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Hepatic sphingomyelin phosphodiesterase 3 promotes steatohepatitis by disrupting membrane sphingolipid metabolism

GSE271333 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2025/02/26 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 16 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
16 samples: 16 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.
Summary (written by the submitters)
Metabolic dysfunction-associated steatohepatitis (MASH) remains a significant health challenge. Herein, we identify sphingomyelin phosphodiesterase 3 (SMPD3) as a key driver of hepatic ceramide accumulation through increasing sphingomyelin hydrolysis at the cell membrane. Hepatocyte-specific Smpd3 gene disruption and pharmacological inhibition of SMPD3 alleviate MASH, whereas reintroducing SMPD3 reverses the resolution of MASH.
Read the full summary ↓
While healthy livers express low-level SMPD3, lipotoxicity-induced DNA damage suppresses SIRT1, triggering an upregulation of SMPD3 during MASH. This disrupts membrane sphingomyelin-ceramide balance and promotes MASH progression by enhancing caveolae-dependent lipid uptake in hepatocytes and extracellular vesicle secretion from steatotic hepatocytes to worsen inflammation and fibrosis. Thus, SMPD3 acts as a central hub integrating key MASH hallmarks. Notably, we discovered a bifunctional agent that simultaneously activates SIRT1 and inhibits SMPD3, which shows significant therapeutic potential in MASH treatment. These findings suggest that inhibition of hepatic SMPD3 restores membrane sphingolipid balance and holds great promise for developing novel MASH therapies.
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 GSE271333_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 PRJNA1130949 and SRA study SRP517592. Searching any of these in the dataset finder brings you back here.

Study design
16 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 16 sample titles: 16 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
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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.