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A bivariate genetic analysis of HDL- and LDL-cholesterol incorporating measured covariates: a Gibbs sampling
W J Mack1, W J Gauderman, D C Thomas
1Department of Preventive Medicine, University of Southern California, Los Angeles 90033.
Abstract:
We analyzed HDL- and LDL-cholesterol levels as a bivariate phenotype in 27 families as a function of major genes, polygenes, and measured covariates using a Monte Carlo sampling technique called Gibbs sampling. Major genes and polygenes exhibited strong effects, when considered separately. While a major gene versus polygene model could not be clearly differentiated for HDL-C, polygenes appeared to play a stronger role than a major gene for LDL-C. There was no evidence of linkage between the two major genes for HDL- and LDL-C, and the correlation in polygenes was negative. The analysis illustrate the potential applicability of Gibbs sampling to such complex problems as the multivariate analysis of continuous phenotypes.