Evidence map›Paper›PMID 41894089›Full record

ReviewMolecular and cellular biochemistry2026

Modulation of miRNA networks by exercise in muscular dystrophies: therapeutic insights and future directions.

Ziyu Wang, Feida Zhao

Abstract readReview
PubMed Publisher
In one paragraph

Review in Molecular and cellular biochemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ziyu WangSchool of Physical Education, Shaoxing University, Shaoxing, 312000, China.
Feida ZhaoCollege of Physical Education, Huzhou University, Huzhou, 313000, China. zhaofeida8909@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Muscular dystrophies (MDs) encompass a diverse group of hereditary disorders characterized by progressive skeletal muscle degeneration and weakness. While current therapeutic strategies primarily focus on symptom management, physical exercise is increasingly recognized as a potent intervention to attenuate disease progression and preserve muscle function. Recent evidence highlights the critical role of microRNAs (miRNAs)—small non-coding RNAs—in post-transcriptional gene regulation, particularly within muscle biology. Exercise dynamically modulates the expression of specific myomiRs (e.g., miR-1, miR-133, miR-206) and inflammation-associated miRNAs (miR-29, miR-146a), which collectively govern processes such as fibrosis, oxidative stress, and regeneration. This review synthesizes current knowledge on the exercise-mediated regulation of miRNA networks in MDs. We delineate the molecular mechanisms linking physical activity to miRNA biogenesis and examine the downstream therapeutic effects on dystrophic pathology. Furthermore, we critically assess the gap between preclinical success in animal models and the scarcity of human clinical data, proposing a roadmap for developing precision exercise interventions that target miRNA networks to enhance therapeutic outcomes. Precision in this context entails miRNA-guided exercise dosing (e.g., adjusting intensity based on real-time miRNA expression profiles), biomarker-driven personalization (e.g., using circulating miRNAs to tailor regimens for individual patients), and integration with gene or exon-skipping therapies to synergistically address subtype-specific pathologies in MDs such as DMD, BMD, and LGMD.

Indexed as

ExerciseGene Expression RegulationGene Regulatory NetworksMicroRNAsMuscular DystrophiesAnimalsHumansMuscle, SkeletalMicroRNAsAntioxidant defenseExerciseFrailtyMuscle agingOxidative stress

Identifiers

What Socratic holds

Textmetadata
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.