基于生物信息学探讨与铜死亡相关的早、晚期动脉粥样硬化的差异基因及潜在标志物
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(1.山东中医药大学第一临床医学院,山东省济南市 250014;2.青岛大学附属青岛市海慈医院 (青岛市中医医院)神经内科,山东省青岛市 266033;3.青岛市黄岛区人民医院中医科,山东省青岛市 266499;4.青岛大学附属青岛市海慈医院(青岛市中医医院)病理科,山东省青岛市 266033)

作者简介:

房慧琴,硕士研究生,研究方向为中西医结合防治神经系统性疾病,E-mail:1261487064@qq.com。通信作者臧运华,博士,主任医师,研究方向为中西医结合防治神经系统性疾病,E-mail:1477817427@qq.com。

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基金项目:

山东省中医药科技发展计划项目(2019-0605);2018—2019年度青岛市中医药科研计划项目(2019-zyy015);青岛市2020年度医药科研指导计划项目(2020-WJZD226);2022年度医药卫生科研指导项目(2022-WJZD041)


Study on differential genes and potential biomarkers of early and advanced atherosclerosis related to cuproptosis based on bioinformatics
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1.The First Clinical Medical College of Shandong University of Traditional Chinese Medicine, Jinan, Shandong 250014, China;2.Department of Neurology, Qingdao Hiser Hospital Affiliated of Qingdao University (Qingdao Traditional Chinese Medicine Hospital), Qingdao, Shandong 266033, China;3.Department of Traditional Chinese Medicine, Qingdao Huangdao District People's Hospital, Qingdao, Shandong 266499, China;4.Department of Pathology, Qingdao Hiser Hospital Affiliated of Qingdao University (Qingdao Traditional Chinese Medicine Hospital), Qingdao, Shandong 266033, China)

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    目的]通过生物信息学的方法筛选出与铜死亡相关的早、晚期动脉粥样硬化的差异基因,探讨其作用机制,并预测其潜在标志物。 [方法]从GEO数据库中下载符合早、晚期动脉粥样硬化相关的信息(GSE28829和GSE43292数据集),进行标准化处理等,从文献中获得19个铜死亡相关基因,并对铜死亡相关基因进行差异分析、富集分析、共识聚类算法、主成分分析、免疫细胞浸润和筛选核心基因以找到其作用机制及潜在标志物。 [结果]最终筛选出10个铜死亡相关差异基因表达,铜死亡相关差异基因相关性分析显示GLS与DBT呈强正相关(r=0.78,P<0.001),NLRP3与DBT、GLS呈强负相关(r=-0.62,P<0.001);铜死亡相关差异基因的GO富集分析显示,主要与铜离子输运、铜离子稳态等过程有关,且KEGG分析显示主要富集在铂耐药性、矿物质吸收、癌症中的中心碳代谢通路上。通过MCODE插件筛选出核心基因SLC31A1、MTF1、ATP7B和ATP7A 4种;免疫细胞浸润以M2巨噬细胞、M0巨噬细胞、静息CD4+T细胞和CD8+T细胞为主(P<0.05);免疫细胞与铜死亡相关差异基因相关性分析显示,在动脉粥样硬化早期,GLS与激活NK细胞呈强正相关(r=0.52,P<0.001),FDX1、SLC31A1与CD8+T细胞呈强负相关(r=-0.51,P<0.001);在动脉粥样硬化晚期,FDX1与M0巨噬细胞呈强正相关(r=0.58,P<0.001),FDX1与CD8+T细胞呈强负相关(r=-0.55,P<0.001);主成分分析显示,根据铜死亡相关差异基因的表达可以明确区分出C1和C2两种亚型。 [结论]铜死亡与动脉粥样硬化发展之间的免疫相关变化很可能是诊治早、晚期动脉粥样硬化的关键,核心基因SLC31A1、MTF1、ATP7B和ATP7A可能是动脉粥样硬化发展的潜在标志物及治疗靶点。

    Abstract:

    Aim To screen the early and advanced atherosclerosis differential genes associated with cuproptosis by bioinformatic methods, and analyze their mechanisms of action, and predict potential biomarkers. Methods The information related to early and advanced atherosclerosis (GSE28829 and GSE43292 data sets) was downloaded from GEO database and standardized. 19 cuproptosis genes were obtained from the literature. Difference analysis, enrichment analysis, consensus clustering algorithm, principal component analysis, immune cell infiltration and screening core genes were used to find their action mechanisms and potential biomarkers. Results Finally, 10 differential genes related to cuproptosis were screened. The correlation analysis of differential genes related to cuproptosis showed a strong positive correlation between GLS and DBT (r=0.78, P<0.001), while NLRP3 showed a strong negative correlation with DBT and GLS (r=-0.62, P<0.001). GO enrichment analysis of differential genes related to cuproptosis was mainly related to copper ion transport and copper homeostasis, and KEGG analysis showed that it was mainly enriched in platinum resistance, mineral absorption and central carbon metabolic pathway in cancer. The PPI network analysis and MCODE were used to screen core genes. The results of immune cell infiltration showed that M2 macrophages, M0 macrophages, resting CD4 memory T cells, and CD8+T cells were dominant (P<0.05). The correlation analysis of differential genes related to immune cells and cuproptosis showed that in the early stage of atherosclerosis, GLS was strongly positively correlated with activated NK cells (r=0.52, P<0.001), FDX1 and SLC31A1 was strongestly negatively correlated with CD8+T cells (r=-0.51, P<0.001); in the advanced stage of atherosclerosis, FDX1 was strongestly positively correlated with M0 macrophages (r=0.58, P<0.001) and FDX1 was strongestly negatively correlated with CD8+T cells (r=-0.55, P<0.001). Principal component analysis showed that two subtypes C1 and C2 could be clearly distinguished according to the expression of cuproptosis-related differential genes. Conclusion The immune-related changes between cuproptosis and the development of atherosclerosis may be the key to the diagnosis and treatment of early and advanced atherosclerosis, and the core genes SLC31A1, MTF1, ATP7B and ATP7A may be potential markers and therapeutic targets for the development of atherosclerosis.

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房慧琴,马晓维,陈秋,崔淑菲,赵军绩,赵宗芹,臧运华.基于生物信息学探讨与铜死亡相关的早、晚期动脉粥样硬化的差异基因及潜在标志物[J].中国动脉硬化杂志,2023,31(11):938~944.

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  • 收稿日期:2023-03-02
  • 最后修改日期:2023-09-01
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  • 在线发布日期: 2023-12-05