2016
A blood RNA signature for tuberculosis disease risk: a prospective cohort study
Abstract: Background Identification of blood biomarkers that prospectively predict progression of Mycobacterium tuberculosis infection to tuberculosis disease may lead to interventions that impact the epidemic. Methods Healthy, M. tuberculosis infected South African adolescents were followed for 2 years; blood was collected every 6 months. A prospective signature of risk was derived from whole blood RNA-Sequencing data by comparing participants who ultimately developed active tuberculosis disease (progressors) with th…
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Cited by 799 publications
(994 citation statements)
References 43 publications
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“…Of interest, IFNγ-induced M1 genes were particularly highly overlapping with Mtb-induced genes with 71 out of 92 (75%), see parenthesis in Table 1 . The overlapping genes included Nos2 , Tnf , Cxcl9 , Cxcl10 , Irg1 , among others, consistent with our previous reports (and others) that Mtb infection does induce interferon-related inflammatory responses in macrophages 26 , 38 , 39 . Taken together, Mtb infection largely affects macrophage gene expression including inflammatory response genes.…”
Section: Resultssupporting
confidence: 91%
“…Of interest, IFNγ-induced M1 genes were particularly highly overlapping with Mtb-induced genes with 71 out of 92 (75%), see parenthesis in Table 1 . The overlapping genes included Nos2 , Tnf , Cxcl9 , Cxcl10 , Irg1 , among others, consistent with our previous reports (and others) that Mtb infection does induce interferon-related inflammatory responses in macrophages 26 , 38 , 39 . Taken together, Mtb infection largely affects macrophage gene expression including inflammatory response genes.…”
Section: Resultssupporting
confidence: 91%
“…Our 20-gene signature also showed discrimination of TB from other diseases, similarly to the 44-gene signature of Kaforou et al 24 . However, our 20-gene signature did not detect influenza from healthy controls, in contrast to all the other reported TB signatures 24 , 27 , 32 , 43 , 44 , which not only detected TB at high specificity and sensitivity against LTBI, but additionally showed a high specificity and sensitivity for influenza versus the controls. Therefore, the development of our 20-gene signature provides a novel approach to discriminate TB from LTBI, whilst not detecting viral infections, here exemplified by influenza, offering scope for further refinement in further translational clinical studies.…”
Section: Discussioncontrasting
confidence: 95%
“…Through the use of RM, we have employed a controlled system with defined dates of infection and in the absence of treatment. While our results did not identify a direct overlap in the genes identified by Berry et al (66), or Zak et al (67), there was overlap between these data sets at the level of pathways and function. All datasets have extensive contribution from the Type I Interferon pathway and antiviral immune response, including interferon induced genes (IFITM1, IFITM3, IFIT3, IFI44, IFIH1, IFIT3, IFI16, IFI35, IFIT2, GBP1, and GBP2 in (66) and MX1, IFRG28, G1P2, SIGLEC1 in our study.…”
Section: Discussioncontrasting
confidence: 94%
