Family Based Tests of Association for Complex Diseases

复杂疾病关联的家庭测试

基本信息

批准号：
7764804
负责人：
NAN MCKENZIE LAIRD
金额：
$ 31.37万
依托单位：
HARVARD SCHOOL OF PUBLIC HEALTH
依托单位国家：
美国
项目类别：
财政年份：
1998
资助国家：
美国
起止时间：
1998-09-30 至 2012-02-29
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7764804
关键词：
Affect Algorithms Alzheimer&apos s Disease Area Asthma Attention deficit hyperactivity disorder Australia Bipolar Disorder Boston Chromosomes Chronic Obstructive Airway Disease Cohort Studies Collaborations Collection Complex Computer software Data Development Disease Disease susceptibility Education Family France Funding Gene Expression Genes Genetic Genetic Models Genomics Genotype Guidelines Haplotypes Human Genome Project Measures Mental Health Methodology Methods Mexico Micro Array Data Modeling Nicotine Dependence Nuclear Family Nucleotides Outcome Parents Participant Phase Phenotype Population Relative (related person)Research Sample Size Screening procedure Single Nucleotide Polymorphism Suggestion Sweden Testing Time Validation Work X Chromosome analytical method base case control conditioning density design family structure flexibility gene environment interaction gene interaction genetic association genetic pedigree genome wide association study genotyping technology method development proband response success trait

项目摘要

DESCRIPTION (provided by applicant): This application will develop statistical methodology and software for genetic association studies with special emphasis on complex disorders in mental health. The success of the Human Genome Project and related efforts, as well as the new genotyping technologies, has revolutionized our ability to understand the genetic underpinnings of complex disorders. The widespread availability of Single Nucleotide Polymorphisms (SNPs) means that genomic regions can be saturated with thousands of SNPs with sufficient density so that, with sufficient sample sizes and appropriate methods for handling the multiple comparisons problem, we can locate Disease Susceptibility Loci using ordinary association studies. Conventional case/control and case/cohort studies are often used in this setting because of their relative ease of collection and good power. Our work has focused on family based genetic association tests because they can protect against potentially spurious results that can arise when there is population substructure. We have previously developed a general approach to the analysis of family data which maintains robustness in a variety of non-standard designs, including missing parents and measured or time-to-onset phenotypes. A potential criticism of our approach is that we do not use 'non- informative' families, or families which do not contain within family information about association. We have turned this potential criticism to an advantage by developing a unique 'screening' algorithm which enables us to handle the multiple comparisons problem quite effectively. In this application we plan to develop additional methodology for family based association tests, and accompanying software in the following areas: tests for gene-gene and gene-environment interaction, tests for whole genome scans involving dichotomous outcomes, methods for identification of complex networks of cis- and trans- acting genes using gene expression data in pedigrees, and tests for association with genes on the x- chromosome. The methods development and implementation will utilize real data from our collaborators in Bipolar Disorder, Nicotine Addiction, Attention Deficit Hyperactivity Disorder, Alzheimer's disease, Asthma, Chronic Obstructive Pulmonary Disease, among others.

描述（由申请人提供）：本申请将开发用于遗传关联研究的统计方法和软件，并特别强调心理健康中的复杂疾病。人类基因组项目和相关工作以及新的基因分型技术的成功彻底改变了我们了解复杂疾病的遗传基础的能力。单核苷酸多态性（SNP）的广泛可用性意味着，基因组区域可以被数千个具有足够密度的SNP饱和，因此，使用普通的关联研究，我们可以通过足够的样本量和适当的方法来处理多重比较问题，我们可以为疾病易感性所见。常规案例/控制和案例/队列研究在这种情况下经常使用，因为它们相对易于收集和良好的功率。我们的工作集中在基于家庭的遗传关联测试上，因为它们可以防止在人口子结构时可能出现的潜在虚假结果。我们以前已经开发了一种对家庭数据分析的一般方法，该方法在各种非标准设计中保持稳健性，包括失踪的父母和测量或发作时间表型。对我们方法的潜在批评是，我们不使用“非信息性”家庭或不包含有关关联的家庭中不包含的家庭。通过开发一种独特的“筛选”算法，我们将这种潜在的批评转变为优势，这使我们能够非常有效地处理多重比较问题。 In this application we plan to develop additional methodology for family based association tests, and accompanying software in the following areas: tests for gene-gene and gene-environment interaction, tests for whole genome scans involving dichotomous outcomes, methods for identification of complex networks of cis- and trans- acting genes using gene expression data in pedigrees, and tests for association with genes on the x- chromosome.该方法的开发和实施将利用我们的躁郁症，尼古丁成瘾，注意力缺陷多动障碍，阿尔茨海默氏病，哮喘，慢性阻塞性肺部疾病等方面的合作者的真实数据。