Multi-ancestry study of the genetics of problematic alcohol use in over 1 million individuals.
МетаанализСтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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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, Nielsen Trine Tollerup, 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
Аннотация
Problematic 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.