What should the genome-wide significance threshold be? Empirical replication of borderline genetic associations

International Journal of Epidemiology

Volumn 41, Issue 1, 2012, Pages 273-286

  Panagiotou, Orestis A ^a   Ioannidis, John P A ^a,b,c,d   Hirschhorn, Joel N ^e   Abecasis, Goncalo R ^e   Frayling, Timothy M ^e   McCarthy, Mark I ^e   Lindgren, Cecilia M ^e   Beaty, Terri H ^e   Eriksson, Nicholas ^e   Polychronakos, Constantin ^e   Kathirensan, Sekar ^e   Plenge, Robert M ^e   Spritz, Richard ^e   Payami, Haydeh ^e   Martin, Eden R ^e   Vance, Jeffery ^e   Su, Wen Hui ^e   Chang, Yu Sun ^e   Bei, Jin Xin ^e   Zeng, Yi Xin ^e   Paré, Guillaume ^e   Faraone, Stephen V ^e   Neale, Benjamine ^e   Anney, Richard J ^e   Traynor, Bryan J ^e   Scherag, André ^e   Hebebrand, Johannes ^e   Hinney, Anke ^e   Froguel, Philippe ^e   Meyre, David ^e   Chanock, Stephen J ^e   Kesheng, Wang ^e   more..

^a UNIVERSITY OF IOANNINA   (Greece)

^b INSTITUTE OF COMPUTER SCIENCE   (Greece)

^c STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^d STANFORD UNIVERSITY   (United States)

^e NONE

Author keywords

False discovery rate; Genome wide association study; Genome wide significance; Meta analysis; Replication

Indexed keywords

ALLELE; GENOME; GENOTYPE; META-ANALYSIS; PHENOTYPE;

ARTICLE; CONFIDENCE INTERVAL; EMPIRICAL RESEARCH; FALSE POSITIVE RESULT; GENE LINKAGE DISEQUILIBRIUM; GENE REPLICATION; GENETIC ASSOCIATION; GENETIC TRAIT; GENETIC VARIABILITY; GENOTYPE PHENOTYPE CORRELATION; HUMAN; PRIORITY JOURNAL;

EMPIRICAL RESEARCH; GENETIC ASSOCIATION STUDIES; GENOME-WIDE ASSOCIATION STUDY; HUMANS; POLYMORPHISM, SINGLE NUCLEOTIDE; REFERENCE STANDARDS;

EID: 84863338087     PISSN: 03005771     EISSN: 14643685     Source Type: Journal    
DOI: 10.1093/ije/dyr178     Document Type: Article

References (102)

