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

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

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.

Study Overview

• Status: Recruiting
• Conditions: PANS; Pediatric Acute-Onset Neuropsychiatric Syndrome
• Intervention / Treatment: Diagnostic test: Psycodiagnostic evaluation; Diagnostic test: Polysomnography; Diagnostic test: 1H-NMR analysis; Diagnostic test: miRNA sequencing

Detailed Description

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.

• Study Type: Observational
• Enrollment (Estimated): 80

Contacts and Locations

• Study Contact: Name: Monica MF Puligheddu, MD, PHD; Phone Number: 070 5109 6016; Email: puligheddu@unica.it
• Study Contact Backup: Name: Antonella Gagliano, MD, PhD; Email: agagliano@oasi.en.it

Study Locations

• Italy
  • CO
    • Novedrate, CO, Italy, 22060
      • Active, not recruiting
      • Università degli Studi eCampus
  • Cagliari
    • Cagliari, Cagliari, Italy, 09042
      • Active, not recruiting
      • Centro di Medicina del Sonno, SC Neurologia, AOU Cagliari
  • Enna
    • Troina, Enna, Italy, 94018
      • Active, not recruiting
      • UOC Neuropsichiatria
  • Messina
    • Messina, Messina, Italy, 98124
      • Recruiting
      • Azienda Ospedaliera Universitaria Gaetano Martino
      • Contact: Eva Germanò, MD, PhD; Phone Number: +39 090 221 2672; Email: protocollo@pec.polime.it
  • Palermo
    • Palermo, Palermo, Italy, 90128
      • Active, not recruiting
      • Dipartimento di Scienze Psicologiche, Pedagogiche, dell¿Esercizio Fisico e della Formazione

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

The study population consists of children and adolescents with a diagnosis of Pediatric Acute-onset Neuropsychiatric Syndrome (PANS) recruited at the referral center, together with age- and sex-matched neurotypical healthy controls recruited from the same geographical area.

Description

Inclusion Criteria:

• (I) PANS diagnosis made according to 2010 NIH criteria

Exclusion Criteria (for the PANS group):

• (I) onset of specific rheumatologic or immunologic diseases;
• (II) presence of a diagnosed cancer or other severe medical illnesses;
• (III) active treatment with steroidal or non-steroidal anti-inflammatory drugs

The control group must include children without autoimmune diseases, neurodevelopmental or psychiatric disorders, and with adequate academic performance and functional level.

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
PANS group; Children and adolescents diagnosed with Pediatric Acute-onset Neuropsychiatric Syndrome (PANS) undergoing clinical, neurophysiological, genetic, metabolomic, miRNA and sleep assessments.	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.
Healthy Controls; Age- and sex-matched neurotypical children without autoimmune, neurodevelopmental or psychiatric disorders undergoing the same assessment protocol for comparison.	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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The primary outcome is the xperimental demonstration that the effects of inflammatory response in CNS is represented by the behavioral and cognitive changes and sleep alterations typically found in PANS.	This outcome aims to corroborate the current evidence on the neuroinflammatory substrate of PANS. Starting from the assumption that brain inflammatory reactions may promote the development of neuropsychiatric symptoms, the study is aimed to enhance the knowledge on the role of specific inflammatory pathways able to deteriorate the neurocircuitry and neurotransmitter systems. Thus, the first expected outcome of this study is the experimental demonstration that the effects of inflammatory response in CNS is represented by the behavioral and cognitive changes typically found in PANS, as well as other neurodevelopmental and psychiatric disorders. In fact, PANS represents the prototypical feature of psychiatric symptoms occurring as a result of an inflammatory state of the CNS. Overcoming the rigid categorical approach, PANS can be seen as one of the possible phenotypic manifestations of the complex pathogenic pathways leading to neurodevelopmental disorders and psychiatric symptoms.	From the enrollment through study completion, an average of 36 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Identification of molecular mechanisms and biological signatures	The combination of metabolomic, genetic, and epigenetic microRNA analyses in PANS patients and in the MIA model, with back translation of human data into rodents. Alteration of genetic, miRNA and metabolomics signatures, as well as the dysregulation of sleep, could represent fundamental key factors which predisposes the behavioral changes by affecting the BBB integrity, the neurotransmitters and the ion channels and receptors, and vice versa. The use of next generation sequencing platforms has demonstrated its reliability and accuracy in screening genetic diseases in particular whole exome sequencing is a very powerful gene discovery tool used to identify ultra-rare genetic factors underlying disease pathogenesis. Therefore, we expect, using next generation sequencing, to shed new light on the complex interaction between the immune dysregulation and acute neuropsychiatric manifestations. MiRNomic analysis will identify select miRNAs (and related target genes) altered in PANS patients.	From the biological samples collection to the end of analysis, an average of 2 years
Development of a translational model	Translating the clinical data to a newly established animal model of PANS (which has been lacking in this field) will add value to the project. We believe that our proposal will expand the knowledge of the mechanisms responsible for PANS and shed light on the role of genetic variants, metabolic and miRNA alterations.	from the start of the study to the first year
Identification of biomarkers and future therapeutic implications	Finally, the identification of predictive and diagnostic markers will lead to the development of new therapeutic strategies for PANS patients. A lack of a strong rationale for using therapeutic strategies based on the regulation of inflammatory responses for psychiatric disorders had strongly delayed the exploration of potential treatments. Therefore, the final expected outcome, is a stimulus to perform RCTs aimed to verify efficacy and tolerability of treatments (steroids, IVIGs, plasma exchange, rituximab, etc), not only for PANS, but also for a constellation of psychiatric symptoms arising from the brain inflammation.	From the enrollment From the enrollment through study completion, an average of 36 months

