Abstract 4164: Decreased Skeletal Muscle Mitochondrial DNA in Patients on High-Dose Simvastatin Therapy
Bibliographic record
Abstract
Background: Statins are used widely to treat dyslipidemia. Statin-induced myopathy (SIM) is a well-recognized side effect that decreases quality of life and complicates patient management. A reliable and convenient method of diagnosing SIM is needed, as patient self-report and creatinine kinase levels are unreliable and light microscopy of skeletal muscle is inconvenient. Statins have been associated with mitochondrial toxicity, which may be related to mitochondrial DNA (mtDNA) levels; mtDNA levels could be a useful marker of SIM. We studied the effect of high-dose statin treatment on mtDNA levels in human skeletal muscle. Method: Skeletal muscle mtDNA to nuclear DNA (nDNA) ratios were measured retrospectively in 86 biopsies obtained from an earlier randomized, double-blind, placebo-controlled trial. Forty-three hypercholesterolemic subjects aged 31 to 69 years were randomly assigned into 3 treatment groups and received placebo (n=14), atorvastatin 40mg/d (n=15), or simvastatin 80mg/d (n=14) for 8 weeks. Biopsy specimens were acquired at baseline and 8 weeks. mtDNA was quantified by extracting total DNA from muscle homogenates then quantifying a nuclear gene (ASPG) and a mitochondrial gene (CCOI) with real-time PCR. Results are expressed as the mtDNA/nDNA ratio. Differences within groups were assessed by the paired t -test and differences between groups by ANOVA with repeated measurements. Results: mtDNA significantly decreased (47%; P =0.0020) in the simvastatin group. Non-significant decreases of 12% occurred in the atorvastatin ( P =0.24) and placebo ( P =0.20) groups. Average baseline ratios of the three groups did not differ significantly ( F =0.655). Conclusion: High-dose simvastatin therapy significantly decreased skeletal muscle mtDNA. mtDNA may be a useful marker of mitochondrial toxicity in statin users, but the clinical relevance of our findings needs to be further investigated.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.000 |
| 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".