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A TWO-GENE SIGNATURE FOR TUBERCULOSIS DIAGNOSIS IN PERSONS WITH ADVANCED HIV
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Abstract
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.
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