Minicã C C, Mbarek H, Pool R, Dolan C V, Boomsma D I, Vink J M
Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands.
Mol Psychiatry. 2017 Jan;22(1):82-88. doi: 10.1038/mp.2016.20. Epub 2016 Mar 29.
By running gene and pathway analyses for several smoking behaviours in the Tobacco and Genetics Consortium (TAG) sample of 74 053 individuals, 21 genes and several chains of biological pathways were implicated. Analyses were carried out using the HYbrid Set-based Test (HYST) as implemented in the Knowledge-based mining system for Genome-wide Genetic studies software. Fifteen genes are novel and were not detected with the single nucleotide polymorphism-based approach in the original TAG analysis. For quantity smoked, 14 genes passed the false discovery rate of 0.05 (corrected for multiple testing), with the top association signal located at the IREB2 gene (P=1.57E-37). Three genomic loci were significantly associated with ever smoked. The top signal is located at the noncoding antisense RNA transcript BDNF-AS (P=6.25E-07) on 11p14. The SLC25A21 gene (P=2.09E-08) yielded the top association signal in the analysis of smoking cessation. The 19q13 noncoding RNA locus exceeded the genome-wide significance in the analysis of age at initiation (P=1.33E-06). Pathways belonging to the Neuronal system pathways, harbouring the nicotinic acetylcholine receptor genes expressing the α (CHRNA 1-9), β (CHRNB 1-4), γ, δ and ɛ subunits, yielded the smallest P-values in the pathway analysis of the quantity smoked (lowest P=4.90E-42). Additionally, pathways belonging to 'a subway map of cancer pathways' regulating the cell cycle, mitotic DNA replication, axon growth and synaptic plasticity were found significantly enriched for genetic variants in ever smokers relative to never smokers (lowest P=1.61E-07). In addition, these pathways were also significantly associated with the quantity smoked (lowest P=4.28E-17). Our results shed light on one of the world's leading causes of preventable death and open a path to potential therapeutic targets. These results are informative in decoding the biological bases of other disease traits, such as depression and cancers, with which smoking shares genetic vulnerabilities.
通过对烟草与遗传学联盟（TAG）中74053名个体的多种吸烟行为进行基因和通路分析，发现了21个基因以及几条生物通路链。分析使用了基于知识的全基因组遗传研究软件中实现的基于杂交集的测试（HYST）。15个基因是新发现的，在TAG最初的单核苷酸多态性分析中未被检测到。对于吸烟量，14个基因通过了错误发现率为0.05（经多重检验校正）的检验，最强关联信号位于IREB2基因处（P = 1.57E - 37）。三个基因组位点与曾经吸烟显著相关。最强信号位于11p14上的非编码反义RNA转录本BDNF-AS处（P = 6.25E - 07）。SLC25A21基因（P = 2.09E - 08）在戒烟分析中产生了最强关联信号。19q13非编码RNA位点在开始吸烟年龄的分析中超过了全基因组显著性水平（P = 1.33E - 06）。属于神经系统通路的通路，包含表达α（CHRNA 1 - 9）、β（CHRNB 1 - 4）、γ、δ和ɛ亚基的烟碱型乙酰胆碱受体基因，在吸烟量的通路分析中产生了最小的P值（最低P = 4.90E - 42）。此外，相对于从不吸烟者，属于“癌症通路的地铁图”且调节细胞周期、有丝分裂DNA复制、轴突生长和突触可塑性的通路在曾经吸烟者中发现基因变异显著富集（最低P = 1.61E - 07）。此外，这些通路也与吸烟量显著相关（最低P = 4.28E - 17）。我们的结果揭示了世界上可预防死亡的主要原因之一，并为潜在治疗靶点开辟了道路。这些结果对于解读其他疾病特征（如抑郁症和癌症）的生物学基础具有参考价值，吸烟与这些疾病具有共同的遗传易感性。
