key: cord-1055024-tuz7vgp3
authors: Mysore, Vijayashree; Cullere, Xavier; Settles, Matthew L.; Ji, Xinge; Kattan, Michael W.; Desjardins, Michaël; Durbin-Johnson, Blythe; Gilboa, Tal; Baden, Lindsey R.; Walt, David R.; Lichtman, Andrew H.; Jehi, Lara; Mayadas, Tanya N.
title: Protective heterologous T cell immunity in COVID-19 induced by the trivalent Measles-Mumps-Rubella and Tetanus-Diptheria-Pertussis vaccine antigens
date: 2021-08-14
journal: Med (N Y)
DOI: 10.1016/j.medj.2021.08.004
sha: 9acd54e5c41299755ecdb142ed1ece0811f2734d
doc_id: 1055024
cord_uid: tuz7vgp3

BACKGROUND T cells control viral infection and promote vaccine durability and in COVID-19 associate with mild disease. We investigated whether prior Measles-Mumps-Rubella (MMR) or Tetanus-Diptheria-Pertussis (Tdap) vaccination elicit cross-reactive T cells that mitigate COVID-19. METHODS Antigen presenting cells (APC) loaded ex vivo with SARS-CoV-2, MMR or Tdap antigens and autologous T cells from COVID-19 convalescent and uninfected individuals, and COVID-19 mRNA vaccinated donors were co-cultured and T cell activation and phenotype were detected by IFN-γ ELISpot assays and flow cytometry. ELISA assays and validation studies identified the APC-derived cytokine(s) driving T cell activation. TCR clonotyping and scRNA-seq identified cross-reactive T cells and their transcriptional profile. A propensity-weighted analysis of COVID-19 patients estimated the effects of MMR and Tdap vaccination on COVID-19 outcomes. FINDINGS High correlation was observed between T cell responses to SARS-CoV-2 (Spike-S1 and Nucleocapsid) and MMR and Tdap proteins in COVID-19 convalescent and vaccinated individuals. The overlapping T cell population contained an effector memory T cell subset (TEMRA) implicated in protective, anti-viral immunity and their detection required APC-derived IL-15, known to sensitize T cells to activation. Cross-reactive TCR repertoires detected in antigen-experienced T cells recognizing SARS-CoV-2, MMR and Tdap epitopes had TEMRA features. Indices of disease severity were reduced in MMR or Tdap vaccinated individuals by 32-38% and 20-23% respectively, among COVID-19 patients. CONCLUSIONS Tdap and MMR memory T cells reactivated by SARS-CoV-2 may provide protection against severe COVID-19 disease. FUNDING National Institutes of Health (R01HL065095, R01AI152522, R01NS097719), donation from Barbara and Amos Hostetter and the Chleck Foundation.

A diverse T cell response is essential for early control of acute viral infection and for the generation of B cells producing protective antibodies. CD4 + helper T cells (Th) induce B cells to produce high affinity antibodies to viral protein antigens. Effector CD8 + T cells (cytotoxic T lymphocytes, CTL) and CD4 + T cells eradicate infected, virus-producing cells via direct killing or by secreting cytokines such as interferon- (IFN-, which enhances inflammatory functions that support viral clearance. Antigen presenting cells (APC) such as classical dendritic cells (DC) play a critical role in initiating the cellular immune response by processing and presenting internalized antigen to T cells, which then become activated and proliferate. T cell expansion following productive immunity usually produces a memory T cell population that can persist for decades. Compared to their naïve precursors, memory T cells are more abundant, have a lower threshold for activation and more rapidly reactivate effector functions following antigen encounter. They are also maintained in barrier tissues to rapidly respond to reinfection. Thus, a major goal of vaccines is the induction of strong and durable T and B cell memory. 1 The appearance of SARS-CoV-2 specific CD4 + and CD8 + T cells early after symptom onset 2-5 is associated with rapid viral clearance and mild disease, 3 whereas delayed T cell responses correlated with worse clinical outcomes. 6 Antigen-specific T-cell responses evaluated by exposing peripheral blood mononuclear cells (PBMC) to peptide pools [7] [8] [9] [10] suggest that Spike (the target of most COVID-19 vaccines), nucleocapsid and M envelope proteins are the most relevant CD4 + and CD8 + T cell targets. 7, 8, [10] [11] [12] On the other hand, peptide-MHC tetramer staining, used to screen epitopes for T cell recognition across various HLA alleles, revealed that CD8 + T cells specific to nucleocapsid were present at a higher frequency than those specific for Spike-or non-structural proteins. 13, 14 In several studies, the magnitude of SARS-CoV-2-specific IgG and IgA titers correlated with the SARS-CoV-2 T cell response. 10, 11, 15 Interestingly, memory T cells specific for related coronaviruses such as those that cause the common cold cross-react with SARS-CoV-2 antigens are present in a large percent of SARS-CoV-2 naive individuals. 7, 8, 11, 16, 17 Moreover, profiling of the TCR repertoire of T cells isolated from naive or COVID-19 convalescent patients and expanded in vitro with predicted immunodominant SARS-CoV-2 peptides show clonal expansion of T cells with TCR sequences recognizing peptides from other viruses, including HCMV, HHV-5 and influenza A. 18 The impact of these pre-existing, cross-reactive memory T cells on COVID-19 outcomes is largely unknown. 19 To elucidate whether SARS-CoV-2 infection results in the activation of memory T cells generated by prior MMR or Tdap vaccination, we examined T cell responses to a range of SARS-CoV-2 antigens and antigens present in the MMR and Tdap vaccines in infected, primarily convalescent patients and uninfected individuals ( Table 1) . Robust T cell responses to Spike-S1 and Nucleocapsid were observed in infected individuals. The response to Spike-S2 was low and variable, consistent with prior reports, 16, 17 while no response to the receptor binding domain (RBD) (within Spike-S1) was detected. Responses to MMR and Tdap antigens were present in all individuals but the frequency of T cells reactive to MMR and Tdap antigens trended higher in the infected versus the uninfected group ( Figure 1D ) leading us to examine whether there was a correlation between T cell recall responses to Spike-S1 and Nucleocapsid and individual MMR or Tdap vaccine antigens. A strong correlation was observed in SARS-CoV-2 infected individuals ( Figure 1E ), suggesting that memory T cells generated by prior MMR and Tdap vaccination are reactivated by SARS-CoV-2 infection. Dendritic cells derived from monocytes (moDCs) are a wellcharacterized source of APCs for in vitro T cell assays. In a subset of infected and naive subjects, DCs derived from monocytes (moDC) were loaded with SARS-CoV-2 or vaccine antigens and assessed for their ability to stimulate autologous T cells. The overall T cell response to moDCs was markedly lower ( Figure  S2A ) than for nAPCs ( Figure 1D) , despite comparable expression of HLA-DR and T cell co-stimulatory molecules ( Figure S2B) ; nevertheless, a significant correlation of T cell responses to Spike-S1 and nucleocapsid with MMR and Pertussis (but not Diptheria and Tetanus) antigens was observed ( Figure  S2C ).

CD8 + T EMRA 37 and counteracts CD4 + T cell suppression by T regulatory cells. 38 We found that supernatants from cultures with nAPCs derived from uninfected and uninfected individuals had log fold higher amounts of IL-15, IL-1, and TNF compared to moDC and low levels of IL-18 ( Figure 1F) . To investigate the contribution of these cytokines to T cell activation, we treated nAPC and T cell co-cultures with neutralizing antibodies. Two IL-15 antibodies significantly reduced the number of IFN- secreting T cells, whereas IL-1 plus IL-18 antibodies and a TNF blocking antibody had no effect ( Figure 1G) . A similar analysis of moDCs showed that blocking IL-15 led a small reduction in T cell activation ( Figure S2D ). Together, these data suggest that higer levels of IL-15 secretion explains the superiority of nAPC containing samples over moDCs in promoting T cell recall responses.

