Prodromal Parkinson's disease as defined per MDS research criteria in the general elderly community

Trajectories of healthy aging and their association with prodromal parkinson disease: The HELIAD study

Background: The aim of the present study was to investigate the association of prodromal PD (pPD) with trajectories of healthy aging, according to its latest definition by the WHO.Methods: In a sample of 1,226 older adults (704 women), PD diagnosis was reached through standard clinical research procedures. Probability of pPD was calculated according to the International Parkinson and Movement Disorder Society's research criteria for PD-free participants. A healthy aging metric was introduced using an item response theory approach (IRT) based on information from validated questionnaires assessing functionality. Four trajectories of healthy aging were created based on whether the healthy aging status of participants was above or below the median at baseline and follow up: High-High, High-Low, Low-High and Low-Low.Results: 34.3% belonged to the High-High group, 15.7% to the High-Low, 18.6% to the Low-High and 31.4% to the Low-Low group. Participants with possible/probable pPD were 78% less likely to belong in High-High trajectory of healthy aging as compared to those without pPD (OR = 0.22, 95%CI 0.06-0.79, p-value = 0,02).Conclusion: Our findings suggest an inverse association of pPD probability with healthy aging among older adults; Further research is needed to investigate the clinical implications of this association.

Identifying prodromal symptoms at high specificity for Parkinson's disease

Introduction

To test drugs with the potential to prevent the onset of Parkinson's disease (PD), it is key to identify individuals in the general population at high risk of developing PD. This is often difficult because most of the clinical markers are non-specific, common in PD but also common in older adults (e.g., sleep problems).

Objective

We aimed to identify the clinical markers at high specificity for developing PD by comparing individuals with PD or prodromal PD to healthy controls.

Methods

We investigated motor and non-motor symptoms (Movement Disorder Society Unified Parkinson's Disease Rating Scale Part 1 and 2 items) in 64 prodromal PD and 422 PD individuals calculating the odds ratios, adjusting for age and gender, for PD and prodromal PD versus 195 healthy controls. Symptoms at high specificity were defined as having an adjusted odds ratio ≥ 6.

Results

Constipation had an adjusted odds ratio, 6.14 [95% CI: 2.94-12.80] showing high specificity for prodromal PD, and speech difficulties had an adjusted odds ratio, 9.61 [95% CI: 7.88-48.81] showing high specificity for PD. The proportion of participants showing these specific markers was moderate (e.g., prevalence of constipation was 43.75% in prodromal PD, and speech difficulties was 33.89% in PD), suggesting these symptoms may make robust predictors of prodromal PD and PD, respectively.

Discussion

Clinical markers at high specificity for developing PD could be used as tools in the screening of general populations to identify individuals at higher risk of developing PD.

Occipital hypometabolism is a risk factor for conversion to Parkinson's disease in isolated REM sleep behaviour disorder

PURPOSE

Isolated REM sleep behaviour disorder (iRBD) patients are at high risk of developing clinical syndromes of the α-synuclein spectrum. Progression markers are needed to determine the neurodegenerative changes and to predict their conversion. Brain imaging with 18F-FDG PET in iRBD is promising, but longitudinal studies are scarce. We investigated the regional brain changes in iRBD over time, related to phenoconversion.

METHODS

Twenty iRBD patients underwent two consecutive 18F-FDG PET brain scans and clinical assessments (3.7 ± 0.6 years apart). Seventeen patients also underwent 123I-MIBG and 123I-FP-CIT SPECT scans at baseline. Four subjects phenoconverted to Parkinson's disease (PD) during follow-up. 18F-FDG PET scans were compared to controls with a voxel-wise single-subject procedure. The relationship between regional brain changes in metabolism and PD-related pattern scores (PDRP) was investigated.

RESULTS

Individual hypometabolism t-maps revealed three scenarios: (1) normal 18F-FDG PET scans at baseline and follow-up (N = 10); (2) normal scans at baseline but occipital or occipito-parietal hypometabolism at follow-up (N = 4); (3) occipital hypometabolism at baseline and follow-up (N = 6). All patients in the last group had pathological 123I-MIBG and 123I-FP-CIT SPECT. iRBD converters (N = 4) showed occipital hypometabolism at baseline (third scenario). At the group level, hypometabolism in the frontal and occipito-parietal regions and hypermetabolism in the cerebellum and limbic regions were progressive over time. PDRP z-scores increased over time (0.54 ± 0.36 per year). PDRP expression was driven by occipital hypometabolism and cerebellar hypermetabolism.

CONCLUSIONS

Our results suggest that occipital hypometabolism at baseline in iRBD implies a short-term conversion to PD. This might help in stratification strategies for disease-modifying trials.

Mediterranean diet is associated with a lower probability of prodromal Parkinson's disease and risk for Parkinson's disease/dementia with Lewy bodies: A longitudinal study

BACKGROUND AND PURPOSE

Lifestyle factors have been implicated in the long-lasting neurodegenerative process in prodromal Parkinson's disease (pPD). The aim was to investigate the associations between adherence to a Mediterranean diet (MeDi) and longitudinal changes of pPD probability and the development of Parkinson's disease (PD) or pPD in a Mediterranean older population.

METHODS

Data from the Hellenic Longitudinal Investigation of Aging and Diet cohort (community-dwelling individuals, aged ≥ 65 years) were used. A detailed food frequency questionnaire was used to evaluate dietary intake and calculate MeDi adherence score, ranging from 0 to 55, with higher scores indicating higher adherence. The probability of pPD was calculated according to the updated Movement Disorder Society research criteria.

RESULTS

In all, 1047 non-PD/dementia with Lewy bodies (DLB) participants were followed for 3 ± 1 years. MeDi adherence was associated with lower increase in pPD probability over time (b = -0.003, 95% confidence interval -0.006 to -0.001, p = 0.010). Forty-nine participants had incident possible/probable pPD (i.e., pPD probability ≥ 30%). Compared to the participants in the lowest quartile of MeDi adherence, those in the higher quartiles had an approximately 60%-70% lower risk for possible/probable pPD (p for trend 0.003). MeDi-pPD associations were driven by both motor and non-motor pPD markers and not from risk markers. Also, 21 participants were diagnosed with PD/DLB at follow-up. For each unit increase in the MeDi score, there was a 9%-10% lower risk for PD/DLB (hazard ratio 0.906 [95% confidence interval 0.823-0.997], p = 0.044).

CONCLUSIONS

Mediterranean diet adherence is associated with lower increase in pPD probability over time and lower possible/probable pPD and PD/DLB incidence in older Mediterranean people. More studies are needed to confirm our results in other populations.

