COVID-19関連追加(20211018-2

mRNAワクチンに誘導される持続性免疫記憶

★当院HP関連ファイル:

2021922日(強固な記憶B細胞の誘発,口腔咽頭リンパ組織におけるresident memory CD8+ T cell

 

mRNAワクチンはSARS-CoV-2およびその変異ウイルスに対する

持続性免疫記憶を誘発する】

Goel RT, et al. mRNA vaccines induce durable immune memory to SARS-CoV-2 and variants of concern. Science. Oct 14, 2021.

https://doi.org/10.1126/science.abm0829.

Abstract

SARS-CoV-2 mRNAワクチン接種後の免疫記憶の持続性はまだ明らかではない.ここで我々は,SARS-CoV-2ナイーブおよび回復した人を対象に,ワクチン接種後6ヶ月のワクチン反応を縦断的に観察した.抗体はピーク時に比べて減少したが,6ヶ月時点でもほとんどの対象者で検出可能であった我々は,mRNAワクチンによって機能的な記憶B細胞が生成され,その数はワクチン接種後36ヶ月間に増加し,これらの細胞の大部分はアルファ,ベータ,およびデルタ変異ウイルスと交差結合(cross-binding)することがわかったmRNAワクチン接種はさらに抗原特異的CD4+およびCD8+ T細胞を誘導し,早期のCD4+ T細胞は長期的な液性免疫と相関していたまた,既存の免疫を持っている人のワクチン接種に対するリコール反応(recall response)は,抗体減衰率を大きく変えることなく,主に抗体レベルを増加させた.これらの知見を総合すると,SARS-CoV-2およびその変異ウイルスに対して,mRNAワクチン接種後少なくとも6ヶ月間,強固な細胞性免疫記憶が維持されることが明らかになった.

 

 

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 wild-type 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 post-vaccination. (E) Correlation between anti-Spike or anti-RBD IgG and neutralizing titers (D614G = black, B.1.351 = green, B.1.617.2 = orange; statistics were calculated using non-parametric 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 timepoints, 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 vs. 2-phase decay) were determined based on 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) non-parametric Wilcoxon test with 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: SARS-CoV-2 mRNA vaccines generate durable and functional memory B cell responses.(A) Experimental design and (B) Gating strategy for quantifying the frequency and phenotype of SARS-CoV-2-specific memory B cells by flow cytometry. Antigen specificity was determined based on 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 timepoints, and summary plots show mean values with the 95% confidence interval. (D) Frequency of isotype-specific Spike+ and (E) Spike+ RBD+ 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 post-vaccination. (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) Correlation of RBD+ memory B cell frequencies by flow cytometry with PSV neutralizing titers of memory B cell-derived antibodies against B.1.351 and (O) B.1.617.2. For D, E, and G, lines connect mean values at different timepoints. For K, L, N, and O, correlations were calculated using non-parametric Spearman rank correlation. Dotted lines indicate the limit of detection of the assay. Statistics were calculated using unpaired non-parametric 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: Memory B cells induced by mRNA vaccination or infection are cross-reactive to SARS-CoV-2 variants of concern and increase in frequency over time.(A) Experimental design and (B) Gating strategy 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+ RBD++++ (all variant 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 timepoint 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 post-vaccination/seropositivity. Pie charts indicate the fraction of WT RBD+ memory B cells that cross-bind 0, 1, 2, or 3 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 post-vaccination/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) non-parametric Wilcoxon test with BH correction for multiple comparisons. Blue, red, and purple values indicate comparisons within naïve, recovered, or infection only groups. * = p < 0.05, ** = p < 0.01, *** = p < 0.001, **** = p < 0.0001, ns = not significant.

