TB Diagnosis May Be Improved With New Three-Gene Panel

A three-gene set can robustly diagnose active tuberculosis (TB) from whole blood samples, according to a study published in the March issue of The Lancet Respiratory Medicine. The authors say that the three-gene set represents an improvement over current diagnostics because it is based on peripheral blood rather than sputum samples, it performed well in the diagnosis of latent tuberculosis versus culture-positive active tuberculosis in children, and HIV status did not change its diagnostic power.

“The multiple gene expression diagnostics that have been derived all suggest that host-response gene expression assays are likely to eventually play an important role in TB diagnostics,” writes lead author Timothy Sweeney, M.D., from Stanford University.

TB remains a large, worldwide public health issue with nearly 10 million new infections per year. Yet, active pulmonary disease remains difficult to diagnose and treatment response is difficult to monitor. Traditional methods such as skin testing and interferon γ release assays are unable to distinguish between latent and active disease. Even newer technology has challenges (sputum-based, reduced accuracy in HIV-positive patients, and not applicable for treatment response monitoring). The World Health Organization (WHO) has called for new non-sputum diagnostics to meet the targets for TB prevention, care, and control.

The present study used samples of active pulmonary tuberculosis infection in whole blood from two public gene expression microarray repositories to derive a diagnostic gene set. Gene expression was assessed in heterogeneous patients from a wide variety of ages and 10 countries. Three datasets (n=1,023) were used for discovery and the gene set was then validated in 11 datasets (n=1,345 samples).

The researchers discovered the genes GBP5, DUSP3, and KLF2 are highly diagnostic for active tuberculosis. They were validated with a global area under the curve of 0.90 for distinguishing active TB from healthy controls; 0.88 for latent tuberculosis; and 0.84 for other diseases. When maximizing the sensitivity, the global threshold test characteristics across all validation datasets were: sensitivity 0.96 and specificity 0.56 for healthy controls versus active TB; sensitivity 0.95 and specificity 0.51 for latent versus active TB; and sensitivity 0.95 and specificity 0.47 for other diseases versus active TB. HIV infection status, bacterial drug resistance, or Bacillus Calmette–Guérin vaccination did not affect expression of the three-gene set. In an additional four cohorts, the TB score declined during treatment datasets (the tuberculosis score fell by 0.02 to 0.05 per week) in patients with active TB, indicating a potential utility of the test for quantitative monitoring of TB treatment response.

The authors say that the small size of the gene set will aid its ultimate clinical application, by reducing costs and complexity.

“The high parsimony and internal normalization of the three-gene set could allow for a point-of-care application, because it might be possible to assay three genes with solar-powered polymerase chain reaction instruments,” writes Sweeney and colleagues. “Although the three-gene set does not meet all needs of the consensus target product profile (e.g., overall sensitivity greater than 0.95 can only be achieved with specificity in the range of 0.50), it is able to fulfill several of the requirements of the consensus target product profile.”

Additionally, the WHO target product profile highlighted a strong need for a new diagnostic with excellent sensitivity that uses non-sputum samples; maintains an overall sensitivity of greater than 80 percent in patients with HIV co-infection; achieves a sensitivity higher than 66 percent in children with culture-positive TB; and is relatively simple to run.

Takeaway: Although the diagnostic and monitoring properties of this three-gene set need to be confirmed by prospective validation with a targeted assay, a three-gene test can improve TB diagnosis by differentiating active disease from latent disease.