Abstract
Abstract Rationale Currently, there are several host immune response-based biomarkers to triage individuals suspected to have Tuberculosis (TB), to predict TB treatment failure and to predict risk of progression from latent TB infection (LTBI) to TB disease. However, validation of these biomarkers in diverse populations, with well-defined clinical endpoints, has been scarce. Moreover, a robust platform to validate TB biomarkers is essential to the development of a universal diagnostic or prognostic clinical test. Objectives NanoString nCounter technology is an amplification-free, highly sensitive digital detection platform that directly measures gene expression of up to 800 targets. Here, we investigated whether NanoString technology could serve as a platform to extensively validate existing TB biomarkers, in a new cohort from South India. Methods A NanoString Codeset that probes 107 genes (NS-TB107), comprising 12 published TB gene signatures and 6 house-keeping genes was developed to quantify RNA from whole blood samples of 80 pulmonary TB patients and 102 individuals with LTBI. The TBSignatureProfiler software was used to score samples for each signature. An ensemble of machine-learning algorithms were used to derive a parsimonious gene signature. Results Gene signatures present in NS-TB107 had statistically significant power to distinguish TB from LTBI in our cohort. A six-gene set (NANO6) derived from this cumulative data, when tested on 10 publicly-available transcriptomic datasets, was highly diagnostic for active TB. Conclusions The NanoString nCounter system provides an efficient platform to validate a panel of existing TB biomarkers and to derive a highly-diagnostic parsimonious candidate TB biomarker. This project has been funded by Award No. USB-31150-XX-13 of the US Civilian Research & Development Foundation (CRDF Global) and by the National Science Foundation under Cooperative Agreement No. OISE-9531011 with Federal funds from the Government of India’s (GOI) Department of Biotechnology (DBT), the Indian Council of Medical Research (ICMR), the United States National Institutes of Health (NIH), National Institute of Allergy and Infectious Diseases (NIAID), Office of AIDS Research (OAR), and distributed in part by CRDF Global.
Published Version
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