OUP accepted manuscript

Developments in the prediction of cognitive changes following deep brain stimulation in persons with Parkinson's disease

INTRODUCTION

Deep brain stimulation (DBS) is an effective treatment for Parkinson's disease (PD) motor symptoms that improves function and quality of life in appropriately selected patients. Because mild to moderate cognitive declines can follow DBS and impact quality of life in a minority of patients, an important consideration involves the cognitive deficit and its prediction.

AREAS COVERED

The author briefly summarizes cognitive outcomes from DBS and reviews in more detail the risks/predictors of post-DBS cognitive dysfunction by mainly focusing on work published between 2018 and 2024 and using comprehensive neuropsychological (NP) evaluations. Most publications concern bilateral subthalamic nucleus (STN) DBS. Comment is offered on challenges and potential avenues forward.

EXPERT OPINION

STN DBS is relatively safe cognitively but declines occur especially in verbal fluency and executive function/working memory. Numerous predictors and risk factors for cognitive outcomes have been identified (age and pre-operative neuropsychological status appear the most robust) but precise risk estimates cannot yet be confidently offered. Future studies should employ study center consortia, follow uniform reporting criteria (to be developed), capitalize on advances in stimulation, biomarkers, and artificial intelligence, and address DBS in diverse groups. Advances offer an avenue to investigate the amelioration of cognitive deficits in PD using neuromodulation.

Prevalence of multiple system atrophy: A literature review

INTRODUCTION

This paper aims to provide a literature overview on multiple system atrophy (MSA) prevalence in European and other pan-European populations.

METHODS

A literature search (PubMed, EMBASE) was performed through 2022 to identify published studies on MSA prevalence in European countries. Of these search results, titles and abstracts were screened for relevance. A standardized assessment tool was used for systematically data extraction and comparison. For studies where only the incidence rate was reported, MSA prevalence was derived based on the incidence and duration of disease.

RESULTS

A total of 24 studies conducted in 14 countries and published between 1995 and 2022 were identified. The prevalence of MSA was reported in 18 (75%) studies and was derived from six (25%) incidence studies. These studies were mainly prospective population-based studies or multi-center studies from specific regions or specialty clinical settings. Two earlier studies in Germany and the Netherlands were conducted using door-to-door design. The time period of evaluation of prevalence ranged from 1990 to 2018. The crude prevalence of MSA ranged from 0.5/100,000 in Spain to 17/100,000 in Japan. Age-specific prevalence rates were provided in five studies, and the reported age ranges varied. The gender-specific crude prevalence was estimated as 2.75/100,000 for men and 1.19/100.000 for women. The derived prevalence was higher (ranging from 0.7-18.9/100,000) than studies where the prevalence was reported.

CONCLUSION

The variations observed in MSA prevalence may result from differences in age distributions of the study populations, study methodology, diagnostic criteria and case assessment strategies of MSA. Thus, the comparability of these studies is limited.

Machine learning-based prediction of longitudinal cognitive decline in early Parkinson's disease using multimodal features

Patients with Parkinson's Disease (PD) often suffer from cognitive decline. Accurate prediction of cognitive decline is essential for early treatment of at-risk patients. The aim of this study was to develop and evaluate a multimodal machine learning model for the prediction of continuous cognitive decline in patients with early PD. We included 213 PD patients from the Parkinson's Progression Markers Initiative (PPMI) database. Machine learning was used to predict change in Montreal Cognitive Assessment (MoCA) score using the difference between baseline and 4-years follow-up data as outcome. Input features were categorized into four sets: clinical test scores, cerebrospinal fluid (CSF) biomarkers, brain volumes, and genetic variants. All combinations of input feature sets were added to a basic model, which consisted of demographics and baseline cognition. An iterative scheme using RReliefF-based feature ranking and support vector regression in combination with tenfold cross validation was used to determine the optimal number of predictive features and to evaluate model performance for each combination of input feature sets. Our best performing model consisted of a combination of the basic model, clinical test scores and CSF-based biomarkers. This model had 12 features, which included baseline cognition, CSF phosphorylated tau, CSF total tau, CSF amyloid-beta1-42, geriatric depression scale (GDS) scores, and anxiety scores. Interestingly, many of the predictive features in our model have previously been associated with Alzheimer's disease, showing the importance of assessing Alzheimer's disease pathology in patients with Parkinson's disease.

