Clinical subtypes and genetic heterogeneity: of lumping and splitting in Parkinson disease

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

BACKGROUND

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

FINDINGS

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

CONCLUSION

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

A Next-Generation Sequencing Study in a Cohort of Sicilian Patients with Parkinson's Disease

Parkinson's disease (PD) is a multisystem and multifactorial disorder and, therefore, the application of modern genetic techniques may assist in unraveling its complex pathophysiology. We conducted a clinical-demographic evaluation of 126 patients with PD, all of whom were Caucasian and of Sicilian ancestry. DNA was extracted from the peripheral blood for each patient, followed by sequencing using a Next-Generation Sequencing system. This system was based on a custom gene panel comprising 162 genes. The sample underwent further filtering, taking into account the allele frequencies of genetic variants, their presence in the Human Gene Mutation Database, and their association in the literature with PD or other movement/neurodegenerative disorders. The largest number of variants was identified in the leucine-rich repeat kinase 2 (LRRK2) gene. However, variants in other genes, such as acid beta-glucosidase (GBA), DNA polymerase gamma catalytic subunit (POLG), and parkin RBR E3 ubiquitin protein ligase (PRKN), were also discovered. Interestingly, some of these variants had not been previously associated with PD. Enhancing our understanding of the genetic basis of PD and identifying new variants possibly linked to the disease will contribute to improved diagnostic accuracy, therapeutic developments, and prognostic insights for affected individuals.

Patient-specific models link neurotransmitter receptor mechanisms with motor and visuospatial axes of Parkinson's disease

Parkinson's disease involves multiple neurotransmitter systems beyond the classical dopaminergic circuit, but their influence on structural and functional alterations is not well understood. Here, we use patient-specific causal brain modeling to identify latent neurotransmitter receptor-mediated mechanisms contributing to Parkinson's disease progression. Combining the spatial distribution of 15 receptors from post-mortem autoradiography with 6 neuroimaging-derived pathological factors, we detect a diverse set of receptors influencing gray matter atrophy, functional activity dysregulation, microstructural degeneration, and dendrite and dopaminergic transporter loss. Inter-individual variability in receptor mechanisms correlates with symptom severity along two distinct axes, representing motor and psychomotor symptoms with large GABAergic and glutamatergic contributions, and cholinergically-dominant visuospatial, psychiatric and memory dysfunction. Our work demonstrates that receptor architecture helps explain multi-factorial brain re-organization, and suggests that distinct, co-existing receptor-mediated processes underlie Parkinson's disease.

Laryngeal symptoms related to motor phenotypes in Parkinson's disease: A systematic review

Objective

This study aimed to systematically review the associations between motor clinical phenotypes in Parkinson's disease (PD) and laryngeal disease symptoms. Laryngeal dysfunctions such as dysphonia and dysphagia are ubiquitous in people with Parkinson's disease (PwPD). Similar to other disease symptoms, they manifest variably across PwPD. Some of the variability within PD has been explained by clinical phenotypes. However, it is unclear how laryngeal symptoms of PD express themselves across these phenotypes.

Methods

Five databases were searched (MEDLINE, CINAHL, Web of Science, Embase, Scopus) in May 2022. After the removal of duplicates, all retrieved records were screened. Cohort, case-control, and cross-sectional studies in English discussing laryngeal symptoms and clinical PD phenotypes were included. Data were extracted, tabulated, and assessed using Moola et al.'s (2021) appraisal tool for systematic reviews of risk and etiology.

Results

The search retrieved 2370 records, representing 540 PwPD. After the removal of duplicates and screening, eight articles were included for review. The most common phenotype categories were tremor-dominant and postural-instability gait disordered (PIGD). Five studies addressed vocal characteristics, while four considered swallowing. Differences and lack of rigor in methodology across studies complicated conclusions, but a tendency for tremor-dominant phenotypes to present with less severe laryngeal symptoms was found.

Conclusion

Some minor differences in laryngeal function were found between tremor-dominant and PIGD phenotypes in PD. However, there is a need for more standardized and high-quality studies when comparing motor phenotypes for laryngeal function.

Defining the Riddle in Order to Solve It: There Is More Than One "Parkinson's Disease"

BACKGROUND

More than 200 years after James Parkinsondescribed a clinical syndrome based on his astute observations, Parkinson's disease (PD) has evolved into a complex entity, akin to the heterogeneity of other complex human syndromes of the central nervous system such as dementia, motor neuron disease, multiple sclerosis, and epilepsy. Clinicians, pathologists, and basic science researchers evolved arrange of concepts andcriteria for the clinical, genetic, mechanistic, and neuropathological characterization of what, in their best judgment, constitutes PD. However, these specialists have generated and used criteria that are not necessarily aligned between their different operational definitions, which may hinder progress in solving the riddle of the distinct forms of PD and ultimately how to treat them.

OBJECTIVE

This task force has identified current in consistencies between the definitions of PD and its diverse variants in different domains: clinical criteria, neuropathological classification, genetic subtyping, biomarker signatures, and mechanisms of disease. This initial effort for "defining the riddle" will lay the foundation for future attempts to better define the range of PD and its variants, as has been done and implemented for other heterogeneous neurological syndromes, such as stroke and peripheral neuropathy. We strongly advocate for a more systematic and evidence-based integration of our diverse disciplines by looking at well-defined variants of the syndrome of PD.

CONCLUSION

Accuracy in defining endophenotypes of "typical PD" across these different but interrelated disciplines will enable better definition of variants and their stratification in therapeutic trials, a prerequisite for breakthroughs in the era of precision medicine. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Olfactory dysfunction is associated with motor function only in tremor-dominant Parkinson's disease

BACKGROUND

The prevalence of olfactory impairment in patients with Parkinson's disease (PD) is 50-90%, and therefore, olfactory dysfunction is one of the most prevalent non-motor symptoms (NMSs) in patients with PD. Numerous studies have evaluated the association between motor and non-motor symptoms and olfactory dysfunction in PD.

AIM

In this study, we investigated the relationship between olfactory dysfunction, which is measured using the UPSIT test, with other motor and non-motor symptoms separately in three motor subtypes of PD, including tremor dominant (TD), postural instability and gait difficulty (PIGD), and indeterminate and healthy subjects.

METHODS

We recruited 487 early-stage PD patients (43 PIGD, 406 TD, and 38 indeterminate) and healthy controls (HCs) (n = 197) from the Parkinson Progression Markers Initiative (PPMI). All participants completed motor and non-motor tests at baseline visit and after 4 years of follow-up. Subjects underwent common PD scaling tests.

RESULTS

Olfactory dysfunction was significantly correlated with declined motor functions only in the TD subtype. Also, significant correlations were noticed between olfactory dysfunction and speed-attention processing and executive function in the HCs as well. Finally, no significant or meaningful association was observed in the PIGD and indeterminate subtype. Anosmia and hyposmia subjects in the TD group had the worse motor and non-motor scores compared to normosmia subjects after 4 years.

CONCLUSION

Olfactory dysfunction was significantly correlated with declined motor functions in the TD subtype. This is indicating that olfactory dysfunction may be an early motor and non-motor biomarker only in the TD subtype. However, it is possible that the involvement of olfactory function in other subtypes is not strong enough to make it a useful marker of diseases progression.

