The clinical heterogeneity of Parkinson's disease and its therapeutic implications

Risk for Mortality in High versus Low Antiparkinsonian Therapy Dose During the First Year of Parkinson's Disease: A Real-World Study

INTRODUCTION

Early, simple predictors for long-term survival in Parkinson's disease (PD) may help identify patients at elevated risk and are crucial for more personalized treatment.

METHODS

This large, retrospective study examined whether higher levodopa equivalent daily dose (LEDD) a year after diagnosis predicts long-term survival.

RESULTS

Mortality risk was increased among 292 patients receiving ≥ 600 mg LEDD versus 2233 patients receiving < 600 mg LEDD (hazard ratio 1.5; 95% confidence interval 1.3-1.7), particularly among patients aged < 75 years (1.8; 1.4-2.4).

CONCLUSION

In PD, higher LEDD can be an early risk marker of increased mortality, probably because it reflects more severe disease.

Client Perceptions of the Individual Packer Managing Fatigue Program: A Mixed-Method Evaluation

Fatigue is common, but under-recognized in Parkinson's disease (PD), with limited treatment options. The aim of this study is to explore the experience of people with PD (PwPD) regarding content and delivery of the individual Packer Managing Fatigue program. This mixed-method study (n = 12) was conducted concurrently with a pilot randomized controlled trial. Data were collected using questionnaires, interviews, and focus groups. Five themes emerged: the program is helpful; the program has strengths; areas for improvement; individual online delivery is feasible; and more support from occupational therapist would be helpful. Quantitative findings confirmed feasibility with high ratings on questionnaires and confidence to use learned strategies. The findings inform future implementation of the Packer Managing Fatigue program and contribute to understanding the needs of PwPD. Future studies might explore program's effectiveness as stand-alone treatment or in combination with other approaches. Tailoring fatigue programs to PwPD's unique needs and characteristics of PD fatigue is suggested.

Parkinson's Disease Progression and Exposure to Contaminated Water at Camp Lejeune

BACKGROUND

We recently reported an increased risk of Parkinson's disease (PD) in service members who resided at Marine Base Camp Lejeune, North Carolina, when water supplies were contaminated with trichloroethylene and other volatile organic compounds (VOCs). Prior studies suggest that environmental exposures may affect PD phenotype or progression, but this has not been reported for VOCs.

OBJECTIVE

The objective of this study was to test whether PD progression is faster in individuals exposed to VOCs in water at Camp Lejeune.

METHODS

A cohort of 172,128 marines residing at Camp Lejeune between 1975 and 1985 was previously assembled. We identified individuals with PD in Veterans Health Administration and Medicare databases between 2000 and 2021. Using estimates derived by the US Agency for Toxic Substances and Disease Registry, we classified individuals as exposed or unexposed to VOCs in residential water. We used Kaplan-Meier and Cox regression models to test differences between exposed and unexposed groups in the time from PD diagnosis until psychosis, fracture, fall, or death.

RESULTS

Among 270 persons with PD, 177 (65.6%) were exposed to VOCs in residential water. Median cumulative exposure was 4970 μg/L-months, >50-fold the permissible level. Time until psychosis, fracture, and fall were all shorter in the exposed group, with adjusted hazard ratios (HRs) exceeding 2: psychosis HR, 2.19 (95% confidence interval [CI]: 0.99-4.83); fracture HR, 2.44 (95% CI: 0.91-6.55); and fall HR, 2.64 (95% CI: 0.97-7.21). A significant dose response was observed for time to fall (P trend, 0.032). No differences were observed for time until death.

CONCLUSIONS

PD progression may be faster in persons exposed to trichloroethylene and other VOCs in water decades earlier. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Empowering the management of early-onset Parkinsons' disease: The role of technology

Early-onset Parkinson's disease (EOPD) is defined as PD with an age of onset after 21 years of age but before 50 years. It displays many important differences to late-onset PD in terms of its pathology, phenotype, presentation and disease course, all of which have consequences for achieving a definitive diagnosis, the choice of therapy and approach to management. Studies show that this younger population is keen to embrace digital technologies as part of PD care, being familiar with using digital tools in their daily lives. Although most of the literature relating to the use of technology in PD applies to the broad population, this review focuses on evidence and potential benefits of the use of digital technologies to support clinical management in EOPD as well as its value in empowering patients to achieve self-management and in improving their quality of life. Digital technologies also have important and increasing roles in providing telehealth, including rehabilitation strategies for motor and non-motor PD symptoms. EOPD is known to be associated with a higher risk of motor fluctuations, so technologies such as wearable sensors have a valuable role for monitoring symptoms, providing timely feedback, and informing treatment decisions. In addition, digital technologies allow easy provision and equitable access to education and networking opportunities that will enable patients to have a better understanding of their condition.

Emerging perspectives on precision therapy for Parkinson's disease: multidimensional evidence leading to a new breakthrough in personalized medicine

PD is a prevalent and progressive neurodegenerative disorder characterized by both motor and non-motor symptoms. Genes play a significant role in the onset and progression of the disease. While the complexity and pleiotropy of gene expression networks have posed challenges for gene-targeted therapies, numerous pathways of gene variant expression show promise as therapeutic targets in preclinical studies, with some already in clinical trials. With the recognition of the numerous genes and complex pathways that can influence PD, it may be possible to take a novel approach to choose a treatment for the condition. This approach would be based on the symptoms, genomics, and underlying mechanisms of the disease. We discuss the utilization of emerging genetic and pathological knowledge of PD patients to categorize the disease into subgroups. Our long-term objective is to generate new insights for the therapeutic approach to the disease, aiming to delay and treat it more effectively, and ultimately reduce the burden on individuals and society.

Radiomics score derived from T1-w/T2-w ratio image can predict motor symptom progression in Parkinson's disease

OBJECTIVES

To clarify the association between a radiomics score (Rad-score) derived from T1-weighted signal intensity to T2-weighted signal intensity (T1-w/T2-w) ratio images and the progression of motor symptoms in Parkinson's disease (PD).

MATERIALS AND METHODS

This retrospective study included patients with PD enrolled in the Parkinson's Progression Markers Initiative. The Movement Disorders Society-Unified Parkinson's Disease Rating Scale Part III score ≥ 33 and/or Hoehn and Yahr stage ≥ 3 indicated motor function decline. The Rad-score was constructed using radiomics features extracted from T1-w/T2-w ratio images. The Kaplan-Meier analysis and Cox regression analyses were used to assess the time differences in motor function decline between the high and low Rad-score groups.

RESULTS

A total of 171 patients with PD were divided into training (n = 101, mean age at baseline, 61.6 ± 9.3 years) and testing (n = 70, mean age at baseline, 61.6 ± 10 years). The patients in the high Rad-score group had a shorter time to motor function decline than those in the low Rad-score group in the training dataset (log-rank test, p < 0.001) and testing dataset (log-rank test, p < 0.001). The multivariate Cox regression using the Rad-score and clinical factors revealed a significant association between the Rad-score and motor function decline in the training dataset (HR = 2.368, 95%CI:1.423-3.943, p < 0.001) and testing dataset (HR = 2.931, 95%CI:1.472-5.837, p = 0.002).

CONCLUSION

Rad-scores based on radiomics features derived from T1-w/T2-w ratio images were associated with the progression of motor symptoms in PD.

CLINICAL RELEVANCE STATEMENT

The radiomics score derived from the T1-weighted/T2-weighted ratio images offers a predictive tool for assessing the progression of motor symptom in patients with PD.

KEY POINTS

Radiomics score derived from T1-weighted/T2-weighted ratio images is correlated with the motor symptoms of Parkinson's disease. A high radiomics score correlated with faster motor function decline in patients with Parkinson's disease. The proposed radiomics score offers predictive insight into the progression of motor symptoms of Parkinson's disease.

Profiling people with Parkinson's disease at risk of cognitive decline: Insights from PPMI and ICICLE-PD data

Introduction

A subset of people with Parkinson's disease (PD) develop dementia faster than others. We aimed to profile PD cognitive subtypes at risk of dementia based on their rate of cognitive decline.

Method

Latent class mixed models stratified subtypes in Parkinson's Progression Markers Initiative (PPMI) (N = 770) and ICICLE-PD (N = 212) datasets based on their decline in the Montreal Cognitive Assessment over at least 4 years. Baseline demographic and cognitive data at diagnosis were compared between subtypes to determine their clinical profile.

Results

Four subtypes were identified: two with stable cognition, one with steady decline, and one with rapid decline. Performance on Judgement of Line Orientation, but not category fluency, was associated with a steady decline in the PPMI dataset, and deficits in category fluency, but not visuospatial function, were associated with a steady decline in the ICICLE-PD dataset.

Discussion

People with PD susceptible to cognitive decline demonstrate unique clinical profiles at diagnosis, although this differed between cohorts.

Highlights

Four cognitive subtypes were revealed in two Parkinson's disease samples.Unique profiles of cognitive impairment were related to cognitive decline.Judgement of Line Orientation/category fluency predictive of steady decline.Global deficits related to rapid cognitive decline and increased dementia risk.

