首页> 外文会议>IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology >Identification Of A Gene Expression Core Signature For Duchenne Muscular Dystrophy (DMD) Via Integrative Analysis Reveals Novel Potential Compounds For Treatment
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Identification Of A Gene Expression Core Signature For Duchenne Muscular Dystrophy (DMD) Via Integrative Analysis Reveals Novel Potential Compounds For Treatment

机译:通过整合分析鉴定Duchenne肌营养不良(DMD)的基因表达核心签名揭示了用于治疗的新型潜在化合物

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Duchenne muscular dystrophy (DMD) is a recessive X-linked form of muscular dystrophy and one of the most prevalent genetic disorders of childhood. DMD is characterized by rapid progression of muscle degeneration, and ultimately death. Currently, glucocorticoids are the only available treatment for DMD, but they have been shown to result in serious side effects. The purpose of this research was to define a core signature of gene expression related to DMD via integrative analysis of mouse and human datasets. This core signature was subsequently used to screen for novel potential compounds that antagonistically affect the expression of signature genes. With this approach we were able to identify compounds that are 1) already used to treat DMD, 2) currently under investigation for treatment, and 3) so far unknown but promising candidates. Our study highlights the potential of meta-analyses through the combination of datasets to unravel previously unrecognized associations and reveal new relationships.
机译:Duchenne肌营养不良(DMD)是一种隐性X型肌营养不良症的形式,也是儿童最普遍的遗传障碍之一。 DMD的特征在于肌肉变性快速进展,最终死亡。目前,糖皮质激素是DMD的唯一​​可用治疗,但它们已被证明导致严重的副作用。本研究的目的是通过小鼠和人类数据集的整合分析定义与DMD相关的基因表达的核心签名。随后使用该核心签名用于筛选用于拮抗拟标基因表达的新型潜在化合物。通过这种方法,我们能够识别已经用于治疗DMD,2)目前正在调查的化合物,以及3)到目前为止未知但有前途的候选人。我们的研究突出了通过数据集的组合来解析以前未被识别的关联并揭示新关系的潜力。

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