Hierarchical clustering of the genetic connectivity matrix reveals the network topology of gene action on brain microstructure: An N=531 twin study

Chiang, Ming-Chang, Barysheva, Marina, McMahon, Katie L., de Zubicaray, Greig I., Johnson, Kori, Martin, Nicholas G., Toga, Arthur W., Wright, Margaret J. and Thompson, Paul M. (2011). Hierarchical clustering of the genetic connectivity matrix reveals the network topology of gene action on brain microstructure: An N=531 twin study. In: 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro. 2011 IEEE 8th International Symposium on Biomedical Imaging (ISBI 2011), Chicago, United States, (832-835). 30 March - 2 April 2011. doi:10.1109/ISBI.2011.5872533

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Author Chiang, Ming-Chang
Barysheva, Marina
McMahon, Katie L.
de Zubicaray, Greig I.
Johnson, Kori
Martin, Nicholas G.
Toga, Arthur W.
Wright, Margaret J.
Thompson, Paul M.
Title of paper Hierarchical clustering of the genetic connectivity matrix reveals the network topology of gene action on brain microstructure: An N=531 twin study
Conference name 2011 IEEE 8th International Symposium on Biomedical Imaging (ISBI 2011)
Conference location Chicago, United States
Conference dates 30 March - 2 April 2011
Proceedings title 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro   Check publisher's open access policy
Journal name Proceedings - International Symposium on Biomedical Imaging   Check publisher's open access policy
Place of Publication Piscataway, NJ, United States
Publisher IEEE
Publication Year 2011
Year available 2011
Sub-type Fully published paper
DOI 10.1109/ISBI.2011.5872533
Open Access Status Not Open Access
ISBN 9781424441273
ISSN 1945-7928
Start page 832
End page 835
Total pages 4
Language eng
Formatted Abstract/Summary
Genetic correlation (rg) analysis determines how much of the correlation between two measures is due to common genetic influences. In an analysis of 4 Tesla diffusion tensor images (DTI) from 531 healthy young adult twins and their siblings, we generalized the concept of genetic correlation to determine common genetic influences on white matter integrity, measured by fractional anisotropy (FA), at all points of the brain, yielding an NxN genetic correlation matrix  rg(x,y) between FA values at all pairs of voxels in the brain. With hierarchical clustering, we identified brain regions with relatively homogeneous genetic determinants, to boost the power to identify causal single nucleotide polymorphisms (SNP). We applied genome-wide association (GWA) to assess associations between 529,497 SNPs  and FA in clusters defined by hubs of the clustered genetic correlation matrix. We identified a network of genes, with a scalefree topology, that influences white matter integrity over multiple brain regions.
Keyword Diffusion tensor imaging
Twins
Hierarchical clustering
Scale-free topology
Genome-wide association
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Conference Paper
Sub-type: 2011 8Th Ieee International Symposium On Biomedical Imaging: From Nano to Macro
Collections: Official 2012 Collection
School of Psychology Publications
Centre for Advanced Imaging Publications
 
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Created: Wed, 19 Oct 2011, 22:54:58 EST by Sandrine Ducrot on behalf of Centre for Advanced Imaging