Li Juan, Nong Jiao, Huang Xiao Yan, Liu Qian, Liu Yuan Yuan, Sun Ji Chao, Zhu Wan Qing, Xie Sheng
Guangxi University of Chinese Medicine, Nanning, China.
First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning, China.
Medicine (Baltimore). 2025 Jun 13;104(24):e42846. doi: 10.1097/MD.0000000000042846.
Atherosclerosis is a chronic, low-grade inflammatory disease affecting the arteries, which causes cardiovascular disease by narrowing the patient's arterial blood vessels, and is currently the number 1 disease killer in the United States. Nevertheless, developing new animal model approaches and novel therapeutic strategies requires time to treat affected individuals who do not benefit from statins. However, the exact mechanism behind AS pathology is still unknown. Mendelian Randomization based on summary data, Bayesian co-localization methods, and bioinformatics analyses were conducted for the integration of genome-wide association studies summary-level data on AS, expression quantitative trait locus (eQTL) study, and the FerrDb database related to the ferroptosis-associated genes in blood. The study exploited the eQTL data, which were obtained from 31,684 participants of mostly European ancestry from the eQTLGen consortium, the genome-wide association studies data from the FinnGen project (data freeze 10), included 51,589 AS cases and 343,079 controls. ATG7, SREBF1, GLRX5, and SRSF9 were found to be associated with ferroptosis-related gene targets in AS, as revealed by summary-data-based Mendelian randomization analysis. ATG7 and SREBF1 genes and the trait of atherosclerosis were influenced strongly by shared causal variation and co-localized as suggested by the co-localization analysis. Enrichment analysis was showed that these genes might be responsible to involved in the autophagy-related biological pathways and ferroptosis. Four key genes associated with ferroptosis in atherosclerosis were identified and can serve as the potential biomarkers for ferroptosis-associated pathways for the disease diagnostic and therapeutic purposes. There is a need to conduct further functional investigations in the future.
动脉粥样硬化是一种影响动脉的慢性、低度炎症性疾病，它通过使患者动脉血管变窄而导致心血管疾病，目前是美国头号疾病杀手。然而，开发新的动物模型方法和新颖的治疗策略需要时间来治疗那些无法从他汀类药物中获益的患者。然而，动脉粥样硬化病理背后的确切机制仍然未知。基于汇总数据的孟德尔随机化、贝叶斯共定位方法以及生物信息学分析被用于整合全基因组关联研究关于动脉粥样硬化的汇总水平数据、表达定量性状位点（eQTL）研究以及与血液中与铁死亡相关基因的FerrDb数据库。该研究利用了eQTL数据，这些数据来自eQTLGen联盟中主要为欧洲血统的31684名参与者，以及来自芬兰基因组计划（数据冻结版本10）的全基因组关联研究数据，其中包括51589例动脉粥样硬化病例和343079例对照。基于汇总数据的孟德尔随机化分析显示，ATG7、SREBF1、GLRX5和SRSF9与动脉粥样硬化中与铁死亡相关的基因靶点有关。共定位分析表明，ATG7和SREBF1基因与动脉粥样硬化性状受到共同因果变异的强烈影响且共定位。富集分析表明，这些基因可能参与自噬相关的生物学途径和铁死亡。确定了与动脉粥样硬化中铁死亡相关的四个关键基因，它们可作为该疾病诊断和治疗目的的铁死亡相关途径的潜在生物标志物。未来有必要进行进一步的功能研究。
