Dopa Responsiveness in Parkinson's Disease.

Background: Dopaminergic responsiveness is a defining feature of Parkinson's disease (PD). However, there is limited information on how this evolves over time.

Objectives: To examine serial dopaminergic responses, if there are distinct patterns, and which factors predict these.

Motor Complications in Parkinson's Disease: Results from 3343 Patients Followed for up to 12 Years.

Background: Motor complications are well recognized in Parkinson's disease (PD), but their reported prevalence varies and functional impact has not been well studied.

Objectives: To quantify the presence, severity, impact and associated factors for motor complications in PD.

Methods: Analysis of three large prospective cohort studies of recent-onset PD patients followed for up to 12 years.

Genotype-phenotype correlation in PRKN-associated Parkinson's disease.

Bi-allelic pathogenic variants in PRKN are the most common cause of autosomal recessive Parkinson's disease (PD). 647 patients with PRKN-PD were included in this international study. The pathogenic variants present were characterised and investigated for their effect on phenotype.

Two sample Mendelian Randomisation using an outcome from a multilevel model of disease progression.

Identifying factors that are causes of disease progression, especially in neurodegenerative diseases, is of considerable interest. Disease progression can be described as a trajectory of outcome over time-for example, a linear trajectory having both an intercept (severity at time zero) and a slope (rate of change). A technique for identifying causal relationships between one exposure and one outcome in observational data whilst avoiding bias due to confounding is two sample Mendelian Randomisation (2SMR).

Addressing Comorbidities in People with Parkinson's Disease: Considerations From An Expert Panel.

In the UK, guidance exists to aid clinicians and patients deciding when treatment for Parkinson's disease (PD) should be initiated and which therapies to consider. National Institute for Health and Care Excellence (NICE) guidance recommends that before starting PD treatment clinicians should discuss the following: the patient's individual clinical circumstances; lifestyle; preferences; needs and goals; as well as the potential benefits and harms of the different drug classes. Individualization of medicines and management in PD significantly improves patients' outcomes and quality of life.

Genome-wide Analysis of Motor Progression in Parkinson Disease.

Background And Objectives: The genetic basis of Parkinson disease (PD) motor progression is largely unknown. Previous studies of the genetics of PD progression have included small cohorts and shown a limited overlap with genetic PD risk factors from case-control studies. Here, we have studied genomic variation associated with PD motor severity and early-stage progression in large longitudinal cohorts to help to define the biology of PD progression and potential new drug targets.

Genetic meta-analysis of levodopa induced dyskinesia in Parkinson's disease.

Importance: Forty percent of Parkinson's disease patients develop levodopa-induced-dyskinesia (LiD) within 4 years of starting levodopa. The genetic basis of LiD remains poorly understood, and there have been few well powered studies.

Objective: To discover common genetic variants in the PD population that increase the probability of developing LiD.

Predicting Ambulatory Capacity in Parkinson's Disease to Analyze Progression, Biomarkers, and Trial Design.

Background: In Parkinson's disease (PD), gait and balance is impaired, relatively resistant to available treatment and associated with falls and disability. Predictive models of ambulatory progression could enhance understanding of gait/balance disturbances and aid in trial design.

Objectives: To predict trajectories of ambulatory abilities from baseline clinical data in early PD, relate trajectories to clinical milestones, compare biomarkers, and evaluate trajectories for enrichment of clinical trials.

Striatal Dopamine Loss in Early Parkinson's Disease: Systematic Review and Novel Analysis of Dopamine Transporter Imaging.

Background: Neuropathological studies, based on small samples, suggest that symptoms of Parkinson's disease (PD) emerge when dopamine/nigrostriatal loss is around 50-80%. Functional neuroimaging can be applied in larger numbers during life, which allows analysis of the extent of dopamine loss more directly.

Objective: To quantify dopamine transporter (DaT) activity by neuroimaging in early PD.

The Clinical Development of Levodopa Inhalation Powder.

Oral levodopa is the most effective treatment for Parkinson disease, but OFF periods emerge over time. Gastrointestinal dysfunction and food effects impact levodopa absorption, contributing to unpredictable control of OFF periods. Inhaled levodopa powder (Inbrija) is approved for on-demand treatment of OFF periods in patients receiving oral levodopa-dopa decarboxylase inhibitors.

Identification of a possible proteomic biomarker in Parkinson's disease: discovery and replication in blood, brain and cerebrospinal fluid.

