With advancements in high‐throughout technologies, studies have been conducted to investigate the role of massive genetic variants in human diseases. While set‐based tests have been developed for binary and continuous disease outcomes, there are few computationally efficient set‐based tests available for time‐to‐event outcomes. To facilitate the genetic association and interaction analyses of time‐to‐event outcomes, We develop a suite of multivariant tests based on weighted V statistics with or without considering potential genetic heterogeneity. In addition to the computation efficiency and nice asymptotic properties, all the new tests can deal with left truncation and competing risks in the survival data, and adjust for covariates. Simulation studies show that the new tests run faster, are more accurate in small samples, and account for confounding effect better than the existing multivariant survival tests. When the genetic effect is heterogeneous across individuals/subpopulations, the association test considering genetic heterogeneity is more powerful than the existing tests that do not account for genetic heterogeneity. Using the new methods, we perform a genome‐wide association analysis of the genotype and age‐to‐Alzheimer's data from the Rush Memory and Aging Project and the Religious Orders Study. The analysis identifies two genes, APOE and APOC1, associated with age to Alzheimer's disease onset.

中文翻译：

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基于加权 V 统计的生存结果的基于集合的遗传关联和相互作用测试

随着高通量技术的进步，已经开展了大量遗传变异在人类疾病中的作用的研究。虽然已经为二元和连续疾病结果开发了基于集合的测试，但很少有计算效率高的基于集合的测试可用于时间到事件结果。为了促进时间到事件结果的遗传关联和相互作用分析，我们开发了一套基于加权 V 统计的多变量检验，考虑或不考虑潜在的遗传异质性。除了计算效率和良好的渐近特性外，所有新测试都可以处理生存数据中的左截断和竞争风险，并调整协变量。模拟研究表明，新测试运行速度更快，在小样本中更准确，并且比现有的多变量生存检验更好地解释混杂效应。当遗传效应在个体/亚群之间存在异质性时，考虑遗传异质性的关联检验比不考虑遗传异质性的现有检验更有效。使用新方法，我们对来自 Rush Memory and Aging Project 和 Religious Orders Study 的基因型和年龄与阿尔茨海默病的数据进行了全基因组关联分析。该分析确定了两个基因，我们对来自 Rush Memory and Aging Project 和 Religious Orders Study 的基因型和年龄与阿尔茨海默病的数据进行全基因组关联分析。该分析确定了两个基因，我们对来自 Rush Memory and Aging Project 和 Religious Orders Study 的基因型和年龄与阿尔茨海默病的数据进行全基因组关联分析。该分析确定了两个基因，APOE和APOC1与阿尔茨海默病发病年龄相关。