Disrupted Brain Network Hubs in Subtype-Specific Parkinson's Disease.

BACKGROUND/AIMS: The topological organization of brain functional networks is impaired in Parkinson's disease (PD). However, the altered patterns of functional network hubs in different subtypes of PD are not completely understood. METHODS: 3T resting-state functional MRI and voxel-based graph-theory analysis were employed to systematically investigate the intrinsic functional connectivity patterns of whole-brain networks. We enrolled 31 patients with PD (12 tremor dominant [TD] and 19 with postural instability/gait difficulty [PIGD]) and 22 matched healthy controls. Whole-brain voxel-wise functional networks were constructed by measuring the temporal correlations of each pair of brain voxels. Functional connectivity strength was calculated to explore the brain network hubs. RESULTS: We found that both the TD and PIGD subtypes had comprehensive disrupted regions. These mainly involved the basal ganglia, cerebellum, superior temporal gyrus, pre- and postcentral gyri, inferior frontal gyrus, middle temporal gyrus, lingual gyrus, insula, and parahippocampal gyrus. Furthermore, the PIGD subgroup had more disrupted hubs in the cerebellum than the TD subgroup. These disruptions of hub connectivity were not correlated with the HY stage or disease duration. CONCLUSION: Our results emphasize the subtype-specific PD-related degeneration of brain hubs, providing novel insights into the pathophysiological mechanisms of connectivity dysfunction in different PD subgroups.

Combined occurrence of a novel TOR1A and a THAP1 mutation in primary dystonia.

BACKGROUND: The ΔGAG deletion of the TOR1A gene (DYT1) is responsible for DYT1 dystonia. However, no other TOR1A mutation has been reported in the Chinese population. METHODS: Two hundred one dystonia patients without the ΔGAG deletion were screened for other mutations in TOR1A. Gene function changes were analyzed by subcellular distribution and luciferase reporter assay. RESULTS: A novel TOR1A mutation (c.581A>T, p.Asp194Val) was found in a patient with early-onset segmental dystonia harboring a THAP1 mutation (c.539T>C, p.Leu180Ser). Overexpression of mutant TOR1A Asp194Val protein induces inclusion formation in SK-N-AS cell lines, and the repressive activity of the mutant THAP1 Leu180Ser protein on TOR1A gene expression is decreased compared with wild-type THAP1. CONCLUSIONS: This is the first report about a dystonia patient harboring two distinct dystonia gene mutations. Functional analysis indicated a potential additive effect of these two mutations, which might provoke the occurrence of dystonic symptoms in this patient.

A progression analysis of motor features in Parkinson's disease based on the mapper algorithm.

Background: Parkinson's disease (PD) is a neurodegenerative disease with a broad spectrum of motor and non-motor symptoms. The great heterogeneity of clinical symptoms, biomarkers, and neuroimaging and lack of reliable progression markers present a significant challenge in predicting disease progression and prognoses. Methods: We propose a new approach to disease progression analysis based on the mapper algorithm, a tool from topological data analysis. In this paper, we apply this method to the data from the Parkinson's Progression Markers Initiative (PPMI). We then construct a Markov chain on the mapper output graphs. Results: The resulting progression model yields a quantitative comparison of patients' disease progression under different usage of medications. We also obtain an algorithm to predict patients' UPDRS III scores. Conclusions: By using mapper algorithm and routinely gathered clinical assessments, we developed a new dynamic models to predict the following year's motor progression in the early stage of PD. The use of this model can predict motor evaluations at the individual level, assisting clinicians to adjust intervention strategy for each patient and identifying at-risk patients for future disease-modifying therapy clinical trials.

Corrigendum: A progression analysis of motor features in Parkinson's disease based on the mapper algorithm.

[This corrects the article DOI: 10.3389/fnagi.2023.1047017.].

Remote scoring models of rigidity and postural stability of Parkinson's disease based on indirect motions and a low-cost RGB algorithm.