Exploring the experiences, priorities and preferences of people living with Parkinson's on exercise and physical activity promotion in the UK

BACKGROUND

People with Parkinson's (PwP) want access to timely, relevant, and specific exercise and physical activity (PA) information to enable them to manage their symptoms and maintain wellbeing and quality of life. Research that promotes exercise in this population group is limited. Little is also known about the clinical practice around PA promotion in this population, especially around the time of diagnosis.

OBJECTIVE

To explore the experiences, preferences, and priorities of PwP around exercise and PA promotion and assess their knowledge on these topics.

METHODS

A cross-sectional online survey for PwP in the United Kingdom was conducted from July to December 2021.

RESULTS

430 participants started the survey and 405 completed it. Participants had a mean age of 65.1 (±9.2) and had been living with Parkinson's for a varying time (up to 2 years = 38%, up to 6 years = 39% and for 7 or more years = 23%). Most participants reported they had not received an education (68%; n = 276) or exercise intervention (54%; n = 217) as part of their routine management by the National Health Service (NHS) since diagnosis and had sought services privately. Knowledge of the overall benefits of exercise was good, however participants lacked specific knowledge on the impact of Parkinson's Disease (PD) on posture, falls and muscle strength. 90% of participants reported they would participate in an exercise and PA education interventions.

CONCLUSIONS

PwP want exercise and PA education interventions that provide knowledge, skills and access to opportunities that enable participation. For the majority, these interventions have not been provided as part of their routine care pathway. To align with the priorities and preferences of PwP, interventions should be offered around the time of diagnosis, include content that is relevant and specific to how exercise and PA can mitigate symptoms of PD and should be delivered in person or online in a group setting.

Brain network centrality and connectivity are associated with clinical subtypes and disease progression in Parkinson's disease

To investigate brain network centrality and connectivity alterations in different Parkinson's disease (PD) clinical subtypes using resting-state functional magnetic resonance imaging (RS-fMRI), and to explore the correlation between baseline connectivity changes and the clinical progression. Ninety-two PD patients were enrolled at baseline, alongside 38 age- and sex-matched healthy controls. Of these, 85 PD patients underwent longitudinal assessments with a mean of 2.75 ± 0.59 years. Two-step cluster analysis integrating comprehensive motor and non-motor manifestations was performed to define PD subtypes. Degree centrality (DC) and secondary seed-based functional connectivity (FC) were applied to identify brain network centrality and connectivity changes among groups. Regression analysis was used to explore the correlation between baseline connectivity changes and clinical progression. Cluster analysis identified two main PD subtypes: mild PD and moderate PD. Two different subtypes within the mild PD were further identified: mild motor-predominant PD and mild-diffuse PD. Accordingly, the disrupted DC and seed-based FC in the left inferior frontal orbital gyrus and left superior occipital gyrus were severe in moderate PD. The DC and seed-based FC alterations in the right gyrus rectus and right postcentral gyrus were more severe in mild-diffuse PD than in mild motor-predominant PD. Moreover, disrupted DC were associated with clinical manifestations at baseline in patients with PD and predicted motor aspects progression over time. Our study suggested that brain network centrality and connectivity changes were different among PD subtypes. RS-fMRI holds promise to provide an objective assessment of subtype-related connectivity changes and predict disease progression in PD.

Novel gene signatures predicting and immune infiltration analysis in Parkinson's disease: based on combining random forest with artificial neural network

BACKGROUND

Parkinson's disease (PD) ranks as the second most prevalent neurodegenerative disorder globally, and its incidence is rapidly rising. The diagnosis of PD relies on clinical characteristics. Although current treatments aim to alleviate symptoms, they do not effectively halt the disease's progression. Early detection and intervention hold immense importance. This study aimed to establish a new PD diagnostic model.

METHODS

Data from a public database were adopted for the construction and validation of a PD diagnostic model with random forest and artificial neural network models. The CIBERSORT platform was applied for the evaluation of immune cell infiltration in PD. Quantitative real-time PCR was performed to verify the accuracy and reliability of the bioinformatics analysis results.

RESULTS

Leveraging existing gene expression data from the Gene Expression Omnibus (GEO) database, we sifted through differentially expressed genes (DEGs) in PD and identified 30 crucial genes through a random forest classifier. Furthermore, we successfully designed a novel PD diagnostic model using an artificial neural network and verified its diagnostic efficacy using publicly available datasets. Our research also suggests that mast cells may play a significant role in the onset and progression of PD.

CONCLUSION

This work developed a new PD diagnostic model with machine learning techniques and suggested the immune cells as a potential target for PD therapy.

Progression subtypes in Parkinson's disease identified by a data-driven multi cohort analysis

The progression of Parkinson's disease (PD) is heterogeneous across patients, affecting counseling and inflating the number of patients needed to test potential neuroprotective treatments. Moreover, disease subtypes might require different therapies. This work uses a data-driven approach to investigate how observed heterogeneity in PD can be explained by the existence of distinct PD progression subtypes. To derive stable PD progression subtypes in an unbiased manner, we analyzed multimodal longitudinal data from three large PD cohorts and performed extensive cross-cohort validation. A latent time joint mixed-effects model (LTJMM) was used to align patients on a common disease timescale. Progression subtypes were identified by variational deep embedding with recurrence (VaDER). In each cohort, we identified a fast-progressing and a slow-progressing subtype, reflected by different patterns of motor and non-motor symptoms progression, survival rates, treatment response, features extracted from DaTSCAN imaging and digital gait assessments, education, and Alzheimer's disease pathology. Progression subtypes could be predicted with ROC-AUC up to 0.79 for individual patients when a one-year observation period was used for model training. Simulations demonstrated that enriching clinical trials with fast-progressing patients based on these predictions can reduce the required cohort size by 43%. Our results show that heterogeneity in PD can be explained by two distinct subtypes of PD progression that are stable across cohorts. These subtypes align with the brain-first vs. body-first concept, which potentially provides a biological explanation for subtype differences. Our predictive models will enable clinical trials with significantly lower sample sizes by enriching fast-progressing patients.

Structural underpinnings and long-term effects of resilience in Parkinson's disease

Resilience in neuroscience generally refers to an individual's capacity to counteract the adverse effects of a neuropathological condition. While resilience mechanisms in Alzheimer's disease are well-investigated, knowledge regarding its quantification, neurobiological underpinnings, network adaptations, and long-term effects in Parkinson's disease is limited. Our study involved 151 Parkinson's patients from the Parkinson's Progression Marker Initiative Database with available Magnetic Resonance Imaging, Dopamine Transporter Single-Photon Emission Computed Tomography scans, and clinical information. We used an improved prediction model linking neuropathology to symptom severity to estimate individual resilience levels. Higher resilience levels were associated with a more active lifestyle, increased grey matter volume in motor-associated regions, a distinct structural connectivity network and maintenance of relative motor functioning for up to a decade. Overall, the results indicate that relative maintenance of motor function in Parkinson's patients may be associated with greater neuronal substrate, allowing higher tolerance against neurodegenerative processes through dynamic network restructuring.

The STRAT-PARK cohort: A personalized initiative to stratify Parkinson's disease

The STRAT-PARK initiative aims to provide a platform for stratifying Parkinson's disease (PD) into biological subtypes, using a bottom-up, multidisciplinary biomarker-based and data-driven approach. PD is a heterogeneous entity, exhibiting high interindividual clinicopathological variability. This diversity suggests that PD may encompass multiple distinct biological entities, each driven by different molecular mechanisms. Molecular stratification and identification of disease subtypes is therefore a key priority for understanding and treating PD. STRAT-PARK is a multi-center longitudinal cohort aiming to recruit a total of 2000 individuals with PD and neurologically healthy controls from Norway and Canada, for the purpose of identifying molecular disease subtypes. Clinical assessment is performed annually, whereas biosampling, imaging, and digital and neurophysiological phenotyping occur every second year. The unique feature of STRAT-PARK is the diversity of collected biological material, including muscle biopsies and platelets, tissues particularly useful for mitochondrial biomarker research. Recruitment rate is ∼150 participants per year. By March 2023, 252 participants were included, comprising 204 cases and 48 controls. STRAT-PARK is a powerful stratification initiative anticipated to become a global research resource, contributing to personalized care in PD.

Cognitive function in different motor subtypes of Parkinson's disease: A systematic review protocol

Background and Aims

As the fastest-growing neurological disorder globally, a better understanding of Parkinson's disease (PD) is needed to improve patient outcomes and reduce the increasing economic and healthcare burden associated with the disease. Whilst classified as a movement disorder, this disease is highly heterogeneous, encompassing a broad range of both motor and non-motor symptoms (NMS). Cognitive impairment, presenting as either mild cognitive impairment or PD-dementia, is one of the most prevalent and disabling NMS. To better understand heterogeneity in PD, researchers have sought to identify subtypes of individuals who share similar symptom profiles. To date, this research has predominantly focused on motor subtyping, with many studies comparing these motor subtypes on non-motor outcomes, such as cognitive impairment. However, despite evidence of a motor-cognitive relationship in healthy aging, findings regarding the presence of a motor-cognitive relationship in PD are inconsistent. In our proposed systematic review, we will investigate motor subtyping studies that have evaluated the relationship between motor and cognitive function in PD. We aim to examine what is currently known about the relationship between motor and cognitive impairment in PD and evaluate the state of the field with respect to the subtyping methods and quality of cognitive assessment tools used.

