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因素相互作用，2型糖尿病继续在全球蔓延。最新基因 在与2型糖尿病及其相关数量性状相关的&gt；400基因座上发现&gt；700变异(QTS： 空腹血糖(Fg)、胰岛素(FI)和血红蛋白A1c(A1c))有助于了解新的T2D病理生物学。然而，大多数 在白人中发现了这一点；需要对受T2D影响不成比例的少数群体进行研究。此外，大多数 关联存在于非编码基因组中，这表明需要对全基因组序列(WGS)进行完整的分析 变异体和效应器基因特征。NHLBI Trans-Omics for Precision Medicine(TOPMed)研究包括 来自五个人群(41,557欧元，23,203例再生障碍性贫血，16,213例)的21,493例T2D流行病例和63,541例对照的WGS 拉丁裔，2,867名亚洲人，1,194名萨摩亚人的脂肪研究)来自28个队列和多达54,407名患有FG的非T2D人， FI或HbA1c，以及T2D的发病年龄、血糖控制水平和T2D事件的纵向随访 事件。在这个项目中，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体 关联的T2D和QTS。我们将在NHLBI BioData催化剂中进行分析。复制新的变种是 提供来自6个生物库(UKBB、BIOME、BioVU、合作伙伴)的100万个不同血统的个体 BB，致敬，MVP)与TOPMed-puputed基因组阵列数据。对于健康翻译，我们将T2D基因分组 风险变量转化为预测未来T2D或表征特定生理轴的多基因风险评分(PRS)，以及 在疾病因果关系的孟德尔随机化(MR)检验中使用变量。接下来，TOPMed进行了血液组学测量 来自也可能识别与T2D病理生物学相关的新生物网络的五个祖先组，包括 全血DNA甲基化(通过测序或微阵列测量，N=11,131)，转录组(RNA-seq) 蛋白质组学(SomaLogic适配子或Olink蛋白质组学，N=7897)和代谢组学(Liquid 色质联用，N=11,631)。在目标2中，我们将测试与T2D和QTS相关的OMIC签名 单独和在T2D病理生物学的多维基因组和基因组网络模型中。最后，在目标3中 我们计划将TOPMed WGS和OMIC结果与定制细胞或特定组织(β细胞、胰岛、肝脏、脂肪和 肌肉)基因组和表观基因组注释(ATAC-SEQ、RNA-SEQ、Hi-C、CHIP-SEQ)在加速医学中 伙伴关系(AMP)T2D糖尿病表观基因组图谱，并与数百个额外的基因组特征关联在 AMP T2D知识门户(T2DKP)，用于“电子变异到功能”和表现学研究。功能齐全 人类T2D和QT基因组与血液和组织特异性基因组整合的图谱即将出现。我们的 多学科、多中心的团队在遗传学和基因组发现方面有着公认的记录。我们正在积极地工作 使用TOPMed、AMP T2D DGA和T2DKP数据。我们处于有利地位，可以实现提案的目标， 打算寻找新的方法来解决T2D在所有高危人群中的全球流行问题。