Li Hong, Xu Yongyun, Wang Aiting, Zhao Chuanxin, Zheng Man, Xiang Chunyan
Dongying People's Hospital (Dongying Hospital of Shandong Provincial Hospital Group), Dongying, 257091, Shandong, People's Republic of China.
J Cardiothorac Surg. 2025 Jan 17;20(1):70. doi: 10.1186/s13019-024-03199-4.
Atherosclerosis (AS) is increasingly recognized as a chronic inflammatory disease that significantly compromises vascular health and acts as a major contributor to cardiovascular diseases. Advancements in lipidomics and metabolomics have unveiled the complex role of fatty acid metabolism (FAM) in both healthy and pathological states. However, the specific roles of fatty acid metabolism-related genes (FAMGs) in shaping therapeutic approaches, especially in AS, remain largely unexplored and are a subject of ongoing research.
This study employed advanced bioinformatics techniques to identify and validate FAMGs associated with AS. We conducted differential expression analysis on a select list of 49 candidate FAMGs. GSEA and GSVA were utilized to elucidate the potential biological roles and pathways of these FAMGs. Subsequently, Lasso regression and SVM-RFE were applied to identify key hub genes and assess the diagnostic efficacy of seven FAMGs in distinguishing AS. The study also explored the correlation between these hub FAMGs and clinical features of AS. Validation of the expression levels of the seven FAMGs was performed using datasets GSE43292 and GSE9820.
The study pinpointed seven FAMGs with a close association to AS: ACSBG2, ELOVL4, ACSL3, CPT2, ALDH2, HSD17B10, and CPT1B. Analysis of their biological functions underscored their significant involvement in critical processes such as fatty acid metabolism, small molecule catabolism, and nucleoside bisphosphate metabolism. The diagnostic potential of these seven FAMGs in AS differentiation showed promising results.
This research has successfully identified seven key FAMGs implicated in AS, offering novel insights into the pathophysiology of the disease. These findings not only contribute to our understanding of AS but also present potential biomarkers for the disease, opening avenues for more effective monitoring and progression tracking of AS.
动脉粥样硬化（AS）日益被认为是一种慢性炎症性疾病，它严重损害血管健康，是心血管疾病的主要促成因素。脂质组学和代谢组学的进展揭示了脂肪酸代谢（FAM）在健康和病理状态下的复杂作用。然而，脂肪酸代谢相关基因（FAMGs）在制定治疗方法，尤其是在AS治疗方法中的具体作用，在很大程度上仍未得到探索，是正在进行的研究课题。
本研究采用先进的生物信息学技术来识别和验证与AS相关的FAMGs。我们对49个候选FAMGs的选定列表进行了差异表达分析。利用基因集富集分析（GSEA）和基因集变异分析（GSVA）来阐明这些FAMGs的潜在生物学作用和途径。随后，应用套索回归和支持向量机递归特征消除（SVM-RFE）来识别关键枢纽基因，并评估7个FAMGs在区分AS方面的诊断效能。该研究还探讨了这些枢纽FAMGs与AS临床特征之间的相关性。使用数据集GSE43292和GSE9820对7个FAMGs的表达水平进行了验证。
该研究确定了7个与AS密切相关的FAMGs：ACSBG2、ELOVL4、ACSL3、CPT2、ALDH2、HSD17B10和CPT1B。对它们生物学功能的分析强调了它们在脂肪酸代谢、小分子分解代谢和核苷二磷酸代谢等关键过程中的显著参与。这7个FAMGs在AS鉴别中的诊断潜力显示出有前景的结果。
本研究成功识别了7个与AS相关的关键FAMGs，为该疾病的病理生理学提供了新的见解。这些发现不仅有助于我们对AS的理解，还为该疾病提供了潜在的生物标志物，为更有效地监测和追踪AS的进展开辟了途径。
