Pre-motor features of Parkinson's disease: the Honolulu-Asia Aging Study experience

A biological definition of neuronal α-synuclein disease: towards an integrated staging system for research

Parkinson's disease and dementia with Lewy bodies are currently defined by their clinical features, with α-synuclein pathology as the gold standard to establish the definitive diagnosis. We propose that, given biomarker advances enabling accurate detection of pathological α-synuclein (ie, misfolded and aggregated) in CSF using the seed amplification assay, it is time to redefine Parkinson's disease and dementia with Lewy bodies as neuronal α-synuclein disease rather than as clinical syndromes. This major shift from a clinical to a biological definition of Parkinson's disease and dementia with Lewy bodies takes advantage of the availability of tools to assess the gold standard for diagnosis of neuronal α-synuclein (n-αsyn) in human beings during life. Neuronal α-synuclein disease is defined by the presence of pathological n-αsyn species detected in vivo (S; the first biological anchor) regardless of the presence of any specific clinical syndrome. On the basis of this definition, we propose that individuals with pathological n-αsyn aggregates are at risk for dopaminergic neuronal dysfunction (D; the second biological anchor). Our biological definition establishes a staging system, the neuronal α-synuclein disease integrated staging system (NSD-ISS), rooted in the biological anchors (S and D) and the degree of functional impairment caused by clinical signs or symptoms. Stages 0-1 occur without signs or symptoms and are defined by the presence of pathogenic variants in the SNCA gene (stage 0), S alone (stage 1A), or S and D (stage 1B). The presence of clinical manifestations marks the transition to stage 2 and beyond. Stage 2 is characterised by subtle signs or symptoms but without functional impairment. Stages 2B-6 require both S and D and stage-specific increases in functional impairment. A biological definition of neuronal α-synuclein disease and an NSD-ISS research framework are essential to enable interventional trials at early disease stages. The NSD-ISS will evolve to include the incorporation of data-driven definitions of stage-specific functional anchors and additional biomarkers as they emerge and are validated. Presently, the NSD-ISS is intended for research use only; its application in the clinical setting is premature and inappropriate.

The pathogenesis of Parkinson's disease

Parkinson's disease is a progressive neurodegenerative condition associated with the deposition of aggregated α-synuclein. Insights into the pathogenesis of Parkinson's disease have been derived from genetics and molecular pathology. Biochemical studies, investigation of transplanted neurons in patients with Parkinson's disease, and cell and animal model studies suggest that abnormal aggregation of α-synuclein and spreading of pathology between the gut, brainstem, and higher brain regions probably underlie the development and progression of Parkinson's disease. At a cellular level, abnormal mitochondrial, lysosomal, and endosomal function can be identified in both monogenic and sporadic Parkinson's disease, suggesting multiple potential treatment approaches. Recent work has also highlighted maladaptive immune and inflammatory responses, possibly triggered in the gut, that accelerate the pathogenesis of Parkinson's disease. Although there are currently no disease-modifying treatments for Parkinson's disease, we now have a solid basis for the development of rational neuroprotective therapies that we hope will halt the progression of this disabling neurological condition.

The epidemiology of Parkinson's disease

The epidemiology of Parkinson's disease shows marked variations in time, geography, ethnicity, age, and sex. Internationally, prevalence has increased over and above demographic changes. There are several potential reasons for this increase, including the decline in other competing causes of death. Whether incidence is increasing, especially in women or in many low-income and middle-income countries where there is a shortage of high-quality data, is less certain. Parkinson's disease is more common in older people and men, and a variety of environmental factors have been suggested to explain why, including exposure to neurotoxic agents. Within countries, there appear to be ethnic differences in disease risk, although these differences might reflect differential access to health care. The cause of Parkinson's disease is multifactorial, and involves genetic and environmental factors. Both risk factors (eg, pesticides) and protective factors (eg, physical activity and tendency to smoke) have been postulated to have a role in Parkinson's disease, although elucidating causality is complicated by the long prodromal period. Following the establishment of public health strategies to prevent cardiovascular diseases and some cancers, chronic neurodegenerative diseases such as Parkinson's disease and dementia are gaining a deserved higher priority. Multipronged prevention strategies are required that tackle population-based primary prevention, high-risk targeted secondary prevention, and Parkinson's disease-modifying therapies for tertiary prevention. Future international collaborations will be required to triangulate evidence from basic, applied, and epidemiological research, thereby enhancing the understanding and prevention of Parkinson's disease at a global level.

Cognitive impairment in REM-sleep behaviour disorder and individuals at risk of Parkinson's disease

BACKGROUND

Mild cognitive impairment (MCI) is commonly present at the time of Parkinson's Disease (PD) diagnosis, but its prevalence amongst individuals at increased risk of PD is unclear.

METHODS

Cognition was assessed using the Montreal Cognitive Assessment (MoCA) in 208 participants in the PREDICT-PD study, and 25 participants with REM-sleep behaviour disorder (RBD). Prevalence of MCI level I was determined in all participants, and level II MCI in the RBD sub-group.

RESULTS

Total MoCA scores were worse in the higher risk than the lower risk group defined as those below the 15th percentile of risk (p = 0.009), and in the RBD group compared to all healthy participants (p < 0.001). The prevalence of MCI level I was 12.8% in the lower-risk, 21.9% in the higher-risk (within the highest 15th percentile) and 64% in RBD participants; 66% of RBD participants had MCI level II with multi-domain MCI, but particularly attention and memory deficits.

CONCLUSIONS

Cognitive impairment is increased in different groups at higher risk of PD, particularly in the subgroup formally diagnosed with RBD.

Risk disclosure in prodromal Parkinson's disease - A survey of neurologists

INTRODUCTION

In the absence of a disease-modifying treatment and prognostic uncertainty, ethics of risk disclosure in prodromal Parkinson's disease (PD) is challenging. Previous studies highlighted several facets of these challenges from the perspective of involved parties. However, to date, the view of neurologists who may encounter individuals with prodromal PD remained unrepresented. Moreover, cross-cultural differences intrinsic to the ethics of risk disclosure are yet to be elucidated. Therefore, we investigated the attitude of neurologists toward risk disclosure in prodromal PD.

METHODS

In this observational study, Turkish neurologists were invited to fill out a questionnaire evaluating their stance on risk disclosure regarding an individual with polysomnography-confirmed REM sleep behavior disorder, which is the strongest risk factor for PD.

RESULTS

More than 90% of the participating 222 neurologists were familiar with prodromal PD. While 15.3% stated that the risk should be disclosed in any case, 6.8% chose no disclosure. The remaining 77.9% favored disclosure only under certain circumstances, the plurality of which was the individual's consent to know about the risk. After reminding the potential neuroprotective effects of exercise and diet, neurologists who chose the option of "no disclosure" decreased to 3.2% (McNemar's test p = 0.008). No significant differences among the neurologists were found regarding sex, academic title, or field of interest.

CONCLUSION

The majority of the neurologists found it appropriate to disclose the risk of future PD only if the individual expresses a desire to know. Also, recognition of the impact of lifestyle factors on PD is important in prognostic counseling.

Gut-brain axis: Review on the association between Parkinson's disease and plant lectins

Gastrointestinal (GI) involvement in the pathogenesis of Parkinson's Disease (PD) has been widely recognized and supported in recent literature. Prospective and retrospective studies found non-motor symptoms within the GI, specifically constipation, precede cardinal signs and cognitive decline by almost 20 years. In 2002, Braak et al. were the first to propose that PD is a six-stage propagating neuropathological process originating from the GI tract (GIT). Aggregated α-synuclein (α-syn) protein from the GIT is pathognomonic for the development of PD. This article reviews the current literature from the past 10 years as well as original research found in PubMed on the combined effects of enteric glial cells and lectins on the development of Parkinson's Disease. Studies have found that these aggregated and phosphorylated proteins gain access to the brain via retrograde transport through fast and slow fibers of intestinal neurons. Plant lectins, commonly found within plant-based diets, have been found to induce Leaky Gut Syndrome and can activate enteric glial cells, causing the release of pro-inflammatory cytokines. Oxidative stress on the enteric neurons, caused by a chronic neuro-inflammatory state, can cause a-syn aggregation and lead to Lewy Body formation, a hallmark finding in PD. Although the current literature provides a connection between the consumption of plant lectins and the pathophysiology of PD, further research is required to evaluate confounding variables such as food antigen mimicry and other harmful substances found in our diets.