Characterization of Parkinson's Disease Subtypes and Related Attributes

Parkinson's disease is a progressive neurodegenerative disease with complex, heterogeneous motor and non-motor symptoms. The current evidence shows that there is still a marked heterogeneity in the subtyping of Parkinson's disease using both clinical and data-driven approaches. Another challenge posed in PD subtyping is the reproducibility of previously identified PD subtypes. These issues require additional results to confirm previous findings and help reconcile discrepancies, as well as establish a standardized application of cluster analysis to facilitate comparison and reproducibility of identified PD subtypes. Our study aimed to address this gap by investigating subtypes of Parkinson's disease using comprehensive clinical (motor and non-motor features) data retrieved from 408 de novo Parkinson's disease patients with the complete clinical data in the Parkinson's Progressive Marker Initiative database. A standardized k-means cluster analysis approach was developed by taking into consideration of common practice and recommendations from previous studies. All data analysis codes were made available online to promote data comparison and validation of reproducibility across research groups. We identified two distinct PD subtypes, termed the severe motor-non-motor subtype (SMNS) and the mild motor- non-motor subtype (MMNS). SMNS experienced symptom onset at an older age and manifested more intense motor and non-motor symptoms than MMNS, who experienced symptom onset at a younger age and manifested milder forms of Parkinson's symptoms. The SPECT imaging makers supported clinical findings such that the severe motor-non-motor subtype showed lower binding values than the mild motor- non-motor subtype, indicating more significant neural damage at the nigral pathway. In addition, SMNS and MMNS show distinct motor (ANCOVA test: F = 47.35, p< 0.001) and cognitive functioning (F = 33.93, p< 0.001) progression trends. Such contrast between SMNS and MMNS in both motor and cognitive functioning can be consistently observed up to 3 years following the baseline visit, demonstrating the potential prognostic value of identified PD subtypes.

The commercial genetic testing landscape for Parkinson's disease

INTRODUCTION

There have been no specific guidelines regarding which genes should be tested in the clinical setting for Parkinson's disease (PD) or parkinsonism. We evaluated the types of clinical genetic testing offered for PD as the first step of our gene curation.

METHODS

The National Institutes of Health (NIH) Genetic Testing Registry (GTR) was queried on 12/7/2020 to identify current commercial PD genetic test offerings by clinical laboratories, internationally.

RESULTS

We identified 502 unique clinical genetic tests for PD, from 28 Clinical Laboratory Improvement Amendments (CLIA)-approved clinical laboratories. These included 11 diagnostic PD panels. The panels were notable for their differences in size, ranging from 5 to 62 genes. Five genes for variant query were included in all panels (SNCA, PRKN, PINK-1, PARK7 (DJ1), and LRRK2). Notably, the addition of the VPS35 and GBA genes was variable. Panel size differences stemmed from inclusion of genes linked to atypical parkinsonism and dystonia disorders, and genes in which the link to PD causation is controversial.

CONCLUSION

There is an urgent need for expert opinion regarding which genes should be included in a commercial laboratory multi-gene panel for PD.

The role of neuroimaging in Parkinson's disease

Parkinson's disease (PD) is a neurodegenerative disorder that affects millions of people worldwide. Two hallmarks of PD are the accumulation of alpha-synuclein and the loss of dopaminergic neurons in the brain. There is no cure for PD, and all existing treatments focus on alleviating the symptoms. PD diagnosis is also based on the symptoms, such as abnormalities of movement, mood, and cognition observed in the patients. Molecular imaging methods such as magnetic resonance imaging (MRI), single-photon emission computed tomography (SPECT), and positron emission tomography (PET) can detect objective alterations in the neurochemical machinery of the brain and help diagnose and study neurodegenerative diseases. This review addresses the application of functional MRI, PET, and SPECT in PD patients. We provide an overview of the imaging targets, discuss the rationale behind target selection, the agents (tracers) with which the imaging can be performed, and the main findings regarding each target's state in PD. Molecular imaging has proven itself effective in supporting clinical diagnosis of PD and has helped reveal that PD is a heterogeneous disorder, which has important implications for the development of future therapies. However, the application of molecular imaging for early diagnosis of PD or for differentiation between PD and atypical parkinsonisms has remained challenging. The final section of the review is dedicated to new imaging targets with which one can detect the PD-related pathological changes upstream from dopaminergic degeneration. The foremost of those targets is alpha-synuclein. We discuss the progress of tracer development achieved so far and challenges on the path toward alpha-synuclein imaging in humans.

Will Artificial Intelligence Replace the Movement Disorders Specialist for Diagnosing and Managing Parkinson's Disease?

The use of artificial intelligence (AI) to help diagnose and manage disease is of increasing interest to researchers and clinicians. Volumes of health data are generated from smartphones and ubiquitous inexpensive sensors. By using these data, AI can offer otherwise unobtainable insights about disease burden and patient status in a free-living environment. Moreover, from clinical datasets AI can improve patient symptom monitoring and global epidemiologic efforts. While these applications are exciting, it is necessary to examine both the utility and limitations of these novel analytic methods. The most promising uses of AI remain aspirational. For example, defining the molecular subtypes of Parkinson's disease will be assisted by future applications of AI to relevant datasets. This will allow clinicians to match patients to molecular therapies and will thus help launch precision medicine. Until AI proves its potential in pushing the frontier of precision medicine, its utility will primarily remain in individualized monitoring, complementing but not replacing movement disorders specialists.

The inconsistency and instability of Parkinson's disease motor subtypes

INTRODUCTION

Tremor-dominant (TD), indeterminate/mixed (ID/M) and postural instability gait difficulty/akinetic-rigid (PIGD/AR) are commonly used subtypes to categorize Parkinson's disease (PD) patients based on their most prominent motor signs. Three different algorithms to determine these motor subtypes are used. Here, we examined if PD subtypes are consistent among algorithms and if subtype stability over time depends on the applied algorithm.

METHODS

Using a large longitudinal PD database, we applied 3 published algorithms of PD motor subtype classification in two sets of analyses: 1) cross-sectional analysis in 1185 patients, determining the prevalence of subtypes in 5-year intervals of disease duration; 2) longitudinal analysis of 178 patients, comparing subtypes of individual patients at baseline (within 5 years of diagnosis) and at follow-up ≥ 5 years after baseline.

RESULTS

Cross-sectionally, prevalence of subtypes varied widely among the 3 algorithms: 5-32% TD, 9-31% ID/M, and 59-75% PIGD/AR. For all 3 algorithms, cross-sectional analysis showed a marked decline of TD prevalence with disease duration and a corresponding increase in PIGD/AR prevalence, driven by increasing gait/balance scores over time. Longitudinally, only 15-36% of baseline TD patients were still categorized as TD at 6.2 ± 1.0 years of follow-up. In 15-39% of baseline TD patients, the subtype changed to ID/M, and 46-50% changed to PIGD/AR. This shift was observed using all 3 algorithms.

CONCLUSION

PD motor subtypes determined by different established algorithms are inconsistent and unstable over time. Lack of subtype fidelity should be considered when interpreting biomarker-subtype correlation and highlights the need for better definition of PD subtypes.

Genome-Wide Association Study Meta-Analysis for Parkinson Disease Motor Subtypes

OBJECTIVE

To discover genetic determinants of Parkinson disease (PD) motor subtypes, including tremor dominant (TD) and postural instability/gait difficulty (PIGD) forms.

METHODS

In 3,212 PD cases of European ancestry, we performed a genome-wide association study (GWAS) examining 2 complementary outcome traits derived from the Unified Parkinson's Disease Rating Scale, including dichotomous motor subtype (TD vs PIGD) or a continuous tremor/PIGD score ratio. Logistic or linear regression models were adjusted for sex, age at onset, disease duration, and 5 ancestry principal components, followed by meta-analysis.

