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@ARTICLE{Winkler:10472,
      author       = {Winkler, A.M. and Kochunov, P. and Blangero, J. and Almasy,
                      L. and Zilles, K. and Fox, P.T. and Duggirala, R. and Glahn,
                      D.C.},
      title        = {{C}ortical thickness or grey matter volume? {T}he
                      importance of selecting the phenotype for imaging genetics
                      studies},
      journal      = {NeuroImage},
      volume       = {53},
      issn         = {1053-8119},
      address      = {Orlando, Fla.},
      publisher    = {Academic Press},
      reportid     = {PreJuSER-10472},
      pages        = {1135 - 1146},
      year         = {2010},
      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.},
      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.},
      keywords     = {Adult / Aged / Aged, 80 and over / Brain: anatomy $\&$
                      histology / Brain Mapping: methods / Female / Humans / Image
                      Interpretation, Computer-Assisted / Magnetic Resonance
                      Imaging / Male / Middle Aged / Pedigree / Phenotype /
                      Quantitative Trait, Heritable / J (WoSType)},
      cin          = {INM-2 / JARA-BRAIN},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-2-20090406 / $I:(DE-82)080010_20140620$},
      pnm          = {Funktion und Dysfunktion des Nervensystems (FUEK409) /
                      89571 - Connectivity and Activity (POF2-89571)},
      pid          = {G:(DE-Juel1)FUEK409 / G:(DE-HGF)POF2-89571},
      shelfmark    = {Neurosciences / Neuroimaging / Radiology, Nuclear Medicine
                      $\&$ Medical Imaging},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:20006715},
      pmc          = {pmc:PMC2891595},
      UT           = {WOS:000282039300040},
      doi          = {10.1016/j.neuroimage.2009.12.028},
      url          = {https://juser.fz-juelich.de/record/10472},
}