Background and ObjectivesPurine-rich element-binding protein A (PURA) gene encodes Pur-α, a conserved protein essential for normal postnatal brain development. Recently, a PURA syndrome characterized by intellectual disability, hypotonia, epilepsy, and dysmorphic features was suggested. The aim of this study was to define and expand the phenotypic spectrum of PURA syndrome by collecting data, including EEG, from a large cohort of affected patients.MethodsData on unpublished and published cases were collected through the PURA Syndrome Foundation and the literature. Data on clinical, genetic, neuroimaging, and neurophysiologic features were obtained.ResultsA cohort of 142 patients was included. Characteristics of the PURA syndrome included neonatal hypotonia, feeding difficulties, and respiratory distress. Sixty percent of the patients developed epilepsy with myoclonic, generalized tonic-clonic, focal seizures, and/or epileptic spasms. EEG showed generalized, multifocal, or focal epileptic abnormalities. Lennox-Gastaut was the most common epilepsy syndrome. Drug refractoriness was common: 33.3% achieved seizure freedom. We found 97 pathogenic variants in PURA without any clear genotype-phenotype associations.DiscussionThe PURA syndrome presents with a developmental and epileptic encephalopathy with characteristics recognizable from neonatal age, which should prompt genetic screening. Sixty percent have drug-resistant epilepsy with focal or generalized seizures. We collected more than 90 pathogenic variants without observing overt genotype-phenotype associations.

Study Objectives PANS (pediatric acute onset neuropsychiatric syndrome) is thought to be the result of several mechanisms and multiple etiologies, ranging from endocrine/metabolic causes to postinfectious autoimmune and neuroinflammatory disorders. Sleep disorders represent one of the most frequent manifestations of PANS, involving around 80% of patients. The present study describes the clinical and polysomnographic features in a group of PANS children identifying the relationships between sleep disorders and other PANS symptoms. Methods All participants underwent a clinical evaluation including comprehensive sleep history, polysomnography, cognitive assessment and blood chemistry examination. A data mining approach with fourth-generation artificial neural networks has been used in order to discover subtle trends and associations among variables. Results Polysomnography showed abnormality in 17 out of 23 recruited subjects (73.9%). In particular, 8/17 children (47%) had ineffective sleep, 10/17 (58.8%) fragmented sleep, 8/17 (47.1%) periodic limb movement disorder (PLMD) and 11/17 (64.7%) REM-sleep without atonia (RSWA). Most subjects presented more than one sleep disturbances. Notably, among the 19/23 patients diagnosed with Tic/Tourette disorder, 8/19 (42.1%) show PLMD and 10/19 (52.6%) RSWA. Artificial neural network methodology and the auto-contractive map exploited the links among the full spectrum of variables revealing the simultaneous connections among them, facing the complexity of PANS phenotype. Conclusion Disordered sleep represents, for prevalence and impact on quality of life, a cardinal symptom in patients with PANS. Thus, considering the weight of sleep disturbances on diagnosis and prognosis of PANS, we could consider the possibility of including them among the major diagnostic criteria.

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