OBJECTIVE:Parkinson's disease (PD) presents challenges in early diagnosis and progression prediction. Recent advancements in machine learning, particularly convolutional-neural-networks (CNNs), show promise in enhancing diagnostic accuracy and prognostic capabilities using neuroimaging data. The aims of this study were: (i) develop a 3D-CNN based on MRI to distinguish controls and PD patients and (ii) employ CNN to predict the progression of PD. METHODS:Three cohorts were selected: 86 mild, 62 moderate-to-severe PD patients, and 60 controls; 14 mild-PD patients and 14 controls from Parkinson's Progression Markers Initiative database, and 38 de novo mild-PD patients and 38 controls. All participants underwent MRI scans and clinical evaluation at baseline and over 2-years. PD subjects were classified in two clusters of different progression using k-means clustering based on baseline and follow-up UDPRS-III scores. A 3D-CNN was built and tested on PD patients and controls, with binary classifications: controls vs moderate-to-severe PD, controls vs mild-PD, and two clusters of PD progression. The effect of transfer learning was also tested. RESULTS:CNN effectively differentiated moderate-to-severe PD from controls (74% accuracy) using MRI data alone. Transfer learning significantly improved performance in distinguishing mild-PD from controls (64% accuracy). For predicting disease progression, the model achieved over 70% accuracy by combining MRI and clinical data. Brain regions most influential in the CNN's decisions were visualized. CONCLUSIONS:CNN, integrating multimodal data and transfer learning, provides encouraging results toward early-stage classification and progression monitoring in PD. Its explainability through activation maps offers potential for clinical application in early diagnosis and personalized monitoring.

The GBA1 related Parkinson’s disease (PD) is associated with more severe non-motor symptoms. To date, studies of the role of GBA1 mutations in the occurrence of impulse control behaviours (ICBs) in PD have yielded controversial results. Our aim was to investigate the frequency and characteristics of ICBs in PD patients with GBA1 mutations. 213 consecutive PD patients were included. Clinical data were gathered via interviews and using the standard set of questionnaires. Genetic analysis of exons 8–11 of the GBA1 gene was performed for all participants. GBA1 variants were detected in 32 out of 213 patients (GBA-PD). ICBs were more frequent in GBA-PD (31.2

Dystonia due to pathogenic variants in the THAP1 gene (DYT-THAP1) shows variable expressivity and reduced penetrance of 50

Background Whether connectome mapping of structural and functional connectivity across the brain could be used to predict patterns of atrophy progression in patients with mild Parkinson disease (PD) has not been well studied. Purpose To assess the structural and functional connectivity of brain regions in healthy controls and its relationship with the spread of gray matter (GM) atrophy in patients with mild PD. Materials and Methods This prospective study included participants with mild PD and controls recruited from a single center between January 2012 and December 2023. Participants with PD underwent three-dimensional T1-weighted brain MRI, and the extent of regional GM atrophy was determined at baseline and every year for 3 years. The structural and functional brain connectome was constructed using diffusion tensor imaging and resting-state functional MRI in healthy controls. Disease exposure (DE) indexes-indexes of the pathology of each brain region-were defined as a function of the structural or functional connectivity of all the connected regions in the healthy connectome and the severity of atrophy of the connected regions in participants with PD. Partial correlations were tested between structural and functional DE indexes of each GM region at 1- or 2-year follow-up and atrophy progression at 2- or 3-year follow-up. Prediction models of atrophy at 2- or 3-year follow-up were constructed using exhaustive feature selection. Results A total of 86 participants with mild PD (mean age at MRI, 60 years ± 8 [SD]; 48 male) and 60 healthy controls (mean age at MRI, 62 years ± 9; 31 female) were included. DE indexes at 1 and 2 years were correlated with atrophy at 2 and 3 years (r range, 0.22-0.33; P value range, .002-.04). Models including DE indexes predicted GM atrophy accumulation over 3 years in the right caudate nucleus and some frontal, parietal, and temporal brain regions (R2 range, 0.40-0.61; all P < .001). Conclusion The structural and functional organization of the brain connectome plays a role in atrophy progression in the early stages of PD. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Yamada in this issue.

