TOPMed Omics of Type 2 Diabetes and Quantitative Traits

2 型糖尿病的 TOPMed 组学和定量特征

• 批准号: 10533311
• 负责人: Alisa Knodle Manning
• 金额: $ 74.77万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-04-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10533311
• 关键词: ATAC-seq; Acceleration; Address; Affect; African American; Age; Alleles; Asian; Atlases; Beta Cell; Bioinformatics; Biological; Biological Markers; Biology; Blood; Cells; Cessation of life; ChIP-seq; Clinical Data; Code; Collaborations; DNA Methylation; Data; Development; Diabetes Mellitus; Dimensions; Disease; East Asian; Environment; Epidemic; Etiology; European; Event; Fatty acid glycerol esters; Future; Gene Frequency; Genes; Genetic; Genetic Risk; Genome; Genomics; Glycosylated hemoglobin A; Goals; Health; Hepatic; Hi-C; Hispanic; Human; Individual; Insulin; Insulin Resistance; Intention; Knowledge; Knowledge Portal; Latino; Lead; Liver; Maps; Measures; Medicine; Mendelian randomization; Methods; Minor; Minority Groups; Molecular; Muscle; National Heart, Lung, and Blood Institute; National Institute of Diabetes and Digestive and Kidney Diseases; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Odds Ratio; Pathway interactions; Peptides; Physiological; Physiology; Population; Populations at Risk; Positioning Attribute; Proteins; Proteomics; Race; Risk; Samoan; Sequence Analysis; Series; Single Nucleotide Polymorphism; System; Testing; Tissue atlas; Tissues; Trans-Omics for Precision Medicine; Transcript; Translations; Untranslated RNA; Variant; Whole Blood; aptamer; biobank; cardiometabolism; case control; catalyst; cohort; data portal; database of Genotypes and Phenotypes; epigenome; epigenomics; fasting glucose; follow-up; genetic variant; genome wide association study; glycemic control; high dimensionality; in silico; insight; islet; liquid chromatography mass spectroscopy; metabolomics; methylomics; multidimensional data; multidisciplinary; network models; novel; novel strategies; obesity genetics; phenomics; polygenic risk score; rare variant; risk variant; statistics; targeted treatment; trait; transcriptome sequencing; transcriptomics; whole genome; working group

Project Summary/Abstract Type 2 diabetes continues to spread globally due to unhealthy environment interacting with genetics. Recent genetic discoveries of >700 variants at >400 loci associated with type 2 diabetes (T2D) and its related quantitative traits (QTs: fasting glucose (FG), insulin (FI) and hemoglobin A1c (A1c)) give insight into new T2D pathobiology. However, most discoveries have been in whites; studies in minority groups disproportionately affected by T2D are needed. Also, most associations are in the non-coding genome, indicating that whole genome sequence (WGS) analysis is needed for full variant and effector gene characterization. The NHLBI Trans-Omics for Precision Medicine (TOPMed) study includes WGS from 21,493 cases of prevalent T2D and 63,541 controls from five populations (41,557 Euro, 23,203 AA, 16,213 Latino, 2,867 Asian, 1,194 Samoan Adiposity Study) from 28 cohorts and up to 54,407 non-T2D individuals with FG, FI or HbA1c, as well as age of T2D onset, level of glycemic control and longitudinal follow-up for incident T2D events. In this project Aim 1 is to test WGS-wide in five ancestry groups for known and new common and rare variants associated T2D and QTs. We will conduct analyses in the NHLBI BioData Catalyst. Replication of novel variants is available in >1 million individuals of diverse ancestry from six biobanks with T2D (UKBB, BioME, BioVU, Partners BB, REGARDS, MVP) with TOPMed-imputed genomic array data. For health translation, we will group T2D genetic risk variants into polygenic risk scores (PRSs) that predict future T2D or characterize specific physiological axes, and use variants in Mendelian Randomization (MR) tests of disease causality. Next, TOPMed has blood omic measures from five ancestry groups that may also identify novel biological networks relevant to T2D pathobiology, including whole blood DNA methylation (measured by sequencing or microarrays, N=11,131), transcriptomics (RNA-seq) (N=8,334), proteomics (SomaLogic aptamers or Olink proteomics, N=7,897) and metabolomics (liquid chromatography/mass spectroscopy, N=11,631). In Aim 2, we will test omic signatures associated with T2D and QTs individually and in multidimensional omic and genomic network models of the pathobiology of T2D. Finally, in Aim 3 we plan to integrate TOPMed WGS and omic results with bespoke cell or tissue-specific (beta cell, islet, liver, fat and muscle) omic and epigenomic annotation (ATAC-seq, RNA-seq, Hi-C, ChIP-seq) in the Accelerating Medicine Partnership (AMP) T2D Diabetes epiGenome Atlas, and with hundreds of additional genomic trait associations in the AMP T2D Knowledge Portal (T2DKP) for ‘in silico variant-to-function’ and phenomic studies. Complete functional mapping with blood and tissue-specific omic integration of the human T2D and QT genome is on the horizon. Our multidisciplinary, multicenter team has a proven track record in genetics and omic discovery. We are actively working with TOPMed, AMP T2D DGA and T2DKP data. We are well positioned to achieve the Aims of the proposal, with the intention to find new approaches to address the global epidemic of T2D in all populations at risk.

