Beta Amyloid Deposition Is Not Associated With Cognitive Impairment in Parkinson's Disease

Antineoplastics for treating Alzheimer's disease and dementia: Evidence from preclinical and observational studies

As the world population ages, there will be an increasing need for effective therapies for aging-associated neurodegenerative disorders, which remain untreatable. Dementia due to Alzheimer's disease (AD) is one of the leading neurological diseases in the aging population. Current therapeutic approaches to treat this disorder are solely symptomatic, making the need for new molecular entities acting on the causes of the disease extremely urgent. One of the potential solutions is to use compounds that are already in the market. The structures have known pharmacokinetics, pharmacodynamics, toxicity profiles, and patient data available in several countries. Several drugs have been used successfully to treat diseases different from their original purposes, such as autoimmunity and peripheral inflammation. Herein, we divulge the repurposing of drugs in the area of neurodegenerative diseases, focusing on the therapeutic potential of antineoplastics to treat dementia due to AD and dementia. We briefly touch upon the shared pathological mechanism between AD and cancer and drug repurposing strategies, with a focus on artificial intelligence. Next, we bring out the current status of research on the development of drugs, provide supporting evidence from retrospective, clinical, and preclinical studies on antineoplastic use, and bring in new areas, such as repurposing drugs for the prion-like spreading of pathologies in treating AD.

The long term effects of uncoupling interventions as a therapy for dementia in humans

In this paper we use simulation methods to study a hypothetical uncoupling agent as a therapy for dementia. We simulate the proliferation of mitochondrial deletion mutants amongst a population of wild-type in human neurons. Mitochondria play a key role in ATP generation. Clonal expansion can lead to the wild-type being overwhelmed by deletions such that a diminished population can no longer fulfil a cell's energy requirement, eventually leading to its demise. The intention of uncoupling is to reduce the formation of deletion mutants by reducing mutation rate. However, a consequence of uncoupling is that the energy production efficacy is also reduced which in turn increases wild-type copy number in order to compensate for the energy deficit. The results of this paper showed that uncoupling reduced the severity of dementia, however, there was some increase in cognitive dysfunction pre-onset of dementia. The effectiveness of uncoupling was dependent upon the timing of intervention relative to the onset of dementia and would necessitate predicting its onset many years in advance.

Radionuclide Imaging of the Neuroanatomical and Neurochemical Substrate of Cognitive Decline in Parkinson's Disease

Cognitive impairment is a frequent manifestation of Parkinson's disease (PD), resulting in decrease in patients' quality of life and increased societal and economic burden. However, cognitive decline in PD is highly heterogenous and the mechanisms are poorly understood. Radionuclide imaging techniques like positron emission tomography (PET) and single photon emission computed tomography (SPECT) have been used to investigate the neurochemical and neuroanatomical substrate of cognitive decline in PD. These techniques allow the assessment of different neurotransmitter systems, changes in brain glucose metabolism, proteinopathy, and neuroinflammation in vivo in PD patients. Here, we review current radionuclide imaging research on cognitive deficit in PD with a focus on predicting accelerating cognitive decline. This research could assist in the development of prognostic biomarkers for patient stratification and have utility in the development of ameliorative or disease-modifying therapies targeting cognitive deficit in PD.

Amyloid-beta and tau protein beyond Alzheimer's disease

ABSTRACT

The aggregation of amyloid-beta peptide and tau protein dysregulation are implicated to play key roles in Alzheimer's disease pathogenesis and are considered the main pathological hallmarks of this devastating disease. Physiologically, these two proteins are produced and expressed within the normal human body. However, under pathological conditions, abnormal expression, post-translational modifications, conformational changes, and truncation can make these proteins prone to aggregation, triggering specific disease-related cascades. Recent studies have indicated associations between aberrant behavior of amyloid-beta and tau proteins and various neurological diseases, such as Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis, as well as retinal neurodegenerative diseases like Glaucoma and age-related macular degeneration. Additionally, these proteins have been linked to cardiovascular disease, cancer, traumatic brain injury, and diabetes, which are all leading causes of morbidity and mortality. In this comprehensive review, we provide an overview of the connections between amyloid-beta and tau proteins and a spectrum of disorders.

Deep Learning-Driven Estimation of Centiloid Scales from Amyloid PET Images with 11C-PiB and 18F-Labeled Tracers in Alzheimer's Disease

BACKGROUND

Standard methods for deriving Centiloid scales from amyloid PET images are time-consuming and require considerable expert knowledge. We aimed to develop a deep learning method of automating Centiloid scale calculations from amyloid PET images with 11C-Pittsburgh Compound-B (PiB) tracer and assess its applicability to 18F-labeled tracers without retraining.

METHODS

We trained models on 231 11C-PiB amyloid PET images using a 50-layer 3D ResNet architecture. The models predicted the Centiloid scale, and accuracy was assessed using mean absolute error (MAE), linear regression analysis, and Bland-Altman plots.

RESULTS

The MAEs for Alzheimer's disease (AD) and young controls (YC) were 8.54 and 2.61, respectively, using 11C-PiB, and 8.66 and 3.56, respectively, using 18F-NAV4694. The MAEs for AD and YC were higher with 18F-florbetaben (39.8 and 7.13, respectively) and 18F-florbetapir (40.5 and 12.4, respectively), and the error rate was moderate for 18F-flutemetamol (21.3 and 4.03, respectively). Linear regression yielded a slope of 1.00, intercept of 1.26, and R2 of 0.956, with a mean bias of -1.31 in the Centiloid scale prediction.

CONCLUSIONS

We propose a deep learning means of directly predicting the Centiloid scale from amyloid PET images in a native space. Transferring the model trained on 11C-PiB directly to 18F-NAV4694 without retraining was feasible.

Early-phase amyloid PET reproduces metabolic signatures of cognitive decline in Parkinson's disease

INTRODUCTION

Recent work suggests that amyloid beta (Aβ) positron emission tomography (PET) tracer uptake shortly after injection ("early phase") reflects brain metabolism and perfusion. We assessed this modality in a predominantly amyloid-negative neurodegenerative condition, Parkinson's disease (PD), and hypothesized that early-phase 18F-florbetaben (eFBB) uptake would reproduce characteristic hypometabolism and hypoperfusion patterns associated with cognitive decline in PD.

METHODS

One hundred fifteen PD patients across the spectrum of cognitive impairment underwent dual-phase Aβ PET, structural and arterial spin labeling (ASL) magnetic resonance imaging (MRI), and neuropsychological assessments. Multiple linear regression models compared eFBB uptake to cognitive performance and ASL MRI perfusion.

RESULTS

Reduced eFBB uptake was associated with cognitive performance in brain regions previously linked to hypometabolism-associated cognitive decline in PD, independent of amyloid status. Furthermore, eFBB uptake correlated with cerebral perfusion across widespread regions.

DISCUSSION

EFBB uptake is a potential surrogate measure for cerebral perfusion/metabolism. A dual-phase PET imaging approach may serve as a clinical tool for assessing cognitive impairment.

Highlights

Images taken at amyloid beta (Aβ) positron emission tomography tracer injection may reflect brain perfusion and metabolism.Parkinson's disease (PD) is a predominantly amyloid-negative condition.Early-phase florbetaben (eFBB) in PD was associated with cognitive performance.eFBB uptake reflects hypometabolism-related cognitive decline in PD.eFBB correlated with arterial spin labeling magnetic resonance imaging measured cerebral perfusion.eFBB distinguished dementia from normal cognition and mild cognitive impairment.Findings were independent of late-phase Aβ burden.Thus, eFBB may serve as a surrogate measure for brain metabolism/perfusion.

Multiomics Blood-Based Biomarkers Predict Alzheimer's Predementia with High Specificity in a Multicentric Cohort Study

BACKGROUND

The primary criteria for diagnosing mild cognitive impairment (MCI) due to Alzheimer's Disease (AD) or probable mild AD dementia rely partly on cognitive assessments and the presence of amyloid plaques. Although these criteria exhibit high sensitivity in predicting AD among cognitively impaired patients, their specificity remains limited. Notably, up to 25% of non-demented patients with amyloid plaques may be misdiagnosed with MCI due to AD, when in fact they suffer from a different brain disorder. The introduction of anti-amyloid antibodies complicates this scenario. Physicians must prioritize which amyloid-positive MCI patients receive these treatments, as not all are suitable candidates. Specifically, those with non-AD amyloid pathologies are not primary targets for amyloid-modifying therapies. Consequently, there is an escalating medical necessity for highly specific blood biomarkers that can accurately detect pre-dementia AD, thus optimizing amyloid antibody prescription.

OBJECTIVES

The objective of this study was to evaluate a predictive model based on peripheral biomarkers to identify MCI and mild dementia patients who will develop AD dementia symptoms in cognitively impaired population with high specificity.

DESIGN

Peripheral biomarkers were identified in a gene transfer-based animal model of AD and then validated during a retrospective multi-center clinical study.

SETTING

Participants from 7 retrospective cohorts (US, EU and Australia).

PARTICIPANTS

This study followed 345 cognitively impaired individuals over up to 13 years, including 193 with MCI and 152 with mild dementia, starting from their initial visits. The final diagnoses, established during their last assessments, classified 249 participants as AD patients and 96 as having non-AD brain disorders, based on the specific diagnostic criteria for each disorder subtype. Amyloid status, assessed at baseline, was available for 82.9% of the participants, with 61.9% testing positive for amyloid. Both amyloid-positive and negative individuals were represented in each clinical group. Some of the AD patients had co-morbidities such as metabolic disorders, chronic diseases, or cardiovascular pathologies.

MEASUREMENTS

We developed targeted mass spectrometry assays for 81 blood-based biomarkers, encompassing 45 proteins and 36 metabolites previously identified in AAV-AD rats.

METHODS

We analyzed blood samples from study participants for the 81 biomarkers. The B-HEALED test, a machine learning-based diagnostic tool, was developed to differentiate AD patients, including 123 with Prodromal AD and 126 with mild AD dementia, from 96 individuals with non-AD brain disorders. The model was trained using 70% of the data, selecting relevant biomarkers, calibrating the algorithm, and establishing cutoff values. The remaining 30% served as an external test dataset for blind validation of the predictive accuracy.

RESULTS

Integrating a combination of 19 blood biomarkers and participant age, the B-HEALED model successfully distinguished participants that will develop AD dementia symptoms (82 with Prodromal AD and 83 with AD dementia) from non-AD subjects (71 individuals) with a specificity of 93.0% and sensitivity of 65.4% (AUROC=81.9%, p<0.001) during internal validation. When the amyloid status (derived from CSF or PET scans) and the B-HEALED model were applied in association, with individuals being categorized as AD if they tested positive in both tests, we achieved 100% specificity and 52.8% sensitivity. This performance was consistent in blind external validation, underscoring the model's reliability on independent datasets.

CONCLUSIONS

The B-HEALED test, utilizing multiomics blood-based biomarkers, demonstrates high predictive specificity in identifying AD patients within the cognitively impaired population, minimizing false positives. When used alongside amyloid screening, it effectively identifies a nearly pure prodromal AD cohort. These results bear significant implications for refining clinical trial inclusion criteria, facilitating drug development and validation, and accurately identifying patients who will benefit the most from disease-modifying AD treatments.

Pathobiology of Cognitive Impairment in Parkinson Disease: Challenges and Outlooks

Cognitive impairment (CI) is a characteristic non-motor feature of Parkinson disease (PD) that poses a severe burden on the patients and caregivers, yet relatively little is known about its pathobiology. Cognitive deficits are evident throughout the course of PD, with around 25% of subtle cognitive decline and mild CI (MCI) at the time of diagnosis and up to 83% of patients developing dementia after 20 years. The heterogeneity of cognitive phenotypes suggests that a common neuropathological process, characterized by progressive degeneration of the dopaminergic striatonigral system and of many other neuronal systems, results not only in structural deficits but also extensive changes of functional neuronal network activities and neurotransmitter dysfunctions. Modern neuroimaging studies revealed multilocular cortical and subcortical atrophies and alterations in intrinsic neuronal connectivities. The decreased functional connectivity (FC) of the default mode network (DMN) in the bilateral prefrontal cortex is affected already before the development of clinical CI and in the absence of structural changes. Longitudinal cognitive decline is associated with frontostriatal and limbic affections, white matter microlesions and changes between multiple functional neuronal networks, including thalamo-insular, frontoparietal and attention networks, the cholinergic forebrain and the noradrenergic system. Superimposed Alzheimer-related (and other concomitant) pathologies due to interactions between α-synuclein, tau-protein and β-amyloid contribute to dementia pathogenesis in both PD and dementia with Lewy bodies (DLB). To further elucidate the interaction of the pathomechanisms responsible for CI in PD, well-designed longitudinal clinico-pathological studies are warranted that are supported by fluid and sophisticated imaging biomarkers as a basis for better early diagnosis and future disease-modifying therapies.

Biological Diagnosis of Alzheimer's Disease Based on Amyloid Status: An Illustration of Confirmation Bias in Medical Research?

Alzheimer's disease (AD) was first characterized by Dr. Alois Alzheimer in 1906 by studying a demented patient and discovering cerebral amyloid plaques and neurofibrillary tangles. Subsequent research highlighted the roles of Aβ peptides and tau proteins, which are the primary constituents of these lesions, which led to the amyloid cascade hypothesis. Technological advances, such as PET scans using Florbetapir, have made it possible to visualize amyloid plaques in living patients, thus improving AD's risk assessment. The National Institute on Aging and the Alzheimer's Association introduced biological diagnostic criteria in 2011, which underlined the amyloid deposits diagnostic value. However, potential confirmation bias may have led researchers to over-rely on amyloid markers independent of AD's symptoms, despite evidence of their limited specificity. This review provides a critical examination of the current research paradigm in AD, including, in particular, the predominant focus on amyloid and tau species in diagnostics. We discuss the potential multifaceted consequences of this approach and propose strategies to mitigate its overemphasis in the development of new biomarkers. Furthermore, our study presents comprehensive guidelines aimed at enhancing the creation of biomarkers for accurately predicting AD dementia onset. These innovations are crucial for refining patient selection processes in clinical trial enrollment and for the optimization of therapeutic strategies. Overcoming confirmation bias is essential to advance the diagnosis and treatment of AD and to move towards precision medicine by incorporating a more nuanced understanding of amyloid biomarkers.

Age-related hearing loss and dementia-related neuropathology: An analysis of the United Kingdom brains for dementia research cohort

Age-related hearing loss frequently precedes or coexists with mild cognitive impairment and dementia. The role specific neuropathologies play in this association, as either a cause or a consequence, is unclear. We therefore aimed to investigate whether specific dementia related neuropathologies were associated with hearing impairment in later life. We analysed data on ante-mortem hearing impairment with post-mortem neuropathological data for 442 participants from the Brains for Dementia Research Cohort. Binary logistic regression models were used to estimate the association of hearing impairment with the presence of each dementia-related neuropathology overall, and with specific staged changes. All analyses adjusted for age and sex, and several sensitivity analyses were conducted to test the robustness of findings. Presence and density of neuritic plaques were associated with higher odds of hearing impairment ante-mortem (OR = 3.65, 95% CI 1.78-7.46 for frequent density of plaques). Presence of any LB disease was likewise associated with hearing impairment (OR = 2.10, 95% CI 1.27-3.48), but this did not increase with higher cortical pathology (OR = 1.53, 95% CI 0.75-3.11). Nonspecific amyloid deposition, neurofibrillary tangle staging, overall AD neuropathology level, and cerebrovascular disease were not clearly associated with increased risks of hearing impairment. Our results provide some support for an association between dementia-related neuropathology and hearing loss and suggest that hearing loss may be associated with a high neuritic plaque burden and more common in Lewy body disease.

Salivary levels of disease-related biomarkers in the early stages of Parkinson's and Alzheimer's disease: A cross-sectional study

Introduction

Finding a non-invasive and repeatable tool has been recommended to make an accurate diagnosis of Alzheimer's disease (AD) and Parkinson's disease (PD).

Methods

70 volunteers participated in three groups: 24 with mild dementia of AD, 24 in the first and second stages of PD, and 22 healthy controls. After valuing the scores of cognitive tests, the salivary levels of phosphorylated tau (p-tau), total alpha-synuclein (α-syn), and beta-amyloid 1-42 (Aβ)‏‎ proteins have been evaluated. Finally, the cutoff points, receiver operating characteristic (ROC), sensitivity, and specificity have been calculated to find accurate and detectable biomarkers.

