What usually refers to the effects of similar environmental conditions on genetically different individuals?

Gloster, H. M., Jr., & Neal, K. Skin cancer in skin of color. Journal of the American Academy of Dermatology 55, 741–760 (2006)

Hunter, D. J. Gene-environment interactions in human disease. Nature Reviews Genetics 6, 287–298 (2005) doi:10.1038/nrg1578 (link to article)

Lower, G. M., et al. N-acetyltransferase phenotype and risk in urinary bladder cancer: Approaches in molecular epidemiology. Preliminary results in Sweden and Denmark. Environmental Health Perspectives 29,71–79 (1979)

Pieau, C., & Dorizzi, M. Oestrogens and temperature-dependent sex determination in reptiles: All is in the gonads. Journal of Endocrinology 181, 367–377 (2004) doi:10.1677/joe.0.1810367

Pieau, C., et al. Temperature sensitivity of sexual differentiation of gonads in the European pond turtle. Journal of Experimental Zoology 270, 86–93 (1994) doi:10.1002/jez.1402700110

Riordan, J. R., et al. Identification of the cystic fibrosis gene: Cloning and characterization of complementary DNA. Science 245, 1066–1073 (1989)

Rommens, J. M., et al. Identification of the cystic fibrosis gene: Chromosome walking and jumping. Science 245, 1059–1065 (1989)

Papers of special note have been highlighted as:

▪ of interest

▪▪ of considerable interest

1. Garrod AE. The incidence of alkatonuria: a study in chemical individuality. Lancet. 1902;160:1616–1620. [Google Scholar]

2. Turesson G. The genotypical response of the plant species to the habitat. Hereditas. 1922;3:211–350. [Google Scholar]

3. Wright S. The roles of nutrition, inbreeding, crossbreeding, and selection in evolution. Proceedings of the Sixth Annual Congress of Genetics. 1932:356–366. [Google Scholar]

4. Gluckman PD, Hanson MA, Beedle AS. Non-genomic transgenerational inheritance of disease risk. Bioessays. 2007;29:145–154. [PubMed] [Google Scholar]

5. Scandalios JG. Response of plant antioxidant defense genes to environmental stress. Adv Genet. 1990;28:1–41. [PubMed] [Google Scholar]

6. Laurie DA, Bennett MD. Nuclear DNA content in the genera Zea and Sorghum: intergeneric, interspecific and intraspecific variation. Heredity. 1985;55:307–313. [Google Scholar]

7. Rayburn AL, Price HJ, Smith JD, Gold JR. C-band heterochromatin and DNA content in Zea mays. Am J Bot. 1985;72:1610–1617. [Google Scholar]

8. Rayburn AL, Auger JA. Nuclear DNA content variation in the ancient indigenous races of Mexican maize. Acta Botanica Neerlandica. 1990;39:197–202. [Google Scholar]

9. Yang W, Kelly T, He J. Genetic epidemiology of obesity. Epidemiol Rev. 2007;29:49–61. [PubMed] [Google Scholar]

10. Allard RW, Bradshaw AD. Implications of genotype–environmental interactions in applied plant breeding. Crop Sci. 1964;4:503–508. [Google Scholar]

11. Allard RW. John Wiley & Sons. Principles Of Plant Breeding. 2. Wiley-Blackwell; NY, USA: 1999. [Google Scholar]

12. Becker HC. Correlations among some statistical measures of phenotypic stability. Euphytica. 1981;30:835–840. [Google Scholar]

13. Haldane JBS. The interaction of nature and nurture. Ann Eugen. 1946;13:197–205. [PubMed] [Google Scholar]

14. Via S. The quantitative genetics of polyphagy in an insect herbivore. II. Genetic correlations in larval performance within and across host plants. Evolution. 1984;38:896–905. [PubMed] [Google Scholar]

15. Baye TM, Wilke RA, Olivier M. Genomic and geographic distribution of private SNPs and pathways in human populations. Per Med. 2009;6:623–641. [PMC free article] [PubMed] [Google Scholar]

16. Schnell FW. A study of methods and categories of plant breeding. Zeitschrift fuer Pflanzenzuechtung. 1982;89:1–18. [Google Scholar]

17. Wacholder S, Rothman N, Caporaso N. Population stratification in epidemiologic studies of common genetic variants and cancer: quantification of bias. J Natl Cancer Inst. 2000;92:1151–1158. [PubMed] [Google Scholar]

18. Campbell CD, Ogburn EL, Lunetta KL, et al. Demonstrating stratification in a European American population. Nat Genet. 2005;37:868–872. [PubMed] [Google Scholar]

19. Pritchard JK, Donnelly P. Case–control studies of association in structured or admixed populations. Theor Popul Biol. 2001;60:227–237. [PubMed] [Google Scholar]

20. Simmonds NW. Genotype (G), environment (E), and GE components of crop yields. Expl Agric. 1981;17:355–362. [Google Scholar]

21. Ziegler A, König IR. Statistical Approach to Genetic Epidemiology: Concepts and Applications. 2. Wiley-VCH; Germany: 2010. [Google Scholar]

