Vaccination is crucial for combating infectious diseases, but older adults often exhibit reduced vaccine responsiveness, leading to increased morbidity, mortality, healthcare costs, and societal impact. Current vaccination programs recommend annual influenza and pneumococcal vaccinations for adults over 65 (or 60 in the Netherlands), and older individuals are a key target group for COVID-19 vaccination. However, vaccine efficacy and humoral/cellular immune responses decline with age due to immunosenescence and potential sex hormone influences. While individual responsiveness varies, understanding the mechanisms underlying this variability is crucial for developing effective vaccination strategies. This study addresses the need for head-to-head comparisons of individual responses to multiple vaccines to determine whether low responsiveness is vaccine-specific or transcends vaccine types. Investigating associations between demographic characteristics, health status (e.g., using the Frailty Index), and vaccine responsiveness is also critical. The study employs a unique approach: three age groups (young adults (25-49), middle-aged adults (50-64), and older adults (≥65)) received three different vaccines (QIV, PCV13, mRNA-1273) over two years. The primary aim is to compare short-term humoral responses across age groups for each vaccine. The secondary aim is to compare humoral response persistence at 6 months. Finally, the study explores vaccine responsiveness across multiple vaccine types within individuals and its association with demographics and the Frailty Index.

Numerous studies have documented the age-associated decline in vaccine responsiveness, particularly in older adults. This decline is attributed to immunosenescence, a general deterioration of the immune system with age, and is influenced by factors such as sex hormones. Research has identified phenotypic changes in the aging immune system and highlighted the role of non-heritable factors. However, a comprehensive understanding of reduced vaccine responsiveness remains elusive. The high inter-individual variability in vaccine responsiveness suggests that the rate of immunosenescence differs between individuals. This underscores the need to target vaccination strategies toward individuals at high risk for severe infections rather than solely relying on chronological age. Current limitations in understanding the immunological mechanisms hinder the development of effective vaccination strategies for older adults. Head-to-head comparisons of individual responses to multiple vaccines are lacking, making it difficult to determine if low responsiveness is vaccine-specific or a generalized phenomenon. Studies investigating the association between demographic and health factors and vaccine responsiveness are also needed.

This study utilized data from the longitudinal VITAL and VITAL-corona intervention studies conducted between 2019 and 2021. Participants were divided into three age groups: young adults (25–49 years), middle-aged adults (50–64 years), and older adults (≥65 years). Recruitment for younger and middle-aged groups was among healthcare workers, while older adults were recruited from a previous cohort. Inclusion criteria required prior seasonal influenza vaccination in 2018-2019, with exclusions based on prior pneumococcal vaccination, allergies, corticosteroid use, immunosuppression, or other relevant health conditions. Participants received three vaccines: a quadrivalent influenza (QIV) booster in autumn 2019, a 13-valent pneumococcal conjugate (PCV13) vaccine in summer/autumn 2020, and a two-dose SARS-CoV-2 mRNA-1273 vaccine series in spring 2021 (or BNT162b2 if already vaccinated). Blood samples were collected at various time points (pre-vaccine, 7 days, 28 days, and 6 months post-vaccination). Humoral responses were assessed using Hemagglutination Inhibition (HI) assays for influenza, fluorescent bead-based multiplex immunoassays (MIA) for pneumococcal serotype-specific IgG concentrations, and bead-based assays for SARS-CoV-2 Spike S1-specific IgG concentrations. A vaccine response score (1-4, with 4 being the highest quartile) was assigned to each vaccine based on the 28-day post-vaccination antibody levels. A dual (QIV and PCV13) and triple (QIV, PCV13, and mRNA-1273) vaccine response score was calculated as the average of the individual scores. Demographic data (age, sex, BMI, Frailty Index, EQ-5D-3L score, number of medications) were collected and compared among different response groups. Unsupervised hierarchical clustering was used to analyze vaccine response patterns. Statistical analyses included Kruskal-Wallis tests, Mann-Whitney U tests, Chi-Squared tests, linear mixed models, and Spearman correlations. Ethical approval was obtained, and all participants provided informed consent.

The study found that the 2019-2020 booster QIV vaccination induced comparable H3N2-specific HI responses at 28 days post-vaccination across all age groups. However, primary PCV13 and mRNA-1273 vaccinations induced significantly lower antibody concentrations in older adults compared to younger adults at 28 days post-vaccination. Persistence of humoral responses at 6 months was shorter in older adults for all vaccines. The study showed that the magnitude of vaccine-induced humoral immunity varied considerably within individuals, depending on the vaccine type. Analysis of the dual (QIV and PCV13) vaccine response revealed that 7.5% of individuals showed a low response to both vaccines, while analysis of the triple vaccine response (QIV, PCV13, and mRNA-1273) identified 8.9% of individuals as low responders across all three vaccines. Hierarchical clustering revealed nine distinct clusters of individuals with diverse vaccine response profiles. Older adults were present in all clusters, but the cluster of individuals showing a low response to all three vaccines had a significantly higher percentage of older adults (53.1%) and the highest average age. Low responders to multiple vaccines were primarily older males and had low pre-vaccination H3N2 titers. No significant associations were found between the Frailty Index and vaccine responsiveness.

This study's findings challenge previous studies reporting reduced responsiveness to annual influenza vaccination in older adults. The comparable QIV response in all age groups may be due to differences in vaccine immunogenicity and pre-existing immunity. The lower antibody concentrations and reduced breadth of response to PCV13 and mRNA-1273 vaccinations in older adults align with the concept of reduced responsiveness to novel antigens due to age-related decline in naive immune cells. The shorter humoral response persistence in older adults may reflect a decline in long-lived plasma cells and memory B cell responses. The high variability in antibody responses among individuals suggests the need to consider individual risk profiles rather than chronological age when designing vaccination strategies. The identification of a group of predominantly older males with low responses to multiple vaccines highlights potential risk factors for low vaccine responsiveness. Further research is needed to elucidate the mechanisms underlying these low responses and to identify additional predictive factors beyond pre-existing immunity and sex.

This study provides valuable insights into age-related and vaccine-specific humoral immune responses to QIV, PCV13, and mRNA-1273 vaccines. The findings emphasize the importance of considering individual risk profiles, particularly older males with low pre-existing immunity, for developing effective vaccination strategies. Future research should focus on unraveling the underlying mechanisms of low vaccine responsiveness and identifying additional predictive biomarkers to guide targeted vaccination approaches.

The study's limitations include the use of different humoral response units for different vaccines, the potential impact of COVID-19 lockdowns on blood sampling, the overrepresentation of healthcare workers among younger and middle-aged adults, and the focus on antibody concentrations without assessment of antibody functionality or cellular immunity. Additionally, the relatively healthy participant cohort, excluding nursing home residents, may limit the generalizability of the findings.