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Urolithin A Provides Cardioprotection and Mitochondrial Quality Enhancement Preclinically and Improves Cardiovascular Health Biomarkers in Humans [mouse_cardiac_aging]

GSE283273 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2025/01/23 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 18 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
18 samples: 18 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
Urolithin A provides cardioprotection and mitochondrial quality enhancement preclinically and improves human cardiovascular health biomarkersiScience · 2025
Summary (written by the submitters)
Cardiovascular diseases (CVDs) remain the primary cause of global mortality. Nutritional interventions hold promise to reduce CVD risks in an increasingly aging population. However, few nutritional interventions are proven to support heart health and act mostly on blood lipid homeostasis rather than at cardiac cell level. Here, we show that mitochondrial quality and dysfunction are a common hallmark in human cardiomyocytes upon heart aging and in chronic conditions.
Read the full summary ↓
Preclinically, the post-biotic and mitophagy activator, Urolithin A (UA), reduced both systolic and diastolic cardiac dysfunction in models of natural aging and heart failure. At a cellular level, this was associated with a recovery of mitochondrial ultrastructural defects and mitophagy. In humans, UA supplementation for 4 months in healthy older adults significantly reduced plasma ceramides clinically validated to predict CVD risks. These findings extend and translate UA’s benefits to heart health, making UA a promising nutritional intervention to support cardiovascular function as we age.
Published in
Urolithin A provides cardioprotection and mitochondrial quality enhancement preclinically and improves human cardiovascular health biomarkers
Liu S, Faitg J, Tissot C et al. · iScience 2025 · PMID 40034121 · doi:10.1016/j.isci.2025.111814
This dataset
Open GSE283273 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 GSE283273_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 PRJNA1193003 and SRA study SRP548659. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40034121) ↗
Study design
18 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 18 sample titles: 18 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
Datasets on a similar topic

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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.