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KMID : 0928520060160020289
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Korean Journal of Lipidology
2006 Volume.16 No. 2 p.289 ~ p.298
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Analysis of Genetic Association with Lipid Profiles Adjusting for Lipid-lowering Drug Effects
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Song Ki-Jun
Park Chan-Mi
Jang Yang-Soo
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Abstract
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Objective: The population-based genetic association studies of continuous traits can be seriously distorted when the traits are subject to the effects of certain treatment. Without appropriate adjustment of treatment effect, the results of analyses may be fundamentally flawed. So, we proposed an statistical approach based on censored normal regression to adjust a treatment effect and applied this method to real data.
Methods: We used data consisting of 1,687 individuals(male 884, female 983) who have the information of lipid profiles(total cholesterol, triglyceride, low density lipoprotein) and single nucleotide polymorphisms(SNPs) from Yonsei cardiovascular genome center. We used a censored normal regression method to analyze the genetic association adjusted for lipid-lowering drug effects and compared its performance to that of ordinary multiple linear regression.
Results: The results of our study provided that the performance of censored normal regression is more powerful than that of multiple linear regression for analysis of genetic association in serum lipid profiles. There were significant genetic association with lipid profiles in each 7 SNPs described in our real data.
Conclusion: We have demonstrated that censored normal regression approach for genetic association analysis can effectively adjust the distorting effect of lipid-lowering drug and recover a marked loss in statistical power.
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KEYWORD
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SNPs, Lipids, Lipid-lowering drug, Censored regression
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