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 α‐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. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Background: The objective of this study was to assess neurofilament light chain as a Parkinson's disease biomarker.Methods: We quantified neurofilament light chain in 2 independent cohorts: (1) longitudinal cerebrospinal fluid samples from the longitudinal de novo Parkinson's disease cohort and (2) a large longitudinal cohort with serum samples from Parkinson's disease, other cognate/neurodegenerative disorders, healthy controls, prodromal conditions, and mutation carriers.Results: In the Parkinson's Progression Marker Initiative cohort, mean baseline serum neurofilament light chain was higher in Parkinson's disease patients (13 ± 7.2 pg/mL) than in controls (12 ± 6.7 pg/mL), P = 0.0336. Serum neurofilament light chain increased longitudinally in Parkinson's disease patients versus controls (P < 0.01). Motor scores were positively associated with neurofilament light chain, whereas some cognitive scores showed a negative association.Conclusions: Neurofilament light chain in serum samples is increased in Parkinson's disease patients versus healthy controls, increases over time and with age, and correlates with clinical measures of Parkinson's disease severity. Although the specificity of neurofilament light chain for Parkinson's disease is low, it is the first blood‐based biomarker candidate that could support disease stratification of Parkinson's disease versus other cognate/neurodegenerative disorders, track clinical progression, and possibly assess responsiveness to neuroprotective treatments. However, use of neurofilament light chain as a biomarker of response to neuroprotective interventions remains to be assessed. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Parkinson’s disease is the second most common neurodegenerative disorder after Alzheimer’s disease and is estimated to affect approximately 1–4% of individuals aged over 60 years old. Although considerable efforts have been invested into developing disease‐modifying therapies for Parkinson’s disease, such efforts have been confounded by the difficulty in accurately diagnosing Parkinson’s disease during life to enable accurate patient stratification for clinical trialling of candidate therapeutics. Therefore, the search for effective biomarkers that can be accurately evaluated during life with non‐invasive means is a pressing issue in the field. Since the discovery of α‐synuclein (α‐syn) as a protein linked to a familial form of Parkinson’s disease, later identified as the major protein component of the neuropathological hallmark of idiopathic Parkinson’s disease, considerable interest has focused on this protein and its distinct conformers. We describe here the progress that has been made in the area of Parkinson’s disease biomarker discovery with a focus on α‐synuclein. In particular, we highlight the novel assays that have been employed and the increasing complexity in evaluating α‐synuclein with regard to the considerable diversity of conformers that exist in the biofluids and peripheral tissues under disease conditions. image “This article is part of the Special Issue Synuclein.”

Parkinson’s disease is increasingly prevalent. It progresses from the pre-motor stage (characterised by non-motor symptoms like REM sleep behaviour disorder), to the disabling motor stage. We need objective biomarkers for early/pre-motor disease stages to be able to intervene and slow the underlying neurodegenerative process. Here, we validate a targeted multiplexed mass spectrometry assay for blood samples from recently diagnosed motor Parkinson’s patients (n = 99), pre-motor individuals with isolated REM sleep behaviour disorder (two cohorts: n = 18 and n = 54 longitudinally), and healthy controls (n = 36). Our machine-learning model accurately identifies all Parkinson patients and classifies 79% of the pre-motor individuals up to 7 years before motor onset by analysing the expression of eight proteins—Granulin precursor, Mannan-binding-lectin-serine-peptidase-2, Endoplasmatic-reticulum-chaperone-BiP, Prostaglaindin-H2-D-isomaerase, Interceullular-adhesion-molecule-1, Complement C3, Dickkopf-WNT-signalling pathway-inhibitor-3, and Plasma-protease-C1-inhibitor. Many of these biomarkers correlate with symptom severity. This specific blood panel indicates molecular events in early stages and could help identify at-risk participants for clinical trials aimed at slowing/preventing motor Parkinson’s disease.

Background: Aggregation of α‐synuclein is central to the pathophysiology of PD. Biomarkers related to α‐synuclein may be informative for PD diagnosis/progression.Objectives: To analyze α‐synuclein in CSF in drug‐naïve PD, healthy controls, and prodromal PD in the Parkinson's Progression Markers Initiative.Methods: Over up to 36‐month follow‐up, CSF total α‐synuclein and its association with MDS‐UPDRS motor scores, cognitive assessments, and dopamine transporter imaging were assessed.Results: The inception cohort included PD (n = 376; age [mean {standard deviation} years]: 61.7 [9.62]), healthy controls (n = 173; age, 60.9 [11.3]), hyposmics (n = 16; age, 68.3 [6.15]), and idiopathic rapid eye movement sleep behavior disorder (n = 32; age, 69.3 [4.83]). Baseline CSF α‐synuclein was lower in manifest and prodromal PD versus healthy controls. Longitudinal α‐synuclein decreased significantly in PD at 24 and 36 months, did not change in prodromal PD over 12 months, and trended toward an increase in healthy controls. The decrease in PD was not shown when CSF samples with high hemoglobin concentration were removed from the analysis. CSF α‐synuclein changes did not correlate with longitudinal MDS‐UPDRS motor scores or dopamine transporter scan.Conclusions: CSF α‐synuclein decreases early in the disease, preceding motor PD. CSF α‐synuclein does not correlate with progression and therefore does not reflect ongoing dopaminergic neurodegeneration. Decreased CSF α‐synuclein may be an indirect index of changes in the balance between α‐synuclein secretion, solubility, or aggregation in the brain, reflecting its overall turnover. Additional biomarkers more directly related to α‐synuclein pathophysiology and disease progression and other markers to be identified by, for example, proteomics and metabolomics are needed. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society