Changes in the Gut Microbiome and Predicted Functional Metabolic Effects in an Australian Parkinson's Disease Cohort

Gut microbiota non-convergence and adaptations in sympatric Tibetan and Przewalski's gazelles

Unraveling the connection between gut microbiota and adaptability in wild species in natural habitats is imperative yet challenging. We studied the gut microbiota of sympatric and allopatric populations of two closely related species, the Procapra picticaudata and P. przewalskii, with the latter showing lower adaptability and adaptive potential than the former. Despite shared habitat, sympatric populations showed no convergence in gut microbiota, revealing distinct microbiota-environment relationships between the two gazelle species. Furthermore, the gut microbiota assembly process of the P. przewalskii was shifted toward homogeneous selection processes relative to that of the P. picticaudata. Those taxa which contributed to the shift were mainly from the phyla Firmicutes and Verrucomicrobiota, with functions highly related to micronutrient and macronutrient metabolism. Our study provides new insights into the complex dynamics between gut microbiota, host adaptability, and environment in wildlife adaptation and highlights the need to consider host adaptability when examining wildlife host-microbiome interplay.

Changes in Bacterial Gut Composition in Parkinson's Disease and Their Metabolic Contribution to Disease Development: A Gut Community Reconstruction Approach

Parkinson's disease (PD) is a chronic and progressive neurodegenerative disease with the major symptoms comprising loss of movement coordination (motor dysfunction) and non-motor dysfunction, including gastrointestinal symptoms. Alterations in the gut microbiota composition have been reported in PD patients vs. controls. However, it is still unclear how these compositional changes contribute to disease etiology and progression. Furthermore, most of the available studies have focused on European, Asian, and North American cohorts, but the microbiomes of PD patients in Latin America have not been characterized. To address this problem, we obtained fecal samples from Colombian participants (n = 25 controls, n = 25 PD idiopathic cases) to characterize the taxonomical community changes during disease via 16S rRNA gene sequencing. An analysis of differential composition, diversity, and personalized computational modeling was carried out, given the fecal bacterial composition and diet of each participant. We found three metabolites that differed in dietary habits between PD patients and controls: carbohydrates, trans fatty acids, and potassium. We identified six genera that changed significantly in their relative abundance between PD patients and controls, belonging to the families Lachnospiraceae, Lactobacillaceae, Verrucomicrobioaceae, Peptostreptococcaceae, and Streptococcaceae. Furthermore, personalized metabolic modeling of the gut microbiome revealed changes in the predicted production of seven metabolites (Indole, tryptophan, fructose, phenylacetic acid, myristic acid, 3-Methyl-2-oxovaleric acid, and N-Acetylneuraminic acid). These metabolites are associated with the metabolism of aromatic amino acids and their consumption in the diet. Therefore, this research suggests that each individual's diet and intestinal composition could affect host metabolism. Furthermore, these findings open the door to the study of microbiome-host interactions and allow us to contribute to personalized medicine.

Gut microbiota alterations are associated with functional outcomes in patients of acute ischemic stroke with non-alcoholic fatty liver disease

Introduction

Patients with acute ischemic stroke (AIS) with non-alcoholic fatty liver disease (NAFLD) frequently have poor prognosis. Many evidences suggested that the changes in gut microbiota may play an important role in the occurrence and development of AIS patients with NAFLD. The purpose of this study was to explore microbial characteristics in patients of AIS with NAFLD, and the correlation between gut microbiota and functional outcomes.

Methods

The patients of AIS were recruited and divided into NAFLD group and non-NAFLD group. The stool samples and clinical information were collected. 16 s rRNA sequencing was used to analyze the characteristics of gut microbiota. The patients of AIS with NAFLD were followed-up to evaluate the functional outcomes of disease. The adverse outcomes were determined by modified Rankin scale (mRS) scores at 3 months after stroke. The diagnostic performance of microbial marker in predicting adverse outcomes was assessed by recipient operating characteristic (ROC) curves.

