» Articles » PMID: 32363646

Group Testing in Mediation Analysis

Overview
Journal Stat Med
Publisher Wiley
Specialty Public Health
Date 2020 May 5
PMID 32363646
Citations 6
Authors
Affiliations
Soon will be listed here.
Abstract

We consider the scenario where there is an exposure, multiple biologically defined sets of biomarkers, and an outcome. We propose a new two-step procedure that tests if any of the sets of biomarkers mediate the exposure/outcome relationship, while maintaining a prespecified familywise error rate. The first step of the proposed procedure is a screening step that removes all groups that are unlikely to be strongly associated with both the exposure and the outcome. The second step adapts recent advances in postselection inference to test if there are true mediators in each of the remaining candidate sets. We use simulation to show that this simple two-step procedure has higher statistical power to detect true mediating sets when compared with existing procedures. We then use our two-step procedure to identify a set of Lysine-related metabolites that potentially mediate the known relationship between increased body mass index and the increased risk of estrogen-receptor positive breast cancer in postmenopausal women.

Citing Articles

A novel statistical framework for meta-analysis of total mediation effect with high-dimensional omics mediators in large-scale genomic consortia.

Xu Z, Wei P PLoS Genet. 2024; 20(11):e1011483.

PMID: 39561194 PMC: 11614268. DOI: 10.1371/journal.pgen.1011483.


Speeding up interval estimation for R2-based mediation effect of high-dimensional mediators via cross-fitting.

Xu Z, Li C, Chi S, Yang T, Wei P Biostatistics. 2024; 26(1).

PMID: 39412139 PMC: 11823199. DOI: 10.1093/biostatistics/kxae037.


A novel statistical framework for meta-analysis of total mediation effect with high-dimensional omics mediators in large-scale genomic consortia.

Xu Z, Wei P bioRxiv. 2024; .

PMID: 38746374 PMC: 11092451. DOI: 10.1101/2024.04.29.591700.


Adaptive bootstrap tests for composite null hypotheses in the mediation pathway analysis.

He Y, Song P, Xu G J R Stat Soc Series B Stat Methodol. 2024; 86(2):411-434.

PMID: 38746015 PMC: 11090400. DOI: 10.1093/jrsssb/qkad129.


Speeding up interval estimation for -based mediation effect of high-dimensional mediators via cross-fitting.

Xu Z, Li C, Chi S, Yang T, Wei P bioRxiv. 2023; .

PMID: 36798366 PMC: 9934518. DOI: 10.1101/2023.02.06.527391.


References
1.
Moutsianas L, Agarwala V, Fuchsberger C, Flannick J, Rivas M, Gaulton K . The power of gene-based rare variant methods to detect disease-associated variation and test hypotheses about complex disease. PLoS Genet. 2015; 11(4):e1005165. PMC: 4407972. DOI: 10.1371/journal.pgen.1005165. View

2.
Flannick J, Mercader J, Fuchsberger C, Udler M, Mahajan A, Wessel J . Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls. Nature. 2019; 570(7759):71-76. PMC: 6699738. DOI: 10.1038/s41586-019-1231-2. View

3.
Imai K, Keele L, Tingley D . A general approach to causal mediation analysis. Psychol Methods. 2010; 15(4):309-34. DOI: 10.1037/a0020761. View

4.
Derkach A, Sampson J, Joseph J, Playdon M, Stolzenberg-Solomon R . Effects of dietary sodium on metabolites: the Dietary Approaches to Stop Hypertension (DASH)-Sodium Feeding Study. Am J Clin Nutr. 2017; 106(4):1131-1141. PMC: 5611778. DOI: 10.3945/ajcn.116.150136. View

5.
Pearl J . Interpretation and identification of causal mediation. Psychol Methods. 2014; 19(4):459-81. DOI: 10.1037/a0036434. View