Resolving the Effects of Maternal and Offspring Genotype on Dyadic Outcomes in Genome Wide Complex Trait Analysis (“M-GCTA”)
- 746 Downloads
Genome wide complex trait analysis (GCTA) is extended to include environmental effects of the maternal genotype on offspring phenotype (“maternal effects”, M-GCTA). The model includes parameters for the direct effects of the offspring genotype, maternal effects and the covariance between direct and maternal effects. Analysis of simulated data, conducted in OpenMx, confirmed that model parameters could be recovered by full information maximum likelihood (FIML) and evaluated the biases that arise in conventional GCTA when indirect genetic effects are ignored. Estimates derived from FIML in OpenMx showed very close agreement to those obtained by restricted maximum likelihood using the published algorithm for GCTA. The method was also applied to illustrative perinatal phenotypes from ~4,000 mother-offspring pairs from the Avon Longitudinal Study of Parents and Children. The relative merits of extended GCTA in contrast to quantitative genetic approaches based on analyzing the phenotypic covariance structure of kinships are considered.
KeywordsMaternal effects Genome wide complex trait analysis GCTA Twins Heritability Bias Genetic relatedness Covariance Environment SNPs
This work was partly conducted in the Medical Research Council Integrative Epidemiology Unit, a research unit supported by the Medical Research Council (MC_UU_12013 to GDS). The study was supported by a Benjamin Meaker visiting professorship at the University of Bristol Institute for Advanced Studies, UK (LJE), an Australian Research Council Future Fellowship (FT130101709, DME), a Medical Research Council Programme Grant (MC_UU_12013/4, DME), National Institute of Health grants P60MD002256 (York, Eaves) and R01AA018333 (Eaves, York) and an Autism Speaks grant (7132,BStP). We thank Peter Visscher and Matthew Robinson for insightful comments on an earlier draft of this paper. We are extremely grateful to all the families who took part in the study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. The UK Medical Research Council and the Wellcome Trust (Grant ref: 092731) and the University of Bristol provide core support for ALSPAC. This publication is the work of the authors and D.M.E will serve as guarantor for the contents of this paper.
- Boker SM, Neale MC, Maes HH, Wilde MJ, Spiegel M, Timothy R, Brick TR, Spies J, Estabrook R, Bates TC, Mehta P, Fox J, von Oertzen T, Gore RJ, Hunter MD, Hackett DC, Karch J, Brandmaier AM (2012) OpenMx 999.0 User GuideGoogle Scholar
- Dawkins R (1989) The extended phenotype. Oxford University Press, OxfordGoogle Scholar
- Evans DM, Zhu G, Dy V, Heath AC, Madden PA, Kemp JP, McMahon G, St Pourcain B, Timpson NJ, Golding J, Lawlor DA, Steer C, Montgomery GW, Martin NG, Smith GD, Whitfield JB (2013) Genome-wide association study identifies loci affecting blood copper, selenium and zinc. Hum Mol Genet 22:3807–3817PubMedCentralPubMedCrossRefGoogle Scholar
- Falconer DS, McKay TFC (1996) Introduction to quantitative genetics, 4th edn. Pearson Education, HarlowGoogle Scholar
- Fatemifar G, Hoggart CJ, Paternoster L, Kemp JP, Prokopenko I, Horikoshi M, Wright VJ, Tobias JH, Richmond S, Zhurov AI, Toma AM, Pouta A, Taanila A, Sipila K, Lähdesmäki R, Pillas D, Geller F, Feenstra B, Melbye M, Nohr EA, Ring SM, St Pourcain B, Timpson NJ, Davey Smith G, Jarvelin MR, Evans DM (2013) Genome-wide association study of primary tooth eruption identifies pleiotropic loci associated with height and craniofacial distances. Hum Mol Genet 22:3807–3817PubMedCentralPubMedCrossRefGoogle Scholar
- Fraser A, Macdonald-Wallis C, Tilling K, Boyd A, Golding J, Davey Smith G, Henderson J, Macleod J, Molloy L, Ness A, Ring S, Nelson SM, Lawlor DA (2013) Cohort profile: the Avon Longitudinal Study of Parents and Children: ALSPAC mothers cohort. Int J Epidemiol 42:97–110PubMedCentralPubMedCrossRefGoogle Scholar
- Wright S (1921) Correlation and Causation. J Agr Res 20:557–585Google Scholar
- Yang J, Manolio TA, Pasquale LR, Boerwinkle E, Caporaso N, Cunningham JM, de Andrade M, Feenstra B, Feingold E, Hayes MG, Hill WG, Landi MT, Alonso A, Lettre G, Lin P, Ling H, Lowe W, Mathias RA, Melbye M, Pugh E, Cornelis MC, Weir BS, Goddard ME, Visscher PM (2011b) Genome partitioning of genetic variation for complex traits using common SNPs. Nat Genet 43:519–525PubMedCrossRefGoogle Scholar