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Genome-Wide Association of Lipid-Lowering Response to Statins in Combined Study Populations

Author

Listed:
  • Mathew J Barber
  • Lara M Mangravite
  • Craig L Hyde
  • Daniel I Chasman
  • Joshua D Smith
  • Catherine A McCarty
  • Xiaohui Li
  • Russell A Wilke
  • Mark J Rieder
  • Paul T Williams
  • Paul M Ridker
  • Aurobindo Chatterjee
  • Jerome I Rotter
  • Deborah A Nickerson
  • Matthew Stephens
  • Ronald M Krauss

Abstract

Background: Statins effectively lower total and plasma LDL-cholesterol, but the magnitude of decrease varies among individuals. To identify single nucleotide polymorphisms (SNPs) contributing to this variation, we performed a combined analysis of genome-wide association (GWA) results from three trials of statin efficacy. Methods and Principal Findings: Bayesian and standard frequentist association analyses were performed on untreated and statin-mediated changes in LDL-cholesterol, total cholesterol, HDL-cholesterol, and triglyceride on a total of 3932 subjects using data from three studies: Cholesterol and Pharmacogenetics (40 mg/day simvastatin, 6 weeks), Pravastatin/Inflammation CRP Evaluation (40 mg/day pravastatin, 24 weeks), and Treating to New Targets (10 mg/day atorvastatin, 8 weeks). Genotype imputation was used to maximize genomic coverage and to combine information across studies. Phenotypes were normalized within each study to account for systematic differences among studies, and fixed-effects combined analysis of the combined sample were performed to detect consistent effects across studies. Two SNP associations were assessed as having posterior probability greater than 50%, indicating that they were more likely than not to be genuinely associated with statin-mediated lipid response. SNP rs8014194, located within the CLMN gene on chromosome 14, was strongly associated with statin-mediated change in total cholesterol with an 84% probability by Bayesian analysis, and a p-value exceeding conventional levels of genome-wide significance by frequentist analysis (P = 1.8×10−8). This SNP was less significantly associated with change in LDL-cholesterol (posterior probability = 0.16, P = 4.0×10−6). Bayesian analysis also assigned a 51% probability that rs4420638, located in APOC1 and near APOE, was associated with change in LDL-cholesterol. Conclusions and Significance: Using combined GWA analysis from three clinical trials involving nearly 4,000 individuals treated with simvastatin, pravastatin, or atorvastatin, we have identified SNPs that may be associated with variation in the magnitude of statin-mediated reduction in total and LDL-cholesterol, including one in the CLMN gene for which statistical evidence for association exceeds conventional levels of genome-wide significance. Trial Registration: PRINCE and TNT are not registered. CAP is registered at Clinicaltrials.gov NCT00451828

Suggested Citation

  • Mathew J Barber & Lara M Mangravite & Craig L Hyde & Daniel I Chasman & Joshua D Smith & Catherine A McCarty & Xiaohui Li & Russell A Wilke & Mark J Rieder & Paul T Williams & Paul M Ridker & Aurobind, 2010. "Genome-Wide Association of Lipid-Lowering Response to Statins in Combined Study Populations," PLOS ONE, Public Library of Science, vol. 5(3), pages 1-10, March.
  • Handle: RePEc:plo:pone00:0009763
    DOI: 10.1371/journal.pone.0009763
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    References listed on IDEAS

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    1. Yongtao Guan & Matthew Stephens, 2008. "Practical Issues in Imputation-Based Association Mapping," PLOS Genetics, Public Library of Science, vol. 4(12), pages 1-11, December.
    2. B. Devlin & Kathryn Roeder, 1999. "Genomic Control for Association Studies," Biometrics, The International Biometric Society, vol. 55(4), pages 997-1004, December.
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    1. Paul T Williams, 2012. "Quantile-Specific Penetrance of Genes Affecting Lipoproteins, Adiposity and Height," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-8, January.
    2. Weihua Shou & Dazhi Wang & Kaiyue Zhang & Beilan Wang & Zhimin Wang & Jinxiu Shi & Wei Huang, 2012. "Gene-Wide Characterization of Common Quantitative Trait Loci for ABCB1 mRNA Expression in Normal Liver Tissues in the Chinese Population," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-10, September.

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