Two loci control tuberculin skin test reactivity in an area hyperendemic for tuberculosis
Bibliographic record
Abstract
Approximately 20% of persons living in areas hyperendemic for tuberculosis (TB) display persistent lack of tuberculin skin test (TST) reactivity and appear to be naturally resistant to infection by Mycobacterium tuberculosis. Among those with a positive response, the intensity of TST reactivity varies greatly. The genetic basis of TST reactivity is not known. We report on a genome-wide linkage search for loci that have an impact on TST reactivity, which is defined either as zero versus nonzero (TST-BINa) or as extent of TST in millimeters (TST-quantitative trait locus [QTL]) in a panel of 128 families, including 350 siblings, from an area of South Africa hyperendemic for TB. We detected a major locus (TST1) on chromosomal region 11p14 (P = 1.4 x 10(-5)), which controls TST-BINa, with a lack of responsiveness indicating T cell-independent resistance to M. tuberculosis. We also detected a second major locus (TST2) on chromosomal region 5p15 (P < 10(-5)), which controls TST-QTL or the intensity of T cell-mediated delayed type hypersensitivity (DTH) to tuberculin. Fine mapping of this region identified SLC6A3, encoding the dopamine transporter DAT1, as a promising gene for further studies. Our results pave the way for the understanding of the molecular mechanisms involved in resistance to M. tuberculosis infection in endemic areas (TST1) and for the identification of critical regulators of T cell-dependent DTH to tuberculin (TST2).
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".