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）：开发新的有效的2型糖尿病（T2D）治疗方法需要确定新的药物靶点，理想情况下，这些靶点需要有强有力的证据证明从人类群体研究中获得临床益处。遗传功能丧失（LoF）变异提供了一种评估人类体内基因活性降低影响的方法。通过观察LoF变异（如CCR5和PCSK9），可以获得靶标验证的特别有力的证据，这些变异提供了对疾病的保护而没有不良后果（如CCR5和PCSK9）。申请人已经从2800名个体（T2D病例和对照组）的DNA样本中收集了高覆盖率的外显子组测序数据，并将使用“外显子组”阵列对bbbb45000名个体（T2D病例和对照组）的非同义蛋白改变变体进行全面的基因分型。为了对LoF变体的这些数据进行系统和有效的分析，必须克服以下几个挑战：(a)开发和应用用于插入和删除变体的鲁棒检测的算法（LoF变体的主要机制，目前的算法对其特征描述不佳），以及对所有类型的LoF变体的准确注释；(b)确定对LoF变异的频谱和特征敏感的统计测试的特征，并将其应用于在病例和对照中检测到的LoF变异目录；(c)对大型独立样本中假定的LoF关联进行随访。为了系统地测试罕见的改变蛋白质的LoF变异在T2D风险中的作用，申请人提出：(a)开发算法来检测序列数据中的缺失，以及使用来自外显子组阵列的数据的较大缺失；将这些算法应用于总计47,000个DNA样本的测序和基因型数据；并对基因组中的LoF变异进行注释；(b)评估LoF分析的罕见变异测试的能力，并使用选定的方法对LoF变异进行关联分析，包括单个LoF变异和基因内的LoF变异集，与T2D以及与葡萄糖、胰岛素、脂质和BMI相关的代谢特征；(c)通过对来自T2D- genes项目的多达10,000个个体（T2D病例和对照）的数据进行计算机随访，并对另外20,000个个体（T2D病例和对照）进行靶向测序，验证LoF变异与T2D风险改变（特别是对T2D的保护）的假定关联。人类遗传学研究的一个中心目标是提供能够指导突破性预防和治疗方法的见解。申请人在数据集、实验室方法和遗传分析算法的开发方面一直处于领先地位，并且已经合作了十多年，将这些方法应用于发现T2D的基因。现在，来自T2D病例和对照的大量临床样本、下一代测序技术和算法改进的融合，使得系统地评估LoF变异对T2D的影响、提名和验证潜在的治疗靶点成为可能。