Methods

Systematic literature searches will be conducted in PubMed, PsycINFO, CINAHL, Scopus, and Web of Science.

Results

Results will be synthesized using meta-analysis and, where meta-analysis is not feasible, narrative synthesis.

Conclusion

Despite the preponderance of motor subtyping research in PD, our study will be the first to systematically review evidence regarding the association between motor subtypes and cognitive impairment. Understanding the nature of the motor-cognitive relationship in PD may lead to important insights regarding shared underlying disease pathology, which would have significant implications for early diagnosis, prognosis, and treatment of cognitive impairment in PD.

From the Gut to the Brain: Is Microbiota a New Paradigm in Parkinson's Disease Treatment?

Parkinson's disease (PD) is recognized as the second most prevalent primary chronic neurodegenerative disorder of the central nervous system. Clinically, PD is characterized as a movement disorder, exhibiting an incidence and mortality rate that is increasing faster than any other neurological condition. In recent years, there has been a growing interest concerning the role of the gut microbiota in the etiology and pathophysiology of PD. The establishment of a brain-gut microbiota axis is now real, with evidence denoting a bidirectional communication between the brain and the gut microbiota through metabolic, immune, neuronal, and endocrine mechanisms and pathways. Among these, the vagus nerve represents the most direct form of communication between the brain and the gut. Given the potential interactions between bacteria and drugs, it has been observed that the therapies for PD can have an impact on the composition of the microbiota. Therefore, in the scope of the present review, we will discuss the current understanding of gut microbiota on PD and whether this may be a new paradigm for treating this devastating disease.

Mitochondrial complex I deficiency stratifies idiopathic Parkinson's disease

Idiopathic Parkinson's disease (iPD) is believed to have a heterogeneous pathophysiology, but molecular disease subtypes have not been identified. Here, we show that iPD can be stratified according to the severity of neuronal respiratory complex I (CI) deficiency, and identify two emerging disease subtypes with distinct molecular and clinical profiles. The CI deficient (CI-PD) subtype accounts for approximately a fourth of all cases, and is characterized by anatomically widespread neuronal CI deficiency, a distinct cell type-specific gene expression profile, increased load of neuronal mtDNA deletions, and a predilection for non-tremor dominant motor phenotypes. In contrast, the non-CI deficient (nCI-PD) subtype exhibits no evidence of mitochondrial impairment outside the dopaminergic substantia nigra and has a predilection for a tremor dominant phenotype. These findings constitute a step towards resolving the biological heterogeneity of iPD with implications for both mechanistic understanding and treatment strategies.

Common genetic risk for Parkinson's disease and dysfunction of the endo-lysosomal system

Parkinson's disease is a progressive neurological disorder, characterized by prominent movement dysfunction. The past two decades have seen a rapid expansion of our understanding of the genetic basis of Parkinson's, initially through the identification of monogenic forms and, more recently, through genome-wide association studies identifying common risk variants. Intriguingly, a number of cellular pathways have emerged from these analysis as playing central roles in the aetiopathogenesis of Parkinson's. In this review, the impact of data deriving from genome-wide analyses for Parkinson's upon our functional understanding of the disease will be examined, with a particular focus on examples of endo-lysosomal and mitochondrial dysfunction. The challenges of moving from a genetic to a functional understanding of common risk variants for Parkinson's will be discussed, with a final consideration of the current state of the genetic architecture of the disorder. This article is part of a discussion meeting issue 'Understanding the endo-lysosomal network in neurodegeneration'.

An interactive web application to identify early Parkinsonian non-tremor-dominant subtypes

BACKGROUND

Parkinson's disease (PD) patients with tremor-dominant (TD) and non-tremor-dominant (NTD) subtypes exhibit heterogeneity. Rapid identification of different motor subtypes may help to develop personalized treatment plans.

METHODS

The data were acquired from the Parkinson's Disease Progression Marker Initiative (PPMI). Following the identification of predictors utilizing recursive feature elimination (RFE), seven classical machine learning (ML) models, including logistic regression, support vector machine, decision tree, random forest, extreme gradient boosting, etc., were trained to predict patients' motor subtypes, evaluating the performance of models through the area under the receiver operating characteristic curve (AUC) and validating by the follow-up data.

RESULTS

The feature subset engendered by RFE encompassed 20 features, comprising some clinical assessments and cerebrospinal fluid α-synuclein (CSF α-syn). ML models fitted in the RFE subset performed better in the test and validation sets. The best performing model was support vector machines with the polynomial kernel (P-SVM), achieving an AUC of 0.898. Five-fold repeated cross-validation showed the P-SVM model with CSF α-syn performed better than the model without CSF α-syn (P = 0.034). The Shapley additive explanation plot (SHAP) illustrated that how the levels of each feature affect the predicted probability as NTD subtypes.

CONCLUSION

An interactive web application was developed based on the P-SVM model constructed from feature subset by RFE. It can identify the current motor subtypes of PD patients, making it easier to understand the status of patients and develop personalized treatment plans.

Time-resolved quantification of fine hand movements as a proxy for evaluating bradykinesia-induced motor dysfunction

Bradykinesia is a behavioral manifestation that contributes to functional dependencies in later life. However, the current state of bradykinesia indexing primarily relies on subjective, time-averaged categorizations of motor deficits, which often yield poor reliability. Herein, we used time-resolved analyses of accelerometer recordings during standardized movements, data-driven factor analyses, and linear mixed effects models (LMEs) to quantitatively characterize general, task- and therapy-specific indices of motor impairment in people with Parkinson's disease (PwP) currently undergoing treatment for bradykinesia. Our results demonstrate that single-trial, accelerometer-based features of finger-tapping and rotational hand movements were significantly modulated by divergent therapeutic regimens. Further, these features corresponded well to current gold standards for symptom monitoring, with more precise predictive capacities of bradykinesia-specific declines achieved when considering kinematic features from diverse movement types together, rather than in isolation. Herein, we report data-driven, sample-specific kinematic profiles of diverse movement types along a continuous spectrum of motor impairment, which importantly, preserves the temporal scale for which biomechanical fluctuations in motor deficits evolve in humans. Therefore, this approach may prove useful for tracking bradykinesia-induced motor decline in aging populations the future.

Hippocampal resting-state connectivity is associated with posterior-cortical cognitive impairment in Parkinson's disease

AIM

Frontal and posterior-cortical cognitive subtypes in Parkinson's disease (PD) present with executive/attention and memory/visuospatial deficits, respectively. As the posterior-cortical subtype is predicted to progress rapidly toward dementia, the present study aimed to explore biological markers of this group using resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS

K-means cluster analysis delineated subtypes (cognitively intact, frontal, posterior-cortical, and globally impaired) among 85 people with PD. A subset of PD participants (N = 42) and 20 healthy controls (HCs) underwent rs-fMRI. Connectivity of bilateral hippocampi with regions of interest was compared between posterior-cortical, cognitively intact, and HC participants using seed-based analysis, controlling for age. Exploratory correlations were performed between areas of interest from the group analysis and a series of cognitive tests.

RESULTS

The posterior-cortical subtype (N = 19) showed weaker connectivity between the left hippocampus and right anterior temporal fusiform cortex compared to the cognitively intact (N = 11) group, p-false discovery rate (FDR) = .01, and weaker connectivity between bilateral hippocampi and most fusiform regions compared to HCs (N = 20). No differences were found between HCs and cognitively intact PD. Exploratory analyses revealed strongest associations between connectivity of the right anterior temporal fusiform cortex and left hippocampus with category fluency (p-FDR = .01).

CONCLUSION

Results suggest that weakened connectivity between the hippocampus and fusiform region is a unique characteristic of posterior-cortical cognitive deficits in PD. Further exploration of hippocampal and fusiform functional integrity as a marker of cognitive decline in PD is warranted.

Exercise and physical activity promotion for people newly diagnosed with Parkinson's disease: a UK survey exploring current practice and the views of healthcare professionals

OBJECTIVES

Exercise and physical activity (PA) are increasingly recognized as important components in the management of Parkinson's disease (PD). Their promotion at diagnosis is essential for better management of symptoms and overall well-being. Healthcare professionals (HCPs) are pivotal to the promotion of exercise and PA, but there is limited guidance on the content of such interventions. This study describes current practice, and explores views of HCPs around PA and exercise promotion at diagnosis for people with PD (PwP) DESIGN: A cross-sectional study using an anonymous online survey.

PARTICIPANTS

HCPs working with PwP in the UK.

