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. 2021 Dec 3;374(6572):abm0829.
doi: 10.1126/science.abm0829. Epub 2021 Dec 3.

mRNA vaccines induce durable immune memory to SARS-CoV-2 and variants of concern

Affiliations

mRNA vaccines induce durable immune memory to SARS-CoV-2 and variants of concern

Rishi R Goel et al. Science. .

Abstract

The durability of immune memory after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) messenger RNA (mRNA) vaccination remains unclear. In this study, we longitudinally profiled vaccine responses in SARS-CoV-2–naïve and –recovered individuals for 6 months after vaccination. Antibodies declined from peak levels but remained detectable in most subjects at 6 months. By contrast, mRNA vaccines generated functional memory B cells that increased from 3 to 6 months postvaccination, with the majority of these cells cross-binding the Alpha, Beta, and Delta variants. mRNA vaccination further induced antigen-specific CD4+ and CD8+ T cells, and early CD4+ T cell responses correlated with long-term humoral immunity. Recall responses to vaccination in individuals with preexisting immunity primarily increased antibody levels without substantially altering antibody decay rates. Together, these findings demonstrate robust cellular immune memory to SARS-CoV-2 and its variants for at least 6 months after mRNA vaccination.

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Figures

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Immune memory after mRNA vaccination.
SARS-CoV-2–specific antibody, memory B, and memory T cell responses were measured at six time points after vaccination, highlighting a coordinated evolution of durable immunological memory. B cell memory was also resilient to VOCs and capable of producing new antibodies upon reactivation. IgG, immunoglobulin G; Ab, antibody; NTD, N-terminal domain; TFH, T follicular helper cell; WT, wild-type.
Fig. 1.
Fig. 1.. SARS-CoV-2 mRNA vaccines induce robust antibody responses.
(A) University of Pennsylvania COVID-19 vaccine study design and cohort summary statistics. (B) Anti-spike and anti-RBD IgG concentrations over time in plasma samples from vaccinated individuals. (C) Pseudovirus neutralization titers against WT D614G or B.1.351 variant spike protein over time in plasma samples from vaccinated individuals. Data are represented as focus reduction neutralization titer 50% (FRNT50) values. (D) Comparison of D614G, B.1.351, and B.1.617.2 FRNT50 values at 6 months postvaccination. (E) Correlation between anti-spike or anti-RBD IgG and neutralizing titers (D614G = black, B.1.351 = green, and B.1.617.2 = orange; statistics were calculated using nonparametric Spearman rank correlation). Dotted lines indicate the limit of detection for the assay. For (B) and (C), black triangles indicate time of vaccine doses, fractions above plots indicate the number of individuals above their individual baseline at memory time points, and summary plots show mean values with the 95% confidence interval. Decay rates were calculated using a piecewise linear mixed-effects model with censoring. Changes in decay rate over time (linear versus two-phase decay) were determined on the basis of a likelihood ratio test. Δ Decay Rates indicates whether decay rates were different in SARS-CoV-2–naïve and –recovered groups. Statistics were calculated using unpaired [(B) and (C)] or paired (D) nonparametric Wilcoxon test with Benjamini-Hochberg (BH) correction. Blue and red values indicate comparisons within naïve or recovered groups. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001; ns, not significant.
Fig. 2.
Fig. 2.. SARS-CoV-2 mRNA vaccines generate durable and functional memory B cell responses.
(A and B) Experimental design (A) and gating strategy (B) for quantifying the frequency and phenotype of SARS-CoV-2–specific memory B cells by flow cytometry. Antigen specificity was determined on the basis of binding to fluorophore-labeled spike, RBD, and influenza HA tetramers. (C) Frequencies of SARS-CoV-2 spike+, spike+ RBD+, and influenza HA+ memory B cells over time in PBMC samples from vaccinated individuals. Data are represented as a percentage of total B cells, black triangles indicate time of vaccine doses, fractions below plots indicate the number of individuals above their individual baseline at memory time points, and summary plots show mean values with the 95% confidence interval. (D and E) Frequency of isotype-specific spike+ (D) and spike+ RBD+ (E) memory B cells over time. IgA was assessed on a subset of subjects. (F) Percent IgG+, IgM+, or IgA+ of SARS-CoV-2–specific memory B cells at 6 months postvaccination. (G) Percent CD71+ of total spike+ memory B cells over time. (H) Experimental design for in vitro differentiation of memory B cells into antibody-secreting cells. (I) Anti-spike IgG levels in culture supernatants over time from PBMCs stimulated with PBS control or R848 + IL-2 (n = 4). (J) Anti-spike IgG levels in culture supernatants after 10 days of stimulation (K) Correlation of spike+ memory B cell frequencies by flow cytometry with anti-spike IgG levels from in vitro stimulation. (L) Correlation of RBD+ memory B cell frequencies by flow cytometry with hACE2-RBD binding inhibition from in vitro stimulation. (M) Pseudovirus (PSV) neutralizing titers against B.1.351 and B.1.617.2 variants in culture supernatants after 10 days of stimulation. (N and O) Correlation of RBD+ memory B cell frequencies by flow cytometry with PSV neutralizing titers of memory B cell–derived antibodies against B.1.351 (N) and B.1.617.2 (O). For (D), (E), and (G), lines connect mean values at different time points. For (K), (L), (N), and (O), correlations were calculated using nonparametric Spearman rank correlation. Dotted lines indicate the limit of detection of the assay. Statistics were calculated using unpaired nonparametric Wilcoxon test with BH correction for multiple comparisons. Blue and red values indicate comparisons within naïve or recovered groups. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001; ns, not significant.
Fig. 3.
Fig. 3.. Memory B cells induced by mRNA vaccination or infection are cross-reactive to SARS-CoV-2 VOCs and increase in frequency over time.
