Genetic analysis of personality traits and alcoholism using a mixed discrete continuous trait variance component model

Stefan A. Czerwinski, Michael C. Mahaney, Jeff T. Williams, Laura Almasy, John Blangero

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Bivariate analyses can improve power to detect linkage. This paper describes one application of a bivariate variance component method for estimating joint likelihoods of a continuous and a discrete trait. This method is applied to the Collaborative Study on the Genetics of Alcoholism data set to investigate the relationship between personality traits derived from the tridimensional personality questionnaire (TPQ) and alcoholism. The results indicate that the novelty-seeking subscale of the TPQ and alcoholism share a strong and significant genetic correlation (ρ(G) = 0.83) and modest environmental correlation (ρ(E) = 0.31). When both traits are considered jointly in a multipoint linkage model compared with the alcoholism trait alone, there is an improvement in the ability to detect and localize a quantitative trait locus on chromosome 4.

Original languageEnglish (US)
Pages (from-to)S121-S126
JournalGenetic epidemiology
Volume17
Issue numberSUPPL. 1
DOIs
StatePublished - 1999
Externally publishedYes

Keywords

  • Linkage
  • Novelty-seeking
  • Pleiotropy

ASJC Scopus subject areas

  • Epidemiology
  • Genetics(clinical)

Fingerprint

Dive into the research topics of 'Genetic analysis of personality traits and alcoholism using a mixed discrete continuous trait variance component model'. Together they form a unique fingerprint.

Cite this