Clinical criteria for subtyping Parkinson's disease: biomarkers and longitudinal progression

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.

Evolution of prodromal Parkinson's disease and dementia with Lewy bodies: a prospective study

Parkinson's disease has a long prodromal stage with various subclinical motor and non-motor manifestations; however, their evolution in the years before Parkinson's disease is diagnosed is unclear. We traced the evolution of early motor and non-motor manifestations of synucleinopathy from the stage of idiopathic rapid eye movement (REM) sleep behaviour disorder until defined neurodegenerative disease. During 2004-16, we recruited and then annually followed 154 polysomnography-proven patients with idiopathic REM sleep behaviour disorder, of whom 55 phenoconverted to defined parkinsonism or dementia. Longitudinal data on multiple prodromal features, including the Unified Parkinson's Disease Rating Scale parts I-III, quantitative motor tests, olfaction, colour vision, cognition, and autonomic functions were gathered annually (average = five follow-up visits, range: 2-12 years). The same measures were also assessed in 102 age- and sex-matched healthy control subjects. By looking backward from the time of dementia or parkinsonism diagnosis, we examined trajectories of each prodromal feature using mixed effect models. Based on analysis, olfactory loss was first to develop, with predicted onset >20 years before phenoconversion. This was followed by impaired colour vision, constipation, and erectile dysfunction, starting 10-16 years prior to phenoconversion. At 7-9 years before phenoconversion, slight urinary dysfunction and subtle cognitive decline could be detected. Among motor symptoms altered handwriting, turning in bed, walking, salivation, speech, and facial expression began to be disrupted starting 7-11 years prior to parkinsonism diagnosis, but remained mild until soon before phenoconversion. Motor examination abnormalities began 5-7 years before phenoconversion, with the alternate tap test having the longest interval (8 years before phenoconversion). Among cardinal motor phenotypes, bradykinesia appeared first, ∼5-6 years prior to phenoconversion, followed by rigidity (Year -3) and tremor (Year -2). With direct prospective evaluation of an idiopathic REM sleep behaviour disorder cohort during phenoconversion, we documented an evolution of prodromal manifestations similar to that predicted by pathological staging models, with predicted prodromal intervals as long as 20 years.

Progression of grey and white matter brain damage in Parkinson's disease: a critical review of structural MRI literature

The current review summarizes the current knowledge on longitudinal cortical and subcortical grey and white matter MRI findings assessed using T1-weighted and one-tensor diffusion-weighted MRI in Parkinson's disease (PD) patients. Results were reviewed according to disease duration, disease severity and cognitive impairment. The most consistent findings are those showing a progressive cortical atrophy accumulation in caudate, putamen, temporal/hippocampal, frontal and parietal areas in de novo PD cases and in the early/middle phase of the disease, with the achievement of a plateau in the later stage. Analyzing results according to the patient cognitive status, only a few studies used longitudinal MRI metrics to predict mild cognitive impairment or dementia conversion in PD patients, suggesting that atrophy of the hippocampus, fronto-temporal areas, caudate, thalamus and accumbens might play a role in this process. Stratifying patients according to disease severity, findings appear partially controversial, although showing a progressive atrophy of basal ganglia over 1 year of follow up and a widespread cortical thinning over 3-6 years in mild to moderate PD patients. Finally, microstructural damage of the main motor and associative WM tracts seems to be present, and rapidly progress, even in the early phase of PD. The utility of structural MRI metrics as biomarkers of PD progression and their role in improving the accuracy of disease progression prediction is still debated.

Brain atrophy in Parkinson's disease with polysomnography-confirmed REM sleep behavior disorder

We aimed to investigate cortical and subcortical brain alterations in people with Parkinson's disease with polysomnography-confirmed rapid eye movement (REM) sleep behavior disorder (RBD). Thirty people with Parkinson's disease, including 15 people with RBD, were recruited and compared with 41 healthy controls. Surface-based cortical and subcortical analyses were performed on T1-weighted images to investigate thickness and shape abnormalities between groups, and voxel-based and deformation-based morphometry were performed to investigate local volume. Correlations were performed in patients to investigate the structural correlates of motor activity during REM sleep. People with RBD showed cortical thinning in the right perisylvian and inferior temporal cortices and shape contraction in the putamen compared with people without RBD. Compared with controls, people with RBD had extensive cortical thinning and volume loss, brainstem volume was reduced, and shape contraction was found in the basal ganglia and hippocampus. In comparison to controls, people without RBD showed more restricted thinning in the sensorimotor, parietal, and occipital cortices, reduced volume in the brainstem, temporal and more posterior areas, and shape contraction in the pallidum and hippocampus. In Parkinson's disease, higher tonic and phasic REM sleep motor activity was associated with contraction of the thalamic surface, extensive cortical thinning, and subtle volume reduction in the middle temporal gyrus. In Parkinson's disease, the presence of RBD is associated with extensive cortical and subcortical abnormalities, suggesting more severe neurodegeneration in people with RBD. This provides potential neuroanatomical correlates for the more severe clinical phenotype reported in people with Parkinson's disease with RBD.

Parkinsonism as a late presentation of lymphomatosis cerebri following high-dose chemotherapy with autologous stem cell transplantation for primary central nervous system lymphoma

Primary central nervous system lymphoma is an aggressive form of non-Hodgkin lymphoma arising in the eyes, meninges, spinal cord, or brain. Treatment of primary CNS lymphoma with a combination of high-dose chemotherapy and autologous stem cell transplantation has been shown to have high rates of remission which is frequently sustained for multiple years. Recurrence of primary CNS lymphoma generally presents with one or multiple contrast enhancing lesions on MRI. In rare cases, lymphoma cells may proliferate diffusely within the brain parenchyma without mass formation, a pattern termed lymphomatosis cerebri. Lymphomatosis cerebri presents a significant diagnostic challenge, and has not been reported to present with parkinsonism. Here, we present a case of initially mass forming, contrast-enhancing primary CNS lymphoma which remitted following chemotherapy and autologous stem cell transplantation, and recurred 7 years post-transplant with symptoms of parkinsonism and a lack of typical lesions on imaging, with lymphomatosis cerebri confirmed at autopsy.

Neuropsychiatric symptoms and cognitive abilities over the initial quinquennium of Parkinson disease

OBJECTIVE

To determine the evolution of numerous neuropsychiatric symptoms and cognitive abilities in Parkinson disease from disease onset.

METHODS

Prospectively collected, longitudinal (untreated, disease onset to year 5), observational data from Parkinson's Progression Markers Initiative annual visits was used to evaluate prevalence, correlates, and treatment of 10 neuropsychiatric symptoms and cognitive impairment in Parkinson disease participants and matched healthy controls.

