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The Quantitative‐MFG Test: A Linear Mixed Effect Model to Detect Maternal‐Offspring Gene Interactions
Author(s) -
Clark Michelle M.,
Blangero John,
Dyer Thomas D.,
Sobel Eric M.,
Sinsheimer Janet S.
Publication year - 2016
Publication title -
annals of human genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.537
H-Index - 77
eISSN - 1469-1809
pISSN - 0003-4800
DOI - 10.1111/ahg.12137
Subject(s) - offspring , biology , score test , genotype , covariate , trait , quantitative trait locus , genetic association , random effects model , linear model , generalized linear mixed model , genome wide association study , single nucleotide polymorphism , genetics , likelihood ratio test , statistics , gene , pregnancy , medicine , computer science , mathematics , meta analysis , programming language
SUMMARY 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 genome‐wide association study 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.