基于基因调控网络的心肌梗死相关分子协同调控模式的研究

Myocardial infarction is one of the most serious types of coronary heart disease, which is a complex disease that affected by multiple factors. Myocardial infarction brings serious psychological and economic burdens for patients and society because of its higher mortality and morbidity. Although there are many studies on the molecular mechanism of myocardial infarction, most of them are focused on a single gene level. Based on the previous studies, the project will integrate molecular expression profiles and the regulatory relationships among molecules that associated with myocardial infarction on a large scale. We aim to systematically construct a gene regulatory network and a dynamic gene regulatory network for myocardial infarction on the genome-wide scale, and the gene regulatory networks include four types of nodes including mRNA, miRNA, transcription factor and lncRNA. Then, we will identify the regulators and synergistic regulatory modules that might play important roles in myocardial infarction, and build the pathway model for synergistic regulatory molecules. In this way, we systematically analyze the potential synergistic regulatory mechanisms and the regulatory dynamics underlying myocardial infarction. At the same time, we will identify some diagnostic and prognostic markers for myocardial infarction that combined with multiple genes. Finally, we will confirm the results by applying biological experiments to the diagnostic and prognostic markers. The completion of the project will bring new perspectives for further understanding the regulation mechanisms of myocardial infarction, and provide theoretical and experiment basis for early diagnosis, prognosis and targeted therapy.

心肌梗死是冠心病最严重的类型之一，是受多因素影响的复杂疾病，因其高发病率和死亡率，为患者和社会带来严重的心理负担和经济负担。对于其分子机制的研究尽管较多，但主要集中于单基因水平。本项目在前期研究工作基础上，首先大规模整合心肌梗死相关分子表达谱及多种分子间的调控互作信息，系统构建全基因组水平包括mRNA、miRNA、转录因子、lncRNA在内的心肌梗死基因调控网络及动态基因调控网络。其次挖掘心肌梗死中核心调控子及协同调控模块，构建多种分子协同调控的通路模型，系统分析心肌梗死相关分子协同调控的潜在机制及其调控的动态性，同时识别心肌梗死多基因联合诊断及预后的标记。最后，运用生物学实验对潜在的诊断及预后标记进行证实。本课题的完成将为深入理解心肌梗死发生发展的分子机制提供新的视角，为心肌梗死患者进行早期诊断、预后评估、靶向治疗提供理论基础和实验依据。

本项目按原计划完成。心肌梗死是冠心病最严重的类型之一，是受多因素影响的复杂疾病，因其高发病率和死亡率，为患者和社会带来严重的心理负担和经济负担。对于其分子机制的研究尽管较多，但主要集中于单基因水平。在本项目的研究过程中，我们整合miRNA-TF共调控网络及外周血单核细胞的时间序列RNA表达数据，构建了心肌梗死进展过程中(心肌梗死发生后1天，4-6天及6个月)动态的miRNA-TF共调控网络，并研究了心肌梗死进展过程中分子协同调控的动态特征，识别了心肌梗死诊断及复发的miRNA及TF生物标记；我们开发了一个计算流程，系统整合心肌梗死相关的lncRNA与mRNA表达谱数据以及miRNA-target互作数据，基于ceRNA调控机制，构建心肌梗死发生与复发相关的lncRNA-mRNA调控网络，识别了心肌梗死发生与复发的lncRNA诊断标记。同时拓展我们的工作：以肥厚型心肌病为模型开发新的识别失调的miRNA-TF前馈环的新方法；提出新的生物信息学方法预测疾病/心肌梗死相关的miRNA及lncRNA；整合药物副作用网络及蛋白质互作网络预测心肌梗死药物副作用相关的蛋白。本课题的完成将为深入理解心肌梗死发生发展的分子机制提供新的视角，为心肌梗死患者进行早期诊断、预后评估、靶向治疗提供理论基础和实验依据。本项目的研究共发表外文期刊论文7篇，其中SCI收录论文6篇，分别发表在《Journal of Cellular and Molecular Medicine》、《Briefings in Bioinformatics》、《Scientific Reports》、《Plos One》等杂志上。