Efficient methods for genome-wide survival analysis of early childhood caries

儿童早期龋齿全基因组生存分析的有效方法

• 批准号: 10696112
• 负责人: Chenxi Li
• 金额: $ 15.08万
• 依托单位: MICHIGAN STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-15 至 2024-09-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10696112
• 关键词: Address; Age; Age related macular degeneration; Archives; Area; Caries prevention; Child; Chronic Disease; Complex; Consensus; Data; Data Set; Dental caries; Dentition; Development; Disease; Early identification; Economically Deprived Population; Environment; Etiology; Event; Family; GAGE; Genes; Genetic; Genetic Heterogeneity; Genetic Predisposition to Disease; Genetic Research; Genetic Risk; Genetic study; Goals; Heritability; Individual; Knowledge; Life Cycle Stages; Logistic Regressions; Mammary Neoplasms; Maps; Methodology; Methods; Modeling; Monitor; Names; Nursery Schools; Outcome; Pathway interactions; Phenotype; Prevention; Primary Dentition; Process; Public Health; Recurrence; Research; School-Age Population; Severities; Signal Transduction; Statistical Methods; Survival Analysis; Testing; Time; Tooth structure; Twin Studies; United States; Variant; affection; age effect; analytical tool; database of Genotypes and Phenotypes; early childhood; experience; genetic architecture; genetic association; genetic epidemiology; genetic variant; genome wide association study; genome-wide; high dimensionality; improved; insight; method development; next generation sequencing; novel; permanent tooth; phenotypic data; population based; risk variant; socioeconomic disadvantage; statistics; success; survival outcome; tooth surface; trait; whole genome

Project Summary Early childhood caries (ECC) is the most common chronic disease in preschool-age children in the United States. It has been shown to have a substantial heritability, but no consensus exists regarding ECC-associated genetic risk loci. Existing genome-wide association studies (GWAS) of ECC are scarce and were based on single-locus association mapping using logistic regression of binary traits (e.g., caries affection status) or count regression of quantitative traits (e.g., dmfs/dmft/dfs/dft). Drawbacks of those approaches include potential misspecification of the age effect, not making full use of tooth-/tooth-surface-level caries lifetime data, potentially weak signals from individual variants, and the burden of multiple testing correction. The first drawback may lead to incorrect type I error rates from model-based association tests. The others hinder statistical power. Multi-locus tests with tooth-/tooth-surface-level ages to caries or the counting process of dmfs/dmft/dfs/dft as phenotypes can address the above drawbacks. However, caries life course data are inevitably interval censored since continuous monitoring of caries affection or severity is impractical in caries research. No existing multi-locus survival tests can apply to tooth- /tooth-surface-level times to caries or the counting process of dmfs/dmft/dfs/dft subject to interval censoring. The goal of this project is to develop two suites of methods for population-based and family-based genetic association analyses of survival outcomes, which address the above drawbacks and the interval censoring complexity, to dissect the genetic architecture of ECC. The specific aims are 1) to develop two suites of set-based genetic association tests respectively for multivariate interval-censored survival outcomes and panel count outcomes and 2) to apply the methods to two large-scale real-world data sets on ECC, Dental Caries: Whole Genome Association and Gene x Environment Studies and ZOE 2.0, to illustrate the utility of the methods and discover subject matter knowledge. Additionally, the new methods will be programmed into R packages to be disseminated through the Comprehensive R Archive Network. The successful completion of this project will address analytic challenges that impede ECC genetic research, and advance the statistical methodology development for population-based and family-based genetic association analyses of survival outcomes in general. The application of the new methods to the real data will provide new insights into the genetic etiology of ECC.

项目摘要 幼儿时期龋齿（ECC）是学龄前儿童中最常见的慢性疾病 美国。它已被证明具有实质性的遗传力，但没有共识 关于与ECC相关的遗传风险基因座。现有全基因组协会研究（GWAS） ECC的稀少 二进制特征（例如，龋齿感情状况）或定量特征的计数回归（例如， DMFS/DMFT/DFS/DFT）。这些方法的缺点包括年龄的潜在错误指定 效果，不充分利用牙齿/牙齿表面级别的龋齿终生数据，可能较弱 来自单个变体的信号以及多个测试校正的负担。第一个缺点 可能导致基于模型的关联测试的I型错误率不正确。其他人则阻碍 统计能力。用牙齿/牙齿表面级别的龋齿或计数的牙齿/牙齿表面级别的多层次测试 DMFS/DMFT/DFS/DFT作为表型的过程可以解决上述缺点。但是，龋齿 由于不断监视龋齿的感情或 龋齿研究中的严重程度是不切实际的。没有现有的多洛克斯群岛生存测试可以适用于牙齿 /牙齿表面级别的龋齿或dmfs/dmft/dfs/dft的计数过程 审查。该项目的目的是为基于人群的和 基于家庭的遗传关联分析生存结果，该分析解决了上述 缺点和间隔检查复杂性，以剖析ECC的遗传结构。这 具体目的是1）分别开发两个基于集合的遗传关联测试的套件 多元间隔审查的生存结果和面板计数结果以及2） 关于ECC，龋齿的两个大型现实世界数据集的方法：整个基因组 关联和基因X环境研究以及ZOE 2.0，以说明方法的实用性 并发现主题知识。此外，新方法将被编程到 通过综合R档案网络传播的r软件包。成功 该项目的完成将解决阻碍ECC遗传研究的分析挑战，并 推进基于人群和基于家庭的遗传的统计方法发展 一般生存结果的关联分析。新方法应用于 实际数据将为ECC的遗传病因提供新的见解。