RESULTS

Among 71 established PD risk variants, we detected multiple suggestive associations with PD motor subtype, including GPNMB (rs199351, p subtype = 0.01, p ratio = 0.03), SH3GL2 (rs10756907, p subtype = 0.02, p ratio = 0.01), HIP1R (rs10847864, p subtype = 0.02), RIT2 (rs12456492, p subtype = 0.02), and FBRSL1 (rs11610045, p subtype = 0.02). A PD genetic risk score integrating all 71 PD risk variants was also associated with subtype ratio (p = 0.026, ß = -0.04, 95% confidence interval = -0.07-0). Based on top results of our GWAS, we identify a novel suggestive association at the STK32B locus (rs2301857, p ratio = 6.6 × 10-7), which harbors an independent risk allele for essential tremor.

CONCLUSIONS

Multiple PD risk alleles may also modify clinical manifestations to influence PD motor subtype. The discovery of a novel variant at STK32B suggests a possible overlap between genetic risk for essential tremor and tremor-dominant PD.

Quantitative mobility measures complement the MDS-UPDRS for characterization of Parkinson's disease heterogeneity

INTRODUCTION

Emerging technologies show promise for enhanced characterization of Parkinson's Disease (PD) motor manifestations. We evaluated quantitative mobility measures from a wearable device compared to the conventional motor assessment, the Movement Disorders Society-Unified PD Rating Scale part III (motor MDS-UPDRS).

METHODS

We evaluated 176 PD subjects (mean age 65, 65% male, 66% H&Y stage 2) during routine clinic visits using the motor MDS-UPDRS and a 10-min motor protocol with a body-fixed sensor (DynaPort MT, McRoberts BV), including the 32-ft walk, Timed Up and Go (TUG), and standing posture with eyes closed. Regression models examined 12 quantitative mobility measures for associations with (i) motor MDS-UPDRS, (ii) motor subtype (tremor dominant vs. postural instability/gait difficulty), (iii) Montreal Cognitive Assessment (MoCA), and (iv) physical functioning disability (PROMIS-29). All analyses included age, gender, and disease duration as covariates. Models iii-iv were secondarily adjusted for motor MDS-UPDRS.

RESULTS

Quantitative mobility measures from gait, TUG transitions, turning, and posture were significantly associated with motor MDS-UPDRS (7 of 12 measures, p < 0.05) and motor subtype (6 of 12 measures, p < 0.05). Compared with motor MDS-UPDRS, several quantitative mobility measures accounted for a 1.5- or 1.9-fold increased variance in either cognition or physical functioning disability, respectively. Among minimally-impaired subjects in the bottom quartile of motor MDS-UPDRS, including subjects with normal gait exam, the measures captured substantial residual motor heterogeneity.

CONCLUSION

Clinic-based quantitative mobility assessments using a wearable sensor captured features of motor performance beyond those obtained with the motor MDS-UPDRS and may offer enhanced characterization of disease heterogeneity.

Cortical thickness in Parkinson's disease: a coordinate-based meta-analysis

Parkinson's disease (PD) is a common age-related neurodegenerative disease that affects the structural architecture of the cerebral cortex. Cortical thickness (CTh) via surface-based morphometry (SBM) analysis is a popular measure to assess brain structural alterations in the gray matter in PD. However, the results of CTh analysis in PD lack consistency and have not been systematically reviewed. We conducted a comprehensive coordinate-based meta-analysis (CBMA) of 38 CTh studies (57 comparison datasets) in 1,843 patients with PD using the latest seed-based d mapping software. Compared with 1,172 healthy controls, no significantly consistent CTh alterations were found in patients with PD, suggesting CTh as an unreliable neuroimaging marker for PD. The lack of consistent CTh alterations in PD could be ascribed to the heterogeneity in clinical populations, variations in imaging methods, and underpowered small sample sizes. These results highlight the need to control for potential confounding factors to produce robust and reproducible CTh results in PD.

Comparison of Three Motor Subtype Classifications in de novo Parkinson's Disease Patients

Objective: The aims of this study were to compare the characteristics of three motor subtype classifications in patients with de novo Parkinson's disease (PD) and to find the most suitable motor subtype classification for identifying non-motor symptoms (NMSs).

Methods: According to previous studies, a total of 256 patients with de novo PD were classified using the tremor-dominant/mixed/akinetic-rigid (TD/mixed/AR), TD/indeterminate/postural instability and gait disturbance (PIGD), and predominantly TD/predominantly PIGD (p-TD/p-PIGD) classification systems.

Results: Among the TD/mixed/AR subgroups, the patients with the AR subtype obtained more severe motor scores than the patients with the TD subtype. Among the TD/indeterminate/PIGD subgroups and between the p-TD and p-PIGD subgroups, the patients with the PIGD/p-PIGD subtype obtained more severe scores related to activities of daily living (ADL), motor and non-motor symptoms, including depression, anxiety, and sleep impairment, than the patients with the TD/p-TD subtype. Furthermore, symptoms in the cardiovascular, gastrointestinal, and miscellaneous domains of the Non-motor Questionnaire (NMSQuest) were more prevalent in the patients with the PIGD/p-PIGD subtypes than the patients with the TD/p-TD subtypes.

Conclusions: The PIGD/p-PIGD subtypes had more severe ADL, motor and non-motor symptoms than the TD/p-TD subtypes. We disclosed for the first time that the TD/indeterminate/PIGD classification seems to be the most suitable classification among the three motor subtype classifications for identifying NMSs in PD.

Altered Insulin Receptor Substrate 1 Phosphorylation in Blood Neuron-Derived Extracellular Vesicles From Patients With Parkinson's Disease

INTRODUCTION

Diabetes increases the risk of Parkinson's disease (PD). The phosphorylation of type 1 insulin receptor substrate (IRS-1) determines the function of insulin signaling pathway. Extracellular vesicles (EVs) are emerging as biomarkers of human diseases. The present study investigated whether PD patients exert altered phosphorylation IRS-1 (p-IRS-1) inside the blood neuron-derived extracellular vesicles (NDEVs).

RESEARCH DESIGN AND METHODS

In total, there were 94 patients with PD and 63 healthy controls recruited and their clinical manifestations were evaluated. Blood NDEVs were isolated using the immunoprecipitation method, and Western blot analysis was conducted to assess total IRS-1, p-IRS-1, and downstream substrates level in blood NDEVs. Statistical analysis was performed using SPSS 19.0, and p < 0.05 was considered significant.

RESULTS

The isolated blood EVs were validated according to the presence of CD63 and HSP70, nanoparticle tracking analysis and transmission electron microscopy. NDEVs were positive with neuronal markers. PD patients exerted significantly higher level of p-IRS-1S312 in blood NDEVs than controls. In addition, the p-IRS-1S312 levels in blood NDEVs was positively associated with the severity of tremor in PD patients after adjusting of age, sex, hemoglobin A1c, and body mass index (BMI).

CONCLUSION

PD patients exerted altered p-IRS-1S312 in the blood NDEVs, and also correlated with the severity of tremor. These findings suggested the association between dysfunctional insulin signaling pathway with PD. The role of altered p-IRS-1S312 in blood NDEVs as a segregating biomarker of PD required further cohort study to assess the association with the progression of PD.

Patient-Derived Midbrain Organoids to Explore the Molecular Basis of Parkinson's Disease

Induced pluripotent stem cell-derived organoids offer an unprecedented access to complex human tissues that recapitulate features of architecture, composition and function of in vivo organs. In the context of Parkinson's Disease (PD), human midbrain organoids (hMO) are of significant interest, as they generate dopaminergic neurons expressing markers of Substantia Nigra identity, which are the most vulnerable to degeneration. Combined with genome editing approaches, hMO may thus constitute a valuable tool to dissect the genetic makeup of PD by revealing the effects of risk variants on pathological mechanisms in a representative cellular environment. Furthermore, the flexibility of organoid co-culture approaches may also enable the study of neuroinflammatory and neurovascular processes, as well as interactions with other brain regions that are also affected over the course of the disease. We here review existing protocols to generate hMO, how they have been used so far to model PD, address challenges inherent to organoid cultures, and discuss applicable strategies to dissect the molecular pathophysiology of the disease. Taken together, the research suggests that this technology represents a promising alternative to 2D in vitro models, which could significantly improve our understanding of PD and help accelerate therapeutic developments.

