Conclusion générale et perspectives
7.2 Partie II : Étude d'association entre les me sures osseuses et les variantes de ESRRG et
E S R R A chez les femmes d'origine européenne
Dans le cadre d'un projet sur l'identification des gènes potentiellement impliqués dans l'étiologie de l'ostéoporose mené au laboratoire du Dr François Rousseau, Hôpital Saint- François d'Assise, CHUQ, nous avons mis à profit une étude d'association par blocs d'ha- plotypes tout en appliquant les nouveaux outils développés dans le cadre de cette thèse pour raffiner deux associations déjà observées avec deux variantes au sein de deux gènes candidats ESRRG et ESRRA (chapitres 5 et 6). Les résultats obtenus suggèrent que le gène ESRRG est un gène de susceptibilité de l'ostéoporose. Le séquençage du bloc étudié au sein de ce gène n'a pas révélé de nouveaux polymorphismes qui peuvent être des candidats potentiels pour des variantes causales. On peut donc conclure que l'association observée avec ESRRG est probablement mieux caractérisée par l'haplotype associé que tout autre SNP individuel. Cependant, l'analyse effectuée au sein du gène ESRRA révèle une asso- ciation significative entre les variantes testées et la mesure de densité minérale osseuse aux lombaires L2L4 dans l'échantillon de Québec. De plus, cette association n'était pas reproduite dans l'échantillon de Toronto. Par ailleurs, l'étude d'évaluation des interactions entre les variantes des deux gènes ESRRG et ESRRA montre une interaction significative entre les variantes des deux gènes et les mesures du talon dans l'échantillon de Québec. Toutefois, cette interaction n'était pas reproduite dans le deuxième échantillon. Le manque de puissance pour les mesures du talon dans l'échantillon de Toronto pourrait être à l'ori- gine du manque de reproductibilité de cette interaction. Une analyse dans un échantillon de taille égale ou supérieure à celle de l'échantillon de Québec est donc recommandée pour clarifier cette question. En résumé, les résultats de cette étude n'ont pas permis de tirerune conclusion sur l'imphcation de ESRRA dans l'étiologie de l'ostéoporose.
En perspective, la stratégie d'analyse présentée dans cette thèse pourra être adoptée pour étudier les effets des autres gènes candidats du sentier des estrogènes ainsi que les gènes candidats des autres sentiers métaboliques de l'ostéoporose. Elle pourra aussi être gé- néralisée aux autres maladies complexes. Une taille d'échantillon plus grande est cependant nécessaire pour l'évaluation des interactions gène-gène.
En conclusion, les études d'association génétique des maladies complexes, incluant celle de l'ostéoporose, sont en pleine expansion grâce au dévelopement permettant de mener des études d'association à l'étendue du génome. Des résultats intéressants sont en proliféra- tion. Cependant, certaines sources de susceptibilité, mieux représentées par les variations génétiques " haplotypes ', restent à exploiter. Nous croyons donc que le modèle développé dans le cadre de cette thèse est un outil fort utile, et complémentaire à l'analyse par SNP, qui contribuera sûrement à identifier différents locus de susceptibilité et, par conséquent, à augmenter la compréhension de l'aspect polygénique qui caractérise les maladies complexes.
Bibliographie
[1] Lander, E. S., Linton, L. M., Birren, B., Nusbaum, C , Zody, M. C , Baldwin, J., Devon, K., Dewar, K., Doyle, M., FitzHugh, W., Funke, R , Gage, D., et al. (2001). Initial sequencing and analysis of the human genome. Nature 409, 860-921.
[2] Venter, J. C , Adams, M. D., Myers, E. W., Li, P. W., Mural, R. J., Sutton, G. G., Smith, H. O., Yandell, M., Evans, C. A., Holt, R. A., Gocayne, J. D., Amanatides, P., et al. (2001). The sequence of the human genome. Science 291, 1304-1351.
[3] International Human Genome Sequencing Consortium (2004). Finishing the euchro- matic sequence of the human genome. Nature 431, 931-945.
[4] François Rousseau, Nathalie Laflamme. Génétique moléculaire humaine : des maladies monogéniques aux maladies complexes. MEDECINE/SCIENCES 2003 ; 19 : 950-4. [5] Hamosh, A., Scott, A. F., Amberger, J. S., Bocchini, C. A., and McKusick, V. A.
(2005). Online Mendelian inheritance in man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic acids Res. 33, D514-D517.
