PD-L1-Centric Whole Blood-Based Immune Signature Profiles of Tuberculosis Patients During Therapy

Authors

• Johanna Eggeling
• Martina Sester
• Christoph Lange
• Jan Heyckendorf
• Barbara Kalsdorf
• Anna M Mandalakas
• Andrew R DiNardo
• David Lewinsohn
• Dagmar Schaub
• Tina Schmidt
• Eva Tolosa
• Maja Reimann
• Patricia M Sánchez Carballo

Language

English

Publication Date

1-1-2026

Journal

Frontiers in Immunology

DOI

10.3389/fimmu.2026.1829438

PMID

42367813

PMCID

PMC13305727

PubMedCentral® Posted Date

6-12-2026

PubMedCentral® Full Text Version

Post-print

Abstract

This prospective study investigated whole blood-based immune cell biomarkers for pulmonary tuberculosis (TB) immunoprofiling. Blood samples from 34 healthy controls and 51 tuberculosis patients were analyzed at three timepoints: Prior to therapy (T0), after 14 days of therapy (T1), and at the end of treatment (Te). Using multiparameter flow cytometry, 386 immune cell populations were analyzed. Predictive models were developed using two machine learning algorithms. A TB5LF change score, which was based on five cell populations, effectively distinguished tuberculosis patients from controls (AUC = 0.89) and tuberculosis patients before and at the end of treatment (AUC = 0.92). Similarly, the TB5Lasso score distinguished tuberculosis patients from controls (AUC = 0.91) and tuberculosis patients before and at the end of treatment (AUC = 0.93) but was inversely correlated with disease severity (r=–0.43). Both scores included PD-L1+CD80- neutrophils and PD-L1+HLA-DR+ CD4+ lymphocytes, highlighting PD-L1-associated and Th1-related immune signatures as candidate biomarkers for TB immunoprofiling. These findings are exploratory and hypothesis-generating, providing a basis for future studies evaluating their potential utility in diagnostic and therapy-monitoring contexts.

Keywords

Humans, B7-H1 Antigen, Female, Male, Biomarkers, Adult, Middle Aged, Tuberculosis, Pulmonary, Prospective Studies, Flow Cytometry, Neutrophils, Th1 Cells, Antitubercular Agents, biomarker, flow cytometry, infectious disease, machine learning, personalized medicine, programmed cell death ligand 1, risk assessment

Published Open-Access

yes

Recommended Citation

Eggeling, Johanna; Sester, Martina; Lange, Christoph; et al., "PD-L1-Centric Whole Blood-Based Immune Signature Profiles of Tuberculosis Patients During Therapy" (2026). Faculty, Staff and Students Publications. 7590.
https://digitalcommons.library.tmc.edu/baylor_docs/7590