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Immune checkpoint TIM-3 regulates microglia and Alzheimer’s disease [snRNAseq_5M]

GSE223423 Mus musculus (mouse) Single-nucleus RNA-seq 10 samples Submitted 2025/05/07 Platform GPL30172
At a glance

Single-nucleus RNA-seq · mouse · 10 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue).
Organism
Mus musculus (mouse)
Samples
10 samples: 3 × 5M_Tim3_cKO.5XFAD vs 3 × 5M_5XFAD vs 2 × 5M_control vs 2 × 5M_Tim3_cKOGroups 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
Immune checkpoint TIM-3 regulates microglia and Alzheimer's diseaseNature · 2025
Summary (written by the submitters)
Microglia are the resident immune cells in the brain and have pivotal roles in neurodevelopment and neuroinflammation1,2. This study investigates the function of the immune-checkpoint molecule TIM-3 (encoded by HAVCR2) in microglia. TIM-3 was recently identified as a genetic risk factor for late-onset Alzheimer’s disease3, and it can induce T cell exhaustion4.
Read the full summary ↓
However, its specific function in brain microglia remains unclear. We demonstrate in mouse models that TGFβ signalling induces TIM-3 expression in microglia. In turn, TIM-3 interacts with SMAD2 and TGFBR2 through its carboxy-terminal tail, which enhances TGFβ signalling by promoting TGFBR-mediated SMAD2 phosphorylation, and this process maintains microglial homeostasis. Genetic deletion of Havcr2 in microglia leads to increased phagocytic activity and a gene-expression profile consistent with the neurodegenerative microglial phenotype (MGnD), also referred to as disease-associated microglia (DAM). Furthermore, microglia-targeted deletion of Havcr2 ameliorates cognitive impairment and reduces amyloid-β pathology in 5×FAD mice (a transgenic model of Alzheimer’s disease). Single-nucleus RNA sequencing revealed a subpopulation of MGnD microglia in Havcr2-deficient 5×FAD mice characterized by increased pro-phagocytic and anti-inflammatory gene expression alongside reduced pro-inflammatory gene expression. These transcriptomic changes were corroborated by single-cell RNA sequencing data across most microglial clusters in Havcr2-deficient 5×FAD mice. Our findings reveal that TIM-3 mediates microglia homeostasis through TGFβ signalling and highlight the therapeutic potential of targeting microglial TIM-3 in Alzheimer’s disease.
Published in
Immune checkpoint TIM-3 regulates microglia and Alzheimer's disease
Kimura K, Subramanian A, Yin Z et al. · Nature 2025 · PMID 40205047 · doi:10.1038/s41586-025-08852-z
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 GSE223423_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: 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 PRJNA926117 and SRA study SRP418559. Searching any of these in the dataset finder brings you back here.

Study design
3 × 5M_Tim3_cKO.5XFAD vs 3 × 5M_5XFAD vs 2 × 5M_control vs 2 × 5M_Tim3_cKO

Supports a between-group comparison across 10 samples.

How we read this: 4 replicated groups read from 10 sample titles; they account for 10 of them. 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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