Abstract
Background
COVID-19 remains a global biothreat because of new immune-evasive SARS-CoV-2 variants, heterogeneous immunity, and evolving vaccine recommendations.
Methods
In this cross-sectional study conducted in September 2024, we evaluated the adaptive immune responses in immunocompetent US active-duty personnel who completed a COVID-19 primary vaccine series but had variable subsequent vaccination and infection histories. We compared responses to 4 circulating variants (JN.1, KP.2, KP.3, LB.1) versus 2 previous dominant vaccine variants (BA.5, XBB.1.5). Analyses were performed based on timing (within or beyond 12 months from enrollment) and type of the most recent exposure, defined as either a COVID-19 vaccination or natural infection.
Results
A total of 317 participants were enrolled over 4 weeks in Japan. Significant reduction was observed in receptor binding domain- and spike-specific binding antibodies, neutralization antibodies, antibody-dependent cell cytotoxicity activity, memory B cells, and CD8+ T cells against circulating variants compared to previous variants. The reduction in humoral responses was more pronounced in those whose most recent exposure was greater than 12 months from enrollment. In contrast, cell-mediated T-cell responses were largely consistent regardless of the timing of the most recent exposure. The type of most recent exposure was not a significant factor in determining the magnitude of current immune responses.
Conclusions
Administration of COVID-19 boosters is likely to enhance cross-reactive humoral responses against SARS-CoV-2 circulating variants, potentially facilitating protection from infection and fewer missed work days among military populations. Ongoing surveillance is needed to inform future vaccine composition, timing of administration, and targeted populations to maximize protective benefits.
Keywords: adaptive immunity, young adults, SARS-CoV-2, US military, vaccine recommendations
Significant reduction in spike-specific antibodies, natural killer cell activity, and memory B cells was observed against circulating SARS-CoV-2 variants in late 2024 compared to prior variants among young immunocompetent adults, suggesting selective benefits of the updated COVID-19 vaccine in this population.
More than 2 years after the World Health Organization declared an end to COVID-19 as a global health emergency [1], COVID-19 remains a significant health concern [2]. More than 400 million people worldwide [3] have been diagnosed with postacute sequelae of COVID-19, leading to substantial productivity and economic costs [4]. The persistent challenge of SARS-CoV-2, the causative agent of COVID-19, is further entrenched because of the continued emergence of new variants with greater immune escape and transmission, waning host immunity, and growing COVID fatigue reflected in poor uptake of new updated vaccines [5]. Studies that encompass all aspects of the adaptive immune system remain essential to understanding durable and protective host immunity [6]. Durable responses from CD8+ T cells, CD4+ T cells, and memory B cells are known to work in conjunction with other components of the immune system for long-term virologic control and prevention of severe outcomes in SARS-CoV-2 infection [7]. However, the temporal dynamics of these adaptive immune cell populations vary across different demographic groups, translating to contrasting clinical characteristics and outcomes [8], hence the need to examine the adaptive immunity in its totality to obtain a more comprehensive understanding.
Since the first emergency use authorization issued in December 2020 to early 2025, US regulatory agencies, in most cases, have granted evidence-based, recommendations for near-universal COVID-19 vaccine authorization to much of the population, in particular those aged 6 months and older [9]. Within the past year, the Food and Drug Administration has been moving more toward individual risk-based shared decision-making and recommendations that are ideally backed by data from randomized controlled trials in young healthy adults below the age of 65 years to evaluate clinical outcomes [10]. Active-duty service members who fall within this category comprise a community facing an elevated risk of SARS-CoV-2 infections because of operating in congregate settings [11], international deployments, and policy changes. Although they do not generally suffer from severe disease because of highly preserved helper T-cell immunity against multiple lineages [12], service members likely suffer from postacute sequelae of COVID-19 at a higher rate than the general population with long-term negative impact on functional performance [13]. Although randomized controlled trials are the gold standard to evaluate vaccine efficacy, they are costly, time-consuming, and unlikely to keep pace with the evolutionary changes of the virus. In late 2024, our group conducted an observational, cross-sectional study among US active-duty sailors stationed in Japan [12]. In this second study iteration, we expanded on prior results by examining additional adaptive immune components against SARS-CoV-2 variants circulating in 2024 using a larger sample size to better inform public and force health protection recommendations.
METHODS
A cross-sectional study was conducted over 4 weeks during August to September 2024, comprising 17 enrollment events in Yokosuka and Atsugi, Japan. US Navy active-duty personnel at least aged 18 years old who completed a COVID-19 vaccine primary series were eligible. Exclusion criteria included those who had cold-like symptoms within the past 30 days; a positive COVID-19 test or vaccine within the past 30 days; pregnant or within 6 weeks of delivery; taking immunosuppressants or diagnosed with an immunocompromising condition. Confirmatory polymerase chain reaction or rapid antigen testing was not performed because of the low pretest probability of active infection in asymptomatic potential participants. Ethics review was conducted by the Institutional Review Board, Naval Medical Research Command (NAMRU2.2023.0001), in compliance with all applicable federal regulations governing the protection of human subjects. In addition to providing blood and saliva, study participants completed a questionnaire (Supplementary Figure 1). Either a vaccination or natural infection (by self-report or identified using medical records) constituted an exposure event with prioritization given to the records in case of discordance.
