Genetics in population health science: Strategies and opportunities

American Journal of Public Health

Volumn 103, Issue SUPPL.1, 2013, Pages

  Belsky, Daniel W ^a   Moffitt, Terrie E ^b,c,d   Caspi, Avshalom ^b,c,d  

^a DUKE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b DUKE UNIVERSITY   (United States)

^c DUKE UNIVERSITY MEDICAL CENTER   (United States)

^d KING'S COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; GENETIC ENGINEERING; GENETICS; GENOTYPE ENVIRONMENT INTERACTION; HUMAN; METHODOLOGY; OBESITY; PUBLIC HEALTH; RISK ASSESSMENT; SMOKING; TRANSLATIONAL RESEARCH;

GENE-ENVIRONMENT INTERACTION; GENETIC ENGINEERING; GENETIC RESEARCH; HUMANS; OBESITY; PUBLIC HEALTH; RISK ASSESSMENT; SMOKING; TRANSLATIONAL MEDICAL RESEARCH;

EID: 84884165344     PISSN: 00900036     EISSN: 15410048     Source Type: Journal    
DOI: 10.2105/AJPH.2012.301139     Document Type: Article

References (99)

1. Green ED, Guyer MS. Charting a course for genomic medicine from base pairs to bedside. Nature. 2011;470 (7333): 204-213.
2. Manolio TA, Green ED. Genomics reaches the clinic: from basic discoveries to clinical impact. Cell. 2011;147 (1): 14-16.
3. Rogowski WH, Grosse SD, Khoury MJ. Challenges of translating genetic tests into clinical and public health practice. Nat Rev Genet. 2009;10(7): 489-495.
4. Bloss CS, Darst BF, Topol EJ, Schork NJ. Direct-toconsumer personalized genomic testing. Hum Mol Genet. 2011;20(R2):R132-R141.
5. Guttmacher AE, McGuire AL, Ponder B, Stefansson K. Personalized genomic information: preparing for the future of genetic medicine. Nat Rev Genet. 2010;11(2): 161-165.
6. Berg JS, Khoury MJ, Evans JP. Deploying whole genome sequencing in clinical practice and public health: meeting the challenge one bin at a time. Genet Med. 2011;13(6): 499-504.
7. Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group. Recommendations from the EGAPP Working Group: genetic testing strategies in newly diagnosed individuals with colorectal cancer aimed at reducing morbidity and mortality from Lynch syndrome in relatives. Genet Med. 2009;11(1): 35-41.
8. Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group. Recommendations from the EGAPP Working Group: genomic profiling to assess cardiovascular risk to improve cardiovascular health. Genet Med. 2010;12(12): 839-843.
9. Khoury MJ, McCabe LL, McCabe ERB. Population screening in the age of genomic medicine. N Engl J Med. 2003;348(1): 50-58.
10. Roberts NJ, Vogelstein JT, Parmigiani G, Kinzler KW, Vogelstein B, Velculescu VE. The predictive capacity of personal genome sequencing. Sci Transl Med. 2012;4 (133): 133ra58.
11. Kathiresan S, Melander O, Anevski D, et al. Polymorphisms associated with cholesterol and risk of cardiovascular events. N Engl J Med. 2008;358(12): 1240-1249.
12. Meigs JB, Shrader P, Sullivan LM, et al. Genotype score in addition to common risk factors for prediction of type 2 diabetes. N Engl J Med. 2008;359(21): 2208-2219.
13. Lyssenko V, Jonsson A, Almgren P, et al. Clinical risk factors, DNA variants, and the development of type 2 diabetes. N Engl J Med. 2008;359(21): 2220-2232.
14. Paynter NP, Chasman DI, Pare G, et al. Association between a literature-based genetic risk score and cardiovascular events in women. JAMA. 2010;303(7): 631-637.
15. Talmud PJ, Hingorani AD, Cooper JA, et al. Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort study. BMJ. 2010;340(1):b4838.
