Evidence map›Paper›PMID 40335465›Full record

SynthesisNature communications2025

Machine learning-based meta-analysis reveals gut microbiome alterations associated with Parkinson's disease.

Stefano Romano, Jakob Wirbel, Rebecca Ansorge, Christian Schudoma, Quinten Raymond Ducarmon, Arjan Narbad, Georg Zeller

Abstract readMeta-Analysis
In one paragraph

Synthesis in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

36 citing papers in PubMed.

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  7. Lifestyle medicine for neuroprotection: evidence and implementation in Asian contexts.Journal of neural transmission (Vienna, Austria : 1996) · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Stefano RomanoQuadram Institute Bioscience, Norwich Research Park, Norwich, UK. stfno.rmno@gmail.com.ORCID http://orcid.org/0000-0002-7600-1953
Jakob WirbelStructural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.ORCID http://orcid.org/0000-0002-4073-3562
Rebecca AnsorgeQuadram Institute Bioscience, Norwich Research Park, Norwich, UK.ORCID http://orcid.org/0000-0002-4770-481X
Christian SchudomaStructural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.ORCID http://orcid.org/0000-0003-1157-1354
Quinten Raymond DucarmonStructural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
Arjan NarbadQuadram Institute Bioscience, Norwich Research Park, Norwich, UK.ORCID http://orcid.org/0000-0003-2968-7558
Georg ZellerStructural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany. georg.zeller@gmail.com.ORCID http://orcid.org/0000-0002-4424-0079

Funding

Deutsche Forschungsgemeinschaft (German Research Foundation) 395357507 - SFB 1371European Molecular Biology Organization (EMBO) EMBO ALTF 1030-2022European Molecular Biology Organization (EMBO) SEG 9093RCUK | Biotechnology and Biological Sciences Research Council (BBSRC) BB/R012490/1RCUK | Biotechnology and Biological Sciences Research Council (BBSRC) BBS/E/F/000PR10356
6 · The paper itself

Abstract

There is strong interest in using the gut microbiome for Parkinson's disease (PD) diagnosis and treatment. However, a consensus on PD-associated microbiome features and a multi-study assessment of their diagnostic value is lacking. Here, we present a machine learning meta-analysis of PD microbiome studies of unprecedented scale (4489 samples). Within most studies, microbiome-based machine learning models accurately classify PD patients (average AUC 71.9%). However, these models are study-specific and do not generalise well across other studies (average AUC 61%). Training models on multiple datasets improves their generalizability (average LOSO AUC 68%) and disease specificity as assessed against microbiomes from other neurodegenerative diseases. Moreover, meta-analysis of shotgun metagenomes delineates PD-associated microbial pathways potentially contributing to gut health deterioration and favouring the translocation of pathogenic molecules along the gut-brain axis. Strikingly, microbial pathways for solvent and pesticide biotransformation are enriched in PD. These results align with epidemiological evidence that exposure to these molecules increases PD risk and raise the question of whether gut microbes modulate their toxicity. Here, we offer the most comprehensive overview to date about the PD gut microbiome and provide future reference for its diagnostic and functional potential.

Indexed as

Gastrointestinal MicrobiomeMachine LearningParkinson DiseaseHumansMetagenome

Identifiers

PMID40335465
PMCPMC12059030

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.