Introduction: Tuberculosis (TB) is a major cause of morbidity and mortality worldwide. The immune response during TB is complex and incompletely characterized, hindering the development of new diagnostics, treatments and vaccines. Studies performed in different disease settings (intermediate versus high burden) have sometimes yielded divergent results, limiting advances in our understanding of TB. We used microarray based approaches to obtain an unbiased comprehensive survey of the host response to TB in both the UK and South Africa. Methods: Whole blood was collected before treatment. RNA was extracted and used for whole genome expression studies using Illumina HT-12 microarrays. This was complemented by multiplexed cytokine analysis using the MILLIPLEX™ Multi-Analyte Profiling system. Biological data was integrated with comprehensive clinical data including radiology. Data mining was performed using Genespring GX 7.3 and Ingenuity® Pathways Analysis software in combination with a novel Genomic Modular Analysis Framework. A subset of patients was assessed at 2 and 12 months post treatment. Results: We identified a robust blood transcriptional signature for Active TB in both intermediate and high burden settings, independent of ethnicity, age and gender. Transcriptional profiles appeared to reflect radiographic extent of disease. Longitudinal analysis revealed that the signature of Active TB disappears during successful treatment. Analysis of blood leucocyte counts and serum cytokines, along with interrogation of gene expression data using pathway and Modular analysis suggests that this signature reflects changes in cellular composition and altered cytokine gene expression, with a key part of the signature being composed of interferon-inducible transcripts. This included several transcripts from the tripartite motif (TRIM) protein family, which have not previously been implicated in TB pathogenesis. Conclusions: This is the first whole genome expression profiling study in human TB. Our findings have implications for understanding disease pathogenesis, and could yield biomarkers for diagnosis and treatment monitoring.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:625276 |
| Date | January 2010 |
| Creators | Berry, M. P. R. |
| Publisher | University College London (University of London) |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://discovery.ucl.ac.uk/19192/ |
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