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Prediction of Susceptibility to First-Line Tuberculosis Drugs by DNA Sequencing.

Authors :
CRyPTIC Consortium and the 100,000 Genomes Project
CRyPTIC Consortium and the 100,000 Genomes Project
Allix-Béguec, Caroline
Arandjelovic, Irena
Bi, Lijun
Beckert, Patrick
Bonnet, Maryline
Bradley, Phelim
Cabibbe, Andrea M
Cancino-Muñoz, Irving
Caulfield, Mark J
Chaiprasert, Angkana
Cirillo, Daniela M
Clifton, David A
Comas, Iñaki
Crook, Derrick W
De Filippo, Maria R
de Neeling, Han
Diel, Roland
Drobniewski, Francis A
Faksri, Kiatichai
Farhat, Maha R
Fleming, Joy
Fowler, Philip
Fowler, Tom A
Gao, Qian
Gardy, Jennifer
Gascoyne-Binzi, Deborah
Gibertoni-Cruz, Ana-Luiza
Gil-Brusola, Ana
Golubchik, Tanya
Gonzalo, Ximena
Grandjean, Louis
He, Guangxue
Guthrie, Jennifer L
Hoosdally, Sarah
Hunt, Martin
Iqbal, Zamin
Ismail, Nazir
Johnston, James
Khanzada, Faisal M
Khor, Chiea C
Kohl, Thomas A
Kong, Clare
Lipworth, Sam
Liu, Qingyun
Maphalala, Gugu
Martinez, Elena
Mathys, Vanessa
Merker, Matthias
Miotto, Paolo
Mistry, Nerges
Moore, David AJ
Murray, Megan
Niemann, Stefan
Omar, Shaheed V
Ong, Rick T-H
Peto, Tim EA
Posey, James E
Prammananan, Therdsak
Pym, Alexander
Rodrigues, Camilla
Rodrigues, Mabel
Rodwell, Timothy
Rossolini, Gian M
Sánchez Padilla, Elisabeth
Schito, Marco
Shen, Xin
Shendure, Jay
Sintchenko, Vitali
Sloutsky, Alex
Smith, E Grace
Snyder, Matthew
Soetaert, Karine
Starks, Angela M
Supply, Philip
Suriyapol, Prapat
Tahseen, Sabira
Tang, Patrick
Teo, Yik-Ying
Thuong, Thuong NT
Thwaites, Guy
Tortoli, Enrico
van Soolingen, Dick
Walker, A Sarah
Walker, Timothy M
Wilcox, Mark
Wilson, Daniel J
Wyllie, David
Yang, Yang
Zhang, Hongtai
Zhao, Yanlin
Zhu, Baoli
CRyPTIC Consortium and the 100,000 Genomes Project
CRyPTIC Consortium and the 100,000 Genomes Project
Allix-Béguec, Caroline
Arandjelovic, Irena
Bi, Lijun
Beckert, Patrick
Bonnet, Maryline
Bradley, Phelim
Cabibbe, Andrea M
Cancino-Muñoz, Irving
Caulfield, Mark J
Chaiprasert, Angkana
Cirillo, Daniela M
Clifton, David A
Comas, Iñaki
Crook, Derrick W
De Filippo, Maria R
de Neeling, Han
Diel, Roland
Drobniewski, Francis A
Faksri, Kiatichai
Farhat, Maha R
Fleming, Joy
Fowler, Philip
Fowler, Tom A
Gao, Qian
Gardy, Jennifer
Gascoyne-Binzi, Deborah
Gibertoni-Cruz, Ana-Luiza
Gil-Brusola, Ana
Golubchik, Tanya
Gonzalo, Ximena
Grandjean, Louis
He, Guangxue
Guthrie, Jennifer L
Hoosdally, Sarah
Hunt, Martin
Iqbal, Zamin
Ismail, Nazir
Johnston, James
Khanzada, Faisal M
Khor, Chiea C
Kohl, Thomas A
Kong, Clare
Lipworth, Sam
Liu, Qingyun
Maphalala, Gugu
Martinez, Elena
Mathys, Vanessa
Merker, Matthias
Miotto, Paolo
Mistry, Nerges
Moore, David AJ
Murray, Megan
Niemann, Stefan
Omar, Shaheed V
Ong, Rick T-H
Peto, Tim EA
Posey, James E
Prammananan, Therdsak
Pym, Alexander
Rodrigues, Camilla
Rodrigues, Mabel
Rodwell, Timothy
Rossolini, Gian M
Sánchez Padilla, Elisabeth
Schito, Marco
Shen, Xin
Shendure, Jay
Sintchenko, Vitali
Sloutsky, Alex
Smith, E Grace
Snyder, Matthew
Soetaert, Karine
Starks, Angela M
Supply, Philip
Suriyapol, Prapat
Tahseen, Sabira
Tang, Patrick
Teo, Yik-Ying
Thuong, Thuong NT
Thwaites, Guy
Tortoli, Enrico
van Soolingen, Dick
Walker, A Sarah
Walker, Timothy M
Wilcox, Mark
Wilson, Daniel J
Wyllie, David
Yang, Yang
Zhang, Hongtai
Zhao, Yanlin
Zhu, Baoli
Source :
The New England journal of medicine; vol 379, iss 15, 1403-1415; 0028-4793
Publication Year :
2018

Abstract

BackgroundThe World Health Organization recommends drug-susceptibility testing of Mycobacterium tuberculosis complex for all patients with tuberculosis to guide treatment decisions and improve outcomes. Whether DNA sequencing can be used to accurately predict profiles of susceptibility to first-line antituberculosis drugs has not been clear.MethodsWe obtained whole-genome sequences and associated phenotypes of resistance or susceptibility to the first-line antituberculosis drugs isoniazid, rifampin, ethambutol, and pyrazinamide for isolates from 16 countries across six continents. For each isolate, mutations associated with drug resistance and drug susceptibility were identified across nine genes, and individual phenotypes were predicted unless mutations of unknown association were also present. To identify how whole-genome sequencing might direct first-line drug therapy, complete susceptibility profiles were predicted. These profiles were predicted to be susceptible to all four drugs (i.e., pansusceptible) if they were predicted to be susceptible to isoniazid and to the other drugs or if they contained mutations of unknown association in genes that affect susceptibility to the other drugs. We simulated the way in which the negative predictive value changed with the prevalence of drug resistance.ResultsA total of 10,209 isolates were analyzed. The largest proportion of phenotypes was predicted for rifampin (9660 [95.4%] of 10,130) and the smallest was predicted for ethambutol (8794 [89.8%] of 9794). Resistance to isoniazid, rifampin, ethambutol, and pyrazinamide was correctly predicted with 97.1%, 97.5%, 94.6%, and 91.3% sensitivity, respectively, and susceptibility to these drugs was correctly predicted with 99.0%, 98.8%, 93.6%, and 96.8% specificity. Of the 7516 isolates with complete phenotypic drug-susceptibility profiles, 5865 (78.0%) had complete genotypic predictions, among which 5250 profiles (89.5%) were correctly predicted. Among the 4037 phenotypic profil

Details

Database :
OAIster
Journal :
The New England journal of medicine; vol 379, iss 15, 1403-1415; 0028-4793
Notes :
application/pdf, The New England journal of medicine vol 379, iss 15, 1403-1415 0028-4793
Publication Type :
Electronic Resource
Accession number :
edsoai.on1391608671
Document Type :
Electronic Resource