Collaborators and Investigators

• Sponsor: University of Cagliari
• Collaborators: University of Palermo; Azienda Ospedaliera Universitaria Policlinico "G. Martino"; Azienda Ospedaliero Universitaria di Cagliari; Oasi Research Institute-IRCCS; Universita Telematica E-Campus

Publications and helpful links

General Publications

• Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, Grody WW, Hegde M, Lyon E, Spector E, Voelkerding K, Rehm HL; ACMG Laboratory Quality Assurance Committee. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015 May;17(5):405-24. doi: 10.1038/gim.2015.30. Epub 2015 Mar 5.
• Swedo E. from research subgroup to clinical syndrome: modifying the PANDAS criteria to describe PANS (Pediatric Acute-onset Neuropsychiatric Syndrome). Pediatr Ther. 2012;02(02). doi:10.41 72/2161-0665.1000113
• Santoni M, Sagheddu C, Serra V, Mostallino R, Castelli MP, Pisano F, Scherma M, Fadda P, Muntoni AL, Zamberletti E, Rubino T, Melis M, Pistis M. Maternal immune activation impairs endocannabinoid signaling in the mesolimbic system of adolescent male offspring. Brain Behav Immun. 2023 Mar;109:271-284. doi: 10.1016/j.bbi.2023.02.002. Epub 2023 Feb 4.
• De Felice M, Melis M, Aroni S, Muntoni AL, Fanni S, Frau R, Devoto P, Pistis M. The PPARalpha agonist fenofibrate attenuates disruption of dopamine function in a maternal immune activation rat model of schizophrenia. CNS Neurosci Ther. 2019 May;25(5):549-561. doi: 10.1111/cns.13087. Epub 2018 Nov 21.
• Vetri L, Cali F, Vinci M, Amato C, Roccella M, Granata T, Freri E, Solazzi R, Romano V, Elia M. A de novo heterozygous mutation in KCNC2 gene implicated in severe developmental and epileptic encephalopathy. Eur J Med Genet. 2020 Apr;63(4):103848. doi: 10.1016/j.ejmg.2020.103848. Epub 2020 Jan 20.
• Ieraci A, Beggiato S, Ferraro L, Barbieri SS, Popoli M. Kynurenine pathway is altered in BDNF Val66Met knock-in mice: Effect of physical exercise. Brain Behav Immun. 2020 Oct;89:440-450. doi: 10.1016/j.bbi.2020.07.031. Epub 2020 Jul 26.
• Carini G, Mingardi J, Bolzetta F, Cester A, Bolner A, Nordera G, La Via L, Ieraci A, Russo I, Maggi S, Calza S, Popoli M, Veronese N, Musazzi L, Barbon A. miRNome Profiling Detects miR-101-3p and miR-142-5p as Putative Blood Biomarkers of Frailty Syndrome. Genes (Basel). 2022 Jan 26;13(2):231. doi: 10.3390/genes13020231.
• Musazzi L, Carini G, Barbieri SS, Maggi S, Veronese N, Popoli M, Barbon A, Ieraci A. Phenotypic Frailty Assessment in SAMP8 Mice: Sex Differences and Potential Role of miRNAs as Peripheral Biomarkers. J Gerontol A Biol Sci Med Sci. 2023 Oct 28;78(11):1935-1943. doi: 10.1093/gerona/glad160.
• Hesselmark E, Bejerot S. Biomarkers for diagnosis of Pediatric Acute Neuropsychiatric Syndrome (PANS) - Sensitivity and specificity of the Cunningham Panel. J Neuroimmunol. 2017 Nov 15;312:31-37. doi: 10.1016/j.jneuroim.2017.09.002. Epub 2017 Sep 9.
• Cunningham MW. Rheumatic fever, autoimmunity, and molecular mimicry: the streptococcal connection. Int Rev Immunol. 2014 Jul-Aug;33(4):314-29. doi: 10.3109/08830185.2014.917411. Epub 2014 Jun 3.
• Bejerot S, Hesselmark E. The Cunningham Panel is an unreliable biological measure. Transl Psychiatry. 2019 Jan 31;9(1):49. doi: 10.1038/s41398-019-0413-x. No abstract available.
• Frankovich J, Thienemann M, Pearlstein J, Crable A, Brown K, Chang K. Multidisciplinary clinic dedicated to treating youth with pediatric acute-onset neuropsychiatric syndrome: presenting characteristics of the first 47 consecutive patients. J Child Adolesc Psychopharmacol. 2015 Feb;25(1):38-47. doi: 10.1089/cap.2014.0081.
• Gagliano A, Galati C, Ingrassia M, Ciuffo M, Alquino MA, Tanca MG, Carucci S, Zuddas A, Grossi E. Pediatric Acute-Onset Neuropsychiatric Syndrome: A Data Mining Approach to a Very Specific Constellation of Clinical Variables. J Child Adolesc Psychopharmacol. 2020 Oct;30(8):495-511. doi: 10.1089/cap.2019.0165. Epub 2020 May 28.
• Gagliano A, Carta A, Tanca MG, Sotgiu S. Pediatric Acute-Onset Neuropsychiatric Syndrome: Current Perspectives. Neuropsychiatr Dis Treat. 2023 May 24;19:1221-1250. doi: 10.2147/NDT.S362202. eCollection 2023.
• Gagliano A, Murgia F, Capodiferro AM, Tanca MG, Hendren A, Falqui SG, Aresti M, Comini M, Carucci S, Cocco E, Lorefice L, Roccella M, Vetri L, Sotgiu S, Zuddas A, Atzori L. 1H-NMR-Based Metabolomics in Autism Spectrum Disorder and Pediatric Acute-Onset Neuropsychiatric Syndrome. J Clin Med. 2022 Nov 1;11(21):6493. doi: 10.3390/jcm11216493.
• Murgia F, Gagliano A, Tanca MG, Or-Geva N, Hendren A, Carucci S, Pintor M, Cera F, Cossu F, Sotgiu S, Atzori L, Zuddas A. Metabolomic Characterization of Pediatric Acute-Onset Neuropsychiatric Syndrome (PANS). Front Neurosci. 2021 May 28;15:645267. doi: 10.3389/fnins.2021.645267. eCollection 2021.
• Zheng J, Frankovich J, McKenna ES, Rowe NC, MacEachern SJ, Ng NN, Tam LT, Moon PK, Gao J, Thienemann M, Forkert ND, Yeom KW. Association of Pediatric Acute-Onset Neuropsychiatric Syndrome With Microstructural Differences in Brain Regions Detected via Diffusion-Weighted Magnetic Resonance Imaging. JAMA Netw Open. 2020 May 1;3(5):e204063. doi: 10.1001/jamanetworkopen.2020.4063.
• Gagliano A, Puligheddu M, Ronzano N, Congiu P, Tanca MG, Cursio I, Carucci S, Sotgiu S, Grossi E, Zuddas A. Artificial Neural Networks Analysis of polysomnographic and clinical features in Pediatric Acute-Onset Neuropsychiatric Syndrome (PANS): from sleep alteration to "Brain Fog". Nat Sci Sleep. 2021 Jul 23;13:1209-1224. doi: 10.2147/NSS.S300818. eCollection 2021.
• Trifiletti R, Lachman HM, Manusama O, Zheng D, Spalice A, Chiurazzi P, Schornagel A, Serban AM, van Wijck R, Cunningham JL, Swagemakers S, van der Spek PJ. Identification of ultra-rare genetic variants in pediatric acute onset neuropsychiatric syndrome (PANS) by exome and whole genome sequencing. Sci Rep. 2022 Jun 30;12(1):11106. doi: 10.1038/s41598-022-15279-3.

