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Publication year
2016Author(s)
Number of pages
13 p.
Source
Human Brain Mapping, 37, 5, (2016), pp. 1788-1800ISSN
Publication type
Article / Letter to editor

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Organization
Neuroinformatics
Donders Centre for Neuroscience
Human Genetics
Psychiatry
Journal title
Human Brain Mapping
Volume
vol. 37
Issue
iss. 5
Languages used
English (eng)
Page start
p. 1788
Page end
p. 1800
Subject
Neuroinformatics; Radboudumc 7: Neurodevelopmental disorders DCMN: Donders Center for Medical NeuroscienceAbstract
Genome-wide association screens aim to identify common genetic variants contributing to the phenotypic variability of complex traits, such as human height or brain morphology. The identified genetic variants are mostly within noncoding genomic regions and the biology of the genotype-phenotype association typically remains unclear. In this article, we propose a complementary targeted strategy to reveal the genetic underpinnings of variability in subcortical brain volumes, by specifically selecting genomic loci that are experimentally validated forebrain enhancers, active in early embryonic development. We hypothesized that genetic variation within these enhancers may affect the development and ultimately the structure of subcortical brain regions in adults. We tested whether variants in forebrain enhancer regions showed an overall enrichment of association with volumetric variation in subcortical structures of >13,000 healthy adults. We observed significant enrichment of genomic loci that affect the volume of the hippocampus within forebrain enhancers (empirical P = 0.0015), a finding which robustly passed the adjusted threshold for testing of multiple brain phenotypes (cutoff of P < 0.0083 at an alpha of 0.05). In analyses of individual single nucleotide polymorphisms (SNPs), we identified an association upstream of the ID2 gene with rs7588305 and variation in hippocampal volume. This SNP-based association survived multiple-testing correction for the number of SNPs analyzed but not for the number of subcortical structures. Targeting known regulatory regions offers a way to understand the underlying biology that connects genotypes to phenotypes, particularly in the context of neuroimaging genetics. This biology-driven approach generates testable hypotheses regarding the functional biology of identified associations. Hum Brain Mapp 37:1788-1800, 2016. (c) 2016 Wiley Periodicals, Inc.
This item appears in the following Collection(s)
- Academic publications [203793]
- Electronic publications [102109]
- Faculty of Medical Sciences [80320]
- Faculty of Science [32109]
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