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See detailStudying the Parkinson's disease metabolome and exposome in biological samples through different analytical and cheminformatics approaches: a pilot study
Talavera Andujar, Begona UL; Aurich, Dagny UL; Aho, Velma UL et al

in Analytical and Bioanalytical Chemistry (2022)

Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease, with an increasing incidence in recent years due to the ageing population. Genetic mutations alone only explain <10% of PD ... [more ▼]

Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease, with an increasing incidence in recent years due to the ageing population. Genetic mutations alone only explain <10% of PD cases, while environmental factors, including small molecules, may play a significant role in PD. In the present work, 22 plasma (11 PD, 11 control) and 19 feces samples (10 PD, 9 control) were analyzed by non-target high resolution mass spectrometry (NT-HRMS) coupled to two liquid chromatography (LC) methods (reversed phase (RP) and hydrophilic interaction liquid chromatography (HILIC)). A cheminformatics workflow was optimized using open software (MS-DIAL and patRoon) and open databases (all public MSP-formatted spectral libraries for MS-DIAL, PubChemLite for Exposomics and the LITMINEDNEURO list for patRoon). Furthermore, five disease-specific databases and three suspect lists (on PD and related disorders) were developed, using PubChem functionality to identifying relevant unknown chemicals. The results showed that non-target screening with the larger databases generally provided better results compared with smaller suspect lists. However, two suspect screening approaches with patRoon were also good options to study specific chemicals in PD. The combination of chromatographic methods (RP and HILIC) as well as two ionization modes (positive and negative) enhanced the coverage of chemicals in the biological samples. While most metabolomics studies in PD have focused on blood and cerebrospinal fluid, we found a higher number of relevant features in feces, such as alanine betaine or nicotinamide, which can be directly metabolized by gut microbiota. This highlights the potential role of gut dysbiosis in PD development. [less ▲]

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See detailAn archaeal compound as a driver of Parkinson’s disease pathogenesis
Trezzi, Jean-Pierre; Aho, Velma UL; Jäger, Christian UL et al

E-print/Working paper (2022)

Patients with Parkinson’s disease (PD) exhibit differences in their gut microbiomes compared to healthy individuals. Although differences have most commonly been described in the abundances of bacterial ... [more ▼]

Patients with Parkinson’s disease (PD) exhibit differences in their gut microbiomes compared to healthy individuals. Although differences have most commonly been described in the abundances of bacterial taxa, changes to viral and archaeal populations have also been observed. Mechanistic links between gut microbes and PD pathogenesis remain elusive but could involve molecules that promote α-synuclein aggregation. Here, we show that 2-hydroxypyridine (2-HP) represents a key molecule for the pathogenesis of PD. We observe significantly elevated 2-HP levels in faecal samples from patients with PD or its prodrome, idiopathic REM sleep behaviour disorder (iRBD), compared to healthy controls. 2-HP is correlated with the archaeal species Methanobrevibacter smithii and with genes involved in methane metabolism, and it is detectable in isolate cultures of M. smithii. We demonstrate that 2-HP is selectively toxic to transgenic α-synuclein overexpressing yeast and increases α-synuclein aggregation in a yeast model as well as in human induced pluripotent stem cell derived enteric neurons. It also exacerbates PD-related motor symptoms, α-synuclein aggregation, and striatal degeneration when injected intrastriatally in transgenic mice overexpressing human α-synuclein. Our results highlight the effect of an archaeal molecule in relation to the gut-brain axis, which is critical for the diagnosis, prognosis, and treatment of PD. [less ▲]

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See detailPeripheral decarboxylase inhibitors paradoxically induce aromatic L-amino acid decarboxylase
Krüger, Rejko UL; Pavelka, Lukas UL; Mollenhauer, Brit et al

in NPJ Parkinson's Disease (2021)

Peripheral decarboxylase inhibitors (PDIs) prevent the conversion of levodopa to dopamine in the blood by the enzyme aromatic L-amino acid decarboxylase (AADC). Alterations in enzyme activity may ... [more ▼]

Peripheral decarboxylase inhibitors (PDIs) prevent the conversion of levodopa to dopamine in the blood by the enzyme aromatic L-amino acid decarboxylase (AADC). Alterations in enzyme activity may contribute to the required higher dosages of levodopa observed in many patients with Parkinson’s disease. We evaluated the effect of levodopa/PDI use on serum AADC enzyme activity. Serum AADC enzyme activity was evaluated in three independent cohorts of patients with Parkinson’s disease or parkinsonism (n = 301) and compared between patients on levodopa/PDI vs. patients not on this medication. AADC enzyme activity was elevated in 62% of patients on levodopa/PDI treatment, compared to 19% of patients not on levodopa/PDI (median 90 mU/L vs. 50 mU/L, p < 0.001). Patients with elevated AADC activity had longer disease duration and higher doses of levodopa/PDI. These findings may implicate that peripheral AADC induction could underlie a waning effect of levodopa, necessitating dose increases to maintain a sustained therapeutic effect. [less ▲]

