Screening and comprehensive analysis of endoplasmic reticulum stress-related biomarkers in atherosclerosis

Xiaomeng Qu, Yiming Shao, Han Li, Yuhan Bao, Zhen Sun and Shuhua Yu

PLOS ONE, 2026, vol. 21, issue 6, 1-17

Abstract: Atherosclerosis (AS) is a chronic inflammatory vascular disorder in which endoplasmic reticulum stress (ERS) plays a crucial regulatory role. However, the biological and translational relevance of ERS-related gene networks in AS remains largely unexplored. This study aimed to identify a robust ERS-related gene signature for AS. We integrated multiple GEO datasets and applied machine learning algorithms, including least absolute shrinkage and selection operator (LASSO) regression, support vector machine-recursive feature elimination (SVM-RFE), and random forest (RF). Five ERS-related signature genes (TRIM25, CYBB, CYBA, MYOC, and PRKAA2) were identified and showed favorable discriminatory performance in the integrated discovery cohort (combined AUC = 0.946). The expression patterns of these genes were further examined at both the mRNA and protein levels by quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting (WB) in an oxidized low-density lipoprotein (ox-LDL)-induced endothelial injury model. Gene set enrichment analysis and immune infiltration analysis indicated that the identified genes were primarily involved in oxidative stress and immune-related pathways. Collectively, this study identifies a machine learning–derived ERS gene signature associated with AS. These findings improve our understanding of ERS-related vascular injury in AS and provide candidate biomarkers for further tissue-level and mechanistic validation.

Date: 2026
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0350047 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 50047&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0350047

DOI: 10.1371/journal.pone.0350047

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().