| Autor: |
Helmut J. F. Salzer, Barbara Kalsdorf, Sebastian Marwitz, Victor Spinu, Frank van Leth, Michael Hoelscher, Elmira Ibraim, Andrea Rachow, Maren Schuhmann, Marius Müller, Jan Heyckendorf, Dörte Nitschkowski, Korkut Avsar, Irina Kontsevaya, Isabelle Suárez, Stefan H. E. Kaufmann, Christoph Lange, Andrew R. DiNardo, Patricia Sanchez-Carballo, Elena Terhalle, Ioana D. Olaru, Jan Rybniker, Cristina Popa, Gunar Günther, Florian P. Maurer, Dagmar Schaub, January Weiner, Thierry Rolling, Markus Unnewehr, Anna M. Mandalakas, Torsten Goldmann, Maja Reimann |
| Rok vydání: |
2020 |
| Předmět: |
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| DOI: |
10.1101/2020.08.21.20177238 |
| Popis: |
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%, pOne Sentence SummaryWe identified and validated a transcriptome model based on a 22-gene signature to predict individual treatment durations for patients with multidrug-resistant tuberculosis. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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