title: Estimating Modifying Effect of Age on Genetic and Environmental Variance Components in Twin Models.
abstract: Twin studies have been adopted for decades to disentangle the relative genetic and environmental contributions for a wide range of traits. However, heritability estimation based on the classical twin models does not take into account dynamic behavior of the variance components over age. Varying variance of the genetic component over age can imply the existence of gene-environment (G×E) interactions that general genome-wide association studies (GWAS) fail to capture, which may lead to the inconsistency of heritability estimates between twin design and GWAS. Existing parametricG×Einteraction models for twin studies are limited by assuming a linear or quadratic form of the variance curves with respect to a moderator that can, however, be overly restricted in reality. Here we propose spline-based approaches to explore the variance curves of the genetic and environmental components. We choose the additive genetic, common, and unique environmental variance components (ACE) model as the starting point. We treat the component variances as variance functions with respect to age modeled by B-splines or P-splines. We develop an empirical Bayes method to estimate the variance curves together with their confidence bands and provide an R package for public use. Our simulations demonstrate that the proposed methods accurately capture dynamic behavior of the component variances in terms of mean square errors with a data set of >10,000 twin pairs. Using the proposed methods as an alternative and major extension to the classical twin models, our analyses with a large-scale Finnish twin data set (19,510 MZ twins and 27,312 DZ same-sex twins) discover that the variances of the A, C, and E components for body mass index (BMI) change substantially across life span in different patterns and the heritability of BMI drops to ∼50% after middle age. The results further indicate that the decline of heritability is due to increasing unique environmental variance, which provides more insights into age-specific heritability of BMI and evidence ofG×Einteractions. These findings highlight the fundamental importance and implication of the proposed models in facilitating twin studies to investigate the heritability specific to age and other modifying factors.
authors: Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, North Carolina liang.he@duke.edu.
authors: Liang
authors: L
authors: He
authors: Department of Mathematical Sciences, University of Oulu, Oulu, Finland Biocenter Oulu, Oulu, Finland.
authors: Mikko J
authors: MJ
authors: Sillanpää
authors: Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
authors: Karri
authors: K
authors: Silventoinen
authors: Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland National Institute for Health and Welfare, Helsinki, Finland Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland.
authors: Jaakko
authors: http://orcid.org/0000-0002-3716-2455
authors: J
authors: Kaprio
authors: Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland Finnish Cancer Registry, Institute for Statistical and Epidemiological Cancer Research, Helsinki, Finland.
authors: Janne
authors: J
authors: Pitkäniemi
mesh_terms: D000375:Aging / Q000235:genetics*; D000465:Algorithms; D059647:Gene-Environment Interaction; D055106:Genome-Wide Association Study; D006801:Humans; D008957:Models, Genetic; D014427:Twins / Q000235:genetics*
keywords: age-specific heritability; body mass index; empirical Bayes predictor; penalized B-splines; twin models