Advanced biological age is associated with improved antibody responses in older high-dose influenza vaccine recipients over four consecutive seasons
Bibliographic record
Abstract
BACKGROUND: Biological aging represents a loss of integrity and functionality of physiological systems over time. While associated with an enhanced risk of adverse outcomes such as hospitalization, disability and death following infection, its role in perceived age-related declines in vaccine responses has yet to be fully elucidated. Using data and biosamples from a 4-year clinical trial comparing immune responses of standard- and high-dose influenza vaccination, we quantified biological age (BA) prior to vaccination in adults over 65 years old (n = 292) using a panel of ten serological biomarkers (albumin, alanine aminotransferase, creatinine, ferritin, free thyroxine, cholesterol, high-density lipoprotein, triglycerides, tumour necrosis factor, interleukin-6) as implemented in the BioAge R package. Hemagglutination inhibition antibody titres against influenza A/H1N1, A/H3N2 and B were quantified prior to vaccination and 4-, 10- and 20- weeks post-vaccination. RESULTS: Counter to our hypothesis, advanced BA was associated with improved post-vaccination antibody titres against the different viral types and subtypes. However, this was dependent on both vaccine dose and CMV serostatus, as associations were only apparent for high-dose recipients (d = 0.16-0.26), and were largely diminished for CMV positive high-dose recipients. CONCLUSIONS: These findings emphasize two important points: first, the loss of physiological integrity related to biological aging may not be a ubiquitous driver of immune decline in older adults; and second, latent factors such as CMV infection (prevalent in up to 90% of older adults worldwide) may contribute to the heterogeneity in vaccine responses of older adults more than previously thought.
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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 | 0.001 | 0.002 |
| 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".