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NAD+ Deficiency Drives Metabolic Dysfunction-Associated Atrial Fibrillation

GSE334551 Mus musculus (mouse) RNA-seq (gene expression) 29 samples Submitted 2026/06/24 Platform GPL24247Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 29 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
29 samples: 6 conditions, mostly with about 4 replicates eachGroups 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.
Summary (written by the submitters)
Atrial fibrillation (AF) is a cardiometabolic disease with obesity and diabetes as major risk factors. The cellular and molecular mechanisms by which obesity and metabolic stressors drive AF are poorly understood. Here we establish a new mouse model of spontaneous, obesity-induced AF. This two-hit model relies on genetic susceptibility coupled with an environmental factor of diet-induced obesity.
Read the full summary ↓
Unbiased multi-omics analyses reveal cardiac conduction pathways, inflammation, and metabolic perturbations in AF. We demonstrate atrial NAD+ deficiency as a central pathological mediator in AF. Pharmacological replenishment of atrial NAD+ levels mitigates AF, protects against cardiac remodeling and fibrosis, reduces inflammation, and improves atrial metabolism. These results highlight the role of a metabolic pathway that could be therapeutically targeted for AF.
This dataset
Open GSE334551 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 GSE334551_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 PRJNA1475449 and SRA study SRP707234. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly with about 4 replicates each
Atria, males, NaV1.5 4w HFD&N ×7 Atria, males, NaV1.5 4w HFD ×5 Atria, males, NaV1.5 4w HFD vehicle ×5 Atria, males, NaV1.5 RD ×4 Atria, males, Ctrls RD ×4 Atria, males Ctrls 4w HFD ×4

Supports a between-group comparison across 29 samples.

How we read this: 6 replicated groups read from 29 sample titles; they account for 29 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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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.