A Multi-Omics Framework for Survival Mediation Analysis of High-Dimensional Proteogenomic Data.

ABSTRACT:

Motivation

Survival analysis plays a crucial role in understanding time-to-event (survival) outcomes such as disease progression. Despite recent advancements in causal mediation frameworks for survival analysis, existing methods are typically based on Cox regression and primarily focus on a single exposure or individual omics layers, often overlooking multi-omics interplay. This limitation hinders the full potential of integrated biological insights.

Results

In this paper, we propose SMAHP, a novel method for survival mediation analysis that simultaneously handles high-dimensional exposures and mediators, integrates multi-omics data, and offers a robust statistical framework for identifying causal pathways on survival outcomes. This is one of the first attempts to introduce

SUBMITTER: Ahn S 

PROVIDER: S-EPMC11952585 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature