Genomics & Informatics

Korea Genome Organization (한국유전체학회)
권호 표지
DOI QR코드

DOI QR Code

A Short History of the Genome-Wide Association Study: Where We Were and Where We Are Going

  • Ikegawa, Shiro (Laboratory of Bone and Joint Diseases, Center for Genomic Medicine)
  • Received : 2012.09.24
  • Accepted : 2012.11.01
  • Published : 2012.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

Recent rapid advances in genetic research are ushering us into the genome sequence era, where an individual's genome information is utilized for clinical practice. The most spectacular results of the human genome study have been provided by genome-wide association studies (GWASs). This is a review of the history of GWASs as related to my work. Further efforts are necessary to make full use of its potential power to medicine.

Keywords

References

  1. Topol EJ, Murray SS, Frazer KA. The genomics gold rush. JAMA 2007;298:218-221. https://doi.org/10.1001/jama.298.2.218
  2. International HapMap Consortium. The International HapMap Project. Nature 2003;426:789-796. https://doi.org/10.1038/nature02168
  3. Lander ES, Linton LM, Birren B, Nusbaum C, Zody MC, Baldwin J, et al. Initial sequencing and analysis of the human genome. Nature 2001;409:860-921. https://doi.org/10.1038/35057062
  4. Istrail S, Sutton GG, Florea L, Halpern AL, Mobarry CM, Lippert R, et al. Whole-genome shotgun assembly and comparison of human genome assemblies. Proc Natl Acad Sci U S A 2004;101:1916-1921. https://doi.org/10.1073/pnas.0307971100
  5. Hirakawa M, Tanaka T, Hashimoto Y, Kuroda M, Takagi T, Nakamura Y. JSNP: a database of common gene variations in the Japanese population. Nucleic Acids Res 2002;30:158-162. https://doi.org/10.1093/nar/30.1.158
  6. Haga H, Yamada R, Ohnishi Y, Nakamura Y, Tanaka T. Gene-based SNP discovery as part of the Japanese Millennium Genome Project: identification of 190,562 genetic variations in the human genome. Single-nucleotide polymorphism. J Hum Genet 2002;47:605-610. https://doi.org/10.1007/s100380200092
  7. Ozaki K, Ohnishi Y, Iida A, Sekine A, Yamada R, Tsunoda T, et al. Functional SNPs in the lymphotoxin-alpha gene that are associated with susceptibility to myocardial infarction. Nat Genet 2002;32:650-654. https://doi.org/10.1038/ng1047
  8. Thomas DC, Haile RW, Duggan D. Recent developments in genomewide association scans: a workshop summary and review. Am J Hum Genet 2005;77:337-345. https://doi.org/10.1086/432962
  9. Morris AP, Cardon LR. Whole genome association. In: Handbook of Statistical Genetics. 3rd ed. (Balding DJ, Bishop M, Cannings C, eds.). Chichester: John Wiley & Sons, 2007. pp. 1238-1263.
  10. International Human Genome Sequencing Consortium. Finishing the euchromatic sequence of the human genome. Nature 2004;431:931-945. https://doi.org/10.1038/nature03001
  11. International HapMap Consortium. A haplotype map of the human genome. Nature 2005;437:1299-1320. https://doi.org/10.1038/nature04226
  12. Pennisi E. Breakthrough of the year: human genetic variation. Science 2007;318:1842-1843. https://doi.org/10.1126/science.318.5858.1842
  13. Mototani H, Mabuchi A, Saito S, Fujioka M, Iida A, Takatori Y, et al. A functional single nucleotide polymorphism in the core promoter region of CALM1 is associated with hip osteoarthritis in Japanese. Hum Mol Genet 2005;14:1009-1017. https://doi.org/10.1093/hmg/ddi093
  14. Suzuki A, Yamada R, Chang X, Tokuhiro S, Sawada T, Suzuki M, et al. Functional haplotypes of PADI4, encoding citrullinating enzyme peptidylarginine deiminase 4, are associated with rheumatoid arthritis. Nat Genet 2003;34:395-402. https://doi.org/10.1038/ng1206
  15. Tanaka N, Babazono T, Saito S, Sekine A, Tsunoda T, Haneda M, et al. Association of solute carrier family 12 (sodium/ chloride) member 3 with diabetic nephropathy, identified by genome-wide analyses of single nucleotide polymorphisms. Diabetes 2003;52:2848-2853. https://doi.org/10.2337/diabetes.52.11.2848
  16. Kim YJ, Go MJ, Hu C, Hong CB, Kim YK, Lee JY, et al. Large-scale genome-wide association studies in East Asians identify new genetic loci influencing metabolic traits. Nat Genet 2011;43:990-995. https://doi.org/10.1038/ng.939
  17. Okada Y, Sim X, Go MJ, Wu JY, Gu D, Takeuchi F, et al. Meta-analysis identifies multiple loci associated with kidney function-related traits in east Asian populations. Nat Genet 2012;44:904-909. https://doi.org/10.1038/ng.2352
  18. Wen W, Cho YS, Zheng W, Dorajoo R, Kato N, Qi L, et al. Meta-analysis identifies common variants associated with body mass index in east Asians. Nat Genet 2012;44:307-311. https://doi.org/10.1038/ng.1087
  19. Sanna S, Jackson AU, Nagaraja R, Willer CJ, Chen WM, Bonnycastle LL, et al. Common variants in the GDF5-UQCC region are associated with variation in human height. Nat Genet 2008;40:198-203. https://doi.org/10.1038/ng.74
  20. Castano Betancourt MC, Cailotto F, Kerkhof HJ, Cornelis FM, Doherty SA, Hart DJ, et al. Genome-wide association and functional studies identify the DOT1L gene to be involved in cartilage thickness and hip osteoarthritis. Proc Natl Acad Sci U S A 2012;109:8218-8223. https://doi.org/10.1073/pnas.1119899109
  21. Miyamoto Y, Shi D, Nakajima M, Ozaki K, Sudo A, Kotani A, et al. Common variants in DVWA on chromosome 3p24.3 are associated with susceptibility to knee osteoarthritis. Nat Genet 2008;40:994-998. https://doi.org/10.1038/ng.176
  22. Nakajima M, Miyamoto Y, Ikegawa S. Cloning and characterization of the osteoarthritis-associated gene DVWA. J Bone Miner Metab 2011;29:300-308. https://doi.org/10.1007/s00774-010-0230-z
  23. Kou I, Takahashi A, Urano T, Fukui N, Ito H, Ozaki K, et al. Common variants in a novel gene, FONG on chromosome 2q33.1 confer risk of osteoporosis in Japanese. PLoS One 2011;6:e19641. https://doi.org/10.1371/journal.pone.0019641
  24. Carninci P, Kasukawa T, Katayama S, Gough J, Frith MC, Maeda N, et al. The transcriptional landscape of the mammalian genome. Science 2005;309:1559-1563. https://doi.org/10.1126/science.1112014

Cited by

  1. Genome-wide association studies on prostate cancer: the end or the beginning? vol.4, pp.9, 2013, https://doi.org/10.1007/s13238-013-3055-4
  2. Advancing Personalized Medicine Through the Application of Whole Exome Sequencing and Big Data Analytics vol.10, pp.1664-8021, 2019, https://doi.org/10.3389/fgene.2019.00049