Exercise-Responsive Non-coding RNAs in Neurodegeneration and Aging: Molecular Mechanisms, Systemic Adaptations, and Biomarker Potential
Year: 2026
Type: article
Abstract: Neurodegenerative diseases (NDDs), including Alzheimer’s disease (AD), Parkinson’s disease (PD), and multiple sclerosis (MS), are characterized by progressive neuronal degeneration, cognitive decline, and limited therapeutic options. Timely diagnosis and effective monitoring of these conditions remain major clinical challenges. Recently, non-coding RNAs (ncRNAs), such as microRNAs, long non-coding RNAs, and circRNAs, have emerged as promising molecular biomarkers due to their regulatory roles in gene expression and remarkable stability in circulating biological fluids. Accumulating evidence indicates that physical exercise can modulate ncRNA expression associated with neuroplasticity, inflammation, oxidative stress, mitochondrial function, and neuronal survival. Exercise-responsive ncRNAs are detectable in blood, cerebrospinal fluid, and extracellular vesicles, underscoring their potential as non-invasive biomarkers for disease diagnosis, prognosis, and therapeutic monitoring. In this review, we adopt a novel framework by combining preclinical and clinical evidence, implementing a reproducible literature search strategy, and applying a comparative analysis across multiple NDDs and aging contexts. This approach enables both a mechanistic and translational perspective, highlighting not just descriptive findings but also disease-specific and exercise-specific ncRNA signatures. Furthermore, emerging methodologies such as liquid biopsy and multi-omics integration are discussed to enhance the translational potential of ncRNA biomarkers. Overall, this review advances the field by providing a critical synthesis that identifies gaps, proposes mechanistic frameworks, and outlines future directions for using exercise-modulated ncRNAs in early detection, monitoring, and personalized interventions in NDDs.
Authors: TianLai Zhao, Bihua Chen
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $4,590
OpenAlex ID: W7225453033