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Alcohol-associated hepatitis induces hepatocyte senescence which is reduced following disease resolution II

GSE270042 Homo sapiens (human) RNA-seq (gene expression) 65 samples Submitted 2025/03/28 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 65 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
Homo sapiens (human)
Samples
65 samples: 18 × Liver, Placebo, d0, patient vs 18 × Liver, Placebo, d28, patient vs 15 × Liver, Canakinumab, d0, patient vs 14 × Liver, Canakinumab, d28, patientGroups 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
Longitudinal paired liver biopsies and transcriptome profiling in alcohol-associated hepatitis reveal dynamic changes in cellular senescenceGut · 2025
Summary (written by the submitters)
Alcohol-associated hepatitis (AH) is an acute form of alcohol-related liver disease (ArLD) with high mortality rate. AH is histologically characterised by cellular processes including steatosis, inflammation and cell death. Apoptosis is the most studied form of cell death in AH; however, the role of cellular senescence, another response to cellular injury, in AH is unknown. Here we aim to explore the mechanisms of ArLD pathophysiology and define the role of senescence in AH.
Published in
Longitudinal paired liver biopsies and transcriptome profiling in alcohol-associated hepatitis reveal dynamic changes in cellular senescence
Rodrigo-Torres D, Kilpatrick AM, Ferreira-Gonzalez S et al. · Gut 2025 · PMID 40122595 · doi:10.1136/gutjnl-2024-334094
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 GSE270042_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 PRJNA1124907 and SRA study SRP514354. Searching any of these in the dataset finder brings you back here.

Study design
18 × Liver, Placebo, d0, patient vs 18 × Liver, Placebo, d28, patient vs 15 × Liver, Canakinumab, d0, patient vs 14 × Liver, Canakinumab, d28, patient

Supports a between-group comparison across 65 samples.

How we read this: 4 replicated groups read from 65 sample titles; they account for 65 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

+ 25 more — browse all 65 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.