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Testing for the indirect effect under the null for genome-wide mediation analyses.

Publication ,  Journal Article
Barfield, R; Shen, J; Just, AC; Vokonas, PS; Schwartz, J; Baccarelli, AA; VanderWeele, TJ; Lin, X
Published in: Genetic epidemiology
December 2017

Mediation analysis helps researchers assess whether part or all of an exposure's effect on an outcome is due to an intermediate variable. The indirect effect can help in designing interventions on the mediator as opposed to the exposure and better understanding the outcome's mechanisms. Mediation analysis has seen increased use in genome-wide epidemiological studies to test for an exposure of interest being mediated through a genomic measure such as gene expression or DNA methylation (DNAm). Testing for the indirect effect is challenged by the fact that the null hypothesis is composite. We examined the performance of commonly used mediation testing methods for the indirect effect in genome-wide mediation studies. When there is no association between the exposure and the mediator and no association between the mediator and the outcome, we show that these common tests are overly conservative. This is a case that will arise frequently in genome-wide mediation studies. Caution is hence needed when applying the commonly used mediation tests in genome-wide mediation studies. We evaluated the performance of these methods using simulation studies, and performed an epigenome-wide mediation association study in the Normative Aging Study, analyzing DNAm as a mediator of the effect of pack-years on FEV1 .

Duke Scholars

Published In

Genetic epidemiology

DOI

EISSN

1098-2272

ISSN

0741-0395

Publication Date

December 2017

Volume

41

Issue

8

Start / End Page

824 / 833

Related Subject Headings

  • Repressor Proteins
  • Models, Genetic
  • Lung Neoplasms
  • Humans
  • Genome-Wide Association Study
  • Epigenomics
  • Epidemiology
  • DNA Methylation
  • Basic Helix-Loop-Helix Proteins
  • 4202 Epidemiology
 

Citation

APA
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ICMJE
MLA
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Barfield, R., Shen, J., Just, A. C., Vokonas, P. S., Schwartz, J., Baccarelli, A. A., … Lin, X. (2017). Testing for the indirect effect under the null for genome-wide mediation analyses. Genetic Epidemiology, 41(8), 824–833. https://doi.org/10.1002/gepi.22084
Barfield, Richard, Jincheng Shen, Allan C. Just, Pantel S. Vokonas, Joel Schwartz, Andrea A. Baccarelli, Tyler J. VanderWeele, and Xihong Lin. “Testing for the indirect effect under the null for genome-wide mediation analyses.Genetic Epidemiology 41, no. 8 (December 2017): 824–33. https://doi.org/10.1002/gepi.22084.
Barfield R, Shen J, Just AC, Vokonas PS, Schwartz J, Baccarelli AA, et al. Testing for the indirect effect under the null for genome-wide mediation analyses. Genetic epidemiology. 2017 Dec;41(8):824–33.
Barfield, Richard, et al. “Testing for the indirect effect under the null for genome-wide mediation analyses.Genetic Epidemiology, vol. 41, no. 8, Dec. 2017, pp. 824–33. Epmc, doi:10.1002/gepi.22084.
Barfield R, Shen J, Just AC, Vokonas PS, Schwartz J, Baccarelli AA, VanderWeele TJ, Lin X. Testing for the indirect effect under the null for genome-wide mediation analyses. Genetic epidemiology. 2017 Dec;41(8):824–833.
Journal cover image

Published In

Genetic epidemiology

DOI

EISSN

1098-2272

ISSN

0741-0395

Publication Date

December 2017

Volume

41

Issue

8

Start / End Page

824 / 833

Related Subject Headings

  • Repressor Proteins
  • Models, Genetic
  • Lung Neoplasms
  • Humans
  • Genome-Wide Association Study
  • Epigenomics
  • Epidemiology
  • DNA Methylation
  • Basic Helix-Loop-Helix Proteins
  • 4202 Epidemiology