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Functional neuroimaging and schizophrenia: a view towards effective connectivity modeling and polygenic risk
We review critical trends in imaging genetics as applied to schizophrenia research, and then discuss some future directions of the field. A plethora of imaging genetics studies have investigated the impact of genetic variation on brain function, since the paradigm of a neuroimaging intermediate phen...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Les Laboratoires Servier
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3811100/ https://www.ncbi.nlm.nih.gov/pubmed/24174900 |
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author | Birnbaum, Rebecca Weinberger, Daniel R. |
author_facet | Birnbaum, Rebecca Weinberger, Daniel R. |
author_sort | Birnbaum, Rebecca |
collection | PubMed |
description | We review critical trends in imaging genetics as applied to schizophrenia research, and then discuss some future directions of the field. A plethora of imaging genetics studies have investigated the impact of genetic variation on brain function, since the paradigm of a neuroimaging intermediate phenotype for schizophrenia first emerged. It was initially posited that the effects of schizophrenia susceptibility genes would be more penetrant at the level of biologically based neuroimaging intermediate phenotypes than at the level of a complex and phenotypically heterogeneous psychiatric syndrome. The results of many studies support this assumption, most of which show single genetic variants to be associated with changes in activity of localized brain regions, as determined by select cognitive controlled tasks. From these basic studies, functional neuroimaging analysis of intermediate phenotypes has progressed to more complex and realistic models of brain dysfunction, incorporating models of functional and effective connectivity, including the modalities of psycho-physiological interaction, dynamic causal modeling, and graph theory metrics. The genetic association approaches applied to imaging genetics have also progressed to more sophisticated multivariate effects, including incorporation of two-way and three-way epistatic interactions, and most recently polygenic risk models. Imaging genetics is a unique and powerful strategy for understanding the neural mechanisms of genetic risk for complex CNS disorders at the human brain level. |
format | Online Article Text |
id | pubmed-3811100 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Les Laboratoires Servier |
record_format | MEDLINE/PubMed |
spelling | pubmed-38111002013-10-30 Functional neuroimaging and schizophrenia: a view towards effective connectivity modeling and polygenic risk Birnbaum, Rebecca Weinberger, Daniel R. Dialogues Clin Neurosci Translational Research We review critical trends in imaging genetics as applied to schizophrenia research, and then discuss some future directions of the field. A plethora of imaging genetics studies have investigated the impact of genetic variation on brain function, since the paradigm of a neuroimaging intermediate phenotype for schizophrenia first emerged. It was initially posited that the effects of schizophrenia susceptibility genes would be more penetrant at the level of biologically based neuroimaging intermediate phenotypes than at the level of a complex and phenotypically heterogeneous psychiatric syndrome. The results of many studies support this assumption, most of which show single genetic variants to be associated with changes in activity of localized brain regions, as determined by select cognitive controlled tasks. From these basic studies, functional neuroimaging analysis of intermediate phenotypes has progressed to more complex and realistic models of brain dysfunction, incorporating models of functional and effective connectivity, including the modalities of psycho-physiological interaction, dynamic causal modeling, and graph theory metrics. The genetic association approaches applied to imaging genetics have also progressed to more sophisticated multivariate effects, including incorporation of two-way and three-way epistatic interactions, and most recently polygenic risk models. Imaging genetics is a unique and powerful strategy for understanding the neural mechanisms of genetic risk for complex CNS disorders at the human brain level. Les Laboratoires Servier 2013-09 /pmc/articles/PMC3811100/ /pubmed/24174900 Text en Copyright: © 2013 Institut la Conférence Hippocrate - Servier Research Group http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc-nd/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Translational Research Birnbaum, Rebecca Weinberger, Daniel R. Functional neuroimaging and schizophrenia: a view towards effective connectivity modeling and polygenic risk |
title | Functional neuroimaging and schizophrenia: a view towards effective connectivity modeling and polygenic risk |
title_full | Functional neuroimaging and schizophrenia: a view towards effective connectivity modeling and polygenic risk |
title_fullStr | Functional neuroimaging and schizophrenia: a view towards effective connectivity modeling and polygenic risk |
title_full_unstemmed | Functional neuroimaging and schizophrenia: a view towards effective connectivity modeling and polygenic risk |
title_short | Functional neuroimaging and schizophrenia: a view towards effective connectivity modeling and polygenic risk |
title_sort | functional neuroimaging and schizophrenia: a view towards effective connectivity modeling and polygenic risk |
topic | Translational Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3811100/ https://www.ncbi.nlm.nih.gov/pubmed/24174900 |
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