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SCIENTIFIC LITERATURE · MED

Gut-brain axis modulation in remote rehabilitation of Parkinson's disease: reconstructing the fecal metabolome and nigral network connectivity.

Front Neurol · 2025-08-15

DOI: 10.3389/fneur.2025.1644490PMID: 40895097

Open accessreview-article; Review; Journal ArticleOriginal source ↗

Research overview

The text below is the source article’s original abstract under a verified reuse license. cc by

The pathogenesis of Parkinson's disease (PD) is gradually evolving from a central neurodegeneration-centered concept to a multi-pathway pathological model at the gut-brain system level. Studies have shown that PD patients commonly exhibit dysbiosis, reduced short-chain fatty acids (SCFAs; microbial fermentation products of dietary fiber that play key roles in host metabolism and immune regulation), abnormal tryptophan metabolism, and impaired gut barrier function. These alterations may contribute to dopaminergic neuronal damage through mechanisms including neuroinflammation, oxidative stress, and α-synuclein (α-syn) aggregation. The vagus nerve plays a critical role in bidirectional gut-brain signaling, and its dysfunction may represent a key route for pathological protein transmission from the periphery to the brain. In response, remote rehabilitation and gut-targeted interventions-including probiotics, prebiotics, dietary modulation, fecal microbiota transplantation (FMT), and transcutaneous vagus nerve stimulation (tVNS)-have shown potential in improving neurological function and inflammation in both animal and clinical studies. Multimodal data analyses have revealed significant associations between SCFA levels in fecal metabolomics and brain imaging features. Despite ongoing challenges in mechanistic extrapolation, biomarker sensitivity, and translational implementation, the integration of metagenomics, metabolomics, neuroimaging, and digital therapeutics-collectively referred to as multi-omics and digital profiling techniques-represents an emerging research direction with the potential to inform future clinical paradigms for precision remote management of PD.

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