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GWAS-based pathway analysis differentiates between fluid and crystallized intelligence
Cognitive abilities vary among people. About 40–50% of this variability is due to general intelligence (g), which reflects the positive correlation among individuals' scores on diverse cognitive ability tests. g is positively correlated with many life outcomes, such as education, occupational s...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Blackwell Publishing Ltd
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4261989/ https://www.ncbi.nlm.nih.gov/pubmed/24975275 http://dx.doi.org/10.1111/gbb.12152 |
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author | Christoforou, A Espeseth, T Davies, G Fernandes, C P D Giddaluru, S Mattheisen, M Tenesa, A Harris, S E Liewald, D C Payton, A Ollier, W Horan, M Pendleton, N Haggarty, P Djurovic, S Herms, S Hoffman, P Cichon, S Starr, J M Lundervold, A Reinvang, I Steen, V M Deary, I J Le Hellard, S |
author_facet | Christoforou, A Espeseth, T Davies, G Fernandes, C P D Giddaluru, S Mattheisen, M Tenesa, A Harris, S E Liewald, D C Payton, A Ollier, W Horan, M Pendleton, N Haggarty, P Djurovic, S Herms, S Hoffman, P Cichon, S Starr, J M Lundervold, A Reinvang, I Steen, V M Deary, I J Le Hellard, S |
author_sort | Christoforou, A |
collection | PubMed |
description | Cognitive abilities vary among people. About 40–50% of this variability is due to general intelligence (g), which reflects the positive correlation among individuals' scores on diverse cognitive ability tests. g is positively correlated with many life outcomes, such as education, occupational status and health, motivating the investigation of its underlying biology. In psychometric research, a distinction is made between general fluid intelligence (gF) – the ability to reason in novel situations – and general crystallized intelligence (gC) – the ability to apply acquired knowledge. This distinction is supported by developmental and cognitive neuroscience studies. Classical epidemiological studies and recent genome-wide association studies (GWASs) have established that these cognitive traits have a large genetic component. However, no robust genetic associations have been published thus far due largely to the known polygenic nature of these traits and insufficient sample sizes. Here, using two GWAS datasets, in which the polygenicity of gF and gC traits was previously confirmed, a gene- and pathway-based approach was undertaken with the aim of characterizing and differentiating their genetic architecture. Pathway analysis, using genes selected on the basis of relaxed criteria, revealed notable differences between these two traits. gF appeared to be characterized by genes affecting the quantity and quality of neurons and therefore neuronal efficiency, whereas long-term depression (LTD) seemed to underlie gC. Thus, this study supports the gF–gC distinction at the genetic level and identifies functional annotations and pathways worthy of further investigation. |
format | Online Article Text |
id | pubmed-4261989 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Blackwell Publishing Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-42619892014-12-15 GWAS-based pathway analysis differentiates between fluid and crystallized intelligence Christoforou, A Espeseth, T Davies, G Fernandes, C P D Giddaluru, S Mattheisen, M Tenesa, A Harris, S E Liewald, D C Payton, A Ollier, W Horan, M Pendleton, N Haggarty, P Djurovic, S Herms, S Hoffman, P Cichon, S Starr, J M Lundervold, A Reinvang, I Steen, V M Deary, I J Le Hellard, S Genes Brain Behav Original Articles Cognitive abilities vary among people. About 40–50% of this variability is due to general intelligence (g), which reflects the positive correlation among individuals' scores on diverse cognitive ability tests. g is positively correlated with many life outcomes, such as education, occupational status and health, motivating the investigation of its underlying biology. In psychometric research, a distinction is made between general fluid intelligence (gF) – the ability to reason in novel situations – and general crystallized intelligence (gC) – the ability to apply acquired knowledge. This distinction is supported by developmental and cognitive neuroscience studies. Classical epidemiological studies and recent genome-wide association studies (GWASs) have established that these cognitive traits have a large genetic component. However, no robust genetic associations have been published thus far due largely to the known polygenic nature of these traits and insufficient sample sizes. Here, using two GWAS datasets, in which the polygenicity of gF and gC traits was previously confirmed, a gene- and pathway-based approach was undertaken with the aim of characterizing and differentiating their genetic architecture. Pathway analysis, using genes selected on the basis of relaxed criteria, revealed notable differences between these two traits. gF appeared to be characterized by genes affecting the quantity and quality of neurons and therefore neuronal efficiency, whereas long-term depression (LTD) seemed to underlie gC. Thus, this study supports the gF–gC distinction at the genetic level and identifies functional annotations and pathways worthy of further investigation. Blackwell Publishing Ltd 2014-09 2014-08-08 /pmc/articles/PMC4261989/ /pubmed/24975275 http://dx.doi.org/10.1111/gbb.12152 Text en © 2014 The Authors. Genes, Brain and Behavior published by International Behavioural and Neural Genetics Society and John Wiley & Sons Ltd. http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
spellingShingle | Original Articles Christoforou, A Espeseth, T Davies, G Fernandes, C P D Giddaluru, S Mattheisen, M Tenesa, A Harris, S E Liewald, D C Payton, A Ollier, W Horan, M Pendleton, N Haggarty, P Djurovic, S Herms, S Hoffman, P Cichon, S Starr, J M Lundervold, A Reinvang, I Steen, V M Deary, I J Le Hellard, S GWAS-based pathway analysis differentiates between fluid and crystallized intelligence |
title | GWAS-based pathway analysis differentiates between fluid and crystallized intelligence |
title_full | GWAS-based pathway analysis differentiates between fluid and crystallized intelligence |
title_fullStr | GWAS-based pathway analysis differentiates between fluid and crystallized intelligence |
title_full_unstemmed | GWAS-based pathway analysis differentiates between fluid and crystallized intelligence |
title_short | GWAS-based pathway analysis differentiates between fluid and crystallized intelligence |
title_sort | gwas-based pathway analysis differentiates between fluid and crystallized intelligence |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4261989/ https://www.ncbi.nlm.nih.gov/pubmed/24975275 http://dx.doi.org/10.1111/gbb.12152 |
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