Perceptual Characterization of Voice Quality in Nonadvanced Stages of Parkinson's Disease

INTRODUCTION

Parkinson's disease (PD) is a neurodegenerative disorder that impacts motor and nonmotor systems, and consequently influences voice. In later stages of the disease, people with PD develop salient hypokinetic dysarthria. However, it is unclear how extensive the voice impairment is in the nonadvanced stages of PD. Therefore, the aim of the current research was to investigate the auditory-perceptual characteristics of voice in people with Parkinson's disease (PWPD) in nonadvanced stages.

METHODS

29 PWPD and 32 healthy older controls were recruited. For each participant, a recording of the sentence "We were away a year ago" was acquired. These recordings were evaluated by 2 licensed and experienced speech-language pathologists, who provided perceptual ratings of overall dysphonia severity, breathiness, roughness, and perceived age.

RESULTS

MANCOVA analysis showed that, when controlling for age and intensity, there was a significant effect of group (P = 0.001) on perceptual voice quality. PWPD were perceived to be significantly older, more breathy and more severely dysphonic than the older healthy controls. No differences were found for the perceived roughness.

CONCLUSIONS

The results suggest that perceptual features of hypokinetic dysarthria in voice, specifically breathiness, are present in nonadvanced stages of PWPD and may contribute to listener perceptions of speaker age. Moreover, the perceptual voice profiles in PWPD showed great variability, possibly reflecting the heterogeneity of disease impact on individuals. The results of this study may inform how research targets rehabilitation and maintenance of voice and laryngeal function in PWPD at nonadvanced stages.

Identifying and predicting Parkinson's disease subtypes through trajectory clustering via bipartite networks

Chronic medical conditions show substantial heterogeneity in their clinical features and progression. We develop the novel data-driven, network-based Trajectory Profile Clustering (TPC) algorithm for 1) identification of disease subtypes and 2) early prediction of subtype/disease progression patterns. TPC is an easily generalizable method that identifies subtypes by clustering patients with similar disease trajectory profiles, based not only on Parkinson’s Disease (PD) variable severity, but also on their complex patterns of evolution. TPC is derived from bipartite networks that connect patients to disease variables. Applying our TPC algorithm to a PD clinical dataset, we identify 3 distinct subtypes/patient clusters, each with a characteristic progression profile. We show that TPC predicts the patient’s disease subtype 4 years in advance with 72% accuracy for a longitudinal test cohort. Furthermore, we demonstrate that other types of data such as genetic data can be integrated seamlessly in the TPC algorithm. In summary, using PD as an example, we present an effective method for subtype identification in multidimensional longitudinal datasets, and early prediction of subtypes in individual patients.

Study protocol of the DUtch PARkinson Cohort (DUPARC): a prospective, observational study of de novo Parkinson's disease patients for the identification and validation of biomarkers for Parkinson's disease subtypes, progression and pathophysiology

Background

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

Methods/design

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

Discussion

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

Trial registration

NCT04180865; registered retrospectively, November 28th 2019.

Distinct subtypes of polycystic ovary syndrome with novel genetic associations: An unsupervised, phenotypic clustering analysis

BACKGROUND

Polycystic ovary syndrome (PCOS) is a common, complex genetic disorder affecting up to 15% of reproductive-age women worldwide, depending on the diagnostic criteria applied. These diagnostic criteria are based on expert opinion and have been the subject of considerable controversy. The phenotypic variation observed in PCOS is suggestive of an underlying genetic heterogeneity, but a recent meta-analysis of European ancestry PCOS cases found that the genetic architecture of PCOS defined by different diagnostic criteria was generally similar, suggesting that the criteria do not identify biologically distinct disease subtypes. We performed this study to test the hypothesis that there are biologically relevant subtypes of PCOS.

METHODS AND FINDINGS

Using biochemical and genotype data from a previously published PCOS genome-wide association study (GWAS), we investigated whether there were reproducible phenotypic subtypes of PCOS with subtype-specific genetic associations. Unsupervised hierarchical cluster analysis was performed on quantitative anthropometric, reproductive, and metabolic traits in a genotyped cohort of 893 PCOS cases (median and interquartile range [IQR]: age = 28 [25-32], body mass index [BMI] = 35.4 [28.2-41.5]). The clusters were replicated in an independent, ungenotyped cohort of 263 PCOS cases (median and IQR: age = 28 [24-33], BMI = 35.7 [28.4-42.3]). The clustering revealed 2 distinct PCOS subtypes: a "reproductive" group (21%-23%), characterized by higher luteinizing hormone (LH) and sex hormone binding globulin (SHBG) levels with relatively low BMI and insulin levels, and a "metabolic" group (37%-39%), characterized by higher BMI, glucose, and insulin levels with lower SHBG and LH levels. We performed a GWAS on the genotyped cohort, limiting the cases to either the reproductive or metabolic subtypes. We identified alleles in 4 loci that were associated with the reproductive subtype at genome-wide significance (PRDM2/KAZN, P = 2.2 × 10-10; IQCA1, P = 2.8 × 10-9; BMPR1B/UNC5C, P = 9.7 × 10-9; CDH10, P = 1.2 × 10-8) and one locus that was significantly associated with the metabolic subtype (KCNH7/FIGN, P = 1.0 × 10-8). We developed a predictive model to classify a separate, family-based cohort of 73 women with PCOS (median and IQR: age = 28 [25-33], BMI = 34.3 [27.8-42.3]) and found that the subtypes tended to cluster in families and that carriers of previously reported rare variants in DENND1A, a gene that regulates androgen biosynthesis, were significantly more likely to have the reproductive subtype of PCOS. Limitations of our study were that only PCOS cases of European ancestry diagnosed by National Institutes of Health (NIH) criteria were included, the sample sizes for the subtype GWAS were small, and the GWAS findings were not replicated.

CONCLUSIONS

In conclusion, we have found reproducible reproductive and metabolic subtypes of PCOS. Furthermore, these subtypes were associated with novel, to our knowledge, susceptibility loci. Our results suggest that these subtypes are biologically relevant because they appear to have distinct genetic architecture. This study demonstrates how phenotypic subtyping can be used to gain additional insights from GWAS data.

Independently together: subthalamic theta and beta opposite roles in predicting Parkinson's tremor

