Skip to main content
SpringerLink
Log in

Genome-Wide Association Studies

  • Protocol
  • First Online:
Genetic Epidemiology

Part of the book series: Methods in Molecular Biology ((MIMB,volume 713))

Abstract

Genome-wide association (GWA) studies are best understood as an extension of candidate gene association studies, scaled up to cover hundreds of thousands of markers across the genome in samples usually of several thousand cases and controls. The GWA approach allows the detection of much smaller effect sizes than with previous linkage-based genome-wide studies. However, this sensitivity makes them vulnerable to false positive findings caused by subtle differences between cases and controls that may arise as a result of issues, such as genotyping errors, population stratification, and sample mix-ups as well as the more obvious issue of multiple testing. After some background and an introduction to GWA, studies are considered stage-by-stage with particular focus on quality control as this is by far the most time-consuming and complex issue related to GWA.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Risch N, Merikangas K (1996) The future of genetic studies of complex human diseases. Science 273(5281): 1516–1517.

    Article  PubMed  CAS  Google Scholar 

  2. Lander ES (1996) The new genomics: global views of biology. Science 274(5287): 536–539.

    Article  PubMed  CAS  Google Scholar 

  3. International HapMap Consortium (2003) The International HapMap Project. Nature 426: 789–796.

    Article  Google Scholar 

  4. McPherson R, Pertsemlidis A, Kavaslar N, Stewart A, Roberts R et al (2007) A common allele on chromosome 9 associated with coronary heart disease. Science 316(5830): 1488–1491.

    Article  PubMed  CAS  Google Scholar 

  5. Helgadottir A, Thorleifsson G, Manolescu A, Gretarsdottir S, Blondal T et al (2007) A common variant on chromosome 9p21 affects the risk of myocardial infarction. Science 316(5830): 1491–1493.

    Article  PubMed  CAS  Google Scholar 

  6. Wellcome Trust Case Control Consortium (2007) Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447: 661–678.

    Article  Google Scholar 

  7. Samani NJ, Erdmann J, Hall AS, Hengstenberg C, Mangino M et al (2007) Genomewide association analysis of coronary artery disease. N Engl J Med 357: 443–453.

    Article  PubMed  CAS  Google Scholar 

  8. Matarin M, Brown WM, Scholz S, Simon-Sanchez J, Fung HC et al (2007) A genome-wide genotyping study in patients with ischaemic stroke: initial analysis and data release. Lancet Neurol 6(5): 414–420.

    Article  PubMed  CAS  Google Scholar 

  9. Hunter DJ, Kraft P, Jacobs KB, Cox DG, Yeager M et al (2007) A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer. Nat Genet 39(7): 870–874.

    Article  PubMed  CAS  Google Scholar 

  10. Stacey SN, Manolescu A, Sulem P, Rafnar T, Gudmundsson J et al (2007) Common variants on chromosomes 2q35 and 16q12 confer susceptibility to estrogen receptor-positive breast cancer. Nat Genet 39(7): 865–869.

    Article  PubMed  CAS  Google Scholar 

  11. Easton DF, Pooley KA, Dunning AM, Pharoah PDP, Thompson D et al (2007) Genome-wide association study identifies novel breast cancer susceptibility loci. Nature 447: 1087–1093.

    Article  PubMed  CAS  Google Scholar 

  12. Sladek R, Rocheleau G, Rung J, Dina C, Shen L et al (2007) A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature 445(7130): 881–885.

    Article  PubMed  CAS  Google Scholar 

  13. Saxena R, Voight BF, Lyssenko V, Burtt NP, de Bakker PI et al (2007) Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 316(5829): 1331–1336.

    Article  PubMed  CAS  Google Scholar 

  14. Zeggini E, Weedon MN, Lindgren CM, Frayling TM, Elliott KS (2007) Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science 316(5829): 1336–1341.