RESULTS

Twenty-nine doctors, 17 nurses and 106 physiotherapists completed the survey. All nurses, 99% of physiotherapists and 72% of doctors reported that they always promote exercise and PA during clinic appointments. HCPs identified how PA impacts PD symptoms, evidence on the role of exercise, and signposting to support groups as core topics in PA promotion for PwP. However, these topics are mainly addressed during physiotherapy appointments. Referrals to physiotherapy occur most frequently when PwP experience falls or mobility issues, rather than at diagnosis. HCPs (52% doctors and 41% of nurses) identified lack of confidence as a barrier to prescribing exercise to PwP.

CONCLUSION

The importance of promoting PA at diagnosis is widely acknowledged by HCPs. There are variations between disciplines in terms of the tools used, and the timing and duration of interventions. Previously identified barriers to exercise promotion were also found in this study, and should be explored further in order to aid the implementation of effective interventions.

Protein-protein interactions regulating α-synuclein pathology

Parkinson's disease (PD) is a neurodegenerative disease characterized by the degeneration of dopaminergic neurons in the substantia nigra pars compacta (SNpc) and the formation of Lewy bodies (LBs). The main proteinaceous component of LBs is aggregated α-synuclein (α-syn). However, the mechanisms underlying α-syn aggregation are not yet fully understood. Converging lines of evidence indicate that, under certain pathological conditions, various proteins can interact with α-syn and regulate its aggregation. Understanding these protein-protein interactions is crucial for unraveling the molecular mechanisms contributing to PD pathogenesis. In this review we provide an overview of the current knowledge on protein-protein interactions that regulate α-syn aggregation. Additionally, we briefly summarize the methods used to investigate the influence of protein-protein interactions on α-syn aggregation and propagation.

Human serum-derived α-synuclein auto-antibodies mediate NMDA receptor-dependent degeneration of CNS neurons

BACKGROUND

Presence of autoantibodies against α-synuclein (α-syn AAb) in serum of the general population has been widely reported. That such peripheral factors may be involved in central nervous system pathophysiology was demonstrated by detection of immunoglobulins (IgGs) in cerebrospinal fluid and brain of Parkinson's disease (PD) patients. Thus, blood-borne IgGs may reach the brain parenchyma through an impaired blood-brain barrier (BBB).

FINDINGS

The present study aims to evaluate the patho-physiological impact of α-syn AAbs on primary brain cells, i.e., on spontaneously active neurons and on astrocytes. Exposure of neuron-astrocyte co-cultures to human serum containing α-syn AAbs mediated a dose-dependent reduction of spontaneous neuronal activity, and subsequent neurodegeneration. Removal specifically of α-syn AAbs from the serum prevented neurotoxicity, while purified, commercial antibodies against α-syn mimicked the neurodegenerative effect. Mechanistically, we found a strong calcium flux into neurons preceding α-syn AAbs-induced cell death, specifically through NMDA receptors. NMDA receptor antagonists prevented neurodegeneration upon treatment with α-syn (auto)antibodies. α-syn (auto)antibodies did not affect astrocyte survival. However, in presence of α-syn, astrocytes reacted to α-syn antibodies by secretion of the chemokine RANTES.

CONCLUSION

These findings provide a novel basis to explain how a combination of BBB impairment and infiltration of IgGs targeting synuclein may contribute to neurodegeneration in PD and argue for caution with α-syn immunization therapies for treatment of PD.

PINK1 is a target of T cell responses in Parkinson's disease

Parkinson's disease (PD) is associated with autoimmune T cells that recognize the protein alpha-synuclein in a subset of individuals. Multiple neuroantigens are targets of autoinflammatory T cells in classical central nervous system autoimmune diseases such as multiple sclerosis (MS). Here, we explored whether additional autoantigenic targets of T cells in PD. We generated 15-mer peptide pools spanning several PD-related proteins implicated in PD pathology, including GBA, SOD1, PINK1, parkin, OGDH, and LRRK2. Cytokine production (IFNγ, IL-5, IL-10) against these proteins was measured using a fluorospot assay and PBMCs from patients with PD and age-matched healthy controls. This approach identified unique epitopes and their HLA restriction from the mitochondrial-associated protein PINK1, a regulator of mitochondrial stability, as an autoantigen targeted by T cells. The T cell reactivity was predominantly found in male patients with PD, which may contribute to the heterogeneity of PD. Identifying and characterizing PINK1 and other autoinflammatory targets may lead to antigen-specific diagnostics, progression markers, and/or novel therapeutic strategies for PD.

Performance of the Dreem 2 EEG headband, relative to polysomnography, for assessing sleep in Parkinson's disease

GOAL AND AIMS

To pilot the feasibility and evaluate the performance of an EEG wearable for measuring sleep in individuals with Parkinson's disease.

FOCUS TECHNOLOGY

Dreem Headband, Version 2.

REFERENCE TECHNOLOGY

Polysomnography.

SAMPLE

Ten individuals with Parkinson's disease.

DESIGN

Individuals wore Dreem Headband during a single night of polysomnography.

CORE ANALYTICS

Comparison of summary metrics, bias, and epoch-by-epoch analysis.

ADDITIONAL ANALYTICS AND EXPLORATORY ANALYSES

Correlation of summary metrics with demographic and Parkinson's disease characteristics.

CORE OUTCOMES

Summary statistics showed Dreem Headband overestimated several sleep metrics, including total sleep, efficiency, deep sleep, and rapid eye movement sleep, with an exception in light sleep. Epoch-by-epoch analysis showed greater specificity than sensitivity, with adequate accuracy across sleep stages (0.55-0.82).

IMPORTANT SUPPLEMENTAL OUTCOMES

Greater Parkinson's disease duration and rapid eye movement behavior were associated with more wakefulness, and worse Parkinson's disease motor symptoms were associated with less deep sleep.

CORE CONCLUSION

The Dreem Headband performs similarly in Parkinson's disease as it did in non-Parkinson's disease samples and shows promise for improving access to sleep assessment in people with Parkinson's disease.

Digital biomarkers of mobility and quality of life in Parkinson's disease based on a wearable motion analysis LAB

BACKGROUND AND OBJECTIVE

Functional mobility, an indicator of the quality of life (QoL), requires fast and flexible changes during motion, which are limited in Parkinson's disease (PD). Recent body-worn sensors have emerged in the last decades as potential solutions to produce digital biomarkers able to quantify mobility outside routine consultations and during real-life scenarios for multiple days at a time. The proposed research aims to study the ability of a wearable motion analysis lab, developed by our team, to produce digital biomarkers of mobility and QoL levels in patients with PD.

METHODS

A cross-sectional study was followed, including 40 patients stratified into three subgroups according to a clinic motor examination and a QoL questionnaire.

RESULTS

The achieved outcomes demonstrate the ability of the proposed high-tech solution to measure prototypical gait impairments and discriminate motor condition (AUC=0,890) and patients' QoL levels (AUC=0,950). Also, from the measured multiple gait-associated parameters, we identified the variables with the most potential to be applied as digital biomarkers of mobility (67 % of the metrics) and QoL (72 % of the metrics) in PD.

CONCLUSIONS

Overall, we confirmed our hypothesis of using our body-worn sensor-based solution for passive or active monitoring of mobility and QoL in PD to produce objective, feasible, and continuous digital biomarkers.

Perceived control as a predictor of medication adherence in people with Parkinson's: a large-scale cross-sectional study

PURPOSE

Medication adherence is a multi-faceted construct associated with several positive consequences in people with chronic conditions. However, non-adherence currently represents a major issue in Parkinson's, potentially due to low perceptions of control. This study investigated the predictive ability of several aspects of perceived control on adherence in people with Parkinson's, while accounting for previously established predictors such as depression and medication variables.

MATERIALS AND METHODS

An online cross-sectional survey was carried out with 1210 adults with Parkinson's from 15 English-speaking countries. Demographic and clinical questions, as well as measures of depression, aspects of perceived control, and medication adherence were included. Pearson's correlations and a 4-block hierarchical regression analysis were performed to assess the relationship between the variables.

RESULTS

Perceived control explained a slightly higher amount of variance in medication adherence compared to medication variables when entered in the last block. Unexpectedly, depression was not significantly related with adherence. Internal locus of control was an independent negative predictor of adherence, while external dimensions of locus of control emerged as independent positive predictors.

CONCLUSIONS

In people with Parkinson's, perceptions of control may have a larger impact on adherence compared to medication variables. Implications for clinical practice and future research are discussed.Implications for RehabilitationPerceived control and depression are considered important constructs for medication adherence in Parkinson's, which in turn is often problematic for affected individuals.The specific predictive value of different aspects of perceived control on medication adherence in Parkinson's is currently unclear.This large-scale study found that perceptions of control may have a larger impact on adherence compared to medication variables, while depression was unrelated to it.A need for psychologically-informed interventions, person-centred approaches to medication management, and Parkinson-specific measures of adherence are highlighted.

