Gut-Brain Axis Dysfunction in Alzheimer's and Parkinson's Diseases: The Role of Dysbiosis, Inflammation, and Therapeutic Targets — A Literature Review
Bibliographic record
Abstract
Introduction: Alzheimer’s disease (AD) and Parkinson’s disease (PD) are the two most common neurodegenerative disorders, causing progressive cognitive and motor decline. High rates of new diagnoses, coupled with increasing evidence linking gastrointestinal (GI) dysfunction to neurodegeneration, highlight the significance of understanding the gut-brain axis (GBA). Changes in gut microbiota composition are associated with amyloid-beta accumulation in AD and α-synuclein aggregation in PD, suggesting that gut dysbiosis and inflammation may worsen disease pathology. Methods: A systematic literature review was conducted using peer-reviewed primary research articles published between 2014 and 2025. Articles were selected based on their relevance to GI inflammation, gut microbiota dysbiosis, and neurodegenerative diseases. Studies involving human participants and relevant animal models were prioritized. Databases searched included PubMed, Google Scholar, ScienceDirect, JSTOR, and SpringerLink. Results: Gut dysbiosis was consistently associated with increased intestinal permeability, systemic inflammation, and neuroinflammatory responses in AD and PD. Specific microbial imbalances correlated with accelerated disease progression and cognitive decline. Animal studies demonstrated that fecal microbiota transplantation from diseased individuals worsened motor and mental symptoms, while interventions targeting gut health, such as probiotics and dietary modifications, reduced neuroinflammation and improved outcomes. Discussion: Findings support the GBA’s critical role in mediating neurodegeneration through immune activation and inflammatory pathways. Dysbiosis-induced changes in microbial metabolite production, including short-chain fatty acids (SCFAs) and tryptophan derivatives, further contribute to neuroinflammatory processes. Despite promising preclinical results, challenges remain in translating gut-targeted therapies to clinical use due to variability in individual microbiomes and limited longitudinal human data. Conclusion: This review emphasizes the gut microbiota as a modifiable factor in the pathogenesis of AD and PD. Targeting GI inflammation and restoring microbial balance may offer novel therapeutic strategies for slowing disease progression. Future research should focus on validating gut-derived biomarkers, personalizing microbiome-based treatments, and conducting longitudinal clinical trials to optimize gut-brain interventions in neurodegenerative diseases.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".