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Deletion of sphingosine 1-phosphate receptor 1 in myeloid cells reduces hepatic inflammatory macrophages and attenuates MASH

GSE288368 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/03/01 Platform GPL13112
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 12 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)
Background: Immune cell-driven inflammation is a key mediator of metabolic dysfunction-associated steatohepatitis (MASH) progression. We have previously demonstrated that pharmacological sphingosine 1-phosphate (S1P) receptor modulation ameliorates MASH and is associated with attenuated accumulation of intrahepatic macrophage and T cell subsets.
Read the full summary ↓
Although S1P receptors are expressed on several immune cell types, given the prominent role of monocyte-derived recruited macrophages in the sterile inflammation of MASH, we hypothesized that deletion of S1P receptor 1 (S1P1) on myeloid cells may ameliorate MASH by reducing the accumulation of proinflammatory monocyte-derived macrophages into the liver. Methods: The LyzMCre approach was used to generate myeloid cell-specific knockout mice, termed S1pr1MKO. Littermate S1pr1loxp/loxp mice were used as wild-type (WT) controls. MASH was established by feeding mice a high-fat, fructose, and -cholesterol (FFC) diet for 24 weeks which leads to the development of steatohepatitis and MASH-defining cardiometabolic risk factors. Liver injury and inflammation were determined by histological and gene expression analyses. Intrahepatic leukocyte populations were analyzed by mass cytometry and immunohistochemistry. Results: Histological examination demonstrated a reduction in liver inflammatory infiltrates and fibrosis in FFC-fed S1pr1MKO compared to WT. There was a corresponding reduction in alanine aminotransferase, a sensitive marker for liver injury. As determined by mass cytometry, a significant decrease in recruited macrophages was noted in the livers of FFC-fed S1pr1MKO mice compared to WT. Gene ontology pathway analysis revealed a significant suppression of the peroxisome proliferator-activated receptor gamma (PPARγ) and mitogen activated protein kinase (MAPK) pathways in S1pr1MKO consistent with attenuated MASH in mice. Conclusion: Deletion of S1P1 in myeloid cells is sufficient to attenuate intrahepatic accumulation of monocyte-derived macrophages and ameliorate murine MASH.
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 GSE288368_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 PRJNA1217035 and SRA study SRP560636. Searching any of these in the dataset finder brings you back here.

Study design
12 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 12 sample titles: 12 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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