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Characterization of ALDH2-deficient alcohol-associated liver disease (duodenum RNA seq)

GSE288043 Mus musculus (mouse) RNA-seq (gene expression) 25 samples Submitted 2025/07/16 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 25 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
25 samples: 5 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.
Paper
Opposite regulation of intestinal and intrahepatic CD8(+) T cells controls alcohol-associated liver disease progressionGut · 2025
Summary (written by the submitters)
Aldehyde dehydrogenase 2 (ALDH2) is a key enzyme to detoxify the ethanol first metabolite acetaldehyde. Approximately 8% world population have inactive ALDH2 and have facial flushing due to high levels of acetaldehyde after alcohol consumption. Alcohol-associated liver disease (ALD) and hepatocellular carcinoma (HCC) in those with inactive ALDH2 have not been characterized.
Read the full summary ↓
ALD pathogeneses in these individuals are likely very different from those with normal ALDH2, different diagnosis criteria and treatment are required for these two populations. Here we studied ALD in inactive Aldh2 knockin (Aldh2KI) mice with chronic ethanol feeding.
Published in
Opposite regulation of intestinal and intrahepatic CD8(+) T cells controls alcohol-associated liver disease progression
Maccioni L, Guan Y, Kim M et al. · Gut 2025 · PMID 40199574 · doi:10.1136/gutjnl-2024-334412
This dataset
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.

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 GSE288043_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1215761 and SRA study SRP559917. Searching any of these in the dataset finder brings you back here.

Study design
5 conditions, mostly with about 4 replicates each
Duo_WT_Half ×7 Duo_KI_Half ×6 Duo_WT_Con ×4 Duo_KI_Con ×4 Duo_WT_Full ×4

Supports a between-group comparison across 25 samples.

How we read this: 5 replicated groups read from 25 sample titles; they account for 25 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
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