Functional genetic variants for type 2 diabetes

2 型糖尿病的功能性遗传变异

• 批准号: 9489331
• 负责人: KAREN L. MOHLKE
• 金额: $ 7.01万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 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/9489331
• 关键词: Address; Adipose tissue; Affect; Alleles; Allelic Imbalance; Awareness; Base Sequence; Binding; Biological; Biological Assay; Biometry; Blood; Cells; Characteristics; Chromatin; Computational Biology; DNA; DNA-Protein Interaction; Data; Data Correlations; Deoxyribonucleases; Diabetes Mellitus; Disease; Electrophoretic Mobility Shift Assay; Epidemiology; Formaldehyde; Gene Expression; Gene Proteins; Gene Targeting; Genes; Genetic; Genetic Transcription; Genome; Genotype; Goals; Haplotypes; Heterogeneity; High-Throughput Nucleotide Sequencing; Human Cell Line; Hypersensitivity; Inherited; Insulin Resistance; Islets of Langerhans; Knowledge; Lead; Linkage Disequilibrium; Liver; Measures; Messenger RNA; Meta-Analysis; Metabolic; MicroRNAs; Modeling; Molecular; Molecular and Cellular Biology; Morbidity - disease rate; Muscle; Non-Insulin-Dependent Diabetes Mellitus; Participant; Pathogenicity; Physiological; Physiology; Play; Protein Isoforms; Proteins; Publishing; RNA Splicing; Regulator Genes; Regulatory Element; Reporter; Resources; Risk; Role; Sampling; Signal Transduction; Site; Specificity; TCF7L2 gene; Testing; Tissues; Transcript; Translating; Transposase; Untranslated RNA; Variant; Visit; Work; base; cell type; chromatin immunoprecipitation; diabetes mellitus genetics; diabetes risk; disease diagnosis; exome sequencing; experience; experimental study; gene function; genetic variant; genome wide association study; genome-wide; glucose uptake; improved; indexing; insight; insulin secretion; islet; knock-down; mortality; multidisciplinary; new therapeutic target; novel therapeutics; overexpression; public health relevance; therapeutic target; trait; transcription factor; transcriptome sequencing

 DESCRIPTION (provided by applicant): Type 2 diabetes (T2D) genetics has realized extraordinary advances, including identification of at least 100 genetic loci at genome-wide significance. However, to convert these loci into targets for new therapies, several gaps in knowledge need to be addressed. Evidence from GWAS and exome sequencing studies strongly suggest that non-coding regulatory variants play a major role in T2D risk, although at most T2D loci, the functional variants, their target genes, the relevant tissues, and the direction of their effect to increase or decrease gene function remain unknown. Allelic heterogeneity and linkage disequilibrium (LD) can make the number of underlying signals and their identities ambiguous. In addition, functional T2D variants may lead to disease through altered insulin secretion, insulin resistance, or other aspects of metabolic risk that may involve several tissues, and the impact of altered gene expression needs to be defined. The overall goal of our proposal is to identify the functional variants, target genes and regulatory mechanisms responsible for noncoding T2D association signals. This proposal builds on our substantial experience with both T2D genetics and functional analyses, including the impressive resources of the METSIM and FUSION studies, the gene regulatory elements we defined in pancreatic islets using chromatin immunoprecipitation (ChIP-seq), DNase hypersensitivity (DNase-seq), and formaldehyde-assisted identification of regulatory elements (FAIRE-seq), and our experimental studies that implicate specific variants, tissues, and directions of effect at the TCF7L2, JAZF1, ARAP1, and CAMK1D T2D loci. We will define the physiological characteristics and multiple signals at T2D loci by testing for association with detailed quantitative traits (QTs) in METSIM and with islet, adipose, and muscle transcript levels and isoforms. Step-wise conditional analysis with simultaneous modeling of multiple loci will be used to define additional association signals, which will be compared with existing trans-ancestry fine-mapping data. We will identify regulatory variants and target genes using signals and allelic imbalances in transcription factor binding, chromatin accessibility, and RNA-seq and miRNA-seq data from T2D-relevant tissues and cells. We will apply an allele-aware pipeline to align sequence data, intersect variants with regulatory elements, and use transcription factor and chromatin allelic imbalances to distinguish likely functional variants from other candidate variants located in regulatory elements. We will identify causal relationships between variants and genes by expression QTs and allelic imbalance, integrated with QT data, and correlation of regulatory elements with expression level across cell types. Finally, we will use experimental studies to identify functional regulatory variants and the molecular mechanisms by which they influence gene and protein activity. Successful completion of these aims will translate T2D association signals into biological insights and therapeutic targets. Pathogenic variants, the mechanisms by which variants affect gene function, and their physiological consequences will be determined, guiding studies that evaluate novel therapies.

 描述（由申请人提供）：2 型糖尿病 (T2D) 遗传学已取得非凡进展，包括鉴定出至少 100 个具有全基因组意义的遗传位点。然而，为了将这些基因座转化为新疗法的靶点，需要解决一些知识空白。来自 GWAS 和外显子组测序研究的证据强烈表明，非编码调控变异在 T2D 风险中发挥着重要作用，尽管大多数 T2D 基因座、功能变异、其靶基因、相关组织和方向 它们对增加或减少基因功能的影响仍然未知。等位基因异质性和连锁不平衡 (LD) 可能会使潜在信号的数量及其身份变得模糊。此外，功能性 T2D 变异可能通过改变胰岛素分泌、胰岛素抵抗或可能涉及多个组织的代谢风险的其他方面而导致疾病， 需要定义基因表达改变的影响。我们提案的总体目标是确定负责非编码 T2D 关联信号的功能变异、靶基因和调控机制。该提案建立在我们在 T2D 遗传学和功能分析方面的丰富经验的基础上，包括 METSIM 和 FUSION 研究的令人印象深刻的资源、我们使用染色质免疫沉淀 (ChIP-seq)、DNase 超敏反应 (DNase-seq) 和甲醛辅助识别调节元件在胰岛中定义的基因调控元件 (FAIRE-seq)，以及我们的实验研究，涉及 TCF7L2、JAZF1、ARAP1 和 CAMK1D T2D 基因座的特定变异、组织和作用方向。我们将通过测试与 METSIM 中详细数量性状 (QT) 以及胰岛、脂肪和肌肉转录水平和亚型的关联来定义 T2D 基因座的生理特征和多个信号。将使用多个基因座同时建模的逐步条件分析来定义额外的关联信号，并将其与现有的跨祖先精细作图数据进行比较。我们将利用转录因子结合中的信号和等位基因不平衡、染色质可及性以及来自 T2D 相关组织和细胞的 RNA-seq 和 miRNA-seq 数据来识别调控变异和靶基因。我们将应用等位基因感知管道来比对序列数据，将变体与调控元件相交叉，并使用转录因子和染色质等位基因不平衡来区分可能的功能变体与位于调控元件中的其他候选变体。我们将通过表达 QT 和等位基因失衡、与 QT 数据整合以及调节元件与跨细胞类型表达水平的相关性来确定变异和基因之间的因果关系。最后，我们将利用实验研究来识别功能调控变异及其影响基因和蛋白质活性的分子机制。成功完成这些目标将把 T2D 关联信号转化为生物学见解和治疗靶点。致病性变异、变异影响基因功能的机制及其生理后果将被确定，从而指导评估新疗法的研究。