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Distinct immunometabolic signatures of type 1 versus type 2 diabetes in a murine model of myocardial infarction

GSE306097 Mus musculus (mouse) RNA-seq (gene expression) 55 samples Submitted 2025/08/26 Platform GPL30172
At a glance

RNA-seq (gene expression) · mouse · 55 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
55 samples: 6 conditions, mostly with about 8 replicates eachGroups 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
Distinct immunometabolic signatures of type 1 versus type 2 diabetes in a murine model of myocardial infarctionCardiovascular diabetology · 2026
Summary (written by the submitters)
Background: Diabetes mellitus (DM), which consists of type I and type 2 diabetes (T1D and T2D), is a known risk factor for myocardial infarction (MI) and negatively impacts post-MI outcomes. However, the mechanisms by which DM exacerbates cardiac remodeling in T1D versus T2D have not been well defined. Here, we assessed acute and chronic post-MI outcomes in T1D and T2D mice, focusing on immune and metabolic pathways.
Read the full summary ↓
Methods: T1D was induced in adult male mice by a single high dose of streptozotocin (STZ), and T2D induced by high fat/fructose feeding and multiple low STZ doses. Two weeks following STZ administration, MI was induced by permanent coronary artery ligation, and mice were studied at days (D) 3, 7, and 28 post-MI. Cardiac function was assessed by echocardiography. Results: Compared to non-diabetic mice, T1D and T2D mice had worse cardiac dysfunction after MI, including increased wall thinning and decreased ejection fraction, despite similar infarct sizes. T1D mice also displayed acute pulmonary congestion. By RNA-sequencing analysis, T1D and T2D mice displayed upregulation of genes associated with canonical chemokine/monocyte-mediated inflammatory pathways, and downregulation of genes associated with extracellular matrix remodeling. T1D and T2D delayed activation of M2-like (CD206+) macrophages in the heart, and impaired normal collagen and elastin deposition after MI. T2D also increased expression of genes associated with T cell activation, and increased CD8+ T cells in the infarct. T1D and T2D hearts showed signs of impaired glucose and ketone oxidation, and T1D hearts had increased markers of fatty acid oxidation. Extracted D3 cardiac macrophages from T1D and T2D mice exhibited higher basal oxygen consumption, and increased M1 markers and chemokine expression. Plasma from T1D and T2D mice increased chemokine expression (Ccl2, Ccl7, Cxcl1) in cultured bone marrow macrophages, and T2D plasma impaired mitochondrial function. Conclusions: DM promotes adverse cardiac remodeling, which is associated with activation of overlapping and unique inflammatory pathways, impaired ECM remodeling, remote metabolic remodeling, and alterations in macrophage metabolism. Our results provide novel insights into potential therapeutic pathways for DM patients suffering from MI.
Published in
Distinct immunometabolic signatures of type 1 versus type 2 diabetes in a murine model of myocardial infarction
O'Quinn KR, Wright CB, Khan M et al. · Cardiovascular diabetology 2026 · PMID 41656217 · doi:10.1186/s12933-026-03099-y
This dataset
Open GSE306097 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 GSE306097_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: 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 PRJNA1309119 and SRA study SRP610577. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41656217) ↗
Study design
6 conditions, mostly with about 8 replicates each
infarct tissue, day 28, non-diabetic, ×11 infarct tissue, day 28, type 1 diabetic, ×10 infarct tissue, day 28, type 2 diabetic, ×10 infarct tissue, day 7, non-diabetic, ×8 infarct tissue, day 7, type 1 diabetic, ×8 infarct tissue, day 7, type 2 diabetic, ×8

Supports a between-group comparison across 55 samples.

How we read this: 6 replicated groups read from 55 sample titles; they account for 55 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

+ 15 more — browse all 55 samples with per-sample file links →

Datasets on a similar topic

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