Distinct baseline immune characteristics associated with responses to conjugated and unconjugated pneumococcal ...

Abstract

Pneumococcal infections cause serious illness and death among older adults. The capsular polysaccharide vaccine PPSV23 and conjugated alternative PCV13 can prevent these infections; yet, underlying immunological responses and baseline predictors remain unknown. We vaccinated 39 older adults (>60 years) with PPSV23 or PCV13 and observed comparable antibody responses (day 28) and plasmablast transcriptional responses (day 10); however, the baseline predictors were distinct. Analyses of baseline flow cytometry and bulk and single-cell RNA-sequencing data revealed a baseline phenotype specifically associated with weaker PCV13 responses, which was characterized by increased expression of cytotoxicity-associated genes, increased frequencies of CD16⁺ natural killer cells and interleukin-17-producing helper T cells and a decreased frequency of type 1 helper T cells. Men displayed this phenotype more robustly and mounted weaker PCV13 responses than women. Baseline expression levels of a distinct gene set predicted PPSV23 responses. This pneumococcal precision vaccinology study in older adults uncovered distinct baseline predictors that might transform vaccination strategies and initiate novel interventions.

Baseline innate and T cell populations are correlates of protection against symptomatic influenza virus infection independent of serology

Article 17 August 2023

Distinct immunological and molecular signatures underpinning influenza vaccine responsiveness in the elderly

Article Open access 12 November 2022

Response to the conjugate pneumococcal vaccine (PCV13) in patients with chronic lymphocytic leukemia (CLL)

Article 17 June 2020

Main

Streptococcus pneumoniae (pneumococcus) infections lead to life-threatening diseases and are responsible for thousands of hospitalizations and deaths annually in the United States¹. Infants and older adults have the highest rates of invasive pneumococcal disease, with an ~10% mortality rate particularly affecting older adults according to reports from the Centers for Disease Control and Prevention reports. Two types of pneumococcal vaccines were approved by the Food and Drug Administration (FDA) for use in this population: the capsular polysaccharide vaccine Pneumovax® (PPSV23) and protein-polysaccharide conjugate vaccines (for example, Prevnar® (PCV13)). PPSV23 contains capsular polysaccharide antigens for 23 serotypes that elicit antibody responses in the absence of CD4⁺ T cell collaboration². Responses to unconjugated polysaccharides are predominantly mediated by the activation of marginal zone (MZ) B cells, which possess hypermutated immunoglobulin genes and express high levels of complement receptor 2 (CD21)^3,4. MZ B cells are not fully mature in newborns and children, resulting in limited success of unconjugated polysaccharide vaccines^3,5,6. Furthermore, older individuals show a marked decrease in frequencies of total memory and MZ B cells, which might contribute to the age-related decline of responses⁷. After activation, MZ B cells terminally differentiate into IgM-, IgG- and IgA-secreting plasma cells⁸. Although MZ B cell activation and IgM production are considered to be T cell independent, IgG and IgA class switching might rely on the presence of non-cognate T cells that secrete IL-21 and/or trigger the CD40/CD40L signaling axis⁸. Conjugated vaccines have been developed (for example, PCV13) to enhance immunogenicity. PCV13 is composed of polysaccharides for the most prevalent 13 serotypes conjugated to a nontoxic variant of diphtheria toxin CRM197. PCV13 induces T cell-dependent activation and expansion of B2 follicular cells, promoting the generation of memory B cells and differentiation of long-lived plasma cells^9,10,11.

Conjugated pneumococcal vaccines are effective among children and young adults¹ and in preventing invasive disease among older adults¹², yet their efficacy declines with age^13,14,15. PCV13 is 90% effective in infants and children, which decreases to 72.8% among older adults. Similarly, the efficacy of PPSV23 is 54% for adults¹⁶. In 2021, other conjugated vaccines were approved, including PCV15 and PCV20, to extend the range of serotypes covered and to simplify pneumococcal immunizations¹⁷. In the United States, the current recommendation for older adults is to receive either PCV20 or PCV15 followed by PPSV23 1 year later.

