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Challenges in reproducibility of genetic association studies: lessons learned from the obesity field

International Journal of Obesity volume 37, pages 559–567 (2013)Cite this article

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Abstract

A robust replication of initial genetic association findings has proved to be difficult in human complex diseases and more specifically in the obesity field. An obvious cause of non-replication in genetic association studies is the initial report of a false positive result, which can be explained by a non-heritable phenotype, insufficient sample size, improper correction for multiple testing, population stratification, technical biases, insufficient quality control or inappropriate statistical analyses. Replication may, however, be challenging even when the original study describes a true positive association. The reasons include underpowered replication samples, gene × gene, gene × environment interactions, genetic and phenotypic heterogeneity and subjective interpretation of data. In this review, we address classic pitfalls in genetic association studies and provide guidelines for proper discovery and replication genetic association studies with a specific focus on obesity.

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References

  1. Finucane MM, Stevens GA, Cowan MJ, Danaei G, Lin JK, Paciorek CJ et al. National, regional, and global trends in body-mass index since 1980: systematic analysis of health examination surveys and epidemiological studies with 960 country-years and 9.1 million participants. Lancet 2011; 377: 557–567.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Wardle J, Carnell S, Haworth CM, Plomin R . Evidence for a strong genetic influence on childhood adiposity despite the force of the obesogenic environment. Am J Clin Nutr 2008; 87: 398–404.

    Article  CAS  PubMed  Google Scholar 

  3. Rankinen T, Zuberi A, Chagnon YC, Weisnagel SJ, Argyropoulos G, Walts B et al. The human obesity gene map: the 2005 update. Obesity 2006; 14: 529–644.

    Article  PubMed  Google Scholar 

  4. Hirschhorn JN, Lohmueller K, Byrne E, Hirschhorn K . A comprehensive review of genetic association studies. Genet Med 2002; 4: 45–61.

    Article  CAS  PubMed  Google Scholar 

  5. Cordell HJ, Clayton DG . Genetic association studies. Lancet 2005; 366: 1121–1131.

    Article  PubMed  Google Scholar 

  6. Willer CJ, Speliotes EK, Loos RJ, Li S, Lindgren CM, Heid IM et al. Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nat Genet 2009; 41: 25–34.

    Article  CAS  PubMed  Google Scholar 

  7. Choquet H, Meyre D . Molecular basis of obesity: current status and future prospects. Curr Genomics 2011; 12: 154–168.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Chanock SJ, Manolio T, Boehnke M, Boerwinkle E, Hunter DJ, Thomas G et al. Replicating genotype-phenotype associations. Nature 2007; 447: 655–660.

    Article  CAS  PubMed  Google Scholar 

  9. Visscher PM, Hill WG, Wray NR . Heritability in the genomics era-concepts and misconceptions. Nat Rev Genet 2008; 9: 255–266.

    Article  CAS  PubMed  Google Scholar 

  10. Burton PR, Tobin MD, Hopper JL . Key concepts in genetic epidemiology. Lancet 2005; 366: 941–951.

    Article  PubMed  Google Scholar 

  11. Haworth CM, Plomin R, Carnell S, Wardle J . Childhood obesity: genetic and environmental overlap with normal-range BMI. Obesity 2008; 16: 1585–1590.

    Article  PubMed  Google Scholar 

  12. North KE, Graff M, Adair LS, Lange EM, Lange LA, Guo G et al. Genetic epidemiology of BMI and body mass change from adolescence to young adulthood. Obesity 2010; 18: 1474–1476.

    Article  PubMed  Google Scholar 

  13. Malis C, Rasmussen EL, Poulsen P, Petersen I, Christensen K, Beck-Nielsen H et al. Total and regional fat distribution is strongly influenced by genetic factors in young and elderly twins. Obes Res 2005; 13: 2139–2145.

