Correlating adverse drug reactions with biological pathways in humans

Huiru Zheng, Haiying Wang, Hua Xu, Zhongming Zhao, Francisco Azuaje

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    2 Citations (Scopus)

    Abstract

    It has been well recognized that adverse drug reactions (ADRs) are a significant cause of morbidity and mortality. There is a growing interest in investigating biological pathways involved in cellular response to drugs. Based on examining the co-occurrence of drugs in pathway activity and ADR profiles, in this paper, we propose a new method to explore the relationship between biological pathways and ADRs at a large scale. Using sparse canonical correlation analysis of 495 drugs with two profiles for 173 pathways and 1385 ADRs, a total of 80 correlated sets of pathways and ADRs were extracted. To evaluate the performance of our method, extracted correlated components were used to retrieve known ADR profiles from drug pathway profiles using a 5-fold cross validation. A relatively high prediction performance (AUC: 0.881) was achieved. This work provides a foundation for future investigation of ADRs in the context of biological pathways under different conditions.

    Original languageEnglish
    Title of host publicationProceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013
    Pages197-200
    Number of pages4
    DOIs
    Publication statusPublished - 2013
    Event2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013 - Shanghai, China
    Duration: 18 Dec 201321 Dec 2013

    Publication series

    NameProceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013

    Conference

    Conference2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013
    Country/TerritoryChina
    CityShanghai
    Period18/12/1321/12/13

    Keywords

    • adverse drug reactions
    • Pathway
    • sparse canonical correlation analysis

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