To characterize the CD4 + and CD8 + T cell lineages activated by SARS-CoV-2, MMR and Tdap antigens in infected individuals, we used flow cytometry to i) assess cell surface markers that define naïve (T NAIVE ), central memory (T CM ), effector memory (T EM ) and effector memory re-expressing CD45RA (T EMRA ) on CD4 + and CD8 + T cells (gating strategy, Figure S3A , B), and ii) measure markers of activation, homing, function and proliferation in T cells with intracellular IFN-. 39 We found that the majority of SARS-CoV-2, Tdap and MMR antigen responsive CD4 + and CD8 + T cell populations were T EMRA (Figure 2A, B) . Antigen-activated CD4 + T EMRA expressed GPR56, a marker of cytotoxicity, 40 and CX3CR1, a marker associated with peripheral surveillance of infected tissue 41, 42 (Figure 2A ) while CD8 + T EM and T EMRA expressed the activation marker CD69 ( Figure 2B) . A small degree of CD3 + T cell proliferation (2.87±0.12%) was also observed. IL-15 blockade caused a significant decrease in the percentage of IFN- + CD4 + and CD8 + T EM and T EMRA ( Figure 2C) . A similar analysis with SARS-CoV-2 loaded moDC showed that IFN- + T cells were primarily CD4 + T EM and a small population of CD4 + and CD8 + T EMRA ; anti-IL-15 had no effect on the observed frequency of any of these populations ( Figure S3C ).

To further define nAPC-stimulated T cell populations, we visualized the profile of CD4 + T cells using viSNE, which uses t-stochastic neighbor embedding (t-SNE) to generate a two dimensional map of cell relatedness based on marker profile similarity. 43 viSNE depicted an IFN- + CD4 + T cell cluster that was responsive to SARS-CoV-2, MMR or Tdap antigens and had features of T EMRA (Figure 2D, Figure S3D ). The prevalence of CD4 + T EMRA cells ranged from 5 to 13%, which is consistent with the reported variability in the frequency of T EMRA (<0.3-18% of total CD4 + T cells) even in the absence of infection. 44 The cluster containing CD4 + T EMRA was significantly reduced after anti-IL-15 treatment ( Figure 2D ). An overlapping region among the three sets of antigen was not dectected for CD8 + T cells (not shown), although inclusion of antibodies to additional markers could identify such overlaps. Collectively, this analysis provides evidence of a distinct population of responsive T EMRA that is similarly enriched in co-cultures with nAPCs presenting SARS-CoV-2, MMR or Tdap antigens and whose activation depends on IL-15 stimulation.

T EMRA are prevalent in convalescent COVID-19 patients. 45 Our data suggest that T EMRA in SARS-CoV-2 infected individuals include a cross-reactive, memory T cell population whose detection ex vivo relied on activation in the presence of IL-15.

To determine whether COVID-19 vaccinated individuals also exhibit an increase in MMR and Tdap specific T cells, we evaluated three uninfected healthy controls before and 2.5 months after receiving the second dose of the Moderna (mRNA-1273) COVID-19 vaccine encoding the SARS-CoV-2 Spike protein.

Vaccination produced a marked increase in the frequency of IFN- + secreting T cells reactive to Spike-S1 that correlated with a pronounced enhancement in the number of T cell clones reactive to MMR and Tdap antigens ( Figure 3A) ; similar results were obtained when antigen was presented by moDCs ( Figure S4 ). As expected, there was no response to nucleocapsid in COVID-19 vaccinated subjects ( Figure 3A) . A high proportion of the IFN- + , Spike-S1 reactive CD4 + and CD8 + T cells expressed T EMRA markers (Figure 3B ,C) as was observed with SARS-CoV-2 infected individuals (Figure 2A, B) . However, unlike infected J o u r n a l P r e -p r o o f 6 individuals, SARS-CoV-2 reactive IFN- + CD4 + T EM was high while the frequency of IFN- + CD8 + T EMRA that are CD69 + was low in COVID-19 vaccinated subjects. T cell dependent antigen recognition relies on the interaction of TCRs in CD8 + and CD4 + T cells with  peptide loaded Class I or II HLA, respectively. TCR and  chains contain 3 hypervariable loops, termed  complementary determining regions (CDR) , of which CDR3 is unique for each clone and the main contributor to peptide-MHC specificity. Thus, T cells that express the same pair of CDR3 nucleotide sequences are highly likely to recognize the same antigen and to be derived from the same clonally expanded T cell. To identify and characterize cells with cross-reactive TCR clonotypes we performed single cell RNA sequencing coupled with T-cell receptor V(D)J sequencing. We profiled 3 replicate batches, each containing T cells isolated from a COVID-19 convalescent patient and stimulated with SARS-CoV-2, MMR or Tdap antigen loaded nAPCs, and T cells from a healthy, uninfected individual that was exposed to SARS-CoV-2 antigen loaded nAPCs as our control for non-antigen specific responses. The characteristics of the profiled convalescent patient and healthy, uninfected control samples are detailed in Table 1 . After data processing and filtering (see Methods), 15,931 cells remained (range, 833 to 1,663 per sample). Principal component analysis was used to reduce the dimensionality of the dataset for graph based clustering and uniform manifold approximation and projection (UMAP) visualization. This resulted in two large groups of T-cells, one from the healthy controls and the other from the COVID-19 convalescent patients ( Figure 4A ), suggesting that the major source of variation in gene expression was antigen-specific T cell activation.

Next, we determined whether T cell clones responsive to SARS-CoV-2 antigens in COVID-19 convalescent patients express the same clonotype CDR3 sequences as T cells responsive to MMR and Tdap antigens. Sequence analysis identified 12,613 unique clonotypes, of which 90 clonotypes shared TCRs (Table S1) . These 90 clonotypes clustered in UMAP space ( Figure 4B ) and were expressed by 1,323 cells (8.3% of the cells profiled) ( Figure 4B ). Each clonotype was unique to a replicate batch. All three replicate batches had cells with shared CDR3 sequences, but such cells were most prevalent in replicate 2, which contained 84 of the 90 shared clonotypes (among 1,301 total cells) ( Figure 4B ). The percent of cross-reactive T cells was 0.15%, 10% and 0.023% in subjects 1, 2 and 3, respectively. The majority (60 of 90) of cross-reactive clonotypes where observed after stimulation with each of the three antigens (SARS-CoV-2, MMR, Tdap), with the remaining 30 being observed after stimulation with SARS-CoV-2 or MMR, and SARS-CoV-2 or Tdap ( Figure 4B ). In addition to these candidate heterologous SARS-CoV-2 CDR3 clonotypes, 10 additional clonotypes where common with MMR and Tdap stimulation ( Figure 4B ). To determine whether the T cells with shared CDR3 sequences are bonafide antigen-responsive T cells, we assessed the expression of mRNAs encoding IL-2RA (CD25), a canonical CD4 + and CD8 + T cell activation marker that encodes for the IL-2 receptor, 46 and activation-induced markers CD134 (OX40, TNFRS4) and CD137 (TNFRS9, 4-1BB), 47 previously reported to be expressed by SARS-CoV-2 reactive T cells. 11 We found that IL-2RA, CD134 and CD137 expression overlapped with antigen stimulated T cells and interestingly, within this group, was significantly higher in those clusters with shared CDR3 sequences as assessed by differential expression analysis. IFN- is not only a robust activation marker for a subset of effector memory T cells following direct TCR activation, but expression of the IFN- mRNA (IFNG) is well-correlated with IFN- protein levels 27 and IL-2 is upregulated by signals from TCR and CD28. 48 Thus, we examined IFNG and IL-2 expression levels. Notably, IFNG expression overlapped with clusters sharing CDR3 sequences, while IL-2 expression did not. Also, differential expression analyses showed that the level of IFNG was markedly higher while IL-2 is significantly lower in clusters with shared CDR3 compared to other activated or control T cells ( Figure 4C and Table S2 ). Together, these studies suggest that high expression of CD134, CD137 and IFN- and low IL-2 distinguishes activated T cells with shared CDR3 sequences from other antigen-activated T cells in the COVID convalescent group.