    Article  PubMed  Google Scholar 

  14. Carnell S, Haworth CM, Plomin R, Wardle J . Genetic influence on appetite in children. Int J Obes 2008; 32: 1468–1473.

    Article  CAS  Google Scholar 

  15. Bouchard C, Tremblay A, Nadeau A, Despres JP, Theriault G, Boulay MR et al. Genetic effect in resting and exercise metabolic rates. Metabolism 1989; 38: 364–370.

    Article  CAS  PubMed  Google Scholar 

  16. Saunders CL, Chiodini BD, Sham P, Lewis CM, Abkevich V, Adeyemo AA et al. Meta-analysis of genome-wide linkage studies in BMI and obesity. Obesity 2007; 15: 2263–2275.

    Article  PubMed  Google Scholar 

  17. Stutzmann F, Vatin V, Cauchi S, Morandi A, Jouret B, Landt O et al. Non-synonymous polymorphisms in melanocortin-4 receptor protect against obesity: the two facets of a Janus obesity gene. Hum Mol Genet 2007; 16: 1837–1844.

    Article  CAS  PubMed  Google Scholar 

  18. Ichimura A, Hirasawa A, Poulain-Godefroy O, Bonnefond A, Hara T, Yengo L et al. Dysfunction of lipid sensor GPR120 leads to obesity in both mouse and human. Nature 2012; 483: 350–354.

    Article  CAS  PubMed  Google Scholar 

  19. Meyre D, Delplanque J, Chevre JC, Lecoeur C, Lobbens S, Gallina S et al. Genome-wide association study for early-onset and morbid adult obesity identifies three new risk loci in European populations. Nat Genet 2009; 41: 157–159.

    Article  CAS  PubMed  Google Scholar 

  20. Scherag A, Dina C, Hinney A, Vatin V, Scherag S, Vogel CI et al. Two new Loci for body-weight regulation identified in a joint analysis of genome-wide association studies for early-onset extreme obesity in French and german study groups. PLoS Genet 2010; 6: e1000916.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Ioannidis JP, Trikalinos TA, Ntzani EE, Contopoulos-Ioannidis DG . Genetic associations in large versus small studies: an empirical assessment. Lancet 2003; 361: 567–571.

    Article  PubMed  Google Scholar 

  22. Boutin P, Dina C, Vasseur F, Dubois S, Corset L, Seron K et al. GAD2 on chromosome 10p12 is a candidate gene for human obesity. PLoS Biol 2003; 1: E68.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Swarbrick MM, Waldenmaier B, Pennacchio LA, Lind DL, Cavazos MM, Geller F et al. Lack of support for the association between GAD2 polymorphisms and severe human obesity. PLoS Biol 2005; 3: e315.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Herbert A, Gerry NP, McQueen MB, Heid IM, Pfeufer A, Illig T et al. A common genetic variant is associated with adult and childhood obesity. Science 2006; 312: 279–283.

    Article  CAS  PubMed  Google Scholar 

  25. Dina C, Meyre D, Samson C, Tichet J, Marre M, Jouret B et al. Comment on ’A common genetic variant is associated with adult and childhood obesity’. Science 2007; 315: 187 author reply 187.

    Article  CAS  PubMed  Google Scholar 

  26. Loos RJ, Barroso I, O'Rahilly S, Wareham NJ . Comment on ’A common genetic variant is associated with adult and childhood obesity’. Science 2007; 315: 187 author reply 187.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Rosskopf D, Bornhorst A, Rimmbach C, Schwahn C, Kayser A, Kruger A et al. Comment on ’A common genetic variant is associated with adult and childhood obesity’. Science 2007; 315: 187 author reply 187.