[6] Koenig, M., Hoffman, E.P., Bertelson, C.J., Monaco, A.P., Feener, C. and Kunkel, L.M. (1987) Complete cloning of the Duchenne muscular dystrophy (DMD) cDNA and preliminary genomic organization of the DMD gene in normal and affected individuals. Cell, 50, 509-17.
[7] Fung, Y.K., Murphree, A.L., T'Ang, A., Qian, J., Hinrichs, S.H. and Benedict, W.F. (1987) Structural evidence for the authenticity of the human retinoblastoma gene. Science, 236, 1657-61.
[8] Kerem, B., Rommens, J.M., Buchanan, J.A., Markiewicz, D., Cox, T.K., Chaloravarti, A., Buchwald, M. and Tsui, L.C. (1989) Identification of the cystic fibrosis gene : genetic analysis. Science, 245, 1073-80.
[9] Verkerk, A.J., Pieretti, M., Sutcliffe, J.S., Fu, Y.H., Kuhl, D . P , Pizzuti, A., Reiner, O., Richards, S., Victoria, M.F., Zhang, F.P. et al. (1991) Identification of a gene (FMR- 1) containing a CGG repeat coincident with a breakpoint cluster region exhibiting length variation in fragile X syndrome. Cell, 65, 905-14.
[10] Brook, J.D., McCurrach, M.E., Harley, H.G., Buckler, A.J., Church, D., Aburatani, H., Hunter, K., Stanton, V . P , Thirion, J . P , Hudson, T. et al. (1992) Molecular basis of myotonic dystrophy : expansion of a trinucleotide (CTG) repeat at the 3' end of a transcript encoding a protein kinase family member. Cell.
[11] Strathdee, C.A., Gavish, H., Shannon, W.R. and Buchwald, M. (1992) Cloning of cDNAs for Fanconi's anaemia by functional complementation. Nature, 358, 434. [12] Savitslcy, K., Bar-Shira, A., Gilad, S., Rotman, G., Ziv, Y., Vanagaite, L., Tagle, D.A.,
Smith, S., Uziel, T., Sfez, S. et al. (1995) A single ataxia telangiectasia gene with a product similar to PI-3 ldnase. Science, 268, 1749-53.
[13] Feder, J.N., Gnirke, A., Thomas, W., Tsuchihashi, Z., Ruddy, D.A., Basava, A., Dor- mishian, F., Domingo, R., Jr., Ellis, M . C , Fullan, A. et al. (1996) A novel MHC class I-like gene is mutated in patients with hereditary haemochromatosis. Nat Genet, 13, 399-408.
[14] Chapman JM, Cooper JD, Todd JA, Clayton DG.Detecting disease associations due to linkage disequilibrium using haplotype tags : a class of tests and the determinants of statistical power.Hum Hered. 2003;56(l-3) :18-31.
[15] Botstein D, Risch N. Discovering genotypes underlying human phénotypes : past successes for mendelian disease, future approaches for complex disease. Nat Genet. 2003 ;33 Suppl :228-237.
[16] Altshuler D, Daly MJ, Lander ES. Genetic mapping in human disease. Science. 2008 Nov 7; 322(5903) :881-8.
[17] Altshuler D, Broolcs LD, Chakravarti A, Collins FS, Daly MJ, Donnelly P ; Interna- tional HapMap Consortium. A haplotype map of the human genome. Nature. 2005 Oct27;437(7063) :1299-320.
Les variants associés aux maladies communes ( C D / C V ) dans les GWA
[18] McPherson R, Pertsemlidis A, Kavaslar N, Stewart A, Roberts R, et al. (2007). A common allele on Chromosome 9 associated with coronary heart disease. Science 316 : 1488-1491.
[19] Helgadottir A, Thorleifsson G, Manolescu A, Gretarsdottir S, Blondal T, et al. (2007) A common variant on chromosome 9p21 affects the risk of myocardial infarction. Science 316 : 1491-1493.
[20] Wellcome Trust Case Control Consortium (2007) Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447 : 661-678. [21] Samani NJ, Erdmann J, Hall AS, Hengstenberg C, Mangino M, et al. (2007) Geno-
mewide association analysis of coronary artery disease. N Engl J Med 357 : 443-453. i
[22] Matarin M, Brown WM, Scholz S, Simon-Sanchez J, Fung HC, et al. (2007) A genome- wide genotyping study in patients with ischaemic stroke : Initial analysis and data release. Lancet Neurol 6 : 414-420.