Peripheral blood mononuclear cells (PBMCs) were isolated by LeucoSep separation using modified National Institute of Allergy and Infectious Diseases procedures [14].
Six variants were selected for analysis: 2 previous dominant variants (PDVs) including Omicron variants BA.5 and XBB.1.5 and 4 circulating variants (CVs) including Omicron variants JN.1, KP.2, KP.3, and LB.1. By mid-September 2024, KP.3, JN.1, KP.2, and LB.1 were the most prevalent lineages worldwide, with JN.1 considered a variant of interest and the other CVs considered variants under monitoring [15]. In addition to the full spike protein, isolated responses to the receptor-binding domain (RBD) were measured due to its dominance in eliciting neutralization antibody titers after SARS-CoV-2 vaccination and infection as well as in driving new immune-evasive mutations in emerging variants [16]. Both BA.5 and XBB.1.5 spike proteins were included in prior COVID-19 vaccines approved by the Food and Drug Administration. Amino acid differences among tested variants are highlighted in Supplementary Table 1 [17].
Enzyme-linked Immunosorbent Assay of RBD and Spike Protein Immunoglobulins
Trimeric S and RBD antigens from 6 selected variants were used. Quantitative enzyme-linked immunosorbent assay was performed as previously described [18]. The limit of detection (LOD) was 10 ng/mL based on standard prepandemic samples. For serum RBD immunoglobulin G (IgG), a cutoff of 861 ng/mL was used as a reference “protective” threshold based on the average of 2 RBD IgG titers previously reported to correlate with high vaccine efficacy and clinically significant host viral neutralizing capacity [19].
Pseudovirus Neutralization
Pseudovirus was produced using the SARS-CoV-2 Spike gene, the lentivirus-derived reporter, and packaging plasmids as previously described [20]. Pseudovirus neutralization assays were performed as previously described [21]. The LOD of the assay was 30 corresponding to the starting dilution factor. A cutoff of 176 calculated by running our assay on the Human SARS-CoV-2 Serology Standard, Lot Number “COVID-NS01097” received from NCI-Frederick National Laboratory for Cancer Research was used as a reference “protective” threshold based on multiple prior studies demonstrating an ND50 of 100 IU/mL corresponding to at least a 90% vaccine efficacy [19, 22].
Memory B Cells Frequencies
Cryopreserved PBMCs were thawed, washed, and stained for viability. After centrifuging and removal of supernatant, B cells were stained with fluorochrome-conjugated streptavidin tetramers attached to the biotinylated RBDs or trimer spike protein of the selected variants, together with a cocktail of phenotyping antibodies. SARS-CoV-2 antigen-positive B cells were identified among memory IgG populations defined as CD19+, dump channel negative, CD10–, CD20+, CD27+, and CD21−/+ (Supplementary Figure 2A-C). “Responders” were identified as participants with positive frequencies within the memory IgG gate above that of a negative control donor run on the same day with study samples to draw gates.
T Cells Frequencies
Assay methods for activation-induced markers (AIM) were performed as described previously [23]. The gating strategy for AIM cells was drawn relative to the negative and positive controls for each donor as shown in Supplementary Figure 2D. The antigen-specific AIM responses were obtained by subtracting the AIM responses in dimethyl sulfoxide cultures. We calculated the variant-specific CD4+ and CD8+ T cell LODs as equal to the mean plus 1.7 standard deviations using 31 prepandemic samples stimulated with the same antigens given previously. “Responders” were defined as participants with T-cell frequencies greater than these cutoffs.
Plate-bound Domain-specific Antibody-dependent Cell Cytotoxicity
Plate-bound natural killer (NK) cell testing using 96-well plates was performed as described previously [24]. Briefly, U-bottom 96-well plates were coated with SARS-CoV-2 antigens. Wells coated with phosphate-buffered saline were used as background controls for setting the LOD cutoff. Serially diluted sera were added and unbound serum was removed by washing. The nonadherent PBMCs were collected and incubated overnight in 6-well plates in the presence of recombinant human interleukin-2. The interleukin-2-treated donor cells were washed and added to the antigen-coated plates and incubated for 2 hours. The cells were washed, stained with an NK cell cocktail, and gated as shown in Supplementary Figure 2E. Antigen-specific responses were calculated by subtracting responses in antigen-coated wells from uncoated wells.
Statistics
GraphPad Prism version 10 was used for data management and analysis. The Wilcoxon signed-rank test was used to compare 2 groups composing of the same participants. The Mann-Whitney U test was used for analysis of differences among 2 independent groups. The chi-square test was used to compare categorical proportions.
