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Spinocerebellar ataxia type 3/Machado–Joseph disease (SCA3/MJD) is a progressive autosomal dominant neurodegenerative disease caused by abnormal CAG repeats in the exon 10 of ATXN3. The accumulation of the mutant ataxin-3 proteins carrying expanded polyglutamine (polyQ) leads to selective degeneration of neurons. Since the pathogenesis of SCA3 has not been fully elucidated, and no effective therapies have been identified, it is crucial to investigate the pathogenesis and seek new therapeutic strategies of SCA3. Induced pluripotent stem cells (iPSCs) can be used as the ideal cell model for the molecular pathogenesis of polyQ diseases. Abnormal CAG expansions mediated by CRISPR/Cas9 genome engineering technologies have shown promising potential for the treatment of polyQ diseases, including SCA3. In this study, SCA3-iPSCs can be corrected by the replacement of the abnormal CAG expansions (74 CAG) with normal repeats (17 CAG) using CRISPR/Cas9-mediated homologous recombination (HR) strategy. Besides, corrected SCA3-iPSCs retained pluripotent and normal karyotype, which can be differentiated into a neural stem cell (NSCs) and neuronal cells, and maintained electrophysiological characteristics. The expression of differentiation markers and electrophysiological characteristics were similar among the neuronal differentiation from normal control iPSCs (Ctrl-iPSCs), SCA3-iPSCs, and isogenic control SCA3-iPSCs. Furthermore, this study proved that the phenotypic abnormalities in SCA3 neurons, including aggregated IC2-polyQ protein, decreased mitochondrial membrane potential (MMP) and glutathione expressions, increased reactive oxygen species (ROS), intracellular Ca2+ concentrations, and lipid peroxidase malondialdehyde (MDA) levels, all were rescued in the corrected SCA3-NCs. For the first time, this study demonstrated the feasibility of CRISPR/Cas9-mediated HR strategy to precisely repair SCA3-iPSCs, and reverse the corresponding abnormal disease phenotypes. In addition, the importance of genetic control using CRISPR/Cas9-mediated iPSCs for disease modeling. Our work may contribute to providing a potential ideal model for molecular mechanism research and autologous stem cell therapy of SCA3 or other polyQ diseases, and offer a good gene therapy strategy for future treatment.

Background Spinocerebellar ataxia type 3 (SCA3) is the most common subtype of SCA without effective treatment. This study aimed to evaluate the comparative efficacy of low-frequency repetitive transcranial magnetic stimulation (rTMS) and intermittent Theta Burst Stimulation (iTBS) in a larger cohort of SCA3 patients. Methods One hundred and twenty patients with SCA3 were randomly assigned to the 3 groups: 40 patients in the 1 Hz rTMS, 40 in the iTBS and 40 in the sham group. Patients underwent 10 sessions of rTMS targeting the cerebellum delivering for 5 consecutive days per week for 2 weeks (a total of 1200 pulses per session). Primary outcomes included the Scale for the Assessment and Rating of Ataxia (SARA) and the International Cooperative Ataxia Rating Scale (ICARS). Secondary outcomes included 10-m walking test (10MWT), nine-hole peg test (9-HPT), and PATA Rate Test (PRT). Outcome assessments were performed at baseline and on the last day of rTMS intervention. Results This study revealed that active rTMS outperformed sham in reducing the SARA and ICARS scores in SCA3 patients, but with no difference between the 1 Hz rTMS and iTBS protocol. Moreover, no significant differences were observed in SARA and ICARS scores between the mild and moderate to severe groups after the 1 Hz rTMS/iTBS therapy. Additionally, no severe adverse events were recorded in this study. Conclusions The study concluded that both 1 Hz rTMS and iTBS interventions targeting the cerebellum are effective to improve the symptoms of ataxia in patients with SCA3.

