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Gut microbiota are related to Parkinson’s disease and clinical phenotype Original paper

Researched by:

  • Dr. Umar ID
    Dr. Umar

    User avatarClinical Pharmacist and Clinical Pharmacy Master’s candidate focused on antibiotic stewardship, AI-driven pharmacy practice, and research that strengthens safe and effective medication use. Experience spans digital health research with Bloomsbury Health (London), pharmacovigilance in patient support programs, and behavioral approaches to mental health care. Published work includes studies on antibiotic use and awareness, AI applications in medicine, postpartum depression management, and patient safety reporting. Developer of an AI-based clinical decision support system designed to enhance antimicrobial stewardship and optimize therapeutic outcomes.

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November 17, 2025

Researched by:

  • Dr. Umar ID
    Dr. Umar

    User avatarClinical Pharmacist and Clinical Pharmacy Master’s candidate focused on antibiotic stewardship, AI-driven pharmacy practice, and research that strengthens safe and effective medication use. Experience spans digital health research with Bloomsbury Health (London), pharmacovigilance in patient support programs, and behavioral approaches to mental health care. Published work includes studies on antibiotic use and awareness, AI applications in medicine, postpartum depression management, and patient safety reporting. Developer of an AI-based clinical decision support system designed to enhance antimicrobial stewardship and optimize therapeutic outcomes.

    Read More

Last Updated: 2015-01-01

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

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.

Location
Finland
Sample Site
Feces
Species
Homo sapiens

What was studied?

This original research article investigated how gut microbiota Parkinson’s disease associations manifest in fecal microbial composition and whether specific bacterial families correlate with clinical motor phenotypes. Using 16S rRNA pyrosequencing of fecal samples from 72 Parkinson’s disease (PD) patients and 72 matched controls, the study examined overall microbial community structure, family-level bacterial abundances, and their relationships to motor symptoms, constipation severity, enteric dysfunction, and non-motor symptom burden. Analyses integrated beta-diversity metrics, generalized linear models, and receiver-operating characteristic assessments to determine which bacterial shifts truly reflected PD rather than comorbidities, medications, or confounding gastrointestinal disorders. This work represents the first comprehensive, whole-microbiome comparison between PD patients and healthy adults, highlighting the importance of microbial community signatures—particularly the depletion of Prevotellaceae and elevation of Enterobacteriaceae—in understanding PD pathophysiology and phenotype expression.

Who was studied?

The study enrolled 72 clinically diagnosed PD patients meeting Queen Square Brain Bank criteria and 72 age- and sex-matched neurologically healthy controls. All participants were recruited within the Helsinki University Hospital system. PD patients had a median disease duration of five years, and all but two were receiving dopaminergic therapy. Exclusion criteria removed individuals with disorders, medications, or gastrointestinal conditions known to influence microbiome composition. Motor severity, phenotype (tremor-dominant vs. postural instability and gait difficulty), non-motor symptoms, constipation, and comorbidities were systematically assessed. Controls lacked Parkinsonism or premotor symptoms and were screened for irritable bowel syndrome to avoid confounding microbial signatures.

Most important findings

The study demonstrated a 77.6% reduction in Prevotellaceae abundance in PD patients, a shift that remained independently associated with PD after correction for constipation, medications, and vascular comorbidities. This depletion was highly sensitive (86.1%) but poorly specific for PD. Logistic models combining Prevotellaceae, Lactobacillaceae, Bradyrhizobiaceae, Clostridiales Incertae Sedis IV, and constipation severity improved diagnostic specificity to 90.3% (page 5 ROC curves). Enterobacteriaceae abundance—visible in phenotype-stratified analyses on page 5—correlated positively with PIGD motor symptoms and akinetic-rigid scores, suggesting a microbiome link to more severe or rapidly progressing motor phenotypes. The study found no significant differences in microbial alpha-diversity but identified shifts in community clustering, demonstrating altered gut ecological structure in PD.

Key implications

These findings underscore a robust link between microbial community alterations and PD, suggesting that the depletion of Prevotellaceae may reflect impaired mucin production, increased gut permeability, and reduced microbial synthesis of thiamine, folate, and neuroactive short-chain fatty acids—all factors relevant to PD pathophysiology. Elevated Enterobacteriaceae in PIGD patients highlights potential microbial contributions to neuroinflammation or endotoxin-related pathways influencing motor severity. While not yet diagnostic, these microbial signatures could support future biomarker development and illuminate gut–brain mechanisms relevant to PD onset, progression, and therapeutic targeting.

Citation

Scheperjans F, Aho V, Pereira PAB, et al. Gut microbiota are related to Parkinson’s disease and clinical phenotype.Movement Disorders. 2014;00:1-9. doi:10.1002/mds.26069

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