Navigating the Frontiers of Machine Learning in Neurodegenerative Disease Therapeutics

Recent advances in machine learning hold tremendous potential for enhancing the way we develop new medicines. Over the years, machine learning has been adopted in nearly all facets of drug discovery, including patient stratification, lead discovery, biomarker development, and clinical trial design. In this review, we will discuss the latest developments linking machine learning and CNS drug discovery. While machine learning has aided our understanding of chronic diseases like Alzheimer's disease and Parkinson's disease, only modest effective therapies currently exist. We highlight promising new efforts led by academia and emerging biotech companies to leverage machine learning for exploring new therapies. These approaches aim to not only accelerate drug development but to improve the detection and treatment of neurodegenerative diseases.

Bilateral deep transcranial magnetic stimulation of motor and prefrontal cortices in Parkinson's disease: a comprehensive review

Parkinson's disease (PD) is a prevalent neurodegenerative disorder characterized by both motor and non-motor symptoms, many of which are resistant to currently available treatments. Since the discovery that non-invasive transcranial magnetic stimulation (TMS) can cause dopamine release in PD patients, there has been growing interest in the use of TMS to fill existing gaps in the treatment continuum for PD. This review evaluates the safety and efficacy of a unique multifocal, bilateral Deep TMS protocol, which has been evaluated as a tool to address motor and non-motor symptoms of PD. Six published clinical trials have delivered a two-stage TMS protocol with an H-Coil targeting both the prefrontal cortex (PFC) and motor cortex (M1) bilaterally (220 PD patients in total; 108 from two randomized, sham-controlled studies; 112 from open label or registry studies). In all studies TMS was delivered to M1 bilaterally (Stage 1) and then to the PFC bilaterally (Stage 2) with approximately 900 pulses per stage. For Stage 1 (M1), two studies delivered 10 Hz at 90% motor threshold (MT) while four studies delivered 1 Hz at 110% MT. For Stage 2 (PFC), all studies delivered 10 Hz at 100% MT. The results suggest that this two-stage Deep TMS protocol is a safe, moderately effective treatment for motor symptoms of PD, and that severely impaired patients have the highest benefits. Deep TMS also improves mood symptoms and cognitive function in these patients. Further research is needed to establish optimal dosing and the long-term durability of treatment effects.

Early-stage idiopathic Parkinson's disease is associated with reduced circular RNA expression

Neurodegeneration in Parkinson's disease (PD) precedes diagnosis by years. Early neurodegeneration may be reflected in RNA levels and measurable as a biomarker. Here, we present the largest quantification of whole blood linear and circular RNAs (circRNA) in early-stage idiopathic PD, using RNA sequencing data from two cohorts (PPMI = 259 PD, 161 Controls; ICICLE-PD = 48 PD, 48 Controls). We identified a replicable increase in TMEM252 and LMNB1 gene expression in PD. We identified novel differences in the expression of circRNAs from ESYT2, BMS1P1 and CCDC9, and replicated trends of previously reported circRNAs. Overall, using circRNA as a diagnostic biomarker in PD did not show any clear improvement over linear RNA, minimising its potential clinical utility. More interestingly, we observed a general reduction in circRNA expression in both PD cohorts, accompanied by an increase in RNASEL expression. This imbalance implicates the activation of an innate antiviral immune response and suggests a previously unknown aspect of circRNA regulation in PD.

Charting Disease Trajectories from Isolated REM Sleep Behavior Disorder to Parkinson's Disease

BACKGROUND

Clinical presentation and progression dynamics are variable in patients with Parkinson's disease (PD). Disease course mapping is an innovative disease modelling technique that summarizes the range of possible disease trajectories and estimates dimensions related to onset, sequence, and speed of progression of disease markers.

OBJECTIVE

To propose a disease course map for PD and investigate progression profiles in patients with or without rapid eye movement sleep behavioral disorders (RBD).

METHODS

Data of 919 PD patients and 88 isolated RBD patients from three independent longitudinal cohorts were analyzed (follow-up duration = 5.1; 95% confidence interval, 1.1-8.1] years). Disease course map was estimated by using eight clinical markers (motor and non-motor symptoms) and four imaging markers (dopaminergic denervation).

RESULTS

PD course map showed that the first changes occurred in the contralateral putamen 13 years before diagnosis, followed by changes in motor symptoms, dysautonomia, sleep-all before diagnosis-and finally cognitive decline at the time of diagnosis. The model showed earlier disease onset, earlier non-motor and later motor symptoms, more rapid progression of cognitive decline in PD patients with RBD than PD patients without RBD. This pattern was even more pronounced in patients with isolated RBD with early changes in sleep, followed by cognition and non-motor symptoms and later changes in motor symptoms.

CONCLUSIONS

Our findings are consistent with the presence of distinct patterns of progression between patients with and without RBD. Understanding heterogeneity of PD progression is key to decipher the underlying pathophysiology and select homogeneous subgroups of patients for precision medicine. © 2023 International Parkinson and Movement Disorder Society.

Prevalence and Incidence of Parkinson's Disease in Latin America: A Meta-Analysis

BACKGROUND

Parkinson's disease (PD) is a rapidly growing neurodegenerative disorder, but up-to-date epidemiological data are lacking in Latin America. We sought to estimate the prevalence and incidence of PD and parkinsonism in Latin America.

METHODS

We searched Medline, Embase, Scopus, Web of Science, Scientific Electronic Library Online, and Literatura Latino-Americana e do Caribe em Ciências da Saúde or the Latin American and Caribbean Health Science Literature databases for epidemiological studies reporting the prevalence or incidence of PD or parkinsonism in Latin America from their inception to 2022. Quality of studies was assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist. Data were pooled via random-effects meta-analysis and analyzed by data source (cohort studies or administrative databases), sex, and age group. Significant differences between groups were determined by meta-regression.

RESULTS

Eighteen studies from 13 Latin American countries were included in the review. Meta-analyses of 17 studies (nearly 4 million participants) found a prevalence of 472 (95% CI, 271-820) per 100,000 and three studies an incidence of 31 (95% CI, 23-40) per 100,000 person-years for PD; and seven studies found a prevalence of 4300 (95% CI, 1863-9613) per 100,000 for parkinsonism. The prevalence of PD differed by data source (cohort studies, 733 [95% CI, 427-1255] vs. administrative databases. 114 [95% CI, 63-209] per 100,000, P < 0.01), age group (P < 0.01), but not sex (P = 0.73). PD prevalence in ≥60 years also differed significantly by data source (cohort studies. 1229 [95% CI, 741-2032] vs. administrative databases, 593 [95% CI, 480-733] per 100,000, P < 0.01). Similar patterns were observed for parkinsonism.

CONCLUSIONS

The overall prevalence and incidence of PD in Latin America were estimated. PD prevalence differed significantly by the data source and age, but not sex. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Parkinson's Disease is Predominantly a Genetic Disease

The discovery of a pathogenic variant in the alpha-synuclein (SNCA) gene in the Contursi kindred in 1997 indisputably confirmed a genetic cause in a subset of Parkinson's disease (PD) patients. Currently, pathogenic variants in one of the seven established PD genes or the strongest known risk factor gene, GBA1, are identified in ∼15% of PD patients unselected for age at onset and family history. In this Debate article, we highlight multiple avenues of research that suggest an important - and in some cases even predominant - role for genetics in PD aetiology, including familial clustering, high rates of monogenic PD in selected populations, and complete penetrance with certain forms. At first sight, the steep increase in PD prevalence exceeding that of other neurodegenerative diseases may argue against a predominant genetic etiology. Notably, the principal genetic contribution in PD is conferred by pathogenic variants in LRRK2 and GBA1 and, in both cases, characterized by an overall late age of onset and age-related penetrance. In addition, polygenic risk plays a considerable role in PD. However, it is likely that, in the majority of PD patients, a complex interplay of aging, genetic, environmental, and epigenetic factors leads to disease development.

Revolutionizing Neurological Disorder Treatment: Integrating Innovations in Pharmaceutical Interventions and Advanced Therapeutic Technologies

Neurological disorders impose a significant burden on individuals, leading to disabilities and a reduced quality of life. However, recent years have witnessed remarkable advancements in pharmaceutical interventions aimed at treating these disorders. This review article aims to provide an overview of the latest innovations and breakthroughs in neurological disorder treatment, with a specific focus on key therapeutic areas such as Alzheimer's disease, Parkinson's disease, multiple sclerosis, epilepsy, and stroke. This review explores emerging trends in drug development, including the identification of novel therapeutic targets, the development of innovative drug delivery systems, and the application of personalized medicine approaches. Furthermore, it highlights the integration of advanced therapeutic technologies such as gene therapy, optogenetics, and neurostimulation techniques. These technologies hold promise for precise modulation of neural circuits, restoration of neuronal function, and even disease modification. While these advancements offer hopeful prospects for more effective and tailored treatments, challenges such as the need for improved diagnostic tools, identification of new targets for intervention, and optimization of drug delivery methods will remain. By addressing these challenges and continuing to invest in research and collaboration, we can revolutionize the treatment of neurological disorders and significantly enhance the lives of those affected by these conditions.

