title: An integrated phenomic approach to multivariate allelic association.
abstract: The increased feasibility of genome-wide association has resulted in association becoming the primary method used to localize genetic variants that cause phenotypic variation. Much attention has been focused on the vast multiple testing problems arising from analyzing large numbers of single nucleotide polymorphisms. However, the inflation of experiment-wise type I error rates through testing numerous phenotypes has received less attention. Multivariate analyses can be used to detect both pleiotropic effects that influence a latent common factor, and monotropic effects that operate at a variable-specific levels, whilst controlling for non-independence between phenotypes. In this study, we present a maximum likelihood approach, which combines both latent and variable-specific tests and which may be used with either individual or family data. Simulation results indicate that in the presence of factor-level association, the combined multivariate (CMV) analysis approach performs well with a minimal loss of power as compared with a univariate analysis of a factor or sum score (SS). As the deviation between the pattern of allelic effects and the factor loadings increases, the power of univariate analyses of both factor and SSs decreases dramatically, whereas the power of the CMV approach is maintained. We show the utility of the approach by examining the association between dopamine receptor D2 TaqIA and the initiation of marijuana, tranquilizers and stimulants in data from the Add Health Study. Perl scripts that takes ped and dat files as input and produces Mx scripts and data for running the CMV approach can be downloaded from www.vipbg.vcu.edu/~sarahme/WriteMx.
authors.affiliation: Genetic Epidemiology, Queensland Institute of Medical Research, Brisbane, Queensland, Australia. sarahMe@qimr.edu.au
authors.forename: Sarah Elizabeth
authors.initials: SE
authors.lastname: Medland
authors.forename: Michael Churton
authors.initials: MC
authors.lastname: Neale
mesh_terms: D000483:Alleles; D005190:Family; D014644:Genetic Variation; D055106:Genome-Wide Association Study / Q000379:methods*; D005838:Genotype; D006801:Humans; D002189:Marijuana Abuse / Q000235:genetics; D015999:Multivariate Analysis; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D017448:Receptors, Dopamine D2 / Q000235:genetics; D015203:Reproducibility of Results; D035781:Siblings
chemical_list: D017448:Receptors, Dopamine D2
references.citation: Mol Psychiatry. 1999 May;4(3):290-6
references.pmid: 10395223
references.citation: Nicotine Tob Res. 2004 Aug;6(4):583-97
references.pmid: 15370155
references.citation: Am J Psychiatry. 1999 Sep;156(9):1440-3
references.pmid: 10484959
references.citation: Am J Hum Genet. 2007 Dec;81(6):1278-83
references.pmid: 17966091
references.citation: Alcohol Clin Exp Res. 2007 Oct;31(10):1645-53
references.pmid: 17850642
references.citation: Behav Genet. 1998 Sep;28(5):329-40
references.pmid: 9926615
references.citation: Twin Res. 2004 Jun;7(3):292-8
references.pmid: 15193174
references.citation: Biostatistics. 2003 Apr;4(2):195-206
references.pmid: 12925516
references.citation: Am J Epidemiol. 2008 Jan 15;167(2):125-38
references.pmid: 17989061
references.citation: Behav Genet. 2004 Sep;34(5):541-7
references.pmid: 15319577
references.citation: Drug Alcohol Depend. 1993 Oct;33(3):271-85
references.pmid: 8261891
references.citation: Nicotine Tob Res. 2007 Dec;9(12):1251-7
references.pmid: 18058343
references.citation: Am J Hum Genet. 2002 Jun;70(6):1599-602
references.pmid: 11992269
references.citation: Behav Brain Funct. 2007 Apr 28;3:22
references.pmid: 17466074
references.citation: Am J Hum Genet. 1999 Jan;64(1):259-67
references.pmid: 9915965
references.citation: Stat Appl Genet Mol Biol. 2004;3:Article17
references.pmid: 16646795