Researchers at the Stanford University School of Medicine have identified a gene expression “signature” that distinguishes patients with active tuberculosis from those with either latent tuberculosis or other diseases. The finding fills a need identified by the World Health Organisation, which in 2014 challenged researchers to develop better diagnostic tests for active TB.
WHO estimates that 9.6m people got sick with TB in 2014 and that 1.5m people died of the disease that year. Yet it remains difficult to diagnose. “One-third of the world’s population is currently infected with TB. Even if only 10% of them get active TB, that’s still 3% of the world’s population – 240m people,” said Dr Purvesh Khatri, assistant professor of medicine and senior author of the paper.
Traditional diagnostic methods, such as the skin prick test and interferon assays, can’t separate patients with active TB from those who are no longer sick or have merely been vaccinated against TB (and most countries vaccinate everyone against TB). These older diagnostics can miss a case of TB in patients with HIV.
A common way to test for TB is to look for the disease-causing bacterium in sputum samples coughed up by patients. But sometimes it’s hard for people to produce sputum on demand, said research associate Dr Tim Sweeney, first author of the paper. “If someone can’t produce adequate sputum, or if you have a kid who can’t follow directions,” it’s hard to diagnose them, he said. And the sputum test is almost useless for monitoring how someone is responding to treatment. As people start to get better, they can’t produce sputum for the test.
The new test developed in the Khatri lab works on an ordinary blood sample and removes the need to collect sputum. It can signal a TB infection even if the individual also has HIV. And it won’t give a positive response if someone only has latent TB or has had a TB vaccine. It also doesn’t matter which strain of TB has infected a person, or even if it has evolved resistance to antibiotic drugs. The test works in both adults and children.
WHO has called for a test that would give a positive result at least 66% of the time when a child has active TB. The Khatri test is 86% sensitive in children. And if the test comes up negative, it’s right 99% of the time. That is, of 100 patients who test negative with the Khatri test, 99 do not have active TB.
The requirements of the test are simple enough that it can potentially be done under relatively basic field conditions in rural and undeveloped areas of the world. Any hospital should be able to perform the test. Villages without electricity could likely use ordinary blood samples and a solar-powered PCR machine, which multiplies strands of DNA, to accurately test people for active TB.
When pathogens infect the cells of the body, the infection sets off a chain reaction that changes the expression of hundreds of human genes. Khatri’s team identified three human genes whose expression changes in a consistent pattern, revealing the presence of an active tuberculosis infection.
The team validated the new three-gene test in a separate set of 1,400 human samples from 11 different data sets, confirming the diagnostic power of the test.
The new test not only accurately distinguishes patients who have active tuberculosis, it could also be used to monitor patients to see if they are getting better and how well they are responding to different treatments. Thus, it can be used not only for diagnosis and to inform treatment, but also to study the effectiveness of different treatments. The test’s hugely accurate negative response would be especially helpful in monitoring the effectiveness of treatments during clinical trials, said Khatri.
He has already begun collecting funding to develop the test for widespread use, both to diagnose TB in patients and to monitor recovery in clinical trials, allowing for more rapid development of better and cheaper treatments.
Active pulmonary tuberculosis is difficult to diagnose and treatment response is difficult to effectively monitor. A WHO consensus statement has called for new non-sputum diagnostics. The aim of this study was to use an integrated multicohort analysis of samples from publically available datasets to derive a diagnostic gene set in the peripheral blood of patients with active tuberculosis.
We searched two public gene expression microarray repositories and retained datasets that examined clinical cohorts of active pulmonary tuberculosis infection in whole blood. We compared gene expression in patients with either latent tuberculosis or other diseases versus patients with active tuberculosis using our validated multicohort analysis framework. Three datasets were used as discovery datasets and meta-analytical methods were used to assess gene effects in these cohorts. We then validated the diagnostic capacity of the three gene set in the remaining 11 datasets.
A total of 14 datasets containing 2572 samples from 10 countries from both adult and paediatric patients were included in the analysis. Of these, three datasets (N=1023) were used to discover a set of three genes (GBP5, DUSP3, and KLF2) that are highly diagnostic for active tuberculosis. We validated the diagnostic power of the three gene set to separate active tuberculosis from healthy controls (global area under the ROC curve (AUC) 0•90 [95% CI 0•85–0•95]), latent tuberculosis (0•88 [0•84–0•92]), and other diseases (0•84 [0•80–0•95]) in eight independent datasets composed of both children and adults from ten countries. Expression of the three-gene set was not confounded by HIV infection status, bacterial drug resistance, or BCG vaccination. Furthermore, in four additional cohorts, we showed that the tuberculosis score declined during treatment of patients with active tuberculosis.
Overall, our integrated multicohort analysis yielded a three-gene set in whole blood that is robustly diagnostic for active tuberculosis, that was validated in multiple independent cohorts, and that has potential clinical application for diagnosis and monitoring treatment response. Prospective laboratory validation will be required before it can be used in a clinical setting.