COMPOSITIONAL MEDIATION ANALYSIS FOR MICROBIOME STUDIES

• 成果类型: Article
• 署名作者: Sohn, Michael B.; Li, Hongzhe
• 署名单位: University of Pennsylvania
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/18-AOAS1210
• 发表日期: 2019
• 页码: 661-681
• 关键词: sensitivity-analysis; dietary patterns; causal; identification; mechanisms; regression; inference; obesity

摘要

Motivated by recent advances in causal mediation analysis and problems in the analysis of microbiome data, we consider the setting where the effect of a treatment on an outcome is transmitted through perturbing the microbial communities or compositional mediators. The compositional and high-dimensional nature of such mediators makes the standard mediation analysis not directly applicable to our setting. We propose a sparse compositional mediation model that can be used to estimate the causal direct and indirect (or mediation) effects utilizing the algebra for compositional data in the simplex space. We also propose tests of total and component-wise mediation effects. We conduct extensive simulation studies to assess the performance of the proposed method and apply the method to a real microbiome dataset to investigate an effect of fat intake on body mass index mediated through the gut microbiome.