Statistical Method for Identifying Genetic Modifiers of Conotruncal Heart De

鉴定圆锥干心脏 De 遗传修饰的统计方法

• 批准号: 9172470
• 负责人: Tao Wang
• 金额: $ 16.89万
• 依托单位: ALBERT EINSTEIN COLLEGE OF MEDICINE, INC
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-01 至 2016-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9172470
• 关键词: Statistical; Method; Identifying; Genetic; Modifiers; Statistical; Method; Identifying; Genetic; Modifiers

DESCRIPTION (provided by applicant): Genetic heterogeneity is one of the major reasons for failure to identify genetic associations of complex diseases. Often, patients with complex diseases have various phenotypic characteristics and can be grouped into variable subtypes, possibly reflecting differences in underlying genetic mechanisms. Existing approaches either ignore genetic heterogeneity among patients, or lack parsimony with a large number of degrees of freedom in test statistics. There is a lack of statistical approaches that can efficiently combie association evidence from varied disease subtypes while accounting for genetic heterogeneity. As such, we propose to test genetic association using a novel three-stage polynomial logistic regression model, which takes genetic heterogeneity among disease subtypes into account while reducing large number of parameters for testing genetic association. We plan to apply the proposed approach to a real dataset from a collaboration study with the goal to find genetic associations of structural cardiovascular malformations in 22q11DS children. We expect that the proposed project will yield a new powerful statistical approach and the corresponding software for identifying genetic associations of complex diseases, and has the potential to identify novel genetic variants, genes and pathways, providing an insight into biological mechanisms of congenital heart defects.

描述（由申请人提供）：遗传异质性是未能识别复杂疾病遗传关联的主要原因之一。通常，患有复杂疾病的患者具有多种表型特征，可以分为可变的亚型，可能反映了潜在的遗传机制的差异。现有方法要么忽略患者之间的遗传异质性，要么缺乏具有大量自由度的测试统计自由度的简约性。缺乏统计方法，可以在考虑遗传异质性的同时有效地将各种疾病亚型的关联证据梳理。因此，我们建议使用一种新型的三阶段多项式回归模型来测试遗传关联，该模型将疾病亚型的遗传异质性考虑到了，同时减少了大量参数以测试遗传关联。我们计划将提出的方法应用于合作研究中的真实数据集中，其目标是在22Q11DS儿童中找到结构性心血管畸形的遗传关联。我们预计拟议的项目将产生一种新的强大统计方法和相应的软件，以识别复杂疾病的遗传关联，并有可能识别新颖的遗传变异，基因和途径，从而深入了解先天性心脏缺陷的生物学机制。