Genetics of Anisotropy Asymmetry: Registration and Sample Size Effects

Authors:
Neda Jahanshad;Agatha D. Lee;Natasha Leporé;Yi-Yu Chou;Caroline C. Brun;Marina Barysheva;Arthur W. Toga;Katie L. Mcmahon;Greig I. Zubicaray;Margaret J. Wright;Paul M. Thompson
Affiliations:
Laboratory of Neuro Imaging, Department of Neurology, UCLA, USA and Medical Imaging Informatics Group, Department of Radiology, UCLA, USA;Laboratory of Neuro Imaging, Department of Neurology, UCLA, USA;Laboratory of Neuro Imaging, Department of Neurology, UCLA, USA;Laboratory of Neuro Imaging, Department of Neurology, UCLA, USA;Laboratory of Neuro Imaging, Department of Neurology, UCLA, USA;Laboratory of Neuro Imaging, Department of Neurology, UCLA, USA;Laboratory of Neuro Imaging, Department of Neurology, UCLA, USA;fMRI Laboratory, Centre for MR, University of Queensland, Brisbane, Australia;fMRI Laboratory, Centre for MR, University of Queensland, Brisbane, Australia;Queensland Institute of Medical Research, Brisbane, Australia;Laboratory of Neuro Imaging, Department of Neurology, UCLA, USA
Venue:
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Year:
2009

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Abstract

Brain asymmetry has been a topic of interest for neuroscientists for many years. The advent of diffusion tensor imaging (DTI) allows researchers to extend the study of asymmetry to a microscopic scale by examining fiber integrity differences across hemispheres rather than the macroscopic differences in shape or structure volumes. Even so, the power to detect these microarchitectural differences depends on the sample size and how the brain images are registered and how many subjects are studied. We fluidly registered 4 Tesla DTI scans from 180 healthy adult twins (45 identical and fraternal pairs) to a geometrically-centered population mean template. We computed voxelwise maps of significant asymmetries (left/right hemisphere differences) for common fiber anisotropy indices (FA, GA). Quantitative genetic models revealed that 47-62% of the variance in asymmetry was due to genetic differences in the population. We studied how these heritability estimates varied with the type of registration target (T1- or T2-weighted) and with sample size. All methods consistently found that genetic factors strongly determined the lateralization of fiber anisotropy, facilitating the quest for specific genes that might influence brain asymmetry and fiber integrity.