(A and B) Experimental design (A) and gating strategy (B) for quantifying the frequency and phenotype of spike subunit and variant-specific memory B cells by flow cytometry. Specific mutations in B.1.1.7, B.1.351, or B.1.617.2 variant RBDs are indicated. (C) Frequencies of spike+ NTD+, spike+ WT RBD+, spike+ all variant+ (all variant RBD binding), and spike+ S2+ memory B cells over time in PBMC samples from vaccinated or convalescent individuals. Data are represented as a percentage of total B cells. (D) Percent NTD+, RBD+, or S2+ of total spike+ memory B cells over time. (E) Representative plots of variant RBD cross-binding gated on spike+ WT RBD+ cells in vaccinated or convalescent individuals. Mean and standard error values at the 6-month time point are indicated. (F) Percent B.1.1.7+, B.1.351+, B.1.617.2+, or all variant+ of WT RBD+ memory B cells over time. (G) Boolean analysis of variant cross-binding memory B cell populations in vaccinated, infected then vaccinated, or infected-only individuals at 6 months after vaccination or seropositivity. Pie charts indicate the fraction of WT RBD+ memory B cells that cross-bind zero, one, two, or three variant RBDs. Colored arcs indicate cross-binding to specific variants. (H) Cross-sectional analysis of variant binding as a percentage of WT RBD+ memory B cells at 6 months after vaccination or seropositivity. For (C), (D), and (F), thick lines indicate mean values, and thin lines represent individual subjects. Statistics were calculated using paired [(C), (D), and (F)] or unpaired (H) nonparametric Wilcoxon test with BH correction for multiple comparisons. Blue, red, and purple values indicate comparisons within naïve, recovered, or infection-only groups, respectively. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001; ns, not significant.
Fig. 4.
Fig. 4.. Variant-binding memory B cell clones use distinct VH genes and evolve through somatic hypermutation.
(A) Experimental design for sorting and sequencing SARS-CoV-2–specific memory B cells. (B) Frequency of RBD++ (B.1.351 variant cross-binding) memory B cells as a percentage of total RBD+ cells. (C) Percentage of sequence copies occupied by the top 20 ranked clones (D20) across naïve B cells and different antigen-binding memory B cell populations. (D) Heatmap and hierarchical clustering of VH gene usage frequencies in memory B cell clones across different antigen-binding populations. Data are represented as the percentage of clones with the indicated VH gene per column. (E and F) Somatic hypermutation (SHM) density plots (E) and boxplots of individual clones across naïve B cells and different antigen-binding memory B cell populations (F). Data are represented as the percent of mutated VH nucleotides. Number of clones sampled for each population is indicated. For (C) to (F), data were filtered on clones with productive rearrangements and ≥2 copies. (G) Venn diagram of clonal lineages that are shared between WT RBD and RBD cross-binding (RBD++) populations. Data were filtered on the basis of larger clones with ≥50% mean copy number frequency (mcf) in each sequencing library. (H) Example lineage trees of clones with overlapping binding to WT and B.1.351 variant RBD. VH genes and CDR3 sequences are indicated. Numbers refer to mutations compared with the preceding vertical node. Colors indicate binding specificity, black dots indicate inferred nodes, and size is proportional to sequence copy number. GL, germline sequence. (I) Classification of SHM within overlapping clones. Each clone was defined as having higher (or equal) SHM in WT RBD binders or RBD++ cross-binders on the basis of average levels of SHM for all WT RBD versus RBD++ sequence variant copies within each lineage. (J) SHM levels within overlapping clones. Data are represented as the percentage of mutated VH nucleotides for WT RBD and RBD++ sequence copies. Statistics were calculated using unpaired nonparametric Wilcoxon test, with BH correction for multiple comparisons in (C) and (F). Notches on boxplots in (F) and (J) indicate a 95% confidence interval of the median. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001; ns, not significant.
Fig. 5.
Fig. 5.. SARS-CoV-2 mRNA vaccines generate durable memory T cell responses.
(A and B) Experimental design (A) and gating strategy (B) for quantifying the frequency of SARS-CoV-2–specific CD4+ and CD8+ T cells by AIM assay. For CD4+ T cells, antigen specificity was defined on the basis of coexpression of CD40L and CD200. For CD8+ T cells, antigen specificity was defined on the basis of expression of at least four of five activation markers, as indicated in (A). (C and D) Frequencies of AIM+ CD4+ T cells (C) and AIM+ CD8+ T cells (D) over time in PBMC samples from vaccinated individuals. Data were background subtracted using a paired unstimulated control for each time point and are represented as a percentage of non-naïve CD4+ or CD8+ T cells. Black triangles indicate time of vaccine doses, fractions above plots indicate the number of individuals above their individual baseline at memory time points, and summary plots show mean values with the 95% confidence interval. Decay rates were calculated using a piecewise linear mixed-effects model with censoring. Δ Decay Rates indicates whether decay rates were different in SARS-CoV-2–naïve and –recovered groups. (E) AIM+ CD4+ T cell memory subsets were identified on the basis of surface expression of CD45RA, CD27, and CCR7. (F) Frequencies of AIM+ CD4+ T cell memory subsets over time. (G) Correlation matrix of memory subset skewing at peak (1-month) response with total AIM+ CD4+ T cell durability at 3 and 6 months. Durability was measured as the percentage of peak response maintained at memory time points for each individual. (H) Correlation between percent of EM1 cells at peak response and 6-month durability. (I) AIM+ CD4+ T helper subsets were defined on the basis of chemokine receptor expression. (J) Frequencies of AIM+ CD4+ T helper subsets over time. For (F) and (J), lines connect mean values at different time points. Dotted lines indicate the limit of detection for the assay. Statistics were calculated using unpaired nonparametric Wilcoxon test with BH correction for multiple comparisons. Correlations were calculated using nonparametric Spearman rank correlation. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001; ns, not significant.
Fig. 6.
Fig. 6.. Immune trajectories and relationships in response to SARS-CoV-2 mRNA vaccination.
(A) UMAP of 12 antigen-specific parameters of antibody, memory B, and memory T cell responses to mRNA vaccination in SARS-CoV-2–naïve and –recovered subjects. Data points represent individual participants and are colored by time point relative to primary vaccine. (B) Kernel density plots of anti-spike IgG, spike+ memory B, AIM CD4+, and AIM+ CD8+ T cells. Red contours represent areas of UMAP space that are enriched for specific immune components. (C) Correlation matrix of antibody and memory B cell responses over time in SARS-CoV-2–naïve subjects. (D) Correlation matrix of T cell and humoral responses over time in SARS-CoV-2–naïve subjects. (E) Decay kinetics of antibody, memory B cell, and memory T cell parameters over time in SARS-CoV-2–naïve and –recovered vaccinees. Data are normalized to prevaccine levels in SARS-CoV-2–recovered individuals to evaluate the effect of boosting preexisting immunity. Lines connect mean values at different time points, ribbons represent the 95% confidence interval of the mean, and dotted lines indicate mean values at baseline. (F) Correlation matrix of baseline memory components and time since infection with antibody recall responses after vaccination in SARS-CoV-2–recovered individuals. Recall responses were calculated as the difference between postvaccination levels and prevaccine baseline. All statistics were calculated using nonparametric Spearman rank correlation.

