Integrative gene network analysis provides novel regulatory relationships, genetic contributions and susceptible targets in autism spectrum disorders.
Integrative gene network analysis provides novel regulatory relationships, genetic contributions and susceptible targets in autism spectrum disorders.
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DOI：
10.1016/j.gene.2012.01.020
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发表时间：
2012-04-01
期刊：
影响因子：
3.5
通讯作者：
Rennert OM
中科院分区：
文献类型：
--
作者：
Lee TL;Raygada MJ;Rennert OM
自闭症谱系障碍(ASD)是一组表现出社会动力、沟通/语言技能和刻板印象行为障碍的疾病。尽管已经通过各种方法鉴定了越来越多的候选基因和分子相互作用，但其发病机制仍然难以捉摸。基于临床观察、可访问的GWAs数据和表达数据集，我们确定了ASDS基因候选。整合基因网络和一种新的以CNV为中心的节点网络(CNN)分析方法突出了ASD相关的关键元件和生物学过程。功能分析确定了神经功能，包括突触胆碱能受体(CHRNA)家族、多巴胺受体(DRD2)，以及社会行为与催产素相关途径之间的相关性。CNN对全基因组遗传和表达数据的分析发现，与PTEN/TSC1/FMR1和mTOR/PI3K调控相关的遗传相关簇。综合分析确定了网络的潜在调节因素，特别是肿瘤坏死因子和β-雌二醇，这表明在自闭症中可能起着核心作用。我们的数据提供了关于潜在疾病机制的信息，以及可能产生新假设的关键调控因素和诊断分子生物标记物。
Autism spectrum disorders (ASDs) are a group of diseases exhibiting impairment in social drive, communication/language skills and stereotyped behaviors. Though an increased number of candidate genes and molecular interactions have been identified by various approaches, the pathogenesis remains elusive. Based on clinical observations, data from accessible GWAS and expression datasets we identified ASDs gene candidates. Integrative gene network and a novel CNV-centric Node Network (CNN) analysis method highlighted ASDs-associated key elements and biological processes. Functional analysis identified neurological functions including synaptic cholinergic receptor (CHRNA) families, dopamine receptor (DRD2), and correlations between social behavior and oxytocin related pathways. CNN analysis of genome-wide genetic and expression data identified inheritance-related clusters related to PTEN/TSC1/FMR1 and mTor/PI3K regulation. Integrative analysis identified potential regulators of networks, specifically TNF and beta-estradiol, suggesting a potential central role in ASDs. Our data provides information on potential disease mechanisms, and key regulators that may generate novel postulations, and diagnostic molecular biomarkers.
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影响因子：
1.9
作者：
Ma D;Salyakina D;Jaworski JM;Konidari I;Whitehead PL;Andersen AN;Hoffman JD;Slifer SH;Hedges DJ;Cukier HN;Griswold AJ;McCauley JL;Beecham GW;Wright HH;Abramson RK;Martin ER;Hussman JP;Gilbert JR;Cuccaro ML;Haines JL;Pericak-Vance MA
通讯作者：
Pericak-Vance MA
影响因子：
2.8
作者：
Pardo, CA;Vargas, DL;Zimmerman, AW
通讯作者：
Zimmerman, AW
DOI：
10.1016/j.chc.2008.06.010
发表时间：
2008-10-01
影响因子：
2.4
作者：
Posey, David J.;Erickson, Craig A.;McDougle, Christopher J.
通讯作者：
McDougle, Christopher J.
影响因子：
4
作者：
Serajee, FJ;Zhong, H;Huq, AHMM
通讯作者：
Huq, AHMM
影响因子：
11
作者：
Coutinho, AM;Oliveira, G;Vicente, AM
通讯作者：
Vicente, AM