A joint linkage/association strategy to interrogate AMD genetic susceptibility

描述(由申请人提供)： 老年性黄斑变性(AMD)是一种多种遗传和环境因素影响临床表型的复杂疾病。这种情况现在是美国老年人法律失明的主要原因。了解完整的遗传流行病学将有助于开发新的治疗方法和预防策略。与AMD相关的几个常见的遗传变异已经被识别出来。我们假设，其余的病因可以通过一些不太常见但功能上显著的遗传变异来解释。这个项目是凯西眼科研究所/俄勒冈健康与科学大学黄斑变性中心和西南生物医学研究基金会遗传学系之间令人兴奋的新合作的开始。新的AMD易感基因将通过使用强大的联合全基因组链接和关联策略在我们先前存在的150个家系集合中识别，这些家系因其对AMD的易感性而变得丰富。我们将增加识别易感性相关遗传变异的可能性，方法是使用存储的视网膜图像仔细量化表型，以识别与基因作用更密切相关的生物学特征。在高密度SNP阵列基因分型后，显示每种AMD相关表型的最佳证据的基因将在无关的AMD病例和对照中复制。还将进行整个外显子组下一代测序，以确定这些家族中存在的罕见或潜在的私人突变。贝叶斯QTN和生物信息学分析将用于预测功能变异。

DESCRIPTION (provided by applicant): Age-related macular degeneration (AMD) is a complex disease in which multiple genetic and environmental components influence the clinical phenotype. The condition is now the major cause of legal blindness in older people in the USA. Understanding the complete genetic epidemiology will enable the development of new therapies and preventive strategies. Several common genetic variants associated with AMD have been identified. We hypothesize that the remaining etiology is explained by a number of individually less common, but functionally significant genetic variants. This project is the beginning of a new and exciting collaboration between the Macular Degeneration Center at the Casey Eye Institute/Oregon Health and Science University and the Department of Genetics to accomplish at the Southwest Foundation for Biomedical Research. Novel AMD-susceptibility genes will be identified by using a powerful joint genome-wide linkage and association strategy in our pre-existing collection of 150 pedigrees enriched for their susceptibility to AMD. We will increase the likelihood of identifying susceptibility-related genetic variation by careful quantification of the phenotype using stored retinal images to identify biological characteristics more closely related to the action of genes. Genes showing the best evidence for each AMD-related phenotype following high-density SNP-array genotyping will be replicated in unrelated AMD cases and controls. Whole Exome Next Generation sequencing will also be undertaken to identify rare or potentially private mutations present in the families. Bayesian QTN and bioinformatics analysis will be used to predict functional variants.