项目概要/摘要 由于不健康的环境与遗传学的相互作用，2 型糖尿病继续在全球蔓延。 在 > 400 个基因座上发现 > 700 个变异，与 2 型糖尿病 (T2D) 及其相关数量性状 (QT： 空腹血糖 (FG)、胰岛素 (FI) 和糖化血红蛋白 (A1c)）可以帮助我们深入了解新的 T2D 病理学。 已在白人中进行了研究；此外，还需要对受 T2D 影响较大的少数群体进行研究。 关联存在于非编码基因组中，表明需要全基因组序列（WGS）分析才能获得完整的结果 NHLBI 精准医学跨组学 (TOPMed) 研究包括变异和效应基因表征。 来自五个人群的 21,493 例流行 T2D 病例和 63,541 例对照的全基因组测序（41,557 欧元、23,203 AA、16,213 拉丁美洲人、2,867 名亚洲人、1,194 名萨摩亚人肥胖研究）来自 28 个队列和多达 54,407 名患有 FG 的非 T2D 个体， FI 或 HbA1c，以及 T2D 发病年龄、血糖控制水平和 T2D 事件的纵向随访 在该项目中，目标 1 是在五个祖先群体中测试 WGS 范围内的已知和新的常见和稀有变异。 我们将在 NHLBI BioData Catalyst 中进行新变异的复制。 来自 6 个 T2D 生物库（UKBB、BioME、BioVU、Partners）的超过 100 万不同血统的个体中存在 BB、REGARDS、MVP）以及 TOPMed 估算的基因组阵列数据 对于健康翻译，我们将 T2D 遗传分组。 将风险变异转化为多基因风险评分 (PRS)，预测未来 T2D 或表征特定的生理轴，以及 使用疾病因果关系的孟德尔随机化 (MR) 测试中的变体 接下来，TOPMed 具有血液组学测量。 来自五个祖先群体，这些群体也可能识别出与 T2D 病理学相关的新生物网络，包括 全血 DNA 甲基化（通过测序或微阵列测量，N=11,131）、转录组学 (RNA-seq) (N=8,334)、蛋白质组学（SomaLogic 适体或 Olink 蛋白质组学，N=7,897）和代谢组学（液体 色谱/质谱，N=11,631）在目标 2 中，我们将测试与 T2D 和 QT 相关的组学特征。 单独地以及在 T2D 病理学的多维组学和基因组网络模型中最后，在目标 3 中。 我们计划将 TOPMed WGS 和组学结果与定制的细胞或组织特异性（β 细胞、胰岛、肝脏、脂肪和 加速医学中的肌肉）组学和表观基因组注释（ATAC-seq、RNA-seq、Hi-C、ChIP-seq） 合作伙伴 (AMP) T2D 糖尿病表观基因组图谱，以及数百个其他基因组性状关联 AMP T2D 知识门户 (T2DKP)，用于“计算机变异到功能”和完整的功能研究。 我们即将推出人类 T2D 和 QT 基因组的血液和组织特异性组学整合图谱。 多学科、多中心团队在遗传学和组学发现方面拥有良好的记录。 借助 TOPMed、AMP T2D DGA 和 T2DKP 数据，我们完全有能力实现提案的目标，并且： 旨在寻找新方法来应对全球所有高危人群中 T2D 的流行。