title: An effective assessment of simvastatin-induced toxicity with NMR-based metabonomics approach.
abstract: BACKGROUND
  Simvastatin, which is used to control elevated cholesterol levels, is one of the most widely prescribed drugs. However, a daily excessive dose can induce drug-toxicity, especially in muscle and liver. Current markers for toxicity reflect mostly the late stages of tissue damage; thus, more efficient methods of toxicity evaluation are desired.
  
  
  RESULTS
  As a new way to evaluate toxicity, we performed NMR-based metabonomics analysis of urine samples. Compared to conventional markers, such as AST, ALT, and CK, the urine metabolic profile provided clearer distinction between the pre- and post-treatment groups treated with toxic levels of simvastatin. Through multivariate statistical analysis, we identified marker metabolites associated with the toxicity. Importantly, we observed that the treatment group could be further categorized into two subgroups based on the NMR profiles: weak toxicity (WT) and high toxicity (HT). The distinction between these two groups was confirmed by the enzyme values and histopathological exams. Time-dependent studies showed that the toxicity at 10 days could be reliably predicted from the metabolic profiles at 6 days.
  
  
  CONCLUSIONS
  This metabonomics approach may provide a non-invasive and effective way to evaluate the simvastatin-induced toxicity in a manner that can complement current measures. The approach is expected to find broader application in other drug-induced toxicity assessments.
authors.affiliation: Department of Biochemistry, Inha University Hospital and Center for Advanced Medical Education by BK21 project, College of Medicine, Inha University, Incheon, Korea.
authors.forename: Hye-Ji
authors.initials: HJ
authors.lastname: Yang
authors.forename: Myung-Joo
authors.initials: MJ
authors.lastname: Choi
authors.forename: He
authors.initials: H
authors.lastname: Wen
authors.forename: Hyuk Nam
authors.initials: HN
authors.lastname: Kwon
authors.forename: Kyung Hee
authors.initials: KH
authors.lastname: Jung
authors.forename: Sang-Won
authors.initials: SW
authors.lastname: Hong
authors.forename: Joon Mee
authors.initials: JM
authors.lastname: Kim
authors.forename: Soon-Sun
authors.initials: SS
authors.lastname: Hong
authors.forename: Sunghyouk
authors.initials: S
authors.lastname: Park
mesh_terms: D000818:Animals; D054316:Biomarkers, Pharmacological / Q000097:blood / Q000378:metabolism / Q000652:urine; D001774:Blood Chemical Analysis / Q000379:methods; D004353:Drug Evaluation, Preclinical / Q000295:instrumentation / Q000379:methods*; D064420:Drug-Related Side Effects and Adverse Reactions / Q000175:diagnosis*; D005260:Female; D000960:Hypolipidemic Agents / Q000009:adverse effects / Q000494:pharmacology; D008099:Liver / Q000187:drug effects / Q000378:metabolism / Q000473:pathology; D055442:Metabolome / Q000187:drug effects; D055432:Metabolomics / Q000295:instrumentation / Q000379:methods*; D019906:Nuclear Magnetic Resonance, Biomolecular / Q000295:instrumentation / Q000379:methods*; D051381:Rats; D017208:Rats, Wistar; D019821:Simvastatin / Q000009:adverse effects* / Q000494:pharmacology; D016896:Treatment Outcome; D016482:Urinalysis / Q000379:methods
chemical_list: D054316:Biomarkers, Pharmacological; D000960:Hypolipidemic Agents; D019821:Simvastatin