Multilevel Twin Models: Geographical Region as a Third Level Variable

Tamimy, Zenab; Kevenaar, Sofieke T.; Hottenga, Jouke Jan; Hunter, Michael D.; Zeeuw, Eveline L. de; Neale, Michael C.; Beijsterveldt, Catharina E. M. van; Dolan, Conor V.; Bergen, Elsje van; Boomsma, Dorret I.

doi:10.1101/2020.11.11.377820

Cited by 3 publications

(2 citation statements)

References 45 publications

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“…In multi-level twin models 60 , variance is decomposed into within-pair variance on the first level, between-family variance on the second level, and the variance of a higher-level clustering variable on the third level. Multi-level twin modeling indicated that regional clustering effects can 10 mask genetic ancestry effects 61 . Importantly, multi-level twin models enable researchers to correct for experimental clustering like batch effects in biomarker or omics studies 62 .…”

Section: Clustering Across Families: Multilevel Twin Modelsmentioning

confidence: 99%

Maximising the Value of Twin Studies in Health and Behaviour

Hagenbeek¹,

Hirzinger²,

Breunig³

et al. 2022

Preprint

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This contribution considers developments in the field of ‘twin studies’ in times of rapid changes in society, and technological and methodological advances. The classical twin design is of value to emerging and re-emerging phenotypes, including those from evolving omics technologies and offers advances for modeling causality, intergenerational transmission, gene-environment correlation and interaction. We summarize what we have learned about twinning and look at whether twins and twin studies are representative of the general population and cover global diversity. We provide an updated overview of twin concordance and discordance for major diseases and disorders, which convey a crucial message: the genetic code is not as deterministic as often believed. This has important implications for genetic risk prediction tools utilized by researchers and clinicians, as predictions can only go as far as the monozygotic twin concordance rates.

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Section: Clustering Across Families: Multilevel Twin Modelsmentioning

confidence: 99%

Maximising the Value of Twin Studies in Health and Behaviour

Hagenbeek¹,

Hirzinger²,

Breunig³

et al. 2022

Preprint

View full text Add to dashboard Cite

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“…We point out that the degree of similarity depends on the heterogeneity of the population in focus and that shared environments comprise both effects that are shared uniquely in families and effects that are shared by larger groupsincluding families. If there are putative factors shared by people in a certain area, the effect should show up as a shared environmental effect in behavioral-genetic studies (Tamimy et al, 2021). However, such effects have been detected to only a very limited degree so far.…”

mentioning

confidence: 99%

Worldwide Well-Being: Simulated Twins Reveal Genetic and (Hidden) Environmental Influences

Røysamb

Moffitt

Caspi

et al. 2023

Perspect Psychol Sci

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What are the major sources of worldwide variability in subjective well-being (SWB)? Twin and family studies of SWB have found substantial heritability and strong effects from unique environments but virtually no effects from shared environments. However, extant findings are not necessarily valid at the global level. Prior studies have examined within-countries variability but did not take into account mean differences across nations. In this article, we aim to estimate the effects of genetic factors, individual environmental exposures, and shared environments for the global population. We combine a set of knowns from national well-being studies (means and standard deviations) and behavioral-genetic studies (heritability) to model a scenario of twin studies across 157 countries. For each country, we simulate data for a set of twin pairs and pool the data into a global sample. We find a worldwide heritability of 31% to 32% for SWB. Individual environmental factors explain 46% to 52% of the variance (including measurement error), and shared environments account for 16% to 23% of the global variance in SWB. Worldwide, well-being is somewhat less heritable than within nations. In contrast to previous within-countries studies, we find a notable effect of shared environments. This effect is not limited to within families but operates at a national level.

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Incorporating Polygenic Risk Scores in the ACE Twin Model to Estimate A–C Covariance

et al. 2021

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The assumption in the twin model that genotypic and environmental variables are uncorrelated is primarily made to ensure parameter identification, not because researchers necessarily think that these variables are uncorrelated. Although the biasing effects of such correlations are well understood, a method to estimate these parameters in the twin model would be useful. Here we explore the possibility of relaxing this assumption by adding polygenic scores to the (univariate) twin model. We demonstrate that this extension renders the additive genetic (A)—common environmental (C) covariance (σAC) identified. We study the statistical power to reject σAC = 0 in the ACE model and present the results of simulations.

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Multilevel Twin Models: Geographical Region as a Third Level Variable

Cited by 3 publications

References 45 publications

Maximising the Value of Twin Studies in Health and Behaviour

Maximising the Value of Twin Studies in Health and Behaviour

Worldwide Well-Being: Simulated Twins Reveal Genetic and (Hidden) Environmental Influences

Incorporating Polygenic Risk Scores in the ACE Twin Model to Estimate A–C Covariance

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