The mechanism of Parkinson oscillation in the cortex: Possible evidence in a feedback model projecting from the globus pallidus to the cortex

The origin, location and cause of Parkinson's oscillation are not clear at present. In this paper, we establish a new cortex-basal ganglia model to study the origin mechanism of Parkinson beta oscillation. Unlike many previous models, this model includes two direct inhibitory projections from the globus pallidus external (GPe) segment to the cortex. We first obtain the critical calculation formula of Parkinson's oscillation by using the method of Quasilinear analysis. Different from previous studies, the formula obtained in this paper can include the self-feedback connection of GPe. Then, we use the bifurcation analysis method to systematically explain the influence of some key parameters on the oscillation. We find that the bifurcation principle of different cortical nuclei is different. In general, the increase of the discharge capacity of the nuclei will cause oscillation. In some special cases, the sharp reduction of the discharge rate of the nuclei will also cause oscillation. The direction of bifurcation simulation is consistent with the critical condition curve. Finally, we discuss the characteristics of oscillation amplitude. At the beginning of the oscillation, the amplitude is relatively small; with the evolution of oscillation, the amplitude will gradually strengthen. This is consistent with the experimental phenomenon. In most cases, the amplitude of cortical inhibitory nuclei (CIN) is greater than that of cortical excitatory nuclei (CEX), and the two direct inhibitory projections feedback from GPe can significantly reduce the amplitude gap between them. We calculate the main frequency of the oscillation generated in this model, which basically falls between 13 and 30 Hz, belonging to the typical beta frequency band oscillation. Some new results obtained in this paper can help to better understand the origin mechanism of Parkinson's disease and have guiding significance for the development of experiments.

Predictive models for the incidence of Parkinson's disease: systematic review and critical appraisal

Numerous predictive models for Parkinson's disease (PD) incidence have been published recently. However, the model performance and methodological quality of those available models are yet needed to be summarized and assessed systematically. In this systematic review, we systematically reviewed the published predictive models for PD incidence and assessed their risk of bias and applicability. Three international databases were searched. Cohort or nested case-control studies that aimed to develop or validate a predictive model for PD incidence were considered eligible. The Prediction model Risk Of Bias ASsessment Tool (PROBAST) was used for risk of bias and applicability assessment. Ten studies covering 10 predictive models were included. Among them, four studies focused on model development, covering eight models, while the remaining six studies focused on model external validation, covering two models. The discrimination of the eight new development models was generally poor, with only one model reported C index > 0.70. Four out of the six external validation studies showed excellent or outstanding discrimination. All included studies had high risk of bias. Three predictive models (the International Parkinson and Movement Disorder Society [MDS] prodromal PD criteria, the model developed by Karabayir et al. and models validated by Faust et al.) are recommended for clinical application by considering model performance and resource-demanding. In conclusion, the performance and methodological quality of most of the identified predictive models for PD incidence were unsatisfactory. The MDS prodromal PD criteria, model developed by Karabayir et al. and model validated by Faust et al. may be considered for clinical use.

Evaluation of the PREDIGT score’s performance in identifying newly diagnosed Parkinson’s patients without motor examination

Several recent publications described algorithms to identify subjects with Parkinson’s disease (PD). In creating the “PREDIGT Score”, we previously developed a hypothesis-driven, simple-to-use formula to potentially calculate the incidence of PD. Here, we tested its performance in the ‘De Novo Parkinson Study’ (DeNoPa) and ‘Parkinson’s Progression Marker Initiative’ (PPMI); the latter included participants from the ‘FOllow Up persons with Neurologic Disease’ (FOUND) cohort. Baseline data from 563 newly diagnosed PD patients and 306 healthy control subjects were evaluated. Based on 13 variables, the original PREDIGT Score identified recently diagnosed PD patients in the DeNoPa, PPMI + FOUND and the pooled cohorts with area-under-the-curve (AUC) values of 0.88 (95% CI 0.83–0.92), 0.79 (95% CI 0.72–0.85), and 0.84 (95% CI 0.8–0.88), respectively. A simplified version (8 variables) generated AUC values of 0.92 (95% CI 0.89–0.95), 0.84 (95% CI 0.81–0.87), and 0.87 (0.84–0.89) in the DeNoPa, PPMI, and the pooled cohorts, respectively. In a two-step, screening-type approach, self-reported answers to a questionnaire (step 1) distinguished PD patients from controls with an AUC of 0.81 (95% CI 0.75–0.86). Adding a single, objective test (Step 2) further improved classification. Among seven biological markers explored, hyposmia was the most informative. The composite AUC value measured 0.9 (95% CI 0.88–0.91) in DeNoPa and 0.89 (95% CI 0.84–0.94) in PPMI. These results reveal a robust performance of the original PREDIGT Score to distinguish newly diagnosed PD patients from controls in two established cohorts. We also demonstrate the formula’s potential applicability to enriching for PD subjects in a population screening-type approach.

Longitudinal clinical and biomarker characteristics of non-manifesting LRRK2 G2019S carriers in the PPMI cohort

We examined 2-year longitudinal change in clinical features and biomarkers in LRRK2 non-manifesting carriers (NMCs) versus healthy controls (HCs) enrolled in the Parkinson's Progression Markers Initiative (PPMI). We analyzed 2-year longitudinal data from 176 LRRK2 G2019S NMCs and 185 HCs. All participants were assessed annually with comprehensive motor and non-motor scales, dopamine transporter (DAT) imaging, and biofluid biomarkers. The latter included cerebrospinal fluid (CSF) Abeta, total tau and phospho-tau; serum urate and neurofilament light chain (NfL); and urine bis(monoacylglycerol) phosphate (BMP). At baseline, LRRK2 G2019S NMCs had a mean (SD) age of 62 (7.7) years and were 56% female. 13% had DAT deficit (defined as <65% of age/sex-expected lowest putamen SBR) and 11% had hyposmia (defined as ≤15th percentile for age and sex). Only 5 of 176 LRRK2 NMCs developed PD during follow-up. Although NMCs scored significantly worse on numerous clinical scales at baseline than HCs, there was no longitudinal change in any clinical measures over 2 years or in DAT binding. There were no longitudinal differences in CSF and serum biomarkers between NMCs and HCs. Urinary BMP was significantly elevated in NMCs at all time points but did not change longitudinally. Neither baseline biofluid biomarkers nor the presence of DAT deficit correlated with 2-year change in clinical outcomes. We observed no significant 2-year longitudinal change in clinical or biomarker measures in LRRK2 G2019S NMCs in this large, well-characterized cohort even in the participants with baseline DAT deficit. These findings highlight the essential need for further enrichment biomarker discovery in addition to DAT deficit and longer follow-up to enable the selection of NMCs at the highest risk for conversion to enable future prevention clinical trials.