Background and objectives: The Movement Disorder Society's Unified Parkinson's Disease Rating Scale Part III (MDS-UPDRS III) is mostly common used for assessing the motor symptoms of Parkinson's disease (PD). In remote circumstances, vision-based techniques have many strengths over wearable sensors. However, rigidity (item 3.3) and postural stability (item 3.12) in the MDS-UPDRS III cannot be assessed remotely since participants need to be touched by a trained examiner during testing. We developed the four scoring models of rigidity of the neck, rigidity of the lower extremities, rigidity of the upper extremities, and postural stability based on features extracted from other available and touchless motions. Methods: The red, green, and blue (RGB) computer vision algorithm and machine learning were combined with other available motions from the MDS-UPDRS III evaluation. A total of 104 patients with PD were split into a train set (89 individuals) and a test set (15 individuals). The light gradient boosting machine (LightGBM) multiclassification model was trained. Weighted kappa (k), absolute accuracy (ACC ± 0), and Spearman's correlation coefficient (rho) were used to evaluate the performance of model. Results: For model of rigidity of the upper extremities, k = 0.58 (moderate), ACC ± 0 = 0.73, and rho = 0.64 (moderate). For model of rigidity of the lower extremities, k = 0.66 (substantial), ACC ± 0 = 0.70, and rho = 0.76 (strong). For model of rigidity of the neck, k = 0.60 (moderate), ACC ± 0 = 0.73, and rho = 0.60 (moderate). For model of postural stability, k = 0.66 (substantial), ACC ± 0 = 0.73, and rho = 0.68 (moderate). Conclusion: Our study can be meaningful for remote assessments, especially when people have to maintain social distance, e.g., in situations such as the coronavirus disease-2019 (COVID-19) pandemic.

Screening of the TMEM151A Gene in Patients With Paroxysmal Kinesigenic Dyskinesia and Other Movement Disorders.

Background: Paroxysmal kinesigenic dyskinesia (PKD) is a rare neurological disorder characterized by recurrent involuntary movements usually triggered by sudden movements. Mutations in the TMEM151A gene were found to be the causative factor of PKD in recent studies. It has also been revealed that loss-of-function is the mechanism by which TMEM151A mutations cause PKD. Methods: To investigate the genetic basis of PKD and broaden the clinical spectrum of the TMEM151A mutations, we recruited 181 patients of Chinese origin with movement disorders (MDs), including 39 PRRT2-negative PKD, 3 paroxysmal exercise-induced dyskinesia (PED), 2 paroxysmal non-kinesigenic dyskinesia (PNKD), 127 isolated dystonia, 8 choreas, and 2 myoclonus-dystonia syndromes. Whole-exome sequencing was applied to identify their possible disease-causing mutations. Then, Sanger sequencing was performed for validation and co-segregation analysis. Genetic analysis was also performed on additional family members of patients with TMEM151A mutations. Clinical manifestations of all PKD cases with mutations in TMEM151A reported, so far, were reviewed. Results: Two novel variants of the TMEM151A gene (NM_153266.4, NP_694998.1), c.627_643dup (p.A215Gfs*53) and c.627delG (p.L210Wfs*52), were identified in 2 patients with PKD by whole-exome sequencing and further Sanger sequencing. Both variants were inherited by the patients from their respective mothers. No mutation of the TMEM151A gene was found in the other type of movement disorders. In reviewing the clinical presentation of TMEM151A-related PKD, no statistically significant difference in the age of onset, family history, duration of attacks, laterality, and phenotype was found between genders. More male patients received treatment and had a good response. A higher proportion of female patients did not receive any treatment, possibly because they had a milder condition of the disease. Conclusions: This study further validated the role of TMEM151A in PKD. Future studies on protein function will be needed to ascertain the pathogenesis of TMEM151A in PKD.

Hyper- and hypo-connectivity in sensorimotor network of drug-naïve patients with cervical dystonia.

