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Mapping the Genetic Variation of Regional Brain Volumes as Explained by All Common SNPs from the ADNI Study
Typically twin studies are used to investigate the aggregate effects of genetic and environmental influences on brain phenotypic measures. Although some phenotypic measures are highly heritable in twin studies, SNPs (single nucleotide polymorphisms) identified by genome-wide association studies (GWA...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3756017/ https://www.ncbi.nlm.nih.gov/pubmed/24015190 http://dx.doi.org/10.1371/journal.pone.0071723 |
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author | Bryant, Christopher Giovanello, Kelly S. Ibrahim, Joseph G. Chang, Jing Shen, Dinggang Peterson, Bradley S. Zhu, Hongtu |
author_facet | Bryant, Christopher Giovanello, Kelly S. Ibrahim, Joseph G. Chang, Jing Shen, Dinggang Peterson, Bradley S. Zhu, Hongtu |
author_sort | Bryant, Christopher |
collection | PubMed |
description | Typically twin studies are used to investigate the aggregate effects of genetic and environmental influences on brain phenotypic measures. Although some phenotypic measures are highly heritable in twin studies, SNPs (single nucleotide polymorphisms) identified by genome-wide association studies (GWAS) account for only a small fraction of the heritability of these measures. We mapped the genetic variation (the proportion of phenotypic variance explained by variation among SNPs) of volumes of pre-defined regions across the whole brain, as explained by 512,905 SNPs genotyped on 747 adult participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We found that 85% of the variance of intracranial volume (ICV) (p = 0.04) was explained by considering all SNPs simultaneously, and after adjusting for ICV, total grey matter (GM) and white matter (WM) volumes had genetic variation estimates near zero (p = 0.5). We found varying estimates of genetic variation across 93 non-overlapping regions, with asymmetry in estimates between the left and right cerebral hemispheres. Several regions reported in previous studies to be related to Alzheimer's disease progression were estimated to have a large proportion of volumetric variance explained by the SNPs. |
format | Online Article Text |
id | pubmed-3756017 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-37560172013-09-06 Mapping the Genetic Variation of Regional Brain Volumes as Explained by All Common SNPs from the ADNI Study Bryant, Christopher Giovanello, Kelly S. Ibrahim, Joseph G. Chang, Jing Shen, Dinggang Peterson, Bradley S. Zhu, Hongtu PLoS One Research Article Typically twin studies are used to investigate the aggregate effects of genetic and environmental influences on brain phenotypic measures. Although some phenotypic measures are highly heritable in twin studies, SNPs (single nucleotide polymorphisms) identified by genome-wide association studies (GWAS) account for only a small fraction of the heritability of these measures. We mapped the genetic variation (the proportion of phenotypic variance explained by variation among SNPs) of volumes of pre-defined regions across the whole brain, as explained by 512,905 SNPs genotyped on 747 adult participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We found that 85% of the variance of intracranial volume (ICV) (p = 0.04) was explained by considering all SNPs simultaneously, and after adjusting for ICV, total grey matter (GM) and white matter (WM) volumes had genetic variation estimates near zero (p = 0.5). We found varying estimates of genetic variation across 93 non-overlapping regions, with asymmetry in estimates between the left and right cerebral hemispheres. Several regions reported in previous studies to be related to Alzheimer's disease progression were estimated to have a large proportion of volumetric variance explained by the SNPs. Public Library of Science 2013-08-28 /pmc/articles/PMC3756017/ /pubmed/24015190 http://dx.doi.org/10.1371/journal.pone.0071723 Text en © 2013 Bryant et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Bryant, Christopher Giovanello, Kelly S. Ibrahim, Joseph G. Chang, Jing Shen, Dinggang Peterson, Bradley S. Zhu, Hongtu Mapping the Genetic Variation of Regional Brain Volumes as Explained by All Common SNPs from the ADNI Study |
title | Mapping the Genetic Variation of Regional Brain Volumes as Explained by All Common SNPs from the ADNI Study |
title_full | Mapping the Genetic Variation of Regional Brain Volumes as Explained by All Common SNPs from the ADNI Study |
title_fullStr | Mapping the Genetic Variation of Regional Brain Volumes as Explained by All Common SNPs from the ADNI Study |
title_full_unstemmed | Mapping the Genetic Variation of Regional Brain Volumes as Explained by All Common SNPs from the ADNI Study |
title_short | Mapping the Genetic Variation of Regional Brain Volumes as Explained by All Common SNPs from the ADNI Study |
title_sort | mapping the genetic variation of regional brain volumes as explained by all common snps from the adni study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3756017/ https://www.ncbi.nlm.nih.gov/pubmed/24015190 http://dx.doi.org/10.1371/journal.pone.0071723 |
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