RESULTS

Of 423 Parkinson disease participants evaluated at baseline, 315 (74.5%) were assessed at year 5. Eight neuropsychiatric symptoms studied increased in absolute prevalence by 6.2-20.9% at year 5 relative to baseline, and cognitive impairment increased by 2.7-6.2%. In comparison, the frequency of neuropsychiatric symptoms in healthy controls remained stable or declined over time. Antidepressant and anxiolytic/hypnotic use in Parkinson disease were common at baseline and increased over time (18% to 27% for the former; 13% to 24% for the latter); antipsychotic and cognitive-enhancing medication use was uncommon throughout (2% and 5% of patients at year 5); and potentially harmful anticholinergic medication use was common and increased over time. At year 5 the cross-sectional prevalence for having three or more neuropsychiatric disorders/cognitive impairment was 56% for Parkinson disease participants versus 13% for healthy controls, and by then seven of the examined disorders had either occurred or been treated at some time point in the majority of Parkinson disease patients. Principal component analysis suggested an affective disorder subtype only.

INTERPRETATION

Neuropsychiatric features in Parkinson disease are common from the onset, increase over time, are frequently comorbid, and fluctuate in severity.

MRI biomarkers of motor and non-motor symptoms in Parkinson's disease

Parkinson's disease is a heterogeneous disorder with both motor and non-motor symptoms that contribute to functional impairment. To develop effective, disease modifying treatments for these symptoms, biomarkers are necessary to detect neuropathological changes early in the disease course and monitor changes over time. Advances in MRI scan sequences and analytical techniques present numerous promising metrics to detect changes within the nigrostriatal system, implicated in the cardinal motor symptoms of the disease, and detect broader dysfunction involved in the non-motor symptoms, such as cognitive impairment. There is emerging evidence that iron sensitive, neuromelanin sensitive, diffusion sensitive, and resting state functional magnetic imaging measures can capture changes within the nigrostriatal system. Iron, neuromelanin, and diffusion sensitive measures demonstrate high specificity and sensitivity in distinguishing Parkinson's disease relative to controls, with inconsistent results differentiating Parkinson's disease relative to atypical parkinsonian disorders. They may also serve as useful monitoring biomarkers, with each possibly detecting different aspects of the disease course (early nigrosome changes versus broader substantia nigra changes). Investigations of non-motor symptoms, such as cognitive impairment, require careful consideration of the nature of cognitive deficits to characterize regional and network specific impairment. While the early, executive dysfunction observed is consistent with nigrostriatal degeneration, the memory and visuospatial impairments, the harbingers of a dementia process reflect dopaminergic independent dysfunction involving broader regions of the brain.

Neuropathological correlates of parkinsonian disorders in a large Dutch autopsy series

The clinical diagnosis in patients with parkinsonian disorders can be challenging, and a definite diagnosis requires neuropathological confirmation. The aim of this study was to examine whether a clinical diagnosis of Parkinson’s disease (PD) and atypical parkinsonian disorders predict the presence of Lewy pathology (LP) and concomitant neuropathological lesions.

We included 293 donors with a history of parkinsonism without dementia at disease onset, collected by the Netherlands Brain Bank (NBB) from 1989 to 2015. We retrospectively categorized donors according the International Parkinson and Movement Disorder Society clinical diagnostic criteria for PD (MDS-PD criteria) as ‘not PD’, ‘probable PD’ or ‘established PD’. We compared the final clinical diagnosis to presence of neuropathological lesions as defined by BrainNet Europe and National Institute on Aging – Alzheimer's Association guidelines.

LP was present in 150 out of 176 donors (85%) with a clinical diagnosis of PD, in 8 out of 101 donors (8%) with atypical parkinsonian disorders and in 4 out of 16 donors (25%) without a definite clinical diagnosis. Independent from age at death, stages of amyloid-β, but not neurofibrillary tau or neuritic plaques, were higher in donors with LP compared to other types of pathology (p = 0.009). The MDS-PD criteria at a certainty level of ‘probable PD’ predicted presence of LP with a diagnostic accuracy of 89.3%. Among donors with LP, ‘established PD’ donors showed similar Braak α-synuclein stages and stages of amyloid-β, neurofibrillary tau and neuritic plaques compared to ‘not PD’ or ‘probable PD’ donors.

In conclusion, both a clinical diagnosis of PD as well as MDS-PD criteria accurately predicted presence of LP in NBB donors. LP was associated with more widespread amyloid-β pathology, suggesting a link between amyloid-β accumulation and LP formation.

The role of disease duration and severity on novel clinical subtypes of Parkinson disease

INTRODUCTION

One of the latest subtyping systems of Parkinson disease (PD) identifies motor severity, cognitive dysfunction, dysautonomia, and rapid eye movement behavior disorder as key features for phenotyping patients into three different subtypes (i.e., mild motor-predominant, diffuse-malignant and intermediate). Since PD subtypes are clinically most relevant if they are mutually exclusive and consistent over-time, we explored the impact of disease stage and duration on these novel subtypes.

METHODS

One-hundred-twenty-two consecutive patients, with a disease duration ranging from 0 to 20 years, were allocated as suggested into these three subtypes. The relationship between either disease duration or stage, as measured by the Hoehn and Yahr staging, and subtype allocation was explored.

RESULTS

Significant differences in subtype distribution were observed across patients stratified according to either disease duration or staging, with the diffuse-malignant subtypes increasing in prevalence as the disease advanced. Both disease duration and staging were independent predictors of subtype allocation.

CONCLUSIONS

These novel PD subtypes are significantly influenced by disease duration and staging, which might suggest that they do not represent mutually exclusive disease pathways. This should be taken into account when attempting correlations with putative biomarkers of disease progression.

Mastering nocturnal jigsaws in Parkinson's disease: a dusk-to-dawn review of night-time symptoms

Finding out about night-time symptoms from Parkinson's disease (PD) patients can be a challenge as many patients and their carers cannot recall many symptoms that occur during the night, resulting in an under-recognition or a large variability of responses from clinical interviews and scales. Moreover, technology-based assessments for most night-time symptoms are still not universally available for use in a patient's home environment. Therefore, most physicians rely on their clinical acumen to capture these night-time symptoms based on pieces of patients' history, bedpartner's reports, clinical features, associated symptoms or conditions. To capture more night-time symptoms, the authors identified common nocturnal symptoms based on how they manifest from dusk to dawn with selected features relevant to PD. While some symptoms occur in healthy individuals, in PD patients, they may impact differently. The authors intend this narrative review to provide a practical guide on how these common night-time symptoms manifest and highlight pertinent issues by focusing on prevalence, clinical symptomatology, and specific relationships to PD. It is also important to recognise that PD-specific sleep disturbances increase with advancing disease with additional contributions from ageing, comorbidities, and medication side effects. However, the relative contribution of each factor to individual symptom may be different in individual patient, necessitating clinical expertise for individual interpretation. While there are debatable issues in certain areas, they underlie the complexity of night-time symptoms. Understanding night-time symptoms in PD is like re-arranging jigsaw pieces of clinical information to create, but never complete, a picture for physicians to instigate appropriate management.

