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

 描述(申请人提供)：2型糖尿病已成为全球健康的主要威胁之一。工业化经济体和新兴经济体糖尿病患病率的迅速上升证明了预防的失败，糖尿病患者的高并发症发生率突显了目前治疗方法的不足。我们对糖尿病发病机制的理解存在重大差距，阻碍了新的预防和治疗策略方面的创新。人类遗传学为解决这些缺陷提供了一种日益强大的方法，并提供了对疾病的机械性见解，从而可能产生与健康相关的好处。这项建议寻求使用人类基因发现工作中的信息，这些信息近年来已经确定了基因组中包含影响T2D风险的DNA序列变异的100多个区域。在将这些发现转化为机械洞察方面取得的进展有限，但最近的几项技术和分析进步改变了这种情况，我们计划利用这些进展。我们的第一个目标是研究驱动这些区域风险关联的特定DNA序列变化。聚集非常大的遗传数据集，特别是来自一系列种族群体的数据集，使得有可能定义可能驱动T2D风险效应的这些变异的子集。我们将收集大量的基因数据集，作为大型国际联盟的一部分，并应用现有的和新的方法来得出这些T2D风险变体的最精确的定位。确定了这些变异后，第二个目标是了解它们扰乱的细胞过程。最近，已经有可能从关键的与糖尿病相关的人类组织，包括胰岛，生成详细的基因组功能图。这些图谱定义了对调节细胞活动至关重要的元素。我们将使用这些地图来突出包含T2D因果变体的特定元素，并启动实验研究来测试出现的功能假说。第三个目标寻求将这些与T2D相关的功能元件与特定的基因、蛋白质、网络和调节其影响的途径联系起来。我们将从各种现有的和新的公共和专有来源收集数据，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，这些努力将导致直接与人类疾病有关的新的蛋白质靶点。这项提案的一个基本特点是，它依赖于已经收集的大量数据集，或者在某些情况下，正在利用现有资金生成数据集。我们在这里要求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社区，特别是通过AMP-T2DGENES联盟门户网站。

 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.