Genome MedicineGenetic & Genomic MedicinePeer-reviewed journal article
Clinical and bacterial determinants of unfavorable tuberculosis treatment outcomes: an observational study in Georgia
Galo Adrián GoigiD, Chloé LoiseauiD, Nino MaghradzeiD, Kakha MchedlishviliiD, Teona AvalianiiD, Ana TsutsunavaiD, Daniela BritesiD, Sevda Kalkan, Sònia BorrelliD, Rusudan Aspindzelashvili, Zaza AvalianiiD, Maia KipianiiD, Nestani TukvadzeiD, Levan Jugheli, Sébastien GagneuxiD
- Citations
- 4
- FWCI
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- Field percentile
- top 8%
Abstract
Tuberculosis (TB) remains a major public health concern. Improving TB control programmes and treatment success rates requires a deeper understanding of the factors that determine disease presentation and patient treatment outcomes. While the demographic and clinical factors influencing treatment outcomes are well documented, the role of bacterial genetics remains limited. In this study, we analyzed the Mycobacterium tuberculosis complex (MTBC) genomes and the associated clinical data from 4,536 TB patients in the country of Georgia covering a period of 13 years. Multivariable modelling confirmed the role of known demographic and clinical factors such as sex, age, body mass index (BMI) and comorbidities in determining treatment outcomes, as well as the efficacy of novel TB treatments containing bedaquiline. In addition, we found that some bacterial variables, including the MTBC lineage, the specific mutations conferring resistance to rifampicin and fluoroquinolones, as well as a high bacterial burden were associated with unfavorable outcomes. GWAS analyses revealed no genetic mutations in the bacteria other than known drug resistance-conferring mutations to be associated with treatment outcomes. However, we found that mutations in the bacterial gene sufD were linked to cavitary disease. Additionally, we observed that mutations in sufD, mutations conferring resistance to rifampicin and fitness compensatory mutations were associated with the bacterial burden within patients. We conclude that both patient and bacterial factors determine disease presentation and clinical outcomes in TB.
- organism: human
- assay: whole-genome sequencing
- research focus: differential expression
- research focus: variant calling
- approach: statistical model
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