RESULTS
Cohort Description
A total of 317 US servicemembers were enrolled into the study (Table 1). Women comprised 21.5%. The median age was 32 years, ranging from 19 to 63, with 79.8% younger than 40 years. A total of 97/317 (30.6%) participants had never received an additional COVID-19 vaccine following the initial series, whereas 27/317 (8.5%) participants had received the updated 2023–2024 formula COVID-19 vaccine containing the XBB.1.5 variant. None of the participants received the 2024–2025 formula vaccine. Fifty-four participants (17.3%) had an exposure event within 12 months of enrollment: 22 (40.7%) with a vaccine and 32 (59.3%) with breakthrough infection.
Table 1.
Cohort and Exposure Groups Breakdown by Sex, Age, Ethnicity, Race, and Rank
| Sex | Age Group | Ethnicity | Race | Rank | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Total (%) | Male (%) | Female (%) | 18–39 yr (%) | ≥ 40 yr (%) | Hispanic (%) | Not Hispanic (%) | American Indian or Alaska Native (%) | Asian (%) | African American (%) | Native Hawaiian or Pacific Islander (%) | White (%) | Mixed (%) | Enlisted (%) | Officer (%) | ||
| Cohort | 317 (100) | 249 (78.5) | 68 (21.5) | 253 (79.8) | 64 (20.2) | 57 (18) | 260 (82) | 5 (1.6) | 75 (23.7) | 57 (18) | 10 (3.2) | 148 (46.7) | 22 (6.9) | 266 (83.9) | 51 (16.1) | |
| Initial series brand | BioNTech BNT162b2 | 143 (45.1) | 103 (72) | 40 (28) | 121 (84.6) | 22 (15.4) | 25 (17.5) | 118 (82.5) | 0 | 31 (21.7) | 31 (21.7) | 5 (3.5) | 66 (46.2) | 10 (7.0) | 122 (85.3) | 21 (14.7) |
| mRNA-1273 | 148 (46.7) | 126 (85.1) | 22 (14.9) | 108 (73.0) | 40 (27.0) | 26 (17.6) | 122 (82.4) | 4 (2.7) | 40 (27.0) | 22 (14.9) | 4 (2.7) | 67 (45.3) | 11 (7.4) | 120 (81.1) | 28 (18.9) | |
| Ad26.COV2.S | 22 (6.9) | 18 (81.8) | 4 (18.2) | 20 (90.9) | 2 (9.1) | 5 (22.7) | 17 (77.3) | 1 (4.5) | 3 (13.6) | 4 (18.2) | 1 (4.5) | 12 (54.5) | 1 (4.5) | 20 (90.9) | 2 (9.1) | |
| Additional vaccine history | No additional vaccines following initial series | 97 (30.6) | 73 (75.3) | 24 (24.7) | 88 (90.7) | 9 (9.3) | 19 (19.6) | 78 (80.4) | 1 (1.0) | 21 (21.6) | 24 (24.7) | 2 (2.1) | 44 (45.4) | 5 (5.2) | 89 (91.8) | 8 (8.2) |
| Received at least one additional vaccine following initial series | 216 (68.1) | 174 (80.6) | 42 (19.4) | 161 (74.5) | 55 (25.5) | 37 (17.1) | 179 (82.9) | 4 (1.9) | 53 (24.5) | 33 (15.3) | 8 (3.7) | 101 (46.8) | 17 (7.9) | 173 (80.1) | 43 (19.9) | |
| Only 1 additional vaccine | 151 (47.6) | 123 (81.5) | 28 (18.5) | 122 (80.8) | 29 (19.2) | 25 (16.6) | 126 (83.4) | 3 (2.0) | 39 (25.8) | 29 (19.2) | 5 (3.3) | 64 (42.4) | 11 (7.3) | 134 (88.7) | 17 (11.3) | |
| Exactly 2 additional vaccines | 53 (16.7) | 41 (77.4) | 12 (22.6) | 35 (66.0) | 18 (34.0) | 12 (22.6) | 41 (77.4) | 1 (1.9) | 10 (18.9) | 3 (5.7) | 3 (5.7) | 30 (56.6) | 6 (11.3) | 35 (66.0) | 18 (34.0) | |
| Exactly 3 additional vaccines | 11 (3.5) | 9 (81.8) | 2 (18.2) | 4 (36.4) | 7 (63.6) | 0 | 11 (100) | 0 | 3 (27.3) | 1 (9.1) | 0 | 6 (54.5) | 1 (9.1) | 4 (36.4) | 7 (63.6) | |
| Exactly 4 additional vaccines | 1 (0.3) | 1 (100) | 0 | 0 | 1 (100) | 0 | 1 (100) | 0 | 1 (100) | 0 | 0 | 0 | 0 | 0 | 1 (100) | |
| Received bivalent vaccine | 72 (22.7) | 57 (79.2) | 15 (20.8) | 48 (66.7) | 24 (33.3) | 13 (18.1) | 59 (81.9) | 2 (2.8) | 16 (22.2) | 6 (8.3) | 2 (2.8) | 40 (55.6) | 6 (8.3) | 49 (68.1) | 23 (31.9) | |
| Infection history | No positive COVID-19 test | 133 (42.0) | 104 (78.2) | 29 (21.8) | 107 (80.5) | 26 (19.5) | 27 (20.3) | 106 (79.7) | 3 (2.3) | 26 (19.5) | 27 (20.3) | 3 (2.3) | 63 (47.4) | 11 (8.3) | 33 (24.8) | 100 (75.2) |
| 1 or more prior positive test | 184 (58.0) | 148 (80.4) | 36 (19.6) | 148 (80.4) | 36 (19.6) | 30 (16.3) | 154 (83.7) | 2 (1.1) | 50 (27.2) | 30 (16.3) | 7 (3.8) | 87 (47.3) | 11 (6.0) | 149 (81.0) | 35 (19.0) | |
