Abstract
Candidate gene association studies aim to establish or characterise association between the genetic variation occurring within a specific gene or locus and a phenotype. If the phenotype is quantitative, then the effect size is often measured as the difference between the genotype specific means or a per allele effect. When the phenotype is binary and the disease is either present or absent, the effect is summarised as a genotype specific risk or relative risk. This chapter focuses on methodology employed when a single or small number of genetic loci are being investigated for an association with a specific phenotype.
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References
Risch, N., Merikangas, K. (1996) The future of genetic studies of complex diseases. Science 273:1516–1517.
Cordell, H.J., Clayton, D.G. (2005) Genetic epidemiology 3 – Genetic association studies. Lancet 366:1121–1131.
Dobson, A.J. (2002) Normal Linear Models. In: An Introduction to Generalised Linear Models, 2nd Edition. Chapman and Hall/CRC: Boca Raton, FL, pp. 85–114.
Vignal, C., Bansal, A.T., Balding, D.J., et al. (2009) Genetic association of the major histocompatibility complex with rheumatoid arthritis implicates two non-DRB1 loci. Arthritis Rheum 60:53–62.
Antoniou, A., Pharoah, P.D.P., Narod, S., et al. (2003) Average risks of breast and ovarian cancer associated with BRCA1 or BRCA2 mutations detected in case series unselected for family history: A combined analysis of 22 studies. Am J Hum Genet 72:1117–1130.
Cancer Research UK FactSheet. http://info.cancerresearchuk.org/cancerstats/types/breast/incidence/
Cox, A., Dunning, A.M., Garcia-Closas, M., et al. (2007) A common coding variant in CASP8 is associated with breast cancer risk. Nat Genet 39:352–358.
Amos, C.I., Wu, X., Broderick, P., Gorlov, I.P., et al. (2008) Genome-wide association scan of tag SNPs identifies a susceptibility locus for lung cancer at 15q25.1. Nat Genet 40:616–622.
Jewell, N.P. (2004) Study Designs. In: Statistics for Epidemiology. Chapman and Hall/CRC: Boca Raton, FL, pp. 43–56.
Dobson, A.J. (2002) Binary Variables and Logistic Regression. In: An Introduction to Generalised Linear Models, 2nd Edition. Chapman and Hall/CRC: Boca Raton, FL, pp. 115–134.
Sutton, A.J., Abrams, K.R., Jones, D.R., Sheldon, T.A., Song, F. (2004) Methods for Meta-Analysis in Medical Research. Wiley: New York.
Sutton, A.J., Abrams, K.R., Jones, D.R., Sheldon, T.A., Song, F. (2004) Publication Bias. In: Methods for Meta-Analysis in Medical Research. Wiley: London, pp. 109–132.
Iles, M.M. (2010) Genome Wide Association. In: M.D. Teare (ed.) Genetic Epidemiology. Springer: New York.
Clayton, D., Chapman, J., Cooper, J. (2004) The use of unphased multilocus genotype data in indirect association studies. Genet Epidemiol 27:415–428.
Guo, Y., Li, J., Bonham, A.J., Wang, Y., Deng, H. (2009) Gains in power for exhaustive analyses of haplotypes using variable-sized sliding window strategy: A comparison of association-mapping strategies. Eur J Hum Genet 17:785–792.
Browning, B.L., Browning, S.R. (2009) A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. Am J Hum Genet 84:210–223.
Price, A.L., Patterson, N., Hancks, D.C., Myers, S., Reich, D., et al. (2008) Effects of cis and trans genetic ancestry on gene expression in African Americans. PLoS Genet 4:e1000294. doi:10.1371/journal.pgen.1000294.
Balding, D.J. (2006) A tutorial on statistical methods for population association studies. Nat Rev Genet 7:781–791.
Chen, Y., Shen, H., Yang, F., Liu, P.-Y., et al. (2009) Choice of phenotype in osteoporosis genetic research. J Bone Miner Metab 27:121–126.
NIH Consensus Development Panel on Osteoporosis Prevention, Diagnosis, and Therapy (2001) Osteoporosis prevention, diagnosis, and therapy. JAMA 285:785–795.
Morrison, N.A., Qi, J.C., Tokita, A., Kelly, P.J., et al. (1994) Prediction of bone density from vitamin D receptor alleles. Nature 367:284–287.
Cooper, G.S., Umbach, D.M. (1996) Are vitamin D receptor polymorphsims associated with bone mineral density? J Bone Miner Res 11:1241–1248.
Thakkinstian, A., D’Este, C., Eisman, J., Nguyen, T., Attia, J. (2004) Meta-analysis of molecular association studies: Vitamin D receptor gene polymorphisms and BMD as a case study. J Bone Miner Res 19:419–428.
Gong, G., Stern, H.S., Cheng, S.C., Fong, N., Mordeson, J., Deng, H.W., et al. (1999) The association of bone mineral density with vitamin D receptor gene polymorphisms. Osteoporos Int 9:55–64.
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Teare, M.D. (2011). Candidate Gene Association Studies. In: Teare, M. (eds) Genetic Epidemiology. Methods in Molecular Biology, vol 713. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-60327-416-6_8
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DOI: https://doi.org/10.1007/978-1-60327-416-6_8
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