Testing for mediation effect with application to human microbiome data.

Pub Date : 2021-07-01 Epub Date: 2019-07-27 DOI:10.1007/s12561-019-09253-3
Haixiang Zhang, Jun Chen, Zhigang Li, Lei Liu
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Abstract

Mediation analysis has been commonly used to study the effect of an exposure on an outcome through a mediator. In this paper, we are interested in exploring the mediation mechanism of microbiome, whose special features make the analysis challenging. We consider the isometric logratio transformation of the relative abundance as the mediator variable. Then, we present a de-biased Lasso estimate for the mediator of interest and derive its standard error estimator, which can be used to develop a test procedure for the interested mediation effect. Extensive simulation studies are conducted to assess the performance of our method. We apply the proposed approach to test the mediation effect of human gut microbiome between the dietary fiber intake and body mass index.

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应用人类微生物组数据测试中介效应。
中介分析通常用于研究暴露于某一因素对结果的影响。在本文中,我们有兴趣探索微生物组的中介机制,因为微生物组的特殊性使分析具有挑战性。我们将相对丰度的等距对数变换视为中介变量。然后,我们提出了对相关中介变量的去偏 Lasso 估计,并推导出其标准误差估计值,可用于开发相关中介效应的检验程序。我们进行了广泛的模拟研究,以评估我们方法的性能。我们将所提出的方法用于检验人类肠道微生物组在膳食纤维摄入量和体重指数之间的中介效应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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