Journal article
Jeanne E Savage, P. Barr, Tanya Phung, Y. Lee, Yingzhe Zhang, V. McCutcheon, Tian Ge, J. Smoller, Lea K. Davis, Jacquelyn Meyers, B. Porjesz, D. Posthuma, T. Mallard, S. Sanchez-Roige
medRxiv, 2023
medRxiv, 2023
Semantic Scholar
DOI
PubMed
Cite
Cite
APA
Click to copy
Savage, J. E., Barr, P., Phung, T., Lee, Y., Zhang, Y., McCutcheon, V., … Sanchez-Roige, S. (2023). Genetic Heterogeneity Across Dimensions of Alcohol Use Behaviors. MedRxiv.
Chicago/Turabian
Click to copy
Savage, Jeanne E, P. Barr, Tanya Phung, Y. Lee, Yingzhe Zhang, V. McCutcheon, Tian Ge, et al. “Genetic Heterogeneity Across Dimensions of Alcohol Use Behaviors.” medRxiv (2023).
MLA
Click to copy
Savage, Jeanne E., et al. “Genetic Heterogeneity Across Dimensions of Alcohol Use Behaviors.” MedRxiv, 2023.
BibTeX Click to copy
@article{jeanne2023a,
title = {Genetic Heterogeneity Across Dimensions of Alcohol Use Behaviors},
year = {2023},
journal = {medRxiv},
author = {Savage, Jeanne E and Barr, P. and Phung, Tanya and Lee, Y. and Zhang, Yingzhe and McCutcheon, V. and Ge, Tian and Smoller, J. and Davis, Lea K. and Meyers, Jacquelyn and Porjesz, B. and Posthuma, D. and Mallard, T. and Sanchez-Roige, S.}
}
Abstract
Background: Increasingly large samples in genome-wide association studies (GWAS) for alcohol use behaviors (AUBs) have led to an influx of implicated genes, yet the clinical and functional understanding of these associations remains low. This is, in part, because most GWASs do not account for complex and varied manifestations of AUBs. This study applied a multidimensional framework to investigate the latent genetic structure underlying heterogeneous dimensions of AUBs. Methods: Multi-modal assessments (self-report, interview, electronic health records) were obtained from approximately 400,000 UK Biobank participants. GWAS was conducted for 18 distinct AUBs, including consumption, drinking patterns, alcohol problems, and clinical sequelae. Latent genetic factors were identified and carried forward to GWAS using genomic structural equation modeling, followed by functional annotation, genetic correlation, and enrichment analyses to interpret the genetic associations. Results: Four latent factors were identified: Problems, Consumption, BeerPref (declining alcohol consumption with a preference for drinking beer), and AtypicalPref (drinking fortified wine and spirits). The latent factors were moderately correlated (rg= .12-.57) and had distinct patterns of associations, with BeerPref in particular implicating many novel genomic regions. Patterns of regional and cell type specific gene expression in the brain also differed between the latent factors. Conclusion: Deep phenotyping and multi-modal assessment is an important next step to improve understanding of the genetic etiology of AUBs, in addition to increasing sample size. Further effort is required to uncover the genetic heterogeneity underlying AUBs using methods that account for their complex, multidimensional nature.