    Article  CAS  PubMed  Google Scholar 

  28. Heid IM, Huth C, Loos RJ, Kronenberg F, Adamkova V, Anand SS et al. Meta-analysis of the INSIG2 association with obesity including 74,345 individuals: does heterogeneity of estimates relate to study design? PLoS Genet 2009; 5: e1000694.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Speliotes EK, Willer CJ, Berndt SI, Monda KL, Thorleifsson G, Jackson AU et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat Genet 2010; 42: 937–948.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Lyon HN, Emilsson V, Hinney A, Heid IM, Lasky-Su J, Zhu X et al. The association of a SNP upstream of INSIG2 with body mass index is reproduced in several but not all cohorts. PLoS Genet 2007; 3: e61.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Colhoun HM, McKeigue PM, Davey Smith G . Problems of reporting genetic associations with complex outcomes. Lancet 2003; 361: 865–872.

    Article  PubMed  Google Scholar 

  32. Chandalia M, Grundy SM, Adams-Huet B, Abate N . Ethnic differences in the frequency of ENPP1/PC1 121Q genetic variant in the Dallas Heart Study cohort. J Diabetes Complications 2007; 21: 143–148.

    Article  PubMed  Google Scholar 

  33. Klimentidis YC, Abrams M, Wang J, Fernandez JR, Allison DB . Natural selection at genomic regions associated with obesity and type-2 diabetes: East Asians and sub-Saharan Africans exhibit high levels of differentiation at type-2 diabetes regions. Hum Genet 2011; 129: 407–418.

    Article  PubMed  Google Scholar 

  34. Kettunen J, Silander K, Saarela O, Amin N, Muller M, Timpson N et al. European lactase persistence genotype shows evidence of association with increase in body mass index. Hum Mol Genet 2010; 19: 1129–1136.

    Article  CAS  PubMed  Google Scholar 

  35. Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM . Prevalence of overweight and obesity in the United States, 1999-2004. JAMA 2006; 295: 1549–1555.

    Article  CAS  PubMed  Google Scholar 

  36. Cardon LR, Palmer LJ . Population stratification and spurious allelic association. Lancet 2003; 361: 598–604.

    Article  PubMed  Google Scholar 

  37. Sen S, Burmeister M . Hardy-Weinberg analysis of a large set of published association studies reveals genotyping error and a deficit of heterozygotes across multiple loci. Hum Genomics 2008; 3: 36–52.

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Gordon D, Finch SJ, Nothnagel M, Ott J . Power and sample size calculations for case-control genetic association tests when errors are present: application to single nucleotide polymorphisms. Hum Hered 2002; 54: 22–33.

    Article  PubMed  Google Scholar 

  39. Bouatia-Naji N, De Graeve F, Bronner G, Lecoeur C, Vatin V, Durand E et al. INS VNTR is not associated with childhood obesity in 1,023 families: a family-based study. Obesity 2008; 16: 1471–1475.

    Article  PubMed  Google Scholar 

  40. Le Stunff C, Fallin D, Schork NJ, Bougneres P . The insulin gene VNTR is associated with fasting insulin levels and development of juvenile obesity. Nat Genet 2000; 26: 444–446.

    Article  CAS  PubMed  Google Scholar 

  41. Peters DL, Barber Rl, Flood EM, Garner HR, O'Keefe GE . Methodologic quality and genotyping reproducibility in studies of tumor necrosis factor -308G->A single nucleotide polymorphism and bacterial sepsis: implications for studies of complex traits. Crit Care Med 2003; 31: 1691–1696.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Saito YA, Talley NJ, de Andrade M, Petersen GM . Case-control genetic association studies in gastrointestinal disease: review and recommendations. Am J Gastroenterol 2006; 101: 1379–1389.

    Article  CAS  PubMed  Google Scholar 

  43. Frayling TM, Timpson NJ, Weedon MN, Zeggini E, Freathy RM, Lindgren CM 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: 889–894.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Page GP, George V, Go RC, Page PZ, Allison DB . ’Are we there yet?’: Deciding when one has demonstrated specific genetic causation in complex diseases and quantitative traits. Am J Hum Genet 2003; 73: 711–719.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Framework for a fully powered risk engine. Nat Genet 2005; 37: 1153.

