Inflammation and B cell activation define a plasma proteome signature predicting tuberculosis in people with HIV.

ABSTRACT: Improved biomarkers for predicting progression to active tuberculosis (TB) are urgently needed, especially in people with HIV, who are at elevated risk. We used high-throughput plasma proteomics and machine learning to identify signatures associated with TB progression in this population. From the Swiss HIV Cohort Study, we analyzed plasma samples collected at least 6 months before TB diagnosis from 91 participants who later developed TB. We selected 293 controls matched for demographic and clinical parameters who remained TB-free to achieve a risk score specific to active TB. In total, 583 samples were analyzed, with 613-1,283 proteins quantified per sample. A random forest classifier predicted a significantly higher median probability of TB progression for cases (33%) than for controls (

SUBMITTER: Kusejko K 

PROVIDER: S-EPMC12505960 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature