BioChip Journal

, Volume 4, Issue 2, pp 99–104 | Cite as

TOXPO: TOXicogenomics knowledgebase for inferring toxicity based on POlymorphism

  • Yunju Jo
  • In Song Koh
  • Hyunsu Bae
  • Moo-Chang Hong
  • Min-Kyu Shin
  • Yang Seok KimEmail author
Original Research


Recently, many state-of-the-art omics technologies are being applied to systems toxicology research because evaluation of toxicity in pre-clinical trials is a big issue in the pharmaceutical industry. Now, genetic polymorphisms are also considered in systems toxicology because polymorphism information can be used to explain individual-specific toxicity and/or side effects. However, in spite of its importance, no well-organized database for individual toxicity has been reported to date. To address this issue, we first extracted toxicity-related human gene information from the CTD, and then, using comparative genomics techniques and retrieving information from animal databases, we gathered the corresponding genes from the mouse and rat. The CTD (Comparative Toxicogenomics Database), dbSNP, RGD (Rat Genome Database), MGI (Mouse Genome Informatics), NHGRI Genome-Wide Association Studies, JMDBASE (Japan Metabolic Disease Database) and GAD (Genetic Association Database) were used as original information sources. The dbSNP was used as a major polymorphism data source, and other related databases were also used to find disease- and/or toxicity-related SNPs. The MSSQL server was used as a database management system and ASP was used to construct a database-web interface. The result of our efforts is TOXPO(TOXico-genomics knowledgebase for inferring toxicity based on POlymorphism), the first database managing toxicogenomics information based on genomic variation. This database is freely available on website


Toxicogenomics SNP Bioinformatics Systems toxicology Database 


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  1. 1.
    Schwardt, O., Kolb, H. & Ernst, B. Drug discovery today. Current Topics in Medicinal Chemistry 3, 1–9 (2003).CrossRefGoogle Scholar
  2. 2.
    Yang, Y., Blomme, E.A.G. & Waring, J.F. Toxicogenomics in drug discovery: from preclinical studies to clinical trials. Chemico-Biological Interactions 150, 71–85 (2004).CrossRefGoogle Scholar
  3. 3.
    Nuwaysir, E.F., Bittner, M., Trent, J., Barrett, J.C. & Afshari, A. Microarrays and toxicology: The advent of toxicogenomics. Molecular Carcinogenesis 24, 153–159 (1999).CrossRefGoogle Scholar
  4. 4.
    Giacomini, K.M. et al. The pharmacogenetics research network: From SNP discovery to clinical drug response. Clinical Pharmacology & Therapeutics 81, 328–345 (2007).CrossRefGoogle Scholar
  5. 5.
    Voisey, J. & Morris, C.P. SNP Technologies for drug discovery: A current review. Current Drug Discovery Technologies 5, 230–235 (2008).CrossRefGoogle Scholar
  6. 6.
    Glubb, D.M., McHugh, P.C., Deng, X., Joyce, P.R. & Kennedy, M.A. Association of a functional polymorphism in the adrenomedullin gene (ADM) with response to paroxetine. The Pharmacogenomics Journal 10, 126–133 (2010).CrossRefGoogle Scholar
  7. 7.
    Wandel, C. et al. CYP3A activity in African American and European American men: Population differences and functional effect of the CYP3A4*1B 5′-promoter region polymorphism. Clinical Pharmacology & Therapeutics 68, 82–91 (2000).CrossRefGoogle Scholar
  8. 8.
    The International HapMap Consortium. A second generation human haplotype map of over 3.1 million SNPs. Nature 449, 851–861 (2007).CrossRefGoogle Scholar
  9. 9.
    Grapes, L. et al. Prospecting for pig single nucleotide polymorphisms in the human genome: have we struck gold? J. Anim. Breed. Genet. 123, 145–151 (2006).CrossRefGoogle Scholar
  10. 10.
  11. 11.
  12. 12.
  13. 13.
    Ginsburg, G.S. & McCarthy, J.J. Personalized medicine: revolutionizing drug discovery and patient care. TRENDS in Biotechnology 19, 491–496 (2001).CrossRefGoogle Scholar
  14. 14.
  15. 15.
  16. 16.
    Davis, A.P. et al. Comparative toxicogenomics database: a knowledgebase and discovery tool for chemicalgene-disease networks. Nucleic Acids Research 37, D786–D792 (2009).CrossRefGoogle Scholar
  17. 17.
  18. 18.
    Olden, K. & Wilson, S. Environmental health and genomics: visions and implications. Nature Review Genetics 1, 149–153 (2000).CrossRefGoogle Scholar
  19. 19.
    Goldstein, D.B. & Cavalleri, G.L. Understanding human diversity. Nature 437, 1241–1242 (2005).CrossRefGoogle Scholar
  20. 20.
    Ng, P.C., Murray, S.S., Levy, S. & Venter, J.C. An agenda for personalized medicine. Nature 461, 724–726 (2009).CrossRefGoogle Scholar
  21. 21.
    Kong, A. et al. Parental origin of sequence variants associated with complex diseases. Nature 462, 868–874 (2009).CrossRefGoogle Scholar
  22. 22.
    Cooper, D.N., Nussbaum, R.L. & Krawczak, M. Proposed guidelines for papers describing DNA polymorphism-disease associations. Hum. Genet. 110, 207–208 (2002).CrossRefGoogle Scholar
  23. 23.
    Nan, H., Kraft, P., Hunter, D.J. & Han, J. Genetic variants in pigmentation genes, pigmentary phenotypes, and risk of skin cancer in Caucasians. Int. J. Cancer 125, 909–917 (2009).CrossRefGoogle Scholar

Copyright information

© The Korean BioChip Society and Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Yunju Jo
    • 1
  • In Song Koh
    • 2
  • Hyunsu Bae
    • 1
  • Moo-Chang Hong
    • 1
  • Min-Kyu Shin
    • 1
  • Yang Seok Kim
    • 1
    Email author
  1. 1.Department of Physiology, College of Oriental MedicineKyung Hee UniversityDongdaemun-gu, SeoulKorea
  2. 2.Department of Physiology & Systems MedicineHanyang University Medical SchoolSeongdong-gu, SeoulKorea

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