Abstract
Whole blood transcriptional signatures distinguishing patients with active tuberculosis from asymptomatic latently infected individuals have been described but, no consensus exists for the composition of optimal reduced gene sets as diagnostic biomarkers that also achieve discrimination from other diseases. We have recapitulated a blood transcriptional signature of active tuberculosis using RNA-Seq, previously reported by microarray that discriminates active tuberculosis from latently infected and healthy individuals, also validated in an independent cohort. We show that an advanced modular approach, which preserves and presents a signature of the entire transcriptome, can better discriminate patients with active tuberculosis from both latently infected and acute viral and bacterial infections. We suggest a method of targeted gene selection across modules for constructing diagnostic biomarkers, more representative of the transcriptome that overcomes some limitations of existing techniques. Finally, we utilise the modular approach to demonstrate dynamic heterogeneity in a longitudinal study of recent tuberculosis contacts.