Results

Findings showed that the salivary level of Aβ was higher in both PD (p < 0.01) and AD (p < 0.001) patients than in controls. Moreover, the level of α-syn in both PD and AD patients was similarly lower than in controls (p < 0.05). However, the level of p-tau was only ‎higher in the AD group than in the control (p < 0.01). Salivary Aβ 1-42 level at a 60.3 pg/ml cutoff point revealed an excellent performance for diagnosing AD (AUC: 0.81).

Conclusion

Evaluation of p-tau, α-syn, and Aβ 1-42 levels in the saliva of AD and PD patients could help the early diagnosis. The p-tau level might be valuable for differentiation between AD and PD. Therefore, these hopeful investigations could be done to reduce the usage of invasive diagnostic methods, which alone is a success in alleviating the suffering of AD and PD patients. Moreover, introducing accurate salivary biomarkers according to the pathophysiology of AD and PD should be encouraged.

Acquired Stuttering in Parkinson's Disease

Background

Parkinson's disease frequently causes communication impairments, but knowledge about the occurrence of new-onset stuttering is limited.

Objectives

To determine the presence of acquired neurogenic stuttering and its relationship with cognitive and motor functioning in individuals with Parkinson's disease.

Method

Conversation, picture description, and reading samples were collected from 100 people with Parkinson's disease and 25 controls to identify the presence of stuttered disfluencies (SD) and their association with neuropsychological test performance and motor function.

Results

Participants with Parkinson's disease presented with twice as many stuttered disfluencies during conversation (2.2% ± 1.8%SD) compared to control participants (1.2% ± 1.2%SD; P < 0.01). 21% of people with Parkinson's disease (n = 20/94) met the diagnostic criterion for stuttering, compared with 1/25 controls. Stuttered disfluencies also differed significantly across speech tasks, with more disfluencies during conversation compared to reading (P < 0.01). Stuttered disfluencies in those with Parkinson's disease were associated with longer time since disease onset (P < 0.01), higher levodopa equivalent dosage (P < 0.01), and lower cognitive (P < 0.01) and motor scores (P < 0.01).

Conclusion

One in five participants with Parkinson's disease presented with acquired neurogenic stuttering, suggesting that speech disfluency assessment, monitoring and intervention should be part of standard care. Conversation was the most informative task for identifying stuttered disfluencies. The frequency of stuttered disfluencies was higher in participants with worse motor functioning, and lower cognitive functioning. This challenges previous suggestions that the development of stuttered disfluencies in Parkinson's disease has purely a motoric basis.

β-Carotene, a Potent Amyloid Aggregation Inhibitor, Promotes Disordered Aβ Fibrillar Structure

The aggregation of amyloid beta (Aβ) into fibrillar aggregates is a key feature of Alzheimer’s disease (AD) pathology. β-carotene and related compounds have been shown to associate with amyloid aggregates and have direct impact on the formation of amyloid fibrils. However, the precise effect of β-carotene on the structure of amyloid aggregates is not known, which poses a limitation towards developing it as a potential AD therapeutic. In this report, we use nanoscale AFM-IR spectroscopy to probe the structure of Aβ oligomers and fibrils at the single aggregate level and demonstrate that the main effect of β-carotene towards modulating Aβ aggregation is not to inhibit fibril formation but to alter the secondary structure of the fibrils and promote fibrils that lack the characteristic ordered beta structure.

Mixed pathology as a rule, not exception: Time to reconsider disease nosology

Parkinson's disease is a progressive neurodegenerative disorder that is associated with motor and nonmotor symptoms. Accumulation of misfolded α-synuclein is considered a key pathological feature during disease initiation and progression. While clearly deemed a synucleinopathy, the development of amyloid-β plaques, tau-containing neurofibrillary tangles, and even TDP-43 protein inclusions occur within the nigrostriatal system and in other brain regions. In addition, inflammatory responses, manifested by glial reactivity, T-cell infiltration, and increased expression of inflammatory cytokines, plus other toxic mediators derived from activated glial cells, are currently recognized as prominent drivers of Parkinson's disease pathology. However, copathologies have increasingly been recognized as the rule (>90%) and not the exception, with Parkinson's disease cases on average exhibiting three different copathologies. While microinfarcts, atherosclerosis, arteriolosclerosis, and cerebral amyloid angiopathy may have an impact on disease progression, α-synuclein, amyloid-β, and TDP-43 pathology do not seem to contribute to progression.

Longitudinal striatal dopamine transporter binding and cerebrospinal fluid alpha-synuclein, amyloid beta, total tau, and phosphorylated tau in Parkinson's disease

BACKGROUND

Previous studies investigated CSF levels of α-synuclein (α-syn), amyloid-β (Aβ1-42), total tau (t-tau), and phosphorylated tau (p-tau) with clinical progression of Parkinson's disease (PD). However, there is limited data on the association between CSF biomarkers and dopamine uptake status in PD.

AIM

In the current study, we aim to investigate the longitudinal association between striatal dopaminergic neuronal loss assessed by dopamine active transporter single photon emission computerized tomography (DaTSCAN) imaging with CSF α-syn, t-tau, p-tau, and Aβ1-42.

METHODS

A total of 413 early-stage PD patients and 187 healthy controls (HCs) from the PPMI. Striatal binding ratios (SBRs) of DaTSCAN images in caudate and putamen nuclei were calculated. We investigated the cross-sectional and longitudinal association between CSF biomarkers and dopamine uptake using partial correlation models adjusted for the effect of age, sex, and years of education over 24 months of follow-up.

RESULTS

The level of CSF α-syn, Aβ1-42, t-tau, and p-tau was significantly higher in HCs compared to PD groups at any time point. We found that higher CSF α-syn was associated with a higher SBR score in the left caudate at baseline (P = 0.038) and after 12 months (P = 0.012) in PD patients. Moreover, SBR scores in the left caudate and CSF Aβ1-42 were positively correlated at baseline (P = 0.021), 12 months (P = 0.006), and 24 months (P = 0.014) in patients with PD. Our findings demonstrated that change in CSF Aβ1-42 was positively correlated with change in SBR score in the left caudate after 24 months in the PD group (P = 0.043).

CONCLUSION

We found that cross-sectional levels of α-syn and Aβ1-42 could reflect the degree of dopaminergic neuron loss in the left caudate nucleus. Interestingly, longitudinal changes in CSF Aβ1-42 could predict the severity of left caudal dopaminergic neuron loss throughout the disease. This suggested that Aβ pathology might precede dopaminergic loss in striatal nuclei in this case left caudate and subsequently cognitive impairment in PD patients, although future studies are needed to confirm our results and expand the understanding of the pathophysiology of cognitive dysfunction in PD.

Extracellular vesicle biomarkers for cognitive impairment in Parkinson's disease

Besides motor symptoms, many individuals with Parkinson's disease develop cognitive impairment perhaps due to coexisting α-synuclein and Alzheimer's disease pathologies and impaired brain insulin signalling. Discovering biomarkers for cognitive impairment in Parkinson's disease could help clarify the underlying pathogenic processes and improve Parkinson's disease diagnosis and prognosis. This study used plasma samples from 273 participants: 103 Parkinson's disease individuals with normal cognition, 121 Parkinson's disease individuals with cognitive impairment (81 with mild cognitive impairment, 40 with dementia) and 49 age- and sex-matched controls. Plasma extracellular vesicles enriched for neuronal origin were immunocaptured by targeting the L1 cell adhesion molecule, then biomarkers were quantified using immunoassays. α-Synuclein was lower in Parkinson's disease compared to control individuals (P = 0.004) and in cognitively impaired Parkinson's disease individuals compared to Parkinson's disease with normal cognition (P < 0.001) and control (P < 0.001) individuals. Amyloid-β42 did not differ between groups. Phosphorylated tau (T181) was higher in Parkinson's disease than control individuals (P = 0.003) and in cognitively impaired compared to cognitively normal Parkinson's disease individuals (P < 0.001) and controls (P < 0.001). Total tau was not different between groups. Tyrosine-phosphorylated insulin receptor substrate-1 was lower in Parkinson's disease compared to control individuals (P = 0.03) and in cognitively impaired compared to cognitively normal Parkinson's disease individuals (P = 0.02) and controls (P = 0.01), and also decreased with increasing motor symptom severity (P = 0.005); serine312-phosphorylated insulin receptor substrate-1 was not different between groups. Mechanistic target of rapamycin was not different between groups, whereas phosphorylated mechanistic target of rapamycin trended lower in cognitively impaired compared to cognitively normal Parkinson's disease individuals (P = 0.05). The ratio of α-synuclein to phosphorylated tau181 was lower in Parkinson's disease compared to controls (P = 0.001), in cognitively impaired compared to cognitively normal Parkinson's disease individuals (P < 0.001) and decreased with increasing motor symptom severity (P < 0.001). The ratio of insulin receptor substrate-1 phosphorylated serine312 to insulin receptor substrate-1 phosphorylated tyrosine was higher in Parkinson's disease compared to control individuals (P = 0.01), in cognitively impaired compared to cognitively normal Parkinson's disease individuals (P = 0.02) and increased with increasing motor symptom severity (P = 0.003). α-Synuclein, phosphorylated tau181 and insulin receptor substrate-1 phosphorylated tyrosine contributed in diagnostic classification between groups. These findings suggest that both α-synuclein and tau pathologies and impaired insulin signalling underlie Parkinson's disease with cognitive impairment. Plasma neuronal extracellular vesicles biomarkers may inform cognitive prognosis in Parkinson's disease.