[23] Hunter DJ, Kraft P, Jacobs KB, Cox DG, Yeager M, et al. (2007) A genomewide association study identifies alleles in FGFR2 associated with risk of sporadic postme- nopausal breast cancer. Nat Genet 39 : 870-874.
[24] Stacey SN, Manolescu A, Sulem P, Rafnar T, Gudmundsson J, et al. (2007) Common variants on Chromosomes 2q35 and 16ql2 confer susceptibility to estrogen receptor- positive breast cancer. Nat Genet 39 : 865-869.
[25] Easton DF, Pooley KA, Dunning AM, Pharoah PDP, Thompson D, et al.(2007) Genome-wide association study identifies novel breast cancer susceptibility loci. Na- ture 447 : 1087-1093.
[26] Sequence variants at the TERT-CLPTM1L locus associate with many cancer types. Rafnar T, Sulem P, Stacey SN, Geller F, Gudmundsson J, Sigurdsson A, Jakobsdottir M, Helgadottir H, Thorlacius S, Aben KK, Blôndal T, Thorgeirsson TE, Thorleif- sson G, Kristjansson K, Thorisdottir K, Ragnarsson R, Sigurgeirsson B, Slmladottir H, Gudbjartsson T, Isaksson HJ, Einarsson GV, Benediktsdottir KR, Agnarsson BA, Olafsson K, Salvarsdottir A, Bjarnason H, Asgeirsdottir M, Kristinsson KT, Mat- thiasdottir S, Sveinsdottir SG, Polidoro S, Hôiom V, Botella-Estrada R, Hemminki K, Rudnai P, Bishop DT, Campagna M, Kellen E, Zeegers MP, de Verdier P, Ferrer A, M a D, Vidal MJ, Andres R, Saez B, Juberias P, Banzo J, Navarrete S, Très A, Kan D, Lindblom A, Gurzau E, Koppova K, de Vegt F, Schalken JA, van der Heijden HF, Smit HJ, Termeer RA, Oosterwijk E, van Hooij O, Nagore E, Porru S, Steineck G, Hansson J, Buntinx F, Catalona WJ, Matullo G, Vineis P, Kiltie AE, Mayordomo JI, Kumar R, Kiemeney LA, Frigge ML, Jonsson T, Saemundsson H, Barkardottir RB, Jonsson E, Jonsson S, Olafsson JH, Gulcher JR, Masson G, Gudbjartsson DF, Kong A, Thorsteinsdottir U, Stefansson K. Nat Genet. 2009 Feb;41(2) :221-7. [27] Lung cancer susceptibility locus at 5pl5.33. McKay JD, Hung RJ, Gaborieau V,
Boffetta P, Chabrier A, Byrnes G, Zaridze D, Mukeria A, Szeszenia-Dabrowska N, Lissowska J, Rudnai P, Fabianova E, Mates D, Bencko V, Foretova L, Janout V, McLaughlin J, Shepherd F, Montpetit A, Narod S, Krokan HE, Skorpen F, Elvestad MB, Vatten L, Nj0lstad I, Axelsson T, Chen C, Goodman G, Barnett M, Loomis MM, Lubinski J, Matyjasik J, Lener M, Oszutowska D, Field J, Liloglou T, Xinarianos G, Cassidy A ; EPIC Study, Vineis P, Clavel-Chapelon F, Palli D, Tumino R, Krogh V, Panico S, Gonzalez CA, Ramon Quires J, Martinez C, Navarro C, Ardanaz E, Lar- ranaga N, Kham KT, Key T, Bueno-de-Mesquita HB, Peeters PH, Trichopoulou A, Linseisen J, Boeing H, Hallmans G, Overvad K, Tjonneland A, Kumle M, Riboli E, Zelenika D, Boland A, Delepine M, Foglio M, Lechner D, Matsuda F, Blanche H, Gut I, Heath S, Lathrop M, Brennan P. Nat Genet. 2008 Dec;40(12) :1404-6.
[28] Sladek R, Rocheleau G, Rung J, Dina C, Shen L, et al. (2007) A genome-wide asso- ciation study identifies novel risk loci for type 2 diabetes. Nature 445 : 881-885. [29] Saxena R, Voight BF, Lyssenko V, Burtt NP, de Bakker PI, et al. (2007) Genome-wide
association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 316 : 1331-1336.
