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A comparison of discrete versus continuous environment in a variance components-based linkage analysis of the COGA
Kevin R Viel1, Diane M Warren, Alfonso Buil
1Department of Epidemiology, Emory University, Atlanta, Georgia, USA. kviel@emory.edu
Background:
The information content of a continuous variable exceeds that of its categorical counterpart. The parameterization of a model may diminish the benefit of using a continuous variable. We explored the use of continuous versus discrete environment in variance components based analyses examining gene x environment interaction in the electrophysiological phenotypes from the Collaborative Study on the Genetics of Alcoholism.
Results:
The parameterization using the continuous environment produced a greater number of significant gene x environment interactions and lower AICs (Akaike's information criterion). In these cases, the genetic variance increased with increasing cigarette pack-years, the continuous environment of interest. This did not, however, result in enhanced LOD scores when linkage analyses incorporated the gene x continuous environment interaction.
Conclusion:
Alternative parameterizations may better represent the functional relationship between the continuous environment and the genetic variance.
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