Abstract
Background: Transcriptomic signatures for tuberculosis (TB) have been proposed and represent a promising diagnostic tool. Data remain limited in persons with advanced HIV.Methods: We enrolled 30 patients with advanced HIV (CD4 <100 cells/mm3) in India; 16 with active TB and 14 without. Whole-blood RNA sequencing was performed; these data were merged with a publicly available dataset from Uganda (n = 33; 18 with TB and 15 without). Transcriptomic profiling and machine learning algorithms identified an optimal gene signature for TB classification. Receiver operating characteristic analysis was used to assess performance.Results: Among 565 differentially expressed genes identified for TB, 40 were shared across India and Uganda cohorts. Common upregulated pathways reflect Toll-like receptor cascades and neutrophil degranulation. The machine-learning decision-tree algorithm selected gene expression values from RAB20 and INSL3 as most informative for TB classification. The signature accurately classified TB in discovery cohorts (India AUC 0.95 and Uganda AUC 1.0; p < 0.001); accuracy was fair in external validation cohorts.Conclusions: Expression values of RAB20 and INSL3 genes in peripheral blood compose a biosignature that accurately classified TB status among patients with advanced HIV in two geographically distinct cohorts. The functional analysis suggests pathways previously reported in TB pathogenesis.
Highlights
Tremendous advances in tuberculosis diagnosis have been made based on nucleic acid amplification of bacteria in the sputum, such as Xpert MTB/RIF sputum smear and culture, which provides results in 2 h [1,2,3,4,5]
Persons living with advanced human immunodeficiency virus (HIV) (CD4 < 100 cells/mm3) are at high risk for TB and are likely to have smear-negative pulmonary or extrapulmonary TB, underscoring the need for non-sputum-based TB diagnostics to support TB control efforts [9,10,11,12,13,14,15]
Using transcriptomic profiling and a machine-learning approach, we aimed to develop and validate a gene signature to fairly classify TB status among persons with advanced HIV from geographically distinct sites
Summary
Tremendous advances in tuberculosis diagnosis have been made based on nucleic acid amplification of bacteria in the sputum, such as Xpert MTB/RIF sputum smear and culture, which provides results in 2 h [1,2,3,4,5]. Sputum-based diagnostics remain problematic in the context of HIV infection. Blood-based transcriptomic signatures, including several parsimonious gene signatures, have been proposed to diagnose and differentiate TB from other respiratory diseases (ORD) and are in various stages of validation [14, 16, 17]. The majority of studies do not include persons living with advanced HIV. Data remain limited in persons with advanced HIV.
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