Dataset Information

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.

SUBMITTER: Saint-Pierre A

PROVIDER: S-EPMC3110051 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature

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Bivariate association analysis in selected samples: application to a GWAS of two bone mineral density phenotypes in males with high or low BMD.

Saint-Pierre Aude A Kaufman Jean-Marc JM Ostertag Agnes A Cohen-Solal Martine M Boland Anne A Toye Kaatje K Zelenika Diana D Lathrop Mark M de Vernejoul Marie-Christine MC Martinez Maria M

European journal of human genetics : EJHG 20110323 6

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 ...[more]

PMID: 21427758

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Project description:This study aimed to better define the role of heel-QUS in fracture prediction. Our results showed that heel-QUS predicts fracture independently of FRAX, BMD, and TBS. This corroborates its use as a case finding/pre-screening tool in osteoporosis management.IntroductionQuantitative ultrasound (QUS) characterizes bone tissue based on the speed of sound (SOS) and broadband ultrasound attenuation (BUA). Heel-QUS predicts osteoporotic fractures independently of clinical risk factors (CRFs) and bone mineral density (BMD). We aimed to investigate whether (1) heel-QUS parameters predict major osteoporotic fractures (MOF) independently of the trabecular bone score (TBS) and (2) the change of heel-QUS parameters over 2.5 years is associated with fracture risk.MethodsOne thousand three hundred forty-five postmenopausal women from the OsteoLaus cohort were followed up for 7 years. Heel-QUS (SOS, BUA, and stiffness index (SI)), DXA (BMD and TBS), and MOF were assessed every 2.5 years. Pearson's correlation and multivariable regression analyses were used to determine associations between QUS and DXA parameters and fracture incidence.ResultsDuring a mean follow-up of 6.7 years, 200 MOF were recorded. Fractured women were older, more treated with anti-osteoporosis medication; had lower QUS, BMD, and TBS; higher FRAX-CRF risk; and more prevalent fractures. TBS was significantly correlated with SOS (0.409) and SI (0.472). A decrease of one SD in SI, BUA or SOS increased the MOF risk by (OR(95%CI)) 1.43 (1.18-1.75), 1.19 (0.99-1.43), and 1.52 (1.26-1.84), respectively, after adjustment for FRAX-CRF, treatment, BMD, and TBS. We found no association between the change of QUS parameters in 2.5 years and incident MOF.ConclusionHeel-QUS predicts fracture independently of FRAX, BMD, and TBS. Thus, QUS represents an important case finding/pre-screening tool in osteoporosis management. The change in QUS over time was not associated with future fractures, making it inappropriate for patient monitoring.

Dataset Information

Bivariate association analysis in selected samples: application to a GWAS of two bone mineral density phenotypes in males with high or low BMD.

Publications

Bivariate association analysis in selected samples: application to a GWAS of two bone mineral density phenotypes in males with high or low BMD.

Similar Datasets

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