University of Oulu

He, L., Pitkäniemi, J., Silventoinen, K. et al. Behav Genet (2017) 47: 620. https://doi.org/10.1007/s10519-017-9866-y

ACEt : an R package for estimating dynamic heritability and comparing twin models

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Author: He, Liang1,2; Pitkäniemi, Janne3,4; Silventoinen, Karri3,5;
Organizations: 1Broad Institute of MIT and Harvard, Cambridge, MA, USA
2Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA
3Department of Public Health, University of Helsinki, Helsinki, Finland
4Finnish Cancer Registry, Institute for Statistical and Epidemiological Cancer Research, Helsinki, Finland
5Population Research Unit, Department of Social Research, University of Helsinki, Helsinki, Finland
6Department of Mathematical Sciences, University of Oulu, Oulu, Finland
7Biocenter Oulu, University of Oulu, Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 1.3 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2019052316735
Language: English
Published: Springer Nature, 2017
Publish Date: 2019-05-23
Description:

Abstract

Estimating dynamic effects of age on the genetic and environmental variance components in twin studies may contribute to the investigation of gene-environment interactions, and may provide more insights into more accurate and powerful estimation of heritability. Existing parametric models for estimating dynamic variance components suffer from various drawbacks such as limitation of predefined functions. We present ACEt, an R package for fast estimating dynamic variance components and heritability that may change with respect to age or other moderators. Building on the twin models using penalized splines, ACEt provides a unified framework to incorporate a class of ACE models, in which each component can be modeled independently and is not limited by a linear or quadratic function. We demonstrate that ACEt is robust against misspecification of the number of spline knots, and offers a refined resolution of dynamic behavior of the genetic and environmental components and thus a detailed estimation of age-specific heritability. Moreover, we develop resampling methods for testing twin models with different variance functions including splines, log-linearity and constancy, which can be easily employed to verify various model assumptions. We evaluated the type I error rate and statistical power of the proposed hypothesis testing procedures under various scenarios using simulated datasets. Potential numerical issues and computational cost were also assessed through simulations. We applied the ACEt package to a Finnish twin cohort to investigate age-specific heritability of body mass index and height. Our results show that the age-specific variance components of these two traits exhibited substantially different patterns despite of comparable estimates of heritability. In summary, the ACEt R package offers a useful tool for the exploration of age-dependent heritability and model comparison in twin studies.

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Series: Behavior genetics
ISSN: 0001-8244
ISSN-E: 1573-3297
ISSN-L: 0001-8244
Volume: 47
Issue: 6
Pages: 620 - 641
DOI: 10.1007/s10519-017-9866-y
OADOI: https://oadoi.org/10.1007/s10519-017-9866-y
Type of Publication: A1 Journal article – refereed
Field of Science: 112 Statistics and probability
1184 Genetics, developmental biology, physiology
3111 Biomedicine
Subjects:
Copyright information: © Springer Science+Business Media, LLC 2017. This is a post-peer-review, pre-copyedit version of an article published in Behavior Genetics Vol. 47 Issue 6. The final authenticated version is available online at: https://doi.org/10.1007/s10519-017-9866-y.