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.

Cognitive Profile in Parkinson's Disease Dementia Patients with Low versus Normal Cerebrospinal Fluid Amyloid Beta

Introduction

In patients with Parkinson's disease (PD), low cerebrospinal fluid (CSF) amyloid beta 1-42 (Ab42) at baseline is the most consistent CSF biomarker as a risk factor for developing dementia. Low CSF Ab42 is, however, a typical hallmark of Alzheimer's disease (AD). Hence, low CSF Ab42 in patients with PD may indicate presence of comorbid AD pathology and may predict a more AD-like cognitive profile when they develop dementia. Our study aimed to investigate if low CSF Ab42 at baseline is associated with a more AD-like cognitive profile in PD patients with dementia.

Methods

In a prospectively followed-up, population-based cohort of newly diagnosed PD patients, we compared the cognitive profile of dementia in those with a low CSF Ab42 level at baseline with that of patients who had normal levels at the time when they developed dementia. Four different cognitive domain z-scores (memory, attention, executive, visuospatial) were calculated. Patients were subdivided into three tertiles or categorized dichotomously based on the baseline CSF Ab42 levels as measured by electrochemiluminescence and ELISA.

Results

During 10-year follow-up, 37 patients met the inclusion criteria. Memory domain composite z-scores, memory subtest z-scores, and the difference between long-delay free recall versus recognition scores were not significantly different between the groups. Composite z-scores of visuospatial functions significantly differed between the tertiles, which was not significant after Bonferroni correction. In the dichotomous group analysis, z-scores of visuospatial functions significantly differed between the two groups. The other cognitive domain z-scores were not significantly different.

Conclusions

In patients with PD dementia, low CSF Ab42 level at baseline is not associated with a specific cognitive profile.

Research Evidence of the Role of the Glymphatic System and Its Potential Pharmacological Modulation in Neurodegenerative Diseases

The glymphatic system is a unique pathway that utilises end-feet Aquaporin 4 (AQP4) channels within perivascular astrocytes, which is believed to cause cerebrospinal fluid (CSF) inflow into perivascular space (PVS), providing nutrients and waste disposal of the brain parenchyma. It is theorised that the bulk flow of CSF within the PVS removes waste products, soluble proteins, and products of metabolic activity, such as amyloid-β (Aβ). In the experimental model, the glymphatic system is selectively active during slow-wave sleep, and its activity is affected by both sleep dysfunction and deprivation. Dysfunction of the glymphatic system has been proposed as a potential key driver of neurodegeneration. This hypothesis is indirectly supported by the close relationship between neurodegenerative diseases and sleep alterations, frequently occurring years before the clinical diagnosis. Therefore, a detailed characterisation of the function of the glymphatic system in human physiology and disease would shed light on its early stage pathophysiology. The study of the glymphatic system is also critical to identifying means for its pharmacological modulation, which may have the potential for disease modification. This review will critically outline the primary evidence from literature about the dysfunction of the glymphatic system in neurodegeneration and discuss the rationale and current knowledge about pharmacological modulation of the glymphatic system in the animal model and its potential clinical applications in human clinical trials.

Machine learning can predict mild cognitive impairment in Parkinson's disease

BACKGROUND

Clinical markers of cognitive decline in Parkinson's disease (PD) encompass several mental non-motor symptoms such as hallucinations, apathy, anxiety, and depression. Furthermore, freezing of gait (FOG) and specific gait alterations have been associated with cognitive dysfunction in PD. Finally, although low cerebrospinal fluid levels of amyloid-β42 have been found to predict cognitive decline in PD, hitherto PET imaging of amyloid-β (Aβ) failed to consistently demonstrate the association between Aβ plaques deposition and mild cognitive impairment in PD (PD-MCI).

AIM

Finding significant features associated with PD-MCI through a machine learning approach.

PATIENTS AND METHODS

Patients were assessed with an extensive clinical and neuropsychological examination. Clinical evaluation included the assessment of mental non-motor symptoms and FOG using the specific items of the MDS-UPDRS I and II. Based on the neuropsychological examination, patients were classified as subjects without and with MCI (noPD-MCI, PD-MCI). All patients were evaluated using a motion analysis system. A subgroup of PD patients also underwent amyloid PET imaging. PD-MCI and noPD-MCI subjects were compared with a univariate statistical analysis on demographic data, clinical features, gait analysis variables, and amyloid PET data. Then, machine learning analysis was performed two times: Model 1 was implemented with age, clinical variables (hallucinations/psychosis, depression, anxiety, apathy, sleep problems, FOG), and gait features, while Model 2, including only the subgroup performing PET, was implemented with PET variables combined with the top five features of the former model.

RESULTS

Seventy-five PD patients were enrolled (33 PD-MCI and 42 noPD-MCI). PD-MCI vs. noPD-MCI resulted in older and showed worse gait patterns, mainly characterized by increased dynamic instability and reduced step length; when comparing amyloid PET data, the two groups did not differ. Regarding the machine learning analyses, evaluation metrics were satisfactory for Model 1 overcoming 80% for accuracy and specificity, whereas they were disappointing for Model 2.

CONCLUSIONS

This study demonstrates that machine learning implemented with specific clinical features and gait variables exhibits high accuracy in predicting PD-MCI, whereas amyloid PET imaging is not able to increase prediction. Additionally, our results prompt that a data mining approach on certain gait parameters might represent a reliable surrogate biomarker of PD-MCI.

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.

Beta amyloid deposition and cognitive decline in Parkinson's disease: a study of the PPMI cohort

The accumulation of beta amyloid in the brain has a complex and poorly understood impact on the progression of Parkinson's disease pathology and much controversy remains regarding its role, specifically in cognitive decline symptoms. Some studies have found increased beta amyloid burden is associated with worsening cognitive impairment in Parkinson's disease, especially in cases where dementia occurs, while other studies failed to replicate this finding. To better understand this relationship, we examined a cohort of 25 idiopathic Parkinson's disease patients and 30 healthy controls from the Parkinson's Progression Marker Initiative database. These participants underwent [¹⁸F]Florbetaben positron emission tomography scans to quantify beta amyloid deposition in 20 cortical regions. We then analyzed this beta amyloid data alongside the longitudinal Montreal Cognitive Assessment scores across 3 years to see how participant's baseline beta amyloid levels affected their cognitive scores prospectively. The first analysis we performed with these data was a hierarchical cluster analysis to help identify brain regions that shared similarity. We found that beta amyloid clusters differently in Parkinson's disease patients compared to healthy controls. In the Parkinson's disease group, increased beta amyloid burden in cluster 2 was associated with worse cognitive ability, compared to deposition in clusters 1 or 3. We also performed a stepwise linear regression where we found an adjusted R² of 0.495 (49.5%) in a model explaining the Parkinson's disease group's Montreal Cognitive Assessment score 1-year post-scan, encompassing the left gyrus rectus, the left anterior cingulate cortex, and the right parietal cortex. Taken together, these results suggest regional beta amyloid deposition alone has a moderate effect on predicting future cognitive decline in Parkinson's disease patients. The patchwork effect of beta amyloid deposition on cognitive ability may be part of what separates cognitive impairment from cognitive sparing in Parkinson's disease. Thus, we suggest it would be more useful to measure beta amyloid burden in specific brain regions rather than using a whole-brain global beta amyloid composite score and use this information as a tool for determining which Parkinson's disease patients are most at risk for future cognitive decline.

