Modeling age x major gene interaction by a variance component approach.
The variance component method has become popular for linkage analysis due to its computational simplicity and generally high power. In this paper we model phenotypic variability of an individual as a mixed effects model in which both the major gene as well as the polygene effects interact with age. We applied the proposed model to the simulated data of Genetic Analysis Workshop 12. We considered the quantitative trait, Q4, in the outbred population. Two major genes influence this trait, each interacting with age independently. Consequently, trait variability is a function of age and also there is interaction of major gene effects with age. By using our model we were able to detect interaction between the major gene effects and age for this trait.
Shete
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Department of Epidemiology, University of Texas M.D. Anderson Cancer Center, 1515 Holcombe Blvd., Box 189, Houston, TX 77030, USA.
Chen
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J
Zhou
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Amos
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CI
D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000483:Alleles; D000704:Analysis of Variance; D002874:Chromosome Mapping / Q000706:statistics & numerical data*; D002886:Chromosomes, Human, Pair 17; D002899:Chromosomes, Human, Pair 9; D005260:Female; D005819:Genetic Markers / Q000235:genetics; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D005838:Genotype; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D008875:Middle Aged; D008957:Models, Genetic; D010641:Phenotype; D019655:Quantitative Trait, Heritable
D005819:Genetic Markers