Genetic association testing with multivariate survival phenotypes under interval censoring

2026-08-31

AI Summary

本文针对多变量区间删失生存数据的遗传关联测试问题，提出了一种新的加权V检验方法（WV-M-IC），并通过模拟研究和实际应用验证了其有效性。

Abstract

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.

Problem

• Genetic association
• Multivariate survival phenotypes
• Interval censoring
• Set-based methods

Innovation

• Multivariate Interval-Censored Data
• Weighted V Tests
• Joint Analysis