    Article  PubMed  CAS  Google Scholar 

  15. Scott LJ, Mohlke KL, Bonnycastle LL, Willer CJ, Li Y et al (2007) A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science 316(5829): 1341–1345.

    Article  PubMed  CAS  Google Scholar 

  16. Frayling TM, Timpson NJ, Weedon MN, Zeggini E, Freathy RM (2007) A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 316(5826): 889–894.

    Article  PubMed  CAS  Google Scholar 

  17. Steinthorsdottir V, Thorleifsson G, Reynisdottir I, Benediktsson R, Jonsdottir T et al (2007) A variant in CDKAL1 influences insulin response and risk of type 2 diabetes. Nat Genet 39(6): 770–775.

    Article  PubMed  CAS  Google Scholar 

  18. Salonen JT, Uimari P, Aalto JM, Pirskanen M, Kaikkonen J et al (2007) Type 2 diabetes whole-genome association study in four populations: the DiaGen consortium. Am J Hum Genet 81(2): 338–345.

    Article  PubMed  CAS  Google Scholar 

  19. Chapman JM, Cooper JD, Todd JA, Clayton DG (2003) Detecting disease associations due to linkage disequilibrium using haplotype tags: a class of tests and the determinants of statistical power. Hum Hered 56: 18–31.

    Article  PubMed  Google Scholar 

  20. Iles MM (2008) What can genome-wide association studies tell us about the genetics of common disease? PLoS Genet 4(2): e33.

    Article  PubMed  Google Scholar 

  21. Novembre J, Johnson T, Bryc K, Kutalik Z, Boyko AR, Auton A, Indap A, King KS, Bergmann S, Nelson MR, Stephens M, Bustamante CD (2008) Genes mirror geography within Europe. Nature 456(7218): 98–101.

    Article  PubMed  CAS  Google Scholar 

  22. Clayton DG, Walker NM, Smyth DJ, Pask R, Cooper JD, Maier LM, Smink LJ, Lam AC, Ovington NR, Stevens HE, Nutland S, Howson JMM, Faham M, Moorhead M, Jones HB, Falkowski M, Hardenbol P, Willis TD, Todd JA (2005) Population structure, differential bias and genomic control in a large-scale, case-control association study. Nat Genet 37: 1243–1246.

    Article  PubMed  CAS  Google Scholar 

  23. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, Maller J, Sklar P, de Bakker PIW, Daly MJ, Sham PC (2007) PLINK: a toolset for whole-genome association and population-based linkage analyses. Am J Hum Genet 81(3): 559–575.

    Article  PubMed  CAS  Google Scholar 

  24. Devlin B, Roeder K (1999) Genomic control for association studies. Biometrics 55: 997–1004.

    Article  PubMed  CAS  Google Scholar 

  25. Devlin B, Roeder K (2001) Genomic control: a new approach to genetic-based association studies. Theor Pop Biol 60: 155–166.

    Article  CAS  Google Scholar 

  26. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet 38(8): 904–909.

    Article  PubMed  CAS  Google Scholar 

  27. Pritchard JK, Stephens M, Rosenberg NA, Donnelly P (2000) Association mapping in structured populations. Am J Hum Genet 67: 170–181.

    Article  PubMed  CAS  Google Scholar 

  28. Satten G, Flanders WD, Yang O (2001) Accounting for unmeasured population structure in case-control studies of genetic association using a novel latent-class model. Am J Hum Genet 68: 466–477.

    Article  PubMed  CAS  Google Scholar 

  29. Novembre J, Stephens M (2008) Interpreting principal component analyses of spatial population genetic variation. Nat Genet 40(5): 646–649.