Staging Parkinson's disease according to the MNCD classification correlates with caregiver burden

BACKGROUND AND OBJECTIVE

Recently, we demonstrated that staging Parkinson's disease (PD) with a novel simple classification called MNCD, based on four axes (motor, non-motor, cognition, and dependency) and five stages, correlated with disease severity and patients' quality of life. Here, we analyzed the correlation of MNCD staging with PD caregiver's status.

PATIENTS AND METHODS

Data from the baseline visit of PD patients and their principal caregiver recruited from 35 centers in Spain from the COPPADIS cohort from January 2016 to November 2017 were used to apply the MNCD total score (from 0 to 12) and MNCD stages (from 1 to 5) in this cross-sectional analysis. Caregivers completed the Zarit Caregiver Burden Inventory (ZCBI), Caregiver Strain Index (CSI), Beck Depression Inventory-II (BDI-II), PQ-10, and EUROHIS-QOL 8-item index (EUROHIS-QOL8).

RESULTS

Two hundred and twenty-four PD patients (63 ± 9.6 years old; 61.2% males) and their caregivers (58.5 ± 12.1 years old; 67.9% females) were included. The frequency of MNCD stages was 1, 7.6%; 2, 58.9%; 3, 31.3%; and 4-5, 2.2%. A more advanced MNCD stage was associated with a higher score on the ZCBI (p < .0001) and CSI (p < .0001), and a lower score on the PQ-10 (p = .001), but no significant differences were observed in the BDI-II (p = .310) and EUROHIS-QOL8 (p = .133). Moderate correlations were observed between the MNCD total score and the ZCBI (r = .496; p < .0001), CSI (r = .433; p < .0001), and BDI-II (r = .306; p < .0001) in caregivers.

CONCLUSION

Staging PD according to the MNCD classification is correlated with caregivers' strain and burden.

Volumetric changes and clinical trajectories in Parkinson's disease: a prospective multicentric study

BACKGROUND

Longitudinal measures of structural brain changes using MRI in relation to clinical features and progression patterns in PD have been assessed in previous studies, but few were conducted in well-defined and large cohorts, including prospective clinical assessments of both motor and non-motor symptoms.

OBJECTIVE

We aimed to identify brain volumetric changes characterizing PD patients, and determine whether regional brain volumetric characteristics at baseline can predict motor, psycho-behavioral and cognitive evolution at one year in a prospective cohort of PD patients.

METHODS

In this multicentric 1 year longitudinal study, PD patients and healthy controls from the MPI-R2* cohort were assessed for demographical, clinical and brain volumetric characteristics. Distinct subgroups of PD patients according to motor, cognitive and psycho-behavioral evolution were identified at the end of follow-up.

RESULTS

One hundred and fifty PD patients and 73 control subjects were included in our analysis. Over one year, there was no significant difference in volume variations between PD and control subjects, regardless of the brain region considered. However, we observed a reduction in posterior cingulate cortex volume at baseline in PD patients with motor deterioration at one year (p = 0.017). We also observed a bilateral reduction of the volume of the amygdala (p = 0.015 and p = 0.041) and hippocampus (p = 0.015 and p = 0.053) at baseline in patients with psycho-behavioral deterioration, regardless of age, dopaminergic treatment and center.

CONCLUSION

Brain volumetric characteristics at baseline may predict clinical trajectories at 1 year in PD as posterior cingulate cortex atrophy was associated with motor decline, while amygdala and hippocampus atrophy were associated with psycho-behavioral decline.

Cognitive impairment and dementia in young onset Parkinson's disease

BACKGROUND AND OBJECTIVE

Patients with young-onset Parkinson's disease (YOPD) have a slower progression. Our aim was to analyze the change in cognitive function in YOPD compared to patients with a later onset and controls.

PATIENTS AND METHODS

Patients with Parkinson's disease (PD) and controls from the COPPADIS cohort were included. Cognitive function was assessed with the Parkinson's Disease Cognitive Rating Scale (PD-CRS) at baseline (V0), 2-year ± 1 month (V2y), and 4-year ± 3 months follow-up (V4y). Regarding age from symptoms onset, patients were classified as YOPD (< 50 years) or non-YOPD (≥ 50). A score in the PD-CRS < 81 was defined as cognitive impairment (CI): ≤ 64 dementia; 65-80 mild cognitive impairment (MCI).

RESULTS

One-hundred and twenty-four YOPD (50.7 ± 7.9 years; 66.1% males), 234 non-YOPD (67.8 ± 7.8 years; 59.3% males) patients, and 205 controls (61 ± 8.3 years; 49.5% males) were included. The score on the PD-CRS and its subscore domains was higher at all visits in YOPD compared to non-YOPD patients and to controls (p < 0.0001 in all analysis), but no differences were detected between YOPD patients and controls. Only non-YOPD patients had significant impairment in their cognitive function from V0 to V4y (p < 0.0001). At V4y, the frequency of dementia and MCI was 5% and 10% in YOPD compared to 25.2% and 22.3% in non-YOPD patients (p < 0.0001). A lower score on the Parkinson's Disease Sleep Scale at baseline was a predictor of CI at V4y in YOPD patients (Adjusted R2 = 0.61; OR = 0.965; p = 0.029).

CONCLUSION

Cognitive dysfunction progressed more slowly in YOPD than in non-YOPD patients.

Clinical subtypes in patients with isolated REM sleep behaviour disorder

Patients with Parkinson's disease (PD) show a broad heterogeneity in clinical presentation, and subtypes may already arise in prodromal disease stages. Isolated REM sleep behaviour disorder (iRBD) is the most specific marker of prodromal PD, but data on clinical subtyping of patients with iRBD remain scarce. Therefore, this study aimed to identify iRBD subtypes. We conducted comprehensive clinical assessments in 66 patients with polysomnography-proven iRBD, including motor and non-motor evaluations, and applied a two-step cluster analysis. Besides, we compared iRBD clusters to matched healthy controls and related the resulting cluster solution to cortical and subcortical grey matter volumes by voxel-based morphometry analysis. We identified two distinct subtypes of patients based on olfactory function, dominant electroencephalography frequency, amount of REM sleep without atonia, depressive symptoms, disease duration, and motor functions. One iRBD cluster (Cluster I, late onset-aggressive) was characterised by higher non-motor symptom burden despite shorter disease duration than the more benign subtype (Cluster II, early onset-benign). Motor functions were comparable between the clusters. Patients from Cluster I were significantly older at iRBD onset and exhibited a widespread reduction of cortical grey matter volume compared to patients from Cluster II. In conclusion, our findings suggest the existence of clinical subtypes already in the prodromal stage of PD. Future longitudinal studies are warranted that replicate these findings and investigate the risk of the more aggressive phenotype for earlier phenoconversion and dementia development.

A framework for integrating artificial intelligence for clinical care with continuous therapeutic monitoring

The complex relationships between continuously monitored health signals and therapeutic regimens can be modelled via machine learning. However, the clinical implementation of the models will require changes to clinical workflows. Here we outline ClinAIOps ('clinical artificial-intelligence operations'), a framework that integrates continuous therapeutic monitoring and the development of artificial intelligence (AI) for clinical care. ClinAIOps leverages three feedback loops to enable the patient to make treatment adjustments using AI outputs, the clinician to oversee patient progress with AI assistance, and the AI developer to receive continuous feedback from both the patient and the clinician. We lay out the central challenges and opportunities in the deployment of ClinAIOps by means of examples of its application in the management of blood pressure, diabetes and Parkinson's disease. By enabling more frequent and accurate measurements of a patient's health and more timely adjustments to their treatment, ClinAIOps may substantially improve patient outcomes.

Free water imaging unravels unique patterns of longitudinal structural brain changes in Parkinson's disease subtypes

Background

Research shows that individuals with Parkinson's disease (PD) who have a postural instability and gait difficulties (PIGD) subtype have a faster disease progression compared to those with a tremor dominant (TD) subtype. Nevertheless, our understanding of the structural brain changes contributing to these clinical differences remains limited, primarily because many brain imaging techniques are only capable of detecting changes in the later stages of the disease.

Objective

Free water (FW) has emerged as a robust progression marker in several studies, showing increased values in the posterior substantia nigra that predict symptom worsening. Here, we examined longitudinal FW changes in TD and PIGD across multiple brain regions.

Methods

Participants were TD and PIGD enrolled in the Parkinson's Progression Marker Initiative (PPMI) study who underwent diffusion MRI at baseline and 2 years later. FW changes were quantified for regions of interest (ROI) within the basal ganglia, thalamus, brainstem, and cerebellum.

Results

Baseline FW in all ROIs did not differ between groups. Over 2 years, PIGD had a greater percentage increase in FW in the putamen, globus pallidus, and cerebellar lobule V. A logistic regression model incorporating percent change in motor scores and FW in these brain regions achieved 91.4% accuracy in discriminating TD and PIGD, surpassing models based solely on clinical measures (74.3%) or imaging (76.1%).

