TOPMed Omics of Cardiovascular Disease in Diabetes

糖尿病心血管疾病的 TOPMed 组学

• 批准号: 10425415
• 负责人: JAMES B MEIGS
• 金额: $ 79.71万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10425415
• 关键词: Address; Age; Alleles; Atherosclerosis; Automobile Driving; Biological; Biological Markers; Biology; Blood; Cardiovascular Diseases; Carotid Artery Plaques; Cessation of life; Clinical; Code; Cohort Studies; Coronary heart disease; DNA Methylation; Data; Diabetes Mellitus; Dimensions; Epidemic; Etiology; Event; Foundations; Genetic; Genetic Transcription; Genetic Variation; Genomics; Goals; Health; Health system; Heart Diseases; Hematological Disease; Individual; Insulin Resistance; Investigation; Knowledge; Lead; Link; Longitudinal cohort; Lung diseases; Measures; Medial; Mendelian randomization; Metabolic; Metabolic Control; Methylation; National Heart, Lung, and Blood Institute; Network-based; Non-Insulin-Dependent Diabetes Mellitus; Pathway interactions; Persons; Proteomics; Resources; Risk; Risk Factors; Scourge; Series; Stroke; Testing; Thick; Tissues; Trans-Omics for Precision Medicine; Translations; Variant; Whole Blood; Woman; aptamer; atherogenesis; base; biobank; cohort; coronary artery calcium; cost; diabetic; dimensional analysis; disability; endothelial dysfunction; experimental study; follow-up; genetic analysis; genomic locus; high dimensionality; insight; liquid chromatography mass spectroscopy; men; metabolomics; methylomics; multidisciplinary; multiple omics; network models; non-diabetic; novel; novel strategies; prevent; proteomic signature; rare variant; stem; transcriptome sequencing; transcriptomics; whole genome

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.

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（通过测量 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) 和中风；亚临床动脉粥样硬化：冠状动脉升高 动脉钙 (CAC)、颈动脉斑块和内膜中层厚度 (cIMT)。就个人而言，但特别是 NHLBI Trans-Omics for Precision 中的组学数据整合在多维网络框架中 医学（TOPMed）研究旨在解决生物医学中的重大问题。在这个应用程序中我们重点关注 2 型糖尿病 (T2D) CVD 的多组学研究。 T2D 是全球范围内日益严重的祸害，导致 CVD 是全球主要流行病。 T2D 患者的 CVD 事件发生频率是其两倍多。原因 因为这种持续的超额风险仍然未知，但可能涉及多个组学的扰动 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 T2D 中 CVD 的生物学基础为遏制全球性疾病提供了明确的机会 CVD大潮。我们提出三个目标。在目标 1 中，我们将分析来自 23,903 个样本的 WGS 数据的遗传变异 来自 5 个血统群体的 T2D 患者来自 28 个队列（11 个纵向队列），由不同种族的男性和女性组成 年龄，包括 15 岁患有普遍的 CVD 和 11 岁患有亚临床动脉粥样硬化。我们已经链接了 WGS 数据到不同的注释资源（例如 ENCODE）。我们有临床协变量，包括 T2D 年龄 代谢控制的发生和水平，以及对CVD事件的纵向随访。常见现象分析 罕见的变异将阐明已知的候选 CVD-T2D 位点并带来新的发现。复制是 来自 5 个生物库的超过 220,000 名不同血统的 T2D 个体中有可用的。已验证的变体将用于 用于预测的因果关系和多基因评分的孟德尔随机化检验。在目标 2 中，我们将分析 在 Aim 1 基因组与 T2D 中 CVD 关联的指导下，单独分析血液组学生物标志物。 TOPMed 有 来自 4 个祖先群体的 2,507 名已测序 T2D 患者的组学数据，并计划提供更多数据。一个 清楚地了解每个组学维度与 T2D 中 CVD 的关联有助于理解 维度作为 T2D 中 CVD 的独特暴露。首先将解释目标 2 组学关联 由目标 1 的 WGS 协会通知，然后将 WGS 信息与所有四个组学维度相结合 （目标 3）。我们将使用基于 Aim 2 关联的方法和基于不可知多维的方法来构建 T2D CVD 病理学的多级网络模型。 “心血管疾病的 TOMed 组学 “糖尿病”对 NOT-HL-19-676 高度敏感，利用 TOPMed 资源来阐明途径 心脏、肺和血液疾病的生物学。我们的团队在组学发现方面拥有良好的记录，旨在 寻找预防和治疗 T2D CVD 的新方法。