Abstract
The GAW20 simulation data set is based upon the companion Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study fenofibrate clinical trial data set that forms the real data example for GAW20. The simulated data problem consists of 200 simulated replications of what might happen if we were to repeat the GOLDN clinical trial 200 independent times, for these exact same subjects, but using a new fictitious drug (called “genomethate”) that has a pharmaco-epigenetic effect on triglyceride response. For each replication, the pre-genomethate values at visits 1 and 2 are constant (ie, pedigree structures, age, sex, all phenotypes, covariates, genome-wide association study (GWAS) genotypes, and visit 2 methylation values), the same as the real GOLDN data across all 200 replications. Only the post-genomethate treatment data (ie, methylation and triglyceride levels for visits 3 and 4) change across the 200 replications. We postulate a growth curve pharmaco-epigenetic response model, in which each patient’s response to genomethate treatment is individualized, and is dependent upon their genotype as well as the methylation state for key genes.
Highlights
The companion Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study fenofibrate clinical trial data set [1,2,3] was the foundation of our Genetic Analysis Workshop 20 (GAW20) simulation
The general simulation strategy was to first simulate visit 4 methylation array data for each subject, and use this plus the genome-wide association study (GWAS) genotypes to produce the simulated triglycerides for visits 3 and 4 post-treatment values
We used the above observed mean and standard deviation of slopes seen in the original GOLDN data, to rescale as follows: sim slopejk1⁄4corrzjkÃsd O slope TG þmean O slope TG
Summary
The companion Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study fenofibrate clinical trial data set [1,2,3] was the foundation of our Genetic Analysis Workshop 20 (GAW20) simulation. The main simulated effect of genomethate is on the phenotype of the individual subject’s triglyceride (TG) values measured as slope in response to treatment (change in mg/dL per unit time of treatment). We first defined a series of subjects’ triglyceride values from the original (real) Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) data [1], which was used to generate the simulations. For the jth subject, the average log triglycerides pre-treatment (average of visits 1 and 2, which are 1 day apart) and. The TG of person j is measured in visits 1, 2, 3 and 4 and averaged as above for each individual as preRx and postRx. The corresponding change in log triglycerides pre-treatment to posttreatment for subject j is given by: Â. =sd O preRx TG where O_preZ -is a standardized normally distributed variable with N(0,1)
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