Metagenomic Analysis Reveals Large‐Scale Disruptions of the Gut Microbiome in Parkinson's Disease
Bibliographic record
Abstract
BACKGROUND: Parkinson's disease (PD) has been consistently linked to alterations within the gut microbiome. OBJECTIVE: Our goal was to identify microbial features associated with PD incidence and progression. METHODS: Metagenomic sequencing was used to characterize taxonomic and functional changes to the PD microbiome and to explore their relation to bacterial metabolites and disease progression. Motor and non-motor symptoms were tracked using Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and levodopa equivalent dose across ≤5 yearly study visits. Stool samples were collected at baseline for metagenomic sequencing (176 PD, 100 controls). RESULTS: PD-derived stool samples had reduced intermicrobial connectivity and seven differentially abundant species compared to controls. A suite of bacterial functions differed between PD and controls, including depletion of carbohydrate degradation pathways and enrichment of ribosomal genes. Faecalibacterium prausnitzii-specific reads contributed significantly to more than half of all differentially abundant functional terms. A subset of disease-associated functional terms correlated with faster progression of MDS-UPDRS part IV and separated those with slow and fast progression with moderate accuracy within a random forest model (area under curve = 0.70). Most PD-associated microbial trends were stronger in those with symmetric motor symptoms. CONCLUSION: We provide further evidence that the PD microbiome is characterized by reduced intermicrobial communication and a shift to proteolytic metabolism in lieu of short-chain fatty acid production, and suggest that these microbial alterations may be relevant to disease progression. We also describe how our results support the existence of gut-first versus brain-first PD subtypes. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".