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

This study investigates the immune response in extrapulmonary tuberculosis (EPTB) using 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
EGAD50000001118	The dataset comprises single-cell RNA sequencing (scRNA-seq) data derived from around 60,000 PBMCs collected from donors across different severity groups of extrapulmonary tuberculosis (EPTB) and healthy controls (3 healthy, 3 mild, 3 intermediate, 3 severe). The data include both transcriptomic and surface protein expression profiles obtained using the BD Rhapsody Single-Cell Multiomics System. Libraries were prepared for whole transcriptome analysis (WTA), AbSeq, and sample tagging, with sequencing performed on a NovaSeq 6000 system.	Illumina NovaSeq 6000	2

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