TOPMed Omics of Cardiovascular Disease in Diabetes

项目概要/摘要 血液组学生物标志物，包括全基因组序列（WGS）、全血甲基化（通过 测序或微阵列），转录（使用RNA-seq），蛋白质组学（SomaLogic适体）和 代谢组学（液相色谱/质谱）已经确定了心血管疾病的新途径， 疾病（CVD：冠心病（CHD）和卒中;亚临床动脉粥样硬化：冠状动脉粥样硬化 动脉钙（CAC）和颈动脉斑块和内膜-中层厚度（cIMT））。个别的，但特别是 在多维网络框架中，NHLBI Trans-Omics for Precision中的组学数据 医学（TOPMed）研究准备解决生物医学中的主要问题。在这个应用程序中，我们专注于 2型糖尿病（T2 D）CVD的多组学研究。T2 D是全球范围内日益严重的祸害， CVD的全球流行病。CVD事件在T2 D患者中的发生频率是T2 D患者的两倍多。的原因 对于这种持续的过度风险仍然未知，但可能涉及多个omic的扰动 从遗传变异到连接胰岛素抵抗、内皮功能障碍和 动脉粥样硬化阐明T2 D中CVD的生物学基础提供了一个明确的机会，可以阻止全球性 心血管疾病的浪潮。我们提出三个目标。在目标1中，我们将分析来自23，903份WGS数据的遗传变异， 来自5个祖先群体的T2 D患者，来自28个队列（11个纵向队列）， 年龄，包括15例普遍CVD和11例亚临床动脉粥样硬化的措施。我们联系了 WGS数据到不同的注释资源（例如ENCODE）。我们有临床协变量，包括T2 D的年龄 代谢控制的开始和水平，以及对意外CVD事件的纵向随访。常见问题分析 和罕见的变异将阐明已知的候选CVD-T2 D基因座并导致新的发现。复制是 在来自5个生物库的> 220，000个不同血统的T2 D个体中可用。经确认的变体将用于 因果关系和多基因评分的孟德尔随机化检验用于预测。在第二章中，我们将分析 血液组学生物标志物，由目标1与T2 D中CVD的基因组关联指导。TOPMed具有 来自4个祖先群体的2，507名测序T2 D患者的子集的组学数据，计划更多。一 清楚地了解T2 D中每个组学维度与CVD的关联有助于理解， 尺寸作为T2 D中CVD的独特暴露。对目标2组学关联的解释将首先是 由目标1的WGS关联告知，然后通过将WGS信息与所有四个组学维度相结合， (Aim 3）。我们将使用Aim 2-基于关联和基于不可知的多维方法来构建 T2 D中CVD病理生物学的多级网络模型。“TOPMed心血管疾病组学， 糖尿病”是高度响应NOT-HL-19-676，利用TOPMed资源阐明途径 心脏、肺和血液疾病的生物学。我们的团队在组学发现方面有着良好的记录，旨在 寻找新的方法来预防和治疗2型糖尿病心血管疾病。

Project Summary/Abstract Blood omic biomarkers, including whole genome sequence (WGS), whole blood methylation (measured by sequencing or microarrays), transcription (using RNA-seq), proteomics (SomaLogic aptamers) and metabolomics (liquid chromatography/mass spectroscopy) have identified novel pathways to cardiovascular disease (CVD: coronary heart disease (CHD) and stroke; subclinical atherosclerosis: elevated coronary artery calcium (CAC), and carotid plaque and intimal-medial thickness (cIMT)). Individually, but especially together in multidimensional network frameworks, omics data in the NHLBI Trans-Omics for Precision Medicine (TOPMed) study are poised to address major problems in biomedicine. In this application we focus on multi-omic investigation of CVD in type 2 diabetes (T2D). T2D is a growing scourge worldwide, driving a major global epidemic of CVD. CVD events occur over twice as frequently in people with T2D. The reasons for this persistent excess risk remain unknown but likely involve perturbations across multiple omic dimensions, from genetic variation to networks that link insulin resistance, endothelial dysfunction and atherogenesis. Elucidation of the biology underlying CVD in T2D offers a clear opportunity to stem the global tide of CVD. We propose three Aims. In Aim 1, we will analyze genetic variation from WGS data from 23,903 people with T2D from 5 ancestry groups from 28 cohorts (11 longitudinal) of men and women of diverse ages, including 15 with prevalent CVD and 11 with measures of subclinical atherosclerosis. We have linked WGS data to diverse annotation resources (e.g. ENCODE). We have clinical covariates including age of T2D onset and level of metabolic control, and longitudinal follow-up for incident CVD events. Analyses of common and rare variation will elucidate known candidate CVD-T2D loci and lead to new discovery. Replication is available in >220,000 T2D individuals of diverse ancestry from 5 biobanks. Validated variants will be used in Mendelian Randomization tests of causality and polygenic scores for prediction. In Aim 2, we will analyze blood omic biomarkers individually, guided by Aim 1 genomic associations with CVD in T2D. TOPMed has omics data on a subset of 2,507 sequenced people with T2D from 4 ancestry groups, with more planned. A clear understanding of the association of each omic dimension with CVD in T2D is useful to understand that dimension as a unique exposure for CVD in T2D. Interpretation of Aim 2 omic associations will first be informed by WGS association from Aim 1, then by combining WGS information with all four omic dimensions (Aim 3). We will use both Aim 2-association-based and agnostic multidimensional-based approaches to build multilevel network models of the pathobiology of CVD in T2D. “TOPMed Omics of Cardiovascular Disease in Diabetes” is highly responsive to NOT-HL-19-676, leveraging TOPMed resources to elucidate the pathway biology of heart, lung and blood diseases. Our team, with a proven track record in omics discovery, aims to find new approaches to prevent and treat CVD in T2D.