  46. Dina C, Meyre D, Gallina S, Durand E, Korner A, Jacobson P et al. Variation in FTO contributes to childhood obesity and severe adult obesity. Nat Genet 2007; 39: 724–726.

    Article  CAS  PubMed  Google Scholar 

  47. Scuteri A, Sanna S, Chen WM, Uda M, Albai G, Strait J et al. Genome-wide association scan shows genetic variants in the FTO gene are associated with obesity-related traits. PLoS Genet 2007; 3: e115.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Hinney A, Nguyen TT, Scherag A, Friedel S, Bronner G, Muller TD et al. Genome wide association (GWA) study for early onset extreme obesity supports the role of fat mass and obesity associated gene (FTO) variants. PLoS One 2007; 2: e1361.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Hattersley AT, McCarthy MI . What makes a good genetic association study? Lancet 2005; 366: 1315–1323.

    Article  PubMed  Google Scholar 

  50. Speliotes EK, Willer CJ, Berndt SI, Monda KL, Thorleifsson G, Jackson AU et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat Genet 2010; 42: 937–948.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Zhao J, Bradfield JP, Zhang H, Sleiman PM, Kim CE, Glessner JT et al. Role of BMI-associated loci identified in GWAS meta-analyses in the context of common childhood obesity in European Americans. Obesity 2011; 19: 2436–2439.

    Article  CAS  PubMed  Google Scholar 

  52. Moonesinghe R, Khoury MJ, Liu T, Ioannidis JP . Required sample size and nonreplicability thresholds for heterogeneous genetic associations. Proc Natl Acad Sci USA 2008; 105: 617–622.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Burton PR, Hansell AL, Fortier I, Manolio TA, Khoury MJ, Little J et al. Size matters: just how big is BIG?: Quantifying realistic sample size requirements for human genome epidemiology. Int J Epidemiol 2009; 38: 263–273.

    Article  PubMed  Google Scholar 

  54. Aschard H, Hancock DB, London SJ, Kraft P . Genome-wide meta-analysis of joint tests for genetic and gene-environment interaction effects. Hum Hered 2010; 70: 292–300.

    Article  PubMed  Google Scholar 

  55. Luan JA, Wong MY, Day NE, Wareham NJ . Sample size determination for studies of gene-environment interaction. Int J Epidemiol 2001; 30: 1035–1040.

    Article  CAS  PubMed  Google Scholar 

  56. Gauderman WJ . Sample size requirements for association studies of gene-gene interaction. Am J Epidemiol 2002; 155: 478–484.

    Article  PubMed  Google Scholar 

  57. Dempfle A, Scherag A, Hein R, Beckmann L, Chang-Claude J, Schafer H . Gene-environment interactions for complex traits: definitions, methodological requirements and challenges. Eur J Hum Genet 2008; 16: 1164–1172.

    Article  CAS  PubMed  Google Scholar 

  58. Hein R, Beckmann L, Chang-Claude J . Sample size requirements for indirect association studies of gene-environment interactions (G x E). Genet Epidemiol 2008; 32: 235–245.

    Article  PubMed  Google Scholar 

  59. Kilpelainen TO, Qi L, Brage S, Sharp SJ, Sonestedt E, Demerath E 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: e1001116.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Okada Y, Kubo M, Ohmiya H, Takahashi A, Kumasaka N, Hosono N et al. Common variants at CDKAL1 and KLF9 are associated with body mass index in east Asian populations. Nat Genet 2012; 44: 302–306.

    Article  CAS  PubMed  Google Scholar 

  61. Gambaro G, Anglani F, D'Angelo A . Association studies of genetic polymorphisms and complex disease. Lancet 2000; 355: 308–311.

