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      Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies

      , , , , , , ,
      NeuroImage
      Elsevier BV

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          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. Copyright 2009 Elsevier Inc. All rights reserved.

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          Author and article information

          Journal
          NeuroImage
          NeuroImage
          Elsevier BV
          10538119
          November 2010
          November 2010
          : 53
          : 3
          : 1135-1146
          Article
          10.1016/j.neuroimage.2009.12.028
          2891595
          20006715
          447b5acf-6fe9-40e5-91b2-3297c259fd78
          © 2010

          https://www.elsevier.com/tdm/userlicense/1.0/

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