Leukodystrophies are genetic disorders leading to progressive white matter degeneration in the central nervous system. Mitochondrial aminoacyl tRNA synthase protein is encoded by the nuclear gene AARS2. An autosomal recessive mutation in this gene has been linked to AARS2 mutation-related adult-onset leukodystrophy (AARS2-L) or infantile mitochondrial cardiomyopathy. To date, only 16 AARS2-L cases have been reported in English literature. Thus, the clinical and genetic characteristics of this disease remain to be defined. Through whole-exome sequencing, we identified a Chinese patient with leukodystrophy related to two novel compounds heterozygous mutation in AARS2 (c.965 G > A, p.R322H; c.334 G > C, p.G112R). These two compounds heterozygous variants in AARS2 gene co-segregated with disease in his family. And pyramidal tracts in the spinal cord were involved. Our findings have important implications on genetic counseling for any case with leukodystrophy and extend the mutational spectrum in AARS2 gene.

Background In polyglutamine (polyQ) diseases, the identification of modifiers and the construction of prediction model for progression facilitate genetic counseling, clinical management and therapeutic interventions. Methods Data were derived from the longest longitudinal study, with 642 examinations by International Cooperative Ataxia Rating Scale (ICARS) from 82 SCA3 participants. Using different time scales of disease duration, we performed multiple different linear, quadratic and piece-wise linear growth models to fit the relationship between ICARS scores and duration. Models comparison was employed to determine the best-fitting model according to goodness-of-fit tests, and the analysis of variance among nested models. Results An acceleration was detected after 13 years of duration: ICARS scores progressed 2.445 (SE: 0.185) points/year before and 3.547 (SE: 0.312) points/year after this deadline. Piece-wise growth model fitted better to studied data than other two types of models. The length of expanded CAG repeat (CAGexp) in ATXN3 gene significantly influenced progression. Age at onset of gait ataxia (AOga), a proxy for aging process, was not an independent modifier but affected the correlation between CAGexp and progression. Additionally, gender had no significant effect on progression rate of ICARS. The piece-wise growth models were determined as the predictive models, and ICARS predictions from related models were available. Conclusions We first confirmed that ICARS progressed as a nonlinear pattern and varied according to different stages in SCA3. In addition to ATXN3 CAGexp, AOga or aging process regulated the progression by interacting with CAGexp.

Existing treatments can only delay the progression of spinocerebellar ataxia type 3/Machado-Joseph disease (SCA3/MJD) after onset, so the prediction of the age at onset (AAO) can facilitate early intervention and follow-up to improve treatment efficacy. The objective of this study was to develop an explainable artificial intelligence (XAI) based on feature optimization to provide an interpretable and more accurate AAO prediction. A total of 1008 affected SCA3/MJD subjects from mainland China were analyzed. The expanded cytosine-adenine-guanine (CAG) trinucleotide repeats of 10 polyQ-related genes were genotyped and included in related models as potential AAO modifiers. The performance of 4 feature optimization methods and 10 machine learning (ML) algorithms were compared, followed by building the XAI based on the SHapley Additive exPlanations (SHAP). The model constructed with an artificial neural network (ANN) and feature optimization of Crossing-Correlation-StepSVM performed best and achieved a coefficient of determination (R2) of 0.653 and mean absolute error (MAE), root mean square error (RMSE), and median absolute error (MedianAE) of 4.544, 6.090, and 3.236 years, respectively. The XAI explained the predicted results, which suggests that the factors affecting the AAO were complex and associated with gene interactions. An XAI based on feature optimization can improve the accuracy of AAO prediction and provide interpretable and personalized prediction.

Multiple system atrophy (MSA) alters skin physiology, potentially impacting skin microbiota. This pilot study investigated whether skin microbiota differs in MSA and whether these differences relate to disease severity. Using 16S rRNA sequencing of cervical and axillary sites in MSA, Parkinson’s disease, and controls, we identified distinct microbial patterns among groups. These patterns allowed cohort classification and showed strong associations with clinical symptoms, suggesting disease-related microbial alterations in MSA.

