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

使用病例亲子三人组设计分析非综合征性口面裂 GWAS 数据

• 批准号: 10436788
• 负责人: Zhongxue Chen
• 金额: --
• 依托单位: TRUSTEES OF INDIANA UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2022-08-12
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10436788
• 关键词: Biology; Childhood; Cleft Lip; Cleft Palate; Clinical Research; Communities; Computer software; Congenital Abnormality; Data; Dental; Detection; Development; Developmental Biology; Disease; Early Diagnosis; Failure; Genes; Genetic; Genetic Diseases; Genomics; Genotype; Goals; Heritability; Knowledge; Lead; Meta-Analysis; Methodology; Methods; Mission; National Institute of Dental and Craniofacial Research; Oral; Outcome; Parents; Phenotype; Play; Prevention; Public Health; Publishing; Research; Research Personnel; Role; Signal Transduction; Statistical Methods; Stratification; Techniques; Testing; Time; Translational Research; Variant; Work; base; craniofacial; design; diagnostic value; family genetics; genetic information; genetic risk factor; genetic variant; genome wide association study; human disease; improved; innovation; novel; novel therapeutic intervention; orofacial cleft; targeted treatment; transmission process

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.

项目概要 案例亲子三人组 (CPT) 设计广泛应用于儿童全基因组关联研究 (GWAS) 疾病，包括非综合征性口面裂出生缺陷（唇裂和腭裂）。 遗传变异，传递不平衡测试（TDT）——众所周知，它对 亚群体分层通常应用于 CPT 数据，但是 TDT 存在一些局限性。 基于的方法可能会导致严重的功率损耗并且无法检测到真实信号；这个问题出现在 目前的非综合征性口面裂 GWAS，因为只有一小部分相关的遗传变异被 因此，目前迫切需要更强大的先进统计方法。 我们提出了一些尖端的统计方法来规避当前测试的局限性并使用额外的方法 通过应用我们提出的方法来从数据中获取信息，从而大大提高检测能力。 通过CPT设计的非综合征性口颌裂GWAS数据，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的潜在机制 通过使用尖端统计方法来识别非综合征性口面部的遗传成分 唇裂出生缺陷，导致更精细的诊断能力并最终获得更好的靶向治疗。 该应用程序的总体目标是开发稳健且强大的统计方法并将其应用于 口面裂出生缺陷数据发现新的遗传风险因素的核心假设是强大的。 如果从数据中获得有用的信息并且完全有效，则可以开发统计方法 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 将会发现拟议研究的基本原理是成功完成将使我们能够获得 对非综合征性口颌裂更有用的遗传信息将得到检验，并得出结论。 通过追求以下具体目标来实现的目标： 1) 开发、测试和验证强大且稳健的 采用病例父母三人组设计的非综合征口面裂 GWAS 统计方法 2) 识别新颖的方法； 通过将所提出的强大的统计方法应用于口颌裂出生的疾病遗传成分 该项目的贡献将是重大的，因为研究结果将增进对缺陷数据的了解。 发育生物学并为非综合征的临床和转化研究创造新的机会 这项提出的研究具有创新性，因为提出的新颖的统计数据。 方法比现有方法更强大，因为它们可以从数据中获取更多信息，并且 更有效地使用它。