← BioTransfer GEO Dataset Finder
GEO series

Single-cell profiling reveals immune aberrations in progressive idiopathic pulmonary fibrosis

GSE233844 Homo sapiens (human) Single-cell RNA-seq 38 samples Submitted 2024/05/09 Platform GPL20301
At a glance

Single-cell RNA-seq · human · 38 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
38 samples: 13 × Stable IPF patient vs 13 × Control Subject vs 12 × Progressive IPF patientGroups 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 Profiling Reveals Immune Aberrations in Progressive Idiopathic Pulmonary FibrosisAmerican journal of respiratory and critical care medicine · 2024
Summary (written by the submitters)
Rationale: Changes in peripheral blood cell populations have been observed but not detailed at single-cell resolution in idiopathic pulmonary fibrosis (IPF). Objectives: To provide an atlas of the changes in the peripheral immune system in stable and progressive IPF. Methods: Peripheral blood mononuclear cells (PBMCs) from IPF patients and controls were profiled using 10x Chromium 5’ single-cell RNA sequencing (scRNA-seq).
Read the full summary ↓
Flow cytometry was used for validation. Protein concentrations of Regulatory T-cells (Tregs) and Monocytes chemoattractants were measured in plasma and lung homogenates from patients and controls. Measurements and Main Results: Thirty-eight PBMC samples from 25 patients with IPF and 13 matched controls yielded 149,564 cells that segregated into 23 subpopulations, corresponding to all expected peripheral blood cell populations. Classical monocytes were increased in progressive and stable IPF compared to controls (32.1%, 25.2%, 17.9%, respectively, p<0.05). Total lymphocytes were decreased in IPF vs controls, and in progressive vs stable IPF (52.6% vs 62.6%, p=0.035). Tregs were increased in progressive IPF (1.8% vs 1.1%, p=0.007), and were associated with decreased survival (P=0.009 in Kaplan-Meier analysis). Flow cytometry analysis confirmed this finding in an independent cohort of IPF patients. Tregs were also increased in two cohorts of lung scRNA-seq. CCL22 and CCL18, ligands for CCR4 and CCR8 Treg chemotaxis receptors, were increased in IPF. Conclusions: The single-cell atlas of the peripheral immune system in IPF, reveals an outcome-predictive increase in classical monocytes and Tregs, as well as evidence for a lung-blood immune recruitment axis involving CCL7 (for classical monocytes) and CCL18/CCL22 (for Tregs).
Published in
Single-Cell Profiling Reveals Immune Aberrations in Progressive Idiopathic Pulmonary Fibrosis
Unterman A, Zhao AY, Neumark N et al. · American journal of respiratory and critical care medicine 2024 · PMID 38717443 · doi:10.1164/rccm.202306-0979OC
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 GSE233844_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: 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 PRJNA978083 and SRA study SRP440530. Searching any of these in the dataset finder brings you back here.

Study design
13 × Stable IPF patient vs 13 × Control Subject vs 12 × Progressive IPF patient

Supports a case/control comparison: 25 samples read as cases, 13 as controls.

How we read this: 3 replicated groups read from 38 sample titles; they account for 38 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
Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.