GEO series

Kupffer cell diversity maintaines liver function in alcohol associated liver disease [scRNA-seq]

GSE269059 Mus musculus (mouse) Single-cell RNA-seq 10 samples Submitted 2024/10/25 Platform GPL24247

At a glance

Single-cell RNA-seq · mouse · 10 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Mus musculus (mouse)
Samples: 10 samples: 10 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: Kupffer cell diversity maintains liver function in alcohol-associated liver diseaseHepatology (Baltimore, Md.) · 2025

Summary (written by the submitters)

Background & Aims: Liver macrophages are heterogeneous and play an important role in alcohol_x0002_associated liver disease (ALD) but there is limited understanding of the functions of specific macrophage subsets in the disease. We used a Western Diet Alcohol (WDA) mouse model of ALD to examine the hepatic myeloid cell compartment by scRNA seq and targeted Kupffer cell (KC) ablation to understand the diversity and function of liver macrophages in ALD.

Read the full summary ↓

Approach and Results: In the WDA liver, KCs and infiltrating monocytes/macrophages (IMs) each represented about 50% of the myeloid pool. Five major KC clusters all expressed genes associated with receptor mediated endocytosis and lipid metabolism, but most were predicted to be non_x0002_inflammatory and antifibrotic with one minor KC cluster having a pro-inflammatory and extracellular matrix degradation gene signature. IM clusters, in contrast, were predicted to be pro_x0002_inflammatory and pro-fibrotic. In vivo diphtheria toxin based selective KC ablation during alcohol exposure resulted in a liver failure phenotype with increases in PT/INR and bilirubin, loss of differentiated hepatocyte gene expression, and an increase in expression of hepatocyte progenitor markers such as EpCAM, CK-7 and Igf2bp3. Gene set enrichment analysis of whole liver RNAseq from the KC ablated WDA mice showed a similar pattern as seen in human alcoholic hepatitis. Conclusions: In this ALD model, KCs are anti-inflammatory and are critical for maintenance of hepatocyte differentiation. IMs are largely pro-inflammatory and contribute more to liver fibrosis. Future targeting of specific macrophage subsets may provide new approaches to treatment of liver failure and fibrosis in ALD.

Published in

Kupffer cell diversity maintains liver function in alcohol-associated liver disease

Sasaki K, Rooge S, Gunewardena S et al. · Hepatology (Baltimore, Md.) 2025 · PMID 38687563 · doi:10.1097/HEP.0000000000000918

This dataset

Open GSE269059 in finder → Find more mouse 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 GSE269059_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1120030 and SRA study SRP511759. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38687563) ↗

Study design

10 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 10 sample titles: 10 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

GSM8305735 Chow diet, replicate 1, scRNAseq
GSM8305736 Chow diet, replicate 2, scRNAseq
GSM8305737 Western diet, replicate 4, scRNAseq
GSM8305738 Western diet alcohol, replicate 4, scRNAseq
GSM8305739 Western diet, replicate 1, scRNAseq
GSM8305740 Western diet, replicate 2, scRNAseq
GSM8305741 Western diet, replicate 3, scRNAseq
GSM8305742 Western diet alcohol, replicate 1, scRNAseq
GSM8305743 Western diet alcohol, replicate 2, scRNAseq
GSM8305744 Western diet alcohol, replicate 3, scRNAseq

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