临床与病理杂志2024，Vol.44Issue(2)：147-156,10.DOI:10.11817/j.issn.2095-6959.2024.230614
整合生物信息学和机器学习方法探究肥厚型心肌病自噬相关机制及鉴定潜在的关键基因
Integrating bioinformatics and machine learning methods to investigate autophagy-related mechanisms and identify potential key genes in hypertrophic cardiomyopathy
摘要
Abstract
Objective:Dysregulation of autophagy is closely associated with hypertrophic cardiomyopathy(HCM),yet its specific mechanisms remain unclear.This study aims to investigate the autophagy-related mechanisms in HCM and identify potential key genes. Methods:Transcriptomic data of myocardial tissues from HCM patients and healthy controls(HC)were analyzed using bioinformatics,including the identification and enrichment analysis of autophagy-related differentially expressed genes(DEGs).Key genes were selected using the least absolute shrinkage and selection operator(LASSO)regression model and support vector machine recursive feature elimination(SVM-RFE)analysis.The expression of key genes was validated using external datasets.Receiver operator characteristic(ROC)curve analysis was performed to evaluate the diagnostic performance of the key genes. Results:By comparing the transcriptomic data of HCM patients with HCs and intersecting with autophagy-related genes,12 autophagy-related DEGs were identified.Enrichment analyses indicated that these genes were mainly involved in pathways such as gastrin signaling,galanin receptor signaling,protein interaction database entries for interleukin-6 and interleukin-7 signaling pathways,protein interaction database activated protein 1 signaling,non-genomic actions of 1,25-dihydroxyvitamin D3,and apoptosis.Six candidate key genes were screened,PRKCD,MYC,DDIT3,CAPN1,HGS,and TMEM74.PRKCD,MYC,and DDIT3 were successfully validated in the external dataset and exhibited good diagnostic performances. Conclusion:PRKCD,MYC,and DDIT3 may serve as key genes associated with autophagy in HCM.关键词
肥厚型心肌病/生物信息学/机器学习/差异表达基因/自噬/关键基因Key words
hypertrophic cardiomyopathy/bioinformatics/machine learning/differentially expressed genes/autophagy/key genes引用本文复制引用
尤红俊,苟棋玲,董梦雅,赵倩倩,常凤军..整合生物信息学和机器学习方法探究肥厚型心肌病自噬相关机制及鉴定潜在的关键基因[J].临床与病理杂志,2024,44(2):147-156,10.基金项目
陕西省人民医院科技发展孵化基金(2023YJY-63).This work was supported by the Science and Technology Development Incubation Fund of Shaanxi Provincial People's Hospital,China(2023YJY-63). （2023YJY-63）
