Advanced Bayesian kernel machine regression for large-scale exposome studies: Making the impossible possible

The Innovation 2026 Open access

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Authors: Yi Guo, Huixun Jia, Ziwei Peng, Xinming Xu, Zhicheng Zhang, Keyu Pan, Yuqin Zhou, Haidong Kan, Zhenyu Wu, Cong Liu
DOI: 10.1016/j.xinn.2025.101248
Cited by: 3
References: 61

Abstract

> 0.97 across scenarios with varying sample sizes and numbers of exposures. Furthermore, A-BKMR introduces novel quantitative metrics for effect estimates and interaction analyses, substantially enhancing interpretability. These advancements establish A-BKMR as an excellent statistical framework for future large-scale exposome studies.

Fields of Study & Subjects

Health Environment Cognitive Aging Epigenetics and DNA Methylation Gaussian Processes and Bayesian Inference

Publication details

Journal / source
The Innovation
Publisher
Elsevier BV
Volume
7
Issue
4
Pages
101248–101248
Publication date
3 January 2026
Language
EN