Results

Our results showed that the composition of gut microbiota between non-NAFLD group and NAFLD group were different. The characteristic bacteria in the patients of AIS with NAFLD was that the relative abundance of Dorea, Dialister, Intestinibacter and Flavonifractor were decreased, while the relative abundance of Enorma was increased. Moreover, the characteristic microbiota was correlated with many clinical parameters, such as mRS scores, mean arterial pressure and fasting blood glucose level. In addition, ROC models based on the characteristic microbiota or the combination of characteristic microbiota with independent risk factors could distinguish functional dependence patients and functional independence patients in AIS with NAFLD (area under curve is 0.765 and 0.882 respectively).

Conclusion

These findings revealed the microbial characteristics in patients of AIS with NAFLD, and further demonstrated the predictive capability of characteristic microbiota for adverse outcomes in patients of AIS with NAFLD.

The gut microbiome and cognition in Parkinson's disease: a systematic review

BACKGROUND

The pathology underlying cognitive changes in people with Parkinson's disease (PD) is not well understood. In healthy older adults, gut microbiome composition has been associated with cognitive function. In people with PD, preliminary evidence suggests that cortical spreading of abnormal alpha-synuclein aggregates may be associated with cognitive impairment. As changes in the gut have been linked to PD onset and associated Lewy body pathology, an investigation of the gut microbiome and cognition in PD is warranted.

OBJECTIVE

To synthesise existing evidence on the relationship between the gut microbiome and cognitive function in PD.

METHODS

A systematic review was conducted to search for peer-reviewed articles and grey literature published to July 2021 across seven electronic databases (MEDLINE, EMBASE, PsycINFO, Scopus, Cochrane Library, ProQuest, and ProQuest Dissertations and Theses). English language articles reporting the relationship between cognition and the gut microbiome in human participants with PD were considered for inclusion. Results were qualitatively synthesised and evidence quality was assessed using the QualSyst tool for quantitative studies.

RESULTS

Five cross-sectional studies reporting the association between the gut microbiome and cognition in 395 participants with PD were included. Studies provided preliminary evidence of a relationship between cognition and gut microbiota within the Bacteroidetes and Firmicutes phyla, however, associations with specific genera were inconsistent across studies.

CONCLUSIONS

Some species of short-chain fatty acid-producing bacteria (e.g. acetate, butyrate, and propionate producers) appear to be reduced in participants with PD with cognitive impairment. More research with larger samples and more consistent methodology is needed to substantiate these findings.

Gut-to-brain spreading of pathology in synucleinopathies: A focus on molecular signalling mediators

Synucleinopathies are a group of neurodegenerative disorders, classically characterized by the accumulation of aggregated alpha synuclein (aSyn) in the central nervous system. Parkinson's disease (PD) and multiple system atrophy (MSA) are the two prominent members of this family. Current treatment options mainly focus on the motor symptoms of these diseases. However, non-motor symptoms, including gastrointestinal (GI) symptoms, have recently gained particular attention, as they are frequently associated with synucleinopathies and often arise before motor symptoms. The gut-origin hypothesis has been proposed based on evidence of an ascending spreading pattern of aggregated aSyn from the gut to the brain, as well as the comorbidity of inflammatory bowel disease and synucleinopathies. Recent advances have shed light on the mechanisms underlying the progression of synucleinopathies along the gut-brain axis. Given the rapidly expanding pace of research in the field, this review presents a summary of the latest findings on the gut-to-brain spreading of pathology and potential pathology-reinforcing mediators in synucleinopathies. Here, we focus on 1) gut-to-brain communication pathways, including neuronal pathways and blood circulation, and 2) potential molecular signalling mediators, including bacterial amyloid proteins, microbiota dysbiosis-induced alterations in gut metabolites, as well as host-derived effectors, including gut-derived peptides and hormones. We highlight the clinical relevance and implications of these molecular mediators and their possible mechanisms in synucleinopathies. Moreover, we discuss their potential as diagnostic markers in distinguishing the subtypes of synucleinopathies and other neurodegenerative diseases, as well as for developing novel individualized therapeutic options for synucleinopathies.

