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: 8541853
• 负责人: David Altshuler
• 金额: $ 56.48万
• 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/8541853
• 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 Targeting; 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; exome sequencing; 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 sequencing; 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.

描述（由申请人提供）：2型糖尿病（T2 D）新的有效疗法的开发需要确定新的药物靶点，理想情况下是通过人群研究的临床获益强有力证据进行验证的药物靶点。遗传性功能丧失（LoF）变体提供了一种评估体内基因活性降低对人体影响的方法。通过观察LoF变体，可以获得靶点验证的特别有力的证据，LoF变体可以提供对疾病的保护，而不会产生不良后果（如CCR 5和PCSK 9）。 申请人已经收集了来自2，800个个体（T2 D病例和对照）中的每一个的DNA样品中的高覆盖外显子组测序数据，并且将使用“外显子组”阵列对> 45，000个个体（T2 D病例和对照）中的非同义蛋白质改变变体的综合集合进行基因分型。为了对LoF变异体的这些数据进行系统的和有效的分析，必须克服几个挑战：（a）开发和应用用于插入和缺失变异体的稳健检测的算法（LoF变体的主要机制，其用当今的算法表征不佳），并且用于所有类别的LoF变体的准确注释;（B）表征对频谱和LoF变体特征敏感的统计学检验，及其在病例和对照中检测到的LoF变体目录中的应用;（c）在大型独立样本中对推定的LoF关联进行随访。 为了系统地测试罕见的改变蛋白质的LoF变体在T2 D风险中的作用，申请人提出：（a）开发算法以检测序列数据中的插入缺失，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样品的序列和基因型数据;以及注释整个基因组的LoF变体;（B）评估用于LoF分析的罕见变异体测试的功效，并使用所选方法对LoF变异体进行关联分析，所述LoF变异体包括单独的LoF变异体和基因内的LoF变异体组，与T2 D，以及与葡萄糖、胰岛素、脂质和BMI的相关代谢性状;以及（c）通过对来自T2 D-GENES项目的多达10，000名个体（T2 D病例和对照）的数据进行计算机模拟随访，并通过对另外20，000名个体（T2 D病例和对照）进行靶向测序，验证LoF变体与T2 D风险改变（特别是对T2 D的保护）的推定关联。 人类遗传学研究的一个中心目标是提供可以指导预防和治疗突破性方法的见解。申请人一直是数据集，实验室方法和遗传分析算法开发的领导者，并且已经合作了十多年，以应用这些方法来发现T2 D的基因。现在，来自T2 D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变体对T2 D的影响成为可能，提名和验证潜在的治疗靶点。