Levodopa-induced dyskinesia in Parkinson's disease: Insights from cross-cohort prognostic analysis using machine learning.

BACKGROUND: Prolonged levodopa treatment in Parkinson's disease (PD) often leads to motor complications, including levodopa-induced dyskinesia (LID). Despite continuous levodopa treatment, some patients do not develop LID symptoms, even in later stages of the disease. OBJECTIVE: This study explores machine learning (ML) methods using baseline clinical characteristics to predict the development of LID in PD patients over four years, across multiple cohorts. METHODS: Using interpretable ML approaches, we analyzed clinical data from three independent longitudinal PD cohorts (LuxPARK, n = 356; PPMI, n = 484; ICEBERG, n = 113) to develop cross-cohort prognostic models and identify potential predictors for the development of LID. We examined cohort-specific and shared predictive factors, assessing model performance and stability through cross-validation analyses. RESULTS: Consistent cross-validation results for single and multiple cohort analyses highlighted the effectiveness of the ML models and identified baseline clinical characteristics with significant predictive value for the LID prognosis in PD. Predictors positively correlated with LID include axial symptoms, freezing of gait, and rigidity in the lower extremities. Conversely, the risk of developing LID was inversely associated with the occurrence of resting tremors, higher body weight, later onset of PD, and visuospatial abilities. CONCLUSIONS: This study presents interpretable ML models for dyskinesia prognosis with significant predictive power in cross-cohort analyses. The models may pave the way for proactive interventions against dyskinesia in PD by optimizing levodopa dosing regimens and adjunct treatments with dopamine agonists or MAO-B inhibitors, and by employing non-pharmacological interventions such as dietary adjustments affecting levodopa absorption for high-risk LID patients.

Isolated REM Sleep without Atonia Is Not Equivalent to REM Sleep Behavior Disorder in Early-Stage Parkinson's Disease.

BACKGROUND: In early-stage Parkinson's disease (PD), rapid eye movement (REM) sleep behavior disorder (RBD) predicts poor cognitive and motor outcome. However, the baseline significance and disease evolution associated with isolated REM sleep without atonia (iRWA, ie, enhanced muscle tone during 8.7% of REM sleep, but no violent behavior) are not well understood. OBJECTIVES: The objective is to determine whether iRWA was a mild form of RBD and progressed similarly over time. METHODS: Participants with early PD (<4 years from medical diagnosis) were included from 2014 to 2021 in a longitudinal study. They underwent interviews and examinations in the motor, cognitive, autonomous, psychiatric, sensory, and sleep domains every year for 4 years along with a video polysomnography and magnetic resonance imaging examination of the locus coeruleus/subcoeruleus complex (LC/LsC) at baseline. The clinical characteristics were compared between groups with normal REM sleep, with iRWA and with RBD, at baseline and for 4 years. RESULTS: Among 159 PD participants, 25% had RBD, 25% had iRWA, and 50% had normal REM sleep. At baseline, the non-motor symptoms were less prevalent and the LC/LsC signal intensity was more intense in participants with iRWA than with RBD. Over 4 years, participants with normal REM sleep and with iRWA had a similar cognitive and motor trajectory, whereas participants with RBD had greater cognitive and motor decline. CONCLUSIONS: We demonstrated that iRWA is frequent in early PD, but is not a milder form of RBD. Both groups have distinct baseline characteristics and clinical trajectories. They should be distinguished in clinical routine and research protocols. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Genotype-phenotype correlation in PRKN-associated Parkinson's disease.

