 of a seemingly long-lasting immunological memory.2,3 Although infection have been thoroughly described.10–14 Current data there is a general consensus on the key role of both T and B cells outline a heterogeneous scenario in which infected individuals in the protection against SARS-CoV-2 infection and the develop- generate a wide range of neutralizing antibodies (from no sero- ment of coronavirus disease 2019 (COVID-19), the specific conversion to rapid development of high titers) with no definitive contribution of each arm of the immune system is still unclear.1 association to age, gender, or disease severity.15–17 Various au- Neutralizing antibodies mediate their protective effect by binding thors have also suggested complex kinetics of neutralizing activ- to the spike (S) glycoprotein of SARS-CoV-2 and by blocking ity decay.3,18,19 This is particularly relevant in the current context viral entry into target cells; however, additional effector functions of viral evolution, as several variants of concern (VOCs) have promoting viral clearance or natural killer (NK)-mediated in- shown total or partial resistance to neutralizing antibodies and fected-cell killing seems to be also relevant in SARS-CoV-2 partial resistance to polyclonal humoral responses elicited by and other viral infections.4 Nevertheless, abundant experimental infection or vaccination.20 Cell Reports Medicine 3, 100523, February 15, 2022 ª 2022 The Author(s). 1 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). ll OPEN ACCESS Article Table 1. Characteristics of individuals included in analysis March 20–June 20 July 20–December 20 January 21–March 21 Non-hospitalized Hospita-lized Non-hospitalized Hospitalized Non-hospitalized Hospitalized (n = 128) (n = 84) (n = 43) (n = 36) (n = 19) (n = 22) p value Gender (female), 92 (72) 39 (46) 24 (56) 12 (33) 9 (47) 5 (23) 0.0006a n (%) Age (years), 47 (38–54) 58 (48–67) 43 (33–53) 55 (45–63) 46 (23–52) 56 (49–62) < 0.0001b median (IQR) Severity Asymptomatic, 12 (9) – 7 (16) – 1 (5) – n (%) Mild, n (%) 116 (91) – 36 (84) – 18 (95) – Hospitalized – 31 (37) – 9 (25) – 2 (9) non-severe, n (%) Hospitalized – 41 (49) – 23 (64) – 20 (91) severe, n (%) Hospitalized – 12 (14) – 4 (11) – 0 (0) (intensive care unit), n (%) Samples per 3 (1–3) 3 (2–4) 2 (1–2) 4 (2–4) 1 (1–2) 3 (2–4) participant median (IQR) Last sampling day, 272 (180–360) 311 (115–362) 116 (21–186) 183 (90–208) 47 (17–108) 32 (28–83) median (IQR) Length of follow up, 172 (0–256) 185 (5–266) 75 (0–166) 169 (7–193) 0 (0–80) 26 (16–76) days median (IQR) IQR: IQR (25th and 75th percentiles). a Chi-square test. b Mann-Whiney test. To understand the dynamics of natural responses to infection, total of 212 participants were recruited during the first-wave we focused on the longitudinal analysis of the neutralizing hu- period, 128 of whom had mild or absent symptomatology moral response in a large cohort of mild/asymptomatic and hos- (WHO progression scale21 levels 1–3; non-hospitalized) and 84 pitalized individuals infected by SARS-CoV-2. Our analysis in- of whom required hospitalization (WHO progression scale21 cludes one of the longest follow-up periods (up to 15 months) levels 4–10) with a wide range of severity from non-severe pneu- and shows that the long-term magnitude of neutralization is monia to intensive care unit admission/death (Table 1). Compa- remarkably stable, being boosted by vaccines, and potentially rable proportions of disease severity were observed in patients threatened by VOCs. Clinical severity of primary infection was recruited in the second (n = 79) and third (n = 41) COVID-19 identified as the main factor determining the kinetics, magnitude, waves. In all cases, the hospitalization groups showed older and quality of neutralizing antibodies. age and lower female frequency when compared with non-hos- pitalized groups (mild or asymptomatic; Table 1). RESULTS Longitudinal analysis of neutralization activity Cohort description For comparative purposes, samples from all patients prior to Our cohort included 332 participants with confirmed SARS-CoV- vaccination, irrespective of the infection wave, were assayed 2 infection who were recruited between March 2020 and March for their plasma neutralization capacity of the original isolate 2021 in Catalonia (Northeastern Spain). Participants were group- WH1 sequence in a validated pseudovirus assay.13 Maximal ed according to the epidemiological waves of the SARS-CoV-2 follow-up periods for unvaccinated individuals infected during pandemic in Spain, defined by an early outbreak caused by the first, second, and third waves were 458, 320, and the original 19B strain and the B.½0A variant (D614G) (from 145 days, respectively. In line with previous analyses,15,17 irre- March to June 2020), a second wave dominated by the 20E spective of the infecting virus, hospitalized patients showed a (EU1) variant (from July to December 2020), and a third wave rapid development of neutralizing activity over the first month af- associated with the emergence of the B.1.1.7/20I Alpha variant ter symptom onset and a transient decrease reaching a plateau covering the January to June 2021 period, until the recent intro- (Figures 1B, 1D, and 1F). This was observed only in the first- and duction of the B.1.617.2 delta variant in June 2021 (Figure S1). A second-wave participants due to the limited follow-up of 2 Cell Reports Medicine 3, 100523, February 15, 2022 ll Article OPEN ACCESS NON-HOSPITALIZED HOSPITALIZED Figure 1. Longitudinal analysis of neutral- A B izing activity 100,000 100,000 (A–F) Neutralization titer of 332 individuals according WAVE 1 WAVE 1 (reciprocal dilution) (reciprocal dilution) Neutralization titer Neutralization titer 10,000 10,000 to disease severity (non-hospitalized or hospitalized groups) and date of infection (wave 1: March–June 1,000 1,000 2020, wave 2: July–December 2020, and wave 3: 100 100 January–March 2021). Dots are single de- 10 10 terminations, and lines indicate individual follow up. Dotted lines indicate the upper and lower limits of 0 100 200 300 400 500 0 100 200 300 400 500 the neutralization assay. Time from symptom onset (days) Time from symptom onset (days) (G and H) Longitudinal smoothing-splines mixed- C D effects models for the different groups shown in (A)– 100,000 100,000 (F). Solid lines indicate the best fit, and light areas WAVE 2 WAVE 2 (reciprocal dilution) (reciprocal dilution) Neutralization titer Neutralization titer 10,000 10,000 indicate confidence intervals (CIs). (I) Non-linear models of the full dataset (n = 190 for 1,000 1,000 non-hospitalized and n = 142 for hospitalized 100 100 groups) were analyzed by smoothing-splines mixed- 10 10 effects