Advanced Haplotype Analyses in Coronary Artery Disease

描述(由申请人提供)： 对人类遗传变异进行建模对于理解复杂疾病的遗传基础至关重要。人类基因组计划已经发现了数百万种DNA序列变异(单核苷酸多态或SNPs)，而且可能存在更多。由于蛋白质的编码发生在染色体上，每条染色体上的SNP组织，即单倍型结构，将对发现与疾病相关的遗传变异最有用。基于单倍型的关联研究是检测复杂疾病的遗传影响的强大程序。然而，单倍型效应与非阶段性基因数据的关联测试可能对单倍型频率的估计敏感，即使在基于家庭的研究设计和完整的基因信息的情况下也是如此。 这项提案的广泛目标集中在加强研究人员用来剖析复杂疾病遗传因素的统计方法的武器库。具体地说，我们建议应用粗糙数据半参数有效模型理论的结果来推导单倍型和单倍型交互效应的最优测试和估计，这些单倍型和单倍型交互效应对于单倍型频率是稳健的，使用非阶段性的、可能丢失的基因数据。我们将考虑的数据结构是由早发性心血管疾病遗传学(GENECARD)研究和GENECARD后代研究中发现的那些数据结构驱动的。此外，我们建议将这些新开发的技术应用于GENECARD样本的精细定位和候选基因研究。 这项研究将构成安德鲁·艾伦博士五年职业发展计划的核心，在三名杰出研究人员的指导下，每一名研究人员都拥有相辅相成的专业知识，并代表本提案中涉及的三个领域：心脏病学、遗传学和统计学。他们提出了一项职业发展计划，将遗传学、心脏病学和遗传流行病学的教学和实践培训与杜克大学独特的研究环境中的持续研究计划结合起来。这一职业发展计划将促进艾伦博士发展成为一名成熟的独立定量研究科学家，在剖析复杂疾病中的遗传因素和心血管遗传学方面拥有专业知识。

DESCRIPTION (provided by applicant): Modeling human genetic variation is critical to understanding the genetic basis of complex disease. The Human Genome Project has discovered millions of DNA sequence variants (single nucleotide polymorphisms or SNPs), and millions more may exist. As the coding for proteins takes place along chromosomes, SNP organization along each chromosome, the haplotype structure, will be most useful for discovering genetic variants associated with disease. Haplotype-based association studies are powerful procedures for detecting genetic influences on complex diseases. However, association tests of haplotype effects with unphased genotype data can be sensitive to estimates of haplotype frequencies even with family-based study designs and complete genotype information. The broad objectives of this proposal focus on enhancing the arsenal of statistical methods researchers use to dissect genetic factors in complex diseases. Specifically, we propose to apply results from coarsened-data semi-parametric efficient model theory to derive optimal tests and estimates of haplotype and haplotype interaction effects that are robust to haplotype frequencies using unphased, and possibly missing, genotype data. The data structures we will consider are motivated by those found in the Genetics of Early Onset Cardiovascular Disease (GENECARD) study and the GENECARD Offspring Study. In addition, we propose to apply these newly developed techniques to the GENECARD samples in fine mapping and candidate gene studies. This research will form the core of a 5-year career development plan for Dr. Andrew Allen under the mentorship of three exceptional researchers, each with expertise that complements one another and represent the three areas addressed in this proposal: cardiology, genetics, and statistics. They propose a career development plan that combines didactic and practical training in genetics, cardiology, and genetic epidemiology with an ongoing research program within the unique research environment of Duke University. This career development plan will foster Dr. Allen's development into an established independent quantitative research scientist with expertise in both methodology for dissecting genetic factors in complex disease and cardiovascular genetics.