Tremor is a core feature of Parkinson’s disease and the most easily recognized Parkinsonian sign. Nonetheless, its pathophysiology remains poorly understood. Here, we show that multispectral spiking activity in the posterior-dorso-lateral oscillatory (motor) region of the subthalamic nucleus distinguishes resting tremor from the other Parkinsonian motor signs and strongly correlates with its severity. We evaluated microelectrode-spiking activity from the subthalamic dorsolateral oscillatory region of 70 Parkinson’s disease patients who underwent deep brain stimulation surgery (114 subthalamic nuclei, 166 electrode trajectories). We then investigated the relationship between patients’ clinical Unified Parkinson’s Disease Rating Scale score and their peak theta (4–7 Hz) and beta (13–30 Hz) powers. We found a positive correlation between resting tremor and theta activity (r = 0.41, P < 0.01) and a non-significant negative correlation with beta activity (r = −0.2, P = 0.5). Hypothesizing that the two neuronal frequencies mask each other’s relationship with resting tremor, we created a non-linear model of their proportional spectral powers and investigated its relationship with resting tremor. As hypothesized, patients’ proportional scores correlated better than either theta or beta alone (r = 0.54, P < 0.001). However, theta and beta oscillations were frequently temporally correlated (38/70 patients manifested significant positive temporal correlations and 1/70 exhibited significant negative correlation between the two frequency bands). When comparing theta and beta temporal relationship (r θ β) to patients’ resting tremor scores, we found a significant negative correlation between the two (r = −0.38, P < 0.01). Patients manifesting a positive correlation between the two bands (i.e. theta and beta were likely to appear simultaneously) were found to have lower resting tremor scores than those with near-zero correlation values (i.e. theta and beta were likely to appear separately). We therefore created a new model incorporating patients’ proportional theta–beta power and r θ βscores to obtain an improved neural correlate of resting tremor (r = 0.62, P < 0.001). We then used the Akaike and Bayesian information criteria for model selection and found the multispectral model, incorporating theta–beta proportional power and their correlation, to be the best fitting model, with 0.96 and 0.89 probabilities, respectively. Here we found that as theta increases, beta decreases and the two appear separately—resting tremor is worsened. Our results therefore show that theta and beta convey information about resting tremor in opposite ways. Furthermore, the finding that theta and beta coactivity is negatively correlated with resting tremor suggests that theta–beta non-linear scale may be a valuable biomarker for Parkinson’s resting tremor in future adaptive deep brain stimulation techniques.

THE IMPACT OF BRAZILIAN SAMBA ON PARKINSON’S DISEASE: ANALYSIS BY THE DISEASE SUBTYPES

ABSTRACT Introduction: People with Parkinson's disease constantly have low levels of physical activity. Dancing has become increasingly important for treating the disease and can help improve non-motor symptoms. Objective: To analyze the influence of Brazilian samba on the non-motor symptoms of PD according to TD and PGID subtypes. Methods: A 12-week, non-randomized clinical trial, through comparison with a control group. The 23 individuals who agreed to participate in the activities formed the experimental group (EG) and the 24 individuals who opted not to participate in the Brazilian samba classes comprised the control group (CG). A questionnaire was applied, composed of validated instruments. Mini Mental State Examination – MMSE; HY – Disability Scale; Unified Parkinson's Disease Rating Scale – UPDRS 1 and total values; Parkinson's Disease Questionnaire – PDQ-39, Parkinson's Disease Sleep Scale – PDSS; Beck Depression Inventory – BDI; Fatigue Severity Scale – FSS and Magnitude of Perceived Changes. Results: After the twelve weeks of intervention, it was observed that the EG showed improvement in the scores of all the tests. The comparison between groups, however, indicated a significant difference in the post-UPDRS1 period in which the EG presented improvement in cognitive impairment, while the CG presented a deficit in these values. The results of the division between disease subtypes show a greater change in the values between individuals of the TD group, when comparing the EG with the CG. For the EG, the greatest difference between pre- and post- intervention was fatigue. Conclusion: There was a positive trend in all the variables studied after the application of the protocol. This demonstrates that interventions such as dance may have greater effects on non-motor symptoms, depending on the expected progression of the disease. The scarcity of studies that use this approach in their analyses may explain the lack of evidence in this symptomatology related to dance. Level of evidence II; Therapeutic studies – Investigating the results of treatment.

Deep learning for clustering of multivariate clinical patient trajectories with missing values

BACKGROUND

Precision medicine requires a stratification of patients by disease presentation that is sufficiently informative to allow for selecting treatments on a per-patient basis. For many diseases, such as neurological disorders, this stratification problem translates into a complex problem of clustering multivariate and relatively short time series because (i) these diseases are multifactorial and not well described by single clinical outcome variables and (ii) disease progression needs to be monitored over time. Additionally, clinical data often additionally are hindered by the presence of many missing values, further complicating any clustering attempts.

FINDINGS

The problem of clustering multivariate short time series with many missing values is generally not well addressed in the literature. In this work, we propose a deep learning-based method to address this issue, variational deep embedding with recurrence (VaDER). VaDER relies on a Gaussian mixture variational autoencoder framework, which is further extended to (i) model multivariate time series and (ii) directly deal with missing values. We validated VaDER by accurately recovering clusters from simulated and benchmark data with known ground truth clustering, while varying the degree of missingness. We then used VaDER to successfully stratify patients with Alzheimer disease and patients with Parkinson disease into subgroups characterized by clinically divergent disease progression profiles. Additional analyses demonstrated that these clinical differences reflected known underlying aspects of Alzheimer disease and Parkinson disease.

CONCLUSIONS

We believe our results show that VaDER can be of great value for future efforts in patient stratification, and multivariate time-series clustering in general.

Subtyping of Parkinson's Disease - Where Are We Up To?

Heterogenous clinical presentations of Parkinson's disease have aroused several attempts in its subtyping for the purpose of strategic implementation of treatment in order to maximise therapeutic effects. Apart from a priori classifications based purely on motor features, cluster analysis studies have achieved little success in receiving widespread adoption. A priori classifications demonstrate that their chosen factors, whether it be age or certain motor symptoms, do have an influence on subtypes. However, the cluster analysis approach is able to integrate these factors and other clinical features to produce subtypes. Differences in inclusion criteria from datasets, in variable selection and in methodology between cluster analysis studies have made it difficult to compare the subtypes. This has impeded such subtypes from clinical applications. This review analysed existing subtypes of Parkinson's disease, and suggested that future research should aim to discover subtypes that are robustly replicable across multiple datasets rather than focussing on one dataset at a time. Hopefully, through clinical applicable subtyping of Parkinson's disease would lead to translation of these subtypes into research and clinical use.

Progression in the LRRK2-Asssociated Parkinson Disease Population

Importance

Few prospective longitudinal studies have evaluated the progression of Parkinson disease (PD) in patients with the leucine-rich repeat kinase 2 (LRRK2 [OMIM 609007]) mutation. Knowledge about such progression will aid clinical trials.

Objective

To determine whether the longitudinal course of PD in patients with the LRRK2 mutation differs from the longitudinal course of PD in patients without the mutation.

Design, Setting, and Participants

A prospective comprehensive assessment of a large cohort of patients from 3 sites with LRRK2 PD or with nonmutation PD was conducted from July 21, 2009, to September 30, 2016. All patients of Ashkenazi Jewish ancestry with PD were approached at each site; approximately 80% agreed to an initial visit. A total of 545 patients of Ashkenazi Jewish descent with PD who had 1 to 4 study visits were evaluated. A total of 144 patients (26.4%) had the LRRK2 G2019S mutation. Patients with GBA (OMIM 606463) mutations were excluded from the analysis.

Main Outcomes and Measures

Linear mixed-effects models for longitudinal motor scores were used to examine the association of LRRK2 mutation status with the rate of change in Unified Parkinson's Disease Rating Scale III scores using disease duration as the time scale, adjusting for sex, site, age, disease duration, cognitive score, and levodopa-equivalent dose at baseline. Mixed-effects models were used to assess change in cognition, as measured by Montreal Cognitive Assessment scores.

Results

Among the 545 participants, 233 were women, 312 were men, and the mean (SD) age was 68.2 (9.1) years for participants with the LRRK2 mutation and 67.8 (10.7) years for those without it. Seventy-two of 144 participants with the LRRK2 mutation and 161 of 401 participants with no mutation were women. The estimate (SE) of the rate of change in the Unified Parkinson's Disease Rating Scale III motor score per year among those with the LRRK2 mutation (0.689 [0.192] points per year) was less than among those without the mutation (1.056 [0.187] points per year; difference, -0.367 [0.149] points per year; P = .02). The estimate (SE) of the difference in the rate of change of the Montreal Cognitive Assessment score between those with the LRRK2 mutation (-0.096 [0.090] points per year) and those without the mutation (-0.192 [0.102] points per year) did not reach statistical significance (difference, 0.097 [0.055] points per year; P = .08).

