Progesterone impairs antigen-non-specific immune protection by CD8 T memory cells via interferon-γ gene hypermethylation
Bibliographic record
Abstract
Pregnant women and animals have increased susceptibility to a variety of intracellular pathogens including Listeria monocytogenes (LM), which has been associated with significantly increased level of sex hormones such as progesterone. CD8 T memory(Tm) cell-mediated antigen-non-specific IFN-γ responses are critically required in the host defense against LM. However, whether and how increased progesterone during pregnancy modulates CD8 Tm cell-mediated antigen-non-specific IFN-γ production and immune protection against LM remain poorly understood. Here we show in pregnant women that increased serum progesterone levels are associated with DNA hypermethylation of IFN-γ gene promoter region and decreased IFN-γ production in CD8 Tm cells upon antigen-non-specific stimulation ex vivo. Moreover, IFN-γ gene hypermethylation and significantly reduced IFN-γ production post LM infection in antigen-non-specific CD8 Tm cells are also observed in pregnant mice or progesterone treated non-pregnant female mice, which is a reversible phenotype following demethylation treatment. Importantly, antigen-non-specific CD8 Tm cells from progesterone treated mice have impaired anti-LM protection when adoptive transferred in either pregnant wild type mice or IFN-γ-deficient mice, and demethylation treatment rescues the adoptive protection of such CD8 Tm cells. These data demonstrate that increased progesterone impairs immune protective functions of antigen-non-specific CD8 Tm cells via inducing IFN-γ gene hypermethylation. Our findings thus provide insights into a new mechanism through which increased female sex hormone regulate CD8 Tm cell functions during pregnancy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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) | 0.000 | 0.001 |
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 teacher head, 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".