Christina M. Sheerin, Rowan K. O’Hara-Payne, Eva E. Lancaster, Hailie Suarez-Rivas, Spit for Science Working Group, Chris Chatzinakos, Elizabeth C. Prom-Wormley, Roseann E. Peterson, Fazil Aliev, Amy E. Adkins, Ananda Amstadter, Thomas Bannard, Peter Barr, Erin C. Berenz, Katie Bountress, Holly Byers, A. Christian Pais, Erin Caraway, James S. Clifford, Megan Cooke, Karen Chartier, Seung B. Cho, Elizabeth Do, Danielle M. Dick, Alexis C. Edwards, Renolda Gelzinis, Neeru Goyal, Sage Hawn, Laura M. Hack, Lisa J. Halberstadt, Sally Kuo, Jacquelyn L. Meyers, Emily Lasko, Jennifer Lend, Emily Lilley, Mackenzie Lind, Elizabeth Long, Alexandra Martelli, Arden Moscati, Anne Morris, Ashlee Moore, Kerry Mitchell, Aashir Nasim, Zoe Neale, Jill Opalesky, Cassie Overstreet, Kimberly Pedersen, Tarah Raldiris, Brien Riley, Jessica Salvatore, Jeanne Savage, David Sosnowski, Rebecca Smith, Jinni Su, Cuie Sun, Nathaniel Thomas, Chloe Walker, Marcie Walsh, Bradley T. Webb, Teresa Willoughby, Brandon Wormley, Madison Woodroof, and Jia Yan
Introduction: Genetic factors impact alcohol consumption and use disorder (AUD), with large-scale genome-wide association studies (GWAS) identifying numerous associated variants. Aggregate genetic methods in combination with important environmental factors (e.g., interpersonal trauma [IPT]) can be applied to expand our understanding of the ways by which genetic and environmental variables work together to influence alcohol consumption and disordered use. The present study aimed to detail the relationships between genome-wide polygenic scores (PGS) for alcohol phenotypes (i.e., alcohol consumption and AUD status) and IPT exposure as well as the interaction between them across ancestry.Methods: Data were drawn from the Spit for Science (S4S) study, a US college student population, where participants reported on IPT exposure prior to college and alcohol consumption and problems during college (N = 9,006; ancestry: 21.3% African [AFR], 12.5% Admixed Americas [AMR], 9.6% East Asian [EAS], 48.1% European [EUR], 8.6% South Asian [SAS]). Two trans-ancestry PGS were constructed, one for alcohol consumption and another for AUD, using large-scale GWAS summary statistics from multiple ancestries weighted using PRS-CSx. Regression models were applied to test for the presence of associations between alcohol-PGS and IPT main and interaction effects.Results: In the meta-analysis across ancestry groups, IPT exposure and PGS were significantly associated with alcohol consumption (βIPT = 0.31, PIPT = 0.0002; βPGS = 0.09, PPGS = 0.004) and AUD (ORIPT = 1.12, PIPT = 3.5 × 10−8; ORPGS = 1.02, PPGS = 0.002). No statistically significant interactions were detected between IPT and sex nor between IPT and PGS. When inspecting ancestry specific results, the alcohol consumption-PGS and AUD-PGS were only statistically significant in the EUR ancestry group (βPGS = 0.09, PPGS = 0.04; ORPGS = 1.02, PPGS = 0.022, respectively).Discussion: IPT exposure prior to college was strongly associated with alcohol outcomes in this college-age sample, which could be used as a preventative measure to identify students at high risk for problematic alcohol use. Additionally, results add to developing evidence of polygenic score association in meta-analyzed samples, highlighting the importance of continued efforts to increase ancestral representation in genetic studies and inclusive analytic approaches to increase the generalizability of results from genetic association studies.