title: Structural equation modeling with latent variables for longitudinal blood pressure traits using general pedigrees.
abstract: Structural equation modeling (SEM) has been used in a wide range of applied sciences including genetic analysis. The recently developed R package,strum,implements a framework for SEM for general pedigree data. We explored different SEM techniques usingstrumto analyze the multivariate longitudinal data and to ultimately test the association of genotypes on blood pressure traits. The quantitative blood pressure (BP) traits, systolic BP (SBP) and diastolic BP (DBP) were analyzed as the main traits of interest with age, sex, and smoking status as covariates. The single nucleotide polymorphism (SNP) genotype information from genome-wide association studies (GWAS) data was used for the test of association. The adjustment for hypertension treatment effect was done by the censored regression approach. Two different longitudinal data models, autoregressive model and latent growth curve model, were used to fit the longitudinal BP traits. The test of association for SNP was done using a novel score test within the SEM framework ofstrum. We found the 10 SNPs within the GWAS suggestivePvalue level, and among those 10, the most significant top 3 SNPs agreed in rank in both analysis models. The general SEM framework instrumis very useful to model and test for the association with massive genotype data and complex systems of multiple phenotypes with general pedigree data.
authors.affiliation: Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106 USA.
authors.forename: Yeunjoo E
authors.initials: YE
authors.lastname: Song
authors.affiliation: Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106 USA ; Center for Clinical Investigation, Case Western Reserve University, Cleveland, OH 44106 USA.
authors.forename: Nathan J
authors.initials: NJ
authors.lastname: Morris
authors.affiliation: Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106 USA ; Center for Proteomics and Bioinformatics, Case Western Reserve University, Cleveland, OH 44106 USA.
authors.forename: Catherine M
authors.initials: CM
authors.lastname: Stein