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

项目摘要 饮酒是心血管疾病（CVD）的一个重要的可改变的生活方式风险因素。进展 高通量技术的发展使得测量和分析各种“组学”，即DNA， 甲基化（甲基化组），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减少酒精消费和CVD的关系。在这份拨款申请中，我们将测试 饮酒改变不同“组学”维度的多个分子过程的假说 这些分子中间体介导了酒精对CVD的影响。 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特定目标。在目标1中，我们首先 鉴定酒精相关转录组标记。然后，我们将研究与酒精相关的 与CVD事件（致死性和非致死性冠心病和缺血性卒中）相关的转录组学标志物，以及 测试这些转录组标志物是否介导酒精摄入对CVD事件的影响。了建设一 多基因风险评分，以检查酒精摄入量、转录组学和遗传学之间的潜在因果关系。 标记物和意外心血管疾病我们还将进行双样本孟德尔随机化（MR）分析，以进一步 测试并量化因果关系。在目标2和3中，我们将确定酒精相关蛋白质组学（目标2） 和代谢组学（Aim 3）标记物，并将使用 类似于目标1中概述的方法。许多与酒精相关的DNA甲基化标志物已经被鉴定， 我们之前在13,000名参与者中进行的研究。因此，在目标4中，我们将研究酒精相关的关系， 使用目标1中概述的类似方法，使用发生CVD的DNA甲基化标志物。在目标5中，我们将 酒精相关的多组学标记物，以确定与酒精相关的关键途径和多组学模块。 酒精摄入量和心血管疾病。我们将进行随机森林分析，以确定其他与酒精相关的多- 组学标记。我们还将进行网络分析，以确定酒精相关的多组学模块 标记。我们将研究这些确定的多组学标记物与CVD事件之间的关系， 将使用生物信息学工具（例如，ENCODE，GTEx，人代谢组 数据库和UniProt）。随着该项目的完成，我们将重点关注这两个新的分子靶点 酒精相关的CVD风险预防和治疗。此外，我们将生成多组学生物标志物， 酒精摄入量数据库，并配有专门的软件，以方便今后调查酒精与 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.