prospective, multi-center cohort

https://pubmed.ncbi.nlm.nih.gov/28549077/

Parkinson’s disease varies widely in clinical manifestations, course of progression and biomarker profiles from person to person. Identification of distinct Parkinson’s disease subtypes is of great priority to illuminate underlying pathophysiology, predict progression and develop more efficient personalized care approaches. There is currently no clear way to define and divide subtypes in Parkinson’s disease. Using data from the Parkinson’s Progression Markers Initiative, we aimed to identify distinct subgroups via cluster analysis of a comprehensive dataset at baseline (i.e. cross-sectionally) consisting of clinical characteristics, neuroimaging, biospecimen and genetic information, then to develop criteria to assign patients to a Parkinson’s disease subtype. Four hundred and twenty-one individuals with de novo early Parkinson’s disease were included from this prospective longitudinal multicentre cohort. Hierarchical cluster analysis was performed using data on demographic and genetic information, motor symptoms and signs, neuropsychological testing and other non-motor manifestations. The key classifiers in cluster analysis were a motor summary score and three non-motor features (cognitive impairment, rapid eye movement sleep behaviour disorder and dysautonomia). We then defined three distinct subtypes of Parkinson’s disease patients: 223 patients were classified as ‘mild motor-predominant’ (defined as composite motor and all three non-motor scores below the 75th percentile), 52 as ‘diffuse malignant’ (composite motor score plus either ≥1/3 non-motor score >75th percentile, or all three non-motor scores >75th percentile) and 146 as ‘intermediate’. On biomarkers, people with diffuse malignant Parkinson’s disease had the lowest level of cerebrospinal fluid amyloid-_ (329.0 ± 96.7 pg/ml, P = 0.006) and amyloid-_/total-tau ratio (8.2 ± 3.0, P = 0.032). Data from deformation-based magnetic resonance imaging morphometry demonstrated a Parkinson’s disease-specific brain network had more atrophy in the diffuse malignant subtype, with the mild motor-predominant subtype having the least atrophy. Although disease duration at initial visit and follow-up time were similar between subtypes, patients with diffuse malignant Parkinson’s disease progressed faster in overall prognosis (global composite outcome), with greater decline in cognition and in dopamine functional neuroimaging after an average of 2.7 years. In conclusion, we introduce new clinical criteria for subtyping Parkinson’s disease based on a comprehensive list of clinical manifestations and biomarkers. This clinical subtyping can now be applied to individual patients for use in clinical practice using baseline clinical information. Even though all participants had a recent diagnosis of Parkinson’s disease, patients with the diffuse malignant subtype already demonstrated a more profound dopaminergic deficit, increased atrophy in Parkinson’s disease brain networks, a more Alzheimer’s disease-like cerebrospinal fluid profile and faster progression of motor and cognitive deficits.

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prospective, cohort study

https://pubmed.ncbi.nlm.nih.gov/32534583/

Background: Parkinson’s Disease (PD) is a heterogeneous, progressive neurodegenerative disorder which is characterized by a variety of motor and non-motor symptoms. To date, no disease modifying treatment for PD exists. Here, the study protocol of the Dutch Parkinson Cohort (DUPARC) is described. DUPARC is a longitudinal cohort study aimed at deeply phenotyping de novo PD patients who are treatment-naïve at baseline, to discover and validate biomarkers for PD progression, subtypes and pathophysiology.

Methods/design: DUPARC is a prospective cohort study in which 150 de novo PD subjects will be recruited through a collaborative network of PD treating neurologists in the northern part of the Netherlands (Parkinson Platform Northern Netherlands, PPNN). Participants will receive follow-up assessments after 1 year and 3 years, with the intention of an extended follow-up with 3 year intervals. Subjects are extensively characterized to primarily assess objectives within three major domains of PD: cognition, gastrointestinal function and vision. This includes brain magnetic resonance imaging (MRI); brain cholinergic PET-imaging with fluoroethoxybenzovesamicol (FEOBV-PET); brain dopaminergic PET-imaging with fluorodopa (FDOPA-PET); detailed neuropsychological assessments, covering all cognitive domains; gut microbiome composition; intestinal wall permeability; optical coherence tomography (OCT); genotyping; motor and non-motor symptoms; overall clinical status and lifestyle factors, including a dietary assessment; storage of blood and feces for additional analyses of inflammation and metabolic parameters. Since the start of the inclusion, at the end of 2017, over 100 PD subjects with a confirmed dopaminergic deficit on FDOPA-PET have been included.

