Transcriptional Mechanisms of Human Insulin Resistance

人类胰岛素抵抗的转录机制

基本信息

批准号：
10337205
负责人：
Evan D Rosen
金额：
$ 63.75万
依托单位：
BETH ISRAEL DEACONESS MEDICAL CENTER
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-04-01 至 2024-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10337205
关键词：
ATAC-seq Address Adipocytes Affect Alleles Allelic Imbalance Area Atlases Automobile Driving Binding Biological Assay CRISPR interference Chromatin Complement Complex Computer Models DNA Binding Data Data Set Development Discipline Disease Elements Enhancers Funding Gene Expression Gene Expression Regulation Genes Genetic Genetic Transcription Genetic Variation Goals Health Hi-C Human Human Genetics Human Genome In Vitro Individual Insulin Insulin Resistance Knock-out Lead Link Maps Metabolic Modeling Molecular Molecular and Cellular Biology Mus Non-Insulin-Dependent Diabetes Mellitus Nuclear Pathogenesis Pathway interactions Peripheral Physiological Positioning Attribute Process Regulator Genes Regulatory Element Reporter Resistance Risk Short Interspersed Nucleotide Elements Single Nucleotide Polymorphism Testing Tissues Untranslated RNA Validation Variant Virulence Factors base editing causal variant cell type diabetes risk differential expression disorder risk epigenetic variation epigenomics genome wide association study glucose uptake human genomics human subject improved in vivo insight insulin sensitivity insulin signaling knock-down loss of function mathematical model next generation novel novel therapeutics overexpression predictive modeling promoter risk variant tool trait transcription factor transcription factor USF transcriptomics translational medicine

项目摘要

ABSTRACT Insulin resistance (IR) is a sine qua non of Type 2 diabetes and a pathogenic factor in many other disease states. The molecular basis of IR is complex, and associated with many interweaving pathways. We have focused on nuclear mechanisms of IR, comprising the combined actions of transcription factors (TFs) and epigenomic modifiers. In the prior funding cycle we have identified several transcriptional regulators of cellular and tissue IR using advanced epigenomic strategies. For the upcoming cycle, we propose to shift to the study of human IR; specifically, the identification of transcriptional mechanisms that drive the development of IR in human adipocytes. Toward this end, we have generated chromatin state maps of primary adipocytes from insulin resistant and sensitive subjects, leading to the identification of thousands of enhancers with differential activity in IR. First, we will link these enhancers to their target genes using a novel mathematical model, and then validate a number of these predictions using CRISPRi. Next, we will assess which of these enhancers and genes show evidence of allelic imbalance, thus implying a genetic basis for their differential enrichment and predicting SNPs responsible for this effect. A massively parallel reporter assay will further implicate individual SNPs and TF motifs as candidates for drivers of IR, thus enabling the prediction of upstream regulators that bind and activate the enhancers. Finally, we will validate causal SNPs using base editing in cultured adipocytes testing their effects on target gene expression and insulin sensitivity. We will also validate candidate upstream regulators using a combination of gain- and loss-of-function approaches in vitro and in vivo. The key deliverable of this proposal will be the elucidation of the detailed transcriptional mechanisms underlying noncoding variation leading to human IR.

抽象的胰岛素抵抗（IR）是2型糖尿病的正弦质量，也是许多其他疾病中的致病因素国家。 IR的分子基础很复杂，并且与许多相互交织的途径有关。我们有专注于IR的核机制，包括转录因子（TFS）和表观基因组修饰剂。在先前的资金周期中，我们已经确定了细胞的几个转录调节剂和组织IR使用晚期表观基因组学策略。对于即将到来的周期，我们建议转向研究人类IR；具体而言，鉴定驱动IR开发的转录机制人脂肪细胞。为此，我们从胰岛素抵抗和敏感受试者，导致鉴定数千个具有差异的增强子 IR活动。首先，我们将使用新颖的数学模型将这些增强剂与其靶基因联系起来，并将然后使用CRISPRI验证许多此类预测。接下来，我们将评估哪些增强剂基因显示了等位基因失衡的证据，从而暗示了其差异的遗传基础并预测负责此效果的SNP。大规模平行的记者分析将进一步牵涉单个SNP和TF图案作为IR驱动程序的候选者，从而实现了上游的预测结合和激活增强器的调节器。最后，我们将使用基础编辑来验证因果SNP 培养的脂肪细胞测试其对靶基因表达和胰岛素敏感性的影响。我们还将验证候选者在体外和功能丧失方法的结合以及在体外和IN的结合体内。该提案的关键将是阐明详细的转录机制基本的非编码变化导致人类IR。