Assessing the Role of Long Noncoding RNA in Nucleus Accumbens in Subjects With Alcohol Dependence.
Assessing the Role of Long Noncoding RNA in Nucleus Accumbens in Subjects With Alcohol Dependence.
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DOI：
10.1111/acer.14479
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发表时间：
2020-12
期刊：
影响因子：
--
通讯作者：
Vladimirov VI
中科院分区：
文献类型：
--
作者：
Drake J;McMichael GO;Vornholt ES;Cresswell K;Williamson V;Chatzinakos C;Mamdani M;Hariharan S;Kendler KS;Kalsi G;Riley BP;Dozmorov M;Miles MF;Bacanu SA;Vladimirov VI
长链非编码RNA（lncRNA）与酒精使用的病因学有关。由于lncRNA为转录组提供了另一层复杂性，因此评估它们在大脑中的表达是了解lncRNA在酒精使用和成瘾中功能的第一个关键步骤。因此，我们试图在一个大的死后酒精脑样本中的丘脑核（NAc）中分析lncRNA表达。通过回归模型评估了41名酒精依赖（AD）受试者和41名对照者NAc中的LncRNA和蛋白编码基因（PCG）表达。加权基因共表达网络分析用于鉴定lncRNA和PCG网络（即，模块）与AD显著相关。在重要模块中，关键网络基因（即，中心）。通过Pearson相关性将lncRNA和PCG中心关联起来，以阐明lncRNA的潜在生物学功能。将lncRNA和PCG中心与GWAS数据进一步整合以鉴定表达数量性状基因座（eQTL）。在Bonferroni校正p值≤ 0.05时，我们鉴定了19个lncRNA和5个PCG重要模块，这些模块富集了神经元和免疫相关过程。在这些模块中，我们分别进一步鉴定了86个和315个PCG和lncRNA枢纽。在10%的错误发现率（FDR）下，lncRNA和PCG中心之间的相关性分析显示3，125个正相关和1，860个负相关。整合枢纽与基因型数据确定了243个eQTL，分别影响39个和204个PCG和lncRNA枢纽的表达。我们的研究确定了与NAc中AD显著相关的lncRNA和基因网络，协调lncRNA和mRNA共表达变化，突出了lncRNA的潜在调控功能，我们的遗传（cis-eQTL）分析为AD的病因学机制提供了新的见解。酒精使用障碍（AUD）是一种使人衰弱的疾病，没有可靠和有效的治疗方法。然而，研究大脑转录组可能有助于阐明AUD的神经病理学。使用基因网络方法，我们可以一睹AUD患者编码和非编码RNA之间复杂的相互作用，并测试临床相关风险遗传因素对这些相互作用的调节作用。此外，通过检查过去的研究和进行富集，将与AUD相关的基因和遗传元件置于背景中
Long noncoding RNA (lncRNA) have been implicated in the etiology of alcohol use. Since lncRNA provide another layer of complexity to the transcriptome, assessing their expression in the brain is the first critical step toward understanding lncRNA functions in alcohol use and addiction. Thus, we sought to profile lncRNA expression in the nucleus accumbens (NAc) in a large postmortem alcohol brain sample. LncRNA and protein‐coding gene (PCG) expressions in the NAc from 41 subjects with alcohol dependence (AD) and 41 controls were assessed via a regression model. Weighted gene coexpression network analysis was used to identify lncRNA and PCG networks (i.e., modules) significantly correlated with AD. Within the significant modules, key network genes (i.e., hubs) were also identified. The lncRNA and PCG hubs were correlated via Pearson correlations to elucidate the potential biological functions of lncRNA. The lncRNA and PCG hubs were further integrated with GWAS data to identify expression quantitative trait loci (eQTL). At Bonferroni adj. p‐value ≤ 0.05, we identified 19 lncRNA and 5 PCG significant modules, which were enriched for neuronal and immune‐related processes. In these modules, we further identified 86 and 315 PCG and lncRNA hubs, respectively. At false discovery rate (FDR) of 10%, the correlation analyses between the lncRNA and PCG hubs revealed 3,125 positive and 1,860 negative correlations. Integration of hubs with genotype data identified 243 eQTLs affecting the expression of 39 and 204 PCG and lncRNA hubs, respectively. Our study identified lncRNA and gene networks significantly associated with AD in the NAc, coordinated lncRNA and mRNA coexpression changes, highlighting potentially regulatory functions for the lncRNA, and our genetic (cis‐eQTL) analysis provides novel insights into the etiological mechanisms of AD. Alcohol use disorder (AUD) is a debilitating disease with no reliable and efficacious treatment. However, studying the brain transcriptome may help elucidate the neuropathology of AUD. Using gene network approaches, we provide a glimpse into the complex interactions between coding and non‐coding RNA from patients with AUD and test the moderating effect of clinically relevant risk genetic elements on these interactions. Furthermore, genes and genetic elements associated with AUD were contextualized by examining past studies and conducting enrichment
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影响因子：
37.3
作者：
Gibb EA;Brown CJ;Lam WL
通讯作者：
Lam WL
DOI：
10.1111/acer.13362
发表时间：
2017-05
期刊：
Alcoholism, clinical and experimental research
影响因子：
--
作者：
Adkins AE;Hack LM;Bigdeli TB;Williamson VS;McMichael GO;Mamdani M;Edwards AC;Aliev F;Chan RF;Bhandari P;Raabe RC;Alaimo JT;Blackwell GG;Moscati A;Poland RS;Rood B;Patterson DG;Walsh D;Collaborative Study of the Genetics of Alcoholism Consortium;Whitfield JB;Zhu G;Montgomery GW;Henders AK;Martin NG;Heath AC;Madden PAF;Frank J;Ridinger M;Wodarz N;Soyka M;Zill P;Ising M;Nöthen MM;Kiefer F;Rietschel M;German Study of the Genetics of Addiction Consortium;Gelernter J;Sherva R;Koesterer R;Almasy L;Zhao H;Kranzler HR;Farrer LA;Maher BS;Prescott CA;Dick DM;Bacanu SA;Mathies LD;Davies AG;Vladimirov VI;Grotewiel M;Bowers MS;Bettinger JC;Webb BT;Miles MF;Kendler KS;Riley BP
通讯作者：
Riley BP
DOI：
10.1111/acer.12341
发表时间：
2014-04
期刊：
Alcoholism, clinical and experimental research
影响因子：
--
作者：
Sutherland GT;Sheedy D;Sheahan PJ;Kaplan W;Kril JJ
通讯作者：
Kril JJ
影响因子：
10.6
作者：
Crews, Fulton T.;Qin, Liya;Sheedy, Donna;Vetreno, Ryan P.;Zou, Jian
通讯作者：
Zou, Jian
影响因子：
4.5
作者：
de Baumont, Angelica;Maschietto, Mariana;Brentani, Helena
通讯作者：
Brentani, Helena