Zheng Hong
Department of Endocrine, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Dalian City 116023, Liaoning Province, China.
Stat Appl Genet Mol Biol. 2019 Jul 9;18(5):/j/sagmb.2019.18.issue-5/sagmb-2018-0052/sagmb-2018-0052.xml. doi: 10.1515/sagmb-2018-0052.
The existence of high cost-consuming and high rate of drug failures suggests the promotion of drug repositioning in drug discovery. Existing drug repositioning techniques mainly focus on discovering candidate drugs for a kind of disease, and are not suitable for predicting candidate drugs for an individual sample. Type 1 diabetes mellitus (T1DM) is a disorder of glucose homeostasis caused by autoimmune destruction of the pancreatic β-cell. Here, we present a novel single sample drug repositioning approach for predicting personalized candidate drugs for T1DM. Our method is based on the observation of drug-disease associations by measuring the similarities of individualized pathway aberrance induced by disease and various drugs using a Kolmogorov-Smirnov weighted Enrichment Score algorithm. Using this method, we predicted several underlying candidate drugs for T1DM. Some of them have been reported for the treatment of diabetes mellitus, and some with a current indication to treat other diseases might be repurposed to treat T1DM. This study conducts drug discovery via detecting the functional connections among disease and drug action, on a personalized or customized basis. Our framework provides a rational way for systematic personalized drug discovery of complex diseases and contributes to the future application of custom therapeutic decisions.
高成本消耗和高药物失败率的存在表明在药物研发中应推广药物重新定位。现有的药物重新定位技术主要集中于为某一种疾病发现候选药物，并不适用于预测针对单个样本的候选药物。1型糖尿病（T1DM）是一种由胰腺β细胞的自身免疫性破坏引起的葡萄糖稳态紊乱疾病。在此，我们提出一种新颖的单样本药物重新定位方法，用于预测T1DM的个性化候选药物。我们的方法基于通过使用Kolmogorov-Smirnov加权富集评分算法测量疾病和各种药物诱导的个体化通路异常的相似性来观察药物-疾病关联。使用这种方法，我们预测了几种T1DM的潜在候选药物。其中一些已被报道用于治疗糖尿病，一些目前用于治疗其他疾病的药物可能被重新用于治疗T1DM。本研究通过在个性化或定制基础上检测疾病与药物作用之间的功能联系来进行药物研发。我们的框架为复杂疾病的系统性个性化药物研发提供了一种合理的方法，并有助于未来定制治疗决策的应用。
