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Novel directions for G × E analysis in psychiatry

G × E in psychiatry may explain why environmental risk factors have big impact in some individuals but not in others, and conversely why relatives that are genetically at risk for disease do not all develop disease. Here we discuss two novel methods that use an aggregate genome-wide measure of genet...

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Detalles Bibliográficos
Autores principales: Vinkhuyzen, A. A. E., Wray, N. R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4411743/
https://www.ncbi.nlm.nih.gov/pubmed/25295644
http://dx.doi.org/10.1017/S2045796014000584
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author Vinkhuyzen, A. A. E.
Wray, N. R.
author_facet Vinkhuyzen, A. A. E.
Wray, N. R.
author_sort Vinkhuyzen, A. A. E.
collection PubMed
description G × E in psychiatry may explain why environmental risk factors have big impact in some individuals but not in others, and conversely why relatives that are genetically at risk for disease do not all develop disease. Here we discuss two novel methods that use an aggregate genome-wide measure of genetic risk to detect G × E and estimate its effect in the population using data currently available and data we anticipate will be available in the near future. The first method exploits summary statistics from large-scale genome-wide association studies ignorant of the environmental conditions and detects G × E in an out-of-sample risk-profiling framework. The second method relies on larger samples and is based on a mixed linear model framework. It estimates variance explained directly from single nucleotide polymorphisms and environmental measures. Both methods have great potential to improve public health interventions focusing on risk-based screening that is informed by both genetic and environmental risk factors.
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spelling pubmed-44117432015-05-01 Novel directions for G × E analysis in psychiatry Vinkhuyzen, A. A. E. Wray, N. R. Epidemiol Psychiatr Sci Editorials G × E in psychiatry may explain why environmental risk factors have big impact in some individuals but not in others, and conversely why relatives that are genetically at risk for disease do not all develop disease. Here we discuss two novel methods that use an aggregate genome-wide measure of genetic risk to detect G × E and estimate its effect in the population using data currently available and data we anticipate will be available in the near future. The first method exploits summary statistics from large-scale genome-wide association studies ignorant of the environmental conditions and detects G × E in an out-of-sample risk-profiling framework. The second method relies on larger samples and is based on a mixed linear model framework. It estimates variance explained directly from single nucleotide polymorphisms and environmental measures. Both methods have great potential to improve public health interventions focusing on risk-based screening that is informed by both genetic and environmental risk factors. Cambridge University Press 2014-10-08 /pmc/articles/PMC4411743/ /pubmed/25295644 http://dx.doi.org/10.1017/S2045796014000584 Text en © Cambridge University Press 2014 This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Editorials
Vinkhuyzen, A. A. E.
Wray, N. R.
Novel directions for G × E analysis in psychiatry
title Novel directions for G × E analysis in psychiatry
title_full Novel directions for G × E analysis in psychiatry
title_fullStr Novel directions for G × E analysis in psychiatry
title_full_unstemmed Novel directions for G × E analysis in psychiatry
title_short Novel directions for G × E analysis in psychiatry
title_sort novel directions for g × e analysis in psychiatry
topic Editorials
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4411743/
https://www.ncbi.nlm.nih.gov/pubmed/25295644
http://dx.doi.org/10.1017/S2045796014000584
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