Persistent DNA Hyper-methylation Dampens Host Anti-Mycobacterial Immunity
Bibliographic record
Abstract
Abstract Mycobacterium tuberculosis (Mtb ) has co-evolved with humans for millennia and developed multiple mechanisms to evade host immunity. Restoring host immunity in order to shorten existing therapy and improve outcomes will require identifying the full complement by which host immunity is inhibited. Perturbing host DNA methylation is a mechanism induced by chronic infections such as HIV, HPV, LCMV and schistosomiasis to evade host immunity. Here, we evaluated the DNA methylation status of TB patients and their asymptomatic household contacts demonstrating that TB patients have DNA hyper-methylation of the IL-2-STAT5, TNF-NF-ϰB and IFN-γ signaling pathways. By MSRE-qPCR, multiple genes of the IL-12-IFN-γ signaling pathway ( IL12B, IL12RB2, TYK2, IFNGR1, JAK1 and JAK2 ) were hyper-methylated in TB patients. The DNA hyper-methylation of these pathways is associated with decreased immune responsiveness with decreased mitogen induced upregulation of IFN-γ, TNF, IL-6 and IL-1β production. The DNA hyper-methylation of the IL-12-IFN-γ pathway was associated with decreased IFN-γ induced gene expression and decreased IL-12 inducible up-regulation of IFN-γ. This work demonstrates that immune cells from TB patients are characterized by DNA hyper-methylation of genes critical to mycobacterial immunity resulting in decreased mycobacteria-specific and non-specific immune responsiveness.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".