Background Parkinson’s disease (PD) is a systemic disease clinically defined by the degeneration of dopaminergic neurons in the brain. While alterations in the gut microbiome composition have been reported in PD, their functional consequences remain unclear. Herein, we addressed this question by an analysis of stool samples from the Luxembourg Parkinson’s Study (n = 147 typical PD cases, n = 162 controls). Results All individuals underwent detailed clinical assessment, including neurological examinations and neuropsychological tests followed by self-reporting questionnaires. Stool samples from these individuals were first analysed by 16S rRNA gene sequencing. Second, we predicted the potential secretion for 129 microbial metabolites through personalised metabolic modelling using the microbiome data and genome-scale metabolic reconstructions of human gut microbes. Our key results include the following. Eight genera and seven species changed significantly in their relative abundances between PD patients and healthy controls. PD-associated microbial patterns statistically depended on sex, age, BMI, and constipation. Particularly, the relative abundances of Bilophila and Paraprevotella were significantly associated with the Hoehn and Yahr staging after controlling for the disease duration. Furthermore, personalised metabolic modelling of the gut microbiomes revealed PD-associated metabolic patterns in the predicted secretion potential of nine microbial metabolites in PD, including increased methionine and cysteinylglycine. The predicted microbial pantothenic acid production potential was linked to the presence of specific non-motor symptoms. Conclusion Our results suggest that PD-associated alterations of the gut microbiome can translate into substantial functional differences affecting host metabolism and disease phenotype.

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While genetic advances have successfully defined part of the complexity in Parkinson’s disease (PD), the clinical characterization of phenotypes remains challenging. Therapeutic trials and cohort studies typically include patients with earlier disease stages and exclude comorbidities, thus ignoring a substantial part of the real-world PD population. To account for these limitations, we implemented the Luxembourg PD study as a comprehensive clinical, molecular and device-based approach including patients with typical PD and atypical parkinsonism, irrespective of their disease stage, age, comorbidities, or linguistic background. To provide a large, longitudinally followed, and deeply phenotyped set of patients and controls for clinical and fundamental research on PD, we implemented an open-source digital platform that can be harmonized with international PD cohort studies. Our interests also reflect Luxembourg-specific areas of PD research, including vision, gait, and cognition. This effort is flanked by comprehensive biosampling efforts assuring high quality and sustained availability of body liquids and tissue biopsies. We provide evidence for the feasibility of such a cohort program with deep phenotyping and high quality biosampling on parkinsonism in an environment with structural specificities and alert the international research community to our willingness to collaborate with other centers. The combination of advanced clinical phenotyping approaches including device-based assessment will create a comprehensive assessment of the disease and its variants, its interaction with comorbidities and its progression. We envision the Luxembourg Parkinson’s study as an important research platform for defining early diagnosis and progression markers that translate into stratified treatment approaches.

BackgroundGender, genetic makeup, and prior experience interact to determine physiological responses to an external perceived stressor. Here, we investigated the contribution of both genetic variants and promoter methylation of the NR3C1 (glucocorticoid receptor) gene to the cardiovascular and hypothalamus-pituitary-adrenal (HPA) axis response to the socially evaluated cold pressor test (seCPT).ResultsTwo hundred thirty-two healthy participants were recruited and underwent the experiment. They were randomly assigned to either the seCPT group (cold water) or a control group (warm water). The seCPT group had a clear stress reaction; salivary cortisol levels and peak systolic and diastolic blood pressure all increased significantly compared to the control group. GR genotype (TthIIII, NR3C1-I, 1H, E22E, R23K, BclI and 9beta) and methylation data were obtained from 218 participants. Haplotypes were built from the GR genotypes, and haplotype 2 (minor allele of BclI) carriers had a higher cortisol response to the seCPT in comparison to non-carriers (20.77 ± 13.22; 14.99 ± 8.42; p = 0.034), as well as independently of the experimental manipulation, higher baseline heart rate (72.44 ± 10.99; 68.74 ± 9.79; p = 0.022) and blood pressure (115.81 ± 10.47; 111.61 ± 10.74; p = 0.048). Average methylation levels throughout promoter 1F and 1H were low (2.76 and 1.69 %, respectively), but there was a strong correlation between individual CpGs and the distance separating them (Pearson’s correlation r = 0.725, p = 3.03 × 10−26). Higher promoter-wide methylation levels were associated with decreased baseline blood pressure, and when incorporated into a linear mixed effect model significantly predicted lower systolic and diastolic blood pressure evolution over time in response to the experimental manipulation. The underlying genotype significantly predicted methylation levels; particularly, the homozygous BclI minor allele was associated with higher methylation in promoter 1H (p = 0.042).ConclusionsThis is one of the first studies linking epigenetic modifications of the GR promoter, receptor genotype and physiological measures of the stress response. At baseline, there were clear genetic and epigenetic effects on blood pressure. The seCPT induced a strong cardiovascular and HPA axis response, and both systems were affected by the functional genetic variants, although methylation also predicted blood pressure reactivity. The return to baseline was predominantly influenced by the genomic sequence. Overall, the physiological response to the seCPT is controlled by an exquisite mix of genetic and epigenetic factors.Electronic supplementary materialThe online version of this article (doi:10.1186/s13148-016-0180-y) contains supplementary material, which is available to authorized users.

25 26 Parkinson's disease (PD) is a systemic disease clinically defined by the degeneration of 27 dopaminergic neurons in the brain. While alterations in the gut microbiome composition have 28 been reported in PD, their functional consequences remain unclear. Herein, we first analysed 29 the gut microbiome of patients and healthy controls by 16S rRNA gene sequencing of stool 30 samples from the Luxembourg Parkinson's study (n=147 typical PD cases, n=162 controls). 31All individuals underwent detailed clinical assessment, including neurological examinations 32 and neuropsychological tests followed by self-reporting questionnaires. Second, we predicted 33 the potential secretion for 129 microbial metabolites through personalised metabolic modelling 34 using the microbiome data and genome-scale metabolic reconstructions of human gut 35 microbes. Our key results include: 1. eight genera and nine species changed significantly in 36 their relative abundances between PD patients and healthy controls. 2. PD-associated microbial 37 patterns statistically depended on sex, age, BMI, and constipation. The relative abundances of 38Bilophila and Paraprevotella were significantly associated with the Hoehn and Yahr staging 39 after controlling for the disease duration. In contrast, dopaminergic medication had no 40 detectable effect on the PD microbiome composition. 3. Personalised metabolic modelling of 41 the gut microbiomes revealed PD-associated metabolic patterns in secretion potential of nine 42 microbial metabolites in PD, including increased methionine and cysteinylglycine. The 43 microbial pantothenic acid production potential was linked to the presence of specific non-44 motor symptoms and attributed to individual bacteria, such as Akkermansia muciniphila and 45 Bilophila wardswarthia. Our results suggest that PD-associated alterations of gut microbiome 46 could translate into functional differences affecting host metabolism and disease phenotype. 47