A Novel Mediation Framework for Absolute Microbiome Abundance with Heterogeneous Mediators and Interaction Effects

Music City Center 

Emerging evidence underscores the dynamic interplay between the human microbiome and the immune system, with the microbiome contributing to disease pathogenesis via mediation of causal pathways in conditions such as Alzheimer's disease and cancer. Yet, traditional mediation analyses are ill-suited for microbiome data, given its compositionality, sparsity, and high dimensionality. To overcome these limitations, we propose Absolute Microbiome Mediation Analysis (AMMA) — a novel framework leveraging the natural effects model, sure independence screening, and microbiome-specific bias correction to infer mediation effects based on absolute microbial abundances. To our knowledge, AMMA is the first method capable of inferring absolute abundances in a mediation framework, demonstrating superior performance in simulation studies.