Bi-allelic pathogenic variants in PRKN are the most common cause of autosomal recessive Parkinson's disease (PD). 647 patients with PRKN-PD were included in this international study. The pathogenic variants present were characterised and investigated for their effect on phenotype. Clinical features and progression of PRKN-PD was also assessed. Among 133 variants in index cases (n = 582), there were 58 (43.6%) structural variants, 34 (25.6%) missense, 20 (15%) frameshift, 10 splice site (7.5%%), 9 (6.8%) nonsense and 2 (1.5%) indels. The most frequent variant overall was an exon 3 deletion (n = 145, 12.3%), followed by the p.R275W substitution (n = 117, 10%). Exon3, RING0 protein domain and the ubiquitin-like protein domain were mutational hotspots with 31%, 35.4% and 31.7% of index cases presenting mutations in these regions respectively. The presence of a frameshift or structural variant was associated with a 3.4 ± 1.6 years or a 4.7 ± 1.6 years earlier age at onset of PRKN-PD respectively (p < 0.05). Furthermore, variants located in the N-terminus of the protein, a region enriched with frameshift variants, were associated with an earlier age at onset. The phenotype of PRKN-PD was characterised by slow motor progression, preserved cognition, an excellent motor response to levodopa therapy and later development of motor complications compared to early-onset PD. Non-motor symptoms were however common in PRKN-PD. Our findings on the relationship between the type of variant in PRKN and the phenotype of the disease may have implications for both genetic counselling and the design of precision clinical trials.

Sleep disorders in Parkinson's disease, an early and multiple problem.

In Parkinson's disease (PD), it remains unclear whether sleep disorders including insomnia, REM sleep behavior disorder (RBD), excessive daytime sleepiness (EDS), restless legs syndrome (RLS) and sleep-disordered breathing (SDB), are isolated or combined, interact with each other and are associated with clinical factors. We sought to determine the prevalence and combinations of the main sleep disorders, and their clinical and polysomnographic associations in early stage PD. Sleep disorders were systematically diagnosed after medical interview and video-polysomnography in 162 participants with early stage PD and 58 healthy controls from the baseline of the longitudinal ICEBERG cohort. Demographic, clinical (motor, cognitive, autonomic, psychological and sensory tests), therapeutic and polysomnographic associations of sleep disorders were investigated. Sleep disorders were frequent (71%) and combined in half of the patients. The number of sleep disorders increased with disease duration and dysautonomia. Insomnia was the most common (41%), followed by definite RBD (25%), EDS (25%), and RLS (16%). These disorders were more frequent than in controls whereas SDB was rare, moderate and similar in both groups. In patients, insomnia (mainly difficulties maintaining sleep) was associated with female gender, shorter sleep time and RLS, but not with motor or psychological symptoms. RBD was associated with dysautonomia and advanced age, but not with motor and cognitive measures. EDS was associated with psychiatric and motor symptoms as well as the sedative effects of dopamine agonists but not with other sleep disturbances. Sleep disturbances are frequent and combined in early patients with PD. Their determinants and markers are more organic than psychological.

Unveiling Assessment Gaps in Parkinson's Disease Psychosis: A Scoping Review.

BACKGROUND: Parkinson's disease psychosis (PDP) is a multidimensional construct that is challenging to measure. Accurate assessment of PDP requires comprehensive and reliable clinical outcome assessment (COA) measures. OBJECTIVE: To identify PDP measurement gaps in available COAs currently used in clinical and research settings. METHODS: We conducted a scoping review using Preferred Reporting Items for Systematic Review and Meta-Analysis Extension for Scoping Reviews (PRISMA-ScR) guidelines. We implemented a three-step search strategy in international databases with keywords related to Parkinson's disease (PD), psychosis, and COA. We analyzed studies using COA to assess PDP, classifying their items according to domains and subdomains. RESULTS: From 5673 identified studies, we included 628 containing 432 PDP core items from 32 COAs. Among the 32 COAs, 19 were PD-specific, containing 266 items, constructed as clinician-reported outcomes (ClinRO) (148 items), patient-reported outcomes (PRO) (112 items), and observer-reported outcomes (ObsRO) (six items). Across all PD-specific COAs, regardless of structure, 89.4% of the items from 27 COAs focused primarily on assessing PDP symptoms' severity, and only 9.7% of items probed the impact of PDP on a person's daily functioning. CONCLUSIONS: Symptom-based domains are currently prioritized for measuring the severity of PDP, with limited coverage of the functional impact of PDP on patients' lives. Whereas the International Parkinson and Movement Disorder Society has traditionally developed a "Unified" COA that culls items from prior COAs to form a new one, a new COA will largely need newly developed items if the functional impact of PDP is prioritized. © 2024 International Parkinson and Movement Disorder Society.

Proxy-analysis of the genetics of cognitive decline in Parkinson's disease through polygenic scores.