Outcome Assessment in Parkinson Disease Prevention Trials: Utility of Clinical and Digital Measures

BACKGROUND AND OBJECTIVES

The prodromal phase of Parkinson disease (PD) is accompanied by subtle clinical signs that are not sufficient for diagnosis but could potentially be measured in the context of clinical trials of therapies intended to delay or prevent more definitive clinical features. The objective of this study was to review the available literature on the presence and time course of subtle motor features in prodromal PD in the context of planning for possible clinical trials.

METHODS

We reviewed the available literature based on expert opinion. We considered a range of outcomes including measurement of clinical features, patient-reported outcomes, digital markers, and clinical diagnosis.

RESULTS

We considered these features and measures in the context of patient stratification, intermediate outcomes, and clinically relevant end points, including phenoconversion.

DISCUSSION

Substantial progress has been made in understanding how motor features evolve in the period immediately before a PD diagnosis. Digital measures hold substantial progress for measurement precision and may be additionally relevant because they can be used in naturalistic environments outside the clinic. Future studies should focus on advancing digital sensor technology and analysis and developing methods to implement available methods, particularly determination of a clinical diagnosis of PD, in a clinical trial context.

Odor Identification by Parkinson’s Disease Patients Tested by Using Sniffin’ Sticks versus Natural Spices

Introduction

Hyposmia is a frequent symptom of Parkinson's disease (PD), which greatly impacts patients' flavor perception and their quality of life. However, PD patients recognize some odors better than others. Identifying which food odors are still recognized by PD patients may be useful for flavor enhancement. Our aim was to evaluate the olfactory identification of Sniffin' Sticks and spice odorants in PD patients and healthy controls (HC), to identify the impact of synthetic odorants compared with real-life food and the impact of odor familiarity and pleasantness on odorant identification in PD patients.

Methods

Sniffin' Sticks odorant identification was evaluated in 80 PD patients and 105 age-matched HC. In a subset, the spice odorant identification was evaluated.

Results

The mean total score was higher for the Sniffin' Sticks than for the spice odor identification test in all participants (55.4% versus 22.5%). Sniffin' Sticks orange, peppermint, rose, and fish odorants were best correctly identified by PD patients, by 62.5, 53.8, 52.9, and 57.5%, respectively. Of the spice odor identification test, garlic and “no stimulus” were best correctly identified by PD patients, by, respectively, 38.2 and 67.6%. HC identified most Sniffin' Sticks odorants and spices better than PD patients. Odorant familiarity determined real-life food odorant identification.

Conclusion

This study demonstrates that some food odorants, both the commercial Sniffin' Sticks as natural odorants, are still recognized by PD patients. Sniffin' Sticks were better recognized compared with real-life odorants, by both HC and PD patients. Odorant familiarity determined PD patients' odorant identification; therefore, familiar food odorants may have potential for a future flavor enhancement. Implications. This is the first study, to our knowledge, to evaluate real-life food odor identification in PD patients. Our results provide a first step towards patient-appropriate flavor enhancement strategies in PD.

Dietary Inflammatory Index score and prodromal Parkinson's disease incidence: The HELIAD study

AIM

The aim of the present study was to investigate the association of the inflammatory potential of diet with prodromal Parkinson's disease (pPD) probability and incidence among community-dwelling older individuals without clinical features of parkinsonism at baseline.

METHODS

The sample consisted of 1,030 participants 65 years old or older, drawn from a population-based cohort study of older adults in Greece (Hellenic Longitudinal Investigation of Aging and Diet - HELIAD). We calculated pPD probability, according to International Parkinson and Movement Disorder Society research criteria. Dietary Inflammatory Index (DII) was used to measure the dietary inflammatory potential, with higher index score reflecting a more pro-inflammatory diet. Associations of baseline DII with pPD probability cross-sectionally, and with possible/probable pPD incidence (pPD probability ≥30%) during the follow-up period, were examined via general linear models and generalized estimating equations, respectively.

RESULTS

Cross-sectionally, one unit increase of DII score[DII (min, max) = -5.83, 6.01]was associated with 4.9% increased pPD probability [β=0.049, 95%CI (0.025-0.090), p<0.001]. Prospectively, 62 participants developed pPD during 3.1±0.9 (mean±SD) years of follow-up. One unit increase in DII was associated with 20.3% increased risk for developing pPD [RR=1.203, 95%CI (1.070-1.351), p=0.002]. Participants in the highest tertile of DII score were 2.6 times more likely to develop pPD [β=2.594, 95%CI (1.332-5.050), p=0.005], compared to those in the lowest tertile.

CONCLUSION

More pro-inflammatory diet was related with higher pPD probability and pPD incidence (pPD probability ≥30%) in a community-dwelling older adult population. Further studies are needed to confirm these findings.

Association of the Polygenic Risk Score With the Probability of Prodromal Parkinson's Disease in Older Adults

Several studies have investigated the association of the Parkinson’s disease (PD) polygenic risk score (PRS) with several aspects of well-established PD. We sought to evaluate the association of PRS with the prodromal stage of PD. We calculated PRS in a longitudinal sample (n = 1120) of community dwelling individuals ≥ 65 years from the HELIAD (The Hellenic Longitudinal Investigation of Aging and Diet) study in order to evaluate the association of this score with the probability of prodromal PD or any of the established risk and prodromal markers in MDS research criteria, using regression multi-adjusted models. Increases in PRS estimated from GWAS summary statistics’ ninety top SNPS with p < 5 × 10^–8 was associated with increased odds of having probable/possible prodromal PD (i.e., ≥ 30% probability, OR = 1.033, 95%CI: 1.009–1.057 p = 0.006). From the prodromal PD risk markers, significant association was found between PRS and global cognitive deficit exclusively (p = 0.003). To our knowledge, our study is the first population based study investigating the association between PRS scores and prodromal markers of Parkinson’s disease. Our results suggest a strong relationship between the accumulation of many common genetic variants, as measured by PRS, and cognitive deficits.

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.

Plasma Glutathione and Prodromal Parkinson's Disease Probability

BACKGROUND

A decrease in glutathione (GSH) levels is considered one of the earliest biochemical changes in Parkinson's disease (PD).

