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Combining Human Disease Genetics and Mouse Model Phenotypes towards Drug Repositioning for Parkinson’s disease

机译:将人类疾病的遗传学和小鼠模型表型结合起来以治疗帕金森氏病

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摘要

Parkinson’s disease (PD) is a severe neurodegenerative disorder without effective treatments. Here, we present a novel drug repositioning approach to predict new drugs for PD leveraging both disease genetics and large amounts of mouse model phenotypes. First, we identified PD-specific mouse phenotypes using well-studied human disease genes. Then we searched all FDA-approved drugs for candidates that share similar mouse phenotype profiles with PD. We demonstrated the validity of our approach using drugs that have been approved for PD: 10 approved PD drugs were ranked within top 10% among 1197 candidates. In predicting novel PD drugs, our approach achieved a mean average precision of 0.24, which is significantly higher (p<e-11) than 0.16 for a state-of-art drug discovery approach based on mouse phenotype data. Comparison of gene expression profiles between PD and top-ranked drug candidates indicates that quetiapine has the potential to treat PD.
机译:帕金森氏病(PD)是一种严重的神经退行性疾病,没有有效的治疗方法。在这里,我们提出了一种新颖的药物重新定位方法,以利用疾病遗传和大量小鼠模型表型来预测PD的新药。首先,我们使用经过深入研究的人类疾病基因鉴定了PD特异性小鼠表型。然后,我们在所有FDA批准的药物中搜索与PD具有相似小鼠表型特征的候选药物。我们使用已批准用于PD的药物证明了我们方法的有效性:在1197个候选药物中,有10种已批准的PD药物在前10%内排名最高。在预测新的PD药物时,我们的方法实现了0.24的平均平均精确度,这比基于小鼠表型数据的最新药物发现方法的平均平均精确度要高得多(p

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