The role of copy number variants (CNV) in type 1 diabetes

拷贝数变异 (CNV) 在 1 型糖尿病中的作用

• 批准号: 7798326
• 负责人: Stephen S. Rich
• 金额: $ 643.07万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-20 至 2014-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7798326
• 关键词: 11p15.5; 6p21.3; Affect; Autistic Disorder; Autoimmune Diseases; Biological Assay; CTLA4 gene; Candidate Disease Gene; Chromosomes, Human, Pair 19; Collection; Complex; Computer Simulation; Copy Number Polymorphism; Crohn' s disease; Data; Disease; Environmental Risk Factor; Eye; Family; Genetic; Genetic Risk; Genome; Genotype; Heart; Human Genetics; Human Genome; Insulin-Dependent Diabetes Mellitus; Intervention; Kidney; Meta-Analysis; Mining; Morbidity - disease rate; Myocardial Infarction; Nerve; Nucleotides; Osteoporosis; Prevention; Public Health; Publications; Regulation; Reporting; Research; Research Design; Resources; Risk; Role; Sampling; Scanning; Schizophrenia; Source; Susceptibility Gene; Testing; Therapeutic; United States; Variant; case control; data mining; diabetes mellitus genetics; diabetes risk; genetic analysis; genetic risk factor; genome wide association study; genome-wide; genome-wide analysis; genome-wide linkage; human disease; mortality; novel; public health relevance; therapeutic target

DESCRIPTION (provided by applicant): Type 1 diabetes (T1D) is a complex autoimmune disorder that arises from the action of multiple genetic and environmental risk factors. The Type 1 Diabetes Genetics Consortium (T1DGC) was established in 2001 to assemble the resources necessary for conducting large-scale genetic studies of T1D. The T1DGC recently reported the findings of a genome-wide linkage scan in 2,496 multiplex T1D families containing 2,658 affected sib-pairs (ASPs) with information on over 6,000 SNPs, and a genome-wide association scan (GWAS) meta- analysis of over 800,000 SNPs in 7,698 cases and 9,068 controls. From the linkage scan, evidence was obtained supporting T1D susceptibility genes in 6p21.3 (HLA), 6q, 2q32.3 (CTLA4), 11p15.5 (INS) and two novel regions on chromosome 19. From the GWAS, 27 novel regions were identified and 18 replicated with P < 0.01 in an independent set of 4,267 cases, 4,463 controls and 2,319 affected sib-pair (ASP) families. Four additional regions were nominally replicated in these samples. The T1DGC has focused on the role of single nucleotide changes in the genome that may modify risk of T1D; however, it is becoming increasingly apparent that copy-number variation (CNV) contributes to the risk for a number of human diseases, including autism, schizophrenia, osteoporosis, early myocardial infarction, and Crohn's disease. Although CNV is clearly an important source of human genetic variation, there have been no publications evaluating the contribution of CNVs to T1D risk. This DP3 application proposes to characterize the role of CNVs in T1D risk in the T1DGC collection of 2,496 ASP families and replicate the findings in a separate collection of T1D ASPs, trio families, cases and controls. The T1DGC proposes a genome-wide analysis of CNVs that will (a) perform genome-wide typing of common CNVs in 2,496 T1DGC ASP families (familial cases of T1D) using the Agilent 8x60K CNV genotyping chip and conduct statistical genetic analysis to identify the most strongly associated CNVs with T1D; (b) replicate the putative associations above in additional T1D ASP families, trios and cases/controls using locus-specific assays; (c) conduct association testing of rare, large CNVs using an in silico data mining approach from T1DGC GWAS data; and (d) identify the proportion of rare LOF CNVs not identifiable from mining T1DGC GWAS data using a subset of 384 T1DGC GWAS samples using a 1M Agilent CNV chip. Our hypothesis is that CNVs contribute to the genetic risk for T1D. Further, a subset of the CNVs may reside in regions already identified by the T1DGC GWAS meta-analysis and, therefore, increase the likelihood that the candidate gene may have a specific function in regulation, thereby identifying potential therapeutic targets. It is important to target the entire genome to identify potential CNV-influenced T1D risk loci. PUBLIC HEALTH RELEVANCE: Type 1 diabetes (T1D) is a complex autoimmune disorder that arises from the action of multiple genetic and environmental risk factors with significant burden to the public health of the United States through the complications (eye, kidney, heart, nerves) and its associated morbidity and mortality. This research proposes to scan the human genome in order to identify structural variants (copy number variants, CNVs) are associated with risk of T1D. Identification of genetic risk factors for T1D is the first step in risk prediction, intervention and developing disease therapeutics (prevention).

