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Mapping the genetic architecture of cortical morphology through neuroimaging: progress and perspectives
Cortical morphology is a key determinant of cognitive ability and mental health. Its development is a highly intricate process spanning decades, involving the coordinated, localized expression of thousands of genes. We are now beginning to unravel the genetic architecture of cortical morphology, tha...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9568576/ https://www.ncbi.nlm.nih.gov/pubmed/36241627 http://dx.doi.org/10.1038/s41398-022-02193-5 |
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author | van der Meer, Dennis Kaufmann, Tobias |
author_facet | van der Meer, Dennis Kaufmann, Tobias |
author_sort | van der Meer, Dennis |
collection | PubMed |
description | Cortical morphology is a key determinant of cognitive ability and mental health. Its development is a highly intricate process spanning decades, involving the coordinated, localized expression of thousands of genes. We are now beginning to unravel the genetic architecture of cortical morphology, thanks to the recent availability of large-scale neuroimaging and genomic data and the development of powerful biostatistical tools. Here, we review the progress made in this field, providing an overview of the lessons learned from genetic studies of cortical volume, thickness, surface area, and folding as captured by neuroimaging. It is now clear that morphology is shaped by thousands of genetic variants, with effects that are region- and time-dependent, thereby challenging conventional study approaches. The most recent genome-wide association studies have started discovering common genetic variants influencing cortical thickness and surface area, yet together these explain only a fraction of the high heritability of these measures. Further, the impact of rare variants and non-additive effects remains elusive. There are indications that the quickly increasing availability of data from whole-genome sequencing and large, deeply phenotyped population cohorts across the lifespan will enable us to uncover much of the missing heritability in the upcoming years. Novel approaches leveraging shared information across measures will accelerate this process by providing substantial increases in statistical power, together with more accurate mapping of genetic relationships. Important challenges remain, including better representation of understudied demographic groups, integration of other ‘omics data, and mapping of effects from gene to brain to behavior across the lifespan. |
format | Online Article Text |
id | pubmed-9568576 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-95685762022-10-16 Mapping the genetic architecture of cortical morphology through neuroimaging: progress and perspectives van der Meer, Dennis Kaufmann, Tobias Transl Psychiatry Expert Review Cortical morphology is a key determinant of cognitive ability and mental health. Its development is a highly intricate process spanning decades, involving the coordinated, localized expression of thousands of genes. We are now beginning to unravel the genetic architecture of cortical morphology, thanks to the recent availability of large-scale neuroimaging and genomic data and the development of powerful biostatistical tools. Here, we review the progress made in this field, providing an overview of the lessons learned from genetic studies of cortical volume, thickness, surface area, and folding as captured by neuroimaging. It is now clear that morphology is shaped by thousands of genetic variants, with effects that are region- and time-dependent, thereby challenging conventional study approaches. The most recent genome-wide association studies have started discovering common genetic variants influencing cortical thickness and surface area, yet together these explain only a fraction of the high heritability of these measures. Further, the impact of rare variants and non-additive effects remains elusive. There are indications that the quickly increasing availability of data from whole-genome sequencing and large, deeply phenotyped population cohorts across the lifespan will enable us to uncover much of the missing heritability in the upcoming years. Novel approaches leveraging shared information across measures will accelerate this process by providing substantial increases in statistical power, together with more accurate mapping of genetic relationships. Important challenges remain, including better representation of understudied demographic groups, integration of other ‘omics data, and mapping of effects from gene to brain to behavior across the lifespan. Nature Publishing Group UK 2022-10-14 /pmc/articles/PMC9568576/ /pubmed/36241627 http://dx.doi.org/10.1038/s41398-022-02193-5 Text en © The Author(s) 2022 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Expert Review van der Meer, Dennis Kaufmann, Tobias Mapping the genetic architecture of cortical morphology through neuroimaging: progress and perspectives |
title | Mapping the genetic architecture of cortical morphology through neuroimaging: progress and perspectives |
title_full | Mapping the genetic architecture of cortical morphology through neuroimaging: progress and perspectives |
title_fullStr | Mapping the genetic architecture of cortical morphology through neuroimaging: progress and perspectives |
title_full_unstemmed | Mapping the genetic architecture of cortical morphology through neuroimaging: progress and perspectives |
title_short | Mapping the genetic architecture of cortical morphology through neuroimaging: progress and perspectives |
title_sort | mapping the genetic architecture of cortical morphology through neuroimaging: progress and perspectives |
topic | Expert Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9568576/ https://www.ncbi.nlm.nih.gov/pubmed/36241627 http://dx.doi.org/10.1038/s41398-022-02193-5 |
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