A Developmentally-Informative Genome-wide Association Study of Alcohol Use Frequency.
- Authors
- 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
- 2024
- Journal
- Behavior genetics
- PMID
- 38108996
- DOI
- 10.1007/s10519-023-10170-x
- PMCID
- PMC10913412
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 nβ=β1,118, early adulthood nβ=β2,762, adulthood nβ=β5,255), the National Longitudinal Study of Adolescent to Adult Health (adolescence nβ=β3,089, early adulthood nβ=β3,993, adulthood nβ=β5,149), and the Avon Longitudinal Study of Parents and Children (ALSPAC; adolescence nβ=β5,382, early adulthood nβ=β3,613). 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.
Common Factor Genomic Structural Equation ModelGenetic variance shared between all three developmental periods is indexed in the common factor. Genetic variance that is distinct from the common factor is indexed in the residuals. Model identification was achieved by fixing the variance of the common factor to one. Factor loadings are labeled with lambda. Residual variances are labeled with epsilon. The model is saturated.
Diagram of the analysis plan in ALSPAC, COGA, and Add HealthThe steps of the analysis plan include data preprocessing, within-sample GWAS, GWAS meta-analysis, estimation of SNP-based heritability and genetic covariances by LD-Score Regression, genomic structural equation modeling with SNP effects, calculation of genetic correlations with other phenotypes, and polygenic risk scoring.
Manhattan plots of gSEM GWAS of total genetic variance in alcohol use frequency in the full sample (ALSPAC, COGA, and Add Health).The genome-wide significance (p<5e-8) is marked in red. The threshold for suggestive significance (p<1e-5) is marked in blue.
Quantile-quantile plots of gSEM GWAS of total genetic variance in alcohol use frequency in the full sample (ALSPAC, COGA, and Add Health).Observed βlog10(p) are plotted against the expected uniform distribution of βlog10(p) under the null hypothesis.
Genetic correlations between alcohol use frequency at different developmental periods and a series of other phenotypes in the full sample (ALSPAC, COGA, and Add Health).Adolescence, Early Adulthood, and Adulthood refer to the Genomic Structural Equation Model GWAS results using the total variance parameterization of the model The X-axis of the plot is truncated at β1 and 1. A list of the phenotypes with sample sizes and citations is included in Table S3. Abbreviation: AUDIT-P = Alcohol Use Disorder Identification Test, Problems Subscale.
Power estimates for the adolescence residual component of the gSEM at the genome-wide significance threshold (p < 5e-8; left) and the suggestive threshold (p<1e-5; right) with SNP effect size Ξ²=0.01Vertical lines in the figure demarcate the observed sample sizes in the discovery analysis of the current study: dotted = adolescence, dot-dashed=early adulthood, dashed = adulthood, solid = common factor.
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External
| Title | Authors | Journal | Year | Link |
|---|---|---|---|---|
| Trajectories of genetic risk across dimensions of alcohol use behaviors. | Savage JE et al. | β | 2026 | β |
| Associations of polygenic scores and developmental trajectories of externalizing behaviors. | Sasia AB et al. | β | 2025 | β |
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| Etiology and correlates of alcohol misuse in early midlife. | Lumpe E et al. | β | 2025 | β |
| Genetic influences for distinct impulsivity domains are differentially associated with early substance use initiation: Results from the ABCD Study. | Kinstler E et al. | β | 2025 | β |
| Binge drinking trajectories across adolescence and early adulthood: Associations with genetic influences for dual-systems impulsive personality traits, alcohol consumption, and alcohol use disorder | Miller AP et al. | β | 2024 | β |
| Considerations for the application of polygenic scores to clinical care of individuals with substance use disorders. | Kember RL et al. | β | 2024 | β |
| Generalized genetic liability to substance use disorders. | Miller AP et al. | β | 2024 | β |