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April 09, 2019; 92 (15 Supplement) May 7, 2019

The Association of Gut Microbiome Composition and Parkinson’s Disease in Patient Cohort of Central California (P3.8-039)

Hsiang-Chin Lori Chou, Venu Lagishetty, Jeff Bronstein, Jonathan Jacobs, Beate Ritz
First published April 16, 2019,
Hsiang-Chin Lori Chou
1Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles Los Angeles CA United States
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Venu Lagishetty
2Division of Digestive Diseases, Department of Medicine Los Angeles CA United States
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Jeff Bronstein
3Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles Los Angeles CA United States
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Jonathan Jacobs
2Division of Digestive Diseases, Department of Medicine Los Angeles CA United States
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Beate Ritz
1Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles Los Angeles CA United States
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Citation
The Association of Gut Microbiome Composition and Parkinson’s Disease in Patient Cohort of Central California (P3.8-039)
Hsiang-Chin Lori Chou, Venu Lagishetty, Jeff Bronstein, Jonathan Jacobs, Beate Ritz
Neurology Apr 2019, 92 (15 Supplement) P3.8-039;

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Abstract

Objective: Our study aims to determine gut microbiome differences in composition and function between Parkinson’s disease (PD) patients and controls.

Background: The gut microbiome has been associated with many diseases. Many studies showed that the microbiome can affect aspects of neurological function, brain activity, and behavior. While several digestive symptoms are well-known non-motor features of PD, the role of the gut microbiome in the neurodegenerative process remains underexplored. Recent reports have suggested that the gut microbiome might also play a role in PD.

Design/Methods: We collected ethanol fixed fecal samples from 52 PD patients living in central California and from 26 household/community controls of similar age and race. After extraction of DNA from samples, the V4 region of the bacterial 16S ribosomal RNA gene was sequenced on the Illumina MiSeq platform. The taxonomic assignments of sequences was performed using open reference operational taxonomic unit (OTU) picking in QIIME against the Greengenes database pre-clustered at 97% identity. The statistical analysis was performed using QIIME and R packages.

Results: We found that the gut microbiome composition of the Control group show a greater richness (OTU counts, Chao 1, ACE) and alpha diversity (Shannon/Simpson Index) compared with the PD patients. Beta diversity analysis demonstrated some compositional difference in the microbiome between PD and controls (PERMANOVA, Bray-Curtis: F=1.10, p=0.286; weighted Unifrac: F=2.07, p=0.071; Unweighted UniFrac: F=1.23, p=0.16). Using negative binomial models to determine the differential abundance of taxa (DESeq2 package in R), we found 30 genera to be different between PD and controls (B-H adjusted p-value<0.05).

Conclusions: In this pilot study, we found differences in the gut microbiome composition comparing PD cases and controls and identified specific bacterial genera that are associated with PD status. In the future, we plan to study whether and which environmental and behavioral factors contribute to the diversity of the microbiome in PD.

Disclosure: Dr. Chou has nothing to disclose. Dr. Lagishetty has nothing to disclose. Dr. Bronstein has nothing to disclose. Dr. Jacobs has nothing to disclose. Dr. Ritz has nothing to disclose.

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