[30] Zeggini E, Weedon MN, Lindgren CM, Frayling TM, Elliott KS (2007) Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science 316 : 1336-1341.
[31] Scott LJ, Mohlke KL, Bonnycastle LL, Wilier CJ, Li Y, et al. (2007) A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science 316 : 1341-1345.
[32] Steinthorsdottir V, Thorleifsson G, Reynisdottir I, Benedilctsson R, Jonsdottir T, et al. (2007) A variant in CDKAL1 influences insulin response and risk of type 2 diabetes. Nat Genet 39 : 770-775.
[33] Salonen JT, Uimari P, Aalto JM, Pirskanen M, Kaikkonen J, et al. (2007) Type 2 dia- betes whole-genome association study in four populations : The DiaGen consortium. Am J Hum Genet 81 : 338-345.
[34] Frayling TM, Timpson NJ, Weedon MN, Zeggini E, Freathy RM (2007) A common variant in the FTO gene is associated with body mass index and predisposes to child- hood and adult obesity. Science 316 : 889-894.
[35] Thomas, G., Jacobs, K. B., Yeager, M., Kraft, P., Wacholder, S., Orr, N., Yu, K., Chatterjee, N.,Welch, R., Hutchinson, A., Crenshaw, A., Cancel-Tassin, G., et al. (2008). Multiple loci identified in a genome-wide association study of prostate cancer. Nat. Genet. 40, 310-315.
[36] Gudmundsson, J., Sulem, P., Manolescu, A., Amundadottir, L. T., Gudbjartsson, D., Helgason, A., Rafnar, T., Bergthorsson, J. T., Agnarsson, B. A., Baker, A., Sigurdsson, A., Benediktsdottir, K. R., et al. (2007). Genome-wide association study identifies a second prostate cancer susceptibility variant at 8q24. Nat. Genet. 39, 631-637.
[37] Haiman, C. A., Patterson, N., Freedman, M. L., Myers, S. R., Pike, M. C , Walis- zewska, A., Neubauer, J., Tandon, A., Schirmer, O, McDonald, G. J., Greenway, S.
C , Stram, D. O., et al. (2007). Multiple regions within 8q24 independently affect risk for prostate cancer. Nat. Genet. 39, 638-644.
[38] Yeager, M., Orr, N., Hayes, R. B., Jacobs, K. B., Kraft, P., Wacholder, S., Minichiello, M. J., Fearnhead, P., Yu, K., Chatterjee, N., Wang, Z., Welch, R , et al. (2007). Genome-wide association study of prostate cancer identifies a second risk locus at 8q24. Nat. Genet. 39, 645-649.
Variantes rares associées aux maladies complexes
[39] Cohen JC, Kiss RS, Pertsemlidis A, Marcel YL, McPherson R, et al. Multiple rare alleles contribute to low plasma levels of HDL cholesterol. Science. 2004 ;305 :869-872.
[40] Romeo S, Pennacchio LA, Fu Y, Boeirwinkle E, Tybjaerg-Hansen A, et al. Population- based resequencing of ANGPTL4 uncovers variations that reduce triglycerides and increase HDL. Nat Genet. 2007;39 :513-516.
[41] Mark M Res. What Can Genome-Wide Association Studies Tell Us about the Genetics of Common Disease. PLoS Genet. 2008 Febraary ; 4(2) : e33.
Bases de données sur les S N P
[42] Smigielski EM, Sirotkin K, Ward M, Sherry ST. dbSNP : a database of single nucleo- tide polymorphisms.Nucleic Acids Res. 2000 Jan 1 ;28(1) :352-5.
[43] Stenson, P. D., Ball, E. V., Mort, M., Phillips, A. D., Shiel, J. A-, Thomas, N. S., Abeysinghe, S., Krawczak, M., and Cooper, D. N. (2003). Human Gene Mutation Database (HGMD). Hum Mutat 21(6), 577-81.
[44] Wilson, S. H., and Olden, K. (2004). The Environmental Genome Project : Phase I and beyond. Mol. Interv. 4, 147-156.
[45] Packer, B. R., Yeager, M., Burdett, L., Welch, R., Beerman, M., Qi, L., Sicotte, H., Staats, B., Acharya, M., Crenshaw, A., Eckert, A., Puri, V., et al. (2006). SNP500 Cancer : A public resource for sequence validation, assay development, and frequency analysis for genetic variation in candidate genes. Nucleic Acids Res. 34, D617-D621.