| Timing of most recent exposure | Less than 12 m | 54 (17.3) | 36 (66.7) | 18 (33.3) | 38 (70.4) | 16 (29.6) | 7 (13.0) | 47 (87.0) | 0 | 14 (25.9) | 9 (16.7) | 1 (1.9) | 28 (51.9) | 2 (3.7) | 40 (74.1) | 14 (25.9) |
| More than 12 m | 259 (82.7) | 210 (81.1) | 49 (18.9) | 211 (81.5) | 48 (18.5) | 49 (18.9) | 210 (81.1) | 5 (1.9) | 60 (23.2) | 48 (18.5) | 9 (3.5) | 117 (45.2) | 20 (7.7) | 222 (85.7) | 37 (14.3) |
One participant was unable to provide samples, and 4 participants did not have verifiable initial series vaccination records. A total of 312 samples were used in binding and neutralizing antibody analyses; 235 in antibody-dependent cell cytotoxicity (ADCC) analyses; 127 in B-cell analyses; and 275 in T-cell analyses (Supplementary Figure 3).
Antibody-associated Responses Were Reduced Against Circulating Variants and in Participants Whose Most Recent Exposure was Beyond 12 Months
Serum IgG and IgA titers to both the RBD (Figure 1A, Supplementary Figure 4A) and spike (Supplementary Figure 6A/C) proteins were significantly lower against CVs compared to PDVs. The median IgG titers against RBD generally declined with each chronologically successive variant, reaching their lowest with the more recently emerged KP.3. KP.3 had the lowest median titers for both binding anti-RBD and anti-spike IgG and IgA responses. A similar pattern of declining response accompanying variant recency was seen in saliva anti-RBD (Supplementary Figure 5A/C) and anti-spike (Supplementary Figure 7A/C) IgG and IgA titers. ADCC to spike (Supplementary Figure 8A) and RBD (Supplementary Figure 8C) also followed a similar pattern with the proportion of antibody-activated NK cells to CVs found to be significantly lower than that to PDVs.
Figure 1.
SARS-CoV-2 serum anti-RBD IgG titer levels were significantly lower against CVs compared to PDVs and in participants whose most recent exposure was greater than 12 m from enrollment for all variants. A, Variant-specific RBD IgG titers for 312 participants with verifiable vaccine records. B, Variant-specific RBD IgG titers based on time of most recent exposure (either vaccination or infection) using the 12-month cutoff from date of study enrollment (n = 54 for those with an exposure within 12 m represented by black circles vs n = 258 for those whose most recent exposure was beyond 12 m represented by orange circles). Log RBD IgG values are shown. The percentages of participants with titers above the reference “protective” titer (861 ng/mL or 2.94 in log scale), represented as dashed line, are shown as donut plots. Median titers are shown below each group in ng/mL. Wilcoxon signed-rank test was performed to show group median differences in panel A and Mann-Whitney U test in panel B. Chi square analysis was performed between selected groups percentages. Significant differences are marked as *P < .05, **P < .01, ***P < .001; ns, not significant. Of note, the LB.1 variant shares the same RBD sequence as that of KP.2. Abbreviations: CVs, circulating variants (JN.1, KP.2, and KP.3); IgG, immunoglobulin G; PDVs, previous dominant variants (BA.5 and XBB.1.5); RBD, receptor-binding domain.
Anti-spike neutralization antibodies (NAb) followed the same trend as the binding antibodies to RBD and spike proteins (Figure 2A). NAb titers against PDVs were significantly higher compared to CVs. LB.1 had the lowest median titer and proportion of donors above the LOD among the CVs. For PDVs, 1.6% to 9.5% of participants had undetectable NAb activity; on the other hand, for CVs, 29.7% to 43% had no detectable NAb response. For PDVs, 4.4% to 27.5% of participants had NAb titers below the “protective” threshold; for CVs, the corresponding proportion of participants increased to 57.6% to 71.8%.
Figure 2.
