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

Kevin R. Viel, Diane M. Warren, Alfonso Buil, Thomas D. Dyer, Tom E. Howard, Laura Almasy

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

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. Conclusion: Alternative parameterizations may better represent the functional relationship between the continuous environment and the genetic variance.

Original languageEnglish (US)
Article numberS57
JournalBMC genetics
Volume6
Issue numberSUPPL.1
DOIs
StatePublished - Dec 30 2005
Externally publishedYes

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

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