Inflammation in multiple system atrophy

Misfolding protein aggregation inside or outside cells is the major pathological hallmark of several neurodegenerative diseases. Among proteinopathies are neurodegenerative diseases with atypical Parkinsonism and an accumulation of insoluble fibrillary alpha-synuclein (synucleinopathies) or hyperphosphorylated tau protein fragments (tauopathies). As there are no therapies available to slow or halt the progression of these disea ses, targeting the inflammatory process is a promising approach. The inflammatory biomarkers could also help in the differential diagnosis of Parkinsonian syndromes. Here, we review inflammation's role in multiple systems atrophy pathogenesis, diagnosis, and treatment.

Parkinson's disease therapy: what lies ahead?

The worldwide prevalence of Parkinson's disease (PD) has been constantly increasing in the last decades. With rising life expectancy, a longer disease duration in PD patients is observed, further increasing the need and socioeconomic importance of adequate PD treatment. Today, PD is exclusively treated symptomatically, mainly by dopaminergic stimulation, while efforts to modify disease progression could not yet be translated to the clinics. New formulations of approved drugs and treatment options of motor fluctuations in advanced stages accompanied by telehealth monitoring have improved PD patients care. In addition, continuous improvement in the understanding of PD disease mechanisms resulted in the identification of new pharmacological targets. Applying novel trial designs, targeting of pre-symptomatic disease stages, and the acknowledgment of PD heterogeneity raise hopes to overcome past failures in the development of drugs for disease modification. In this review, we address these recent developments and venture a glimpse into the future of PD therapy in the years to come.

Pathomechanisms of cognitive impairment in progressive supranuclear palsy

Progressive supranuclear palsy (PSP) is a neurodegenerative disorder characterized by early postural instability and falls, oculomotor dysfunction (vertical supranuclear gaze palsy), parkinsonism with poor response to levodopa, pseudobulbar palsy, and cognitive impairment. This four-repeat tauopathy is morphologically featured by accumulation of tau protein in neurons and glia causing neuronal loss and gliosis in the extrapyramidal system associated with cortical atrophy and white matter lesions. Cognitive impairment being frequent in PSP and more severe than in multiple system atrophy and Parkinson disease, is dominated by executive dysfunction, with milder difficulties in memory, and visuo-spatial and naming dysfunctions. Showing longitudinal decline, it has been related to a variety of pathogenic mechanisms associated with the underlying neurodegenerative process, such as involvement of cholinergic and muscarinergic dysfunctions, and striking tau pathology in frontal and temporal cortical regions associated with reduced synaptic density. Altered striatofrontal, fronto-cerebellar, parahippocampal, and multiple subcortical structures, as well as widespread white matter lesions causing extensive connectivity disruptions in cortico-subcortical and cortico-brainstem connections, support the concept that PSP is a brain network disruption disorder. The pathophysiology and pathogenesis of cognitive impairment in PSP, as in other degenerative movement disorders, are complex and deserve further elucidation as a basis for adequate treatment to improve the quality of life of patients with this fatal disease.

Cerebrospinal Fluid Biomarkers of Synaptic Dysfunction are Altered in Parkinson's Disease and Related Disorders

BACKGROUND

Synaptic dysfunction and degeneration are central contributors to the pathogenesis and progression of parkinsonian disorders. Therefore, identification and validation of biomarkers reflecting pathological synaptic alterations are greatly needed and could be used in prognostic assessment and to monitor treatment effects.

OBJECTIVE

To explore candidate biomarkers of synaptic dysfunction in Parkinson's disease (PD) and related disorders.

METHODS

Mass spectrometry was used to quantify 15 synaptic proteins in two clinical cerebrospinal fluid (CSF) cohorts, including PD (n₁  = 51, n₂  = 101), corticobasal degeneration (CBD) (n₁  = 11, n₂  = 3), progressive supranuclear palsy (PSP) (n₁  = 22, n₂  = 21), multiple system atrophy (MSA) (n₁  = 31, n₂  = 26), and healthy control (HC) (n₁  = 48, n₂  = 30) participants, as well as Alzheimer's disease (AD) (n₂  = 23) patients in the second cohort.

