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.

项目摘要/摘要 由于不健康的环境与遗传学相互作用，2型糖尿病继续在全球范围内传播。最近的遗传 与2型糖尿病（T2D）及其相关的定量性状相关的> 400个局部> 400个局部的发现> 700个变体的发现（QTS： 空腹葡萄糖（FG），胰岛素（FI）和血红蛋白A1C（A1C））可深入了解新的T2D病理学。但是，大多数 发现有白人。需要在少数群体中受T2D影响不成比例的研究。另外，大多数 关联在非编码基因组中，表明全基因组序列（WGS）分析需要完整 变体和效应子基因表征。 NHLBI精密医学的跨词（TopMed）研究包括 来自21,493例普遍存在T2D的WG和来自五个人群的63,541个对照（41,557欧元，23,203 AA，16,213 拉丁裔，2,867个亚洲人，1,194个萨摩亚脂肪材料研究），来自28个同龄人，最多54,407名非T2D患者 FI或HBA1C以及T2D发作的年龄，血糖控制水平和纵向随访T2D 事件。在这个项目中，目标1是在五个祖先的WGS范围内测试已知和新的常见和稀有变体 相关的T2D和QT。我们将在NHLBI Biodata催化剂中进行分析。新颖变体的复制是 来自T2D的六个生物库（UKBB，BIOME，BIOVU，合作伙伴）的100万个潜水员血统的人可供选择 BB，问卷，MVP），带有最高的基因组阵列数据。对于健康翻译，我们将分组T2D遗传 风险变异变体为多基因风险评分（PRS）预测未来的T2D或表征特定的物理轴，并且 在疾病计算的孟德尔随机化（MR）测试中使用变体。接下来，上面有血液OMIC测量 来自五个祖先，这些祖先也可以识别与T2D病理生物学相关的新型生物网络，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适体或奥林克蛋白质组学，n = 7,897）和代谢组学（液体 色谱/质谱，n = 11,631）。在AIM 2中，我们将测试与T2D和QT相关的OMIC特征 T2D病理生物学的单独和多维的OMIC和基因组网络模型。最后，在目标3中 我们计划将最高的WGS和OMIC结果与定制细胞或组织特异性（β细胞，小岛，肝脏，脂肪和 肌肉）在加速医学中的胶质和表观基因组注释（ATAC-SEQ，RNA-SEQ，HI-C，CHIP-SEQ） 合作伙伴关系（AMP）T2D糖尿病表观基因组图中，以及数百种基因组性状关联 AMP T2D知识门户（T2DKP）用于“在硅变异到功能”和现象研究中。完整的功能 人类T2D和QT基因组的血液和组织特异性的OMIC整合映射即将到来。我们的 多学科的多中心团队在遗传学和OMIC发现方面具有良好的记录。我们正在积极工作 使用顶部，AMP T2D DGA和T2DKP数据。我们有好处，可以实现提案的目标， 打算在所有处于危险中的人群中寻找新方法来解决T2D全球流行病的新方法。