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使用机器学习和生物信息学识别的冠状动脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉静脉

Ming Shen^1,2, Meixian Chen³, Yu Chen⁴

¹Department of Cardiology, the 926th Hospital of the Joint Logistic Support Force of PLA, Affiliated Hospital of Kunming University of Science and Technology, Kaiyuan, 661600, Yunnan, China. Dr_shenming@163.com.

Scientific reports

|October 15, 2024

概括

研究人员确定了LRRK2和ANKRD13A作为关键的线粒细胞衰变相关的生物标志物,用于静脉静脉阻塞 (ISR),这是冠状动脉疾病治疗的并发症. 这些发现为早期诊断和精准医学方法提供了新的途径,以提高治疗效率.

科学领域:

心血管生物学心血管生物学
分子医学是分子医学.
基因组学就是基因组学.

背景情况:

穿皮冠状动脉干预 (PCI) 与支架植入是冠状动脉疾病 (CAD) 的首要治疗方法.
静脉静脉复缩 (ISR) 仍然是一个显著的限制,降低了PCI的长期有效性.
对于血管健康至关重要的线粒细胞衰竭在ISR病变发生过程中的作用尚不清楚.

研究的目的:

为了确定ISR.的菌相关生物标志物.
阐明基因菌参与ISR的基础分子机制.
探索ISR的潜在治疗策略.

主要方法:

差异基因表达分析确定了169个差异表达基因 (DEG).
与线粒细胞相关基因 (MRG) 的交叉产生了23个不同表达的线粒细胞相关基因 (DEMRG).
权重基因共同表达网络分析 (WGCNA) 和机器学习算法 (Logistic-LASSO,RF,SVM-RFE) 确定了LRRK2和ANKRD13A作为关键生物标志物.

主要成果:

确定了LRRK2和ANKRD13A作为ISR.ISR.的强大的菌相关生物标志物.
结合这些基因的诺莫图显示出对ISR的有希望的诊断准确性.
基因组丰富分析 (GSEA) 和免疫透分析揭示了这些生物标志物与ISR中的免疫/炎症反应之间的关联.

结论:

LRRK2和ANKRD13A是ISR.的重要菌相关生物标志物.
这些生物标志物与ISR中的免疫和炎症过程有关.
这项研究为早期ISR诊断和个性化治疗干预提供了新的见解.

关键词:

生物标志物生物标志物冠状动脉疾病是一种冠状动脉疾病.免疫系统的透.实体静脉复缩 (英语:In-stent restenosis) 是一种体内静脉复缩.机器学习是机器学习.线粒细胞衰变 (mitophagy) 是一种

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