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Data Mining of IFNgamma-induced macrophage and Atherosclerotic Plaque Transcriptomes predicts a macrophage-specific role of STAT1 in human atherosclerosis [BMDM]

GSE276416 Mus musculus (mouse) Single-cell RNA-seq 18 samples Submitted 2024/09/09 Platform GPL21273
At a glance

Single-cell RNA-seq · mouse · 18 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
18 samples: 6 conditions, mostly in triplicateGroups 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
Integrative multi-omics analysis of IFNγ-induced macrophages and atherosclerotic plaques reveals macrophage-dependent STAT1-driven transcription in atherosclerosisFrontiers in immunology · 2025
Summary (written by the submitters)
Atherosclerosis is a chronic inflammatory disease of the blood vessels, characterized by atherosclerotic lesions. Early vascular injury initiates excessive inflammatory and immune responses, communicated by blood leukocytes and cells from the vasculature. Key factors contributing to early stages of atherosclerosis and plaque development include the pro-inflammatory cytokine IFNγ, which is vital for both innate and adaptive immunity and is also expressed at high levels in atherosclerotic lesions.
Read the full summary ↓
Recent discoveries provide novel evidence to suggest that IFNγ-activated STAT1 orchestrates a platform of cell-type common and specific inflammatory responses in Vascular Smooth Muscle Cells (VSMC) and macrophages (MΦ) that are instrumental in the onset and progression of atherosclerotic plaque formation. Therefore, we compared genome-wide transcriptional responses of mouse VSMCs and bone marrow-derived macrophages (BMDMs) in time-dependent IFNγ response using RNA-seq. We identified genes upregulated both in a common and cell-type-specific manner. Next, comparative analysis with RNAseq data from aortic plaques from HFD-treated ApoEKO mice identified 225 differentially expressed genes with a BMDM-specific character. These included many known IFNγ target genes containing putative GAS and ISRE sites in their promoters. Likewise, using a scRNAseq data set obtained from human coronary atherosclerotic plaques, identified 98 pro-inflammatory and pro-atherogenic genes that were characterized as BMDM-specific and exclusively expressed in foamy, inflammatory, monocytes and tissue-resident BMDM subtypes. Finally, we identified a 25 BMDM-specific gene subset commonly expressed in mouse and human plaques, over-representing STAT1-binding sites and predominantly associated with Leukocyte Chemotaxis and Migration. These results provide strong evidence for a BMDM-specific role of STAT1 in coronary artery plaque development and identify a BMDM-specific STAT1-dependent pro-inflammatory gene signature that could serve to monitor and diagnose plaque progression in human atherosclerosis.
Published in
Integrative multi-omics analysis of IFNγ-induced macrophages and atherosclerotic plaques reveals macrophage-dependent STAT1-driven transcription in atherosclerosis
Eskandarian Boroujeni M, Lopacinska N, Antonczyk A et al. · Frontiers in immunology 2025 · PMID 40607379 · doi:10.3389/fimmu.2025.1590953
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 GSE276416_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 PRJNA1157326 and SRA study SRP530680. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly in triplicate
BMDM, UN, ×3 BMDM, IFNy 0,5h, ×3 BMDM, IFNy 2h, ×3 BMDM, IFNy 4h, ×3 BMDM, IFNy 8h, ×3 BMDM, IFNy 24h, ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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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