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Semin Reprod Med 2016; 34(04): 196-204
DOI: 10.1055/s-0036-1585406
Review Article
Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

An Introduction to Genome-Wide Association Studies: GWAS for Dummies

A. G. Uitterlinden
1   Department of Internal Medicine, Genetic Laboratory, Erasmus MC, Rotterdam, The Netherlands
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Publikationsverlauf

Publikationsdatum:
11. August 2016 (online)

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Abstract

Although the genetic origin of many human diseases and phenotypes has been long and widely recognized, identification of the causative gene alleles has been limited, slow, and cumbersome. This has changed substantially with the introduction of genome-wide association studies (GWASs) a decade ago, fueled by studies and reference projects of human genetic diversity and the development of novel DNA analysis technology applicable to high-throughput and large-scale data generation. Although GWASs essentially combine epidemiological study designs with molecular genetic analysis techniques, it has also fundamentally changed the way in which research was done in human genetics by the introduction of large consortia of collaborating investigators. GWASs have over flooded many clinical and basic research areas with gene discoveries, including those in reproductive medicine. This review describes aspects of GWAS methodology and how this field of human genetics is developing.

Keywords

genome-wide association study - complex disease - SNP - arrays
 

  • References

  • 1 Chong JX, Buckingham KJ, Jhangiani SN , et al; Centers for Mendelian Genomics. The genetic basis of Mendelian phenotypes: discoveries, challenges, and opportunities. Am J Hum Genet 2015; 97 (2) 199-215
    CrossrefPubMedGoogle Scholar
  • 2 Visscher PM, Brown MA, McCarthy MI, Yang J. Five years of GWAS discovery. Am J Hum Genet 2012; 90 (1) 7-24
    CrossrefPubMedGoogle Scholar
  • 3 Yang J, Bakshi A, Zhu Z , et al; LifeLines Cohort Study. Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index. Nat Genet 2015; 47 (10) 1114-1120
    CrossrefPubMedGoogle Scholar
  • 4 Hofman A, Brusselle GG, Darwish Murad S , et al. The Rotterdam study: 2016 objectives and design update. Eur J Epidemiol 2015; 30 (8) 661-708
    CrossrefPubMedGoogle Scholar
  • 5 Zheng HF, Forgetta V, Hsu YH , et al; AOGC Consortium; UK10K Consortium. Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture. Nature 2015; 526 (7571) 112-117
    CrossrefPubMedGoogle Scholar
  • 6 Minikel EV, Vallabh SM, Lek M , et al; Exome Aggregation Consortium (ExAC). Quantifying prion disease penetrance using large population control cohorts. Sci Transl Med 2016; 8 (322) 322ra9
    CrossrefPubMedGoogle Scholar