Mild cognitive impairment among LRRK2 and GBA1 patients with Parkinson's disease.

BACKGROUND: Mild cognitive impairment (MCI) is common in Parkinson's disease (PD). We aimed to assess the incidence of MCI among patients with PD, carriers of mutations in LRRK2 and GBA1 genes, based on the movement disorder society (MDS) criteria for the diagnosis of MCI in early-stage PD. METHODS: Patients with PD were included if they scored ≤2 on the Hoehn and Yahr and ≤6 years since motor symptom onset. A group of age and gender matched healthy adults served as controls. A neuropsychological cognitive battery was used covering five cognitive domains (executive functions, working memory, memory, visuospatial and language). MCI was explored while applying two methods (level I and II). Frequency of MCI was assessed in comparison between groups. RESULTS: 70 patients with idiopathic PD (iPD) (68 % males), 42 patients with LRRK2-PD (61 % males), 83 patients with GBA1-PD (63 % males) and 132 age and gender matched controls (61 % males), participated in this study. PD groups were similar in clinical characteristics. Level I criteria were positive in 57.5 % of iPD, 43 % of LRRK2-PD and 63.4 % of the GBA1-PD (p = 0.071). Level II criteria was met by 39 % of iPD, 14 % LRRK2-PD and 41 % of GBA1-PD (p < 0.001), when using a 2 standard-deviation (SD) threshold. GBA1-PD and iPD showed impairments on multiple domains even in the more conservative 2 SD, reflecting MCI. CONCLUSIONS: The majority of our PD cohort was classified as MCI when assessed with strict criteria. GBA1-PD and iPD showed a more widespread pattern of MCI compared with LRRK2-PD.

Validity of the Short Weekly Calendar Planning Activity in patients with Parkinson disease and nonmanifesting LRRK2 and GBA carriers.

BACKGROUND AND PURPOSE: Subtle executive dysfunction is common in people newly diagnosed with Parkinson disease (PD), even when general cognitive abilities are intact. This study examined the Short Weekly Calendar Planning Activity (WCPA-10)'s known-group construct validity, comparing persons with PD to healthy controls (HCs) and nonmanifesting carriers of LRRK2 and GBA gene mutations to HCs. Additionally, convergent and ecological validity was examined. METHODS: The study included 73 participants: 22 with idiopathic PD (iPD) who do not carry any of the founder GBA mutations or LRRK2-G2019S, 29 nonmanifesting carriers of the G2019S-LRRK2 (n = 14) and GBA (n = 15) mutations, and 22 HCs. Known-group validity was determined using the WCPA-10, convergent validity by also using the Montreal Cognitive Assessment (MoCA) and Color Trails Test (CTT), and ecological validity by using the WCPA-10, Schwab and England Activities of Daily Living Scale (SE ADL), and Physical Activity Scale for the Elderly (PASE). RESULTS: Known-group validity of the WCPA-10 was established for the iPD group only; they followed fewer rules (p = 0.020), were slower (p = 0.003) and less efficient (p = 0.001), used more strategies (p = 0.017) on the WCPA-10, and achieved significantly lower CTT scores (p < 0.001) than the HCs. The nonmanifesting carriers and HCs were similar on all cognitive tests. Convergent and ecological validity of the WCPA-10 were partially established, with few correlations between WCPA-10 outcome measures and the MoCA (r = 0.50, r = 0.41), CTT-2 (r = 0.43), SE ADL (r = 0.41), and PASE (r = 0.54, r = 0.46, r = 0.31). CONCLUSIONS: This study affirms the known-group validity for most (four) WCPA-10 scores and partially confirms its convergent and ecological validity for PD.

A wearable sensor and machine learning estimate step length in older adults and patients with neurological disorders.

