Analyzing nonsyndromic orofacial clefts GWAS data with case-parent trio design

项目总结 病例-亲本三元组(CPT)设计被广泛应用于儿童全基因组关联研究(GWASs) 疾病，包括非综合征性口腔面部裂出生缺陷(唇裂和腭裂)。要检测关联的 遗传变异，传递不平衡检验(TDT)-已知对 子总体分层-通常应用于CPT数据。然而，与TDT相关的几个限制- 基于方法的方法可能会导致严重的断电和无法检测到真实信号；此问题在 目前的非综合征性口面部裂GWAS，因为只有一小部分相关的遗传变异 到目前为止已经确认。因此，迫切需要更强大的先进统计方法。 我们提出了一些前沿的统计方法，这些方法绕过了当前测试的局限性，并使用了额外的 来自数据的信息以实质上获得检测功率。通过将我们建议的方法应用于 通过CPT设计，我们期望发现许多新的遗传危险因素。 该项目的长期目标是帮助研究人员更好地了解这些疾病的潜在机制 用尖端统计学方法识别非综合征口腔颌面部遗传成分的条件 裂隙出生缺陷，导致更完善的诊断能力，并最终更好地有针对性的治疗。这个 本应用程序的总体目标是开发强大的统计方法，并将其应用于 口裂出生缺陷数据发现新的遗传危险因素。中心假设是强大的 如果从数据中获得有用的信息，并且充分和高效，就可以开发统计方法 同时，通过使用这些强大的尖端统计方法，更多的疾病遗传变异 将会被发现。拟议研究的理由是，成功完成研究将使我们能够获得 非综合征性唇裂的更多有用的遗传信息。核心假设将得到检验，而 通过追求以下具体目标实现的目标：1)开发、测试和验证强大的健壮性 病例-父母三联设计用于非综合征性口腔颌面裂的统计方法2)确定新的 将所提出的强有力的统计学方法应用于口裂出生的疾病遗传成分 缺陷数据。这个项目的贡献将是巨大的，因为这些发现将促进对 发育生物学，为非综合征的临床和翻译研究创造新的机会 口腔裂先天缺陷。这项拟议的研究具有创新性，因为提出的新的统计方法 方法比现有方法更强大，因为它们从数据中利用了更多信息，并且 更有效地利用它。

PROJECT SUMMARY Case-parent trio (CPT) design is widely used in genome-wide association studies (GWASs) for childhood diseases, including nonsyndromic orofacial cleft birth defects (cleft lip and cleft palate). To detect associated genetic variants, the transmission disequilibrium test (TDT)—which is known to be robust against the subpopulation stratification—is usually applied to CPT data. However, several limitations associated with TDT- based methods may result in serious power loss and failure to detect true signals; this problem shows up in current nonsyndromic orofacial cleft GWASs, as only a small portion of associated genetic variants have been identified so far. Substantially more powerful advanced statistical approaches are therefore desperately needed. We propose some cutting-edge statistical methods that circumvent the limitations of current tests and use extra information from the data to substantially gain detection power. By applying our proposed methodology to nonsyndromic orofacial cleft GWAS data with CPT design, we expect to discover many novel genetic risk factors. The long-term goal of this project is to help researchers better understand the underlying mechanisms of these conditions by using cutting-edge statistical approaches to identify genetic components of nonsyndromic orofacial cleft birth defects, leading to more refined diagnostic capabilities and ultimately better targeted therapies. The overall objective of this application is to develop robust and powerful statistical approaches and apply them to the orofacial cleft birth defects data to discover novel genetic risk factors. The central hypothesis is that powerful statistical approaches can be developed if useful information from the data is obtained and fully and efficiently used; meanwhile, through use of these powerful cutting-edge statistical methods, more disease genetic variants will be discovered. The rationale for the proposed research is that successful completion will enable us to obtain more useful genetic information for nonsyndromic orofacial clefts. The central hypothesis will be tested and the objective attained by pursuing the following specific aims: 1) Develop, test, and validate powerful and robust statistical approaches for nonsyndromic orofacial cleft GWAS with case-parent trio design; 2) Identify novel disease genetic components by applying the proposed powerful statistical approaches to the orofacial cleft birth defects data. The contribution of this project will be significant because the findings will advance knowledge of developmental biology and create new opportunities for clinical and translational research in nonsyndromic orofacial cleft birth defects. This proposed research is innovative because the proposed novel statistical approaches are more powerful than existing methods in that they harness more information from the data and use it more efficiently.