Trans-omic Analysis of Alcohol Consumption and its Relation to Cardiovascular Disease

项目总结 饮酒是心血管疾病(CVD)的一个重要的可改变的生活方式危险因素。预付款 高通量技术已经使测量和分析各种“组学”，即DNA成为可能 甲基化(甲基组)、基因表达(转录组)、蛋白质(蛋白质组)和代谢物(代谢组)， 以具有成本效益的方式与酒精消费和心血管疾病有关。在这项拨款建议中，我们将测试 假设饮酒改变了跨越不同“组学”维度的多个分子过程 这些分子中间体在酒精对心血管疾病的影响中起中介作用。 为了验证这一假设，我们将组建一个多学科团队来测试五个具体目标。在目标1中，我们将首先 识别与酒精相关的转录标记物。然后我们将研究与酒精相关的 与心血管疾病(致命性和非致命性冠心病和缺血性中风)相关的转录标记物 测试这些转录标记物是否在酒精摄入对心血管疾病事件的影响中起中介作用。我们将建造 多基因风险评分，以检查酒精摄入量、转录水平 标记物和事件心血管疾病。我们还将进行两样本孟德尔随机化(MR)分析，以进一步 测试并量化因果关系。在目标2和目标3中，我们将识别与酒精相关的蛋白质组(目标2) 和代谢(AIM 3)标记物，并将测试酒精、组学标记物和心血管疾病之间的关系 目标1中概述的类似方法。许多与酒精相关的DNA甲基化标记已被 我们之前在&gt；13,000名参与者中进行的研究。因此，在目标4中，我们将研究与酒精相关的 使用目标1中概述的类似方法将DNA甲基化标记与事件心血管疾病相关联。在目标5中，我们将整合 与酒精相关的多组学标记，用于识别与酒精相关的关键途径和多组学模块 酒精摄入和心血管疾病。我们将进行随机森林分析，以确定更多与酒精相关的 组学标记。我们还将进行网络分析，以确定与酒精相关的多重组学模块 记号笔。我们将研究这些已识别的多组学标记与心血管事件之间的关系，以及 将使用生物信息学工具(例如，ENCODE、GTEx、人类代谢组)对这些标记进行功能性注释 数据库和UniProt)。随着这个项目的完成，我们将重点介绍这两个新的分子靶标 预防和治疗与酒精相关的心血管疾病风险。此外，我们将产生一个多组学生物标记物 酒精摄入量数据库，配有量身定制的软件，以方便未来调查酒精与 其他非传染性疾病，如神经退行性疾病。

PROJECT SUMMARY Alcohol consumption is an important modifiable lifestyle risk factor for cardiovascular disease (CVD). Advances in high-throughput technologies have made it possible to measure and analyze a variety of ‘omics’, that is, DNA methylation (methylome), gene expression (transcriptome), protein (proteome) and metabolite (metabolome), in relation to alcohol consumption and CVD in a cost-efficient manner. In this grant proposal, we will test the hypothesis that alcohol consumption alters multiple molecular processes across different “omics” dimensions and these molecular intermediates mediate alcohol’s effects on CVD. To test this hypothesis, we will assemble a multidisciplinary team to test five Specific Aims. In Aim 1, we will first identify alcohol-associated transcriptomic markers. We will then examine the associations of alcohol-associated transcriptomic markers with incident CVD (fatal and nonfatal coronary heart disease and ischemic stroke), and test whether these transcriptomic markers mediate the effect of alcohol intake on incident CVD. We will construct polygenic risk scores to examine the potential causal relationships between alcohol intake, transcriptomic markers, and incident CVD. We will also conduct a two-sample Mendelian randomization (MR) analysis to further test and quantify the causal relationships. In Aims 2 and 3, we will identify alcohol-associated proteomic (Aim 2) and metabolomic (Aim 3) markers and will test the relationship between alcohol, omics markers and CVD using similar methods outlined in Aim 1. Many alcohol-associated DNA methylation markers have been identified by our prior study in >13,000 participants. Therefore, in Aim 4, we will examine the relations of alcohol-associated DNA methylation markers with incident CVD using similar methods outlined in Aim 1. In Aim 5, we will integrate alcohol-associated multi-omics markers to identify key pathways and multi-omics modules associated with alcohol intake and CVD. We will perform Random Forest analysis to identify additional alcohol-associated multi- omics markers. We will also perform network analyses to identify modules of alcohol-associated multi-omics markers. We will examine the relationships between these identified multi-omics markers with incident CVD, and will functionally annotate these markers using bioinformatics tools (e.g., ENCODE, GTEx, Human Metabolome Database, and UniProt). With the completion of this project, we will highlight the novel molecular targets for both alcohol-associated CVD risk prevention and treatment. In addition, we will generate a multi-omics biomarker database of alcohol intake with tailored software to facilitate the future investigations of alcohol’s relations with other non-communicable diseases such as neurodegenerative diseases.