OBJECTIVE

The authors explored the potential role of plasma GSH as a risk/susceptibility biomarker for prodromal PD (pPD) by examining its longitudinal associations with pPD probability trajectories.

METHODS

A total of 405 community-dwelling participants (median age [interquartile range] = 73.2 [7.41] years) without clinical features of parkinsonism were followed for a mean (standard deviation) of 3.0 (0.9) years.

RESULTS

A 1 μmol/L increase in plasma GSH was associated with 0.4% (95% confidence interval [CI], 0.1%-0.7%; P = 0.017) less increase in pPD probability for 1 year of follow-up. Compared with participants in the lowest GSH tertile, participants in the highest GSH tertile had a 12.9% (95% CI, 22.4%-2.2%; P = 0.020) slower rate of increase of pPD probability for 1 year of follow-up.

CONCLUSION

Plasma GSH was associated with pPD probability trajectories; therefore, it might assist in the identification of individuals who are likely to reach the threshold for pPD diagnosis more rapidly. © 2021 International Parkinson and Movement Disorder Society.

Mild Parkinsonian Signs: A Systematic Review of Clinical, Imaging, and Pathological Associations

Mild parkinsonian signs (MPS) have been widely studied during the past 3 decades and proposed as a risk marker for neurodegenerative disease. This systematic review explores the epidemiology, clinical and prognostic associations, radiological features, and pathological findings associated with MPS in older adults free from neurodegenerative disease. We find that MPS as currently defined are strongly associated with increasing age and increased risk of development of Parkinson's disease (PD), all-cause dementia, disability, and death. Positive associations with later PD are found mainly in younger populations and those with other features of prodromal PD. There are currently no consistent radiological findings for MPS, and pathological studies have shown that MPS, at least in the oldest old, are often underpinned by mixed neuropathologies, including those associated with Alzheimer's disease, cerebrovascular disease, nigral neuronal loss, and Lewy bodies. Different subcategories of MPS appear to convey varying risk and specificity for PD and other outcomes. MPS overall are not specific for parkinsonian disorders and, although associated with increased risk of PD, can reflect multiple pathologies, particularly in older individuals. "Mild motor signs" appears a more appropriate term to avoid prognostic and pathological implications, and larger future studies to prospectively examine outcomes and associations of specific MPS subcategories are required. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

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.

Risk Disclosure in Prodromal Parkinson's Disease

BACKGROUND

Impressive progress in the understanding of the prodromal phase of Parkinson's disease (PD) in recent years has enabled the generation of disease prediction models. However, a remaining diagnostic uncertainty and lack of therapeutic options for affected individuals has resulted in a variety of ethical issues that have not to date been addressed sufficiently. Moreover, differences in the specificity of prodromal symptoms and possible subtypes of PD, especially the presence of rapid eye movement (REM) sleep behavior disorder (RBD), may have an important impact on prognostic counseling.

OBJECTIVES

To derive a guideline for risk disclosure in prodromal PD based on the current literature and expert opinion.

METHODS

We performed (1) a literature review on prognostic counseling in PD and (2) consulted with international experts on prodromal PD using a semi-structured questionnaire based on a Delphi approach to evaluate recommendations for risk disclosure in PD.

RESULTS

The literature research revealed only 11 publications addressing prognostic counseling, with only two studies directly addressing affected individuals and most studies focusing on risk disclosure in RBD. The expert survey revealed the importance of distinguishing between individuals with and without RBD in prognostic counseling.

CONCLUSIONS

Based on the current literature and expert recommendations, a guideline for risk disclosure in prodromal PD for clinical care and research could be elaborated. Prognostic counseling should include differentiation between individuals with and without RBD, taking into account the high uncertainty of risk calculation in RBD-negative prodromal PD. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

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.

The Genetics of Parkinson's Disease and Implications for Clinical Practice

The genetic landscape of Parkinson’s disease (PD) is characterised by rare high penetrance pathogenic variants causing familial disease, genetic risk factor variants driving PD risk in a significant minority in PD cases and high frequency, low penetrance variants, which contribute a small increase of the risk of developing sporadic PD. This knowledge has the potential to have a major impact in the clinical care of people with PD. We summarise these genetic influences and discuss the implications for therapeutics and clinical trial design.

Comparison in detection of prodromal Parkinson's disease patients using original and updated MDS research criteria in two independent cohorts

INTRODUCTION

MDS research criteria for prodromal Parkinson's disease (pPD) were published in 2015 and updated in 2019. We aimed to determine the difference in pPD patient detection rates in two cohorts recruited via gastrointestinal symptoms (PARCAS study) and the presence of a probable REM sleep behaviour disorder (PDBIOM study) using the original and updated criteria.

METHODS

We evaluated all risk and prodromal markers, except genetic testing, plasma urate and physical inactivity, in both cohorts and DaT scan, diabetes mellitus type II and cognitive deficit in the PARCAS cohort. Thresholds of 50% probability for possible pPD and 80% for probable pPD were used.

RESULTS

PPD status as identified by the original/updated criteria showed differences for probable pPD (n = 8/9; original/updated criteria) and possible pPD (n = 9/13) in the PARCAS cohort (total n = 158), as well as for probable pPD (n = 19/21) and possible pPD (n = 6/3) in the PDBIOM cohort (total n = 48). A high concordance rate was found between the two criteria sets (p < 0.001 for all groups).

CONCLUSION

All probable pPD cases remained in the same category after evaluation with both criteria; three possible pPD cases based on the original criteria exceeded the threshold for probable pPD based on the updated criteria, and five possible new pPD cases were detected, with only one shift in the opposite direction. The updated MDS pPD research criteria tend to identify more patients as positive, yet their accuracy needs to be determined in prospective studies.

Frailty and Prodromal Parkinson's Disease: Results From the HELIAD Study

BACKGROUND

To investigate the association between frailty, Parkinson's disease (PD), and the probability of prodromal Parkinson's disease (prodromal PD) in Greek community-dwelling older individuals.

METHODS

Parkinson's disease diagnosis was reached through standard clinical research procedures. Probability of prodromal PD was calculated according to the International Parkinson and Movement Disorder Society's research criteria for PD-free participants. Frailty was evaluated according to definitions of the phenotypic and multidomain approach. Logistic and linear regression models were performed to investigate associations between frailty (predictor) and the probability of prodromal PD, either continuous or dichotomous (≥30% probability score), or PD (outcome).

