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A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence
Intelligence, or general cognitive function, is phenotypically and genetically correlated with many traits, including a wide range of physical, and mental health variables. Education is strongly genetically correlated with intelligence (r(g) = 0.70). We used these findings as foundations for our use...
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/PMC6344370/ https://www.ncbi.nlm.nih.gov/pubmed/29326435 http://dx.doi.org/10.1038/s41380-017-0001-5 |
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author | Hill, W. D. Marioni, R. E. Maghzian, O. Ritchie, S. J. Hagenaars, S. P. McIntosh, A. M. Gale, C. R. Davies, G. Deary, I. J. |
author_facet | Hill, W. D. Marioni, R. E. Maghzian, O. Ritchie, S. J. Hagenaars, S. P. McIntosh, A. M. Gale, C. R. Davies, G. Deary, I. J. |
author_sort | Hill, W. D. |
collection | PubMed |
description | Intelligence, or general cognitive function, is phenotypically and genetically correlated with many traits, including a wide range of physical, and mental health variables. Education is strongly genetically correlated with intelligence (r(g) = 0.70). We used these findings as foundations for our use of a novel approach—multi-trait analysis of genome-wide association studies (MTAG; Turley et al. 2017)—to combine two large genome-wide association studies (GWASs) of education and intelligence, increasing statistical power and resulting in the largest GWAS of intelligence yet reported. Our study had four goals: first, to facilitate the discovery of new genetic loci associated with intelligence; second, to add to our understanding of the biology of intelligence differences; third, to examine whether combining genetically correlated traits in this way produces results consistent with the primary phenotype of intelligence; and, finally, to test how well this new meta-analytic data sample on intelligence predicts phenotypic intelligence in an independent sample. By combining datasets using MTAG, our functional sample size increased from 199,242 participants to 248,482. We found 187 independent loci associated with intelligence, implicating 538 genes, using both SNP-based and gene-based GWAS. We found evidence that neurogenesis and myelination—as well as genes expressed in the synapse, and those involved in the regulation of the nervous system—may explain some of the biological differences in intelligence. The results of our combined analysis demonstrated the same pattern of genetic correlations as those from previous GWASs of intelligence, providing support for the meta-analysis of these genetically-related phenotypes. |
format | Online Article Text |
id | pubmed-6344370 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-63443702019-01-25 A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence Hill, W. D. Marioni, R. E. Maghzian, O. Ritchie, S. J. Hagenaars, S. P. McIntosh, A. M. Gale, C. R. Davies, G. Deary, I. J. Mol Psychiatry Immediate Communication Intelligence, or general cognitive function, is phenotypically and genetically correlated with many traits, including a wide range of physical, and mental health variables. Education is strongly genetically correlated with intelligence (r(g) = 0.70). We used these findings as foundations for our use of a novel approach—multi-trait analysis of genome-wide association studies (MTAG; Turley et al. 2017)—to combine two large genome-wide association studies (GWASs) of education and intelligence, increasing statistical power and resulting in the largest GWAS of intelligence yet reported. Our study had four goals: first, to facilitate the discovery of new genetic loci associated with intelligence; second, to add to our understanding of the biology of intelligence differences; third, to examine whether combining genetically correlated traits in this way produces results consistent with the primary phenotype of intelligence; and, finally, to test how well this new meta-analytic data sample on intelligence predicts phenotypic intelligence in an independent sample. By combining datasets using MTAG, our functional sample size increased from 199,242 participants to 248,482. We found 187 independent loci associated with intelligence, implicating 538 genes, using both SNP-based and gene-based GWAS. We found evidence that neurogenesis and myelination—as well as genes expressed in the synapse, and those involved in the regulation of the nervous system—may explain some of the biological differences in intelligence. The results of our combined analysis demonstrated the same pattern of genetic correlations as those from previous GWASs of intelligence, providing support for the meta-analysis of these genetically-related phenotypes. Nature Publishing Group UK 2018-01-11 2019 /pmc/articles/PMC6344370/ /pubmed/29326435 http://dx.doi.org/10.1038/s41380-017-0001-5 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 | Immediate Communication Hill, W. D. Marioni, R. E. Maghzian, O. Ritchie, S. J. Hagenaars, S. P. McIntosh, A. M. Gale, C. R. Davies, G. Deary, I. J. A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence |
title | A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence |
title_full | A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence |
title_fullStr | A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence |
title_full_unstemmed | A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence |
title_short | A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence |
title_sort | combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence |
topic | Immediate Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6344370/ https://www.ncbi.nlm.nih.gov/pubmed/29326435 http://dx.doi.org/10.1038/s41380-017-0001-5 |
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