Drooling in Parkinson's Disease: Prevalence and Progression from the Non-motor International Longitudinal Study

Sialorrhoea in Parkinson’s disease (PD) is an often neglected yet key non-motor symptom with impact on patient quality of life. However, previous studies have shown a broad range of prevalence figures. To assess prevalence of drooling in PD and its relationship to quality of life, we performed a retrospective analysis of 728 consecutive PD patients who had a baseline and follow-up assessment as part of the Non-motor International Longitudinal Study (NILS), and for whom drooling presence and severity were available, assessed through the Non-Motor Symptoms Scale (NMSS). In addition, we analysed the prevalence of associated dysphagia through self-reported outcomes. Quality of life was assessed through the PDQ-8 scale. Baseline (disease duration 5.6 years) prevalence of drooling was 37.2% (score ≥ 1 NMSS question 19), and after 3.27 ± 1.74 years follow-up, this was 40.1% (p = 0.17). The prevalence of drooling increased with age (p < 0.001). The severity of drooling, however, did not change (p = 0.12). While in 456 patients without drooling at baseline, only 16% (n = 73) had dysphagia (question 20 of the NMSS), in those with drooling this was 34.3% (p < 0.001). At follow-up, the number of patients with dysphagia had increased, 20.4% with no drooling had dysphagia, and 43.6% with drooling had dysphagia. Both at baseline and follow-up, drooling severity was significantly positively associated with quality of life (PDQ-8; r = 0.199; p < 0.001). In moderately advanced PD patients, subjective drooling occurs in over one-third of patients and was significantly associated with decreased quality of life. Dysphagia occurred significantly more often in patients with drooling.

The Challenge of Disease-Modifying Therapies in Parkinson's Disease: Role of CSF Biomarkers

The development of disease modifying strategies in Parkinson's disease (PD) largely depends on the ability to identify suitable populations after accurate diagnostic work-up. Therefore, patient molecular profiling and disease subtyping are mandatory. Thus far, in clinical trials, PD has been considered to be a "single entity". Conversely, in front of the common feature of nigro-striatal degeneration, PD is pathogenically heterogeneous with a series of several biological and molecular pathways that differently contribute to clinical development and progression. Currently available diagnostic criteria for PD mainly rely on clinical features and imaging biomarkers, thus missing to identify the contribution of pathophysiological pathways, also failing to catch abnormalities occurring in the early stages of disease. Cerebrospinal fluid (CSF) is a promising source of biomarkers, with the high potential for reflecting early changes occurring in PD brain. In this review, we provide an overview on CSF biomarkers in PD, discussing their association with different molecular pathways involved either in pathophysiology or progression in detail. Their potential application in the field of disease modifying treatments is also discussed.

Prognosis and Neuropathologic Correlation of Clinical Subtypes of Parkinson Disease

Importance

Clinical subtyping of Parkinson disease at diagnosis is useful in estimating disease course and survival. Severity and rate of progression of neuropathologies are important determinants of clinical Parkinson subtypes.

Objective

To provide longitudinal clinical disease-course data and neuropathologic correlation for newly proposed Parkinson disease subtypes.

Design, Setting, and Participants

Retrospective cohort study of consecutive patients with autopsy-confirmed Parkinson disease who were regularly seen throughout their disease course by hospital specialists in the United Kingdom and donated their brain at death to the Queen Square Brain Bank between January 2009 and December 2017. Patients with additional neuropathologic diagnoses, monogenic forms of parkinsonism, or insufficiently detailed clinical information were excluded. Based on severity of motor symptoms, rapid eye movement sleep behavior disorder, and autonomic and cognitive function at diagnosis, patients were classified adapting a subtyping classification into mild-motor predominant, intermediate, or diffuse malignant subtypes.

Main Outcomes and Measures

Time from diagnosis to disease milestones (recurrent falls, wheelchair dependence, dementia, and care home placement) and death were compared between subtypes, and their risk was estimated using Cox hazard regression models. Severity and distribution of Lewy pathology and Alzheimer disease-related pathology were assessed using staging systems.

Results

From a total of 146 patients, 111 patients were included (67 men [60.4%]; mean [SD] age at diagnosis, 62.5 [11.5] years). The diffuse malignant subtype had earlier development of milestones and reduced survival. Cox proportional hazard regression showed an increased adjusted risk of any disease milestone (hazard ratio, 10.90; 95% CI, 5.51-21.58; P < .001) and death (hazard ratio, 3.65; 95% CI, 1.98-6.75; P < .001) in the diffuse malignant group. Age at diagnosis was the only additional variable with statistical significance (adjusted hazard ratio for death, 1.14; 95% CI, 1.11-1.17; P <.001). Staging of Lewy pathology and Alzheimer disease-related pathology did not differ between subtypes, although they showed different rates of progression, and the latter was associated with age at death.

Conclusions and Relevance

Parkinson clinical subtypes at diagnosis may estimate disease course and survival, which may be useful in providing a more accurate prognosis in individual patients in clinical practice and helping to stratify subgroups in clinical trials. Different severity and progression of neuropathologies are important determinants of Parkinson subtypes, and age at diagnosis should be included in future subtype classifications.

Excess of singleton loss-of-function variants in Parkinson's disease contributes to genetic risk

BACKGROUND

Parkinson's disease (PD) is a neurodegenerative disorder with complex genetic architecture. Besides rare mutations in high-risk genes related to monogenic familial forms of PD, multiple variants associated with sporadic PD were discovered via association studies.

METHODS

We studied the whole-exome sequencing data of 340 PD cases and 146 ethnically matched controls from the Parkinson's Progression Markers Initiative (PPMI) and performed burden analysis for different rare variant classes. Disease prediction models were built based on clinical, non-clinical and genetic features, including both common and rare variants, and two machine learning methods.

RESULTS

We observed a significant exome-wide burden of singleton loss-of-function variants (corrected p=0.037). Overall, no exome-wide burden of rare amino acid changing variants was detected. Finally, we built a disease prediction model combining singleton loss-of-function variants, a polygenic risk score based on common variants, and family history of PD as features and reached an area under the curve of 0.703 (95% CI 0.698 to 0.708). By incorporating a rare variant feature, our model increased the performance of the state-of-the-art classification model for the PPMI dataset, which reached an area under the curve of 0.639 based on common variants alone.

CONCLUSION

The main finding of this study is to highlight the contribution of singleton loss-of-function variants to the complex genetics of PD and that disease risk prediction models combining singleton and common variants can improve models built solely on common variants.

Diagnosis and Treatment of Parkinson Disease: A Review

IMPORTANCE

Parkinson disease is the most common form of parkinsonism, a group of neurological disorders with Parkinson disease-like movement problems such as rigidity, slowness, and tremor. More than 6 million individuals worldwide have Parkinson disease.