16. Ripatti S, Tikkanen E, Orho-Melander M, et al. A multilocus genetic risk score for coronary heart disease: case-control and prospective cohort analyses. Lancet. 2010;376(9750): 1393-1400.
17. Manolio TA. Genomewide association studies and assessment of the risk of disease. N Engl J Med. 2010;363 (2): 166-176.
18. Helfand M, Buckley DI, Freeman M, et al. Emerging risk factors for coronary heart disease: a summary of systematic reviews conducted for the US Preventive Services Task Force. Ann Intern Med. 2009;151(7): 496-507.
19. McCormack M, Alfirevic A, Bourgeois S, et al. HLAA 3101 and carbamazepine-induced hypersensitivity reactions in Europeans. N Engl J Med. 2011;364(12): 1134-1143.
20. Auffray C, Caulfield T, Khoury MJ, Lupski JR, Schwab M, Veenstra T. Looking back at genomic medicine in 2011. Genome Med. 2012;4(1): 9.
21. National Human Genome Research Institute. eMERGE project. Available at: http://www.genome.gov/27540473. Accessed July 25, 2013.
22. Permanente Kaiser. Research program on genes, environment, and health. Available at: http://www.dor. kaiser.org/external/DORExternal/rpgeh/index.aspx. Accessed July 25, 2013.
23. Yoon PW, Scheuner MT, Peterson-Oehlke KL, Gwinn M, Faucett A, Khoury MJ. Can family history be used as a tool for public health and preventive medicine? Genet Med. 2002;4(4): 304-310.
24. Olney RS, Yoon PW. Role of family medical history information in pediatric primary care and public health: introduction. Pediatrics. 2007;120(suppl 2): S57-S59.
25. Morrison AC, Bare LA, Chambless LE, et al. Prediction of coronary heart disease risk using a genetic risk score: the Atherosclerosis Risk in Communities study. Am J Epidemiol. 2007;166(1): 28-35.
26. Plomin R, Haworth CMA, Davis OSP. Common disorders are quantitative traits. Nat Rev Genet. 2009;10 (12): 872-878.
27. Wray NR, Goddard ME, Visscher PM. Prediction of individual genetic risk to disease from genome-wide association studies. Genome Res. 2007;17(10): 1520-1528.
28. Belsky DW, Moffitt TE, Houts R, et al. Polygenic risk, rapid childhood growth, and the development of obesity: evidence from a 4-decade longitudinal study. Arch Pediatr Adolesc Med. 2012;166(6): 515-521.
29. Paynter N, Chasman DI, Pare G, et al. Prospective evaluation of a comprehensive genetic risk score for future cardiovascular events among 19,313 initially healthy women: the Women's Genome Health Study. Circulation. 2009;120(18):S607.
30. Yang J, Manolio TA, Pasquale LR, et al. Genome partitioning of genetic variation for complex traits using common SNPs. Nat Genet. 2011;43(6): 519-525.
31. Yang WJ, Kelly T, He J. Genetic epidemiology of obesity. Epidemiol Rev. 2007;29(1): 49-61.
32. Goldman D, Oroszi G, Ducci F. The genetics of addictions: uncovering the genes. Nat Rev Genet. 2005;6 (7): 521-532.
33. Keinan A, Clark AG. Recent explosive human population growth has resulted in an excess of rare genetic variants. Science. 2012;336(6082): 740-743.
34. Gibson G. Rare and common variants: twenty arguments. Nat Rev Genet. 2012;13(2): 135-145.
35. Visscher PM, Hill WG, Wray NR. Heritability in the genomics era-concepts and misconceptions. Nat Rev Genet. 2008;9(4): 255-266.
36. Belsky DW, Moffitt TE, Baker TB, et al. Polygenic risk accelerates the developmental progression to heavy, persistent smoking and nicotine dependence: evidence from a 4-decade longitudinal study. JAMA Psychiatry. 2013;70(5): 534-542.
