AUTHOR=Murgia Federica , Gagliano Antonella , Tanca Marcello G. , Or-Geva Noga , Hendren Aran , Carucci Sara , Pintor Manuela , Cera Francesca , Cossu Fausto , Sotgiu Stefano , Atzori Luigi , Zuddas Alessandro 

TITLE=Metabolomic Characterization of Pediatric Acute-Onset Neuropsychiatric Syndrome (PANS)

JOURNAL=Frontiers in Neuroscience

VOLUME=Volume 15 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2021.645267

DOI=10.3389/fnins.2021.645267

ISSN=1662-453X

ABSTRACT=PANS is a controversial clinical entity, consisting of a complex constellation of psychiatric symptoms, adventitious changes, and expression of various serological alterations, likely sustained by an autoimmune/inflammatory disease. Detection of novel biomarkers of PANS is highly desirable for both diagnostic and therapeutic management of affected patients. Analysis of metabolites has proven useful in detecting biomarkers for other neuroimmune-psychiatric diseases. Here we utilize the metabolomics approach to determine whether it is possible to define a specific metabolic pattern in patients affected by PANS compared to healthy subjects. 
Design: This observational case-control study tested consecutive patients referred for PANS between June 2019 to May 2020 were enrolled in this observational case-control study. PANS diagnosis was confirmed according to PANS working criteria (National Institute of Mental Health (NIMH 2010).  Age and sex-matched healthy subjects were recruited as controls. 
Methods: Serum samples were obtained from each participant and were analysed using Nuclear Magnetic Resonance spectroscopy. Subsequently, multivariate and univariate statistical analyses and Receiving Operator Curves (ROC) were performed. 
Results: Thirty-four outpatients referred for PANS (mean age 9.5 yrs.; SD 2.9, 71% male) and 25 neurotypical subjects matched for age, gender, and intelligence quotient were subjected to metabolite analysis. Separation of the samples, in line with the presence of PANS diagnosis, was observed by applying a supervised model (R2X=0.44, R2Y=0.54, Q2=0.44, p-value <0.0001). The significantly changed variables were 2-OH butyrate, glycine, glutamine, histidine, tryptophan. Pathway analysis indicated that phenylalanine, tyrosine, and tryptophan metabolism as well as glutamine and glutamate metabolism were most altered. 
Conclusions: We found a unique plasma metabolic profile in PANS patients, significantly different from healthy children, that suggests the involvement of specific patterns of neurotransmission (tryptophan, glycine, histamine/histidine) as well as a more general state of neuroinflammation and oxidative stress (glutamine, 2-Hydroxybutyrate, and tryptophan-kynurenine pathway) in the disorder. This metabolomics study offers new insights into biological mechanisms underpinning the disorder and supports research of other potential biomarkers implicated in PANS.