OBSERVATIONS

Diagnosis of Parkinson disease is based on history and examination. History can include prodromal features (eg, rapid eye movement sleep behavior disorder, hyposmia, constipation), characteristic movement difficulty (eg, tremor, stiffness, slowness), and psychological or cognitive problems (eg, cognitive decline, depression, anxiety). Examination typically demonstrates bradykinesia with tremor, rigidity, or both. Dopamine transporter single-photon emission computed tomography can improve the accuracy of diagnosis when the presence of parkinsonism is uncertain. Parkinson disease has multiple disease variants with different prognoses. Individuals with a diffuse malignant subtype (9%-16% of individuals with Parkinson disease) have prominent early motor and nonmotor symptoms, poor response to medication, and faster disease progression. Individuals with mild motor-predominant Parkinson disease (49%-53% of individuals with Parkinson disease) have mild symptoms, a good response to dopaminergic medications (eg, carbidopa-levodopa, dopamine agonists), and slower disease progression. Other individuals have an intermediate subtype. For all patients with Parkinson disease, treatment is symptomatic, focused on improvement in motor (eg, tremor, rigidity, bradykinesia) and nonmotor (eg, constipation, cognition, mood, sleep) signs and symptoms. No disease-modifying pharmacologic treatments are available. Dopamine-based therapies typically help initial motor symptoms. Nonmotor symptoms require nondopaminergic approaches (eg, selective serotonin reuptake inhibitors for psychiatric symptoms, cholinesterase inhibitors for cognition). Rehabilitative therapy and exercise complement pharmacologic treatments. Individuals experiencing complications, such as worsening symptoms and functional impairment when a medication dose wears off ("off periods"), medication-resistant tremor, and dyskinesias, benefit from advanced treatments such as therapy with levodopa-carbidopa enteral suspension or deep brain stimulation. Palliative care is part of Parkinson disease management.

CONCLUSIONS AND RELEVANCE

Parkinson disease is a heterogeneous disease with rapidly and slowly progressive forms. Treatment involves pharmacologic approaches (typically with levodopa preparations prescribed with or without other medications) and nonpharmacologic approaches (such as exercise and physical, occupational, and speech therapies). Approaches such as deep brain stimulation and treatment with levodopa-carbidopa enteral suspension can help individuals with medication-resistant tremor, worsening symptoms when the medication wears off, and dyskinesias.

Prognostic factors of Rapid symptoms progression in patients with newly diagnosed parkinson's disease

Tracking symptoms progression in the early stages of Parkinson's disease (PD) is a laborious endeavor as the disease can be expressed with vastly different phenotypes, forcing clinicians to follow a multi-parametric approach in patient evaluation, looking for not only motor symptomatology but also non-motor complications, including cognitive decline, sleep problems and mood disturbances. Being neurodegenerative in nature, PD is expected to inflict a continuous degradation in patients' condition over time. The rate of symptoms progression, however, is found to be even more chaotic than the vastly different phenotypes that can be expressed in the initial stages of PD. In this work, an analysis of baseline PD characteristics is performed using machine learning techniques, to identify prognostic factors for early rapid progression of PD symptoms. Using open data from the Parkinson's Progression Markers Initiative (PPMI) study, an extensive set of baseline patient evaluation outcomes is examined to isolate determinants of rapid progression within the first two and four years of PD. The rate of symptoms progression is estimated by tracking the change of the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) total score over the corresponding follow-up period. Patients are ranked according to their progression rates and those who expressed the highest rates of MDS-UPDRS total score increase per year of follow-up period are assigned into the rapid progression class, using 5- and 10-quantiles partition. Classification performance against the rapid progression class was evaluated in a per quantile partition analysis scheme and in quantile-independent approach, respectively. The results shown a more accurate patient discrimination with quantile partitioning, however, a much more compact subset of baseline factors is extracted in the latter, making a more suitable for actual interventions in practice. Classification accuracy improved in all cases when using the longer 4-year follow-up period to estimate PD progression, suggesting that a prolonged patient evaluation can provide better outcomes in identifying rapid progression phenotype. Non-motor symptoms are found to be the main determinants of rapid symptoms progression in both follow-up periods, with autonomic dysfunction, mood impairment, anxiety, REM sleep behavior disorders, cognitive decline and memory impairment being alarming signs at baseline evaluation, along with rigidity symptoms, certain laboratory blood test results and genetic mutations.

Identifying sub-phenotypes of acute kidney injury using structured and unstructured electronic health record data with memory networks

Acute Kidney Injury (AKI) is a common clinical syndrome characterized by the rapid loss of kidney excretory function, which aggravates the clinical severity of other diseases in a large number of hospitalized patients. Accurate early prediction of AKI can enable in-time interventions and treatments. However, AKI is highly heterogeneous, thus identification of AKI sub-phenotypes can lead to an improved understanding of the disease pathophysiology and development of more targeted clinical interventions. This study used a memory network-based deep learning approach to discover AKI sub-phenotypes using structured and unstructured electronic health record (EHR) data of patients before AKI diagnosis. We leveraged a real world critical care EHR corpus including 37,486 ICU stays. Our approach identified three distinct sub-phenotypes: sub-phenotype I is with an average age of 63.03±17.25 years, and is characterized by mild loss of kidney excretory function (Serum Creatinine (SCr) 1.55±0.34 mg/dL, estimated Glomerular Filtration Rate Test (eGFR) 107.65±54.98 mL/min/1.73 m²). These patients are more likely to develop stage I AKI. Sub-phenotype II is with average age 66.81±10.43 years, and was characterized by severe loss of kidney excretory function (SCr 1.96±0.49 mg/dL, eGFR 82.19±55.92 mL/min/1.73 m²). These patients are more likely to develop stage III AKI. Sub-phenotype III is with average age 65.07±11.32 years, and was characterized moderate loss of kidney excretory function and thus more likely to develop stage II AKI (SCr 1.69±0.32 mg/dL, eGFR 93.97±56.53 mL/min/1.73 m²). Both SCr and eGFR are significantly different across the three sub-phenotypes with statistical testing plus postdoc analysis, and the conclusion still holds after age adjustment.

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.

Is It Possible to Conduct a Multi-Arm Multi-Stage Platform Trial in Parkinson's Disease: Lessons Learned from Other Neurodegenerative Disorders and Cancer

Many potential disease modifying therapies have been identified as suitable for clinical evaluation in Parkinson's disease (PD). Currently, the evaluation of compounds in phase II and phase III clinical trials in PD are set up in isolation, a process that is lengthy, costly and lacks efficiency. This review will introduce the concept of a multi-arm, multi-stage (MAMS) trial platform which allows for the assessment of several potential therapies at once, transitioning seamlessly from a phase II safety and efficacy study to a phase III trial by means of an interim analysis. At the interim checkpoint, ineffective arms are dropped and replaced by new treatment arms, thereby allowing for the continuous evaluation of interventions. MAMS trial platforms already exist for prostate, renal and oropharyngeal cancer and are currently being developed for progressive multiple sclerosis (PMS) and motor neuron disease (MND) within the UK. As a MAMS trial will evaluate many potential treatments it is of critical importance that a widely endorsed core protocol is developed which will investigate outcomes and objectives meaningful to patients. This review will discuss the challenges of drug selection, trial design, stratification and outcome measures and will share strategies implemented in the planned MAMS trials for MND and PMS that may be of interest to the PD field.

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.

