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Gaining a Pathway Insight into Genetic Association Data

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Genetic Variation

Part of the book series: Methods in Molecular Biology ((MIMB,volume 628))

Abstract

The recent application of high throughput genotyping in humans has yielded numerous insights into the genetic basis of human phenotypes and unprecedented amount of genetic variation data. Each genome wide significant finding has explained only a tiny proportion of phenotypic variation, yet genome wide association studies (GWAS) in their entirety can provide unprecedented windows into the molecular genetics of these phenotypes. New methods are emerging to mine modest association signals from these data using information on biological pathways and networks underlying the phenotype variation. These methods promise to enhance the information extracted from GWAS providing grounds for follow up studies of both a genetic and molecular nature.

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References

  1. Altshuler, D., Daly, M.J. and Lander, E.S. (2008) Genetic mapping in human disease. Science, 322, 881-888.

    Article  PubMed  CAS  Google Scholar 

  2. Dudbridge, F. and Gusnanto, A. (2008) Estimation of significance thresholds for genomewide association scans. Genet. Epidemiol., 32, 227-234.

    Article  PubMed  Google Scholar 

  3. McCarthy, M.I. and Hirschhorn, J.N. (2008) Genome-wide association studies: potential next steps on a genetic journey. Hum. Mol. Genet., 17, R156-R165.

    Article  PubMed  CAS  Google Scholar 

  4. Altshuler, D., Hirschhorn, J.N., Klannemark, M., Lindgren, C.M., Vohl, M.C., Nemesh, J., et al. (2000) The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes. Nat. Genet., 26, 76-80.

    Article  PubMed  CAS  Google Scholar 

  5. Stefansson, H., Rujescu, D., Cichon, S., Pietilainen, O.P., Ingason, A., Steinberg, S., et al. (2008) Large recurrent microdeletions associated with schizophrenia. Nature, 455, 232-236.

    Article  PubMed  CAS  Google Scholar 

  6. Pericak-Vance, M.A., Bebout, J.L., Gaskell, P.C., Jr., Yamaoka, L.H., Hung, W.Y., Alberts, M.J., et al. (1991) Linkage studies in familial Alzheimer disease: evidence for chromosome 19 linkage. Am. J. Hum. Genet., 48, 1034-1050.

    PubMed  CAS  Google Scholar 

  7. Roses, A.D., Saunders, A.M., Huang, Y., Strum, J., Weisgraber, K.H. and Mahley, R.W. (2007) Complex disease-associated pharmacogenetics: drug efficacy, drug safety, and confirmation of a pathogenetic hypothesis (Alzheimer’s disease). Pharmacogenomics J., 7, 10-28.

    Article  PubMed  CAS  Google Scholar 

  8. Goldstein, D.B. (2009) Common genetic variation and human traits. N. Engl. J. Med., 360, 1696-1698.

    Article  PubMed  CAS  Google Scholar 

  9. Smedley, D., Haider, S., Ballester, B., Holland, R., London, D., Thorisson, G. and Kasprzyk, A. (2009) BioMart - biological queries made easy. BMC Genomics, 10, 22.

    Article  PubMed  Google Scholar 

  10. Taylor, J., Schenck, I., Blankenberg, D. and Nekrutenko, A. (2007) Using galaxy to perform large-scale interactivve data analyses. Curr. Protoc. Bioinformatics, Chapter 10, Unit.

  11. Webster, J.A., Gibbs, J.R., Clarke, J., Ray, M., Zhang, W., Holmans, P., et al. (2009) Genetic control of human brain transcript expression in Alzheimer disease. Am. J. Hum. Genet., 84, 445-458.

    Article  PubMed  CAS  Google Scholar 

  12. Liu, Q., Dinu, I., Adewale, A.J., Potter, J.D. and Yasui, Y. (2007) Comparative evaluation of gene-set analysis methods. BMC Bioinformatics, 8, 431.

    Article  PubMed  Google Scholar 

  13. Lehner, B. and Lee, I. (2008) Network-guided genetic screening: building, testing and using gene networks to predict gene function. Brief. Funct. Genomic. Proteomic., 7, 217-227.

    Article  PubMed  CAS  Google Scholar 

  14. Subramanian, A., Tamayo, P., Mootha, V.K., Mukherjee, S., Ebert, B.L., Gillette, M.A., et al. (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. U.S.A., 102, 15545-15550.

    Article  PubMed  CAS  Google Scholar 

  15. Chuang, H.Y., Lee, E., Liu, Y.T., Lee, D. and Ideker, T. (2007) Network-based classification of breast cancer metastasis. Mol. Syst. Biol., 3, 140.

    Article  PubMed  Google Scholar 

  16. Jiang, Z. and Gentleman, R. (2007) Extensions to gene set enrichment. Bioinformatics, 23, 306-313.

    Article  PubMed  Google Scholar 

  17. Li, J. and Ji, L. (2005) Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix. Heredity, 95, 221-227.

    Article  PubMed  CAS  Google Scholar 

  18. Bergholdt, R., Storling, Z.M., Lage, K., Karlberg, E.O., Olason, P.I., Aalund, M., et al. (2007) Integrative analysis for finding genes and networks involved in diabetes and other complex diseases. Genome Biol., 8, R253.

    Article  PubMed  Google Scholar 

  19. Wang, K., Zhang, H., Kugathasan, S., Annese, V., Bradfield, J.P., Russell, R.K., et al. (2009) Diverse genome-wide association studies associate the IL12/IL23 pathway with Crohn Disease. Am. J. Hum. Genet., 84, 399-405.

    Article  PubMed  CAS  Google Scholar 

  20. Baranzini, S.E., Galwey, N.W., Wang, J., Khankhanian, P., Lindberg, R., Pelletier, D., et al. (2009) Pathway and network-based analysis of genome-wide association studies in multiple sclerosis. Hum. Mol. Genet.

    Google Scholar 

  21. Gibson, G. (2009) Decanalization and the origin of complex disease. Nat. Rev. Genet., 10, 134-140.

    Article  PubMed  CAS  Google Scholar 

  22. Wu, X., Jiang, R., Zhang, M.Q. and Li, S. (2008) Network-based global inference of human disease genes. Mol. Syst. Biol., 4, 189.

    Article  PubMed  Google Scholar 

  23. Loscalzo, J., Kohane, I. and Barabasi, A.L. (2007) Human disease classification in the postgenomic era: a complex systems approach to human pathobiology. Mol. Syst. Biol., 3, 124.

    Article  PubMed  Google Scholar 

  24. Veyrieras, J.B., Kudaravalli, S., Kim, S.Y., Dermitzakis, E.T., Gilad, Y., Stephens, M. and Pritchard, J.K. (2008) High-resolution mapping of expression-QTLs yields insight into human gene regulation. PLoS Genet., 4, e1000214.

    Article  PubMed  Google Scholar 

  25. Moskvina, V., Craddock, N., Holmans, P., Nikolov, I., Pahwa, J.S., Green, E., Owen, M.J. and O’Donovan, M.C. (2009) Gene-wide analyses of genome-wide association data sets: evidence for multiple common risk alleles for schizophrenia and bipolar disorder and for overlap in genetic risk. Mol. Psychiatry, 14, 252-260.

    Article  PubMed  CAS  Google Scholar 

  26. Nam, D. and Kim, S.Y. (2008) Gene-set approach for expression pattern analysis. Brief. Bioinformatics, 9, 189-197.

    Article  PubMed  Google Scholar 

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Author information

Authors and Affiliations

  1. NIHR Biomedical Research Centre for Mental Health, South London and Maudsley NHS Foundation Trust and Institute of Psychiatry and MRC Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London, London, UK

    Inti Pedroso

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  1. Inti Pedroso
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Correspondence to Inti Pedroso .

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Editors and Affiliations

  1. Medicines Research Centre, GlaxoSmithKline R&D Limited, Gunnels Wood Road, Stevenage, Hertfordshire, SG12NY, United Kingdom

    Michael R. Barnes

  2. Institute of Psychiatry, Social, Genetic & Developmental, King's College, Denmark Hill 111, London, SE58AF, United Kingdom

    Gerome Breen

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Pedroso, I. (2010). Gaining a Pathway Insight into Genetic Association Data. In: Barnes, M., Breen, G. (eds) Genetic Variation. Methods in Molecular Biology, vol 628. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-60327-367-1_20

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  • DOI: https://doi.org/10.1007/978-1-60327-367-1_20

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  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-60327-366-4

  • Online ISBN: 978-1-60327-367-1

  • eBook Packages: Springer Protocols

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