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 IFNγ gene hypermethylation.Our findings thus provide insights into a new mechanism through which increased female sex hormone regulate CD8 Tm cell functions during pregnancy. Author summaryIncreased female sex hormones during pregnancy generate a temporary immune suppression status in the pregnant that protect the developing fetus from maternal rejection but renders the pregnant highly susceptible to various pathogens.However, molecular mechanisms underlying such an increased maternal susceptibility to pathogens during
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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) | 0.001 | 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".