Correction: Chromatin architecture in addiction circuitry identifies risk genes and potential biological mechanisms underlying cigarette smoking and alcohol use traits.
Correction: Chromatin architecture in addiction circuitry identifies risk genes and potential biological mechanisms underlying cigarette smoking and alcohol use traits.
复制标题
更正：成瘾回路中的染色质结构识别了吸烟和饮酒特征背后的风险基因和潜在生物机制。
DOI：
10.1038/s41380-022-01678-5
复制
发表时间：
2022
影响因子：
11
通讯作者：
Won,Hyejung
中科院分区：
文献类型：
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作者：
Sey,NancyYA;Hu,Benxia;Iskhakova,Marina;Lee,Sool;Sun,Huaigu;Shokrian,Neda;BenHutta,Gabriella;Marks,JesseA;Quach,BryanC;Johnson,EricO;Hancock,DanaB;Akbarian,Schahram;Won,Hyejung
报告了Nancy YA Sey，Benxia Hu，Marina Iskhakova，Sool Lee，Huaigu Sun，Neda Shokrian，Gabriella Ben Hutta，Jesse A.作者：Bryan C. Quach，Eric O.约翰逊，达纳B。汉考克，Schahram Akbarian和Hyejung Won（分子精神病学，2022 [Jul]，2027 [7]，3085-3094）。在原始文章中，在图3B中，将打印错误Hippocmapus更正为Hippocampus。原文已更正。(The原始文章的以下摘要出现在记录2022-55128-001中）。吸烟和饮酒是全世界使用最普遍的物质之一，在可预防的发病率和死亡率中占很大比例，突出了了解其病因的公共卫生意义。全基因组关联研究（GWAS）已经成功地确定了与吸烟和饮酒性状相关的遗传变异。然而，绝大多数风险变异存在于基因组的非编码区，其靶基因和神经生物学机制尚不清楚。染色体构象图谱可以通过绘制风险相关调控变体与靶基因的相互作用谱来解决这一知识缺口。为了研究与吸烟和饮酒性状相关的常见变异的功能影响，我们将基于皮质和新生成的中脑多巴胺能神经元Hi-C数据集构建的Hi-C耦合MAGMA（H-MAGMA）应用于尼古丁依赖、每天吸烟、有问题的饮酒和每周饮酒的GWAS汇总统计。已确定的风险基因映射到与吸烟和饮酒特征相关的关键途径，包括药物代谢过程和神经元凋亡。风险基因在皮质多巴胺能、中脑多巴胺能、GABA能和多巴胺能神经元中高度表达，表明它们是理解遗传风险因素影响吸烟和饮酒的机制的相关细胞类型。最后，我们确定了吸烟和饮酒性状之间的多效性基因，假设它们可能揭示了物质不可知的，共享的成瘾神经生物学机制。多效性基因的数量在多巴胺能神经元中比在皮质神经元中高约26倍，强调了多巴胺能上行通路在介导一般成瘾表型中的关键作用。总的来说，大脑区域和神经元亚型特异性3D基因组结构通过将遗传风险因素与其靶基因联系起来，有助于完善吸烟，酒精和一般成瘾表型的神经生物学假设。（PsycInfo数据库记录（c）2023阿帕，保留所有权利）
Reports an error in" Chromatin architecture in addiction circuitry identifies risk genes and potential biological mechanisms underlying cigarette smoking and alcohol use traits" by Nancy YA Sey, Benxia Hu, Marina Iskhakova, Sool Lee, Huaigu Sun, Neda Shokrian, Gabriella Ben Hutta, Jesse A. Marks, Bryan C. Quach, Eric O. Johnson, Dana B. Hancock, Schahram Akbarian and Hyejung Won (Molecular Psychiatry, 2022 [Jul], Vol 27 [7], 3085-3094). In the original article, in Fig. 3B, a typo Hippocmapus was corrected to Hippocampus. The original article has been corrected.(The following abstract of the original article appeared in record 2022-55128-001). Cigarette smoking and alcohol use are among the most prevalent substances used worldwide and account for a substantial proportion of preventable morbidity and mortality, underscoring the public health significance of understanding their etiology. Genome-wide association studies (GWAS) have successfully identified genetic variants associated with cigarette smoking and alcohol use traits. However, the vast majority of risk variants reside in non-coding regions of the genome, and their target genes and neurobiological mechanisms are unknown. Chromosomal conformation mappings can address this knowledge gap by charting the interaction profiles of risk-associated regulatory variants with target genes. To investigate the functional impact of common variants associated with cigarette smoking and alcohol use traits, we applied Hi-C coupled MAGMA (H-MAGMA) built upon cortical and newly generated midbrain dopaminergic neuronal Hi-C datasets to GWAS summary statistics of nicotine dependence, cigarettes per day, problematic alcohol use, and drinks per week. The identified risk genes mapped to key pathways associated with cigarette smoking and alcohol use traits, including drug metabolic processes and neuronal apoptosis. Risk genes were highly expressed in cortical glutamatergic, midbrain dopaminergic, GABAergic, and serotonergic neurons, suggesting them as relevant cell types in understanding the mechanisms by which genetic risk factors influence cigarette smoking and alcohol use. Lastly, we identified pleiotropic genes between cigarette smoking and alcohol use traits under the assumption that they may reveal substance-agnostic, shared neurobiological mechanisms of addiction. The number of pleiotropic genes was~ 26-fold higher in dopaminergic neurons than in cortical neurons, emphasizing the critical role of ascending dopaminergic pathways in mediating general addiction phenotypes. Collectively, brain region-and neuronal subtype-specific 3D genome architecture helps refine neurobiological hypotheses for smoking, alcohol, and general addiction phenotypes by linking genetic risk factors to their target genes.(PsycInfo Database Record (c) 2023 APA, all rights reserved)