Peripheral blood leukocyte gene expression studies revealed transcriptional differences in responses to PPSV23 and influenza vaccines among healthy adults^18,19. However, these studies did not include conjugated pneumococcal vaccines and excluded older adults partially due to the complexity of evaluating their responses. To address these gaps, we recruited 39 healthy pneumococcal vaccine-naive adults ≥60 years old who received PCV13 or PPSV23. We collected blood from this cohort longitudinally and studied their baseline immune phenotypes and immune responses following vaccination by using multiple assays. Our systems vaccinology approach uncovered distinct baseline gene expression modules associated with PCV13 and PPSV23 responses, which can pave the way toward more precise administration of these vaccines.

Results

Serological responses of older adults to PCV13 and PPSV23

During the 2017–2018 seasons, 39 older adults (≥60 years of age with no history of pneumonia disease or vaccination) were recruited and randomized to receive either a dose of PCV13 (ten men and nine women) or PPSV23 (ten men and ten women). Vaccines were administered from May to early fall to avoid overlap with the influenza vaccine season. Donors in each arm of the study and the men and women in each arm were comparable in terms of age, body mass index (BMI), cytomegalovirus (CMV) seropositivity and frailty index (Fig. 1a). Donors were not on any confounding treatments, but some were on medications for common chronic diseases (Supplementary Table 1a,b).

**Fig. 1: Functional antibody response to PCV13 and PPSV23 in older adults.**

Blood samples were collected 7 d before vaccination (baseline) and at 1, 10, 28 and 60 d after vaccination. Previously, we showed that transcriptional innate responses to PPSV23 peaked at day 1, whereas adaptive responses peaked at day 7 and remained high until day 14 in adults¹⁹. Hence, days 1 and 10 were chosen to capture the innate and adaptive responses while also ensuring participant safety and adherence to the institutional review board recommendations regarding the maximum volume of blood one can collect from older adults (550 ml over an 8-week period or 69 ml per week). We generated longitudinal flow cytometry and RNA-sequencing (RNA-seq) data to study immune responses to these two vaccines (Fig. 1a). Pneumococcal vaccine responses can be assessed by measuring antibody levels using enzyme-linked immunosorbent assays (ELISAs) or antibody function using opsonophagocytic activity (OPA). OPA measures the ability of antibodies to effectively opsonize bacteria and is ideal for quantifying responses because it mimics the in vivo mechanisms of antibody protection²⁰ and is hence considered state of the art for FDA approvals²¹. Unlike children, many older adults already possess high ELISA antibody levels before vaccination, making functional OPA assays more attractive in this population²⁰. Therefore, we used OPA to quantify antibody responses from serum (at baseline and 28 d after vaccination). Because OPA assays require a substantial volume of serum, we prioritized the 13 most prevalent serotypes: the 12 shared serotypes and serotype 6A from PCV13 (Supplementary Table 2)²². Quantifying the common serotypes enabled a side-by-side comparison of these two vaccines.

We developed three multivariate measures to quantify vaccine responses: (1) strength of the response (the sum of fold change values between baseline and day 28 for all serotypes), (2) extent (the number of serotypes (of 13) to which the donor elicits significant (that is, an OPA titer of ≥8) responses) and (3) rank (the rank of an individual's vaccine responsiveness in the cohort based on aggregate responses for all serotypes, where higher ranks represent stronger responses; Fig. 1b,c, Extended Data Fig. 1a,b and Supplementary Table 2d,h). To assess whether quantifying PPSV23 responses using 13 serotypes fully captures responsiveness to this vaccine, we reanalyzed OPA titers for all 23 serotypes from another study¹¹, which revealed a strong and significant correlation between ranking using 13 serotypes and ranking using all serotypes (R = 0.91, P = 0.013; Extended Data Fig. 1g). Strength and extent of responsiveness were highly correlated with the rank, while capturing different aspects of vaccine responses (Extended Data Fig. 1c). BMI, frailty index and number of concomitant medications were not associated with responsiveness to either vaccine (Extended Data Fig. 1d and Supplementary Table 1a,b).