Conclusion

The results further suggest the use of FW to study disease progression in PD and provide insight into the differential course of brain changes in early-stage PD subtypes.

Longitudinal follow up of data-driven cognitive subtypes in Parkinson's disease

AIM

The dual syndrome hypothesis proposes that there are two cognitive subtypes in Parkinson's disease (PD): a frontal subtype with executive/attention impairment and gradual cognitive decline, and a posterior-cortical subtype with memory/visuospatial deficits and rapid cognitive decline. We aimed to compare the rate of global cognitive decline between subtypes derived using data-driven methods and explore their longitudinal performance within specific cognitive domains to better understand the prognosis of each subtype.

METHOD

Frontal, posterior-cortical, globally impaired, and cognitively intact PD subtypes were identified at baseline using k-means clustering (N = 85), and 29 participants (34%) returned for follow-up assessments on average 4.87 years from baseline. Linear mixed effects models compared progression of subtypes on global cognition; psychological symptoms; parkinsonism; and the memory, attention, executive, language, and visuospatial cognitive domains.

RESULTS

The frontal subtype was lost to attrition. While rate of change in parkinsonism, anxiety, and apathy differed between subtypes, there was no difference in the rate of global cognitive decline. However, the posterior-cortical subtype declined most rapidly in verbal memory, card sorting, trail making, and judgement of line orientation (JLO), while the cognitively intact group declined most rapidly on verbal memory and semantic fluency. The globally impaired subtype declined most rapidly in JLO, although this should be interpreted with caution due to high attrition.

CONCLUSION

Despite limited sample size, the present study supports the differential progression of the posterior-cortical subtype compared to cognitively intact and globally impaired PD. These results encourage further, large-scale longitudinal investigations of cognitive subtypes in PD.

Differential Implications of Cerebral Hypoperfusion and Hyperperfusion in Parkinson's Disease

BACKGROUND

Patients with Parkinson's disease (PD) exhibit widespread brain perfusion changes.

OBJECTIVE

This study investigated whether cerebral regions with hypoperfusion and hyperperfusion have differential effects on motor and cognitive symptoms in PD using early-phase 18 F-N-(3-fluoropropyl)-2β-carboxymethoxy-3β-(4-iodophenyl) nortropane (18 F-FP-CIT) positron emission tomography (PET) scans.

METHODS

We enrolled 394 patients with newly diagnosed PD who underwent dual-phase 18 F-FP-CIT PET scans. Indices reflecting associated changes in regional cerebral hypoperfusion and hyperperfusion on early-phase 18 F-FP-CIT PET scans were calculated as PD[hypo] and PD[hyper] , respectively. The associations of PD[hypo] and PD[hyper] on motor and cognitive symptoms at baseline were assessed using multivariate linear regression. Also, Cox regression and linear mixed models were performed to investigate the effects of baseline PD[hypo] and PD[hyper] on longitudinal outcomes.

RESULTS

There was a weak correlation between PD[hypo] and PD[hyper] (γ = -0.19, P < 0.001). PD[hypo] was associated with baseline Unified Parkinson's Disease Rating Scale Part III scores (β = -1.02, P = 0.045), rapid increases in dopaminergic medications (β = -18.02, P < 0.001), and a higher risk for developing freezing of gait (hazard ratio [HR] = 0.67, P = 0.019), whereas PD[hyper] was not associated. Regarding cognitive function, PD[hypo] was more relevant to the baseline cognitive performance levels of visuospatial, memory, and frontal/executive function than PD[hyper] . However, greater PD[hyper] was associated with future dementia conversion (HR = 1.43, P = 0.004), whereas PD[hypo] was not associated.

CONCLUSIONS

These findings suggest that PD[hypo] and PD[hyper] may differentially affect motor and cognitive functions in patients with PD. © 2023 International Parkinson and Movement Disorder Society.

Correlation of SV2C rs1423099 single nucleotide polymorphism with sporadic Parkinson's disease in Han population in Southern China

BACKGROUND

The synaptic vesicle glycoprotein 2 (SV2) has been implicated in synaptic function throughout the brain. Accumulating evidence investigated that SV2C contributed to dopamine release and the disrupted expression of SV2C was considered to be a unique feature of PD that may facilitate dopaminergic neuron dysfunction.

OBJECTIVE

This study aimed to examine the relationship between the SV2C rs1423099 single nucleotide polymorphism and sporadic Parkinson's disease (PD) in the Chinese Han population.

MATERIALS AND METHODS

This study enrolled 351 patients with sporadic PD and 240 normal controls in Chinese Han population. Peripheral blood DNA was extracted by DNA extraction kits and the rs1423099 genotype was analyzed by Agena MassARRAY DNA mass spectrometry. The differences in genotype and allele distribution frequencies between PD patients and control groups were compared using chi-squared tests or Fisher's exact tests.

RESULTS

No statistical difference was revealed in age and sex distribution between the cases and control groups, and the distribution of genotype and allele frequencies was consistent with the Hardy-Weinberg equilibrium test. In SV2C rs1423099 dominant model, the frequency of the CC/CT genotype was significantly higher in the PD group compared to the control group (OR = 4.065,95% CI: 2.801-10.870, p = 0.002). Nevertheless, in the recessive model, CC or CT/TT genotypes have no statistical difference in the two groups (p = 0.09). Additionally, in allelic analysis, the C allele was investigated to increase the risk of PD (OR = 1.346, 95% CI: 1.036-1.745, p = 0.026); Furthermore, subgroup analysis suggested that those carrying the C allele in the male subgroup were at a higher risk to afflicted with PD (OR = 1.637, 95% CI: 1.147-2.336, p = 0.006).

CONCLUSION

SV2C rs1423099 single nucleotide polymorphism was associated with sporadic Parkinson's disease in the Chinese Han population, particularly in males.

Validation of the Swedish Patient-Reported Outcomes in Parkinson's Disease Scale in Outpatients

BACKGROUND

Successful treatment of Parkinson's disease (PD) requires symptom monitoring. Patient-Reported Outcomes in Parkinson's Disease (PRO-PD) is a broad scale that covers 35 motor and nonmotor symptoms, but its validation is limited.

OBJECTIVE

The aim was to validate PRO-PD in a random sample of outpatients with PD.

METHODS

Of 2123 PD patients who visited outpatient clinics in West Sweden over a 12-month period, 25% were randomly selected and invited to participate in a longitudinal observational study. Included patients were assessed at baseline, 1 year, and 3 years, with a subset also assessed at 3 to 6 months. The assessments included PRO-PD, other patient-reported scales, and Clinical Impression of Severity Index for Parkinson's Disease (CISI-PD).

RESULTS

The study included 286 PD patients. PRO-PD ratings were available from 716 (96%) of 747 study visits. All PRO-PD items exhibited positive skewness without ceiling effects. Internal consistency at baseline was excellent (Cronbach's α: 0.93). Six-month test-retest reliability was good (intraclass correlation coefficient: 0.87). Convergent validity was good, with correlation coefficients between total PRO-PD and the 8-Item Parkinson's Disease Questionnaire of 0.70, the Non-Motor Symptoms Questionnaire of 0.70, EuroQoL Five-Dimension Five-Level Scale of 0.71, and CISI-PD of 0.69. Median PRO-PD score at baseline was 995 (interquartile range: 613-1399), with a median yearly increase of 71 (interquartile range: -21 to 111). Items representing axial motor symptoms increased most over time. The minimal clinically important change in total score was 119.

CONCLUSIONS

PRO-PD was found reliable and valid for monitoring symptoms in a representative sample of outpatients with PD. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Visual velocity perception dysfunction in Parkinson's disease

OBJECTIVE

Compared with motor deficits, sensory information processing in Parkinson's disease (PD) is relatively unexplored. While there is increasing interest in understanding the sensory manifestations of PD, the extent of sensory abnormality in PD has remained relatively unexplored. Furthermore, most investigations on the sensory aspects of PD involve motor aspects, causing confounding results. As sensory deficits often arise in early PD development stages, they present a potential technological target for diagnosis and disease monitoring that is affordable and accessible. Considering this, the current study's aim is to assess visual spatiotemporal perception independent of goal directed movements in PD by designing and using a scalable computational tool.

METHODS

A flexible 2-D virtual reality environment was created to evaluate various cases of visual perception. Using the tool, an experimental task quantifying the visual perception of velocity was tested on 37 individuals with PD and 17 age-matched control participants.

RESULTS

PD patients, both ON and OFF PD therapy, displayed perceptual impairments (p = 0.001 and p = 0.008, respectively) at slower tested velocity magnitudes. These impairments were even observed in early stages of PD (p = 0.015).

CONCLUSION

Visual velocity perception is impaired in PD patients, which suggests impairments in visual spatiotemporal processing occur in PD and provides a promising modality to be used with disease monitoring software.

SIGNIFICANCE

Visual velocity perception shows high sensitivity to PD at all stages of the disease. Dysfunction in visual velocity perception may contribute to observed motor dysfunction in PD.

