An eQTL variant of ZXDC is associated with IFN-γ production following Mycobacterium tuberculosis antigen-specific stimulation
Bibliographic record
Abstract
Abstract There is a large inter-individual variability in the response to Mycobacterium tuberculosis infection. In previous linkage analyses, we identified a major locus on chromosome region 8q controlling IFN-γ production after stimulation with live BCG (Bacillus Calmette-Guérin), and a second locus on chromosome region 3q affecting IFN-γ production triggered by the 6-kDa early secretory antigen target (ESAT-6), taking into account the IFN-γ production induced by BCG (IFNγ-ESAT6BCG). High-density genotyping and imputation identified ~100,000 variants within each linkage region, which we tested for association with the corresponding IFN-γ phenotype in families from a tuberculosis household contact study in France. Significant associations were replicated in a South African familial sample. The most convincing association observed was that between the IFNγ-ESAT6BCG phenotype and rs9828868 on chromosome 3q (p = 9.8 × 10−6 in the French sample). This variant made a significant contribution to the linkage signal (p < 0.001), and a trend towards the same association was observed in the South African sample. This variant was reported to be an eQTL of the ZXDC gene, biologically linked to monocyte IL-12 production through CCL2/MCP1. The identification of rs9828868 as a genetic driver of IFNγ production in response to mycobacterial antigens provides new insights into human anti-tuberculosis 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".