The Alterations of Gut Microbiome and Lipid Metabolism in Patients with Spinal Muscular Atrophy

INTRODUCTION

Spinal muscular atrophy (SMA) can cause multiple system dysfunction, especially lipid metabolic disorders, for which management strategies are currently lacking. Microbes are related to metabolism and the pathogenesis of neurological diseases. This study aimed to preliminarily explore the alterations in the gut microbiota in SMA and the potential relationship between altered microbiota and lipid metabolic disorders.

METHODS

Fifteen patients with SMA and 17 gender- and age-matched healthy controls were enrolled in the study. Feces and fasting plasma samples were collected. 16S ribosomal RNA sequencing and nontargeted metabolomics analysis were performed to explore the correlation between microbiota and differential lipid metabolites.

RESULTS

No significant difference was found in microbial diversity (α- and β-diversity) between the SMA and control groups, with both groups having a relatively similar community structure. However, compared to the control group, the SMA group showed an increased relative abundance of the genera Ruminiclostridium, Gordonibacter, Enorma, Lawsonella, Frisingicoccus, and Anaerofilum and a decreased abundance of the genera Catabacter, Howardella, Marine_Methylotrophic_Group_3, and Lachnospiraceae_AC2044_group. The concurrent metabolomic analysis showed that the SMA group had 56 different kinds of lipid metabolite levels than did the control group. Additionally, the Spearman correlation suggested a correlation between the altered differential lipid metabolites and the above-mentioned altered microbiota.

CONCLUSIONS

The gut microbiome and lipid metabolites differed between the patients with SMA and the control subjects. The altered microbiota may be related with the lipid metabolic disorders in SMA. However, further study is necessary to clarify the mechanism of lipid metabolic disorders and develop management strategies to improve the related complications in SMA.

Predicting Neurodegenerative Disease Using Prepathology Gut Microbiota Composition: a Longitudinal Study in Mice Modeling Alzheimer's Disease Pathologies

The gut microbiota-brain axis is suspected to contribute to the development of Alzheimer's disease (AD), a neurodegenerative disease characterized by amyloid-β plaque deposition, neurofibrillary tangles, and neuroinflammation. To evaluate the role of the gut microbiota-brain axis in AD, we characterized the gut microbiota of female 3xTg-AD mice modeling amyloidosis and tauopathy and wild-type (WT) genetic controls. Fecal samples were collected fortnightly from 4 to 52 weeks, and the V4 region of the 16S rRNA gene was amplified and sequenced on an Illumina MiSeq. RNA was extracted from the colon and hippocampus, converted to cDNA, and used to measure immune gene expression using reverse transcriptase quantitative PCR (RT-qPCR). Diversity metrics were calculated using QIIME2, and a random forest classifier was applied to predict bacterial features that are important in predicting mouse genotype. Gene expression of glial fibrillary acidic protein (GFAP; indicating astrocytosis) was elevated in the colon at 24 weeks. Markers of Th1 inflammation (il6) and microgliosis (mrc1) were elevated in the hippocampus. Gut microbiota were compositionally distinct early in life between 3xTg-AD mice and WT mice (permutational multivariate analysis of variance [PERMANOVA], 8 weeks, P = 0.001, 24 weeks, P = 0.039, and 52 weeks, P = 0.058). Mouse genotypes were correctly predicted 90 to 100% of the time using fecal microbiome composition. Finally, we show that the relative abundance of Bacteroides species increased over time in 3xTg-AD mice. Taken together, we demonstrate that changes in bacterial gut microbiota composition at prepathology time points are predictive of the development of AD pathologies. IMPORTANCE Recent studies have demonstrated alterations in the gut microbiota composition in mice modeling Alzheimer's disease (AD) pathologies; however, these studies have only included up to 4 time points. Our study is the first of its kind to characterize the gut microbiota of a transgenic AD mouse model, fortnightly, from 4 weeks of age to 52 weeks of age, to quantify the temporal dynamics in the microbial composition that correlate with the development of disease pathologies and host immune gene expression. In this study, we observed temporal changes in the relative abundances of specific microbial taxa, including the genus Bacteroides, that may play a central role in disease progression and the severity of pathologies. The ability to use features of the microbiota to discriminate between mice modeling AD and wild-type mice at prepathology time points indicates a potential role of the gut microbiota as a risk or protective factor in AD.