models (gray and orange narrow lines) or fitted to a non-linear two-phase exponential decay 0 100 200 300 400 500 0 100 200 300 400 500 model (light and dark blue lines). Decay rate con- Time from symptom onset (days) Time from symptom onset (days) stants are described on the right side of the figure. E F 100,000 100,000 WAVE 3 WAVE 3 (reciprocal dilution) (reciprocal dilution) Neutralization titer Neutralization titer 10,000 10,000 1,000 1,000 and long-lived plasma and memory B cells 100 100 and modeled data from all patients to a two-phase exponential decay. The longitu- 10 10 dinal modeling revealed that hospitalized 0 100 200 300 400 500 0 100 200 300 400 500 individuals had a significantly rapid first- Time from symptom onset (days) Time from symptom onset (days) phase decay (half-life of 26 days) and a G H 10,000 NON-HOSPITALIZED 10,000 HOSPITALIZED flat slope in the second phase (half-life of (reciprocal dilution) (reciprocal dilution) Neutralization titer Neutralization titer 533 days; Figure 1I). Conversely, a flat 1,000 1,000 slope (i.e., not significantly different from 0 in any phase) was observed in individuals 100 100 Wave 1 Wave 1 with asymptomatic infection or mild dis- Wave 2 Wave 2 Wave 3 Wave 3 ease (Figure 1I). These data confirm that, 0 100 200 300 400 500 0 100 200 300 400 500 despite different individual patterns, a large Time from symptom onset (days) Time from symptom onset (days) fraction of infected individuals (87% in non- hospitalized and 96% in hospitalized) I 10,000 generate detectable long-lasting neutral- (reciprocal dilution) Neutralization titer Decay rate P value Half-life HOSPITALIZED HOSPITALIZED (days– 1 ) (dif from 0) (days) izing antibodies (infective dose [ID]50 > 60). 1,000 1st phase decay 0.027 <0.0001 26 2nd phase decay 0.0013 ns 533 (flat) Impact of vaccination 100 NON- Decay rate P value Half-life NON-HOSPITALIZED HOSPITALIZED (days– 1 ) (dif from 0) Massive vaccination campaigns across (days) 1st phase decay 0.0048 ns flat developed countries have positively 0 100 200 300 400 500 2nd phase decay –0.0024 ns flat impacted the course of the COVID-19 Time from symptom onset (days) pandemic and have interfered with the follow-up of immune responses induced by natural infection. During routine follow- recently infected patients. In contrast, mildly affected or asymp- up visits, we identified 58 vaccinated individuals in our cohort. tomatic individuals developed a lower maximal neutralization Participants showed a wide range of vaccination status in terms titer with flatter behavior (Figures 1A, 1C, and 1E), although an of type of vaccine (21% received BNT162b2 [Pfizer-BioNTech], early peak could be observed in some of the second-wave par- 62% mRNA-1273 [Moderna], and 17% AZD1222 [AstraZeneca- ticipants who had earlier sampling (Figure 1C). Longitudinal anal- Oxford]), number of doses (only 55% had received the full ysis using smoothing-splines mixed-effects models showed 2-dose schedule), and time from the last dose (BNT162b2 overlapping kinetics for the different waves in each clinical group vaccinees analyzed at longer time points after vaccination). (Figures 1G and 1H), although neutralizing activity tended to Despite these differences, vaccines boosted pre-existing reach higher values at the peak (around 30 days) in hospitalized neutralizing responses in all non-hospitalized (n = 40) and patients from the third wave (mostly infected by the Alpha hospitalized (n = 18) participants (Figures 2A and 2B). A direct variant; Figure 1H). According to recent data,22 we assumed comparison of pre- and post-vaccination titers of neutralizing the generation of early short-lived plasmablast/plasma cells antibodies clearly confirms a highly significant increase in both Cell Reports Medicine 3, 100523, February 15, 2022 3 ll OPEN ACCESS Article A B Figure 2. Impact of vaccination on convales- VACCINATED cent plasma neutralizing activity V VACC A D NON-HOSPITALIZED INATE NON-HOSPITA T LIZED VACC V INATE A D HOSPITA VACCINATED T LIZED VA VAX HOSPITALIZED (A and B) Single measurements (dots) and individual 100000 100,000 100,000 100000 dilution) (reciprocal dilution) (reciprocal dilution) evolution (lines) of the longitudinal analysis for titer Neutralization titer Neutralization titer 10000 10,000 10,000 10000 vaccinated non-hospitalized (n = 40) and hospital- Neutralization ized (n = 18) individuals. Blue dots (light or dark) (reciprocal 1000 1,000 1,000 1000 correspond to pre-vaccination measurements. 100 Post-vaccine data are color-coded according to 100 vaccine schedules: BNT162b2 (maroon), mRNA- 10 10 1273 (red), and AZD1222 (purple). Full symbols indicate full schedule (two doses), while half circles 0 100 200 300 400 500 0 100 200 300 400 500 indicate one single dose. Time from symptom onset (days) Time from symptom onset (days) (C) Comparison of pre- and post-vaccination neutralizing antibody titers in both groups. Lower p values indicate paired comparison (Wilcoxon test) of pre- and post-values. Upper p value indicates Mann-Whitney comparison of pre-vaccination be- C 0.2919 tween groups. Geometric means of neutralization titer for each group are indicated. Dotted lines indi- 0.0667 100,000 cate the upper and lower limits of detection. (reciprocal dilution) Neutralization titer 10,000 8851 4595 1,000 762 249 100 subgroups, using only values with measur- 10 p<0.0001 p<0.0001 able neutralization titers for both WH1 PRE POST PRE POST and the variant of interest, showed no NON-HOSPITALIZED HOSPITALIZED differences between non-hospitalized and hospitalized groups for the Alpha/ B.1.1.7 variant (with a mean fold change around 1). On the other hand, statistically groups (p < 0.0001). Pre-vaccination titers tended to be lower in significant differences were observed for the Beta/B.1.351 non-hospitalized than in hospitalized individuals (geometric variant, which induced a higher relative loss of neutralization in mean, 249 and 762, respectively, p = 0.0667) and reached com- hospitalized patients (p = 0.0350; Figure 3B), while the Delta/ parable levels after vaccination (4,595 and 8,851, respectively; B.1.617.2 variant showed again intermediate behavior with a Figure 2C; p = 0.2919). However, the heterogeneous vaccine more pronounced decrease in hospitalized patients that did schedules and sampling times prevented further analysis. not reach significance (p = 0.3425; Figure 3B). As a conse- quence, the median magnitudes of neutralization against WH1, Impact of viral variants Alpha, and Delta were all superior in hospitalized individuals It is well known that SARS-CoV-2 VOCs show variable degrees compared with in non-hospitalized individuals (p = 0.0005, of resistance to neutralizing