37. Purcell SM, Wray NR, Stone JL, et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature. 2009;460(7256): 748-752.
38. Wald NJ, Hackshaw AK, Frost CD. When can a risk factor be used as a worthwhile screening test? BMJ. 1999;319(7224): 1562-1565.
39. Pepe MS, Janes H, Longton G, Leisenring W, Newcomb P. Limitations of the odds ratio in gauging the performance of a diagnostic, prognostic, or screening marker. Am J Epidemiol. 2004;159(9): 882-890.
40. Rockhill B. Theorizing about causes at the individual level while estimating effects at the population level: implications for prevention. Epidemiology. 2005;16(1): 124-129.
41. Huang Y, Pepe MS, Feng Z. Evaluating the predictiveness of a continuous marker. Biometrics. 2007;63 (4): 1181-1188.
42. Pencina MJ, D'Agostino RB Sr, D'Agostino RB Jr, Vasan RS. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat. Med. 2008;27(2): 157-172; discussion 207-212.
43. Belsky DW, Moffitt TE, Sugden K, et al. Development and evaluation of a genetic risk score for obesity. Biodemogr Social Biol. 2013;59(1): 87-104.
44. Hindorff LA, Sethupathy P, Junkins HA, et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc Natl Acad Sci U S A. 2009;106(23): 9362-9367.
45. Frayling TM, Timpson NJ, Weedon MN, et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science. 2007;316(5826): 889-894.
46. Plomin R, McGuffin P. Psychopathology in the postgenomic era. Annu Rev Psychol. 2003;54(1): 205-228.
47. Chen R, Mias GI, Li-Pook-Than J, et al. Personal omics profiling reveals dynamic molecular and medical phenotypes. Cell. 2012;148(6): 1293-1307.
48. Weissman MM, Brown AS, Talati A. Translational epidemiology in psychiatry: linking population to clinical and basic sciences. Arch Gen Psychiatry. 2011;68(6): 600-608.
49. Cirulli ET, Goldstein DB. Uncovering the roles of rare variants in common disease through whole-genome sequencing. Nat Rev Genet. 2010;11(6): 415-425.
50. Alkan C, Coe BP, Eichler EE. Genome structural variation discovery and genotyping. Nat Rev Genet. 2011;12(5): 363-376.
51. Ioannidis JP, Khoury MJ. Improving validation practices in "omics" research. Science. 2011;334(6060): 1230-1232.
52. Hindorff LA, Junkins HA, Mehta JP, Manolio TA. A catalog of published genome-wide association studies. Available at: http://www.genome.gov/gwastudies. Accessed April 30, 2010.
53. Gelernter J. Developmental perspective on the role of genes in smoking risk. Biol Psychiatry. 2011;69 (7): 616-617.
54. Ben-Shlomo Y, Kuh D. A life course approach to chronic disease epidemiology: conceptual models, empirical challenges and interdisciplinary perspectives. Int J Epidemiol. 2002;31(2): 285-293.
55. Ben-Shlomo Y. Rising to the challenges and opportunities of life course epidemiology. Int J Epidemiol. 2007;36(3): 481-483.
56. Nichols LM, Masdeu JC, Mattay VS, et al. Interactive effect of apolipoproteine genotype and age on hippocampal activation during memory processing in healthy adults. Arch Gen Psychiatry. 2012;69(8): 804-813.
57. Hartz SM, Short SE, Saccone NL, et al. Increased genetic vulnerability to smoking at CHRNA5 in earlyonset smokers. Arch Gen Psychiatry. 2012;69(8): 854-860.
58. Weiss RB, Baker TB, Cannon DS, et al. A candidate gene approach identifies the CHRNA5-A3-B4 region as a risk factor for age-dependent nicotine addiction. PLoS Genet. 2008;4(7):e1000125.
