Long-term genome-wide blood RNA expression profiles yield novel molecular response candidates for IFN-β-1b treatment in relapsing remitting MS
Long-term genome-wide blood RNA expression profiles yield novel molecular response candidates for IFN-β-1b treatment in relapsing remitting MS
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DOI：
10.2217/pgs.09.152
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发表时间：
2010-02-01
期刊：
影响因子：
2.1
通讯作者：
Zettl, Uwe K.
中科院分区：
文献类型：
--
作者：
Goertsches, Robert H.;Hecker, Michael;Zettl, Uwe K.
目的：在多发性硬化症患者中，重组干扰素-β (rIFN-β) 治疗在减少临床恶化方面部分有效。然而，其分子作用机制仍在进一步研究中。材料和方法：我们使用 DNA 微阵列（Affymetrix，加利福尼亚州，美国）和 25 名复发缓解型多发性硬化症患者的外周单核血细胞来分析 rIFN-β 给药 2 年内的纵向转录谱。通过应用独立标准的组合获得差异表达基因组，从而提供有效的数据管理和基因过滤，以解决技术和生物噪音。基因本体术语关联分析和科学文献文本挖掘被用来探索基因相互作用的证据。结果：治疗开始后，我们确定了 42 个（第 2 天）、175 个（第 1 个月）、103 个（第 12 个月）和 108 个（第 24 个月）差异表达基因。观察到已建立的 IFN-β 标记基因表达增加，以及循环 IFN-β 反应候选基因的差异表达。 MS4A1 (CD20) 是 B 细胞耗竭疗法的已知靶标，一个月后其表达显着下调。 CMPK2、FCER1A 和 FFAR2 似乎是迄今为止未被识别的与多发性硬化症治疗相关的差异表达基因，这些基因随着时间的推移而受到一致的调节。总体而言，获得了 54 个基因之间的 84 种相互作用，其中两个主要基因网络在治疗的早期阶段被识别：第一个（n = 15 个基因）由大多数已知的 IFN-β 激活基因组成，而第二个（n = 12）主要包含下调基因，迄今为止在多发性硬化症阵列研究中尚未与 IFN-β 效应相关。结论：我们既拓宽了 IFN-β 作用机制相关成分的知识，又鉴定了 IFN-β 调节基因之间的时间依赖性相互作用。
Aims: In multiple sclerosis patients, treatment with recombinant IFN-beta (rIFN-beta) is partially efficient in reducing clinical exacerbations. However, its molecular mechanism of action is still under scrutiny. Materials & methods: We used DNA microarrays (Affymetrix, CA, USA) and peripheral mononuclear blood cells from 25 relapsing remitting multiple sclerosis patients to analyze the longitudinal transcriptional profile within 2 years of rIFN-beta administration. Sets of differentially expressed genes were attained by applying a combination of independent criteria, thereby providing efficient data curation and gene filtering that accounted for technical and biological noise. Gene ontology term-association analysis and scientific literature text mining were used to explore evidence of gene interaction. Results: Post-therapy initiation, we identified 42 (day 2), 175 (month 1), 103 (month 12) and 108 (month 24) differentially expressed genes. Increased expression of established IFN-beta marker genes, as well as differential expression of circulating IFN-beta-responsive candidate genes, were observed. MS4A1 (CD20), a known target of B-cell depletion therapy, was significantly downregulated after one month. CMPK2, FCER1A, and FFAR2 appeared as hitherto unrecognized multiple sclerosis treatment-related differentially expressed genes that were consistently modulated over time. Overall, 84 interactions between 54 genes were attained, of which two major gene networks were identified at an earlier stage of therapy: the first (n = 15 genes) consisted of mostly known IFN-beta-activated genes, whereas the second (n = 12) mainly contained downregulated genes that to date have not been associated with IFN-beta effects in multiple sclerosis array research. Conclusion: We achieved both a broadening of the knowledge of IFN-beta mechanism-of-action-related constituents and the identification of time-dependent interactions between IFN-beta regulated genes.