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See detailIntegrated Analyses of Microbiome and Longitudinal Metabolome Data Reveal Microbial-Host Interactions on Sulfur Metabolism in Parkinson’s Disease
Hertel, Johannes; Harms, Amy C.; Heinken, Almut et al

in Cell Reports (2019), 29(7), 1767-1777

Parkinson’s disease (PD) exhibits systemic effects on human metabolism with emerging roles for the gut microbiome. Here, we integrated longitudinal metabolome data from 30 drug-naïve, de-novo PD patients ... [more ▼]

Parkinson’s disease (PD) exhibits systemic effects on human metabolism with emerging roles for the gut microbiome. Here, we integrated longitudinal metabolome data from 30 drug-naïve, de-novo PD patients and 30 matched controls with constraint-based modeling of gut microbial communities derived from an independent, drug-naïve PD cohort, and prospective data from a general population. Our key results are i) longitudinal trajectory of metabolites associated with the interconversion of methionine and cysteine via cystathionine differed between PD patients and controls, ii) dopaminergic medication showed strong lipidomic signatures, iii) taurine-conjugated bile acids correlated with the severity of motor symptoms, while low levels of sulfated taurolithocholate were associated with incident PD in the general population, and iv) computational modeling predicted changes in sulfur metabolism, driven by A. muciniphila and B. wadsworthia, consistent with the changed metabolome. In conclusion, the multi-omics integration revealed PD-specific patterns in microbial-host sulfur co-metabolism that may contribute to PD severity. [less ▲]

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See detailDistinct metabolomic signature in cerebrospinal fluid in early parkinson's disease: Early Parkinson'S CSF Metabolic Signature
Trezzi, Jean-Pierre UL; Galozzi, Sara; Jäger, Christian UL et al

in Movement Disorders (2017)

Objective: The purpose of this study was to profile cerebrospinal fluid (CSF) from early-stage PD patients for disease-related metabolic changes and to determine a robust biomarker signature for early ... [more ▼]

Objective: The purpose of this study was to profile cerebrospinal fluid (CSF) from early-stage PD patients for disease-related metabolic changes and to determine a robust biomarker signature for early-stage PD diagnosis. Methods: By applying a non-targeted and mass spectrometry-driven approach, we investigated the CSF metabolome of 44 early-stage sporadic PD patients yet without treatment (DeNoPa cohort). We compared all detected metabolite levels with those measured in CSF of 43 age- and gender-matched healthy controls. After this analysis, we validated the results in an independent PD study cohort (T€ubingen cohort). Results: We identified that dehydroascorbic acid levels were significantly lower and fructose, mannose, and threonic acid levels were significantly higher (P <.05) in PD patients when compared with healthy controls. These changes reflect pathological oxidative stress responses, as well as protein glycation/glycosylation reactions in PD. Using a machine learning approach based on logistic regression, we successfully predicted the origin (PD patients vs healthy controls) in a second (n518) as well as in a third and completely independent validation set (n536). The biomarker signature is composed of the three markers—mannose, threonic acid, and fructose—and allows for sample classification with a sensitivity of 0.790 and a specificity of 0.800. Conclusion: We identified PD-specific metabolic changes in CSF that were associated with antioxidative stress response, glycation, and inflammation. Our results disentangle the complexity of the CSF metabolome to unravel metabolome changes related to earlystage PD. The detected biomarkers help understanding PD pathogenesis and can be applied as biomarkers to increase clinical diagnosis accuracy and patient care in early-stage PD. [less ▲]

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See detailMetabolic profiling of body fluids and multivariate data analysis
Trezzi, Jean-Pierre UL; Jäger, Christian UL; Galozzi, Sara et al

in MethodsX (2017), 4(1), 95-103

Metabolome analyses of body fluids are challenging due pre-analytical variations, such as pre-processing delay and temperature, and constant dynamical changes of biochemical processes within the samples ... [more ▼]

Metabolome analyses of body fluids are challenging due pre-analytical variations, such as pre-processing delay and temperature, and constant dynamical changes of biochemical processes within the samples. Therefore, proper sample handling starting from the time of collection up to the analysis is crucial to obtain high quality samples and reproducible results. A metabolomics analysis is divided into 4 main steps: 1) Sample collection, 2) Metabolite extraction, 3) Data acquisition and 4) Data analysis. Here, we describe a protocol for gas chromatography coupled to mass spectrometry (GC–MS) based metabolic analysis for biological matrices, especially body fluids. This protocol can be applied on blood serum/plasma, saliva and cerebrospinal fluid (CSF) samples of humans and other vertebrates. It covers sample collection, sample pre-processing, metabolite extraction, GC–MS measurement and guidelines for the subsequent data analysis. [less ▲]

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See detailThe nasal and gut microbiome in Parkinson's disease and idiopathic rapid eye movement sleep behavior disorder.
Heintz, Anna UL; Pandey, Urvashi; Wicke, Tamara et al

in Movement disorders : official journal of the Movement Disorder Society (2017)

BACKGROUND: Increasing evidence connects the gut microbiota and the onset and/or phenotype of Parkinson's disease (PD). Differences in the abundances of specific bacterial taxa have been reported in PD ... [more ▼]

BACKGROUND: Increasing evidence connects the gut microbiota and the onset and/or phenotype of Parkinson's disease (PD). Differences in the abundances of specific bacterial taxa have been reported in PD patients. It is, however, unknown whether these differences can be observed in individuals at high risk, for example, with idiopathic rapid eye movement sleep behavior disorder, a prodromal condition of alpha-synuclein aggregation disorders including PD. OBJECTIVES: To compare microbiota in carefully preserved nasal wash and stool samples of subjects with idiopathic rapid eye movement sleep behavior disorder, manifest PD, and healthy individuals. METHODS: Microbiota of flash-frozen stool and nasal wash samples from 76 PD patients, 21 idiopathic rapid eye movement sleep behavior disorder patients, and 78 healthy controls were assessed by 16S and 18S ribosomal RNA amplicon sequencing. Seventy variables, related to demographics, clinical parameters including nonmotor symptoms, and sample processing, were analyzed in relation to microbiome variability and controlled differential analyses were performed. RESULTS: Differentially abundant gut microbes, such as Akkermansia, were observed in PD, but no strong differences in nasal microbiota. Eighty percent of the differential gut microbes in PD versus healthy controls showed similar trends in idiopathic rapid eye movement sleep behavior disorder, for example, Anaerotruncus and several Bacteroides spp., and correlated with nonmotor symptoms. Metagenomic sequencing of select samples enabled the reconstruction of genomes of so far uncharacterized differentially abundant organisms. CONCLUSION: Our study reveals differential abundances of gut microbial taxa in PD and its prodrome idiopathic rapid eye movement sleep behavior disorder in comparison to the healthy controls, and highlights the potential of metagenomics to identify and characterize microbial taxa, which are enriched or depleted in PD and/or idiopathic rapid eye movement sleep behavior disorder. (c) 2017 International Parkinson and Movement Disorder Society. [less ▲]

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