 

 

 

 

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 percent of clones with the indicated VH gene per column. (E) Somatic hypermutation (SHM) density plots (bin width = 1) and (F) boxplots of individual clones across naïve B cells and different antigen-binding memory B cell populations. Data are represented as the percent of mutated VH nucleotides. Number of clones sampled for each population is indicated. For C-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 based on 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 to 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 based on average levels of SHM for all WT RBD vs. RBD++ sequence variant copies within each lineage. (J) SHM levels within overlapping clones. Data are represented as the percent of mutated VH nucleotides for WT RBD and RBD++ sequence copies. Statistics were calculated using paired non-parametric 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: SARS-CoV-2 mRNA vaccines generate durable memory T cell responses.(A) Experimental design and (B) Gating strategy 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 based on co-expression of CD40L and CD200. For CD8+ T cells, antigen specificity was defined based on expression of at least 4/5 activation markers as indicated in A. (C) Frequencies of AIM+ CD4+ T and (D) AIM+ CD8+ T cells over time in PBMC samples from vaccinated individuals. Data were background subtracted using a paired unstimulated control for each timepoint 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 timepoints, 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 based on 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 percent of peak response maintained at memory timepoints 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 based on chemokine receptor expression. (J) Frequencies of AIM+ CD4+ T helper subsets over time. For F and J, lines connect mean values at different timepoints. Dotted lines indicate the limit of detection for the assay. Statistics were calculated using unpaired non-parametric Wilcoxon test with BH correction for multiple comparisons. Correlations were calculated using non-parametric Spearman rank correlation. * = p < 0.05, ** = p < 0.01, *** = p < 0.001, **** = p < 0.0001, ns = not significant.

 

 

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 timepoint 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 pre-vaccine levels in SARS-CoV-2 recovered individuals to evaluate the effect of boosting pre-existing immunity. Lines connect mean values at different timepoints, 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 post-vaccination levels and pre-vaccine baseline. All statistics were calculated using non-parametric Spearman rank correlation.

 

 

 

 

Concluding Remarks

これらの研究は,SARS-CoV-2 mRNAワクチン接種後の免疫記憶の進化についての洞察を与えてくれる.特に,mRNAワクチン接種後3ヶ月〜6ヶ月の間は,たとえ抗体レベルが低下してもSARS-CoV-2特異的記憶B細胞が継続して増加したことから,長期にわたる胚中心反応(14)により,ワクチン接種後少なくとも数ヶ月間は,循環する記憶B細胞が生成され続けていることが示唆される.これらの記憶B細胞の大部分は,B.1.1.7(アルファ),B.1.351(ベータ),B.1.617.2(デルタ)などのVOCsを交差結合(cross-bind)することができ,クローン関係(clonal relationships)から,これらの交差結合記憶B細胞の少なくとも一部は,最初は変異体結合(variant binding)を持たないクローンから体細胞超変異(somatic hypermutation)によって進化したことがわかった.このような変異体結合の進化は,将来の変異体に対する抗体応答を標的としたブースター戦略に影響を与える可能性がある.本研究で示されたように,これらの記憶B細胞は迅速なリコール応答(recall response)を起こすことができ,感染時やブースターワクチン接種時に新たな抗体の供給源となる.さらに,ワクチン接種6ヶ月後の記憶B細胞は,軽症COVID-19から回復した6ヶ月後の記憶B細胞と比較して,VOCsを結合する能力が質的に優れていたことから,mRNAワクチン接種と感染によって生成される免疫には違いがあると考えられる変異体結合は,mRNAワクチンの2回接種後に急速に進展したが,感染後はよりゆっくりと進展し,他のアプローチから得られた結論と一致した(17).持続性のあるB細胞記憶(durable B cell memory)に加えて,SARS-CoV-2特異的記憶CD4+T細胞は,mRNAワクチン接種後36ヶ月間は相対的に安定しており,大多数のワクチン接種者は6ヶ月時点で強固なCD4+T細胞応答を維持していた.早期のCD4+T細胞応答は,3ヶ月および6ヶ月の液性応答と相関しており,ワクチン接種に対する全体的な応答を形成する上でT細胞免疫が果たす役割が明らかになった.これらのデータを総合すると,mRNAワクチン接種後,少なくとも6ヶ月間は細胞性免疫が持続し,ほとんどの人で高品質の記憶B細胞と強力なCD4+T細胞記憶が維持されることが明らかになった

