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作用引起。1型糖尿病遗传联盟（T1DGC）成立于2001年，旨在收集开展大规模T1D遗传研究所需的资源。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发现，其中包含2,658个受影响的兄弟姐妹对（asp），其中包含超过6,000个snp的信息，以及对7,698例病例和9,068例对照的超过800,000个snp进行全基因组关联扫描（GWAS） meta分析。通过连锁扫描，获得了支持6p21.3 （HLA）、6q、2q32.3 （CTLA4）、11p15.5 （INS）和19号染色体上两个新区域T1D易感基因的证据。从GWAS中，鉴定出27个新区域，在4,267例病例、4,463例对照和2,319个受影响兄弟姐妹对（ASP）家庭的独立组中，有18个重复区域（P < 0.01）。在这些样本中名义上复制了另外四个区域。T1DGC关注的是基因组中可能改变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）增加了许多人类疾病的风险，包括自闭症、精神分裂症、骨质疏松症、早期心肌梗死和克罗恩病。虽然CNV显然是人类遗传变异的一个重要来源，但目前还没有评估CNV对T1D风险贡献的出版物。该DP3应用程序提出表征CNVs在2,496个ASP家族的T1DGC集合中T1D风险中的作用，并在T1D ASP，三家族，病例和对照的单独集合中复制研究结果。T1DGC提出了一种全基因组CNVs分析方法，该方法将(a)使用Agilent 8x60K CNV基因分型芯片对2496个T1DGC ASP家族（T1D家族病例）的常见CNVs进行全基因组分型，并进行统计遗传分析，以确定与T1D相关性最强的CNVs；(b)在其他T1D ASP家族、三元组和病例/对照中使用位点特异性分析重复上述假定的关联；(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CNVs进行关联测试；(d)使用1M Agilent CNV芯片，使用384个T1DGC GWAS样本的子集，确定从挖掘T1DGC GWAS数据中无法识别的稀有LOF CNV的比例。我们的假设是，CNVs增加了T1D的遗传风险。此外，cnv的一个子集可能存在于T1DGC GWAS meta分析已经确定的区域，因此，增加了候选基因在调控中具有特定功能的可能性，从而确定了潜在的治疗靶点。重要的是要针对整个基因组来识别潜在的cnv影响的T1D风险位点。

项目成果

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

全基因组对1型糖尿病中未标记拷贝数变异的作用的评估。

• DOI: 10.1371/journal.pgen.1004367
• 发表时间: 2014
• 期刊: PLoS genetics
• 影响因子: 4.5
• 作者: Zanda M;Onengut-Gumuscu S;Walker N;Shtir C;Gallo D;Wallace C;Smyth D;Todd JA;Hurles ME;Plagnol V;Rich SS
• 通讯作者: Rich SS

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。

• DOI: 10.1002/gepi.21674
• 发表时间: 2012
• 期刊: Genetic epidemiology
• 影响因子: 2.1
• 作者: Zanda,Manuela;Onengut,Suna;Walker,Neil;Todd,JohnA;Clayton,DavidG;Rich,StephenS;Hurles,MatthewE;Plagnol,Vincent
• 通讯作者: Plagnol,Vincent