title: A comparison of discrete versus continuous environment in a variance components-based linkage analysis of the COGA data.
abstract: 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.
authors.affiliation: Department of Epidemiology, Emory University, Atlanta, Georgia, USA. kviel@emory.edu
authors.forename: Kevin R
authors.initials: KR
authors.lastname: Viel
authors.forename: Diane M
authors.initials: DM
authors.lastname: Warren
authors.forename: Alfonso
authors.initials: A
authors.lastname: Buil
authors.forename: Thomas D
authors.initials: TD
authors.lastname: Dyer
authors.forename: Tom E
authors.initials: TE
authors.lastname: Howard
authors.forename: Laura
authors.initials: L
authors.lastname: Almasy
mesh_terms: D000437:Alcoholism / Q000235:genetics*; D000704:Analysis of Variance; D002874:Chromosome Mapping; D003299:Cooperative Behavior; D030541:Databases, Genetic; D004777:Environment; D006801:Humans