22. Elston RC, Johnson WD. Basic Biostatistics For Geneticists And Epidemiologists: A Practical Approach. John Wiley & Sons; Hoboken, NJ, USA: 2008. [Google Scholar]

23. Vercelli D. Discovering susceptibility genes for asthma and allergy. Nat Rev Immunol. 2008;8:169–182. [PubMed] [Google Scholar]

24. Lin PI, Vance JM, Pericak-Vance MA, Martin ER. No gene is an island: the flip-flop phenomenon. Am J Hum Genet. 2007;80:531–538. [PMC free article] [PubMed] [Google Scholar]

25. Hernandez LM, Blazer DG, editors. Genes, Behavior, and the Social Environment: Moving Beyond the Nature/Nurture Debate. National Academies Press; Washington, DC, USA: 2006. [Google Scholar]

26. Pocock SJ. Clinical Trials: A Practical Approach. John Wiley & Sons; Hoboken, NJ, USA: 2004. [Google Scholar]

27. Lilienfeld DE, Stolley PD. Foundations of Epidemiology. 3. Oxford University Press; Oxford, UK: 1994. [Google Scholar]

28. Andrieu N, Goldstein AM. The case-combined-control design was efficient in detecting gene–environment interactions. J Clin Epidemiol. 2004;57:662–671. [PubMed] [Google Scholar]

29. Moffitt TE, Caspi A, Rutter M. Strategy for investigating interactions between measured genes and measured environments. Arch Gen Psychiatry. 2005;62:473–481. [PubMed] [Google Scholar]

30. Hemminki K, Lorenzo Bermejo J, Forsti A. The balance between heritable and environmental aetiology of human disease. Nat Rev Genet. 2006;7:958–965. [PubMed] [Google Scholar]

31. Dempfle A, Scherag A, Hein R, et al. Gene-environment interactions for complex traits: definitions, methodological requirements and challenges. Eur J Hum Genet. 2008;16:1164–1172. [PubMed] [Google Scholar]

32. Taubes G. Epidemiology faces its limits. Science. 1995;269:164–169. [PubMed] [Google Scholar]

33. Campbell MJ, Donner A, Klar N. Developments in cluster randomized trials and statistics in medicine. Stat Med. 2007;26:2–19. [PubMed] [Google Scholar]

34. Risch N, Merikangas K. The future of genetic studies of complex human diseases. Science. 1996;273:1516–1517. [PubMed] [Google Scholar]

35. McCarty CA, Wilke RA. Biobanks and pharmacogenomics. Pharmacogenomics. 2010;11(5):637–41. [PubMed] [Google Scholar]

36. McCarty CA, Wilke RA, Giampietro PF, Wesbrook SD, Caldwell MD. Marshfield Clinic Personalized Medicine Research Project (PMRP): design, methods, and recruitment for a large population-based biobank. Per Med. 2005;2:49–79. [PubMed] [Google Scholar]

37▪. Ritchie MD, Denny JC, Crawford DC, et al. Robust replication of genotype–phenotype associations across multiple diseases in an electronic medical record. Am J Hum Genet. 2010;86:560–572. Demonstrates that biobanks linked to routine clinical practice-based data can be used to characterize genetic associations previously idenitified in disease-based cohorts. [PMC free article] [PubMed] [Google Scholar]

38▪. Baye TM, Wilke RA. Mapping genes that predict treatment outcome in admixed populations. Pharmacogenomics J. 2010;10(6):465–477. Features the utilization of ancestry information in quantifying genetic determinants and interactions of treatment in an admixed population. [PMC free article] [PubMed] [Google Scholar]

39. Hunter DJ, Kraft P, Jacobs KB, et al. A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer. Nat Genet. 2007;39:870–874. [PMC free article] [PubMed] [Google Scholar]

40. Sladek R, Rocheleau G, Rung J, et al. A genome-wide association study identifies novel risk loci for Type II diabetes. Nature. 2007;445:881–885. [PubMed] [Google Scholar]

41. Yeager M, Orr N, Hayes RB, et al. Genome-wide association study of prostate cancer identifies a second risk locus at 8q24. Nat Genet. 2007;39:645–649. [PubMed] [Google Scholar]

42. Daly AK, Donaldson PT, Bhatnagar P, et al. HLA-B*5701 genotype is a major determinant of drug-induced liver injury due to flucloxacillin. Nat Genet. 2009;41:816–819. [PubMed] [Google Scholar]

43. Barber MJ, Mangravite LM, Hyde CL, et al. Genome-wide association of lipid-lowering response to statins in combined study populations. PLoS ONE. 2010;5:e9763. [PMC free article] [PubMed] [Google Scholar]

44. Moore JH, Williams SM. Epistasis and its implications for personal genetics. Am J Hum Genet. 2009;85:309–320. [PMC free article] [PubMed] [Google Scholar]

45. Willer CJ, Speliotes EK, Loos RJ, et al. Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nat Genet. 2009;41:25–34. [PMC free article] [PubMed] [Google Scholar]

46. McCarthy MI, Hirschhorn JN. Genome-wide association studies: potential next steps on a genetic journey. Hum Mol Genet. 2008;17:R156–R165. [PMC free article] [PubMed] [Google Scholar]