RESULTS

Across both cohorts, lower levels of the neuronal pentraxins (NPTX; 1, 2, and receptor) were found in PD, MSA, and PSP, compared with HC. In MSA and PSP, lower neurogranin, AP2B1, and complexin-2 levels compared with HC were observed. In AD, levels of 14-3-3 zeta/delta, beta- and gamma-synuclein were higher compared with the parkinsonian disorders. Lower pentraxin levels in PD correlated with Mini-Mental State Exam scores and specific cognitive deficits (NPTX2; rho = 0.25-0.32, P < 0.05) and reduced dopaminergic pre-synaptic integrity as measured by DaTSCAN (NPTX2; rho = 0.29, P = 0.023). Additionally, lower levels were associated with the progression of postural imbalance and gait difficulty symptoms (All NPTX; β-estimate = -0.025 to -0.038, P < 0.05) and cognitive decline (NPTX2; β-estimate = 0.32, P = 0.021).

CONCLUSIONS

These novel findings show different alterations of synaptic proteins in parkinsonian disorders compared with AD and HC. The neuronal pentraxins may serve as prognostic CSF biomarkers for both cognitive and motor symptom progression in PD. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Outcome Measures for Disease-Modifying Trials in Parkinson's Disease: Consensus Paper by the EJS ACT-PD Multi-Arm Multi-Stage Trial Initiative

BACKGROUND

Multi-arm, multi-stage (MAMS) platform trials can accelerate the identification of disease-modifying treatments for Parkinson's disease (PD) but there is no current consensus on the optimal outcome measures (OM) for this approach.

OBJECTIVE

To provide an up-to-date inventory of OM for disease-modifying PD trials, and a framework for future selection of OM for such trials.

METHODS

As part of the Edmond J Safra Accelerating Clinical Trials in Parkinson Disease (EJS ACT-PD) initiative, an expert group with Patient and Public Involvement and Engagement (PPIE) representatives' input reviewed and evaluated available evidence on OM for potential use in trials to delay progression of PD. Each OM was ranked based on aspects such as validity, sensitivity to change, participant burden and practicality for a multi-site trial. Review of evidence and expert opinion led to the present inventory.

RESULTS

An extensive inventory of OM was created, divided into: general, motor and non-motor scales, diaries and fluctuation questionnaires, cognitive, disability and health-related quality of life, capability, quantitative motor, wearable and digital, combined, resource use, imaging and wet biomarkers, and milestone-based. A framework for evaluation of OM is presented to update the inventory in the future. PPIE input highlighted the need for OM which reflect their experience of disease progression and are applicable to diverse populations and disease stages.

CONCLUSION

We present a range of OM, classified according to a transparent framework, to aid selection of OM for disease-modifying PD trials, whilst allowing for inclusion or re-classification of relevant OM as new evidence emerges.

High risk of developing dementia in Parkinson's disease: a Swedish registry-based study

Dementia have substantial negative impact on the affected individual, their care partners and society. Persons living with Parkinson’s disease (PwP) are also to a large extent living with dementia. The aim of this study is to estimate time to dementia in PD using data from a large quality register with access to baseline clinical and patient reported data merged with Swedish national health registries. Persons with Parkinson’s disease in the Swedish Neuro Registries/Parkinson’s Disease Swedish PD Registry (PARKreg) in Sweden were included and linked to national health registries and matched by sex and age to controls without PD. Time to dementia was analysed with Cox regression models assuming proportional hazards, with time since diagnosis as the underlying time variable. In this large prospective cohort study, PwP had approximately four times higher risk of developing dementia as compared to age and sex-matched controls, a finding which remained after adjusting for potential confounders. The present results underline the high risk of dementia in PD and further emphasize the importance of developing symptomatic and ultimately disease modifying strategies to counteract this part of the non-motor symptomatology in PD.