Applying an Integrative Heritable Component Approach to the Identification of Highly Heritable Traits in Diseases with Complex Etiology

Description/Abstract/Artist Statement

Despite numerous recent genome-wide association studies on alcohol use, progress in identifying genetic associations for Alcohol Use Disorder (AUD) has been limited due to the extensive heterogeneity associated with this disorder in terms of clinical manifestations, underlying genetics, and environmental factors. To address this challenge, we propose the use of a novel statistical approach which integrates phenotypic, genotypic, and environmental data to derive disease related traits with maximized heritability. The method will be applied in two phases. In phase 1, a statistical method will be developed that aims to identify a function that leads to the identification of a trait with a maximized heritability estimate. This method will make use of a linear-mixed-model which will account for the moderating effects of environmental factors. We will further investigate the application of a constraint to the derived traits which will allow them to be interpreted as severity indexes for alcohol use disorder. In phase 2, genome-wide association studies will be conducted to identify genetic risk factors associated with the derived traits.

Presenting Author Name/s

Ivy Garrenton

Faculty Advisor/Mentor

Jiangwen Sun

Faculty Advisor/Mentor Department

Computer Science

College Affiliation

College of Sciences

Presentation Type

Poster

Disciplines

Computer Sciences

Session Title

Poster Session

Location

Learning Commons Lobby @ Perry Library

Start Date

3-25-2023 8:30 AM

End Date

3-25-2023 10:00 AM

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Mar 25th, 8:30 AM Mar 25th, 10:00 AM

Applying an Integrative Heritable Component Approach to the Identification of Highly Heritable Traits in Diseases with Complex Etiology

Learning Commons Lobby @ Perry Library

Despite numerous recent genome-wide association studies on alcohol use, progress in identifying genetic associations for Alcohol Use Disorder (AUD) has been limited due to the extensive heterogeneity associated with this disorder in terms of clinical manifestations, underlying genetics, and environmental factors. To address this challenge, we propose the use of a novel statistical approach which integrates phenotypic, genotypic, and environmental data to derive disease related traits with maximized heritability. The method will be applied in two phases. In phase 1, a statistical method will be developed that aims to identify a function that leads to the identification of a trait with a maximized heritability estimate. This method will make use of a linear-mixed-model which will account for the moderating effects of environmental factors. We will further investigate the application of a constraint to the derived traits which will allow them to be interpreted as severity indexes for alcohol use disorder. In phase 2, genome-wide association studies will be conducted to identify genetic risk factors associated with the derived traits.