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A Genetic Investigation of the Well-Being Spectrum
The interrelations among well-being, neuroticism, and depression can be captured in a so-called well-being spectrum (3-phenotype well-being spectrum, 3-WBS). Several other human traits are likely linked to the 3-WBS. In the present study, we investigate how the 3-WBS can be expanded. First, we const...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6497622/ https://www.ncbi.nlm.nih.gov/pubmed/30810878 http://dx.doi.org/10.1007/s10519-019-09951-0 |
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author | Baselmans, B. M. L. van de Weijer, M. P. Abdellaoui, A. Vink, J. M. Hottenga, J. J. Willemsen, G. Nivard, M. G. de Geus, E. J. C. Boomsma, D. I. Bartels, M. |
author_facet | Baselmans, B. M. L. van de Weijer, M. P. Abdellaoui, A. Vink, J. M. Hottenga, J. J. Willemsen, G. Nivard, M. G. de Geus, E. J. C. Boomsma, D. I. Bartels, M. |
author_sort | Baselmans, B. M. L. |
collection | PubMed |
description | The interrelations among well-being, neuroticism, and depression can be captured in a so-called well-being spectrum (3-phenotype well-being spectrum, 3-WBS). Several other human traits are likely linked to the 3-WBS. In the present study, we investigate how the 3-WBS can be expanded. First, we constructed polygenic risk scores for the 3-WBS and used this score to predict a series of traits that have been associated with well-being in the literature. We included information on loneliness, big five personality traits, self-rated health, and flourishing. The 3-WBS polygenic score predicted all the original 3-WBS traits and additionally loneliness, self-rated health, and extraversion (R(2) between 0.62% and 1.58%). Next, using LD score regression, we calculated genetic correlations between the 3-WBS and the traits of interest. From all candidate traits, loneliness and self-rated health were found to have the strongest genetic correlations (r(g) = − 0.79, and r(g)= 0.64, respectively) with the 3-WBS. Lastly, we use Genomic SEM to investigate the factor structure of the proposed spectrum. The best model fit was obtained for a two-factor model including the 5-WBS traits, with two highly correlated factors representing the negative- and positive end of the spectrum. Based on these analyses we propose to include loneliness and self-rated health in the WBS and use a 5-phenotype well-being spectrum in future studies to gain more insight into the determinants of human well-being. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10519-019-09951-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6497622 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-64976222019-05-17 A Genetic Investigation of the Well-Being Spectrum Baselmans, B. M. L. van de Weijer, M. P. Abdellaoui, A. Vink, J. M. Hottenga, J. J. Willemsen, G. Nivard, M. G. de Geus, E. J. C. Boomsma, D. I. Bartels, M. Behav Genet Original Research The interrelations among well-being, neuroticism, and depression can be captured in a so-called well-being spectrum (3-phenotype well-being spectrum, 3-WBS). Several other human traits are likely linked to the 3-WBS. In the present study, we investigate how the 3-WBS can be expanded. First, we constructed polygenic risk scores for the 3-WBS and used this score to predict a series of traits that have been associated with well-being in the literature. We included information on loneliness, big five personality traits, self-rated health, and flourishing. The 3-WBS polygenic score predicted all the original 3-WBS traits and additionally loneliness, self-rated health, and extraversion (R(2) between 0.62% and 1.58%). Next, using LD score regression, we calculated genetic correlations between the 3-WBS and the traits of interest. From all candidate traits, loneliness and self-rated health were found to have the strongest genetic correlations (r(g) = − 0.79, and r(g)= 0.64, respectively) with the 3-WBS. Lastly, we use Genomic SEM to investigate the factor structure of the proposed spectrum. The best model fit was obtained for a two-factor model including the 5-WBS traits, with two highly correlated factors representing the negative- and positive end of the spectrum. Based on these analyses we propose to include loneliness and self-rated health in the WBS and use a 5-phenotype well-being spectrum in future studies to gain more insight into the determinants of human well-being. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10519-019-09951-0) contains supplementary material, which is available to authorized users. Springer US 2019-02-27 2019 /pmc/articles/PMC6497622/ /pubmed/30810878 http://dx.doi.org/10.1007/s10519-019-09951-0 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Research Baselmans, B. M. L. van de Weijer, M. P. Abdellaoui, A. Vink, J. M. Hottenga, J. J. Willemsen, G. Nivard, M. G. de Geus, E. J. C. Boomsma, D. I. Bartels, M. A Genetic Investigation of the Well-Being Spectrum |
title | A Genetic Investigation of the Well-Being Spectrum |
title_full | A Genetic Investigation of the Well-Being Spectrum |
title_fullStr | A Genetic Investigation of the Well-Being Spectrum |
title_full_unstemmed | A Genetic Investigation of the Well-Being Spectrum |
title_short | A Genetic Investigation of the Well-Being Spectrum |
title_sort | genetic investigation of the well-being spectrum |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6497622/ https://www.ncbi.nlm.nih.gov/pubmed/30810878 http://dx.doi.org/10.1007/s10519-019-09951-0 |
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