Multiplex phenotypes

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A trait that is dependent on two or more genes is called polygenic, multifactorial, or a multiplex phenotype. Examples of a polygenic trait include height, obesity, blood pressure, coronary artery disease, asthma, diabetes mellitus, or the formation of the jaw during embryonic development. Mul tiplex phenotypes might also include some defined toxicity of an environmental agent (at a given exposure for a defined time). It is becoming increasingly clear that there is never really a simple Mendelian (single gene) human disease.3 Diseases that had been considered monogenic, such as Gaucher disease or phenylketonuria, are known to be affected by modifier genes andenvironmental factors. For example, the same N370S mutation in the glucocerebrosidase gene can result in the death of an 8-year-old boy with severe Gaucher disease and in a reasonably normal life for the child's 80-year-old grandfather who has only a somewhat enlarged liver and spleen. Such strikingly different Gaucher disease phenotypes strongly suggest that modifier genes and/or environmental factors contribute to what was previously taught to medical students as being a monogenic disease.

For two alleles at one locus, as described above, the ratio of genotype distribution is 1:2:1. For two alleles at two loci, this distribution becomes 1:4:6:4:1. For two alleles at three loci, this genotype distribution becomes 1:6:15:20:15:6:1. One can see how quickly the genotype (and usually also the phenotype) distribution becomes complex as the number of genes increases. The number of genes contributing to the risk of coronary artery disease is estimated to be greater than 100.3 If toxicity to an environmental chemical involves just 5 or 10 genes rather than 100, it is easy to appreciate that in most cases one will see a gradient from those most sensitive to the chemical to those most resistant to the chemical. The same can be said for pharmaco-genetic disorders, and a mathematical analysis involving extreme discordant phenotype methodology has been recently offered4 as a statistically powerful means by which a genotype can be correlated with an unequivocal pheno-type. The same should also hold true when any ecogenetic or other complex disease is studied. The outliers, or individuals at the extreme ends of the spectrum of any phenotype, are the most informative patients to scientists who wish to dissect the genes responsible for any phenotype.4

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