RESULTS

Data from 1765 participants aged 65 and older were included in the present analysis. Parkinson's disease and prodromal PD prevalence were 1.9% and 3.0%, respectively. Compared to nonfrail participants, those who were frail, as identified with either the Fried frailty phenotype or Frailty Index had approximately 4 (odds ratio [OR] 4.09, 95% confidence interval [CI] 1.54-10.89) and 12 times (OR 12.16, 95% CI 5.46-27.09) higher odds of having a PD diagnosis, respectively. Moreover, compared to the nonfrail, frail participants as identified with either the Fried frailty phenotype or Frailty Index had 2.8 (OR 2.83, 95% CI 1.09-7.37) and 8.3 times (OR 8.39, 95% CI 4.56-15.42) higher odds of having possible/probable prodromal PD, respectively.

CONCLUSIONS

Frailty status was associated with prodromal PD and PD, suggesting common characteristics or underlying mechanisms of these conditions. Although prospective studies are warranted, acknowledging the possible association of frailty, PD, and prodromal PD may improve their clinical management.

Inflammatory Mechanisms in Parkinson's Disease: From Pathogenesis to Targeted Therapies

Inflammation is a critical factor contributing to the progressive neurodegenerative process observed in Parkinson's disease (PD). Microglia, the immune cells of the central nervous system, are activated early in PD pathogenesis and can both trigger and propagate early disease processes via innate and adaptive immune mechanisms such as upregulated immune cells and antibody-mediated inflammation. Downstream cytokines and gene regulators such as microRNA (miRNA) coordinate later disease course and mediate disease progression. Biomarkers signifying the inflammatory and neurodegenerative processes at play within the central nervous system are of increasing interest to clinical teams. To be effective, such biomarkers must achieve the highest sensitivity and specificity for predicting PD risk, confirming diagnosis, or monitoring disease severity. The aim of this review was to summarize the current preclinical and clinical evidence that suggests that inflammatory processes contribute to the initiation and progression of neurodegenerative processes in PD. In this article, we further summarize the data about main inflammatory biomarkers described in PD to date and their potential for regulation as a novel target for disease-modifying pharmacological strategies.

Premotor Parkinson's disease: Overview of clinical symptoms and current diagnostic methods

Parkinson's disease (PD) is characterized by typical motor symptoms. However, recent studies show several non-motor features that may precede the development of the motor symptoms of PD. The best known premotor symptoms include hyposmia, REM sleep behavior disorder (RBD), constipation, and depression; other symptoms are excessive daytime somnolence, orthostatic hypotension and symptomatic hypotension, erectile or urinary dysfunction, musculoskeletal symptoms, pain, and global cognitive deficit. In this review, we summarize currently available diagnostic methods for these symptoms. We also briefly summarize neuroimaging, polyneuropathy, peripheral markers, and cerebrospinal fluid biomarkers that may be used in the early diagnosis of PD.

Extracellular Vesicles as Nanotherapeutics for Parkinson's Disease

Extracellular vesicles (EVs) are naturally occurring membranous structures secreted by normal and diseased cells, and carrying a wide range of bioactive molecules. In the central nervous system (CNS), EVs are important in both homeostasis and pathology. Through receptor-ligand interactions, direct fusion, or endocytosis, EVs interact with their target cells. Accumulating evidence indicates that EVs play crucial roles in the pathogenesis of many neurodegenerative disorders (NDs), including Parkinson's disease (PD). PD is the second most common ND, characterized by the progressive loss of dopaminergic (DAergic) neurons within the Substantia Nigra pars compacta (SNpc). In PD, EVs are secreted by both neurons and glial cells, with either beneficial or detrimental effects, via a complex program of cell-to-cell communication. The functions of EVs in PD range from their etiopathogenetic relevance to their use as diagnostic tools and innovative carriers of therapeutics. Because they can cross the blood-brain barrier, EVs can be engineered to deliver bioactive molecules (e.g., small interfering RNAs, catalase) within the CNS. This review summarizes the latest findings regarding the role played by EVs in PD etiology, diagnosis, prognosis, and therapy, with a particular focus on their use as novel PD nanotherapeutics.

Metabolic syndrome does not influence the phenotype of LRRK2 and GBA related Parkinson's disease

In order toevaluate the influence of the metabolic syndrome (MS) (obesity, hypertension, elevated triglycerides, reduced levels of HDL cholesterol and glucose impairment) on the phenotype of LRRK2 and GBA Parkinson’s disease (PD), and on the prevalence of prodromal features among individuals at risk, we collected, laboratory test results, blood pressure, demographic, cognitive, motor, olfactory and affective information enabling the assessment of each component of MS and the construction of the MDS prodromal probability score. The number of metabolic components and their levels were compared between participants who were separated based on disease state and genetic status. One hundred and four idiopathic PD, 40 LRRK2-PD, 70 GBA-PD, 196 healthy non-carriers, 55 LRRK2-NMC and 97 GBA-NMC participated in this study. PD groups and non manifesting carriers (NMC) did not differ in the number of metabolic components (p = 0.101, p = 0.685, respectively). LRRK2-PD had higher levels of triglycerides (p = 0.015) and higher rates of prediabetes (p = 0.004), while LRRK2-NMC had higher triglyceride levels (p = 0.014). NMC with probability rates for prodromal PD above 50% had higher frequencies of hypertriglyceridemia and prediabetes (p < 0.005, p = 0.023 respectively). While elevated triglycerides and prediabetes were more frequent among LRRK2 carriers, MS does not seem to influence GBA and LRRK2-PD phenotype.

Clinical and Imaging Markers of Prodromal Parkinson's Disease

The diagnosis of Parkinson's disease (PD) relies on the clinical effects of dopamine deficiency, including bradykinesia, rigidity and tremor, usually manifesting asymmetrically. Misdiagnosis is common, due to overlap of symptoms with other neurodegenerative disorders such as multiple system atrophy and progressive supranuclear palsy, and only autopsy can definitively confirm the disease. Motor deficits generally appear when 50–60% of dopaminergic neurons in the substantia nigra are already lost, limiting the effectiveness of potential neuroprotective therapies. Today, we consider PD to be not just a movement disorder, but rather a complex syndrome non-motor symptoms (NMS) including disorders of sleep-wake cycle regulation, cognitive impairment, disorders of mood and affect, autonomic dysfunction, sensory symptoms and pain. Symptomatic LRRK2 mutation carriers share non-motor features with individuals with sporadic PD, including hyposmia, constipation, impaired color discrimination, depression, and sleep disturbance. Following the assumption that the pre-symptomatic gene mutation carriers will eventually exhibit clinical symptoms, their neuroimaging results can be extended to the pre-symptomatic stage of PD. The long latent phase of PD, termed prodromal-PD, represents an opportunity for early recognition of incipient PD. Early recognition could allow initiation of possible neuroprotective therapies at a stage when therapies might be most effective. The number of markers with the sufficient level of evidence to be included in the MDS research criteria for prodromal PD have increased during the last 10 years. Here, we review the approach to prodromal PD, with an emphasis on clinical and imaging markers and report results from our neuroimaging study, a retrospective evaluation of a cohort of 39 participants who underwent DAT-SPECT scan as part of their follow up. The study was carried out to see if it was possible to detect subclinical signs in the preclinical (neurodegenerative processes have commenced, but there are no evident symptoms or signs) and prodromal (symptoms and signs are present, but are yet insufficient to define disease) stages of PD.

