Title: Developing new tools to facilitate a targeted approach to testing and treatment for latent tuberculosis infection.
Funder: Department of Health and Social Care

Abstract: Background:Tuberculosis (TB) rates in the UK remain higher than most other Western European countries. Current strategies to improve UK TB control include huge investment in a national latent TB infection (LTBI) screening programme among recent migrants from high TB-incidence settings. However, current LTBI diagnostics offer poor predictive value for progression to TB disease. This results in a significant burden of unnecessary treatment, associated toxicity, and wasted NHS resources. Integration of data-driven models for clinical risk-profiling and novel whole-blood transcriptional bio-signatures of subclinical TB provides unprecedented opportunity to address this problem, by allowing us to identify those at highest-risk of developing TB, and focus resources on those needing treatment most.Aim:I propose to facilitate a targeted approach to LTBI testing and treatment by developing new tools to refine risk-profiling of patients with LTBI.Objectives: To develop a predictive model for the risk of progression from LTBI to TB disease in low-incidence settings using an individual participant data (IPD) meta-analysis. To test the hypothesis that blood transcriptional signatures of subclinical TB correlate with the risk-prediction model developed in Objective 1. To test the hypothesis that resolution of blood transcriptional signatures of subclinical TB occurs more frequently in patients receiving effective LTBI treatment. Methods: I will conduct a systematic review to identify studies examining progression risk from LTBI to TB disease in low-incidence settings. I will pool the data and perform an IPD meta-analysis using TB incidence as the primary outcome. Using a proportional hazards model, I will construct a risk-calculator for progression. I will test the correlation between the risk-calculator and transcriptional signature expression in two LTBI patient cohorts: (a) an existing cohort (n=600); and (b) a prospective cohort in a natural history study of LTBI (n=1,000). I will enrol 80 patients with LTBI who express a blood transcriptional biomarker of subclinical TB. After excluding clinical TB disease, I will offer them LTBI treatment. I will then undertake longitudinal clinical assessments and blood transcriptional measurements 6, 12, and 26 weeks after starting treatment, mirrored by measurements at the same time intervals in patients who decline treatment. The primary outcome will be to compare the proportion of cases with abnormal transcriptional biomarkers at 12 and 26 weeks in the treated vs. untreated groups. Impact and Dissemination:The IPD meta-analysis will provide the strongest evidence available regarding progression risk from LTBI to TB disease in low-incidence settings. This will inform NHS policies regarding which populations should be targeted for LTBI testing and treatment. The risk-calculator will allow NHS staff and patients to make better-informed decisions about LTBI treatment. The comparison of treatment and non-treatment resolution of transcriptional signatures of subclinical TB will provide critical validation of these novel biomarkers as a platform for a definitive clinical trial for their application in the NHS. Results will be disseminated to: the public via a TB charity, social media and press releases; to the scientific community through conferences and publications; and to policymakers by direct engagement and via advocates.

Lay abstract: Why is this research needed?Tuberculosis (TB) rates in the UK remain higher than most Western European countries. An important way of preventing people from developing TB is to treat those who have latent' TB infection (LTBI). This refers to people who have been infected with the bacteria, but their immune system is able to control it. However, over time, up to one in ten of these people will become unwell with TB disease. Identifying people with LTBI therefore allows us to treat them before this happens, and before the infection spreads to others. For this reason, the NHS is investing a lot of money in a national migrant LTBI screening programme.However, the challenge is that one in four people are thought to have LTBI worldwide. We are currently unable to accurately predict which of these people will develop TB. Drugs used to treat LTBI must be taken for a long-time, and have side-effects. We would therefore like to identify people with LTBI who are at highest risk of developing TB so we can prevent as many cases as possible, while reducing unnecessary treatment for others, drug side-effects and NHS costs. This project will address this problem by developing new tools to help us to predict who will develop TB more accurately and therefore target our testing and treatment better.What will be done?Firstly, I will produce a risk-calculator' that will estimate the chance of developing TB for any individual with LTBI. This depends on many factors, including: age, gender, where they have lived in the world, contact with others with TB, and how well their immune system functions. To do this, I will collect information from all previous studies on this topic from the UK and similar countries. By pooling these results together, I will answer this question more precisely than ever before.Secondly, I will assess whether a new blood test that measures specific human gene-levels may help us identify people with LTBI who are at highest-risk of developing TB. These gene-levels are known to change before people become unwell with TB. To do this, I will assess whether our 'risk-calculator' estimates agree with results of the blood test in two separate patient groups (a previously collected group, and a new study group). I will then assess whether the blood test result returns to normal with LTBI treatment by enrolling 80 people with LTBI who have an abnormal test. I will offer them all LTBI treatment. We know that some people with LTBI choose not to take LTBI treatment; I will compare the blood test results in those who accept treatment with those who choose not to take it.How will the results be used?The estimates of the chances of developing TB in people with LTBI will be the strongest evidence available on this subject. These results will directly inform national policies about which people should be tested and treated for LTBI. The risk-calculator' will allow both healthcare providers and patients to make better-informed decisions about LTBI testing and treatment.I then hope to show that the gene-level blood test normalises with LTBI treatment. If so, this would strengthen the evidence that the test may help us identify people who are at high-risk of developing TB. I would then recommend a larger study to investigate its application, aiming for NHS implementation within five years.Our results will be circulated publicly via a TB charity, social media and press releases; to healthcare staff through conferences and journal articles; and to people who write our national LTBI testing and treatment policies by direct discussions, and via advocates.

Research activity codes: 4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health categories: INFECTION