Extending genetic linkage analysis to diffusion tensor images to map single gene effects on brain fiber architecture

Chiang, Ming-Chang, Avedissian, Christina, Barysheva, Marina, Toga, Arthur W., McMahon, Katie L., De Zubicaray, Greig I., Wright, Margaret J. and Thompson, Paul M. (2009). Extending genetic linkage analysis to diffusion tensor images to map single gene effects on brain fiber architecture. In: Guang-Zhong Yang, David Hawkes, Daniel Rueckert, Alison Noble and Chris Taylor, Proceedings, Part II, MICCAI 2009: 12th International Conference. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2009, London, United Kingdom, (506-513). 20-24 September 2009.


Author Chiang, Ming-Chang
Avedissian, Christina
Barysheva, Marina
Toga, Arthur W.
McMahon, Katie L.
De Zubicaray, Greig I.
Wright, Margaret J.
Thompson, Paul M.
Title of paper Extending genetic linkage analysis to diffusion tensor images to map single gene effects on brain fiber architecture
Conference name Medical Image Computing and Computer-Assisted Intervention - MICCAI 2009
Conference location London, United Kingdom
Conference dates 20-24 September 2009
Proceedings title Proceedings, Part II, MICCAI 2009: 12th International Conference   Check publisher's open access policy
Journal name Lecture Notes in Computer Science   Check publisher's open access policy
Place of Publication Heidelberg, Germany
Publisher Springer
Publication Year 2009
Sub-type Fully published paper
DOI 10.1007/978-3-642-04271-3
ISBN 9783642042706
3642042708
ISSN 0302-9743
Editor Guang-Zhong Yang
David Hawkes
Daniel Rueckert
Alison Noble
Chris Taylor
Volume 5762/2009
Start page 506
End page 513
Total pages 8
Collection year 2010
Language eng
Abstract/Summary We extended genetic linkage analysis - an analysis widely used in quantitative genetics - to 3D images to analyze single gene effects on brain fiber architecture. We collected 4 Tesla diffusion tensor images (DTI) and genotype data from 258 healthy adult twins and their non-twin siblings. After high-dimensional fluid registration, at each voxel we estimated the genetic linkage between the single nucleotide polymorphism (SNP), Val66Met (dbSNP number rs6265), of the BDNF gene (brain-derived neurotrophic factor) with fractional anisotropy (FA) derived from each subject’s DTI scan, by fitting structural equation models (SEM) from quantitative genetics. We also examined how image filtering affects the effect sizes for genetic linkage by examining how the overall significance of voxelwise effects varied with respect to full width at half maximum (FWHM) of the Gaussian smoothing applied to the FA images. Raw FA maps with no smoothing yielded the greatest sensitivity to detect gene effects, when corrected for multiple comparisons using the false discovery rate (FDR) procedure. The BDNF polymorphism significantly contributed to the variation in FA in the posterior cingulate gyrus, where it accounted for around 90-95% of the total variance in FA. Our study generated the first maps to visualize the effect of the BDNF gene on brain fiber integrity, suggesting that common genetic variants may strongly determine white matter integrity. This work was funded in part by NIH grant R01 HD050735.
Subjects 920199 Clinical Health (Organs, Diseases and Abnormal Conditions) not elsewhere classified
970111 Expanding Knowledge in the Medical and Health Sciences
060410 Neurogenetics
080106 Image Processing
170205 Neurocognitive Patterns and Neural Networks
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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Created: Fri, 09 Apr 2010, 13:59:25 EST by Sandrine Ducrot on behalf of Centre For Magnetic Resonance