Eukaryotic Reference-based RNA Sequencing of MAEC stimulated by LPS and overexpressing PCSK9
Source: CNGBdb Project (ID CNP0009248)
Source: CNGBdb Project (ID CNP0009248)
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Description: Research Objectives
Vascular endothelial dysfunction serves as a critical initiator of atherosclerosis, with lipopolysaccharide (LPS)-induced inflammation playing a pivotal role in endothelial injury. While the lipid-lowering effects of Proprotein Convertase Subtilisin/Kexin type 9 (PCSK9) are well established, its direct mechanisms in regulating vascular inflammation and endothelial function remain elusive. This study aims to systematically investigate the molecular regulatory network of PCSK9 in endothelial inflammatory injury using a Mouse Aortic Endothelial Cell (MAEC) model. An in vitro model was established combining LPS stimulation with PCSK9 overexpression, followed by high-throughput eukaryotic reference transcriptome sequencing.
Results
MAECs were stimulated with LPS to mimic an inflammatory microenvironment and transfected with a PCSK9 overexpression plasmid to modulate expression levels. Total RNA was subsequently extracted for transcriptome sequencing and bioinformatic analysis to identify differentially expressed genes (DEGs) and enriched pathways. The results indicate that PCSK9 expression levels significantly influence the characteristics of LPS-induced inflammatory responses in endothelial cells.
Conclusions and Significance
The core conclusion of this study is that PCSK9 overexpression not only exacerbates LPS-induced endothelial inflammatory injury but also compromises endothelial barrier stability by suppressing extracellular matrix (ECM)-related signaling pathways. This finding reveals a novel mechanism by which PCSK9 promotes endothelial inflammatory injury at the transcriptome level, suggesting that beyond lipid metabolism, PCSK9 directly participates in regulating ECM homeostasis. These results provide critical experimental evidence for a deeper understanding of the "non-lipid-lowering" effects of PCSK9 in cardiovascular disease.
Data type: Transcriptome or Gene expression
Sample scope: Monoisolate
Relevance: Medical
Submitter: 方荣沣(Rongfeng Fang); 内蒙古医科大学
Release date: 2026-03-31
Last updated: 2026-03-31
DOI: 10.26036/CNP0009248
Data size: 49.21GB
