Strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS): Explanation and elaboration

Journal of Clinical Epidemiology

Volumn 64, Issue 8, 2011, Pages

  Janssens, A Cecile J W ^a   Ioannidis, John P A ^b,c,d,e,f   Bedrosian, Sara ^g   Boffetta, Paolo ^h,i   Dolan, Siobhan M ^j   Dowling, Nicole ^g   Fortier, Isabel ^k   Freedman, Andrew N ^l   Grimshaw, Jeremy M ^m,n   Gulcher, Jeffrey ^o   Gwinn, Marta ^g   Hlatky, Mark A ^p   Janes, Holly ^q   Kraft, Peter ^r   Melillo, Stephanie ^g   O'Donnell, Christopher J ^s,t   Pencina, Michael J ^u,x   Ransohoff, David ^v   Schully, Sheri D ^l   Seminara, Daniela ^l   Winn, Deborah M ^l   Wright, Caroline F ^w   Van Duijn, Cornelia M ^a   Little, Julian ⁿ   Khoury, Muin J ^g,r   more..

^a ERASMUS MEDICAL CENTER   (Netherlands)

^b UNIVERSITY OF IOANNINA   (Greece)

^c INSTITUTE OF COMPUTER SCIENCE   (Greece)

^d TUFTS UNIVERSITY SCHOOL OF MEDICINE   (United States)

^e TUFTS MEDICAL CENTER   (United States)

^f STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^g NATIONAL CENTER ON BIRTH DEFECTS AND DEVELOPMENTAL DISABILITIES   (United States)

^h MOUNT SINAI SCHOOL OF MEDICINE   (United States)

ⁱ INTERNATIONAL PREVENTION RESEARCH INSTITUTE   (France)

^j ALBERT EINSTEIN COLLEGE OF MEDICINE   (United States)

^k Public Population Project in Genomics P3G   (Canada)

^l NATIONAL CANCER INSTITUTE   (United States)

^m OTTAWA HOSPITAL RESEARCH INSTITUTE   (Canada)

ⁿ UNIVERSITY OF OTTAWA   (Canada)

^o DECODE GENETICS   (Iceland)

^p STANFORD UNIVERSITY   (United States)

^q Fred Hutchinson Cancer Research Center   (United States)

^r HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

^s FRAMINGHAM HEART STUDY   (United States)

^t MASSACHUSETTS GENERAL HOSPITAL   (United States)

^u BOSTON UNIVERSITY   (United States)

^v UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

^w PHG FOUNDATION   (United Kingdom)

^x HARVARD CLINICAL RESEARCH INSTITUTE   (United States)

more..

Author keywords

[No Author keywords available]

Indexed keywords

ANTIOXIDANT; INSULIN; PLACEBO; ZINC;

ARTICLE; DIABETES MELLITUS; GENETIC ANALYSIS; GENETIC RISK; GENETIC RISK PREDICTION STUDY; GENETIC VARIABILITY; GENOTYPE; HUMAN; MEDICAL RESEARCH; NONHUMAN; PRIORITY JOURNAL; PROSTATE CANCER; PROSTATECTOMY; RETINA MACULA AGE RELATED DEGENERATION; SINGLE NUCLEOTIDE POLYMORPHISM; STUDY DESIGN; CANCER RISK; CARDIOVASCULAR RISK; CLINICAL PRACTICE; CLINICAL RESEARCH; EVIDENCE BASED MEDICINE; HEALTH CARE; MEDICAL EDUCATION; PRACTICE GUIDELINE; PROGNOSIS; RISK ASSESSMENT; TREATMENT RESPONSE;

CHECKLIST; GENETIC RESEARCH; GENOME-WIDE ASSOCIATION STUDY; GENOMICS; HUMANS; MODELS, GENETIC; PUBLISHING; FORECASTING; GENETIC MARKERS; GENETIC PREDISPOSITION TO DISEASE; GUIDELINES AS TOPIC; RESEARCH DESIGN; RISK ASSESSMENT;

EID: 79959687158     PISSN: 08954356     EISSN: 18785921     Source Type: Journal    
DOI: 10.1016/j.jclinepi.2011.02.003     Document Type: Article

References (92)

