Prediction of Susceptibility to First-Line Tuberculosis Drugs by DNA Sequencing
The authors’ full names (listed in alphabetical order) and academic degrees are as follows: Caroline Allix-Béguec, Ph.D., Irena Arandjelovic, Ph.D., Lijun Bi, Ph.D., Patrick Beckert, Ph.D., Maryline Bonnet, Ph.D., Phelim Bradley, D.Phil., Andrea M. Cabibbe, Ph.D., Irving Cancino-Mu？oz, Ph.D., Mark J. Caulfield, F.Med.Sci., Angkana Chaiprasert, Ph.D., Daniela M. Cirillo, M.D., David A. Clifton, D.Phil., I？aki Comas, Ph.D., Derrick W. Crook, F.R.C.Path., Maria R. De Filippo, Ph.D., Han de Neeling, Ph.D., Roland Diel, Ph.D., Francis A. Drobniewski, Ph.D., Kiatichai Faksri, Ph.D., Maha R. Farhat, M.D., Joy Fleming, Ph.D., Philip Fowler, Ph.D., Tom A. Fowler, Ph.D., Qian Gao, Ph.D., Jennifer Gardy, Ph.D., Deborah Gascoyne-Binzi, Ph.D., Ana-Luiza Gibertoni-Cruz, M.R.C.P., Ana Gil-Brusola, Ph.D., Tanya Golubchik, Ph.D., Ximena Gonzalo, M.D., Louis Grandjean, Ph.D., Guangxue He, Ph.D., Jennifer L. Guthrie, M.Sc., Sarah Hoosdally, Ph.D., Martin Hunt, Ph.D., Zamin Iqbal, D.Phil., Nazir Ismail, F.C.Path., James Johnston, M.D., Faisal M. Khanzada, M.Phil., Chiea C. Khor, D.Phil., Thomas A. Kohl, Ph.D., Clare Kong, Ph.D., Sam Lipworth, M.B., B.S., Qingyun Liu, Ph.D., Gugu Maphalala, Ph.D., Elena Martinez, Ph.D., Vanessa Mathys, Ph.D., Matthias Merker, Ph.D., Paolo Miotto, Ph.D., Nerges Mistry, Ph.D., David A.J. Moore, F.R.C.P., Megan Murray, M.D., Stefan Niemann, Ph.D., Rick T.-H. Ong, Ph.D., Tim E.A. Peto, D.Phil., James E. Posey, Ph.D., Therdsak Prammananan, Ph.D., Alexander Pym, Ph.D., Camilla Rodrigues, M.D., Mabel Rodrigues, Ph.D., Timothy Rodwell, Ph.D., Gian M. Rossolini, M.D., Elisabeth Sánchez Padilla, M.D., Marco Schito, Ph.D., Xin Shen, Ph.D., Jay Shendure, Ph.D., Vitali Sintchenko, Ph.D., Alex Sloutsky, Ph.D., E. Grace Smith, F.R.C.Path., Matthew Snyder, Ph.D., Karine Soetaert, Ph.D., Angela M. Starks, Ph.D., Philip Supply, Ph.D., Prapat Suriyapol, Ph.D., Sabira Tahseen, M.B., B.S., Patrick Tang, Ph.D., Yik-Ying Teo, Ph.D., Thuong N.T. Thuong, Ph.D., Guy Thwaites, F.R.C.P., Enrico Tortoli, Ph.D., Shaheed V. Omar, Ph.D., Dick van Soolingen, Ph.D., A. Sarah Walker, Ph.D., Timothy M. Walker, D.Phil., Mark Wilcox, M.D., Daniel J. Wilson, D.Phil., David Wyllie, Ph.D., Yang Yang, Ph.D., Hongtai Zhang, Ph.D., Yanlin Zhao, Ph.D., and Baoli Zhu, Ph.D.
Abstract
BACKGROUND
The 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.
METHODS
We 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.
RESULTS
A 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 profiles that were predicted to be pansusceptible, 3952 (97.9%) were correctly predicted.
CONCLUSIONS
Genotypic predictions of the susceptibility of M. tuberculosis to first-line drugs were found to be correlated with phenotypic susceptibility to these drugs. (Funded by the Bill and Melinda Gates Foundation and others.)
