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Activity Number: 173 - Recent Advances on Neuroimaging Analysis
Type: Contributed
Date/Time: Monday, July 30, 2018 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Imaging
Abstract #329006 Presentation
Title: Statistical Inference for Neuroimaging Genetics
Author(s): Long Feng* and Xuan Bi and Heping Zhang
Companies: Yale University and Yale University and Yale University School of Public Health
Keywords: imaging genetics; inference; genomic data

Mental disorder is highly heritable and has strong association with human brain structures including cortical regions, whose measurements are biomarkers that may lead to revelation of implicit mechanisms causing psychiatric disorders and cognitive disabilities. In fact, while certain genetic variants have strong influence on human cortical brain regions, the effect of heritability from a single variant is weak in general, and in many studies interaction and synergy among genetic variants are observed. Therefore, the study of polygenicity is necessary. Toward this end, we consider a new statistical inference approach in addition to the standard genome-wide association studies (GWAS) to uncover the potential polygenic effects on cortical regions and mental illnesses. We conduct genome-wide association studies of the area, thickness and volume of sixty six human cortical brain regions derived from magnetic resonance imaging scans of both children and adolescents.

Authors who are presenting talks have a * after their name.

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