1. M.J. Khoury, M. Gwinn, P.W. Yoon, N. Dowling, C.A. Moore, and L.A. Bradley The continuum of translation research in genomic medicine: how can we accelerate the appropriate integration of human genome discoveries into health care and disease prevention? Genet Med 9 2007 665 674 (Pubitemid 350287151)
2. M.A. Hlatky, P. Greenland, D.K. Arnett, C.M. Ballantyne, M.H. Criqui, and M.S. Elkind Criteria for evaluation of novel markers of cardiovascular risk: a scientific statement from the American Heart Association Circulation 119 2009 2408 2416
3. A.C.J.W. Janssens, and C.M. Van Duijn Genome-based prediction of common diseases: methodological considerations for future research Genome Med 1 2009 20
4. M.J. Pencina, R.B. D'Agostino Sr., R.B. D'Agostino Jr., and R.S. Vasan Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond Stat Med 27 2008 157 172 (Pubitemid 351193639)
5. R. Mihaescu, M. van Zitteren, M. van Hoek, E.J. Sijbrands, A.G. Uitterlinden, and J.C. Witteman Improvement of risk prediction by genomic profiling: reclassification measures versus the area under the receiver operating characteristic curve Am J Epidemiol 172 2010 353 361
6. J.M. Seddon, R. Reynolds, J. Maller, J.A. Fagerness, M.J. Daly, and B. Rosner Prediction model for prevalence and incidence of advanced age-related macular degeneration based on genetic, demographic, and environmental variables Invest Ophthalmol Vis Sci 50 2009 2044 2053
7. R.K. Weersma, P.C. Stokkers, A.A. van Bodegraven, R.A. van Hogezand, H.W. Verspaget, and D.J. de Jong Molecular prediction of disease risk and severity in a large Dutch Crohn's disease cohort Gut 58 2009 388 395
8. J. Wang, M.R. Ban, G.Y. Zou, H. Cao, T. Lin, and B.A. Kennedy Polygenic determinants of severe hypertriglyceridemia Hum Mol Genet 17 2008 2894 2899
9. P.A. Kyzas, D. Denaxa-Kyza, and J.P. Ioannidis Quality of reporting of cancer prognostic marker studies: association with reported prognostic effect J Natl Cancer Inst 99 2007 236 243
10. P.A. Kyzas, K.T. Loizou, and J.P. Ioannidis Selective reporting biases in cancer prognostic factor studies J Natl Cancer Inst 97 2005 1043 1055 (Pubitemid 41417921)
11. L.M. McShane, D.G. Altman, W. Sauerbrei, S.E. Taube, M. Gion, and G.M. Clark REporting recommendations for tumor MARKer prognostic studies (REMARK) Nat Clin Pract Urol 2 2005 416 422 (Pubitemid 43115010)
12. P.A. Kyzas, D. Denaxa-Kyza, and J.P. Ioannidis Almost all articles on cancer prognostic markers report statistically significant results Eur J Cancer 43 2007 2559 2579 (Pubitemid 350086938)
13. I. Tzoulaki, G. Liberopoulos, and J.P. Ioannidis Assessment of claims of improved prediction beyond the Framingham risk score JAMA 302 2009 2345 2352
14. E. von Elm, and M. Egger The scandal of poor epidemiological research BMJ 329 2004 868 869 (Pubitemid 39422927)
15. I. Simera, D. Moher, J. Hoey, K.F. Schulz, and D.G. Altman A catalogue of reporting guidelines for health research Eur J Clin Invest 40 2010 35 53
16. E. Von Elm, D.G. Altman, M. Egger, S.J. Pocock, P.C. Gotzsche, and J.P. Vandenbroucke The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies PLoS Med 4 2007 e296
17. J. Little, J.P. Higgins, J.P. Ioannidis, D. Moher, F. Gagnon, and E. von Elm STrengthening the REporting of Genetic Association Studies (STREGA): an extension of the STROBE statement PLoS Med 6 2009 e22
18. P.M. Bossuyt, J.B. Reitsma, D.E. Bruns, C.A. Gatsonis, P.P. Glasziou, and L.M. Irwig Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative BMJ 326 2003 41 44 (Pubitemid 36110721)