Investigation of somatic CNVs in brains of synucleinopathy cases using targeted SNCA analysis and single cell sequencing

Synucleinopathies are mostly sporadic neurodegenerative disorders of partly unexplained aetiology, and include Parkinson's disease (PD) and multiple system atrophy (MSA). We have further investigated our recent finding of somatic SNCA (α-synuclein) copy number variants (CNVs, specifically gains) in synucleinopathies, using Fluorescent in-situ Hybridisation for SNCA, and single-cell whole genome sequencing for the first time in a synucleinopathy. In the cingulate cortex, mosaicism levels for SNCA gains were higher in MSA and PD than controls in neurons (> 2% in both diseases), and for MSA also in non-neurons. In MSA substantia nigra (SN), we noted SNCA gains in > 3% of dopaminergic (DA) neurons (identified by neuromelanin) and neuromelanin-negative cells, including olig2-positive oligodendroglia. Cells with CNVs were more likely to have α-synuclein inclusions, in a pattern corresponding to cell categories mostly relevant to the disease: DA neurons in Lewy-body cases, and other cells in the striatonigral degeneration-dominant MSA variant (MSA-SND). Higher mosaicism levels in SN neuromelanin-negative cells may correlate with younger onset in typical MSA-SND, and in cingulate neurons with younger death in PD. Larger sample sizes will, however, be required to confirm these putative findings. We obtained genome-wide somatic CNV profiles from 169 cells from the substantia nigra of two MSA cases, and pons and putamen of one. These showed somatic CNVs in ~ 30% of cells, with clonality and origins in segmental duplications for some. CNVs had distinct profiles based on cell type, with neurons having a mix of gains and losses, and other cells having almost exclusively gains, although control data sets will be required to determine possible disease relevance. We propose that somatic SNCA CNVs may contribute to the aetiology and pathogenesis of synucleinopathies, and that genome-wide somatic CNVs in MSA brain merit further study.

Longitudinal brain atrophy distribution in advanced Parkinson's disease: What makes the difference in "cognitive status" converters?

We investigated the brain atrophy distribution pattern and rate of regional atrophy change in Parkinson's disease (PD) in association with the cognitive status to identify the morphological characteristics of conversion to mild cognitive impairment (MCI) and dementia (PDD). T1-weighted longitudinal 3T MRI data (up to four follow-up assessments) from neuropsychologically well-characterized advanced PD patients (n = 172, 8.9 years disease duration) and healthy elderly controls (n = 85) enrolled in the LANDSCAPE study were longitudinally analyzed using a linear mixed effect model and atlas-based volumetry and cortical thickness measures. At baseline, PD patients presented with cerebral atrophy and cortical thinning including striatum, temporoparietal regions, and primary/premotor cortex. The atrophy was already observed in "cognitively normal" PD patients (PD-N) and was considerably more pronounced in cognitively impaired PD patients. Linear mixed effect modeling revealed almost similar rates of atrophy change in PD and controls. The group comparison at baseline between those PD-N whose cognitive performance remained stable (n = 42) and those PD-N patients who converted to MCI/PDD ("converter" cPD-N, n = 26) indicated suggested cortical thinning in the anterior cingulate cortex in cPD-N patients which was correlated with cognitive performance. Our results suggest that cortical brain atrophy has been already expanded in advanced PD patients without overt cognitive deficits while atrophy progression in late disease did not differ from "normal" aging regardless of the cognitive status. It appears that cortical atrophy begins early and progresses already in the initial disease stages emphasizing the need for therapeutic interventions already at disease onset.

Predicting severity and prognosis in Parkinson's disease from brain microstructure and connectivity

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White matter disruption occurs in Parkinson's disease across several brain regions.

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DTI properties could identify clinically distinct subtypes of Parkinson's disease.

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Structural neural disruption can predict clinical outcomes in Parkinson's disease.

Objectives: Investigating biomarkers to demonstrate progression of Parkinson's disease (PD) is of high priority. We investigated the association of brain structural properties with progression of clinical outcomes and their ability to differentiate clinical subtypes of PD.

Methods: A comprehensive set of clinical features was evaluated at baseline and 4.5-year follow-up for 144 de-novo PD patients from the Parkinson's Progression Markers Initiative. We created a global composite outcome (GCO) by combining z-scores of non-motor and motor symptoms, motor signs, overall activities of daily living and global cognition, as a single numeric indicator of prognosis. We classified patients into three subtypes based on multi-domain clinical criteria: ‘mild motor-predominant’, ‘intermediate’ and ‘diffuse-malignant’. We analyzed diffusion-weighted scans at the early drug-naïve stage and extracted fractional anisotropy and mean diffusivity (MD) of basal ganglia and cortical sub-regions. Then, we employed graph theory to calculate network properties and used network-based statistic to investigate our primary hypothesis.

Results: Baseline MD of globus pallidus was associated with worsening of motor severity, cognition, and GCO after 4.5 years of follow-up. Connectivity disruption at baseline was correlated with decline in cognition, and increase in GCO. Baseline MD of nucleus accumbens, globus pallidus and basal-ganglia were linked to clinical subtypes at 4.5-year of follow-up. Disruption in sub-cortical networks associated with being subtyped as ‘diffuse-malignant’ versus ‘mild motor-predominant’ after 4.5 years.

Conclusions: Diffusion imaging analysis at the early de-novo stage of PD was able to differentiate clinical sub-types of PD after 4.5 years and was highly associated with future clinical outcomes of PD.

Local vulnerability and global connectivity jointly shape neurodegenerative disease propagation

It is becoming increasingly clear that brain network organization shapes the course and expression of neurodegenerative diseases. Parkinson disease (PD) is marked by progressive spread of atrophy from the midbrain to subcortical structures and, eventually, to the cerebral cortex. Recent discoveries suggest that the neurodegenerative process involves the misfolding and prion-like propagation of endogenous α-synuclein via axonal projections. However, the mechanisms that translate local "synucleinopathy" to large-scale network dysfunction and atrophy remain unknown. Here, we use an agent-based epidemic spreading model to integrate structural connectivity, functional connectivity, and gene expression and to predict sequential volume loss due to neurodegeneration. The dynamic model replicates the spatial and temporal patterning of empirical atrophy in PD and implicates the substantia nigra as the disease epicenter. We reveal a significant role for both connectome topology and geometry in shaping the distribution of atrophy. The model also demonstrates that SNCA and GBA transcription influence α-synuclein concentration and local regional vulnerability. Functional coactivation further amplifies the course set by connectome architecture and gene expression. Altogether, these results support the theory that the progression of PD is a multifactorial process that depends on both cell-to-cell spreading of misfolded proteins and regional vulnerability.

Gray Matter Changes in Parkinson's and Alzheimer's Disease and Relation to Cognition

PURPOSE OF REVIEW

We summarize structural (s)MRI findings of gray matter (GM) atrophy related to cognitive impairment in Alzheimer's disease (AD) and Parkinson's disease (PD) in light of new analytical approaches and recent longitudinal studies results.

RECENT FINDINGS

The hippocampus-to-cortex ratio seems to be the best sMRI biomarker to discriminate between various AD subtypes, following the spatial distribution of tau pathology, and predict rate of cognitive decline. PD is clinically far more variable than AD, with heterogeneous underlying brain pathology. Novel multivariate approaches have been used to describe patterns of early subcortical and cortical changes that relate to more malignant courses of PD. New emerging analytical approaches that combine structural MRI data with clinical and other biomarker outcomes hold promise for detecting specific GM changes in the early stages of PD and preclinical AD that may predict mild cognitive impairment and dementia conversion.