Impact of Gastrointestinal Symptoms on Health-Related Quality of Life in an Australian Parkinson’s Disease Cohort

Background. Gastrointestinal symptoms (GIS) in people with Parkinson’s disease (PwP) are often underreported and may remain untreated. Constipation is a common nonmotor symptom that can adversely affect health-related quality of life (QoL); however, the impact of other GIS has not been adequately investigated. Objectives. To investigate the relationship between QoL and constipation using the Bristol Stool Chart, bowel movement frequency, and a perceived constipation measure; and to explore the relationship between QoL and other GIS in an Australian PD cohort. Methods. The impact of constipation and other GIS on QoL, as measured using the PDQ-39 scale, was assessed in a cohort of 144 (89 males, 55 females) clinic-attending PwP. Constipation was assessed using the Bristol Stool Chart as well as a composite constipation measure, and the Gastrointestinal Symptom Rating Scale (GSRS) was used to rate other GIS. Covariate corrected linear regression models were utilised to determine significant associations between GIS and QoL scores. Results. Individual and combined constipation measures were significantly associated with poorer QoL ( $p=0.032$ and $p=0.002$ , respectively). Analysis of GSRS symptom domains showed that in addition to symptoms of gastrointestinal hypomotility, a number of other symptoms such as increased eructation and increased flatus were also associated with poorer QoL. Conclusions. The findings point to the importance of GIS as contributor to health-related QoL in PwP. A better understanding of the relationship between GIS and QoL will help facilitate the development of more effective screening and treatment programs to improve symptom management and QoL for PwP.

Lactiplantibacillus plantarum ST-III-fermented milk improves autistic-like behaviors in valproic acid-induced autism spectrum disorder mice by altering gut microbiota

Introduction

Autism spectrum disorder (ASD) is a serious neurodevelopmental disorder with a rising incidence. More and more studies have shown that abnormal microbiota composition may aggravate the behavioral symptoms and biological signs of ASD, and interventions of probiotics and diet have emerged as a potential improvement measure.

Methods

Lactiplantibacillus plantarum ST-III-fermented milk was applied as an oral intervention in a valproic acid (VPA)-induced ASD mice model, and the effect of probiotic intake on autistic-related behaviors and gut microbiota composition was evaluated by behavioral tests and 16S rRNA gene sequencing.

Results

Gender specificity was shown in VPA-induced behavioral abnormalities in a mouse model, and L. plantarum ST-III-fermented milk was effective in ameliorating the impaired social interaction in male ASD mouse models, but not for the anxiety behavior exhibited by female ASD mouse models. Meanwhile, dietary changes were found to be the main cause of the altered gut microbiota in mice, and additional intake of L. plantarum ST-III-fermented milk seemed to improve autistic-like behaviors in male ASD mouse models by modulating specific gut microbes.

Discussion

These findings suggest that L. plantarum ST-III-fermented milk may play a beneficial role in improving the behavioral symptoms of ASD and is expected to be one of the candidate functional foods for ASD.

The Interplay between Gut Microbiota and Parkinson's Disease: Implications on Diagnosis and Treatment

The bidirectional interaction between the gut microbiota (GM) and the Central Nervous System, the so-called gut microbiota brain axis (GMBA), deeply affects brain function and has an important impact on the development of neurodegenerative diseases. In Parkinson’s disease (PD), gastrointestinal symptoms often precede the onset of motor and non-motor manifestations, and alterations in the GM composition accompany disease pathogenesis. Several studies have been conducted to unravel the role of dysbiosis and intestinal permeability in PD onset and progression, but the therapeutic and diagnostic applications of GM modifying approaches remain to be fully elucidated. After a brief introduction on the involvement of GMBA in the disease, we present evidence for GM alterations and leaky gut in PD patients. According to these data, we then review the potential of GM-based signatures to serve as disease biomarkers and we highlight the emerging role of probiotics, prebiotics, antibiotics, dietary interventions, and fecal microbiota transplantation as supportive therapeutic approaches in PD. Finally, we analyze the mutual influence between commonly prescribed PD medications and gut-microbiota, and we offer insights on the involvement also of nasal and oral microbiota in PD pathology, thus providing a comprehensive and up-to-date overview on the role of microbial features in disease diagnosis and treatment.