Step length is an important diagnostic and prognostic measure of health and disease. Wearable devices can estimate step length continuously (e.g., in clinic or real-world settings), however, the accuracy of current estimation methods is not yet optimal. We developed machine-learning models to estimate step length based on data derived from a single lower-back inertial measurement unit worn by 472 young and older adults with different neurological conditions, including Parkinson's disease and healthy controls. Studying more than 80,000 steps, the best model showed high accuracy for a single step (root mean square error, RMSE = 6.08 cm, ICC(2,1) = 0.89) and higher accuracy when averaged over ten consecutive steps (RMSE = 4.79 cm, ICC(2,1) = 0.93), successfully reaching the predefined goal of an RMSE below 5 cm (often considered the minimal-clinically-important-difference). Combining machine-learning with a single, wearable sensor generates accurate step length measures, even in patients with neurologic disease. Additional research may be needed to further reduce the errors in certain conditions.

Identifying Subtle Motor Deficits Before Parkinson's Disease is Diagnosed: What to Look for?

Motor deficits typical of Parkinson's disease (PD), such as gait and balance disturbances, tremor, reduced arm swing and finger movement, and voice and breathing changes, are believed to manifest several years prior to clinical diagnosis. Here we describe the evidence for the presence and progression of motor deficits in this pre-diagnostic phase in order to provide suggestions for the design of future observational studies for an effective, quantitatively oriented investigation. On the one hand, these future studies must detect these motor deficits in as large (potentially, population-based) cohorts as possible with high sensitivity and specificity. On the other hand, they must describe the progression of these motor deficits in the pre-diagnostic phase as accurately as possible, to support the testing of the effect of pharmacological and non-pharmacological interventions. Digital technologies and artificial intelligence can substantially accelerate this process.

Digital Mobility Measures: A Window into Real-World Severity and Progression of Parkinson's Disease.

BACKGROUND: Real-world monitoring using wearable sensors has enormous potential for assessing disease severity and symptoms among persons with Parkinson's disease (PD). Many distinct features can be extracted, reflecting multiple mobility domains. However, it is unclear which digital measures are related to PD severity and are sensitive to disease progression. OBJECTIVES: The aim was to identify real-world mobility measures that reflect PD severity and show discriminant ability and sensitivity to disease progression, compared to the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scale. METHODS: Multicenter real-world continuous (24/7) digital mobility data from 587 persons with PD and 68 matched healthy controls were collected using an accelerometer adhered to the lower back. Machine learning feature selection and regression algorithms evaluated associations of the digital measures using the MDS-UPDRS (I-III). Binary logistic regression assessed discriminatory value using controls, and longitudinal observational data from a subgroup (n = 33) evaluated sensitivity to change over time. RESULTS: Digital measures were only moderately correlated with the MDS-UPDRS (part II-r = 0.60 and parts I and III-r = 0.50). Most associated measures reflected activity quantity and distribution patterns. A model with 14 digital measures accurately distinguished recently diagnosed persons with PD from healthy controls (81.1%, area under the curve: 0.87); digital measures showed larger effect sizes (Cohen's d: [0.19-0.66]), for change over time than any of the MDS-UPDRS parts (Cohen's d: [0.04-0.12]). CONCLUSIONS: Real-world mobility measures are moderately associated with clinical assessments, suggesting that they capture different aspects of motor capacity and function. Digital mobility measures are sensitive to early-stage disease and to disease progression, to a larger degree than conventional clinical assessments, demonstrating their utility, primarily for clinical trials but ultimately also for clinical care. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Differences in EEG Event-Related Potentials during Dual Task in Parkinson's Disease Carriers and Non-Carriers of the G2019S-LRRK2 Mutation.

