Abstract
BackgroundTuberculosis (TB) continues to cause a high toll of disease and death among children worldwide. The diagnosis of childhood TB is challenged by the paucibacillary nature of the disease and the difficulties in obtaining specimens. Whereas scientific and clinical research efforts to develop novel diagnostic tools have focused on TB in adults, childhood TB has been relatively neglected. Blood transcriptional profiling has improved our understanding of disease pathogenesis of adult TB and may offer future leads for diagnosis and treatment. No studies applying gene expression profiling of children with TB have been published so far.ResultsWe identified a 116-gene signature set that showed an average prediction error of 11% for TB vs. latent TB infection (LTBI) and for TB vs. LTBI vs. healthy controls (HC) in our dataset. A minimal gene set of only 9 genes showed the same prediction error of 11% for TB vs. LTBI in our dataset. Furthermore, this minimal set showed a significant discriminatory value for TB vs. LTBI for all previously published adult studies using whole blood gene expression, with average prediction errors between 17% and 23%. In order to identify a robust representative gene set that would perform well in populations of different genetic backgrounds, we selected ten genes that were highly discriminative between TB, LTBI and HC in all literature datasets as well as in our dataset. Functional annotation of these genes highlights a possible role for genes involved in calcium signaling and calcium metabolism as biomarkers for active TB. These ten genes were validated by quantitative real-time polymerase chain reaction in an additional cohort of 54 Warao Amerindian children with LTBI, HC and non-TB pneumonia. Decision tree analysis indicated that five of the ten genes were sufficient to classify 78% of the TB cases correctly with no LTBI subjects wrongly classified as TB (100% specificity).ConclusionsOur data justify the further exploration of our signature set as biomarkers for potential childhood TB diagnosis. We show that, as the identification of different biomarkers in ethnically distinct cohorts is apparent, it is important to cross-validate newly identified markers in all available cohorts.
Highlights
Tuberculosis (TB) continues to cause a high toll of disease and death among children worldwide
We identified new gene signatures in childhood TB by comparing gene expression profiles of Warao Amerindian children with TB, latent TB infection (LTBI) and healthy controls (HC)
Identification of signature genes Genome-wide transcription profiles in whole blood from 9 TB patients, 9 LTBI and 9 HC were generated using Affymetrix exon arrays comprising approximately one million probes, which are mapped to 22011 unique features (Affymetrix core gene set)
Summary
Tuberculosis (TB) continues to cause a high toll of disease and death among children worldwide. Blood transcriptional profiling has improved our understanding of disease pathogenesis of adult TB and may offer future leads for diagnosis and treatment. No studies applying gene expression profiling of children with TB have been published so far. Correlation analysis, a method selecting genes that are correlated with a single differentially expressed gene, was used to identify a biomarker set in a Gambian cohort [5]. No studies applying gene expression profiling of children with TB have been published, and it is unknown whether the existing signature gene sets are applicable to childhood cohorts. We identified new gene signatures in childhood TB by comparing gene expression profiles of Warao Amerindian children with TB, LTBI and HC. We validated the identified gene signatures from this study in an independent cohort of children with LTBI, HC or non-TB pneumonia. We estimated the predictive value of our gene signatures in previously performed adult studies and we compared the discriminatory power of the literature signature gene sets with our gene set
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