responses elicited by natural infec- 0.0003, and 0.0048 respectively), while statistical significance tion or vaccination.20 Therefore, to evaluate the impact of the was lost for the Beta variant (p = 0.3107; Figure 3A). most relevant VOCs on long-term neutralizing activity, a subset Following previous reports correlating protection with neutrali- of 60 unvaccinated individuals with follow-up periods beyond zation titers,7,23 we estimated the frequency of individuals with un- 300 days was analyzed against Alpha, Beta, and Delta variants. detectable, low, and high neutralization titers using a previously A global analysis showed that long-term neutralizing responses described cutoff value of 250.2 The analysis showed that 33% blocked the WH1 and the Alpha (B.1.1.7) variants with similar po- of individuals had undetectable or low neutralization against the tency, while lower titers were measured against the Beta WH1 or the Alpha variant, increasing to 52% or 41% for the (B.1.351) variant (p = 0.0001), and an intermediate but not signif- Beta and Delta variants, respectively. In all cases, the frequency icant loss of neutralization was observed against the more trans- of non-neutralizers and low neutralizers was higher in non-hospi- missible Delta variant (Figure 3A). The analysis of non-hospital- talized individuals, reaching 63% against the Beta variant, ized and hospitalized subgroups showed similar but not compared with 36% in hospitalized patients (Figure 3C) identical results. We observed a highly significant loss (p % 0.0001) of neutralizing capacity against the Beta variant in hospi- Factors determining long-term neutralizing activity talized individuals (Figure 3A) but a lower loss in non-hospitalized Despite similar long-term stability in non-hospitalized and hospi- individuals, reaching significance when compared with the Alpha talized individuals, neutralizing activity was highly heteroge- but not with the original WH1 variant (p = 0.4020; Figure 3A). To neous with the presence of non-neutralizer and highly neutralizer quantitatively assess these differences, we compared the ratio patients in both groups (see Figure 3). Therefore, we analyzed of neutralization titers between the original WH1 sequence and the factors that potentially define the magnitude of long-term the tested variants as a measure of the relative loss of neutraliza- neutralization (>300 days after infection) in unvaccinated in- tion for each individual. The comparison of this parameter among fected patients. A multivariate analysis including severity group, 4 Cell Reports Medicine 3, 100523, February 15, 2022 ll Article OPEN ACCESS 0.0048 0.0005 A 0.0003 0.0001 0.0062 <0.0001 0.0061 <0.0001 0.0250 <0.0001 (reciprocal dilution) 10,000 10,000 Neutralization titer 1,000 1,000 100 100 361 381 192 288 215 233 151 191 731 742 265 505 10 10 WH1 ALPHA BETA DELTA WH1 ALPHA BETA DELTA WH1 ALPHA BETA DELTA ALL PATIENTS NON-HOSP HOSP B ALPHA BETA DELTA 100 0.6655 100 0.0350 0.3425 Loss of neutralization 100 relative to WH1 0.93x 0.99x 1.61x 2.87x 1.17x 1.5x 10 10 10 1 1 1 0.1 0.1 0.1 NON- HOSP HOSP NON- HOSP HOSP NON- HOSP HOSP C WUHAN ALPHA BETA T DELTA T P TS PARTICIPAN (n=60) ALL P <60 60-250 >250 <60 60-250 >250 <60 60-250 >250 <60 60-250 >250 HOSPITALIZED (n=35) NON- 0.03 0.0002 0.03 0.003 HOSPITALIZED (n=25) (legend on next page) Cell Reports Medicine 3, 100523, February 15, 2022 5 ll OPEN ACCESS Article age, and gender showed that only severity, as defined by hospi- stability, as has also been described for SARS-CoV and MERS- talization, was independently associated with the magnitude of CoV.33–38 This raises an optimistic scenario, as neutralizing anti- responses (p = 0.0285; Figure 4A). Consistent with the close rela- body levels are highly predictive of immune protection,5,7,39,40 tionship between age and severity, age showed a significant ef- although sporadic cases of reinfection have been reported fect in the univariate analysis that was lost in the multivariate even in the presence of neutralizing antibodies.41,42 model (p = 0.0951; Figure 4B), while gender had no impact Our results complement previous studies that evaluated mid- (Figure 4C). term immunity2,17,18,43,44 and are in line with current evidence A similar approach was used to assess the impact of severity, showing a long-lasting neutralizing response for at least 1 age, and gender on variant cross-neutralization ratios (shown in year45–47 and the presence of receptor-binding domain (RBD)- Figure 3B). In this case, the multivariate analysis ruled out any specific memory B cells3,48 and long-lived bone marrow plasma impact of age and gender in the loss of neutralization against cells.22 Although several mechanisms have been proposed that Alpha, Beta, and Delta variants, which pointed to severity as may lead to the long-term persistence of antibodies,49 the pres- the main determinant, although it only reached significance for ence of long-lived plasma cells has received more support in the Beta variant (p = 0.0259; Table S2). recent years,50–52 and a biphasic model considering short- and long-lived plasma cells has been described.53,54 On this basis DISCUSSION and considering the neutralizing capacity of plasma as a surro- gate marker of the plasma-cell lifespan, we fitted our data to a To our knowledge, this report has analyzed the neutralizing two-phase exponential decay curve, probably reflecting both response against SARS-CoV-2 with the longest follow-up to short- and long-lived plasma cells. Therefore, our data point to date, with sampling more than 1 year after symptom onset, in an initial and transient generation or expansion of short-lived a large cohort with a broad spectrum of clinical disease presen- SARS-CoV-2-specific plasmablast/plasma cells in hospitalized tation (from asymptomatic to patients requiring intensive care) patients. While the selection of high-affinity B cells into germinal over different COVID-19 outbreaks in Catalonia. Longitudinal centers seems to be a hallmark for the generation of long-lived sampling allowed us to model accurate kinetics of neutralizing plasma cells,55 short-lived cells can be generated following an activity for the different waves (associated with different viral var- extrafollicular response,51 which does not necessarily imply iants). The temporal patterns for each wave appear to repeat immunoglobulin evolution through somatic hypermutation nor themselves independently of the infecting variant but with a selection of high-affinity B cells. Interestingly, hospitalized pa- strong impact of disease severity, as previously defined.13 tients showed a more limited cross-neutralizing response In comparison to the apparent short-lasting immunity against against the Beta variant relative to WH1, suggesting that B cell seasonal human coronaviruses,24,25 the neutralizing response responses in severe disease, despite being higher in magnitude, developed against SARS-CoV-2 shows a dynamic pattern could be less cross-neutralizing. Although the association of similar to the ones described against other coronaviruses that severity and magnitude of neutralizing responses has been cause severe acute respiratory illness, such as SARS-CoV and pointed out for early responses in different studies,2,13,56 our Middle East respiratory syndrome (MERS)-CoV. For these vi- data extend this observation to the long-term responses, also ruses, several studies detected neutralizing antibodies in the first suggesting a discordant relationship between the magnitude days after diagnosis with a rapid increase peaking between and quality of antibodies in hospitalized individuals. 2 weeks and 1 month post-symptom onset. Thereafter, there In the cohort studied, we observed that neutralizing activity is was a decline and, subsequently, a ‘‘stabilization’’ that was significantly boosted after vaccination, although the longevity of maintained beyond 1 year after infection in most cases and this response still needs to be determined. Based on our data on was related to disease severity.26–32 Our data demonstrate the unvaccinated infected individuals, the vaccination of people who long-term persistence of neutralizing antibodies against SARS- have overcome the SARS-CoV-2 infection should lead to a long- CoV-2 in most individuals with COVID-19. Although long-term in- lasting protection. But this information must be interpreted care- creases were observed in qualitative spline models, biexponen- fully since new emerging variants of the virus could escape both tial fitted models confirm a flat slope and therefore predict longer natural and vaccine-induced immunity.57 Figure 3. Impact of SARS-CoV-2 variants on long-term neutralizing activity (A–C) Neutralization titers, against WH1, Alpha, Beta, and Delta spike variants, measured on convalescent plasmas collected more than 300 days after symptom onset from non-hospitalized (n = 35) and hospitalized (n = 25) patients (see Table S1 for details). (A) Neutralization titers (ID50 expressed as reciprocal dilutions) from all patients (left) or divided into non-hospitalized and hospitalized patients (right). Bars and values below symbols indicate the geometric mean titer in each group. p values show the comparison of median titers among the four viruses (Friedman test with Dunn’s multiple comparison) or the comparison of the same variant between the two groups (Kruskal-Wallis test with Dunn’s multiple comparison). Only sig- nificant differences are shown. Dotted lines indicate lower limits of detection. (B) Loss of neutralization titers against variants (indicated on top) compared with WH1 pseudovirus (lower values identify maintained neutralization). Samples with undetectable titers for both WH1 and the analyzed variant were removed from the analysis. Bars and values indicate the median ratio, and p values indicate the comparison of the two patient groups (Mann-Whitney test). (C) Frequency of long-term non-neutralizers (ID50 < 60), low neutralizers (i.e., ID50 between 60 and 250 after 300 days post-symptom onset), and high neutralizers (ID > 250, light gray) in all patients and separately in hospitalized and non-hospitalized groups. p values show the comparison of frequency between both groups for each variant (chi-square test). 6 Cell Reports Medicine 3, 100523, February 15, 2022 ll Article OPEN ACCESS A B C p = 0.028 p = 0.095 p = 0.879 (reciprocal dilution) (reciprocal dilution) (reciprocal dilution) 1,000 1,000 Neutralization titer Neutralization titer 1,000 Neutralization titer 100 100 100 20 30 40 50 60 70 80 Female Male Non-Hospitalized Hospitalized Age (years) Figure 4. Factors determining long-term neutralizing titer (A–C) Factor effects by multivariate linear regression for samples collected more than 300 days post-symptom onset from 99 participants. Estimated effect (dots) and 95% CI (bars or bands) are plotted, and the p value is shown for each predictor covariate: (A) severity, (B) age, and (C) gender. Multivariate analyses were performed with R-3.6.3 software. To address the impact of VOCs, we tested neutralization titers mune-related factors. In addition, the long-term impact of vacci- against Alpha, Beta, and Delta variants. Despite showing lower nation is still an open question; therefore, beyond the clear titers, non-hospitalized individuals tended to have better relative boosting effect observed, we cannot draw further conclusions cross-neutralization against all variants tested. Of note, the loss due to heterogeneous vaccine schedules and sampling times. of neutralization titers observed in our study was lower than the Our longitudinal analysis confirmed the early decay and long- values reported for vaccinated individuals.58 We did not observe term maintenance of neutralizing activity observed in other co- changes for the Alpha variant, and the ratios calculated for the horts.10,12 Moreover, our data identified different dynamics of Beta and Delta variants compared with the WH1 isolate below short- and long-lived responses after infection. In particular, 3-fold. This fact could be related to antibody evolution after re- severity of primary infection is associated with the emergence covery from infection and is consistent with data reporting of short-lived antibodies (not observed in non-hospitalized indi- increased cross-neutralization in vaccinated or unvaccinated viduals) and the generation of higher titers of less cross-neutral- COVID-19 convalescent individuals.48,58,59 Therefore, we exclu- izing long-lived antibodies (beyond 1 year). sively observed a significant reduction of titers for the Beta variant, resulting in a high frequency of individuals with undetect- STAR+METHODS able or low (<250) neutralizing capacities that were significantly higher in non-hospitalized individuals. When analyzing the clin- Detailed methods are provided in the online version of this paper ical and demographic factors that could influence the long- and include the following: term neutralizing antibody response, we did not observe any dif- ferences between women and men. In contrast, age shows a d KEY RESOURCES TABLE certain tendency (older participants present higher neutralizing d RESOURCE AVAILABILITY activity) whose significance was evident in the univariate analysis B Lead contact but did not reach significance in the multivariate linear regres- B Materials availability sion. This latter result could indicate that