    Article  CAS  PubMed  Google Scholar 

  62. Peng S, Zhu Y, Xu F, Ren X, Li X, Lai M . FTO gene polymorphisms and obesity risk: a meta-analysis. BMC Med 2011; 9: 71.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Groves CJ, Zeggini E, Walker M, Hitman GA, Levy JC, O'Rahilly S et al. Significant linkage of BMI to chromosome 10p in the U.K. population and evaluation of GAD2 as a positional candidate. Diabetes 2006; 55: 1884–1889.

    Article  CAS  PubMed  Google Scholar 

  64. Sovio U, Mook-Kanamori DO, Warrington NM, Lawrence R, Briollais L, Palmer CN et al. Association between common variation at the FTO locus and changes in body mass index from infancy to late childhood: the complex nature of genetic association through growth and development. PLoS Genet 2011; 7: e1001307.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Salanti G, Southam L, Altshuler D, Ardlie K, Barroso I, Boehnke M et al. Underlying genetic models of inheritance in established type 2 diabetes associations. Am J Epidemiol 2009; 170: 537–545.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Meyre D, Bouatia-Naji N, Tounian A, Samson C, Lecoeur C, Vatin V et al. Variants of ENPP1 are associated with childhood and adult obesity and increase the risk of glucose intolerance and type 2 diabetes. Nat Genet 2005; 37: 863–867.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. McAteer JB, Prudente S, Bacci S, Lyon HN, Hirschhorn JN, Trischitta V et al. The ENPP1 K121Q polymorphism is associated with type 2 diabetes in European populations: evidence from an updated meta-analysis in 42,042 subjects. Diabetes 2008; 57: 1125–1130.

    Article  CAS  PubMed  Google Scholar 

  68. Ioannidis JP . Why most published research findings are false. PLoS Med 2005; 2: e124.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Ioannidis JP, Trikalinos TA . Early extreme contradictory estimates may appear in published research: the Proteus phenomenon in molecular genetics research and randomized trials. J Clin Epidemiol 2005; 58: 543–549.

    Article  PubMed  Google Scholar 

  70. Ott J, Kamatani Y, Lathrop M . Family-based designs for genome-wide association studies. Nat Rev Genet 2011; 12: 465–474.

    Article  CAS  PubMed  Google Scholar 

  71. Risch N, Merikangas K . The future of genetic studies of complex human diseases. Science 1996; 273: 1516–1517.

    Article  CAS  PubMed  Google Scholar 

  72. Yang J, Wray NR, Visscher PM . Comparing apples and oranges: equating the power of case-control and quantitative trait association studies. Genet Epidemiol 2010; 34: 254–257.

    Article  PubMed  Google Scholar 

  73. Putter C, Pechlivanis S, Nothen MM, Jockel KH, Wichmann HE, Scherag A . Missing heritability in the tails of quantitative traits? A simulation study on the impact of slightly altered true genetic models. Hum Hered 2011; 72: 172–180.

    Article  Google Scholar 

  74. Zondervan KT, Cardon LR . Designing candidate gene and genome-wide case-control association studies. Nat Protoc 2007; 2: 2492–2501.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Rouskas K, Kouvatsi A, Paletas K, Papazoglou D, Tsapas A, Lobbens S et al. Common variants in FTO, MC4R, TMEM18, PRL, AIF1, and PCSK1 show evidence of association with adult obesity in the Greek population. Obesity 2012; 20: 389–395.

    Article  CAS  PubMed  Google Scholar 

  76. Allison DB, Schork NJ . Selected methodological issues in meiotic mapping of obesity genes in humans: issues of power and efficiency. Behav Genet 1997; 27: 401–421.

    Article  CAS  PubMed  Google Scholar 

  77. Visscher TL, Viet AL, Kroesbergen IH, Seidell JC . Underreporting of BMI in adults and its effect on obesity prevalence estimations in the period 1998 to 2001. Obesity 2006; 14: 2054–2063.

    Article  PubMed  Google Scholar 

  78. Muller MJ, Bosy-Westphal A, Krawczak M . Genetic studies of common types of obesity: a critique of the current use of phenotypes. Obes Rev 2010; 11: 612–618.