[46] Gong L, Owen RP, Gor W, Altman RB, Klein TE. PharmGKB : an integrated re- source of pharmacogenomic data and knowledge. Curr Protoc Bioinformatics. 2008 Sep ;Chapter 14 :Unitl4.7.
[47] Kruglyak L, Nickerson DA (2001) Variation is the spice of life. Nat Genet 27 :234-236.
[48] Reich, D. E., and Lander, E. S. (2001). On the allelic spectrum of human disease. Trends Genet. 17, 502-510.
Les CISTVs
[49] Iafrate, A. J., Feuk, L., Rivera, M. N., Listewnik, M. L., Donahoe, P. K., Qi, Y., Scherer, S. W., and Lee, C. (2004). Detection-of large-scale variation in the human genome. Nat. Genet. 36, 949-951.
[50] Sebat, J., Lakshmi, B., Troge, J., Alexander, J., Young, J., Lundin, P., Maner, S., Massa, H., Walker, M., Chi, M., Navin, N., Lucito, R. et al. (2004). Large-scale copy number polymorphism in the human genome. Science 305, 525-528.
[51] Gonzalez, E., Kulkarni, H., Bolivar, H., Mangano, A., Sanchez, R., Catano, G., Nibbs, R. J., Freedman, B. I., Quinones, M. P., Bamshad, M. J., Murthy, K. K., Rovin, B. H. et al. (2005). The influence of CCL3L1 gene-containing segmental duplications on HIV-1/AIDS susceptibility. Science (New York, N.Y.) 307, 1434-1440.
[52] Orr N, Chanock S. Common genetic variation and human disease. Adv Genet. 2008 ;62 :l-32.
[53] Cardon LR, Bell JI. Association study designs for complex diseases. Nat Rev Genet. 2001 ;2 :91-99.
[54] lies MM. What can genome-wide association studies tell us about the genetics of common disease? PLoS Genet. 2008 Feb;4(2) :e33.
[55] Clark AG. The role of haplotypes in candidate gene studies. Genet Epidemiol. 2004 Dec ;27(4) :321-33. Review.
[56] Bakker PI, Yelenslcy R, Pe'er I, Gabriel SB, Daly MJ, Altshuler D (2005) Efficiency and power in genetic association studies. Nat Genet 37 :1217-1223.
[57] Carlson CS, Eberle MA, Rieder MJ, Yi Q, Kruglyak L, Nickerson DA (2004) Selecting a maximally informative set of singlenucleotide polymorphisms for association analyses using linkage disequilibrium. Am J Hum Genet 74 :106-120.
[58] Chapman JM, Cooper JD, Todd JA, Clayton DG (2003) Detecting disease associa- tions due to linkage disequilibrium using haplotype tags : a class of tests and the determinants of statistical power. Hum Hered 56 :18-31.
[59] Weale ME, Depondt C, MacDonald SJ, Smith A, Lai PS, Shorvon SD, Wood NW, Goldstein DB (2003) Selection and evaluation of tagging SNPs in the neuronal-sodium- channel gene SCN1A : implications for linkage-disequilibrium gene mapping. Am J Hum Genet 73 :551-565.
[60] Stram DO, Pearce C, Bretslcy P, Freedman M, Hirschhorn J, Altshuler D, Kolonel L, Henderson B, Thomas DC (2003a) Modeling and E-M estimation of haplotype-specific relative rislcs from genotype data for a case-control study of unrelated individuals. Hum Hered 55 :179-190.
[61] Noah Zaitlen, Hyun Min Kang, Eleazar Esltin, and Eran Halperin. Leveraging the HapMap Correlation Structure in Association Studies. The American Journal of Hu- man Genetics Volume 80 April 2007.
[62] Gabriel SB, Schaffner SF, Nguyen H, Moore JM, Roy J, Blumenstiel B, Higgins J, DeFelice M, Lochner A, Faggart M, Liu-Cordero SN, Rotimi C, Adeyemo A, Cooper R, Ward R, Lander ES, Daly M J, Altshuler D. The stracture of haplotype blocks in the human genome. Science. 2002 Jun 21,296(5576) :2225-9.
[63] Wang N, Akey JM, Zhang K, Chakraborty R, Jin L. Distribution of recombination crossovers and the origin of haplotype blocks : the interplay of population history, recombination, and mutation. Am J Hum Genet. 2002 Nov;71(5) :1227-34.