19. A.C. Plint, D. Moher, A. Morrison, K. Schulz, D.G. Altman, C. Hill, and I. Gaboury Does the CONSORT checklist improve the quality of reports of randomised controlled trials? A systematic review Med J Aust 185 2006 263 267 (Pubitemid 44382877)
20. M.J. Khoury, and J.S. Dorman The Human Genome Epidemiology Network Am J Epidemiol 148 1998 1 3 (Pubitemid 28317537)
21. A.N. Freedman, D. Seminara, M.H. Gail, P. Hartge, G.A. Colditz, and R. Ballard-Barbash Cancer risk prediction models: a workshop on development, evaluation, and application J Natl Cancer Inst 97 2005 715 723 (Pubitemid 40872378)
22. M.J. Khoury, M. Gwinn, and J.P. Ioannidis The emergence of translational epidemiology: from scientific discovery to population health impact Am J Epidemiol 172 2010 517 524
23. K.G. Moons, D.G. Altman, Y. Vergouwe, and P. Royston Prognosis and prognostic research: application and impact of prognostic models in clinical practice BMJ 338 2009 b606
24. D.G. Altman, K.F. Schulz, D. Moher, M. Egger, F. Davidoff, and D. Elbourne The revised CONSORT statement for reporting randomized trials: explanation and elaboration Ann Intern Med 134 2001 663 694 (Pubitemid 32322245)
25. P.M. Bossuyt, J.B. Reitsma, D.E. Bruns, C.A. Gatsonis, P.P. Glasziou, and L.M. Irwig The STARD statement for reporting studies of diagnostic accuracy: explanation and elaboration Ann Intern Med 138 2003 W1 12
26. A. Liberati, D.G. Altman, J. Tetzlaff, C. Mulrow, P.C. Gotzsche, and J.P. Ioannidis The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration PLoS Med 6 2009 e1000100
27. J.P. Vandenbroucke, E. von Elm, D.G. Altman, P.C. Gotzsche, C.D. Mulrow, and S.J. Pocock Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration PLoS Med 4 2007 e297
28. T. Sparso, N. Grarup, C. Andreasen, A. Albrechtsen, J. Holmkvist, and G. Andersen Combined analysis of 19 common validated type 2 diabetes susceptibility gene variants shows moderate discriminative value and no evidence of gene-gene interaction Diabetologia 52 2009 1308 1314
29. C.A. Salinas, J.S. Koopmeiners, E.M. Kwon, L. FitzGerald, D.W. Lin, and E.A. Ostrander Clinical utility of five genetic variants for predicting prostate cancer risk and mortality Prostate 69 2009 363 372
30. J. Lauenborg, N. Grarup, P. Damm, K. Borch-Johnsen, T. Jorgensen, O. Pedersen, and T. Hansen Common Type 2 Diabetes Risk Gene Variants Associate with Gestational Diabetes J Clin Endocrinol Metab 94 2009 145 150
31. V. Lyssenko, A. Jonsson, P. Almgren, N. Pulizzi, B. Isomaa, and T. Tuomi Clinical risk factors, DNA variants, and the development of type 2 diabetes N Engl J Med 359 2008 2220 2232
32. M.N. Weedon, M.I. McCarthy, G. Hitman, M. Walker, C.J. Groves, and E. Zeggini Combining information from common type 2 diabetes risk polymorphisms improves disease prediction PLOS Med 3 2006 e374
33. A.C. Morrison, L.A. Bare, L.E. Chambless, S.G. Ellis, M. Malloy, and J.P. Kane Prediction of coronary heart disease risk using a genetic risk score: the Atherosclerosis Risk in Communities Study Am J Epidemiol 166 2007 28 35 (Pubitemid 47234300)
34. J.B. van der Net, A.C.J.W. Janssens, J.C. Defesche, J.J. Kastelein, E.J.G. Sijbrands, and E.W. Steyerberg Usefulness of genetic polymorphisms and conventional risk factors to predict coronary heart disease in patients with familial hypercholesterolemia Am J Cardiol 103 2009 375 380
35. X. Wu, J. Lin, H.B. Grossman, M. Huang, J. Gu, and C.J. Etzel Projecting individualized probabilities of developing bladder cancer in white individuals J Clin Oncol 25 2007 4974 4981 (Pubitemid 350220430)