Serial olfactory testing for the diagnosis of prodromal Parkinson's disease in the PARS study

BACKGROUND

The Parkinson Associated Risk Syndrome (PARS) study was designed to evaluate whether screening with olfactory testing and dopamine transporter (DAT) imaging could identify participants at risk for developing Parkinson's disease (PD).

OBJECTIVE

Hyposmia on a single test has been associated with increased risk of PD, but, taken alone, lacks specificity. We evaluated whether repeating olfactory testing improves the diagnostic characteristics of this screening approach.

METHODS

Participants completed up to 10 years of clinical and imaging evaluations in the PARS cohort. Olfaction was assessed with the University of Pennsylvania Smell Identification Test at baseline and on average 1.4 years later. Multiple logistic regression and Cox proportional hazards regression were used to estimate the hazard of development of clinical PD or abnormal DAT imaging.

RESULTS

Of 186 participants who were initially hyposmic, 28% reverted to normosmia on repeat testing (reverters). No initially normosmic subjects and only 2% of reverters developed DAT imaging progression or clinical PD, compared to 29% of subjects with persistent hyposmia who developed abnormal DAT and 20% who developed clinical PD. The relative risk of clinical conversion to PD was 8.3 (95% CI:0.92-75.2, p = 0.06) and of abnormal DAT scan was 12.5 (2.4-156.2, p = 0.005) for persistent hyposmia, compared to reversion.

CONCLUSIONS

Persistent hyposmia on serial olfactory testing significantly increases the risk of developing clinical PD and abnormal DAT imaging, compared to hyposmia on a single test. Repeat olfactory testing may be an efficient and cost-effective strategy to improve identification of at-risk patients for early diagnosis and disease modification studies.

Who to Enroll in Parkinson Disease Prevention Trials? The Case for Composite Prodromal Cohorts

Significant progress has been made in expanding our understanding of prodromal Parkinson disease (PD), particularly for recognition of early motor and nonmotor signs and symptoms. Although identification of these prodromal features may improve our understanding of the earliest stages of PD, they are individually insufficient for early disease detection and enrollment of participants in prevention trials in most cases because of low sensitivity, specificity, and positive predictive value. Composite cohorts, composed of individuals with multiple co-occurring prodromal features, are an important resource for conducting prodromal PD research and eventual prevention trials because they are more representative of the population at risk for PD, allow investigators to evaluate the efficacy of an intervention across individuals with varying prodromal feature patterns, are able to produce larger sample sizes, and capture individuals at different stages of prodromal PD. A key challenge in identifying individuals with prodromal disease for composite cohorts and prevention trial participation is that we know little about the natural history of prodromal PD. To move toward prevention trials, it is critical that we better understand common prodromal feature patterns and be able to predict the probability of progression and phenoconversion. Ongoing research in cohort studies and administrative databases is beginning to address these questions, but further longitudinal analyses in a large population-based sample are necessary to provide a convincing and definitive strategy for identifying individuals to be enrolled in a prevention trial.

Neurocognitive functioning of patients with early-stage Parkinson's disease

Parkinson's disease (PD) is a neurological disorder commonly associated with motor deficits. However, cognitive impairment is also common in patients with PD. Cognitive concerns in PD may affect multiple domains of neurocognition and vary across different stages of the disease. Extant research has focused mainly on cognitive deficits in middle to late stages of PD, whereas few studies have examined the unique cognitive profiles of patients with early-stage PD. This study addressed this gap in the published literature and examined neurocognitive functioning and functional capacity of patients with de novo PD, focusing on the unique pattern of cognitive deficits specific to the early stage of the disease. Results indicated that the pattern of cognitive deficits in patients with PD (n = 55; mean age = 72.93) was significantly different from healthy controls (n = 59; mean age = 71.88). Specifically, tasks related to executive functioning, attention, and verbal memory demonstrated the most pronounced deficits in patients with early-stage PD. Clinical implications of these findings are discussed.

Cognition in prodromal Parkinson's disease

One characteristic of Parkinson's disease (PD) is a prodromal phase, lasting many years during which both pre-clinical motor and non-motor symptoms occur. Around one-fifth of patients with PD manifest mild cognitive impairment at time of clinical diagnosis. Thus, important challenges are to define the time of onset of cognitive dysfunction in the prodromal phase of PD, and to define its co-occurrence with other specific characteristics. Evidence for cognitive change in prodromal PD comes from various study designs, including both longitudinal and cross-sectional approaches with different target groups. These studies support the concept that changes in global cognitive function and alterations in executive functions occur, and that these changes may be present up to 6 years before clinical PD diagnosis. Notably, this evidence led to including global cognitive impairment as an independent prodromal marker in the recently updated research criteria of the Movement Disorder Society for prodromal PD. Knowledge in this field, however, is still at its beginning, and evidence is sparse about many aspects of this topic. Further longitudinal studies including standardized assessments of global and domain-specific cognitive functions are needed to gain further knowledge about the first appearance, the course, and the interaction of cognitive deficits with other non-motor symptoms in prodromal stage PD. Treatment approaches, including non-pharmacological interventions, in individuals with prodromal PD might help to prevent or delay cognitive dysfunction in early PD.

The epidemiology of cognitive function in Parkinson's disease

Epidemiology is the study of the distribution of disease in human populations, which is important in evaluating burden of illness, identifying modifiable risk factors, and planning for current and projected needs of the health care system. Parkinson's disease (PD) is the second most common serious neurodegenerative illness and is expected to further increase in prevalence. Cognitive changes are increasingly viewed as an integral non-motor feature in PD, emerging even in the prodromal phase of the disease. The prevalence of PD-MCI ranges from 20% to 40% depending on the population studied. The incidence of PD-dementia increases with duration of disease, with estimates growing from 3% to 30% of individuals followed for 5 years or less to over 80% after 20 years. There are several challenges in estimating the frequency of cognitive change, including only recently standardized diagnostic criteria, variation depending on exact neuropsychological evaluations performed, and differences in population sampling. Clinical features associated with cognitive decline include older age, increased disease duration and severity, early gait dysfunction, dysautonomia, hallucinations and other neuropsychiatric features, the presence of REM behavior disorder, and posterior predominant dysfunction on neuropsychological testing. There is increasing evidence that genetic risk factors, in particular GBA and MAPT mutations, contribute to cognitive change. Possible protective factors include higher cognitive reserve and regular exercise. Important sequelae of cognitive decline in PD include higher caregiver burden, decreased functional status, and increased risk of institutionalization and mortality. Many remaining uncertainties regarding the epidemiology of cognitive change in PD require future research, with improved biomarkers and more sensitive and convenient outcome measures.

Parkinson's disease: the nutrition perspective

Parkinson's disease (PD) is the second most common neurodegenerative disease after Alzheimer's disease and affects about 1% of the population over the age of 60 years in industrialised countries. The aim of this review is to examine nutrition in PD across three domains: dietary intake and the development of PD; whole body metabolism in PD and the effects of PD symptoms and treatment on nutritional status. In most cases, PD is believed to be caused by a combination of genetic and environmental factors and although there has been much research in the area, evidence suggests that poor dietary intake is not a risk factor for the development of PD. The evidence about body weight changes in both the prodromal and symptomatic phases of PD is inconclusive and is confounded by many factors. Malnutrition in PD has been documented as has sarcopaenia, although the prevalence of the latter remains uncertain due to a lack of consensus in the definition of sarcopaenia. PD symptoms, including those which are gastrointestinal and non-gastrointestinal, are known to adversely affect nutritional status. Similarly, PD treatments can cause nausea, vomiting and constipation, all of which can adversely affect nutritional status. Given that the prevalence of PD will increase as the population ages, it is important to understand the interplay between PD, comorbidities and nutritional status. Further research may contribute to the development of interventional strategies to improve symptoms, augment care and importantly, enhance the quality of life for patients living with this complex neurodegenerative disease.