Cognitive decline is common in Parkinson's disease (PD) and its genetic risk factors are not well known to date, besides variants in the GBA and APOE genes. However, variation in complex traits is caused by numerous variants and is usually studied with genome-wide association studies (GWAS), requiring a large sample size, which is difficult to achieve for outcome measures in PD. Taking an alternative approach, we computed 100 polygenic scores (PGS) related to cognitive, dementia, stroke, and brain anatomical phenotypes and investigated their association with cognitive decline in six longitudinal cohorts. The analysis was adjusted for age, sex, genetic ancestry, follow-up duration, GBA and APOE status. Then, we meta-analyzed five of these cohorts, comprising a total of 1702 PD participants with 6156 visits, using the Montreal Cognitive Assessment as a cognitive outcome measure. After correction for multiple comparisons, we found four PGS significantly associated with cognitive decline: intelligence (p = 5.26e-13), cognitive performance (p = 1.46e-12), educational attainment (p = 8.52e-10), and reasoning (p = 3.58e-5). Survival analyses highlighted an offset of several years between the first and last quartiles of PGS, with significant differences for the PGS of cognitive performance (5 years) and educational attainment (7 years). In conclusion, we found four PGS associated with cognitive decline in PD, all associated with general cognitive phenotypes. This study highlights the common genetic factors between cognitive decline in PD and the general population, and the importance of the participant's cognitive reserve for cognitive outcome in PD.

Charting Disease Trajectories from Isolated REM Sleep Behavior Disorder to Parkinson's Disease.

BACKGROUND: Clinical presentation and progression dynamics are variable in patients with Parkinson's disease (PD). Disease course mapping is an innovative disease modelling technique that summarizes the range of possible disease trajectories and estimates dimensions related to onset, sequence, and speed of progression of disease markers. OBJECTIVE: To propose a disease course map for PD and investigate progression profiles in patients with or without rapid eye movement sleep behavioral disorders (RBD). METHODS: Data of 919 PD patients and 88 isolated RBD patients from three independent longitudinal cohorts were analyzed (follow-up duration = 5.1; 95% confidence interval, 1.1-8.1] years). Disease course map was estimated by using eight clinical markers (motor and non-motor symptoms) and four imaging markers (dopaminergic denervation). RESULTS: PD course map showed that the first changes occurred in the contralateral putamen 13 years before diagnosis, followed by changes in motor symptoms, dysautonomia, sleep-all before diagnosis-and finally cognitive decline at the time of diagnosis. The model showed earlier disease onset, earlier non-motor and later motor symptoms, more rapid progression of cognitive decline in PD patients with RBD than PD patients without RBD. This pattern was even more pronounced in patients with isolated RBD with early changes in sleep, followed by cognition and non-motor symptoms and later changes in motor symptoms. CONCLUSIONS: Our findings are consistent with the presence of distinct patterns of progression between patients with and without RBD. Understanding heterogeneity of PD progression is key to decipher the underlying pathophysiology and select homogeneous subgroups of patients for precision medicine. © 2023 International Parkinson and Movement Disorder Society.

Volumetric changes and clinical trajectories in Parkinson's disease: a prospective multicentric study.

BACKGROUND: Longitudinal measures of structural brain changes using MRI in relation to clinical features and progression patterns in PD have been assessed in previous studies, but few were conducted in well-defined and large cohorts, including prospective clinical assessments of both motor and non-motor symptoms. OBJECTIVE: We aimed to identify brain volumetric changes characterizing PD patients, and determine whether regional brain volumetric characteristics at baseline can predict motor, psycho-behavioral and cognitive evolution at one year in a prospective cohort of PD patients. METHODS: In this multicentric 1 year longitudinal study, PD patients and healthy controls from the MPI-R2* cohort were assessed for demographical, clinical and brain volumetric characteristics. Distinct subgroups of PD patients according to motor, cognitive and psycho-behavioral evolution were identified at the end of follow-up. RESULTS: One hundred and fifty PD patients and 73 control subjects were included in our analysis. Over one year, there was no significant difference in volume variations between PD and control subjects, regardless of the brain region considered. However, we observed a reduction in posterior cingulate cortex volume at baseline in PD patients with motor deterioration at one year (p = 0.017). We also observed a bilateral reduction of the volume of the amygdala (p = 0.015 and p = 0.041) and hippocampus (p = 0.015 and p = 0.053) at baseline in patients with psycho-behavioral deterioration, regardless of age, dopaminergic treatment and center. CONCLUSION: Brain volumetric characteristics at baseline may predict clinical trajectories at 1 year in PD as posterior cingulate cortex atrophy was associated with motor decline, while amygdala and hippocampus atrophy were associated with psycho-behavioral decline.

