A prebiotic diet intervention can restore faecal short chain fatty acids in Parkinson's Disease yet fails to restore the gut microbiome homeostasis
Bibliographic record
Abstract
ABSTRACT Despite extensive research, current treatment of Parkinson's Disease (PD) remains symptomatic and disease modifying approaches are urgently required. A promising approach is to target the gut-brain-axis by modifying the intestinal microbiota and the herein produced metabolites. We decided to test this approach by modifying key metabolites of bacterial intestinal fermentation: short chain fatty acids (SCFA), known to be decreased in PD patients. A prospective, controlled pilot study was conducted in 11 couples, with one PD patient and healthy spouse as control (CO) each. Participants followed a 4-week diet rich in dietary fibre in addition to the intake of a prebiotic sirup (Lactulose). Metagenomes and metabolites of the gut microbiota, urinary metabolites and clinical characteristics were assessed. The short-term dietary intervention significantly augmented gastrointestinal SCFA production, likely associated with increased Bifidobacteria spp. PD associated gastrointestinal symptoms improved with increasing SCFA levels. The pre-existing bacterial dysbiosis associated with PD, such as depletion of genera Blautia, Dorea, and Erysipelatoclostridium in PD, persisted within the study period. Some pathobionts, i.e. Klebsiella, were reduced after the intervention. Bacterial metabolite composition (both faecal and urine metabolomes) shifted towards the composition of the healthy control in PD after the intervention. Among these brain-relevant gut metabolic functions improved in PD patients, such as S-Adenosyl methionine (SAM), 3,4-Dihydroxyphenylacetic acid (DOPAC), Glutathione (GSH), Tryptophan and inositol related changes, involved in neuroprotective and antioxidant pathways. Despite the small cohort size and short-term study period a minor dietary intervention was sufficient to improve gastrointestinal symptoms in PD and altered metabolic parameters in a presumed neuroprotective manner, warranting further investigation in larger cohorts.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".