1. McCarthy MI, Abecasis GR, Cardon LR et al. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nat Rev Genet 2008;9: 356-69.
2. A Catalog of Published Genome-Wide Association Studies. National Human Genome Research Institute. Available at http://www.genome.gov/26525384 (01 July 2011, date last accessed).
3. Ioannidis JP. Non-replication and inconsistency in the genome-wide association setting. Hum Hered 2007;64: 203-13.
4. Moonesinghe R, Khoury MJ, Liu T, Ioannidis JP. Required sample size and nonreplicability thresholds for heterogeneous genetic associations. Proc Natl Acad Sci USA 2008;105:617-22.
5. Kraft P, Zeggini E, Ioannidis JP. Replication in genome-wide association studies. Stat Sci 2009;24:561-73.
6. Chanock SJ, Manolio T, Boehnke M et al. Replicating genotype-phenotype associations. Nature 2007;447: 655-60.
7. 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.
8. Zeggini E, Scott LJ, Saxena R et al. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nat Genet 2008;40:638-45.
9. Ionita-Laza I, McQueen MB, Laird NM, Lange C. Genomewide weighted hypothesis testing in family-based association studies, with an application to a 100K scan. Am J Hum Genet 2007;81:607-14.
10. Storey JD, Tibshirani R. Statistical significance for genomewide studies. Proc Natl Acad Sci USA 2003;100: 9440-45.
11. Efron B. Simultaneous inference: When should hypothesis testing problems be combined? The Ann Appl Stat 2008;2:197-223.
12. Purcell S, Neale B, Todd-Brown K et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007;81:559-75.
13. Martin LJ, Woo JG, Avery CL et al. Multiple testing in the genomics era: findings from Genetic Analysis Workshop 15, Group 15. Genet Epidemiol 2007; 31(Suppl 1):S124-31.
14. Song K, Lu Q, Lin X, Waterworth D, Elston RC. Genome-wide association studies using an adaptive two-stage analysis for a case-control design. BMC Proc 2007;1(Suppl 1):S147.
15. Bland JM, Altman DG. Multiple significance tests: the Bonferroni method. BMJ 1995;310:170.
16. Ludbrook J. Multiple comparison procedures updated. Clin Exp Pharmacol Physiol 1998;25:1032-37.
17. Roeder K, Wasserman L. Genome-wide significance levels and weighted hypothesis testing. Stat Sci 2009;24: 398-413.
18. Aschard H, Guedj M, Demenais F. A two-step multiple-marker strategy for genome-wide association studies. BMC Proc 2007;1(Suppl 1):S134.
19. Stacey SN, Manolescu A, Sulem P et al. Common variants on chromosomes 2q35 and 16q12 confer susceptibility to estrogen receptor-positive breast cancer. Nat Genet 2007; 39:865-69.
20. Maraganore DM, de Andrade M, Lesnick TG et al. High-resolution whole-genome association study of Parkinson disease. Am J Hum Genet 2005;77:685-93.
21. Zanke BW, Greenwood CM, Rangrej J et al. Genome-wide association scan identifies a colorectal cancer susceptibility locus on chromosome 8q24. Nat Genet 2007;39: 989-94.
22. Anttila V, Stefansson H, Kallela M et al. Genome-wide association study of migraine implicates a common susceptibility variant on 8q22.1. Nat Genet 2010;42:869-73.
23. Soranzo N, Spector TD, Mangino M et al. A genome-wide meta-analysis identifies 22 loci associated with eight hematological parameters in the HaemGen consortium. Nat Genet 2009;41:1182-90.
24. Kathiresan S, Melander O, Guiducci C et al. Six new loci associated with blood low-density lipoprotein cholesterol, high-density lipoprotein cholesterol or triglycerides in humans. Nat Genet 2008;40:189-97.
25. Kamatani Y, Matsuda K, Okada Y et al. Genome-wide association study of hematological and biochemical traits in a Japanese population. Nat Genet 2010;42:210-15.
26. The Wellcome Trust Case Control Consortium. Genomewide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 2007;447: 661-78.
27. Barrett JC, Cardon LR. Evaluating coverage of genomewide association studies. Nat Genet 2006;38:659-62.
