Human Mucosal-Associated Invariant T Cells in Older Individuals Display Expanded TCRαβ Clonotypes with Potent Antimicrobial Responses
Bibliographic record
Abstract
Abstract Mucosal-associated invariant T (MAIT) cells are important for immune responses against microbial infections. Although known to undergo marked numerical changes with age in humans, our understanding of how MAIT cells are altered during different phases across the human life span is largely unknown. Although also abundant in the tissues, our study focuses on MAIT cell analyses in blood. Across the human life span, we show that naive-like MAIT cells in umbilical cord blood switch to a central/effector memory-like profile that is sustained into older age. Whereas low-grade levels of plasma cytokine/chemokine were apparent in older donors (>65 y old), surprisingly, they did not correlate with the ex vivo MAIT hyperinflammatory cytokine profile observed in older adults. Removal of MAIT cells from older individuals and an aged environment resulted in the reversal of the baseline effector molecule profile comparable with MAIT cells from younger adults. An upregulated basal inflammatory profile accounted for reduced Escherichia coli–specific responses in aged MAIT cells compared with their young adult counterparts when fold change in expression levels of GzmB, CD107a, IFN-γ, and TNF was examined. However, the magnitude of antimicrobial MR1-dependent activation remained as potent and polyfunctional as with younger adults. Paired TCRαβ analyses of MAIT cells revealed large clonal expansions in older adults and tissues that rivalled, remarkably, the TCRαβ repertoire diversity of virus-specific CD8+ T cells. These data suggest that MAIT cells in older individuals, although associated with large clonal TCRαβ expansions and increased baseline inflammatory potential, demonstrate plasticity and provide potent antimicrobial immunity.
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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 | 0.000 |
| 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) | 0.002 | 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".