Epigenetic alterations in rotator cuff tendinopathy and degenerative cuff tears: a systematic review
Bibliographic record
Abstract
Background: Rotator cuff (RC) tendinopathy and degenerative cuff tears are common, disabling conditions with a complex molecular etiology. Furthermore, RC pathology becomes increasingly common with age, especially in the case of supraspinatus tendon injury. Concurrent with increased RC pathology during aging are epigenetic alterations, which makes the relationship between RC pathology and epigenetic alterations an area of interest. The role of epigenetics in RC pathology is still being elucidated but has potential to provide diagnostic biomarkers and therapeutic targets. We aimed to systematically review the altered epigenetic signatures and mechanisms underlying RC pathology. Methods: Four electronic databases (PubMed, Embase.com, Cochrane, and Google Scholar) were searched 27 August, 2024, for primary studies reporting on epigenetic alterations (DNA methylation, histone modifications, noncoding RNAs) in RC tendinopathy and associated atraumatic cuff tear tissue. Risk of bias and methodological quality of all included studies were assessed according to the Newcastle-Ottawa Scale. Results: Of the 1,190 identified references, 39 studies were included, totaling 464 human and 641 animal model participant shoulders. We identified altered expression of 87 microRNAs, 24 of which were reported on in multiple studies, 62 long noncoding RNAs, 26 circular RNAs, 9 histone modifications or histone-modifying enzymes, and 11 genes exhibiting altered DNA methylation within the disease state. Epigenetic signatures were most commonly associated with inflammation, extracellular matrix degeneration, muscle atrophy, and fatty infiltration. We also report on 15 studies characterizing epigenetic therapeutics (5 microRNA, 1 long noncoding RNA, 3 histone-modifying enzymes, and 6 gene silencing RNA). Conclusion: Our findings indicate that epigenetic regulation may play an important role in the pathophysiology of RC tendinopathy and degenerative tear and that there is a high potential for epigenetic biomarkers and therapeutics to aid in the diagnosis, prognosis, and treatment of this condition.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.000 | 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) | 0.004 | 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".