We next used graph-based clustering to partition cells with the characteristics of cells with shared CDR3 sequences to examine their gene expression profile. This identified 30 cell populations (clusters). Clusters 2, 15, and 18 ( Figure 4D ) were markedly enriched for cells with shared CDR3 sequences (69%, 59%, and 54% of these clusters, respectively). Twelve other clusters contained a smaller (≤ 15%) fraction of cells 7 with shared CDR3 sequences (Table S1). We next sought to identify a gene expression signature for cells in clusters 2, 15, and 18. These clusters contained a total of 1810 cells, of which 1,154 (63.7%) were cells with shared CDR3 sequences (84 of the 90 identified clonotypes). Differential expression analysis of these clusters relative to all other clusters identified 386 genes that were expressed at significantly higher levels ( Table S2) . The top 50 genes for cells with shared CDR3 sequences (by statistical significance) are shown in a heatmap ( Figure 4E) . Notably, of these genes, 13 were identified as T EMRA markers in Patil et al. 49 , and 6 were identified as T EMRA markers in Szabo et al. 46 . (Figure 4E , Table S2 ).

Investigation of TCR and  chain combinations within cells with shared CDR3 sequences shows they are mostly unique pairings, with only one  chain pairing with 2  chains (represented by the 'curved' arcs) ( Figure 4F and Table S1 ).

There is growing epidemiological evidence that vaccinations can impact morbidity and mortality beyond their effect on the diseases they prevent. 20, 21 In COVID-19, a significant association between MMR vaccination status and lower COVID-19 disease severity was observed 50 and high titers of mumps antibodies were more likely to be associated with asymptomatic or less severe COVID-19 disease. 51 These studies were however limited by small sample size 50, 51 or survey research methodology 50 and may be confounded by co-variables that influence both the likelihood of getting vaccinated with MMR or Tdap and the risk of progressing to severe COVID. To address these challenges, we performed a retrospective cohort study with overlap propensity score weighting. All patients were seen at the Cleveland Clinic Health System in Ohio or Florida and tested positive for COVID-19 between March 8, 2020, and March 31, 2021 (73,582 COVID-19 positive patients). The cohort included 11,483 patients vaccinated with MMR and 36,793 patients vaccinated with Tdap (Table S3) , a skewing that is consistent with vaccination scheduling, as the single trivalent MMR is given in childhood and only became available in 1971, 52 whereas the Tdap is given as a booster every 10 years. Our propensity score matching 53 was effective at making the two groups comparable as evidenced by the identical scores across patient groups for both the MMR and Tdap comparisons ( Table 2) . After adjusting for 44 patient characteristics ( Table 2) , two primary endpoints reflecting disease severity (COVID-related hospitalization, and COVID-related admission to the intensive care unit or death) were decreased in patients previously vaccinated for MMR by 38% and 32%, respectively, and in patients previously vaccinated for Tdap by 23% and 20%, respectively at the 5% level of significance ( Figure 5A , Table 2 ). Differential effects of sex and age on the observed relationships between Tdap and MMR and disease outcomes were not hypothesized a priori, but were explored given the emerging literature on the topic. 54, 55 At the 5% level of significance, we found that receiving the MMR or Tdap was more highly associated with a decreased rate of hospitalization in women than in men ( Figure  5B ). We also found that Tdap was more highly associated with a decrease in rate of hospitalization in younger (age < 50 years) versus older individuals ( Figure 5C ). If we conservatively apply the Bonferroni method to adjust for multiple testing, only the sex difference for MMR and hospitalization remains significant at the 5% level. The time interval from vaccination (either MMR or Tdap) to positive COVID-19 test was not significantly associated with outcome, possibly because this cohort is dominated by individuals who had MMR or Tdap vaccines within the past 20 years. Thus, this may not be the ideal dataset to test the effect of interval from vaccination to disease.

J o u r n a l P r e -p r o o f 8

Our findings provide definitive cellular and molecular evidence that heterologous adaptive immunity exists between SARS-CoV-2 and antigens present in Tdap and MMR vaccines. We observe enhanced in vitro T cell recall responses to Tdap and MMR antigens in individuals with a history of SARS-CoV-2 infection or uninfected individuals immunized with the COVID-19 vaccine, and a strong correlation between the magnitude of the effector memory T cell response activated by exposure to APCs loaded with SARS-CoV-2 antigens and Tdap or MMR vaccine antigens. We identify identical TCR clonotypes in T cells activated by SARS-CoV-2, Tdap or MMR antigens, thus providing clear molecular evidence for adaptive heterologous immunity. We also demonstrate that the cross-reactive T cells resemble cytotoxic T EMRA , known to contribute to anti-viral immunity. Heterologous immunity can variously alter disease outcomes by providing enhanced immunity or by exacerbating immunopathology or lessening viral control. 20 Our propensityweighted analysis of a large COVID-19 patient cohort adjusted for multiple patient characteristics revealed that severe disease outcomes were reduced in MMR or Tdap vaccinated individuals.

Our ability to detect cross-reactive T cells was enabled by three features of our approach: 1) read out on IFN generation, which predominantly identifies activated effector memory versus naïve T cells; 27,28 2) use of highly immunogenic nAPC that generate IL-15, 22 which sensitizes T cells with low TCR binding affinity for antigens; [34] [35] [36] [37] [38] 56 and 3) an epitope unbiased approach in which the relevant peptide epitopes were generated by physiological antigen-processing rather than exposure to a limited set of viral peptide epitopes, 7-10 which may not represent the specificities of cross-reactive clones generated during a natural SARS-CoV-2 infection. To date, T cell functional responses to vaccines have been difficult to evaluate due to the lack of sensitive in vitro assays. Our approach, described herein, may help bridge this gap.

Heterologous immunity with examples of protection against widely divergent pathogens has been documented in mice and humans. 21, 57, 58 Innate heterologous immunity can result from antigen-nonspecific functional epigenetic rewiring of monocyte/macrophage precursors in response to one pathogen that induces immunity to a second unrelated infection. 57 In humans, this has been best studied in the context of Bacille Calmette-Guérin vaccine for tuberculosis, which may afford some protection against SARS-CoV-2. 59-61 Adaptive heterologous immunity is mediated by memory T cells and antibodies and has been documented for infections by or immunization against bacteria and viruses in experimental mouse models and in humans. 20 ,62 Yet, to our knowledge, definitive identification of the relevant epitopes or the crossreacting lymphocyte clones in humans has not been previously achieved. Our data provide direct molecular evidence of overlapping TCRs in T cell clones that respond to SARS-CoV-2 proteins and Tdap and MMR vaccine antigens. The high frequency of overlap in TCR CDR3 sequences across viral (MMR) and bacterial (Tdap) antigens in SARS-CoV-2 infected individuals suggests that heterologous immunity is prevalent in humans. This is consistent with the estimate that effective immunity during a human's lifetime requires that each of the unique 10 7 -10 8 TCRs recognize up to 10 6 theoretical peptides, 63-65 the finding that TCR polyspecificity is a general characteristic of T cell recognition 66 and the presence of large numbers of memory CD4 + T cells that recognize viral peptides in unexposed adults. 62 A study of human T cell crossreactivity between unrelated HLA-A2-restricted influenza A virus-and Epstein-Barr virus-encoded epitopes suggests that cross-reactive epitopes bind with lower affinity and may theoretically lead to the broadening of the TCR repertoire. 67 Our studies using highly immunogenic nAPCs that release IL-15, which can lower the threshold for TCR activation likely facilitated the in vitro detection of expanded low affinity, crossreactive MMR and Tdap memory T cells in SARS-CoV-2 infected individuals.

