Document Type
Article
Abstract
Numerous mutations are now known that have significant effects on various phenotypes; many of these mutations are of interest because they influence quantitative risk factors for major diseases. Such diversity raises the question of how much genetic heterogeneity we should expect to find in the effects of alleles, that is, the size of the effects, the number of severe alleles, and their frequency in the population. Can evolutionary models suggest a general pattern? In this article we examine what is currently known about several basic aspects of the problem. These include the distribution of quantitative effects of new mutations on a phenotype, the distribution of allelic effects that would be found in a natural population, and the relationship between these effects and Darwinian fitness. We discuss these issues in light of various models that have been proposed and the existing relevant data. Then we consider how these points relate to the distribution of genetic effects on an important hum an trait, the cholesterol ratio, an important risk factor for coronary heart disease. The complexities of quantitative traits and inadequacies in the available data prevent definitive models that can directly connect the mutational effects, allelic effects, and fitness distributions from being developed, and we consider how sample limitations and the nonequilibrium of hum an populations caused by our demographic history make rigorous solutions difficult. However, based on what is currently known, we argue that for human quantitative chronic disease risk factors the nearly neutral models of allelic evolution at single loci probably apply reasonably well. In general, and although much is still speculative, the data available for such risk factors are consistent with these expectations and may enable us to predict many aspects of etiologic heterogeneity for human disease.
Recommended Citation
Connor, Adam; Weiss, Kenneth M.; and Weeks, Stephen C.
(1993)
"Evolutionary Models of Quantitative Disease Risk Factors,"
Human Biology:
Vol. 65:
Iss.
6, Article 4.
Available at:
https://digitalcommons.wayne.edu/humbiol/vol65/iss6/4