Were genome-wide linkage studies a waste of time? Exploiting candidate regions within genome-wide association studies

Genetic Epidemiology

Volumn 34, Issue 2, 2010, Pages 107-118

  Yoo, Yun J ^a   Bull, Shelley B ^a,b   Paterson, Andrew D ^b,c   Waggott, Daryl ^a   Sun, Lei ^b  

^a MOUNT SINAI HOSPITAL   (Canada)

^b UNIVERSITY OF TORONTO   (Canada)

^c HOSPITAL FOR SICK CHILDREN   (Canada)

Author keywords

False discovery rate; Genome wide association; Genome wide linkage; Prior information; Statistical power

Indexed keywords

ARTICLE; COMPUTER PROGRAM; GENETIC ANALYSIS; GENETIC ASSOCIATION; GENETIC LINKAGE; HUMAN; HUMAN GENOME; MAJOR CLINICAL STUDY; MEDICAL INFORMATION; NON INSULIN DEPENDENT DIABETES MELLITUS;

COMPUTER SIMULATION; DIABETES MELLITUS, TYPE 2; FINLAND; GENETIC PREDISPOSITION TO DISEASE; GENOME, HUMAN; GENOME-WIDE ASSOCIATION STUDY; HUMANS; LINKAGE (GENETICS); MODELS, GENETIC; MODELS, STATISTICAL; POLYMORPHISM, SINGLE NUCLEOTIDE; RESEARCH DESIGN; UNITED STATES;

EID: 76649111363     PISSN: 07410395     EISSN: 10982272     Source Type: Journal    
DOI: 10.1002/gepi.20438     Document Type: Article

References (29)

