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.2017 May;32(5):739-749.
doi: 10.1002/mds.26942. Epub 2017 Feb 14.

Parkinson's disease and Parkinson's disease medications have distinct signatures of the gut microbiome

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Parkinson's disease and Parkinson's disease medications have distinct signatures of the gut microbiome

Erin M Hill-Burns et al. Mov Disord.2017 May.

Abstract

Background: There is mounting evidence for a connection between the gut and Parkinson's disease (PD). Dysbiosis of gut microbiota could explain several features of PD.

Objective: The objective of this study was to determine if PD involves dysbiosis of gut microbiome, disentangle effects of confounders, and identify candidate taxa and functional pathways to guide research.

Methods: A total of 197 PD cases and 130 controls were studied. Microbial composition was determined by 16S rRNA gene sequencing of DNA extracted from stool. Metadata were collected on 39 potential confounders including medications, diet, gastrointestinal symptoms, and demographics. Statistical analyses were conducted while controlling for potential confounders and correcting for multiple testing. We tested differences in the overall microbial composition, taxa abundance, and functional pathways.

Results: Independent microbial signatures were detected for PD (P = 4E-5), participants' region of residence within the United States (P = 3E-3), age (P = 0.03), sex (P = 1E-3), and dietary fruits/vegetables (P = 0.01). Among patients, independent signals were detected for catechol-O-methyltransferase-inhibitors (P = 4E-4), anticholinergics (P = 5E-3), and possibly carbidopa/levodopa (P = 0.05). We found significantly altered abundances of the Bifidobacteriaceae, Christensenellaceae, [Tissierellaceae], Lachnospiraceae, Lactobacillaceae, Pasteurellaceae, and Verrucomicrobiaceae families. Functional predictions revealed changes in numerous pathways, including the metabolism of plant-derived compounds and xenobiotics degradation.

Conclusion: PD is accompanied by dysbiosis of gut microbiome. Results coalesce divergent findings of prior studies, reveal altered abundance of several taxa, nominate functional pathways, and demonstrate independent effects of PD medications on the microbiome. The findings provide new leads and testable hypotheses on the pathophysiology and treatment of PD. © 2017 International Parkinson and Movement Disorder Society.

Keywords: Parkinson's disease; confounding; functional pathways; gut microbiome; medications.

© 2017 International Parkinson and Movement Disorder Society.

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Figures

Figure 1
Figure 1. The relative abundances of PD-associated taxa
Boxplots show the abundance of A) 13 OTUs, B) 8 genera, and C) 7 families that differed significantly between controls (orange) and PD cases (blue). Taxa are identified by A) taxon ID and family and genus names, B) family and genus names, or C) family names. The relative abundance (proportion) is plotted as log10 scale on the y axis. The notch in each box indicates the confidence interval of the median. The bottom, middle, and top boundaries of each box represent the first, second (median), and third quartiles of the abundance. The whiskers (lines extending from the top and bottom of the box) extend to points within 1.5 times the interquartile range. The points extending above the whiskers are outliers. Note that the relative position of confidence intervals of the median is only a visual proxy for the difference between groups. Statistical testing was performed on the means.
Figure 2
Figure 2. Predicted functional differences between PD and control microbiomes
Twenty-six metabolic pathways differed significantly between cases and controls. Pathways that were more abundant in cases are on the positive side (blue circle with 95% CI). Pathways that were more abundant in controls are on the negative side (orange circle). q-value: the Storey FDR-corrected P-value. Mean proportions are shown in stacks for cases (blue) and controls (orange). Difference in mean proportions = mean proportion in cases minus mean proportion in controls. Only metabolic pathways at KEGG hierarchical level 1 were investigated to limit inclusion of nonbacterial pathways. Tests were conducted at KEGG hierarchical level 3, which included 136 pathways present in ≥10% of samples. The letter in front of each pathway name indicates the KEGG hierarchical level 2 for that pathway (A=Amino acid metabolism, B=Biosynthesis of other secondary metabolites, C=Carbohydrate metabolism, D=Energy metabolism, E=Enzyme families (none detected at FDR<0.05), F=Glycan biosynthesis and metabolism, G=Lipid metabolism, H=Metabolism of cofactors and vitamins, I=Metabolism of other amino acids, J=Metabolism of terpenoids and polyketides, K=Nucleotide metabolism (none detected at FDR<0.05), L=Xenobiotics biodegradation and metabolism.)
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