Prodromal Cognitive Deficits and the Risk of Subsequent Parkinson’s Disease

Background: There is growing interest in identifying individuals who are in the prodromal phase of Parkinson’s disease (PD), as these individuals are potentially suitable for inclusion in intervention trials to prevent clinically manifest PD. However, it is less clear whether—and to what extent—cognitive deficits are present in prodromal PD. Methods: A systematic query was conducted through PubMed and Embase for prospective observational cohort studies that (a) assessed cognitive performance in individuals free of manifest PD at baseline and (b) subsequently followed up participants for incident PD. We grouped the results by cognitive domain, and for domains that had been reported in at least three separate studies, we performed random-effects, inverse variance meta-analyses based on summary statistics. Results: We identified nine articles suitable for inclusion, with a total of 215 patients with phenoconversion and 13,524 individuals remaining disease-free at follow-up. The studies were highly heterogeneous in study design, study population, and cognitive test batteries. Studies that included only cognitive screening measures such as MMSE or MoCA reported no association between worse cognitive performance and onset of manifest PD (combined odds ratio 1.08; 95% confidence interval 0.66–1.77). By contrast, studies that used extensive cognitive testing batteries found that global cognitive deficits were associated with an increased risk of manifest PD. In domain-specific analyses, there was evidence for an association between worse executive functioning (OR 1.45; 95% CI 1.10–1.92), but not memory (OR 1.20; 95% CI 0.85–1.70) or attention (OR 0.98; 95% CI 0.23–4.26), and clinically manifest PD. Conclusion: Although some caution due to high heterogeneity among published studies is warranted, the available evidence suggests that global and executive cognitive deficits are prodromal features of PD. Collaborative prospective studies with extensive cognitive test batteries are required to shed light on domain-specific deficits, temporal relations, and subgroup differences in prodromal cognitive deficits in PD.

Prevalence of Prodromal Symptoms of Parkinson's Disease in the Late Middle-Aged Population

BACKGROUND

The prodromal phase of Parkinson's disease (PD) can last up to 20 years and is characterized by a variety of non-motor symptoms.

OBJECTIVE

To determine the prevalence of a selection of non-motor symptoms known to be associated with an increased risk of developing PD in a late middle-aged population-based sample and to determine their association with motor function.

METHODS

At a mean age of 60.3 years, 775 subjects were recruited from the Longitudinal Aging Study Amsterdam (LASA). Hyposmia, cognitive impairment, patient-reported constipation, possible REM-sleep behavior disorder, depression, and anxiety were indexed as known PD risk factors. Additionally, 1) the PD screening questionnaire, 2) four physical performance tests, and 3) a functional limitations questionnaire, were used to determine whether the presence of two or more PD risk factors was associated with reduced motor function.

RESULTS

The prevalence of single risk factors ranged between 3 and 13%. Approximately 11% of subjects had two or more PD risk factors. Motor functioning of subjects with two or more PD risk factors was significantly worse than performance of subjects without or with a single risk factor (all p values≤0.001).

CONCLUSION

Approximately 11% of the late middle-aged population has two or more known PD risk factors. Among these subjects self-perceived PD symptoms and reduced physical performance are more prevalent, suggesting that at least some of these subjects may be in the prodromal phase of PD.

A cross-sectional study of Parkinson’s disease and the prodromal phase in community-dwelling older adults in eastern Japan

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This study aimed to clarify the recent prevalence rate of PD and prodromal PD. (78/85).

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Questionnaire-based approach was conducted to investigate prodromal PD. (71/85).

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714 community-dwelling older adults aged 65 or more were enrolled. (66/85).

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Prevalence rate of PD was 279.7 per 100,000 in this study. (58/85).

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Prevalence rate and probability of prodromal PD were 5034.5 and 0.057. (70/85).

Introduction

Parkinson’s disease (PD) is more prevalent in the aging population, and epidemiological evidence must be constantly updated to provide an accurate understanding of PD prevalence. Various nonmotor symptoms of PD precede the onset of motor symptoms and prodromal PD. The detection of such symptoms is crucial yet remains challenging. In this study, we aimed to clarify the current prevalence of PD and prodromal PD.

Methods

We enrolled 714 community-dwelling older adults (330 men and 384 women) aged ≥ 65 years (mean age 76.3 years). We used a self-administered questionnaire based on the International Parkinson and Movement Disorder Society prodromal PD criteria to obtain information on prodromes and calculate PD probability. Patients with a probability of ≥ 0.3 were considered as having prodromal PD. We analyzed the crude prevalence rates of PD and prodromal PD.

Results

The crude prevalence rate of PD in our sample was 279.7 per 100,000 persons. The crude prevalence rate of prodromal PD and PD probability were 5034.5 per 100,000 persons and 0.057 ± 0.121, respectively. Never smoker (61.4%), physical inactivity (47.0%), regular pesticide exposure (30.7%), and urinary dysfunction (26.5%) were frequent positive prodromes. Subjects with higher PD probability possessed more variable prodromal markers than those with lower probability.

Conclusion

We examined current prevalence rates of PD and prodromal PD in community-dwelling older adults aged ≥ 65 years in Japan. Our questionnaire-based approach to examine prodromal PD provided valuable evidence for the prevalence of prodromal PD in the aging population.

Longitudinal Study of SNCA Rep1 Polymorphism on Executive Function in Early Parkinson's Disease

The alpha-synuclein gene promoter (SNCA-Rep1) is associated with Parkinson's disease (PD), but its relationship with performance across individual cognitive domains in early PD is unknown. This study aims to investigate Rep1 polymorphism and longitudinal change in cognition in early PD. In this longitudinal study, Rep1 allele lengths ("long" and "short") were determined in 204 early PD patients. All participants underwent annual neuropsychological assessments and followed up for 3 years. Linear-mixed model was performed to investigate the association of Rep1 status and longitudinal change in individual cognitive domains. At 3 years, significant decline in executive function was observed in long Rep1 allele carriers vs short allele carriers, controlling for potential confounders. This is the first longitudinal study demonstrating that long Rep1 allele carriers are at higher risk for executive dysfunction in early PD.

Mapping Actuarial Criteria for Parkinson’s Disease-Mild Cognitive Impairment onto Data-Driven Cognitive Phenotypes

Prevalence rates for mild cognitive impairment in Parkinson’s disease (PD-MCI) remain variable, obscuring the diagnosis’ predictive utility of greater dementia risk. A primary factor of this variability is inconsistent operationalization of normative cutoffs for cognitive impairment. We aimed to determine which cutoff was optimal for classifying individuals as PD-MCI by comparing classifications against data-driven PD cognitive phenotypes. Participants with idiopathic PD (n = 494; mean age 64.7 ± 9) completed comprehensive neuropsychological testing. Cluster analyses (K-means, Hierarchical) identified cognitive phenotypes using domain-specific composites. PD-MCI criteria were assessed using separate cutoffs (−1, −1.5, −2 SD) on ≥2 tests in a domain. Cutoffs were compared using PD-MCI prevalence rates, MCI subtype frequencies (single/multi-domain, executive function (EF)/non-EF impairment), and validity against the cluster-derived cognitive phenotypes (using chi-square tests/binary logistic regressions). Cluster analyses resulted in similar three-cluster solutions: Cognitively Average (n = 154), Low EF (n = 227), and Prominent EF/Memory Impairment (n = 113). The −1.5 SD cutoff produced the best model of cluster membership (PD-MCI classification accuracy = 87.9%) and resulted in the best alignment between PD-MCI classification and the empirical cognitive profile containing impairments associated with greater dementia risk. Similar to previous Alzheimer’s work, these findings highlight the utility of comparing empirical and actuarial approaches to establish concurrent validity of cognitive impairment in PD.

Characterizing mild cognitive impairment in prodromal Parkinson's disease: A community-based study in China

Objective

The International Parkinson and Movement Disorder Society (MDS) has published research criteria for prodromal Parkinson's disease (pPD), which includes cognitive impairment as a prodromal marker. However, the clinical features of mild cognitive impairment (MCI) in pPD remain unknown. Our study aimed to evaluate the frequency and clinical features of mild cognitive impairment of pPD in the elderly in China.