36. S.S. Wong, N.L. Wilczynski, R.B. Haynes, and R. Ramkissoonsingh Developing optimal search strategies for detecting sound clinical prediction studies in MEDLINE AMIA Annu Symp Proc 2003 728 732
37. N.L. Wilczynski, and R.B. Haynes Developing optimal search strategies for detecting clinically sound prognostic studies in MEDLINE: an analytic survey BMC Med 2 2004 23
38. Y.S. Aulchenko, S. Ripatti, I. Lindqvist, D. Boomsma, I.M. Heid, and P.P. Pramstaller Loci influencing lipid levels and coronary heart disease risk in 16 European population cohorts Nat Genet 41 2009 47 55
39. A.C.J.W. Janssens, and C.M. Van Duijn Genome-based prediction of common diseases: advances and prospects Hum Mol Genet 17 2008 R166 R173
40. M. van Hoek, A. Dehghan, J.C. Witteman, C.M. Van Duijn, A.G. Uitterlinden, and B.A. Oostra Predicting type 2 diabetes based on polymorphisms from genome-wide association studies: a population-based study Diabetes 57 2008 3122 3128
41. M. Vaxillaire, J. Veslot, C. Dina, C. Proenca, S. Cauchi, and G. Charpentier Impact of common type 2 diabetes risk polymorphisms in the DESIR prospective study Diabetes 57 2008 244 254
42. H. Lango, C.N. Palmer, A.D. Morris, E. Zeggini, A.T. Hattersley, and M.I. Mc Carthy Assessing the combined impact of 18 common genetic variants of modest effect sizes on type 2 diabetes risk Diabetes 57 2008 3129 3135
43. J. Maller, S. George, S. Purcell, J. Fagerness, D. Altshuler, M.J. Daly, and J.M. Seddon Common variation in three genes, including a noncoding variant in CFH, strongly influences risk of age-related macular degeneration Nat Genet 38 2006 1055 1059 (Pubitemid 44325932)
44. S. Kathiresan, O. Melander, D. Anevski, C. Guiducci, N.P. Burtt, and C. Roos Polymorphisms associated with cholesterol and risk of cardiovascular events N Engl J Med 358 2008 1240 1249 (Pubitemid 351439225)
45. J.B. Meigs, P. Shrader, L.M. Sullivan, J.B. McAteer, C.S. Fox, and J. Dupuis Genotype score in addition to common risk factors for prediction of type 2 diabetes N Engl J Med 359 2008 2208 2219
46. H.M. Wain, E.A. Bruford, R.C. Lovering, M.J. Lush, M.W. Wright, and S. Povey Guidelines for human gene nomenclature Genomics 79 2002 464 470 (Pubitemid 34274283)
47. S.T. Sherry, M.H. Ward, M. Kholodov, J. Baker, L. Phan, E.M. Smigielskie, and K. Sirotkin dbSNP: the NCBI database of genetic variation Nucleic Acids Res 29 2001 308 311 (Pubitemid 32054478)
48. A.W. Plat, H.E.J.H. Stoffers, O.H. Klungel, C.P. van Schayck, P.W. de Leeuw, and F.L. Soomers The contribution of six polymorphisms to cardiovascular risk in a Dutch high-risk primary care population: the HIPPOCRATES project J Hum Hypertens 23 2009 659 667
49. P.J. Talmud, A.D. Hingorani, J.A. Cooper, M.G. Marmot, E.J. Brunner, and M. Kumari Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort study BMJ 340 2010 b4838
50. M.S. Pepe, and H.E. Janes Gauging the performance of SNPs, biomarkers, and clinical factors for predicting risk of breast cancer J Natl Cancer Inst 100 2008 978 979 (Pubitemid 352019802)
51. M.V. Podgoreanu, W.D. White, R.W. Morris, J.P. Mathew, M. Stafford-Smith, and I.J. Welsby Inflammatory gene polymorphisms and risk of postoperative myocardial infarction after cardiac surgery Circulation 114 2006 I 275
52. S.E. Humphries, J.A. Cooper, P.J. Talmud, and G.J. Miller Candidate gene genotypes, along with conventional risk factor assessment, improve estimation of coronary heart disease risk in healthy UK men Clin Chem 53 2007 8 16 (Pubitemid 46047758)