Conclusions and Relevance

Prospective longitudinal follow-up of patients with PD with or without the LRRK2 G2019S mutation supports data from a cross-sectional study and demonstrates a slower decline in motor Unified Parkinson's Disease Rating Scale scores among those with LRRK2 G2019S-associated PD.

Frequency of Cognitive Impairment in Patients with Parkinson's Disease

Introduction

More than its motor symptoms, cognitive impairment is being increasingly identified as a cause of worse functional outcome, morbidity and mortality, and caregiver dependence in Parkinson’s disease (PD). The aim of this study was to identify the frequency of cognitive decline and evaluate the factors associated with it.

Methods

In this cross-sectional study, 124 PD patients fulfilling the United Kingdom Parkinson’s Disease Society Brain Bank Clinical Diagnostic Criteria were included. Motor and non-motor symptoms were recorded. Disease duration, age at the time of onset, and severity of disease on Hoehn and Yahr Scale (HY scale) were recorded. Data was entered and analyzed using SPSSs v. 22.0.

Results

The ratio of men to women was 7.2:1. The mean age of the participants was 64 ± 10 years (range: 38-82 years). Rigidity (n = 121; 97.5%), bradykinesia (n = 119; 95.9%), and tremor (n = 11; 90.3%) were the three most common symptoms. Cognitive impairment was present in 45 (36.3%) patients. Cognitive decline was more frequent in patients of age less than 50 years at the time of disease onset (p < 0.00001) and in those with disease duration more than 10 years (p = 0.00001). Patients with longer disease duration had more severe disease (stage III or above on HY scale; p = 0.008).

Conclusion

Motor symptoms such as rigidity, bradykinesia, and tremor remain the most frequent clinical presentation among Pakistani Parkinson’s patients. One-third of these patients have cognitive dysfunction. Early age at the time of disease onset and longer duration of disease were associated with cognitive impairment.

Critical Roles of Glutaredoxin in Brain Cells-Implications for Parkinson's Disease

SIGNIFICANCE

Glutaredoxin (Grx)1, an evolutionarily conserved and ubiquitous enzyme, regulates redox signal transduction and protein redox homeostasis by catalyzing reversible S-glutathionylation. Grx1 plays different roles in different cell types. In Parkinson's disease (PD), Grx1 regulates apoptosis signaling in dopaminergic neurons, so that loss of Grx1 leads to increased cell death; in microglial cells, Grx1 regulates proinflammatory signaling, so that upregulation of Grx1 promotes cytokine production. Here we examine the regulatory roles of Grx1 in PD with a view toward therapeutic innovation. Recent Advances: In postmortem midbrain PD samples, Grx1 was decreased relative to controls, specifically within dopaminergic neurons. In Caenorhabditis elegans models of PD, loss of the Grx1 homologue led to exacerbation of the neurodegenerative phenotype. This effect was partially relieved by overexpression of neuroprotective DJ-1, consistent with regulation of DJ-1 content by Grx1. Increased GLRX copy number in PD patients was associated with earlier PD onset; and Grx1 levels correlated with levels of proinflammatory tumor necrosis factor-α in mouse and human brain samples. In vitro studies showed Grx1 to be upregulated on proinflammatory activation of microglia. Direct overexpression of Grx1 increased microglial activation; silencing Grx1 diminished activation. Grx1 upregulation in microglia corresponded to increased neuronal cell death in coculture. Overall, these studies identify competing roles of Grx1 in PD etiology.

CRITICAL ISSUES

The dilemma regarding Grx1 as a PD therapeutic target is whether to stimulate its upregulation for neuroprotection or inhibit its proinflammatory activity.

FUTURE DIRECTIONS

Further investigation is needed to understand the preponderant role of Grx1 regarding dopaminergic neuronal survival.

Two conformationally distinct α-synuclein oligomers share common epitopes and the ability to impair long-term potentiation

Parkinson’s Disease (PD) is a neurodegenerative disease for which there currently is no cure. Aggregation of the pre-synaptic protein α-synuclein (aSN) into oligomers (αSOs) is believed to play a key role in PD pathology, but little is known about αSO formation in vivo and how they induce neurodegeneration. Both the naturally occurring polyunsaturated fatty acid docosahexaenoic acid (DHA) and the lipid peroxidation product 4-hydroxynonenal (HNE), strongly upregulated during ROS conditions, stimulate the formation of αSOs, highlighting a potential role in PD. Yet, insight into αSOs structure and biological effects is still limited as most oligomer preparations studied to date are heterogeneous in composition. Here we have aggregated aSN in the presence of HNE and DHA and purified the αSOs using size exclusion chromatography. Both compounds stimulate formation of spherical αSOs containing anti-parallel β-sheet structure which have the same shape as unmodified αSOs though ca. 2-fold larger. Furthermore, the yield and stabilities of these oligomers are significantly higher than for unmodified aSN. Both modified and unmodified αSOs permeabilize synthetic vesicles, show high co-localisation with glutamatergic synapses and decrease Long Term Potentiation (LTP), in line with the reported synaptotoxic effects of αSOs. We conclude that DHA- and HNE-αSOs are convenient models for pathogenic disease-associated αSOs in PD.

Genetic Impact on Clinical Features in Parkinson's Disease: A Study on SNCA-rs11931074

SNCA-rs11931074 had been demonstrated to be strongly correlated with PD risk. However, there was lack of comprehensive analysis of SNCA-rs11931074-related clinical features which may help explain clinical heterogeneity of PD. In our study, we performed association analyses on the relationship between SNCA-rs11931074 and motor symptoms, nonmotor symptoms, and comorbidities in PD. 611 rs11931074 carriers and 113 rs11931074 noncarriers were enrolled. In the clinical phenotype analyses, the Unified Parkinson's Disease Rating Scale part II (UPDRS II) and part III (UPDRS III) scores of rs11931074 carriers were lower than those of noncarriers (SC: −0.083, p=0.035; SC: −0.140, p ≤ 0.001). The Charlson Comorbidity Index (CCI) score of carriers was lower than that of noncarriers (SC: −0.097, p=0.009). No significant statistical differences were found between the variant and other clinical features such as motor complications and nonmotor symptoms. The SNCA-rs11931074 carriers may present with more benign clinical profiles than noncarriers with less severe motor symptoms and comorbidity burden.

Genetic variants of PARK genes in Korean patients with early-onset Parkinson's disease

Early-onset Parkinson's disease (EOPD) can be linked to different genetic backgrounds depending on the disease characteristics. In Korean patients with EOPD, however, only 5 PARK genes have been tested. We recruited 70 patients with EOPD from 4 hospitals in Korea, and 12 PARK genes were screened via multigene panel sequencing. Large insertions or deletions were confirmed by multiplex ligation-dependent probe amplification. We found 20 rare variants (2 in SNCA, 2 in PRKN, 6 in LRRK2, 3 in PINK1, 1 in DJ1, 4 in FBX07, 1 in HTRA2, and 1 in EIG4G1) in 20 subjects regardless of heterogeneity. Two pathogenic variants (SNCA in 2 subjects and DJ1 in one) were from 3 subjects, and 7 likely pathogenic variants (SNCA, LRRK2, FBXO7, and 2 in PINK1 and PRKN) from 7. Akinetic-rigid subtype and dystonia were more common in patients with EOPD with rare variants than in those without rare variants. Multigene panel tests can be effective at identifying genetic variants in patients with EOPD. In addition, we suggest there are different genetic backgrounds in patients with EOPD.

