Yale University, New Haven, CT, USA.
VA CT Healthcare System, West Haven, CT, USA.
Addiction. 2022 Apr;117(4):1117-1127. doi: 10.1111/add.15697. Epub 2021 Oct 24.
Molecular genetic studies of alcohol and nicotine use have identified many genome-wide association study (GWAS) loci. We measured associations between drinking and smoking polygenic scores (PGS) and trajectories of alcohol and nicotine use outcomes from late childhood to early adulthood, substance-specific versus broader-liability PGS effects, and if PGS performance varied for consumption versus problematic substance use.
DESIGN, SETTING, PARTICIPANTS AND MEASUREMENTS: We fitted latent growth curve models with structured residuals to scores on measures of alcohol and nicotine use and problems from ages 14 to 34 years. We then estimated associations between the intercept (initial status) and slope (rate of change) parameters and PGSs for drinks per week (DPW), problematic alcohol use (PAU), cigarettes per day (CPD) and ever being a regular smoker (SMK), controlling for sex and genetic principal components. All data were analyzed in the United States. PGSs were calculated for participants of the Minnesota Twin Family Study (n = 3225) using results from the largest GWAS of alcohol and nicotine consumption and problematic use to date.
Each PGS was associated with trajectories of use for their respective substances [i.e. DPW (β = 0.08; β = 0.02-0.12) and PAU (β = 0.12; β = -0.02 to 0.31) for alcohol; CPD (β = 0.08; β = 0.04-0.14) and SMK (β = 0.18; β = 0.05-0.36) for nicotine]. The PAU and SMK PGSs also exhibited cross-substance associations (i.e. PAU for nicotine-specific intercepts and SMK for alcohol intercepts and slope). All identified SMK PGS effects remained as significant predictors of nicotine and alcohol trajectories (β = 0.15; β = 0.02-0.33), even after adjusting for the respective effects of all other PGSs.
Substance use-related polygenic scores (PGSs) vary in the strength and generality versus specificity of their associations with substance use and problems over time. The regular smoking PGS appears to be a robust predictor of substance use trajectories and seems to measure both nicotine-specific and non-specific genetic liability for substance use, and potentially externalizing problems in general.
酒精和尼古丁使用的分子遗传研究已经确定了许多全基因组关联研究（GWAS）位点。我们测量了从儿童后期到成年早期的饮酒和吸烟多基因评分（PGS）与酒精和尼古丁使用结果之间的关联，特定物质与更广泛责任 PGS 效应，以及 PGS 表现是否因消费与有问题的物质使用而有所不同。
设计、设置、参与者和测量：我们使用结构残差拟合了带有结构残差的潜在增长曲线模型，以衡量从 14 岁到 34 岁的酒精和尼古丁使用和问题的得分。然后，我们根据每周饮酒量（DPW）、酒精使用障碍（PAU）、每日吸烟量（CPD）和是否经常吸烟（SMK）的截距（初始状态）和斜率（变化率）参数，以及性别和遗传主成分，估计了 PGS 与这些参数之间的关联。所有数据均在美国进行分析。PGS 是使用迄今为止最大的酒精和尼古丁消费和有问题使用 GWAS 的结果，为明尼苏达双胞胎家庭研究（n=3225）的参与者计算得出的。
每个 PGS 都与各自物质的使用轨迹相关联[即 DPW（β=0.08；β=0.02-0.12）和 PAU（β=0.12；β=0.02-0.31）对于酒精；CPD（β=0.08；β=0.04-0.14）和 SMK（β=0.18；β=0.05-0.36）对于尼古丁]。PAU 和 SMK PGS 也表现出跨物质的关联（即 PAU 对尼古丁特异性截距，SMK 对酒精截距和斜率）。即使调整了所有其他 PGS 的各自影响，所有确定的 SMK PGS 效应仍然是尼古丁和酒精轨迹的显著预测因素（β=0.15；β=0.02-0.33）。
随着时间的推移，与物质使用相关的多基因评分（PGS）在与物质使用和问题的关联的强度、普遍性与特异性方面存在差异。定期吸烟 PGS 似乎是物质使用轨迹的有力预测指标，并且似乎可以衡量尼古丁特异性和非特异性物质使用的遗传倾向，以及一般的外化问题。
