The goal of this proposed research is to generate a genetic architecture of brain development.
We aim to achieve this goal in two solid steps. We first utilize our existing brain MR imaging measurements (traditional MRI volumetry, brain connectivity, resting state activity) of 235 individuals, 125 with autism and 110 typically developing subjects, to build a data structure of brain regions of interest that have at least 50% estimated heritability for typical brains, sorted first by size and then by components of structura-functional variability. In our next step, we interrogate whole-exome and whole-genome sequences and network analysis of molecular pathways by state-of-the-art molecular genetics methods in reference to this data structure. We expect that this detailed analysis of variability and extremes in brain imaging phenotypes in autism will result in the discovery of new genetic associations that reveal new biological pathways and advance our understanding of autism neuropathology and its severely impairing clinical manifestations. Our results will thus change imaging genetics in autism research.

Public Health Relevance

Given the high prevalence of autism and the immense, lifelong adverse impact it has on affected individuals and their families, the present lack of any effective treatment or preventive intervention based on the biology of the disorder has produced an burgeoning, very expensive public health burden on the United States and worldwide horizon. This application seeks to break this long-standing barrier to gene discovery and public health benefit by plumbing the wealth of information found in abnormal brain variation and to employ the knowledge gained from this previously untapped source to identify genetic associations and molecular pathways that lead to autism and its effective treatment.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH097464-05
Application #
9327797
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Gilotty, Lisa
Project Start
2013-08-29
Project End
2019-07-31
Budget Start
2017-08-01
Budget End
2019-07-31
Support Year
5
Fiscal Year
2017
Total Cost
Indirect Cost
Name
University of Wisconsin Madison
Department
Pediatrics
Type
Graduate Schools
DUNS #
161202122
City
Madison
State
WI
Country
United States
Zip Code
53715
McLaughlin, Kristine; Travers, Brittany G; Dadalko, Olga I et al. (2018) Longitudinal development of thalamic and internal capsule microstructure in autism spectrum disorder. Autism Res 11:450-462
Prigge, Molly B D; Bigler, Erin D; Travers, Brittany G et al. (2018) Social Responsiveness Scale (SRS) in Relation to Longitudinal Cortical Thickness Changes in Autism Spectrum Disorder. J Autism Dev Disord 48:3319-3329
Kecskemeti, Steven; Samsonov, Alexey; Velikina, Julia et al. (2018) Robust Motion Correction Strategy for Structural MRI in Unsedated Children Demonstrated with Three-dimensional Radial MPnRAGE. Radiology 289:509-516
Dean 3rd, D C; Lange, N; Travers, B G et al. (2017) Multivariate characterization of white matter heterogeneity in autism spectrum disorder. Neuroimage Clin 14:54-66
Dean 3rd, Douglas C; Travers, Brittany G; Adluru, Nagesh et al. (2016) Investigating the Microstructural Correlation of White Matter in Autism Spectrum Disorder. Brain Connect 6:415-33
Green, Ryan R; Bigler, Erin D; Froehlich, Alyson et al. (2016) Beery VMI performance in autism spectrum disorder. Child Neuropsychol 22:795-817
Schrodi, Steven J (2016) Reflections on the Field of Human Genetics: A Call for Increased Disease Genetics Theory. Front Genet 7:106
Farmer, Cristan A; Kaat, Aaron J; Mazurek, Micah O et al. (2016) Confirmation of the Factor Structure and Measurement Invariance of the Children's Scale of Hostility and Aggression: Reactive/Proactive in Clinic-Referred Children With and Without Autism Spectrum Disorder. J Child Adolesc Psychopharmacol 26:10-8
Maadooliat, Mehdi; Bansal, Naveen K; Upadhya, Jiblal et al. (2016) The Decay of Disease Association with Declining Linkage Disequilibrium: A Fine Mapping Theorem. Front Genet 7:217
Schrodi, Steven J (2016) The Use of Multiplicity Corrections, Order Statistics and Generalized Family-Wise Statistics with Application to Genome-Wide Studies. PLoS One 11:e0154472

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