AI 中文总结
研究针对孟德尔随机化在无效工具变量存在时的问题，提出借用辅助结果性状工具变量改进推断。先引入共同异质性统计量及理论识别次要性状，扩展两种方法，模拟研究和实际应用表明新方法能更好控制错误、提高功效。
AI 中文摘要
孟德尔随机化（MR）是一种广泛使用的方法，利用基因变异作为工具变量来推断暴露对结果的因果效应。然而，现有方法在存在无效工具变量时仍易受偏差和/或功效损失的影响。我们假设密切相关的结果性状在给定暴露的潜在有效工具变量上可能有很大重叠，因此跨这些性状借用工具变量（IB）可以产生更稳健的MR推断。为实现这一想法，我们首先引入一种新的共同异质性统计量及其在不同范式下的渐近理论，用于识别可能与主要性状共享有效工具变量的次要结果性状。然后，我们提出了两种流行方法MR-Mode和MR-PRESSO的扩展，利用次要性状改进对主要性状的MR推断。广泛的模拟研究表明，所提出的共同异质性统计量具有预期的有限样本性质，基于IB的方法始终优于其标准对应方法，随着结果性状间有效工具变量重叠程度的增加，收益也会增加。对既定的阳性和阴性对照假设的应用表明，基于IB的方法能更好地控制I型错误并提高功效。我们通过重新审视关于维生素D对心脏代谢性状因果效应的长期争论假设，进一步说明了这些方法的实际效用。
英文摘要
Mendelian randomization (MR) is a widely used approach for inferring causal effects of exposures on outcomes using genetic variants as instrumental variables; however, existing methods remain vulnerable to bias and/or loss of power in the presence of invalid instruments. We hypothesize that closely related outcome traits are likely to have a large overlap in underlying valid instruments in relation to a given exposure and that instrument borrowing (IB) across such traits can therefore yield more robust MR inference. To operationalize this idea, we first introduce a novel coheterogeneity statistic and its asymptotic theory under different paradigms which can be used to identify secondary outcome traits that are likely to share valid instruments with the primary trait. We then propose extensions of two popular methods, MR-Mode and MR-PRESSO, that improve MR inference for the primary trait, taking advantage of a secondary trait. Extensive simulation studies demonstrate that the proposed coheterogeneity statistic has expected finite-sample properties and IB-based methods consistently outperform their standard counterparts, with gains increasing as the degree of overlap in valid instruments across outcome traits grows. Applications to established positive and negative control hypotheses suggest that IB-based methods offer improved control of type I error and increased power. We further illustrate the practical utility of these methods by revisiting the long-debated hypothesis on the causal effect of vitamin D on cardiometabolic traits.
