Network analysis of transcriptional regulation in response to intramuscular interferon-β-1a multiple sclerosis treatment
Network analysis of transcriptional regulation in response to intramuscular interferon-β-1a multiple sclerosis treatment
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DOI：
10.1038/tpj.2010.77
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发表时间：
2012-04-01
影响因子：
2.8
通讯作者：
Zettl, U. K.
中科院分区：
文献类型：
--
作者：
Hecker, M.;Goertsches, R. H.;Zettl, U. K.
干扰素-β（IFN-β）是治疗多发性硬化症（MS）的主要药物之一。本研究的目的是表征肌内IFN-β-1a治疗诱导的复发-缓解型MS患者的转录效应。通过使用Affyphase DNA微阵列，我们获得了IFN-β给药前4周内24例MS患者外周血单核细胞的全基因组表达谱。我们确定了121个基因，与基线相比显著上调或下调，在治疗开始后1周表达变化更大。11个转录因子结合位点（TFBS）在这些基因的调控区中过度表达，包括IFN调控因子和NF-κ B的那些。然后，我们应用TFBS整合最小角度回归，一种新的综合算法，从基因表达数据和TFBS信息推导基因调控网络，重建分子相互作用的基础网络。一个以NF-κ B为中心的基因子网络在IFN-β相关副作用患者中高度表达。通过实时PCR确认表达改变，并应用文献挖掘来评估网络推理的准确性。The Pharmacogenomics Journal（2012）12，134-146; doi：10.1038/tpj.2010.77; 2010年10月19日在线发表
Interferon-beta (IFN-beta) is one of the major drugs for multiple sclerosis (MS) treatment. The purpose of this study was to characterize the transcriptional effects induced by intramuscular IFN-beta-1a therapy in patients with relapsing-remitting form of MS. By using Affymetrix DNA microarrays, we obtained genome-wide expression profiles of peripheral blood mononuclear cells of 24 MS patients within the first 4 weeks of IFN-beta administration. We identified 121 genes that were significantly up-or downregulated compared with baseline, with stronger changed expression at 1 week after start of therapy. Eleven transcription factor-binding sites (TFBS) are overrepresented in the regulatory regions of these genes, including those of IFN regulatory factors and NF-kappa B. We then applied TFBS-integrating least angle regression, a novel integrative algorithm for deriving gene regulatory networks from gene expression data and TFBS information, to reconstruct the underlying network of molecular interactions. An NF-kappa B-centered sub-network of genes was highly expressed in patients with IFN-beta-related side effects. Expression alterations were confirmed by real-time PCR and literature mining was applied to evaluate network inference accuracy. The Pharmacogenomics Journal (2012) 12, 134-146; doi:10.1038/tpj.2010.77; published online 19 October 2010