The Impact of Human Gene Knockouts in Type 2 Diabetes and Related Traits

人类基因敲除对 2 型糖尿病及相关特征的影响

• 批准号: 8460348
• 负责人: David Altshuler
• 金额: $ 61.78万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-15 至 2016-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8460348
• 关键词: Algorithms; Alleles; CCR5 gene; Cataloging; Catalogs; Characteristics; Clinical; Clinical Data; Code; Collaborations; Collection; Computer Simulation; DNA; DNA Sequence; Data; Data Analyses; Data Set; Defect; Detection; Development; Disease; Drug Delivery Systems; Europe; European; Evaluation; Frequencies; Funding; Genes; Genetic; Genetic Research; Genome; Genotype; Glucose; Goals; HIV Infections; Human; Human Genetics; Hypertension; Individual; Inherited; Insulin; KCNJ1 gene; Laboratories; Lipids; Low-Density Lipoproteins; Metabolic; Methods; Morbidity - disease rate; Mutation; Myocardial Infarction; National Institute of Diabetes and Digestive and Kidney Diseases; Non-Insulin-Dependent Diabetes Mellitus; Nucleotides; Pain; Pharmaceutical Preparations; Play; Population; Predisposition; Prevalence; Prevention; Prevention approach; Prevention therapy; Proteins; Public Health; Research Personnel; Risk; Role; Sampling; Statistical Methods; Technology; Testing; Therapeutic; Validation; Variant; base; case control; design; diabetes control; diabetes risk; drug discovery; effective therapy; exome; follow-up; gene discovery; gene function; genetic analysis; genome sequencing; genome wide association study; improved; in vivo; insertion/deletion mutation; insight; knockout gene; loss of function; mortality; next generation; novel; research study; therapeutic target; trait

DESCRIPTION (provided by applicant): The development of new and effective therapies for type 2 diabetes (T2D) requires the identification of novel drug targets, ideally ones that are validated by strong evidence of clinical benefit from studies in human populations. Inherited loss of function (LoF) variants offer one approach to assess the impact of reducing gene activity in humans in vivo. Particularly strong evidence for target validation can be obtained by observing LoF variants that provide protection against disease without undesirable consequences (as in CCR5 and PCSK9). The applicants have collected high coverage exome sequencing data in DNA samples from each of 2,800 individuals (T2D cases and controls), and will have genotyped a comprehensive collection of non-synonymous protein altering variants in >45,000 individuals (T2D cases and controls) using the "exome" array. To perform a systematic and well powered analysis of these data for LoF variants, several challenges must be overcome: (a) development and application of algorithms for robust detection of insertion and deletion variants (a major mechanism for LoF variants which is poorly characterized with today's algorithms), and for the accurate annotation of all classes of LoF variants; (b) characterization of statistical tests that re sensitive for the frequency spectrum and characteristics of LoF variants, and their application to the catalogue of LoF variants detected in cases and controls; and (c) follow-up of putative LoF associations in large, independent samples. To test systematically the role of rare protein-altering LoF variants in risk of T2D, the applicants propose: (a) to develop algorithms to detect indels in sequence data, and larger deletions using data from the exome array; to apply these algorithms to sequence and genotype data totalling >47,000 DNA samples; and to annotate LoF variants across the genome; (b) to evaluate the power of rare variant tests for LoF analysis, and to perform association analyses using chosen methods for LoF variants, both singly and for sets of LoF variants within a gene, with T2D, as well as with the related metabolic traits of glucose, insulin, lipids, and BMI; and (c) to validate putative associations of LoF variants with altered rik of T2D (in particular, protection from T2D) by performing in silico follow-up in data on up to 10,000 individuals (T2D cases and controls) from the T2D-GENES Project, and by targeted sequencing in 20,000 additional individuals (T2D cases and controls). A central goal of human genetics research is to provide insights that can guide breakthrough approaches to prevention and therapy. The applicants have been leaders in the development of datasets, laboratory methods, and algorithms for genetic analysis, and have collaborated for over a decade to apply these methods to discover genes for T2D. Now, the convergence of large clinical samples from T2D cases and controls, of next-generation sequencing technology, and of algorithmic improvements make it possible to evaluate systematically LoF variants for effects on T2D, nominating and validating potential therapeutic targets. PUBLIC HEALTH RELEVANCE: The rising prevalence of type 2 diabetes in the US and worldwide represents one of the major challenges to public health, and improved options for treatment and prevention are required. The present proposal builds on a longstanding and productive collaboration between researchers in the US and Europe to understand the genetic basis of type 2 diabetes, and to use this information to reveal disease mechanisms. In this proposal, we will focus on the subset of DNA sequence variants that have the most dramatic effects on gene function (loss of function coding variants), and seek to define the role that these play in type 2 diabetes predisposition.

