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International Research Team Develops Blood Test for Tuberculosis Risk Assessment

NEW YORK (GenomeWeb) – An international team — led by researchers at the South African Tuberculosis Vaccine Initiative at the University of Cape Town and the Center for Infectious Disease Research in Seattle — has identified an RNA expression signature in blood that can pinpoint when someone is most likely to develop an active tuberculosis infection.

"Active tuberculosis is the disease that makes people very sick, killing 1.5 million every year," Daniel Zak, first author on the paper and researcher at the Center for Infectious Disease Research in Seattle, told GenomeWeb in an email. "It is also during active tuberculosis that the infection gets spread. Latent tuberculosis infection is without symptoms and people are otherwise healthy. The difference between latent and active is that people with latent tuberculosis have immune systems that can keep the bacteria in check."

The study notes that nearly a third of the world's population is infected with either latent or active tuberculosis. In order to prevent the spread of the disease, medical professionals need a way to identify when an infection might become active and therefore spreadable . "We've found that this is a slow process, and that signals in the blood indicate a person, who is otherwise healthy, is actually transitioning to active TB up to one-and-a-half years before they really get sick," Zak said.

As they reported yesterday in The Lancet, the team's aim was to determine whether it was possible to find a specific signature that could identify when someone with a latent tuberculosis infection was on their way to contracting the active disease. 

The researchers' prospective study enrolled 6,363 participants from the South African Adolescent Cohort Study (ACS), and 4,466 participants from independent South African and Gambian cohorts. They followed the participants in both cohorts for over two years, collecting blood samples every six months, and monitoring the adolescents for disease progression. They also performed whole-blood RNA sequencing analysis on Illumina HiSeq-2000 sequencers. 

The researchers then compared participants who developed active tuberculosis disease over the study period with those who remained healthy, and were able to derive a prospective signature of risk from the whole-blood RNA sequencing data. After they adapted their expression analysis to be identifiable using multiplex quantitative real-time PCR (qRT-PCR), the signature was used to predict tuberculosis disease in untouched adolescent samples and in samples from independent cohorts of South African and Gambian adult participants. 

The researchers validated their RNA sequencing and qRT-PCR-based risk signature by blind prediction on untouched samples from the ACS test set. They also validated their qRT-PCR-based tuberculosis risk signature by blind prediction on independent samples from the South African and Gambian cohorts. 

As they wrote in their paper, the blood-based signatures they identified in healthy individuals "can predict progression to active tuberculosis disease, and pave the way for the establishment of diagnostic methods that are scalable and inexpensive." 

Christine Sizemore, a tuberculosis researcher at the National Institute of Allergy and Infectious Disease who was not involved in the study, told GenomeWeb that "the signature is robust despite age difference, geographical location, and exposure," further adding that the time frame and size of the study was a noteworthy feat that was likely only possible because of the international collaboration and support that the research received. 

"The main impact [of the blood-based signature] would be to try and treat people before they get sick to ultimately prevent disease and prevent the spread of the infection," Zak added. "But we did find that it is also an excellent diagnostic signature for discriminating active TB from latent and from other respiratory diseases." 

Another team of researchers at Stanford University, who published their research in The Lancet Respiratory Medicine earlier this year, have also developed RNA expression signatures to diagnose tuberculosis. However, their expression profile is different from the one identified by Zak and his colleagues and is not meant to determine risk assessment for the disease.

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