A comparison of discrete versus continuous environment in a variance components-based linkage analysis of the COGA data.
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.


CONCLUSIONS
Alternative parameterizations may better represent the functional relationship between the continuous environment and the genetic variance.
Viel
Kevin R
KR
Department of Epidemiology, Emory University, Atlanta, Georgia, USA. kviel@emory.edu
Warren
Diane M
DM
Buil
Alfonso
A
Dyer
Thomas D
TD
Howard
Tom E
TE
Almasy
Laura
L
D000437:Alcoholism / Q000235:genetics*; D000704:Analysis of Variance; D002874:Chromosome Mapping; D003299:Cooperative Behavior; D030541:Databases, Genetic; D004777:Environment; D006801:Humans