One of the main reasons for studying the origins and nature of human genetic variation is that the similarities and differences in the type and frequencies of genetic variations among populations can have a profound impact on studies that attempt to understand the influence of genes on disease risk.
For example, some genetic variations, like the apolipoprotein E protein polymorphisms, are found in every population and have very similar genotype frequencies around the world. This genetic variation is associated with the increased risk of heart disease and Alzheimer’s disease. This association has been tested in many populations around the world. Additionally, other mutations such as the 10kb deletion in the LDL-R gene described above are more population-specific variations.
Furthermore, the effect of a genetic variation on the continuum of risk found in any population corresponds directly with its frequency. For instance, common genetic polymorphisms with frequencies near 50 percent cannot be associated with large phenotypic effects within a population because the genotype classes each represent a large fraction of the population.
Since most risk is normally distributed, the average risk for a highly widespread genotype class cannot deviate from the overall risk of the population to any large degree. This connection between genotype frequency and effect does not necessarily mean that common variations cannot have significant effects. The statistical significance of a connection between a genetic variation and a disease is a joint function of sample size and the size of the effect.
Additionally, genetic research among populations that differ in their genotype frequencies can also differ in their inferences about which polymorphisms have significant effects even if the absolute phenotypic effect is the same. Cheverud and Routman offer a more formal statistical explanation of this phenomenon and its impact on understanding and interpreting gene-gene interactions.
Another aspect that must be considered in understanding the connection between genetic variations and measures of disease susceptibility is the population differences in the correlations between genotype frequencies at different SNP locations.
There are two common reasons why the frequency of an allele or genotype at a particular SNP could be correlated with the frequency of an allele or genotype for a different SNP. The first reason is a phenomenon known as linkage disequilibrium. Linkage disequilibrium creates correlations among SNPs as a result of the mutation’s history. When mutations happen, they occur on a particular genetic background, which creates a correlation with the other SNPs on the chromosome.
The other common reason for the frequency of an allele or genotype at a particular SNP is the mixing of populations. This is known as admixture which occurs typically through migration, meaning that SNPs with population-specific frequencies will be correlated in a larger mixed sample. In this case, population stratification is the cause of the correlation.
There has been a great deal of genetic epidemiological research on this phenomenon and how to control for it. Population stratification is thought to be a possible source of spurious genetic associations with disease.
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