Biomarkers for Diagnosis and Treatment Response in Pediatric Acute-Onset Neuropsychiatric Syndrome (PANS)

The specific aim 1 is the Neurophysiological and clinical characterization of sleep and Electroencephalographic (EEG) patterns. This aim focuses on the systematic characterization of sleep architecture and EEG features in pediatric patients with Pediatric Acute Neuropsychiatric Syndrome (PANS), a domain that remains largely unexplored despite growing clinical evidence of sleep disturbances in this population. Preliminary reports and consensus guidelines suggest the presence of nonspecific EEG abnormalities, including focal or generalized slowing and, less frequently, epileptiform activity. However, no structured, systematic evaluation has been conducted to define their prevalence, clinical correlates, and longitudinal evolution.

Polysomnographic studies in PANS suggest a high burden of sleep disturbances, including insomnia, parasomnias, periodic limb movement disorder, and Rapid Eye Movement stage (REM) sleep abnormalities such as REM sleep without atonia and REM behavior disorder. These alterations may contribute to daytime cognitive dysfunction, attentional deficits, fatigue, and "brain fog," which are commonly reported in affected children. All enrolled patients will undergo standardized overnight polysomnography and EEG recording at baseline and after treatment. Sleep architecture, respiratory parameters, limb movements, and EEG activity will be analyzed according to American Academy of Sleep Medicine (AASM) criteria. The aim is to define objective neurophysiological markers associated with disease severity and clinical symptom clusters.

A cohort of at least 50 pediatric patients (3-18 years) with a clinical diagnosis of PANS will be recruited at the Child and Adolescent Neuropsychiatry Unit of the Azienda Ospedaliero Universitaria (AOU) Policlinico "G. Martino" in Messina. Diagnosis will be confirmed independently by two child neuropsychiatrists according to established consensus criteria. Clinical characterization will include standardized assessments of symptom severity and functioning, including psychometric scales, and cognitive evaluation using age-appropriate intellectual evaluation through the Wechsler scales. A detailed clinical history will be collected, including the disease course, infectious triggers, autoimmune comorbidities, family history, and treatment response.

A control group of at least 30 age- and sex-matched neurotypical subjects will be enrolled. Exclusion criteria include major medical, neurological, or psychiatric conditions and current immunomodulatory treatments.

All participants will undergo comprehensive laboratory screening to exclude systemic conditions and will be evaluated using standardized cognitive and neuropsychological batteries. Sleep assessment will include a clinical interview, overnight polysomnography, and a standard EEG recording, all performed within the same week as the clinical evaluation. Sleep scoring will follow AASM criteria and will be conducted by experienced sleep medicine specialists. Data from clinical, neuropsychological, neurophysiological, genetic, and molecular assessments will be integrated into a unified database for multilevel correlation analyses.

The specific Aim 2 regards the identification of molecular, genetic, and metabolomic biomarkers. This aim is designed to identify biological markers associated with PANS onset, clinical heterogeneity, and treatment response using a multi-omics approach that integrates genetic, transcriptomic, and metabolic data. Genetic susceptibility will be investigated using whole-exome sequencing (WES) in parent-proband trios, with a focus on de novo and ultra-rare variants affecting immune regulation, microglial function, and synaptic pathways that have been implicated in neurodevelopmental disorders. Circulating microRNAs (miRNAs) will be profiled by Ribonucleic Acid (RNA) sequencing of whole-blood samples to identify dysregulated miRNA signatures that may reflect central nervous system immune and synaptic alterations. Selected findings will be validated by Reverse Transcription-Quantitative Polymerase Chain Reaction (RT-qPCR), and bioinformatic analyses will be used to define affected molecular pathways. Metabolomic profiling will be performed using Proton Nuclear Magnetic Resonance (¹H-NMR) spectroscopy to characterize serum metabolic signatures associated with PANS and to assess correlations with symptom severity. In addition, plasma levels of brain-derived neurotrophic factor (BDNF) and markers of oxidative stress and inflammation (e.g., IL-6 and kynurenine pathway metabolites) will be quantified to assess neuroimmune and neurotrophic dysregulation. Collectively, these approaches aim to identify convergent biomarker signatures reflecting underlying disease mechanisms and clinically relevant phenotypes. For reach this aim, Serum samples will be analyzed using 1H-NMR spectroscopy for untargeted metabolomic profiling. Multivariate statistical analyses will be applied to identify metabolic signatures differentiating PANS patients from controls and to explore correlations with clinical severity. Genetic analyses will be conducted using whole-exome sequencing in parent-proband trios to identify rare and de novo variants that may be involved in immune regulation and synaptic function. miRNA profiling will be performed on whole blood using next-generation sequencing platforms, followed by validation through RT-qPCR. Bioinformatic analyses will identify enriched pathways and predicted gene targets. Plasma and serum biomarkers, including BDNF, inflammatory cytokines, and oxidative stress markers, will be quantified using standardized biochemical assays.

Finally, specific Aim 3 is the translational investigation using a maternal immune activation (MIA) animal model to provide causal mechanisms underlying PANS-related phenotypes. A maternal immune activation (MIA) model will be used to mimic prenatal immune challenge and its impact on neurodevelopment. Pregnant Sprague-Dawley rats will receive poly(I:C) during gestation to induce a controlled maternal immune response. Offspring will be evaluated during postnatal development and adulthood using behavioral paradigms assessing stereotyped behavior, social interaction, and cognitive performance. Neurophysiological alterations will be assessed through in vivo electrophysiological recordings in the ventral tegmental area and prefrontal cortex, focusing on dopaminergic and cortical circuit activity. Fast-scan cyclic voltammetry will be used to evaluate dopamine dynamics in the nucleus accumbens. Complementary ex vivo patch-clamp and multi-electrode array recordings will further characterize neuronal excitability and network connectivity. Molecular analyses will include quantification of miRNA expression, gene expression profiles, and biochemical markers of neuroinflammation, oxidative stress, and neurotrophic signaling in brain tissue and blood. Cross-species comparisons will be performed to identify conserved molecular signatures between human PANS patients and the MIA model.

MIA will be induced in pregnant Sprague-Dawley rats using poly(I:C) administration during gestation. Offspring will be evaluated for behavioral, cognitive, and social phenotypes using standardized paradigms, including stereotypy assessment, three-chamber social interaction tests, and novel object recognition. Neurophysiological recordings will be performed in vivo and ex vivo to assess dopaminergic and cortical circuit function. Dopamine dynamics will be measured in the nucleus accumbens using fast-scan cyclic voltammetry.

Molecular analyses will include gene expression and miRNA profiling in brain regions and peripheral blood, alongside quantification of inflammatory, oxidative, and neurotrophic markers using enzyme-linked immunosorbent assay (ELISA), Western blot, high-performance liquid chromatography (HPLC), and RT-qPCR.

• Expression levels of selected microRNAs [Срок оценки: From the biological samples collection to the end of analysis, an average of 2 years]
• Metabolomic profile [Срок оценки: From the biological samples collection to the end of analysis, an average of 2 years]
• Frequency of pathogenic and likely pathogenic genetic variants [Срок оценки: From the biological samples collection to the end of analysis, an average of 2 years]
• Molecular signatures in the maternal immune activation model [Срок оценки: From the biological samples collection to the end of analysis, an average of 2 years]
• Diagnostic performance of candidate biomarkers [Срок оценки: From enrollment through study completion (approximately 36 months)]