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Impaired cardiac branched-chain amino acid metabolism in a novel model of diabetic cardiomyopathy

GSE268260 Mus musculus (mouse) RNA-seq (gene expression) 10 samples Submitted 2025/04/23 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 10 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
10 samples: 10 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
Impaired cardiac branched-chain amino acid metabolism in a novel model of diabetic cardiomyopathyCardiovascular diabetology · 2025
Summary (written by the submitters)
Metabolic alterations occur in the heart of patients with type 2 diabetes mellitus (T2DM). However, the relationships between branched-chain amino acid (BCAA) metabolism and the pathophysiology of diabetic cardiomyopathy (DbCM) remain unclear. Here, we sought to establish a novel model of DbCM and reveal its metabolic alterations, especially focusing on BCAA metabolism.
Read the full summary ↓
Using adipocyte-specific 3′-phosphoinositide–dependent kinase 1 (PDK1)-deficient (A-PDK1KO) mice as a new model of DbCM, we demonstrated that cardiac BCAA catabolic enzymes were down-regulated in these mice, leading to the accumulation of BCAAs in the heart. Mechanistically, the accumulation of the BCAA leucine could cause cardiac hypertrophy via the activation of mammalian target of rapamycin complex 1 (mTORC1). A-PDK1KO mice mimic the cardiac phenotypes and metabolic alterations seen in human DbCM and exhibit impaired BCAA metabolism in the heart. This model may contribute to a better understanding of DbCM pathophysiology and the development of novel therapies for it.
Published in
Impaired cardiac branched-chain amino acid metabolism in a novel model of diabetic cardiomyopathy
Asakura J, Nagao M, Shinohara M et al. · Cardiovascular diabetology 2025 · PMID 40240904 · doi:10.1186/s12933-025-02725-5
This dataset
Open GSE268260 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 GSE268260_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 PRJNA1115897 and SRA study SRP509565. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40240904) ↗
Study design
10 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 10 sample titles: 10 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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