Multiple system atrophy (MSA) is a rare neurodegenerative disease characterized by neuronal loss and gliosis, with oligodendroglial cytoplasmic inclusions (GCIs) containing α-synuclein being the primary pathological hallmark. Clinical presentations of MSA overlap with other parkinsonian disorders, such as Parkinson\'s disease (PD), dementia with Lewy bodies (DLB), and progressive supranuclear palsy (PSP), posing challenges in early diagnosis. Numerous studies have reported alterations in DNA methylation in neurodegenerative diseases, with candidate loci being identified in various parkinsonian disorders including MSA, PD, and PSP. Although MSA and PSP present with substantial white matter pathology, alterations in white matter have also been reported in PD. However, studies comparing the DNA methylation architectures of white matter in these diseases are lacking. We therefore aimed to investigate genome-wide DNA methylation patterns in the frontal lobe white matter of individuals with MSA (n = 17), PD (n = 17), and PSP (n = 16) along with controls (n = 15) using the Illumina EPIC array, to identify shared and disease-specific DNA methylation alterations. Genome-wide DNA methylation profiling of frontal lobe white matter in the three parkinsonian disorders revealed substantial commonalities in DNA methylation alterations in MSA, PD, and PSP. We further used weighted gene correlation network analysis to identify disease-associated co-methylation signatures and identified dysregulation in processes relating to Wnt signaling, signal transduction, endoplasmic reticulum stress, mitochondrial processes, RNA interference, and endosomal transport to be shared between these parkinsonian disorders. Our overall analysis points toward more similarities in DNA methylation patterns between MSA and PD, both synucleinopathies, compared to that between MSA and PD with PSP, which is a tauopathy. Our results also highlight several shared DNA methylation changes and pathways indicative of converging molecular mechanisms in the white matter contributing toward neurodegeneration in all three parkinsonian disorders.

Anderson-Fabry disease (AFD) is a genetic sphingolipidosis involving virtually the entire body. Among its manifestation, the involvement of the central and peripheral nervous system is frequent. In recent decades, it has become evident that, besides cerebrovascular damage, a pure neuronal phenotype of AFD exists in the central nervous system, which is supported by clinical, pathological, and neuroimaging data. This neurodegenerative phenotype is often clinically characterized by an extrapyramidal component similar to the one seen in prodromal Parkinson\'s disease (PD). We analyzed the biological, clinical pathological, and neuroimaging data supporting this phenotype recently proposed in the literature. Moreover, we compared the neurodegenerative PD phenotype of AFD with a classical monogenic vascular disease responsible for vascular parkinsonism and cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). A substantial difference in the clinical and neuroimaging features of neurodegenerative and vascular parkinsonism phenotypes emerged, with AFD being potentially responsible for both forms of the extrapyramidal involvement, and CADASIL mainly associated with the vascular subtype. The available studies share some limitations regarding both patients\' information and neurological and genetic investigations. Further studies are needed to clarify the potential association between AFD and extrapyramidal manifestations.

Diagnostic tests for Parkinsonism based on speech samples have shown promising results. Although abnormal auditory feedback integration during speech production and impaired rhythmic organization of speech are known in Parkinsonism, these aspects have not been incorporated into diagnostic tests. This study aimed to identify Parkinsonism using a novel speech behavioral test that involved rhythmically repeating syllables under different auditory feedback conditions. The study included 30 individuals with Parkinson\'s disease (PD) and 30 healthy subjects. Participants were asked to rhythmically repeat the PA-TA-KA syllable sequence, both whispering and speaking aloud under various listening conditions. The results showed that individuals with PD had difficulties in whispering and articulating under altered auditory feedback conditions, exhibited delayed speech onset, and demonstrated inconsistent rhythmic structure across trials compared to controls. These parameters were then fed into a supervised machine-learning algorithm to differentiate between the two groups. The algorithm achieved an accuracy of 85.4%, a sensitivity of 86.5%, and a specificity of 84.3%. This pilot study highlights the potential of the proposed behavioral paradigm as an objective and accessible (both in cost and time) test for identifying individuals with Parkinson\'s disease.

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UNASSIGNED: Trazodone is an antidepressant agent approved for treating major depressive disorders and is also prescribed for insomnia due to its sedative effect. In a few cases, trazodone was associated with parkinsonism. Herein, we describe a case of parkinsonism after a brief exposure to a moderate dose of trazodone.
UNASSIGNED: To describe a case of a patient with trazodone-induced parkinsonism in which the diagnosis was suspected after the exclusion of other common and serious causes.
UNASSIGNED: A case report of trazodone-induced parkinsonism.
UNASSIGNED: A 58-year-old male with sleeping problems was prescribed trazodone 50 mg daily at bedtime. The subject doubled the dosage without medical advice a week later. After 14 days of trazodone treatment, he started to experience difficulty in moving his upper limbs and recurrent falling. Neuroimaging, electrodiagnostic studies, and laboratory exams were unremarkable. Trazodone was discontinued, and the patient fully recovered. Noteworthy, the patient developed a recurrence of the motor symptoms with trazodone-rechallenge.
UNASSIGNED: Our case showed reversibly induced parkinsonism after a short intake of a moderate dose of trazodone which was prescribed for insomnia. The patient had a complete recovery after trazodone withdrawal. Noteworthy, the symptoms recurred upon trazodone-rechallenge.

