Characterizing dysbiosis of gut microbiome in PD: evidence for overabundance of opportunistic pathogens Original paper
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Dr. Umar
Read MoreClinical 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.
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?
PD gut microbiome opportunistic pathogens were investigated in a large microbiome-wide association study designed to robustly identify gut microbial signatures linked to Parkinson’s disease (PD). The authors reanalyzed a previously published 16S rRNA V4 dataset and added a new, larger cohort, applying harmonized protocols for stool collection, DNA extraction, sequencing, and bioinformatics. They tested whether global β-diversity differed between PD and controls and then performed hypothesis-free genus-level MWAS using two complementary methods (ANCOM and Kruskal–Wallis) with stringent multiple-testing correction. Correlation-network analysis was then used to determine whether PD-associated genera formed ecological clusters. The study specifically asked whether PD is characterized by consistent microbial patterns across heterogeneous US populations and whether alterations involve opportunistic pathogens, short-chain fatty-acid (SCFA)–producing taxa, or probiotic genera that might be relevant as mechanistic or therapeutic targets.
Who was studied?
Two independent US cohorts from movement-disorder clinics were included, totaling 535 PD patients and 320 controls. Dataset 1 comprised 212 PD cases and 136 controls from Seattle (WA), Albany (NY), and Atlanta (GA); dataset 2 comprised 323 PD cases and 184 controls from Birmingham (AL). All PD diagnoses used UK Brain Bank criteria, while controls self-reported no neurological disease. Extensive metadata captured constipation, gastrointestinal symptoms, diet, BMI, medications, and sample transport time; these variables were interrogated as potential confounders and included in multivariable models when associated with microbiome composition. PD medications, especially levodopa and adjuncts, were analyzed separately because of collinearity with PD status, with dose–response analyses examining whether differential taxa reflected disease or treatment effects.
Most important findings
PD status explained a small but significant proportion of gut β-diversity, independent of age, sex, BMI, constipation, gastrointestinal discomfort, diet, geography, and sample travel time. Fifteen genera were reproducibly associated with PD in both datasets and by both statistical methods. A positively correlated “cluster 1” of opportunistic pathogens—Porphyromonas, Prevotella (a specific SILVA-defined genus), and Corynebacterium_1—was consistently enriched in PD, with species-level BLAST assignments dominated by organisms typically reported in polymicrobial wound and mucosal infections. “cluster 2” of ten SCFA-producing genera from the Lachnospiraceae and Ruminococcaceae families (including Faecalibacterium, Roseburia, Agathobacter, Blautia, Butyricicoccus, Fusicatenibacter, Lachnospira, and uncultured Lachnospiraceae groups) was significantly depleted in PD, suggesting reduced butyrate production and impaired barrier and anti-inflammatory functions. A “cluster 3” comprising carbohydrate-metabolizing probiotic genera Bifidobacterium and Lactobacillus was increased in PD; importantly, their abundance, as well as the depletion of cluster-2 SCFA producers, correlated with higher levodopa dose, whereas the opportunistic-pathogen cluster did not, implying that probiotic expansion and SCFA loss may be amplified by dopaminergic therapy.
Key implications
For clinicians, this work supports a PD gut microbiome signature characterized by overabundance of polymicrobial opportunistic pathogens, loss of SCFA-producing commensals, and expansion of probiotic carbohydrate metabolizers. The pathogen-rich cluster provides concrete genera and species for mechanistic testing of Braak’s “gut-origin” hypothesis, including potential roles in triggering mucosal α-synuclein and neuroinflammation. Concurrent depletion of SCFA producers is consistent with impaired gut barrier integrity, constipation, and systemic inflammation, though it is likely not specific to PD. The levodopa-linked rise in Bifidobacterium and Lactobacillus suggests that common probiotic strains may interact with PD pharmacotherapy—possibly altering levodopa bioavailability and immune tone—highlighting a need for caution when recommending over-the-counter probiotics and for trials that stratify by microbial baseline and drug exposure. Collectively, these microbiome clusters offer candidate genera for inclusion in PD-focused microbiome signature databases and for future longitudinal and interventional studies.
Citation
Wallen ZD, Appah M, Dean MN, et al. Characterizing dysbiosis of gut microbiome in PD: evidence for overabundance of opportunistic pathogens. npj Parkinsons Dis. 2020;6:11. doi:10.1038/s41531-020-0112-6
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.
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.
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.
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.
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.
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.