Beyond GWAS of insulin resistance: An integrated approach to translate genetic association to function

项目摘要/摘要 胰岛素抵抗是一种生理状态，在这种状态下正常水平的胰岛素无法调节血糖水平， 即使在没有2型糖尿病的情况下，也有强有力的证据表明，胰岛素抵抗显著 增加动脉粥样硬化和明显的心血管疾病的风险。在过去的几年里，我们已经确定了 13个胰岛素抵抗易感基因，但除3个外，所有易感基因和致病机制尚不清楚 在这些基因座中，剩下的10个基因座在胰岛素抵抗发生中的作用还没有研究。 系统地。这为深入的生理和机制研究提供了一座金矿 了解肥胖、胰岛素抵抗和心血管疾病之间的联系可能会导致新的 可能对公共卫生产生巨大影响的预防和治疗方法。建立和建立 为了表征与胰岛素抵抗相关的基因，我们计划在大型人类队列中进行实验 使用斑马鱼和基于细胞的模型进行功能跟踪。 我们将使用来自大鼠的详细表型信息来表征所建议的胰岛素抵抗基因座 以人群为基础的样本(总N=13,811)，用动态血糖和胰岛素测量进行评估 代谢、代谢组、转录组、表观基因组和蛋白质组学分析以及电子数据 公共资源的基因调控和转录。 下一步，我们将把55个候选基因送到我们的流水线上，以便使用 高通量可视化技术和生化测量。我们使用CRISPR-CAS9技术 敲除这10个迄今尚未特化的基因中的55个同源基因，并研究 扰乱这些基因对胰岛素抵抗的影响。 最后，我们将优先使用脂肪细胞中的基因敲除来进行机制研究的五个候选基因 和肝细胞研究葡萄糖、胰岛素和脂肪代谢、基因表达和代谢途径。 通过对假设与胰岛素抵抗有关的基因座进行详细的后续分析，我们预计 建立其中几个基因座的致病基因和作用机制。深入的刻画 使用体内和体外模型将为因果关系和作用机制提供进一步的证据， 以及对可能成为可行药物靶点的第一次评估。我们将全面整合的方法 通过在功能模型系统中进行实验来描述人类的特性提供了一个翻译框架， 它的设计更有可能产生与人类生物学和医学相关的研究结果。重要的是，我们有 获得独特的学习材料、最先进的方法，并有良好的成功记录 这一领域的合作。我们的工作预计将造福科学界，导致新的重要 对胰岛素抵抗、心血管疾病和2型糖尿病的洞察。

PROJECT SUMMARY/ABSTRACT Insulin resistance is a physiological state in which normal levels of insulin fail to regulate blood glucose levels, and even in the absence of type 2 diabetes, there is strong evidence that insulin resistance dramatically increases risk for atherosclerosis and overt cardiovascular disease. In the past few years, we have identified 13 susceptibility loci for insulin resistance, but the causal gene and mechanisms are unknown for all but three of these loci, and the role of the ten remaining loci for development of insulin resistance has not been studied systematically. This represents a gold mine for in-depth physiological and mechanistic studies as increased understanding of the links between obesity, insulin resistance and cardiovascular disease may lead to new approaches to prevention and treatment that could have a huge public health impact. To establish and characterize genes associated with insulin resistance, we plan experiments in large human cohorts with functional follow-up using zebrafish and cell-based models. We will characterize suggested insulin resistance loci using detailed phenotypic information from large population-based samples (total N=13,811) assessed with dynamic measures of glucose and insulin metabolism, metabolomic, transcriptomic, epigenomic and proteomic profiling together with in silico data on gene regulation and transcription from public resources. Next, we will take 55 candidate genes forward to our pipeline for efficient characterization in zebrafish using high-throughput visualization techniques and biochemical measurements. We use CRISPR-Cas9 techniques to knockout the orthologous 55 genes from the 10 loci that are uncharacterized to date, and study the effect of perturbing these genes on insulin resistance. Finally, we will prioritize five candidate genes for mechanistic studies using gene knockdown in adipocytes and hepatocytes to study glucose, insulin and lipid metabolism, gene expression and metabolic pathways. By performing detailed follow-up analyses of loci hypothesized to be involved in insulin resistance, we expect to establish causal genes and mechanisms of action for several of these loci. The in-depth characterization using in vivo and in vitro models will provide further evidence towards causality and the mechanisms of action, as well as a first evaluation of which could be viable drug targets. Our approach of integrating comprehensive characterization in humans with experiments in functional model systems provides a translational framework, which by design is more likely to yield findings relevant for human biology and medicine. Importantly, we have access to unique study materials, state-of-the art methodology, and have a strong track record of successful collaborations in this field. Our work is anticipated to benefit the scientific community, to lead to new important insights into insulin resistance, cardiovascular disease and type 2 diabetes.