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Spatial transcriptomic profiling of the human aortic valve reveals cellular sex differences near sites of calcification

GSE306288 Homo sapiens (human) Single-cell RNA-seq 17 samples Submitted 2026/06/03 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 17 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
17 samples: 17 samples, each with a distinct title — no replicated groupsGroups 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
Spatial and Single-Cell Mapping Reveals Valvular Interstitial Cell and Macrophage Sex Differences in Calcific Aortic Valve DiseaseArteriosclerosis, thrombosis, and vascular biology · 2026
Summary (written by the submitters)
Sex differences in aortic valve stenosis (AVS) progression have been documented clinically, but the underlying cellular mechanisms that drive sex-dependent calcification in aortic valve tissue remain poorly understood. Here, we harnessed single cell and spatial transcriptomics to investigate mechanisms that drive sex dependent spatial organization of valvular interstitial cell (VIC) and macrophage gene expression near calcification sites in human male and female aortic valve tissue.
Read the full summary ↓
Histological analyses of aortic valve tissues stratified into healthy and diseased cohorts based on degree of calcification reveal increased valve calcification area in diseased male aortic valves relative to female, and increased valve thickening in diseased female aortic valves. Single cell sequencing analysis of heterogeneous valvular interstitial cell (VIC) populations reveals male-dependent gene expression of the Activator Protein 1 (AP-1) transcription factor complex. Spatial transcriptomics and RNA-FISH analyses of VIC populations near sites of calcification revealed male-dependent gene expression localization of Cartilage Oligomeric Matrix Protein (COMP), as opposed to diffuse COMP expression in female VICs. Cell-cell communication analyses were used to determine female-specific macrophage-VIC interactions. Secreted phosphoprotein 1 (also known as osteopontin) expressed from macrophages interacts with the cell surface receptor CD44 expressed by VICs to drive a pro-fibrotic phenotype in female aortic valves. Together, our results reveal sex differences in VIC and macrophage heterogeneity and functions near sites of calcification in aortic valve tissue. Our results highlight the importance of sex-based transcriptomics analyses to understand the cellular phenotypes responsible for causing sex differences in aortic valve fibrosis calcification.
Published in
Spatial and Single-Cell Mapping Reveals Valvular Interstitial Cell and Macrophage Sex Differences in Calcific Aortic Valve Disease
Baddour T, Ninh VK, Gorashi RM et al. · Arteriosclerosis, thrombosis, and vascular biology 2026 · PMID 42206364 · doi:10.1161/ATVBAHA.126.324694
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 GSE306288_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 PRJNA1310428 and SRA study SRP612249. Searching any of these in the dataset finder brings you back here.

Study design
17 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 17 sample titles: 17 distinct titles with little repetition. 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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