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3-Hydroxystearic acid promotes cholesterol efflux and attenuates atherosclerosis via the ALKBH5/PAX-8/ABCA1 pathway

GSE317586 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 2 samples Submitted 2026/02/18 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 2 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Samples
2 samples
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
3-Hydroxystearic acid promotes cholesterol efflux and attenuates atherosclerosis via the ALKBH5/PAX-8/ABCA1 pathwayFrontiers in immunology · 2026
Summary (written by the submitters)
Introduction: Atherosclerosis can trigger various cardiovascular and cerebrovascular diseases with complex pathogenesis. Macrophage proliferation, inflammatory responses, and lipid phagocytosis, which induce foam cell formation and accumulation, are critical in the development of early atherosclerotic lesions. The role of 3-Hydroxystearic acid (C18-3OH), a recently identified gut microbiota-derived metabolite, in atherosclerosis has not yet been clarified.
Read the full summary ↓
This study aimed to investigate the role of the ALKBH5/PAX-8/ABCA1 pathway in C18-3OH-mediated regulation of macrophage cholesterol efflux and atherosclerosis and explore novel mechanisms of ABCA1 regulation from the perspective of m6A modification. Methods: RT-qPCR and Western blotting were used to detect gene and protein expression, respectively. ChIP-Seq was used to screen PAX-8 target genes, and ChIP-qPCR was used to validate PAX-8 binding to ABCA1. The SRAMP platform was used to predict m6A modification sites in PAX-8 mRNA sequences. Methylated RNA immunoprecipitation-qPCR (MeRIP-qPCR) was used to measure m6A modification levels of PAX-8 mRNA in foam cells. UHPLC-OEMS untargeted metabolomics were used to analyze differential fatty acid metabolites in an atherosclerotic mouse model. Specific kits were used to detect serum liver function markers (aspartate transaminase, AST; alanine aminotransferase, ALT), renal function markers (serum creatinine, Scr; blood urea nitrogen, BUN), and lipid profiles (HDL-C, TG, LDL-C, TC). Aortic sinus sections were prepared, and H&E, Oil Red O, and Masson staining were used to evaluate atherosclerotic plaques. Results: The results demonstrated that C18-3OH promoted cholesterol efflux in foam cells and alleviated lipid accumulation by upregulating ABCA1 expression. C18-3OH inhibited ALKBH5, increased PAX-8 mRNA m6A modification and PAX-8 expression, and upregulated ABCA1 to enhance cholesterol efflux. Serum metabolomics revealed reduced C18-3OH levels in high-fat diet-fed apoE-/- atherosclerotic mice. C18-3OH suppressed aortic ALKBH5 expression, elevated m6A modification of PAX-8 mRNA, and increased PAX-8 and ABCA1 expression. Furthermore, C18-3OH improved lipid metabolism and reduced the atherosclerotic plaque area in apoE-/- mice. Discussion: This study clarifies the impact and mechanisms of gut microbiota-derived C18-3OH on atherosclerosis progression, providing novel strategies for the precise prevention and treatment of atherosclerosis.
Published in
3-Hydroxystearic acid promotes cholesterol efflux and attenuates atherosclerosis via the ALKBH5/PAX-8/ABCA1 pathway
Zhou QY, Liu W, Zhao ZW et al. · Frontiers in immunology 2026 · PMID 41694370 · doi:10.3389/fimmu.2026.1750021
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 GSE317586_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1414503 and SRA study SRP666448. Searching any of these in the dataset finder brings you back here.

Samples in this study

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