← BioTransfer GEO Dataset Finder
GEO series

ACMSD inhibition corrects fibrosis, inflammation, and DNA damage in MASLD/MASH

GSE253380 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2024/09/23 Platform GPL23479Platform GPL23227
At a glance

RNA-seq (gene expression) · human · 48 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
48 samples: 48 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
ACMSD inhibition corrects fibrosis, inflammation, and DNA damage in MASLD/MASHJournal of hepatology · 2025
Summary (written by the submitters)
Recent findings reveal the importance of tryptophan-initiated de novo nicotinamide adenine dinucleotide (NAD+) synthesis in the liver, a process previously considered secondary to biosynthesis from nicotinamide. Here we show that inhibiting α-amino-β-carboxymuconate-ε-semialdehyde decarboxylase (ACMSD) promotes de novo NAD+ synthesis and reduces DNA damage ex vivo, in vivo and in human liver organoid (HLO) models.
Read the full summary ↓
In mouse models of MASLD/MASH, de novo NAD+ biosynthesis is suppressed, and transcriptomic DNA damage signatures correlate with disease severity; In humans, Mendelian randomization-based genetic analysis suggests a notable impact of genomic stress on liver disease susceptibility. Therapeutic inhibiting ACMSD in mice elevates liver NAD+ and reverses MASLD/MASH, mitigating fibrosis, inflammation and DNA damage. Similar outcomes are recapitulated in HLO models of steatohepatitis and DNA damage. Our findings highlight the benefits of ACMSD inhibition for boosting hepatic NAD+ and genomic protection, indicating its therapeutic promise in liver diseases marked by NAD+ and genomic stress.
Published in
ACMSD inhibition corrects fibrosis, inflammation, and DNA damage in MASLD/MASH
Liu YJ, Kimura M, Li X et al. · Journal of hepatology 2025 · PMID 39181211 · doi:10.1016/j.jhep.2024.08.009
This dataset
Open GSE253380 in finder → Find more 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 GSE253380_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 PRJNA1065436 and SRA study SRP484006. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39181211) ↗
Study design
48 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 48 sample titles: 48 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

+ 8 more — browse all 48 samples with per-sample file links →

Datasets on a similar topic

Search all 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.