59. McMillen IC, Robinson JS. Developmental origins of the metabolic syndrome: prediction, plasticity, and programming. Physiol Rev. 2005;85(2): 571-633.
60. Frongillo EA, Lampl M. Early identification of children at risk of developing obesity. Arch Pediatr Adolesc Med. 2011;165(11): 1043-1044.
61. Jackson KM, Sher KJ, Rose RJ, Kapiro J. Trajectories of Tobacco Use from Adolescence to Adulthood: Are the Most Informative Phenotypes Tobacco Specific? Bethesda, MD: National Cancer Institute; 2009.
62. Bierut LJ. Genetic vulnerability and susceptibility to substance dependence. Neuron. 2011;69(4): 618-627.
63. Muennig P, Robertson D, Johnson G, Campbell F, Pungello EP, Neidell M. The effect of an early education program on adult health: the Carolina Abecedarian Project randomized controlled trial. Am J Public Health. 2011;101(3): 512-516.
64. Campbell FA, Pungello EP, Burchinal M, et al. Adult outcomes as a function of an early childhood educational program: an Abecedarian Project follow-up. Dev Psychol. 2012;48(4): 1033-1043.
65. Belfield CR, Nores M, Barnett S, Schweinhart L. The high/scope Perry preschool program: cost-benefit analysis using data from the age-40 followup. J Hum Resour. 2006;41(1): 162-190.
66. Heckman JJ, Moon SH, Pinto R, Savelyev PA, Yavitz A. The rate of return to the HighScope Perry Preschool Program. J Public Econ. 2010;94(1-2): 114-128.
67. Karelis AD. Metabolically healthy but obese individuals. Lancet. 2008;372(9646): 1281-1283.
68. Stefan N, Kantartzis K, Machann J, et al. Identification and characterization of metabolically benign obesity in humans. Arch Intern Med. 2008;168(15): 1609-1616.
69. McBride CM, Bryan AD, Bray MS, Swan GE, Green ED. Health behavior change: can genomics improve behavioral adherence? Am J Public Health. 2012;102 (3): 401-405.
70. Bryan AD, Hutchison KE. The role of genomics in health behavior change: challenges and opportunities. Public Health Genomics. 2012;15(3-4): 139-145.
71. Boffetta P, Winn DM, Ioannidis JP, et al. Recommendations and proposed guidelines for assessing the cumulative evidence on joint effects of genes and environments on cancer occurrence in humans. Int J Epidemiol. 2012;41(3): 686-704.
72. Link BG, Phelan J. Social conditions as fundamental causes of disease. J Health Soc Behav. 1995;35(extra issue): 80-94.
73. Bambra C, Gibson M, Sowden A, Wright K, Whitehead M, Petticrew M. Tackling the wider social determinants of health and health inequalities: evidence from systematic reviews. J Epidemiol Community Health. 2010;64(4): 284-291.
74. Marmot M. Social determinants of health inequalities. Lancet. 2005;365(9464): 1099-1104.
75. Bloom DE, Canning D. Policy forum: public health. The health and wealth of nations. Science. 2000;287 (5456): 1207-1209.
76. Shanahan MJ, Hofer SM. Social context in geneenvironment interactions: retrospect and prospect. J Gerontol B Psychol Sci Soc Sci. 2005;60(special issue 1): 65-76.
77. Boardman JD, Blalock CL, Pampel FC, Hatemi PK, Heath AC, Eaves LJ. Population composition, public policy, and the genetics of smoking. Demography. 2011;48(4): 1517-1533.
78. Barbeau EM, Krieger N, Soobader MJ. Working class matters: socioeconomic disadvantage, race/ethnicity, gender, and smoking in NHIS 2000. Am J Public Health. 2004;94(2): 269-278.
79. Drewnowski A. Obesity, diets, and social inequalities. Nutr Rev. 2009;67(suppl 1):S36-S39.
