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

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 (16%; <i>P</i> < 0.001). In this matched population, the score achieved an area under the receiver-operating characteristic curve of 0.77, an area under the precision-recall curve (AUPRC) of 0.60 (as compared to an expected AUPRC of 0.29), as well as a specificity of 87.3% and a sensitivity of 58.6% using the optimal threshold of 0.311. The plasma proteome of individuals who progressed to active TB showed a distinct shift toward systemic inflammation, B cell activation, and immunoglobulin production. Independent of progression to active TB, the proteome score correlated with broader indicators of immune suppression, including lower CD4 counts and unsuppressed HIV RNA. This suggests that integrating proteomic and clinical data could enhance the overall predictive power of the score.IMPORTANCEWe still lack reliable tools to predict who will develop tuberculosis (TB) among people with HIV. Moreover, the underlying biological events driving progression remain poorly understood. Our study reveals early immune changes that include unexpected alterations in B cell activation and antibody responses. These findings suggest that humoral immunity may play a more important role in TB pathogenesis than previously recognized and offer promising new directions for biomarker discovery and targeted prevention.

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Journal
mBio
Published
2025-08-28
DOI
https://doi.org/10.1128/mbio.01585-25
Citations
1
Primary Topic
Tuberculosis Research and Epidemiology
Type
article
Field-Weighted Citation Impact
1.40

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article

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

Enos Bernasconi, Niklaus Daniel Labhardt, Diane Duroux, Marius Zeeb et al.
1 citations
mBio
Tuberculosis Research and Epidemiology
1.40
article

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

Enos Bernasconi, Niklaus Daniel Labhardt, Diane Duroux, Marius Zeeb, Johannes Nemeth, Gilles Wandeler, Doris Russenberger, Huldrych F. Günthard, Ben C. Collins, Matthias Cavassini, Roger D. Kouyos, Mohammad Arefian, Katharina Kusejko, Sabine Haller, Matthias Hoffmann, Cédric Dollé
article en
1 citations

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 (16%; <i>P</i> < 0.001). In this matched population, the score achieved an area under the receiver-operating characteristic curve of 0.77, an area under the precision-recall curve (AUPRC) of 0.60 (as compared to an expected AUPRC of 0.29), as well as a specificity of 87.3% and a sensitivity of 58.6% using the optimal threshold of 0.311. The plasma proteome of individuals who progressed to active TB showed a distinct shift toward systemic inflammation, B cell activation, and immunoglobulin production. Independent of progression to active TB, the proteome score correlated with broader indicators of immune suppression, including lower CD4 counts and unsuppressed HIV RNA. This suggests that integrating proteomic and clinical data could enhance the overall predictive power of the score.IMPORTANCEWe still lack reliable tools to predict who will develop tuberculosis (TB) among people with HIV. Moreover, the underlying biological events driving progression remain poorly understood. Our study reveals early immune changes that include unexpected alterations in B cell activation and antibody responses. These findings suggest that humoral immunity may play a more important role in TB pathogenesis than previously recognized and offer promising new directions for biomarker discovery and targeted prevention.

mBioVol. 16(10)
University of Geneva (CH), University of Bern (CH), Queen's University Belfast (GB), University of Basel (CH), University of Zurich (CH), University Hospital of Bern (CH), Centre Hospitalier Universitaire Vaudois (CH), University Hospital of Basel (CH), ETH Zurich (CH), Ente Ospedaliero Cantonale (CH), Shenzhen International Travel Health Care Center (CN), Quantitative BioSciences (US), University Hospital of Zurich (CH), Institute of Virology of the Slovak Academy of Sciences (SK), Ostschweizer Kinderspital (CH)
National Science Foundation, Eli Lilly and Company, Pfizer, AstraZeneca, GlaxoSmithKline, Gilead Sciences, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, National Institutes of Health
Openalex Percentile: Top 17%
Tuberculosis Research and Epidemiology
1.40
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