Study record dates

Study Major Dates

• Study Start (Actual): August 8, 2024
• Primary Completion (Estimated): February 28, 2027
• Study Completion (Estimated): February 28, 2027

Study Registration Dates

• First Submitted: July 3, 2026
• First Submitted That Met QC Criteria: July 15, 2026
• First Posted (Actual): July 22, 2026

Study Record Updates

• Last Update Posted (Actual): July 22, 2026
• Last Update Submitted That Met QC Criteria: July 15, 2026
• Last Verified: July 1, 2026

More Information

Terms related to this study

• Keywords: Neuroinflammation; Biomarkers; Translational research; PANS; Pediatric Acute-Onset Neuropsychiatric Syndrome; sleep Disorders; Maternal Immune Activation (MIA); Microglia activation; Whole-exome sequencing (WES); microRNA (miRNA) profiling; Metabolomics (¹H-NMR spectroscopy); nflammatory biomarkers
• Additional Relevant MeSH Terms: Neurologic Manifestations; Nervous System Diseases; Mental Disorders; Pathologic Processes; Inflammation; Pathological Conditions, Signs and Symptoms; Signs and Symptoms; Neuroinflammatory Diseases; Sleep Wake Disorders; Pediatric acute-onset neuropsychiatric syndrome; Diagnostic Techniques and Procedures; Diagnosis; Monitoring, Physiologic; Polysomnography
• Other Study ID Numbers: BIOMA-PANS

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No