NK- and T-cell granzyme B and K expression correlates with age, CMV infection and influenza vaccine-induced antibody titres in older adults
Bibliographic record
Abstract
Granzymes are a family of serine-proteases that act as critical mediators in the cytolytic and immunomodulatory activities of immune cells such as CD8 + T-cells and natural killer (NK) cells. Previous work indicates that both granzyme B (GZB) and K (GZK) are increased with age in CD8 + T-cells, and in the case of GZB, contribute to dysfunctional immune processes observed in older adults. Here, we sought to determine how GZB and GZK expression in NK-cells, and CD4 + , CD8 + , and gamma-delta T-cells, quantified in terms of positive cell frequency and mean fluorescence intensity (MFI), differed with age, age-related health-traits and the antibody response to high-dose influenza vaccine. We found that the frequency and MFI of GZB-expressing NK-cells, and CD8 + and Vδ1+ T-cells, and GZK-expressing CD8 + T-cells was significantly higher in older (66–97 years old; n = 75) vs. younger (24–37 years old; n = 10) adults by up to 5-fold. There were no significant associations of GZB/GZK expression with sex, frailty or plasma levels of TNF or IL-6 in older adults, but those who were seropositive for cytomegalovirus (CMV) exhibited significantly higher frequencies of GZB+ NK-cells, and CD4 + , CD8 + and Vδ1+ T-cells, and GZK+ CD8 + T-cells (Cohen’s d = .5–1.5). Pre-vaccination frequencies of GZB+ NK-cells were positively correlated with vaccine antibody responses against A/H3N2 (d = .17), while the frequencies of GZK+ NK and CD8 + T-cells were inversely associated with A/H1N1 (d = −0.18 to −0.20). Interestingly, GZK+ NK-cell frequency was inversely correlated with pre-vaccination A/H1N1 antibody titres, as well as those measured over the previous 4 years, further supporting a role for this subset in influencing vaccine antibody-responses. These findings further our understanding of how granzyme expression in different lymphoid cell-types may change with age, while suggesting that they influence vaccine responsiveness in older adults.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".