Evidence map›Paper›PMID 23749189›Full record

ArticleNature genetics2013

Mycobacterium tuberculosis mutation rate estimates from different lineages predict substantial differences in the emergence of drug-resistant tuberculosis.

Christopher B Ford, Rupal R Shah, Midori Kato Maeda, Sebastien Gagneux, Megan B Murray, Ted Cohen, James C Johnston, Jennifer Gardy, Marc Lipsitch, Sarah M Fortune

Abstract read
In one paragraph

Article in Nature genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 270 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
270citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

270 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. ClinicalFrontiers in microbiology · 2025
    Pooled it
  3. Pooled it
  4. Pooled it
  5. Acquisition of Rifampin Resistance in Pulmonary Tuberculosis.Antimicrobial agents and chemotherapy · 2017
    Trial
  6. Article
  7. Microbiology spectrum · 2026
    Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Observational
  14. Article
  15. Article
  16. Article
  17. The unique role ofmBio · 2026
    Article
  18. Article
  19. Article
  20. Article

210 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Christopher B FordDepartment of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, MA, USA.
Rupal R Shah
Midori Kato Maeda
Sebastien Gagneux
Megan B Murray
Ted Cohen
James C Johnston
Jennifer Gardy
Marc Lipsitch
Sarah M Fortune

Funding

Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI HANAGE, WILLIAM · 2009 to 2018
$26.4M
Real-time surveillance to support dynamic and predictive models of MDR/XDR TBU19AI076217 · NIAID · BRIGHAM AND WOMEN'S HOSPITAL · PI FARMER, PAUL EDWARD · 2007 to 2011
$13.5M
Variation in M. tuberculosis in response to host selectionDP2OD001378 · OD · HARVARD SCHOOL OF PUBLIC HEALTH · PI FORTUNE, SARAH · 2007 to 2009
$2.5M
IMMUNOLOGY AND INFECTIOUS DISEASES IN PUBLIC HEALTHT32AI007638 · NIAID · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI RUBIN, ERIC J. · 2000 to 2014
$2.2M
Howard Hughes Medical InstituteNCCDPHP CDC HHS DP2 0D001378NIAID NIH HHS T32 AI007638NIAID NIH HHS U19 AI076217NIGMS NIH HHS 1 U54 GM088558NIGMS NIH HHS U54 GM088558NIH HHS DP2 OD001378
6 · The paper itself

Abstract

A key question in tuberculosis control is why some strains of M. tuberculosis are preferentially associated with resistance to multiple drugs. We demonstrate that M. tuberculosis strains from lineage 2 (East Asian lineage and Beijing sublineage) acquire drug resistances in vitro more rapidly than M. tuberculosis strains from lineage 4 (Euro-American lineage) and that this higher rate can be attributed to a higher mutation rate. Moreover, the in vitro mutation rate correlates well with the bacterial mutation rate in humans as determined by whole-genome sequencing of clinical isolates. Finally, using a stochastic mathematical model, we demonstrate that the observed differences in mutation rate predict a substantially higher probability that patients infected with a drug-susceptible lineage 2 strain will harbor multidrug-resistant bacteria at the time of diagnosis. These data suggest that interventions to prevent the emergence of drug-resistant tuberculosis should target bacterial as well as treatment-related risk factors.

Indexed as

Mutation RateAntibiotics, AntitubercularBiomarkers, PharmacologicalCommunicable Diseases, EmergingComputer SimulationDrug Resistance, Multiple, BacterialGenetic SpeciationHumansMutationMycobacterium tuberculosisPrognosisTuberculosis, Multidrug-ResistantAntibiotics, AntitubercularBiomarkers, Pharmacological

Identifiers

PMID23749189
PMCPMC3777616

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.