Metabolic Myopathies Discovered During Investigations of Statin Myopathy
Bibliographic record
Abstract
The statins have emerged as the dominant class of drug for the treatment of hypercholesterolemia. These medications are generally well tolerated. However, myalgias, the most frequent side-effect, occur in up to 7% of patients. Transaminitis and skeletal myotoxicity, with elevated serum creatine kinase (CK) levels (i.e., >10 times the upper limit of normal), occur with reported frequencies of 1% and 0.1%, respectively. Various hypotheses have been proposed to explain the relationship between statin therapy and the spectrum of muscle dysfunction manifested by myalgia, myopathy, and rhabdomyolysis. Statin-mediatd inhibition of mevalonate metabolism impairs the synthesis of isoprenylated products–the most notable of which is ubiquinone. However, isoprenylation is responsible for the post-translational modification of up to 2% of cellular proteins. Therefore, numerous metabolic pathways are potentially modified by statin-mediated hypoprenylation. Subclinical defects in one or more energy-deriving pathways may be unmasked upon exposure to the pleotropic effects of statins. Such pharmacogenomic synergism may underlie the development of “statin myopathy” in a subset of patients. In this regard, we describe four patients with mutations in the myophosphorylase (PYGM; MIM 232600), myoadenylate deaminase (AMPD1; MIM 102770), and carnitine palmitoyltransferase (CPT2; MIM 600650) genes whose diagnoses became apparent during the course of investigations for statin-induced myalgias and hyperCKemia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".