Methods for mediation analysis with high-dimensional DNA methylation data: Possible choices and comparisons

Epigenetic researchers often evaluate DNA methylation as a potential mediator of the effect of social/environmental exposures on a health outcome. Modern statistical methods for jointly evaluating many mediators have not been widely adopted. We compare seven methods for high-dimensional mediation an...

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Bibliographic Details
Published in:PLoS genetics 2023-11, Vol.19 (11), p.e1011022-e1011022
Main Authors: Clark-Boucher, Dylan, Zhou, Xiang, Du, Jiacong, Liu, Yongmei, Needham, Belinda L, Smith, Jennifer A, Mukherjee, Bhramar
Format: Article
Language:English
Subjects:
Analysis
Bayes Theorem
Bayesian analysis
Cardiovascular disease
Diabetes
DNA
DNA methylation
DNA Methylation - genetics
Environmental Exposure
Epidemiology
Epigenetic inheritance
Epigenetics
Gene expression
Health aspects
Humans
Hypotheses
Linear Models
Mediation
Mediation Analysis
Methods
Methylation
Simulation methods
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Summary:Epigenetic researchers often evaluate DNA methylation as a potential mediator of the effect of social/environmental exposures on a health outcome. Modern statistical methods for jointly evaluating many mediators have not been widely adopted. We compare seven methods for high-dimensional mediation analysis with continuous outcomes through both diverse simulations and analysis of DNAm data from a large multi-ethnic cohort in the United States, while providing an R package for their seamless implementation and adoption. Among the considered choices, the best-performing methods for detecting active mediators in simulations are the Bayesian sparse linear mixed model (BSLMM) and high-dimensional mediation analysis (HDMA); while the preferred methods for estimating the global mediation effect are high-dimensional linear mediation analysis (HILMA) and principal component mediation analysis (PCMA). We provide guidelines for epigenetic researchers on choosing the best method in practice and offer suggestions for future methodological development.
ISSN:1553-7404
1553-7390
1553-7404
DOI:10.1371/journal.pgen.1011022