age by itself is not a B Data and code availability determinant component but depends on other cofactors, as d EXPERIMENTAL MODEL AND SUBJECT DETAILS could be the severity of the disease, which is highlighted as B Study overview and subjects the main determinant of the magnitude of long-term responses. B Cell lines This is in line with the evidence described so far,44,47 although it d METHOD DETAILS disagrees with another study describing antibody kinetics influ- B Pseudovirus generation and neutralization assay enced by gender.46 Despite the clear effect of severity, there is d QUANTIFICATION AND STATISTICAL ANALYSIS still a high individual heterogeneity in the magnitude of neutrali- zation achieved by participants in each group (non-hospitalized SUPPLEMENTAL INFORMATION or hospitalized individuals) that needs further study to unveil Supplemental information can be found online at https://doi.org/10.1016/j. additional determinants. xcrm.2022.100523. ACKNOWLEDGMENTS Limitations of the study Our analysis provides one of the largest datasets on neutralizing This work was partially funded by Grifols, the Departament de Salut of the Gen- activity (in number of participants and follow-up time) but is eralitat de Catalunya (grants SLD016 to J.B. and SLD015 to J.C.), the Spanish limited by the lack of parallel data on T cells and other im- Health Institute Carlos III and the European Regional Development Fund (grant Cell Reports Medicine 3, 100523, February 15, 2022 7 ll OPEN ACCESS Article PI17/01518 and PI20/00093 to J.B. and PI18/01332 to J.C.), CERCA Pro- 9. AD, J., AJ, H., N, M., M, M., and HC, W. (1999). What level of hepatitis B gramme/Generalitat de Catalunya 2017 SGR 252, and the crowdfunding initia- antibody is protective? J. Infect. Dis. 179, 489–492. tives #joemcorono, BonPreu/Esclat, and Correos. The funders had no role in 10. Zhao, J., Yuan, Q., Wang, H., Liu, W., Liao, X., Su, Y., Wang, X., Yuan, J., study design, data collection and analysis, the decision to publish, or the prep- Li, T., Li, J., et al. (2020). Antibody responses to SARS-CoV-2 in patients aration of the manuscript. E.P. was supported by a doctoral grant from the Na- with Novel coronavirus disease 2019. Clin. Infect. Dis. 71, 2027–2034. tional Agency for Research and Development of Chile (ANID) (72180406). We 11. Xiao, A.T., Gao, C., and Zhang, S. (2020). Profile of specific antibodies to are grateful to all participants and the technical staff of IrsiCaixa for sample SARS-CoV-2: the first report. J. Infect. 81, 147–178. processing. Francesc López-Seguı́ provided medical writing support during the preparation of the manuscript. 12. Suthar, M.S., Zimmerman, M.G., Kauffman, R.C., Mantus, G., Linderman, S.L., Hudson, W.H., Vanderheiden, A., Nyhoff, L., Davis, C.W., Adekunle, O., et al. (2020). Rapid generation of neutralizing antibody responses in AUTHOR CONTRIBUTIONS COVID-19 patients. Cell Rep. Med. 1, 100040. J.B. and B.C. designed and coordinated the study. E.P, B.T., S.M., F.T.-F., 13. Trinité, B., Tarrés-Fraixas, F., Rodon, J., Pradenas, E., Urrea, V., Marfil, R.O., C.R., J.R., J.V.-A., J.S., and N.I.-U. performed and analyzed neutraliza- S.S., Rodriguez de la Concepción, M.L., Avila-Nieto, C., Aguilar-Gurrieri, tion assays. E.P., B.T., and V.U. performed statistical analysis. M.N.-J., R.P., C., Barajas, A., et al. (2021). SARS-CoV-2 infection elicits a rapid neutral- L.M., A.C., R.T., M.M., V.G., A.V., and J.C. selected patients and coordinated izing antibody response that correlates with disease severity. Sci. Rep. 11, data. J.B. and E.P. drafted the manuscript, and all authors have made sub- 2608. stantial contributions to the revision of the subsequent versions. All authors 14. Long, Q.X., Tang, X.J., Shi, Q.L., Li, Q., Deng, H.J., Yuan, J., Hu, J.L., Xu, approved the submitted version of the manuscript and agreed both to be W., Zhang, Y., Lv, F.J., et al. (2020). Clinical and immunological assess- personally accountable for their own contributions and to ensure the accuracy ment of asymptomatic SARS-CoV-2 infections. Nat. Med. 26, 1200–1204. or integrity of any part of the work. 15. Wang, X., Guo, X., Xin, Q., Pan, Y., Hu, Y., Li, J., Chu, Y., Feng, Y., and Wang, Q. (2020). Neutralizing antibody responses to severe acute respira- DECLARATION OF INTERESTS tory syndrome coronavirus 2 in coronavirus disease 2019 inpatients and convalescent patients. Clin. Infect. Dis. 71, 2688–2694. Unrelated to the submitted work, J.B. and J.C. are founders and shareholders 16. Ibarrondo, F.J., Fulcher, J.A., Goodman-Meza, D., Elliott, J., Hofmann, C., of AlbaJuna Therapeutics, SL. B.C. is founder and shareholder of AlbaJuna Hausner, M.A., Ferbas, K.G., Tobin, N.H., Aldrovandi, G.M., and Yang, Therapeutics, SL, and AELIX Therapeutics, SL. The other authors declare no O.O. (2020). Rapid decay of anti–SARS-CoV-2 antibodies in Persons competing interests. with mild Covid-19. N. Engl. J. Med. 383, 1085–1087. 17. Wajnberg, A., Amanat, F., Firpo, A., Altman, D.R., Bailey, M.J., Mansour, Received: August 23, 2021 M., McMahon, M., Meade, P., Mendu, D.R., Muellers, K., et al. (2020). Revised: November 12, 2021 Robust neutralizing antibodies to SARS-CoV-2 infection persist for Accepted: January 17, 2022 months. Science 370, 1227–1230. Published: January 24, 2022 18. Gaebler, C., Wang, Z., Lorenzi, J.C.C., Muecksch, F., Finkin, S., To- REFERENCES kuyama, M., Cho, A., Jankovic, M., Schaefer-Babajew, D., Oliveira, T.Y., et al. (2021). Evolution of antibody immunity to SARS-CoV-2. Nature 1. Sette, A., and Crotty, S. (2021). Adaptive immunity to SARS-CoV-2 and 591, 639–644. COVID-19. Cell 184, 861–880. 19. Wheatley, A.K., Juno, J.A., Wang, J.J., Selva, K.J., Reynaldi, A., Tan, H.-X., 2. Pradenas, E., Trinité, B., Urrea, V., Marfil, S., Ávila-Nieto, C., Rodrı́guez de Lee, W.S., Wragg, K.M., Kelly, H.G., Esterbauer, R., et al. (2021). Evolution la Concepción, M.L., Tarrés-Freixas, F., Pérez-Yanes, S., Rovirosa, C., of immune responses to SARS-CoV-2 in mild-moderate COVID-19. Nat. Ainsua-Enrich, E., et al. (2021). Stable neutralizing antibody levels Commun. 12, 1162. 6 months after mild and severe COVID-19 episodes. Med 2, 313–320.e4. 20. Planas, D., Bruel, T., Grzelak, L., Guivel-Benhassine, F., Staropoli, I., Por- 3. Dan, J.M., Mateus, J., Kato, Y., Hastie, K.M., Yu, E.D., Faliti, C.E., Grifoni, rot, F., Planchais, C., Buchrieser, J., Rajah, M.M., Bishop, E., et al. (2021). A., Ramirez, S.I., Haupt, S., Frazier, A., et al. (2021). Immunological mem- Sensitivity of infectious SARS-CoV-2 B.1.1.7 and B.1.351 variants to ory to SARS-CoV-2 assessed for up to 8 months after infection. Science neutralizing antibodies. Nat. Med. 27, 917–924. 80, 371. 