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Genetic Influences on the Covariance and Genetic Correlations in a Bivariate Twin Model: An Application to Well-Being
The distinction between genetic influences on the covariance (or bivariate heritability) and genetic correlations in bivariate twin models is often not well-understood or only one is reported while the results show distinctive information about the relation between traits. We applied bivariate twin...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8093176/ https://www.ncbi.nlm.nih.gov/pubmed/33582898 http://dx.doi.org/10.1007/s10519-021-10046-y |
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author | de Vries, Lianne P. van Beijsterveldt, Toos C. E. M. Maes, Hermine Colodro-Conde, Lucía Bartels, Meike |
author_facet | de Vries, Lianne P. van Beijsterveldt, Toos C. E. M. Maes, Hermine Colodro-Conde, Lucía Bartels, Meike |
author_sort | de Vries, Lianne P. |
collection | PubMed |
description | The distinction between genetic influences on the covariance (or bivariate heritability) and genetic correlations in bivariate twin models is often not well-understood or only one is reported while the results show distinctive information about the relation between traits. We applied bivariate twin models in a large sample of adolescent twins, to disentangle the association between well-being (WB) and four complex traits (optimism, anxious-depressed symptoms (AD), aggressive behaviour (AGG), and educational achievement (EA)). Optimism and AD showed respectively a strong positive and negative phenotypic correlation with WB, the negative correlation of WB and AGG is lower and the correlation with EA is nearly zero. All four traits showed a large genetic contribution to the covariance with well-being. The genetic correlations of well-being with optimism and AD are strong and smaller for AGG and EA. We used the results of the models to explain what information is retrieved based on the bivariate heritability versus the genetic correlations and the (clinical) implications. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10519-021-10046-y. |
format | Online Article Text |
id | pubmed-8093176 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-80931762021-05-05 Genetic Influences on the Covariance and Genetic Correlations in a Bivariate Twin Model: An Application to Well-Being de Vries, Lianne P. van Beijsterveldt, Toos C. E. M. Maes, Hermine Colodro-Conde, Lucía Bartels, Meike Behav Genet Original Research The distinction between genetic influences on the covariance (or bivariate heritability) and genetic correlations in bivariate twin models is often not well-understood or only one is reported while the results show distinctive information about the relation between traits. We applied bivariate twin models in a large sample of adolescent twins, to disentangle the association between well-being (WB) and four complex traits (optimism, anxious-depressed symptoms (AD), aggressive behaviour (AGG), and educational achievement (EA)). Optimism and AD showed respectively a strong positive and negative phenotypic correlation with WB, the negative correlation of WB and AGG is lower and the correlation with EA is nearly zero. All four traits showed a large genetic contribution to the covariance with well-being. The genetic correlations of well-being with optimism and AD are strong and smaller for AGG and EA. We used the results of the models to explain what information is retrieved based on the bivariate heritability versus the genetic correlations and the (clinical) implications. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10519-021-10046-y. Springer US 2021-02-13 2021 /pmc/articles/PMC8093176/ /pubmed/33582898 http://dx.doi.org/10.1007/s10519-021-10046-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Research de Vries, Lianne P. van Beijsterveldt, Toos C. E. M. Maes, Hermine Colodro-Conde, Lucía Bartels, Meike Genetic Influences on the Covariance and Genetic Correlations in a Bivariate Twin Model: An Application to Well-Being |
title | Genetic Influences on the Covariance and Genetic Correlations in a Bivariate Twin Model: An Application to Well-Being |
title_full | Genetic Influences on the Covariance and Genetic Correlations in a Bivariate Twin Model: An Application to Well-Being |
title_fullStr | Genetic Influences on the Covariance and Genetic Correlations in a Bivariate Twin Model: An Application to Well-Being |
title_full_unstemmed | Genetic Influences on the Covariance and Genetic Correlations in a Bivariate Twin Model: An Application to Well-Being |
title_short | Genetic Influences on the Covariance and Genetic Correlations in a Bivariate Twin Model: An Application to Well-Being |
title_sort | genetic influences on the covariance and genetic correlations in a bivariate twin model: an application to well-being |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8093176/ https://www.ncbi.nlm.nih.gov/pubmed/33582898 http://dx.doi.org/10.1007/s10519-021-10046-y |
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