Statins are prescribed widely to lower plasma low-density lipoprotein (LDL) concentrations and cardiovascular disease risk1 and have been shown to have beneficial effects in a broad range of patients2,3. However, statins are associated with an increased risk, albeit small, of clinical myopathy4 and type 2 diabetes5. Despite evidence for substantial genetic influence on LDL concentrations6, pharmacogenomic trials have failed to identify genetic variations with large effects on either statin efficacy7,8,9 or toxicity10, and have produced little information regarding mechanisms that modulate statin response. Here we identify a downstream target of statin treatment by screening for the effects of in vitro statin exposure on genetic associations with gene expression levels in lymphoblastoid cell lines derived from 480 participants of a clinical trial of simvastatin treatment7. This analysis identified six expression quantitative trait loci (eQTLs) that interacted with simvastatin exposure, including rs9806699, a cis-eQTL for the gene glycine amidinotransferase (GATM) that encodes the rate-limiting enzyme in creatine synthesis. We found this locus to be associated with incidence of statin-induced myotoxicity in two separate populations (meta-analysis odds ratio = 0.60). Furthermore, we found that GATM knockdown in hepatocyte-derived cell lines attenuated transcriptional response to sterol depletion, demonstrating that GATM may act as a functional link between statin-mediated lowering of cholesterol and susceptibility to statin-induced myopathy.

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Gene Expression Omnibus

Data deposits

The gene expression data have been deposited in the Gene Expression Omnibus (GEO) under accession number GSE36868 and in Synapse (https://www.synapse.org/) under accession number syn299510. Code and analytical output complementary to this analysis are also provided through Synapse (https://www.synapse.org/#!Synapse:syn299510). The genotype data have been deposited in the database for genotypes and phenotypes (dbGaP, http://www.ncbi.nlm.nih.gov/gap) under accession number phs000481. The full set of eQTLs identified in our study is available at http://eqtl.uchicago.edu.


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This project was funded by a grant from the US National Institutes of Health (NIH), U01 HL69757. B.E.E. was funded through the Bioinformatics Research Development Fund, supported by K. and G. Gould and NIH grant K99/R00 HG006265. M.S. was funded by NIH grant HG002585. We acknowledge the efforts of T. Kitchner and R. Mareedu for case validation in the Marshfield cohort. SEARCH was supported by the Medical Research Council, British Heart Foundation, National Health Service Genetic Knowledge Park, Centre National de Génotypage and Merck. The Heart Protection Study was funded by grants from the Medical Research Council, British Heart Foundation, Roche Vitamins and Merck. J.C.H. acknowledges support from the BHF Centre of Research Excellence, Oxford, UK. Genetic analysis in JUPITER was funded by a grant from AstraZeneca to D.I.C. and P.M.R.

Author information

Author notes

    • Lara M. Mangravite
    •  & Barbara E. Engelhardt

    These authors contributed equally to this work.

    • Barbara E. Engelhardt
    •  & Mark J. Rieder

    Present addresses: Biostatistics and Bioinformatics Department and Department of Statistical Science, Duke University, Durham, North Carolina, USA (B.E.E.); Adaptive Biotechnologies, Seattle, Washington, USA (M.J.R.).


  1. Sage Bionetworks, 1100 Fairview Avenue North, Seattle, Washington 98109, USA

    • Lara M. Mangravite
    •  & Brigham H. Mecham
  2. Department of Human Genetics, University of Chicago, 920 East 58th Street, Chicago, Illinois 60637, USA

    • Barbara E. Engelhardt
    • , Bryan Howie
    • , Heejung Shim
    •  & Matthew Stephens
  3. Children’s Hospital Oakland Research Institute, 5700 Martin Luther King Jr Way, Oakland, California 94609, USA

    • Marisa W. Medina
    • , Devesh Naidoo
    •  & Ronald M. Krauss
  4. Department of Genome Sciences, University of Washington, 3720 15th Avenue Northeast, Seattle, Washington 98195, USA

