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Proteo-transcriptional architecture of human pressure overload: implications for heart failure

GSE262690 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 58 samples Submitted 2025/05/01 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 58 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Samples
58 samples: 20 conditions, mostly in duplicateGroups 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
Integrated multiomics of pressure overload in the human heart prioritizes targets relevant to heart failureNature communications · 2025
Summary (written by the submitters)
Chronic pressure overload initiates a series of molecular alterations in the human heart that predate macroscopic organ-level remodeling and downstream heart failure (HF). We hypothesized that integrating easily accessible circulating mediators (proteome) with their expression in the heart (transcriptome) may prioritize targets for study in human pressure overload.
Read the full summary ↓
Among individuals with severe aortic stenosis (AS)—a pressure overload state—we measured the circulating proteome (Olink) and examined associations with myocardial structure/function (N=519), cardiac MRI-based tissue fibrosis (N=145), and outcomes in AS (N=802). We constructed proteomic signatures of cardiac remodeling and tested their association with HF in the UK Biobank (N=36,668). For proteo-transcriptional integration, we examined a "remodeling proteome” prioritized by proteome-phenotype relations at the transcriptional level via single nuclear RNA-sequencing (snRNA-seq) in 20 human hearts (11 with AS at the time of surgical aortic valve replacement [AVR] and 9 donor hearts not used for transplantation). We identified three principal components of myocardial remodeling (across 12 echocardiographic measures in 503 patients with AS) loaded on cardiac morphology, systolic, and diastolic function traits. Proteins associated with these components (the “remodeling proteome”) specified both known and novel mediators of fibrosis, hypertrophy, and oxidative stress, several of which were associated with interstitial fibrosis by cardiac MRI. Proteomic signatures of remodeling were strongly linked to mortality (AS cohort and UK Biobank) and incident HF (UK Biobank). At a myocardial level, we observed broad differential expression of genes encoding the remodeling proteome between AS and donor hearts, featuring convergent fibrosis pathways (WNT9A, ITGA6, AGRN, CRIM1, SEMA4C, LAYN, PTX3, HMOX1) and metabolic-inflammatory signaling (ENPP2/ATX, TNF), among others. Differential expression of proteo-transcriptionally prioritized genes was prominent in fibroblasts, cardiomyocytes, and endothelial cells. Proteo-transcriptional prioritization in human pressure overload hearts identifies both known and novel targets that are mechanistically relevant to HF pathogenesis. Future integrative studies to index circulating biomarkers over time to myocardial tissue level is warranted to inform pathways of HF progression.
Published in
Integrated multiomics of pressure overload in the human heart prioritizes targets relevant to heart failure
Lindman BR, Perry AS, Lance ML et al. · Nature communications 2025 · PMID 40715126 · doi:10.1038/s41467-025-62201-2
This dataset
Open GSE262690 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 GSE262690_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1093010 and SRA study SRP498466. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40715126) ↗
Study design
20 conditions, mostly in duplicate
S11_001 ×4 S11_002 ×4 S12_003 ×4 S12_007 ×4 S12_008 ×4 S12_010 ×4 S14_012 ×4 S16_013 ×4 +12 more

Supports a between-group comparison across 58 samples.

How we read this: 20 replicated groups read from 58 sample titles; they account for 58 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

+ 18 more — browse all 58 samples with per-sample file links →

Datasets on a similar topic

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