Methods

The cross‐sectional community‐based study recruited 2688 participants aged ≥50 years. Subjects were diagnosed with pPD according to the MDS criteria. Overall, 39 pPD and 22 healthy controls underwent comprehensive clinical and neuropsychological assessment. MCI was also diagnosed by the MDS criteria. Next, we investigated the relationship between clinical factors and cognition.

Results

Among the 2,663 dementia‐free and Parkinson disease (PD)‐free participants, 55 met the criteria for pPD (2.1%) and 23 pPD met the criteria for MCI. Memory, attention/working memory, and executive function were the most frequent impaired domains, and amnestic MCI multidomain phenotype was the most frequent MCI subtype (69.57%) in pPD. Additionally, correlation analysis revealed that the global cognitive performance was negatively related to UPDRS‐III score (r = −0.456, p = 0.004).

Conclusion

MCI, specifically impairment in memory, attention/working memory, and executive domain, is present at the prodromal stage of PD. In addition, cognitive performance is correlated with motor symptoms in pPD. Our results reflect that cognitive profile, combined with motor symptoms, can help clinicians to identify individuals with pPD early, as those would be the optimal candidates for neuroprotective therapy.

Increased functional connectivity in a population at risk of developing Parkinson's disease

BACKGROUND

While the concept of prodromal Parkinson's disease (PD) is well established, reliable markers for the diagnosis of this disease stage are still lacking. We investigated the functional connectivity of the putamina in a resting-state functional MRI analysis in persons with at least two prodromal factors for PD, which is considered a high risk for PD (HRPD) group, in comparison to PD patients and controls.

METHODS

We included 16 PD patients, 20 healthy controls and 20 HRPD subjects. Resting state echo planar images and anatomical T1-weighted images were acquired with a Siemens Prisma 3 T scanner. The computation of correlation maps of the left and the right putamen to the rest of the brain was done in a voxel-wise approach using the REST toolbox. Finally, group differences in the correlation maps were compared on voxel-level and summarized in cluster z-statistics.

RESULTS

Compared to both PD patients and healthy controls, the HRPD group showed higher functional connectivity of both putamina to brain regions involved in execution of motion and coordination (cerebellum, vermis, pre- and postcentral gyrus, supplementary motor area) as well as the planning of movement (precuneus, cuneus, superior medial frontal lobe).

CONCLUSIONS

Higher functional connectivity of the putamina of HRPD subjects to other brain regions involved in motor execution and planning may indicate a compensatory mechanism. Follow-up evaluation and independent longitudinal studies should test whether our results reflect a dynamic process associated with a prodromal PD state.

Predicting Parkinson's Disease and Its Pathology via Simple Clinical Variables

Background:

Parkinson’s disease (PD) is a chronic, disabling neurodegenerative disorder.

Objective:

To predict a future diagnosis of PD using questionnaires and simple non-invasive clinical tests.

Methods:

Participants in the prospective Kuakini Honolulu-Asia Aging Study (HAAS) were evaluated biannually between 1995–2017 by PD experts using standard diagnostic criteria. Autopsies were sought on all deaths. We input simple clinical and risk factor variables into an ensemble-tree based machine learning algorithm and derived models to predict the probability of developing PD. We also investigated relationships of predictive models and neuropathologic features such as nigral neuron density.

Results:

The study sample included 292 subjects, 25 of whom developed PD within 3 years and 41 by 5 years. 116 (46%) of 251 subjects not diagnosed with PD underwent autopsy. Light Gradient Boosting Machine modeling of 12 predictors correctly classified a high proportion of individuals who developed PD within 3 years (area under the curve (AUC) 0.82, 95%CI 0.76–0.89) or 5 years (AUC 0.77, 95%CI 0.71–0.84). A large proportion of controls who were misclassified as PD had Lewy pathology at autopsy, including 79%of those who died within 3 years. PD probability estimates correlated inversely with nigral neuron density and were strongest in autopsies conducted within 3 years of index date (r = –0.57, p < 0.01).

Conclusion:

Machine learning can identify persons likely to develop PD during the prodromal period using questionnaires and simple non-invasive tests. Correlation with neuropathology suggests that true model accuracy may be considerably higher than estimates based solely on clinical diagnosis.

Heterogeneity of prodromal Parkinson symptoms in siblings of Parkinson disease patients

A prodromal phase of Parkinson's disease (PD) may precede motor manifestations by decades. PD patients' siblings are at higher risk for PD, but the prevalence and distribution of prodromal symptoms are unknown. The study objectives were (1) to assess motor and non-motor features estimating prodromal PD probability in PD siblings recruited within the European PROPAG-AGEING project; (2) to compare motor and non-motor symptoms to the well-established DeNoPa cohort. 340 PD siblings from three sites (Bologna, Seville, Kassel/Goettingen) underwent clinical and neurological evaluations of PD markers. The German part of the cohort was compared with German de novo PD patients (dnPDs) and healthy controls (CTRs) from DeNoPa. Fifteen (4.4%) siblings presented with subtle signs of motor impairment, with MDS-UPDRS-III scores not clinically different from CTRs. Symptoms of orthostatic hypotension were present in 47 siblings (13.8%), no different to CTRs (p = 0.072). No differences were found for olfaction and overall cognition; German-siblings performed worse than CTRs in visuospatial-executive and language tasks. 3/147 siblings had video-polysomnography-confirmed REM sleep behavior disorder (RBD), none was positive on the RBD Screening Questionnaire. 173/300 siblings had <1% probability of having prodromal PD; 100 between 1 and 10%, 26 siblings between 10 and 80%, one fulfilled the criteria for prodromal PD. According to the current analysis, we cannot confirm the increased risk of PD siblings for prodromal PD. Siblings showed a heterogeneous distribution of prodromal PD markers and probability. Additional parameters, including strong disease markers, should be investigated to verify if these results depend on validity and sensitivity of prodromal PD criteria, or if siblings' risk is not elevated.

Non-Motor Features of Parkinson's Disease in Women

BACKGROUND

Non-motor symptoms are common in Parkinson's disease (PD) and some, including hyposmia, constipation, and REM sleep behavior disorder, often precede the clinical diagnosis.

OBJECTIVE

To assess the relation between combinations of non-motor features and presence of PD among women.

METHODS

A nested case-control study was conducted among women in the Nurses' Health Study. Women were eligible if they responded to screening questions for constipation and probable REM sleep behavior disorder (pRBD) on a 2012 questionnaire and were under age 85 on January 1, 2012. 87 women with confirmed PD and 14,170 women without PD agreed to participate and completed in 2015 the Brief Smell Identification Test to assess hyposmia, as well as a questionnaire to assess parkinsonism and other non-motor PD features, including depressive symptoms, excessive daytime sleepiness, impaired color vision, and body pain.

RESULTS

In age-adjusted logistic models, each non-motor feature was significantly associated with PD, and the odds of PD increased exponentially with the number of features. Women with constipation, pRBD, and hyposmia had an age-adjusted OR for PD of 211 (95% CI 84.2-529) compared to women with none of these features. The odds of having PD rose further with the presence of additional non-motor signs. Comparing women with at least 6 of the 7 features assessed in this study to women with one or none, the age-adjusted OR for PD was 356 (95% CI 113-1126).

CONCLUSION

Results suggest that these non-motor features could be useful in discriminating PD patients from controls in women, and since they often appear during the prodromal period of PD, their combinations may prove useful for identifying populations at high risk of developing PD.

Probing the Pre-diagnostic Phase of Parkinson's Disease in Population-Based Studies

Parkinson's disease covers a wide spectrum of symptoms, ranging from early non-motor symptoms to the characteristic bradykinesia, tremor and rigidity. Although differences in the symptomatology of Parkinson's disease are increasingly recognized, there is still a lack of insight into the heterogeneity of the pre-diagnostic phase of Parkinson's disease. In this perspective, we highlight three aspects regarding the role of population-based studies in providing new insights into the heterogeneity of pre-diagnostic Parkinson's disease. First we describe several specific advantages of population-based cohort studies, including the design which overcomes some common biases, the broad data collection and the high external validity. Second, we draw a parallel with the field of Alzheimer's disease to provide future directions to uncover the heterogeneity of pre-diagnostic Parkinson's disease. Finally, we anticipate on the emergence of prevention and disease-modification trials and the potential role of population-based studies herein. In the coming years, bridging gaps between study designs will be essential to make vital advances in elucidating the heterogeneity of pre-diagnostic Parkinson's disease.

