Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado; Department of Molecular, Cellular, and Developmental Biology, University of Colorado Boulder, Boulder, Colorado.
Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania.
Biol Psychiatry. 2019 Jun 1;85(11):946-955. doi: 10.1016/j.biopsych.2018.11.024. Epub 2018 Dec 6.
Smoking and alcohol use have been associated with common genetic variants in multiple loci. Rare variants within these loci hold promise in the identification of biological mechanisms in substance use. Exome arrays and genotype imputation can now efficiently genotype rare nonsynonymous and loss of function variants. Such variants are expected to have deleterious functional consequences and to contribute to disease risk.
We analyzed ∼250,000 rare variants from 16 independent studies genotyped with exome arrays and augmented this dataset with imputed data from the UK Biobank. Associations were tested for five phenotypes: cigarettes per day, pack-years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted stratified heritability analyses, single-variant tests, and gene-based burden tests of nonsynonymous/loss-of-function coding variants. We performed a novel fine-mapping analysis to winnow the number of putative causal variants within associated loci.
Meta-analytic sample sizes ranged from 152,348 to 433,216, depending on the phenotype. Rare coding variation explained 1.1% to 2.2% of phenotypic variance, reflecting 11% to 18% of the total single nucleotide polymorphism heritability of these phenotypes. We identified 171 genome-wide associated loci across all phenotypes. Fine mapping identified putative causal variants with double base-pair resolution at 24 of these loci, and between three and 10 variants for 65 loci. Twenty loci contained rare coding variants in the 95% credible intervals.
Rare coding variation significantly contributes to the heritability of smoking and alcohol use. Fine-mapping genome-wide association study loci identifies specific variants contributing to the biological etiology of substance use behavior.
吸烟和饮酒与多个基因座中的常见遗传变异有关。这些基因座内的稀有变异有望在确定物质使用中的生物学机制方面发挥作用。外显子组阵列和基因型推断现在可以有效地对稀有非同义变异和功能丧失变异进行基因分型。这些变异预计会产生有害的功能后果,并导致疾病风险增加。
我们分析了来自 16 项独立研究的约 25 万个稀有变体,这些变体通过外显子组阵列进行了基因分型,并通过英国生物库的推断数据扩充了这个数据集。对五个表型进行了关联测试:每天吸烟量、吸烟年包数、吸烟起始年龄、吸烟起始年龄和每周饮酒量。我们进行了分层遗传分析、单变体测试和非同义/功能丧失编码变异的基因负担测试。我们进行了一项新的精细映射分析,以减少与关联基因座相关的假定因果变异的数量。
根据表型的不同,Meta 分析样本量从 152348 到 433216 不等。稀有编码变异解释了 1.1%至 2.2%的表型变异,反映了这些表型中总单核苷酸多态性遗传率的 11%至 18%。我们在所有表型中发现了 171 个全基因组关联基因座。精细映射确定了 24 个基因座的双碱基分辨率的假定因果变异,65 个基因座中有 3 到 10 个变异。20 个基因座包含 95%置信区间内的稀有编码变异。
稀有编码变异对吸烟和饮酒使用的遗传率有显著贡献。全基因组关联研究基因座的精细映射确定了对物质使用行为生物学病因有贡献的特定变异。