This application seeks funding for research to help understand the genetic influences on neuroanatomical shapes. Imaging genetics is a major new direction in brain mapping because it goes beyond simple descriptions to more mechanistic understandings of which genes and environmental factors affect disease expression or risk. Unique to our approach is access to an existing dataset collected on more than 1000 twins, all with GWAS and neuroimaging data. We will use this data to develop maps of: (1) the heritability of subcortical and cortical gray matter shapes, (2) the heritability of the shape of white matter tracts, (3) the influence of brain-derived neurotrophic factor (BDNF), catechol-O-methyltransferase (COMT), and fat mass and obesity-associated (FTO) polymorphisms on gray and white matter shapes, and (4) genome-wide association studies (GWAS) to identify new genes or single nucleotide polymorphisms (SNPs) that influence neuroanatomical shapes. The results generated will greatly advance our knowledge of how genes influence neuroanatomy. In addition, we will develop software tools to facilitate the community's use of neuroimaging data to characterize subtle genetic effects. Project deliverables include the dissemination of a complete, open- source multimodal imaging genetics toolkit. Through accelerating research in imaging genetics, and combining mathematical approaches from multiple fields, this project will invigorate biomedical research and expedite the merging of huge arsenals of neuroimaging data and GWAS data. The activities in the project are extremely responsive to the NIH's mission in advancing GWAS to identify common genetic factors that influence health and disease.

Public Health Relevance

This unique large-scale investigation will improve understanding of the complex ways in which genetics exert influence over human neuroanatomy. By providing the larger research community with mathematically sophisticated software tools, we will create opportunities to advance progress in many psychiatric and neurological diseases.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
1R01MH094343-01A1
Application #
8295646
Study Section
Molecular Neurogenetics Study Section (MNG)
Program Officer
Freund, Michelle
Project Start
2012-07-01
Project End
2017-03-31
Budget Start
2012-07-01
Budget End
2013-03-31
Support Year
1
Fiscal Year
2012
Total Cost
$611,489
Indirect Cost
$214,418
Name
University of California Los Angeles
Department
Neurology
Type
Schools of Medicine
DUNS #
092530369
City
Los Angeles
State
CA
Country
United States
Zip Code
90095
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Li, Junning; Shi, Yonggang; Toga, Arthur W (2016) Transformation Invariant Control of Voxel-Wise False Discovery Rate. IEEE Trans Med Imaging 35:2243-2257
Li, Junning; Shi, Yonggang; Toga, Arthur W (2016) Mapping Brain Anatomical Connectivity Using Diffusion Magnetic Resonance Imaging: Structural connectivity of the human brain. IEEE Signal Process Mag 33:36-51
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Clark, Kristi A; Helland, Turid; Specht, Karsten et al. (2015) Reply: Cortical differences in preliterate children at familiar risk of dyslexia are similar to those observed in dyslexic readers. Brain 138:e379
Li, Junning; Shi, Yonggang; Toga, Arthur W (2014) Diffusion of fiber orientation distribution functions with a rotation-induced riemannian metric. Med Image Comput Comput Assist Interv 17:249-56
Toga, Arthur W; Thompson, Paul M (2014) Connectopathy in ageing and dementia. Brain 137:3104-6
Medland, Sarah E; Jahanshad, Neda; Neale, Benjamin M et al. (2014) Whole-genome analyses of whole-brain data: working within an expanded search space. Nat Neurosci 17:791-800

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