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

Chuanbo Huang; Weili Yang; Junpei Wang; Yuan Zhou; Bin Geng; Georgios Kararigas; Jichun Yang; Qinghua Cui

doi:10.1016/j.jgg.2018.07.002

Volume 45 Issue 7

Jul. 2018

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

doi: 10.1016/j.jgg.2018.07.002

a
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 University, Beijing 100191, China
b
School of Mathematics Sciences, Huaqiao University, Quanzhou 362021, China
c
Hypertension Center, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Beijing 100037, China
d
Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität 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
e
Center of Bioinformatics, Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China

More Information

Corresponding author: E-mail address: yangj@bjmu.edu.cn (Jichun Yang); E-mail address: cuiqinghua@bjmu.edu.cn (Qinghua Cui)
Received Date: 2018-01-08
Accepted Date: 2018-07-04
Rev Recd Date: 2018-05-18

Available Online: 2018-07-24

Publish Date: 2018-07-20

Abstract

Abstract

Enrichment analysis methods, e.g., gene set enrichment analysis, represent one class of important bioinformatical 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, DrugPattern 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. DrugPattern is available at http://www.cuilab.cn/drugpattern.
- Enrichment analysis,
- Drug,
- Data mining,
- oxLDL,
- Type 2 diabetes

These authors contributed equally to this work.

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References(49)

References

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