Applying whole genome sequencing to predict phenotypic drug resistance in Mycobacterium tuberculosis: leveraging 20 years of nationwide data from Denmark

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Standard

Applying whole genome sequencing to predict phenotypic drug resistance in Mycobacterium tuberculosis : leveraging 20 years of nationwide data from Denmark. / Kurtzhals, Mads Lindholm; Norman, Anders; Svensson, Erik; Lillebaek, Troels; Folkvardsen, Dorte Bek.

I: Antimicrobial Agents and Chemotherapy, 2024.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Kurtzhals, ML, Norman, A, Svensson, E, Lillebaek, T & Folkvardsen, DB 2024, 'Applying whole genome sequencing to predict phenotypic drug resistance in Mycobacterium tuberculosis: leveraging 20 years of nationwide data from Denmark', Antimicrobial Agents and Chemotherapy. https://doi.org/10.1128/aac.00430-24

APA

Kurtzhals, M. L., Norman, A., Svensson, E., Lillebaek, T., & Folkvardsen, D. B. (2024). Applying whole genome sequencing to predict phenotypic drug resistance in Mycobacterium tuberculosis: leveraging 20 years of nationwide data from Denmark. Antimicrobial Agents and Chemotherapy, [e0043024]. https://doi.org/10.1128/aac.00430-24

Vancouver

Kurtzhals ML, Norman A, Svensson E, Lillebaek T, Folkvardsen DB. Applying whole genome sequencing to predict phenotypic drug resistance in Mycobacterium tuberculosis: leveraging 20 years of nationwide data from Denmark. Antimicrobial Agents and Chemotherapy. 2024. e0043024. https://doi.org/10.1128/aac.00430-24

Author

Kurtzhals, Mads Lindholm ; Norman, Anders ; Svensson, Erik ; Lillebaek, Troels ; Folkvardsen, Dorte Bek. / Applying whole genome sequencing to predict phenotypic drug resistance in Mycobacterium tuberculosis : leveraging 20 years of nationwide data from Denmark. I: Antimicrobial Agents and Chemotherapy. 2024.

Bibtex

@article{7706ff8562d640598fc3a5411fec6069,
title = "Applying whole genome sequencing to predict phenotypic drug resistance in Mycobacterium tuberculosis: leveraging 20 years of nationwide data from Denmark",
abstract = "Infection with Mycobacterium tuberculosis remains one of the biggest causes of death from a single microorganism worldwide, and the continuous emergence of drug resistance aggravates our ability to cure the disease. New improved resistance detection methods are needed to provide adequate treatment, such as whole genome sequencing (WGS), which has been used increasingly to identify resistance-conferring mutations over the last decade. The steadily increasing knowledge of resistance-conferring mutations increases our ability to predict resistance based on genomic data alone. This study evaluates the performance of WGS to predict M. tuberculosis complex resistance. It compares WGS predictions with the phenotypic (culture-based) drug susceptibility results based on 20 years of nationwide Danish data. Analyzing 6,230 WGS-sequenced samples, the sensitivities for isoniazid, rifampicin, ethambutol, and pyrazinamide were 82.5% [78.0%-86.5%, 95% confidence interval (CI)], 97.3% (90.6%-99.7%, 95% CI), 58.0% (43.2%-71.8%, 95% CI), and 60.5% (49.0%-71.2%, 95% CI), respectively, and specificities were 99.8% (99.7%-99.9%, 95% CI), 99.8% (99.7%-99.9%, 95% CI), 99.4% (99.2%-99.6%, 95% CI), and 99.9% (99.7%-99.9%, 95% CI), respectively. A broader range of both sensitivities and specificities was observed for second-line drugs. The results conform with previously reported values and indicate that WGS is reliable for routine resistance detection in resource-rich tuberculosis low-incidence and low-resistance settings such as Denmark.",
author = "Kurtzhals, {Mads Lindholm} and Anders Norman and Erik Svensson and Troels Lillebaek and Folkvardsen, {Dorte Bek}",
year = "2024",
doi = "10.1128/aac.00430-24",
language = "English",
journal = "Antimicrobial Agents and Chemotherapy",
issn = "0066-4804",
publisher = "American Society for Microbiology",

