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Transcriptomic profiles of liver biopsies in obese patients with metabolic dysfunction-associated steatotic liver disease

GSE281797 Homo sapiens (human) RNA-seq (gene expression) 94 samples Submitted 2025/12/10 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 94 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
94 samples
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
Global molecular landscape of early MASLD progression in human obesityeLife · 2026
Summary (written by the submitters)
The molecular mechanisms underlying early-stage metabolic dysfunction-associated steatotic liver disease (MASLD) is poorly understood. This study characterized the transcriptomic alterations in obese patients with no pathology or early-stage MASLD. 94 snap-frozen liver biopsies were analyzed through high-throughput RNA sequencing. Distinct features involved in the development of hepatic steatosis and fibrosis were identified. This study also provided novel insights in mechanisms involved in the onset of fibrosis, highlighting potential therapeutic targets.
Published in
Global molecular landscape of early MASLD progression in human obesity
Zhao Q, De Nardo W, Wang R et al. · eLife 2026 · PMID 41870035 · doi:10.7554/eLife.109534
This dataset
Open GSE281797 in finder → Find more human 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 GSE281797_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 PRJNA1185558 and SRA study SRP544867. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41870035) ↗
Study design
A cohort of 94 individual samples

The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Sample titles run HumanLiver_S308 … HumanLiver_S398 and carry no group information.

Samples in this study

+ 54 more — browse all 94 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.