A SNPshot of PubMed to associate genetic variants with drugs, diseases, and adverse reactions

  • Authors:

  • JöRg Hakenberg;Dmitry Voronov;Ví Hí NguyêN;Shanshan Liang;Saadat Anwar;Barry Lumpkin;Robert Leaman;Luis Tari;Chitta Baral

  • Affiliations:

  • Arizona State University, Computer Science Department, 699 S Mill Ave., Tempe, AZ 85281, USA and Hoffmann-La Roche, Inc., Pharma Research and Early Development, 340 Kingsland St., Nutley, NJ 07110 ...;Arizona State University, Computer Science Department, 699 S Mill Ave., Tempe, AZ 85281, USA and Ural Federal University, IT Department, Turgeneva St. 4, Ekaterinburg 620075, Russian Federation;Arizona State University, Computer Science Department, 699 S Mill Ave., Tempe, AZ 85281, USA;Arizona State University, Computer Science Department, 699 S Mill Ave., Tempe, AZ 85281, USA;Arizona State University, Computer Science Department, 699 S Mill Ave., Tempe, AZ 85281, USA;Arizona State University, Computer Science Department, 699 S Mill Ave., Tempe, AZ 85281, USA;Arizona State University, Department of Biomedical Informatics, 425 N Fifth St., Phoenix, AZ 85004, USA;Hoffmann-La Roche, Inc., Pharma Research and Early Development, 340 Kingsland St., Nutley, NJ 07110, USA;Arizona State University, Computer Science Department, 699 S Mill Ave., Tempe, AZ 85281, USA

  • Venue:
  • Journal of Biomedical Informatics
  • Year:
  • 2012

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Abstract

Motivation: Genetic factors determine differences in pharmacokinetics, drug efficacy, and drug responses between individuals and sub-populations. Wrong dosages of drugs can lead to severe adverse drug reactions in individuals whose drug metabolism drastically differs from the ''assumed average''. Databases such as PharmGKB are excellent sources of pharmacogenetic information on enzymes, genetic variants, and drug response affected by changes in enzymatic activity. Here, we seek to aid researchers, database curators, and clinicians in their search for relevant information by automatically extracting these data from literature. Approach: We automatically populate a repository of information on genetic variants, relations to drugs, occurrence in sub-populations, and associations with disease. We mine textual data from PubMed abstracts to discover such genotype-phenotype associations, focusing on SNPs that can be associated with variations in drug response. The overall repository covers relations found between genes, variants, alleles, drugs, diseases, adverse drug reactions, populations, and allele frequencies. We cross-reference these data to EntrezGene, PharmGKB, PubChem, and others. Results: The performance regarding entity recognition and relation extraction yields a precision of 90-92% for the major entity types (gene, drug, disease), and 76-84% for relations involving these types. Comparison of our repository to PharmGKB reveals a coverage of 93% of gene-drug associations in PharmGKB and 97% of the gene-variant mappings based on 180,000 PubMed abstracts. Availability: http://bioai4core.fulton.asu.edu/snpshot.