发表机构
Michigan State University; University of Michigan; University of Florida（密歇根州立大学; 密歇根大学; 佛罗里达大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究针对区间删失下多变量生存表型，开发了WV-M-IC方法，经模拟和ZOE 2.0研究验证，其检验功效优于单一结局分析，可用于遗传关联检测。
AI 中文摘要
基于集合的遗传关联检验是通过联合分析多个遗传变异来检测遗传对复杂性状影响的有效框架。尽管已开发出针对区间删失生存结局的集合方法，但现有方法主要关注单一生存表型，未充分利用多个相关结局的信息。本文开发了两种针对多变量区间删失数据的加权V检验（WV-M-IC），将加权V统计框架（Wu等人，2021）扩展用于多个相关区间删失生存结局的联合分析。通过模拟研究评估这些方法的性能，结果表明，与单一结局分析相比，所提方法可提升检验功效。我们将所提方法应用于ZOE 2.0研究，以探究儿童龋齿进展情况。
英文摘要
Set-based genetic association tests provide a powerful framework for detecting genetic effects on complex traits by jointly analyzing multiple genetic variants. Although set-based methods have been developed for interval-censored survival outcomes, existing approaches primarily focus on a single survival phenotype and therefore do not fully use information from multiple correlated outcomes. In this paper, we develop two Weighted V Tests for Multivariate Interval-Censored Data (WV-M-IC), extending the weighted V-statistic framework (Wu et al., 2021) to the joint analysis of multiple correlated interval-censored survival outcomes. The performance of these methods is evaluated through simulation studies, showing that the proposed approaches can provide power gains compared with single-outcome analyses. We apply the proposed methods to the ZOE 2.0 study to investigate dental caries progression in children.
