Bivariate linear mixed model analysis to test joint associations of genetic variants on systolic and diastolic blood pressure

BMC Proceedings

Proceedings

Joseph Beyene¹  Binod Neupane¹ 

[1] Population Genomics Program, McMaster University, 1200 Main Street West, L8N 3Z5, Hamilton, Ontario, Canada;

关键词: Diastolic Blood Pressure;    Genetic Analysis Workshop;    Linear Mixed Model Analysis;    Real Data Analysis;    Genotyping Call Rate;   

DOI  :  10.1186/1753-6561-8-S1-S75

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY   
© Neupane and Beyene; licensee BioMed Central Ltd. 2014