28. Hoggart CJ, Clark TG, De Iorio M, Whittaker JC, Balding DJ. Genome-wide significance for dense SNP and resequencing data. Genet Epidemiol 2008;32:179-85.
29. Pe'er I, Yelensky R, Altshuler D, Daly MJ. Estimation of the multiple testing burden for genomewide association studies of nearly all common variants. Genet Epidemiol 2008;32:381-85.
30. Orr N, Chanock S. Common genetic variation and human disease. Adv Genet 2008;62:1-32.
31. International HapMap Consortium. A haplotype map of the human genome. Nature 2005;437:1299-320.
32. Becker T, Herold C, Meesters C, Mattheisen M, Baur MP. Significance Levels in Genome-Wide Interaction Analysis (GWIA). Ann Hum Genet 2010;75:29-35.
33. Johnson RC, Nelson GW, Troyer JL et al. Accounting for multiple comparisons in a genome-wide association study (GWAS). BMC Genomics 2010;11:724.
34. 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 USA 2009;106:9362-67.
35. Ioannidis JP, Patsopoulos NA, Evangelou E. Heterogeneity in meta-analyses of genome-wide association investigations. PLoS One 2007;2:e841.
36. Zeggini E, Ioannidis JP. Meta-analysis in genome-wide association studies. Pharmacogenomics 2009;10:191-201.
37. Pereira TV, Patsopoulos NA, Salanti G, Ioannidis JP. Discovery properties of genome-wide association signals from cumulatively combined data sets. Am J Epidemiol 2009;170:1197-206.
38. Kippola TA, Santorico SA. Methods for combining multiple genome-wide linkage studies. Methods Mol Biol 2010; 620:541-60.
39. Hedges LV, Cooper H, Bushman BJ. Testing the null hypothesis in meta-anatysis: a comparison of combined probability and confidence interval procedures. Psychol Bull 1992;111:188-94.
40. StataCorp 2007. Stata Statistical Software: Release 10. College Station, TX: StataCorp LP.
41. Johnson AD, Handsaker RE, Pulit SL, Nizzari MM, O'Donnell CJ, de Bakker PI. SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap. Bioinformatics 2008;24:2938-39.
42. Sladek R, Rocheleau G, Rung J et al. A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature 2007;445:881-85.
43. Saxena R, Voight BF, Lyssenko V et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 2007;316:1331-36.
44. Scott LJ, Mohlke KL, Bonnycastle LL et al. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science 2007;316:1341-45.
45. Zeggini E, Weedon MN, Lindgren CM et al. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science 2007;316:1336-41.
46. Soranzo N, Rivadeneira F, Chinappen-Horsley U et al. Meta-analysis of genome-wide scans for human adult stature identifies novel Loci and associations with measures of skeletal frame size. PLoS Genet 2009;5:e1000445.
47. Gudbjartsson DF, Walters GB, Thorleifsson G et al. Many sequence variants affecting diversity of adult human height. Nat Genet 2008;40:609-15.
48. Weedon MN, Lango H, Lindgren CM et al. Genome-wide association analysis identifies 20 loci that influence adult height. Nat Genet 2008;40:575-83.
49. Ferreira MA, O'Donovan MC, Meng YA et al. Collaborative genome-wide association analysis supports a role for ANK3 and CACNA1C in bipolar disorder. Nat Genet 2008;40:1056-58.
50. Hunt KA, Zhernakova A, Turner G et al. Newly identified genetic risk variants for celiac disease related to the immune response. Nat Genet 2008;40:395-402.
51. Medland SE, Nyholt DR, Painter JN et al. Common variants in the trichohyalin gene are associated with straight hair in Europeans. Am J Hum Genet 2009;85: 750-55.
52. Mangold E, Ludwig KU, Birnbaum S et al. Genome-wide association study identifies two susceptibility loci for nonsyndromic cleft lip with or without cleft palate. Nat Genet 2010;42:24-26.
53. Grant SF, Wang K, Zhang H et al. A genome-wide association study identifies a locus for nonsyndromic cleft lip with or without cleft palate on 8q24. J Pediatr 2009;155: 909-13.
54. van Es MA, van Vught PW, Blauw HM et al. Genetic variation in DPP6 is associated with susceptibility to amyotrophic lateral sclerosis. Nat Genet 2008;40:29-31.