BACKGROUND: High-frequency repeated transcranial magnetic stimulation (rTMS) stimulating the primary motor cortex (M1) is an alternative, adjunctive therapy for improving the motor symptoms of Parkinson\'s disease (PD). However, whether the high frequency of rTMS positively correlates to the improvement of motor symptoms of PD is still undecided. By controlling for other parameters, a disease animal model may be useful to compare the neuroprotective effects of different high frequencies of rTMS.
OBJECTIVE: The current exploratory study was designed to compare the protective effects of four common high frequencies of rTMS (5, 10, 15, and 20 Hz) and iTBS (a special form of high-frequency rTMS) and explore the optimal high-frequency rTMS on an animal PD model.
METHODS: Following high frequencies of rTMS application (twice a week for 5 weeks) in a MPTP/probenecid-induced chronic PD model, the effects of the five protocols on motor behavior as well as dopaminergic neuron degeneration levels were identified. The underlying molecular mechanisms were further explored.
RESULTS: We found that all the high frequencies of rTMS had protective effects on the motor functions of PD models to varying degrees. Among them, the 10, 15, and 20 Hz rTMS interventions induced comparable preservation of motor function through the protection of nigrostriatal dopamine neurons. The enhancement of brain-derived neurotrophic factor (BDNF), dopamine transporter (DAT), and vesicular monoamine transporter 2 (VMAT-2) and the suppression of TNF-α and IL-1β in the nigrostriatum were involved in the process. The efficacy of iTBS was inferior to that of the above three protocols. The effect of 5 Hz rTMS protocol was weakest.
CONCLUSIONS: Combined with the results of the present study and the possible side effects induced by rTMS, we concluded that 10 Hz might be the optimal stimulation frequency for preserving the motor functions of PD models using rTMS treatment.

Parkinson\'s disease (PD) is characterized by motor impairments caused by degeneration of dopamine neurons in the substantia nigra pars compacta. In addition to these symptoms, PD patients often suffer from non-motor comorbidities including sleep and psychiatric disturbances, which are thought to depend on concomitant alterations of serotonergic and noradrenergic transmission. A primary locus of serotonergic neurons is the dorsal raphe nucleus (DRN), providing brain-wide serotonergic input. Here, we identified electrophysiological and morphological parameters to classify serotonergic and dopaminergic neurons in the murine DRN under control conditions and in a PD model, following striatal injection of the catecholamine toxin, 6-hydroxydopamine (6-OHDA). Electrical and morphological properties of both neuronal populations were altered by 6-OHDA. In serotonergic neurons, most changes were reversed when 6-OHDA was injected in combination with desipramine, a noradrenaline (NA) reuptake inhibitor, protecting the noradrenergic terminals. Our results show that the depletion of both NA and dopamine in the 6-OHDA mouse model causes changes in the DRN neural circuitry.

N-3-[18F]fluoropropyl-2β-carbomethoxy-3β-4-iodophenyl nortropane ([18F]FP-CIT) is a radiopharmaceutical for dopamine transporter (DAT) imaging using positron emission tomography (PET) to detect dopaminergic neuronal degeneration in patients with parkinsonian syndrome. [18F]FP-CIT was granted approval by the Ministry of Food and Drug Safety in 2008 as the inaugural radiopharmaceutical for PET imaging, and it has found extensive utilization across numerous institutions in Korea. This review article presents an imaging procedure for [18F]FP-CIT PET to aid nuclear medicine physicians in clinical practice and systematically reviews the clinical studies associated with [18F]FP-CIT PET.

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Freezing of gait (FoG) is a prevalent symptom among individuals with Parkinson\'s disease and related disorders. FoG detection from videos has been developed recently; however, the process requires using videos filmed within a controlled environment. We attempted to establish an automatic FoG detection method from videos taken in uncontrolled environments such as in daily clinical practices. Motion features of 16 patients were extracted from timed-up-and-go test in 109 video data points, through object tracking and three-dimension pose estimation. These motion features were utilized to form the FoG detection model, which combined rule-based and machine learning-based models. The rule-based model distinguished the frames in which the patient was walking from those when the patient has stopped, using the pelvic position coordinates; the machine learning-based model distinguished between FoG and stop using a combined one-dimensional convolutional neural network and long short-term memory (1dCNN-LSTM). The model achieved a high intraclass correlation coefficient of 0.75-0.94 with a manually-annotated duration of FoG and %FoG. This method is novel as it combines object tracking, 3D pose estimation, and expert-guided feature selection in the preprocessing and modeling phases, enabling FoG detection even from videos captured in uncontrolled environments.