描述（由申请人提供）：开发2型糖尿病（T2D）的新有效疗法需要鉴定新的药物靶标，理想情况下，这些糖尿病是通过人群研究中临床益处的有力证据来验证的。遗传功能丧失（LOF）变体提供了一种方法来评估减少体内人类基因活性的影响。可以通过观察LOF变体可获得防止疾病而没有不良后果的LOF变体（如CCR5和PCSK9中）来获得目标验证的特别有力证据。 申请人已收集了来自2,800个个体（T2D病例和对照组）中每个个体的DNA样品中的高覆盖外显子组测序数据，并将使用“ Exome”阵列彻底收集了> 45,000个个体（T2D病例和对照）中非同义蛋白改变变体的全面收集。要对LOF变体进行系统的系统分析，必须克服几个挑战：（a）开发和应用算法，用于可靠地检测插入和缺失变体（LOF变体的主要机制）（与当今算法相关的主要特征），以及所有lof veriants of Lof veriants sermate senteration senteration senteration of lof sentiants; （b）表征对LOF变体的频谱和特征敏感的统计检验，以及它们在案例和对照中检测到的LOF变体目录中的应用； （c）大型独立样本中推定的LOF关联的随访。 为了系统地测试稀有蛋白质改变LOF变体在T2D风险中的作用，申请人提出：（a）开发算法以序列数据检测indinels，并使用来自Exome阵列的数据进行较大的删除；将这些算法应用于序列和基因型数据，总计> 47,000个DNA样品；并注释整个基因组的LOF变体； （b）评估LOF分析的稀有变体测试的能力，并使用所选方法对LOF变体进行了关联分析，无论是单独的和具有T2D的LOF变体的集合，以及具有T2D的LOF变体，以及与葡萄糖，胰岛素，脂质，脂质和BMI的相关代谢性状； （c）通过对T2D的RIK（尤其是保护T2D的RIK）验证推定的关联，通过对T2D基因项目的多达10,000个个体（T2D病例和对照）进行硅的随访，并在20,000个其他个体（T2D病例和对照组中）中对多达10,000个个体（T2D病例和对照组）进行验证。 人类遗传学研究的一个核心目标是提供可以指导预防和治疗突破方法的见解。申请人一直是用于遗传分析的数据集，实验室方法和算法的领导者，并且已经合作了十多年，以应用这些方法来发现T2D的基因。现在，来自T2D病例和对照，下一代测序技术以及算法改进的大型临床样本的收敛使您可以系统地评估对T2D的影响，提名和验证潜在的治疗靶标。 公共卫生相关性：美国和全球2型糖尿病的患病率上升是公共卫生面临的主要挑战之一，需要改善治疗和预防选择。本提案建立在美国和欧洲研究人员之间的长期和富有成效的合作上，以了解2型糖尿病的遗传基础，并使用这些信息来揭示疾病机制。在此提案中，我们将重点关注对基因功能（功能编码变体丢失）具有最大作用的DNA序列变体的子集，并试图定义这些作用 玩2型糖尿病易感性。