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Location and etiology modulate fibroblast activation in the failing human heart

GSE298023 Homo sapiens (human) Single-nucleus RNA-seq 18 samples Submitted 2025/11/08 Platform GPL24676
At a glance

Single-nucleus RNA-seq · human · 18 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). 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
18 samples: 6 × Cardiac, Heart Failure, DCM, s vs 5 × Cardiac, Heart Failure, ICM, s vs 5 × Cardiac, Heart Failure, ICM-scar, s vs 2 × Cardiac, non-Failure , Donor, sGroups 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
Location and aetiology are determinants of fibroblast activation and heterogeneity in the failing human heartGenome medicine · 2025
Summary (written by the submitters)
Cardiac fibrosis is a major contributor to heart failure (HF), yet its therapeutic targeting remains limited due to the complexity of fibrosis types and distributions. This study investigates fibroblast heterogeneity and spatial organization in the left ventricle of human hearts from non-failing donors and HF patients with ischemic or dilated cardiomyopathy.
Read the full summary ↓
Using single-nucleus RNA sequencing and spatial transcriptomics, distinct fibroblast subpopulations were identified, with resident fibroblasts being depleted in HF and replaced by disease-associated states. Differences in activation ligands, transcriptional trajectories, and spatial localization revealed divergent fibroblast transitions between scar and interstitial fibrosis, and between HF subtypes. These results provide insight into fibroblast dynamics and offer potential targets to modulate fibrosis in heart failure.
Published in
Location and aetiology are determinants of fibroblast activation and heterogeneity in the failing human heart
Youness M, Ekhteraei-Tousi S, Nagaraju CK et al. · Genome medicine 2025 · PMID 41310709 · doi:10.1186/s13073-025-01580-z
This dataset
Open GSE298023 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 GSE298023_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 PRJNA1267120 and SRA study SRP587286. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41310709) ↗
Study design
6 × Cardiac, Heart Failure, DCM, s vs 5 × Cardiac, Heart Failure, ICM, s vs 5 × Cardiac, Heart Failure, ICM-scar, s vs 2 × Cardiac, non-Failure , Donor, s

Supports a between-group comparison across 18 samples.

How we read this: 4 replicated groups read from 18 sample titles; they account for 18 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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