Background: Biallelic pathogenic variants in the ANO10 gene cause autosomal recessive progressive ataxia (ATX-ANO10). Methods: Following the MDSGene protocol, we systematically investigated genotype-phenotype relationships in ATX-ANO10 based on the clinical and genetic data from 82 published and 12 newly identified patients. Results: Most patients (>80%) had loss-of-function (LOF) variants. The most common variant was c.1150_1151del, found in all 29 patients of Romani ancestry, who had a 14-year earlier mean age at onset than patients homozygous for other LOF variants. We identified previously undescribed clinical features of ATX-ANO10 (e.g., facial muscle involvement and strabismus) suggesting the involvement of brainstem pathology, and we propose a diagnostic algorithm that may aid clinical ATX-ANO10 diagnosis. Conclusions: The early disease onset in patients with c.1150_1151del may indicate the existence of genetic/environmental disease-modifying factors in the Romani population. Our findings will inform patient counseling and may improve our understanding of the disease mechanism. (c) 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Most of the heritability in frontotemporal dementia (FTD) is accounted for by autosomal dominant hexanucleotide expansion in the chromosome 9 open reading frame 72 (C9orf72), pathogenic/likely pathogenic variants in progranulin (GRN), and microtubule-associated protein tau (MAPT) genes. Until now, there has been no systematic analysis of these genes in the Serbian population. Herein, we assessed the frequency of the C9orf72 expansion, pathogenic/likely pathogenic variants in GRN and MAPT in a well-characterized group of 472 subjects (FTD, Alzheimer's disease - AD, mild cognitive impairment - MCI, and unspecified dementia - UnD), recruited in the Memory Center, Neurology Clinic, University Clinical Center of Serbia. The C9orf72 repeat expansion was detected in 6.98% of FTD cases (13.46% familial; 2.6% sporadic). In the UnD subgroup, C9orf72 repeat expansions were detected in 4.08% (8% familial) individuals. Pathogenic variants in the GRN were found in 2.85% of familial FTD cases. Interestingly, no MAPT pathogenic/likely pathogenic variants were detected, suggesting possible geographical specificity. Our findings highlight the importance of wider implementation of genetic testing in neurological and psychiatric practice managing patients with cognitive-behavioral and motor symptoms.

INTRODUCTION:Motor imagery (MI) involves recreating a movement mentally without physically performing the movement itself. MI has a positive impact on motor performance, motor learning and neural plasticity. We analysed the connection between motor imagination and altered movement execution in individuals with dystonia, a complex sensorimotor disorder. The aim of our study was to examine MI ability in patients with functional dystonia (FD) in comparison to organic dystonia (OD). METHODS:Our case-control study involved 46 patients, 22 with FD and 24 with OD. The assessment consisted of specific questionnaire and standardized motor, cognitive and psychiatric scales. The KVIQ-20 was used to test MI in each patient. RESULTS:Patients with FD scored lower on both global visual and kinaesthetic scales of the KVIQ-20 exam compared to patients with OD (63.1 ± 18.5 vs. 73.7 ± 13.2, and 54.9 ± 21.9 vs. 68.8 ± 18.2, respectively). Patients with FD also exhibited visual and/or kinaesthetic MI impairment in different body segments. The internal perspective when imagining movements was preferred in both patients with FD and OD. CONCLUSION:FD patients showed global dysfunction of visual and kinaesthetic MI abilities. Techniques for MI improvements might have a potential role in dystonia rehabilitation.