BACKGROUND: The G2019S-LRRK2 gene mutation is a common cause of hereditary Parkinson's disease (PD), associated with a higher frequency of the postural instability gait difficulty (PIGD) motor phenotype yet with preserved cognition. This study investigated neurophysiological changes during motor and cognitive tasks in PD patients with and without the G2019S-LRRK2 mutation. METHODS: 33 iPD patients and 22 LRRK2-PD patients performed the visual Go/NoGo task (VGNG) during sitting (single-task) and walking (dual-task) while wearing a 64-channel EEG cap. Event-related potentials (ERP) from Fz and Pz, specifically N200 and P300, were extracted and analyzed to quantify brain activity patterns. RESULTS: The LRRK2-PD group performed better in the VGNG than the iPD group (group*task; p = 0.05). During Go, the iPD group showed reduced N2 amplitude and prolonged N2 latency during walking, whereas the LRRK2-PD group showed only shorter latency (group*task p = 0.027). During NoGo, opposite patterns emerged; the iPD group showed reduced N2 and increased P3 amplitudes during walking while the LRRK2-PD group demonstrated increased N2 and reduced P3 (N2: group*task, p = 0.010, P3: group*task, p = 0.012). CONCLUSIONS: The LRRK2-PD group showed efficient early cognitive processes, reflected by N2, resulting in greater neural synchronization and prominent ERPs. These processes are possibly the underlying mechanisms for the observed better cognitive performance as compared to the iPD group. As such, future applications of intelligent medical sensing should be capable of capturing these electrophysiological patterns in order to enhance motor-cognitive functions.

Overnight Distribution of REM Sleep Features in People with Parkinson's Disease (PD) and Non-PD Controls.

BACKGROUND: Rapid eye movement (REM) sleep behavior disorder (RBD) is a leading predictor of Parkinson's disease (PD). Diagnosis is performed in the sleep laboratory by detecting pathological REM sleep without atonia (RSWA). The evidence on the overnight distribution of RSWA% is conflicting. OBJECTIVE: To investigate the temporal distribution of the number of ocular movements per REM sleep minute (REM density), and RSWA% in people with PD and non-PD controls. METHODS: All participants underwent a single overnight evaluation in a sleep laboratory. Clinical evaluation was performed on a separate day. REM density and RSWA% were compared between PD and controls both across four sleep periods and individual REM cycles. RESULTS: A total of 51 participants with recorded RSWA in polysomnography laboratory were included, 28 with PD aged 64±9 years with a disease duration of 3.3±2.9 years, and 23 controls aged 55±8 years. People with PD had lower REM density and higher RSWA% compared to controls. As expected, REM density was higher towards the morning. In contrast, RSWA% was equally distributed across the night, for both PD and controls. CONCLUSIONS: PD pathology affects REM sleep features, but not the overnight distribution of those features. While REM density increased towards the end of the night, RSWA% was equally distributed across the night for both PD and controls. Our findings have clinical implications for diagnosing RBD, as quantification of RSWA% in any sleep cycle is sufficient for reliably evaluating total RSWA% and reduced REM density may be a marker of PD.

Imaging Markers in Genetic Forms of Parkinson's Disease.

Parkinson's disease (PD) is a complex neurodegenerative disorder characterized by motor symptoms such as bradykinesia, rigidity, and resting tremor. While the majority of PD cases are sporadic, approximately 15-20% of cases have a genetic component. Advances in neuroimaging techniques have provided valuable insights into the pathophysiology of PD, including the different genetic forms of the disease. This literature review aims to summarize the current state of knowledge regarding neuroimaging findings in genetic PD, focusing on the most prevalent known genetic forms: mutations in the GBA1, LRRK2, and Parkin genes. In this review, we will highlight the contributions of various neuroimaging modalities, including positron emission tomography (PET), single-photon emission computed tomography (SPECT), and magnetic resonance imaging (MRI), in elucidating the underlying pathophysiological mechanisms and potentially identifying candidate biomarkers for genetic forms of PD.

Bio-potential noise of dry printed electrodes: physiology versus the skin-electrode impedance.

Objective. To explore noise characteristics and the effect physiological activity has on the link between impedance and noise.Approach. Dry-printed electrodes are emerging as a new and exciting technology for skin electro-physiology. Such electrode arrays offer many advantages including user convenience, quick placement, and high resolution. Here we analyze extensive electro-physiological data recorded from the arm and the face to study and quantify the noise of dry electrodes, and to characterize the link between noise and impedance. In particular, we studied the effect of the physiological state of the subject (e.g. rapid eye movement sleep) on noise.Main results. We show that baseline noise values extracted from dry electrodes in the arm are in agreement with the Nyquist equation. In the face, on the other hand, the measured noise values were higher than the values predicted by the Nyquist equation. In addition, we studied how different electrode properties affect performances, including electrode size, shape, and material properties.Significance. Altogether, the results presented here provide a basis for understanding dry electrode performances and substantiate their great potential in electro-physiological investigations.