Nanoscale Infrared Spectroscopy Identifies Structural Heterogeneity in Individual Amyloid Fibrils and Prefibrillar Aggregates

Amyloid plaques are one of the central manifestations of Alzheimer's disease pathology. Aggregation of the amyloid beta (Aβ) protein from amorphous oligomeric species to mature fibrils has been extensively studied. However, structural heterogeneities in prefibrillar species, and how that affects the structure of later-stage aggregates are not yet well understood. The integration of infrared spectroscopy with atomic force microscopy (AFM-IR) allows for identifying the signatures of individual nanoscale aggregates by spatially resolving spectra. We use AFM-IR to demonstrate that amyloid oligomers exhibit significant structural variations as evidenced in their infrared spectra. This heterogeneity is transmitted to and retained in protofibrils and fibrils. We show that amyloid fibrils do not always conform to their putative ordered structure and structurally different domains exist in the same fibril. We further demonstrate that these structural heterogeneities manifest themselves as a lack of β sheet structure in amyloid plaques in Alzheimer's tissue using infrared imaging.

Nigral neuropathology of Parkinson's motor subtypes coincide with circuitopathies: a scoping review

The neuropathological substrates of Parkinson’s disease (PD) patients with motor subtypes tremor-dominance (TD), non-tremor dominance (nTD), postural instability and gait difficulty (PIGD), and akinetic-rigid (AR) are not completely differentiated. While extensive pathological research has been conducted on neuronal tissue of PD patients, data have not been discussed in the context of mechanistic circuitry theories differentiating motor subtypes. It is, therefore, expected that a more specific and tailored management of PD symptoms can be accomplished by understanding symptom-specific neuropathological mechanisms with the detail histology can provide. This scoping review gives an overview of the literature comparing TD and nTD PD motor subtypes by clarify observed pathology with underlying physiological circuitry theories. Studies using an array of pathological examination techniques have shown significant differences between TD and nTD PD subtypes. nTD PD patients show higher neuronal loss, gliosis, extraneuronal melanin deposits, and neuroaxonal dystrophy in multiple subregions of the substantia nigra (SN) related to the overactivity of the indirect motor loop. TD patients show more severe cell loss specifically in medial SN subdivisions, and have damage in the retrorubral field A-8 that projects to the dorsolateral striatum and ventromedial thalamus in the direct motor loop. Pathological studies are consistent with neuroimaging data and support contemporary mechanistic circuitry theories of PD motor symptom genesis. Further multimodal neuroimaging and histological studies are required to validate and expand upon these findings.

Morphological basis of Parkinson disease-associated cognitive impairment: an update

Cognitive impairment is one of the most salient non-motor symptoms of Parkinson disease (PD) that poses a significant burden on the patients and carers as well as being a risk factor for early mortality. People with PD show a wide spectrum of cognitive dysfunctions ranging from subjective cognitive decline and mild cognitive impairment (MCI) to frank dementia. The mean frequency of PD with MCI (PD-MCI) is 25.8% and the pooled dementia frequency is 26.3% increasing up to 83% 20 years after diagnosis. A better understanding of the underlying pathological processes will aid in directing disease-specific treatment. Modern neuroimaging studies revealed considerable changes in gray and white matter in PD patients with cognitive impairment, cortical atrophy, hypometabolism, dopamine/cholinergic or other neurotransmitter dysfunction and increased amyloid burden, but multiple mechanism are likely involved. Combined analysis of imaging and fluid markers is the most promising method for identifying PD-MCI and Parkinson disease dementia (PDD). Morphological substrates are a combination of Lewy- and Alzheimer-associated and other concomitant pathologies with aggregation of α-synuclein, amyloid, tau and other pathological proteins in cortical and subcortical regions causing destruction of essential neuronal networks. Significant pathological heterogeneity within PD-MCI reflects deficits in various cognitive domains. This review highlights the essential neuroimaging data and neuropathological changes in PD with cognitive impairment, the amount and topographical distribution of pathological protein aggregates and their pathophysiological relevance. Large-scale clinicopathological correlative studies are warranted to further elucidate the exact neuropathological correlates of cognitive impairment in PD and related synucleinopathies as a basis for early diagnosis and future disease-modifying therapies.

Quantification of Brain β-Amyloid Load in Parkinson's Disease With Mild Cognitive Impairment: A PET/MRI Study

Background

Mild cognitive impairment in Parkinson's disease (PD-MCI) is associated with faster cognitive decline and conversion to dementia. There is uncertainty about the role of β-amyloid (Aβ) co-pathology and its contribution to the variability in PD-MCI profile and cognitive progression.

Objective

To study how presence of Aβ affects clinical and cognitive manifestations as well as regional brain volumes in PD-MCI.

Methods

Twenty-five PD-MCI patients underwent simultaneous PET/3T-MRI with [¹⁸F]flutemetamol and a clinical and neuropsychological examination allowing level II diagnosis. We tested pairwise differences in motor, clinical, and cognitive features with Mann–Whitney U test. We calculated [¹⁸F]flutemetamol (FMM) standardized uptake value ratios (SUVR) in striatal and cortical ROIs, and we performed a univariate linear regression analysis between the affected cognitive domains and the mean SUVR. Finally, we investigated differences in cortical and subcortical brain regional volumes with magnetic resonance imaging (MRI).

Results

There were 8 Aβ+ and 17 Aβ- PD-MCI. They did not differ for age, disease duration, clinical, motor, behavioral, and global cognition scores. PD-MCI-Aβ+ showed worse performance in the overall executive domain (p = 0.037). Subcortical ROIs analysis showed significant Aβ deposition in PD-MCI-Aβ+ patients in the right caudal and rostral middle frontal cortex, in precuneus, in left paracentral and pars triangularis (p < 0.0001), and bilaterally in the putamen (p = 0.038). Cortical regions with higher amyloid load correlated with worse executive performances (p < 0.05). Voxel-based morphometry (VBM) analyses showed no between groups differences.

Conclusions

Presence of cerebral Aβ worsens executive functions, but not motor and global cognitive abilities in PD-MCI, and it is not associated with middle-temporal cortex atrophy. These findings, together with the observation of significant proportion of PD-MCI-Aβ-, suggest that Aβ may not be the main pathogenetic determinant of cognitive deterioration in PD-MCI, but it would rather aggravate deficits in domains vulnerable to Parkinson primary pathology.

Imaging Cognitive Impairment and Impulse Control Disorders in Parkinson's Disease

Dementia and mild forms of cognitive impairment as well as neuropsychiatric symptoms (i. e., impulse control disorders) are frequent and disabling non-motor symptoms of Parkinson's disease (PD). The identification of changes in neuroimaging studies for the early diagnosis and monitoring of the cognitive and neuropsychiatric symptoms associated with Parkinson's disease, as well as their pathophysiological understanding, are critical for the development of an optimal therapeutic approach. In the current literature review, we present an update on the latest structural and functional neuroimaging findings, including high magnetic field resonance and radionuclide imaging, assessing cognitive dysfunction and impulse control disorders in PD.

No Influence of Age-Related Hearing Loss on Brain Amyloid-β

BACKGROUND

Hearing loss is independently associated with a faster rate of cognitive decline in older adults and has been identified as a modifiable risk factor for dementia. The mechanism for this association is unknown, and there has been limited exploration of potential casual pathology.

OBJECTIVE

Our objective was to investigate whether there was an association between degree of audiometrically measured hearing loss (HL) and brain amyloid-β (Aβ) in a pre-clinical sample.

METHODS

Participants of the Australian Imaging and Biomarker Longitudinal Study (AIBL; n = 143) underwent positron emission tomography (PET) imaging and objective measurement of hearing thresholds within 5 years of imaging, as well as cognitive assessment within 2 years of imaging in this observational cohort study.

RESULTS

With one exception, study participants who had cognitive assessments within 2 years of their PET imaging (n = 113) were classified as having normal cognition. There was no association between cognitive scores and degree of hearing loss, or between cognitive scores and Aβ load. No association between HL and Aβ load was found once age was controlled for. As previously reported, positive Apolipoprotein E4 (APOE4) carrier status increased the risk of being Aβ positive (p = 0.002).