1. Al-Kateb H, Boright AP, Mirea L, Xie X, Sutradhar R, Mowjoodi A, Bharaj B, Liu M, Bucksa JM, Arends VL, Steffes MW, Cleary PA, Sun W, Lachin JM, Thorner PS, Ho M, McKnight AJ, Maxwell PA, Savage DA, Kidd KK, Kidd JR, Speed WC, Orchard TJ, Miller RG, Sun L, Bull SB, Paterson AD, the DCCT/EDIC research group. 2008. Multiple superoxide dismutase 1/splicing factor serine alanine 15 variants are associated with the development and progression of diabetic nephropathy: the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Genetics study. Diabetes 57:218-228.
2. Amos CI, Zhu DK. 1996. Assessing genetic linkage. Ann Hum Genet 60:143-160.
3. Bacanu SA. 2005. Robust estimation of critical values for genome scans to detect linkage. Genet Epidemiol 28:24-32.
4. Benjamini Y, Hochberg Y. 1995. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc B 57:289-300.
5. Biernacka J, Sun L, Bull SB. 2005. Simultaneous localization of two linked disease susceptibility genes. Genet Epidemiol 28:33-47.
6. Chen GK, Witte JS. 2007. Enriching the analysis of genomewide association studies with hierarchical modeling. Am J Hum Genet 81:397-403.
7. Craiu RV, Sun L. 2008. Choosing the lesser evil: trade-off between false discovery rate and non-discovery rate. Stat Sin 18:861-879.
8. Dudbridge F, Gusnanto A. 2008. Estimation of significance thresholds for genomewide association scans. Genet Epidemiol 32:227-234.
9. Genovese CR, Roeder K, Wasserman L. 2006. False discovery control with P-value weighting. Biometrika 93:509-524.
10. Greenwood C, Rangrej J, Sun L. 2007. Optimal selection of markers for validation or replication from genome-wide association studies. Genet Epidemiol 31:396-407.
11. Huang B, Rangreg J, Paterson AD, Sun L. 2007. The multiplicity problem in linkage analysis of gene expression data - the power of differentiating cis- and trans-acting regulators. BMC Proc 1:S142.
12. Ioannidis JP, Trikalinos TA, Khoury MJ. 2006. Implications of small effect sizes of individual genetic variants on the design and interpretation of genetic association studies of complex diseases. Am J Epidemiol 164:609-614.
13. Kong A, Cox N. 1997. Allele-sharing models: LOD scores and accurate linkage tests. Am J Hum Genet 61:1179-1188.
14. C, Li M, Lange EM, Watanabe RM. 2008. Prioritized subset analysis: Improving power in genome-wide association analysis. Hum Hered 65:129-141.
15. Liang KY, Chiu YF, Beaty TH. 2001. A robust identity-by-descent procedure using affected sib-pairs: multipoint mapping for complex diseases. Hum Hered 51:64-78.
16. Looker HC, Nelson RG, Chew E, Klein R, Klein BEK, Knowler WC, Hanson RL. 2007. Genome-wide linkage analyses to identify loci for diabetic retinopathy. Diabetes 56:1160-1166.
17. Manolio TA, Brooks LD, Collins FS. 2008. A HapMap harvest of insights into the genetics of common disease. J Clin Invest 118:1590-1605.
18. NCBI dbGap: http://www.ncbi.nlm.nih.gov/sites/entrez?Db=gap.
19. Pe'er I, de Bakker PW, Maller J, Yelensky R, Altshuler D, Daly MJ. 2006. Evaluating and improving power in whole-genome association studies using fixed marker sets. Nat Genet 38:663-667.
20. Rodriguez-Murillo L, Greenberg DA. 2008. Genetic association analysis: a primer on how it works, its strengths and its weaknesses. Int J Androl 31:546-556.
21. Roeder K, Bacanu SA, Wasserman L, Devlin B. 2006. Using linkage genome scans to improve power of association in genome scans. Am J Hum Genet 78:243-252.
22. Roeder K, Devlin B, Wasserman L. 2007. Improving power in genome-wide association studies: Weights tip the scale. Genet Epidemiol 31:741-747.
23. Scott LJ, Mohlke KL, Bonnycastle LL, Willer CJ, Li Y, Duren WL, Erdos MR, Stringham HM, Chines PS, Jackson AU, Prokunina-Olsson L, Ding CJ, Swift AJ, Narisu N, Hu T, Pruim R, Xiao R, Li XY, Conneely KN, Riebow NL, Sprau AG, Tong M, White PP, Hetrick KN, Barnhart MW, Bark CW, Goldstein JL, Watkins L, Xiang F, Saramies J, Buchanan TA, Watanabe RM, Valle TT, Kinnunen L, Abecasis GR, Pugh EW, Doheny KF, Bergman RN, Tuomilehto J, Collins FS, Boehnke M. 2007. A Genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science 316:1341-1345.
24. Silander K, Scott LJ, Valle TT, Mohlke KL, Stringham HM, Wiles KR, Duren WL, Doheny KF, Pugh EW, Chines P, Narisu N, White PP, Fingerlin TE, Jackson AU, Li C, Ghosh S, Magnuson VL, Colby K, Erdos MR, Hill JE, Hollstein P, Humphreys KM, Kasad RA, Lambert J, Lazaridis KN, Lin G, Morales-Mena A, Patzkowski K, Pfahl C, Porter R, Rha D, Segal L, Suh YD, Tovar J, Unni A, Welch C, Douglas JA, Epsterin M, Hauser E, Hagopian W, Buchanan TA, Watanabe RM, Bergman RN, Tuomilehto J, Collins FS, Boehnke M. 2004. A large set of Finnish affected sibling pair families with type 2 diabetes suggests susceptibility loci on chromosomes 6, 11, and 14. Diabetes 53:821-829.
25. Storey JD. 2002. A direct approach to false discovery rates. J R Stat Soc B 64:479-498.
26. Sun L, Craiu RV, Paterson AD, Bull SB. 2006. Stratified false discovery control for large-scale hypothesis testing with application to genome-wide association studies. Genet Epidemiol 30:519-530. Tenesa A, Farrington SM, Prendergast JGD, Porteous ME, Walker M, Haq N, Barnetson RA, Theodoratou E, Cetnarskyj R, Cartwright N, Semple C, Clark AJ, Reid FJL, Smith LA, Kavoussanakis K, Koessler T, Pharoah PDP, Buch S, Schafmayer C, Tepel J, Schreiber S, Völzke H, Schmidt CO, Hampe J, Chang-Claude J, Hoffmeister M, Brenner H, Wilkening S, Canzian F, Capella G, Moreno V, Deary IJ, Starr JM, Tomlinson IPM, Kemp Z, Howarth K, Carvajal-Carmona L, Webb E, Broderick P, Vijayakrishnan J, Houlston RS, Rennert G, Ballinger D, Rozek L, Gruber SB, Matsuda K, Kidokoro T, Nakamura Y, Zanke BW, Greenwood CMT, Rangrej J, Kustra R, Montpetit A, Hudson TJ, Gallinger S, Campbell H, Dunlop MG. 2008. Genome-wide association scan identifies a colorectal cancer susceptibility locus on 11q23 and replicates risk loci at 8q24 and 18q21. Nat Genet 40:631-637.
27. The Wellcome Trust Case Control Consortium. 2007. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 controls. Nature 447:661-678.
28. Thomson D,Witte JS, Slattery M, Goldgar D. 2004. Increased power for case-control studies of single nucleotide polymorphisms through incorporation of family history and genetic constraints. Genet Epidemiol 27:215-224.
29. Zeggini E, Scott LJ, Saxena R, Voight BF, Marchini JL, Hu T, de Bakker PIW, Abecasis GR, Almgren P, Andersen G, Ardlie K, Boström KB, Bergman RN, Bonnycastle LL, Borch-Johnsen K, Burtt NP, Chen H, Chines PS, Daly MJ, Deodhar P, Ding CJ, Doney ASF, Duren WL, Elliott KS, Erdos MR, Frayling TM, Freathy RM, Gianniny L, Grallert H, Grarup N, Groves CJ, Guiducci C, Hansen T, Herder C, Hitman GA, Hughes TE, Isomaa B, Jackson AU, Jørgensen T, Kong A, Kubalanza K, Kuruvilla FG, Kuusisto J, Langenberg C, Lango H, Lauritzen T, Li Y, Lindgren CM, Lyssenko V, Marvelle AF, Meisinger C, Midthjell K, Mohlke KL, Morken MA, Morris AD, Narisu N, Nilsson P, Owen KR, Palmer CNA, Payne F, Perry JRB, Pettersen E, Platou C, Prokopenko I, Qi L, Qin L, Rayner NW, Rees M, Roix JJ, Sandbćk A, Shields B, Sjögren M, Steinthorsdottir V, Stringham HM, Swift AJ, Thorleifsson G, Thorsteinsdottir U, Timpson NJ, Tuomi T, Tuomilehto J, Walker M, Watanabe RM, Weedon MN, Willer CJ, Wellcome Trust Case Control Consortium, Illig T, Hveem K, Hu FB, Laakso M, Stefansson K, Pedersen O,Wareham NJ, Barroso I,Hattersley AT, Collins FS, Groop L, McCarthy MI, Boehnke M, Altshuler D. 2008.Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nat Genet 40:638-645.