Introduction/Aims: Understanding the differences in neuropsychiatric symptoms (NPSs) across tauopathies, particularly in the early stages of the disease, may aid in differential diagnosis. The aims of the research are as follows: a) to examine the patterns of NPSs in primary (frontotemporal dementia - FTD and progressive supranuclear palsy - PSP) and secondary (Alzheimer's disease - AD) tauopathies; b) to examine the differences in NPSs reported by patients and caregivers. Methods: The study included 312 patients, 176 of whom had a disease duration of ≤3 years. The presence of NPSs based on caregiver's report was assessed by neuropsychiatric questionnaire (NPI). Patient's assessment of NPSs was examined by Hamilton's Depression and Anxiety Scales and the Apathy Scale. Results: In AD, the most common and severe neuropsychiatric symptoms are mood disorders and apathy. In contrast, agitation-related symptoms are also prominent in FTD and PSP. The profile of NPSs in FTD and PSP is similar, but irritability and aberrant motor behavior are more pronounced in FTD, while sleep disturbances are dominant in PSP. The prevalence of NPSs reported by caregivers on NPI was higher than that reported by patients. Conclusions: FTD and PSP are characterized by more frequent and more severe NPSs and have distinct psychiatric patterns compared to AD, even in the early disease course. Caregiver's observations of the patient's behavior could be of key importance in distinguishing these tauopathies, particularly in the absence of hard motor and cognitive symptoms in early disease course. Assessments of depression, anxiety, and apathy by patients themselves and their caregivers differ significantly, and data from these two sources cannot be considered interchangeable and comparable.

Catechol-O-methyltransferase (COMT) is one of the cardinal enzymes in the degradation of catecholamines and levodopa. Genetic variants of the COMT gene may affect COMT enzyme activity. The most examined COMT gene polymorphism is the nonsynonymous single nucleotide polymorphism (SNP) in exon 4 (Val108/158Met; rs4680). This highly functional polymorphism is responsible for fourfold variations in enzyme activity and Dopamine catabolism. Recent data suggested that even synonymous SNPs of the COMT gene can lead to changes in enzyme activity. Genetically determined COMT activity can affect an individual's response to levodopa therapy and carries the risk of complications from prolonged levodopa use in Parkinson's disease (PD) patients. Identifying at-risk individuals through genetic susceptibility markers could help to prevent the development of levodopa-induced complications in PD.

To decipher the mechanisms of network-based neurodegeneration in Parkinson's disease (PD) investigating the relationship between functional connectivity (FC) in healthy connectome and grey matter (GM) atrophy accumulation in mild PD patients, and to develop a predictive model for atrophy spreading in PD.

BACKGROUND:The newly discovered intronic repeat expansions in the genes encoding replication factor C subunit 1 (RFC1) and fibroblast growth factor 14 (FGF14) frequently cause late-onset cerebellar ataxia.OBJECTIVES:To investigate the presence of RFC1 and FGF14 pathogenic repeat expansions in Serbian patients with adult-onset cerebellar ataxia.METHODS:The study included 167 unrelated patients with sporadic or familial cerebellar ataxia. The RFC1 repeat expansion analysis was performed by duplex PCR and Sanger sequencing, while the FGF14 repeat expansion was tested for by long-range PCR, repeat-primed PCR, and Sanger sequencing.RESULTS:We identified pathogenic repeat expansions in RFC1 in seven patients (7/167; 4.2%) with late-onset sporadic ataxia with neuropathy and chronic cough. Two patients also had bilateral vestibulopathy. Repeat expansions in FGF14 were found in nine unrelated patients (9/167; 5.4%) with ataxia, less than half of whom presented with neuropathy and two-thirds with global brain atrophy. Tremor and episodic features were the most frequent additional characteristics in carriers of uninterrupted FGF14 repeat expansions. Among the 122 sporadic cases, 12 (9.8%) carried an expansion in either RFC1 or FGF14, comparable to 4/45 (8.9%) among the patients with a positive family history.CONCLUSIONS:Pathogenic repeat expansions in RFC1 and FGF14 are relatively frequent causes of adult-onset cerebellar ataxia, especially among sporadic patients, indicating that family history should not be considered when prioritizing ataxia patients for testing of RFC1 or FGF14 repeat expansions.