80. Poulton R, Caspi A, Milne BJ, et al. Association between children's experience of socioeconomic disadvantage and adult health: a life-course study. Lancet. 2002;360(9346): 1640-1645.
81. Li S, Zhao JH, Luan J, et al. Physical activity attenuates the genetic predisposition to obesity in 20,000 men and women from EPIC-Norfolk prospective population study. PLoS Med. 2010;7(8): e1000332.
82. Qi Q, Chu AY, Kang JH, et al. Sugar-sweetened beverages and genetic risk of obesity. N Engl J Med. 2012;367(15): 1387-1396.
83. Johnson EO, Chen LS, Breslau N, et al. Peer smoking and the nicotinic receptor genes: an examination of genetic and environmental risks for nicotine dependence. Addiction. 2010;105(11): 2014-2022.
84. Xie P, Kranzler HR, Zhang H, et al. Childhood adversity increases risk for nicotine dependence and interacts with a5 nicotinic acetylcholine receptor genotype specifically in males. Neuropsychopharmacology. 2012;37(3): 669-676.
85. Caspi A, McClay J, Moffitt TE, et al. Role of genotype in the cycle of violence in maltreated children. Science. 2002;297(5582): 851-854.
86. Thomas D. Gene-environment-wide association studies: emerging approaches. Nat Rev Genet. 2010;11 (4): 259-272.
87. Khoury MJ, Wacholder S. Invited commentary: from genome-wide association studies to gene-environmentwide interaction studies-challenges and opportunities. Am J Epidemiol. 2009;169(2): 227-230.
88. Cornelis MC, Tchetgen EJ, Liang L, et al. Geneenvironment interactions in genome-wide association studies: a comparative study of tests applied to empirical studies of type 2 diabetes. Am J Epidemiol. 2012;175 (3): 191-202.
89. Moffitt TE, Caspi A, Rutter M. Strategy for investigating interactions between measured genes and measured environments. Arch Gen Psychiatry. 2005;62 (5): 473-481.
90. Kilpeläinen TO, Qi L, Brage S, et al. Physical activity attenuates the influence of FTO variants on obesity risk: a meta-analysis of 218,166 adults and 19,268 children. PLoS Med. 2011;8(11):e1001116.
91. van Ijzendoorn MH, Bakermans-Kranenburg MJ, Belsky J, et al. Gene-by-environment experiments: a new approach to finding the missing heritability. Nat Rev Genet. 2011;12(12): 881.
92. Patel SR. Reduced sleep as an obesity risk factor. Obes Rev. 2009;10(suppl 2): 61-68.
93. Prats-Puig A, Grau-Cabrera P, Riera-Perez E, et al. Variations in the obesity genes FTO, TMEM18 and NRXN3 influence the vulnerability of children to weight gain induced by short sleep duration. Int J Obes (Lond). 2013;37(2): 182-187.
94. Rose JE, Behm FM, Drgon T, Johnson C, Uhl GR. Personalized smoking cessation: interactions between nicotine dose, dependence and quit-success genotype score. Mol Med. 2010;16(7-8): 247-253.
95. King DP, Paciga S, Pickering E, et al. Smoking cessation pharmacogenetics: analysis of varenicline and bupropion in placebo-controlled clinical trials. Neuropsychopharmacology. 2012;37(3): 641-650.
96. Chen LS, Baker TB, Piper ME, et al. Interplay of genetic risk factors (CHRNA5-CHRNA3-CHRNB4) and cessation treatments in smoking cessation success. Am J Psychiatry. 2012;169(7): 735-742.
97. Evans JP, Burke W, Khoury M. The rules remain the same for genomic medicine: the case against "reverse genetic exceptionalism." Genet Med. 2010;12(6): 342-343.
98. Evans JP, Meslin EM, Marteau TM, Caulfield Genomics T. Deflating the genomic bubble. Science. 2011;331(6019): 861-862.
99. Sullivan P. Don't give up on GWAS. Mol Psychiatry. 2012;17(1): 2-3.