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Unique Mycobacterium tuberculosis-specific blood immune signatures in sarcoidosis: implications for clinical diagnosis

GSE287043 Homo sapiens (human) RNA-seq (gene expression) 542 samples Submitted 2025/12/03 Platform GPL16791Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 542 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
542 samples: 542 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Mycobacterium tuberculosis-specific blood immune signatures distinguish sarcoidosis from tuberculosis diseaseJournal of immunology (Baltimore, Md. : 1950) · 2026
Summary (written by the submitters)
Sarcoidosis is a granulomatous systemic inflammatory disease predominantly affecting lungs. It shares histopathological, clinical and immune features with tuberculosis (TB). There are currently no diagnostic tests to formally identify sarcoidosis; clinicians first need to rule out the presence of other diseases, including TB. We characterized Mycobacterium tuberculosis (Mtb)-specific immune responses in blood of pulmonary sarcoidosis patients in comparison to active tuberculosis (ATB), Mtb-sensitized and non-sensitized healthy controls using flow cytometry and transcriptomics.
Read the full summary ↓
We found that sarcoidosis was associated with i) a marked reduction in the frequency of antigen-reactive T cells in response to both Mtb peptides and Mtb lysate, ii) increased frequency of monocytes ex vivo and after in vitro stimulation, and iii) increased expression of phagocytic genes compared to Mtb-infected and healthy cohorts. Combination of Mtb-specific T cell and monocyte gene or flow cytometry signatures in Mtb-stimulated PBMC could efficiently distinguish sarcoidosis from ATB with high specificity and sensitivity, and to a lower extent from Mtb-sensitized and non-sensitized healthy controls. These biomarkers offer promising aspects for developing effective diagnostic tests for sarcoidosis, in particular for differential diagnosis from tuberculosis.
Published in
Mycobacterium tuberculosis-specific blood immune signatures distinguish sarcoidosis from tuberculosis disease
Chihab LY, Cheng C, Hillman H et al. · Journal of immunology (Baltimore, Md. : 1950) 2026 · PMID 41105206 · doi:10.1093/jimmun/vkaf274
This dataset
Open GSE287043 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE287043_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1211053 and SRA study SRP557562. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41105206) ↗
Study design
542 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from the first 400 of 542 sample titles: 400 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 502 more — browse all 542 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.