In mice, a prior infection with various unrelated pathogens, lymphocytic choriomeningitis virus (LCMV), Pichinde virus (PICV), murine cytomegalovirus (MCMV), influenza A virus (IAV) or Bacillus Calmette-Guerin (BCG) resulted in a one to two log reduction in organ viral titers in vaccinia virus (VACV) infected mice at 3-4 days after infection. [68] [69] [70] However, protective heterologous immunity was observed only in a subset of mice even though they were genetically identical and depended on the repertoire of CDR3 sequences that bind a given epitope in the cross-reactive CD8 + T cell memory pool of each animal. 21, 71 Interestingly, protective immunity was seen with as little as 0.6% cross-reactive CD8 + T cells 72, 73 and was reliant on IFN- generated by CD8 + and CD4 + memory T cells. 70, 74 Thus, both individual private CDR3 specificity and the number of cross-reactive IFN-  memory T cells can determine the outcome of heterologous infection between viruses. These studies align with our findings in human samples; we show that the cross-reactive T cell pool is comprised of IFN- producing CD8 + and CD4 + T cells and observe low (0.023%) to high (10%) frequency of cross-reactive T cells with shared TCR-CDR3 clonotypes in the 3 individuals evaluated. In mice, heterologous immunity is not necessarily reciprocal. For example, mice previously infected with VACV were not protected from LCMV, MCMV or PICV; 70 this was linked to an increase in the number of cross-reactive memory CD8 + T cells in LCMV versus VACV immunized mice. 72 Moreover, a T cell clone recognizing a cross-reactive epitope in one virus does not necessarily react with that epitope in the heterologous virus. 21 Thus, prior COVID-19 vaccination will not necessarily provide immunity to measles, mumps and rubella, or diphtheria, tetanus and pertussis toxins.

The presence of T cell cross-reactivity in COVID-19 is strengthend by reported comparative in silico analyses of SARS-CoV-2 proteins and vaccine peptides. A sequence in tetanus toxin protein significantly matched a region of SARS-CoV-2 Spike predicted to interact with an MHC-I receptor encoded by the corresponding HLA while a segment of the Measles virus hemagglutinin significantly overlapped with a segment of the SARS-CoV-2 ORF7b protein with predicted T-cell antigenicity. 75 A comprehensive study by Reche et al. 76 , indicates that combination Diptheria-Tetanus-Pertussis vaccines are significant sources of T-cell cross reactivity to the SARS-CoV-2 orferome. Overall sequence similarities between SARS-CoV-2 and MMR vaccine antigens have also been reported, 77-79 albeit CD4 + or CD8 + T cell epitopes were not specifically examined in these studies.

We found that the phenotype and transcriptional profile of the cross-reactive T cell clusters primarily comprise IFN- + T cells that are IL-2and have features of T EMRA , a cytotoxic effector memory T cell subset unique to humans that are implicated in protective anti-viral immunity. 41, 42, 80, 81 For example, the frequency of CD4 + T EMRA in Dengue virus correlates with vaccine-elicted protection 40, 80, 82 and CD8 + T EMRA may control viral load during early HIV infection. 81 In influenza, pre-existing IFN- + , IL-2 -CD8 + T EMRA T cells crossreactive with different viral subtypes correlate with less severe illness in individuals lacking pre-existing humoral immunity 83 and a large percent of these T EMRA express CCR5 upon viral exposure, which is critical for recruitment of CD8 + T cells to the lung during respiratory viral infection. 84 Supporting evidence that the lung localized T EMRA may elicit viral clearance comes from a study in tissue harvested from organ donors, which shows that CD8 + T cell T EMRA represent 20-30% of CD8 + T cells in the lung, a frequency that is comparable to that in spleen and blood. 85 viral immunity particularly to pathogens that evolve to evade recognition by neutralizing antibodies. 1 In COVID-19, additional SARS-CoV-2 variants in the Spike protein may emerge such as the highly transmisable delta variant. 93 This, in turn, could trigger additional waves of resurgence 94 and potentially inter-species transmission. In our studies, the robust correlation of MMR and Tdap reactive memory T cells to Spike-S1 and the more invariant nucleocapsid protein that contains the highest density of SARS-CoV-2 epitopes recognized by CD8 + T cells 13 predicts that nucleocapsid mediated reactivation of MMR and Tdap memory cells could provide immunity to SARS-CoV-2 Spike variants. The markedly enhanced T cell responses to MMR and Tdap antigens not only in infected but also vaccinated individuals, suggests that reactivated MMR and Tdap memory T cells may provide protective heterologous T cell immunity following COVID-19 vaccination. The observed prevalence of heterologous immunity in our studies may have implications for vaccine development against future novel pathogens, as the effectiveness of vaccines may correlate with their ability to harness pre-existing memory T cells generated by prior infections or vaccines. Interestingly, in mice, T cells specific for cross-reactive epitopes in the memory pool are maintained while non-cross-reactive epitopes are selectively lost, which could shape the response to future viral infections. 95 We posit that intentional MMR or Tdap vaccine-induced heterologous immunity to SARS-CoV-2 could enhance the effectiveness and durability of COVID-19 vaccines by generating an expanded population of SARS-CoV-2-specific memory T cells that respond vigorously to the vaccines and, in countries where COVID-19 vaccines are not yet available, provide protection from severe disease.

In conclusion, our studies provide evidence of broad cross-reactivity between T cells responsive to SARS-CoV-2, MMR and Tdap antigens in humans. The breadth of cross-reactive CDR3 sequences to these three distinct pathogens suggests that adaptive heterologous immunity is prevalent in humans. The correlation of MMR and Tdap vaccination in COVID-19 patients with a decrease in disease severity may reflect the observed cross-reactivity of MMR and Tdap vaccine antigens not only with Spike-S1 protein but also with the relatively invariant nucleocapsid protein. A signature of cytotoxic effector memory T cells (T EMRA ) in responding cross-reactive cells, and the reported prevalence of these cells in recovered COVID-19 patients, 45 suggests that this T cell subset may promote robust, heterologous anti-viral immunity in COVID-19. Finally, our studies predict that MMR or Tdap vaccination together with approved COVID-19 vaccines may afford greater and more durable protection, particularly against emerging Spike variants, than the vaccines alone.

Our ex vivo correlation analysis of T cell activation on nAPCs loaded with viral antigens from MMR, Tdap and SARS-CoV-2 indicates that responses to these antigens are interdependent and thus infers that heterologous immunity exists between MMR, Tdap and SARS-CoV-2 antigens. However, definitive evidence of cross-reactivity requires the stimulation of T cells with APCs loaded with viral antigen A, isolation of the activated clones and restimulation with APCs loaded with viral antigen B. We were unable to conduct this well-validated conventional method because, to date, we have been unable to preserve nAPCs over the weeks required to examine the response of T cells to the first and then second antigen challenge. Nonetheless, our correlative analysis along with the TCR clonotyping which showed that CDR3 sequences, known to be unique for each T cell clones and the main contributors of peptide-MHC specificity, are present in T cells activated by 3 different sets of trivalent antigens provides strong evidence that cross-reactive T cells are present. Another limitation of our in vitro approach is the use of highly immunogenic nAPCs, which may overestimate the extent of cross-reactivity that occurs in individuals if antigen presentation in vivo is not primarily driven by similarly potent APCs. Inter-individual variability in this parameter is also likely. Although our risk assessment was completed with a large, well-characterized cohort of COVID-19 patients, a limitation is that the history of MMR and/or Tdap vaccination may be underreported, which could lead to some degree of misclassification. Our study also cannot definitively determine if remote vaccination with MMR or Tdap associates with disease outcomes as the patient cohort was dominated by individuals with MMR or Tdap vaccinations within the past 20 years. Finally, we cannot distinguish the contribution of adaptive versus innate heterologous immunity in the estimated effects of MMR and Tdap vaccination on disease outcomes. K. and L.J. declare that they have no competing interests to disclose. D.R.W has a financial interest in Quanterix Corporation, a company that develops an ultra-sensitive digital immunoassay platform. He is an inventor of the Simoa technology, founder of the company and serves on its Board of Directors. The anti-SARS-CoV-2 Simoa assays in this publication have been licensed by Brigham and Women's Hospital to Quanterix Corporation. T.G. receives royalty payments from Brigham and Women's Hospital for the antibodies assay technology. T.M. has a financial interest in neuAPC Therapeutics, a company that will develop AAC for the generation of neutrophil-derived antigen presenting cells (nAPC) and serves as one of its scientific advisors. V.M., X.C. and T.M. have a provisional patent on the generation of immunogenic nAPCs and methods of use therof.

