基于生物信息学方法对扩张型心肌病患者中衰老相关基因的综合分析

目的利用生物信息学方法综合分析扩张型心肌病(DCM)患者中衰老相关基因。方法从CellAge数据库提取衰老细胞相关基因,GEO数据库中与DCM相关的数据集GSE19303、GSE17800和GSE42955,然后利用R语言鉴定出GSE19303和GSE17800的差异表达基因。从衰老相关基因和差异表达基因中选择的差异表达衰老相关基因(DESRGs)通过GO、KEGG和PPI网络进行分析,基因表达和ROC曲线筛选诊断基因,构建诊断基因的miRNA-基因网络。结果共验证出10个DESRGs,即LSAMP、RMI2、EMILIN1、CERCAM、MAP3K7CL、CNN1、MMP3、UCHL1、PLK4、APEX2,经GO分析上述差异基因的生物学过程主要集中在胶原代谢过程、细胞成分生物发生的正调控、丝裂原激活蛋白激酶级联的负调控的生物学过程和通路中。GSE17800和GSE42955数据集DCM组与对照组DESRGs表达水平除MAP3K7CL、MMP3、UCHL1、APEX2外,其余6个DESRGs差异均有统计学意义(P<0.05)。ROC分析显示GSE17800所有DESRGs基因的AUC均大于0.65,其中RMI2(AUC=0.916,95%CI=0.832~0.977)的诊断价值最高,其次是PLK4(AUC=0.850,95%CI=0.683~0.961)。在GSE42955验证集ROC分析结果发现,除CERCAM外,其余DESRGs基因的AUC均大于0.65,其中RMI2(AUC=0.917,95%CI=0.781~0.986)的诊断价值最高,其次是PLK4(AUC=0.833,95%CI=0.591~0.964)。以AUC>0.8为标准选择诊断基因,训练集和验证集中重叠的诊断基因有:RMI2和PLK4,具有较高的诊断价值。结论LSAMP、RMI2、EMILIN1、CERCAM、MAP3K7CL、CNN1、UCHL1、PLK4、APEX2等DESRGs可能参与了DCM的发生发展,RMI2和PLK4为DCM的潜在特异性生物标志物。

Impact of miRNAs on cardiovascular aging

Aging is a multidimensional process that leads to an increased risk of developing severe diseases, such as cancer and cardiovascular, neurodegenerative, and immunological diseases. Recently, small non-coding RNAs known as microRNAs （miRNAs） have been shown to regulate gene expression, which contributes to many physiological and pathophysiological processes in humans. Increasing evidence suggests that changes in miRNA expression profiles contribute to cellular senescence, aging and aging-related diseases. However, only a few miRNAs whose functions have been elucidated have been associated with aging and/or aging-related diseases. This article reviews the currently available findings regarding the roles of aging-related miRNAs, with a focus on cardiac and cardiovascular aging.