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001     10472
005     20210129210522.0
024 7 _ |2 pmid
|a pmid:20006715
024 7 _ |2 pmc
|a pmc:PMC2891595
024 7 _ |2 DOI
|a 10.1016/j.neuroimage.2009.12.028
024 7 _ |2 WOS
|a WOS:000282039300040
024 7 _ |a altmetric:1859851
|2 altmetric
037 _ _ |a PreJuSER-10472
041 _ _ |a eng
082 _ _ |a 610
084 _ _ |2 WoS
|a Neurosciences
084 _ _ |2 WoS
|a Neuroimaging
084 _ _ |2 WoS
|a Radiology, Nuclear Medicine & Medical Imaging
100 1 _ |0 P:(DE-HGF)0
|a Winkler, A.M.
|b 0
245 _ _ |a Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies
260 _ _ |a Orlando, Fla.
|b Academic Press
|c 2010
300 _ _ |a 1135 - 1146
336 7 _ |a Journal Article
|0 PUB:(DE-HGF)16
|2 PUB:(DE-HGF)
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|0 0
|2 EndNote
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a article
|2 DRIVER
440 _ 0 |0 4545
|a NeuroImage
|v 53
|x 1053-8119
|y 3
500 _ _ |a 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.
520 _ _ |a 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.
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|a Funktion und Dysfunktion des Nervensystems (FUEK409)
536 _ _ |0 G:(DE-HGF)POF2-89571
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588 _ _ |a Dataset connected to Web of Science, Pubmed
650 _ 2 |2 MeSH
|a Adult
650 _ 2 |2 MeSH
|a Aged
650 _ 2 |2 MeSH
|a Aged, 80 and over
650 _ 2 |2 MeSH
|a Brain: anatomy & histology
650 _ 2 |2 MeSH
|a Brain Mapping: methods
650 _ 2 |2 MeSH
|a Female
650 _ 2 |2 MeSH
|a Humans
650 _ 2 |2 MeSH
|a Image Interpretation, Computer-Assisted
650 _ 2 |2 MeSH
|a Magnetic Resonance Imaging
650 _ 2 |2 MeSH
|a Male
650 _ 2 |2 MeSH
|a Middle Aged
650 _ 2 |2 MeSH
|a Pedigree
650 _ 2 |2 MeSH
|a Phenotype
650 _ 2 |2 MeSH
|a Quantitative Trait, Heritable
650 _ 7 |2 WoSType
|a J
653 2 0 |2 Author
|a Brain cortical thickness
653 2 0 |2 Author
|a Brain surface area
653 2 0 |2 Author
|a Heritability
700 1 _ |0 P:(DE-HGF)0
|a Kochunov, P.
|b 1
700 1 _ |0 P:(DE-HGF)0
|a Blangero, J.
|b 2
700 1 _ |0 P:(DE-HGF)0
|a Almasy, L.
|b 3
700 1 _ |0 P:(DE-Juel1)131714
|a Zilles, K.
|b 4
|u FZJ
700 1 _ |0 P:(DE-HGF)0
|a Fox, P.T.
|b 5
700 1 _ |0 P:(DE-HGF)0
|a Duggirala, R.
|b 6
700 1 _ |0 P:(DE-HGF)0
|a Glahn, D.C.
|b 7
773 _ _ |0 PERI:(DE-600)1471418-8
|a 10.1016/j.neuroimage.2009.12.028
|g Vol. 53, p. 1135 - 1146
|p 1135 - 1146
|q 53<1135 - 1146
|t NeuroImage
|v 53
|x 1053-8119
|y 2010
856 7 _ |2 Pubmed Central
|u http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2891595
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