Blood was collected from uninfected (UNI) and PCR-confirmed, SARS-CoV-2 Infected (INF) donors. Plasma was analyzed for antibodies to SARS-CoV-2 antigens and cytokines. Blood was divided and treated with Isotype control or AAC for 2 hrs to induce nAPCs and neutrophils were then isolated and cultured in GM-CSF for 2 days. Isotype treated controls remain neutrophils. PBMCs were harvested to isolate CD3 + T cells and monocytes, which were cultured in cytokines to generate dendritic cells (moDC). Neutrophils (Isotype), nAPC (AAC) and moDC were loaded without or with antigen and cocultured with autologous T cells on IFN- ELISpot plates for 18hrs. Loaded antigens included Spike S1 subunit (Sp1), Spike S2 subunit (Sp2) (1-4) and infected (1-9) individuals were co-cultured at a 1:5 ratio with autologous T cells and Spike-S1 on IFN-ELISpot plates and the number of IFN + spots were counted. C) IgG titers in sera of uninfected and infected donors to SARS-CoV-2 antigens, Sp1, NC, Spike S1 and S2 (Spike) and RBD. Red arrows in B)-C) identify samples with IFN- + T cells but no detectable SARS-CoV-2 specific IgG titers. D) nAPCs generated from 8 uninfected and 18 infected donors were loaded with vehicle (-) or indicated individual SARS-CoV-2. MMR or Tdap antigens and analyzed for T cell responses as in B). Representative images of wells with IFN-  spots are shown (right). *p<0.05; **p<0.005 by two-tailed Mann-Whitney test with Bonferroni correction for multiple comparisons. E) A correlation of Spike-S1 or Nucleocapsid derived IFN-  spots with indicated vaccine antigens (circles) and percent of nAPCs generated (diamonds), which varies between individuals, in infected donors was conducted using Spearman's rank correlation coefficients (r). F) Cytokine levels detected in the supernatants of neutrophils treated with isotype (neut) or AAC (to generate nAPCs) and cultured for 48hrs, and monocyte derived dendritic cells (moDC). **p<0.005 using two-way analysis of variance and Bonferroni's multiple comparison test. G) As in B), ELISpot assays measuring IFN- secretion by T cells co-cultured with nAPCs pulsed with combined SARS-CoV-2 (Spike S1, Nucleocapsid, RBD), between SARS-CoV-2 (SARS), MMR and TDP antigens (purple). The phenotype of the overlapping population between the antigens was defined by evaluating the following markers, CD4, CD45RA, CCR7, CD27, GPR56, CX3CR1 and IFN-and shown as heatmaps along with a continuous scale. See also Figure S3 .

A) Blood was analyzed from three individuals approximately 3 months before and 2.5 months after receiving the Moderna mRNA-based COVID-19 vaccine. nAPC generated from blood neutrophils were loaded with indicated individual SARS-CoV-2, MMR or Tdap (TDP) antigens and IFN- secretion by cocultured autologous T cells was evaluated on ELISpot plates as described in Figure 1 . Images of one well with IFN-  spots representative of triplicates are shown. Asterisk (*) denotes too many IFN-  spots to count. B-C) The phenotype of T cells was examined by flow cytometry as in Figure 2A 46 (column labelled "Szabo"). Rows and columns were grouped by overall expression pattern using hierarchical clustering. Lollipops (right) highlight cytotoxic T cell effector molecule genes. F) Circos plot of sequences with shared CDR3 sequences. Each sector on the innermost track corresponds to an  chain (TRA, blue) or  chain (TRB, red). The width of a sector is proportional to the number of times the  or  chain sequence occurs. An arc between an  and  chain indicates these sequences are combined in a single CDR3 sequence. The antigen is shown in the third track. The Seurat cluster is shown in the fourth track; not all clusters have cells with shared CDR3 sequences so fewer than 30 clusters are shown. The preponderance of straight lines spanning across the plot shows that in nearly all cases, a given  chain is combined with only one  chain, and vice versa. See also Table S1 and S2.

Overlap Propensity Score Weighted-Analysis Odds Ratios with 95% Confidence Intervals presented for the whole cohort (A), and then stratified by gender (B) and age (C). The upper limit of the 95% confidence intervals for the adjusted odds ratios was less than 1 for both risk of hospitalization and risk of transfer to the intensive care unit or death for patients with a history of prior vaccination for either MMR or Tdap. See also Table S3 . 

Further information and requests for resources and reagents will be fulfilled by the lead contact, Tanya N. Mayadas (tmayadas@rics.bwh.harvard.edu).

This study did not generate new unique reagents.

 Sequence data that support the findings of this study have been deposited in the Gene Expression Omnibus (GEO) database and are publicly available as of the date of publication. An accession number is listed in the key resource  Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

The patient datasets used in the current study are available upon request under appropriate data use agreements with the specific parties interested in academic collaboration. For further information, please contact Drs. Lara Jehi (JEHIL@ccf.org) or Michael Kattan (kattanm@ccf.org)

Blood samples for in vitro studies were obtained from consented healthy, self-reporting SARS-CoV-2 uninfected volunteers under a Mass General Brigham Institutional Review Board (IRB)-approved protocol (1999P001694). COVID-19 patients signed informed consent to participate in a Mass General Brigham IRB-approved COVID-19 observational sample collection protocol (2020P000849).

The retrospective cohort study risk assessment used the Cleveland Clinic COVID-19 Enterprise Registry, which was created on March 17, 2020 as a resource for COVID-19 research across the health system. More than 300 data points are extracted from the electronic health record through a combination of manual pulls and validated natural language processing algorithms on all patients tested for COVID-19 in our facilities in Ohio and Florida (18 regional hospitals and 220 outpatient locations). 96, 97 A waiver of informed consent (oral or written) from study participants in the COVID-19 registry was granted by the Cleveland Clinic Health System institutional review board. For this study, we included all COVID positive patients diagnosed between March 2020 and March 31, 2021. Infection with SARS-CoV-2 was confirmed by laboratory testing using the Centers for Disease Control and Prevention reverse transcription-polymerase chain reaction SARS-CoV-2 assay.

J o u r n a l P r e -p r o o f 20 SARS-CoV-2 serological Simoa assays for IgG against four viral antigen Spike 1 subunit (S1), Spike (stabilized ectodomain of Spike with mutated furin cleavage site), Nucleocapsid, and RBD were prepared and preformed as previously described. 32 Briefly, plasma samples were diluted 4000-fold in Homebrew Detector/Sample Diluent (Quanterix Corp.). Four antigen-conjugated capture beads were mixed and diluted in Bead Diluent, with a total of 500,000 beads per reaction (125,000 of each bead type). Biotinylated antihuman IgG antibodies (Bethyl Laboratories A80-148B) were diluted in Homebrew Detector/Sample Diluent to final concentrations of 7.73ng/mL. Streptavidin--galactosidase (SβG) was diluted to 30 pM in SβG Diluent (Quanterix). The serology assay was performed on an HD-X Analyzer (Quanterix) in an automated three-step assay. Average Enzyme per Bead (AEB) values were calculated by the HD-X Analyzer software. All samples were measured in duplicates.