After vaccination, OPA titer levels significantly increased for both vaccines cumulatively (Fig. 1d) and for each serotype (Extended Data Fig. 1e). Stronger PCV13 responses were detected for serotype 4 and the PCV13-specific serotype 6A (Extended Data Fig. 1e). Although PPSV23 does not contain serotype 6A, it induced increased 6A responses potentially due to cross-reactivity with serotype 6B. Baseline OPA titers were comparable between the two cohorts (P = 0.2); however, individuals vaccinated with PCV13 had stronger responses (Fig. 1d; P = 0.05) even after excluding serotype 6A (P = 0.089; Extended Data Fig. 1f). Level of responsiveness varied from one individual to another. In the group treated with PCV13, top responder PREV18 (female, 67 years old) responded significantly to all serotypes except for 19A, whereas the bottom responder PREV89 (male, 73 years old) elicited significant responses to only two serotypes (Fig. 1b). In PPSV23, top responder PVAX90 (male, 64 years old) responded to ten serotypes, whereas the bottom responder PVAX25 (female, 71 years old) did not respond significantly to any of the tested serotypes (Fig. 1c). Our ranking strategy captured this heterogeneity at the donor level. There was a significant inverse correlation between baseline OPA titer levels and fold change in titers (Extended Data Fig. 2a–c), in alignment with previous studies²³. There was a significant negative correlation between cumulative OPA titers at baseline and vaccine responsiveness rank (Extended Data Fig. 2d). Given this association, we calculated the maximum residual after baseline adjustment (maxRBA) values (Extended Data Fig. 1a,b), which correct for baseline titer levels by modeling fold increase in titer levels as an exponential function of the baseline titer levels. maxRBA and rank correlated significantly for both vaccines (Extended Data Fig. 1c).

Donor age was negatively associated with both strength (Fig. 1e; R = −0.71 and P = 0.00067 for PCV13, R = −0.31 and P = 0.18 for PPSV23) and rank (Extended Data Fig. 2d). Although male and female donors were comparable in terms of age, frailty and BMI (Supplementary Table 1b), women mounted stronger responses to the PCV13 vaccine (P = 0.053 for strength, P = 0.079 for rank; Fig. 1f), which was not observed for PPSV23 (Fig. 1g). Four of five top responders were women and four of five bottom responders were men in the group treated with PCV13. Overall, these data showed that both pneumococcal vaccines induced strong antibody responses; yet, at the individual level, the degree of responsiveness was variable. For PCV13, donor age significantly contributed to this variation, and there was a trend for stronger responsiveness for women. Interestingly, neither age nor sex was significantly associated with PPSV23 responsiveness.

PCV13 and PPSV23 induce similar transcriptional responses

We generated longitudinal bulk RNA-seq data at baseline and days 1, 10 and 60 from peripheral blood mononuclear cells (PBMCs) from 31 donors (15 PCV13 and 16 PPSV23), including strong responders (SRs) and weak responders (WRs) for each vaccine while also balancing female and male samples. Samples from 30 donors that passed quality control were used in differential analyses. Gene expression profiles after vaccination were compared to those at baseline (day −7; Supplementary Table 3). There were no significant transcriptional changes for days 1 or 60. However, at day 10, 50 and 41 genes were differentially expressed compared to baseline (false discovery rate (FDR) < 0.05), respectively, for PCV13 and PPSV23 (Extended Data Fig. 3a). Upregulated genes after vaccination included immunoglobulin heavy chain genes IGHG2 and IGHA2 and plasmablast-associated genes JCHAIN and MZB1 (Fig. 2a). The activity of these genes peaked at day 10 and returned to baseline levels by day 60 (Fig. 2b). A cumulative plasmablast activity score using plasma cell-specific genes¹⁹ (n = 33 genes) confirmed a significant and comparable increase in the expression of plasmablast-associated genes at day 10 for both vaccines that returned to baseline levels at day 60 (Fig. 2b). IGHG2, encoding the IgG2 isotype, was among the most upregulated genes for both vaccines (Fig. 2c). IGHA2, encoding the IgA2 isotype, was also upregulated for both vaccines (Fig. 2c and Extended Data Fig. 3b), in alignment with the serology data²⁴.

**Fig. 2: Plasmablast response elicited after vaccination at day 10 in PBMCs.**

Pneumococcal vaccines upregulated distinct immunoglobulin genes compared to the influenza vaccine. Reanalysis of prior PBMC RNA-seq data on influenza vaccine responses in younger adults showed upregulated expression of IGHG1 and IGHG3 at day 7, whereas pneumococcal vaccines upregulated the expression of IGHA2 and IGHG2 (Fig. 2d and Extended Data Fig. 3c). Transcriptional activation of plasmablast-associated genes significantly correlated with PCV13 responsiveness (R = 0.57, P = 0.034), mainly driven by IGHG2 expression (Extended Data Fig. 3d,f), which was not the case for PPSV23 (Extended Data Fig. 3e,f). Together, transcriptional profiling before and after vaccination revealed that both pneumococcal vaccines induced significant and similar plasmablast responses 10 d after vaccination, including increased transcription of genes encoding IgG2 and IgA2 antibody isotypes, contrasting with those (IgG1, IgG3 and IgA1) induced by the influenza vaccine.

Baseline frequencies of T_H1 and T_H17 cells are linked to PCV13 responses

We performed a longitudinal flow cytometry analysis of different cell populations in freshly isolated PBMCs at baseline (day −7) and after vaccination at days 1, 10, 28 and 60 to study B cell (naive, memory and plasmablast cells), CD4⁺ T cell (naive, type 1 helper T (T_H1), type 2 helper T (T_H2), interleukin-17 (IL-17)-producing helper T (T_H17), IL-10-producing helper T (T_H10), follicular helper T (T_FH), type 1 T_FH (T_FH1), type 2 T_FH (T_FH2) and IL-17-producing T_FH (T_FH17) cells) and dendritic cell (DC) subsets (type 2 classical DCs (cDC2s), type 1 cDCs (cDC1s) and plasmacytoid DCs (pDCs); Supplementary Table 4a and Extended Data Fig. 4a,b). Despite the robust plasmablast transcriptional signature, their absolute numbers were only marginally increased at day 10 for both vaccines (Fig. 3a, top). There were no significant changes in other B cell subsets after vaccination or between the two cohorts (Extended Data Fig. 4b). Among the studied T cell subsets, only ICOS⁺ T_FH cell numbers significantly increased at day 10 for both vaccines (Fig. 3a, bottom, and Extended Data Fig. 4b). There were no significant changes in other T cell or DC subsets after vaccination (Extended Data Fig. 4b). Cell numbers were similar between the two cohorts for all cell types both at baseline and after vaccination (Extended Data Fig. 4b). Therefore, the most significant changes included an increase in plasmablasts and ICOS⁺ T_FH cells at day 10, which was comparable between the two vaccines. However, unlike our previous observations for influenza vaccines²⁵, changes in these cell types did not correlate with vaccine responsiveness (Extended Data Fig. 4c).

**Fig. 3: Baseline T_H1:T_H17 cell ratio and cytotoxic gene expression are predictive of PCV13 vaccine responsiveness rank.**

To uncover baseline cellular predictors, we performed correlation analyses between the prevaccination absolute cell numbers for B cell, T cell and DC subsets and vaccine responsiveness (rank) for each vaccine. None of the profiled cell types were significantly associated with PPSV23 (Fig. 3b). By contrast, T_H1 cell frequency (R = 0.74, P = 0.0012) was positively associated with PCV13 responses, while proinflammatory T_H17 cell frequency (R = −0.72, P = 0.0015) was negatively associated with PCV13 responses (Fig. 3b,c; see Extended Data Fig. 5a,b for cell numbers). The ratio of T_H1 cell frequency to T_H17 cell frequency was the strongest predictor of PCV13 responses (R = 0.63, P = 0.0089) but not PPSV23 responses (Fig. 3b and Extended Data Fig. 5c). There was no significant difference in T_FH frequency between SRs and WRs, although T_FH1 cells showed a positive association with PCV13 responsiveness, and T_FH17 cells showed a negative association with PCV13 responsiveness (Fig. 3b). We observed sex differences in T_H1 and T_H17 cell frequencies; women had higher T_H1 (P = 0.012) and lower T_H17 cell frequencies (P = 0.028) than men (Fig. 3d and Extended Data Fig. 5c). Women with higher T_H1:T_H17 cell ratios mounted stronger responses to PCV13 (Extended Data Fig. 5c). These two cell types and their ratios were not significantly associated with age (Fig. 3e). Together, these data established that individuals with higher frequencies of T_H1 cells and lower frequencies of T_H17 cells before vaccination mount stronger responses to the conjugated PCV13 vaccine.

Baseline CYTOX level is negatively associated with PCV13 responses

To identify baseline transcriptional signatures associated with vaccine responsiveness, we conducted weighted gene coexpression network analysis (WGCNA) on PBMC RNA-seq data, which yielded 33 gene modules. We associated these modules with vaccine responsiveness, sex, age and T_H1:T_H17 cell ratio. Of 33 modules, only 1 (midnight blue, 260 genes) was significantly (P = 0.02) and specifically associated with PCV13 responses (Extended Data Fig. 6a and Supplementary Table 5a). Genes in this module were enriched in the 'natural killer cell mediated cell cytotoxicity' KEGG pathway (P = 0.000003639) and included NCAM1, the marker gene for natural killer (NK) cells, and several transcripts (GNLY, PRF1 and GZMB) encoding cytotoxic functions²⁶ (Supplementary Table 6a). This cytotoxicity-associated gene module is hereafter referred to as the CYTOX module. Baseline expression levels of CYTOX genes in PBMCs was negatively associated with responsiveness to PCV13 (for example, for NCAM1, R = −0.82 and P = 0.00038) but not responsiveness to PPSV23 (Fig. 3f). In addition, on average, PBMCs from men showed higher expression of CYTOX genes than PBMCs from women in both cohorts (Fig. 3g and Supplementary Table 6a). Expression levels of the top CYTOX genes increased with age, albeit not significantly (Fig. 3h); age-related upregulation of these genes was also observed in a larger cohort (n = 41 men and 34 women; P < 0.05 (ref. ²⁷); Extended Data Fig. 6b). A different module (dark green, 134 genes) was specifically associated with reduced PPSV23 responses (P = 0.05; Extended Data Fig. 6a,c and Supplementary Table 6b), including genes associated with the cell cycle and transcriptional regulation (ANGEL2, MRE11, MTERF1, NUP107 and YTHDC2); however, they were not associated with any immune cell type or function. The top genes in this module showed no significant association with age and sex (Extended Data Fig. 6d,e). To summarize, WGCNA of the baseline PBMC RNA-seq data revealed two distinct gene sets that are significantly associated with PCV13 and PPSV23 responses.

The CYTOX signature stems from CD16⁺ NK cells

To identify cells bearing the CYTOX signature, we generated single-cell RNA-seq (scRNA-seq) data from prevaccination PBMCs of 11 PCV13 donors (6 SRs and 5 WRs), resulting in 52,702 cells after quality control (Fig. 4a and Supplementary Table 7). Clustering of PBMCs generated 24 clusters, which were annotated into monocytes (CD14 and CD16), DCs (monocyte-derived DCs, cDC1s and cDC2s), B cells (naive cells, memory cells, switched memory B cells, age-associated B cells and plasma cells), CD4⁺ T cells (naive, memory, regulatory T (T_reg) and cytotoxic CD4⁺ T cells), CD8⁺ T cells (naive and memory cells (granzyme K⁺ T cells, effector memory T cells expressing CD45RA (TEMRA), mucosal-associated invariant T cells and γδ T cells)) and NK cells (CD56^brightCD16⁻ and CD56^dimCD16⁺; Fig. 4a and Extended Data Fig. 7a,b). Among these, only two cell subsets were significantly different between SRs and WRs (Fig. 4b and Extended Data Fig. 8a), where SRs had more naive CD8⁺ T cells (P = 0.03) and fewer CD16⁺ NK cells (P = 0.03; Fig. 4b and Extended Data Fig. 8a).