}

RIS

TY - JOUR

T1 - Applying whole genome sequencing to predict phenotypic drug resistance in Mycobacterium tuberculosis

T2 - leveraging 20 years of nationwide data from Denmark

AU - Kurtzhals, Mads Lindholm

AU - Norman, Anders

AU - Svensson, Erik

AU - Lillebaek, Troels

AU - Folkvardsen, Dorte Bek

PY - 2024

Y1 - 2024

N2 - Infection with Mycobacterium tuberculosis remains one of the biggest causes of death from a single microorganism worldwide, and the continuous emergence of drug resistance aggravates our ability to cure the disease. New improved resistance detection methods are needed to provide adequate treatment, such as whole genome sequencing (WGS), which has been used increasingly to identify resistance-conferring mutations over the last decade. The steadily increasing knowledge of resistance-conferring mutations increases our ability to predict resistance based on genomic data alone. This study evaluates the performance of WGS to predict M. tuberculosis complex resistance. It compares WGS predictions with the phenotypic (culture-based) drug susceptibility results based on 20 years of nationwide Danish data. Analyzing 6,230 WGS-sequenced samples, the sensitivities for isoniazid, rifampicin, ethambutol, and pyrazinamide were 82.5% [78.0%-86.5%, 95% confidence interval (CI)], 97.3% (90.6%-99.7%, 95% CI), 58.0% (43.2%-71.8%, 95% CI), and 60.5% (49.0%-71.2%, 95% CI), respectively, and specificities were 99.8% (99.7%-99.9%, 95% CI), 99.8% (99.7%-99.9%, 95% CI), 99.4% (99.2%-99.6%, 95% CI), and 99.9% (99.7%-99.9%, 95% CI), respectively. A broader range of both sensitivities and specificities was observed for second-line drugs. The results conform with previously reported values and indicate that WGS is reliable for routine resistance detection in resource-rich tuberculosis low-incidence and low-resistance settings such as Denmark.

AB - Infection with Mycobacterium tuberculosis remains one of the biggest causes of death from a single microorganism worldwide, and the continuous emergence of drug resistance aggravates our ability to cure the disease. New improved resistance detection methods are needed to provide adequate treatment, such as whole genome sequencing (WGS), which has been used increasingly to identify resistance-conferring mutations over the last decade. The steadily increasing knowledge of resistance-conferring mutations increases our ability to predict resistance based on genomic data alone. This study evaluates the performance of WGS to predict M. tuberculosis complex resistance. It compares WGS predictions with the phenotypic (culture-based) drug susceptibility results based on 20 years of nationwide Danish data. Analyzing 6,230 WGS-sequenced samples, the sensitivities for isoniazid, rifampicin, ethambutol, and pyrazinamide were 82.5% [78.0%-86.5%, 95% confidence interval (CI)], 97.3% (90.6%-99.7%, 95% CI), 58.0% (43.2%-71.8%, 95% CI), and 60.5% (49.0%-71.2%, 95% CI), respectively, and specificities were 99.8% (99.7%-99.9%, 95% CI), 99.8% (99.7%-99.9%, 95% CI), 99.4% (99.2%-99.6%, 95% CI), and 99.9% (99.7%-99.9%, 95% CI), respectively. A broader range of both sensitivities and specificities was observed for second-line drugs. The results conform with previously reported values and indicate that WGS is reliable for routine resistance detection in resource-rich tuberculosis low-incidence and low-resistance settings such as Denmark.

U2 - 10.1128/aac.00430-24

DO - 10.1128/aac.00430-24

M3 - Journal article

C2 - 38904390

JO - Antimicrobial Agents and Chemotherapy

JF - Antimicrobial Agents and Chemotherapy

SN - 0066-4804

M1 - e0043024

ER -

ID: 396924665