A systems biology strategy reveals biological pathways and plasma biomarker candidates for potentially toxic statin-induced changes in muscle

Abstract

Background: Aggressive lipid lowering with high doses of statins increases the risk of statin-induced myopathy. However, the cellular mechanisms leading to muscle damage are not known and sensitive biomarkers are needed to identify patients at risk of developing statin-induced serious side effects.

Methodology: We performed bioinformatics analysis of whole genome expression profiling of muscle specimens and UPLC/MS based lipidomics analyses of plasma samples obtained in an earlier randomized trial from patients either on high dose simvastatin (80 mg), atorvastatin (40 mg), or placebo.

Principal findings: High dose simvastatin treatment resulted in 111 differentially expressed genes (1.5-fold change and p-value<0.05), while expression of only one and five genes was altered in the placebo and atorvastatin groups, respectively. The Gene Set Enrichment Analysis identified several affected pathways (23 gene lists with False Discovery Rate q-value<0.1) in muscle following high dose simvastatin, including eicosanoid synthesis and Phospholipase C pathways. Using lipidomic analysis we identified previously uncharacterized drug-specific changes in the plasma lipid profile despite similar statin-induced changes in plasma LDL-cholesterol. We also found that the plasma lipidomic changes following simvastatin treatment correlate with the muscle expression of the arachidonate 5-lipoxygenase-activating protein.

Conclusions: High dose simvastatin affects multiple metabolic and signaling pathways in skeletal muscle, including the pro-inflammatory pathways. Thus, our results demonstrate that clinically used high statin dosages may lead to unexpected metabolic effects in non-hepatic tissues. The lipidomic profiles may serve as highly sensitive biomarkers of statin-induced metabolic alterations in muscle and may thus allow us to identify patients who should be treated with a lower dose to prevent a possible toxicity.

Figure 1. Partial least squares discriminant analysis (PLS/DA) of serum lipidomics data.

Results after 8 week treatment from placebo (N = 11), atorvastatin (N = 14), and simvastatin (N = 12) groups, with 132 identified lipid species included in analysis as variables. For each molecular species and each subject, its level after the 8 week treatment period was scaled by subtracting its median level across all subjects prior to treatment and divided by corresponding standard deviation. Four latent variables were used in the model (Q ² = 0.46). The labels are patient ID numbers. The lines outlining different groups are shown as a guide. (A) The scores for Latent Variables (LV) 1 and 3 reveal serum lipid changes specific to the statin treatment (LV1) as well as statin-specific changes (LV3). (B) Loadings on LV3 for most important lipids in simvastatin or atorvastatin groups selected by VIP analysis. Only lipids for which at least one of the two groups has VIP value greater than 2 are shown.

Figure 2. PLS/DA analysis on combined muscle gene expression and serum lipid data.

Results after intervention for the subjects from placebo (N = 5), atorvastatin (N = 6), and simvastatin (N = 6) groups. Total 38 genes from four enriched pathways and 132 lipids were included in the analysis as variables. Data was autoscaled prior to multivariate analysis. Three latent variables were used in the model (Q ² = 0.50). The labels are patient ID numbers. (A) The PLS/DA score plot reveals treatment-specific differences between the treatments are observed in molecular profiles after intervention. (B) Loadings for the first two latent variables reveal plasma lipid classes and muscle pathways associated with specific interventions. LPC is shorthand for lysophosphatidylcholine (for example GPCho(18∶0/0∶0)).

Figure 3. Regression of plasma lipid data on arachidonate 5-lipoxygenase activating protein (ALOX5AP) muscle gene expression profile using the lasso method.

25 lipid variables were chosen to build the regression model. (A) ALOX5AP expression values as predicted by the model. (B) Regression coefficients for the lipid species selected by lasso.