Task-Related Reorganization of Cognitive Network in Parkinson's Disease Using Electrophysiology.

BACKGROUND: Cognitive deficits in Parkinson's disease (PD) patients are well described, however, their underlying neural mechanisms as assessed by electrophysiology are not clear. OBJECTIVES: To reveal specific neural network alterations during the performance of cognitive tasks in PD patients using electroencephalography (EEG). METHODS: Ninety participants, 60 PD patients and 30 controls underwent EEG recording while performing a GO/NOGO task. Source localization of 16 regions of interest known to play a pivotal role in GO/NOGO task was performed to assess power density and connectivity within this cognitive network. The connectivity matrices were evaluated using a graph-theory approach that included measures of cluster-coefficient, degree, and global-efficiency. A mixed-model analysis, corrected for age and levodopa equivalent daily dose was performed to examine neural changes between PD patients and controls. RESULTS: PD patients performed worse in the GO/NOGO task (P < 0.001). The power density was higher in δ and θ bands, but lower in α and ß bands in PD patients compared to controls (interaction group × band: P < 0.001), indicating a general slowness within the network. Patients had more connections within the network (P < 0.034) than controls and these were used for graph-theory analysis. Differences between groups in graph-theory measures were found only in cluster-coefficient, which was higher in PD compared to controls (interaction group × band: P < 0.001). CONCLUSIONS: Cognitive deficits in PD are underlined by alterations at the brain network level, including higher δ and θ activity, lower α and ß activity, increased connectivity, and segregated network organization. These findings may have important implications on future adaptive deep brain stimulation. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Novel variants in genes related to vesicle-mediated-transport modify Parkinson's disease risk.

OBJECTIVES: VPS35 and VPS13 have been associated with Parkinson's disease (PD), and their shared phenotype in yeast when reduced in function is abnormal vacuolar transport. We aim to test if additional potentially deleterious variants in other genes that share this phenotype can modify the risk for PD. METHODS: 77 VPS and VPS-related genes were analyzed using whole-genome-sequencing data from 202 PD patients of Ashkenazi Jewish (AJ) ancestry. Filtering was done based on quality and functionality scores. Ten variants in nine genes were further genotyped in 1200 consecutively recruited unrelated AJ-PD patients, and allele frequencies and odds ratio calculated compared to gnomAD-AJ-non-neuro database, in un-stratified (n = 1200) and stratified manner (LRRK2-G2019S-PD patients (n = 145), GBA-PD patients (n = 235), and non-carriers of these mutations (NC, n = 787)). RESULTS: Five variants in PIK3C3, VPS11, AP1G2, HGS and VPS13D were significantly associated with PD-risk. PIK3C3-R768W showed a significant association in an un-stratified (all PDs) analysis, as well as in stratified (LRRK2, GBA, and NC) analyses (Odds ratios = 2.71, 5.32, 3.26. and 2.19 with p = 0.0015, 0.002, 0.0287, and 0.0447, respectively). AP1G2-R563W was significantly associated in LRRK2-carriers (OR = 3.69, p = 0.006) while VPS13D-D2932N was significantly associated in GBA-carriers (OR = 5.45, p = 0.0027). VPS11-C846G and HGS-S243Y were significantly associated in NC (OR = 2.48 and 2.06, with p = 0.022 and 0.0163, respectively). CONCLUSIONS: Variants in genes involved in vesicle-mediated protein transport and recycling pathways, including autophagy and mitophagy, may differentially modify PD-risk in LRRK2-carriers, GBA carriers, or NC. Specifically, PIK3C3-R768W is a PD-risk allele, with the highest effect size in LRRK2-G2019S carriers. These results suggest oligogenic effect that may depends on the genetic background of the patient. An unbiased burden of mutations approach in these genes should be evaluated in additional PD and control groups. The mechanisms by which these novel variants interact and increase PD-risk should be researched in depth for better tailoring therapeutic intervention for PD prevention or slowing disease progression.