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.

Deep Learning With EEG Spectrograms in Rapid Eye Movement Behavior Disorder

REM Behavior Disorder (RBD) is now recognized as the prodromal stage of α-synucleinopathies such as Parkinson's disease (PD). In this paper, we describe deep learning models for diagnosis/prognosis derived from a few minutes of eyes-closed resting electroencephalography data (EEG) collected at baseline from idiopathic RBD patients (n = 121) and healthy controls (HC, n = 91). A few years after the EEG acquisition (4±2 years), a subset of the RBD patients were eventually diagnosed with either PD (n = 14) or Dementia with Lewy bodies (DLB, n = 13), while the rest remained idiopathic RBD. We describe first a simple deep convolutional neural network (DCNN) with a five-layer architecture combining filtering and pooling, which we train using stacked multi-channel EEG spectrograms from idiopathic patients and healthy controls. We treat the data as in audio or image classification problems where deep networks have proven successful by exploiting invariances and compositional features in the data. For comparison, we study a simple deep recurrent neural network (RNN) model using three stacked Long Short Term Memory network (LSTM) cells or gated-recurrent unit (GRU) cells-with very similar results. The performance of these networks typically reaches 80% (±1%) classification accuracy in the balanced HC vs. PD-conversion classification problem. In particular, using data from the best single EEG channel, we obtain an area under the curve (AUC) of 87% (±1%)-while avoiding spectral feature selection. The trained classifier can also be used to generate synthetic spectrograms using the DeepDream algorithm to study what time-frequency features are relevant for classification. We find these to be bursts in the theta band together with a decrease of bursting in the alpha band in future RBD converters (i.e., converting to PD or DLB in the follow up) relative to HCs. From this first study, we conclude that deep networks may provide a useful tool for the analysis of EEG dynamics even from relatively small datasets, offering physiological insights and enabling the identification of clinically relevant biomarkers.

Motor function and the probability of prodromal Parkinson's disease in older adults

BACKGROUND

Identification and characterization of Parkinson's disease (PD) in its prodromal stage is crucial.

OBJECTIVE

The objective of this study was to investigate the association between motor function and the probability of prodromal PD in a community-dwelling older population.

METHODS

We used data from a population-based cohort of older adults (HELIAD study). Subjective motor function was evaluated with a 12-item motor symptoms questionnaire and objective motor function indirectly with a physical activity questionnaire and two gait speed tests. The probability of prodromal PD was calculated according to the Movement Disorder Society research criteria for n = 1731 without PD. Regression multiadjusted models were used to investigate the associations between each motor measure and prodromal PD probability.

RESULTS

For each unit increase in motor symptoms score and for each kcal/kg/day lower energy expenditure (corresponding to 20 minutes of light walking/day for a 75-kg man) there was a 27% and 3% higher probability for prodromal PD, respectively (P < 0.001). Having at least one subjective motor symptom increased the odds of having possible/probable prodromal PD (n = 49; P < 0.05). Including subjective and indirect motor variables in the same model showed that both (symptoms and physical activity) contributed significantly to the model (P < 0.01). Excluding subthreshold parkinsonism from the calculation showed that gait speed less than 0.8 m/s was also associated with a higher prodromal PD probability score (P < 0.001).

CONCLUSIONS

Subjective motor symptoms as well as simple objective motor measures of physical activity or gait speed are associated with a higher probability of prodromal PD in older adults. These data may serve to enable the early identification of prodromal PD cohorts, particularly if they are confirmed in longitudinal studies. © 2019 International Parkinson and Movement Disorder Society.

Evolution and clustering of prodromal parkinsonian features in GBA1 carriers

Background

Five to 25% of patients with PD carry glucocerebrosidase gene mutations, and 10% to 30% of glucocerebrosidase carriers will develop PD by age 80. Stratification of PD risk in glucocerebrosidase carriers provides an opportunity to target disease‐modifying therapies.

Objective

Cross‐sectional and longitudinal survey of prodromal PD signs among glucocerebrosidase carriers.

Design

Prospective assessment of 82 glucocerebrosidase mutation carriers and 35 controls over 4 to 5 years for prodromal clinical PD features.

Results

At all time points, olfactory (measured using University of Pennsylvania Smell Identification Test) and cognitive (Montreal Cognitive Assessment) function and the International Parkinson and Movement Disorder Society UPDRS parts II and III scores were significantly worse amongst glucocerebrosidase mutation carriers. Progression to microsmia (odds ratio: 8.5; 95% confidence interval: 2.6–28.2; P < 0.05) and mild cognitive impairment (odds ratio: 4.2; 95% confidence interval: 1.1–16.6; P < 0.05) were more rapid compared to controls. Those with worse olfaction also had worse cognition (OR, 1.5; 95% CI: 0.0–2.8; P < 0.05) and depression (OR, 1.3; 95% CI: 0.6–2.8; P < 0.05). No participants reached the MDS prodromal PD diagnostic criteria before PD diagnosis. One participant developed PD. He did not fulfill the International Parkinson and Movement Disorder Society prodromal PD criteria before diagnosis.

Conclusion

Assessment of individual and clustered PD prodromal features may serve as a useful tool to identify high‐risk subjects for conversion to PD. As a result of the low conversion rate in our glucocerebrosidase mutation carriers to date, prospective validation is needed in larger cohorts to establish the profile of these features in PD convertors. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Biomarkers of Parkinson's disease: 20 years later

Despite intensive effort, biomarker research for the detection of prodromal stage, diagnosis and progression of Parkinson's disease (PD) falls short of expectations. This article reviews the attempts in the last 20 years to find a biomarker, addresses challenges along the biomarker search and suggests the steps that should be taken to overcome these challenges. Although several biomarkers are currently available, none of them is specific enough for diagnosis, prediction of future PD or disease progression. The main reason for the failure finding a strong biomarker seems to be drastic heterogeneity of PD, which exhibits itself in all domains; from the clinic to pathophysiology or genetics. The diversity in patient selection, assessment methods or outcomes in biomarker studies also limit the interpretation and generalizability of the data. In search of a reliable biomarker, consideration of novel approaches encompassing individual demographic, clinical, genetic, epigenetic and environmental differences, employment of strategies enabling marker combinations, designing multicenter studies with compatible assessment methods, integration of data from preclinical domains and utilization of novel technology-based assessments are necessary.

