The DrugPattern tool for drug set enrichment analysis and its prediction for beneficial effects of oxLDL on type 2 diabetes

作     者：Chuanbo Huang Weili Yang Junpei wang Yuan Zhou Bin Geng Georgios Kararigas Jichun Yang Qinghua Cui 

作者机构：Department of Biomedical Informatics Department of Physiology and Pathophysiology MOE Key Lab of Cardiovascular Sciences School of Basic Medical Sciences Center for Non-Coding RNA Medicine Peking UniversityBeijing 100191China School of Mathematics Sciences Huaqiao University Quanzhou 362021 China Hypertension Center Fuwai Hospital Chinese Academy of Medical Sciences and Peking Union Medical CollegeState Key Laboratory of Cardiovascular Disease National Center for Cardiovascular Diseases Beijing 100037 China Charit-Universitatsmedizin Berlin. Corporate Member of Freie Universitat Berlin Humboldt-Universitat zu Berlin Berlin Institute of Health Institute of Gender in Medicine and Center for Cardiovascular Research. DZHK (German Centre for Cardiovascular Research) 10115 Berlin Germany Center of Bioinformatics Key Laboratory for Neuro-lnformation of Ministry of Education School of Life Science and Technology University of Electronic Science and Technology of China Chengdu 610054 China 

出 版 物：《Journal of Genetics and Genomics》 (遗传学报（英文版）)

年 卷 期：2018年第45卷第7期

页      面：389-397页

核心收录：

学科分类：0710[理学-生物学] 07[理学] 09[农学] 

基　　金：supported by the Special Project on Precision Medicine under the National Key R&D Program (2016YFC0903003 and 2017YFC0909600) the National Natural Science Foundation of China (Nos. 81670462 and 81422006 to Q.C 81670748 and 81471035 to J.Y.) Beijing Natural Science Foundation (No.7171006 to J.Y.) 

主　　题：Enrichment analysis Drug Data mining oxLDL Type 2 diabetes 

摘      要：Enrichment analysis methods, e.g., gene set enrichment analysis, represent one class of important bio- informatical resources for mining patterns in biomedical datasets. However, tools for inferring patterns and rules of a list of drugs are limited. In this study, we developed a web-based tool, DrugPattern, for drug set enrichment analysis. We first collected and curated 7019 drug sets, including indications, adverse reactions, targets, pathways, etc. from public databases. For a list of interested drugs, DrugPat- tern then evaluates the significance of the enrichment of these drugs in each of the 7019 drug sets. To validate DrugPattern, we employed it for the prediction of the effects of oxidized low-density lipoprotein （oxLDL）, a factor expected to be deleterious. We predicted that oxLDL has beneficial effects on some diseases, most of which were supported by evidence in the literature. Because DrugPattern predicted the potential beneficial effects of oxLDL in type 2 diabetes （T2D）, animal experiments were then performed to further verify this prediction. As a result, the experimental evidences validated the DrugPattern prediction that oxLDL indeed has beneficial effects on T2D in the case of energy restriction. These data confirmed the prediction accuracy of our approach and revealed unexpected protective roles for oxLDL in various diseases. This study provides a tool to infer patterns and rules in biomedical datasets based on drug set enrichment analysis.