Modifiable risk and protective factors in disease development, progression and clinical subtypes of Parkinson's disease: What do prospective studies suggest?

Parkinson's disease (PD) is a neurodegenerative disorder whose pathogenesis depends on a combination of genetic and environmental factors. The aim of the present review was to provide an updated description of the findings emerging from prospective longitudinal cohort studies on the possible risk/protective factors underlying the development, progression and clinical subtypes of PD. We reviewed all the environmental, lifestyle, dietary, comorbid and pharmacological factors that have been investigated as possible modifiable protective/risk factors for PD by longitudinal studies. Only a few factors have the epidemiological evidence and the biological plausibility to be considered risk (pesticides, dairy products, β2-adrenoreceptor antagonists) or protective (smoking, caffeine and tea intake, physical activity, gout, vitamin E intake, non-steroidal anti-inflammatory drugs and β2-adrenoreceptor agonists) factors for PD. Caffeine intake and physical activity also seem to slow down the progression of the disease, thus representing good candidates for primary prevention and disease modifying strategies in PD. Possible modifiable risk factors of PD subtypes is almost unknown and this might depend on the uncertain biological and neuropathological reliability of clinical subtypes. The results of the present review suggest that only eleven risk/protective factors may be associated with the risk of PD. It may be possible to target some of these factors for preventive interventions aimed at reducing the risk of developing and the rate of progression of PD.

Orthostatic hypotension and REM sleep behaviour disorder: impact on clinical outcomes in α-synucleinopathies

OBJECTIVE

Review the effect of orthostatic hypotension (OH) and rapid-eye-movement sleep behavioural disorder (RBD) on survival, cognitive impairment and postural stability, and discuss pathogenic mechanisms involved in the association of these two common non-motor features with relevant clinical outcomes in α-synucleinopathies.

METHODS

We searched PubMed (January 2007-February 2019) for human studies of OH and RBD evaluating cognitive impairment, postural instability, and survival in Parkinson's disease (PD), dementia with Lewy bodies (DLB), multiple system atrophy (MSA) and pure autonomic failure (PAF). Included studies were analysed for design, key results and limitations as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

RESULTS

OH and RBD showed a positive association with cognitive impairment in PD and DLB, conflicting association in PAF, and no association in MSA. OH was correlated with incident falls and postural instability in PD and DLB but not in MSA. The association between RBD and postural instability was inconclusive; positive in five studies, negative in seven. OH, but not RBD, correlated with reduced survival in PD, DLB and MSA. The combination of OH and RBD was associated with cognitive impairment and more rapid progression of postural instability.

CONCLUSIONS

OH and RBD yielded individual and combined negative effects on disability in α-synucleinopathies, reflecting a 'malignant' phenotype of PD with early cognitive impairment and postural instability. Underlying mechanisms may include involvement of selected brainstem cholinergic and noradrenergic nuclei.

Relations of non-motor symptoms and dopamine transporter binding in REM sleep behavior disorder

The aim of this study was to evaluate associations of motor and non-motor symptoms with dopamine transporter binding in prodromal stage of synucleinopathies. We examined 74 patients with idiopathic REM sleep behavior disorder (RBD), which is a prodromal synucleinopathy, and 39 controls using Movement Disorders Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), Montreal Cognitive Assessment, University of Pennsylvania Smell Identification Test (UPSIT), Farnsworth-Munsell 100 hue test, orthostatic test, Scales for Outcomes in PD-Autonomic, Beck depression inventory-II, State-Trait Anxiety Inventory, and video-polysomnography. Electromyographic muscle activity during REM sleep was quantified according to Sleep Innsbruck-Barcelona criteria. In 65 patients, dopamine transporter single-photon emission computed tomography (DAT-SPECT) imaging was performed, putaminal binding ratio was calculated and scans were classified as normal, borderline, or abnormal. Compared to controls, RBD patients had significantly more severe scores in all examined tests. Patients with abnormal DAT-SPECT had higher MDS-UPDRS motor score (p = 0.006) and higher prevalence of orthostatic hypotension (p = 0.008). Putaminal binding ratio was positively associated with UPSIT score (p = 0.03) and negatively associated with tonic (p = 0.003) and phasic (p = 0.01) muscle activity during REM sleep. These associations likely reflect simultaneous advancement of underlying pathology in substantia nigra and susceptible brainstem and olfactory nuclei in prodromal synucleinopathy.

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.

Assessment of a prognostic MRI biomarker in early de novo Parkinson's disease

BACKGROUND

Commonly used neuroimaging biomarkers in Parkinson's disease (PD) are useful for diagnosis but poor at predicting outcomes. We explored whether an atrophy pattern from whole-brain structural MRI, measured in the drug-naïve early stage, could predict PD prognosis.

METHODS

362 de novo PD patients with T1-weighted MRI (n = 222 for the main analysis, 140 for the validation analysis) were recruited from the Parkinson's Progression Markers Initiative (PPMI). We investigated a previously identified PD-specific network atrophy pattern as a potential biomarker of disease severity and prognosis. Progression trajectories of motor function (MDS-UPDRS-part III), cognition (Montreal Cognitive Assessment (MoCA)), and a global composite outcome measure were compared between atrophy tertiles using mixed effect models. The prognostic value of the MRI atrophy measure was compared with 123I ioflupane single photon emission computed tomography, the postural-instability-gait-disturbance score, and cerebrospinal fluid markers.

FINDINGS

After 4.5 years follow-up, PD-specific atrophy network score at baseline significantly predicted change in UPDRS-part III (r = -0.197, p = .003), MoCA (r = 0.253, p = .0002) and global composite outcome (r = -0.249, p = .0002). Compared with the 3rd tertile (i.e. least atrophy), the tertile with the highest baseline atrophy (i.e. the 1st tertile) had a 3-point annual faster progression in UPDRS-part III (p = .012), faster worsening of posture-instability gait scores (+0.21 further annual increase, p < .0001), faster decline in MoCA (-0.74 further annual decline in MoCA, p = .0372) and a + 0.38 (p = .0029) faster annual increase in the global composite z-score. All findings were replicated in a validation analysis using 1.5T MRI. Receiver operating characteristic analysis confirmed the superiority of the MRI biomarker, although it had modest AUC values (0.63). By comparison, the other biomarkers were limited in their ability to predict prognosis either in the main or validation analysis.

INTERPRETATION

A PD-specific network atrophy pattern predicts progression of motor, cognitive, and global outcome in PD, and is a better predictor of prognosis than any of the other tested biomarkers. Therefore, it has potential as a prognostic biomarker for clinical trials of early PD.