53. N.P. Paynter, D.I. Chasman, J.E. Buring, D. Shiffman, N.R. Cook, and P.M. Ridker Cardiovascular disease risk prediction with and without knowledge of genetic variation at chromosome 9p21.3 Ann Intern Med 150 2009 65 72
54. X. Lin, K. Song, N. Lim, X. Yuan, T. Johnson, and A. Abderrahmani Risk prediction of prevalent diabetes in a Swiss population using a weighted genetic score-the CoLaus Study Diabetologia 52 2009 600 608
55. J.P. Ioannidis Why most discovered true associations are inflated Epidemiology 19 2008 640 648
56. S.E. Bleeker, H.A. Moll, E.W. Steyerberg, A.R. Donders, G. Derksen-Lubsen, D.E. Grobbee, and K.G. Moons External validation is necessary in prediction research: a clinical example J Clin Epidemiol 56 2003 826 832 (Pubitemid 37162656)
57. D.G. Altman, Y. Vergouwe, P. Royston, and K.G. Moons Prognosis and prognostic research: validating a prognostic model BMJ 338 2009 b605
58. P. Royston, K.G. Moons, D.G. Altman, and Y. Vergouwe Prognosis and prognostic research: Developing a prognostic model BMJ 338 2009 b604
59. H. Janes, M.S. Pepe, and W. Gu Assessing the value of risk predictions by using risk stratification tables Ann Intern Med 149 2008 751 760
60. E.W. Steyerberg, A.J. Vickers, N.R. Cook, T. Gerds, M. Gonen, and N. Obuchowski Assessing the Performance of Prediction Models: A Framework for Traditional and Novel Measures Epidemiology 21 2010 128 138
61. M.S. Pepe, Z. Feng, Y. Huang, G. Longton, R. Prentice, I.M. Thompson, and Y. Zheng Integrating the predictiveness of a marker with its performance as a classifier Am J Epidemiol 167 2008 362 368 (Pubitemid 351197592)
62. A.C.J.W. Janssens, and M.J. Khoury Assessment of improved prediction beyond traditional risk factors: when does a difference make a difference? Circ: Cardiovasc Genet 3 2010 3 5
63. N.R. Cook, and P.M. Ridker Advances in measuring the effect of individual predictors of cardiovascular risk: the role of reclassification measures Ann Intern Med 150 2009 795 802
64. S.L. Zheng, J. Sun, F. Wiklund, S. Smith, P. Stattin, and G. Li Cumulative association of five genetic variants with prostate cancer N Engl J Med 358 2008 910 919 (Pubitemid 351397090)
65. A.D. Oxman, and G.H. Guyatt A consumer's guide to subgroup analyses Ann Intern Med 116 1992 78 84
66. R.J.A. Little, and D.B. Rubin Statistical analysis with missing data 1987 John Wiley & Sons New York
67. J.P. Ioannidis, E.Y. Loy, R. Poulton, and K.S. Chia Researching genetic versus nongenetic determinants of disease: a comparison and proposed unification Sci Transl Med 1 2009 7ps8
68. G.D. Smith, D.A. Lawlor, R. Harbord, N. Timpson, I. Day, and S. Ebrahim Clustered environments and randomized genes: a fundamental distinction between conventional and genetic epidemiology PLoS Med 4 2007 e352
69. S.M. Purcell, N.R. Wray, J.L. Stone, P.M. Visscher, and M.C. O'Donovan Common polygenic variation contributes to risk of schizophrenia and bipolar disorder Nature 460 2009 748 752
70. J.P. Ioannidis Why most published research findings are false PLoS Med 2 2005 e124
71. J.P. Ioannidis Limitations are not properly acknowledged in the scientific literature J Clin Epidemiol 60 2007 324 329 (Pubitemid 46341712)
72. R. Horton The hidden research paper JAMA 287 2002 2775 2778 (Pubitemid 34591961)
73. M. Docherty, and R. Smith The case for structuring the discussion of scientific papers BMJ 318 1999 1224 1225 (Pubitemid 29210047)
74. M. Clarke, and I. Chalmers Discussion sections in reports of controlled trials published in general medical journals: islands in search of continents? JAMA 280 1998 280 282 (Pubitemid 28493908)
