Using a latent growth curve model for an integrative assessment of the effects of genetic and environmental factors on multiple phenotypes.
We propose the use of latent growth curve model to assess the influence of genetic, environmental, demographic, and lifestyle factors on multiple phenotypes related to coronary heart disease. We model four quantitative traits (systolic blood pressure, high-density lipoprotein, low-density lipoprotein, and triglycerides) simultaneously in a multivariate framework that allows us to study their change over time, assess individual variation, and investigate cross-phenotype relationships. Environmental, demographic, and lifestyle covariates are included at different levels of the model as time-varying or time-invariant, as appropriate. To investigate the change over time attributed to genetic factors, we use candidate markers that have previously been shown to be associated with the quantitative traits. We illustrate our approach using independent observations from the offspring cohort of the Framingham Heart Study data.
Hamid
Jemila S
JS
Biostatistics Methodology Unit, Child Health Evaluative Sciences, The Hospital for Sick Children Research Institute, 555 University Avenue Toronto, Ontario M5G 1X8, Canada. jemila@utstat.toronto.edu.
Roslin
Nicole M
NM
Paterson
Andrew D
AD
Beyene
Joseph
J