Author ORCID Identifier

Defense Date


Document Type


Degree Name

Doctor of Philosophy



First Advisor

David Chester

Second Advisor

Jessica Salvatore

Third Advisor

Danielle Dick

Fourth Advisor

Nathan Gillespie

Fifth Advisor

Peter Barr

Sixth Advisor

Wendy Kliewer; Mary Loos


Frequent alcohol use can lead to alcohol use disorder, which accounts for three million deaths and over 133 million life years lost to disability and death worldwide per year. Alcohol use behaviors unfold across development, beginning with initiation of drinking and progressing through various escalating stages of use. Alcohol use behaviors are also under genetic influence. Genome-wide association represents the state-of-the-science statistical methodology for identifying genes associated with alcohol use outcomes. However, contemporary genome-wide association study (GWAS) methods typically do not account for variability in genetic effects throughout development. In this project, I applied novel multivariate genomic methods to combine developmentally-informative phenotype data and GWAS to create polygenic scores (PGS) that are specific to developmental stage. Longitudinal cohort studies targeted for gene-identification analyses include the Collaborative Study on the Genetics of Alcoholism (adolescence n=1,118, early adulthood n=2,762, adulthood n=5,255), the National Longitudinal Study of Adolescent to Adult Health (adolescence n=3,089, early adulthood n=3,993, adulthood n=5,149), and the Avon Longitudinal Study of Parents and Children (ALSPAC; adolescence n=5,382, early adulthood n=3,613). PGS validation analyses were conducted in the COGA sample using an alternate version of the discovery analysis with COGA removed. Results suggest that genetic liability for alcohol use frequency in adolescence may be distinct from genetic liability for alcohol use frequency later in developmental periods. Additionally, a developmentally-informative approach to polygenic score construction yielded nominal, but not statistically significant, improvements in phenotype prediction in adulthood. The current work was underpowered at all steps of the analysis plan. Small sample sizes and low statistical power limit the substantive conclusions that can be drawn regarding these research questions, replication in well-powered samples is warranted.


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Available for download on Friday, May 03, 2024