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Browsing by Author "Mallard, Travis T."
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Item Item-Level Genome-Wide Association Study of the Alcohol Use Disorders Identification Test in Three Population-Based Cohorts(American Psychiatric Association, 2022) Mallard, Travis T.; Savage, Jeanne E.; Johnson, Emma C.; Huang, Yuye; Edwards, Alexis C.; Hottenga, Jouke J.; Grotzinger, Andrew D.; Gustavson, Daniel E.; Jennings, Mariela V.; Anokhin, Andrey; Dick, Danielle M.; Edenberg, Howard J.; Kramer, John R.; Lai, Dongbing; Meyers, Jacquelyn L.; Pandey, Ashwini K.; Harden, Kathryn Paige; Nivard, Michel G.; de Geus, Eco J. C.; Boomsma, Dorret I.; Agrawal, Arpana; Davis, Lea K.; Clarke, Toni-Kim; Palmer, Abraham A.; Sanchez-Roige, Sandra; Biochemistry and Molecular Biology, School of MedicineObjective: Genome-wide association studies (GWASs) of the Alcohol Use Disorders Identification Test (AUDIT), a 10-item screen for alcohol use disorder (AUD), have elucidated novel loci for alcohol consumption and misuse. However, these studies also revealed that GWASs can be influenced by numerous biases (e.g., measurement error, selection bias), which may have led to inconsistent genetic correlations between alcohol involvement and AUD, as well as paradoxically negative genetic correlations between alcohol involvement and psychiatric disorders and/or medical conditions. The authors used genomic structural equation modeling to elucidate the genetics of alcohol consumption and problematic consequences of alcohol use as measured by AUDIT. Methods: To explore these unexpected differences in genetic correlations, the authors conducted the first item-level and the largest GWAS of AUDIT items (N=160,824) and applied a multivariate framework to mitigate previous biases. Results: The authors identified novel patterns of similarity (and dissimilarity) among the AUDIT items and found evidence of a correlated two-factor structure at the genetic level ("consumption" and "problems," rg=0.80). Moreover, by applying empirically derived weights to each of the AUDIT items, the authors constructed an aggregate measure of alcohol consumption that was strongly associated with alcohol dependence (rg=0.67), moderately associated with several other psychiatric disorders, and no longer positively associated with health and positive socioeconomic outcomes. Lastly, by conducting polygenic analyses in three independent cohorts that differed in their ascertainment and prevalence of AUD, the authors identified novel genetic associations between alcohol consumption, alcohol misuse, and health. Conclusions: This work further emphasizes the value of AUDIT for both clinical and genetic studies of AUD and the importance of using multivariate methods to study genetic associations that are more closely related to AUD.Item Mapping Pathways by which Genetic Risk Influences Adolescent Externalizing Behavior: The Interplay between Externalizing Polygenic Risk Scores, Parental Knowledge, and Peer Substance Use(Springer, 2021) Kuo, Sally I-Chun; Salvatore, Jessica E.; Barr, Peter B.; Aliev, Fazil; Anokhin, Andrey; Bucholz, Kathleen K.; Chan, Grace; Edenberg, Howard J.; Hesselbrock, Victor; Kamarajan, Chella; Kramer, John R.; Lai, Dongbing; Mallard, Travis T.; Nurnberger, John I., Jr.; Pandey, Gayathri; Plawecki, Martin H.; Sanchez-Roige, Sandra; Waldman, Irwin; Palmer, Abraham A.; Externalizing Consortium; Dick, Danielle M.; Biochemistry and Molecular Biology, School of MedicineGenetic predispositions and environmental influences both play an important role in adolescent externalizing behavior; however, they are not always independent. To elucidate gene-environment interplay, we examined the interrelationships between externalizing polygenic risk scores, parental knowledge, and peer substance use in impacting adolescent externalizing behavior across two time-points in a high-risk longitudinal sample of 1,200 adolescents (764 European and 436 African ancestry; Mage = 12.99) from the Collaborative Study on the Genetics of Alcoholism. Results from multivariate path analysis indicated that externalizing polygenic scores were directly associated with adolescent externalizing behavior but also indirectly via peer substance use, in the European ancestry sample. No significant polygenic association nor indirect effects of genetic risk were observed in the African ancestry group, likely due to more limited power. Our findings underscore the importance of gene-environment interplay and suggest peer substance use may be a mechanism through which genetic risk influences adolescent externalizing behavior.Item Multi-ancestry study of the genetics of problematic alcohol use in over 1 million individuals(Springer Nature, 2023) Zhou, Hang; Kember, Rachel L.; Deak, Joseph D.; Xu, Heng; Toikumo, Sylvanus; Yuan, Kai; Lind, Penelope A.; Farajzadeh, Leila; Wang, Lu; Hatoum, Alexander S.; Johnson, Jessica; Lee, Hyunjoon; Mallard, Travis T.; Xu, Jiayi; Johnston, Keira J. A.; Johnson, Emma C.; Galimberti, Marco; Dao, Cecilia; Levey, Daniel F.; Overstreet, Cassie; Byrne, Enda M.; Gillespie, Nathan A.; Gordon, Scott; Hickie, Ian B.; Whitfield, John B.; Xu, Ke; Zhao, Hongyu; Huckins, Laura M.; Davis, Lea K.; Sanchez-Roige, Sandra; Madden, Pamela A. F.; Heath, Andrew C.; Medland, Sarah E.; Martin, Nicholas G.; Ge, Tian; Smoller, Jordan W.; Hougaard, David M.; Børglum, Anders D.; Demontis, Ditte; Krystal, John H.; Gaziano, J. Michael; Edenberg, Howard J.; Agrawal, Arpana; Million Veteran Program; Justice, Amy C.; Stein, Murray B.; Kranzler, Henry R.; Gelernter, Joel; Biochemistry and Molecular Biology, School of MedicineProblematic alcohol use (PAU), a trait that combines alcohol use disorder and alcohol-related problems assessed with a questionnaire, is a leading cause of death and morbidity worldwide. Here we conducted a large cross-ancestry meta-analysis of PAU in 1,079,947 individuals (European, N = 903,147; African, N = 122,571; Latin American, N = 38,962; East Asian, N = 13,551; and South Asian, N = 1,716 ancestries). We observed a high degree of cross-ancestral similarity in the genetic architecture of PAU and identified 110 independent risk variants in within- and cross-ancestry analyses. Cross-ancestry fine mapping improved the identification of likely causal variants. Prioritizing genes through gene expression and chromatin interaction in brain tissues identified multiple genes associated with PAU. We identified existing medications for potential pharmacological studies by a computational drug repurposing analysis. Cross-ancestry polygenic risk scores showed better performance of association in independent samples than single-ancestry polygenic risk scores. Genetic correlations between PAU and other traits were observed in multiple ancestries, with other substance use traits having the highest correlations. This study advances our knowledge of the genetic etiology of PAU, and these findings may bring possible clinical applicability of genetics insights-together with neuroscience, biology and data science-closer.