Multi-tissue network analysis for drug prioritization in knee osteoarthritis
Multi-tissue network analysis for drug prioritization in knee osteoarthritis
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DOI：
10.1038/s41598-019-51627-6
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发表时间：
2019-07
影响因子：
4.6
通讯作者：
M. Neidlin;Smaragda Dimitrakopoulou;L. Alexopoulos
中科院分区：
文献类型：
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作者：
M. Neidlin;Smaragda Dimitrakopoulou;L. Alexopoulos
膝关节骨性关节炎（OA）是一种影响软骨、滑膜、半月板和软骨下骨等多种组织的关节疾病。这种复杂疾病的病理生理学仍未完全了解，现有的药物策略仅限于疼痛缓解治疗。因此，我们开发了一种考虑OA的多种机制和多组织性质的计算方法，以建议药物化合物。具体来说，加权基因共表达网络分析（WGCNA）被用于鉴定在四个关节组织中保存的基因模块。选择这些模块的驱动基因作为基于网络的药物发现方法的输入。WGCNA确定了两个保留的模块，描述了与细胞外基质生理学和免疫系统反应相关的功能。建议影响各种抗炎途径的化合物和针对凝血途径的药物。前10个化合物中有9个被证实与OA相关，并且显著优于不包括WGCNA的随机方法。本文提出的方法是一种可行的策略，可以识别多组织疾病（如OA）中的重叠分子机制，并将这些信息用于药物发现和化合物优先排序。
Knee osteoarthritis (OA) is a joint disease that affects several tissues: cartilage, synovium, meniscus and subchondral bone. The pathophysiology of this complex disease is still not completely understood and existing pharmaceutical strategies are limited to pain relief treatments. Therefore, a computational method was developed considering the diverse mechanisms and the multi-tissue nature of OA in order to suggest pharmaceutical compounds. Specifically, weighted gene co-expression network analysis (WGCNA) was utilized to identify gene modules that were preserved across four joint tissues. The driver genes of these modules were selected as an input for a network-based drug discovery approach. WGCNA identified two preserved modules that described functions related to extracellular matrix physiology and immune system responses. Compounds that affected various anti-inflammatory pathways and drugs targeted at coagulation pathways were suggested. 9 out of the top 10 compounds had a proven association with OA and significantly outperformed randomized approaches not including WGCNA. The method presented herein is a viable strategy to identify overlapping molecular mechanisms in multi-tissue diseases such as OA and employ this information for drug discovery and compound prioritization.