CONCLUSION

Degree of HL was not associated with positive Aβ status.

The role of amyloids in Alzheimer's and Parkinson's diseases

With varying clinical symptoms, most neurodegenerative diseases are associated with abnormal loss of neurons. They share the same common pathogenic mechanisms involving misfolding and aggregation, and these visible aggregates of proteins are deposited in the central nervous system. Amyloid formation is thought to arise from partial unfolding of misfolded proteins leading to the exposure of hydrophobic surfaces, which interact with other similar structures and give rise to form dimers, oligomers, protofibrils, and eventually mature fibril aggregates. Accumulating evidence indicates that amyloid oligomers, not amyloid fibrils, are the most toxic species that causes Alzheimer's disease (AD) and Parkinson's disease (PD). AD has recently been recognized as the 'twenty-first century plague', with an incident rate of 1% at 60 years of age, which then doubles every fifth year. Currently, 5.3 million people in the US are afflicted with this disease, and the number of cases is expected to rise to 13.5 million by 2050. PD, a disorder of the brain, is the second most common form of dementia, characterized by difficulty in walking and movement. Keeping the above views in mind, in this review we have focused on the roles of amyloid in neurodegenerative diseases including AD and PD, the involvement of amyloid in mitochondrial dysfunction leading to neurodegeneration, are also considered in the review.

Amyloid-β PET Classification on Cognitive Aging Stages Using the Centiloid Scale

PROPOSE

This study aims to explore the use of the Centiloid (CL) method in amyloid-β PET quantification to evaluate distinct cognitive aging stages, investigating subjects' mismatch classification using different cut-points for amyloid-β positivity.

PROCEDURES

The CL equation was applied in four groups of individuals: SuperAgers (SA), healthy age-matched controls (AC), healthy middle-aged controls (MC), and Alzheimer's disease (AD). The amyloid-β burden was calculated and compared between groups and quantitative variables. Three different cut-points (Jack CR, Wiste HJ, Weigand SD, et al., Alzheimer's Dement 13:205-216, 2017; Salvadó G, Molinuevo JL, Brugulat-Serrat A, et al., Alzheimer's Res Ther 11:27, 2019; and Amadoru S, Doré V, McLean CA, et al., Alzheimer's Res Ther 12:22, 2020) were applied in CL values to differentiate the earliest abnormal pathophysiological accumulation of Aβ and the established Aβ pathology.

RESULTS

The AD group exhibited a significantly increased Aβ burden compared to the MC, but not AC groups. Both healthy control (MC and AC) groups were not significantly different. Visually, the SA group showed a diverse distribution of CL values compared with MC; however, the difference was not significant. The CL values have a moderate and significant relationship between Aβ visual read, RAVLT DR and MMSE. Depending on the cut-point used, 10 CL, 19 CL, or 30 CL, 7.5% of our individuals had a different classification in the Aβ positivity. For the AC group, we obtained about 40 to 60% of the individuals classified as positive.

CONCLUSION

SuperAgers exhibited a similar Aβ load to AC and MC, differing in cognitive performance. Independently of cut-point used (10 CL, 19 CL, or 30 CL), three SA individuals were classified as Aβ positive, showing the duality between the individual's clinics and the biological definition of Alzheimer's. Different cut-points lead to Aβ positivity classification mismatch in individuals, and an extra care is needed for individuals who have a CL value between 10 and 30 CL.

Intracortical surface-based MR diffusivity to investigate neurologic and psychiatric disorders: a review

Diffusion tensor imaging (DTI) allows the quantification of water diffusivity within the cerebral cortex. Alterations in cortical mean diffusivity (MD) have been suggested to reflect microstructural damage. Interestingly, microstructural changes can be detected in the absence of macrostructural alterations such as cortical thinning or gray matter volume loss. However, volume-based neuroimaging techniques for the study of cortical MD have shown some limitations in terms of intersubject registration, partial volume correction, and smoothing artifacts. In this review, we summarize how a surface-based approach for the assessment of intracortical MD has not only overcome these technical limitations, but also provided important contributions to the fields of neurology and psychiatry. Since its proposal in 2018, the use of this neuroimaging technique has revealed cortical microstructural alterations in a wide range of clinical contexts, including Alzheimer's disease, Parkinson's disease, schizophrenia, Huntington's disease, multiple sclerosis, amyotrophic lateral sclerosis, and primary progressive aphasia. In most cases, the detection of early intracortical MD alterations preceded the identification of macrostructural changes. Importantly, microstructural damage significantly correlated with cognitive performance and biomarker measures, suggesting a potential role for its use in clinical trials as a sensitive imaging marker of neurodegeneration. Given that DTI is a widely available imaging modality, these encouraging results motivate further research using this novel neuroimaging metric in other clinical contexts. Overall, this technique has shed light into the key role of early cortical degeneration in many diseases where cortical involvement was previously thought to have limited clinical and biological significance.

The contribution of beta-amyloid to dementia in Lewy body diseases: a 1-year follow-up study

Dementia in Lewy Body Diseases (Parkinson’s disease and dementia with Lewy Bodies) affects progression of disabilities, quality of life and well-being. Understanding its pathogenetic mechanisms is critical to properly implement disease-modifying strategies. It has been hypothesized that synuclein- and amyloid-pathology act synergistically aggravating cognitive decline in elderly patients but their precise contribution to dementia is debated. In this study, we aimed at exploring if presence of amyloid deposits influences clinical, cognitive and neuroanatomical correlates of mental decline in a cohort of 40 Parkinson’s disease patients with normal cognition (n = 5), mild cognitive impairment (n = 22), and dementia (n = 13) as well as in Dementia with Lewy Bodies (n = 10). Patients underwent simultaneous 3 T PET/MRI with [¹⁸F]-flutemetamol and were assessed with an extensive baseline motor and neuropsychological examination, which allowed level II diagnosis of mild cognitive impairment and dementia. The role of amyloid positivity on each cognitive domain, and on the rate of conversion to dementia at 1-year follow-up was explored. A Kaplan Meier and the Log Rank (Mantel–Cox) test were used to assess the pairwise differences in time-to-develop dementia in Parkinson’s disease patients with and without significant amyloidosis. Furthermore, the presence of an Alzheimer’s dementia-like morphological pattern was evaluated using visual and automated assessment of T₁-weighted and T₂-weighted MRI images. We observed similar percentage of amyloid deposits in Parkinson’s disease dementia and dementia with Lewy Bodies cohorts (50% in each group) with an overall prevalence of 34% of significant amyloid depositions in Lewy Body Diseases. PET amyloid positivity was associated with worse global cognition (Montreal Cognitive Assessment and Mini Mental State Examination), executive and language difficulties. At 12-month follow-up, amyloid positive Parkinson’s disease patients were more likely to have become demented than those without amyloidosis. Moreover, there was no difference in the presence of an Alzheimer’s disease-like atrophy pattern and in vascular load (at Fazekas scale) between Lewy Body Diseases with and without significant amyloid deposits. Our findings suggest that in Lewy Body Diseases, amyloid deposition enhances cognitive deficits, particularly attention-executive and language dysfunctions. However, the large number of patients without significant amyloid deposits among our cognitively impaired patients indicates that synuclein pathology itself plays a critical role in the development of dementia in Lewy Body Diseases.

Parkinson disease-associated cognitive impairment

Parkinson disease (PD) is the second most common neurodegenerative disorder, affecting >1% of the population ≥65 years of age and with a prevalence set to double by 2030. In addition to the defining motor symptoms of PD, multiple non-motor symptoms occur; among them, cognitive impairment is common and can potentially occur at any disease stage. Cognitive decline is usually slow and insidious, but rapid in some cases. Recently, the focus has been on the early cognitive changes, where executive and visuospatial impairments are typical and can be accompanied by memory impairment, increasing the risk for early progression to dementia. Other risk factors for early progression to dementia include visual hallucinations, older age and biomarker changes such as cortical atrophy, as well as Alzheimer-type changes on functional imaging and in cerebrospinal fluid, and slowing and frequency variation on EEG. However, the mechanisms underlying cognitive decline in PD remain largely unclear. Cortical involvement of Lewy body and Alzheimer-type pathologies are key features, but multiple mechanisms are likely involved. Cholinesterase inhibition is the only high-level evidence-based treatment available, but other pharmacological and non-pharmacological strategies are being tested. Challenges include the identification of disease-modifying therapies as well as finding biomarkers to better predict cognitive decline and identify patients at high risk for early and rapid cognitive impairment.

