Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, USA.
Lieber Institute for Brain Development (LIBD), Baltimore, MD, USA.
Neuropsychopharmacology. 2024 Oct;49(11):1749-1757. doi: 10.1038/s41386-024-01885-4. Epub 2024 Jun 4.
Smoking is a leading cause of preventable morbidity and mortality. Smoking is heritable, and genome-wide association studies (GWASs) of smoking behaviors have identified hundreds of significant loci. Most GWAS-identified variants are noncoding with unknown neurobiological effects. We used genome-wide genotype, DNA methylation, and RNA sequencing data in postmortem human nucleus accumbens (NAc) to identify cis-methylation/expression quantitative trait loci (meQTLs/eQTLs), investigate variant-by-cigarette smoking interactions across the genome, and overlay QTL evidence at smoking GWAS-identified loci to evaluate their regulatory potential. Active smokers (N = 52) and nonsmokers (N = 171) were defined based on cotinine biomarker levels and next-of-kin reporting. We simultaneously tested variant and variant-by-smoking interaction effects on methylation and expression, separately, adjusting for biological and technical covariates and correcting for multiple testing using a two-stage procedure. We found >2 million significant meQTL variants (p< 0.05) corresponding to 41,695 unique CpGs. Results were largely driven by main effects, and five meQTLs, mapping to NUDT12, FAM53B, RNF39, and ADRA1B, showed a significant interaction with smoking. We found 57,683 significant eQTL variants for 958 unique eGenes (p< 0.05) and no smoking interactions. Colocalization analyses identified loci with smoking-associated GWAS variants that overlapped meQTLs/eQTLs, suggesting that these heritable factors may influence smoking behaviors through functional effects on methylation/expression. One locus containing MUSTN1 and ITIH4 colocalized across all data types (GWAS, meQTL, and eQTL). In this first genome-wide meQTL map in the human NAc, the enriched overlap with smoking GWAS-identified genetic loci provides evidence that gene regulation in the brain helps explain the neurobiology of smoking behaviors.
吸烟是可预防的发病率和死亡率的主要原因。吸烟具有遗传性,吸烟行为的全基因组关联研究(GWAS)已经确定了数百个重要的位点。大多数 GWAS 确定的变体是非编码的,具有未知的神经生物学效应。我们使用全基因组基因型、DNA 甲基化和 RNA 测序数据,在死后的人类伏隔核(NAc)中识别顺式甲基化/表达数量性状基因座(meQTLs/eQTLs),研究全基因组范围内的变体与吸烟的相互作用,并覆盖在吸烟 GWAS 确定的基因座上的 QTL 证据,以评估其调节潜力。根据可替宁生物标志物水平和近亲报告,将活跃吸烟者(N=52)和不吸烟者(N=171)定义。我们同时测试了变体和变体与吸烟的相互作用对甲基化和表达的影响,分别调整了生物学和技术协变量,并使用两阶段程序对多重测试进行了校正。我们发现了超过 200 万个具有统计学意义的 meQTL 变体(p<0.05),对应于 41695 个独特的 CpG。结果主要由主要效应驱动,5 个 meQTL 映射到 NUDT12、FAM53B、RNF39 和 ADRA1B,与吸烟存在显著的相互作用。我们发现了 57683 个具有统计学意义的 eQTL 变体,对应于 958 个独特的 eGenes(p<0.05),且没有吸烟的相互作用。共定位分析确定了与吸烟相关的 GWAS 变体与 meQTL/eQTL 重叠的基因座,表明这些可遗传因素可能通过对甲基化/表达的功能影响,影响吸烟行为。一个包含 MUSTN1 和 ITIH4 的基因座在所有数据类型(GWAS、meQTL 和 eQTL)中都发生了共定位。在人类 NAc 的全基因组范围内首次进行的 meQTL 图谱中,与吸烟 GWAS 确定的遗传基因座的丰富重叠提供了证据,表明大脑中的基因调控有助于解释吸烟行为的神经生物学。