BACKGROUND: Diagnosis of tuberculosis (TB) in people with HIV (PWH) remains difficult. Since the first pathogen-host interaction in TB occurs in the upper airway, host transcriptomic analysis on nasal specimens may identify novel diagnostic biomarkers. We aimed to demonstrate differences in nasal gene expression in PWH and TB disease versus PWH without TB, evaluate the performance of nasal signatures in predicting TB and compare nasal gene profiles with blood. METHODS: We enrolled adults in Uganda with newly diagnosed HIV and symptoms of pulmonary TB disease. We collected nasal cells and blood for RNA sequencing to identify differentially expressed genes (DEGs) and enriched pathways between PWH and TB disease and PWH without TB. Supervised machine-learning of gene expression data was used to predict TB. RESULTS: 40 PWH were enrolled (median age: 34 years, median CD4 count: 182), including 20 with TB disease and 20 without. We identified 44 nasal DEGs and 238 blood DEGs, with three overlapping DEGs between samples. Models trained using all 44 nasal DEGs had a cross-validated area under the curve between 0.87-0.90 for predicting TB disease. A simplified signature (SPIB, SHISA2, TESPA1 and CD1B) met WHO criteria for a TB triage test. Among adults with TB, pathways related to the inflammatory response were downregulated in nasal samples and upregulated in blood. CONCLUSION: There are distinct nasal gene expression patterns associated with TB, not seen in blood. Differences in nasal gene expression in PWH who have TB disease, versus those without TB, highlight their potential as diagnostic biomarkers.