[64] Wall JD, Pritchard JK. 2003. Assessing the performance of the haplotype block model of linkage disequilibrium. Am J Hum Genet 73 : 502-516.
[65] McVean GA, Myers SR, Hunt S, Deloukas P, Bentley DR, Donnelly P. 2004. The fine- scale structure of recombination rate variation in the human genome. Science 304 : 581-584.
[66] Hollox EJ, Poulter M, Zvarik M, Ferak V, Krause A, Jenkins T, Saha N, Kozlov AI, Swallow DM. Lactase haplotype diversity in the Old World. Am J Hum Genet. 2001 Jan ;68(1) :160-172.
[67] Tavtigian SV, Simard J, Teng DH, Abtin V, Baumgard M, Beck A, Camp NJ, Carillo AR, Chen Y, Dayananth P, Desrochers M, Dumont M, Farnham JM, Frank D, Frye C, Ghaffari S, Gupte JS, Hu R, Iliev D, Janecki T, Kort EN, Laity KE, Leavitt A, Leblanc G, McArthur-Morrison J, Pederson A, Penn B, Peterson KT, Reid JE, Richards S, Schroeder M, Smith R, Snyder SC, Swedlund B, Swensen J, Thomas A, Tranchant M, Woodland AM, Labrie F, Skolnick MH, Neuhausen S, Rommens J, Cannon-Albright LA. A candidate prostate cancer susceptibility gene at chromosome 17p. Nat Genet. 2001 Feb ;27(2) :172-80.
[68] Drysdale CM, McGraw DW, Stack CB, Stephens JC, Judson RS, Nandabalan K, j \ r - nold K, Ruano G, Liggett SB. Complex promoter and coding region beta 2-adrenergic receptor haplotypes alter receptor expression *and predict in vivo responsiveness. Proc Natl Acad Sci U S A . 2000 Sep 12 ;97(19) :10483-8.
[69] Daly MJ, Rioux JD, Schaffher SF, Hudson TJ, Lander ES. High-resolution haplotype structure in the human genome. Nat Genet 29(2) :229-260 (2001).
[70] Johnson GC, Esposito L, Barratt BJ, Smith AN, Heward J, Di Genova G, Ueda H, Cordell HJ, Eaves IA, Dudbridge F, Twells RC, Payne F, Hughes W, Nutland S, Stevens H, Carr P, Tuomilehto-Wolf E, Tuomilehto J, Gough SC, Clayton DG, Todd JA. Haplotype tagging for the identification of common disease genes. Nat Genet. 2001 Oct ;29(2) :233-7.
[71] Patil N, Berno AJ, Hinds DA, Barrett WA, Doshi JM, Hacker CR, Kautzer CR, Lee DH, Marjoribanks C, McDonough DP, Nguyen BT, Norris MC, Sheehan JB, Shen N, Stern D, Stokowski RP, Thomas DJ, Trulson MO, Vyas KR, Frazer KA, Fodor SP,
Cox DR. Bloclts of limited haplotype diversity revealed by high-resolution scanning of human chromosome 21. Science. 2001 Nov 23;294(5547) :1719-23.
[72] Takeuchi F, Yanai K, Moiii T, Ishinaga Y, Taniguchi-Yanai K, Nagano S, Kato N. Lin- kage disequilibrium grouping of single nucleotide polymorphisms (SNPs) reflecting ha- plotype phylogeny for efficient selection of tag SNPs. Genetics. 2005 May ;170(1) :291- 304.
[73] Miretti MM, Walsh EC, Ke X, Delgado M, Griffiths M, Hunt S, Morrison J, Whittaker P, Lander ES, Cardon LR, Bentley DR, Rioux JD, Beck S, Deloukas P. A high- resolution linkage-disequilibrium map of the human major histocompatibility complex and first generation of tag single-nucleotide polymorphisms. Am J Hum Genet. 2005 Apr;76(4) :634-46.
[74] Munroe P B , Caulfield MJ. Genetics of hypertension. Curr Opin Genet Dev. 2000 ;10 :325-329.
[75] Reich DE, Lander ES. On the allelic spectrum of human disease. Trends Genet. 2001 ;17 :502-510.
[76] The International HapMap Consortium. The International HapMap Project. Nature. 2003 Dec 18 ;426(6968) :789-96.
[77] Akey J, Jin L, Xiong M. Haplotypes vs single marker linkage disequilibrium tests : what do we gain? Eur J Hum Genet. 2001 Apr;9(4) :291-300.
