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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
medicine
Gene-expression patterns in whole blood identify subjects at risk for recurrent tuberculosis
Journal of Infectious Diseases, Volume 195, No. 3, Year 2007
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Description
Background. The majority of patients with tuberculosis who comply with appropriate treatment are cured. However, ∼5% subsequently have a repeat disease episode, usually within 2 years of successful combination therapy. Presently, there is no way of predicting which patients will experience a relapse. Methods. We identified 10 subjects who had previously experienced recurrent tuberculosis and carefully matched them to cured subjects who had had only 1 episode of tuberculosis, to patients with active tuberculosis, and to latently infected healthy subjects. We compared their ex vivo whole-blood gene-expression profiles by use of DNA array technology and confirmed the results by use of quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR). Results. The 4 clinical tuberculosis groups exhibited distinct patterns of gene expression. The gene-transcript profiles of the patients with recurrent tuberculosis were more similar to those of the patients with active tuberculosis than to those of the cured or latently infected subjects. Discriminant analysis of a training data set showed that 9 genes were sufficient to classify the subjects. We confirmed that measurement of the expression of these genes by qRT-PCR can accurately discriminate between subjects in a test set of samples. Conclusions. A simple test based on gene-expression patterns may be used as a biomarker of cure while identifying patients who are at risk for relapse. This would facilitate the introduction of new tuberculosis drugs. © 2006 by the Infectious Diseases Society of America. All rights reserved.
Authors & Co-Authors
Mistry, Rohit
Unknown Affiliation
Cliff, Jacqueline Margaret
Unknown Affiliation
Clayfon, Christopher L.
Unknown Affiliation
Beyers, Nulda
Unknown Affiliation
Mohamed, Yasmin S.
Unknown Affiliation
Wilson, Paul A.
Unknown Affiliation
Dockrell, Hazel M.
Unknown Affiliation
Wallace, Don M.
Unknown Affiliation
Van Helden, Paul D.
Unknown Affiliation
Duncan, Ken
Unknown Affiliation
Lukey, Pauline T.
Unknown Affiliation
Statistics
Citations: 158
Authors: 11
Affiliations: 5
Identifiers
Doi:
10.1086/510397
ISSN:
00221899
Research Areas
Genetics And Genomics
Study Approach
Quantitative