SARS-CoV-2 serum anti-spike pseudovirus neutralization antibody (NAb) levels were significantly lower against CVs compared to PDVs and were consistently lower in participants whose most recent exposure was greater than 12 m from enrollment for all variants. A, Variant-specific NAb titers for 312 participants with verifiable vaccine records. B, Variant-specific NAb titers based on time of most recent exposure (either vaccination or infection) using the 12-month cutoff from date of study enrollment (n = 54 for those with an exposure within 12 m represented by black circles vs n = 258 for those whose most recent exposure was beyond 12 m represented by orange circles). Log ND50 values are shown on the y-axis. The percentages of participants with titers above the LOD (30 or 1.5 in log scale) and above the “protective” titer (176.5 or 2.2 in log scale), represented by the bottom and top horizontal dashes lines respectively, are shown as donut plots. Median titers are shown below each group in ng/mL. Wilcoxon signed-rank test was performed to show group median differences in panel A and Mann-Whitney U test in panel B. Chi-square analysis was performed between selected groups percentages. Significant differences are marked as *P < .05, **P < .01, ***P < .001; ns, not significant. Abbreviations: CVs, circulating variants (JN.1, KP.2, KP.3, and LB.1); LOD, limit of detection. PDVs, previous dominant variants (BA.5 and XBB.1.5); ND50, 50% neutralization dose.
For both serum and saliva anti-RBD IgG (Figure 1B, Supplementary Figure 5B), serum and saliva anti-spike IgG (Supplementary Figures 6B/7B), and serum NAb (Figure 2B), the median titers measured against all tested variants among participants whose most recent exposure was greater than 12 months from enrollment were significantly lower compared to those among participants with an exposure within 12 months. A similar trend was observed in spike-specific (Supplementary Figure 8B) and RBD-specific (Supplementary Figure 8D) antibody-dependent NK cell activity; however, statistical significance was not reached in all instances. In contrast, regardless of the timing of the most recent COVID-19 exposure, there was no statistical differences among all IgA serum and saliva responses (Supplementary Figures 5D/7D). For CVs, there was no statistically significant difference in the serum anti-RBD IgG and anti-spike NAb titers of participants whose most recent exposure was a vaccine versus natural infection, regardless of whether the exposure occurred within 12 or beyond 12 months from enrollment (Supplementary Figures 4C/9A). Similarly, the NAb titers were not statistically different based on the receipt status of additional vaccines beyond the 2021 initial vaccination series (Supplementary Figure 9B; with the exception of BA.5 and XBB.1.5). Those who had exactly 1 prior positive COVID-19 test consistently had higher NAb levels than those with no prior infections; NAb levels were not statistically different for previously infected participants regardless of the number of infection episodes (Supplementary Figure 9C). For all CVs, NAb levels were not statistically different among all participants regardless of the primary vaccine series type received (Supplementary Figure 9D).
B-cell Responses to SARS-CoV-2 Were Reduced Against Circulating Variants and in Participants Whose Most Recent Exposure was Greater Than 12 Months, Except for KP.2
The frequency of variant RBD-specific IgG-positive memory B cells (MBC) against CVs were significantly lower than those against PDVs (Figure 3A). The proportion of “responders” was above 98.4%, and there was no significant difference among all variants.
Figure 3.
SARS-CoV-2 RBD-specific IgG-positive memory B cell (MBC) frequencies were significantly lower against CVs compared to PDVs with significantly higher percentages of both RBD-specific and spike-specific MBCs observed among participants whose most recent exposure was within 12 m of enrollment for all antigens except KP.2 RBD. A, Variant-specific MBC frequencies for 127 selected participants with viable PBMCs. B, Variant-specific MBC frequencies based on time of most recent exposure (either vaccination or infection) using the 12-month cutoff from date of study enrollment (n = 39 for those with an exposure within 12 m represented by black circles vs n = 88 for those whose most recent exposure was beyond 12 m represented by orange circles). The percentages of MBC “responders” are shown as donut plots. MBC “responder” is defined as having an MBC frequency higher than the negative control sample run on the same day. The dashed line represents the median frequency meeting gating criteria per variant across all days of analysis from a negative control donor. Median frequencies are shown below each group. Wilcoxon signed-rank test was performed to show group median differences in panel A and Mann-Whitney U test in panel B. Significant differences are marked as *P < .05, **P < .01, ***P < .001, ****P < .0001; ns, not significant. Abbreviations: CVs, circulating variants (JN.1, KP.2, KP.3, and LB.1); IgG, immunoglobulin G; RBD, receptor-binding domain; PBMCs, peripheral blood mononuclear cells; PDVs, previous dominant variants (BA.5 and XBB.1.5).
In addition, for all variants except KP.2, the peripheral MBC frequencies in participants were statistically lower among participants whose most recent COVID-19 exposure was greater than 12 months from enrollment (Figure 3B). For all variants, MBC responses were statistically similar regardless of the nature of the most recent exposure on both sides of the 12-month cutoff (Supplementary Figure 10A). Participants who received any additional vaccinations beyond the initial series completed in 2021 had significantly higher peripheral antigen-specific IgG-positive MBC frequencies to all measured variants compared to those who received only the initial series vaccination (Supplementary Figure 10B). In contrast, for all variants, there were no significant differences in MBC responses based on number of prior infections (Supplementary Figure 10C). MBC responses were statistically greatest among participants who received the mRNA-1273 primary vaccines series, followed by BNT162b2, and lowest among those who received Ad26.COV2.S (Supplementary Figure 10D).
