Metagenomic Analysis Reveals Large-Scale Disruptions of the Gut Microbiome in Parkinson’s Disease Original paper
Microbiome Signatures identifies and validates condition-specific microbiome shifts and interventions to accelerate clinical translation. Our multidisciplinary team supports clinicians, researchers, and innovators in turning microbiome science into actionable medicine.
Karen Pendergrass is a microbiome researcher specializing in microbiome-targeted interventions (MBTIs). She systematically analyzes scientific literature to identify microbial patterns, develop hypotheses, and validate interventions. As the founder of the Microbiome Signatures Database, she bridges microbiome research with clinical practice. In 2012, based on her own investigative research, she became the first documented case of FMT for Celiac Disease—four years before the first published case study.
What was studied?
This study performed a comprehensive metagenomic analysis to investigate large-scale disruptions in the gut microbiome of individuals with Parkinson’s disease (PD). The research aimed to identify specific microbial features—both taxonomic (species-level) and functional (metabolic pathways)—associated with PD incidence and progression. Researchers utilized shotgun metagenomic sequencing of baseline stool samples to characterize microbial community structure, connectivity, and functions, and explored associations with disease severity, progression, and microbially derived metabolites. Crucially, the study sought to elucidate how alterations in the gut microbiome might be linked not only to PD status but also to the rate at which motor complications develop, providing longitudinal insights into the microbiome’s potential role in PD pathogenesis and subtype differentiation.
Who was studied?
The cohort consisted of 276 individuals recruited in Canada: 176 patients diagnosed with Parkinson’s disease and 100 healthy controls, all aged between 40 and 85. PD participants were within 12 years of motor symptom onset (mean duration six years). Stringent exclusion criteria were applied to minimize confounding factors, including recent antibiotic or probiotic use, gastrointestinal infections, GI cancer, inflammatory bowel disease, and the use of the PD medication entacapone due to its strong effects on the microbiome. The control group was matched for age and sex distribution. Clinical assessments included the MDS-UPDRS (Movement Disorder Society Unified Parkinson’s Disease Rating Scale), levodopa equivalent dose, depression (Beck Depression Inventory II), and fatigue (Fatigue Severity Scale). Up to five years of longitudinal follow-up data were available for 121 PD participants, allowing for the analysis of disease progression in relation to microbiome features.
Most important findings
The study revealed that the gut microbiome in PD is less interconnected than in controls, evidenced by a reduction in taxon–taxon connections and lower betweenness centrality—particularly among Firmicutes. Seven bacterial species were differentially abundant: Alistipes indistinctus, Blautia obeum, Collinsella aerofaciens, Coprococcus catus, and Ruthenibacterium lactatiformans were enriched in PD, while Blautia wexlerae, Faecalibacterium prausnitzii, Roseburia hominis, Roseburia intestinalis, and Roseburia inulinivorans were depleted. Importantly, several short-chain fatty acid (SCFA) producers (e.g., F. prausnitzii, Roseburia spp.) were reduced, consistent with prior PD studies.
Functionally, PD microbiomes showed depleted carbohydrate degradation pathways—especially those involved in hexuronate/hexuronide metabolism—and an enrichment of ribosomal and proteolytic genes. Notably, Faecalibacterium prausnitzii contributed disproportionately to many of the depleted functional pathways, even when not differentially abundant itself. Disease-associated functional terms, particularly those related to protein catabolism and purine metabolism, correlated with faster progression of motor complications. The study also found that PD-associated microbial trends were significantly stronger in participants with symmetric motor symptoms, supporting the existence of “gut-first” PD subtypes.
Microbial metabolites such as p-cresol and phenylacetylglutamine were positively correlated with enriched species like Blautia obeum and with increased oxaloacetate-to-phosphoenolpyruvate metabolism, suggesting a shift toward proteolytic and gluconeogenic metabolism in the PD gut. Random forest models confirmed that metagenomic data outperformed clinical covariates in predicting PD status and progression rates, highlighting the diagnostic and prognostic potential of microbiome signatures.
Key implications
This study reinforces the strong association between PD and a disrupted, functionally altered gut microbiome, characterized by fragmentation of microbial networks, loss of SCFA producers, and a shift toward proteolytic metabolism. The identification of specific microbial taxa and pathways linked to disease progression, especially among patients with symmetric motor symptoms (“gut-first” PD), suggests that the microbiome could not only serve as a biomarker for PD risk and subtype but may also play an active role in disease pathogenesis. These findings support targeting the gut microbiome in future therapeutic interventions and highlight the importance of stratifying PD patients by motor phenotype or putative disease origin in clinical trials and research. For clinicians, these microbial signatures and their functional consequences may enhance patient risk stratification and open new avenues for disease-modifying strategies.
Citation
Metcalfe-Roach A, Cirstea MS, Yu AC, et al. Metagenomic Analysis Reveals Large-Scale Disruptions of the Gut Microbiome in Parkinson’s Disease. Mov Disord. 2024;39(10):1740-1751. doi:10.1002/mds.29959
Short-chain fatty acids are microbially derived metabolites that regulate epithelial integrity, immune signaling, and microbial ecology. Their production patterns and mechanistic roles provide essential functional markers within microbiome signatures and support the interpretation of MBTIs, MMAs, and systems-level microbial shifts across clinical conditions.