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Substantial SNP-based heritability estimates for working memory performance
Working memory (WM) is an important endophenotype in neuropsychiatric research and its use in genetic association studies is thought to be a promising approach to increase our understanding of psychiatric disease. As for any genetically complex trait, demonstration of sufficient heritability within...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4203010/ https://www.ncbi.nlm.nih.gov/pubmed/25203169 http://dx.doi.org/10.1038/tp.2014.81 |
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author | Vogler, C Gschwind, L Coynel, D Freytag, V Milnik, A Egli, T Heck, A de Quervain, D J-F Papassotiropoulos, A |
author_facet | Vogler, C Gschwind, L Coynel, D Freytag, V Milnik, A Egli, T Heck, A de Quervain, D J-F Papassotiropoulos, A |
author_sort | Vogler, C |
collection | PubMed |
description | Working memory (WM) is an important endophenotype in neuropsychiatric research and its use in genetic association studies is thought to be a promising approach to increase our understanding of psychiatric disease. As for any genetically complex trait, demonstration of sufficient heritability within the specific study context is a prerequisite for conducting genetic studies of that trait. Recently developed methods allow estimating trait heritability using sets of common genetic markers from genome-wide association study (GWAS) data in samples of unrelated individuals. Here we present single-nucleotide polymorphism (SNP)-based heritability estimates (h(2)(SNP)) for a WM phenotype. A Caucasian sample comprising a total of N=2298 healthy and young individuals was subjected to an N-back WM task. We calculated the genetic relationship between all individuals on the basis of genome-wide SNP data and performed restricted maximum likelihood analyses for variance component estimation to derive the h(2)(SNP) estimates. Heritability estimates for three 2-back derived WM performance measures based on all autosomal chromosomes ranged between 31 and 41%, indicating a substantial SNP-based heritability for WM traits. These results indicate that common genetic factors account for a prominent part of the phenotypic variation in WM performance. Hence, the application of GWAS on WM phenotypes is a valid method to identify the molecular underpinnings of WM. |
format | Online Article Text |
id | pubmed-4203010 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-42030102014-11-06 Substantial SNP-based heritability estimates for working memory performance Vogler, C Gschwind, L Coynel, D Freytag, V Milnik, A Egli, T Heck, A de Quervain, D J-F Papassotiropoulos, A Transl Psychiatry Original Article Working memory (WM) is an important endophenotype in neuropsychiatric research and its use in genetic association studies is thought to be a promising approach to increase our understanding of psychiatric disease. As for any genetically complex trait, demonstration of sufficient heritability within the specific study context is a prerequisite for conducting genetic studies of that trait. Recently developed methods allow estimating trait heritability using sets of common genetic markers from genome-wide association study (GWAS) data in samples of unrelated individuals. Here we present single-nucleotide polymorphism (SNP)-based heritability estimates (h(2)(SNP)) for a WM phenotype. A Caucasian sample comprising a total of N=2298 healthy and young individuals was subjected to an N-back WM task. We calculated the genetic relationship between all individuals on the basis of genome-wide SNP data and performed restricted maximum likelihood analyses for variance component estimation to derive the h(2)(SNP) estimates. Heritability estimates for three 2-back derived WM performance measures based on all autosomal chromosomes ranged between 31 and 41%, indicating a substantial SNP-based heritability for WM traits. These results indicate that common genetic factors account for a prominent part of the phenotypic variation in WM performance. Hence, the application of GWAS on WM phenotypes is a valid method to identify the molecular underpinnings of WM. Nature Publishing Group 2014-09 2014-09-09 /pmc/articles/PMC4203010/ /pubmed/25203169 http://dx.doi.org/10.1038/tp.2014.81 Text en Copyright © 2014 Macmillan Publishers Limited http://creativecommons.org/licenses/by-nc-nd/3.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/ |
spellingShingle | Original Article Vogler, C Gschwind, L Coynel, D Freytag, V Milnik, A Egli, T Heck, A de Quervain, D J-F Papassotiropoulos, A Substantial SNP-based heritability estimates for working memory performance |
title | Substantial SNP-based heritability estimates for working memory performance |
title_full | Substantial SNP-based heritability estimates for working memory performance |
title_fullStr | Substantial SNP-based heritability estimates for working memory performance |
title_full_unstemmed | Substantial SNP-based heritability estimates for working memory performance |
title_short | Substantial SNP-based heritability estimates for working memory performance |
title_sort | substantial snp-based heritability estimates for working memory performance |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4203010/ https://www.ncbi.nlm.nih.gov/pubmed/25203169 http://dx.doi.org/10.1038/tp.2014.81 |
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