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RECRUITING
NCT07718958

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

Sponsor: University of Cagliari

View on ClinicalTrials.gov

Summary

Pediatric Acute-onset Neuropsychiatric Syndrome (PANS) is a complex neuropsychiatric disorder characterized by the abrupt onset of symptoms and currently diagnosed mainly on clinical criteria, as reliable diagnostic biomarkers are still lacking. The primary objective of this project is to identify and validate a panel of neurophysiological, molecular, genetic, and metabolomic biomarkers associated with disease onset, clinical trajectory, and response to antimicrobial, anti-inflammatory, and immunomodulatory treatments. Identifying objective biomarkers will improve diagnostic accuracy, facilitate earlier diagnosis, clarify disease mechanisms, and support the development of more targeted therapeutic strategies. PANS is currently considered a multifactorial immune-mediated inflammatory brain disorder resulting from the interaction of genetic susceptibility, immune dysregulation, infections, and environmental factors such as stress or trauma. Current evidence suggests that both innate and adaptive immune responses contribute to disease pathophysiology through interactions between the peripheral immune system and the central nervous system. The pathogenic process may begin during fetal life through Maternal Immune Activation (MIA), whereby maternal infections or immune dysregulation induce inflammatory responses that increase susceptibility to neurodevelopmental disorders. During the postnatal period, infectious agents, including viruses, Mycoplasma pneumoniae, and Haemophilus influenzae, may trigger immune activation, leading to blood-brain barrier disruption, glial activation, and abnormalities within cortico-basal ganglia circuits thought to underlie PANS symptoms. To achieve these objectives, the project will adopt a multidisciplinary translational approach that combines the enrolment and characterization of pediatric patients with PANS with complementary studies in animal models. Particular emphasis will be placed on clinical and sleep features, together with molecular and metabolomic profiling, to identify biomarkers with diagnostic and prognostic value and to investigate the biological pathways underlying disease onset and progression. Given the high clinical, social, and economic burden of PANS, which frequently follows a chronic or relapsing-remitting course requiring long-term healthcare support, earlier diagnosis and a better understanding of disease mechanisms could significantly improve patient management. More broadly, the project will contribute to understanding the immune-mediated pathogenic pathways underlying PANS and related neurodevelopmental disorders, supporting the transition from symptom-based classification toward mechanism-based diagnosis and treatment.

Official title: BIOMA-PANS - Diagnostic and Treatment-response BIOMArkers in Children and Adolescents With PANS (Pediatric Acute-onset Neuropsychiatric Syndrome)

Key Details

Gender

All

Age Range

3 Years - 18 Years

Study Type

OBSERVATIONAL

Enrollment

80

Start Date

2024-08-08

Completion Date

2027-02-28

Last Updated

2026-07-22

Healthy Volunteers

Yes

Interventions

DIAGNOSTIC_TEST

Psycodiagnostic evaluation

Psycodiagnostic scales and tests to identify and quantify symptoms: Pediatric Acute Neuropsychiatric Symptom Scale (PANSS); Children's Yale-Brown Obsessive-Compulsive Scale (CY-BOCS); punteggio Yale Global Tic Severity Scale (YGTSS); Pediatric Anxiety Rating Scale (PARS); Children's Global Assessment Scale (C-GAS). Il quoziente intellettivo (QI) sarà misurato mediante la WPPSI-III (Wechsler Preschool and Primary Scale of Intelligence- III) o la WISC-IV (Wechsler Intelligence Scale for Children - IV), according to children's age

DIAGNOSTIC_TEST

Polysomnography

will be performed by means of a video complete polysomnography (PSG), following the AASM standard criteria. The following parameters will be included in the PSG study: EEG, electrooculogram, electromyogram (EMG) of submental muscle, EMG of bilateral tibialis anterior muscle and one single-lead ECG. The sleep respiratory pattern will be assessed by means of nasal airflow, thoracic and abdominal respiratory effort, and oxygen saturation, during the study night. Sleep signals will be stored on hard disk in European data format for further analysis. The polysomnographic parameters to be evaluated are: Total Sleep Time (TST), Sleep Efficiency (SE), Sleep Latency (SL), REM Latency, N1% TST, N2% TST, N3% TST, REM% TST, Wake After Sleep Onset % (WASO%), Awakenings, Periodic Limb Movement Index (PLMI), RSWA (REM Sleep Without Atonia), RAI (REM atonia index), and the presence of frequent change position. Standard EEG will be performed following International 10-20 system

DIAGNOSTIC_TEST

1H-NMR analysis

the samples will be analyzed with a Varian UNITY INOVA 500 spectrometer, which will operate at 499 MHz and equip with a 5 mm triple resonance probe with z-axis pulsed field gradients and an auto-sampler with 50 locations. One dimensional 1H-NMR spectra will be collected at 300 K with a pre-sat pulse sequence to suppress the residual water's signal. The spectra will be recorded with a spectral width of 6,000 Hz; a frequency of 2 Hz; an acquisition time of 1.5 s; a relaxation delay of 2 ms; and a 90 pulse of 9.5 ms. The number of scans will be at least of 250. Using MestReNova software, each 1H-NMR spectrum will be divided into consecutive "bins" of 0.04 ppm. A spectral area will be selected for the investigation, excluding the other regions in order to remove variations in the pre-saturation of the residual water resonance and spectral regions of noise. The study aims to isolate genomic DNA from PANS patients' peripheral blood leukocytes. Whole-exome sequencing (WES) analysis will be c

DIAGNOSTIC_TEST

miRNA sequencing

miRNA sequencing will be performed at the Center for Omics Sciences facility at IRCCS Ospedale San Raffaele. Bioinformatic analysis will be performed on the raw data obtained from sequencing. To detect differentially expressed miRNAs, a negative binomial regression considering several biological covariates will be used, and miRNAs with log2(FC)\>\|1 a p-value\<0.05 will be selected. Multiple testing correction will be applied to control the false-discovery rate using the Benjamini-Hochberg (BH) procedure. Blood level expression of selected miRNAs will be evaluated by qPCR. Plasma/Serum levels of selected markers will be evaluated by qPCR, western blot or ELISA analyses.

Locations (5)

Centro di Medicina del Sonno, SC Neurologia, AOU Cagliari

Cagliari, Cagliari, Italy

Università degli Studi eCampus

Novedrate, CO, Italy

UOC Neuropsichiatria

Troina, Enna, Italy

Azienda Ospedaliera Universitaria Gaetano Martino

Messina, Messina, Italy

Dipartimento di Scienze Psicologiche, Pedagogiche, dell¿Esercizio Fisico e della Formazione

Palermo, Palermo, Italy