    • Joshua D. Smith
    • , Mark J. Rieder
    •  & Deborah A. Nickerson
  5. Department of Genetics, University of Pennsylvania, 415 Curie Boulevard, Philadelphia, Pennsylvania 19103, USA

    • Christopher D. Brown
  6. Center for Cardiovascular Disease Prevention, Division of Preventative Medicine, Brigham and Women’s Hospital, 900 Commonwealth Drive, Boston, Massachusetts 02115, USA

    • Daniel I. Chasman
    •  & Paul M. Ridker
  7. Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University Medical Center, 23rd Avenue South, Nashville, Tennessee 37232, USA

    • QiPing Feng
    •  & Russell A. Wilke
  8. Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, 1124 West Carson Street, Torrance, California 90502, USA

    • Yii.-Der I. Chen
    •  & Jerome I. Rotter
  9. Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Richard Doll Building, Old Road Campus, Roosevelt Drive, Oxford OX3 7LF, UK

    • Jemma C. Hopewell
    • , Sarah Parish
    • , Jane Armitage
    •  & Rory Collins
  10. Department of Statistics, Eckhart Hall, 5734 South University Avenue, University of Chicago, Chicago, Illinois 60637, USA

    • Matthew Stephens


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L.M.M. designed experiment and analyses, generated samples, performed analyses, and wrote the manuscript. B.E.E. designed and performed analyses and wrote the manuscript. C.D.B. performed analyses of ENCODE data. B.H.M. designed and performed correlation analyses. J.D.S., M.J.R. and D.A.N. generated expression and genotype data. M.W.M. and D.N. designed, performed and analysed functional experiments. B.H. and H.S. developed and performed the imputation methodology. R.A.W, Q.F., J.D.S., M.J.R. and D.A.N. collected and genotyped the myopathy cohort from the Marshfield clinic and performed association analyses. J.C.H., S.P., J.A. and R.C. collected and genotyped myopathy cohort from the SEARCH trial and performed association analyses in that cohort along with the Heart Protection Study. J.I.R. and Y.-D.I.C. measured creatine kinase in CAP. D.I.C. and P.M.R. measured creatine kinase and performed related analyses in JUPITER. M.S. supervised, designed and contributed to analyses, and participated in manuscript development. R.M.K. supervised the project and participated in experimental design and manuscript development. M.S. and R.M.K. co-directed this project.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Lara M. Mangravite or Matthew Stephens or Ronald M. Krauss.

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    This file contains Supplementary Figures 1-5, Supplementary Methods, Supplementary Data, Supplementary Tables 2, 4, 7, 8, 9 and additional references. See separate files for Supplementary Tables 1, 3, 5 and 6.

Excel files

  1. 1.

    Supplementary Table 1

    Stable cis-eQTLs identified in association with gene expression following simvastatin exposure (treated, T), control exposure (control, C), or averaged across both exposures (averaged, S). Top eQTL listed for each gene. Significance threshold set at log10BF=3.24.

  2. 2.

    Supplementary Table 3

    Supplementary Table 3 Stable trans-eQTLs identified in association with gene expression following simvastatin exposure (treated, T), control exposure (control, C), or averaged across both exposures (averaged, S). Significance threshold set at log10BF=7.20.

  3. 3.

    Supplementary Table 5

    Differential cis-eQTLs identified by univariate analysis to be in association with gene expression following simvastatin exposure (treated, T), control exposure (control, C), or averaged across both exposures (averaged, S). Top eQTL listed for each gene with log10BF>2.0. Significance threshold set at log10BF=4.9.

  4. 4.

    Supplementary Table 6

    Differential trans-eQTLs identified by univariate analysis as associated with gene expression following simvastatin exposure (treated, T), control exposure (control, C), or averaged across both exposures (averaged, S). Top eQTL listed for each gene with log10BF>5.0. Significance threshold set at log10BF=7.20.

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