ArticleEnvironmental health perspectives2020
Challenges Raised by Mediation Analysis in a High-Dimension Setting.
Article in Environmental health perspectives, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Cord blood epigenome-wide meta-analysis in six European-based child cohorts identifies signatures linked to rapid weight growth.BMC medicine · 2023Pooled it
- Assessing environmental exposures in children: toward a comprehensive exposome approach.Pediatric research · 2026Review
- Relevance and challenges of exposome studies for environmental health research.Environmental health : a global access science source · 2026Review
- Integrative Analysis of Multimodal Omics Data.Annual review of statistics and its application · 2026Article
- Evaluating Methods for High-Dimensional Mediation in Metabolomics Data.Environmental science & technology · 2026Article
- Microbiome mediation analysis: methods, assumptions, and practical considerations.Frontiers in cellular and infection microbiology · 2026Review
- Placental DNA methylation key topics: sex- and cell-type specificity, mediation, multi-omics, and biomarker discovery.Epigenomics · 2025Review
- Medication literacy and treatment adherence in people living with human immunodeficiency virus: Mediating effects of psychosocial factors.World journal of psychiatry · 2025Review
- Non-Traditional Lipid Parameters and Risk of Adverse Pregnancy Outcomes in Gestational Diabetes Mellitus: Mediation by Maternal Metabolites.Journal of diabetes · 2025Observational
- Neighborhood environment associations with cognitive function and structural brain measures in older African Americans.BMC medicine · 2025Article
- Early prenatal but not postnatal glucocorticoid exposure is associated with enhanced HPA axis activity into adulthood in a wild primate.Proceedings. Biological sciences · 2025Article
- A Bayesian high-dimensional mediation analysis for multilevel genome-wide epigenetic data.Journal of applied statistics · 2025Article
- Methods for the Analysis of Multiple Epigenomic Mediators in Environmental Epidemiology.Current environmental health reports · 2024Review
- Adaptive bootstrap tests for composite null hypotheses in the mediation pathway analysis.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2024Article
- Mapping Brain Structure Variability in Chronic Pain: The Role of Widespreadness and Pain Type and Its Mediating Relationship With Suicide Attempt.Biological psychiatry · 2024Article
- Depression score mediate the association between a body shape index and infertility in overweight and obesity females, NHANES 2013-2018.BMC women's health · 2023Article
- High-Dimensional Mediation Analysis: A New Method Applied to Maternal Smoking, Placental DNA Methylation, and Birth Outcomes.Environmental health perspectives · 2023Article
- Article
- Exposomics as a tool to investigate differences in health and disease by sex and gender.Exposome · 2023Review
- Epigenetic Alterations of Maternal Tobacco Smoking during Pregnancy: A Narrative Review.International journal of environmental research and public health · 2021Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMediation analysis is used in epidemiology to identify pathways through which exposures influence health. The advent of high-throughput (omics) technologies gives opportunities to perform mediation analysis with a high-dimension pool of covariates.
objectiveWe aimed to highlight some biostatistical issues of this expanding field of high-dimension mediation. DISCUSSION: The mediation techniques used for a single mediator cannot be generalized in a straightforward manner to high-dimension mediation. Causal knowledge on the relation between covariates is required for mediation analysis, and it is expected to be more limited as dimension and system complexity increase. The methods developed in high dimension can be distinguished according to whether mediators are considered separately or as a whole. Methods considering each potential mediator separately do not allow efficient identification of the indirect effects when mutual influences exist among the mediators, which is expected for many biological (e.g., epigenetic) parameters. In this context, methods considering all potential mediators simultaneously, based, for example, on data reduction techniques, are more adapted to the causal inference framework. Their cost is a possible lack of ability to single out the causal mediators. Moreover, the ability of the mediators to predict the outcome can be overestimated, in particular because many machine-learning algorithms are optimized to increase predictive ability rather than their aptitude to make causal inference. Given the lack of overarching validated framework and the generally complex causal structure of high-dimension data, analysis of high-dimension mediation currently requires great caution and effort to incorporate
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