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Mutant huntingtin induces neuronal apoptosis via derepressing the non-canonical poly(A) polymerase PAPD5.
MicroRNAs (miRNAs) are small non-coding RNAs that play crucial roles in post-transcriptional gene regulation. Poly(A) RNA polymerase D5 (PAPD5) catalyzes the addition of adenosine to the 3' end of miRNAs. In this study, we demonstrate that the Yin Yang 1 protein, a transcriptional repressor of PAPD5, is recruited to both RNA foci and protein aggregates, resulting in an upregulation of PAPD5 expression in Huntington's disease (HD). Additionally, we identify a subset of PAPD5-regulated miRNAs with increased adenylation and reduced expression in our disease model. We focus on miR-7-5p and find that its reduction causes the activation of the TAB2-mediated TAK1-MKK4-JNK pro-apoptotic pathway. This pathway is also activated in induced pluripotent stem cell-derived striatal neurons and post-mortem striatal tissues isolated from HD patients. In addition, we discover that a small molecule PAPD5 inhibitor, BCH001, can mitigate cell death and neurodegeneration in our disease models. This study highlights the importance of PAPD5-mediated miRNA dysfunction in HD pathogenesis and suggests a potential therapeutic direction for the disease.
Detection of formal thought disorders in child and adolescent psychosis using machine learning and neuropsychometric data
IntroductionFormal Thought Disorder (FTD) is a significant clinical feature of early-onset psychosis, often associated with poorer outcomes. Current diagnostic methods rely on clinical assessment, which can be subjective and time-consuming. This study aimed to investigate the potential of neuropsychological tests and machine learning to differentiate individuals with and without FTD.MethodsA cohort of 27 young people with early-onset psychosis was included. Participants underwent neuropsychological assessment using the Iowa Gambling Task (IGT) and Simple Reaction Time (SRT) tasks. A range of machine learning models (Logistic Regression (LR), Support Vector Machines (SVM), Random Forest (RF) and eXtreme Gradient Boosting (XGBoost)) were employed to classify participants into FTD-positive and FTD-negative groups based on these neuropsychological measures and their antipsychotic regimen (medication load in chlorpromazine equivalents).ResultsThe best performing machine learning model was LR with mean +/- standard deviation of cross validation Receiver Operating Characteristic Area Under Curve (ROC AUC) score of 0.850 (+/- 0.133), indicating moderate-to-good discriminatory performance. Key features contributing to the model’s accuracy included IGT card selections, SRT reaction time (most notably standard deviation) and chlorpromazine equivalent milligrams. The model correctly classified 24 out of 27 participants.DiscussionThis study demonstrates the feasibility of using neuropsychological tests and machine learning to identify FTD in early-onset psychosis. Early identification of FTD may facilitate targeted interventions and improve clinical outcomes. Further research is needed to validate these findings in larger, more diverse populations and to explore the underlying neurocognitive mechanisms.
Diagnosis and Management of Multifocal Motor Neuropathy in the United Kingdom: A Multicentre Survey
ABSTRACTBackgroundWe conducted a survey to determine the current diagnosis and treatment of multifocal motor neuropathy (MMN) in the United Kingdom.MethodsDemographic, diagnostic and treatment data were collected at nine UK neuroscience centres.ResultsNinety‐five subjects were included. Mean age at diagnosis was 49.9 years (SD: 11.4). Males were more commonly affected (ratio: 1.9:1). Diagnostic delay was > 1 year from the time of first neurological assessment, in > 50% of subjects. Applying modified EFNS/PNS 2010 criteria, 69/95 (72.6%) had definite MMN, 10/95 (10.5%) had probable MMN, 15/95 (15.8%) had possible MMN, through treatment responsiveness in 9/15 (60%) and 1/95 (1.1%) did not meet criteria. Cerebrospinal fluid examination, anti‐GM1 antibody testing and brachial plexus magnetic resonance imaging were non‐contributory. Immunoglobulin response was reported in 90/92 subjects (97.8%), and 84/90 (93.3%) remained on treatment after a mean of 9.4 years, at a mean dose of 26.2 g/week (range: 4–114). Mean long‐term immunoglobulin dose was 30%–60% higher than reported in neighbouring countries. Contrasting with previous reports of frequent loss of immunoglobulin response and functional decline, our physician‐assessed long‐term outcome was favourable (stable or improving) in 74/84 (88.1%) treated subjects.InterpretationMMN diagnosis and treatment in the United Kingdom are comparable to that of neighbouring countries and follow existing guidelines. Diagnostic delay after the first neurological assessment is considerable. Electrophysiology shows at least one definite/probable conduction block in nearly 90% of cases. The mean long‐term immunoglobulin dose is higher in the United Kingdom than reported elsewhere, although highly variable. Whether higher doses of immunoglobulin may improve long‐term outcomes requires further study.