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Using Mycobacterium tuberculosis Single-Nucleotide Polymorphisms To Predict Fluoroquinolone Treatment Response.

Abstract

Clinical phenotypic fluoroquinolone susceptibility testing of Mycobacterium tuberculosis is currently based on M. tuberculosis growth at a single critical concentration, which provides limited information for a nuanced clinical response. We propose using specific resistance-conferring M. tuberculosis mutations in gyrA together with population pharmacokinetic and pharmacodynamic modeling as a novel tool to better inform fluoroquinolone treatment decisions. We sequenced the gyrA resistance-determining region of 138 clinical M. tuberculosis isolates collected from India, Moldova, Philippines, and South Africa and then determined each strain's MIC against ofloxacin, moxifloxacin, levofloxacin, and gatifloxacin. Strains with specific gyrA single-nucleotide polymorphisms (SNPs) were grouped into high or low drug-specific resistance categories based on their empirically measured MICs. Published population pharmacokinetic models were then used to explore the pharmacokinetics and pharmacodynamics of each fluoroquinolone relative to the empirical MIC distribution for each resistance category to make predictions about the likelihood of patients achieving defined therapeutic targets. In patients infected with M. tuberculosis isolates containing SNPs associated with a fluoroquinolone-specific low-level increase in MIC, models suggest increased fluoroquinolone dosing improved the probability of achieving therapeutic targets for gatifloxacin and moxifloxacin but not for levofloxacin and ofloxacin. In contrast, among patients with isolates harboring SNPs associated with a high-level increase in MIC, increased dosing of levofloxacin, moxifloxacin, gatifloxacin, or ofloxacin did not meaningfully improve the probability of therapeutic target attainment. We demonstrated that quantifiable fluoroquinolone drug resistance phenotypes could be predicted from rapidly detectable gyrA SNPs and used to support dosing decisions based on the likelihood of patients reaching therapeutic targets. Our findings provide further supporting evidence for the moxifloxacin clinical breakpoint recently established by the World Health Organization.

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