Cognitive function in men with non-motor features of Parkinson's disease

Objective

Subtle cognitive deficits can occur during the prodromal phase of Parkinson’s disease (PD), commonly in conjunction with hyposmia. However, little is known about the association between cognitive function and other features suggestive of prodromal PD. We evaluated the association of non-motor prodromal PD features, including hyposmia, constipation and probable REM sleep behaviour disorder (pRBD), with objective measures of cognitive function and self-reported cognitive decline.

Methods

The study population comprised 804 men who responded to a telephone cognitive interview in 2016–2017. Participants included 680 individuals with hyposmia, of whom 45 had confirmed PD, and 124 men without hyposmia. Among these men, we evaluated objective cognitive function and subjective cognitive decline to determine whether the presence of non-motor features of prodromal PD was associated with cognitive functioning. Analyses were adjusted for age, physical activity, body mass index, smoking status and coffee consumption.

Results

Individuals with non-motor features of prodromal PD had worse objective and subjective cognitive performance relative to men without non-motor features. Cognitive impairment was particularly prevalent among individuals with concurrent hyposmia, pRBD and constipation (multivariate-adjusted OR=3.80; 95% CI 1.52 to 9.47 for objective poor cognitive function; OR=8.71; 95% CI 3.18 to 23.83 for subjective cognitive decline). As expected, both objective (OR=7.91) and subjective (OR=17.42) cognitive impairment were also more common among men with confirmed PD.

Conclusions

Our study suggests that cognition is commonly affected in individuals with non-motor prodromal PD features, particularly when multiple of these features are present.

Challenges in the diagnosis of Parkinson's disease

Parkinson's disease is the second most common neurodegenerative disease and its prevalence has been projected to double over the next 30 years. An accurate diagnosis of Parkinson's disease remains challenging and the characterisation of the earliest stages of the disease is ongoing. Recent developments over the past 5 years include the validation of clinical diagnostic criteria, the introduction and testing of research criteria for prodromal Parkinson's disease, and the identification of genetic subtypes and a growing number of genetic variants associated with risk of Parkinson's disease. Substantial progress has been made in the development of diagnostic biomarkers, and genetic and imaging tests are already part of routine protocols in clinical practice, while novel tissue and fluid markers are under investigation. Parkinson's disease is evolving from a clinical to a biomarker-supported diagnostic entity, for which earlier identification is possible, different subtypes with diverse prognosis are recognised, and novel disease-modifying treatments are in development.

Changes in Gastrointestinal Microbiome Composition in PD: A Pivotal Role of Covariates

Altered gut microbiota may trigger or accelerate alpha-synuclein aggregation in the enteric nervous system in Parkinson's disease (PD). While several previous studies observed gut microbiota alterations in PD, findings like diversity indices, and altered bacterial taxa itself show a considerable heterogeneity across studies. We recruited 179 participants, of whom 101 fulfilled stringent inclusion criteria. Subsequently, the composition of the gut microbiota in 71 PD patients and 30 healthy controls was analyzed, sequencing V3–V4 regions of the bacterial 16S ribosomal RNA gene in fecal samples. Our goal was (1) to evaluate whether gut microbiota are altered in a southern German PD cohort, (2) to delineate the influence of disease duration, stage, and motor impairment, and (3) to investigate the influence of PD associated covariates like constipation and coffee consumption. Aiming to control for a large variety of covariates, strict inclusion criteria were applied. Finally, propensity score matching was performed to correct for, and to delineate the effect of remaining covariates (non-motor symptom (NMS) burden, constipation, and coffee consumption) on microbiota composition. Prior to matching altered abundances of distinct bacterial classes, orders, families, and genera were observed. Both, disease duration, and stage influenced microbiome composition. Interestingly, levodopa equivalent dose influenced the correlation of taxa with disease duration, while motor impairment did not. Applying different statistical tests, and after propensity score matching to control for NMS burden, constipation and coffee consumption, Faecalibacterium and Ruminococcus were most consistently reduced in PD compared to controls. Taken together, similar to previous studies, alterations of several taxa were observed in PD. Yet, further controlling for PD associated covariates such as constipation and coffee consumption revealed a pivotal role of these covariates. Our data highlight the impact of these PD associated covariates on microbiota composition in PD. This suggests that altered microbiota may mediate the protective effect of i.e., coffee consumption and the negative effect of constipation in PD.

Gradient boosting for Parkinson's disease diagnosis from voice recordings

Background

Parkinson’s Disease (PD) is a clinically diagnosed neurodegenerative disorder that affects both motor and non-motor neural circuits. Speech deterioration (hypokinetic dysarthria) is a common symptom, which often presents early in the disease course. Machine learning can help movement disorders specialists improve their diagnostic accuracy using non-invasive and inexpensive voice recordings.

Method

We used “Parkinson Dataset with Replicated Acoustic Features Data Set” from the UCI-Machine Learning repository. The dataset included 44 speech-test based acoustic features from patients with PD and controls. We analyzed the data using various machine learning algorithms including Light and Extreme Gradient Boosting, Random Forest, Support Vector Machines, K-nearest neighborhood, Least Absolute Shrinkage and Selection Operator Regression, as well as logistic regression. We also implemented a variable importance analysis to identify important variables classifying patients with PD.

Results

The cohort included a total of 80 subjects: 40 patients with PD (55% men) and 40 controls (67.5% men). Disease duration was 5 years or less for all subjects, with a mean Unified Parkinson’s Disease Rating Scale (UPDRS) score of 19.6 (SD 8.1), and none were taking PD medication. The mean age for PD subjects and controls was 69.6 (SD 7.8) and 66.4 (SD 8.4), respectively. Our best-performing model used Light Gradient Boosting to provide an AUC of 0.951 with 95% confidence interval 0.946–0.955 in 4-fold cross validation using only seven acoustic features.

Conclusions

Machine learning can accurately detect Parkinson’s disease using an inexpensive and non-invasive voice recording. Light Gradient Boosting outperformed other machine learning algorithms. Such approaches could be used to inexpensively screen large patient populations for Parkinson’s disease.

Alpha Synuclein Connects the Gut-Brain Axis in Parkinson's Disease Patients - A View on Clinical Aspects, Cellular Pathology and Analytical Methodology

Parkinson’s disease (PD) is marked by different kinds of pathological features, one hallmark is the aggregation of α-synuclein (aSyn). The development of aSyn pathology in the substantia nigra is associated to the manifestation of motor deficits at the time of diagnosis. However, most of the patients suffer additionally from non-motor symptoms, which may occur already in the prodromal phase of the disease years before PD is diagnosed. Many of these symptoms manifest in the gastrointestinal system (GIT) and some data suggest a potential link to the occurrence of pathological aSyn forms within the GIT. These clinical and pathological findings lead to the idea of a gut-brain route of aSyn pathology in PD. The identification of pathological aSyn in the intestinal system, e.g., by GIT biopsies, is therefore of highest interest for early diagnosis and early intervention in the phase of formation and propagation of aSyn. However, reliable methods to discriminate between physiological and pathological forms of enteral aSyn on the cellular and biochemical level are still missing. Moreover, a better understanding of the physiological function of aSyn within the GIT as well as its structure and pathological aggregation pathways are crucial to understand its role within the enteric nervous system and its spreading from the gut to the brain. In this review, we summarize clinical manifestations of PD in the GIT, and discuss biochemical findings from enteral biopsies. The relevance of pathological aSyn forms, their connection to the gut-brain axis and new developments to identify pathologic forms of aSyn by structural features are critically reviewed.

Cognitive and functional changes in prediagnostic phase of Parkinson disease: A population-based study

INTRODUCTION

Prodromal non-motor symptoms precede, often by decades, motor signs and diagnosis of Parkinson's disease. It is however still uncertain if cognitive changes belong to the spectrum of non-motor prodromal Parkinson's disease. Thanks to the very long-term follow-up of the PAQUID population-based cohort, we assessed trajectories of cognitive complaints and functioning over a 13-year period before the diagnosis of late onset Parkinson's disease.