T-cell Responses to SARS-CoV-2 Were Generally Lower Against Circulating Variants but Largely Unaffected by Timing and Nature of Most Recent Exposure
Although there was no significant difference of the frequency of spike-specific CD8+ T cells between BA.5 with XBB.1.5, CD8+ responses against all CVs were significantly lower than XBB.1.5 (Figure 4A). A similar pattern was seen in CD4+ T-cell responses; however, when comparing the PDVs, the response against BA.5 was significantly lower than that against XBB.1.5 (Figure 4C). Among the CVs, KP.3 T-cell frequencies were the lowest for both antigen-specific AIM-positive CD8+ and CD4+ responses.
Figure 4.
SARS-CoV-2 spike-specific AIM-positive CD8+ (cytotoxic) and CD4+ (helper) T-cell frequencies were consistently lower against CVs compared to PDVs, with the exception of BA.5 in the case of CD4+; all T-cell responses were similar based on timing of the most recent exposure for all variants. A, Variant-specific CD8+ T-cell frequencies for 275 selected participants with PBMCs. B, Variant-specific CD8+ T-cell frequencies based on time of most recent exposure (either vaccination or infection) using the 12-month cutoff from date of study enrollment (n = 48 for those with an exposure within 12 m represented by black circles vs n = 227 for those whose most recent exposure was beyond 12 m represented by orange circles). CD8+ AIM positivity defined as CD1 + and CD6 + . C, Variant-specific CD4+ T-cell frequencies for the same 275 participants. D, Variant-specific CD4+ T-cell frequencies based on time of most recent exposure using the 12-month cutoff from date of study. CD4+ AIM positivity defined as CD1+ and CD137+. The percentages of CD8+ and CD4+ T-cell “responders” are shown as donut plots. CD8+ and CD4+ T-cell “responder” is defined as having a baseline-adjusted frequency greater than the LOD, defined as 1.7 standard deviations above the baseline frequency of 31 prepandemic PBMC samples when tested against respective study variants (CD8+ LOD cutoffs: .0206 for BA.5, 0.0233 for XBB.1.5, 0.03140 for JN.1, 0.0872 for KP.2, 0.0263 for KP.3, and 0.0299 for LB.1; CD4+ LOD cutoffs: 0.0238 for BA.5, 0.0515 for XBB.1.5, 0.0286 for JN.1, 0.0990 for KP.2, 0.0629 for KP.3, and 0.0614 for LB.1; all values measured in %). Median frequencies are shown below each group. Wilcoxon signed-rank test was performed to show group median differences in panels A and C, whereas the Mann-Whitney U test was used in panels B and D. Significant differences are marked as *P < .05, **P < .01, ***P < .001; ns, not significant. Abbreviations: AIM, activation-induced markers; CD, cluster of differentiation; CVs, circulating variants (JN.1, KP.2, KP.3, and LB.1); PDVs, previous dominant variants (BA.5 and XBB.1.5); PBMCs, peripheral blood mononuclear cells; LOD, limit of detection.
For all tested variants in almost all instances of comparison, there was no statistically significant difference in CD8+ or CD4+ T-cell response among participants regardless of the timing (Figures 4B/4D) or nature (Supplementary Figures 11A/12A) of the most recent exposure. Similarly, there was no significant difference in T-cell responses (Supplementary Figures 11C/12C) based on number of prior infections. Although there were largely no significant differences in CD8+ T-cell responses based on COVID-19 vaccination history (Supplementary Figure 11B), participants who received any additional vaccinations beyond the initial series in 2021 had significantly higher peripheral antigen-specific AIM-positive CD4+ T-cell frequencies to all measured variants compared to those who received only the initial series vaccination (Supplementary Figure 12B). CD4+ T-cell responses were consistently greatest among participants who received the mRNA-1273 primary vaccine series, followed by BNT162b2, and lowest among those who received Ad26.COV2.S with statistical significance reached for BA.5, XBB.1.5, JN.1, and KP.3 variants (Supplementary Figure 12D).
DISCUSSION
In our young cohort of service members sampled in September 2024, we observed consistent and significant reduction among multiple components of the adaptive immune system including binding antibodies, neutralization antibodies, ADCC activity, memory B cells, and CD8+ T cells against CVs compared to PDVs, with the notable exception of CD4+ T-cell responses. In addition, a more recent exposure in the past 12 months from either vaccination or infection increased not only quantitative and functional antibody responses, but also circulating IgG-positive MBCs, compared to individuals whose most recent exposure was more than 12 months from enrollment. However, a similar pattern was not found for CD4+ and CD8+ cells. These results suggest that an updated COVID-19 vaccine may selectively enhance humoral over cellular responses which are already preserved, especially in those without a SARS-CoV-2 exposure event within the past 12 months.
