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REGION-SPECIFIC GENE EXPRESSION AND SEX INFORM ABOUT DISEASE SUSCEPTIBILITY IN THE AORTA - MCAM Knockdown

GSE292995 Homo sapiens (human) Single-cell RNA-seq 30 samples Submitted 2025/06/30 Platform GPL34281
At a glance

Single-cell RNA-seq · human · 30 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
30 samples: 15 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
Region-specific gene expression and sex inform about disease susceptibility in the aortaNature cardiovascular research · 2025
Summary (written by the submitters)
Pathology in large vessels frequently develops at specific locations, implying that local stressors and spatially restricted gene expression are likely contributors to disease susceptibility. To identify site- and sex-specific differences that could inform about vulnerability, we performed single-cell transcriptomics in the carotids, aortic arch, thoracic, and abdominal aorta.
Read the full summary ↓
Our findings revealed: (1) regionally defined transcriptional profiles, (2) signatures associated with embryonic origins, and (3) differential contributions of sex-specific effectors. Sex differences were predominantly observed in the thoracic and abdominal aorta. MCAM/CD146, a transcript with sex-skewed expression in vSMC of the abdominal aorta showed a 2.5-fold lower expression in males when compared to females. siRNA knockdown was performed to identify downstream targets of MCAM in vascular smooth muscle cells and to assess if sex affected number and biological function of genes modulated by changes in MCAM expression. MCAM was found to be further downregulated in vSMC associated with aortic aneurysms in humans. The findings reveal underlying diversity within vSMC populations with relevance to understanding site-specific and sex-specific variation of vascular pathologies.
Published in
Region-specific gene expression and sex inform about disease susceptibility in the aorta
Romay MC, Ma F, Mompeón A et al. · Nature cardiovascular research 2025 · PMID 40841834 · doi:10.1038/s44161-025-00692-4
This dataset
Open GSE292995 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 GSE292995_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 PRJNA1242326 and SRA study SRP573383. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40841834) ↗
Study design
15 conditions, mostly in duplicate
G82-MCAM-1SI ×2 G82-NEG_CONTROL_SI ×2 G88-MCAM-1SI ×2 G88-NEG_CONTROL_SI ×2 G88-vSMC ×2 LN983-MCAM-1SI ×2 LN983-NEG_CONTROL_SI ×2 LN983-vSMC ×2 +7 more

Supports a between-group comparison across 30 samples.

How we read this: 15 replicated groups read from 30 sample titles; they account for 30 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

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