21. Marshall, J.C., Murthy, S., Diaz, J., Adhikari, N., Angus, D.C., Arabi, Y.M., 4. Carrillo, J., Izquierdo-Useros, N., Ávila-Nieto, C., Pradenas, E., Clotet, B., Baillie, K., Bauer, M., Berry, S., Blackwood, B., et al. (2020). A minimal and Blanco, J. (2020). Humoral immune responses and neutralizing anti- common outcome measure set for COVID-19 clinical research. Lancet bodies against SARS-CoV-2; implications in pathogenesis and protective Infect. Dis. 20, e192–e197. immunity. Biochem. Biophys. Res. Commun. 538, 187–191. 22. Turner, J.S., Kim, W., Kalaidina, E., Goss, C.W., Rauseo, A.M., Schmitz, 5. Khoury, D.S., Cromer, D., Reynaldi, A., Schlub, T.E., Wheatley, A.K., Juno, A.J., Hansen, L., Haile, A., Klebert, M.K., Pusic, I., et al. (2021). SARS- J.A., Subbarao, K., Kent, S.J., Triccas, J.A., and Davenport, M.P. (2021). CoV-2 infection induces long-lived bone marrow plasma cells in humans. Neutralizing antibody levels are highly predictive of immune protection Nature 7867, 421–425. from symptomatic SARS-CoV-2 infection. Nat. Med. 27, 1–7. 23. Gilbert, P.B., Montefiori, D.C., McDermott, A., Fong, Y., Benkeser, D., 6. Lumley, S.F., O’Donnell, D., Stoesser, N.E., Matthews, P.C., Howarth, A., Deng, W., et al. (2021). Immune correlates analysis of the mRNA-1273 Hatch, S.B., Marsden, B.D., Cox, S., James, T., Warren, F., et al. (2021). COVID-19 vaccine efficacy clinical trial. Science 375, 43–50. Antibody status and incidence of SARS-CoV-2 infection in Health care 24. Edridge, A.W.D., Kaczorowska, J., Hoste, A.C.R., Bakker, M., Klein, M., workers. N. Engl. J. Med. 384, 533–540. Loens, K., Jebbink, M.F., Matser, A., Kinsella, C.M., Rueda, P., et al. 7. Addetia, A., Crawford, K.H.D.D., Dingens, A., Zhu, H., Roychoudhury, P., (2020). Seasonal coronavirus protective immunity is short-lasting. Nat. Huang, M.-L.L., Jerome, K.R., Bloom, J.D., and Greninger, A.L. (2020). Med. 26, 1691–1693. Neutralizing antibodies correlate with protection from SARS-CoV-2 in hu- 25. Callow, K.A., Parry, H.F., Sergeant, M., and Tyrrell, D.A.J. (1990). The time mans during a fishery vessel outbreak with high attack rate. J. Clin. Micro- course of the immune response to experimental coronavirus infection of biol. 58, 1–11. man. Epidemiol. Infect. 105, 435–446. 8. Plotkin, S.A. (2010). Correlates of protection induced by vaccination. Clin. 26. Al-Abdely, H.M., Midgley, C.M., Alkhamis, A.M., Abedi, G.R., Lu, X., Vaccin. Immunol. 17, 1055–1065. Binder, A.M., Alanazi, K.H., Tamin, A., Banjar, W.M., Lester, S., et al. 8 Cell Reports Medicine 3, 100523, February 15, 2022 ll Article OPEN ACCESS (2019). Middle east respiratory syndrome coronavirus infection dynamics 42. Brehm, T.T., Pfefferle, S., von Possel, R., Kobbe, R., Nörz, D., Schmiedel, and antibody responses among clinically diverse patients, Saudi Arabia. S., Grundhoff, A., Olearo, F., Emmerich, P., Robitaille, A., et al. (2021). Emerg. Infect. Dis. 25, 753–766. Sars-cov-2 reinfection in a healthcare worker despite the presence of 27. Choe, P.G., Perera, R.A.P.M., Park, W.B., Song, K.H., Bang, J.H., Kim, detectable neutralizing antibodies. Viruses 13, 661. E.S., Kim, H.B., Ko, L.W.R., Park, S.W., Kim, N.J., et al. (2017). MERS- 43. Dupont, L., Snell, L.B., Graham, C., Seow, J., Merrick, B., Hallett, S.R., CoV antibody responses 1 year after symptom onset, South Korea, et al. (2021). Neutralizing antibody activity in convalescent sera from infec- 2015. Emerg. Infect. Dis. 23, 1079–1084. tion in humans with SARS-CoV-2 and variants of concern. Nat. Microbiol. 6, 1433–1442. 28. Corman, V.M., Albarrak, A.M., Omrani, A.S., Albarrak, M.M., Farah, M.E., Almasri, M., Muth, D., Sieberg, A., Meyer, B., Assiri, A.M., et al. (2016). Viral 44. Ortega, N., Ribes, M., Vidal, M., Rubio, R., Aguilar, R., Williams, S., Barrios, shedding and antibody response in 37 patients with Middle East respira- D., Alonso, S., Hernández-Luis, P., Mitchell, R.A., et al. (2021). Seven- tory syndrome coronavirus infection. Clin. Infect. Dis. 62, 477–483. month kinetics of SARS-CoV-2 antibodies and role of pre-existing anti- bodies to human coronaviruses. Nat. Commun. 12, 4740. 29. Nie, Y., Wang, G., Shi, X., Zhang, H., Qiu, Y., He, Z., Wang, W., Lian, G., Yin, X., Du, L., et al. (2004). Neutralizing antibodies in patients with severe 45. Muena, N.A., Garcı́a-Salum, T., Pardo-Roa, C., Serrano, E.F., Levican, J., acute respiratory syndrome-associated coronavirus infection. J. Infect. José Avendaño, M., Almonacid, L.I., Valenzuela, G., Poblete, E., Salinas, Dis. 190, 1119–1126. E., et al. (2021). Long-lasting neutralizing antibody responses in SARS- CoV-2 seropositive individuals are 1 robustly boosted by immunization 30. Park, W.B., Perera, R.A.P.M., Choe, P.G., Lau, E.H.Y., Choi, S.J., Chun, with the CoronaVac and BNT162b2 vaccines. medRxiv. https://doi.org/ J.Y., Oh, H.S., Song, K.H., Bang, J.H., Kim, E.S., et al. (2015). Kinetics 10.1101/2021.05.17.21257197. of serologic responses to MERS coronavirus infection in humans, South Korea. Emerg. Infect. Dis. 21, 2186–2189. 46. Gallais, F., Gantner, P., Bruel, T., Velay, A., Planas, D., Wendling, M.-J., et al. (2021). Evolution of antibody responses up to 13 months after 31. Temperton, N.J., Chan, P.K., Simmons, G., Zambon, M.C., Tedder, R.S., SARS-CoV-2 infection and risk of reinfection. eBioMedicine 71. https:// Takeuchi, Y., and Weiss, R.A. (2005). Longitudinally profiling neutralizing doi.org/10.1101/2021.05.07.21256823. antibody response to SARS coronavirus with pseudotypes. Emerg. Infect. Dis. 11, 411–416. 47. Haveri, A., Ekström, N., Solastie, A., Virta, C., Österlund, P., Isosaari, E., et al. (2021). Persistence of neutralizing antibodies a year after SARS- 32. Huang, A.T., Garcia-Carreras, B., Hitchings, M.D.T., Yang, B., Katzelnick, CoV-2 infection in humans. European Journal of Immunology 51, 3202– L.C., Rattigan, S.M., Borgert, B.A., Moreno, C.A., Solomon, B.D., 3213. https://doi.org/10.1101/2021.07.13.21260426. Trimmer-Smith, L., et al. (2020). A systematic review of antibody mediated immunity to coronaviruses: kinetics, correlates of protection, and associ- 48. Wang, Z., Muecksch, F., Schaefer-Babajew, D., Finkin, S., Viant, C., Gae- ation with severity. Nat. Commun. 11, 1–16. bler, C., Hoffmann, H.H., Barnes, C.O., Cipolla, M., Ramos, V., et al. (2021). Naturally enhanced neutralizing breadth against SARS-CoV-2 33. Cao, W.-C., Liu, W., Zhang, P.-H., Zhang, F., and Richardus, J.H. (2007). one year after infection. Nature 595, 1–10. Disappearance of antibodies to SARS-associated coronavirus after recov- ery. N. Engl. J. Med. 357, 1162–1163. 49. Slifka, M.K., and Ahmed, R. (1998). Long-lived plasma cells: a mechanism for maintaining persistent antibody production. Curr. Opin. Immunol. 