ORIGINAL RESEARCH article
Front. Cardiovasc. Med.
Sec. Atherosclerosis and Vascular Medicine
Volume 12 - 2025 | doi: 10.3389/fcvm.2025.1600321
An oxidative stress-related molecular signature in atherosclerosis: identification of risk genes, construction of a diagnostic model, and characterization of immunocyte landscape
Provisionally accepted
- Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China
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Atherosclerosis (AS), the main reason for cardiovascular disorders and stroke, is a complex, multifactorial disease. Numerous studies have shown that oxidative stress and circadian disruption are paramount causes of the development of AS and its complications. Nevertheless, there is no applicable related diagnostic model to assess the AS clinical risk according to patients' oxidative stress status and circadian rhythm molecules expression. This study aimed to conduct an oxidative stress-circadian rhythm-related model in AS cohort (GSE100927 and GSE43292), which could reveal the potential relation between AS and oxidative stress with circadian rhythm. We screened the significant oxidative stress-circadian rhythm-related genes in AS samples by integrating two datasets by various machine learning methods. Then, we conducted an oxidative stress-circadian rhythm-related diagnostic model based on 6 risk genes (IL1RN、CA2、PDE8B、RYR2、DPP4、TDO2) identified through LASSO regression analysis and a nomogram diagram. Calibration and decision curve analysis (DCA) showed the relevant accuracy of the risk model. Receiver operating characteristic curve (ROC) delineated the higher reliability of our model than each single risk gene diagnostic model. Then, we verified the accuracy of our model in the validation dataset (GSE27034). Latent regulatory networks (including miRNA, transcription factor, and small molecule compound) regarding risk genes were also constructed by ENCORO, ChIPBase, and CTD databases. We observed a worse immune infiltration degree in a high-risk group of AS samples than that in a low-risk group based on the linear predictor derived from our Logistic model. Finally, we clustered the AS samples into two subtypes by risk genes expression pattern, and interestingly, we also illustrated the obvious discrepancy of immune cells infiltration between the two different subtypes.
Keywords: oxidative stress, circadian rhythm, atherosclerosis, risk model, immune infiltration Abbreviations operating characteristic curve, ROC, Differentially expressed genes, DEGs, Gene Ontology, GO, Kyoto Encyclopedia of Genes and Genomes, KEGG, gene set enrichment analysis, GSEA, low-density lipoprotein cholesterol, LDL, hydrogen peroxide, H2O2, matrix metalloproteinases, MMP
Received: 26 Mar 2025; Accepted: 05 Jun 2025.
Copyright: © 2025 Li, Ling, Wei, Tang, Zhang and Huang. 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: Zhaohe Huang, Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China
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