Association Between Frailty and Free-Living Walking Performance in People With Multiple Sclerosis.

OBJECTIVE: The purpose of this study was to examine the association between frailty and the quantity and quality of free-living walking and the mediating effect of frailty on the relationship between disability and walking performance in people with multiple sclerosis (MS). METHODS: Ninety-nine people with relapsing-remitting MS (mean age = 49.3 [SD = 9.8] years; 73.7% women; Expanded Disability Status Scale [EDSS] score range = 2.0-6.0) wore a triaxial accelerometer for 7 days. Recorded measures reflected the quantity (daily step counts, number of 30-second walking bouts, and signal vector magnitude [SVM]) and quality (gait speed, step cadence, step and stride regularity, and sample entropy) of walking. For each walking quality measure, the typical (median), best (90th percentile), and worst (10th percentile) values were calculated. Frailty was evaluated through a 38-item frailty index. RESULTS: Participants were classified as not frail (n = 31), moderately frail (n = 34), and severely frail (n = 34) on the basis of established procedures. Patients who were moderately and severely frail exhibited poorer performance in all measures of walking quantity and quality, except for sample entropy, than individuals who were not frail. No differences in free-living walking performance were observed between the moderately and severely frail groups. Frailty did not mediate the relationship between disability (EDSS) and measures of walking quality. Conversely, frailty had a significant mediating effect on the relationship between disability and measures of walking quantity, such as daily step counts (indirect effect: b = -220.42, 95% CI = -452.03 to -19.65) and SVM (indirect effect: b = -1.00, 95% CI = -1.86 to -0.30). CONCLUSION: Frailty is associated with poorer free-living walking performance in people with MS. The study findings suggest that frailty, rather than disability, may be primarily responsible for the lower amount of physical activity performed by people with MS in the real world. IMPACT: The observation that frailty and disability are differently related to measures of walking quality and quantity underscores the importance of a targeted approach to rehabilitation in people with MS.

Decreased aperiodic neural activity in Parkinson's disease and dementia with Lewy bodies.

Neural oscillations and signal complexity have been widely studied in neurodegenerative diseases, whereas aperiodic activity has not been explored yet in those disorders. Here, we assessed whether the study of aperiodic activity brings new insights relating to disease as compared to the conventional spectral and complexity analyses. Eyes-closed resting-state electroencephalography (EEG) was recorded in 21 patients with dementia with Lewy bodies (DLB), 28 patients with Parkinson's disease (PD), 27 patients with mild cognitive impairment (MCI) and 22 age-matched healthy controls. Spectral power was differentiated into its oscillatory and aperiodic components using the Irregularly Resampled Auto-Spectral Analysis. Signal complexity was explored using the Lempel-Ziv algorithm (LZC). We found that DLB patients showed steeper slopes of the aperiodic power component with large effect sizes compared to the controls and MCI and with a moderate effect size compared to PD. PD patients showed steeper slopes with a moderate effect size compared to controls and MCI. Oscillatory power and LZC differentiated only between DLB and other study groups and were not sensitive enough to detect differences between PD, MCI, and controls. In conclusion, both DLB and PD are characterized by alterations in aperiodic dynamics, which are more sensitive in detecting disease-related neural changes than the traditional spectral and complexity analyses. Our findings suggest that steeper aperiodic slopes may serve as a marker of network dysfunction in DLB and PD features.

Monitoring sleep stages with a soft electrode array: Comparison against vPSG and home-based detection of REM sleep without atonia.