METHODS

This study relies on a matched nested case-control sample selected from the cohort. Of the 3777 initial subjects of the cohort, 43 developed incident Parkinson's disease over the follow-up. The mean age at diagnosis was 78.0 (standard deviation = 5.8) years and 46.5% were men. These cases were matched to 86 elderly control subjects. Scores of different cognitive domains, daily function, and depressive symptoms were described throughout the follow-up using mixed-effects models.

RESULTS

No significant global cognitive decline preceded the diagnosis of late onset Parkinson's disease. However, psychomotor speed appeared significantly slower 2 years before the diagnosis and depressive symptoms 12 years before. Global score of instrumental activities of daily living became altered 2-3 years preceding the diagnosis of late onset Parkinson's disease, including the use of public transportation that was altered ten years before the diagnosis.

CONCLUSION

In late onset Parkinson's disease, while global cognitive functions seem preserved, psychomotor speed starts to decline 2 years before the diagnosis and activities of daily living are also impacted. Depressive symptoms appear very early in the prediagnosic phase.

Cognitive Performance in Parkinson's Disease in the Brain Health Registry

The study of cognition in Parkinson's disease (PD) traditionally requires exhaustive recruitment strategies. The current study examines data collected by the Brain Health Registry (BHR) to determine whether ongoing efforts to improve the recruitment base for therapeutic trials in Alzheimer's disease may be similarly effective for PD research, and whether online cognitive measurements can discriminate between participants who do and do not report a PD diagnosis. Participants enrolled in the BHR (age ≥50) with self-reported PD data and online cognitive testing available were included (n = 11,813). Associations between baseline cognitive variables and diagnostic group were analyzed using logistic regression. Linear mixed effects models were used to analyze longitudinal data. A total of 634 participants reported PD diagnosis at baseline with no self-reported cognitive impairment and completed cognitive testing. Measures of visual learning and memory, processing speed, attention, and working memory discriminated between self-reported PD and non-PD participants after correcting for multiple comparisons (p values < 0.006). Scores on all cognitive tests improved over time in PD and controls with the exception of processing speed, which remained stable in participants with PD while improving in those without. We demonstrate that a novel online approach to recruitment and longitudinal follow-up of study participants is effective for those with self-reported PD, and that significant differences exist between those with and without a reported diagnosis of PD on computerized cognitive measures. These results have important implications for recruitment of participants with PD into targeted therapeutic trials or large-scale genetic and cognitive studies.

Electrocardiographic changes predate Parkinson's disease onset

Autonomic nervous system involvement precedes the motor features of Parkinson's disease (PD). Our goal was to develop a proof-of-concept model for identifying subjects at high risk of developing PD by analysis of cardiac electrical activity. We used standard 10-s electrocardiogram (ECG) recordings of 60 subjects from the Honolulu Asia Aging Study including 10 with prevalent PD, 25 with prodromal PD, and 25 controls who never developed PD. Various methods were implemented to extract features from ECGs including simple heart rate variability (HRV) metrics, commonly used signal processing methods, and a Probabilistic Symbolic Pattern Recognition (PSPR) method. Extracted features were analyzed via stepwise logistic regression to distinguish between prodromal cases and controls. Stepwise logistic regression selected four features from PSPR as predictors of PD. The final regression model built on the entire dataset provided an area under receiver operating characteristics curve (AUC) with 95% confidence interval of 0.90 [0.80, 0.99]. The five-fold cross-validation process produced an average AUC of 0.835 [0.831, 0.839]. We conclude that cardiac electrical activity provides important information about the likelihood of future PD not captured by classical HRV metrics. Machine learning applied to ECGs may help identify subjects at high risk of having prodromal PD.

New Sensor and Wearable Technologies to Aid in the Diagnosis and Treatment Monitoring of Parkinson's Disease

Parkinson's disease (PD) is a degenerative disorder of the brain characterized by the impairment of the nigrostriatal system. This impairment leads to specific motor manifestations (i.e., bradykinesia, tremor, and rigidity) that are assessed through clinical examination, scales, and patient-reported outcomes. New sensor-based and wearable technologies are progressively revolutionizing PD care by objectively measuring these manifestations and improving PD diagnosis and treatment monitoring. However, their use is still limited in clinical practice, perhaps because of the absence of external validation and standards for their continuous use at home. In the near future, these systems will progressively complement traditional tools and revolutionize the way we diagnose and monitor patients with PD.

Validation of a new olfactory test for Chinese Parkinson's disease patients

INTRODUCTION

Hyposmia is a common non-motor symptom in Parkinson's disease (PD) and has been used to assist PD diagnosis and early screening of prodromal patients. Although the Brief Smell Identification Test (B-SIT) is the most commonly used olfactory test, its utility was limited by the culture difference in recognition of the smells included in the test. We have developed a new modified B-SIT test for Chinese (B-SITC), and validated and compare it with B-SIT in Chinese PD patients.

METHODS

From 2015 to 2018, PD patients were recruited from the Movement Disorder Clinic of Xuanwu Hospital and healthy controls were recruited from the Beijing Longitudinal Study on Aging Cohort II. The two olfactory tests were used in healthy volunteers and PD patients.

RESULTS

A total of 428 subjects participated in the study: 211 healthy controls and 217 PD patients. The average B-SIT and B-SITC scores were significantly different between control and PD groups (B-SIT, 9.18 ± 1.94 vs. 6.90 ± 2.44, P = 0.0001; B-SITC, 8.60 ± 1.93 vs. 5.91 ± 2.21, P = 0.0001). The B-SITC had good sensitivity (73.1%), specificity (76.8%), positive predictive value (76.8%), and negative predictive value (73.1%) for the diagnosis of Chinese PD, and the area under the curve (AUC) value was greater for the B-SITC than for the B-SIT (0.838 vs. 0.761).

CONCLUSIONS

The B-SITC is useful for the clinical assessment of olfactory function in Chinese PD patients.

Prodromal PD: A new nosological entity

Recent years have brought a rapid growth in knowledge of the prodromal phase of Parkinson's disease (PD). It is now clear that the clinical phase of PD is preceded by a phase of progressing neurodegeneration lasting many years. This involves not only central nervous system structures outside the substantia nigra and neurotransmitter systems other than the dopaminergic system, but also the peripheral nervous systems. Different ways of alpha-synuclein spreading are presumed, corresponding to typical prodromal non-motor symptoms like constipation, REM sleep behavior disorder (RBD) and hyposmia. Moreover, many risk and prodromal markers have been identified and combined in the prodromal research criteria, which can be used to calculate an individual's probability of being in the prodromal phase of PD. Apart from specific genetic risk markers, including most importantly GBA- and LRRK2 mutations, RBD is currently the most important prodromal marker, predicting PD with a very high likelihood. This makes individuals with RBD a promising cohort for future clinical trials to detect and treat PD in its prodromal phase. New markers, especially those derived from tissue biopsies, quantitative motor assessment and imaging, appear very promising; these are paving the way for a better understanding of the prodromal phase and its potential clinicopathological subtypes, and a more precise probability calculation.

Parkinson Disease Epidemiology, Pathology, Genetics, and Pathophysiology

Parkinson disease is a complex, age-related, neurodegenerative disease associated with dopamine deficiency and both motor and nonmotor deficits. Many environmental and genetic factors influence Parkinson disease risk, with different factors predominating in different patients. These factors converge on specific pathways, including mitochondrial dysfunction, oxidative stress, protein aggregation, impaired autophagy, and neuroinflammation. Ultimately, treatment of Parkinson disease may focus on targeted therapies for pathophysiologically defined subtypes of Parkinson disease patients.

