Frank van Leth - A 22-gene transcriptomic model indicating individual

Journal article

J. Heyckendorf, S. Marwitz, M. Reimann, K. Avsar, A. DiNardo, G. Günther, M. Hoelscher, E. Ibraim, B. Kalsdorf, S. Kaufmann, I. Kontsevaya, F. V. Leth, A. Mandalakas, F. Maurer, Marius Müller, Dörte Nitschkowski, I. Olaru, C. Popa, A. Rachow, T. Rolling, J. Rybniker, H. Salzer, Patricia M Sánchez-Carballo, M. Schuhmann, D. Schaub, V. Spînu, I. Suárez, E. Terhalle, M. Unnewehr, J. Weiner, T. Goldmann, C. Lange
medRxiv, 2020

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APA Click to copy
Heyckendorf, J., Marwitz, S., Reimann, M., Avsar, K., DiNardo, A., Günther, G., … Lange, C. (2020). A 22-gene transcriptomic model indicating individual therapy durations in multidrug-resistant tuberculosis. MedRxiv.

Chicago/Turabian Click to copy
Heyckendorf, J., S. Marwitz, M. Reimann, K. Avsar, A. DiNardo, G. Günther, M. Hoelscher, et al. “A 22-Gene Transcriptomic Model Indicating Individual Therapy Durations in Multidrug-Resistant Tuberculosis.” medRxiv (2020).

MLA Click to copy
Heyckendorf, J., et al. “A 22-Gene Transcriptomic Model Indicating Individual Therapy Durations in Multidrug-Resistant Tuberculosis.” MedRxiv, 2020.

BibTeX Click to copy

@article{j2020a,
  title = {A 22-gene transcriptomic model indicating individual therapy durations in multidrug-resistant tuberculosis},
  year = {2020},
  journal = {medRxiv},
  author = {Heyckendorf, J. and Marwitz, S. and Reimann, M. and Avsar, K. and DiNardo, A. and Günther, G. and Hoelscher, M. and Ibraim, E. and Kalsdorf, B. and Kaufmann, S. and Kontsevaya, I. and Leth, F. V. and Mandalakas, A. and Maurer, F. and Müller, Marius and Nitschkowski, Dörte and Olaru, I. and Popa, C. and Rachow, A. and Rolling, T. and Rybniker, J. and Salzer, H. and Sánchez-Carballo, Patricia M and Schuhmann, M. and Schaub, D. and Spînu, V. and Suárez, I. and Terhalle, E. and Unnewehr, M. and Weiner, J. and Goldmann, T. and Lange, C.}
}

Abstract

Emerging multidrug-resistant tuberculosis is a major global health challenge. The World Health Organization currently recommends treatment durations of 9-18 months or more for patients with multidrug-resistant tuberculosis. We identified and validated a host-RNA signature to serve as a biomarker for individualized therapy durations for patients with multidrug-resistant tuberculosis. Adult patients with pulmonary tuberculosis were prospectively enrolled into 5 independent cohorts in Germany and Romania. Clinical and microbiological data, and whole-blood for RNA transcriptomic analysis were collected at pre-defined timepoints throughout therapy. Treatment outcomes were ascertained one year after end-of-therapy. A whole-blood RNA therapy end model was developed in a multi-step process involving a machine-learning algorithm to identify hypothetical individual end-of-treatment timepoints. Fifty patients with drug-susceptible tuberculosis and 30 patients with multidrug-resistant tuberculosis were recruited in the German identification cohorts (DS- and MDR-GIC), 28 patients with drug-susceptible tuberculosis and 32 patients with multidrug-resistant tuberculosis in the German validation cohorts (DS- and MDR-GVC), and 52 patients with multidrug-resistant tuberculosis in the Romanian validation cohort (MDR-RVC). A 22-gene RNA model that defined cure-associated end-of-therapy timepoints was derived from the DS- and MDR-GIC data. The model accurately predicted clinical outcomes for patients in the DS-GVC (AUC=0.937 [95%CI:0.899-0.976]) and suggested that cure may be achieved with shorter treatment durations for tuberculosis patients in the MDR-GIC (mean reduction 218.0 days, 34.2%, p<0.001), the MDR-GVC (mean reduction 211.0 days, 32.9%, p<0.001), and the MDR-RVC (mean reduction of 161.0 days, 23.4%, p=0.001). Biomarker-guided management may substantially shorten the duration of therapy for many patients with multidrug-resistant tuberculosis.