Plasma cytokines were measured in plasma samples using the CorPlex Cytokine Panel (Quanterix Corp), which included sample diluent buffer. Plasma samples were diluted 4-fold in sample diluent buffer and assays were performed following the CorPlex manufacturer protocols. Each CorPlex cytokine panel kit was analyzed by the SP-X Imaging and Analysis System (Quanterix Corp.). All samples were measured in duplicates.

Blood and serum collection: Peripheral blood was drawn into tubes containing trisodium citrate, citric acid and dextrose (Vacutainer ACD Solution A, BD). Serum was obtained by drawing blood into BD Vacutainer™ Venous Blood Collection Tubes SST, followed by centrifugation at 2500xg for 30 min and removal of the resulting supernatant.

Anti-FcRIIIB (3G8) (Biolegend) was conjugated to FITC-Ovalbumin (#O23020, Thermofisher) by Biolegend as a custom order and referred to as antibody-antigen conjugate (AAC). Importantly, Ovalbumin in the AAC served as a model antigen in mouse models but is irrelevant for our human studies.

Human blood treatments to generate neutrophil derived APC (nAPC): 10mls human blood was supplemented with GM-CSF (10 ng/ml) for 30 min at 37C followed by addition of 30µg AAC or FITC-IgG isotype control for 2 hrs at 37C. Blood was then incubated with Hetasep (STEMCELL Technologies) according to manufacturer protocols to deplete red blood cells and enrich leukocytes. Neutrophils were isolated from the leukocyte-rich plasma layer using a Easysep Neutrophil enrichment kit (STEMCELL Technologies) and placed in RPMI media, which was supplemented with 10% autologous serum, penicillin/streptomycin (50 U/ml penicillin and 50 mg/ml streptomycin) and 20ng/ml GM-CSF. After 48 hours, cells were harvested using Accutase and evaluated by flow cytometry for surface markers of APCs.

Monocyte isolation and culture to generate monocyte-derived DCs (moDC): Peripheral blood mononuclear cells were isolated using Lymphoprep (Stemcell technologies, Canada). Monocytes were positively selected by anti-CD14-coated magnetic beads (Miltenyi biotec, Germany) to >98% purity. Monocytes were cultured in complete medium supplemented with GM-CSF (50ng/ml) and IL-4 (10ng/ml). Cells were harvested after 7 days and evaluated for surface markers CD11c, HLA-DR and CD14.

T cell isolation: PBMCs were isolated from peripheral blood using Lymphoprep (Stemcell technologies, Vancouver, Canada) density gradient medium, aliquoted in 1ml cryopreservation tubes at a concentration of 5 million cells/ml and frozen. The tubes were thawed after 2 days to isolate CD3 + T cells for co-culture studies. For isolation of CD3 + T cells, negative selection was performed using EasySep Human T cell isolation kit (#17951, Stemcell technologies, Vancouver, Canada). The CD3 + T cells were labelled with 1µM Cell Trace Violet dye (#C34557, ThermoFisher Sientific) according to manufacturer's instructions just prior to setting up their co-cultures.

Co-culturing nAPC/moDC and T cells: nAPCs derived from neutrophils and moDCs were harvested and co-cultured with Cell trace Violet labelled CD3 + T cells isolated from PBMCs at a ratio of 1:5 (nAPC:T cells) on a IFN ELISpot plate and incubated for 18h. Additionally, the co-cultures were incubated with vehicle alone (PBS) or the following antigens individually or in combinations as indicated in the Result section: SARS-COV-2 antigens 5µg/ml Spike-S1 subunit (S1-fc), 8.85µg/ml Spike S2 subunit (S2-his), 7.8µg/ml Spike S1 receptor binding domain (RBD-fc), 2.35µg/ml Nucleocapsid protein (NC his); inactivated Measles, Mumps, Rubella viral preparations at 5µg of total protein/ml; 5µg/ml of heat inactivated Pertussis toxin, Diphtheria toxin, Tetanus toxoid. T cells alone were incubated with a cocktail of PMA and ionomycin (Biolegend, Cat #423301) as a positive control.

Antibody blocking treatments: Neutralizing antibodies were used as follows. Anti-IL15(1) (Invitrogen, #16-0157-82) at 5µg/ml, anti-IL15(2) (R&D systems, #MAB247) at 5µg/ml, anti-IL1 (R&D systems, #MAB201) 1.6µg/ml and anti-IL18 (MBL, #D044-3) at 1.8µg/ml. Antibodies remained during the entire period of coculture.

ELISpot kits to measure the secretion of human IFN- (R&D Systems, #EL285) were used according to manufacturer's protocols. Fresh CD3 + T cells (Cell trace violet labelled) isolated from PBMCs and nAPCs were plated in triplicates at a ratio of 1:5 (nAPC:CD3 + T cells) per well and incubated with indicated antigens and/or blocking antibodies for 18h. Samples were processed according to manufacturer's protocol and results were quantitated using an ELISpot reader (CTL ImmunoSpot® S6 Fluorescent Analyzer).

Results are a mean of triplicate wells and reported as number of spots per million T cells.

Forty-eight hour cultures of isotype or AAC (also containing unconverted neutrophils because unlike mouse, 22 human nAPCs are non-adherent) treated neutrophils and 7 day generated monocyte-derived DCs (moDC) were cultured for an additional 72h and supernatants were collected and analyzed for cytokine and chemokine levels using human cytokine 42-plex discovery assay (Eve Technologies, Calgary, AB).

Flow cytometry was performed on a FACSCanto II. FCS (flow cytometry standard format) 3.0 data file was used to export data that was analyzed using FlowJo (Mac version 10.7). Compensation controls were created for each fluorochrome. BD multicolor compensation beads and cells were used to set up compensation for the individual fluorochromes. For all experiments, cells were stained with the Fixable Viability Dye eFluor 780 (ThermoFisher) to gate out dead cells. Forward and side scatter gates were used to discriminate doublets and debris (FSC-A, FSC-H, SSC-A x SSC-H). Matched isotypes were used as controls and negative gating was based on FMO (fluorescence minus one) strategy. Only viable cells were included for the studies.

For surface staining, single cell suspensions in FACS buffer (PBS supplemented with 2% FCS and 2mM EDTA) were incubated with human TruStain FcX for 10 min at 4C. Samples were incubated with the indicated fluorochrome-conjugated antibodies for 30 min at 4C, washed with PBS and fixed with 1% paraformaldehyde.

To evaluate surface markers on nAPCs, antibodies to the following were used: CD15, CD66b, CD11c, HLA-DR, CD40, CD86 and CCR7. Within the viable single cell population, CD11c+ and HLA-DR+ events were further gated for CD66b and CD15 expression. The CD11c+, HLA-DR+, CD15+ and CD66b+ population was further analyzed for CD40, CD86 and CCR7 markers.

To evaluate cell surface markers on T cells, antibodies to the following markers were used: CD3, CD4, CD8, CD45RA, CCR7, CD27, GPR56, CX3CR1, IFN-. Subsets of T cells were classified based on CD45RA, CCR7 and CD27. Live, singlet CD3 + cells were assessed for proliferation by monitoring CFSE stained T cells for Cell trace violet signal dilution. For detection of intracellular IFN-, T cells were treated with Brefeldin A (3ug/ml) for 5h, stained with surface markers, fixed for 30min, permeabilized with BD Perm/Wash (BD Biosciences) and stained with anti-IFN-. Cells were washed with permeabilization buffer and analyzed by flow cytometry.

Sample files were exported as FCS 3.0 files from FACSDiva and imported into flowJo v.10.7.1 software for subsequent analysis. The following plug-ins were used: Downsample (1.1), t-distributed stochastic neighbor embedding (tSNE) and FlowSOM (2.6). To visualize the high-dimensional data in two dimensions, the t-SNE algorithm was applied on data. Cells were selected for each sample at random, downsampled and merged into a single expression matrix prior to tSNE analysis. tSNE was performed unsupervised from a maximum of 5,000 randomly selected cells from each sample, with a perplexity set to 80, using the implementation of tSNE plugin in flowJo. Events were identified by gating on live, singlet intact CD3 + CD4 + or CD8 + T cells and were included in generating the tSNE plots. The Barnes-Hut implementation of t-SNE with 1,000 iterations, a perplexity parameter of 30, and a trade-off θ of 0.5, was used for applying the dimensionality reduction algorithm. The output was in the form of 2 columns corresponding to t-SNE dimension 1 and dimension 2. t-SNE maps were generated by plotting each event by its t-SNE dimensions in a dot-plot.

Intensities for markers of interest were overlaid on the dot-plot to show the expression of those markers on different cell islands and facilitate assignment of cell subsets to these islands using FlowSOM plugin. Samples were examined by running tSNE with the following markers: CD4, CD45RA, CCR7, CD27, GPR56, CX3CR1, IFN-. Phenotypic characteristics of the cell island are shown as heatmaps.

Sample preparation: nAPCs were co-cultured with CD3 + T cells isolated from PBMCs at a ratio of 1:5 (nAPC : T cells) and incubated for 18h. The co-cultures were incubated with SARS-COV-2 antigens (5µg/ml S1-fc, 7.8µg/ml RBD-fc, 2.35µg/ml NC his) or Measles, Mumps and Rubella viral preparations (5µg of total protein/ml) or 5µg/ml of Diphtheria toxin, Tetanus toxoid and Pertussis toxin. After 18hrs, the cells were harvested using Accutase, aliquoted in 1ml cryopreservation tubes at a concentration of 1.2 million cells/ml and frozen at -80C. Samples were sent to MedGenome, Inc. Foster City, CA, for library preparation and sequencing. performing all the necessary barcode processing, mapping to the Human reference genome (GRCh38-2020-A, GENCODE v32/Ensembl 98) and unique molecular identifier (UMI) expression counting; each batch contained an estimated > 7K cells. The gene-cell matrix of all cells was analyzed in R v4.0.3 with Seurat v3.9.9. 99 Individual antibody sample hashtags were used to distinguish cells from the four samples within batch (Normal, Convalescent Covid, MMR and Tdap), requiring at least 100 antibody reads present per cell and tag specificity of >80% to a single sample. V(D)J Clonotypes were linked to the scRNA expression by common cell barcode. The following cell filtering criteria were then applied: gene number greater than 1,000, unique UMI count between 1,000 and 50,000 and mitochondrial gene content < 10%. After filtering, a total of 15,931 cells were left across all 12 samples for the subsequent analysis, of which 14,362 have a V(D)J clonotype defined. All samples were processed together and the matrix was normalized using 'LogNormalize' method with default parameters. Then, the top 2,000 variable genes were identified using the 'vst' method from Seurat's FindVariableFeatures function which is used for scaling, dimensionality reduction and clustering. The variables batch, S.Score and G2M.Score from the CellCycleScoring function, percent.mito, and nFeature_RNA were regressed out using ScaleData and PCA was performed. Finally, UMAP and graph-based clustering was performed using the top 50 principal components for visualizing the cells. A cluster resolution of 1.75 with 23 clusters was chosen for downstream analysis. Differential gene expression analysis: Wilcoxon rank-sum tests as implemented in Seurat v. 4.0.0 (FindMarkers function) were used to perform differential gene expression (DEG) analysis. For enriched clusters (2, 15, 19) containing cells with candidate heterologous T cells (as outlined above), DEGs were generated relative to all of the other clusters. A gene was considered significant with adjusted P < 0.05. Only genes upregulated relative to all other cells were considered as markers for the purposes of this analysis.

The heatmap plot was created using the R package ComplexHeatmap, version 2.6.2. The Circos plot was generated using the R package circlize, version 0.4.12.

Statistical analyses for cell-based assays were performed using Graphpad prism 8 (LaJolla, CA), and JMP10 software (SAS Institute, Inc, USA). All the data included in the studies are expressed as mean ± SEM. *P <0.05 and **P <0.005 was considered significant.

All descriptive statistics were reported as counts (percentages) or median (interquartile ranges [IQRs]). For comparison of demographic variables and comorbidities among cohorts, Wilcoxon signed-rank tests were used for numeric variables, while χ2 or Fisher exact tests were used for categorical variables.

Overlap propensity score weighting was performed to address potential confounding in comparing non-MMR/Tdap vaccinated and MMR/Tdap vaccinated patients given their baseline differences. The overlap propensity score weighting method was chosen given its benefits of preservation of numbers of individuals in each group and of achieving higher levels of precision in the resulting estimates. This methodology is preferred when the propensity score distributions among the groups are dissimilar and when the propensity scores are clustered near the extremes (i.e., close to zero or one). A propensity score for being MMR/Tdap vaccinated was estimated from a multivariable logistic regression model. For the outcomes of hospital and J o u r n a l P r e -p r o o f 24 intensive care unit (ICU) admission or death of COVID-19 test-positive patients, the propensity score logistic regression model included covariates that were found to be associated with the outcome in our previous work.

The overlap propensity score weighting method was then applied where each patient's statistical weight is the probability of that patient being assigned to the opposite group. Overlap propensity score weighted logistic regression models were used to investigate associations between vaccine status and the probability of hospital admission for COVID-19, and ICU admission or death for COVID-19 illness. The results are thus reported as weighted proportions, odds ratios, and 95% confidence intervals.

To address the effect of the time interval between date of vaccine and date of COVID test to the outcomes, we used the time interval as a covariate into multivariable logistic regression models, adjusting for the same covariates as with the overlap propensity scoring models. The time interval is modeled with restricted cubic splines because of suspected nonlinear effects.

Statistical analyses were performed using R 4.0. P values were 2-sided, with a significance threshold of 0.05. Figure 5 .

 T cell responses to SARS-CoV-2, MMR and Tdap vaccine proteins are highly correlated.

 SARS-CoV-2, MMR and Tdap antigen-experienced T cells share identical TCRs. 

Other Healthy con. COVID conv.

con. COVID conv. 

T Cell Memory: Understanding COVID-19

Antigen-Specific Adaptive Immunity to SARS-CoV-2 in Acute COVID-19 and Associations with Age and Disease Severity

Early induction of functional SARS-CoV-2-specific T cells associates with rapid viral clearance and mild disease in COVID-19 patients

Phenotype and kinetics of SARS-CoV-2-specific T cells in COVID-19 patients with acute respiratory distress syndrome

Characterization of pre-existing and induced SARS-CoV-2-specific CD8(+) T cells

Acute SARS-CoV-2 Infection Impairs Dendritic Cell and T Cell Responses

SARS-CoV-2-specific T cell immunity in cases of COVID-19 and SARS, and uninfected controls

SARS-CoV-2-derived peptides define heterologous and COVID-19-induced T cell recognition

Divergent SARS-CoV-2-specific T-and B-cell responses in severe but not mild COVID-19 patients

Broad and strong memory CD4(+) and CD8(+) T cells induced by SARS-CoV-2 in UK convalescent individuals following COVID-19

Targets of T Cell Responses to SARS-CoV-2 Coronavirus in Humans with COVID-19 Disease and Unexposed Individuals

Robust T Cell Immunity in Convalescent Individuals with Asymptomatic or Mild COVID-19

Unbiased Screens Show CD8(+) T Cells

Patients Recognize Shared Epitopes in SARS-CoV-2 that Largely Reside outside the Spike Protein

CD8+ T cell responses in convalescent COVID-19 individuals target epitopes from the entire SARS-CoV-2 proteome and show kinetics of early differentiation

Detection of SARS-CoV-2-Specific Humoral and Cellular Immunity in COVID-19 Convalescent Individuals

SARS-CoV-2-reactive T cells in healthy donors and patients with COVID-19

Selective and cross-reactive SARS-CoV-2 T cell epitopes in unexposed humans

Cross-viral protection against SARS-CoV-2?

