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Genetic and Diagnostic Biomarker Development in ASD Toddlers Using Resting State Functional MRI

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Yale University New Haven United States

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Our overarching strategy is to exploit three large neuroimagingneurobehavioral datasets to identify brain-imaging based biomarkers for Autism Spectrum DisordersASD. At Yale, we focus on determining if brain networks are influenced by genetic factors and if these genetic factors also influence other traits associated with ASD. Specifically, we will provide heritability estimates and test for pleitropy between putative ASD functional and structural networks and cognitive and behavioral traits. To demonstrate the feasibility of this analytic approach, we conducted an initial analysis with over 250 seed regions simultaneously to provide measures of brain connectivity within 14 previously derived functional networks. Next, we estimated heritability for these structural and functional networks, examined the coheritability between different modalities e.g. function and structure and searched the genome for chromosomal loci influencing these networks. We demonstrated that many of these intrinsic brain networks are heritable, that different genetic factors influence brain function and structure and localized a number of chromosomal regions that harbor genes influencing brain connectivity. These findings, which were presented at the annual meeting of the Organization for Human Brain Mapping, clearly demonstrate our ability to conduct similar analyses with ASD specific networks, one these are identified in the BrainMap and ACE datasets.

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Technical Report,01 Sep 2015,31 Aug 2016



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Approved For Public Release;

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