Sleep disorders are symptomatic hallmarks of a variety of medical conditions. Accurately identifying the specific stage in which these disorders occur is particularly important for the correct diagnosis of non-rapid eye movement and rapid eye movement parasomnias. In-lab polysomnography suffers from limited availability and does not reflect habitual sleep conditions, which is especially important in older adults and those with neurodegenerative diseases. We aimed to explore the feasibility and validity of a new wearable system for accurately measuring sleep at home. The system core technology is soft, printed dry electrode arrays and a miniature data acquisition unit with a cloud-based data storage for offline analysis. The positions of the electrodes allow manual scoring following the American Association of Sleep Medicine guidelines. Fifty participants (21 healthy subjects, mean age 56.6 ± 8.4 years; and 29 patients with Parkinson's disease, 65.4 ± 7.6 years) underwent a polysomnography evaluation with parallel recording with the wearable system. Total agreement between the two systems reached Cohen's kappa (k) of 0.688 with agreement in each stage of: wake k = 0.701; N1 = 0.224; N2 = 0.584; N3 = 0.410; and rapid eye movement = 0.723. Moreover, the system reliably detected rapid eye movement sleep without atonia with a sensitivity of 85.7%. Additionally, a comparison between sleep as measured in the sleep lab with data collected from a night at home showed significantly lower wake after sleep onset at home. The results demonstrate that the system is valid, accurate and allows for the exploration of sleep at home. This new system offers an opportunity to help detect sleep disorders on a larger scale than possible today, fostering better care.

Variants in PSMB9 and FGR differentially affect Parkinson's disease risk in GBA and LRRK2 mutation carriers.

INTRODUCTION: Recent studies found an association between Parkinson's disease (PD) and alterations in the innate immune system. However, whether the involvement of this system in two of the known genetic forms of PD, GBA-PD and LRRK2-PD, and in patients who do not carry these mutations is different, is yet to be determined. We aimed to test if genetic variations in the innate immune genes are differentially associated with PD in these subgroups. METHODS: Innate immune genes were identified and classified into sub-lists according to Reactome pathways. Whole-genome-sequencing (WGS) was performed on 201 unrelated Ashkenazi-Jewish (AJ) PD patients including 104 GBA-PD, 32 LRRK2-PD, and 65 non-carriers-PD (NC-PD). To identify genes with different burden between these subgroups of PD, gene-based Sequence kernel association optimal unified test (SKAT-O) analysis was performed on innate immune pathways. Candidate variants within the significant genes were further genotyped in a cohort of 1200 unrelated, consecutively recruited, AJ-PD patients, and to evaluate their association with PD-risk their allele frequencies were compared to AJ-non-neuro cases in gnomAD database, in a stratified and un-stratified manner. RESULTS: SKAT-O analysis showed significantly different burden for PSMB9 (GBA-PD versus NC-PD) and FGR (GBA-PD versus LRRK2-PD). Two candidate variants in PSMB9 showed an association with GBA-PD-risk and NC-PD-risk while one FGR variant showed an association with LRRK2-PD-risk. CONCLUSION: Our data supports differential involvement of innate immunity risk alleles in PD and emphasizes the differences between the GBA- and LRRK2-PD subgroups.

A novel performance scoring quantification framework for stress test set-ups.

Stress tests, e.g., the cardiac stress test, are standard clinical screening tools aimed to unmask clinical pathology. As such stress tests indirectly measure physiological reserves. The term reserve has been developed to account for the dis-junction, often observed, between pathology and clinical manifestation. It describes a physiological capacity that is utilized in demanding situations. However, developing a new and reliable stress test based screening tool is complex, prolonged, and relies extensively on domain knowledge. We propose a novel distributional-free machine-learning framework, the Stress Test Performance Scoring (STEPS) framework, to model expected performance in a stress test. A performance scoring function is trained with measures taken during the performance in a given task while exploiting information regarding the stress test set-up and subjects' medical state. Multiple ways of aggregating performance scores at different stress levels are suggested and are examined with an extensive simulation study. When applied to a real-world data example, an AUC of 84.35[95%CI: 70.68 - 95.13] was obtained for the STEPS framework to distinguish subjects with neurodegeneration from controls. In summary, STEPS improved screening by exploiting existing domain knowledge and state-of-the-art clinical measures. The STEPS framework can ease and speed up the production of new stress tests.