Discussion: DUPARC is the first study to combine data within, but not limited to, the non-motor domains of cognition, gastrointestinal function and vision in PD subjects over time. As a de novo PD cohort, with treatment naïve subjects at baseline, DUPARC provides a unique opportunity for biomarker discovery and validation without the possible confounding influences of dopaminergic medication.

Trial registration: NCT04180865; registered retrospectively, November 28th 2019.

“Longitudinal Studies Parkinson’s Disease Progression Europe”; Parkinson’s Disease Progression Clinical Studies Europe

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longitudinal, observational, cohort

https://pubmed.ncbi.nlm.nih.gov/32758176/

Background: The diagnosis of Parkinson’s Disease (PD) remains a challenge and is currently based on the assessment of clinical symptoms. PD is also a heterogeneous disease with great variability in symptoms, disease course, and response to therapy. There is a general need for a better understanding of this heterogeneity and the interlinked long-term changes in brain function and structure in PD. Over the past years there is increasing interest in the value of new paradigms in Magnetic Resonance Imaging (MRI) and the potential of ultra-high field strength imaging in the diagnostic work-up of PD. With this multimodal 7 T MRI study, our objectives are: 1) To identify distinctive MRI characteristics in PD patients and to create a diagnostic tool based on these differences. 2) To correlate MRI characteristics to clinical phenotype, genetics and progression of symptoms. 3) To detect future imaging biomarkers for disease progression that could be valuable for the evaluation of new therapies.

Methods: The TRACK-PD study is a longitudinal observational study in a cohort of 130 recently diagnosed (≤ 3 years after diagnosis) PD patients and 60 age-matched healthy controls (HC). A 7 T MRI of the brain will be performed at baseline and repeated after 2 and 4 years. Complete assessment of motor, cognitive, neuropsychiatric and autonomic symptoms will be performed at baseline and follow-up visits with wearable sensors, validated questionnaires and rating scales. At baseline a blood DNA sample will also be collected.

Discussion: This is the first longitudinal, observational, 7 T MRI study in PD patients. With this study, an important contribution can be made to the improvement of the current diagnostic process in PD. Moreover, this study will be able to provide valuable information related to the different clinical phenotypes of PD and their correlating MRI characteristics. The long-term aim of this study is to better understand PD and develop new biomarkers for disease progression which may help new therapy development. Eventually, this may lead to predictive models for individual PD patients and towards personalized medicine in the future.

Trial registration: Dutch Trial Register, NL7558 . Registered March 11, 2019.

Keywords: Biomarkers; Cohort studies; Parkinson’s disease; Ultra-high field MRI.

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prospective, longitudinal, single-center cohort study

https://pubmed.ncbi.nlm.nih.gov/31315608/

Abstract
Background: Our understanding of the etiology, pathophysiology, phenotypic diversity, and progression of Parkinson’s disease has stagnated. Consequently, patients do not receive the best care, leading to unnecessary disability, and to mounting costs for society. The Personalized Parkinson Project (PPP) proposes an unbiased approach to biomarker development with multiple biomarkers measured longitudinally. Our main aims are: (a) to perform a set of hypothesis-driven analyses on the comprehensive dataset, correlating established and novel biomarkers to the rate of disease progression and to treatment response; and (b) to create a widely accessible dataset for discovery of novel biomarkers and new targets for therapeutic interventions in Parkinson’s disease.