Prevalence of pre-diagnostic symptoms did not differ between LRRK2-related, GBA-related and idiopathic patients with Parkinson's disease

INTRODUCTION

Glucocerebrosidase (GBA) mutations and leucine-rich repeat kinase 2 (LRRK2) variants are the most common genetic risk factors for late-onset Parkinson's disease (PD). In this study, we aimed to investigate the differences in pre-diagnostic symptoms of PD associated with the variants.

METHODS

The participants were recruited from 24 centers across China and genotyped for LRRK2 G2385R and R1628P variants and GBA L444P mutation. Participants were surveyed with structural questionnaires for history of environmental exposure and living habits and interviewed to collect the time at onset of each symptoms before diagnosis. We compared the cumulative prevalence and manifestation pattern of symptoms between groups using multiple logistic regression, adjusting age and gender.

RESULTS

Total 1799 PD patients were recruited, including 226 patients with LRRK2 G2385R or R1628P variant, 44 with GBA L444P mutation, three with both LRRK2 and GBA mutation, and 1526 idiopathic patients. The cumulative prevalence of non-motor and typical motor symptoms did not differ between groups before diagnosis (P > 0.05). The manifestation sequences of non-motor symptoms were indistinguishable between the LRRK2-carriers, GBA-carriers, and idiopathic PD subjects, and followed the sequence of constipation, hyposmia, sleep disorders, anxiety and depression, sexual dysfunction, urinary incontinency, dizziness and cognition. Slightly higher prevalence of hypomimia and micrographia were detected in the GBA-carriers.

CONCLUSIONS

The prevalence of pre-diagnostic symptoms is almost indistinguishable between the LRRK2-carriers, GBA-carriers, and idiopathic PD before diagnosis; the sequence of the manifestation of non-motor symptoms largely conforms to the Braak stage for both genetic-related and idiopathic late-onset PD.

Spinal Lewy body pathology in older adults without an antemortem diagnosis of Parkinson's disease

To test the hypothesis that Lewy body pathology (LBs) is present in the spinal cord of older community-dwelling adults without a clinical diagnosis of Parkinson's disease (PD). We studied 162 prospective autopsies from older adults with PD (N = 6) and without PD (N = 156). We documented the presence of LBs in cerebrum and brainstem structures from each of the six regions used for Braak PD staging and four spinal cord levels (C5/6, T7, L4/5 and S4/5). Parkinsonism proximate to death was based on a previously validated measure present if two or more of the four signs of parkinsonism were present based on a modified version of the Unified Parkinson's Disease Rating Scale (UPDRS). Fifty-three of 156 individuals without PD (34%) had LBs in a least one site within the CNS. About half of cases with LBs in the cerebrum or brainstem, (25/53, 47%) also had spinal LBs. Almost 90% (22/25, 88%) of cases with spinal LBs had LBs in the cerebrum (Braak stages 4-6) and about 10% (3/25, 12%) had only brainstem LBs (Braak stages 1-3). Four of six cases with PD showed LBs in cerebrum, brainstem and spinal cord. Individuals with LBs in the spinal cord were more likely to have clinical parkinsonism proximate to death compared to individuals with LBs in brainstem and cerebrum alone (52% vs. 32%; Chi-Square x2  = 5.368, d.f. = 1, P = 0.0.021) and more severe nigral neuronal loss (48% vs. 11%; Chi-Square x2  = 9.049, d.f. = 1, P = 0.003). These findings were unchanged when we included cases with a history of PD. Older community-dwelling adults without a clinical diagnosis of PD have evidence of LBs throughout the CNS including the spinal cord which is associated with parkinsonism and more severe nigral neuronal loss.

Comparison of two motor subtype classifications in de novo Parkinson's disease

BACKGROUND

Clinical subtypes of Parkinson's disease (PD) have been empirically defined based on the prominent motor symptoms. The aim of this study was to compare the prevalence of non-motor symptoms across PD motor subtypes in patients with PD.

METHODS

A total of 192 patients with de novo PD were included. The patients were classified into the tremor-dominant/mixed/akinetic-rigid (TD/mixed/AR) and tremor-dominant/mixed/postural instability and gait disturbance (TD/mixed/PIGD) subtypes, according to previous reports.

RESULTS

In the TD/mixed/AR classification, scores for scales related to motor symptoms and activities of daily living (ADL) were significantly different among the groups, and patients with the AR subtype demonstrated more severe scores than patients with the TD subtype. In the TD/mixed/PIGD classification, age, age at symptom onset, scores on motor-related scales, ADL, and non-motor symptoms were significantly different among the groups. Scores including the modified Hoehn and Yahr stages, the motor and ADL subscores of the Unified Parkinson's Disease Rating Scale, the Beck Depression Inventory, and the Non-Motor Symptom Assessment Scale were significantly different after adjustments for age and age at symptom onset, and patients with the PIGD subtype obtained more severe scores than patients with the TD subtype.

CONCLUSION

The TD/mixed/PIGD classification seems to be more suitable for identifying non-motor abnormalities than the TD/mixed/AR classification.

Intercepting Parkinson disease non-motor subtypes: A proof-of-principle study in a clinical setting

The construct of non-motor symptoms (NMS) subtyping in Parkinson Disease (PD) is emerging as a line of research in the light of its potential role in etiopathological interpretation of PD heterogeneity. Different approaches of NMS subtyping have been proposed: an anatomical model suggests that NMS aggregate according to the underpinning pathology; other researchers find aggregation of NMS according to the motor phenotype; the contribution of genetic background to NMS has also been assessed, primarily focusing on cognitive impairment. We have analyzed NMS burden assessed through an extensive clinical and neuropsychological battery in 137 consecutive non-demented PD patients genotyped for MAPT haplotypes (H1/H1 vs H2 carriers) in order to explore the applicability of the "anatomo-clinical", "motor" or "genetic" models for subtyping PD in a clinical setting; a subsequent independent analysis was conducted to verify a possible cluster distribution of NMS. No clear-cut NMS profiles according to the previously described models emerged: in our population, the autonomic dysfunctions and depressive symptoms represent the leading determinant of NMS clusters, which seems to better fit with the hypothesis of a "neurotransmitter-based" model. Selective preferential neurotransmitter network dysfunctions may account for heterogeneity of PD and could address translational research.

Analysis of age-related changes in psychosine metabolism in the human brain

α-Synuclein aggregation has been linked to Gaucher’s disease (GD) and Krabbe’s disease (KD), lysosomal conditions affecting glycosphingolipid metabolism. α-Synuclein pathology has been directly attributed to the dysregulation of glycosphingolipids in both conditions, specifically to increased galactosylsphingosine (psychosine) content in the context of KD. Furthermore, the gene (GALC) coding for the psychosine degrading enzyme galactosylceramidase (GALC), has recently been identified as a risk loci for Parkinson’s disease. However, it is unknown if changes in psychosine metabolism and GALC activity in the context of the aging human brain correlate with Parkinson’s disease. We investigated psychosine accumulation and GALC activity in the aging brain using fresh frozen post-mortem tissue from Parkinson’s (PD, n = 10), Alzheimer’s (AD, n = 10), and healthy control patients (n = 9), along with tissue from neuropsychiatric patients (schizophrenia, bipolar disorder and depression, n = 15 each). An expanded mutational analysis of PD (n = 20), AD (n = 10), and healthy controls (n = 30) examined if PD was correlated with carriers for severe GALC mutations. Psychosine content within the cerebral cortex of PD patients was elevated above control patients. Within all patients, psychosine displayed a significant (p<0.05) and robust regional distribution in the brain with higher levels in the white matter and substantia nigra. A mutational analysis revealed an increase in the incidence of severe GALC mutations within the PD patient population compared to the cohorts of Alzheimer’s patients and healthy controls tested. In addition to α-synuclein pathology identified in the KD brain, control patients identified as GALC mutational carriers or possessing a GALC pathogenic variant had evidence of α-synuclein pathology, indicating a possible correlation between α-synuclein pathology and dysregulation of psychosine metabolism in the adult brain. Carrier status for GALC mutations and prolonged exposure to increased psychosine could contribute to α-synuclein pathology, supporting psychosine metabolism by galactosylceramidase as a risk factor for Parkinson’s disease.