55. Lesch KP, Timmesfeld N, Renner TJ et al. Molecular genetics of adult ADHD: converging evidence from genome-wide association and extended pedigree linkage studies. J Neural Transm 2008;115:1573-85.
56. Pare G, Chasman DI, Parker AN et al. Novel association of HK1 with glycated hemoglobin in a non-diabetic population: a genome-wide evaluation of 14,618 participants in the Women's Genome Health Study. PLoS Genet 2008;4: e1000312.
57. Han J, Kraft P, Nan H et al. A genome-wide association study identifies novel alleles associated with hair color and skin pigmentation. PLoS Genet 2008;4:e1000074.
58. Murabito JM, Rosenberg CL, Finger D et al. A genome-wide association study of breast and prostate cancer in the NHLBI's Framingham Heart Study. BMC Med Genet 2007;8(Suppl 1):S6.
59. Amundadottir L, Kraft P, Stolzenberg-Solomon RZ et al. Genome-wide association study identifies variants in the ABO locus associated with susceptibility to pancreatic cancer. Nat Genet 2009;41:986-90.
60. Ng CC, Yew PY, Puah SM et al. A genome-wide association study identifies ITGA9 conferring risk of nasopharyngeal carcinoma. J Hum Genet 2009;54:392-97.
61. Samani NJ, Erdmann J, Hall AS et al. Genomewide association analysis of coronary artery disease. N Engl J Med 2007;357:443-53.
62. De Jager PL, Jia X, Wang J et al. Meta-analysis of genome scans and replication identify CD6, IRF8 and TNFRSF1A as new multiple sclerosis susceptibility loci. Nat Genet 2009;41:776-82.
63. Yang Q, Kathiresan S, Lin JP, Tofler GH, O'Donnell CJ. Genome-wide association and linkage analyses of hemostatic factors and hematological phenotypes in the Framingham Heart Study. BMC Med Genet 2007;8(Suppl 1):S12.
64. Willer CJ, Sanna S, Jackson AU et al. Newly identified loci that influence lipid concentrations and risk of coronary artery disease. Nat Genet 2008;40:161-69.
65. Simon-Sanchez J, Schulte C, Bras JM et al. Genome-wide association study reveals genetic risk underlying Parkinson's disease. Nat Genet 2009;41:1308-12.
66. Shi J, Levinson DF, Duan J et al. Common variants on chromosome 6p22.1 are associated with schizophrenia. Nature 2009;460:753-57.
67. Raychaudhuri S, Remmers EF, Lee AT et al. Common variants at CD40 and other loci confer risk of rheumatoid arthritis. Nat Genet 2008;40:1216-23.
68. Birlea SA, Gowan K, Fain PR, Spritz RA. Genome-wide association study of generalized vitiligo in an isolated European founder population identifies SMOC2, in close proximity to IDDM8. J Invest Dermatol 2010;130: 798-803.
69. Heard-Costa NL, Zillikens MC, Monda KL et al. NRXN3 is a novel locus for waist circumference: a genome-wide association study from the CHARGE Consortium. PLoS Genet 2009;5:e1000539.
70. Johansson A, Marroni F, Hayward C et al. Linkage and genome-wide association analysis of obesity-related phenotypes: association of weight with the MGAT1 gene. Obesity 2010;18:803-808.
71. Teslovich TM, Musunuru K, Smith AV et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature 2010;466:707-13.
72. Lango Allen H, Estrada K, Lettre G et al. Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature 2010;467:832-38.
73. Stahl EA, Raychaudhuri S, Remmers EF et al. Genome-wide association study meta-analysis identifies seven new rheumatoid arthritis risk loci. Nat Genet 2010; 42:508-14.
74. Bei JX, Li Y, Jia WH et al. A genome-wide association study of nasopharyngeal carcinoma identifies three new susceptibility loci. Nat Genet 2010;42:599-603.
75. Tse KP, Su WH, Chang KP et al. Genome-wide association study reveals multiple nasopharyngeal carcinomaassociated loci within the HLA region at chromosome 6p21.3. Am J Hum Genet 2009;85:194-203.
76. Gorroochurn P, Hodge SE, Heiman GA, Durner M, Greenberg DA. Non-replication of association studies: "pseudo-failures" to replicate? Genet Med 2007;9:325-31.
