The role of the gut microbiome in Parkinson’s disease
Bibliographic record
Abstract
Parkinson’s disease (PD) is a common neurodegenerative disorder that is best characterized by motor impairment. Gut-related symptoms are prevalent in PD, including dysbiosis of the microbiome, which is relatively consistent across cohorts. Anti-inflammatory short-chain fatty acid (SCFA) producers are less abundant, while PD-associated taxa perform a variety of pro-inflammatory functions including LPS production and protein fermentation. Microbial metabolism of sulfur, bile acids (BAs), and neurotransmitters – particularly glutamate – may also disrupt homeostatic balance, spurring PD pathology. Together, microbial mechanisms likely promote a subset of PD cases by disrupting the gut barrier, activating the immune system, and increasing the systemic spread of microbial metabolites which trigger inflammation. Certain PD symptoms are associated with gut-first PD, and may be useful for building PD cohorts where the microbiome is more likely to be a relevant factor. The oral PD microbiome, though relatively understudied, may also promote PD through inflammatory mechanisms. Gut microbial interventions have provided some causal evidence for microbial involvement in PD, but existing studies are few and difficult to compare. Future PD microbiome studies will benefit from a personalized medicine approach, taking symptom presentation, medications, and multi-omics data into account and using standardized methodologies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".