47. Cantor RM, Lange K, Sinsheimer JS. Prioritizing GWAS results: a review of statistical methods and recommendations for their application. Am J Hum Genet. 2010;86:6–22. [PMC free article] [PubMed] [Google Scholar]

48. Dickson SP, Wang K, Krantz I, Hakonarson H, Goldstein DB. Rare variants create synthetic genome-wide associations. PLoS Biol. 2010;8:e1000294. [PMC free article] [PubMed] [Google Scholar]

49. Robinson R. Common disease, multiple rare (and distant) variants. PLoS Biol. 2010;8:e1000293. [PMC free article] [PubMed] [Google Scholar]

50. Marchini J, Howie B. Genotype imputation for genome-wide association studies. Nat Rev Genet. 2010;11:499–511. [PubMed] [Google Scholar]

51. Marchini J, Howie B, Myers S, McVean G, Donnelly P. A new multipoint method for genome-wide association studies by imputation of genotypes. Nat Genet. 2007;39:906–913. [PubMed] [Google Scholar]

52▪▪. McCarty CA, Wilke RA. Biobanking and pharmacogenomics. Pharmacogenomics. 2010;11:637–641. Features the utilization of clinical practice-based datasets for quantifying genetic determinants of treatment outcome specifically within the context of relevant covariates. [PubMed] [Google Scholar]

53. Schatz M, Clark S, Camargo CA., Jr Sex differences in the presentation and course of asthma hospitalizations. Chest. 2006;129:50–55. [PubMed] [Google Scholar]

54. Eder W, Ege MJ, von Mutius E. The asthma epidemic. N Engl J Med. 2006;355:2226–2235. [PubMed] [Google Scholar]

55. Weiss ST, Raby BA, Rogers A. Asthma genetics and genomics 2009. Curr Opin Genet Dev. 2009;19:279–282. [PubMed] [Google Scholar]

56. Snyder EM, Beck KC, Dietz NM, et al. Influence of β2-adrenergic receptor genotype on airway function during exercise in healthy adults. Chest. 2006;129:762–770. [PubMed] [Google Scholar]

57. Drazen JM, Silverman EK, Lee TH. Heterogeneity of therapeutic responses in asthma. Br Med Bull. 2000;56:1054–1070. [PubMed] [Google Scholar]

58. Choudhry S, Ung N, Avila PC, et al. Pharmacogenetic differences in response to albuterol between Puerto Ricans and Mexicans with asthma. Am J Respir Crit Care Med. 2005;171:563–570. [PubMed] [Google Scholar]

59. Litonjua AA, Silverman EK, Tantisira KG, et al. β 2-adrenergic receptor polymorphisms and haplotypes are associated with airways hyperresponsiveness among nonsmoking men. Chest. 2004;126:66–74. [PubMed] [Google Scholar]

60. Ordovas JM, Mooser V. Nutrigenomics and nutrigenetics. Curr Opin Lipidol. 2004;15:101–108. [PubMed] [Google Scholar]

61. Brennan P. Gene–environment interaction and aetiology of cancer: what does it mean and how can we measure it? Carcinogenesis. 2002;23:381–387. [PubMed] [Google Scholar]

62. Gardiner SJ, Begg EJ. Pharmacogenetic testing for drug metabolizing enzymes: is it happening in practice? Pharmacogenet Genomics. 2005;15:365–369. [PubMed] [Google Scholar]

63. Zhang G, Khoo SK, Laatikainen T, et al. Opposite gene by environment interactions in Karelia for CD14 and CC16 single nucleotide polymorphisms and allergy. Allergy. 2009;64:1333–1341. [PubMed] [Google Scholar]

64. Bottema RW, Reijmerink NE, et al. Interleukin 13, CD14, pet and tobacco smoke influence atopy in three Dutch cohorts: the allergenic study. Eur Respir J. 2008;32:593–602. [PubMed] [Google Scholar]

65. Wilke RA, Lin DW, Roden DM, et al. Identifying genetic risk factors for serious adverse drug reactions: current progress and challenges. Nat Rev Drug Discov. 2007;6:904–916. [PMC free article] [PubMed] [Google Scholar]


Page 2

Analysis of variance taking genotype, treatment and environment as random into the analytical model.

Sourced.f.m.s.E(m.s.)
Genotypef1 = g−1m1σ2 + rσ2gte + erσ2gt + rtσ2ge + rteσ2g
Treatmentf2 = t−1m2σ2 + rσ2tge + erσ2gt + rgσ2te + regσ2t
Environmentf3 = e−1m3σ2 + rσ2gte + rtσ2ge + rgσ2te + rtgσ2e
G–Tf4 = f1f2m4σ2 + σ2gte + erσ2gt
G–Ef5 = f1f3m5σ2 + σ2gte + rtσ2ge
E–Tf6 = f2f3m6σ2 + σ2gte + rgσ2te
G–E–Tf7 = f1f2f3m7σ2 + σ2gte
ErrorF8 = (r−1)(g−1)tem8σ2