**Fig. 4: CD16⁺ NK cell frequency in PBMCs is negatively associated with PCV13 vaccine responses.**

Blood NK cells include immature CD56^brightCD16⁻ NK cells that produce the chemokine XCL1 and the mature, highly cytotoxic CD56^dimCD16⁺ cells, both of which were captured in the scRNA-seq data (Fig. 4c). However, only the CD16⁺ NK cells were significantly associated with vaccine responsiveness, where WRs had higher frequencies of these cells (Fig. 4d,e and Extended Data Fig. 8b). In line with their stronger PCV13 responses (Fig. 1f), women had lower CD16⁺ NK cell frequencies than men (P = 0.042; Fig. 4f). We calculated CYTOX scores at single-cell resolution using the average expression of CYTOX genes. The CYTOX score was highest in the NK cell populations, followed by the cytotoxic CD8⁺ T cell populations (Extended Data Fig. 9a). There was no significant difference between the CYTOX scores of SRs and WRs neither for the memory CD4⁺ T cell clusters (Extended Data Fig. 9b–e) nor for other cell types, including TEMRAs that have high CYTOX scores (Extended Data Fig. 9e). Together, these data establish that CD16⁺ NK cells comprise the population of cells that bears the CYTOX signature, where the increased frequency of CD16⁺ NK cells is associated with reduced PCV13 responses.

Differential gene expression analyses between CD16⁺ NK cells of SRs and WRs revealed 38 differentially expressed genes (FDR of 5%; Fig. 5a and Supplementary Table 8). CD16⁺ NK cells from WRs showed higher expression of cytotoxic genes (GNLY and GZMH) and IFNG, indicating a more 'cytotoxic' and 'activated' phenotype. Furthermore, WR CD16⁺ NK cells expressed higher levels of the inhibitory receptor gene KLRC2 (NKG2C), suggesting a more advanced maturation stage²⁸. CD16⁺ NK cells from WRs also overexpressed amphiregulin (AREG), a ligand for the epidermal growth factor receptor that is upregulated after inflammation and mitochondrial stress in immune cells²⁹. Although CMV can modulate NK cell phenotypes³⁰, CMV positivity (10 of 39 donors) was not associated with responsiveness to either vaccine (Fig. 5b). These data suggest that CD16⁺ NK cells from PCV13 WRs had a more cytotoxic and activated transcriptional phenotype than the same cells from SRs.

**Fig. 5: Increased cytotoxicity in CD16⁺ NK cells of PCV13 WRs.**

PPSV23 responses are independent of CD16⁺ NK cell frequency

To establish whether CD16⁺ NK cells are also associated with PPSV23 responsiveness, we used CIBERSORTx and inferred cell-type frequency from bulk data by using cell-type-specific expression from scRNA-seq data (Fig. 4a). First, we confirmed that inferred CD16⁺ NK cell frequencies match scRNA-seq-based frequencies using 11 donors for whom we have both scRNA-seq and bulk PBMC RNA-seq data (R = 0.97, P = 5.4 × 10^–6; Fig. 5c and Extended Data Fig. 10a). In the PCV13 cohort, inferred CD16⁺ NK cell frequency significantly correlated with responsiveness (R = −0.69, P = 0.0067), reinforcing our observation. By contrast, the CD16⁺ NK cell frequency was not associated with PPSV23 responsiveness (R = −0.094, P = 0.73; Fig. 5d and Extended Data Fig. 10b). Together with the lack of association between CYTOX genes and PPSV23 responsiveness (Fig. 3e), these analyses established that CD16⁺ NK cells are important only for responses to the conjugated PCV13 vaccine. Notably, donors with higher CD16⁺ NK cell frequencies also had higher T_H17 cell frequencies (R = 0.86, P = 0.00067) and lower T_H1 cell frequencies (R = −0.72, P = 0.012; Fig. 5e), which was not observed for CD16⁻ NK cells (Extended Data Fig. 10c).

To study the role of CD16⁺ NK cells in responses to other vaccines in older adults, we reanalyzed bulk PBMC RNA-seq data from the previously published Fluzone study (n = 16, 65+ years old)³¹. CIBERSORTx-inferred CD16⁺ NK cell frequencies did not show significant differences between responders and non-responders (P = 0.22; Fig. 5f). However, reanalyses of scRNA-seq data from individuals treated with the adjuvanted influenza vaccine Fluad (n = 6, 65 years old)³² showed that CD16⁺ NK cell frequencies were higher in non-responders than in responders (three responders and three non-responders; P = 0.072; Fig. 5f). Together, these...

Influenza Virus Symptoms