BACKGROUND: Cervical dystonia (CD) is the most common form of focal dystonia with involuntary movements and postures of the head. The pathogenesis and neural mechanisms underlying CD have not been fully elucidated. METHODS: Twenty-seven newly drug-naïve patients with CD and 21 healthy controls (HCs) were recruited with clinical assessment and resting-state functional magnetic resonance imaging (rs-fMRI) scanning. Severity of CD was measured by Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS) and Tsui scores. Whole-brain voxel-wise intrinsic connectivity (IC) and seed-based functional connectivity (FC) analyses were performed for detection of changes in the CD group relative to HCs, controlling for age, gender, and global time series correlation, followed by correlation analyses of IC, seed-based FC and clinically relevant features, respectively. RESULTS: In comparison with HCs, CD patients showed significantly increased IC measurement in the anterior part of the left supramarginal gyrus and extended to the inferior left postcentral gyrus (AL-SMG/IL-PCG). With this cluster as a seed, decreased FC was found in the right precentral and postcentral gyrus. Moreover, the regional IC value in the AL-SMG/IL-PCG was significantly positively correlated with TWSTRS-1 (severity) score, and significantly negatively correlated with the associated seed-based FC strength. CONCLUSIONS: Our results showed signs of both hyper- and hypo-connectivity in bilateral regions of the sensorimotor network related to CD. The imbalance of functional connectivity (both hyper- and hypo-) may hint both overloading and disrupted somatosensory or sensorimotor integration dysfunction within the sensorimotor network underlying the pathophysiology of CD, thus providing a network target for future therapies.

Motor Progression in Early-Stage Parkinson's Disease: A Clinical Prediction Model and the Role of Cerebrospinal Fluid Biomarkers.

Background: The substantial heterogeneity of clinical symptoms and lack of reliable progression markers in Parkinson's disease (PD) present a major challenge in predicting accurate progression and prognoses. Increasing evidence indicates that each component of the neurovascular unit (NVU) and blood-brain barrier (BBB) disruption may take part in many neurodegenerative diseases. Since some portions of CSF are eliminated along the neurovascular unit and across the BBB, disturbing the pathways may result in changes of these substances. Methods: Four hundred seventy-four participants from the Parkinson's Progression Markers Initiative (PPMI) study (NCT01141023) were included in the study. Thirty-six initial features, including general information, brief clinical characteristics and the current year's classical scale scores, were used to build five regression models to predict PD motor progression represented by the coming year's Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part III score after redundancy removal and recursive feature elimination (RFE)-based feature selection. Then, a threshold range was added to the predicted value for more convenient model application. Finally, we evaluated the CSF and blood biomarkers' influence on the disease progression model. Results: Eight hundred forty-nine cases were included in the study. The adjusted R2 values of three different categories of regression model, linear, Bayesian and ensemble, all reached 0.75. Models of the same category shared similar feature combinations. The common features selected among the categories were the MDS-UPDRS Part III score, Montreal Cognitive Assessment (MOCA) and Rapid Eye Movement Sleep Behavior Disorder Questionnaire (RBDSQ) score. It can be seen more intuitively that the model can achieve certain prediction effect through threshold range. Biomarkers had no significant impact on the progression model within the data in the study. Conclusions: By using machine learning and routinely gathered assessments from the current year, we developed multiple dynamic models to predict the following year's motor progression in the early stage of PD. These methods will allow clinicians to tailor medical management to the individual and identify at-risk patients for future clinical trials examining disease-modifying therapies.

Nitrated alpha-synuclein in minor salivary gland biopsies in Parkinson's disease.

