Transcriptional profiles predict treatment outcome in patients with tuberculosis and diabetes at diagnosis and at two weeks after initiation of anti-tuberculosis treatment.

ABSTRACT

BACKGROUND: Globally, the tuberculosis (TB) treatment success rate is approximately 85%, with treatment failure, relapse and death occurring in a significant proportion of pulmonary TB patients. Treatment success is lower among people with diabetes mellitus (DM). Predicting treatment outcome early after diagnosis, especially in TB-DM patients, would allow early treatment adaptation for individuals and may improve global TB control. METHODS: Samples were collected in a longitudinal cohort study of adult TB patients from South Africa (n  =  94) and Indonesia (n  =  81), who had concomitant DM (n  =  59), intermediate hyperglycaemia (n  =  79) or normal glycaemia/no DM (n  =  37). Treatment outcome was monitored, and patients were categorized as having a good (cured) or poor (failed, recurrence, died) outcome during treatment and 12 months follow-up. Whole blood transcriptional profiles before, during and at the end of TB treatment were characterized using unbiased RNA-Seq and targeted gene dcRT-MLPA. FINDINGS: We report differences in whole blood transcriptome profiles, which were observed before initiation of treatment and throughout treatment, between patients with a good versus poor TB treatment outcome. An eight-gene and a 22-gene blood transcriptional signature distinguished patients with a good TB treatment outcome from patients with a poor TB treatment outcome at diagnosis (AUC = 0·815) or two weeks (AUC = 0·834) after initiation of TB treatment, respectively. High accuracy was obtained by cross-validating this signature in an external cohort (AUC = 0·749). INTERPRETATION: These findings suggest that transcriptional profiles can be used as a prognostic biomarker for treatment failure and success, even in patients with concomitant DM. FUNDING: The research leading to these results, as part of the TANDEM Consortium, received funding from the European Community's Seventh Framework Programme (FP7/2007-2013 Grant Agreement No. 305279) and the Netherlands Organization for Scientific Research (NWO-TOP Grant Agreement No. 91214038). The research leading to the results presented in the Indian validation cohort was supported by Research Council of Norway Global Health and Vaccination Research (GLOBVAC) projects RCN 179342, 192534, and 248042, the University of Bergen (Norway).