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Fluoxetine disrupts cholesterol metabolism in endothelial cells via SREBP2 activation

GSE304246 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2026/07/01 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 16 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
16 samples: 4 × 24L012729_FO_Fluoxetine_i vs 4 × 24L012733_FO_Fluoxetine_i vs 4 × 24L012737_FO_Vehicle_i vs 4 × 24L012738_FO_Vehicle_iGroups 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
Fluoxetine disrupts cholesterol metabolism in endothelial cells via SREBP2 activationTranslational psychiatry · 2026
Summary (written by the submitters)
Fluoxetine is a selective serotonin reuptake inhibitor (SSRI) widely prescribed for the treatment of depressive disorders. However, its long-term cardiovascular safety remains unknown. Here, we report an association between fluoxetine intake and an increased risk of cardiovascular diseases in the UK biobank cohort . In PCSK9-overexpression mouse model of atherosclerosis and primary human endothelial cells (ECs), we uncover that fluoxetine deregulates lipid and cholesterol metabolism.
Read the full summary ↓
Fluoxetine triggered an upregulation of cholesterol metabolism genes in ECs, leading to accumulation of lipid droplets, with higher levels of cholesterol esters, ceramides, sphingolipids and fatty acids. The disruption of lipid homeostasis was associated with increased cholesterol biosynthesis, and low-density lipoprotein (LDL) uptake in ECs via the LDL receptor. Mechanistically, fluoxetine activates the SREBP2 transcription factor, and SREPB2 inhibition attenuates lipid accumulation in ECs. Our findings reveal a mechanism through which fluoxetine-induced reprogramming of lipid metabolism in ECs can contribute to cardiovascular diseases.
Published in
Fluoxetine disrupts cholesterol metabolism in endothelial cells via SREBP2 activation
Oliveira F, Papa C, Hagemann T et al. · Translational psychiatry 2026 · PMID 42337263 · doi:10.1038/s41398-026-04197-x
This dataset
Open GSE304246 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 GSE304246_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 PRJNA1299477 and SRA study SRP605610. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42337263) ↗
Study design
4 × 24L012729_FO_Fluoxetine_i vs 4 × 24L012733_FO_Fluoxetine_i vs 4 × 24L012737_FO_Vehicle_i vs 4 × 24L012738_FO_Vehicle_i

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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
Datasets on a similar topic

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