10, 34. Liu, L., Xie, J., Sun, J., Han, Y., Zhang, C., Fan, H., Liu, Z., Qiu, Z., He, Y., 252–258. and Li, T. (2011). Longitudinal profiles of immunoglobulin G antibodies against severe acute respiratory syndrome coronavirus components and 50. Radbruch, A., Muehlinghaus, G., Luger, E.O., Inamine, A., Smith, K.G.C., neutralizing activities in recovered patients. Scand. J. Infect. Dis. 43, Dörner, T., and Hiepe, F. (2006). Competence and competition: the chal- 515–521. lenge of becoming a long-lived plasma cell. Nat. Rev. Immunol. 6, 741–750. 35. Alshukairi, A.N., Zhao, J., Al-Mozaini, M.A., Wang, Y., Dada, A., Baharoon, S.A., Alfaraj, S., Ahmed, W.A., Enani, M.A., Elzein, F.E., et al. (2021). 51. Khodadadi, L., Cheng, Q., Radbruch, A., and Hiepe, F. (2019). The main- Longevity of middle east respiratory syndrome coronavirus antibody re- tenance of memory plasma cells. Front. Immunol. 0, 721. sponses in humans, Saudi Arabia. Emerg. Infect. Dis. 27, 1472–1476. 52. Manz, R.A., Hauser, A.E., Hiepe, F., and Radbruch, A. (2004). Maintenance of serum antibody levels. Annu. Rev. Immunol. 23, 367–386. 36. Anderson, D.E., Tan, C.W., Chia, W.N., Young, B.E., Linster, M., Low, J.H., Tan, Y.-J., Chen, M.I.-C., Smith, G.J.D., Leo, Y.S., et al. (2020). Lack of 53. Slifka, M.K., Antia, R., Whitmire, J.K., and Ahmed, R. (1998). Humoral im- cross-neutralization by SARS patient sera towards SARS-CoV-2. Emerg. munity due to long-lived plasma cells. Immunity 8, 363–372. Microbes Infect. 9, 900–902. 54. Miller, J.J. (1964). An autoradiographic study of plasma cell and lympho- 37. Payne, D.C., Iblan, I., Rha, B., Alqasrawi, S., Haddadin, A., Al Nsour, M., cyte survival in rat popliteal lymph nodes. J. Immunol. 92, 673–681. Alsanouri, T., Ali, S.S., Harcourt, J., Miao, C., et al. (2016). Persistence 55. Suan, D., Sundling, C., and Brink, R. (2017). Plasma cell and memory B cell of antibodies against middle east respiratory syndrome coronavirus. differentiation from the germinal center. Curr. Opin. Immunol. 45, 97–102. Emerg. Infect. Dis. 22, 1824–1826. 56. Vanshylla, K., Di Cristanziano, V., Kleipass, F., Dewald, F., Schommers, P., 38. Mo, H., Zeng, G., Ren, X., Li, H., Ke, C., Tan, Y., Cai, C., Lai, K., Chen, R., Gieselmann, L., Gruell, H., Schlotz, M., Ercanoglu, M.S., Stumpf, R., et al. Chan-Yeung, M., et al. (2006). Longitudinal profile of antibodies against (2021). Kinetics and correlates of the neutralizing antibody response to SARS-coronavirus in SARS patients and their clinical significance. Respir- SARS-CoV-2 infection in humans. Cell Host Microbe 29, 917–929.e4. ology 11, 49–53. 57. Garcia-Beltran, W.F., Lam, E.C., St. Denis, K., Nitido, A.D., Garcia, Z.H., 39. Kim, Y. Il, Kim, S.M., Park, S.J., Kim, E.H., Yu, K.M., Chang, J.H., Kim, E.J., Hauser, B.M., Feldman, J., Pavlovic, M.N., Gregory, D.J., Poznansky, Casel, M.A.B., Rollon, R., Jang, S.G., et al. (2021). Critical role of neutral- M.C., et al. (2021). Multiple SARS-CoV-2 variants escape neutralization izing antibody for SARS-CoV-2 reinfection and transmission. Emerg. Mi- by vaccine-induced humoral immunity. Cell 184, 2372–2383.e9. crobes Infect. 10, 152–160. 58. Carreño, J.M., Alshammary, H., Singh, G., Raskin, A., Amanat, F., 40. Earle, K.A., Ambrosino, D.M., Fiore-Gartland, A., Goldblatt, D., Gilbert, Amoako, A., Gonzalez-Reiche, A.S., van de Guchte, A., study group, P., P.B., Siber, G.R., Dull, P., and Plotkin, S.A. (2021). Evidence for antibody Srivastava, K., et al. (2021). Evidence for retained spike-binding and as a protective correlate for COVID-19 vaccines. Vaccine 39, 4423–4428. neutralizing activity against emerging SARS-CoV-2 variants in serum of 41. Zhang, J., Ding, N., Ren, L., Song, R., Chen, D., Zhao, X., Chen, B., Han, J., COVID-19 mRNA vaccine recipients. EBioMedicine 73, 103626. Li, J., Song, Y., et al. (2021). COVID-19 reinfection in the presence of 59. Trinité, B., Pradenas, E., Marfil, S., Rovirosa, C., Urrea, V., Tarrés-Freixas, neutralizing antibodies. Natl. Sci. Rev. 8, 2021. F., Ortiz, R., Rodon, J., Vergara-Alert, J., Segalés, J., et al. (2021). Previous Cell Reports Medicine 3, 100523, February 15, 2022 9 ll OPEN ACCESS Article SARS-CoV-2 infection increases B.1.1.7 cross-neutralization by vacci- virus entry and its immune cross-reactivity with SARS-CoV. Nat. Commun. nated individuals. Viruses 13, 1135. 11, 1620. 60. Connor, R.I., Chen, B.K., Choe, S., and Landau, N.R. (1995). Vpr is required for efficient replication of human immunodeficiency virus type-1 62. Sánchez-Palomino, S., Massanella, M., Carrillo, J., Garcı́a, A., Garcı́a, F., in mononuclear phagocytes. Virology 206, 935–944. González, N., Merino, A., Alcamı́, J., Bofill, M., Yuste, E., et al. (2011). A 61. Ou, X., Liu, Y., Lei, X., Li, P., Mi, D., Ren, L., Guo, L., Guo, R., Chen, T., Hu, cell-to-cell HIV transfer assay identifies humoral responses with broad J., et al. (2020). Characterization of spike glycoprotein of SARS-CoV-2 on neutralization activity. Vaccine 29, 5250–5259. 10 Cell Reports Medicine 3, 100523, February 15, 2022 ll Article OPEN ACCESS STAR+METHODS KEY RESOURCES TABLE REAGENT or RESOURCE SOURCE IDENTIFIER Bacterial and virus strains pNL4-3.Luc.R-.E- NIH ARP Cat#3418 SARS-CoV-2.SctD19 This paper N/A pcDNA3.1(+) GeneArt/Thermo Fisher Scientific Cat#810330DE pVSV-G Clontech Sánchez-Palomino et al48 Chemicals, peptides, and recombinant proteins Fetal Bovine Serum Thermo Fisher Scientific Cat#10270106 Dulbecco’s Modified Eagle Medium Thermo Fisher Scientific Cat#41966052 Expi293 Expression Medium Thermo Fisher Scientific Cat#A1435102 Opti-MEM I Reduced Serum Medium Thermo Fisher Scientific Cat#31985070 ExpiFectamine 293 Transfection Kit Thermo Fisher Scientific Cat#A14524 Versene Thermo Fisher Scientific Cat#15040033 Puromycin Thermo Fisher Scientific Cat#A1113803 DEAE-Dextran Sigma-Aldrich Cat#D9885-100G BriteLite Plus Luciferase PerkinElmer Cat#6066769 Experimental models: Cell lines Expi293F GnTI- cells Thermo Fisher Scientific Cat#A39240 HEK293T/hACE2 cells Integral Molecular Cat#C-HA101 Software and algorithms GraphPad Prism v9.3.1 GraphPad Software https://www.graphpad.com/scientific-software/prism/ R v3.6.3 R Foundation for Statistical Computing https://www.r-project.org/ ‘‘nlme’’ R Package R Foundation for Statistical Computing https://cran.r-project.org/web/packages ‘‘sme’’ R Package R Foundation for Statistical Computing https://cran.r-project.org/web/packages Other GeneArt Gene Synthesis Thermo Fisher Scientific N/A RESOURCE AVAILABILITY Lead contact Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Julià Blanco (jblanco@irsicaixa.es). Materials availability The plasmids pcDNA3.1 SARS-CoV-2.SctD19 are available upon request to the lead contact. Data