Objective: The natural history of spinocerebellar ataxia type 3 (SCA3) has been reported in several populations, and show heterogeneity in progression rate and affecting factors. However, it remains unexplored in the population in mainland China. This study is aimed to identify the disease progression rate and its potential affecting factors in patients with SCA3 in mainland China. Participants and Methods: We enrolled patients with genetically confirmed SCA3 in mainland China. Patients were seen at three visits-baseline, 1 year, and 2 years. The primary outcome was the Scale for the Assessment and Rating of Ataxia (SARA), and the secondary outcomes were the Inventory of Non-Ataxia Signs (INAS) as well as the SCA Functional Index (SCAFI). Results: Between October 1, 2015, and September 30, 2016, we enrolled 263 patients with SCA3. We analyzed 247 patients with at least one follow-up visit. The annual progression rate on SARA was 1.49 points per year (SE 0.08, 95% confidence interval [CI] 1.33-1.65, p < 0.0001). Annual progression of INAS and SCAFI were 0.56 points per year (SE 0.05, 95%CI 0.47-0.66, p < 0.001) and -0.30 points per year (SE 0.01, 95% CI -0.33~-0.28, p < 0.001), respectively. Faster progression in SARA was associated with longer length of expanded allele of ATXN3 (p < 0.0001); faster progression in INAS was associated with lower INAS at baseline (p < 0.0001); faster decline in SCAFI was associated with shorter length of normal allele of ATXN3 (p = 0.036) and higher SCAFI at baseline (p < 0.0001). Conclusion: Our results provide quantitative data on the disease progression of patients with SCA3 in mainland China and corresponding affecting factors, which could facilitate the sample size calculation and patient stratification in the future clinical trials.

Background Multiple-system atrophy is a rapidly progressive neurodegenerative disease with incomplete survival data, limiting the understanding of long-term outcomes. This study aimed to investigate a comprehensive data including survival time and prognostic factors. Methods Individual patient data were pooled from studies reporting Kaplan–Meier curves, and then, survival curves were generated. The pooled median survival times were derived using weighted median of medians approach and hazard ratios of risk factors were analyzed using either fixed- or random-effects model. Results 37 studies involving 6145 patients were included. The median survival time for MSA patients was 8.23 years (95% CI 8.02–8.56) based on reconstructed individual patient data. The pooled weighted median time was 8.0 years (95% CI 7.51–9.0). The following variables were found as unfavorable prognostic factors (hazard ratio with 95% CI are shown): age at onset (1.02, 1.01–1.03), poor levodopa response (1.55, 1.14–2.11), parkinsonism onset (1.30, 1.05–1.62), falls (1.84, 1.4–2.4), dysautonomia onset (1.48, 1.16–1.9), autonomic failure (2.52, 1.42–4.48), orthostatism hypotension (1.39, 1.16–1.66), bladder catheterization (1.81, 1.41–2.31), and stridor (1.5, 1.12–2.02). Conclusion Survival time in MSA was evaluated using multiple methodological approaches, revealing a median survival of 8.0 years, and clinical variables like early autonomic failure and frequently falls were identified as predictors of poor survival outcomes.

Background The longitudinal dynamics of neurofilament light chain (NfL) in multiple system atrophy (MSA) were incompletely illuminated. This study aimed to explore whether the plasma NfL (pNfL) could serve as a potential biomarker of clinical diagnosis and disease progression for MSA. Methods We quantified pNfL concentrations in both a large cross-sectional cohort with 214 MSA individuals, 65 PD individuals, and 211 healthy controls (HC), and a longitudinal cohort of 84 MSA patients. Propensity score matching (PSM) was used to balance the age between the three groups. The pNfL levels between groups were compared using Kruskal–Wallis test. Linear mixed models were performed to explore the disease progression-associated factors in longitudinal MSA cohort. Random forest model as a complement to linear models was employed to quantify the importance of predictors. Results Before and after matching the age by PSM, the pNfL levels could reliably differentiate MSA from HC and PD groups, but only had mild potential to distinguish PD from HC. By combining linear and nonlinear models, we demonstrated that pNfL levels at baseline, rather than the change rate of pNfL, displayed potential prognostic value for progression of MSA. The combination of baseline pNfL levels and other modifiers, such as subtypes, Hoehn–Yahr stage at baseline, was first shown to improve the diagnosis accuracy. Conclusions Our study contributed to a better understanding of longitudinal dynamics of pNfL in MSA, and validated the values of pNfL as a non-invasive sensitive biomarker for the diagnosis and progression. The combination of pNfL and other factors is recommended for better monitoring and prediction of MSA progression.