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ORIGINAL RESEARCH article

Front. Immunol.

Sec. Inflammation

Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1642984

This article is part of the Research TopicCommunity Series in Crosstalk in Ferroptosis, Immunity & Inflammation: Volume IIView all 6 articles

Abnormal Lipid Metabolism and Atherosclerosis: A New Perspective on Organelle Function Regulation and Ferroptosis

Provisionally accepted
Xize  WuXize Wu1*Yuxi  HuangYuxi Huang1Jiaqi  RenJiaqi Ren1Pan  XuePan Xue2Qiuying  WuQiuying Wu1Qicheng  CaiQicheng Cai1Ruiyin  WangRuiyin Wang1Teng  FengTeng Feng1Shan  GaoShan Gao1Bo  WangBo Wang1Meijia  ChengMeijia Cheng1,3Yue  LiYue Li3*Lihong  GongLihong Gong3*
  • 1Liaoning University of Traditional Chinese Medicine, Shenyang, China
  • 2Dazhou Vocational College of Traditional Chinese Medicine, Dazhou, China
  • 3Liaoning University of Traditional Chinese Medicine Affiliated Hospital, Shenyang, China

The final, formatted version of the article will be published soon.

Background: Atherosclerosis (AS), characterized by lipid accumulation, contributes significantly to global cardiovascular morbidity. Ferroptosis, an iron-dependent form of cell death triggered by lipid peroxidation, is emerging as a critical player in AS progression. Therefore, our study seeks to elucidate the intricate mechanisms of ferroptosis within the lipid metabolism pathway in AS.Methods: Differentially expressed genes were identified from the GSE100927 dataset, subsequently isolating AS lipid metabolism-related ferroptosis genes (ASLMRFeGs). Unsupervised cluster analysis was performed on AS samples to identify molecular clusters. WGCNA was performed to uncover module Hub genes. Multiple machine learning models (LASSO, SVM-RFE, RF) were applied to screen Hub genes. Experimental validation was performed by ox-LDL-induced HUVECs and RAW 264.7 cells. Single-cell data analyzes the gene structure and gene expression status of individual cells.Results: Six ASLMRFeGs (CTSB, CYBB, DPP4, HILPDA, HMOX1, IL1B) alter the immune microenvironment in AS. AS samples were stratified into two molecular clusters, exhibiting significant variations in inflammation and immune responses. Enrichment analysis of the 225 module Hub genes showed close association with inflammation, immune responses, cytoskeleton organization, and various organelles. Machine learning identified four candidate Hub genes (TYROBP, CSF1R, LCP2, C1QA). In vitro experiments showed that dysregulated lipid metabolism promotes ferroptosis, and inhibition of ferroptosis improves mitochondrial and lysosomal dysfunction and suppresses endoplasmic reticulum stress. Ferrostatin-1, an ferroptosis inhibitor, attenuated the ox-LDLinduced upregulation of CYBB, HMOX1, IL1B, TYROBP, and CSF1R genes. A nomogram for predicting AS risk was constructed incorporating the expression levels of these five validated Hub genes. Single-cell data analysis results suggested that these genes were highly expressed in foam cells, inflammatory macrophages, smooth muscle cells, and helper T cells.In AS, abnormal lipid metabolism may drive ferroptosis via key regulatory genes (CYBB, HMOX1, IL1B, TYROBP, CSF1R), while also reshaping the immune microenvironment, potentially through the modulation of organelle function.

Keywords: Atherosclerosis, ferroptosis, bioinformatics, machine learning, mitochondrion, Lysosome

Received: 07 Jun 2025; Accepted: 29 Jul 2025.

Copyright: © 2025 Wu, Huang, Ren, Xue, Wu, Cai, Wang, Feng, Gao, Wang, Cheng, Li and Gong. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Xize Wu, Liaoning University of Traditional Chinese Medicine, Shenyang, China
Yue Li, Liaoning University of Traditional Chinese Medicine Affiliated Hospital, Shenyang, China
Lihong Gong, Liaoning University of Traditional Chinese Medicine Affiliated Hospital, Shenyang, China

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