Assessment of Validity of a Blood-Based 3-Gene Signature Score for Progression and Diagnosis of Tuberculosis, Disease Severity, and Treatment Response

Abstract

Key Points Question How does a previously described blood-based 3-gene tuberculosis score perform as a screening test and a disease monitoring tool for all stages of tuberculosis? Findings In this nested case-contral study, the 3-gene tuberculosis score was associated with progression from latent Mycobacterium tuberculosis infection to active tuberculosis 6 months prior to sputum conversion with 86% sensitivity and 84% specificity, diagnosed patients with active tuberculosis with 90% sensitivity and 70% specificity, and correlated with treatment response and the severity of lung pathology. Meaning The 3-gene tuberculosis score can be implemented as a rapid, blood-based screening and triage test with the required World Health Organization target product profiles for the accurate detection and tracking of progressive, active, and treated tuberculosis disease.

Concise whole blood transcriptional signatures for incipient tuberculosis: A systematic review and patient-level pooled meta-analysis

“…Moreover, integral to both diagnostic accuracy and impact studies is the translation of transcriptional measurements from un-scalable genome-wide approaches such RNAseq to the reproducible quantification of selected signature genes, with appropriately defined cut-offs. While this has been performed for some signatures using PCR-based platforms 16,17,30,42 , no signature platforms have yet been validated for implementation in a near-patient or commercial assay.…”

“…9 LTBI = latent TB infection; SVM = support vector machine; PLHIV = people living with HIV; LASSO = least absolute shrinkage and selection operator. 10 # Anderson38, Huang11, Kaforou25 and Walter45 included 42,13,27 and 51 genes in the original descriptions, respectively (genes not included in current models 11 were either duplicates, or not identifiable in RNAseq data). 12 * Calculated using non-log transformed data using model coefficients from original publication.…”

Clinical Development of New TB Vaccines: Recent Advances and Next Steps

“…How can a new TB vaccination strategy offer protection both to "most of those at risk, " as well as "those most at risk, " given current limitations of predictive and diagnostic tests? Large cohort studies have identified proteomic and transcriptomic (Suliman et al, 2018b;Zak et al, 2016;Warsinske et al, 2018) host blood biomarkers and high IGRA conversion threshold values (interferon-gamma >4.0 IU/mL) (Winje et al, 2018;Andrews et al, 2017) that predict which infected individuals have highest risk of progression to TB disease. However, it is highly unlikely that pre-vaccination screening, even to identify IGRA-positive people, would be feasible in high TB incidence developing countries with limited resources and constrained health system capacity.…”

SIMON: open-source knowledge discovery platform

“…ML has a profound impact on biological research [10][11][12] , including genomics 13 , proteomics [14][15][16] , cell image analysis 17 , drug discovery and development 18 , and cell phenotyping 6,19,20 which revolutionized our understanding of biological complexity. Recently, using systems-level analysis of genetic, transcriptional, and proteomic signatures to predict patients' response to vaccines 21,22 , therapies and disease progression [23][24][25][26][27] , ML has become primary computational approach used in the 'precision medicine' 28 .…”