GEO series

Growth arrest of thoracic aortic aneurysms in aging Marfan mice

GSE333518 Mus musculus (mouse) RNA-seq (gene expression) 8 samples Submitted 2026/06/25 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 8 samples

What it is: RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism: Mus musculus (mouse)
Samples: 8 samples: 8 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: Growth arrest of thoracic aortic aneurysms in aging Marfan miceAmerican journal of physiology. Heart and circulatory physiology · 2026

Summary (written by the submitters)

There remains a pressing need to identify pathologic mechanisms that render a thoracic aortic aneurysm susceptible to continued enlargement, dissection, or rupture, yet additional insight can be gleaned by understanding compensatory mechanisms that limit disease progression and thereby stabilize a lesion. Our biomechanical data suggest that the ascending aorta within a common mouse model of Marfan syndrome, Fbn1C1041G/+, exhibits progressive disease from 12 weeks to 1 year of age but near growth arrest from 1 to 2 years of age.

Read the full summary ↓

Comparison of the biomechanical phenotype, histological characteristics, and proteomic signature from 12 weeks to 1 year to 2 years plus the transcriptional profile from 12 weeks to 2 years suggests that multiple differentially expressed genes (including downregulated Ltbp3 and Rictor) and associated proteins may contribute to late-term growth arrest. Although there is a need to understand better the interconnected roles of temporal changes in differential gene expression and protein abundance, modulating TGFβ signaling and reducing mTOR signaling appears to merit increased attention in limiting aneurysmal expansion in Marfan syndrome.

Published in

Growth arrest of thoracic aortic aneurysms in aging Marfan mice

Means CW, Mays G, Yeung N et al. · American journal of physiology. Heart and circulatory physiology 2026 · PMID 42222959 · doi:10.1152/ajpheart.00007.2026

This dataset

Open GSE333518 in finder → Find more mouse 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 GSE333518_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1471223 and SRA study SRP704230. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42222959) ↗

Study design

8 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 8 sample titles: 8 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

GSM9766754 MFS 12Wk 1 [12wk_M-1]
GSM9766755 MFS 12Wk 2 [12wk_M-2]
GSM9766756 MFS 12Wk 3 [12wk_M-3]
GSM9766757 MFS 12Wk 4 [12wk_M-4]
GSM9766758 MFS 2Y 1 [166_257]
GSM9766759 MFS 2Y 2 [172_326]
GSM9766760 MFS 2Y 3 [192_314]
GSM9766761 MFS 2Y 4 [193_209]

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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.