Predicting the ferroptosis-associated gene targets in atherosclerosis by integrating GWAS and eQTL studies summary data

通过整合 GWAS 和 eQTL 研究汇总数据预测动脉粥样硬化中与铁死亡相关的基因靶点

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Abstract

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.

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