77. Seminara D, Khoury MJ, O'Brien TR et al. The emergence of networks in human genome epidemiology: challenges and opportunities. Epidemiology 2007;18:1-8.
78. Manolio TA, Rodriguez LL, Brooks L et al. New models of collaboration in genome-wide association studies: the Genetic Association Information Network. Nat Genet 2007;39:1045-51.
79. Mailman MD, Feolo M, Jin Y et al. The NCBI dbGaP database of genotypes and phenotypes. Nat Genet 2007; 39:1181-86.
80. McCarty CA, Chisholm RL, Chute CG et al. The eMERGE Network: a consortium of biorepositories linked to electronic medical records data for conducting genomic studies. BMC Med Genomics 2011;4:13.
81. Zeggini E. Next-generation association studies for complex traits. Nat Genet 2011;43:287-88.
82. Day-Williams AG, Zeggini E. The effect of nextgeneration sequencing technology on complex trait research. Eur J Clin Invest 2011;41:561-67.
83. Cambien F. Heritability, weak effects, and rare variants in genomewide association studies. Clin Chem 2011;57: 1263-66.
84. Hirschhorn JN, Lohmueller K, Byrne E, Hirschhorn K. A comprehensive review of genetic association studies. Genet Med 2002;4:45-61.
85. Greene CS, Penrod NM, Williams SM, Moore JH. Failure to replicate a genetic association may provide important clues about genetic architecture. PLoS One 2009;4:e5639.
86. Thomas D. Gene-environment-wide association studies: emerging approaches. Nat Rev Genet 2010;11:259-72.
87. Panagiotou OA, Evangelou E, Ioannidis JP. Genome-wide significant associations for variants with minor allele frequency of 5% or less-an overview: a HuGE review. Am J Epidemiol 2010;172:869-89.
88. Manolio TA, Collins FS, Cox NJ et al. Finding the missing heritability of complex diseases. Nature 2009;461:747-53.
89. Ioannidis JP, Tarone R, McLaughlin JK. The false positive to false negative ratio in epidemiologic investigations. Epidemiology 2011;22:450-56.
90. Park JH, Wacholder S, Gail MH et al. Estimation of effect size distribution from genome-wide association studies and implications for future discoveries. Nat Genet 2010; 42:570-75.
91. So H-C, Yip BHK, Sham P. Estimating the total number of susceptibility variants underlying complex diseases from genome-wide association studies. PLoS One 2010;5: e13898.
92. Khoury MJ, Bertram L, Boffetta P et al. Genome-wide association studies, field synopses, and the development of the knowledge base on genetic variation and human diseases. Am J Epidemiol 2009;170:269-79.
93. Bertram L, McQueen MB, Mullin K, Blacker D, Tanzi RE. Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database. Nat Genet 2007;39:17-23.
94. Ioannidis JP, Trikalinos TA, Ntzani EE, Contopoulos-Ioannidis DG. Genetic associations in large versus small studies: an empirical assessment. Lancet 2003;361: 567-71.
95. Ioannidis JP. Common genetic variants for breast cancer: 32 largely refuted candidates and larger prospects. J Natl Cancer Inst 2006;98:1350-53.
96. Ioannidis JP, Ntzani EE, Trikalinos TA, Contopoulos-Ioannidis DG. Replication validity of genetic association studies. Nat Genet 2001;29:306-309.
97. Kraft P. Curses-winner's and otherwise-in genetic epidemiology. Epidemiology 2008;19:649-51.
98. Zhong H, Prentice R. Correcting "winner's curse" in odds ratios from genomewide association findings for major complex human diseases. Genet Epidemiol 2010; 34:78-91.
99. Zollner S, Pritchard J. Overcoming the winner's curse: estimating penetrance parameters from case-control data. Am J Hum Genet 2007;80:605-15.
100. Galvan A, Ioannidis JP, Dragani TA. Beyond genome-wide association studies: genetic heterogeneity and individual predisposition to cancer. Trends Genet 2010;26:132-41.
101. Durbin R, Abecasis G, Altshuler D et al. A map of human genome variation from population-scale sequencing. Nature 2010;467:1061-73.
102. Ashley E, Butte A, Wheeler M et al. Clinical assessment incorporating a personal genome. Lancet 2010;375: 1525-35.