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Compensating for literature annotation bias when predicting novel drug-disease relationships through Medical Subject Heading Over-representation Profile (MeSHOP) similarity Cheung, Warren A.; Ouellette, B. F. F.; Wasserman, Wyeth W.

Abstract

Background: Using annotations to the articles in MEDLINE®/PubMed®, over six thousand chemical compounds with pharmacological actions have been tracked since 1996. Medical Subject Heading Over-representation Profiles (MeSHOPs) quantitatively leverage the literature associated with biological entities such as diseases or drugs, providing the opportunity to reposition known compounds towards novel disease applications. Methods: A MeSHOP is constructed by counting the number of times each medical subject term is assigned to an entity-related research publication in the MEDLINE database and calculating the significance of the count by comparing against the count of the term in a background set of publications. Based on the expectation that drugs suitable for treatment of a disease (or disease symptom) will have similar annotation properties to the disease, we successfully predict drug-disease associations by comparing MeSHOPs of diseases and drugs. Results: The MeSHOP comparison approach delivers an 11% improvement over bibliometric baselines. However, novel drug-disease associations are observed to be biased towards drugs and diseases with more publications. To account for the annotation biases, a correction procedure is introduced and evaluated. Conclusions: By explicitly accounting for the annotation bias, unexpectedly similar drug-disease pairs are highlighted as candidates for drug repositioning research. MeSHOPs are shown to provide a literature-supported perspective for discovery of new links between drugs and diseases based on pre-existing knowledge.

Item Metadata

Title
Compensating for literature annotation bias when predicting novel drug-disease relationships through Medical Subject Heading Over-representation Profile (MeSHOP) similarity
Creator
Cheung, Warren A.; Ouellette, B. F. F.; Wasserman, Wyeth W.
Contributor
Child and Family Research Institute
Publisher
BioMed Central
Date Issued
2013-05-07
Description
Background: Using annotations to the articles in MEDLINE®/PubMed®, over six thousand chemical compounds with pharmacological actions have been tracked since 1996. Medical Subject Heading Over-representation Profiles (MeSHOPs) quantitatively leverage the literature associated with biological entities such as diseases or drugs, providing the opportunity to reposition known compounds towards novel disease applications. Methods: A MeSHOP is constructed by counting the number of times each medical subject term is assigned to an entity-related research publication in the MEDLINE database and calculating the significance of the count by comparing against the count of the term in a background set of publications. Based on the expectation that drugs suitable for treatment of a disease (or disease symptom) will have similar annotation properties to the disease, we successfully predict drug-disease associations by comparing MeSHOPs of diseases and drugs. Results: The MeSHOP comparison approach delivers an 11% improvement over bibliometric baselines. However, novel drug-disease associations are observed to be biased towards drugs and diseases with more publications. To account for the annotation biases, a correction procedure is introduced and evaluated. Conclusions: By explicitly accounting for the annotation bias, unexpectedly similar drug-disease pairs are highlighted as candidates for drug repositioning research. MeSHOPs are shown to provide a literature-supported perspective for discovery of new links between drugs and diseases based on pre-existing knowledge.
Genre
Article
Type
Text
Language
eng
Date Available
2016-01-25
Provider
Vancouver : University of British Columbia Library
Rights
Attribution 4.0 International (CC BY 4.0)
DOI
10.14288/1.0228401
URI
http://hdl.handle.net/2429/56706
Affiliation
Science, Faculty of; Medical Genetics, Department of; Medicine, Faculty of; Molecular Medicine and Therapeutics, Centre for; Non UBC
Citation
BMC Medical Genomics. 2013 May 07;6(Suppl 2):S3
Publisher DOI
10.1186/1755-8794-6-S2-S3
Peer Review Status
Reviewed
Scholarly Level
Faculty
Copyright Holder
Cheung et al.; licensee BioMed Central Ltd.
Rights URI
http://creativecommons.org/licenses/by/4.0/
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Attribution 4.0 International (CC BY 4.0)