Imperial College London
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ProfessorAnneO'Garra

Faculty of Medicine, National Heart & Lung Institute

Chair in Infection Immunology
 
 
 
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Contact

 

a.ogarra

 
 
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Location

 

Norfolk PlaceSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Singhania:2018:10.1038/s41467-018-04579-w,
author = {Singhania, A and Verma, R and Graham, CM and Lee, J and Tran, T and Richardson, M and Lecine, P and Leissner, P and Berry, MPR and Wilkinson, RJ and Kaiser, K and Rodrigue, M and Woltmann, G and Haldar, P and O'Garra, A},
doi = {10.1038/s41467-018-04579-w},
journal = {Nature Communications},
title = {A modular transcriptional signature identifies phenotypic heterogeneity of human tuberculosis infection},
url = {http://dx.doi.org/10.1038/s41467-018-04579-w},
volume = {9},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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 from other diseases. Here we show a blood transcriptional signature of active tuberculosis using RNA-Seq, confirming microarray results, that discriminates active tuberculosis from latently infected and healthy individuals, validating this signature in an independent cohort. Using an advanced modular approach, we utilise the information from the entire transcriptome, which includes overabundance of type I interferon-inducible genes and underabundance of IFNG and TBX21, to develop a signature that discriminates active tuberculosis patients from latently infected individuals or those with acute viral and bacterial infections. We suggest that methods targeting gene selection across multiple discriminant modules can improve the development of diagnostic biomarkers with improved performance. Finally, utilising the modular approach, we demonstrate dynamic heterogeneity in a longitudinal study of recent tuberculosis contacts.
AU  - Singhania,A
AU  - Verma,R
AU  - Graham,CM
AU  - Lee,J
AU  - Tran,T
AU  - Richardson,M
AU  - Lecine,P
AU  - Leissner,P
AU  - Berry,MPR
AU  - Wilkinson,RJ
AU  - Kaiser,K
AU  - Rodrigue,M
AU  - Woltmann,G
AU  - Haldar,P
AU  - O'Garra,A
DO  - 10.1038/s41467-018-04579-w
PY  - 2018///
SN  - 2041-1723
TI  - A modular transcriptional signature identifies phenotypic heterogeneity of human tuberculosis infection
T2  - Nature Communications
UR  - http://dx.doi.org/10.1038/s41467-018-04579-w
UR  - https://www.ncbi.nlm.nih.gov/pubmed/29921861
UR  - http://hdl.handle.net/10044/1/60326
VL  - 9
ER  -
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