The Association of β-Amyloid with Cognition and Striatal Dopamine in Early, Non-Demented Parkinson's Disease

BACKGROUND

Co-occurrence of β-amyloid (Aβ) pathology has been reported in Parkinson's disease (PD), and Aβ deposition in the brain may contribute to cognitive decline in patients with PD. Whether striatal dopamine uptake and cognitive status differ with amyloid deposition has been reported in only a few studies.

OBJECTIVE

The purpose of this study was to investigate the association among striatal dopaminergic availability, Aβ-positivity, and motor and cognitive status in early and non-demented PD.

METHODS

A total of 98 newly-diagnosed, non-medicated, and non-demented patients with PD were included in this study. Cognitive status was assessed using neuropsychological testing. Patients with mild cognitive impairment (MCI) were stratified into two groups: amnestic MCI (aMCI) and non-amnestic MCI (naMCI). Patient motor status was examined using the Unified Parkinson's Disease Rating Scale (UPDRS) and positron emission tomography (PET) with 18F-N-(3-fluoropropyl)-2beta-carbon ethoxy-3beta-(4-iodophenyl) nortropane (18F-FP-CIT). All patients also underwent 18F-florbetaben (18F-FBB) PET and were divided based on the results into Aβ-positive and Aβ-negative groups.

RESULTS

Eighteen patients had Aβ-positivity in 18F-FBB PET and 67 had MCI. Sixteen of 18 with Aβ-positive patients had MCI. The Aβ-positive group had higher frequency of MCI, especially amnestic-type, and lower dopaminergic activities in the left ventral striatum, but not with UPDRS motor score.

CONCLUSION

Amyloid pathology was associated with MCI, especially amnestic-subtype, in early and non-demented PD patients and with low dopaminergic activities in the left ventral striatum. This finding suggests that PD patients with Aβ-positivity have AD-related cognitive pathophysiology in PD and associated impaired dopaminergic availability in the ventral striatum can affect the pathophysiology in various ways.

Investigating hypotheses of neurodegeneration by learning dynamical systems of protein propagation in the brain

We introduce a theoretical framework for estimating, comparing and interpreting mechanistic hypotheses on long term protein propagation across brain networks in neurodegenerative disorders (ND). The model is expressed within a Bayesian non-parametric regression setting, where mechanisms of protein dynamics are inferred by means of gradient matching on dynamical systems (DS). The Bayesian formalism, combined with stochastic variational inference, naturally allows for model comparison via assessment of model evidence, while providing uncertainty quantification of causal relationship underlying protein progressions. When applied to in-vivo AV45-PET brain imaging data measuring topographic amyloid deposition in Alzheimer's disease (AD), our model identified the mechanisms of accumulation, clearance and propagation as the best suited DS for bio-mechanical description of amyloid dynamics in AD, enabling realistic and accurate personalized simulation of amyloidosis.

Multiparametric magnetic resonance imaging and positron emission tomography findings in neurodegenerative diseases: Current status and future directions

Neurodegenerative diseases (NDDs) are characterized by progressive neuronal loss, leading to dementia and movement disorders. NDDs broadly include Alzheimer's disease, frontotemporal lobar degeneration, parkinsonian syndromes, and prion diseases. There is an ever-increasing prevalence of mild cognitive impairment and dementia, with an accompanying immense economic impact, prompting efforts aimed at early identification and effective interventions. Neuroimaging is an essential tool for the early diagnosis of NDDs in both clinical and research settings. Structural, functional, and metabolic imaging modalities, including magnetic resonance imaging (MRI) and positron emission tomography (PET), are widely available. They show encouraging results for diagnosis, monitoring, and treatment response evaluation. The current review focuses on the complementary role of various imaging modalities in relation to NDDs, the qualitative and quantitative utility of newer MRI techniques, novel radiopharmaceuticals, and integrated PET/MRI in the setting of NDDs.

Novel PET Biomarkers to Disentangle Molecular Pathways across Age-Related Neurodegenerative Diseases

There is a need to disentangle the etiological puzzle of age-related neurodegenerative diseases, whose clinical phenotypes arise from known, and as yet unknown, pathways that can act distinctly or in concert. Enhanced sub-phenotyping and the identification of in vivo biomarker-driven signature profiles could improve the stratification of patients into clinical trials and, potentially, help to drive the treatment landscape towards the precision medicine paradigm. The rapidly growing field of neuroimaging offers valuable tools to investigate disease pathophysiology and molecular pathways in humans, with the potential to capture the whole disease course starting from preclinical stages. Positron emission tomography (PET) combines the advantages of a versatile imaging technique with the ability to quantify, to nanomolar sensitivity, molecular targets in vivo. This review will discuss current research and available imaging biomarkers evaluating dysregulation of the main molecular pathways across age-related neurodegenerative diseases. The molecular pathways focused on in this review involve mitochondrial dysfunction and energy dysregulation; neuroinflammation; protein misfolding; aggregation and the concepts of pathobiology, synaptic dysfunction, neurotransmitter dysregulation and dysfunction of the glymphatic system. The use of PET imaging to dissect these molecular pathways and the potential to aid sub-phenotyping will be discussed, with a focus on novel PET biomarkers.

Clustering of Alzheimer's and Parkinson's disease based on genetic burden of shared molecular mechanisms

One of the visions of precision medicine has been to re-define disease taxonomies based on molecular characteristics rather than on phenotypic evidence. However, achieving this goal is highly challenging, specifically in neurology. Our contribution is a machine-learning based joint molecular subtyping of Alzheimer's (AD) and Parkinson's Disease (PD), based on the genetic burden of 15 molecular mechanisms comprising 27 proteins (e.g. APOE) that have been described in both diseases. We demonstrate that our joint AD/PD clustering using a combination of sparse autoencoders and sparse non-negative matrix factorization is reproducible and can be associated with significant differences of AD and PD patient subgroups on a clinical, pathophysiological and molecular level. Hence, clusters are disease-associated. To our knowledge this work is the first demonstration of a mechanism based stratification in the field of neurodegenerative diseases. Overall, we thus see this work as an important step towards a molecular mechanism-based taxonomy of neurological disorders, which could help in developing better targeted therapies in the future by going beyond classical phenotype based disease definitions.

On the Role of Platelet-Generated Amyloid Beta Peptides in Certain Amyloidosis Health Complications

As do many other immunity-related blood cells, platelets release antimicrobial peptides that kill bacteria, fungi, and even certain viruses. Here we review the literature suggesting that there is a similarity between the antimicrobials released by other blood cells and the amyloid-related Aβ peptide released by platelets. Analyzing the literature, we also propose that platelet-generated Aβ amyloidosis may be more common than currently recognized. This systemic Aβ from a platelet source may participate in various forms of amyloidosis in pathologies ranging from brain cancer, glaucoma, skin Aβ accumulation, and preeclampsia to Alzheimer’s disease and late-stage Parkinson’s disease. We also discuss the advantages and disadvantages of specific animal models for studying platelet-related Aβ. This field is undergoing rapid change, as it evaluates competing ideas in the light of new experimental observations. We summarized both in order to clarify the role of platelet-generated Aβ peptides in amyloidosis-related health disorders, which may be helpful to researchers interested in this growing area of investigation.

The Impact of Amyloid-Beta Positivity with 18F-Florbetaben PET on Neuropsychological Aspects in Parkinson's Disease Dementia

The neuropathology of Parkinson’s disease dementia (PDD) is heterogenous, and the impacts of each pathophysiology and their synergistic effects are not fully understood. The aim of this study was to evaluate the frequency and impacts of co-existence with Alzheimer’s disease in patients with PDD by using 18F-florbetaben PET imaging. A total of 23 patients with PDD participated in the study. All participants underwent 18F-florbetaben PET and completed a standardized neuropsychological battery and assessment of motor symptoms. The results of cognitive tests, neuropsychiatric symptoms, and motor symptoms were analyzed between the positive and negative 18F-florbetaben PET groups. Four patients (17.4%) showed significant amyloid burden. Patients with amyloid-beta showed poorer performance in executive function and more severe neuropsychiatric symptoms than those without amyloid-beta. Motor symptoms assessed by UPDRS part III and the modified H&Y Scale were not different between the two groups. The amyloid PET scan of a patient with PDD can effectively reflect a co-existing Alzheimer’s disease pathology. Amyloid PET scans might be able to help physicians of PDD patients showing rapid progression or severe cognitive/behavioral features.

