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Plasma Extracellular Vesicle Modulate Immune Cell Transcriptional Responses Following Acute Myocardial Infarction

GSE313527 Homo sapiens (human) RNA-seq (gene expression) 74 samples Submitted 2026/03/25 Platform GPL21290
At a glance

RNA-seq (gene expression) · human · 74 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
Homo sapiens (human)
Samples
74 samples: 60 distinct titles, 14 of them repeatedGroups 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
Plasma extracellular vesicle modulate immune cell transcriptional responses following acute myocardial infarctioniScience · 2026
Summary (written by the submitters)
Plasma extracellular vesicles (EVs) increase during acute myocardial infarction (MI), correlate with myocardial injury, and mobilise immune cells from the spleen to the circulation. These cells are transcriptionally activated even before tissue recruitment, yet the mechanisms driving this priming are unclear. We show that plasma EVs isolated at hospital presentation with MI are enriched in miRNA‑320b.
Read the full summary ↓
Endothelial cells upregulate miRNA‑320b in EVs following inflammatory stimulation. Target gene pathway analysis revealed enrichment in adhesion and cytokine signalling. Endothelial EVs promoted monocyte adhesion and induced IL6 and TNF mRNA expression in macrophages while dampening cytokine secretion. RNA-sequencing of MI patient neutrophils and monocytes confirmed significant enrichment of miRNA‑320b targets. Peripheral blood mononuclear cells treated with MI EVs showed similar gene regulation. These findings suggest that EV‑mediated transfer of miRNA‑320b primes immune cells for adhesion and cytokine signalling. Understanding this axis may enable therapeutic immunomodulation of immune cells to improve repair following MI.
Published in
Plasma extracellular vesicle modulate immune cell transcriptional responses following acute myocardial infarction
Timms L, Ridley R, Braithwaite A et al. · iScience 2026 · PMID 41852720 · doi:10.1016/j.isci.2026.114665
This dataset
Open GSE313527 in finder → Find more human 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 GSE313527_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 PRJNA1380110 and SRA study SRP654721. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41852720) ↗
Study design
60 distinct titles, 14 of them repeated
1.EV.NSTEMI.20 ×2 5.EV.STEMI.23 ×2 1.EV.STEMI.19 ×2 2.EV.NSTEMI.23 ×2 3.EV.NSTEMI.4 ×2 4.EV.NSTEMI.27 ×2 5.EV.STEMI.24 ×2 1.EV.LPS.IFNg.NSTEMI.20 ×2 +6 more

How we read this: Read from 74 sample titles: 60 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

+ 34 more — browse all 74 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.