    Article  PubMed  CAS  Google Scholar 

  30. Bishop DT, Demenais F, Iles MM, Harland M, Taylor JC, Corda E, Randerson-Moor J, Aitken JF, Avril MF, Azizi E, Bakker B, Bianchi-Scarrà G, Bressac-de Paillerets B, Calista D, Cannon-Albright LA, Chin-A-Woeng T, Dębniak T, Galore-Haskel G, Ghiorzo P, Gut I, Hansson J, Hočevar M, Höiom V, Hopper JL, Ingvar C, Kanetsky PA, Kefford RF, Landi MT, Lang J, Lubiński J, Mackie R, Malvehy J, Mann GJ, Martin NG, Montgomery GW, van Nieuwpoort FA, Novakovic S, Olsson H, Puig S, Weiss M, van Workum W, Zelenika D, Brown KM, Goldstein AM, Gillanders EM, Boland A, Galan P, Elder DE, Gruis NA, Hayward NK, Lathrop GM, Barrett JH, Newton Bishop JA (2009) Genome-wide association study identifies three loci associated with melanoma risk. Nat Genet 41(8): 920–925.

    Article  PubMed  CAS  Google Scholar 

  31. Gonzalez JR, Carrasco JL, Dudbridge F, Armengol L, Estivill X, Moreno V (2008) Maximising association statistics over genetic models. Genet Epidem 32: 246–254.

    Article  Google Scholar 

  32. Bacanu S-A, Nelson MR, Ehm MG (2008) Comparison of association methods for dense marker data. Genet Epidem 32: 791–799.

    Article  Google Scholar 

  33. Lunetta KL, Hayward BL, Segal J, Van Eerdewegh P (2004) Screening large-scale association study data: exploiting interactions using random forests. BMC Genet 5: 32.

    Article  PubMed  Google Scholar 

  34. Stefansson H, Rye DB, Hicks A, Petursson H, Ingason A (2007) A genetic risk factor for periodic limb movements in sleep. N Engl J Med 357(7): 639–647.

    Article  PubMed  CAS  Google Scholar 

  35. Gudmundsson J, Sulem P, Manolescu A, Amundadottir LT, Gudbjartsson D et al (2007) Genome-wide association study identifies a second prostate cancer susceptibility variant at 8q24. Nat Genet 39: 631–637.

    Article  PubMed  CAS  Google Scholar 

  36. International Multiple Sclerosis Genetics Consortium (2007) Risk alleles for multiple sclerosis identified by a genomewide study. N Engl J Med 357(9): 851–862.

    Article  Google Scholar 

  37. Haiman CA, Le Marchand L, Yamamato J, Stram DO, Sheng X et al (2007) A common genetic risk factor for colorectal and prostate cancer. Nat Genet 39: 954–956.

    Article  PubMed  CAS  Google Scholar 

  38. Zöllner S, Pritchard JK (2007) Overcoming the winner’s curse: estimating penetrance parameters from case-control data. Am J Hum Genet 80(4): 605–615.

    Article  PubMed  Google Scholar 

  39. Garner C (2007) Upward bias in odds ratio estimates from genome-wide association studies. Genet Epidemiol 31: 288–295.

    Article  PubMed  Google Scholar 

  40. NCI-NHGRI Working Group on Replication in Association Studies (2007) Replicating genotype-phenotype associations. Nature 447: 655–660.

    Article  Google Scholar 

  41. Marchini J, Howie B, Myers S, McVean G, Donnelly P (2007) A new multipoint method for genome-wide association studies via imputation of genotypes. Nat Genet 39: 906–913.

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Section of Epidemiology and Biostatistics, Leeds Institute for Molecular Medicine, University of Leeds, Leeds, UK

    Mark M. Iles

Authors
  1. Mark M. Iles
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Health and Related Research, Health Services Research, University of Sheffield, Regent Street 30, Sheffield, S1 4DA, United Kingdom

    M. Dawn Teare

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer Science+Business Media, LLC

About this protocol

Cite this protocol

Iles, M.M. (2011). Genome-Wide 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_7

Download citation

  • DOI: https://doi.org/10.1007/978-1-60327-416-6_7

  • Published:

  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-60327-415-9

  • Online ISBN: 978-1-60327-416-6

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation