Including endophenotypes as covariates in variance component heritability and linkage analysis.
The purpose of these analyses was to determine if incorporating or adjusting for covariates in genetic analyses helped or hindered in genetic analyses, specifically heritability and linkage analyses. To study this question, two types of covariate models were used in the simulated Genetic Analysis Workshop 14 dataset in which the true gene locations are known. All four populations of one replicate were combined for the analyses. The first model included typical covariates of sex and cohort (population) and the second included the typical covariates and also those related endophenotypes that are thought to be associated with the trait (phenotypes A, B, C, D, E, F, G, H, I, J, K, and L). A final best fit model produced in the heritability analyses was used for linkage. Linkage for disease genes D1, D3, and D4 were localized using models with and without the covariates. The use of inclusion of covariates did not appear to have any consistent advantage or disadvantage for the different phenotypes in regards to gene localization or false positive rate.
Bailey
Julia N
JN
Neuropsychiatric Institute and Epilepsy Genetics/Genomics Laboratories, University of California at Los Angeles School of Medicine, Los Angeles, CA, USA. jbailey@mednet.ucla.edu
D008040:Genetic Linkage; D006801:Humans; D040582:Inheritance Patterns / Q000235:genetics*; D008126:Lod Score; D010554:Personality Disorders; D010641:Phenotype