[78] Fallin, D., Cohen, A., Essioux, L., Chumakov, I., Blumenfeld, M., Cohen, D., and Schork, N. J. (2001). Genetic analysis of case/control data using estimated haplotype frequencies : Application to APOE locus variation and Alzheimer's disease. Genome Res. 11, 143-151.
[79] Kankova, K., Stejskalov, A., Hertlov, M., and Znojil, V. (2005). Haplotype analysis of RAGE gene : Identification of a haplotype marker for diabetic nephropathy in type 2 diabetes mellitus. Nephrol. Dial. Transplant. 20, 1093-1102.
[80] Bader JS. The relative power of SNPs and haplotype as genetic markers for association tests. Pharmacogenomics. 2001 Feb;2(l) :ll-24.
[81] Long AD, Langley CH. The power of association studies to detect the contribution of candidate genetic loci to variation in complex traits. Genome Res. 1999 Aug ;9(8) :720- 31.
[82] Slager SL, Huang J, Vieland VJ. Effect of allelic heterogeneity on the power of the transmission disequilibrium test. Genet Epidemiol. 2000 Feb;18(2) :143-56.
[83] Morris RW, Kaplan NL.On the advantage of haplotype analysis in the presence of multiple disease susceptibility alleles. Genet Epidemiol. 2002 Oct ;23(3) :221-33.
[84] Schaid D J. Evaluating associations of haplotypes with traits. Genet Epidemiol. (2004) Dec ;27(4) :348-64. Review.
[85] Liu N, Zhang K, Zhao H. Haplotype-association analysis. Adv Genet. 2008 ;60 :335- 405.
[86] Zaykin DV. et al. Testing Association of statistically inferred haplotypes with discrets and continuous traits in samples of unrelated individuals. Human heredity ; 2002 ; 53, 2 : p79.
[87] Burgtorf C, Kepper P, Hoehe M, Schmitt C, Reinhardt R, Lehrach H, Sauer S. Clone- based systematic haplotyping (CSH) : a procedure for physical haplotyping of whole genomes. Genome Res. 2003 Dec;13(12) :2717-24. (43).
[88] Paul P. and Apgar J. Single-molecular dilution and multiple displacement amplifica- tion for molecular haplotyping. BioTechniques 38, 4 :553-559 (2005) .44
[89] Ding C. and Cantor CR. Direct molecular haplotyping of long-range genomic DNA withMl-PCR. PNSA 24, 100 : 7449-7453 (2003)45.
[90] Eitan Y. and kashi Y. Direct micro-haplotyping by multiple double PCR amplifica- tions of specific alleles (MD-PASA). Nucleic Acids Research 30, 12 e62 (2002).46.
[91] Costas J, Salas A, Phillips C, Carracedo A. Human genome-wide screen of haplotype- like blocks of reduced diversity. Gene. 2005 Apr 11 ;349 :219-25. ; 47.
[92] Dawson E, Abecasis GR, Bumpstead S, Chen Y, Hunt S, Beare DM, Pabial J, Di- bling T, Tinsley E, Kirby S, Carter D, Papaspyridonos M, Livingstone S, Ganske R, Lohmussaar E, Zernant J, Tonisson N, Renan M, Magi R, Puurand T, Vilo J, Kurg A, Rice K, Deloukas P, Mott R, Metspalu A, Bentley DR, Cardon LR, Dunham L. A first-generation linkage disequilibrium map of human chromosome 22. Nature. 2002 Aug 1 ;418(6897) :544-8. ; 48.
[93] Abecasis GR, Noguchi E, Heinzmann A, Traherne JA, Bhattacharyya S, Leaves NI, Anderson GG, Zhang Y, Lench NJ, Carey A, Cardon LR, Moffatt MF, Coolcson WO.. Extent and distribution of linkage disequilibrium in three genomic regions. Am J Hum Genet. 2001 Jan;68(l) :191-19.49.
[94] Excoffier L, Slatlrin M. 1995. Maximum likelihood estimation of molecular haplotype frequencies in a diploid population. Mol Biol Evol 12 :921-927. 50.
[95] Niu T, Qin ZS, Xu X, Liu JS. 2002. Bayesian haplotype inference for multiple linked single-nucleotide polymorphisms. Am J Hum Genet 70 :157-169. 51.
