Abstract
Current diagnostic tests for tuberculosis (TB) are not able to predict reactivation disease progression from latent TB infection (LTBI). The main barrier to predicting reactivation disease is the lack of our understanding of host biomarkers associated with progression from latent infection to active disease. Here, we applied an immune-based gene expression profile by NanoString platform to identify whole blood markers that can distinguish active TB from other lung diseases (OPD), and that could be further evaluated as a reactivation TB predictor. Among 23 candidate genes that differentiated patients with active TB from those with OPD, nine genes (CD274, CEACAM1, CR1, FCGR1A/B, IFITM1, IRAK3, LILRA6, MAPK14, PDCD1LG2) demonstrated sensitivity and specificity of 100%. Seven genes (C1QB, C2, CCR2, CCRL2, LILRB4, MAPK14, MSR1) distinguished TB from LTBI with sensitivity and specificity between 82 and 100%. This study identified single gene candidates that distinguished TB from OPD and LTBI with high sensitivity and specificity (both > 82%), which may be further evaluated as diagnostic for disease and as predictive markers for reactivation TB.
Highlights
Tuberculosis (TB), an aerosol-borne disease caused by Mycobacterium tuberculosis (Mtb), is one of the top 10 causes of death worldwide and the leading cause of death from a single infectious agent[1]
We report the results of an immune-based gene expression profile study based on the NanoString technology in patients with active TB and other pulmonary diseases (OPD), healthy donors with latent TB infection (LTBI), and uninfected health controls (HC)
We evaluated 594 inflammatory genes in whole blood from TB patients and controls
Summary
Tuberculosis (TB), an aerosol-borne disease caused by Mycobacterium tuberculosis (Mtb), is one of the top 10 causes of death worldwide and the leading cause of death from a single infectious agent[1]. The GeneXpert MTB/RIF requires sophisticated technology and a well-trained staff, and not affordable or sustainable in most healthcare systems[7]. None of these sputum-based tests can predict reactivation TB. TB diagnosis has extensively been researched[10] and many of them have focused on distinguishing latent infection from active TB11–13 None of these gene signatures has so far been translated into a point of care (POC) diagnostic test. We report the results of an immune-based gene expression profile study based on the NanoString technology in patients with active TB and other pulmonary diseases (OPD), healthy donors with latent TB infection (LTBI), and uninfected health controls (HC). We identified 23 and seven genes associated with inflammatory mechanisms that distinguished with high sensitivity and specificity, patients with TB from OPD and LTBI, respectively
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
