Whole Genome Association Analysis of the Diabetes Heart Study
Whole Genome Association Analysis of the Diabetes Heart Study
批准号:
7782636
负责人:
DONALD W BOWDEN
金额:
$72.43万
依托单位国家:
美国
项目类别:
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-04-01 至 2014-01-31
关键词:
AdmixtureAffectAmericanAmishAmplifiersAncillary StudyArterial DisorderArteriesAtherosclerosisBioinformaticsBiologyBlood VesselsCalcifiedCandidate Disease GeneCardiovascular DiseasesCaringCarotid Artery PlaquesCarotid Atherosclerotic DiseaseClinicalCollaborationsCommunitiesComputer SimulationCopy Number PolymorphismCoronaryDNA ResequencingDataData SetData SourcesDatabasesDepositionDevelopmentDiabetes MellitusEpidemiologyEthnic OriginEuropeanEvaluationEventFamilyFamily StudyFoundationsFramingham Heart StudyFutureGenesGeneticGenetic PolymorphismGenomeGenome ScanGenomicsGenotypeGoalsHeartHeart DiseasesIndividualMeasuresMeta-AnalysisMethodsMolecular GeneticsNon-Insulin-Dependent Diabetes MellitusPatientsPhasePhenotypePoliciesPopulationProductivityPublicationsRaceRecruitment ActivityResourcesRiskSamplingSampling StudiesScanningTestingThickUltrasonographyVariantVascular calcificationX-Ray Computed Tomographybasecalcificationdata sharingdatabase of Genotypes and Phenotypesexperiencefollow-upgene discoverygenetic analysisgenetic epidemiologygenome wide association studyinnovationinsightmortalitynovelpublic health relevanceresearch studytrait
中文摘要
描述(由申请人提供):本提案的目标是确定糖尿病患者心血管疾病(CVD)的基因。糖尿病对心血管疾病的发展有着深远的影响。本研究的重点是CVD的亚临床测量:血管钙化斑块和颈动脉粥样硬化。在糖尿病心脏研究的第一阶段,我们成功招募了564个患有多发性2型糖尿病(T2DM)的家庭中的1443名受试者,并对其进行了广泛的表型分析。这为研究糖尿病富集人群(85%)的心血管疾病和其他相关特征创造了独特的数据资源。进行了广泛的遗传和流行病学分析。这些结果为利用全基因组关联研究(GWAS)方法鉴定重要基因提供了坚实的基础。具体目标是:1);糖尿病心脏研究受试者的GWAS基因分型和分析。整个欧美样本将在Affymetrix SNP Array 6.0平台上进行基因分型。将对基因型数据进行综合分析,以确定与血管钙化斑块和颈动脉壁厚度亚临床CVD的主要指标相关的位点/基因。2). 冠状动脉钙化斑块与颈动脉壁厚度的meta分析。将在Framingham心脏研究、动脉病变遗传流行病学网络(GENOA)、Amish家族钙化研究(AFCS)和糖尿病心脏研究中对欧美样本进行冠状动脉钙化斑块和颈动脉壁厚度的GWAS数据的meta分析。将评估Aims 2中的高分多态性在其他研究样本中的复制性,以进一步测试与以下因素的关联:a)欧洲裔美国人的流行心血管疾病,b)其他种族/种族的亚临床心血管疾病,以及c)其他种族/种族的流行心血管疾病。4)。密集的分子遗传分析,新颖的分析和生物信息学方法将用于识别影响变异的性状。从Aims 2和3中获得的最佳复制位点将进行额外的基因分型(如果合适)和重测序,以明确定义风险位点。创新的分析方法将用于定义性状相关的变异。我们组建了一支经验丰富、高效的跨学科团队来进行这项有前途的研究。
英文摘要
DESCRIPTION (provided by applicant): The goal of this proposal is to identify genes that contribute to cardiovascular disease (CVD) in people with diabetes. Diabetes is a profound influence on CVD development. The focus of this study is subclinical measures of CVD: vascular calcified plaque and carotid atherosclerosis. In the first phase of the Diabetes Heart Study we successfully recruited and extensively phenotyped 1443 subjects in 564 families with multiple type 2 diabetes (T2DM) affected subjects. This created a unique data resource for the study of CVD and other related traits in a diabetes-enriched (85%) population. Extensive genetic and epidemiological analyses were performed. These results provide a strong foundation for the proposed identification of important genes using a Genome Wide Association Study (GWAS) approach. Specific Aims are: 1). GWAS genotyping and analysis of subjects from the Diabetes Heart Study. The entire European American sample will be genotyped on the Affymetrix SNP Array 6.0 platform. A comprehensive analysis of the genotypic data will be carried out to identify loci/genes associated with the primary measures of subclinical CVD of vascular calcified plaque and carotid wall thickness. 2). Replication and meta analyses of coronary calcified plaque and carotid wall thickness. A meta analysis of European American samples with GWAS data for coronary calcified plaque and, where possible, carotid wall thickness, will be performed in the Framingham Heart Study, Genetic Epidemiology Network of Arteriopathy (GENOA), Amish Family Calcification Study (AFCS), and the Diabetes Heart Study. 3). High scoring polymorphisms from Aims 2 will be evaluated for replication in other study samples to further test for association with: a) prevalent CVD in European Americans, b) subclinical CVD in other ethnicities/races, and c) prevalent CVD in other ethnicities/races. 4). Intensive molecular genetic analysis, novel analytic, and bioinformatic approaches will be used to identify trait influencing variants. The best replicated loci from the Aims 2 & 3 will be subjected to additional genotyping (if appropriate) and resequencing to clearly define risk loci. Innovative analysis approaches will be used to define trait associated variants. We have assembled an experienced, highly productive, interdisciplinary team to perform this promising study.
PUBLIC HEALTH RELEVANCE: In this research study, genes which contribute to heart disease in people with diabetes will be identified.
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海外基金