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Blood-Based Molecular Signatures to Enable Rapid EPTB Diagnosis

By LabMedica International staff writers
Posted on 24 Nov 2025

Extrapulmonary tuberculosis (EPTB) remains difficult to diagnose and treat because it spreads beyond the lungs and lacks easily accessible biomarkers. More...

Despite TB infecting 10 million people yearly, the immune mechanisms driving EPTB have remained unclear. A new study now maps the disease’s molecular activity in blood, identifying immune patterns that could lead to targeted therapies and non-invasive diagnostic tests.

In the collaborative study, researchers at the German Center for Infection Research (DZIF), Braunschweig, Germany) used blood samples from EPTB patients for applying multi-omics profiling, including single-cell RNA sequencing, to chart how immune cells communicate during infection.

The approach revealed complex signaling networks involving interferon and interleukin-1 pathways, as well as activation patterns of T cells and natural killer cells. Based on these molecular interactions, researchers identified three distinct “immunotypes,” each representing a unique disease course. The findings, published in Nature Communications, show that these immunotypes expose new biological mechanisms that shape how EPTB develops and progresses.

In addition to immune profiling, the team constructed gene expression–based biomarkers that accurately differentiated extrapulmonary from pulmonary TB. Current diagnosis of EPTB often requires invasive tissue biopsy; however, the newly identified blood signatures could serve as a future non-invasive diagnostic tool. These markers may help clinicians detect EPTB earlier, classify disease severity, and tailor treatments more precisely.

The investigators emphasize that integrating clinical data was essential to correctly interpret molecular findings and connect them to real patient outcomes. Their blood-based biomarker panel is now being validated in the larger mEX-TB clinical study, marking a step towards translation into clinical practice.

"These findings have the potential to substantially advance the diagnosis and treatment of tuberculosis and to facilitate the development of targeted, personalized therapies," said Dr. Thomas Ulas, a bioinformatician at the DZNE.

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