Brain dysfunction in gait disorders of Caribbean atypical Parkinsonism and progressive supranuclear palsy patients: A comparative study.

INTRODUCTION: Gait disorders and falls occur early in progressive supranuclear palsy (PSP-RS) and Caribbean atypical parkinsonism (Caribbean AP). However, the link between these signs and brain lesions has never been explored in these patient populations. Here, we investigate and compare the imaging factors that relate to gait and balance disorders in Caribbean AP and PSP-RS patients. METHODS: We assessed gait and balance using clinical scales and gait recordings in 16 Caribbean AP and 15 PSP-RS patients and 17 age-matched controls. We measured the grey and white matter brain volumes on 3 T brain MRI images. We performed a principal component analysis (PCA) including all the data to determine differences and similarities between groups, and explore the relationship between gait disorders and brain volumes. RESULTS: Both Caribbean AP patients and PSP-RS have marked gait and balance disorders with similar severity. In both groups, gait and balance disorders were found to be most strongly related to structural changes in the lateral cerebellum, caudate nucleus, and fronto-parietal areas. In Caribbean AP patients, gait disorders were also related to additional changes in the cortex, including frontal, insular, temporal and cuneus lobes, whereas in PSP-RS patients, additional white matter changes involved the mesencephalon and parahippocampal gyrus. CONCLUSION: Gait and balance disorders in Caribbean AP patients are mainly related to dysfunction of cortical brain areas involved in visuo-sensorimotor processing and self-awareness, whereas these signs mainly result from premotor-brainstem-cerebellar network dysfunction in PSP-RS patients, brain areas involved in initiation and maintenance of locomotor pattern and postural adaptation.

Differences in Survival across Monogenic Forms of Parkinson's Disease.

OBJECTIVE: Survival of patients with monogenic Parkinson's disease may depend on the causative genes associated with the disease. In this study, we compare survival of patients with Parkinson's disease according to the presence of SNCA, PRKN, LRRK2, or GBA mutations. METHODS: Data from the French Parkinson Disease Genetics national multicenter cohort study were used. Patients with sporadic and familial Parkinson's disease were recruited between 1990 and 2021. Patients were genotyped for the presence of mutations in the SNCA, PRKN, LRRK2, or GBA genes. Vital status was collected from the National death register for participants born in France. Hazard ratios (HRs) and 95% confidence intervals (CIs) were computed using multivariable Cox proportional hazards regression. RESULTS: Of the 2,037 patients with Parkinson's disease, 889 had died after a follow-up of up to 30 years. Patients with PRKN (n = 100, HR = 0.41; p = 0.001) and LRRK2 mutations (n = 51, HR = 0.49; p = 0.023) had longer survival than those without any mutation, whereas patients with SNCA (n = 20, HR = 9.88; p < 0.001) or GBA mutations (n = 173, HR = 1.33; p = 0.048) had shorter survival. INTERPRETATION: Survival differs across genetic forms of Parkinson's disease, with higher mortality for patients with SNCA or GBA mutations, and lower mortality for those with PRKN or LRRK2 mutations. Differences in severity and disease progression among monogenic forms of Parkinson's disease likely explain these findings, which has important consequences for genetic counselling and choice of end points for future clinical trials for targeted therapies. ANN NEUROL 2023;94:123-132.

Neuromelanin-Sensitive Magnetic Resonance Imaging Changes in the Locus Coeruleus/Subcoeruleus Complex in Patients with Typical and Atypical Parkinsonism.

BACKGROUND: The locus coeruleus/subcoeruleus complex (LC/LsC) is a structure comprising melanized noradrenergic neurons. OBJECTIVE: To study the LC/LsC damage across Parkinson's disease (PD) and atypical parkinsonism in a large group of subjects. METHODS: We studied 98 healthy control subjects, 47 patients with isolated rapid eye movement sleep behavior disorder (RBD), 75 patients with PD plus RBD, 142 patients with PD without RBD, 19 patients with progressive supranuclear palsy (PSP), and 19 patients with multiple system atrophy (MSA). Twelve patients with MSA had proven RBD. LC/LsC signal intensity was derived from neuromelanin magnetic resonance imaging using automated software. RESULTS: The signal intensity was reduced in all parkinsonian syndromes compared with healthy control subjects, except in PD without RBD. The signal intensity decreased as age increased. Moreover, the signal intensity was lower in MSA than in isolated RBD and PD without RBD groups. In PD, the signal intensity correlated negatively with the percentage of REM sleep without atonia. There were no differences in signal intensity between PD plus RBD, PSP, and MSA. CONCLUSIONS: Neuromelanin signal intensity was reduced in all parkinsonian disorders, except in PD without RBD. The presence of RBD in parkinsonian disorders appears to be associated with lower neuromelanin signal intensity. Furthermore, lower LC/LsC signal changes in PSP could be partly caused by the effect of age. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

NigraNet: An automatic framework to assess nigral neuromelanin content in early Parkinson's disease using convolutional neural network.

BACKGROUND: Parkinson's disease (PD) demonstrates neurodegenerative changes in the substantia nigra pars compacta (SNc) using neuromelanin-sensitive (NM)-MRI. As SNc manual segmentation is prone to substantial inter-individual variability across raters, development of a robust automatic segmentation framework is necessary to facilitate nigral neuromelanin quantification. Artificial intelligence (AI) is gaining traction in the neuroimaging community for automated brain region segmentation tasks using MRI. OBJECTIVE: Developing and validating AI-based NigraNet, a fully automatic SNc segmentation framework allowing nigral neuromelanin quantification in patients with PD using NM-MRI. METHODS: We prospectively included 199 participants comprising 144 early-stage idiopathic PD patients (disease duration = 1.5 ± 1.0 years) and 55 healthy volunteers (HV) scanned using a 3 Tesla MRI including whole brain T1-weighted anatomical imaging and NM-MRI. The regions of interest (ROI) were delineated in all participants automatically using NigraNet, a modified U-net, and compared to manual segmentations performed by two experienced raters. The SNc volumes (Vol), volumes corrected by total intracranial volume (Cvol), normalized signal intensity (NSI) and contrast-to-noise ratio (CNR) were computed. One-way GLM-ANCOVA was performed while adjusting for age and sex as covariates. Diagnostic performance measurement was assessed using the receiver operating characteristic (ROC) analysis. Inter and intra-observer variability were estimated using Dice similarity coefficient (DSC). The agreements between methods were tested using intraclass correlation coefficient (ICC) based on a mean-rating, two-way, mixed-effects model estimates for absolute agreement. Cronbach's alpha and Bland-Altman plots were estimated to assess inter-method consistency. RESULTS: Using both methods, Vol, Cvol, NSI and CNR measurements differed between PD and HV with an effect of sex for Cvol and CNR. ICC values between the methods demonstrated optimal agreement for Cvol and CNR (ICC > 0.9) and high reproducibility (DSC: 0.80) was also obtained. The SNc measurements also showed good to excellent consistency values (Cronbach's alpha > 0.87). Bland-Altman plots of agreement demonstrated no association of SNc ROI measurement differences between the methods and ROI average measurements while confirming that 95 % of the data points were ranging between the limits of mean difference (d ± 1.96xSD). Percentage changes between PD and HV were -27.4 % and -17.7 % for Vol, -30.0 % and -22.2 % for Cvol, -15.8 % and -14.4 % for NSI, -17.1 % and -16.0 % for CNR for automatic and manual measurements respectively. Using automatic method, in the entire dataset, we obtained the areas under the ROC curve (AUC) of 0.83 for Vol, 0.85 for Cvol, 0.79 for NSI and 0.77 for CNR whereas in the training dataset of 0.96 for Vol, 0.95 for Cvol, 0.85 for NSI and 0.85 for CNR. Disease duration correlated negatively with NSI of the patients for both the automatic and manual measurements. CONCLUSIONS: We presented an AI-based NigraNet framework that utilizes a small MRI training dataset to fully automatize the SNc segmentation procedure with an increased precision and more reproducible results. Considering the consistency, accuracy and speed of our approach, this study could be a crucial step towards the implementation of a time-saving non-rater dependent fully automatic method for studying neuromelanin changes in clinical settings and large-scale neuroimaging studies.

Intrasubject subcortical quantitative referencing to boost MRI sensitivity to Parkinson's disease.

Several postmortem studies have shown iron accumulation in the substantia nigra of Parkinson's disease patients. Iron concentration can be estimated via MRI-R2∗ mapping. To assess the changes in R2∗ occurring in Parkinson's disease patients compared to controls, a multicentre transversal study was carried out on a large cohort of Parkinson's disease patients (n = 163) with matched controls (n = 82). In this study, 44 patients and 11 controls were removed due to motion artefacts, 21 patient and 6 controls to preserve matching. Thus, 98 patients and 65 age and sex-matched healthy subjects were selected with enough image quality. The study was conducted on patients with early to late stage Parkinson's disease. The images were acquired at 3Tesla in 12 clinical centres. R2∗ values were measured in subcortical regions of interest (substantia nigra, red nucleus, striatum, globus pallidus externus and globus pallidus internus) contralateral (dominant side) and ipsilateral (non dominant side) to the most clinically affected hemibody. As the observed inter-subject R2∗ variability was significantly higher than the disease effect, an original strategy (intrasubject subcortical quantitative referencing, ISQR) was developed using the measurement of R2∗ in the red nucleus as an intra-subject reference. R2∗ values significantly increased in Parkinson's disease patients when compared with controls; in the substantia nigra (SN) in the dominant side (D) and in the non dominant side (ND), respectively (PSN_D and PSN_ND < 0.0001). After stratification into four subgroups according to the disease duration, no significant R2∗ difference was found in all regions of interest when comparing Parkinson's disease subgroups. By applying our ISQR strategy, R2(ISQR)∗ values significantly increased in the substantia nigra (PSN_D and PSN_ND < 0.0001) when comparing all Parkinson's disease patients to controls. R2(ISQR)∗ values in the substantia nigra significantly increased with the disease duration (PSN_D = 0.01; PSN_ND = 0.03) as well as the severity of the disease (Hoehn & Yahr scale <2 and ≥ 2, PSN_D = 0.02). Additionally, correlations between R2(ISQR)∗ and clinical features, mainly related to the severity of the disease, were found. Our results support the use of ISQR to reduce variations not directly related to Parkinson's disease, supporting the concept that ISQR strategy is useful for the evaluation of Parkinson's disease.

Relationship between Substantia Nigra Neuromelanin Imaging and Dual Alpha-Synuclein Labeling of Labial Minor in Salivary Glands in Isolated Rapid Eye Movement Sleep Behavior Disorder and Parkinson's Disease.

We investigated the presence of misfolded alpha-Synuclein (α-Syn) in minor salivary gland biopsies in relation to substantia nigra pars compacta (SNc) damage measured using magnetic resonance imaging in patients with isolated rapid eye movement sleep behavior disorder (iRBD) and Parkinson's disease (PD) as compared to healthy controls. Sixty-one participants (27 PD, 16 iRBD, and 18 controls) underwent a minor salivary gland biopsy and were scanned using a 3 Tesla MRI. Deposits of α-Syn were found in 15 (55.6%) PD, 7 (43.8%) iRBD, and 7 (38.9%) controls using the anti-aggregated α-Syn clone 5G4 antibody and in 4 (14.8%) PD, 3 (18.8%) iRBD and no control using the purified mouse anti-α-Syn clone 42 antibody. The SNc damages obtained using neuromelanin-sensitive imaging did not differ between the participants with versus without α-Syn deposits (irrespective of the antibodies and the disease group). Our study indicated that the α-Syn detection in minor salivary gland biopsies lacks sensitivity and specificity and does not correlate with the SNc damage, suggesting that it cannot be used as a predictive or effective biomarker for PD.

Machine Learning-Based Prediction of Impulse Control Disorders in Parkinson's Disease From Clinical and Genetic Data.

Goal: Impulse control disorders (ICDs) are frequent non-motor symptoms occurring during the course of Parkinson's disease (PD). The objective of this study was to estimate the predictability of the future occurrence of these disorders using longitudinal data, the first study using cross-validation and replication in an independent cohort. Methods: We used data from two longitudinal PD cohorts (training set: PPMI, Parkinson's Progression Markers Initiative; test set: DIGPD, Drug Interaction With Genes in Parkinson's Disease). We included 380 PD subjects from PPMI and 388 PD subjects from DIGPD, with at least two visits and with clinical and genetic data available, in our analyses. We trained three logistic regressions and a recurrent neural network to predict ICDs at the next visit using clinical risk factors and genetic variants previously associated with ICDs. We quantified performance using the area under the receiver operating characteristic curve (ROC AUC) and average precision. We compared these models to a trivial model predicting ICDs at the next visit with the status at the most recent visit. Results: The recurrent neural network (PPMI: 0.85 [0.80 - 0.90], DIGPD: 0.802 [0.78 - 0.83]) was the only model to be significantly better than the trivial model (PPMI: ROC AUC = 0.75 [0.69 - 0.81]; DIGPD: 0.78 [0.75 - 0.80]) on both cohorts. We showed that ICDs in PD can be predicted with better accuracy with a recurrent neural network model than a trivial model. The improvement in terms of ROC AUC was higher on PPMI than on DIGPD data, but not clinically relevant in both cohorts. Conclusions: Our results indicate that machine learning methods are potentially useful for predicting ICDs, but further works are required to reach clinical relevance.

Deep Learning-Based Neuromelanin MRI Changes of Isolated REM Sleep Behavior Disorder.

BACKGROUND: Isolated REM sleep behavior disorder (iRBD) is considered a prodromal stage of parkinsonism. Neurodegenerative changes in the substantia nigra pars compacta (SNc) in parkinsonism can be detected using neuromelanin-sensitive MRI. OBJECTIVE: To investigate SNc neuromelanin changes in iRBD patients using fully automatic segmentation. METHODS: We included 47 iRBD patients, 134 early Parkinson's disease (PD) patients and 55 healthy volunteers (HVs) scanned at 3 Tesla. SNc regions-of-interest were delineated automatically using convolutional neural network. SNc volumes, volumes corrected by total intracranial volume, signal-to-noise ratio (SNR) and contrast-to-noise ratio were computed. One-way general linear models (GLM) analysis of covariance (ANCOVA) was conducted while adjusting for age and sex. RESULTS: All SNc measurements differed significantly between the three groups (except SNR in iRBD). Changes in iRBD were intermediate between those in PD and HVs. CONCLUSIONS: Using fully automated SNc segmentation method and neuromelanin-sensitive imaging, iRBD patients showed neurodegenerative changes in the SNc at a lower level than in PD patients. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Functional MAOB Gene Intron 13 Polymorphism Predicts Dyskinesia in Parkinson's Disease.

Identification of individual risk factors for motor complications in Parkinson's disease (PD) can help to guide personalised medical treatment, particularly since treatment options are still limited. To determine whether common functional gene polymorphisms in the dopamine metabolism predict the onset of motor complications in PD, we performed a retrospective, observer-blinded follow-up study of 30 PD patients who underwent genotyping of dopa-decarboxylase (DDC; rs921451), monoamine oxidase B (MAOB; rs1799836), catechol-O-methyltransferase (COMT; rs4680), and dopamine transporter (DAT; variable number tandem repeat) polymorphisms. Onset of wearing-off and dyskinesias was determined by blinded clinical assessments. Predictive values of genotypes for motor complications were evaluated using Cox proportional hazard models. During a median follow-up time of 11.6 years, 23 (77%) of 30 PD patients developed wearing-off, 16 (53%) dyskinesias, and 23 (77%) any motor complication. The MAOB (rs1799836) polymorphism predicted development of dyskinesias with MAOB CC/(C)/CT genotypes (resulting in low/intermediate brain enzyme activity) being associated with lower hazard ratios (unadjusted HR [95% CI]: 0.264 [0.089-0.787]; p=0.012; adjusted HR [95% CI]: 0.142 [0.039-0.520]; p=0.003) than MAOB TT/(T) genotypes (resulting in high brain enzyme activity). DDC (rs921451), COMT (rs4680), and DAT (VNTR) polymorphisms were not predictive of motor complications. Together, the MAOB (rs1799836) polymorphism predicts the development of dyskinesias in PD patients. Our results need confirmation in larger cohorts. If confirmed, individual assessment of this polymorphism might be helpful for early risk stratification and could comprise a step towards patient-tailored therapeutic strategies to prevent or delay motor complications in the course of PD.

Voice characteristics from isolated rapid eye movement sleep behavior disorder to early Parkinson's disease.

BACKGROUND: Speech disorders are amongst the first symptoms to appear in Parkinson's disease (PD). OBJECTIVES: We aimed to characterize PD voice signature from the prodromal stage (isolated rapid eye movement sleep behavior disorder, iRBD) to early PD using an automated acoustic analysis and compare male and female patients. We carried out supervised learning classifications to automatically detect patients using voice only. METHODS: Speech samples were acquired in 256 French speakers (117 participants with early PD, 41 with iRBD, and 98 healthy controls), with a professional quality microphone, a computer microphone and their own telephone. High-level features related to prosody, phonation, speech fluency and rhythm abilities were extracted. Group analyses were performed to determine the most discriminant features, as well as the impact of sex, vocal tasks, and microphone type. These speech features were used as inputs of a support vector machine and were combined with classifiers using low-level features. RESULTS: PD related impairments were found in prosody, pause durations and rhythmic abilities, from the prodromal stage. These alterations were more pronounced in men than in women. Early PD detection was achieved with a balanced accuracy of 89% in males and 70% in females. Participants with iRBD were detected with a balanced accuracy of 63% (reaching 70% in the subgroup with mild motor symptoms). CONCLUSION: This study provides new insight in the characterization of sex-dependent early PD speech impairments, and demonstrates the valuable benefit of including automated voice analysis in future diagnostic procedures of prodromal PD.

Parkinson Disease and Subthalamic Nucleus Deep Brain Stimulation: Cognitive Effects in GBA Mutation Carriers.

OBJECTIVE: This study was undertaken to compare the rate of change in cognition between glucocerebrosidase (GBA) mutation carriers and noncarriers with and without subthalamic nucleus deep brain stimulation (STN-DBS) in Parkinson disease. METHODS: Clinical and genetic data from 12 datasets were examined. Global cognition was assessed using the Mattis Dementia Rating Scale (MDRS). Subjects were examined for mutations in GBA and categorized as GBA carriers with or without DBS (GBA+DBS+, GBA+DBS-), and noncarriers with or without DBS (GBA-DBS+, GBA-DBS-). GBA mutation carriers were subcategorized according to mutation severity (risk variant, mild, severe). Linear mixed modeling was used to compare rate of change in MDRS scores over time among the groups according to GBA and DBS status and then according to GBA severity and DBS status. RESULTS: Data were available for 366 subjects (58 GBA+DBS+, 82 GBA+DBS-, 98 GBA-DBS+, and 128 GBA-DBS- subjects), who were longitudinally followed (range = 36-60 months after surgery). Using the MDRS, GBA+DBS+ subjects declined on average 2.02 points/yr more than GBA-DBS- subjects (95% confidence interval [CI] = -2.35 to -1.69), 1.71 points/yr more than GBA+DBS- subjects (95% CI = -2.14 to -1.28), and 1.49 points/yr more than GBA-DBS+ subjects (95% CI = -1.80 to -1.18). INTERPRETATION: Although not randomized, this composite analysis suggests that the combined effects of GBA mutations and STN-DBS negatively impact cognition. We advise that DBS candidates be screened for GBA mutations as part of the presurgical decision-making process. We advise that GBA mutation carriers be counseled regarding potential risks associated with STN-DBS so that alternative options may be considered. ANN NEUROL 2022;91:424-435.