A modular transcriptional signature identifies phenotypic heterogeneity of human tuberculosis infection

• DOI: 10.1038/s41467-018-04579-w
• Publication Date: 2018-06-07T09:17:00Z
• Authors: Akul Singhania; Raman Verma; Christine M. Graham; Jo Lee; Trang Tran; Matthew Richardson; Patrick Lecine; Philippe Leissner; Matthew P. R. Berry; Robert J. Wilkinson; Karine Kaiser; Marc Rodrigue; Gerrit Woltmann; Pranabashis Haldar; Anne O’Garra
• Keywords: Gene signature; Signature (topology)

Whole blood transcriptional signatures distinguishing active tuberculosis patients from asymptomatic latently infected individuals exist. Consensus has not been achieved regarding the optimal reduced gene sets as diagnostic biomarkers that also achieve discrimination other diseases. Here we show a signature of using RNA-Seq, confirming microarray results, discriminates and healthy individuals, validating this in an independent cohort. Using advanced modular approach, utilise information entire transcriptome, which includes overabundance type I interferon-inducible genes underabundance IFNG TBX21, to develop or those with acute viral bacterial infections. We suggest methods targeting selection across multiple discriminant modules can improve development improved performance. Finally, utilising demonstrate dynamic heterogeneity longitudinal study recent contacts.