BackgroundA 4-item score based on >= 2 features out of orthostatic hypotension, overactive bladder, urinary retention and postural instability was previously shown to early distinguish the Parkinson-variant of multiple system atrophy (MSA-P) from Parkinson's disease (PD) with 78% sensitivity and 86% specificity. ObjectivesTo replicate and improve the 4-item MSA-P score. MethodsWe retrospectively studied 161 patients with early parkinsonism [ie, <= 2 years disease duration or no postural instability, aged 64 (57; 68) years, 44% females] and a diagnosis of clinically established MSA-P (n = 38) or PD (n = 123) after >= 24 months follow-up. ResultsThe 4-item MSA-P score had a 92% sensitivity and 78% specificity for a final MSA-P diagnosis. By including dopaminergic responsiveness and postural deformities into a 6-item score (range: 0-6), reaching >= 3 points at early disease identified MSA-P patients with 89% sensitivity and 98% specificity. ConclusionsThe 6-item MSA-P score is a cost-effective tool to pinpoint individuals with early-stage MSA-P.

Parkinson's disease (PD) is the fastest-growing neurodegenerative disorder, currently affecting ~7 million people worldwide. PD is clinically and genetically heterogeneous, with at least 10% of all cases explained by a monogenic cause or strong genetic risk factor. However, the vast majority of our present data on monogenic PD is based on the investigation of patients of European White ancestry, leaving a large knowledge gap on monogenic PD in underrepresented populations. Gene-targeted therapies are being developed at a fast pace and have started entering clinical trials. In light of these developments, building a global network of centers working on monogenic PD, fostering collaborative research, and establishing a clinical trial-ready cohort is imperative. Based on a systematic review of the English literature on monogenic PD and a successful team science approach, we have built up a network of 59 sites worldwide and have collected information on the availability of data, biomaterials, and facilities. To enable access to this resource and to foster collaboration across centers, as well as between academia and industry, we have developed an interactive map and online tool allowing for a quick overview of available resources, along with an option to filter for specific items of interest. This initiative is currently being merged with the Global Parkinson's Genetics Program (GP2), which will attract additional centers with a focus on underrepresented sites. This growing resource and tool will facilitate collaborative research and impact the development and testing of new therapies for monogenic and potentially for idiopathic PD patients.

In this paper, a method based on gait analysis and deep learning was developed and explored for the recognition of Parkinson’s disease (PD). The study comprised 33 patients with PD and 15 healthy subjects (CTRL). Two deep learning models were designed and compared: convolutional neural network (CNN) and long short-term memory network (LSTM). The networks were trained on data that was recorded using a wireless and wearable system comprised of inertial and force sensors while performing a gait task. The influence of different data lengths on the performance of models was also examined. The best result was obtained using a CNN model fed with 8 seconds long walking sequences, with an accuracy of 92.49% for the classification of all PD patients and CTRL subjects. The obtained results showed that methods based on deep learning and gait analysis could contribute to objective and automatized recognition of Parkinson’s disease with high accuracy.

Background Most of DYT genotypes follow an autosomal dominant inheritance pattern with reduced penetrance; the mechanisms underlying the disease development remain unclear. The objective of the study was to investigate cortical thickness, grey matter (GM) volumes and white matter (WM) alterations in asymptomatic (DYT-A) and symptomatic dystonia (DYT-S) mutation carriers. Methods Eight DYT-A (four DYT-TOR1A and four DYT-THAP1), 14 DYT-S (seven DYT-TOR1A, and seven DYT-THAP1), and 37 matched healthy controls underwent 3D T1-weighted and diffusion tensor (DT) MRI to study cortical thickness, cerebellar and basal ganglia GM volumes and WM microstructural changes. Results DYT-S showed thinning of the frontal and motor cortical regions related to sensorimotor and cognitive processing, together with putaminal atrophy and subcortical microstructural WM damage of both motor and extra-motor tracts such as cerebral peduncle, corona radiata, internal and external capsule, temporal and orbitofrontal WM, and corpus callosum. DYT-A had cortical thickening of middle frontal areas and WM damage of the corona radiata. Conclusions DYT genes phenotypic expression is associated with alterations of both motor and extra-motor WM and GM regions. Asymptomatic genetic status is characterized by a very subtle affection of the WM motor pathway, together with an increased cortical thickness of higher-order frontal regions that might interfere with phenotypic presentation and disease manifestation.