    Article  CAS  PubMed  Google Scholar 

  79. Gradmark AM, Rydh A, Renstrom F, De Lucia-Rolfe E, Sleigh A, Nordstrom P et al. Computed tomography-based validation of abdominal adiposity measurements from ultrasonography, dual-energy X-ray absorptiometry and anthropometry. Br J Nutr 2010; 104: 582–588.

    Article  CAS  PubMed  Google Scholar 

  80. Fisher JO, Cai G, Jaramillo SJ, Cole SA, Comuzzie AG, Butte NF . Heritability of hyperphagic eating behavior and appetite-related hormones among Hispanic children. Obesity 2007; 15: 1484–1495.

    Article  PubMed  Google Scholar 

  81. Tracy RP . 'Deep phenotyping': characterizing populations in the era of genomics and systems biology. Curr Opin Lipidol 2008; 19: 151–157.

    Article  CAS  PubMed  Google Scholar 

  82. Kilpelainen TO, Zillikens MC, Stancakova A, Finucane FM, Ried JS, Langenberg C et al. Genetic variation near IRS1 associates with reduced adiposity and an impaired metabolic profile. Nat Genet 2011; 43: 753–760.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Muller MJ, Bosy-Westphal A, Later W, Haas V, Heller M . Functional body composition: insights into the regulation of energy metabolism and some clinical applications. Eur J Clin Nutr 2009; 63: 1045–1056.

    Article  CAS  PubMed  Google Scholar 

  84. Hoh J, Ott J . Genetic dissection of diseases: design and methods. Curr Opin Genet Dev 2004; 14: 229–232.

    Article  CAS  PubMed  Google Scholar 

  85. Geller F, Reichwald K, Dempfle A, Illig T, Vollmert C, Herpertz S et al. Melanocortin-4 receptor gene variant I103 is negatively associated with obesity. Am J Hum Genet 2004; 74: 572–581.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Benzinou M, Creemers JW, Choquet H, Lobbens S, Dina C, Durand E et al. Common nonsynonymous variants in PCSK1 confer risk of obesity. Nat Genet 2008; 40: 943–945.

    Article  CAS  PubMed  Google Scholar 

  87. Liu YJ, Guo YF, Zhang LS, Pei YF, Yu N, Yu P et al. Biological pathway-based genome-wide association analysis identified the vasoactive intestinal peptide (VIP) pathway important for obesity. Obesity 2010; 18: 2339–2346.

    Article  CAS  PubMed  Google Scholar 

  88. Johansson A, Marroni F, Hayward C, Franklin CS, Kirichenko AV, Jonasson I et al. Linkage and genome-wide association analysis of obesity-related phenotypes: association of weight with the MGAT1 gene. Obesity 2010; 18: 803–808.

    Article  CAS  PubMed  Google Scholar 

  89. Du H, Vimaleswaran KS, Angquist L, Hansen RD, van der AD, Holst C et al. Genetic polymorphisms in the hypothalamic pathway in relation to subsequent weight change-the DiOGenes study. PLoS One 2011; 6: e17436.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Greenawalt DM, Dobrin R, Chudin E, Hatoum IJ, Suver C, Beaulaurier J et al. A survey of the genetics of stomach, liver, and adipose gene expression from a morbidly obese cohort. Genome Res 2011; 21: 1008–1016.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. McCarthy MI, Abecasis GR, Cardon LR, Goldstein DB, Little J, Ioannidis JP et al. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nat Rev Genet 2008; 9: 356–369.

    Article  CAS  PubMed  Google Scholar 

  92. Nielsen DM, Ehm MG, Weir BS . Detecting marker-disease association by testing for Hardy-Weinberg disequilibrium at a marker locus. Am J Hum Genet 1998; 63: 1531–1540.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Wacholder S, Chanock S, Garcia-Closas M, El Ghormli L, Rothman N . Assessing the probability that a positive report is false: an approach for molecular epidemiology studies. J Natl Cancer Inst 2004; 96: 434–442.