[96] Qin ZS, Niu T, Liu JS. 2002. Partition-hgation-expectation-maximization algorithm for haplotype inference with single nucleotide polymorphisms. Am J Hum Genet 71 :1242-1247. 52.
[97] Stephens M, Smith NJ, Donnelly P. 2001. A new statistical method for haplotype reconstruction from population data. Am J Hum Genet 68 : 978-989. 53.
[98] Tregouet DA, Escolano S, Tiret L, Mallet A, Golmard JL. 2004. A new for haplotype- based association analysis : the stochastic-EM algorithm. Ann Hum Genet 68 : 165- 177. 54.
[99] Sabbagh A, Darlu P. Inferring haplotypes at the NAT2 locus : the computational approach. BMC Genet. 2005 Jun 2;6(1) :30. 55.
[100] Adkins RM. Comparison of the accuracy of methods of computational haplotype inference using a large empirical dataset. BMC Genet. 2004 Aug 3;5(1) :22. 56. [101] Lu X, Niu T, Liu JS. Haplotype infoimation and linkage disequilibrium mapping for
[102] Niu T. Algorithms for inferring haplotypes. Genet Epidemiol. 2004 Dec ;27(4) :334- 47. 58.
[103] Thomas S, Porteous D, Visscher PM. Power of direct vs. indirect haplotyping in association studies. (2004), Genet. Epidemiol. 26 :116-124 59.
[104] Thomas S, Porteous D, Visscher P.. Correction for Thomas et al., 2004, Genet. Epidemiol. 26 :116-124.Genet Epidemiol. 2005 Sep;29(2) :171. 60.
[105] Fallin D, Schork NJ. Accuracy of haplotype frequency estimation for biallelic loci, via the expectation-maximization algorithm for unphased diploid genotype data. Am J Hum Genet. 2000 Oct ;67(4) :947-59. (62).
[106] Lin, S., Cutlet, D. J., Zwick, M. E., and Chakravarti, A. (2002). Haplotype inference in random population samples. Am. J. Hum. Genet. 71, 1129-1137.
[107] Niu, T. H., Qin, Z. H. S., Xu, X. P., and Liu, J. S. (2002b). Bayesian haplotype inference for multiple linked single-nucleotide polymorphisms. Am. J. Hum. Genet. 70, 157-169.
[108] Morris, A., Pedder, A., and Ayres, K. (2003). Linkage disequilibrium assessment via log-linear modeling of SNP haplotype frequencies. Genet. Epidemiol. 25, 106-114.
[109] Stephens,M., and Donnelly, P. (2003).Acomparison of bayesian methods for haplo- type reconstruction from population genotype data. Am. J. Hum. Genet. 73, 1162- 1169.
[110] Stephens, M., and Scheet, P. (2005). Accounting for decay of linkage disequilibrium in haplotype inference and missing-data imputation. Am. J. Hum. Genet. 76, 449-462.
[Ill] Scheet P, Stephens M. A fast and flexible statistical model for large-scale population genotype data : applications to inferring missing genotypes and haplotypic phase. Am J Hum Genet. 2006 Apr ;78(4) :629-44.
[112] Stephens, M., Smith, N. J., and Donnelly, P. (2001). A new statistical method for haplotype reconstruction from population data. Am. J. Hum. Genet. 68, 978-989.
[113] Zhang, K., and Zhao, H. (2006). A comparison of several methods for haplotype frequency estimation and haplotype reconstruction for tightly finked markers from general pedigrees. Genet. Epidemiol. 30, 423-437.
[114] Dempster, A. P., Laird, N. M., and Rubin, D. B. (1977). Maximum likelihood esti- mation from incomplete data via the EM algorithm (with discussion). J. R. Stat. Soc. B 39, 1-38.
[115] Excoffier, L., and Slatlrin, M. (1995). Maximum-likelihood estimation of molecular haplotype frequencies in a diploid population. Mol. Biol. Evol. 12, 921-927.
[116] Hawley, M. E., and Kidd, K. K. (1995). HAPLO : A program using the EM algorithm to estimate the frequencies of multi-site haplotypes. J. Hered. 86, 409-411.
[117] Long, J. C , Williams, R. C , and Urbanek, M. (1995). An E-M algorithm and testing strategy for multiple-locus haplotypes. Am. J. Hum. Genet. 56, 799-810.
[118] Qin, Z. H. S., Niu, T. H., and Liu, J. S. (2002). Partition-ligation-expectation- maximization algorithm for haplotype inference with single-nucleotide polymorphisms.