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Pathways to smoking behaviours: biological insights from the Tobacco and Genetics Consortium meta-analysis

机译:吸烟行为的途径:烟草与遗传学协会荟萃分析的生物学见解

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摘要

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.
机译:通过对74 053个个体的烟草和遗传学联盟(TAG)样本中的几种吸烟行为进行基因和途径分析,共涉及21个基因和若干生物途径链。使用在基于基因组的全基因组研究软件的基于知识的挖掘系统中实施的基于杂交集的测试(HYST)进行分析。十五个基因是新颖的,在原始TAG分析中未使用基于单核苷酸多态性的方法检测到。对于抽烟量,有14个基因通过了0.05的错误发现率(经多次测试校正),且最高关联信号位于IREB2基因上(P = 1.57E-37)。三个基因组位点与曾经吸烟有关。最高信号位于11p14的非编码反义RNA转录本BDNF-AS(P = 6.25E-07)。 SLC25A21基因(P = 2.09E-08)在戒烟分析中产生了最高的关联信号。在开始时的年龄分析中,19q13非编码RNA基因座超过了全基因组范围的意义(P = 1.33E-06)。属于神经元系统途径的途径含有表达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,在途径分析中产生的P值最小。吸烟量(最低P = 4.90E-42)。此外,与从未吸烟者相比,曾经吸烟者的遗传变异被发现丰富了调节细胞周期,有丝分裂DNA复制,轴突生长和突触可塑性的“癌症途径地铁图”(最低P = 1.61E-07)。 。此外,这些途径还与吸烟量显着相关(最低P = 4.28E-17)。我们的研究结果揭示了可预防死亡的世界领先原因之一,并开辟了通往潜在治疗靶点的道路。这些结果有助于解读吸烟与其他遗传特征易感的其他疾病特征(如抑郁症和癌症)的生物学基础。

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