TY - JOUR
T1 - Drug-penetration gradients associated with acquired drug resistance in patients with tuberculosis
AU - Dheda, Keertan
AU - Lenders, Laura
AU - Magombedze, Gesham
AU - Srivastava, Shashikant
AU - Raj, Prithvi
AU - Arning, Erland
AU - Ashcraft, Paula
AU - Bottiglieri, Teodoro
AU - Wainwright, Helen
AU - Pennel, Timothy
AU - Linegar, Anthony
AU - Moodley, Loven
AU - Pooran, Anil
AU - Pasipanodya, Jotam G.
AU - Sirgel, Frederick A.
AU - Van Helden, Paul D.
AU - Wakeland, Edward K
AU - Warren, Robin M.
AU - Gumbo, Tawanda
N1 - Funding Information:
Supported by Baylor Research Institute and the NIH (T.G.) and by the South African Medical Research Council, the European Developing Clinical Trials Partnership, the National Research Foundation, and the Oppenheimer Foundation (K.D.).
Publisher Copyright:
© 2018 by the American Thoracic Society.
PY - 2018/11/1
Y1 - 2018/11/1
N2 - Rationale: Acquired resistance is an important driver of multidrugresistant tuberculosis (TB), even with good treatment adherence. However, exactly what initiates the resistance and how it arises remain poorly understood. Objectives: To identify the relationship between drug concentrations and drug susceptibility readouts (minimuminhibitory concentrations [MICs]) in the TB cavity. Methods: We recruited patients with medically incurable TB who were undergoing therapeutic lung resection while on treatment with a cocktail of second-line anti-TB drugs. On the day of surgery, antibiotic concentrations were measured in the blood and at seven prespecified biopsy sites within each cavity. Mycobacterium tuberculosis was grown from each biopsy site,MICs of each drug identified, and whole-genome sequencing performed. Spearman correlation coefficients between drug concentration and MIC were calculated. Measurements and Main Results: Fourteen patients treated for a median of 13 months (range, 5-31 mo) were recruited. MICs and drug resistance-associated single-nucleotide variants differed between the different geospatial locations within each cavity, and with pretreatment and serial sputum isolates, consistent with ongoing acquisition of resistance. However, pretreatment sputum MIC had an accuracy of only 49.48% in predicting cavitary MICs. There were large concentration-distance gradients for each antibiotic. The location-specific concentrations inversely correlated with MICs (P,0.05) and therefore acquired resistance. Moreover, pharmacokinetic/pharmacodynamic exposures known to amplify drug-resistant subpopulations were encountered in all positions. Conclusions: These data inform interventional strategies relevant to drug delivery, dosing, and diagnostics to prevent the development of acquired resistance. The role of high intracavitary penetration as a biomarker of antibiotic efficacy, when assessing new regimens, requires clarification.
AB - Rationale: Acquired resistance is an important driver of multidrugresistant tuberculosis (TB), even with good treatment adherence. However, exactly what initiates the resistance and how it arises remain poorly understood. Objectives: To identify the relationship between drug concentrations and drug susceptibility readouts (minimuminhibitory concentrations [MICs]) in the TB cavity. Methods: We recruited patients with medically incurable TB who were undergoing therapeutic lung resection while on treatment with a cocktail of second-line anti-TB drugs. On the day of surgery, antibiotic concentrations were measured in the blood and at seven prespecified biopsy sites within each cavity. Mycobacterium tuberculosis was grown from each biopsy site,MICs of each drug identified, and whole-genome sequencing performed. Spearman correlation coefficients between drug concentration and MIC were calculated. Measurements and Main Results: Fourteen patients treated for a median of 13 months (range, 5-31 mo) were recruited. MICs and drug resistance-associated single-nucleotide variants differed between the different geospatial locations within each cavity, and with pretreatment and serial sputum isolates, consistent with ongoing acquisition of resistance. However, pretreatment sputum MIC had an accuracy of only 49.48% in predicting cavitary MICs. There were large concentration-distance gradients for each antibiotic. The location-specific concentrations inversely correlated with MICs (P,0.05) and therefore acquired resistance. Moreover, pharmacokinetic/pharmacodynamic exposures known to amplify drug-resistant subpopulations were encountered in all positions. Conclusions: These data inform interventional strategies relevant to drug delivery, dosing, and diagnostics to prevent the development of acquired resistance. The role of high intracavitary penetration as a biomarker of antibiotic efficacy, when assessing new regimens, requires clarification.
KW - acquired drug resistance
KW - drug gradient
KW - lung cavity
KW - sputum MIC
KW - whole-genome sequencing
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U2 - 10.1164/rccm.201711-2333OC
DO - 10.1164/rccm.201711-2333OC
M3 - Article
C2 - 29877726
AN - SCOPUS:85050748574
SN - 1073-449X
VL - 198
SP - 1208
EP - 1219
JO - American journal of respiratory and critical care medicine
JF - American journal of respiratory and critical care medicine
IS - 9
ER -