Open questions on the nature of Parkinson's disease: from triggers to spreading pathology

Parkinson's disease (PD) is a movement disorder identified more than 200 years ago; today it is defined by specific motor symptoms that together receive the name of parkinsonism. PD diagnosis is reached with the full parkinsonian syndrome, but in recent years, a series of non-motor symptoms have arisen as intrinsic components of PD. These non-motor symptoms are variable, creating a widely heterogenous disease presentation. Some non-motor symptoms appear in late disease stages and are explained as the natural progression of PD pathology into other brain centres, including the frontal cortex. Other symptoms can appear a decade or earlier preceding PD diagnosis, particularly hyposmia (loss of smell) and constipation. These early symptoms and the accompanying protein pathology have stimulated a lively conversation about the origin and nature of PD and other related conditions: some authors propose that PD starts in the olfactory mucosa and the gut due to direct exposure to toxins or pathogens. This pathology then travels by anatomically interconnected networks to the midbrain to cause motor symptoms and the cortex to cause late complications. Other models propose that PD develops in multiple independent foci that do not require pathology spread. We will review these hypotheses in the context of recent developments regarding the spread of amyloids and propose a mixed model where a multifocal origin explains the variable presentation of PD, while cell-to-cell spread explains stereotypical disease progression.

Determinants of diagnostic latency in Chinese people with Parkinson's disease

Background

Clinical diagnosis of Parkinson’s disease (PD) has always lagged behind clinical symptoms. The diagnostic latency might be influenced by many factors. The diagnostic latency of Chinese people with PD has been unknown. Here we designed this cross-sectional study with the purpose to identify the diagnostic latency and its determinants in Chinese people with PD.

Methods

One hundred and thirty-one newly diagnosed people with PD were recruited into this study. Demographic and clinical characteristics as well as a detailed clinical history were collected. Motor and non-motor symptoms (NMSs) severity were assessed with appropriate assessment scales. Medical professional types in the first medical consultations were also recorded. According to the initially presenting motor phenotypes, patients would be divided into the groups of rest tremor, limb rigidity, movement slowness and walking problems. The investigated variables would be compared among the four groups.

Results

The PD diagnostic latency in China was around 15 months. It closely correlated to the severity of motor symptoms, anxiety and depression as well as the number of NMSs. The diagnostic latency significantly varied among the groups of different motor phenotypes of onset. Finally, initially presenting with limb rigidity, having more NMSs, motor symptoms at a more serious degree and the initial medical consultations with physicians or specialists of non-neurology were considered as determinants of a longer diagnostic latency of PD.

Conclusions

Patients presenting with minor motor symptoms and disturbing NMSs as well as physicians’ unfamiliarity with PD symptomology were determinants of the diagnostic delay of PD. Health education in community and improvement of the referral system might be proper strategies to shorten the diagnostic latency of PD.

Regional neuropathology distribution and verbal fluency impairments in Parkinson's disease

BACKGROUND

Verbal fluency deficits are common in patients with Parkinson's disease. The association of these impairments with regional neuropathological changes is unexplored.

OBJECTIVES

Determine if patients with verbal fluency impairments have greater neuropathological burden in frontal, temporal, and limbic regions and if Lewy bodies or neurofibrillary tangles were associated with verbal fluency impairments.

METHODS

Data was derived from the Arizona Study of Aging and Neurodegenerative Disorders. 47 individuals who completed phonemic and semantic verbal fluency tasks and met clinicopathological criteria for Parkinson's disease (with and without comorbid Alzheimer's disease) were included. Impairment on fluency tasks was defined by normative data, and the density of neuropathology in temporal, limbic, and frontal regions was compared between groups.

RESULTS

Individuals with semantic fluency impairments had greater total pathology (Lewy bodies + neurofibrillary tangles) in limbic structures (W = 320.0, p = .033, r_pb = .33), while those who had phonemic fluency impairments had increased total neuropathology in frontal (W = 364.5, p = .011, r_pb = .37), temporal (W = 356.5, p = .022, r_pb = .34), and limbic regions (W = 357.0, p = .024, r_pb = .34). Greater Lewy body density was found in those with verbal fluency impairments, though trends for greater neurofibrillary tangle density were noted as well.

CONCLUSIONS

Impaired phonemic fluency was associated with higher Lewy body and tangle burden in frontal, temporal, and limbic regions, while impaired semantic fluency was associated with greater limbic pathology. Though neurofibrillary tangles trended higher in several regions in those with impaired verbal fluency, higher Lewy body density in general was associated with verbal fluency deficits. Implications for research and clinical practice are discussed.

Higher probability of prodromal Parkinson disease is related to lower cognitive performance

OBJECTIVE

Given the limited information on cognitive function before Parkinson disease (PD) clinical onset in the general population, we sought to assess prodromal PD (pPD) probability and relate it to detailed cognitive performance in a community cohort.

METHODS

In a population-based cohort of 1,629 dementia-free and PD-free participants ≥65 years of age in Greece, we assessed probability of pPD according to the International Parkinson and Movement Disorder Society's criteria. Clinical cognitive diagnoses (cognitively unimpaired, mild cognitive impairment [MCI], dementia) considering neuropsychological testing and functional status were assigned in consensus conferences. Cognitive performance in 5 cognitive domains was assessed by a detailed neuropsychological battery and summarized in the form of z scores. We investigated associations between pPD probability (and its individual constituents) and cognitive outcomes.

RESULTS

The median probability of pPD was 1.81% (0.2%-96.7%). Participants with MCI had higher probability of pPD compared to those with normal cognition (p < 0.001). Higher probability of pPD was related to lower performance in all cognitive domains (memory, language, executive, attention, and visuospatial function) (p < 0.001). Lower cognitive performance was further associated with certain nonmotor markers of pPD, such as daytime somnolence, depression, urinary dysfunction, constipation, and subthreshold parkinsonism (p < 0.001).

CONCLUSIONS

Higher probability of pPD was associated with lower cognitive performance in all domains and higher probability of MCI. This may reflect a widespread pathologic process although future studies are warranted to infer causality. These results suggest to clinicians that they should assess cognition early, and to researchers that they should further look into the possible mechanisms that may underlie this observation.

Parkinsonism Risk Factors in Salt Lake City, Utah: A Community-Based Study

BACKGROUND

The prevalence of dream enactment behavior and other risk factors for a parkinsonian disorder is not well documented.

METHODS

A survey on prevalence of parkinsonism risk factors was designed using two validated instruments (REM behavior disorder single item question, bowel movement frequency for constipation) and three exploratory instruments (for hallucinations, cognitive and olfactory complaints.) It was sent by mail and email to patients aged 50 and over at two University of Utah community clinics in Salt Lake City. A total of 7888 unique patients were sent the survey, and 1607 responses were recorded (response rate 20%). Those whose age was missing (n = 117) or less than 50 years (n = 10) were excluded from the analysis.

RESULTS

Of the 1406 without personal diagnosis of neurodegenerative disease 62.7% were female, and median age was 63. Family history (FH) of Parkinson's disease was endorsed by 9%, constipation (defined as a bowel movement less than once per day) by 19%, mild cognitive complaints (MCI) 15.8%, dream enactment 13.7%, subjective hyposmia or anosmia 18.2%, and at least one potential psychotic symptom in 37.6%. Multivariable logistic regression showed male gender, mild cognitive complaints, hearing voices, and at least one potentially psychotic symptom to be significantly associated with dream enactment.

CONCLUSIONS

This survey shows that dream enactment, a strong predictor of risk for synucleinopathy, is relatively common in the older population; because such individuals rarely come to medical attention of a sleep clinic, such survey research may be useful to identify and recruit at-risk individuals for trials aimed at preventing neurodegenerative disease.

