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Multidimensional heritability analysis of neuroanatomical shape
In the dawning era of large-scale biomedical data, multidimensional phenotype vectors will play an increasing role in examining the genetic underpinnings of brain features, behaviour and disease. For example, shape measurements derived from brain MRI scans are multidimensional geometric descriptions...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5116071/ https://www.ncbi.nlm.nih.gov/pubmed/27845344 http://dx.doi.org/10.1038/ncomms13291 |
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author | Ge, Tian Reuter, Martin Winkler, Anderson M. Holmes, Avram J. Lee, Phil H. Tirrell, Lee S. Roffman, Joshua L. Buckner, Randy L. Smoller, Jordan W. Sabuncu, Mert R. |
author_facet | Ge, Tian Reuter, Martin Winkler, Anderson M. Holmes, Avram J. Lee, Phil H. Tirrell, Lee S. Roffman, Joshua L. Buckner, Randy L. Smoller, Jordan W. Sabuncu, Mert R. |
author_sort | Ge, Tian |
collection | PubMed |
description | In the dawning era of large-scale biomedical data, multidimensional phenotype vectors will play an increasing role in examining the genetic underpinnings of brain features, behaviour and disease. For example, shape measurements derived from brain MRI scans are multidimensional geometric descriptions of brain structure and provide an alternate class of phenotypes that remains largely unexplored in genetic studies. Here we extend the concept of heritability to multidimensional traits, and present the first comprehensive analysis of the heritability of neuroanatomical shape measurements across an ensemble of brain structures based on genome-wide SNP and MRI data from 1,320 unrelated, young and healthy individuals. We replicate our findings in an extended twin sample from the Human Connectome Project (HCP). Our results demonstrate that neuroanatomical shape can be significantly heritable, above and beyond volume, and can serve as a complementary phenotype to study the genetic determinants and clinical relevance of brain structure. |
format | Online Article Text |
id | pubmed-5116071 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-51160712017-01-13 Multidimensional heritability analysis of neuroanatomical shape Ge, Tian Reuter, Martin Winkler, Anderson M. Holmes, Avram J. Lee, Phil H. Tirrell, Lee S. Roffman, Joshua L. Buckner, Randy L. Smoller, Jordan W. Sabuncu, Mert R. Nat Commun Article In the dawning era of large-scale biomedical data, multidimensional phenotype vectors will play an increasing role in examining the genetic underpinnings of brain features, behaviour and disease. For example, shape measurements derived from brain MRI scans are multidimensional geometric descriptions of brain structure and provide an alternate class of phenotypes that remains largely unexplored in genetic studies. Here we extend the concept of heritability to multidimensional traits, and present the first comprehensive analysis of the heritability of neuroanatomical shape measurements across an ensemble of brain structures based on genome-wide SNP and MRI data from 1,320 unrelated, young and healthy individuals. We replicate our findings in an extended twin sample from the Human Connectome Project (HCP). Our results demonstrate that neuroanatomical shape can be significantly heritable, above and beyond volume, and can serve as a complementary phenotype to study the genetic determinants and clinical relevance of brain structure. Nature Publishing Group 2016-11-15 /pmc/articles/PMC5116071/ /pubmed/27845344 http://dx.doi.org/10.1038/ncomms13291 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International 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/4.0/ |
spellingShingle | Article Ge, Tian Reuter, Martin Winkler, Anderson M. Holmes, Avram J. Lee, Phil H. Tirrell, Lee S. Roffman, Joshua L. Buckner, Randy L. Smoller, Jordan W. Sabuncu, Mert R. Multidimensional heritability analysis of neuroanatomical shape |
title | Multidimensional heritability analysis of neuroanatomical shape |
title_full | Multidimensional heritability analysis of neuroanatomical shape |
title_fullStr | Multidimensional heritability analysis of neuroanatomical shape |
title_full_unstemmed | Multidimensional heritability analysis of neuroanatomical shape |
title_short | Multidimensional heritability analysis of neuroanatomical shape |
title_sort | multidimensional heritability analysis of neuroanatomical shape |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5116071/ https://www.ncbi.nlm.nih.gov/pubmed/27845344 http://dx.doi.org/10.1038/ncomms13291 |
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