Does common cold coronavirus infection protect against severe SARS-CoV-2 disease?

Virus-Induced T Cell-Mediated Heterologous Immunity and Vaccine Development

Vaccination and heterologous immunity: educating the immune system

FcgR engagement reprograms neutrophils into antigen cross-presenting cells that elicit acquired immunity

Successful Vaccines

Monocyte-Derived Dendritic Cells as Antigen-Presenting Cells in T-Cell Proliferation and Cytokine Production

Human in vivo-differentiated monocyte-derived dendritic cells

Choosing and preparing antigenpresenting cells

Combined Single-Cell Measurement of Cytokine mRNA and Protein Identifies T Cells with Persistent Effector Function

Single-cell transcriptomics identifies an effectorness gradient shaping the response of CD4(+) T cells to cytokines

Breadth of concomitant immune responses prior to patient recovery: a case report of non-severe COVID-19

Clinical features of patients infected with 2019 novel coronavirus in Wuhan

Seroprevalence and humoral immune durability of anti-SARS-CoV-2 antibodies in Wuhan, China: a longitudinal, population-level, cross-sectional study

Ultrasensitive high-resolution profiling of early seroconversion in patients with COVID-19

Inflammatory cytokines as a third signal for T cell activation

IL-7-and IL-15-mediated TCR sensitization enables T cell responses to self-antigens

IL-15/IL-15Ralpha-mediated avidity maturation of memory CD8+ T cells

The deubiquitinase Otub1 controls the activation of CD8(+) T cells and NK cells by regulating IL-15-mediated priming

IL-15 boosts the function and migration of human terminally differentiated CD8+ T cells by inducing a unique gene signature

IL-15 augments TCR-induced CD4+ T cell expansion in vitro by inhibiting the suppressive function of CD25 High CD4+ T cells

Comparative Multi-Donor Study of IFNgamma Secretion and Expression by Human PBMCs Using ELISPOT Side-by-Side with

Unique phenotypes and clonal expansions of human CD4 effector memory T cells re-expressing CD45RA

Cytotoxic CD4 T Cells: Differentiation, Function, and Application to Dengue Virus Infection

Dengue virus infection elicits highly polarized CX3CR1+ cytotoxic CD4+ T cells associated with protective immunity

viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia

An Integrated Workflow To Assess Technical and Biological Variability of Cell Population Frequencies in Human Peripheral Blood by Flow Cytometry

Immunological memory to SARS-CoV-2 assessed for up to 8 months after infection

Single-cell transcriptomics of human T cells reveals tissue and activation signatures in health and disease

Activation-induced Markers Detect Vaccine-Specific CD4(+) T Cell Responses Not Measured by Assays Conventionally Used in Clinical Trials. Vaccines (Basel) 6

Regulation of interleukin-2 gene enhancer activity by the T cell accessory molecule CD28

Precursors of human CD4(+) cytotoxic T lymphocytes identified by single-cell transcriptome analysis

Relationship between MMR vaccination and severity of Covid-19 infection. Survey among primary care physicians

Analysis of Measles-Mumps-Rubella (MMR) Titers of Recovered COVID-19 Patients

Measles, mumps, and rubella virus vaccine (M-M-RII): a review of 32 years of clinical and postmarketing experience

Overlap Weighting: A Propensity Score Method That Mimics Attributes of a Randomized Clinical Trial

The non-specific and sex-differential effects of vaccines

Influence of immune aging on vaccine responses

Control of memory CD8(+) T cell longevity and effector functions by IL-15

Trained Innate Immunity, Epigenetics, and Covid-19

Heterologous Immunity: Role in Natural and Vaccine-Induced Resistance to Infections

BCG-induced trained immunity: can it offer protection against COVID-19?

BCG-Induced Cross-Protection and Development of Trained Immunity: Implication for Vaccine Design

Trained Immunity: a Tool for Reducing Susceptibility to and the Severity of SARS-CoV-2 Infection

Virus-specific CD4(+) memoryphenotype T cells are abundant in unexposed adults

A direct estimate of the human alphabeta T cell receptor diversity

A single autoimmune T cell receptor recognizes more than a million different peptides

TCRs with Distinct Specificity Profiles Use Different Binding Modes to Engage an Identical Peptide-HLA Complex

T cell receptor crossreactivity as a general property of T cell recognition

Broad cross-reactive TCR repertoires recognizing dissimilar Epstein-Barr and influenza A virus epitopes

Specific history of heterologous virus infections determines anti-viral immunity and immunopathology in the lung

CD4 T-cell-mediated heterologous immunity between mycobacteria and poxviruses

Protective heterologous antiviral immunity and enhanced immunopathogenesis mediated by memory T cell populations

Private specificities of CD8 T cell responses control patterns of heterologous immunity

Evaluation of non-reciprocal heterologous immunity between unrelated viruses

A functional and kinetic comparison of antiviral effector and memory cytotoxic T lymphocyte populations in vivo and in vitro

Memory CD8+ T cells in heterologous antiviral immunity and immunopathology in the lung

In silico comparative study of SARS-CoV-2 proteins and antigenic proteins in BCG, OPV, MMR and other vaccines: evidence of a possible putative protective effect

Potential Cross-Reactive Immunity to SARS-CoV-2 From Common Human Pathogens and Vaccines

Does Early Childhood Vaccination Protect Against COVID-19? Front Mol Biosci 7

MMR Vaccine and COVID-19: Measles Protein Homology May Contribute to Cross-Reactivity or to

Homologous protein domains in SARS-CoV-2 and measles, mumps and rubella viruses: Preliminary evidence that MMR vaccine might provide protection against COVID-19

Rapid Induction and Maintenance of Virus-Specific CD8(+) TEMRA and CD4(+) TEM Cells Following Protective Vaccination Against Dengue Virus Challenge in Humans

Human immunodeficiency virus type 1 (HIV-1)-specific CD8+ T(EMRA) cells in early infection are linked to control of HIV-1 viremia and predict the subsequent viral load set point

Dengue-specific CD8+ T cell subsets display specialized transcriptomic and TCR profiles

Cellular immune correlates of protection against symptomatic pandemic influenza

The chemokine receptor CCR5 plays a key role in the early memory CD8+ T cell response to respiratory virus infections

Distribution and compartmentalization of human circulating and tissue-resident memory T cell subsets

A small jab -a big effect: nonspecific immunomodulation by vaccines

Non-specific immunological effects of selected routine childhood immunisations: systematic review

Childhood Immunization and COVID-19: An Early Narrative Review. Front Public Health 8

Exploratory analysis of immunization records highlights decreased SARS-CoV-2 rates in individuals with recent non-COVID-19 vaccinations

Vaccination history for diphtheria and tetanus is associated with less severe COVID-19

Development and validation of a model for individualized prediction of hospitalization risk in 4,536 patients with COVID-19

Immune memory in convalescent patients with asymptomatic or mild COVID-19

Immune Evasion of SARS-CoV-2 Emerging Variants: What Have We Learnt So Far? Viruses

Resurgence of COVID-19 in Manaus, Brazil, despite high seroprevalence

T cell immunodominance and maintenance of memory regulated by unexpectedly cross-reactive pathogens

Individualizing Risk Prediction for Positive Coronavirus Disease 2019 Testing: Results From 11,672 Patients

Association of Use of Angiotensin-Converting Enzyme Inhibitors and Angiotensin II Receptor Blockers With Testing Positive for Coronavirus Disease 2019 (COVID-19)

Massively parallel digital transcriptional profiling of single cells

Comprehensive Integration of Single-Cell Data

We would like to thank Brigham and Women's Hospital and MassCPR for their support in collecting samples from SARS-CoV-2 infected patients, Colin Heyson for statistical advice, Pascal Yazbeck and Chi-An Cheng for technical assistance, and Jon Aster for scientific discussion and advice. 

J o u r n a l P r e -p r o o f 11