首页|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

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

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原文链接
  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
目的:自噬调节异常与肥厚型心肌病(hypertrophic cardiomyopathy,HCM)密切相关,然而其具体机制仍未阐明.本研究拟探究HCM自噬相关机制及鉴定潜在的关键基因.方法:对HCM患者和健康对照者(healthy controls,HC)的心肌组织转录谱数据进行生物信息学分析,包括自噬相关差异表达基因(differentially expressed genes,DEGs)的鉴定和富集分析,利用最小绝对收缩和选择算子(least absolute shrinkage and selection operator,LASSO)回归模型和支持向量机递归特征消除(support vector machine recursive feature elimination,SVM-RFE)分析来筛选关键基因.外部数据集验证关键基因的表达.绘制受试者操作特征(receiver operator characteristic,ROC)曲线评估关键基因的诊断效能.结果:通过比较HCM患者和HC的转录谱数据,并与自噬相关基因取交集,筛选出12个自噬相关DEGs.富集分析表明这些基因主要参与胃泌素信号通路、甘丙肽受体通路、蛋白质相互作用数据库中的白细胞介素-6和白细胞介素-7信号通路、蛋白质相互作用数据库中的激活蛋白1信号通路、1,25-二羟基维生素D3的非基因组作用和凋亡等.筛选出6个候选关键基因,即PRKCD、MYC、DDIT3、CAPN1、HGS和TMEM74.PRKCD、MYC和DDIT3在验证数据集中成功验证,且具备较好的诊断效能.结论:PRKCD、MYC和DDIT3可能是HCM自噬相关的关键基因.
Integrating bioinformatics and machine learning methods to investigate autophagy-related mechanisms and identify potential key genes in hypertrophic cardiomyopathy
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.

hypertrophic cardiomyopathybioinformaticsmachine learningdifferentially expressed genesautophagykey genes

尤红俊、苟棋玲、董梦雅、赵倩倩、常凤军

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陕西省人民医院心血管内科,西安 710068

西安国际医学中心医院心肺康复科,西安 710100

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

陕西省人民医院科技发展孵化基金Science and Technology Development Incubation Fund of Shaanxi Provincial People's Hospital,China

2023YJY-632023YJY-63

2024

10.11817/j.issn.2095-6959.2024.230614

临床与病理杂志
中南大学

临床与病理杂志

CSTPCD
影响因子：0.559
ISSN：1673-2588
年,卷(期)：2024.44(2)
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