Microbiota Dysbiosis in Parkinson Disease—In Search of a Biomarker

Numerous studies have highlighted the role of the gastrointestinal system in Parkinson disease pathogenesis. It is likely triggered by proinflammatory markers produced by specific gut bacteria. This review’s aim is to identify gut bacterial biomarkers of Parkinson disease. A comprehensive search for original research papers on gut microbiota composition in Parkinson disease was conducted using the PubMed, Embase, and Scopus databases. Research papers on intestinal permeability, nasal and oral microbiomes, and interventional studies were excluded. The yielded results were categorized into four groups: Parkinson disease vs. healthy controls; disease severity; non-motor symptoms; and clinical phenotypes. This review was conducted in accordance with the PRISMA 2020 statement. A total of 51 studies met the eligibility criteria. In the Parkinson disease vs. healthy controls group, 22 bacteria were deemed potentially important. In the disease severity category, two bacteria were distinguished. In the non-motor symptoms and clinical phenotypes categories, no distinct pathogen was identified. The studies in this review report bacteria of varying taxonomic levels, which prevents the authors from reaching a clear conclusion. Future research should follow a unified methodology in order to identify potential biomarkers for Parkinson disease.

The Many Ages of Microbiome–Gut–Brain Axis

Frailty during aging is an increasing problem associated with locomotor and cognitive decline, implicated in poor quality of life and adverse health consequences. Considering the microbiome–gut–brain axis, we investigated, in a longitudinal study, whether and how physiological aging affects gut microbiome composition in wild-type male mice, and if and how cognitive frailty is related to gut microbiome composition. To assess these points, we monitored mice during aging at five selected experimental time points, from adulthood to senescence. At all selected experimental times, we monitored cognitive performance using novel object recognition and emergence tests and measured the corresponding Cognitive Frailty Index. Parallelly, murine fecal samples were collected and analyzed to determine the respective alpha and beta diversities, as well as the relative abundance of different bacterial taxa. We demonstrated that physiological aging significantly affected the overall gut microbiome composition, as well as the relative abundance of specific bacterial taxa, including Deferribacterota, Akkermansia, Muribaculaceae, Alistipes, and Clostridia VadinBB60. We also revealed that 218 amplicon sequence variants were significantly associated to the Cognitive Frailty Index. We speculated that some of them may guide the microbiome toward maladaptive and dysbiotic conditions, while others may compensate with changes toward adaptive and eubiotic conditions.

Nutritional Intake and Gut Microbiome Composition Predict Parkinson's Disease

Background

Models to predict Parkinson's disease (PD) incorporating alterations of gut microbiome (GM) composition have been reported with varying success.

Objective

To assess the utility of GM compositional changes combined with macronutrient intake to develop a predictive model of PD.

Methods

We performed a cross-sectional analysis of the GM and nutritional intake in 103 PD patients and 81 household controls (HCs). GM composition was determined by 16S amplicon sequencing of the V3-V4 region of bacterial ribosomal DNA isolated from stool. To determine multivariate disease-discriminant associations, we developed two models using Random Forest and support-vector machine (SVM) methodologies.

Results

Using updated taxonomic reference, we identified significant compositional differences in the GM profiles of PD patients in association with a variety of clinical PD characteristics. Six genera were overrepresented and eight underrepresented in PD patients relative to HCs, with the largest difference being overrepresentation of Lactobacillaceae at family taxonomic level. Correlation analyses highlighted multiple associations between clinical characteristics and select taxa, whilst constipation severity, physical activity and pharmacological therapies associated with changes in beta diversity. The random forest model of PD, incorporating taxonomic data at the genus level and carbohydrate contribution to total energy demonstrated the best predictive capacity [Area under the ROC Curve (AUC) of 0.74].

Conclusion

The notable differences in GM diversity and composition when combined with clinical measures and nutritional data enabled the development of a predictive model to identify PD. These findings support the combination of GM and nutritional data as a potentially useful biomarker of PD to improve diagnosis and guide clinical management.