Intestinal biomarkers, microbiota composition, and genetic predisposition to inflammatory bowel disease as predictors of Parkinson's disease manifestation

BackgroundParkinson's disease (PD) is often accompanied by gastrointestinal symptoms. While elevated inflammatory biomarkers have been reported in PD patients compared to controls, the role of intestinal dysmotility and inflammation in disease manifestation is not fully understood.ObjectiveThis study sought to determine if fecal biomarkers and genetic predisposition to intestinal inflammation could help identify PD subtypes for future targeted therapies.MethodsThe association of disease activity, assessed through United Parkinson's disease Rating Scale (UPDRS) and Non-Motor Symptoms Questionnaire (NMSQ), with constipation severity, fecal calprotectin and six short-chain fatty acid (SCFA) levels, polygenic risk scores (PRS) for inflammatory bowel disease (IBD) and PD, and microbiota diversity were investigated in 95 participants with established PD using regression analyses. Unsupervised k-means clustering was applied to stratify PD patients based on inflammatory biomarkers.ResultsHaving constipation was linked to worse mentation (UPDRSI, adj.<i>p</i> = 0.03) and more limited daily living activities (UPDRSII, adj.<i>p</i> = 0.03), with symptom severity linearly associated with higher disease activity (UPDRSI, adj.<i>p</i> = 0.002; NMSQ-total, adj.<i>p</i> = 0.02). Fecal calprotectin was elevated in those with constipation (<i>p</i> = 0.02) and associated with longer disease duration irrespective of the age (adj.<i>p</i> = 0.02). Cluster analysis demonstrated that PD patients with a higher non-motor symptom UPDRSII score were more likely to have more severe constipation, lower fecal SCFA levels, lower bacterial diversity, and higher PRS-CD and PRS-IBD.ConclusionsGut dysmotility, along with pro-inflammatory intestinal profiles, and greater genetic predisposition to IBD were observed in PD patients with worse non-motor symptoms. Monitoring intestinal biomarkers may help identify PD patients for targeted interventions.