title: Bivariate association analysis in selected samples: application to a GWAS of two bone mineral density phenotypes in males with high or low BMD.
abstract: Our specific aims were to evaluate the power of bivariate analysis and to compare its performance with traditional univariate analysis in samples of unrelated subjects under varying sampling selection designs. Bivariate association analysis was based on the seemingly unrelated regression (SUR) model that allows different genetic models for different traits. We conducted extensive simulations for the case of two correlated quantitative phenotypes, with the quantitative trait locus making equal or unequal contributions to each phenotype. Our simulation results confirmed that the power of bivariate analysis is affected by the size, direction and source of the phenotypic correlations between traits. They also showed that the optimal sampling scheme depends on the size and direction of the induced genetic correlation. In addition, we demonstrated the efficacy of SUR-based bivariate test by applying it to a real Genome-Wide Association Study (GWAS) of Bone Mineral Density (BMD) values measured at the lumbar spine (LS) and at the femoral neck (FN) in a sample of unrelated males with low BMD (LS Z-scores ≤ -2) and with high BMD (LS and FN Z-scores >0.5). A substantial amount of top hits in bivariate analysis did not reach nominal significance in any of the two single-trait analyses. Altogether, our studies suggest that bivariate analysis is of practical significance for GWAS of correlated phenotypes.
authors.affiliation: INSERM U563, Toulouse, France. aude.saint-pierre@inserm.fr
authors.forename: Aude
authors.initials: A
authors.lastname: Saint-Pierre
authors.forename: Jean-Marc
authors.initials: JM
authors.lastname: Kaufman
authors.forename: Agnes
authors.initials: A
authors.lastname: Ostertag
authors.forename: Martine
authors.initials: M
authors.lastname: Cohen-Solal
authors.forename: Anne
authors.initials: A
authors.lastname: Boland
authors.forename: Kaatje
authors.initials: K
authors.lastname: Toye
authors.forename: Diana
authors.initials: D
authors.lastname: Zelenika
authors.forename: Mark
authors.initials: M
authors.lastname: Lathrop
authors.forename: Marie-Christine
authors.initials: MC
authors.lastname: de Vernejoul
authors.forename: Maria
authors.initials: M
authors.lastname: Martinez
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D015519:Bone Density / Q000235:genetics*; D003198:Computer Simulation; D005272:Femur Neck / Q000737:chemistry*; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study / Q000379:methods*; D006801:Humans; D008159:Lumbar Vertebrae / Q000737:chemistry*; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci; D012044:Regression Analysis