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The genetic relationships between brain structure and schizophrenia

Genetic risks for schizophrenia are theoretically mediated by genetic effects on brain structure but it has been unclear which genes are associated with both schizophrenia and cortical phenotypes. We accessed genome-wide association studies (GWAS) of schizophrenia (N = 69,369 cases; 236,642 controls...

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Autores principales: Stauffer, Eva-Maria, Bethlehem, Richard A. I., Dorfschmidt, Lena, Won, Hyejung, Warrier, Varun, Bullmore, Edward T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10684873/
https://www.ncbi.nlm.nih.gov/pubmed/38016951
http://dx.doi.org/10.1038/s41467-023-43567-7
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author Stauffer, Eva-Maria
Bethlehem, Richard A. I.
Dorfschmidt, Lena
Won, Hyejung
Warrier, Varun
Bullmore, Edward T.
author_facet Stauffer, Eva-Maria
Bethlehem, Richard A. I.
Dorfschmidt, Lena
Won, Hyejung
Warrier, Varun
Bullmore, Edward T.
author_sort Stauffer, Eva-Maria
collection PubMed
description Genetic risks for schizophrenia are theoretically mediated by genetic effects on brain structure but it has been unclear which genes are associated with both schizophrenia and cortical phenotypes. We accessed genome-wide association studies (GWAS) of schizophrenia (N = 69,369 cases; 236,642 controls), and of three magnetic resonance imaging (MRI) metrics (surface area, cortical thickness, neurite density index) measured at 180 cortical areas (N = 36,843, UK Biobank). Using Hi-C-coupled MAGMA, 61 genes were significantly associated with both schizophrenia and one or more MRI metrics. Whole genome analysis with partial least squares demonstrated significant genetic covariation between schizophrenia and area or thickness of most cortical regions. Genetic similarity between cortical areas was strongly coupled to their phenotypic covariance, and genetic covariation between schizophrenia and brain phenotypes was strongest in the hubs of structural covariance networks. Pleiotropically associated genes were enriched for neurodevelopmental processes and positionally concentrated in chromosomes 3p21, 17q21 and 11p11. Mendelian randomization analysis indicated that genetically determined variation in a posterior cingulate cortical area could be causal for schizophrenia. Parallel analyses of GWAS on bipolar disorder, Alzheimer’s disease and height showed that pleiotropic association with MRI metrics was stronger for schizophrenia compared to other disorders.
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spelling pubmed-106848732023-11-30 The genetic relationships between brain structure and schizophrenia Stauffer, Eva-Maria Bethlehem, Richard A. I. Dorfschmidt, Lena Won, Hyejung Warrier, Varun Bullmore, Edward T. Nat Commun Article Genetic risks for schizophrenia are theoretically mediated by genetic effects on brain structure but it has been unclear which genes are associated with both schizophrenia and cortical phenotypes. We accessed genome-wide association studies (GWAS) of schizophrenia (N = 69,369 cases; 236,642 controls), and of three magnetic resonance imaging (MRI) metrics (surface area, cortical thickness, neurite density index) measured at 180 cortical areas (N = 36,843, UK Biobank). Using Hi-C-coupled MAGMA, 61 genes were significantly associated with both schizophrenia and one or more MRI metrics. Whole genome analysis with partial least squares demonstrated significant genetic covariation between schizophrenia and area or thickness of most cortical regions. Genetic similarity between cortical areas was strongly coupled to their phenotypic covariance, and genetic covariation between schizophrenia and brain phenotypes was strongest in the hubs of structural covariance networks. Pleiotropically associated genes were enriched for neurodevelopmental processes and positionally concentrated in chromosomes 3p21, 17q21 and 11p11. Mendelian randomization analysis indicated that genetically determined variation in a posterior cingulate cortical area could be causal for schizophrenia. Parallel analyses of GWAS on bipolar disorder, Alzheimer’s disease and height showed that pleiotropic association with MRI metrics was stronger for schizophrenia compared to other disorders. Nature Publishing Group UK 2023-11-28 /pmc/articles/PMC10684873/ /pubmed/38016951 http://dx.doi.org/10.1038/s41467-023-43567-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Stauffer, Eva-Maria
Bethlehem, Richard A. I.
Dorfschmidt, Lena
Won, Hyejung
Warrier, Varun
Bullmore, Edward T.
The genetic relationships between brain structure and schizophrenia
title The genetic relationships between brain structure and schizophrenia
title_full The genetic relationships between brain structure and schizophrenia
title_fullStr The genetic relationships between brain structure and schizophrenia
title_full_unstemmed The genetic relationships between brain structure and schizophrenia
title_short The genetic relationships between brain structure and schizophrenia
title_sort genetic relationships between brain structure and schizophrenia
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10684873/
https://www.ncbi.nlm.nih.gov/pubmed/38016951
http://dx.doi.org/10.1038/s41467-023-43567-7
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