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.

项目摘要/摘要 血液基因组生物标志物，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适配子)和 代谢组学(液相色谱/质谱学)已经确定了心血管疾病的新途径 疾病(心血管疾病：冠心病和中风；亚临床动脉粥样硬化：冠状动脉病变 动脉钙化(CAC)、颈动脉斑块和内中膜厚度(CIMT))。个别的，但特别是 在多维网络框架中，NHLBI Transans-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。在本应用程序中，我们重点介绍 2型糖尿病患者心血管疾病的多组学研究T2D在全球范围内是一个日益严重的祸害，推动着 心血管疾病在全球范围内的重大流行。T2D患者发生心血管事件的频率是后者的两倍以上。原因何在 对于这种持续的超额风险仍然未知，但可能涉及多个OMIC的扰动 维度，从遗传变异到连接胰岛素抵抗、内皮功能障碍和 动脉粥样硬化的形成。阐明T2D心血管疾病的生物学基础提供了一个明确的机会来阻止全球 心血管疾病的浪潮。我们提出了三个目标。在目标1中，我们将分析来自23,903个WGS数据的遗传变异 来自28个(纵向11个)不同性别的男性和女性的5个祖先群体的T2D患者 年龄，包括15名常见的心血管疾病患者和11名亚临床动脉粥样硬化患者。我们已经联系在一起 将WGS数据转换为不同的注释资源(例如ENCODE)。我们有包括T2D年龄在内的临床协变量 代谢控制的开始和水平，以及对心血管事件的纵向跟踪。对常见问题的分析 罕见的变异将阐明已知的候选CVD-T2D基因座，并导致新的发现。复制是 可在来自5个生物库的220,000个不同血统的T2D个体中使用。经过验证的变种将用于 因果关系的孟德尔随机化检验和预测的多基因得分。在目标2中，我们将分析 血液基因组生物标记物单独，由Aim 1基因组学指导与T2D中的心血管疾病的相关性。TOPMed有 2,507人的子集的组学数据对来自4个祖先组的T2D患者进行了测序，并计划进行更多测序。一个 清楚地了解T2D中每个基因组维度与心血管疾病的关联有助于理解 在T2D中，维度是心血管疾病的唯一暴露。对目标2经济关联的解释将首先是 由目标1的WGS关联通知，然后通过将WGS信息与所有四个OMIC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的多维方法来构建 二维脑血管病病理生物学的多层网络模型。《TOPMed Omics of心血管疾病》 糖尿病“对NOT-HL-19-676高度敏感，利用TOPM资源阐明该途径 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，目标是 寻找预防和治疗T2D脑血管病的新方法。