Relationships of gut microbiota, short-chain fatty acids, inflammation, and the gut barrier in Parkinson's disease
Background
Previous studies have reported that gut microbiota, permeability, short-chain fatty acids (SCFAs), and inflammation are altered in Parkinson’s disease (PD), but how these factors are linked and contribute to disease processes and symptoms remains uncertain. This study sought to compare and identify associations among these factors in PD patients and controls to elucidate their interrelations and links to clinical manifestations of PD.
Methods
Stool and plasma samples and clinical data were collected from 55 PD patients and 56 controls. Levels of stool SCFAs and stool and plasma inflammatory and permeability markers were compared between patients and controls and related to one another and to the gut microbiota.
Results
Calprotectin was increased and SCFAs decreased in stool in PD in a sex-dependent manner. Inflammatory markers in plasma and stool were neither intercorrelated nor strongly associated with SCFA levels. Age at PD onset was positively correlated with SCFAs and negatively correlated with CXCL8 and IL-1β in stool. Fecal zonulin correlated positively with fecal NGAL and negatively with PD motor and non-motor symptoms. Microbiota diversity and composition were linked to levels of stool SCFAs, inflammation, and zonulin. Certain relationships differed between patients and controls and by sex.
Conclusions
Intestinal inflammatory responses and reductions in fecal SCFAs occur in PD, are related to the microbiota and to disease onset, and are not reflected in plasma inflammatory profiles. Some of these relationships are PD- and sex-dependent. Alterations in microbiota-host interactions and links between intestinal inflammation and reduced SCFA levels and earlier PD onset warrant further investigation.
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This is a list of supplementary files associated with this preprint. Click to download.
Additional File 1.docx Supplementary Methods Extended descriptions of measurements for SCFAs and inflammatory and permeability markers and details of statistical analyses.
Additional File 2.pdf R Markdown The full R code used for the analyses with output.
Additional File 3.xlsx Inflammatory and permeability marker and SCFA concentrations Table detailing A) levels of all analytes in this study by PD/control status and B) by both PD/control status and sex. P-values reflect Wilcoxon rank sum tests.
Additional File 4.pdf Scatterplots for significantly correlated clinical variables and SCFAs or inflammatory or permeability markers Scatterplots visualizing relationships of significantly (p<0.05, Pearson) correlated analytes and clinical variables A) measured in all subjects and B) measured only in PD patients.
Additional File 5.pdf Microbial diversity and PD-related variables. A) Table summarizing p-values for comparisons of alpha and beta diversity; B) Scatterplots of significant correlations for alpha diversity and PD-related variables; C) NMDS ordination plots for PD-related variables.
Additional File 6.xlsx Linear regression for alpha diversity, inflammatory and permeability markers/SCFAs, and PD/control status A) Model: log(variable) ~ sex + PD/control + Diversity; B) Model: log(variable) ~ sex + PD/control * Diversity; C) Stool calprotectin and additional confounders derived from Figure 3; D) Propionic acid and additional confounders derived from Figure 3.
Additional File 7.xlsx Associations of beta diversity with inflammatory and permeability markers/SCFAs and PD/control status Permutational multivariate analysis of variance using distance matrices A) without interactions, B) with interaction (model: community dissimilarity ~ PD/control * variable).
Additional File 8.pdf NMDS ordination plots for beta diversity, PD/control status, and select analytes NMDS ordination plots for the stool markers and SCFAs associated with the most notable beta diversity difference. Variables were split into two categories by median.
Additional File 9.xlsx Enterotype comparisons A) Number of subjects classified to each enterotype in the control and PD groups; B) Comparison of inflammatory and permeability markers/SCFA levels between enterotypes P-values reflect Kruskal-Wallis test and values corrected with Benjamini & Hochberg false discovery rate method.
Additional File 10.pdf Scatterplots of genera relative abundances by SCFA levels Scatterplots visualizing significant (p<0.05, Pearson correlation) relationships between SCFAs and relative abundance of most differentially abundant bacterial genera as determined by differential expression analysis for sequence count data.
Additional File 11.xlsx Differentially abundant taxa for variables of interest. Table of differential expression analysis for sequence count data results for families and genera that had a multiple comparison corrected p < 0.05 in at least one comparison for A) acetic, propionic, and butyric acid or B) stool NGAL, zonulin, and calprotectin. Confounders included in the confounder-corrected models were Rome III 9-15 sum score and sex.
Additional File 12.pdf Scatter plots of genera relative abundances by stool inflammatory and permeability marker levels Scatterplots visualizing significant (p<0.05, Pearson correlation) relationships between A) NGAL, B) zonulin, and C) calprotectin and relative abundance of most differentially abundant bacterial genera as determined by differential expression analysis for sequence count data.
Additional File 13.xslx Table summarizing all key results of this study.
Posted 04 Jan, 2021
On 16 Jan, 2021
Received 16 Jan, 2021
Received 15 Jan, 2021
On 14 Jan, 2021
Invitations sent on 14 Dec, 2020
On 13 Dec, 2020
On 13 Dec, 2020
On 13 Dec, 2020
On 25 Sep, 2020
Received 09 Sep, 2020
Received 07 Sep, 2020
Invitations sent on 31 Aug, 2020
On 31 Aug, 2020
On 31 Aug, 2020
On 31 Aug, 2020
On 27 Aug, 2020
On 26 Aug, 2020
On 26 Aug, 2020
On 21 Aug, 2020
Relationships of gut microbiota, short-chain fatty acids, inflammation, and the gut barrier in Parkinson's disease
Posted 04 Jan, 2021
On 16 Jan, 2021
Received 16 Jan, 2021
Received 15 Jan, 2021
On 14 Jan, 2021
Invitations sent on 14 Dec, 2020
On 13 Dec, 2020
On 13 Dec, 2020
On 13 Dec, 2020
On 25 Sep, 2020
Received 09 Sep, 2020
Received 07 Sep, 2020
Invitations sent on 31 Aug, 2020
On 31 Aug, 2020
On 31 Aug, 2020
On 31 Aug, 2020
On 27 Aug, 2020
On 26 Aug, 2020
On 26 Aug, 2020
On 21 Aug, 2020
Background
Previous studies have reported that gut microbiota, permeability, short-chain fatty acids (SCFAs), and inflammation are altered in Parkinson’s disease (PD), but how these factors are linked and contribute to disease processes and symptoms remains uncertain. This study sought to compare and identify associations among these factors in PD patients and controls to elucidate their interrelations and links to clinical manifestations of PD.
Methods
Stool and plasma samples and clinical data were collected from 55 PD patients and 56 controls. Levels of stool SCFAs and stool and plasma inflammatory and permeability markers were compared between patients and controls and related to one another and to the gut microbiota.
Results
Calprotectin was increased and SCFAs decreased in stool in PD in a sex-dependent manner. Inflammatory markers in plasma and stool were neither intercorrelated nor strongly associated with SCFA levels. Age at PD onset was positively correlated with SCFAs and negatively correlated with CXCL8 and IL-1β in stool. Fecal zonulin correlated positively with fecal NGAL and negatively with PD motor and non-motor symptoms. Microbiota diversity and composition were linked to levels of stool SCFAs, inflammation, and zonulin. Certain relationships differed between patients and controls and by sex.
Conclusions
Intestinal inflammatory responses and reductions in fecal SCFAs occur in PD, are related to the microbiota and to disease onset, and are not reflected in plasma inflammatory profiles. Some of these relationships are PD- and sex-dependent. Alterations in microbiota-host interactions and links between intestinal inflammation and reduced SCFA levels and earlier PD onset warrant further investigation.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7