and code availability All data reported in this paper will be shared by the lead contact upon request. This paper does not report original code. Any addi- tional information required to reanalyze the data reported in this paper is available from the lead contact upon request. EXPERIMENTAL MODEL AND SUBJECT DETAILS Study overview and subjects The study KING was approved by the Hospital Ethics Committee Board from Hospital Universitari Germans Trias i Pujol (HUGTiP, PI- 20-122 and PI-20-217) and was further amended to include vaccinated individuals. All participants provided written informed consent before inclusion. Plasma samples were obtained from individuals of the prospective KING cohort of the HUGTiP (Badalona, Spain). The recruitment period lasted from March 2020 to March 2021, thus covering the three consecutive outbreaks of COVID-19 in Catalonia (Figure S1). Cell Reports Medicine 3, 100523, February 15, 2022 e1 ll OPEN ACCESS Article The KING cohort included individuals with a documented positive RT-qPCR result from nasopharyngeal swab and/or a positive sero- logical diagnostic test. Participants were recruited irrespective of age and disease severity including asymptomatic status in various settings, including primary care, hospital, and epidemiological surveillance based on contact tracing. We collected plasma samples at the time of COVID-19 diagnosis and at 3, 6 and 12 months after diagnosis. Additionally, hospitalized individuals were sampled twice a week during acute infection. Viral sequences were available from a subset of participants (n = 26, 8% of the cohort) and confirmed the expected prevalence of B.1 variant during the first wave (67% of sequences), 20E(EU1) variant during the second one (70% of sequences) and alpha variant after January 2021 (80% of sequences). Cell lines HEK293T cells overexpressing WT human ACE-2 (Integral Molecular, USA) were used as target in pseudovirus-based neutralization assay. Cells were maintained in T75 flasks with Dulbecco’s Modified Eagle’s Medium (DMEM) supplemented with 10% FBS and 1 mg/ml of Puromycin (Thermo Fisher Scientific, USA). Expi293F cells (Thermo Fisher Scientific) are a HEK293 cell derivative adapted for suspension culture that were used for SARS- CoV-2 pseudovirus production. Cells were maintained under continuous shaking in Erlenmeyer flasks following manufacturer’s guidelines. METHOD DETAILS Pseudovirus generation and neutralization assay HIV reporter pseudoviruses expressing SARS-CoV-2 S protein and Luciferase were generated. pNL4-3.Luc.R-.E- was obtained from the NIH AIDS Reagent Program.60 SARS-CoV-2.SctD19 was generated (GeneArt) from the full protein sequence of the original WH1 SARS-CoV-2 spike (Genbank MN908947.3) with a deletion of the last 19 amino acids in C-terminal,61 human-codon optimized and inserted into pcDNA3.1(+). A similar procedure was followed to generate expression plasmids for the alpha (69-70 del, Y144 del, N501Y, A570D, P681H, T716I, S982A and D1118H), beta (L18F, D80S, D215G, L242_244 Del, R246I, K417N, E484K, N501Y, D614G, A701V) and delta (T19R, 157-158del, L452R, T478K, D614G, P681R, D950N) variants of SARS-CoV-2 S protein59 according to consensus data (www.outbreak.info/). Expi293F cells were transfected using ExpiFectamine293 Reagent (Thermo Fisher Scien- tific) with pNL4-3.Luc.R-.E- and SARS-CoV-2.SctD19 (WH1, alpha, beta or delta), at an 8:1 ratio, respectively. Control pseudoviruses were obtained by replacing the S protein expression plasmid with a VSV-G protein expression plasmid as reported.62 Supernatants were harvested 48 hours after transfection, filtered at 0.45 mm, frozen, and titrated on HEK293T cells overexpressing WT human ACE- 2 (Integral Molecular, USA). This neutralization assay has been previously validated in a large subset of samples and negative controls with a replicative viral inhibition assay.13 Neutralization assays were performed in duplicate. Briefly, in Nunc 96-well cell culture plates (Thermo Fisher Scientific), 200 TCID50 of pseudovirus were preincubated with three-fold serial dilutions (1/60–1/14,580) of heat-inactivated plasma samples for 1 hour at 37 C. Then, 2x104 HEK293T/hACE2 cells treated with DEAE-Dextran (Sigma-Aldrich) were added. Results were read after 48 hours using the EnSight Multimode Plate Reader and BriteLite Plus Luciferase reagent (PerkinElmer, USA). The values were normalized, and the ID50 (reciprocal dilution inhibiting 50% of the infection) was calculated by plotting and fitting all duplicate neutralization values and the log of plasma dilution to a 4-parameters equation in Prism 9.0.2 (GraphPad Software, USA). QUANTIFICATION AND STATISTICAL ANALYSIS Continuous variables were described using medians and the interquartile range (IQR, defined by the 25th and 75th percentiles), whereas categorical factors were reported as percentages over available data. Quantitative variables were compared using the Mann-Whitney test, and percentages using the chi-squared test. For the longitudinal analysis of neutralizing activity, patients were grouped into two severity groups according to the WHO progression scale21 asymptomatic or mild (levels 1-3), and hospitalized (levels 4-10). Longitudinal kinetics of neutralization activity for hospitalized and mild groups were analyzed by nonlinear models in two ways, parametric and non-parametric models and stratifying by severity in both cases. We fitted a non-parametric model using smooth- ing-splines mixed-effects model using the ‘‘sme’’ package of R. The final part of this model, showing an increase in neutralization activity, is unreliable due to the small sample size available in that stretch. We also analyzed the observed decrease of neutralization after 30 days by a biexponential decay model [y=P1*exp(-k1*t) + P2*exp(-k2*t)] fitting a nonlinear mixed-effects model and using ‘‘nlme’’ package of R. In this case three samples were excluded due to their influence in the model fitting since were samples after 350 days with and important increase of neutralization with respect the previous determinations and although we cannot rule out their veracity, they had a great impact on the proper fit of the model due to the lack of sample size in the final part of the follow-up. Differences in neutralization between both groups after 300 days since symptoms were analyzed. We also analyzed the effect of age and gender using a multivariate linear model adjusting by severity to avoid confusion effects, especially for age that are asso- ciated with severity. Statistical analyses were performed using R-3.6.3 (R Foundation for Statistical Computing) and Prism 9.0.2 (GraphPad Software). e2 Cell Reports Medicine 3, 100523, February 15, 2022