The natural history study of preclinical genetic Creutzfeldt-Jakob Disease (CJD): a prospective longitudinal study protocol.

BACKGROUND: Creutzfeldt-Jakob Disease (CJD) is the most common prion disease in humans causing a rapidly progressive neurological decline and dementia and is invariably fatal. The familial forms (genetic CJD, gCJD) are caused by mutations in the PRNP gene encoding for the prion protein (PrP). In Israel, there is a large cluster of gCJD cases, carriers of an E200K mutation in the PRNP gene, and therefore the largest population of at-risk individuals in the world. The mutation is not necessarily sufficient for the formation and accumulation of the pathological prion protein (PrPsc), suggesting that other, genetic and non-genetic factors affect the age at symptoms onset. Here we present the protocol of a cross-sectional and longitudinal natural history study of gCJD patients and first-degree relatives of gCJD patients, aiming to identify biological markers of preclinical CJD and risk factors for phenoconversion. METHODS: The study has two groups: Patients diagnosed with gCJD, and first-degree healthy relatives (HR) (both carriers and non-carriers of the E200K mutation in the PRNP gene) of patients diagnosed with gCJD. At baseline, and at the end of every year, healthy participants are invited for an "in-depth" visit, which includes a clinical evaluation, blood and urine collection, gait assessment, brain MRI, lumbar puncture (LP), and Polysomnography (PSG). At 6 months from baseline, and then halfway through each year, participants are invited for a "brief" visit, which includes a clinical evaluation, short cognitive assessment, and blood and urine collection. gCJD patients will be invited for one "in-depth" visit, similar to the baseline visit of healthy relatives. DISCUSSION: This continuous follow-up of the participants and the frequent assessments will allow early identification and diagnosis in case of conversion into disease. The knowledge generated from this study is likely to advance the understanding of the underlying clinicopathological processes that occur at the very beginning of CJD, as well as potential genetic and environmental risk factors for the development of the disease, therefore advancing the development of safe and efficient interventions. TRIAL REGISTRATION: The study is an observational study. It has registered retrospectively in https://clinicaltrials.gov/ and has been assigned an identification number NCT05746715.

The Influence of GBA and LRRK2 on Mood Disorders in Parkinson's Disease.

Background: Mood disorders have emerged as major non-motor comorbidities in Parkinson's disease (PD) even at the prodromal stage of the disease. Mutations in the LRRK2 and GBA genes are common among Ashkenazi Jews, with more severe phenotype reported for GBA-PD. Objective: To explore the association between genetic status and mood related disorders before and after diagnosis of PD and the association between mood-related medications, phenotype, and genetic status. Methods: Participants were genotyped for mutations in the LRRK2 and GBA genes. State of depression, anxiety and non-motor features were evaluated using validated questionnaires. History of mood disorders prior to diagnosis of PD and use of mood-related medications were assessed. Results: The study included 105 idiopathic PD (iPD), 55 LRRK2-PD and 94 GBA-PD. Scores on mood related questionnaires and frequency of depression and anxiety before diagnosis were similar between the groups (p>0.05). However, more GBA-PD patients used mood related medications before PD diagnosis than LRRK2-PD and iPD (16.5% vs 7.1% and 8.2%, p=0.044). LRRK2-PD and GBA-PD receiving mood-related medications at time of assessment had worse motor and non-motor phenotype compared to those that did not (p<0.05). LRRK2-PD receiving mood related-medications at time of assessment, scored higher on mood-related questionnaires compared to LRRK2-PD not receiving such medications (p<0.04). Conclusions: Prodromal GBA-PD are more frequently treated with mood related-medications despite equal rates of reported mood-related disorders, while LRRK2-PD with mood-related disorders experience high rates of anxiety and depression despite treatment, attesting to the need of more precise assessment and treatment of these genetic subgroups.