Neuropathology and pathogenesis of extrapyramidal movement disorders: a critical update-I. Hypokinetic-rigid movement disorders

Extrapyramidal movement disorders include hypokinetic rigid and hyperkinetic or mixed forms, most of them originating from dysfunction of the basal ganglia (BG) and their information circuits. The functional anatomy of the BG, the cortico-BG-thalamocortical, and BG-cerebellar circuit connections are briefly reviewed. Pathophysiologic classification of extrapyramidal movement disorder mechanisms distinguish (1) parkinsonian syndromes, (2) chorea and related syndromes, (3) dystonias, (4) myoclonic syndromes, (5) ballism, (6) tics, and (7) tremor syndromes. Recent genetic and molecular-biologic classifications distinguish (1) synucleinopathies (Parkinson's disease, dementia with Lewy bodies, Parkinson's disease-dementia, and multiple system atrophy); (2) tauopathies (progressive supranuclear palsy, corticobasal degeneration, FTLD-17; Guamian Parkinson-dementia; Pick's disease, and others); (3) polyglutamine disorders (Huntington's disease and related disorders); (4) pantothenate kinase-associated neurodegeneration; (5) Wilson's disease; and (6) other hereditary neurodegenerations without hitherto detected genetic or specific markers. The diversity of phenotypes is related to the deposition of pathologic proteins in distinct cell populations, causing neurodegeneration due to genetic and environmental factors, but there is frequent overlap between various disorders. Their etiopathogenesis is still poorly understood, but is suggested to result from an interaction between genetic and environmental factors. Multiple etiologies and noxious factors (protein mishandling, mitochondrial dysfunction, oxidative stress, excitotoxicity, energy failure, and chronic neuroinflammation) are more likely than a single factor. Current clinical consensus criteria have increased the diagnostic accuracy of most neurodegenerative movement disorders, but for their definite diagnosis, histopathological confirmation is required. We present a timely overview of the neuropathology and pathogenesis of the major extrapyramidal movement disorders in two parts, the first one dedicated to hypokinetic-rigid forms and the second to hyperkinetic disorders.

Heterogeneous Patterns of Striatal Dopamine Loss in Patients with Young- versus Old-Onset Parkinson's Disease: Impact on Clinical Features

Objective

Ample evidence has suggested that age at onset of Parkinson’s disease (PD) is associated with heterogeneous clinical features in individuals. We hypothesized that this may be attributed to different patterns of nigrostriatal dopamine loss.

Methods

A total of 205 consecutive patients with de novo PD who underwent ¹⁸F-FP-CIT PET scans (mean follow-up duration, 6.31 years) were divided into three tertile groups according to their age at onset of parkinsonian motor symptoms. Striatal dopamine transporter (DAT) availability was compared between the old- (n = 73) and young-onset (n = 66) groups. In addition, the risk of developing freezing of gait (FOG) and longitudinal requirements for dopaminergic medications were examined.

Results

The old-onset PD group (mean age at onset, 72.66 years) exhibited more severe parkinsonian motor signs than the young-onset group (52.58 years), despite comparable DAT availability in the posterior putamen; moreover, the old-onset group exhibited more severely decreased DAT availability in the caudate than the young-onset group. A Cox regression model revealed that the old-onset PD group had a higher risk for developing FOG than the young-onset group [hazard ratio 2.523, 95% confidence interval (1.239–5.140)]. The old-onset group required higher doses of dopaminergic medications for symptom control than the young-onset group over time.

Conclusion

The present study demonstrated that the old-onset PD group exhibited more severe dopamine loss in the caudate and were more likely to develop gait freezing, suggesting that age at onset may be one of the major determinants of the pattern of striatal dopamine depletion and progression of gait disturbance in PD.

Dyskinesia in multiple system atrophy and progressive supranuclear palsy

In the differential diagnosis of Parkinson syndromes, the response to L-Dopa is an essential criterion for the diagnosis of idiopathic Parkinson's syndrome (IPS), and the presence of L-Dopa-induced dyskinesia (LID) is considered a supportive criterion. This implies that in the presence of LID an atypical Parkinson-syndrome (APS) is unlikely. However, dyskinesia, and in particular LID, can also be present in APS such as MSA and PSP, although less frequently, and with varying clinical appearance. We conclude that whilst presence of dyskinesia provides support for a diagnosis of IPD, they do not allow reliable differentiation from APS.

Alteration of Tremor Dominant and Postural Instability Gait Difficulty Subtypes During the Progression of Parkinson's Disease: Analysis of the PPMI Cohort

Background: Classifying PD into tremor dominant (TD) and postural instability gait difficulty (PIGD) subtypes may have several limitations, such as its diagnostic inconsistency and inability to reflect disease stage. In this study, we investigated the patterns of progression and dopaminergic denervation, by prospective evaluation at regular time intervals. Methods: 325 PD dopamine replacement drug-naïve patients (age 61.2 ± 9.7, M:F = 215:110) were enrolled. Patients were grouped into TD, indeterminant, and PIGD subtypes. Clinical parameters and I-123 FP-CIT SPECT images of each groups were analyzed and compared at baseline, 1, 2, and 4 years of follow up periods. Results: Baseline I-123 FP-CIT uptakes of the striatum were significantly higher in the TD group compared with the indeterminant group and PIGD group (p < 0.01). H & Y stage and MDS-UPDRS part III scores of the indeterminant group were significantly worse at baseline, compared with the TD and PIGD groups (p < 0.001 and p < 0.01, respectively), and MDS-UPDRS part II scores of the indeterminant group were significantly worse than the PIGD group (p < 0.001). There were no other significant differences of age, gender, weight, duration of PD, SCOPA-AUT, MOCA, usage of dopamine agonists, and levodopa equivalent daily doses at baseline. After 4 years of follow up, there were no differences of I-123 FP-CIT uptakes or clinical parameters, except for the MDS-UPDRS part II between the TD and indeterminant group (p < 0.05). The motor-subtypes were reevaluated at the 4 years period, and the proportion of patients grouped to the PIGD subtype increased. In the reevaluated PIGD group, MDS-UPDRS part II score (p < 0.001), SCOPA-AUT (p < 0.001), the proportion of patients who developed levodopa induced dyskinesia were higher than the reevaluated TD group, and the striatal I-123 FP-CIT uptakes were significantly lower (p < 0.01). Conclusion: There are no significant differences of symptoms and dopaminergic innervation between the TD and PIGD group after a certain period of follow up. Significant portion of patients switched from the TD subtype to the PIGD subtype during disease progression, and had a worse clinical prognosis.

Cortical thinning in patients with REM sleep behavior disorder is associated with clinical progression

The aim of this study is to determine whether structural MRI measures are associated with clinical impairment and progression to a Lewy body disease in patients with idiopathic REM sleep behavior disorder (iRBD). Twenty-seven patients with iRBD in addition to patients with de novo PD and healthy controls were included from the Parkinson's Progression Markers Initiative. Patients with iRBD were followed for up to 3 years. Clinical and MRI measures were compared across groups and the association between clinical features and structural MRI was assessed in iRBD patients. Cox regression analyses were applied to identify risk factors for progressing to a Lewy body disease in iRBD. Our results showed that, at baseline, iRBD patients showed parietal and occipital cortical thinning, compared to controls. They also showed worse motor and non-motor abilities, some of which correlated with motor, frontal or temporal cortical thinning. At follow-up, six (22%) iRBD patients were diagnosed with a Lewy body disorder. These patients showed cortical thinning in frontal, occipital and parietal areas compared to iRBD non-converters. Cortical thinning was a significant predictor for future development of a Lewy body disorder (HR: 0.784; 95% CI: 0.640-0.960; p = 0.02). We conclude that cortical thinning is associated with worse motor and non-motor abilities, and predicts conversion to a Lewy body disorder in iRBD, suggesting it could be used to select candidates for clinical trials to delay the onset of neurodegenerative disease.