Metabolic Disturbances in the Gut-brain Axis of a Mouse Model of MPTP-induced Parkinsonism Evaluated by Nuclear Magnetic Resonance

Parkinson's Disease is a synucleinopathy that primarily affects the dopaminergic cells of the central nervous system, leading to motor and gastrointestinal disturbances. However, intestinal peripheral neurons undergo a similar neurodegeneration process, marked by α-synuclein (αSyn) accumulation and loss of mitochondrial homeostasis. We investigated the metabolic alterations in different biometrics that compose the gut-brain axis (blood, brain, large intestine, and feces) in an MPTP-induced mouse model of sporadic Parkinson's Disease. Animals received escalating administration of MPTP. Tissues and fecal pellets were collected, and the metabolites were identified through the untargeted Nuclear Magnetic Resonance spectroscopic (1H NMR) technique. We found differences in many metabolites from all the tissues evaluated. The differential expression of metabolites in these samples mainly reflects inflammatory aspects, cytotoxicity, and mitochondrial impairment (oxidative stress and energy metabolism) in the animal model used. The direct evaluation of fecal metabolites revealed changes in several classes of metabolites. This data reinforces previous studies showing that Parkinson's disease is associated with metabolic perturbation not only in brain-related tissues, but also in periphery structures such as the gut. In addition, the evaluation of the microbiome and metabolites from gut and feces emerge as promising sources of information for understanding the evolution and progression of sporadic Parkinson's Disease.

Neuromelanin-sensitive MRI correlates of cognitive and motor function in Parkinson's disease with freezing of gait

Substantia nigra pars compacta (SNc) and locus coeruleus (LC) are neuromelanin-rich nuclei implicated in diverse cognitive and motor processes in normal brain function and disease. However, their roles in aging and neurodegenerative disease mechanisms have remained unclear due to a lack of tools to study them in vivo. Preclinical and post-mortem human investigations indicate that the relationship between tissue neuromelanin content and neurodegeneration is complex. Neuromelanin exhibits both neuroprotective and cytotoxic characteristics, and tissue neuromelanin content varies across the lifespan, exhibiting an inverted U-shaped relationship with age. Neuromelanin-sensitive MRI (NM-MRI) is an emerging modality that allows measurement of neuromelanin-associated contrast in SNc and LC in humans. NM-MRI robustly detects disease effects in these structures in neurodegenerative conditions, including Parkinson's disease (PD). Previous NM-MRI studies of PD have largely focused on detecting disease group effects, but few studies have reported NM-MRI correlations with phenotype. Because neuromelanin dynamics are complex, we hypothesize that they are best interpreted in the context of both disease stage and aging, with neuromelanin loss correlating with symptoms most clearly in advanced stages where neuromelanin loss and neurodegeneration are coupled. We tested this hypothesis using NM-MRI to measure SNc and LC volumes in healthy older adult control individuals and in PD patients with and without freezing of gait (FOG), a severe and disabling PD symptom. We assessed for group differences and correlations between NM-MRI measures and aging, cognition and motor deficits. SNc volume was significantly decreased in PD with FOG compared to controls. SNc volume correlated significantly with motor symptoms and cognitive measures in PD with FOG, but not in PD without FOG. SNc volume correlated significantly with aging in PD. When PD patients were stratified by disease duration, SNc volume correlated with aging, cognition, and motor deficits only in PD with disease duration >5 years. We conclude that in severe or advanced PD, identified by either FOG or disease duration >5 years, the observed correlations between SNc volume and aging, cognition, and motor function may reflect the coupling of neuromelanin loss with neurodegeneration and the associated emergence of a linear relationship between NM-MRI measures and phenotype.

Neuromelanin-sensitive MRI correlates of cognitive and motor function in Parkinson's disease with freezing of gait

Substantia nigra pars compacta (SNc) and locus coeruleus (LC) are neuromelanin-rich nuclei implicated in diverse cognitive and motor processes in normal brain function and disease. However, their roles in aging and neurodegenerative disease mechanisms have remained unclear due to a lack of tools to study them in vivo. Preclinical and post-mortem human investigations indicate that the relationship between tissue neuromelanin content and neurodegeneration is complex. Neuromelanin exhibits both neuroprotective and cytotoxic characteristics, and tissue neuromelanin content varies across the lifespan, exhibiting an inverted U-shaped relationship with age. Neuromelanin-sensitive MRI (NM-MRI) is an emerging modality that allows measurement of neuromelanin-associated contrast in SNc and LC in humans. NM-MRI robustly detects disease effects in these structures in neurodegenerative and psychiatric conditions, including Parkinson's disease (PD). Previous NM-MRI studies of PD have largely focused on detecting disease group effects, but few studies have reported NM-MRI correlations with phenotype. Because neuromelanin dynamics are complex, we hypothesize that they are best interpreted in the context of both disease stage and aging, with neuromelanin loss correlating with symptoms most clearly in advanced stages where neuromelanin loss and neurodegeneration are coupled. We tested this hypothesis using NM-MRI to measure SNc and LC volumes in healthy older adult control individuals and in PD patients with and without freezing of gait (FOG), a severe and disabling PD symptom. We assessed for group differences and correlations between NM-MRI measures and aging, cognition and motor deficits. SNc volume was significantly decreased in PD with FOG compared to controls. SNc volume correlated significantly with motor symptoms and cognitive measures in PD with FOG, but not in PD without FOG. SNc volume correlated significantly with aging in PD. When PD patients were stratified by disease duration, SNc volume correlated with aging, cognition, and motor deficits only in PD with disease duration >5 years. We conclude that in severe or advanced PD, identified by either FOG or disease duration >5 years, the observed correlations between SNc volume and aging, cognition, and motor function may reflect the coupling of neuromelanin loss with neurodegeneration and the associated emergence of a linear relationship between NM-MRI measures and phenotype.

A structural magnetic resonance imaging review of clinical motor outcomes from deep brain stimulation in movement disorders

Patients with movement disorders treated by deep brain stimulation do not always achieve successful therapeutic alleviation of motor symptoms, even in cases where surgery is without complications. Magnetic resonance imaging (MRI) offers methods to investigate structural brain-related factors that may be predictive of clinical motor outcomes. This review aimed to identify features which have been associated with variability in clinical post-operative motor outcomes in patients with Parkinson's disease, dystonia, and essential tremor from structural MRI modalities. We performed a literature search for articles published between 1 January 2000 and 1 April 2022 and identified 5197 articles. Following screening through our inclusion criteria, we identified 60 total studies (39 = Parkinson's disease, 11 = dystonia syndromes and 10 = essential tremor). The review captured a range of structural MRI methods and analysis techniques used to identify factors related to clinical post-operative motor outcomes from deep brain stimulation. Morphometric markers, including volume and cortical thickness were commonly identified in studies focused on patients with Parkinson's disease and dystonia syndromes. Reduced metrics in basal ganglia, sensorimotor and frontal regions showed frequent associations with reduced motor outcomes. Increased structural connectivity to subcortical nuclei, sensorimotor and frontal regions was also associated with greater motor outcomes. In patients with tremor, increased structural connectivity to the cerebellum and cortical motor regions showed high prevalence across studies for greater clinical motor outcomes. In addition, we highlight conceptual issues for studies assessing clinical response with structural MRI and discuss future approaches towards optimizing individualized therapeutic benefits. Although quantitative MRI markers are in their infancy for clinical purposes in movement disorder treatments, structural features obtained from MRI offer the powerful potential to identify candidates who are more likely to benefit from deep brain stimulation and provide insight into the complexity of disorder pathophysiology.

Combining skin and olfactory α-synuclein seed amplification assays (SAA)-towards biomarker-driven phenotyping in synucleinopathies

Seed amplification assays (SAA) are becoming commonly used in synucleinopathies to detect α-synuclein aggregates. Studies in Parkinson's disease (PD) and isolated REM-sleep behavior disorder (iRBD) have shown a considerably lower sensitivity in the olfactory epithelium than in CSF or skin. To get an insight into α-synuclein (α-syn) distribution within the nervous system and reasons for low sensitivity, we compared SAA assessment of nasal brushings and skin biopsies in PD (n = 27) and iRBD patients (n = 18) and unaffected controls (n = 30). α-syn misfolding was overall found less commonly in the olfactory epithelium than in the skin, which could be partially explained by the nasal brushing matrix exerting an inhibitory effect on aggregation. Importantly, the α-syn distribution was not uniform: there was a higher deposition of misfolded α-syn across all sampled tissues in the iRBD cohort compared to PD (supporting the notion of RBD as a marker of a more malignant subtype of synucleinopathy) and in a subgroup of PD patients, misfolded α-syn was detectable only in the olfactory epithelium, suggestive of the recently proposed brain-first PD subtype. Assaying α-syn of diverse origins, such as olfactory (part of the central nervous system) and skin (peripheral nervous system), could increase diagnostic accuracy and allow better stratification of patients.