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See detailLIPAD (LRRK2/Luebeck International Parkinson's Disease) Study Protocol: Deep Phenotyping of an International Genetic Cohort
Usnich, Tatiana; Vollstedt, Eva-Juliane; Schell, Nathalie et al

in Frontiers in Neurology (2021), 12

Background: Pathogenic variants in the Leucine-rich repeat kinase 2 ( LRRK2) gene are the most common known monogenic cause of Parkinson's disease (PD). LRRK2 -linked PD is clinically indistinguishable ... [more ▼]

Background: Pathogenic variants in the Leucine-rich repeat kinase 2 ( LRRK2) gene are the most common known monogenic cause of Parkinson's disease (PD). LRRK2 -linked PD is clinically indistinguishable from idiopathic PD and inherited in an autosomal dominant fashion with reduced penetrance and variable expressivity that differ across ethnicities and geographic regions. Objective: To systematically assess clinical signs and symptoms including non-motor features, comorbidities, medication and environmental factors in PD patients, unaffected LRRK2 pathogenic variant carriers, and controls. A further focus is to enable the investigation of modifiers of penetrance and expressivity of LRRK2 pathogenic variants using genetic and environmental data. Methods: Eligible participants are invited for a personal or online examination which comprises completion of a detailed eCRF and collection of blood samples (to obtain DNA, RNA, serum/plasma, immune cells), urine as well as household dust. We plan to enroll 1,000 participants internationally: 300 with LRRK2 -linked PD, 200 with LRRK2 pathogenic variants but without PD, 100 PD patients with pathogenic variants in the GBA or PRKN genes, 200 patients with idiopathic PD, and 200 healthy persons without pathogenic variants. Results: The eCRF consists of an investigator-rated (1 h) and a self-rated (1.5 h) part. The first part includes the Movement Disorder Society Unified Parkinson's Disease Rating, Hoehn \&Yahr, and Schwab \& England Scales, the Brief Smell Identification Test, and Montreal Cognitive Assessment. The self-rating part consists of a PD risk factor, food frequency, autonomic dysfunction, and quality of life questionnaires, the Pittsburgh Sleep Quality Inventory, and the Epworth Sleepiness as well as the Hospital Anxiety and Depression Scales. The first 15 centers have been initiated and the first 150 participants enrolled (as of March 25th, 2021). Conclusions: LIPAD is a large-scale international scientific effort focusing on deep phenotyping of LRRK2 -linked PD and healthy pathogenic variant carriers, including the comparison with additional relatively frequent genetic forms of PD, with a future perspective to identify genetic and environmental modifiers of penetrance and expressivity Clinical Trial Registration: ClinicalTrials.gov , NCT04214509. [less ▲]

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See detailDeep sncRNA-seq of the PPMI cohort to study Parkinson’s disease progression
Kern, Fabian; Fehlmann, Tobias; Violich, Ivo et al

E-print/Working paper (2020)

Coding and non-coding RNAs have diagnostic and prognostic importance in Parkinson’s diseases (PD). We studied circulating small non-coding RNAs (sncRNAs) in 7, 003 samples from two longitudinal PD cohorts ... [more ▼]

Coding and non-coding RNAs have diagnostic and prognostic importance in Parkinson’s diseases (PD). We studied circulating small non-coding RNAs (sncRNAs) in 7, 003 samples from two longitudinal PD cohorts (Parkinson’s Progression Marker Initiative (PPMI) and Luxembourg Parkinson’s Study (NCER-PD)) and modelled their influence on the transcriptome. First, we sequenced sncRNAs in 5, 450 blood samples of 1, 614 individuals in PPMI. The majority of 323 billion reads (59 million reads per sample) mapped to miRNAs. Other covered RNA classes include piRNAs, rRNAs, snoRNAs, tRNAs, scaRNAs, and snRNAs. De-regulated miRNAs were associated with the disease and disease progression and occur in two distinct waves in the third and seventh decade of live. Originating mostly from a characteristic set of immune cells they resemble a systemic inflammation response and mitochondrial dysfunction, two hallmarks of PD. By profiling 1, 553 samples from 1, 024 individuals in the NCER-PD cohort using an independent technology, we validate relevant findings from the sequencing study. Finally, network analysis of sncRNAs and transcriptome sequencing of the original cohort identified regulatory modules emerging in progressing PD patients.Competing Interest StatementThe authors have declared no competing interest. [less ▲]

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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 (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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