Genetic analysis of structural brain connectivity using DICCCOL models of diffusion MRI in 522 twins
Zhu, Dajiang, Zhan, Liang, Faskowitz, Joshua, Daianu, Madelaine, Jahanshad, Neda, de Zubicaray, Greig I., McMahon, Katie L., Martin, Nicholas G., Wright, Margaret J., & Thompson, Paul M. (2015) Genetic analysis of structural brain connectivity using DICCCOL models of diffusion MRI in 522 twins. In 12th IEEE International Symposium on Biomedical Imaging (ISBI 2015), 16-19 April 2015, Brooklyn, NY.
Genetic and environmental factors affect white matter connectivity in the normal brain, and they also influence diseases in which brain connectivity is altered. Little is known about genetic influences on brain connectivity, despite wide variations in the brain's neural pathways. Here we applied the 'DICCCOL' framework to analyze structural connectivity, in 261 twin pairs (522 participants, mean age: 21.8 y ± 2.7SD). We encoded connectivity patterns by projecting the white matter (WM) bundles of all 'DICCCOLs' as a tracemap (TM). Next we fitted an A/C/E structural equation model to estimate additive genetic (A), common environmental (C), and unique environmental/error (E) components of the observed variations in brain connectivity. We found 44 'heritable DICCCOLs' whose connectivity was genetically influenced (α2>1%); half of them showed significant heritability (α2>20%). Our analysis of genetic influences on WM structural connectivity suggests high heritability for some WM projection patterns, yielding new targets for genome-wide association studies.
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|Item Type:||Conference Paper|
|Keywords:||medical imaging, connectivity pattern, DICCCOL, environmental factors, genome-wide assosicaiton studies|
|Divisions:||Current > QUT Faculties and Divisions > Faculty of Health|
|Copyright Owner:||Copyright 2015 IEEE|
|Deposited On:||15 Apr 2016 02:43|
|Last Modified:||19 Apr 2016 15:32|
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