We showed that the variant-specific neutralizing antibody titers were significantly lower among CVs compared to PDVs and the level of contraction was associated with 2 factors: exposure within the past 12 months and chronological sequence of the variants. The latter is well illustrated by the progressive decrease in both the proportion of participants who have a response above the 176 IU/mL correlate of protection threshold and those who have any response greater than the limit of detection, with the genetically similar KP.2 and KP.3 being nearly identical. The extensive number of amino acid changes between the PDVs versus CVs [25], particularly on the key immunogenic RBD domain such as R346T, F456L, and Q493E [26], may explain the continuous escape of neutralizing antibodies. Of note, even though KP.2 and LB.1 share the same RBD sequence, the lowest NAb titer was observed against LB.1, the latest variant in our study, suggesting that non-RBD mutations in the N-terminal domain such as DelS31 and Q183H also play a key role in viral neutralization [27]. The contraction in both neutralizing and binding antibody responses, which have been shown to be valid correlates of protection [28], suggests a potential benefit for a vaccine booster among young health adults. Although difficult to quantify the benefit, the results suggest an improved response likely among approximately one third of participants who lacked a detectable response to CVs and even perhaps among the 60%, on average among the 4 CVs, of participants who lacked a response above the threshold of protection [29]. However, the duration of humoral protection is difficult to estimate [30, 31].
Peripheral, variant-specific anti-RBD and spike-specific MBC frequencies declined in proportion to variant recency, likely as a result of immune imprinting of these remote strains secondary to repeated exposures of more ancestral variants through vaccination and infection [32]. Despite this decline, all participants exhibited detectable responses to both PDVs as well as JN.1, with nearly all individuals demonstrating MBC frequencies above the negative control when tested against KP.2 and KP.3 RBD (99.2% and 98.4%, respectively). These findings indicate that the majority of individuals retain a cross-reactive MBC repertoire ready to be recalled and capable of rapid engagement on exposure or vaccination. Importantly, MBC frequencies were higher among participants with recent exposure (<12 months) and among those who had received additional SARS-CoV-2 vaccinations beyond the primary series, suggesting that further boosting with vaccination may augment protective MBC pools in individuals with lower circulating levels, override immune imprinting [33], and thus potentially offer greater protection to emerging variants.
Cellular immune responses had a different pattern in which CD8+ T-cell responses against CVs were significantly lower compared to PDVs, but the timing of the last exposure did not matter. This stable temporal preservation of both subsets of T-cell responses across all tested variants is consistent with other recently published studies that demonstrated durable, broad, and highly cross-reactive T-cell responses [34, 35]. This is likely due to a high proportion of T-cell epitopes being conserved and therefore unaffected by Omicron mutations combined with the long-term durability of T-cell responses following an exposure event [36, 37]. Because the number of previous exposures allow for greater T-cell polyfunctionality and cross-protection among various emerging strains, a vaccine “booster” might not improve CD8+ responses to CVs but could nevertheless provide protection against future strains. Of note, we also found that participants with additional vaccines beyond the initial series in 2021 had significantly higher CD4+ responses for all tested variants; since the majority of these individuals received a booster beyond 1 year from enrollment (72 of 92), this trend, in combination with the findings given previously, supports the notion that boosting by vaccination both replenished and maintained durable CD4 responses long-term [8, 38]. When compared to results from a similar military population in 2023 [12], T-cell responses against both BA.5 and XBB.1.5 dropped by a factor of 1.5- to 7-fold, a trend that was also observed when comparing responses against 2023 CVs (EG.5 and BA.2.86) versus 2024 CVs. Despite this decline over only 1 year, a reduced antigen-specific T-cell pool may still be adequate to protect against hospitalization, severe disease, and death thanks to their durability [39].
This study has several limitations. It is a cross-sectional design collecting data only at one timepoint, limiting an assessment of immune response kinetics. The sample size is relatively small consisting of mostly men, limiting certain sub-group analyses and generalizability. Only self-reported cases and cases documented in the electronic medical record were considered an exposure by infection; therefore, asymptomatic as well as unrecalled and undocumented pauci-symptomatic cases were not identified. In addition, the pseudovirus neutralization platform has drawbacks compared to the live virus system including the inability to simulate the process of viral proliferation and release following cell transfection; differences in distribution, conformation, and density pattern from the “natural” state; and difficulty in accurately quantifying the amount of spike protein relative to pseudovirus titers [40].
The results from this study, even though obtained only from US Navy sailors, are generalizable to other young healthy adults. Future studies should examine the immune responses of participants who have never received any COVID-19 vaccine as well as high-risk populations, including those with immunocompromising conditions and pregnant women.
CONCLUSIONS
Rapid execution of a comprehensive study investigating variant-specific adaptive immune responses can help inform the need for contemporary SARS-CoV-2 vaccines and quantify the potential benefits if administered. The 2024–2025 formula COVID-19 vaccine would likely enhance both binding and neutralizing antibody responses to circulating variants, especially those without an exposure in the past 12 months. Continuous surveillance against new variants is needed to inform the need for, composition, and timing of SARS-CoV-2 updated vaccines.
Supplementary Material
Notes
Acknowledgments. The authors acknowledge the outstanding support from LCDR Sarah Jenkins (NMRC Diagnostics and Surveillance Department Head) who supported the investigators in all aspects of study especially preparation, logistics, enrollment, sampling, and shipping of samples for testing. We must also acknowledge dedication and commitment of U.S. Navy sailors and their respective commands without whom this project would not have been possible.
