[HTML][HTML] Investigating resistance in clinical Mycobacterium tuberculosis complex isolates with genomic and phenotypic antimicrobial susceptibility testing: a multicentre …

I Finci, A Albertini, M Merker, S Andres… - The Lancet …, 2022 - thelancet.com
I Finci, A Albertini, M Merker, S Andres, N Bablishvili, I Barilar, T Cáceres, V Crudu
The Lancet Microbe, 2022thelancet.com
Background Whole-genome sequencing (WGS) of Mycobacterium tuberculosis complex has
become an important tool in diagnosis and management of drug-resistant tuberculosis.
However, data correlating resistance genotype with quantitative phenotypic antimicrobial
susceptibility testing (AST) are scarce. Methods In a prospective multicentre observational
study, 900 clinical M tuberculosis complex isolates were collected from adults with drug-
resistant tuberculosis in five high-endemic tuberculosis settings around the world (Georgia …
Background
Whole-genome sequencing (WGS) of Mycobacterium tuberculosis complex has become an important tool in diagnosis and management of drug-resistant tuberculosis. However, data correlating resistance genotype with quantitative phenotypic antimicrobial susceptibility testing (AST) are scarce.
Methods
In a prospective multicentre observational study, 900 clinical M tuberculosis complex isolates were collected from adults with drug-resistant tuberculosis in five high-endemic tuberculosis settings around the world (Georgia, Moldova, Peru, South Africa, and Viet Nam) between Dec 5, 2014, and Dec 12, 2017. Minimum inhibitory concentrations (MICs) and resulting binary phenotypic AST results for up to nine antituberculosis drugs were determined and correlated with resistance-conferring mutations identified by WGS.
Findings
Considering WHO-endorsed critical concentrations as reference, WGS had high accuracy for prediction of resistance to isoniazid (sensitivity 98·8% [95% CI 98·5–99·0]; specificity 96·6% [95% CI 95·2–97·9]), levofloxacin (sensitivity 94·8% [93·3–97·6]; specificity 97·1% [96·7–97·6]), kanamycin (sensitivity 96·1% [95·4–96·8]; specificity 95·0% [94·4–95·7]), amikacin (sensitivity 97·2% [96·4–98·1]; specificity 98·6% [98·3–98·9]), and capreomycin (sensitivity 93·1% [90·0–96·3]; specificity 98·3% [98·0–98·7]). For rifampicin, pyrazinamide, and ethambutol, the specificity of resistance prediction was suboptimal (64·0% [61·0–67·1], 83·8% [81·0–86·5], and 40·1% [37·4–42·9], respectively). Specificity for rifampicin increased to 83·9% when borderline mutations with MICs overlapping with the critical concentration were excluded. Consequently, we highlighted mutations in M tuberculosis complex isolates that are often falsely identified as susceptible by phenotypic AST, and we identified potential novel resistance-conferring mutations.
Interpretation
The combined analysis of mutations and quantitative phenotypes shows the potential of WGS to produce a refined interpretation of resistance, which is needed for individualised therapy, and eventually could allow differential drug dosing. However, variability of MIC data for some M tuberculosis complex isolates carrying identical mutations also reveals limitations of our understanding of the genotype and phenotype relationships (eg, including epistasis and strain genetic background).
Funding
Bill & Melinda Gates Foundation, German Centre for Infection Research, German Research Foundation, Excellence Cluster Precision Medicine of Inflammation (EXC 2167), and Leibniz ScienceCampus EvoLUNG.
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