Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, Atlanta, GA, USA.
Smith Lab, Department of Gynecology and Obstetrics, Emory University School of Medicine, Atlanta, GA, USA.
Nicotine Tob Res. 2021 Nov 5;23(12):2102-2109. doi: 10.1093/ntr/ntab105.
Heritability estimates of nicotine dependence (ND) range from 40% to 70%, but discovery GWAS of ND are underpowered and have limited predictive utility. In this work, we leverage genetically correlated traits and diseases to increase the accuracy of polygenic risk prediction.
We employed a multi-trait model using summary statistic-based best linear unbiased predictors (SBLUP) of genetic correlates of DSM-IV diagnosis of ND in 6394 individuals of European Ancestry (prevalence = 45.3%, %female = 46.8%, µ age = 40.08 [s.d. = 10.43]) and 3061 individuals from a nationally-representative sample with Fagerström Test for Nicotine Dependence symptom count (FTND; 51.32% female, mean age = 28.9 [s.d. = 1.70]). Polygenic predictors were derived from GWASs known to be phenotypically and genetically correlated with ND (i.e., Cigarettes per Day [CPD], the Alcohol Use Disorders Identification Test [AUDIT-Consumption and AUDIT-Problems], Neuroticism, Depression, Schizophrenia, Educational Attainment, Body Mass Index [BMI], and Self-Perceived Risk-Taking); including Height as a negative control. Analyses controlled for age, gender, study site, and the first 10 ancestral principal components.
The multi-trait model accounted for 3.6% of the total trait variance in DSM-IV ND. Educational Attainment (β = -0.125; 95% CI: [-0.149,-0.101]), CPD (0.071 [0.047,0.095]), and Self-Perceived Risk-Taking (0.051 [0.026,0.075]) were the most robust predictors. PGS effects on FTND were limited.
Risk for ND is not only polygenic, but also pleiotropic. Polygenic effects on ND that are accessible by these traits are limited in size and act additively to explain risk.
These findings enhance our understanding of inherited genetic factors for nicotine dependence. The data show that genome-wide association study (GWAS) findings across pre- and comorbid conditions of smoking are differentially associated with nicotine dependence and that when combined explain significantly more trait variance. These findings underscore the utility of multivariate approaches to understand the validity of polygenic scores for nicotine dependence, especially as the power of GWAS of broadly-defined smoking behaviors increases. Realizing the potential of GWAS to inform complex smoking behaviors will require similar theory-driven models that reflect the myriad of mechanisms that drive individual differences.
尼古丁依赖（ND）的遗传力估计范围在 40%到 70%之间，但 ND 的发现 GWAS 效力不足，预测效用有限。在这项工作中，我们利用遗传相关特征和疾病来提高多基因风险预测的准确性。
我们使用了一种多特征模型，该模型使用了基于汇总统计的最佳线性无偏预测因子（SBLUP），对 6394 名欧洲血统个体（患病率=45.3%，女性比例=46.8%，µ年龄=40.08 [s.d.=10.43]）和 3061 名来自全国代表性样本的个体进行了 DSM-IV ND 诊断的遗传相关性研究，这些个体的 Fagerström 尼古丁依赖测试症状数（FTND；51.32%女性，平均年龄=28.9 [s.d.=1.70]）。多基因预测因子来自与 ND 表型和遗传相关的 GWAS（即，每天吸烟量 [CPD]、酒精使用障碍识别测试 [AUDIT-Consumption 和 AUDIT-Problems]、神经质、抑郁、精神分裂症、教育程度、体重指数 [BMI] 和自我感知风险承担）；包括身高作为负对照。分析控制了年龄、性别、研究地点和前 10 个祖先主成分。
多特征模型解释了 DSM-IV ND 总特征变异的 3.6%。教育程度（β=-0.125；95%CI：[-0.149，-0.101]）、CPD（0.071 [0.047，0.095]）和自我感知风险承担（0.051 [0.026，0.075]）是最可靠的预测因子。PGS 对 FTND 的影响有限。
ND 的风险不仅是多基因的，而且是多效性的。通过这些特征可获得的 ND 的多基因效应在大小上是有限的，并以累加的方式解释风险。
这些发现增进了我们对尼古丁依赖遗传因素的理解。这些数据表明，在吸烟的预先和并发条件下进行的全基因组关联研究（GWAS）发现与尼古丁依赖的相关性不同，并且当组合在一起时，可显著解释更多的特征变异。这些发现强调了使用多变量方法来理解尼古丁依赖的多基因评分的有效性，特别是随着广泛定义的吸烟行为的 GWAS 效力的提高。要实现 GWAS 对复杂吸烟行为的潜在作用，就需要类似的理论驱动模型，反映驱动个体差异的众多机制。