Alpha-synuclein (α-SYN) is found in peripheral autonomic neuronal network apart from brain in Parkinson's disease (PD). Nitrated α-SYN is an undesirable modification associated with oxidative and nitrative damage and has been found extensively in brain, gastrointestinal(GI) tract and blood cells in PD. We aim to investigate the presence of nitrated α-SYN in minor salivary gland biopsy in PD. Patients with PD and age-matched controls underwent minor salivary gland biopsy. Motor impairment was assessed by Hoehn-Yahr (H-Y) stage and Unified Parkinson's Disease Rating Scale (UPDRS) Part III in off-state. 11C-methyl-N-2b-carbomethoxy-3b-(4-fluorophenyl) tropane (11C-CFT) DAT-PET scan was performed in all subjects. Immunohistochemical staining for nitrated α-SYN was performed in the minor salivary gland tissues. The minor salivary gland tissues of 8 PD cases and 7 controls with early stage (H-Y stage 1-2) were detected. All PD patients showed asymmetrical and reduction of 11C-CFT uptake in the caudate, anterior and posterior putamen, while all control subjects showed normal DAT-PET scan. Positive nitrated α-SYN immunostaining was observed in all PD patients (8/8,100%) but not in control subjects (0/7). The results were consistent well with that of DAT-PET. These nitrated alpha-synuclein positive structures were mainly located in the periacinar stroma in PD patients. Our result suggests that nitrated α-SYN exists in the early stage and is probably a promising biomarker for PD. Minor salivary gland is an ideal site for α-SYN nitration detection. Despite of the small number of subjects, attention should be given to α-SYN nitration in PD and more investigations on nitrated α-SYN in different sites and large sample using should be explored in future.

Alpha-Synuclein in Peripheral Tissues in Parkinson's Disease.

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

Heterogeneity among patients with Parkinson's disease: cluster analysis and genetic association.

The clinical heterogeneity of Parkinson's disease (PD) reveals the presence of several PD subtypes. The objectives of this study were to identify PD subtypes using cluster analysis (CA) and to determine the association between the subtypes and the polymorphisms in LRRK2 (G2385R and R1628P) and GBA (L444P) genes. A k-means CA of demographics, disease progression, motor and non-motor symptoms was performed from 1,510 Chinese PD patients from the Chinese National Consortium on Neurodegenerative Diseases. Pearson correlation analysis was performed to eliminate uninformative characteristics. Blood samples from 852 patients were obtained for genetic analysis of LRRK2 and GBA. Genotypic associations between various subtypes and genetic variants were examined using chi-square test. We identified four different subtypes: subtype 1 was non-tremor dominant (NTD, n=469; 31.1%); subtype 2 had a rapid disease progression with late onset (RDP-LO, n=67; 4.4%); subtype 3 had benign pure motor characteristics (BPM, n=778; 51.5%) without non-motor disturbances; and subtype 4 was tremor dominant with slow disease progression (TD-SP, n=196; 13.0%). Subtypes 1, 2, and 4 had similar mean age of onset. No associations were identified between polymorphisms in LRRK2 (R1628P) and GBA (L444P) genes and the four subtypes (P>0.05).

Different patterns of spontaneous brain activity between tremor-dominant and postural instability/gait difficulty subtypes of Parkinson's disease: a resting-state fMRI study.

AIMS: Postural instability/gait difficulty (PIGD) and tremor-dominant (TD) subtypes of Parkinson's disease (PD) show different clinical manifestations; however, their underlying neural substrates remain incompletely understood. This study aimed at investigating the subtype-specific patterns of spontaneous brain activity in PD. METHODS: Thirty-one patients with PD (12 TD/19 PIGD) and 22 healthy gender- and age-matched controls were recruited. Resting-state functional magnetic resonance imaging data were collected, and amplitude of low-frequency fluctuations (ALFF) was measured. Voxelwise one-way analysis of covariance and post hoc analyses of ALFF were performed among the three groups, with age and gender as covariates (levodopa daily dosage and gray matter volume as additional covariates for validation analysis). Correlations of clinical variables (e.g., disease duration and PIGD/tremor subscale score) with ALFF values were examined. RESULTS: Compared with controls, patients with TD exhibited higher ALFF in the right cerebellar posterior lobe and patients with PIGD exhibited lower ALFF in the bilateral putamen and cerebellar posterior lobe, and higher values primarily in several cortical areas including the inferior and superior temporal gyrus, superior frontal, and parietal gyrus. Compared with patients with PIGD, patients with TD had higher ALFF in the bilateral putamen and the cerebellar posterior lobe, as well as lower ALFF in the bilateral temporal gyrus and the left superior parietal lobule. In all patients, ALFF in the bilateral cerebellar posterior lobe positively correlated with tremor score and ALFF in the bilateral putamen negatively correlated with PIGD score. CONCLUSION: Different patterns of spontaneous neural activity in the cerebellum and putamen may underlie the neural substrate of PD motor subtypes.

