Circulating cell-free RNA in blood as a host response biomarker for detection of tuberculosis.
Adrienne ChangConor J LoyDaniel Eweis-LaBolleJoan S LenzAmy SteadmanAlfred AndgramaNguyen Viet NhungCharles YuWilliam WorodriaClaudia M DenkingerPayam NahidAdithya CattamanchiIwijn De VlaminckPublished in: Nature communications (2024)
Tuberculosis (TB) remains a leading cause of death from an infectious disease worldwide, partly due to a lack of effective strategies to screen and triage individuals with potential TB. Whole blood RNA signatures have been tested as biomarkers for TB, but have failed to meet the World Health Organization's (WHO) optimal target product profiles (TPP). Here, we use RNA sequencing and machine-learning to investigate the utility of plasma cell-free RNA (cfRNA) as a host-response biomarker for TB in cohorts from Uganda, Vietnam and Philippines. We report a 6-gene cfRNA signature, which differentiates TB-positive and TB-negative individuals with AUC = 0.95, 0.92, and 0.95 in test, training and validation, respectively. This signature meets WHO TPPs (sensitivity: 97.1% [95% CI: 80.9-100%], specificity: 85.2% [95% CI: 72.4-100%]) regardless of geographic location, sample collection method and HIV status. Overall, our results identify plasma cfRNA as a promising host response biomarker to diagnose TB.
Keyphrases
- mycobacterium tuberculosis
- cell free
- machine learning
- pulmonary tuberculosis
- emergency department
- hiv aids
- infectious diseases
- human immunodeficiency virus
- hiv infected
- hiv positive
- hepatitis c virus
- single cell
- artificial intelligence
- gene expression
- antiretroviral therapy
- risk assessment
- human health
- deep learning
- climate change
- quantum dots
- big data
- nucleic acid
- loop mediated isothermal amplification