Phenotype-Genotype Interactions and Type 2 Diabetes

描述（由申请人提供）：2型糖尿病在全球范围内的流行比例正在增加。控制糖尿病需要了解其发病机制中涉及的基因和基因-环境相互作用。连锁分析是识别糖尿病等复杂疾病基因的关键初始策略，但许多研究仅提供了与2型糖尿病或相关性状基因组连锁的暗示性证据。异质性2型糖尿病表型有助于适度的连锁信号。特别是，三个主要的表型糖尿病风险因素：父母糖尿病，后代肥胖和老年相关的发病，都引入异质性，削弱了基因与糖尿病表达的关联。Frachial Heart研究（FHS）收集了广泛的横截面和纵向表型数据，并对来自相对同质社区的330个家系内的1702个父母和后代的基因组微卫星标记进行了分型。在这个R21应用程序中，我们提出了现有FHS数据的二次分析，作为一种具有成本效益的手段来测试糖尿病遗传学的假设，并指导下一步的定位克隆。我们将关注染色体Iq、10 q和1 Iq，其中在未分层分析中存在与糖尿病性状的暗示性联系。我们将通过定义表型亚层来减少表型异质性，包括有和没有父亲和/或母亲糖尿病的家庭，相对瘦与相对肥胖的家庭，或相对年轻与相对老年发病的糖尿病家庭。糖尿病表型包括偶发糖尿病或糖尿病相关的数量性状（HbA 1c、葡萄糖和胰岛素的血浆水平）。分析将使用分层有序子集的方差分量（VC）模型，或将包括基因与分层相互作用的正式测试，或考虑印记效应、可变发病年龄表型（生存分析）或时变性状（VC纵向性状分析）。我们的假设是，连锁分析，减少异质性将细化证据的连锁智商，10 q，1智商，并将确定亚层糖尿病基因更有可能被隔离。结果将为未来的实验室工作提供基础，并将增加对糖尿病发病机制中表型-基因型相互作用的理解。

DESCRIPTION (provided by applicant): Type 2 diabetes mellitus is increasing in epidemic proportions worldwide. Control of diabetes requires an understanding of the genes and gene-environment interactions involved in its pathogenesis. Linkage analysis is a key initial strategy to identify genes for complex disorders like diabetes, but many studies provide only suggestive evidence for genomic linkage to type 2 diabetes or related traits. The heterogeneous type 2 diabetes phenotype contributes to modest linkage signals. In particular, three major phenotypic diabetes risk factors: parental diabetes, offspring obesity, and older age-related onset, all introduce heterogeneity that weakens the association of genes with expression of diabetes. The Framingham Heart Study (FHS) has collected extensive cross-sectional and longitudinal phenotypic data and typed genomic micro satellite markers on 1702 parents and offspring within 330 pedigrees from a relatively homogeneous community. In this R21 application we propose secondary analyses of existing FHS data as a cost-effective means to test hypotheses about diabetes genetics and to guide next steps for positional cloning. We will focus on chromosomes Iq, lOq, and 1 Iq, where there is suggestive linkage to diabetes traits in unstratified analyses. We will reduce phenotypic heterogeneity by defining phenotypic sub-strata, including families with and without paternal and/or maternal diabetes, relatively lean vs. relatively obese families, or families with relatively younger vs. relatively older-onset diabetes. Diabetes phenotypes include incident diabetes or diabetes-related quantitative traits (plasma levels of HbAic, glucose and insulin). Analyses will use variance components (VC) models of ordered subsets of strata, or will include formal tests of gene-by-strata interaction, or account for imprinting effects, variable age-of-onset phenotypes (in survival analyses), or for time-varying traits (in VC longitudinal trait analyses). Our hypothesis is that linkage analyses that reduce heterogeneity will refine evidence for linkage on Iq, 10q, 1 Iq, and will identify sub-strata where diabetes genes are more likely to be segregating. Results will provide a foundation for future laboratory efforts and will increase understanding of phenotype-genotype interactions in diabetes pathogenesis.