Estimation of environmental and genetic components of quantitative traits with application to serum cholesterol levels

Abstract

A mixed model of environmental, polygenic, and major locus effects is developed, allowing for environmental correlations between first-degree relatives and spouses. Maximum-likelihood techniques are used to determine the relative contributions of each of these effects to a quantitative trait. Inclusion of a nuclear family in the sample is assumed to depend on the value of the quantitative trait of one member of the family, so conditional distributions are used. Application of the method to serum cholesterol data from the general population shows that the addition of a polygenic effect to a model that assumes only an environmental effect makes a significant improvement. A completely dominant single gene is also found to be influencing serum cholesterol levels. Although cholesterol levels have been adjusted for a range of factors, such as age, sex, weight/height, and marital status, environmental factors still account for about half the variability in the residual values.