Immunometabolic Biomarkers to Advance TB Diagnosis and Treatment Monitoring

PROJECT SUMMARY/ABSTRACT Among the 10.6 million persons estimated to develop tuberculosis (TB) disease each year, ~40% are never notified to public health programs, leading to delays in treatment and increased TB transmission and mortality. Current diagnostics for pulmonary TB require microbiologic testing of sputum specimens, which is often

unavailable in primary care settings in low- and middle-income countries, where most TB disease occurs. Further, clinicians lack reliable measures of TB disease severity and treatment response, limiting their ability to individualize treatment regimens and duration. There is a tremendous need for rapid, point-of-care, biomarker-

based tests that can be performed on easily obtained clinical samples (e.g., blood or urine) to diagnose TB disease and monitor response to treatment. However, the lack of effective TB biomarkers is a critical limitation to developing a new generation of point-of-care TB diagnostics. To address key knowledge gaps, this research

will examine the use of high-resolution plasma immunometabolic profiling, defined as simultaneous measurement of plasma metabolites, oxylipins, and cytokines, to discover plasma molecular biomarker signatures with potential for translation to point-of-care tests to diagnose and manage TB disease. The Specific Aims of this proposal are

to: (1) determine the plasma immunometabolic biomarker signatures that most accurately identify persons with pulmonary TB disease in a population of adults referred for TB evaluation; (2) determine the accuracy of plasma immunometabolic signatures to assess disease severity in persons with pulmonary TB; and (3) determine

whether plasma immunometabolic signatures can predict treatment response and risk of relapse in persons with TB disease. The aims of this project will be achieved by enrolling a cohort of patients at the time of TB diagnosis and following them prospectively during treatment and for 1-year post-TB treatment. Plasma immunometabolic

signatures will be compared in persons with pulmonary TB disease versus persons with TB symptoms in whom a diagnosis of TB is ultimately excluded. We will further elucidate plasma molecular signatures associated with pulmonary TB disease severity as measured by the extent of lung involvement of disease including cavitation on

computed tomography imaging of the chest. Serial plasma samples will be measured during TB treatment to determine the molecular signatures that predict time to sputum culture conversion, as well as treatment failure and relapse. The analyses will include multiple modeling strategies to select the plasma biomarkers that most

accurately identify each clinical outcome, with validation in banked plasma samples from geographically diverse TB cohorts. This proposal will directly address the lack of effective clinical TB biomarkers to improve TB diagnostics and promote a precision medicine approach to TB treatment by identifying markers of disease

severity and treatment response. The long-term goal of the proposed work is to create point-of-care tests based on host immunometabolic biomarker signatures that allow clinicians in practice settings without a laboratory to diagnose TB disease, assess disease severity, and monitor response to treatment.