title: Bivariate linear mixed model analysis to test joint associations of genetic variants on systolic and diastolic blood pressure.
abstract: Genetic variants that predispose adults and the elderly to high blood pressure are largely unknown. We used a bivariate linear mixed model approach to jointly test the associations of common single-nucleotide polymorphisms with systolic and diastolic blood pressure using data from a genome-wide association study consisting of genetic variants from chromosomes 3 and 9 and longitudinal measured phenotypes and environment variables from unrelated individuals of Mexican American ethnicity provided by the Genetic Analysis Workshop 18. Despite the small sample size of a maximum of 131 unrelated subjects, a few single-nucleotide polymorphisms appeared significant at the genome-wide level. Simulated data, which was also provided by Genetic Analysis Workshop 18 organizers, showed higher power of the bivariate approach over univariate analysis to detect the association of a selected single-nucleotide polymorphism with modest effect. This suggests that the bivariate approach to longitudinal data of jointly measured and correlated phenotypes can be a useful strategy to identify candidate single-nucleotide polymorphisms that deserve further investigation.
authors.affiliation: Population Genomics Program, McMaster University, 1200 Main Street West, Hamilton, Ontario, L8N 3Z5, Canada.
authors.forename: Binod
authors.initials: B
authors.lastname: Neupane
authors.affiliation: Population Genomics Program, McMaster University, 1200 Main Street West, Hamilton, Ontario, L8N 3Z5, Canada.
authors.forename: Joseph
authors.initials: J
authors.lastname: Beyene