The Joint Analysis of Multi-Omics Data Revealed the Methylation-Expression Regulations in Atrial Fibrillation
The Joint Analysis of Multi-Omics Data Revealed the Methylation-Expression Regulations in Atrial Fibrillation
复制标题
多组学数据联合分析揭示心房颤动的甲基化表达调控
DOI：
10.3389/fbioe.2020.00187
复制
发表时间：
2020-03-12
影响因子：
5.7
通讯作者：
Zhang, Yangyang
中科院分区：
文献类型：
--
作者：
Liu, Ban;Shi, Xin;Zhang, Yangyang
心房颤动（房颤）是最常见的心律失常之一。房颤的原因包括年龄、男性、糖尿病、高血压、瓣膜疾病和收缩/舒张功能障碍。但在分子水平上，其机制在很大程度上是未知的。本研究收集了10例持续性房颤患者、10例阵发性房颤患者和10例健康体检者，进行甲基化EPICBead芯片和RNA测序。通过使用基于机器学习的特征选择方法Boruta分析甲基化和基因表达数据，我们确定了与AF密切相关的关键基因，并发现了它们之间的相互联系。结果提示KIF 15甲基化可能调控PSMC 3、TINAG和NUDT 6的表达。这些发现可能有助于从多组学角度理解房颤的分子机制。
Atrial fibrillation (AF) is one of the most prevalent heart rhythm disorder. The causes of AF include age, male sex, diabetes, hypertension, valve disease, and systolic/diastolic dysfunction. But on molecular level, its mechanisms are largely unknown. In this study, we collected 10 patients with persistent atrial fibrillation, 10 patients with paroxymal atrial fibrillation and 10 healthy individuals and did Methylation EPICBead Chip and RNA sequencing. By analyzing the methylation and gene expression data using machine learning based feature selection method Boruta, we identified the key genes that were strongly associated with AF and found their interconnections. The results suggested that the methylation of KIF15 may regulate the expression of PSMC3, TINAG, and NUDT6. The identified AF associated methylation-expression regulations may help understand the molecular mechanisms of AF from a multi-omics perspective.