The mutational signatures of poor treatment outcomes on the drug-susceptible Mycobacterium tuberculosis genome

  1. Yiwang Chen
  2. Qi Jiang
  3. Mijiti Peierdun
  4. Howard E Takiff
  5. Qian Gao  Is a corresponding author
  1. Fudan University, China
  2. Wuhan University, China
  3. Xinjiang Medical University, China
  4. Instituto Venezolano de Investigaciones Cientificas, Venezuela

Abstract

Drug resistance is a known risk factor for poor tuberculosis (TB) treatment outcomes, but the contribution of other bacterial factors to poor outcomes in drug susceptible TB is less well understood. Here, we generate a population-based dataset of drug-susceptible Mycobacterium tuberculosis (MTB) isolates from China to identify factors associated with poor treatment outcomes. We analyzed whole-genome sequencing (WGS) data of MTB strains from 3196 patients, including 3105 patients with good and 91 patients with poor treatment outcomes, and linked genomes to patient epidemiological data. A genome-wide association study (GWAS) was performed to identify bacterial genomic variants associated with poor outcomes. Risk factors identified by logistic regression analysis were used in clinical models to predict treatment outcomes. GWAS identified fourteen MTB fixed mutations associated with poor treatment outcomes, but only 24.2% (22/91) of strains from patients with poor outcomes carried at least one of these mutations. Isolates from patients with poor outcomes showed a higher ratio of reactive oxygen species (ROS)-associated mutations compared to isolates from patients with good outcomes (26.3% vs 22.9%, t test, P=0.027). Patient age, sex, and duration of diagnostic delay were also independently associated with poor outcomes. Bacterial factors alone had poor power to predict poor outcomes with an AUC of 0.58. The AUC with host factors alone was 0.70, but increased significantly to 0.74 (DeLong's test, P = 0.01) when bacterial factors were also included. In conclusion, although we identified MTB genomic mutations that are significantly associated with poor treatment outcomes in drug-susceptible TB cases, their effects appear to be limited.

Data availability

Files containing sequencing reads were deposited in the National Institutes of Health Sequence Read Archive under BioProject PRJNA869190.

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Yiwang Chen

    School of Basic Medical Sciences, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  2. Qi Jiang

    School of Public Health, Wuhan University, Wuhan, China
    Competing interests
    The authors declare that no competing interests exist.
  3. Mijiti Peierdun

    Department of Epidemiology and Biostatistics, Xinjiang Medical University, Urumqi, China
    Competing interests
    The authors declare that no competing interests exist.
  4. Howard E Takiff

    Instituto Venezolano de Investigaciones Cientificas, Caracas, Venezuela
    Competing interests
    The authors declare that no competing interests exist.
  5. Qian Gao

    School of Basic Medical Sciences, Fudan University, Shanghai, China
    For correspondence
    qiangao@fudan.edu.cn
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8489-3672

Funding

National Natural Science Foundation of China (81661128043,81871625)

  • Qian Gao

National Natural Science Foundation of China (82230078)

  • Qi Jiang

Shanghai Municipal Science and Technology Major Project (ZD2021CY001)

  • Qian Gao

Fundamental Research Funds for the Central Universities (2042021kf0041)

  • Qi Jiang

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Bavesh D Kana, University of the Witwatersrand, South Africa

Version history

  1. Received: November 9, 2022
  2. Preprint posted: November 21, 2022 (view preprint)
  3. Accepted: May 2, 2023
  4. Accepted Manuscript published: May 3, 2023 (version 1)
  5. Version of Record published: May 16, 2023 (version 2)

Copyright

© 2023, Chen et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Yiwang Chen
  2. Qi Jiang
  3. Mijiti Peierdun
  4. Howard E Takiff
  5. Qian Gao
(2023)
The mutational signatures of poor treatment outcomes on the drug-susceptible Mycobacterium tuberculosis genome
eLife 12:e84815.
https://doi.org/10.7554/eLife.84815

Share this article

https://doi.org/10.7554/eLife.84815

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