Centre for Bioinformatics, Biomarker Discovery & Information-Based Medicine, University of Newcastle, and Hunter Medical Research Institute, Newcastle, Australia.
PLoS One. 2010 Dec 1;5(12):e14176. doi: 10.1371/journal.pone.0014176.
Several lines of evidence suggest that transcription factors are involved in the pathogenesis of Multiple Sclerosis (MS) but complete mapping of the whole network has been elusive. One of the reasons is that there are several clinical subtypes of MS and transcription factors that may be involved in one subtype may not be in others. We investigate the possibility that this network could be mapped using microarray technologies and contemporary bioinformatics methods on a dataset derived from whole blood in 99 untreated MS patients (36 Relapse Remitting MS, 43 Primary Progressive MS, and 20 Secondary Progressive MS) and 45 age-matched healthy controls.
METHODOLOGY/PRINCIPAL FINDINGS: We have used two different analytical methodologies: a non-standard differential expression analysis and a differential co-expression analysis, which have converged on a significant number of regulatory motifs that are statistically overrepresented in genes that are either differentially expressed (or differentially co-expressed) in cases and controls (e.g., V$KROX_Q6, p-value <3.31E-6; V$CREBP1_Q2, p-value <9.93E-6, V$YY1_02, p-value <1.65E-5).
CONCLUSIONS/SIGNIFICANCE: Our analysis uncovered a network of transcription factors that potentially dysregulate several genes in MS or one or more of its disease subtypes. The most significant transcription factor motifs were for the Early Growth Response EGR/KROX family, ATF2, YY1 (Yin and Yang 1), E2F-1/DP-1 and E2F-4/DP-2 heterodimers, SOX5, and CREB and ATF families. These transcription factors are involved in early T-lymphocyte specification and commitment as well as in oligodendrocyte dedifferentiation and development, both pathways that have significant biological plausibility in MS causation.
有几条证据表明转录因子与多发性硬化症（MS）的发病机制有关，但完整的网络图谱一直难以绘制。原因之一是 MS 存在几种临床亚型，而可能涉及一种亚型的转录因子可能不存在于其他亚型中。我们研究了使用微阵列技术和当代生物信息学方法在来自 99 名未经治疗的 MS 患者（36 名复发缓解型 MS、43 名原发性进展型 MS 和 20 名继发性进展型 MS）和 45 名年龄匹配的健康对照者全血样本的数据集上绘制该网络的可能性。
方法/主要发现：我们使用了两种不同的分析方法：一种是非标准的差异表达分析和差异共表达分析，这两种方法都集中在大量调控基序上，这些基序在病例和对照组中差异表达（或差异共表达）的基因中存在统计学上的过度表达，例如 V$KROX_Q6，p 值<3.31E-6；V$CREBP1_Q2，p 值<9.93E-6，V$YY1_02，p 值<1.65E-5。
结论/意义：我们的分析揭示了一个转录因子网络，该网络可能使 MS 或其一种或多种疾病亚型中的多个基因失调。最显著的转录因子基序是早期生长反应 EGR/KROX 家族、ATF2、YY1（阴阳 1）、E2F-1/DP-1 和 E2F-4/DP-2 异二聚体、SOX5、CREB 和 ATF 家族。这些转录因子参与早期 T 淋巴细胞的特异性和定向，以及少突胶质细胞的去分化和发育，这两个途径在 MS 发病机制中具有重要的生物学意义。
