Association between bacterial homoplastic variants and radiological pathology in tuberculosis
Bibliographic record
Abstract
Background Understanding how pathogen genetic factors contribute to pathology in TB could enable tailored treatments to the most pathogenic and infectious strains. New strategies are needed to control drug-resistant TB, which requires longer and costlier treatment. We hypothesised that the severity of radiological pathology on the chest radiograph in TB disease was associated with variants arising independently, multiple times (homoplasies) in the Mycobacterium tuberculosis genome. Methods We performed whole genome sequencing (Illumina HiSeq2000 platform) on M. tuberculosis isolates from 103 patients with drug-resistant TB in Lima between 2010 and 2013. Variables including age, sex, HIV status, previous TB disease and the percentage of lung involvement on the pretreatment chest radiograph were collected from health posts of the national TB programme. Genomic variants were identified using standard pipelines. Results Two mutations were significantly associated with more widespread radiological pathology in a multivariable regression model controlling for confounding variables (Rv2828c.141, RR 1.3, 95% CI 1.21 to 1.39, p<0.01; rpoC.1040 95% CI 1.77 to 2.16, RR 1.9, p<0.01). The rpoB.450 mutation was associated with less extensive radiological pathology (RR 0.81, 95% CI 0.69 to 0.94, p=0.03), suggestive of a bacterial fitness cost for this mutation in vivo. Patients with a previous episode of TB disease and those between 10 and 30 years of age also had significantly increased radiological pathology. Conclusions This study is the first to compare the M. tuberculosis genome to radiological pathology on the chest radiograph. We identified two variants significantly positively associated with more widespread radiological pathology and one with reduced pathology. Prospective studies are warranted to determine whether mutations associated with increased pathology also predict the spread of drug-resistant TB.
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How this classification was reachedexpand
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".