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Genomic analysis of family data reveals additional genetic effects on intelligence and personality
Pedigree-based analyses of intelligence have reported that genetic differences account for 50–80% of the phenotypic variation. For personality traits these effects are smaller, with 34–48% of the variance being explained by genetic differences. However, molecular genetic studies using unrelated indi...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6294741/ https://www.ncbi.nlm.nih.gov/pubmed/29321673 http://dx.doi.org/10.1038/s41380-017-0005-1 |
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author | Hill, W. David Arslan, Ruben C. Xia, Charley Luciano, Michelle Amador, Carmen Navarro, Pau Hayward, Caroline Nagy, Reka Porteous, David J. McIntosh, Andrew M. Deary, Ian J. Haley, Chris S. Penke, Lars |
author_facet | Hill, W. David Arslan, Ruben C. Xia, Charley Luciano, Michelle Amador, Carmen Navarro, Pau Hayward, Caroline Nagy, Reka Porteous, David J. McIntosh, Andrew M. Deary, Ian J. Haley, Chris S. Penke, Lars |
author_sort | Hill, W. David |
collection | PubMed |
description | Pedigree-based analyses of intelligence have reported that genetic differences account for 50–80% of the phenotypic variation. For personality traits these effects are smaller, with 34–48% of the variance being explained by genetic differences. However, molecular genetic studies using unrelated individuals typically report a heritability estimate of around 30% for intelligence and between 0 and 15% for personality variables. Pedigree-based estimates and molecular genetic estimates may differ because current genotyping platforms are poor at tagging causal variants, variants with low minor allele frequency, copy number variants, and structural variants. Using ~20,000 individuals in the Generation Scotland family cohort genotyped for ~700,000 single-nucleotide polymorphisms (SNPs), we exploit the high levels of linkage disequilibrium (LD) found in members of the same family to quantify the total effect of genetic variants that are not tagged in GWAS of unrelated individuals. In our models, genetic variants in low LD with genotyped SNPs explain over half of the genetic variance in intelligence, education, and neuroticism. By capturing these additional genetic effects our models closely approximate the heritability estimates from twin studies for intelligence and education, but not for neuroticism and extraversion. We then replicated our finding using imputed molecular genetic data from unrelated individuals to show that ~50% of differences in intelligence, and ~40% of the differences in education, can be explained by genetic effects when a larger number of rare SNPs are included. From an evolutionary genetic perspective, a substantial contribution of rare genetic variants to individual differences in intelligence, and education is consistent with mutation-selection balance. |
format | Online Article Text |
id | pubmed-6294741 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-62947412018-12-17 Genomic analysis of family data reveals additional genetic effects on intelligence and personality Hill, W. David Arslan, Ruben C. Xia, Charley Luciano, Michelle Amador, Carmen Navarro, Pau Hayward, Caroline Nagy, Reka Porteous, David J. McIntosh, Andrew M. Deary, Ian J. Haley, Chris S. Penke, Lars Mol Psychiatry Article Pedigree-based analyses of intelligence have reported that genetic differences account for 50–80% of the phenotypic variation. For personality traits these effects are smaller, with 34–48% of the variance being explained by genetic differences. However, molecular genetic studies using unrelated individuals typically report a heritability estimate of around 30% for intelligence and between 0 and 15% for personality variables. Pedigree-based estimates and molecular genetic estimates may differ because current genotyping platforms are poor at tagging causal variants, variants with low minor allele frequency, copy number variants, and structural variants. Using ~20,000 individuals in the Generation Scotland family cohort genotyped for ~700,000 single-nucleotide polymorphisms (SNPs), we exploit the high levels of linkage disequilibrium (LD) found in members of the same family to quantify the total effect of genetic variants that are not tagged in GWAS of unrelated individuals. In our models, genetic variants in low LD with genotyped SNPs explain over half of the genetic variance in intelligence, education, and neuroticism. By capturing these additional genetic effects our models closely approximate the heritability estimates from twin studies for intelligence and education, but not for neuroticism and extraversion. We then replicated our finding using imputed molecular genetic data from unrelated individuals to show that ~50% of differences in intelligence, and ~40% of the differences in education, can be explained by genetic effects when a larger number of rare SNPs are included. From an evolutionary genetic perspective, a substantial contribution of rare genetic variants to individual differences in intelligence, and education is consistent with mutation-selection balance. Nature Publishing Group UK 2018-01-10 2018 /pmc/articles/PMC6294741/ /pubmed/29321673 http://dx.doi.org/10.1038/s41380-017-0005-1 Text en © The Author(s) 2018 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Hill, W. David Arslan, Ruben C. Xia, Charley Luciano, Michelle Amador, Carmen Navarro, Pau Hayward, Caroline Nagy, Reka Porteous, David J. McIntosh, Andrew M. Deary, Ian J. Haley, Chris S. Penke, Lars Genomic analysis of family data reveals additional genetic effects on intelligence and personality |
title | Genomic analysis of family data reveals additional genetic effects on intelligence and personality |
title_full | Genomic analysis of family data reveals additional genetic effects on intelligence and personality |
title_fullStr | Genomic analysis of family data reveals additional genetic effects on intelligence and personality |
title_full_unstemmed | Genomic analysis of family data reveals additional genetic effects on intelligence and personality |
title_short | Genomic analysis of family data reveals additional genetic effects on intelligence and personality |
title_sort | genomic analysis of family data reveals additional genetic effects on intelligence and personality |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6294741/ https://www.ncbi.nlm.nih.gov/pubmed/29321673 http://dx.doi.org/10.1038/s41380-017-0005-1 |
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