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. 2022 Feb 8;55(2):355-365.e4.
doi: 10.1016/j.immuni.2022.01.001. Epub 2022 Jan 6.

mRNA-1273 vaccine-induced antibodies maintain Fc effector functions across SARS-CoV-2 variants of concern

Paulina Kaplonek  1 , Stephanie Fischinger  1 , Deniz Cizmeci  1 , Yannic C Bartsch  1 , Jaewon Kang  1 , John S Burke  1 , Sally A Shin  1 , Diana Dayal  2 , Patrick Martin  2 , Colin Mann  3 , Fatima Amanat  4 , Boris Julg  1 , Eric J Nilles  5 , Elon R Musk  2 , Anil S Menon  2 , Florian Krammer  4 , Erica Ollman Saphire  3 , Andrea Carfi  6 , Galit Alter  7
Affiliations

mRNA-1273 vaccine-induced antibodies maintain Fc effector functions across SARS-CoV-2 variants of concern

Paulina Kaplonek et al. Immunity. .

Abstract

SARS-CoV-2 mRNA vaccines confer robust protection against COVID-19, but the emergence of variants has generated concerns regarding the protective efficacy of the currently approved vaccines, which lose neutralizing potency against some variants. Emerging data suggest that antibody functions beyond neutralization may contribute to protection from the disease, but little is known about SARS-CoV-2 antibody effector functions. Here, we profiled the binding and functional capacity of convalescent antibodies and Moderna mRNA-1273 COVID-19 vaccine-induced antibodies across SARS-CoV-2 variants of concern (VOCs). Although the neutralizing responses to VOCs decreased in both groups, the Fc-mediated responses were distinct. In convalescent individuals, although antibodies exhibited robust binding to VOCs, they showed compromised interactions with Fc-receptors. Conversely, vaccine-induced antibodies also bound robustly to VOCs but continued to interact with Fc-receptors and mediate antibody effector functions. These data point to a resilience in the mRNA-vaccine-induced humoral immune response that may continue to offer protection from SARS-CoV-2 VOCs independent of neutralization.

Keywords: COVID-19; Fc effector function; SARS-CoV-2; mRNA-1273 vaccination; vaccines; variants of concern.

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Conflict of interest statement

Declaration of interests G.A. is the founder of Seromyx Systems Inc. A.C. is an employee of Moderna Inc. D.D., P.M., A.S.M., and E.R.M. are employees of Space Exploration Technologies Corp. All other authors have declared no competing interests.

Figures

Figure 1
Figure 1
SARS-CoV-2 natural infection and mRNA-1273 vaccination induce IgG1, IgG3, IgM, and IgA antibodies across SARS-CoV-2 VOCs (A) The dot plots represent the relationship between WT D614G spike antibody binding (x axis) and N501YΔ69–70 (red) and D614G E484K (black) spike variants (y axis) across convalescent COVID-19 patients (n = 305). (B) Line graphs represent the overall binding profile to the D614G S, N501YΔ69–70 S, and D614G E484K S plotted on the comparative line antigens in the same group of convalescent subjects. (C) The correlation plot shows the relationship between WT D614G spike antibody binding (x axis) and the full B.1.1.7 (red), D614G E484K (black), and the D614G K417N (gray) spike variants (y axis) across mRNA-1273-vaccinated individuals at peak immunogenicity (n = 44). (D) Line graphs represent the same data as the overall binding profile to the D614G S, B.1.17 S (red), D614G E484K S (black), and the D614G K417N S (gray) in the group of vaccinated subjects. A Pearson correlation was used to establish the strength of the relationship between WT and VOC antigen binding. Dots represent the mean value of replicates per serum sample. The fold change was calculated as a ratio of WT binding compared with each VOC, which is indicated in the bracket. Matched nonparametric Friedman test with Dunn’s multiple comparisons test was used to calculate the statistical significance for line graphs. Only statistically significant values are shown, and the asterisks represent the adjusted p values: (∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p <0.0001). See also Figures S1–S4.
Figure 2
Figure 2
More robust SARS-CoV-2 VOC-specific Fc-receptor binding is driven by mRNA-1273 vaccination compared with SARS-CoV-2 natural infection (A) The dot plots show the overall FcγR2a, FcγR2b, FcγR3a, and FcγR3b binding to D614G (x axis) and to N501YΔ69–70 (red) and D614G E484K (black) spike variants (y axis) across convalescent COVID-19 patients (n = 305). (B) The line graphs show the overall FcR binding profile to D614G S (green), N501YΔ69–70 S (red), and D614G E484K S (black) in the same group of convalescent subjects. (C) The dot plots show the overall FcγR2a, FcγR2b, FcγR3a, and FcγR3b binding to D614G (x axis) and to B.1.1.7 (black), B.1.351 (red), and P.1 (gray) in mRNA-1273-vaccinated individuals (y axis). (D) The line graph shows the overall FcR binding profile to the D614G, D614G E484K (black), and the D614G K417N (gray) spike variants across mRNA-1273-vaccinated individuals. A Pearson correlation was used to establish the strength of the relationship between wild-type and VOC antigen binding. Dots represent the mean value of replicates per serum sample. The fold change was calculated as a ratio of WT binding compared with each VOC, which is indicated in the bracket. Matched nonparametric Friedman test with Dunn’s multiple comparisons test was used to calculate the statistical significance for line graphs. Only statistically significant values are shown, and the asterisks represent the adjusted p values: (∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p <0.0001).
Figure 3
Figure 3
mRNA-1273 vaccination induces RBD-specific antibody responses to SARS-CoV-2 VOCs (A–H) The dot plots show the relationship of (A) IgG1, (B) IgG3, (C) IgM, and (D) IgA as well as (E) FcγR2a, (F) FcγR2b, (G) FcγR3a, and (H) FcγR3b binding profiles with the WT RBD (x axis) or RBD VOCs (y axis) across mRNA-1273-vaccinated individuals (n = 44). The line graphs show the response to each of the RBDs across the same set of mRNA-1273 vaccine samples. A Pearson correlation was used to establish the strength of the relationship between WT and VOC antigen binding. Dots represent the mean value of replicates per serum sample. The fold change was calculated as a ratio of WT binding compared with each VOC, which is indicated in the bracket. Matched nonparametric Friedman test with Dunn’s multiple comparisons test was used to calculate the statistical significance for line graphs. Only statistically significant values are shown, and the asterisks represent the adjusted p values: (∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001).
Figure 4
Figure 4
SARS-CoV-2-specific antibody-mediated effector functions to VOCs are different across COVID-19 convalescent individuals and mRNA-1273 vaccine recipients (A–F) The functional vaccine-induced immune responses for antibody-mediated complement deposition (ADCD) (A and B), antibody-mediated neutrophil phagocytosis (ADNP) (C and D), and antibody-mediated monocyte phagocytosis (ADCP) (E and F) were analyzed in a cohort of SARS-CoV-2-infected (n = 305) and mRNA-1273-immunized individuals (n = 44). The dot plots represent the average functional activity in the cohort, with each dot representing the mean of two biological replicates. The fold change was calculated as a ratio of WT binding compared with each VOC, which is indicated in the bracket. Matched nonparametric Friedman test with Dunn’s multiple comparisons test was used to calculate the statistical significance for line graphs. Only statistically significant values are shown, and the asterisks represent the adjusted p values: (∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001).
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