    Article  PubMed  PubMed Central  Google Scholar 

  94. Lin DY . An efficient Monte Carlo approach to assessing statistical significance in genomic studies. Bioinformatics 2005; 21: 781–787.

    Article  CAS  PubMed  Google Scholar 

  95. Skol AD, Scott LJ, Abecasis GR, Boehnke M . Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies. Nat Genet 2006; 38: 209–213.

    Article  CAS  PubMed  Google Scholar 

  96. Serre D, Montpetit A, Pare G, Engert JC, Yusuf S, Keavney B et al. Correction of population stratification in large multi-ethnic association studies. PLoS One 2008; 3: e1382.

    Article  PubMed  PubMed Central  Google Scholar 

  97. Price AL, Helgason A, Palsson S, Stefansson H, Clair D, Andreassen OA et al. The impact of divergence time on the nature of population structure: an example from Iceland. PLoS Genet 2009; 5: e1000505.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Wu C, DeWan A, Hoh J, Wang Z . A comparison of association methods correcting for population stratification in case-control studies. Ann Hum Genet 2011; 75: 418–427.

    Article  PubMed  PubMed Central  Google Scholar 

  99. Hoggart CJ, Parra EJ, Shriver MD, Bonilla C, Kittles RA, Clayton DG et al. Control of confounding of genetic associations in stratified populations. Am J Hum Genet 2003; 72: 1492–1504.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Tian C, Gregersen PK, Seldin MF . Accounting for ancestry: population substructure and genome-wide association studies. Hum Mol Genet 2008; 17 (R2): R143–R150.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Sillanpaa MJ . Overview of techniques to account for confounding due to population stratification and cryptic relatedness in genomic data association analyses. Heredity 2011; 106: 511–519.

    Article  CAS  PubMed  Google Scholar 

  102. Spielman RS, McGinnis RE, Ewens WJ . Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM). Am J Hum Genet 1993; 52: 506–516.

    CAS  PubMed  PubMed Central  Google Scholar 

  103. Zollner S, Pritchard JK . Overcoming the winner's curse: estimating penetrance parameters from case-control data. Am J Hum Genet 2007; 80: 605–615.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Ioannidis JP, Patsopoulos NA, Evangelou E . Heterogeneity in meta-analyses of genome-wide association investigations. PLoS One 2007; 2: e841.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Gallo V, Egger M, McCormack V, Farmer PB, Ioannidis JP, Kirsch-Volders M et al. STrengthening the Reporting of OBservational studies in Epidemiology - Molecular Epidemiology (STROBE-ME): An Extension of the STROBE Statement. PLoS Med 2011; 8: e1001117.

    Article  PubMed  PubMed Central  Google Scholar 

  106. Minelli C, Thompson JR, Abrams KR, Thakkinstian A, Attia J . The quality of meta-analyses of genetic association studies: a review with recommendations. Am J Epidemiol 2009; 170: 1333–1343.

    Article  PubMed  PubMed Central  Google Scholar 

  107. Khoury MJ, Little J, Gwinn M, Ioannidis JP . On the synthesis and interpretation of consistent but weak gene-disease associations in the era of genome-wide association studies. Int J Epidemiol 2007; 36: 439–445.

    Article  PubMed  Google Scholar 

  108. Choquet H, Meyre D . Genetics of obesity: what have we learned? Curr Genomics 2011; 12: 169–179.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank Dipika Desai and Emeritus Professor Patricia Chang for reviewing and editing of the manuscript, and the reviewers for their helpful comments.

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  1. Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada

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Li, A., Meyre, D. Challenges in reproducibility of genetic association studies: lessons learned from the obesity field. Int J Obes 37, 559–567 (2013). https://doi.org/10.1038/ijo.2012.82

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