Host transcription in active and latent tuberculosis

Our understanding of tuberculosis (TB) is heavily colored by the available diagnostic tools. Active TB is identifiable first because of the presence of clinical symptoms, such as chronic cough, fever and weight loss. Active TB may be confirmed by the identification of the causative bacteria, Mycobacterium tuberculosis (Mtb), but in many cases bacteria are undetectable. Latent TB is defined by the presence of a T-cell-mediated immune response to Mtb in an asymptomatic individual. This immunological response to Mtb is widely believed to indicate the presence of viable organisms that might cause active disease in the future, although how many people with a detectable immune response actually harbor Mtb is unknown. The tests used to identify active and latent Mtb infection are among the oldest in modern medicine, dating back to the late 19th century. Thus, much of our understanding of human TB has been frozen for more than a century.Can a systematic, molecular approach to understanding the host response to Mtb provide new insights into the course of human disease? A recent study by Anne O'Garra and her colleagues suggests that it can [1]. To characterize host responses to Mtb in an unbiased manner they chose to use whole-genome transcriptional profiling. They collected blood from HIV-negative patients from the UK with well-demonstrated active TB, those with positive tests for latent TB but no evidence of active disease and healthy controls. The investigators prepared RNA from these blood samples and hybridized it to microarrays containing more than 48,000 probes for human sequences. Focusing on a training set of samples, they used statistical tests and clustering to identify a set of 393 genes whose expression is significantly different between patients with active disease and those with latent or no disease.They then looked at the independent test and validation groups from the UK and South Africa, respectively, and found that the expression levels of these genes could