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Bivariate Genome-Wide Association Study of Genetically Correlated Neuroimaging Phenotypes from DTI and MRI through a Seemingly Unrelated Regression Model

  • Neda Jahanshad
  • Priya Bhatt
  • Derrek P. Hibar
  • Julio E. Villalon
  • Talia M. Nir
  • Arthur W. Toga
  • Clifford R. JackJr.
  • Matt A. Bernstein
  • Michael W. Weiner
  • Katie L. McMahon
  • Greig I. de Zubicaray
  • Nicholas G. Martin
  • Margaret J. Wright
  • Paul M. Thompson
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8159)

Abstract

Large multisite efforts (e.g., the ENIGMA Consortium), have shown that neuroimaging traits including tract integrity (from DTI fractional anisotropy, FA) and subcortical volumes (from T1-weighted scans) are highly heritable and promising phenotypes for discovering genetic variants associated with brain structure. However, genetic correlations (r g) among measures from these different modalities for mapping the human genome to the brain remain unknown. Discovering these correlations can help map genetic and neuroanatomical pathways implicated in development and inherited risk for disease. We use structural equation models and a twin design to find r g between pairs of phenotypes extracted from DTI and MRI scans. When controlling for intracranial volume, the caudate as well as related measures from the limbic system - hippocampal volume - showed high r g with the cingulum FA. Using an unrelated sample and a Seemingly Unrelated Regression model for bivariate analysis of this connection, we show that a multivariate GWAS approach may be more promising for genetic discovery than a univariate approach applied to each trait separately.

Keywords

Neuroimaging genetics brain connectivity bivariate analysis GWAS genetic correlation 

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Neda Jahanshad
    • 1
  • Priya Bhatt
    • 1
  • Derrek P. Hibar
    • 1
  • Julio E. Villalon
    • 1
  • Talia M. Nir
    • 1
  • Arthur W. Toga
    • 1
  • Clifford R. JackJr.
    • 2
  • Matt A. Bernstein
    • 2
  • Michael W. Weiner
    • 3
    • 4
  • Katie L. McMahon
    • 5
  • Greig I. de Zubicaray
    • 6
  • Nicholas G. Martin
    • 7
  • Margaret J. Wright
    • 7
  • Paul M. Thompson
    • 1
  1. 1.Imaging Genetics Center, Laboratory of Neuro Imaging, Department of NeurologyUCLA School of MedicineLos AngelesUSA
  2. 2.Department of RadiologyMayo ClinicRochesterUSA
  3. 3.Department of Radiology, Medicine, and PsychiatryUC San FranciscoUSA
  4. 4.Department of Veterans Affairs Medical CenterSan FranciscoUSA
  5. 5.Centre for Advanced ImagingUniversity of QueenslandBrisbaneAustralia
  6. 6.School of PsychologyUniversity of QueenslandBrisbaneAustralia
  7. 7.Queensland Institute of Medical ResearchBrisbaneAustralia

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