18F-Florbetaben Amyloid PET Imaging: A Chinese Study in Cognitive Normal Controls, Mild Cognitive Impairment, and Alzheimer's Disease Patients

Objective

To evaluate amyloid-β deposition with ¹⁸F-florbetaben (FBB) PET imaging against ¹¹C-PIB PET in cognitive normal controls (NC), mild cognitive impairment (MCI), and Alzheimer’s disease (AD) patients.

Methods

We recruited 45 subjects (15 in each group of NC, MCI, and mild/moderate AD) who had undergone dynamic ¹⁸F-FBB amyloid PET imaging. For comparison study, 17 participants, including six NC, five MCI, and six AD patients, also underwent ¹¹C-PIB PET imaging on separate days. Standardized uptake value ratios (SUVR) were calculated using the cerebellar cortex as the reference region with regions of interest (ROI) manually defined on co-registered CT. Quantitative analysis of mean cortical uptake was calculated using global SUVR. Spearman correlation analysis between MMSE scores and SUVR of 18F-FBB and 11C-PIB images were calculated.

Results

One (7%) of the 15 NC participants, nine (60%) of 15 MCI patients, and 12 (80%) of 15 AD patients had amyloid-positive lesions on ¹⁸F-FBB PET images. In AD patients, global SUVR was significantly higher than those of MCI patients (1.73 ± 0.62 vs. 1.55 ± 0.11, P < 0.001) and NC subjects (1.73 ± 0.62 vs. 1.13 ± 0.43, P < 0.001). In the comparison study, one NC participant, five MCI patients, and five AD patients had amyloid-positive lesions on ¹¹C-PIB PET images. There was a significant linear correlation (r² = 0.81, P < 0.001) between ¹⁸F-FBB and PIB global SUVR values. MMSE scores had negative correlations with SUVR on ¹¹C-PIB PET (r₁ = –0.650, P = 0.005) or SUVR on ¹⁸F-FBB PET (r₂ = –0.754, P < 0.0001).

Conclusion

Our study suggests that ¹⁸F-FBB is a useful tracer for the evaluation of amyloid-β deposition in vivo and that global SUVR of ¹⁸F-FBB PET might be a reliable tool in the diagnosis of AD.

Cognition Deficits in Parkinson's Disease: Mechanisms and Treatment

Parkinson's disease (PD) is the second most common progressive neurodegenerative disorder mainly in middle-elderly population, which represents diverse nonmotor symptoms (NMS) besides such well-documented motor symptoms as bradykinesia, resting tremor, rigidity, and postural instability. With the advancement of aging trend worldwide, the global prevalence of PD is mounting up year after year. Nowadays, accumulating lines of studies have given a comprehensive and thorough coverage of motor symptoms in PD. Yet much less attention as compared has been paid to the nonmotor symptoms of PD, such as cognition deficits. Of note, a patient with PD who suffers from cognitive impairment may harbour a statistically significantly higher risk of progressing toward dementia, which negatively affects their life expectancy and daily functioning and overall lowers the global quality of life. Furthermore, it is a widely held view that cognitive dysfunction does not just occur in the late stage of PD. On the basis of numerous studies, mild cognitive impairment (MCI) is a harbinger of dementia in PD, which is observed as an intermediate state with considerable variability; some patients remain stable and some even revert to normal cognition. Considered that the timing, profile, and rate of cognitive impairment vary greatly among PD individuals, it is extremely urgent for researchers and clinicians alike to identify and predict future cognitive decline in this population. Simultaneously, early screening and canonical management of PD with cognitive deficits are very imperative to postpone the disease progression and improve the prognosis of patients. In our review, we focus on a description of cognitive decline in PD, expound emphatically the pathological mechanisms underlying cognition deficits in PD, then give a comprehensive overview of specific therapeutic strategies, and finally dissect what fresh insights may bring new exciting prospect for the subfield.

Imaging Mild Cognitive Impairment and Dementia in Parkinson's Disease

Cognitive dysfunction is a significant non-motor feature of Parkinson's disease, with the risk of dementia increasing with prolonged disease duration. Multiple cognitive domains are affected, and the pathophysiology cannot be explained by dopaminergic loss alone. Sophisticated neuroimaging techniques can detect the nature and extent of extra-nigral involvement by targeting neurotransmitters, abnormal protein aggregates and tissue metabolism. This review identifies the functional and anatomical imaging characteristics that predict cognitive impairment in PD, the limitations that challenge this process, and the avenues of potential research.

New markers in Parkinson's disease

Parkinson's disease (PD) is a chronic, debilitating neurodegenerative disorder characterized clinically by a variety of progressive motor and nonmotor symptoms. Currently, there is a dearth of diagnostic tools available to predict, diagnose or mitigate disease risk or progression, leading to a challenging dilemma within the healthcare management system. The search for a reliable biomarker for PD that reflects underlying pathology is a high priority in PD research. Currently, there is no reliable single biomarker predictive of risk for motor and cognitive decline, and there have been few longitudinal studies of temporal progression. A combination of multiple biomarkers might facilitate earlier diagnosis and more accurate prognosis in PD. In this review, we focus on the recent developments of serial biomarkers for PD from a variety of clinical, biochemical, genetic and neuroimaging perspectives.

Differences in cognitive profiles between Lewy body and Parkinson's disease dementia

Dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD) not only differ for the time of onset of cognitive deficits but also present variability in affected functions which are relevant in understanding underlying pathology. Cognitive performance of two global cognitive screening scales, the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA), as well as of a neuropsychological test battery, was evaluated in 18 DLB and 21 PDD patients. Feasibility for each cognitive test was investigated. Both MMSE and MoCA are feasible assessments in PDD and DLB patients. MoCA was more sensitive in discriminating groups as higher number of DLB patients showed pathological performances on the Digit Span Forward subitem (p = 0.049). The Stroop test in PDD and the Trail Making Tests-A and B, and the Benton's judgment of line orientation tests in both groups were considered not feasible. Among feasible cognitive tests in at least one group, Rey-Osterrieth complex figure test copy (p = 0.013) and semantic fluency (p = 0.038) are sensitive in discriminating DLB from PDD cognitive profile. Trail Making Tests-A and B, the Benton's judgment of line orientation and the Stroop tests are not feasible for assessing patients with frank dementia. Longitudinal studies should not include those tasks to reduce the risk of missing data once disease progresses and dementia develops. DLB patients present more severe and widespread cognitive dysfunction than PDD, particularly in attentive, visuospatial, and language domains.

Pathological Influences on Clinical Heterogeneity in Lewy Body Diseases

PD, PD with dementia, and dementia with Lewy bodies are clinical syndromes characterized by the neuropathological accumulation of alpha-synuclein in the CNS that represent a clinicopathological spectrum known as Lewy body disorders. These clinical entities have marked heterogeneity of motor and nonmotor symptoms with highly variable disease progression. The biological basis for this clinical heterogeneity remains poorly understood. Previous attempts to subtype patients within the spectrum of Lewy body disorders have centered on clinical features, but converging evidence from studies of neuropathology and ante mortem biomarkers, including CSF, neuroimaging, and genetic studies, suggest that Alzheimer's disease beta-amyloid and tau copathology strongly influence clinical heterogeneity and prognosis in Lewy body disorders. Here, we review previous clinical biomarker and autopsy studies of Lewy body disorders and propose that Alzheimer's disease copathology is one of several likely pathological contributors to clinical heterogeneity of Lewy body disorders, and that such pathology can be assessed in vivo. Future work integrating harmonized assessments and genetics in PD, PD with dementia, and dementia with Lewy bodies patients followed to autopsy will be critical to further refine the classification of Lewy body disorders into biologically distinct endophenotypes. This approach will help facilitate clinical trial design for both symptomatic and disease-modifying therapies to target more homogenous subsets of Lewy body disorders patients with similar prognosis and underlying biology. © 2019 International Parkinson and Movement Disorder Society.