Deciphering the genetic architecture of variation in the immune response to <i>Mycobacterium tuberculosis</i> infection
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Tuberculosis (TB) is a major public health problem. One-third of the world's population is estimated to be infected with Mycobacterium tuberculosis (MTB), the etiological agent causing TB, and active disease kills nearly 2 million individuals worldwide every year. Several lines of evidence indicate that interindividual variation in susceptibility to TB has a heritable component, yet we still know little about the underlying genetic architecture. To address this, we performed a genome-wide mapping study of loci that are associated with functional variation in immune response to MTB. Specifically, we characterized transcript and protein expression levels and mapped expression quantitative trait loci (eQTL) in primary dendritic cells (DCs) from 65 individuals, before and after infection with MTB. We found 198 response eQTL, namely loci that were associated with variation in gene expression levels in either untreated or MTB-infected DCs, but not both. These response eQTL are associated with natural regulatory variation that likely affects (directly or indirectly) host interaction with MTB. Indeed, when we integrated our data with results from a genome-wide association study (GWAS) for pulmonary TB, we found that the response eQTL were more likely to be genetically associated with the disease. We thus identified a number of candidate loci, including the MAPK phosphatase DUSP14 in particular, that are promising susceptibility genes to pulmonary TB.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it