BACKGROUND:Vitamin D is a steroid hormone, known to be involved in the pathogenesis of various neurodegenerative disorders, including Parkinson's disease (PD). We aimed to clarify the relationship between hypovitaminosis D and the predisposition for PD and its clinical presentation. An additional aim was to examine the specific gene polymorphisms associated with vitamin D level. MATERIAL AND METHODS:Total level of 25(OH)-vitamin D (25(OH)D) was measured in the serum of parkinsonian patients (n = 113) and controls (n = 82) using a commercial immunoassay. Genetic analyses were performed using Taqman assays on Real Time PCR amplification system. RESULTS:Higher frequency of vitamin D deficiency (<50 nmol/L) was observed in PD patients, compared to controls (40.7% and 23.2%, respectively, P = 0.010). It was also a positive predictive marker of PD (OR, 2.27; 95% CI, 1.206-4.298; P < 0.011). Significantly higher UPDRS (35.85 ± 1.35 and 32.09 ± 0.99, respectively, P = 0.023) and HY scores (2(1.5-2.5) and 1.5(1.0-2.0), respectively, P = 0.005) were present in patients with 25(OH)D level < 50 nmol/L compared to patients with 25(OH)D level ≥ 50 nmol/L. Despite some trends observed, differences in allelic and genotypic distribution between controls and patients, as well as between subgroups, did not reach the level of significance (P > 0.05). CONCLUSIONS:Findings of this study confirm the hypothesis of a significant relationship between hypovitaminosis D and PD. We demonstrated higher prevalence of vitamin D deficiency in PD patients, as well as its predictive potential for the onset and progression of PD.

Biallelic mutations in PINK1 and PRKN cause recessively inherited Parkinson’s disease (PD). Though some studies suggest that PINK1 / PRKN monoallelic mutations may not contribute to risk, deep phenotyping assessment showed that PINK1 or PRKN monoallelic pathogenic variants were at a significantly higher rate in PD compared to controls. Given the established role of PINK1 and Parkin in regulating mitochondrial dynamics, we explored mitochondrial DNA (mtDNA) integrity and inflammation as potential disease modifiers in carriers of mutations in these genes. MtDNA integrity, global gene expression and serum cytokine levels were investigated in a large collection of biallelic (n=84) and monoallelic (n=170) carriers of PINK1 / PRKN mutations, iPD patients (n=67) and controls (n=90). Affected and unaffected PINK1 / PRKN monoallelic mutation carriers can be distinguished by heteroplasmic mtDNA variant load (AUC=0.83, CI:0.74-0.93). Biallelic PINK1 / PRKN mutation carriers harbor more heteroplasmic mtDNA variants in blood (p=0.0006, Z=3.63) compared to monoallelic mutation carriers. This enrichment was confirmed in iPSC-derived and postmortem midbrain neurons from biallelic PRKN -PD patients. Lastly, the heteroplasmic mtDNA variant load was found to correlate with IL6 levels in PINK1 / PRKN mutation carriers (r=0.57, p=0.0074). PINK1 / PRKN mutations predispose individuals to mtDNA variant accumulation in a dose- and disease-dependent manner. MtDNA variant load over time is a potential marker of disease manifestation in PINK1 / PRKN mutation carriers.