Trajectories of genetic risk across dimensions of alcohol use behaviors.

Jeanne E Savage, Fazil Aliev, Peter B Barr, Maia Choi, Gabin Drouard, Megan E Cooke, Sally I Kuo, Mallory Stephenson, Sarah J Brislin, Zoe E Neale, Antti Latvala, Richard J Rose, Jaakko Kaprio, Danielle M Dick, Jacquelyn Meyers, Jessica E Salvatore, Danielle Posthuma
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Abstract

Background: Alcohol use behaviors (AUBs) manifest in a variety of normative and problematic ways across the life course, all of which are heritable. Twin studies show that genetic influences on AUBs change across development, but this is usually not considered in research identifying and investigating the genes linked to AUBs.

Aims: Understanding the dynamics of how genes shape AUBs could point to critical periods in which interventions may be most effective and provide insight into the mechanisms behind AUB-related genes. In this project, we investigate how genetic associations with AUBs unfold across development using longitudinal modelling of polygenic scores (PGSs).

Design: Using results from genome-wide association studies (GWASs), we created PGSs to index individual-level genetic risk for multiple AUB-related dimensions: Consumption , Problems , a variable pattern of drinking associated with a preference for beer ( BeerPref ), and externalizing behavior ( EXT ). We created latent growth curve models and tested PGSs as predictors of latent growth factors (intercept, slope, quadratic) underlying trajectories of AUBs.

Setting: PGSs were derived in six longitudinal epidemiological cohorts from the US, UK, and Finland.

Participants: Participant data were obtained from AddHealth, ALSPAC, COGA, FinnTwin12, the older Finnish Twin Cohort, and Spit for Science (total N = 19,194). These cohorts included individuals aged 14 to 67, with repeated measures collected over a span of 4 to 36 years.

Measurements: Primary measures included monthly frequency of typical alcohol consumption (CON) and heavy episodic drinking (HED).

Findings: Results indicated that higher PGSs for all AUBs are robustly associated with higher mean levels of CON and/or HED (B = 0.064-0.333, p < 3.09E-04). However, these same genetic indices were largely not associated with drinking trajectories across cohorts. In the meta-analysis, only PGSs for chronic alcohol Problems consistently predicted a steeper slope (increasing trajectory) of CON across time (B = 0.470, p = 4.20E-06).

Conclusions: The results indicate that genetic associations with AUBs not only differ between behaviors, but also across developmental time points and across cohorts. Genetic studies that take such heterogeneity into account are needed to better represent the underlying etiology of AUBs. Individual-level genetic profiles may be useful to point to personalized intervention timelines, particularly for individuals with high alcohol Problems genetic risk scores.

酒精使用行为各维度的遗传风险轨迹。
背景:酒精使用行为(aub)在整个生命过程中以各种规范和有问题的方式表现出来,所有这些都是可遗传的。双胞胎研究表明,在发育过程中,基因对aub的影响会发生变化,但在识别和调查与aub相关的基因时,通常不会考虑到这一点。目的:了解基因如何塑造aub的动力学可以指出干预可能最有效的关键时期,并提供对aub相关基因背后机制的见解。在这个项目中,我们使用多基因评分(pgs)纵向建模来研究与aub的遗传关联如何在发育过程中展开。设计:利用全基因组关联研究(GWASs)的结果,我们创建了pgs,以索引多个aub相关维度的个人水平遗传风险:消费、问题、与啤酒偏好相关的可变饮酒模式(BeerPref)和外化行为(EXT)。我们建立了潜在生长曲线模型,并测试了pgs作为aub潜在生长因子(截距、斜率、二次曲线)潜在轨迹的预测因子。背景:pgs来自美国、英国和芬兰的6个纵向流行病学队列。参与者:参与者数据来自AddHealth、ALSPAC、COGA、FinnTwin12、老年芬兰双胞胎队列和Spit for Science(总N = 19,194)。这些队列包括14至67岁的个体,在4至36年的时间里收集了重复的测量数据。测量:主要测量包括每月典型酒精消费(CON)和重度间歇性饮酒(HED)的频率。结果表明,所有aub患者较高的pgs与较高的CON和/或HED平均水平密切相关(B = 0.064-0.333, p < 3.09E-04)。然而,这些相同的遗传指数在很大程度上与人群的饮酒轨迹无关。在荟萃分析中,只有慢性酒精问题的pgs一致预测CON随时间的斜率更陡(增加轨迹)(B = 0.470, p = 4.20E-06)。结论:研究结果表明,与aub的遗传关联不仅在行为之间存在差异,而且在发育时间点和群体之间也存在差异。需要考虑到这种异质性的遗传学研究来更好地代表aub的潜在病因。个体水平的遗传概况可能有助于指出个性化的干预时间表,特别是对于酒精问题遗传风险评分较高的个体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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