THAP1/DYT6 sequence variants in non-DYT1 early-onset primary dystonia in China and their effects on RNA expression.

Mutations in the THAP1 gene were recently identified as the cause of DYT6 primary dystonia. More than 40 mutations in this gene have been described in different populations. However, no previous report has identified sequence variations that affect the transcript process of the THAP1 gene. In addition, the mutation frequency in Chinese early-onset primary dystonia has not been well characterized. One hundred and two unrelated patients with non-DYT1 early-onset primary dystonia (age at onset <26 years), family members of participants with mutations, and 200 neurologically normal controls were screened for THAP1 gene mutations. The effects of the identified mutations on RNA expression were analyzed using semi-quantitative real-time PCR. Seven sequence variants (c.63_66del TTTC, c.161G>T, c.224A>T, c.267G>A, c.339T>C, c.449A>C, and c.539T>C) were identified in this group of patients (6.9%). In this cohort, 15 subjects (seven unrelated patients and eight family members) were detected to have THAP1 sequence variants. Among these 15 subjects, 11 were manifested (penetrance of DYT6 was 73.3%) and seven presented with craniocervical involvement (63.6%). However, one patient manifested paroxysmal headshake, and one presented with essential hand tremor. Semi-quantitative real-time PCR indicated that a novel silent mutation (c.267G>A) decreased the expression of THAP1 in human lymphocytes. Our findings indicated that THAP1 sequence variants are not common in non-DYT1 early-onset primary dystonia in China and that the clinical manifestation may vary. One silent mutation (c.267G>A) was shown to affect THAP1 expression.

Subcellular distribution of THAP1 and alterations in the microstructure of brain white matter in DYT6 dystonia.

BACKGROUND: Mutations in the THAP1 gene have recently been identified as the cause of DYT6 primary dystonia. However, the changes in THAP1 gene function and in the microstructure of brain white matter have not been well-characterized. METHODS: Four different mutations of THAP1 expression (clones F22fs71X, C54F, F25fs53X, and L180S) were transfected into HEK-293T cells. The subcellular distribution of THAP1 in each clone was identified using immunofluorescence microscopy and Western blot. Six patients who harbored these THAP1 mutations underwent diffusion tensor magnetic resonance imaging (DTI) of the brain. The fractional anisotropy (FA) and mean diffusivity (MD) were measured in twenty-four regions of interest (ROI). RESULTS: In two truncated mutations (F22fs71X and F25fs53X), the subcellular distribution of THAP1 were both in the cytoplasm and nucleus. However, the subcellular distribution was detected almost in the nucleus in two missense mutations (C54F and L180S). In the DTI maps, the average values of fractional anisotropy (FA), a measure of axonal integrity and coherence, was reduced (p < 0.005) in the subgyral white matter of the sensorimotor cortex of the DYT1 carriers, comparing with controls. CONCLUSIONS: Truncated THAP1 mutations (F22fs71X and F25fs53X) can alter the subcellular distributions, while some missense mutation (C54F and L180S) can not. The axonal integrity and coherence in the region of sensorimotor area of the brain was damaged in DYT6 dystonia.