Update of

  • mRNA Vaccination Induces Durable Immune Memory to SARS-CoV-2 with Continued Evolution to Variants of Concern.
    Goel RR, Painter MM, Apostolidis SA, Mathew D, Meng W, Rosenfeld AM, Lundgreen KA, Reynaldi A, Khoury DS, Pattekar A, Gouma S, Kuri-Cervantes L, Hicks P, Dysinger S, Hicks A, Sharma H, Herring S, Korte S, Baxter AE, Oldridge DA, Giles JR, Weirick ME, McAllister CM, Awofolaju M, Tanenbaum N, Drapeau EM, Dougherty J, Long S, D'Andrea K, Hamilton JT, McLaughlin M, Williams JC, Adamski S, Kuthuru O; UPenn COVID Processing Unit; Frank I, Betts MR, Vella LA, Grifoni A, Weiskopf D, Sette A, Hensley SE, Davenport MP, Bates P, Luning Prak ET, Greenplate AR, Wherry EJ. Goel RR, et al. bioRxiv [Preprint]. 2021 Aug 23:2021.08.23.457229. doi: 10.1101/2021.08.23.457229. bioRxiv. 2021. Update in: Science. 2021 Dec 03;374(6572):abm0829. doi: 10.1126/science.abm0829 PMID: 34462751 Free PMC article. Updated. Preprint.

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