Abstract
A mediation model explores the direct and indirect effects between an independent variable and a dependent variable by including other variables (or mediators). Mediation analysis has recently been used to dissect the direct and indirect effects of genetic variants on complex diseases using case-control studies. However, bias could arise in the estimations of the genetic variant-mediator association because the presence or absence of the mediator in the study samples is not sampled following the principles of case-control study design. In this case, the mediation analysis using data from case-control studies might lead to biased estimates of coefficients and indirect effects. In this article, we investigated a multiple-mediation model involving a three-path mediating effect through two mediators using case-control study data. We propose an approach to correct bias in coefficients and provide accurate estimates of the specific indirect effects. Our approach can also be used when the original case-control study is frequency matched on one of the mediators. We employed bootstrapping to assess the significance of indirect effects. We conducted simulation studies to investigate the performance of the proposed approach, and showed that it provides more accurate estimates of the indirect effects as well as the percent mediated than standard regressions. We then applied this approach to study the mediating effects of both smoking and chronic obstructive pulmonary disease (COPD) on the association between the CHRNA5-A3 gene locus and lung cancer risk using data from a lung cancer case-control study. The results showed that the genetic variant influences lung cancer risk indirectly through all three different pathways. The percent of genetic association mediated was 18.3% through smoking alone, 30.2% through COPD alone, and 20.6% through the path including both smoking and COPD, and the total genetic variant-lung cancer association explained by the two mediators was 69.1%.
Highlights
IntroductionA mediation model is a statistical approach that explores the direct and indirect effects of an independent variable (i.e., initial variable) on a dependent variable (i.e., outcome variable) by including one or more mediating variables (or mediators) [1]
A mediation model is a statistical approach that explores the direct and indirect effects of an independent variable on a dependent variable by including one or more mediating variables [1]
We reported the total effect of the genetic variant on the disease (TE), as well as the percentages of the singlenucleotide polymorphism (SNP)-disease association explained by different paths (PM1, PM2, PM3, and PMt)
Summary
A mediation model is a statistical approach that explores the direct and indirect effects of an independent variable (i.e., initial variable) on a dependent variable (i.e., outcome variable) by including one or more mediating variables (or mediators) [1]. There have been efforts in using mediation analysis to dissect the direct and indirect effects of genetic variants on complex diseases in genetic variant association studies [3,4,5,6,7] Most of these studies used data from genome-wide association (GWA) studies, in which the outcome variables were selected on the basis of case-control study design. According to recent studies of secondary phenotypes, the bias could arise in the estimations of the genetic variant-mediator association because the presence or absence of the mediator (i.e., cases and controls with respect to the mediator) is not sampled following the principles of case-control study design [8,9,10,11,12] In this case, the mediation analysis using data from case-control studies might lead to biased indirect effect estimates, either over- or under-estimated depending on the prevalence values of outcome and mediators
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
