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FABP4, marker of worse prognosis in cardiovascular disease, induces neutrophil’s proatherogenic phenotype which is modulated by semaglutide

GSE310742 Homo sapiens (human) RNA-seq (gene expression) 22 samples Submitted 2025/12/11 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 22 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
22 samples: 22 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
FABP4, marker of worse prognosis in cardiovascular disease, induces neutrophil's proatherogenic phenotype which is modulated by semaglutideJournal of molecular and cellular cardiology · 2026
Summary (written by the submitters)
Dysfunctional epicardial adiposity is a risk factor for coronary artery disease (CAD). Its genesis is associated with an upregulation of fatty acid binding protein 4 (FABP4) levels, which might exert paracrine inflammatory and atherogenic mechanisms on the cardiovascular system. We aimed to study the prognosis of patients with high systemic FABP4, its association with a neutrophil proatherogenic phenotype, involved mechanisms and its modulation by semaglutide, a glucagon-like peptide-1 receptor agonist (GLP-1ra).
Read the full summary ↓
Higher plasma FABP4 levels than 50 ng/mL were associated with heart failure (HF) onset during follow-up. In patients with CAD, these levels were associated with pro-inflammatory and pro-atherogenic neutrophil profile markers as MPO, NGAL and CD11b, analysed by real-time PCR. The group of patients with the highest FABP4 levels exhibited higher levels of MMP9, CXCR2, and CD11b in neutrophils. A preclinical model, based on neutrophils and coronary endothelial cells, determined the effects of FABP4 on neutrophils' respiratory burst, by flow cytometry, activity of NF-kB, by western blot checking IkBa phosphorylation, CD11b integrin expression levels and adhesion to coronary endothelial cells. A modulation of the neutrophils' transcriptome, analysed by RNA-seq, and plasma chemokine CCL5 levels suggested changes in leukocyte migration and platelet activation pathways in patients who reduced plasma FABP4 levels after semaglutide treatment. Thus, supraphysiological levels of FABP4 induce pro-inflammatory and proatherogenic mechanisms in neutrophils and coronary endothelial cells. Its modulation by semaglutide could explain its benefits on coronary artery disease (CAD).
Published in
FABP4, marker of worse prognosis in cardiovascular disease, induces neutrophil's proatherogenic phenotype which is modulated by semaglutide
Sánchez-López D, García-Vega D, Viñuela JE et al. · Journal of molecular and cellular cardiology 2026 · PMID 41183609 · doi:10.1016/j.yjmcc.2025.10.009
This dataset
Open GSE310742 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 GSE310742_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 PRJNA1367016 and SRA study SRP655307. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41183609) ↗
Study design
22 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 22 sample titles: 22 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
Datasets on a similar topic

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