Longitudinal Connectomes as a Candidate Progression Marker for Prodromal Parkinson's Disease

Parkinson's disease is the second most prevalent neurodegenerative disorder in the Western world. It is estimated that the neuronal loss related to Parkinson's disease precedes the clinical diagnosis by more than 10 years (prodromal phase) which leads to a subtle decline that translates into non-specific clinical signs and symptoms. By leveraging diffusion magnetic resonance imaging brain (MRI) data evaluated longitudinally, at least at two different time points, we have the opportunity of detecting and measuring brain changes early on in the neurodegenerative process, thereby allowing early detection and monitoring that can enable development and testing of disease modifying therapies. In this study, we were able to define a longitudinal degenerative Parkinson's disease progression pattern using diffusion magnetic resonance imaging connectivity information. Such pattern was discovered using a de novo early Parkinson's disease cohort (n = 21), and a cohort of Controls (n = 30). Afterward, it was tested in a cohort at high risk of being in the Parkinson's disease prodromal phase (n = 16). This progression pattern was numerically quantified with a longitudinal brain connectome progression score. This score is generated by an interpretable machine learning (ML) algorithm trained, with cross-validation, on the longitudinal connectivity information of Parkinson's disease and Control groups computed on a nigrostriatal pathway-specific parcellation atlas. Experiments indicated that the longitudinal brain connectome progression score was able to discriminate between the progression of Parkinson's disease and Control groups with an area under the receiver operating curve of 0.89 [confidence interval (CI): 0.81-0.96] and discriminate the progression of the High Risk Prodromal and Control groups with an area under the curve of 0.76 [CI: 0.66-0.92]. In these same subjects, common motor and cognitive clinical scores used in Parkinson's disease research showed little or no discriminative ability when evaluated longitudinally. Results suggest that it is possible to quantify neurodegenerative patterns of progression in the prodromal phase with longitudinal diffusion magnetic resonance imaging connectivity data and use these image-based patterns as progression markers for neurodegeneration.

Recent Advances in Biomarkers for Parkinson's Disease

Parkinson's disease (PD) is one of the common progressive neurodegenerative disorders with several motor and non-motor symptoms. Most of the motor symptoms may appear at a late stage where most of the dopaminergic neurons have been already damaged. In order to provide better clinical intervention and treatment at the onset of disease, it is imperative to find accurate biomarkers for early diagnosis, including prodromal diagnosis and preclinical diagnosis. At the same time, these reliable biomarkers can also be utilized to monitor the progress of the disease. In this review article, we will discuss recent advances in the development of PD biomarkers from different aspects, including clinical, biochemical, neuroimaging and genetic aspects. Although various biomarkers for PD have been developed so far, their specificity and sensitivity are not ideal when applied individually. So, the combination of multimodal biomarkers will greatly improve the diagnostic accuracy and facilitate the implementation of personalized medicine.

Noninvasive delivery of an α-synuclein gene silencing vector with magnetic resonance-guided focused ultrasound

BACKGROUND

The characteristic progression of Lewy pathology in Parkinson's disease likely involves intercellular exchange and the accumulation of misfolded α-synuclein amplified by a prion-like self-templating mechanism. Silencing of the α-synuclein gene could provide long-lasting disease-modifying benefits by reducing the requisite substrate for the spreading aggregation.

OBJECTIVES

As a result of the poor penetration of viral vectors across the blood-brain barrier, gene therapy for central nervous system disorders requires direct injections into the affected brain regions, and invasiveness is further increased by the need for bilateral delivery to multiple brain regions. Here we test a noninvasive approach by combining low-intensity magnetic resonance-guided focused ultrasound and intravenous microbubbles that can transiently increase the access of brain impermeant therapeutic macromolecules to targeted brain regions.

METHODS

Transgenic mice expressing human α-synuclein were subjected to magnetic resonance-guided focused ultrasound targeted to 4 brain regions (hippocampus, substantia nigra, olfactory bulb, and dorsal motor nucleus) in tandem with intravenous microbubbles and an adeno-associated virus serotype 9 vector bearing a short hairpin RNA sequence targeting the α-synuclein gene.

RESULTS

One month following treatment, α-synuclein immunoreactivity was decreased in targeted brain regions, whereas other neuronal markers such as synaptophysin or tyrosine hydroxylase were unchanged, and cell death and glial activation remained at basal levels.

CONCLUSIONS

These results demonstrate that magnetic resonance-guided focused ultrasound can effectively, noninvasively, and simultaneously deliver viral vectors targeting α-synuclein to multiple brain areas. Importantly, this approach may be useful to alter the progression of Lewy pathology along selected neuronal pathways, particularly as prodromal PD markers improve early diagnoses. © 2018 International Parkinson and Movement Disorder Society.

The enteric nervous system in PD: gateway, bystander victim, or source of solutions

Apart from the characteristic and progressive motor- and movement-related problems, Parkinson's disease (PD) patients also suffer from several non-motor symptoms, including gastrointestinal dysfunction. The fact that the enteric nervous system (ENS) controls motility and that one of the typical PD hallmarks, α-synuclein-positive deposits, has also been found in the intestinal wall have rendered the ENS and the gut a popular subject of study in the context of PD. The possibility that these deposits could serve as an early biomarker is obviously of tremendous medical benefit but also the idea that the gut may possibly be a gateway via which the disease is initiated and progressively makes its way via the peripheral nerves to the central nervous system has increased the interest in the ENS-PD link. Furthermore, the fact that gastrointestinal symptoms are present in PD suggests that the ENS might be affected as well. However, despite a large body of literature on the topic, the actual role or the magnitude of involvement of the ENS in PD remains elusive. The multitudes of experimental approaches and animal models have complicated the interpretation of results and the outcome of different studies does not necessarily align well. In this review, we chose to highlight some elements of interest and some items of confusion, particularly those where research should be focusing. We also list a number of open questions in the field that could serve as a guideline for future, preferably concerted research.

Initial cognitive changes in Parkinson's disease

The focus on cognitive impairment in neurodegenerative diseases, including PD, is shifting from the dementia stage to earlier stages of impairment, including mild cognitive impairment. This shift is driven primarily by the desire to improve long-term outcomes by delivering therapeutic interventions earlier in the clinical course, even presymptomatically in those at highest risk, and at the initial stage in the pathophysiological cascade that underpins common dementia syndromes. This article focuses on key findings and challenges in studying earliest stages of cognitive decline in PD, including a detailed examination of neuropsychological testing, cognitive performance in early and prodromal PD, epidemiological research for PD mild cognitive impairment to date, and expert recommendations for assessment. © 2018 International Parkinson and Movement Disorder Society.

Detecting Motor Impairment in Early Parkinson's Disease via Natural Typing Interaction With Keyboards: Validation of the neuroQWERTY Approach in an Uncontrolled At-Home Setting

Background

Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease and one of the most common forms of movement disorder. Although there is no known cure for PD, existing therapies can provide effective symptomatic relief. However, optimal titration is crucial to avoid adverse effects. Today, decision making for PD management is challenging because it relies on subjective clinical evaluations that require a visit to the clinic. This challenge has motivated recent research initiatives to develop tools that can be used by nonspecialists to assess psychomotor impairment. Among these emerging solutions, we recently reported the neuroQWERTY index, a new digital marker able to detect motor impairment in an early PD cohort through the analysis of the key press and release timing data collected during a controlled in-clinic typing task.

Objective

The aim of this study was to extend the in-clinic implementation to an at-home implementation by validating the applicability of the neuroQWERTY approach in an uncontrolled at-home setting, using the typing data from subjects’ natural interaction with their laptop to enable remote and unobtrusive assessment of PD signs.

Methods

We implemented the data-collection platform and software to enable access and storage of the typing data generated by users while using their computer at home. We recruited a total of 60 participants; of these participants 52 (25 people with Parkinson’s and 27 healthy controls) provided enough data to complete the analysis. Finally, to evaluate whether our in-clinic-built algorithm could be used in an uncontrolled at-home setting, we compared its performance on the data collected during the controlled typing task in the clinic and the results of our method using the data passively collected at home.

Results

Despite the randomness and sparsity introduced by the uncontrolled setting, our algorithm performed nearly as well in the at-home data (area under the receiver operating characteristic curve [AUC] of 0.76 and sensitivity/specificity of 0.73/0.69) as it did when used to evaluate the in-clinic data (AUC 0.83 and sensitivity/specificity of 0.77/0.72). Moreover, the keystroke metrics presented a strong correlation between the 2 typing settings, which suggests a minimal influence of the in-clinic typing task in users’ normal typing.

Conclusions

The finding that an algorithm trained on data from an in-clinic setting has comparable performance with that tested on data collected through naturalistic at-home computer use reinforces the hypothesis that subtle differences in motor function can be detected from typing behavior. This work represents another step toward an objective, user-convenient, and quasi-continuous monitoring tool for PD.