Integrating genome-scale data to reveal causal mechanisms in type 2 diabetes

整合基因组规模数据揭示 2 型糖尿病的因果机制

• 批准号: 9054840
• 负责人: Mark Ian McCarthy
• 金额: $ 36.18万
• 依托单位: UNIVERSITY OF OXFORD
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-05-01 至 2020-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9054840
• 关键词: Address; Ally; Area; Automobile Driving; Beta Cell; Biological; Biology; CRISPR/Cas technology; Cell Line; Cell physiology; Cessation of life; Chromatin; Communities; Complication; Computer Simulation; DNA Sequence; Data; Data Aggregation; Data Analyses; Data Set; Development; Diabetes Mellitus; Disease; Elements; Enhancers; Equipment and supply inventories; Ethnic group; Failure; Fatty acid glycerol esters; Frequencies; Funding; Funding Opportunities; Gene Proteins; Genes; Genetic; Genome; Genome Mappings; Genomics; Health; Home environment; Human; Human Genetics; In Vitro; Individual; International; Investments; Islets of Langerhans; Knowledge; Location; Maps; Mediating; Medicine; Meta-Analysis; Methods; Methylation; Molecular; Muscle; Non-Insulin-Dependent Diabetes Mellitus; Pathogenesis; Pathway interactions; Phenotype; Physiology; Predisposition; Prevalence; Prevention; Prevention strategy; Process; Proteins; Research; Research Personnel; Resolution; Risk; Rodent; Sampling; Scanning; Signal Transduction; Small Interfering RNA; Source; Stem cells; System; Testing; Therapeutic; Tissues; Transcript; Trust; United States National Institutes of Health; Untranslated RNA; Ursidae Family; Variant; Weight; base; burden of illness; case control; data integration; diabetes risk; epigenomics; exome; genome wide association study; genome-wide; global health; human disease; human tissue; improved; in vivo; innovation; insight; insulin secretion; islet; man; multidisciplinary; novel; novel strategies; phenome; programs; research study; response; risk variant; transcription factor; transcriptomics

 DESCRIPTION (provided by applicant): Type 2 diabetes has emerged as one of the leading threats to global health. The rapid rise in diabetes prevalence in both industrialized and emerging economies bears testament to the failures of prevention, and high rates of complication in those with diabetes highlight the inadequacies of current therapeutic approaches. Major gaps in our understanding of the mechanisms responsible for the development of diabetes represent obstacles to innovation with respect to novel preventative and therapeutic strategies. Human genetics provides an increasingly-powerful approach for addressing these deficiencies and providing mechanistic insights into disease that can result in health-related benefits. This proposal seeks to use information from human genetic discovery efforts that have, in recent years, identified over 100 regions of the genome which harbor DNA sequence variants influencing T2D-risk. There has been limited progress in turning these discoveries into mechanistic insights but several recent technological and analytical advances have transformed the situation, and it is these that we plan to exploit. Our first aim is to home i on the specific DNA sequence changes driving the risk-associations in these regions. The aggregation of very large genetic datasets, particularly when derived from a range of ethnic groups, makes it possible to define the subset of these variants likely to be driving the T2D-risk effect. We will take extensive genetic data sets collected as part of large international consortia and apply existing and novel approaches to derive the most precise localization of these T2D-risk variants yet obtained. Having identified these variants, the second aim is to understand the cellular processes they perturb. Recently, it has become possible to generate detailed functional maps of the genome from key diabetes- relevant human tissues, including the pancreatic islet. These maps define elements crucial for regulating cellular activity. We will use these maps to highlight the specific elements that contain T2D-causal variants, and initiate experimental studies to test the functional hypotheses that emerge. The third aim seeks to connect these T2D-associated functional elements to the specific genes, proteins, networks and pathways that mediate their effects. We will aggregate data from a variety of existing and novel public and proprietary sources, each of which provides complementary clues to the relevance of the regional genes to T2D development. Most medicines act on specific protein targets, and these efforts will result in novel protein targets that are directly implicated in human disease. An essential feature of this proposal is that it relies on extensive data sets that have already been collected, or, in some cases, are being generated with existing funding. The funding we request here will support the further integration of these data, and also enable its dissemination to the wider research community, most particularly via the AMP-T2DGENES consortium portal.

 描述（由申请人提供）：2 型糖尿病已成为全球健康的主要威胁之一。工业化国家和新兴经济体中糖尿病患病率的迅速上升证明了预防措施的失败，而糖尿病患者的高并发症发生率凸显了当前治疗方法的不足。我们对糖尿病发生机制的理解存在重大差距，这阻碍了新型预防和治疗策略的创新。人类遗传学提供了一种日益强大的方法来解决这些缺陷，并提供对疾病的机制见解，从而带来与健康相关的益处。该提案旨在利用人类基因发现工作的信息，近年来，这些工作已确定了基因组中 100 多个区域，这些区域含有影响 T2D 风险的 DNA 序列变异。在将这些发现转化为机械见解方面进展有限，但最近的一些技术和分析进展已经改变了这种情况，而我们计划利用的正是这些进展。我们的首要目标是了解驱动这些区域风险关联的特定 DNA 序列变化。非常大的遗传数据集的聚合，特别是来自一系列种族群体的遗传数据集，使得可以定义可能驱动 T2D 风险效应的这些变异的子集。我们将利用大型国际联盟收集的广泛遗传数据集，并应用现有的和新颖的方法来对这些 T2D 风险变异进行最精确的定位。识别出这些变异后，第二个目标是了解它们扰乱的细胞过程。最近，从关键的糖尿病相关人体组织（包括胰岛）生成详细的基因组功能图谱已成为可能。这些图谱定义了调节细胞活动的关键元素。我们将使用这些图来突出显示包含 T2D 因果变异的特定元素，并启动实验研究来测试出现的功能假设。第三个目标旨在将这些与 T2D 相关的功能元件与介导其作用的特定基因、蛋白质、网络和途径联系起来。我们将汇总来自各种现有和新颖的公共和专有来源的数据，每个来源都为区域基因与 T2D 发展的相关性提供补充线索。大多数药物作用于特定的蛋白质靶点，这些努力将产生与人类疾病直接相关的新蛋白质靶点。该提案的一个重要特征是，它依赖于已经收集的广泛数据集，或者在某些情况下，利用现有资金生成的数据集。我们在此申请的资金将支持这些数据的进一步整合，并使其能够传播到更广泛的研究界，特别是通过 AMP-T2DGENES 联盟门户。