4.5 Article

The genetic architecture of fasting plasma triglyceride response to fenofibrate treatment

期刊

EUROPEAN JOURNAL OF HUMAN GENETICS
卷 16, 期 5, 页码 603-613

出版社

NATURE PUBLISHING GROUP
DOI: 10.1038/sj.ejhg.5202003

关键词

fenofibrate; triglyceride; VLDL; gene-drug interaction; epistasis; gene -gene interaction

资金

  1. NHGRI NIH HHS [T32 HG000040, T32 HG00040] Funding Source: Medline
  2. NHLBI NIH HHS [U01 HL072524, U01 HL072524-01, U 01 HL72524] Funding Source: Medline

向作者/读者索取更多资源

Metabolic response to the triglyceride (TG)- lowering drug, fenofibrate, is shaped by interactions between genetic and environmental factors, yet knowledge regarding the genetic determinants of this response is primarily limited to single- gene effects. Since very low- density lipoprotein ( VLDL) is the central carrier of fasting TG, identifying factors that affect both total TG and VLDL - TG response to fenofibrate is critical for predicting individual fenofibrate response. As part of the Genetics of Lipid Lowering Drugs and Diet Network ( GOLDN) study, 688 individuals from 161 families were genotyped for 91 single- nucleotide polymorphisms ( SNPs) in 25 genes known to be involved in lipoprotein metabolism. Using generalized estimating equations to control for family structure, we performed linear modeling to investigate whether single SNPs, single covariates, SNP - SNP interactions, and/ or SNP-covariate interactions had a significant association with the change in total fasting TG and fasting VLDL - TG after 3 weeks of fenofibrate treatment. A 10-iteration fourfold cross-validation procedure was used to validate significant associations and quantify their predictive abilities. More than one- third of the significant, cross-validated SNP - SNP interactions predicting each outcome involved just five SNPs, showing that these SNPs are of key importance to fenofibrate response. Multiple variable models constructed using the top-ranked SNP covariate interactions explained 11.9% more variation in the change in TG and 7.8% more variation in the change in VLDL than baseline TG alone. These results yield insight into the complex biology of fenofibrate response, which can be used to target fenofibrate therapy to individuals who are most likely to benefit from the drug.

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