Author Contributions. H. C. N. had full access to all the study data and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: H. C. N. and A. G. L. Participant enrollment and data collection: H. C. N., A. G. L., J. R. G., D. L. W., I. V. E., T. J. M., A. P. M., M. A. S., and Culmen study team members. Sample processing: P. S., H. S. F., H. C. N., and Culmen study team members. Laboratory work: P. S., C. A. B., K. G. L., L. S., Y. C., L. P., I. F., H. W., and S. J. K. Data analysis and interpretation: P. S., C. A. B., K. G. L., S. J. K., H. C. N., and A. G. L. Drafting and revision of manuscript: H. C. N., A. G. L., P. S., S. J. K., C. A. B., and H. S. F. Study coordination: H. C. N, A. G. L., M. A. S., and Culmen study team members. All authors read and approved the final article.
Disclaimer. The views expressed in this article are those of the authors and should not be construed to reflect the official policy or represent the positions of the Department of the Navy, Department of the Army, Department of Defense, or the US government. Material has been reviewed by the Walter Reed Army Institute of Research. There is no objection to its presentation and/or publication. The investigators have adhered to the policies for protection of human subjects as described in AR 70-25. LCDR Huy C. Nguyen, MC, USN NAMRU-IP; LCDR Jose R. Garcia, MSC, NAMRU-IP; LCDR Dawn L. Weir, MSC, NAMRU-IP; LCDR Irina V. Etobayeva, MSC, NAMRU-IP; CAPT Andrew G. Letizia, MC, USN NAMRU-IP; HM2 Thomas J. McCarthy, USN NAMRU-IP; and Chief Adelbert P. Matanza, USN NAMRU-IP are military service members. This work was prepared as part of their official duties. Title 17 USC 105 provides that copyright protection under this title is not available for any work of the US government. Title 17 USC 101 defines a US government work as work prepared by a military service member or employee of the US government as part of that person's official duties.
Data availability statement. The data underlying this article are available in the article and in its online Supplementary material.
Financial Support. This work was supported by funds from the U.S. Bureau of Medicine and Surgery (BUMED) Restore Core Basic Operational Med Research Sciences to H.C.N. and A.G.L. The study number is NV.6.R22.
Patient consent statement. All participants' written consent were obtained. The design of the study was approved by Naval Medical Research Command Institutional Review Board and conforms to all standards currently applied in the United States.
Contributor Information
Huy C Nguyen, U.S. Naval Medical Research Unit INDO PACIFIC, Science Directorate, Singapore, Singapore.
Li Pan, Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, Maryland, USA; Naval Medical Research Command, Diagnostics and Surveillance Department, Silver Spring, Maryland, USA.
Kerri G Lal, Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, Maryland, USA; Walter Reed Army Institute of Research, US Military HIV Research Program, B Cell Biology, Silver Spring, Maryland, USA.
Corey A Balinsky, Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, Maryland, USA; Naval Medical Research Command, Diagnostics and Surveillance Department, Silver Spring, Maryland, USA.
Jose R Garcia, U.S. Naval Medical Research Unit INDO PACIFIC, Science Directorate, Singapore, Singapore.
Dawn L Weir, U.S. Naval Medical Research Unit INDO PACIFIC, Science Directorate, Singapore, Singapore.
Irina V Etobayeva, U.S. Naval Medical Research Unit INDO PACIFIC, Science Directorate, Singapore, Singapore.
Thomas J McCarthy, U.S. Naval Medical Research Unit INDO PACIFIC, Science Directorate, Singapore, Singapore.
Adelbert P Matanza, U.S. Naval Medical Research Unit INDO PACIFIC, Science Directorate, Singapore, Singapore.
Lauren Smith, Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, Maryland, USA; Walter Reed Army Institute of Research, US Military HIV Research Program, B Cell Biology, Silver Spring, Maryland, USA.
Ying Cheng, Naval Medical Research Command, Diagnostics and Surveillance Department, Silver Spring, Maryland, USA; Leidos Holdings Inc., Reston, Maryland, USA.
Isabella Fox, Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, Maryland, USA; Naval Medical Research Command, Diagnostics and Surveillance Department, Silver Spring, Maryland, USA.
Hao Wang, Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, Maryland, USA; Naval Medical Research Command, Diagnostics and Surveillance Department, Silver Spring, Maryland, USA.
Hayley S Foo, U.S. Naval Medical Research Unit INDO PACIFIC, Science Directorate, Singapore, Singapore.
Mary Ann Serote, Naval Medical Readiness Training Command Yokosuka, Laboratory Department, Yokosuka, Japan.
Shelly J Krebs, Walter Reed Army Institute of Research, US Military HIV Research Program, B Cell Biology, Silver Spring, Maryland, USA.
Peifang Sun, Naval Medical Research Command, Diagnostics and Surveillance Department, Silver Spring, Maryland, USA.
Andrew G Letizia, U.S. Naval Medical Research Unit INDO PACIFIC, Science Directorate, Singapore, Singapore.
Supplementary Data
Supplementary materials are available at Open Forum Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.
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