75. B. Lumbreras, L.A. Parker, M. Porta, M. Pollan, J.P. Ioannidis, and I. Hernandez-Aguado Overinterpretation of clinical applicability in molecular diagnostic research Clin Chem 55 2009 786 794
76. J. Gulcher, and K. Stefansson Genetic risk information for common diseases may indeed be already useful for prevention and early detection Eur J Clin Invest 40 2010 56 63
77. F. Liu, K. van Duijn, J.R. Vingerling, A. Hofman, A.G. Uitterlinden, A.C. Janssens, and M. Kayser Eye color and the prediction of complex phenotypes from genotypes Curr Biol 19 2009 R192 R193
78. W. Yu, T. Liu, R. Valdez, M. Gwinn, and M.J. Khoury Application of support vector machine modeling for prediction of common diseases: the case of diabetes and pre-diabetes BMC Med Inform Decis Mak 10 2010 16
79. J.P. Ioannidis, D.B. Allison, C.A. Ball, I. Coulibaly, X. Cui, and A.C. Culhane Repeatability of published microarray gene expression analyses Nat Genet 41 2009 149 155
80. M.D. Mailman, M. Feolo, Y. Jin, M. Kimura, K. Tryka, and R. Bagoutdinov The NCBI dbGaP database of genotypes and phenotypes Nat Genet 39 2007 1181 1186 (Pubitemid 47482671)
81. T.A. Manolio, L.L. Rodriguez, L. Brooks, G. Abecasis, D. Ballinger, and M. Daly New models of collaboration in genome-wide association studies: the Genetic Association Information Network Nat Genet 39 2007 1045 1051 (Pubitemid 47340660)
82. P.A. Rochon, J. Hoey, A.W. Chan, L.E. Ferris, J. Lexchin, and S.R. Kalkaer Financial conflicts of interest checklist 2010 for clinical research studies Open Medicine 4 2010 e70
83. J.P. Vandenbroucke STREGA, STROBE, STARD, SQUIRE, MOOSE, PRISMA, GNOSIS, TREND, ORION, COREQ, QUOROM, REMARK. and CONSORT: for whom does the guideline toll? J Clin Epidemiol 62 2009 594 596
84. D. Moher, K.F. Schulz, I. Simera, and D.G. Altman Guidance for developers of health research reporting guidelines PLoS Med 7 2010 e1000217
85. N. Smidt, A.W. Rutjes, D.A. van der Windt, R.W. Ostelo, P.M. Bossuyt, and J.B. Reitsma The quality of diagnostic accuracy studies since the STARD statement: has it improved? Neurology 67 2006 792 797 (Pubitemid 44394191)
86. S. Hopewell, S. Dutton, L. Yu, A. Chan, and D.G. Altman The quality of reports of randomised trials in 2000 and 2006: comparative study of articles indexed in PubMed BMJ 340 2010 c723
87. D.G. Altman, I. Simera, J. Hoey, D. Moher, and K. Schulz EQUATOR: reporting guidelines for health research Lancet 371 2008 1149 1150 (Pubitemid 351467721)
88. N.R. Cook Use and misuse of the receiver operating characteristic curve in risk prediction Circulation 115 2007 928 935 (Pubitemid 46294733)
89. B. Balkau, C. Lange, L. Fezeu, J. Tichet, B. Lauzon-Guillain, and S. Czemichow Predicting diabetes: clinical, biological, and genetic approaches: data from the Epidemiological Study on the Insulin Resistance Syndrome (DESIR) Diabetes Care 31 2008 2056 2061
90. V. Lyssenko, P. Almgren, D. Anevski, M. Orho-Melander, M. Sjogren, and C. Saloranta Genetic prediction of future type 2 Diabetes PLOS Med 2 2005 e345
91. M. Beekman, C. Nederstigt, H.E. Suchiman, D. Kremer, B. van der, reggen, and N. Lakenberg Genome-wide association study (GWAS)-identified disease risk alleles do not compromise human longevity Proc Natl Acad Sci U S A 107 2010 18046 18049
92. A.C.J.W. Janssens, Y.S. Aulchenko, S. Elefante, G.J.J.M. Borsboom, E.W. Steyerberg, and C.M. van Duijn Predictive testing for complex diseases using multiple genes: fact or fiction? Genet Med 8 2006 395 400 (Pubitemid 44289001)