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000010472 0247_ $$2pmc$$apmc:PMC2891595
000010472 0247_ $$2DOI$$a10.1016/j.neuroimage.2009.12.028
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000010472 041__ $$aeng
000010472 082__ $$a610
000010472 084__ $$2WoS$$aNeurosciences
000010472 084__ $$2WoS$$aNeuroimaging
000010472 084__ $$2WoS$$aRadiology, Nuclear Medicine & Medical Imaging
000010472 1001_ $$0P:(DE-HGF)0$$aWinkler, A.M.$$b0
000010472 245__ $$aCortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies
000010472 260__ $$aOrlando, Fla.$$bAcademic Press$$c2010
000010472 300__ $$a1135 - 1146
000010472 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article
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000010472 3367_ $$2BibTeX$$aARTICLE
000010472 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000010472 3367_ $$2DRIVER$$aarticle
000010472 440_0 $$04545$$aNeuroImage$$v53$$x1053-8119$$y3
000010472 500__ $$aThe authors gratefully acknowledge Jack W. Kent Jr. for his invaluable support. The authors thank the Athinoula Martinos Center for Biomedical Imaging and the FMRIB Imaging Analysis Group for providing software used for the analyses. Financial support for this study was provided by NIMH grants MH0708143 (PI: D. C. Glahn), MH078111 (PI: J. Blangero) and MH083824 (PI: D. C. Glahn) and by the NIBIB grant EB006395 (P. Kochunov). SOLAR is supported by NIMH grant MH59490 (J. Blangero). None of the authors have financial interests to disclose.
000010472 520__ $$aChoosing 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.
000010472 536__ $$0G:(DE-Juel1)FUEK409$$2G:(DE-HGF)$$aFunktion und Dysfunktion des Nervensystems (FUEK409)$$cFUEK409$$x0
000010472 536__ $$0G:(DE-HGF)POF2-89571$$a89571 - Connectivity and Activity (POF2-89571)$$cPOF2-89571$$fPOF II T$$x1
000010472 588__ $$aDataset connected to Web of Science, Pubmed
000010472 65320 $$2Author$$aBrain cortical thickness
000010472 65320 $$2Author$$aBrain surface area
000010472 65320 $$2Author$$aHeritability
000010472 650_2 $$2MeSH$$aAdult
000010472 650_2 $$2MeSH$$aAged
000010472 650_2 $$2MeSH$$aAged, 80 and over
000010472 650_2 $$2MeSH$$aBrain: anatomy & histology
000010472 650_2 $$2MeSH$$aBrain Mapping: methods
000010472 650_2 $$2MeSH$$aFemale
000010472 650_2 $$2MeSH$$aHumans
000010472 650_2 $$2MeSH$$aImage Interpretation, Computer-Assisted
000010472 650_2 $$2MeSH$$aMagnetic Resonance Imaging
000010472 650_2 $$2MeSH$$aMale
000010472 650_2 $$2MeSH$$aMiddle Aged
000010472 650_2 $$2MeSH$$aPedigree
000010472 650_2 $$2MeSH$$aPhenotype
000010472 650_2 $$2MeSH$$aQuantitative Trait, Heritable
000010472 650_7 $$2WoSType$$aJ
000010472 7001_ $$0P:(DE-HGF)0$$aKochunov, P.$$b1
000010472 7001_ $$0P:(DE-HGF)0$$aBlangero, J.$$b2
000010472 7001_ $$0P:(DE-HGF)0$$aAlmasy, L.$$b3
000010472 7001_ $$0P:(DE-Juel1)131714$$aZilles, K.$$b4$$uFZJ
000010472 7001_ $$0P:(DE-HGF)0$$aFox, P.T.$$b5
000010472 7001_ $$0P:(DE-HGF)0$$aDuggirala, R.$$b6
000010472 7001_ $$0P:(DE-HGF)0$$aGlahn, D.C.$$b7
000010472 773__ $$0PERI:(DE-600)1471418-8$$a10.1016/j.neuroimage.2009.12.028$$gVol. 53, p. 1135 - 1146$$p1135 - 1146$$q53<1135 - 1146$$tNeuroImage$$v53$$x1053-8119$$y2010
000010472 8567_ $$2Pubmed Central$$uhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC2891595
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000010472 915__ $$0StatID:(DE-HGF)0010$$aJCR/ISI refereed
000010472 9141_ $$y2010
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