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Prediction of Susceptibility to First-Line Tuberculosis Drugs by DNA Sequencing, N Engl J Med, 11 Oct 2018
N Engl J Med, 11 October, 2018，DOI: http://dx.doi.org/10.1056/NEJMoa1800474
Prediction of Susceptibility to First-Line Tuberculosis Drugs by DNA Sequencing
The authors’ full names (listed in alphabetical order) and academic degrees are as follows: Caroline Allix-Béguec, Ph.D., Irena Arandjelovic, Ph.D., Lijun Bi, Ph.D., Patrick Beckert, Ph.D., Maryline Bonnet, Ph.D., Phelim Bradley, D.Phil., Andrea M. Cabibbe, Ph.D., Irving Cancino-Mu？oz, Ph.D., Mark J. Caulfield, F.Med.Sci., Angkana Chaiprasert, Ph.D., Daniela M. Cirillo, M.D., David A. Clifton, D.Phil., I？aki Comas, Ph.D., Derrick W. Crook, F.R.C.Path., Maria R. De Filippo, Ph.D., Han de Neeling, Ph.D., Roland Diel, Ph.D., Francis A. Drobniewski, Ph.D., Kiatichai Faksri, Ph.D., Maha R. Farhat, M.D., Joy Fleming, Ph.D., Philip Fowler, Ph.D., Tom A. Fowler, Ph.D., Qian Gao, Ph.D., Jennifer Gardy, Ph.D., Deborah Gascoyne-Binzi, Ph.D., Ana-Luiza Gibertoni-Cruz, M.R.C.P., Ana Gil-Brusola, Ph.D., Tanya Golubchik, Ph.D., Ximena Gonzalo, M.D., Louis Grandjean, Ph.D., Guangxue He, Ph.D., Jennifer L. Guthrie, M.Sc., Sarah Hoosdally, Ph.D., Martin Hunt, Ph.D., Zamin Iqbal, D.Phil., Nazir Ismail, F.C.Path., James Johnston, M.D., Faisal M. Khanzada, M.Phil., Chiea C. Khor, D.Phil., Thomas A. Kohl, Ph.D., Clare Kong, Ph.D., Sam Lipworth, M.B., B.S., Qingyun Liu, Ph.D., Gugu Maphalala, Ph.D., Elena Martinez, Ph.D., Vanessa Mathys, Ph.D., Matthias Merker, Ph.D., Paolo Miotto, Ph.D., Nerges Mistry, Ph.D., David A.J. Moore, F.R.C.P., Megan Murray, M.D., Stefan Niemann, Ph.D., Rick T.-H. Ong, Ph.D., Tim E.A. Peto, D.Phil., James E. Posey, Ph.D., Therdsak Prammananan, Ph.D., Alexander Pym, Ph.D., Camilla Rodrigues, M.D., Mabel Rodrigues, Ph.D., Timothy Rodwell, Ph.D., Gian M. Rossolini, M.D., Elisabeth Sánchez Padilla, M.D., Marco Schito, Ph.D., Xin Shen, Ph.D., Jay Shendure, Ph.D., Vitali Sintchenko, Ph.D., Alex Sloutsky, Ph.D., E. Grace Smith, F.R.C.Path., Matthew Snyder, Ph.D., Karine Soetaert, Ph.D., Angela M. Starks, Ph.D., Philip Supply, Ph.D., Prapat Suriyapol, Ph.D., Sabira Tahseen, M.B., B.S., Patrick Tang, Ph.D., Yik-Ying Teo, Ph.D., Thuong N.T. Thuong, Ph.D., Guy Thwaites, F.R.C.P., Enrico Tortoli, Ph.D., Shaheed V. Omar, Ph.D., Dick van Soolingen, Ph.D., A. Sarah Walker, Ph.D., Timothy M. Walker, D.Phil., Mark Wilcox, M.D., Daniel J. Wilson, D.Phil., David Wyllie, Ph.D., Yang Yang, Ph.D., Hongtai Zhang, Ph.D., Yanlin Zhao, Ph.D., and Baoli Zhu, Ph.D.
Abstract
BACKGROUND
The 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.
METHODS
We 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.
RESULTS
A 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 profiles that were predicted to be pansusceptible, 3952 (97.9%) were correctly predicted.CONCLUSIONS
Genotypic predictions of the susceptibility of M. tuberculosis to first-line drugs were found to be correlated with phenotypic susceptibility to these drugs. (Funded by the Bill and Melinda Gates Foundation and others.)文章链接：https://www.nejm.org/doi/10.1056/NEJMoa1800474