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.

Advances in the Research of Risk Factors and Prodromal Biomarkers of Parkinson's Disease

Parkinson's disease (PD) is the second most common neurodegenerative disease in the world. With the advent of an aging population and improving life expectancy worldwide, the number of PD patients is expected to increase, which may lead to an urgent need for effective preventive and diagnostic strategies for PD. Although there is increasing research regarding the pathogenesis of PD, there is limited knowledge regarding the prevention of PD. Moreover, the diagnosis of PD depends on clinical criteria, which require the occurrence of bradykinesia and at least one symptom of rest tremor or rigidity. However, converging evidence from clinical, genetic, neuropathological, and imaging studies suggests the initiation of PD-specific pathology prior to the initial presentation of these classical motor clinical features by years or decades. This latent stage of neurodegeneration in PD is a particularly important stage for effective neuroprotective therapies, which might retard the progression or prevent the onset of PD. Therefore, the exploration of risk factors and premotor biomarkers is not only crucial to the early diagnosis of PD but is also helpful in the development of effective neuroprotection and health care strategies for appropriate populations at risk for PD. In this review, we searched and summarized ∼249 researches and 31 reviews focusing on the risk factors and prodromal biomarkers of PD and published in MEDLINE.

The Association of Olfactory Dysfunction, Frailty, and Mortality Is Mediated by Inflammation: Results from the InCHIANTI Study

Background

Olfactory dysfunction might unveil the association between ageing and frailty, as it is associated with declining cognitive function, depression, reduced physical performance, reduced dietary intake, and mortality; all these conditions are characterized by increased levels of inflammatory parameters. The present study is aimed at evaluating the association between olfactory dysfunction, frailty, and mortality and whether such association might be mediated by inflammation.

Methods

We analysed data of 1035 participants aged 65+ enrolled in the “InCHIANTI” study. Olfactory function was tested by the recognition of the smells of coffee, mint, and air. Olfactory dysfunction was defined as lack of recognition of at least two smells. Considering the items “shrinking,” “exhaustion,” “sedentariness,” “slowness,” and “weakness” included in the Fried definition, frailty was defined as the presence of at least three criteria, prefrailty of one or two, and robustness of none. Serum interleukin-6 (IL-6) was measured in duplicate by high-sensitivity enzyme-linked immunosorbent assays. Logistic regression was adopted to assess the association of frailty with olfactory function, as well as with the increasing number of olfactory deficits. Cox regression was used to test the association between olfactory dysfunction and 9-year survival.

Results

Olfactory dysfunction was associated with frailty, after adjusting (OR 1.94, 95% CI = 1.07-3.51; P = .028); analysis of the interaction term indicated that the association varied according to interleukin-6 levels (P for interaction = .005). Increasing levels of olfactory dysfunction were associated with increasing probability of being frail. Also, olfactory dysfunction was associated with reduced survival (HR 1.52, 95% CI = 1.16-1.98; P = .002); this association varied according to the presence of frailty (P for interaction = .017) and prefrailty status (P for interaction = .046), as well as increased interleukin-6 levels (P for interaction = .011).

Conclusions

Impairment of olfactory function might represent a marker of frailty, prefrailty, and consequently reduced survival in an advanced age. Inflammation might represent the possible link between these conditions.

Alpha-Synuclein in Peripheral Tissues in Parkinson's Disease

Parkinson's disease (PD) is a common neurodegenerative disorder. To date, the diagnosis of PD relies mainly on clinical manifestations whereas neuropathological confirmation of the brain is only possible with postmortem studies. Neuronal loss in the substantia nigra pars compacta (SNc) associated with Lewy bodies/neurites is the pathological hallmark feature of PD. The major component of Lewy pathology (LP) is misfolded alpha-synuclein (α-SYN). There is evidence that the distribution of LP is not only limited to the brain but extends to peripheral tissues, including gastrointestinal tract, salivary glands, olfactory mucosa, skin, retina, adrenal gland, and heart. Sensitivity and specificity of α-SYN detection in PD vary greatly among studies due to methodological heterogeneity, such as sampling sites and size, tissue preparation, staining techniques, and antibodies used. Of note, α-SYN has also been found in preclinical and prodromal PD. Further in vivo studies focusing on favorable biopsy sites and standard techniques are needed to get better understanding of α-SYN deposits in preclinical, prodromal, and clinical PD.

Non-motor features of Parkinson's disease in a nested case-control study of US men

BACKGROUND

Several non-motor features may individually contribute to identify prodromal Parkinson's disease (PD), but little is known on how they interact.

METHODS

We conducted a case-control study nested within the Health Professionals Follow-up Study in a large cohort of men age 40-75 at recruitment in 1986. Cases (n=120) had confirmed PD, were<85 in January 2012, returned a 2012 questionnaire with questions on probable rapid eye movement sleep behaviour disorder (RBD) and constipation sent to all cohort participants and completed in 2014 the Brief Smell Identification Test and a questionnaire assessing parkinsonism and other non-motor PD features (including depressive symptoms, excessive daytime sleepiness, impaired colour vision and body pain). Controls (n=6479) met the same criteria as cases, except for the PD diagnosis.

RESULTS

Concurrent constipation, probable RBD and hyposmia were present in 29.3% of cases and 1.1% of controls, yielding an age-adjusted OR of 160(95%CI 72.8to353) for three features versus none. The odds of PD increased exponentially with additional non-motor features (OR for 6-7 features versus none: 1325; 95%CI333to5279). Among men without PD, the number of non-motor features was associated with odds of parkinsonism (OR for 6-7 features versus none: 89; 95%CI21.2to375). We estimated that in a population with a prodromal PD prevalence of 2%, concurrent constipation, probable RBD and hyposmia would have a maximum sensitivity of 29% and a positive predictive value (PPV) of 35%. The PPV could increase up to 70% by including additional features, but with sharply decreased sensitivity.

CONCLUSIONS

Concurrent constipation, probable RBD and hyposmia are strongly associated with PD. Because these features often precede motor symptoms and their co-occurrence could provide an efficient method for early PD identification.

