A genetic analysis of cortical thickness in 372 twins

Joshi, Anand A., Lepore, Natasha, Joshi, Shantanu, Lee, Agatha D., Barysheva, Marina, de Zubicaray, Greig I., Wright, Margaret J., McMahon, Katie L., Toga, Arthur W. and Thompson, Paul M. (2010). A genetic analysis of cortical thickness in 372 twins. In: , 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro. IEEE International Symposium on Biomedical Imaging (ISBI 2010), Rotterdam, The Netherlands, (101-104). 14-17 April 2010.

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Author Joshi, Anand A.
Lepore, Natasha
Joshi, Shantanu
Lee, Agatha D.
Barysheva, Marina
de Zubicaray, Greig I.
Wright, Margaret J.
McMahon, Katie L.
Toga, Arthur W.
Thompson, Paul M.
Title of paper A genetic analysis of cortical thickness in 372 twins
Conference name IEEE International Symposium on Biomedical Imaging (ISBI 2010)
Conference location Rotterdam, The Netherlands
Conference dates 14-17 April 2010
Proceedings title 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro   Check publisher's open access policy
Journal name 2010 7th Ieee International Symposium On Biomedical Imaging: From Nano to Macro   Check publisher's open access policy
Place of Publication Piscatawa, NJ, U.S.A.
Publisher Institute of Electrical and Electronics Engineers ( IEEE )
Publication Year 2010
Sub-type Fully published paper
DOI 10.1109/ISBI.2010.5490405
ISBN 9781424441259
ISSN 1945-7928
Volume 1-2
Issue Article number 5490405
Start page 101
End page 104
Total pages 4
Collection year 2011
Language eng
Abstract/Summary Imaging genetics is a new field of neuroscience that blends methods from computational anatomy and quantitative genetics to identify genetic influences on brain structure and function. Here we analyzed brain MRI data from 372 young adult twins to identify cortical regions in which gray matter volume is influenced by genetic differences across subjects. Thickness maps, reconstructed from surface models of the cortical gray/white and gray/CSF interfaces, were smoothed with a 25 mm FWHM kernel and automatically parcellated into 34 regions of interest per hemisphere. In structural equation models fitted to volume values at each surface vertex, we computed components of variance due to additive genetic (A), shared (C) and unique (E) environmental factors, and tested their significance. Cortical regions in the vicinity of the perisylvian language cortex, and at the frontal and temporal poles, showed significant additive genetic variance, suggesting that volume measures from these regions may provide quantitative phenotypes to narrow the search for quantitative trait loci that influence brain structure. ©2010 IEEE.
Keyword Brain
Cortex
Genetics
Image analysis
Magnetic resonance imaging
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes session WE-PS2: BRAIN IMAGING AND ANALYSIS I

Document type: Conference Paper
Collections: Official 2011 Collection
Centre for Advanced Imaging Publications
 
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Created: Wed, 09 Mar 2011, 16:01:19 EST by Sandrine Ducrot on behalf of Centre for Advanced Imaging