Multi-ancestry study of the genetics of problematic alcohol use in >1 million individuals

Abstract

Problematic alcohol use (PAU) is a leading cause of death and disability worldwide. To improve our understanding of the genetics of PAU, we conducted a large cross-ancestry meta-analysis of PAU in 1,079,947 individuals. 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/or chromatin interaction in brain tissues identified multiple genes associated with PAU. We identified existing medications for potential pharmacological studies by drug repurposing analysis. Cross-ancestry polygenic risk scores (PRS) showed better performance in independent sample than single-ancestry PRS. Genetic correlations between PAU and other traits were observed in multiple ancestries, with other substance use traits having the highest correlations. The analysis of diverse ancestries contributed significantly to the findings, and fills an important gap in the literature.

Adverse Childhood Events, Mood and Anxiety Disorders, and Substance Dependence: Gene X Environment Effects and Moderated Mediation

“…The mediation analyses combined all individuals irrespective of self-identified race. We used summary statistics from large genome-wide association studies (GWAS) of M/ADs, 36–44 and SUDs 45–49 to derive latent genetic factors for the two traits using genomic structural equation modeling (gSEM). Using summary statistics from GWAS on the latent genetic factors, we calculated PRS in the Yale-Penn sample.…”

“…Second, there was greater heterogeneity in the M/AD latent variable than the SD latent variable, as evidenced by the lower trait loadings. This, combined with the smaller discovery GWAS for M/ADs 36,37,38,39,40,41,42,43,44 than for SUDs, particularly among African-ancestry individuals, 45,46,47,49 may have contributed to the failure to detect moderated mediation effects for the M/AD PRS. Among African-ancestry individuals, the smaller discovery samples also limited statistical power of the SD latent genetic factor and PRS.…”

Functional 3’-UTR Variants Identify Regulatory Mechanisms Impacting Alcohol Use Disorder and Related Traits

“…, and related traits [10][11][12][13][14][15][16][17][18] . Though these strategies have expanded our understanding of the genetics of alcohol related traits, they are still limited in how much they can unveil about the underlying mechanisms.…”

Genetic Heterogeneity Across Dimensions of Alcohol Use Behaviors

“…Although AUBs have varying clinical and epidemiological correlates (Gunn, Finn, Endres, Gerst, & Spinola, 2013; Savage & Dick, 2023; Smith, Shevlin, Murphy, & Houston, 2010), all of its diverse forms have a substantial heritable component, with twin studies suggesting that genetics account for approximately 40-60% of individual differences (Dick, Meyers, Rose, Kaprio, & Kendler, 2011; Verhulst, Neale, & Kendler, 2015). Large-scale genome-wide association studies (GWASs) have begun to yield success in identifying the specific genes underlying the heritability of AUBs (Deak & Johnson, 2021), particularly for normative drinking (Liu et al, 2019; Mallard et al, 2022) and PAU (Zhou et al, 2023; Zhou et al, 2020).…”

“…This perspective has often prompted researchers to prioritize studying phenotypes that have been measured in large samples, even if the available phenotypic measures are shallow or unidimensional. This strategy has proven successful at increasing the number of variants and genomic loci associated with AUBs (Gelernter et al, 2019; Kranzler et al, 2019; Liu et al, 2019; Sanchez-Roige et al, 2019; Walters et al, 2018; Zhou et al, 2023; Zhou et al, 2020), but it has proven challenging to advance clinical or functional understanding of these statistical associations. For example, in comparison with the single significant locus found in a GWAS of alcohol dependence (AD) in approximately 50,000 individuals (Walters et al, 2018), a GWAS of PAU in over 400,000 individuals (Zhou et al, 2020) increased the number of associated risk loci to 29.…”