Methods/design: This is a prospective, longitudinal, single-center cohort study. The cohort will comprise 650 persons with Parkinson’s disease. The inclusion criteria are purposely broad: age ≥ 18 years; and disease duration ≤5 years. Participants are followed for 2 years, with three annual assessments at the study center. Outcomes include a clinical assessment (including motor and neuro-psychological tests), collection of biospecimens (stool, whole blood, and cerebrospinal fluid), magnetic resonance imaging (both structural and functional), and ECG recordings (both 12-lead and Holter). Additionally, collection of physiological and environmental data in daily life over 2 years will be enabled through the Verily Study Watch. All data are stored with polymorphic encryptions and pseudonyms, to guarantee the participants’ privacy on the one hand, and to enable data sharing on the other. The data and biospecimens will become available for scientists to address Parkinson’s disease-related research questions.

Discussion: The PPP has several distinguishing elements: all assessments are done in a single center; inclusion of “real life” subjects; deep and repeated multi-dimensional phenotyping; and continuous monitoring with a wearable device for 2 years. Also, the PPP is powered by privacy and security by design, allowing for data sharing with scientists worldwide respecting participants’ privacy. The data are expected to open the way for important new insights, including identification of biomarkers to predict differences in prognosis and treatment response between patients. Our long-term aim is to improve existing treatments, develop new therapeutic approaches, and offer Parkinson’s disease patients a more personalized disease management approach.

Trial registration: Clinical Trials NCT03364894 . Registered December 6, 2017 (retrospectively registered).

Keywords: Biomarkers; Cohort studies; Disease progression; Parkinson’s disease; Wearable device.

“Longitudinal Studies Parkinson’s Disease Progression Europe”; Parkinson’s Disease Progression Clinical Studies Europe

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cohort study

Germany

https://pubmed.ncbi.nlm.nih.gov/30468694/

Objectives: The objectives of this study were to investigate (1) the annual rate of progression of motor and cognitive symptoms and (2) baseline predictors of different modalities for this progression in early Parkinson’s disease (PD) when compared with healthy controls.

Methods: A total of 135 de novo PD and 109 healthy controls (of the De Novo Parkinson cohort) were investigated at baseline and after 24 and 48 months. To delineate motor progression and cognitive decline, the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale part III (MDS-UPDRS III) and the Mini-Mental Status Examination (MMSE) were selected. Baseline variables used to predict progression included sociodemographic factors, comorbidities, motor/nonmotor symptoms, polysomnography, MRI, and laboratory biomarkers in serum and CSF.

Results: Symptoms worsened over 4 years in PD with an annual change of 1.8 points on the MDS-UPDRS III and 0.2 points on the MMSE. Baseline predictors of worse progression of motor symptoms in PD included male sex, orthostatic blood pressure drop, diagnosis of coronary artery disease, arterial hypertension, elevated serum uric acid, and CSF neurofilament light chain. Predictors of cognitive decline in PD included previous heavy alcohol abuse, current diagnoses of diabetes mellitus, arterial hypertension, elevated periodic limb movement index during sleep, decreased hippocampal volume by MRI, higher baseline levels of uric acid, C-reactive protein, high density lipoprotein (HDL) cholesterol, and glucose levels.

Conclusion: Cardiovascular risk factors, deregulated blood glucose, uric acid metabolism, and inflammation were identified as risk markers for faster disease progression. Our panel of risk parameters needs validation during our continuing follow-up and also in independent patient cohorts. © 2018 International Parkinson and Movement Disorder Society.

Keywords: Parkinson’s disease/parkinsonism; cohort studies; outcome research.

“Longitudinal Studies Parkinson’s Disease Progression Europe”; Parkinson’s Disease Progression Clinical Studies Europe

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Observational

Spain

https://pubmed.ncbi.nlm.nih.gov/31179586/

“Longitudinal Studies Parkinson’s Disease Progression Europe”; Parkinson’s Disease Progression Clinical Studies Europe

“Longitudinal Studies Parkinson’s Disease Progression Europe”; Parkinson’s Disease Progression Clinical Studies Europe

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