A Developmentally-Informative Genome-wide Association Study of Alcohol Use Frequency


Thomas, Nathaniel S.; Gillespie, Nathan A.; Chan, Grace; Edenberg, Howard J.; Kamarajan, Chella; Kuo, Sally I. Chun; Miller, Alex P.; Nurnberger, John I.; Tischfield, Jay; & Dick, Danielle M., et al. (2023). A Developmentally-Informative Genome-wide Association Study of Alcohol Use Frequency. Behavior Genetics.


Contemporary genome-wide association study (GWAS) methods typically do not account for variability in genetic effects throughout development. We applied genomic structural equation modeling to combine developmentally-informative phenotype data and GWAS to create polygenic scores (PGS) for alcohol use frequency 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. The age-specific PGS predicts an increase of 4 drinking days per year per PGS standard deviation when modeled separately from the common factor PGS in adulthood. The current work was underpowered at all steps of the analysis plan. Though small sample sizes and low statistical power limit the substantive conclusions that can be drawn regarding these research questions, this work provides a foundation for future genetic studies of developmental variability in the genetic underpinnings of alcohol use behaviors and genetically-informed, age-matched phenotype prediction.





Reference Type

Journal Article

Journal Title

Behavior Genetics


Thomas, Nathaniel S.
Gillespie, Nathan A.
Chan, Grace
Edenberg, Howard J.
Kamarajan, Chella
Kuo, Sally I. Chun
Miller, Alex P.
Nurnberger, John I.
Tischfield, Jay
Dick, Danielle M.
Salvatore, Jessica E.

Year Published



December 18, 2023





Reference ID