Individualized risk for statin-induced myopathy: Current knowledge, emerging challenges and potential solutions

Department of Medicine, Vanderbilt University Medical Center, Oates Institute for Experimental Therapeutics, Nashville, TN, USA.
Pharmacogenomics (Impact Factor: 3.22). 04/2012; 13(5):579-94. DOI: 10.2217/pgs.12.11
Source: PubMed


Skeletal muscle toxicity is the primary adverse effect of statins. In this review, we summarize current knowledge regarding the genetic and nongenetic determinants of risk for statin induced myopathy. Many genetic factors were initially identified through candidate gene association studies limited to pharmacokinetic (PK) targets. Through genome-wide association studies, it has become clear that SLCO1B1 is among the strongest PK predictors of myopathy risk. Genome-wide association studies have also expanded our understanding of pharmacodynamic candidate genes, including RYR2. It is anticipated that deep resequencing efforts will define new loci with rare variants that also contribute, and sophisticated computational approaches will be needed to characterize gene-gene and gene-environment interactions. Beyond environment, race is a critical covariate, and its influence is only partly explained by geographic differences in the frequency of known pharmacodynamic and PK variants. As such, admixture analyses will be essential for a full understanding of statin-induced myopathy.

Download full-text


Available from: Tesfaye M Baye, Feb 06, 2015
44 Reads
    • "A range of risk factors have been reported for statin-associated myopathy, including female gender (though not in all studies), low body mass index, older age, intense physical exercise, comorbidities such as hypothyroidism, and – most importantly – interactions with other drugs such as amiodarone and fibrates.5 In candidate gene studies, polymorphisms in a variety of genes affecting statin pharmacokinetics or pharmacodynamics have also been reported to influence statin-induced myopathy (reviewed in 32). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Statin drugs are highly effective in lowering blood concentrations of LDL-cholesterol, with concomitant reduction in risk of major cardiovascular events. Although statins are generally regarded as safe and well-tolerated, some users develop muscle symptoms that are mostly mild but in rare cases can lead to life-threatening rhabdomyolysis. The SEARCH genome-wide association study, which has been independently replicated, found a significant association between the rs4149056 (c.521T>C) single-nucleotide polymorphism (SNP) in the SLCO1B1 gene, and myopathy in individuals taking 80 mg simvastatin per day, with an odds ratio of 4.5 per rs4149056 C allele. The purpose of this paper is to assemble evidence relating to the analytical validity, clinical validity and clinical utility of using SLCO1B1 rs4149056 genotyping to inform choice and dose of statin treatment, with the aim of minimising statin-induced myopathy and increasing adherence to therapy. Genotyping assays for the rs4149056 SNP appear to be robust and accurate, though direct evidence for the performance of array-based platforms in genotyping individual SNPs was not found. Using data from the SEARCH study, calculated values for the clinical sensitivity, specificity, positive- and negative-predictive values of a test for the C allele to predict definite or incipient myopathy during 5 years of 80 mg/day simvastatin use were 70.4%, 73.7%, 4.1% and 99.4% respectively. There is a need for studies comparing the clinical validity of SLCO1B1 rs4149056 genotyping with risk scores for myopathy based on other factors such as racial background, statin type and dose, gender, body mass index, co-medications and co-morbidities. No direct evidence was found for clinical utility of statin prescription guided by SLCO1B1 genotype.
    PLoS Currents 12/2013; 5. DOI:10.1371/currents.eogt.d21e7f0c58463571bb0d9d3a19b82203
  • Pharmacogenomics 08/2012; 13(11):1223-5. DOI:10.2217/pgs.12.107 · 3.22 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Genetic risk prediction uses genetic data to individualize prediction of outcome or effect from a known harmful toxicant. Several examples of toxicogenetics (usually binary traits) are discussed, reflecting largely Mendelian traits before the Human Genome Project began in 1990. Numerous complexities of the genome and what constitutes "a gene" have emerged during these past two decades. Examples of toxicogenomics (continuous outcomes, gradients) are examined. Most xenobiotic-induced environmental diseases resemble human complex diseases or other multifactorial traits such as height; these traits result from hundreds of low-effect genes. Consequently, uncovering an association between a trait and a genetic variant in a large cohort can provide important information about underlying biology; however, screening for a specific variant in an individual worker or patient has poor predictive value and little clinical utility. Individualized risk assessment for toxicants that cause environmental diseases, although a lofty goal, remains to be achieved.
    Annual Review of Pharmacology 01/2013; 53(1):355-75. DOI:10.1146/annurev-pharmtox-011112-140241 · 18.37 Impact Factor
Show more