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: 10571345
• 负责人: Chenxi Li
• 金额: $ 15.95万
• 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/10571345
• 关键词: Address; Age; Age related macular degeneration; Archives; Area; Caries prevention; Child; Chronic Disease; Complex; Consensus; Data; Data Set; Dental caries; Development; Disease; Environment; Etiology; Event; Family; GAGE; Genes; Genetic; Genetic Heterogeneity; Genetic Predisposition to Disease; Genetic Research; Genetic Risk; Genetic study; Goals; Heritability; Individual; Knowledge; Lead; Life Cycle Stages; Logistic Regressions; Mammary Neoplasms; Methodology; Methods; Modeling; Monitor; Names; Nursery Schools; Outcome; Pathway interactions; Phenotype; Prevention; Primary Dentition; Process; Public Health; Recurrence; Research; Severities; Signal Transduction; Statistical Methods; Survival Analysis; Testing; Time; Tooth structure; Twin Studies; United States; Variant; affection; age effect; analytical tool; base; database of Genotypes and Phenotypes; disadvantaged population; 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 幼儿龋病是我国学龄前儿童最常见的慢性疾病， 美国的它已被证明有很大的遗传性，但没有共识存在 关于ECC相关的遗传风险位点。现有的全基因组关联研究（GWAS） 的ECC是稀缺的，并基于单位点关联映射使用逻辑回归 二元特征（例如，龋齿影响状态）或数量性状的计数回归（例如， dmfs/dmft/dfs/dft）。这些方法的缺点包括潜在的年龄错误 影响，没有充分利用牙齿/牙齿表面水平的龋齿寿命数据，可能很弱 来自个体变体的信号，以及多重测试校正的负担。第一个缺点 可能导致基于模型的关联测试的不正确的I类错误率。其他阻碍 统计力量多位点测试与牙齿/牙齿表面水平年龄龋或计数 DMFS/DMFT/DFS/DFT作为表型的方法可以解决上述缺点。然而，龋齿 由于持续监测龋齿影响或 严重性在龋齿研究中是不切实际的。现有的多位点生存测试不能适用于牙齿- /牙面水平龋坏时间或dmfs/dmft/dfs/dft受间隔的计数过程 审查。该项目的目标是开发两套基于人口的方法， 基于家族的生存结局遗传关联分析，解决上述问题 缺陷和区间删失的复杂性，剖析ECC的遗传结构。的 具体目标是：1）开发两套基于集合的遗传关联检验， 多变量区间删失生存结局和组计数结局，以及2）应用 方法对两个大规模的真实世界的数据集ECC，龋齿：全基因组 协会和基因x环境研究和ZOE 2.0，以说明该方法的实用性 发现主题知识。此外，新方法将被编程到 R软件包将通过综合R档案网络传播。成功 该项目的完成将解决阻碍ECC遗传研究的分析挑战， 促进基于群体和基于家庭的遗传学统计方法的发展 一般生存结局的关联分析。本文介绍了新方法在 真实的数据将为ECC的遗传病因学提供新的见解。