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High Dimensional Analysis of Sputum Cell Transcriptomes Identifies novel pathways associated with Clinical Phenotypes of Asthma

GSE270863 Homo sapiens (human) Single-cell RNA-seq 24 samples Submitted 2025/06/24 Platform GPL20301
At a glance

Single-cell RNA-seq · human · 24 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
24 samples: 16 × sputum, asthma, vs 8 × sputum, control,Groups 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
Single-cell RNA Sequencing Analysis of Sputum Cell Transcriptomes Reveals Pathways and Communication Networks That Contribute to the Pathogenesis of AsthmabioRxiv : the preprint server for biology · 2025
Summary (written by the submitters)
Background: Asthma is a chronic inflammatory disease of the airways driven by interactions among structural cells of the airway, the immune system, and the environment. Characterization of cells isolated from the sputum has been used to study the pathogenesis of asthma and optimize treatment regimens, but the cellular transcriptomes and intercellular communication changes in the sputum of asthma are not well understood.
Read the full summary ↓
Methods: Single cell RNA sequencing was applied to cells isolated from the sputum from 16 patients with asthma and 8 non-asthmatic normal controls. Cell identity was determined by analysis of curated cell marker genes combined with SingleR annotation. Cell specific gene expression and communication networks were compared between asthma and controls and were correlated with asthma phenotypes. Findings: 15 different cell populations were identified, including several types of macrophages, monocytes, dendritic cells, and lymphocytes as well as several rare (<2%) cell types such as mast cells, innate lymphoid cells, and bronchial epithelial cells. Analysis of the intercellular communications demonstrated that signaling pathways are generally more active in asthma compared to control. CD4+ cells and dendritic cells had the largest increase in outgoing signals to other cell types. One of the strongest signal was the ADAM12 and CCL22 ligand-receptor pathways showing the strongest shift between asthma and controls. Interpretation: Analysis of cellular transcriptomes in the sputum demonstrates innate and adaptive mechanisms are increased in asthma. Increased expression of ADAM12 suggests a critical role in the pathogenesis of asthma.
Published in
Single-cell RNA Sequencing Analysis of Sputum Cell Transcriptomes Reveals Pathways and Communication Networks That Contribute to the Pathogenesis of Asthma
Yan X, Liu Q, Adams T et al. · bioRxiv : the preprint server for biology 2025 · PMID 40236103 · doi:10.1101/2025.03.31.646405
This dataset
Open GSE270863 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 GSE270863_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1128660 and SRA study SRP516371. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40236103) ↗
Study design
16 × sputum, asthma, vs 8 × sputum, control,

Supports a between-group comparison across 24 samples.

How we read this: 2 replicated groups read from 24 sample titles; they account for 24 of them. 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
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