Onset and Remission of Psychosis in Parkinson's Disease: Pharmacologic and Motoric Markers

BACKGROUND

Psychosis is among the most disabling complications of Parkinson's disease (PD). The chronicity of PD psychosis remains understudied and the relative importance of dopaminergic therapy versus the disease process itself in engendering psychosis remains unclear.

OBJECTIVES

To examine pharmacologic and motoric correlates of PD psychosis onset and remission in a longitudinally monitored PD cohort.

METHODS

We analyzed data from 165 participants enrolled in a longitudinal PD study through the Morris K. Udall Parkinson's Disease Research Center of Excellence at Johns Hopkins University. Evaluations included formal psychiatric assessment and were conducted at two-year intervals. Regression with generalized estimated equations (GEE) was used to produce unadjusted and adjusted estimates for time-varying longitudinal associations between psychosis and putative risk factors.

RESULTS

Sixty-two participants (37.6%) were diagnosed with psychosis during at least one evaluation. Of forty-nine participants with psychosis followed over multiple evaluations, 13 (26.5%) demonstrated remission despite significant Hoehn & Yahr stage increase (p=0.009); two of these cases later relapsed. Multivariable regression with GEE identified dementia diagnosis, akinesia-rigidity, anticholinergic usage, and levodopa-carbidopa dose to be significantly associated with psychosis, while disease duration was not. A sub-analysis of 30 incident psychosis cases suggested that dopamine agonist dose was lowered after psychosis onset with a compensatory increase in levodopa-carbidopa dosage.

CONCLUSIONS

Our findings suggest that in the context of standard therapy, PD-related psychotic disorder can remit at a frequency of approximately 27%. Additionally, akinetic-rigid motor impairment was more strongly associated with psychosis than disease duration, independent of cognitive impairment and medications.

From Reproducibility to Translation in Neurodegenerative Disease

Despite tremendous investment and preclinical success in neurodegenerative disease, effective disease-altering treatments for patients have remained elusive. One highly cited reason for this discrepancy is flawed animal study design and reporting. If this can be broadly remedied, reproducibility of preclinical studies will improve. However, without concurrent efforts to improve generalizability, these improvements may not translate effectively from animal experiments to more complex human neurodegenerative diseases. Mechanistic and phenotypic variability of neurodegenerative disease is such that most models are only able to interrogate individual aspects of complex phenomena. One approach is to consider animals as models of individual targets rather than as models of individual diseases and to migrate the concept of predictive validity from the individual model to the body of experiments that demonstrate translatability of a target. Both exploratory and therapeutic preclinical studies are dependent upon study design methods that promote rigor and reproducibility. However, the body of evidence that is needed to demonstrate efficacy in therapeutic studies is substantially broader than that needed for exploratory studies. In addition to requiring rigor within individual experiments, convincing evidence for therapeutic potential must assess the relationships between model choice, intended goal of the intervention, pharmacologic criteria, and integration of biomarker data with outcome measures that are clinically relevant to humans. It is conceivable that proof-of-concept studies will migrate to cell-based systems and that animal systems will be increasingly reserved for more distal translational purposes. If this occurs, it is likely to prompt reexamination of what the term "translational" truly means.

Gray Matter Abnormalities in Idiopathic Parkinson's Disease: Evaluation by Diffusional Kurtosis Imaging and Neurite Orientation Dispersion and Density Imaging

Mapping gray matter (GM) pathology in Parkinson's disease (PD) with conventional MRI is challenging, and the need for more sensitive brain imaging techniques is essential to facilitate early diagnosis and assessment of disease severity. GM microstructure was assessed with GM-based spatial statistics applied to diffusion kurtosis imaging (DKI) and neurite orientation dispersion imaging (NODDI) in 30 participants with PD and 28 age- and gender-matched controls. These were compared with currently used assessment methods such as diffusion tensor imaging (DTI), voxel-based morphometry (VBM), and surface-based cortical thickness analysis. Linear discriminant analysis (LDA) was also used to test whether subject diagnosis could be predicted based on a linear combination of regional diffusion metrics. Significant differences in GM microstructure were observed in the striatum and the frontal, temporal, limbic, and paralimbic areas in PD patients using DKI and NODDI. Significant correlations between motor deficits and GM microstructure were also noted in these areas. Traditional VBM and surface-based cortical thickness analyses failed to detect any GM differences. LDA indicated that mean kurtosis (MK) and intra cellular volume fraction (ICVF) were the most accurate predictors of diagnostic status. In conclusion, DKI and NODDI can detect cerebral GM abnormalities in PD in a more sensitive manner when compared with conventional methods. Hence, these methods may be useful for the diagnosis of PD and assessment of motor deficits. Hum Brain Mapp 38:3704-3722, 2017. © 2017 Wiley Periodicals, Inc.

The underlying mechanism of prodromal PD: insights from the parasympathetic nervous system and the olfactory system

Neurodegeneration of Parkinson's disease (PD) starts in an insidious manner, 30-50% of dopaminergic neurons have been lost in the substantia nigra before clinical diagnosis. Prodromal stage of the disease, during which the disease pathology has started but is insufficient to result in clinical manifestations, offers a valuable window for disease-modifying therapies. The most focused underlying mechanisms linking the pathological pattern and clinical characteristics of prodromal PD are the prion hypothesis of alpha-synuclein and the selective vulnerability of neurons. In this review, we consider the two potential portals, the vagus nerve and the olfactory bulb, through which abnormal alpha-synuclein can access the brain. We review the clinical, pathological and neuroimaging evidence of the parasympathetic nervous system and the olfactory system in the neurodegenerative process and using the two systems as models to discuss the internal homogeneity and heterogeneity of the prodromal stage of PD, including both the clustering and subtyping of symptoms and signs. Finally, we offer some suggestions on future directions for imaging studies in prodromal Parkinson's disease.

An empirical method to cluster objective nebulizer adherence data among adults with cystic fibrosis

BACKGROUND

The purpose of using preventative inhaled treatments in cystic fibrosis is to improve health outcomes. Therefore, understanding the relationship between adherence to treatment and health outcome is crucial. Temporal variability, as well as absolute magnitude of adherence affects health outcomes, and there is likely to be a threshold effect in the relationship between adherence and outcomes. We therefore propose a pragmatic algorithm-based clustering method of objective nebulizer adherence data to better understand this relationship, and potentially, to guide clinical decisions.

METHODS TO CLUSTER ADHERENCE DATA

This clustering method consists of three related steps. The first step is to split adherence data for the previous 12 months into four 3-monthly sections. The second step is to calculate mean adherence for each section and to score the section based on mean adherence. The third step is to aggregate the individual scores to determine the final cluster ("cluster 1" = very low adherence; "cluster 2" = low adherence; "cluster 3" = moderate adherence; "cluster 4" = high adherence), and taking into account adherence trend as represented by sequential individual scores. The individual scores should be displayed along with the final cluster for clinicians to fully understand the adherence data.

THREE ILLUSTRATIVE CASES

We present three cases to illustrate the use of the proposed clustering method.

CONCLUSION

This pragmatic clustering method can deal with adherence data of variable duration (ie, can be used even if 12 months' worth of data are unavailable) and can cluster adherence data in real time. Empirical support for some of the clustering parameters is not yet available, but the suggested classifications provide a structure to investigate parameters in future prospective datasets in which there are accurate measurements of nebulizer adherence and health outcomes.