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Background: Epilepsy is a chronic neurological disorder affecting individuals globally, marked by recurrent and apparently unpredictable seizures that pose significant challenges, including increased mortality, injuries, and diminished quality of life. Despite advancements in treatments, a significant proportion of people with epilepsy continue to experience uncontrolled seizures. The apparent unpredictability of these events has been identified as a major concern for people with epilepsy, highlighting the need for innovative seizure forecasting technologies., Objective: The ATMOSPHERE study aimed to develop and evaluate a digital intervention, using wearable technology and data science, that provides real-time, individualized seizure forecasting for individuals living with epilepsy. This paper reports the protocol for one of the workstreams focusing on the design and testing of a prototype to capture real-time input data needed for predictive modeling. The first aim was to collaboratively design the prototype (work completed). The second aim is to conduct an "in-the-wild" study to assess usability and refine the prototype (planned research)., Methods: This study uses a person-based approach to design and test the usability of a prototype for real-time seizure precipitant data capture. Phase 1 (work completed) involved co-design with individuals living with epilepsy and health care professionals. Sessions explored users' requirements for the prototype, followed by iterative design of low-fidelity, static prototypes. Phase 2 (planned research) will be an "in-the-wild" usability study involving the deployment of a mid-fidelity, functional prototype for 4 weeks, with the collection of mixed methods usability data to assess the prototype's real-world application, feasibility, acceptability, and engagement. This phase involves primary participants (adults diagnosed with epilepsy) and, optionally, their nominated significant other. The usability study will run in 3 rounds of deployment and data collection, aiming to recruit 5 participants per round, with prototype refinement between rounds., Results: The phase-1 co-design study engaged 22 individuals, resulting in the development of a mid-fidelity, functional prototype based on identified requirements, including the tracking of evidence-based and personalized seizure precipitants. The upcoming phase-2 usability study is expected to provide insights into the prototype's real-world usability, identify areas for improvement, and refine the technology for future development. The estimated completion date of phase 2 is the last quarter of 2024., Conclusions: The ATMOSPHERE study aims to make a significant step forward in epilepsy management, focusing on the development of a user-centered, noninvasive wearable device for seizure forecasting. Through a collaborative design process and comprehensive usability testing, this research aims to address the critical need for predictive seizure forecasting technologies, offering a promising approach to improving the lives of individuals with epilepsy. By leveraging predictive analytics and personalized machine learning models, this technology seeks to offer a novel approach to managing epilepsy, potentially improving clinical outcomes, including quality of life, through increased predictability and seizure management., International Registered Report Identifier (irrid): DERR1-10.2196/60129., (©Emily E V Quilter, Samuel Downes, Mairi Therese Deighan, Liz Stuart, Rosie Charles, Phil Tittensor, Leandro Junges, Peter Kissack, Yasser Qureshi, Aravind Kumar Kamaraj, Amberly Brigden. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 19.09.2024.)

Background: Multiple system atrophy is a neurodegenerative disease with α-synuclein aggregation in glial cytoplasmic inclusions, leading to dysautonomia, parkinsonism, and cerebellar ataxia., Objective: The aim of this study was to validate the accuracy of the International Parkinson and Movement Disorder Society Multiple System Atrophy clinical diagnostic criteria, particularly considering the impact of the newly introduced brain magnetic resonance imaging (MRI) markers., Methods: Diagnostic accuracy of the clinical diagnostic criteria for multiple system atrophy was estimated retrospectively in autopsy-confirmed patients with multiple system atrophy, Parkinson's disease, progressive supranuclear palsy, and corticobasal degeneration., Results: We identified a total of 240 patients. Sensitivity of the clinically probable criteria was moderate at symptom onset but improved with disease duration (year 1: 9%, year 3: 39%, final ante mortem record: 77%), whereas their specificity remained consistently high (99%-100% throughout). Sensitivity of the clinically established criteria was low during the first 3 years (1%-9%), with mild improvement at the final ante mortem record (22%), whereas specificity remained high (99%-100% throughout). When MRI features were excluded from the clinically established criteria, their sensitivity increased considerably (year 1: 3%, year 3: 22%, final ante mortem record: 48%), and their specificity was not compromised (99%-100% throughout)., Conclusions: The International Parkinson and Movement Disorder Society multiple system atrophy diagnostic criteria showed consistently high specificity and low to moderate sensitivity throughout the disease course. The MRI markers for the clinically established criteria reduced their sensitivity without improving specificity. Combining clinically probable and clinically established criteria, but disregarding MRI features, yielded the best sensitivity with excellent specificity and may be most appropriate to select patients for therapeutic trials. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society., (© 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.)

Biallelic pathogenic variants in the PNPLA6 gene cause a broad spectrum of disorders leading to gait disturbance, visual impairment, anterior hypopituitarism and hair anomalies. PNPLA6 encodes neuropathy target esterase (NTE), yet the role of NTE dysfunction on affected tissues in the large spectrum of associated disease remains unclear. We present a systematic evidence-based review of a novel cohort of 23 new patients along with 95 reported individuals with PNPLA6 variants that implicate missense variants as a driver of disease pathogenesis. Measuring esterase activity of 46 disease-associated and 20 common variants observed across PNPLA6-associated clinical diagnoses unambiguously reclassified 36 variants as pathogenic and 10 variants as likely pathogenic, establishing a robust functional assay for classifying PNPLA6 variants of unknown significance. Estimating the overall NTE activity of affected individuals revealed a striking inverse relationship between NTE activity and the presence of retinopathy and endocrinopathy. This phenomenon was recaptured in vivo in an allelic mouse series, where a similar NTE threshold for retinopathy exists. Thus, PNPLA6 disorders, previously considered allelic, are a continuous spectrum of pleiotropic phenotypes defined by an NTE genotype:activity:phenotype relationship. This relationship, and the generation of a preclinical animal model, pave the way for therapeutic trials, using NTE as a biomarker., (Published by Oxford University Press on behalf of the Guarantors of Brain 2024.)