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Differential Transcriptome Features of Peripheral Blood Mononuclear Cells in Pulmonary Sarcoidosis with and without Extrapulmonary Lesions

GSE302854 Homo sapiens (human) RNA-seq (gene expression) 40 samples Submitted 2025/12/05 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 40 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
40 samples
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
Differential Transcriptomic Features of Peripheral Blood Mononuclear Cells in Pulmonary Sarcoidosis with and Without Extrapulmonary Lesions in an East Asian PopulationBiomedicines · 2025
Summary (written by the submitters)
Sarcoidosis is a systemic granulomatous disease of unknown etiology. Pulmonary sarcoidosis with extrapulmonary lesions (EPL), especially in cardiac sarcoidosis, is associated with poor prognosis. The transcriptome features of peripheral blood mononuclear cells (PBMCs) could be crucial in sarcoidosis pathogenesis. However, the gene expression characteristics associated with EPL development in pulmonary sarcoidosis remain unknown.
Read the full summary ↓
Therefore, we investigated gene expression patterns associated with the development of EPL in pulmonary sarcoidosis. First, we conducted trascriptome analysis between patients with pulmonary sarcoidosis and healthy controls. Principal component analysis (PCA) revealed a clear distinction between them, with 227 differentially expressed genes detected. Enrichment analysis revealed upregulated immunological pathways related to granuloma formation in pulmonary sarcoidosis PBMCs, including T helper 17 and tumor necrosis factor-alpha signaling pathways, inflammatory cytokine production, and response to external stimuli. Furtheremore, PCA differentiated patients with pulmonary sarcoidosis with and without EPL, and 206 differentially expressed genes identified, including interferon-gamma (IFNG) and interferon lambda receptor 1 (IFNLR1). Gene ontology (GO) analysis revealed that interleukin 6 (IL-6) and IL-23 production were upregulated in patients with pulmonary sarcoidosis and EPL. In cardiac sarcoidosis, nitric oxide synthases (NOS), including NOS1 and NOS2, were upregulated in PBMCs. The current study strengthens our understanding of the mechanisms underlying granuloma formation in sarcoidosis and demonstrates the differential transcriptome features of PBMCs in patients with pulmonary sarcoidosis with and without EPL, highlighting IFNG and IFNLR1 upregulation. The upregulation of these genes may be related to EPL development and could serve as potential therapeutic targets for sarcoidosis.
Published in
Differential Transcriptomic Features of Peripheral Blood Mononuclear Cells in Pulmonary Sarcoidosis with and Without Extrapulmonary Lesions in an East Asian Population
Murai Y, Kawasaki T, Imamoto T et al. · Biomedicines 2025 · PMID 41463010 · doi:10.3390/biomedicines13122998
This dataset
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.

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 GSE302854_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1292468 and SRA study SRP601431. Searching any of these in the dataset finder brings you back here.

Samples in this study

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