Glucocerebrosidase mutations and phenoconversion of REM sleep behavior disorder to parkinsonism and dementia

BACKGROUND

Mutations in the glucocerebrosidase (GBA) gene are strongly associated with REM sleep behavior disorder (RBD). It is unclear whether GBA mutations might affect clinical phenotype or rate of phenoconversion to parkinsonism or dementia.

METHODS

We sequenced GBA in polysomnographic-proven idiopathic RBD (iRBD) patients. The effect of GBA mutations on clinical neurodegenerative markers and phenoconversion rate was assessed.

RESULTS

Of 102 patients sequenced, 13 (13%) had GBA mutations and 89 did not. Aside from lower self-reported age of RBD onset in subjects with GBA mutations, no significant differences were observed in any clinical marker between patients with and without mutations. However, GBA mutations were associated with 3.2-fold higher phenoconversion rate from RBD to parkinsonism and/or dementia (95% CI = 1.4-7.3, p = 0.006).

CONCLUSION

Although GBA mutations do not appear to affect clinical neurodegenerative markers (and thus are not differentiable as an independent subtype of iRBD), they may accelerate the conversion of RBD to defined neurodegenerative synucleinopathy.

Biomarkers for Dementia, Fatigue, and Depression in Parkinson's Disease

Parkinson's disease is a common multisystem neurodegenerative disorder characterized by typical motor and non-motor symptoms. There is an urgent need for biomarkers for assessment of disease severity, complications and prognosis. In addition, biomarkers reporting the underlying pathophysiology assist in understanding the disease and developing neuroprotective therapies. Ultimately, biomarkers could be used to develop a more efficient personalized approach for clinical trials and treatment strategies. With the goal to improve quality of life in Parkinson's disease it is essential to understand and objectively monitor non-motor symptoms. This narrative review provides an overview of recent developments of biomarkers (biofluid samples and imaging) for three common neuropsychological syndromes in Parkinson's disease: dementia, fatigue, and depression.

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

Although Parkinson's disease (PD) is primarily a movement disorder, there are a range of associated nonmotor symptoms, including cognitive impairment, depression and sleep disturbance. These can occur throughout the disease course, even predating the motor syndrome. However, both motor and nonmotor symptoms are variable between individual patients. Rate of disease progression is also heterogenous: although 50% have reached key milestones of either postural instability or dementia within 4 years from diagnosis, almost a quarter have a good prognosis at 10 years. In this review we discuss how a range of different factors including clinical features, pathology and genetics, have been used to describe the heterogeneity of PD. We explore the value of longitudinal studies of incident PD cohorts, based on our own experience in Cambridgeshire, to define differences in rates of disease progression and predictors of outcome, including how such studies have informed the development of prognostic models which can be used at an individual patient level. Finally, we discuss the benefits of better understanding the basis of heterogeneity of PD in terms of implications for the development and trialling of more targeted therapies for different subgroups of patients, including regenerative approaches.

Risk factors for possible REM sleep behavior disorder: A CLSA population-based cohort study

OBJECTIVE

To assess sociodemographic, socioeconomic, and clinical correlates of idiopathic REM sleep behavior disorder (RBD) in a 30,097-person national cohort.

METHODS

Participants 45 to 85 years of age in Canada were collected as part of the Canadian Longitudinal Study on Aging. Possible RBD (pRBD) was screened with the REM Sleep Behavior Disorder Single-Question Screen, a questionnaire with 94% specificity and 87% sensitivity. To improve diagnostic accuracy, those screening positive for apnea or non-REM parasomnia (young-onset pRBD) and those self-reporting dementia or Parkinson disease were excluded. A series of sociodemographic, lifestyle, and mental health variables were analyzed cross-sectionally. Potential correlates were assessed via multivariable logistic regression.

RESULTS

Of 30,097 participants, 958 (3.2%) were identified as having pRBD. Male sex (odds ratio [OR] 2.09, 95% confidence interval [CI] 1.78-2.44) and lower education (OR 0.95, 95% CI 0.92-0.98) were associated with pRBD. Participants with pRBD had smoked more (pack-years OR 1.01, 95% CI 1.00-1.01) and were more likely to be moderate to heavy drinkers (OR 1.25, 95% CI 1.04-1.51). There was a strong association between pRBD and self-reported antidepressant treatment for depression (OR 2.77, 95% CI 2.23-3.45), psychological distress (OR 1.61, 95% CI 1.44-1.80), mental illness (OR 2.09, 95% CI 1.75-2.49), and posttraumatic stress disorder (OR 2.68, 95% CI 1.97-3.65).

CONCLUSIONS

Our study replicated previous reported associations between pRBD and smoking, low education, and male sex and found previously unreported links with alcohol use and psychological distress. Risk factors for pRBD differ from those previously defined for neurodegenerative synucleinopathies.

Data-Driven Subtyping of Parkinson's Disease Using Longitudinal Clinical Records: A Cohort Study

Parkinson's disease (PD) is associated with diverse clinical manifestations including motor and non-motor signs and symptoms, and emerging biomarkers. We aimed to reveal the heterogeneity of PD to define subtypes and their progression rates using an automated deep learning algorithm on the top of longitudinal clinical records. This study utilizes the data collected from the Parkinson's Progression Markers Initiative (PPMI), which is a longitudinal cohort study of patients with newly diagnosed Parkinson's disease. Clinical information including motor and non-motor assessments, biospecimen examinations, and neuroimaging results were used for identification of PD subtypes. A deep learning algorithm, Long-Short Term Memory (LSTM), was used to represent each patient as a multi-dimensional time series for subtype identification. Both visualization and statistical analysis were performed for analyzing the obtained PD subtypes. As a result, 466 patients with idiopathic PD were investigated and three subtypes were identified. Subtype I (Mild Baseline, Moderate Motor Progression) is comprised of 43.1% of the participants, with average age 58.79 ± 9.53 years, and was characterized by moderate functional decay in motor ability but stable cognitive ability. Subtype II (Moderate Baseline, Mild Progression) is comprised of 22.9% of the participants, with average age 61.93 ± 6.56 years, and was characterized by mild functional decay in both motor and non-motor symptoms. Subtype III (Severe Baseline, Rapid Progression) is comprised 33.9% of the patients, with average age 65.32 ± 8.86 years, and was characterized by rapid progression of both motor and non-motor symptoms. These subtypes suggest that when comprehensive clinical and biomarker data are incorporated into a deep learning algorithm, the disease progression rates do not necessarily associate with baseline severities, and the progression rate of non-motor symptoms is not necessarily correlated with the progression rate of motor symptoms.