Mediterranean diet adherence is related to reduced probability of prodromal Parkinson's disease

BACKGROUND

The International Parkinson and Movement Disorder Society recently introduced a methodology for probability score calculation for prodromal PD.

OBJECTIVES

To assess the probability of prodromal PD in an older population and investigate its possible association with Mediterranean diet adherence.

METHODS

Data from a population-based cohort study of older adults (HEllenic Longitudinal Investigation of Aging and Diet) in Greece were used. Probability of prodromal PD was calculated according to International Parkinson and Movement Disorder Society research criteria. A detailed food frequency questionnaire was used to evaluate dietary intake and calculate Mediterranean diet adherence score, ranging from 0 to 55, with higher scores indicating higher adherence.

RESULTS

Median probability of prodromal PD was 1.9%, ranging from 0.2 to 96.7% in 1,731 PD-free individuals aged ≥ 65 (41% male). Lower probability for prodromal PD (P < 0.001) in the higher Mediterranean diet adherence groups was noted, driven mostly by nonmotor markers of prodromal PD, depression, constipation, urinary dysfunction, and daytime somnolence. Each unit increase in Mediterranean diet score was associated with a 2% decreased probability for prodromal PD (P < 0.001). Compared to participants in the lowest quartile of Mediterranean diet adherence, those in the highest quartile were associated with a ∼21% lower probability for prodromal PD.

CONCLUSIONS

Adherence to the Mediterranean diet is associated with lower probability of prodromal PD in older people. Further studies are needed to elucidate the potential causality of this association, potential relation of the Mediterranean diet to delayed onset or lower incidence of PD, as well as the underlying neurobiological mechanisms. © 2018 International Parkinson and Movement Disorder Society.

Diagnostic biomarkers for Parkinson's disease at a glance: where are we?

Parkinson's disease (PD) is a neurodegenerative disorder whose aetiology remains unclear: degeneration involves several neurotransmission systems, resulting in a heterogeneous disease characterized by motor and non-motor symptoms. PD causes progressive disability that responds only to symptomatic therapies. Future advances include neuroprotective strategies for use in at-risk populations before the clinical onset of disease, hence the continuing need to identify reliable biomarkers that can facilitate the clinical diagnosis of PD. In this evaluative review, we summarize information on potential diagnostic biomarkers for use in the clinical and preclinical stages of PD.

Advances in markers of prodromal Parkinson disease

Efforts to develop neuroprotective therapy for Parkinson disease (PD) are focusing on the early stages of disease, which offer the best opportunity to intervene. Early PD can be divided into preclinical, prodromal and clinical stages; in this Review, we focus on the prodromal stage and markers that can be used to identify prodromal PD. We consider the necessary properties of a marker, before providing an overview of the proven and potential markers of prodromal PD, including clinical nonmotor markers, clinical motor markers, neuroimaging markers and tissue biomarkers. Markers for which the ability to predict conversion to PD is supported by the strongest evidence include olfactory loss, REM sleep behaviour disorder and constipation. Markers with the highest diagnostic strength include REM sleep behaviour disorder, dopaminergic imaging and subtle motor parkinsonism. The lead time - the period between the appearance of a marker and conversion to PD - is highly variable between markers, ranging from 5 years for impaired motor performance to >20 years for autonomic symptoms. The cost of screening for these markers also varies dramatically: some require just questionnaires, whereas others require sophisticated scanning techniques. Finally, we summarize how prodromal and risk markers can be combined to estimate the probability that an individual has prodromal PD, with a focus on the International Parkinson Disease and Movement Disorders Society (MDS) Prodromal Parkinson Criteria.

Sleep-related motor and behavioral disorders: Recent advances and new entities

Patients with sleep-related motor and behavioral disorders present to a variety of subspecialty clinics (neurology, sleep medicine, respiratory medicine, psychiatry). Diagnosing these disorders can be difficult, and sometimes they have a significant impact on quality of life. Alongside a number of common and well-recognized conditions, several new disease entities have been described in recent years that present with abnormal nocturnal motor phenomena (such as ADCY5-associated disease and anti-IgLON5 disease). Our understanding of the neural basis and prognostic significance of other sleep-related disorders has also grown, particularly rapid eye movement sleep behavior disorder. This review (along with a collection of previously unpublished videos) is intended to aid in the recognition and treatment of these patients. The recent change in terminology from nocturnal frontal lobe epilepsy to sleep-related hypermotor epilepsy is also discussed. © 2018 International Parkinson and Movement Disorder Society.

Application of the Movement Disorder Society prodromal criteria in healthy G2019S-LRRK2 carriers

BACKGROUND

In 2015, the International Parkinson and Movement Disorder Society Task Force recommended research criteria for the estimation of prodromal PD.

OBJECTIVES

We aimed to evaluate, for the first time, the criteria in first-degree relatives of Ashkenazi Jewish G2019S-LRRK2 PD patients, who are considered a population at risk for developing PD, and assess the sensitivity and specificity of the criteria in identifying phenoconverters.

METHODS

Participants were evaluated longitudinally over a period of 5 years (average follow-up: 49.2 ± 12.3 months). Likelihood ratios and probability estimations were calculated based on the International Parkinson and Movement Disorder Society Research Criteria for Prodromal Parkinson's Disease markers and examined for each assessment point.

RESULTS

One hundred twenty healthy carriers (49.53 ± 13.4 years; 54% female) and 111 healthy noncarriers (48.43 ± 15.79 years; 49% female) participated in this study. Probability scores were significantly higher in healthy carriers than healthy noncarriers (P < 0.0001). Of the 20 participants (8.6%) who met criteria for probable prodromal PD at baseline, 17 were healthy carriers. Participants who reached the threshold were older (P < 0.0001), had higher UPDRS-III (P < 0.001), lower cognitive function (P = 0.001), and more nonmotor symptoms (P < 0.0001), compared to those who did not. Ten participants were diagnosed with incident PD within 5 years from baseline resulting in a specificity of 91.82% (95% confidence interval: 86.69-96.94), sensitivity of 80% (95% confidence interval: 55.21-100), positive predictive value of 47.06% (95% confidence interval: 23.33-70.79), and negative predictive value of 98.06% (95% confidence interval: 95.39-100). All 10 phenoconvertors were G2019S-LRRK2 carriers.

CONCLUSIONS

The results showed the utility of using the criteria and high sensitivity and specificity in identifying prodromal PD in this high-risk unique cohort. These results may be valuable for future disease modification clinical trials. © 2018 International Parkinson and Movement Disorder Society.