Journal Article

PreJuSER-10472

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies

Winkler, A. M. ; Kochunov, P. ; Blangero, J. ; Almasy, L. ; Zilles, K.FZJ* ; Fox, P. T. ; Duggirala, R. ; Glahn, D. C.

2010
Academic Press Orlando, Fla.

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Please use a persistent id in citations: doi:10.1016/j.neuroimage.2009.12.028

Abstract: Choosing the appropriate neuroimaging phenotype is critical to successfully identify genes that influence brain structure or function. While neuroimaging methods provide numerous potential phenotypes, their role for imaging genetics studies is unclear. Here we examine the relationship between brain volume, grey matter volume, cortical thickness and surface area, from a genetic standpoint. Four hundred and eighty-six individuals from randomly ascertained extended pedigrees with high-quality T1-weighted neuroanatomic MRI images participated in the study. Surface-based and voxel-based representations of brain structure were derived, using automated methods, and these measurements were analysed using a variance-components method to identify the heritability of these traits and their genetic correlations. All neuroanatomic traits were significantly influenced by genetic factors. Cortical thickness and surface area measurements were found to be genetically and phenotypically independent. While both thickness and area influenced volume measurements of cortical grey matter, volume was more closely related to surface area than cortical thickness. This trend was observed for both the volume-based and surface-based techniques. The results suggest that surface area and cortical thickness measurements should be considered separately and preferred over gray matter volumes for imaging genetic studies.

Keyword(s): Adult (MeSH) ; Aged (MeSH) ; Aged, 80 and over (MeSH) ; Brain: anatomy & histology (MeSH) ; Brain Mapping: methods (MeSH) ; Female (MeSH) ; Humans (MeSH) ; Image Interpretation, Computer-Assisted (MeSH) ; Magnetic Resonance Imaging (MeSH) ; Male (MeSH) ; Middle Aged (MeSH) ; Pedigree (MeSH) ; Phenotype (MeSH) ; Quantitative Trait, Heritable (MeSH) ; J ; Brain cortical thickness (auto) ; Brain surface area (auto) ; Heritability (auto)

Note: The authors gratefully acknowledge Jack W. Kent Jr. for his invaluable support. The authors thank the Athinoula Martinos Center for Biomedical Imaging and the FMRIB Imaging Analysis Group for providing software used for the analyses. Financial support for this study was provided by NIMH grants MH0708143 (PI: D. C. Glahn), MH078111 (PI: J. Blangero) and MH083824 (PI: D. C. Glahn) and by the NIBIB grant EB006395 (P. Kochunov). SOLAR is supported by NIMH grant MH59490 (J. Blangero). None of the authors have financial interests to disclose.

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Contributing Institute(s):

1. Molekulare Organisation des Gehirns (INM-2)
2. Jülich-Aachen Research Alliance - Translational Brain Medicine (JARA-BRAIN)

Research Program(s):

1. Funktion und Dysfunktion des Nervensystems (FUEK409) (FUEK409)
2. 89571 - Connectivity and Activity (POF2-89571) (POF2-89571)

Appears in the scientific report 2010

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