Functional genetic variants for type 2 diabetes

 描述（由申请人提供）：2型糖尿病（T2 D）遗传学已经取得了非凡的进展，包括鉴定出至少100个具有全基因组意义的遗传基因座。然而，要将这些基因座转化为新疗法的靶点，需要解决几个知识空白。来自GWAS和外显子组测序研究的证据强烈表明，非编码调控变体在T2 D风险中起主要作用，尽管在大多数T2 D基因座，功能变体、其靶基因、相关组织和方向突变在T2 D风险中起重要作用。 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）可以使潜在信号的数量和它们的身份模糊不清。此外，功能性T2 D变体可能通过改变胰岛素分泌、胰岛素抵抗或可能涉及几种组织的代谢风险的其他方面导致疾病， 基因表达改变的影响需要明确。我们建议的总体目标是确定负责非编码T2 D关联信号的功能变体、靶基因和调控机制。该提案基于我们在T2 D遗传学和功能分析方面的丰富经验，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在胰岛中定义的基因调控元件（ChIP-seq），DNA酶超敏反应（DNase-seq），以及甲醛辅助的调控元件鉴定（FAIRE-seq），以及我们的实验研究，这些研究涉及TCF 7 L2，JAZF 1，ARAP 1和CAMK 1D T2 D基因座的特定变体，组织和作用方向。我们将通过测试与METSIM中的详细数量性状（QT）以及与胰岛、脂肪和肌肉转录水平和亚型的关联来定义T2 D基因座的生理特征和多种信号。逐步条件分析与多个基因座的同时建模将被用来定义额外的关联信号，这将与现有的跨祖先精细映射数据进行比较。我们将使用来自T2 D相关组织和细胞的转录因子结合、染色质可及性以及RNA-seq和miRNA-seq数据中的信号和等位基因不平衡来识别调控变体和靶基因。我们将应用等位基因感知管道来比对序列数据，将变体与调控元件交叉，并使用转录因子和染色质等位基因失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和等位基因不平衡，结合QT数据，以及调控元件与细胞类型表达水平的相关性来确定变体和基因之间的因果关系。最后，我们将使用实验研究来确定功能调节变体和它们影响基因和蛋白质活性的分子机制。这些目标的成功完成将把T2 D相关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，指导评估新疗法的研究。

 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.