Biomarkers to aid diagnosis and delineate the progression of Parkinson's disease are vital for targeting treatment in the early phases of the disease. Here, we aim to discover a multi-protein panel representative of Parkinson's and make mechanistic inferences from protein expression profiles within the broader objective of finding novel biomarkers. We used aptamer-based technology (SomaLogic®) to measure proteins in 1599 serum samples, 85 cerebrospinal fluid samples and 37 brain tissue samples collected from two observational longitudinal cohorts (the Oxford Parkinson's Disease Centre and Tracking Parkinson's) and the Parkinson's Disease Brain Bank, respectively.

Universal clinical Parkinson's disease axes identify a major influence of neuroinflammation.

Background: There is large individual variation in both clinical presentation and progression between Parkinson's disease patients. Generation of deeply and longitudinally phenotyped patient cohorts has enormous potential to identify disease subtypes for prognosis and therapeutic targeting.

Methods: Replicating across three large Parkinson's cohorts (Oxford Discovery cohort (n = 842)/Tracking UK Parkinson's study (n = 1807) and Parkinson's Progression Markers Initiative (n = 472)) with clinical observational measures collected longitudinally over 5-10 years, we developed a Bayesian multiple phenotypes mixed model incorporating genetic relationships between individuals able to explain many diverse clinical measurements as a smaller number of continuous underlying factors ("phenotypic axes").

Association between the LRP1B and APOE loci and the development of Parkinson's disease dementia.

Parkinson's disease is one of the most common age-related neurodegenerative disorders. Although predominantly a motor disorder, cognitive impairment and dementia are important features of Parkinson's disease, particularly in the later stages of the disease. However, the rate of cognitive decline varies among Parkinson's disease patients, and the genetic basis for this heterogeneity is incompletely understood.

Genetics of validated Parkinson's disease subtypes in the Oxford Discovery and Tracking Parkinson's cohorts.

Objectives: To explore the genetics of four Parkinson's disease (PD) subtypes that have been previously described in two large cohorts of patients with recently diagnosed PD. These subtypes came from a data-driven cluster analysis of phenotypic variables.

Methods: We looked at the frequency of genetic mutations in glucocerebrosidase (GBA) and leucine-rich repeat kinase 2 against our subtypes.

The Impact of Type 2 Diabetes in Parkinson's Disease.

Background: Type 2 diabetes (T2DM) is an established risk factor for developing Parkinson's disease (PD), but its effect on disease progression is not well understood.

Objective: The aim of this study was to investigate the influence of T2DM on aspects of disease progression in PD.

Methods: We analyzed data from the Tracking Parkinson's study to examine the effects of comorbid T2DM on PD progression and quality of life by comparing symptom severity scores assessing a range of motor and nonmotor symptoms.

Combining biomarkers for prognostic modelling of Parkinson's disease.

Background: Patients with Parkinson's disease (PD) have variable rates of progression. More accurate prediction of progression could improve selection for clinical trials. Although some variance in clinical progression can be predicted by age at onset and phenotype, we hypothesise that this can be further improved by blood biomarkers.

Neuromelanin-MRI to Quantify and Track Nigral Depigmentation in Parkinson's Disease: A Multicenter Longitudinal Study Using Template-Based Standardized Analysis.

Background: Clinical diagnosis and monitoring of Parkinson's disease (PD) remain challenging because of the lack of an established biomarker. Neuromelanin-magnetic resonance imaging (NM-MRI) is an emerging biomarker of nigral depigmentation indexing the loss of melanized neurons but has unknown prospective diagnostic and tracking performance in multicenter settings.

Objectives: The aim was to investigate the diagnostic accuracy of NM-MRI in early PD in a multiprotocol setting and to determine and compare serial NM-MRI changes in PD and controls.

Genetic Stratification of Age-Dependent Parkinson's Disease Risk by Polygenic Hazard Score.

Background: Parkinson's disease (PD) is a highly age-related disorder, where common genetic risk variants affect both disease risk and age at onset. A statistical approach that integrates these effects across all common variants may be clinically useful for individual risk stratification. A polygenic hazard score methodology, leveraging a time-to-event framework, has recently been successfully applied in other age-related disorders.

Optimising classification of Parkinson's disease based on motor, olfactory, neuropsychiatric and sleep features.

Olfactory loss, motor impairment, anxiety/depression, and REM-sleep behaviour disorder (RBD) are prodromal Parkinson's disease (PD) features. PD risk prediction models typically dichotomize test results and apply likelihood ratios (LRs) to scores above and below cut-offs. We investigate whether LRs for specific test values could enhance classification between PD and controls.