Human Skeletal Muscle Drug Transporters Determine Local Exposure and Toxicity of Statins
Bibliographic record
Abstract
RATIONALE: The 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors, or statins, are important drugs used in the treatment and prevention of cardiovascular disease. Although statins are well tolerated, many patients develop myopathy manifesting as muscle aches and pain. Rhabdomyolysis is a rare but severe toxicity of statins. Interindividual differences in the activities of hepatic membrane drug transporters and metabolic enzymes are known to influence statin plasma pharmacokinetics and risk for myopathy. Interestingly, little is known regarding the molecular determinants of statin distribution into skeletal muscle and its relevance to toxicity. OBJECTIVE: We sought to identify statin transporters in human skeletal muscle and determine their impact on statin toxicity in vitro. METHODS AND RESULTS: We demonstrate that the uptake transporter OATP2B1 (human organic anion transporting polypeptide 2B1) and the efflux transporters, multidrug resistance-associated protein (MRP)1, MRP4, and MRP5 are expressed on the sarcolemmal membrane of human skeletal muscle fibers and that atorvastatin and rosuvastatin are substrates of these transporters when assessed using a heterologous expression system. In an in vitro model of differentiated, primary human skeletal muscle myoblast cells, we demonstrate basal membrane expression and drug efflux activity of MRP1, which contributes to reducing intracellular statin accumulation. Furthermore, we show that expression of human OATP2B1 in human skeletal muscle myoblast cells by adenoviral vectors increases intracellular accumulation and toxicity of statins and such effects were abrogated when cells overexpressed MRP1. CONCLUSIONS: These results identify key membrane transporters as modulators of skeletal muscle statin exposure and toxicity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".