School of Medicine Publications and Presentations
Document Type
Article
Publication Date
1-2016
Abstract
Maternal-offspring gene interactions, aka maternal-fetal genotype (MFG) incompatibilities, are neglected in complex diseases and quantitative trait studies. They are implicated in birth to adult onset diseases but there are limited ways to investigate their influence on quantitative traits. We present the Quantitative-MFG (QMFG) test, a linear mixed model where maternal and offspring genotypes are fixed effects and residual correlations between family members are random effects. The QMFG handles families of any size, common or general scenarios of MFG incompatibility, and additional covariates. We develop likelihood ratio tests (LRTs) and rapid score tests and show they provide correct inference. In addition, the LRT’s alternative model provides unbiased parameter estimates. We show that testing the association of SNPs by fitting a standard model, which only considers the offspring genotypes, has very low power or can lead to incorrect conclusions. We also show that offspring genetic effects are missed if the MFG modeling assumptions are too restrictive. With GWAS data from the San Antonio Family Heart Study, we demonstrate that the QMFG score test is an effective and rapid screening tool. The QMFG test therefore has important potential to identify pathways of complex diseases for which the genetic etiology remains to be discovered.
Recommended Citation
Clark, M. M., Blangero, J., Dyer, T. D., Sobel, E. M., & Sinsheimer, J. S. (2016). The Quantitative-MFG Test: A Linear Mixed Effect Model to Detect Maternal-Offspring Gene Interactions. Annals of Human Genetics, 80(1), 63–80. https://doi.org/10.1111/ahg.12137
First Page
63
Last Page
80
Publication Title
Annals of Human Genetics
DOI
10.1111/ahg.12137
Academic Level
faculty
Mentor/PI Department
Office of Human Genetics
Comments
© 2015 John Wiley & Sons Ltd/University College London. Original published version available at https://doi.org/10.1111/ahg.12137