描述（由申请人提供）：1 型糖尿病 (T1D) 是一种复杂的自身免疫性疾病，由多种遗传和环境风险因素的作用引起。 1 型糖尿病遗传学联盟 (T1DGC) 成立于 2001 年，旨在汇集开展大规模 T1D 遗传学研究所需的资源。 T1DGC 最近报告了对 2,496 个多重 T1D 家族进行全基因组连锁扫描的结果，其中包含 2,658 个受影响的同胞对 (ASP)，其中包含超过 6,000 个 SNP 的信息，以及对超过 800,000 个 SNP 进行的全基因组关联扫描 (GWAS) 荟萃分析。 7,698 个病例和 9,068 个对照中的 SNP。从连锁扫描中，获得了支持 T1D 易感基因的证据：6p21.3 (HLA)、6q、2q32.3 (CTLA4)、11p15.5 (INS) 和 19 号染色体上的两个新区域。从 GWAS 中，发现了 27 个新区域在一组独立的 4,267 例病例、4,463 名对照和2,319 个受影响的兄弟姐妹 (ASP) 家庭。在这些样本中名义上复制了另外四个区域。 T1DGC 重点关注基因组中可能改变 T1D 风险的单核苷酸变化的作用；然而，越来越明显的是，拷贝数变异（CNV）会增加许多人类疾病的风险，包括自闭症、精神分裂症、骨质疏松症、早期心肌梗塞和克罗恩病。尽管 CNV 显然是人类遗传变异的重要来源，但目前还没有出版物评估 CNV 对 T1D 风险的影响。该 DP3 应用建议在 2,496 个 ASP 家族的 T1DGC 集合中描述 CNV 在 T1D 风险中的作用，并在 T1D ASP、三重家族、病例和对照的单独集合中复制研究结果。 T1DGC 提出对 CNV 进行全基因组分析，该分析将 (a) 使用安捷伦 8x60K CNV 基因分型芯片对 2,496 个 T1DGC ASP 家族（T1D 家族病例）中的常见 CNV 进行全基因组分型，并进行统计遗传分析，以识别最常见的 CNV。 CNV 与 T1D 密切相关； (b) 使用位点特异性测定在其他 T1D ASP 家族、三重奏和病例/对照中复制上述假定的关联； (c) 使用来自 T1DGC GWAS 数据的计算机数据挖掘方法对罕见的大型 CNV 进行关联测试； (d) 使用 1M 安捷伦 CNV 芯片，使用 384 个 T1DGC GWAS 样本的子集，确定通过挖掘 T1DGC GWAS 数据无法识别的罕见 LOF CNV 的比例。我们的假设是 CNV 会增加 T1D 的遗传风险。此外，CNV 的一个子集可能位于 T1DGC GWAS 荟萃分析已识别的区域中，因此增加了候选基因可能具有特定调节功能的可能性，从而识别潜在的治疗靶点。重要的是要针对整个基因组来识别潜在的受 CNV 影响的 T1D 风险位点。 公共卫生相关性： 1 型糖尿病 (T1D) 是一种复杂的自身免疫性疾病，由多种遗传和环境危险因素的作用引起，通过并发症（眼、肾、心脏、神经）及其相关发病率给美国的公共卫生造成重大负担和死亡率。这项研究建议扫描人类基因组，以确定与 1 型糖尿病风险相关的结构变异（拷贝数变异，CNV）。识别 T1D 遗传风险因素是风险预测、干预和开发疾病治疗（预防）的第一步。

项目成果

A genome-wide assessment of the role of untagged copy number variants in type 1 diabetes.

对未标记拷贝数变异在 1 型糖尿病中的作用进行全基因组评估。

• 发表时间: 2014
• 影响因子: 4.5
• 作者: Zanda, Manuela;Onengut;Walker, Neil;Shtir, Corina;Gallo, Daniel;Wallace, Chris;Smyth, Deborah;Todd, John A;Hurles, Matthew E;Plagnol, Vincent;Rich, Stephen S
• 通讯作者: Rich, Stephen S

Validity of the family-based association test for copy number variant data in the case of non-linear intensity-genotype relationship.

在非线性强度-基因型关系的情况下，基于家族的关联测试对拷贝数变异数据的有效性。

• 发表时间: 2012-12
• 影响因子: 2.1
• 作者: Zanda, Manuela;Onengut, Suna;Walker, Neil;Todd, John A;Clayton, David G;Rich, Stephen S;Hurles, Matthew E;Plagnol, Vincent
• 通讯作者: Plagnol, Vincent