これらのデータはまた,感染予防 vs 重症化予防,入院予防,死亡予防におけるワクチンの効果が異なる可能性を理解する上でも参考になる(10, 11).時間の経過とともに抗体価が減少すると,ワクチン接種によって感染が完全に防止される,あるいは無菌免疫(sterilizing immunity)に近い状態を得る可能性は低くなる.しかし,細胞性免疫の持続性は少なくとも6ヶ月間示されたことから,宿主における最初のウイルス複製と播種を制限し,重症化を防ぐことができる迅速なリコール反応に寄与していると考えられる.最後に,感染後に既存の免疫を持っている人を調べることで,ブースターワクチン接種の効果の可能性について洞察を得ることができた.今回の実験では,感染前の免疫をmRNAワクチンでブーストした場合,主に一過性の抗体価の上昇が見られたが,細胞性免疫記憶の長期的な増加はほとんど見られなかった.抗体減衰率は,ワクチン接種したSARS-CoV-2ナイーブおよび回復した人でほぼ同様であったことから,ワクチンの追加接種は,SARS-CoV-2の免疫記憶の基本的な状況を根本的に変えることなく,一時的に抗体を介した防御を延長することを示唆している.今後は,既接種者へのmRNAワクチンの3回目接種や,ワクチン接種後に発生したSARS-CoV-2感染など,他の種類の免疫ブーストを行った場合にも同様の動態があるかどうかを調べることが重要である.にもかかわらず,これらのデータは,mRNAワクチン接種後6ヶ月の時点で免疫記憶が持続していることを示す証拠であり,ワクチン接種を受けた集団の感染率に関する疫学データの解釈や,ブースターワクチン戦略の実施に関連する.

本研究は,サンプル数が多く,抗原特異的獲得免疫応答の複数の要素を統合的に測定できるなど,全体的に優れた点があるものの、いくつかの限界がある.第一に,全体の対象者数は,高度な免疫プロファイリングを行う研究として十分であるが,疫学研究や第3相臨床試験に比べるとまだ限られている.特に,ワクチン接種後6ヶ月まで完全にサンプリングされていたのは,SARS-CoV-2感染に対する既存の免疫を持つ910人のみであった.第二に,この研究時点では,個人の免疫コンポーネントにとっての反応の動態を完全には捉えていない可能性がある.例えば,6ヶ月以降では,抗体レベルが観察された速度で減衰し続けるのではなく,安定している可能性がある.さらに,ワクチン接種と感染によって誘発される変異体特異的免疫記憶(variant-specific immune memory)の比較は,軽症COVID-19症例に限定されており,より重症疾患は含まれていない.また,感染時のサンプル採取時点は,ワクチン接種の研究とほぼ一致しているが,ほとんどの症例で急性のPCR検査陽性というのではなく,血清検査が陽性となった後に縦断的にサンプルを採取しているため,実際の感染日と完全に一致しているわけではない.CD8+T細胞応答については,AIM assayはワクチン接種後のピーク反応を捉えるのに有効であった; しかし,このassaymemory timepointsで非常に低頻度のCD8+T細胞を検出するのに十分な感度ではないかもしれない.ワクチン接種後の記憶CD8+T細胞応答をさらに調べるためには,MHC tetramersなどの他のアプローチが必要になるだろう.最後に,我々のコホートは若い健康者に偏っている.そのため,今回の結果は、高齢者や慢性疾患および/または免疫が低下している集団におけるワクチン誘発性免疫の持続性を完全には表していない可能性があり,これらの集団における経時的な免疫応答をより定量化するためには,今後の研究が必要である.

 

 

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