Genetic risk factors associated with lipid‐lowering drug‐induced myopathies
Bibliographic record
Abstract
Lipid-lowering drugs produce myopathic side effects in up to 7% of treated patients, with severe rhabdomyolysis occurring in as many as 0.5%. Underlying metabolic muscle diseases have not been evaluated extensively. In a cross-sectional study of 136 patients with drug-induced myopathies, we report a higher prevalence of underlying metabolic muscle diseases than expected in the general population. Control groups included 116 patients on therapy with no myopathic symptoms, 100 asymptomatic individuals from the general population never exposed to statins, and 106 patients with non-statin-induced myopathies. Of 110 patients who underwent mutation testing, 10% were heterozygous or homozygous for mutations causing three metabolic myopathies, compared to 3% testing positive among asymptomatic patients on therapy (P = 0.04). The actual number of mutant alleles found in the test group patients was increased fourfold over the control group (P < 0.0001) due to an increased presence of mutation homozygotes. The number of carriers for carnitine palmitoyltransferase II deficiency and for McArdle disease was increased 13- and 20-fold, respectively, over expected general population frequencies. Homozygotes for myoadenylate deaminase deficiency were increased 3.25-fold with no increase in carrier status. In 52% of muscle biopsies from patients, significant biochemical abnormalities were found in mitochondrial or fatty acid metabolism, with 31% having multiple defects. Variable persistent symptoms occurred in 68% of patients despite cessation of therapy. The effect of statins on energy metabolism combined with a genetic susceptibility to triggering of muscle symptoms may account for myopathic outcomes in certain high-risk groups.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".