Multi-omics analysis reveals immune programs delineating disease severity in extrapulmonary tuberculosis

This study investigates the immune response in extrapulmonary tuberculosis (EPTB) using a combination of bulk and single-cell RNA sequencing. Hierarchical clustering of patient transcriptomes identified three distinct levels of disease severity, uncovering immunological pathways involved in disease progression, including interferon and IL-1β-mediated signaling. The findings also led to the development of a diagnostic gene expression signature for both EPTB and pulmonary TB, offering potential improvements in TB diagnosis and treatment.

Type: RNASeq
Archiver: European Genome-Phenome Archive (EGA)

1 Dataset 1 Publication

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID	Description	Technology	Samples
EGAD50000000943	This dataset provides insight into the immune response in extrapulmonary tuberculosis (EPTB), using bulk RNA-seq data to analyze different disease severities. Hierarchical clustering identified three distinct levels of severity, revealing disease progression driven by interferon and IL-1β-mediated signaling. Additionally, the dataset helped develop a diagnostic gene expression signature for both EPTB and pulmonary TB.	Illumina NovaSeq 6000	50

Publications	Citations
Deep immune profiling delineates hallmarks of disease heterogeneity in extrapulmonary tuberculosis. Theobald SJ, Dahm K, Lange D, Spintge JB, Winter S, Klingmüller A, Holsten L, Simonis A, De Domenico E, Walczak H, van Uelft M, Schultze JL, Beyer MD, Ulas T, Suárez I, Rybniker J. Nat Commun 16: 2025 9662	0