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Early and accurate diagnosis of autism spectrum disorders (ASD) and tailored therapeutic interventions can improve prognosis. ADOS-2 is a standardized test for ASD diagnosis. However, owing to ASD heterogeneity, the presence of false positives remains a challenge for clinicians. In this study, retrospective data from patients with ASD and multi-systemic developmental disorder (MSDD), a term used to describe children under the age of 3 with impaired communication but with strong emotional attachments, were tested by machine learning (ML) models to assess the best predictors of disease development as well as the items that best describe these two autism spectrum disorder presentations. Maternal and infant data as well as ADOS-2 score were included in different ML testing models. Depending on the outcome to be estimated, a best-performing model was selected. RIDGE regression model showed that the best predictors for ADOS social affect score were gut disturbances, EEG retrievals, and sleep problems. Linear Regression Model showed that term pregnancy, psychomotor development status, and gut disturbances were predicting at best for the ADOS Repetitive and Restricted Behavior score. The LASSO regression model showed that EEG retrievals, sleep disturbances, age at diagnosis, term pregnancy, weight at birth, gut disturbances, and neurological findings were the best predictors for the overall ADOS score. The CART classification and regression model showed that age at diagnosis and weight at birth best discriminate between ASD and MSDD.

Autism Spectrum Disorder (ASD) encompasses a clinical spectrum of neurodevelopmental conditions that display significant heterogeneity in etiology, symptomatology, and severity. We previously compared 30 young children with idiopathic ASD and 30 unrelated typically-developing controls, detecting an imbalance in several compounds belonging mainly to the metabolism of purines, tryptophan and other amino acids, as well as compounds derived from the intestinal flora, and reduced levels of vitamins B6, B12 and folic acid. The present study describes significant urinary metabolomic differences within 14 pairs, including one child with idiopathic ASD and his/her typically-developing sibling, tightly matched by sex and age to minimize confounding factors, allowing a more reliable identification of the metabolic fingerprint related to ASD. By using a highly sensitive, accurate and unbiased approach, suitable for ensuring broad metabolite detection coverage on human urine, and by applying multivariate statistical analysis, we largely replicate our previous results, demonstrating a significant perturbation of the purine and tryptophan pathways, and further highlight abnormalities in the “phenylalanine, tyrosine and tryptophan” pathway, essentially involving increased phenylalanine and decreased tyrosine levels, as well as enhanced concentrations of bacterial degradation products, including phenylpyruvic acid, phenylacetic acid and 4-ethylphenyl-sulfate. The outcome of these within-family contrasts consolidates and extends our previous results obtained from unrelated individuals, adding further evidence that these metabolic imbalances may be linked to ASD rather than to environmental differences between cases and controls. It further underscores the excess of some gut microbiota-derived compounds in ASD, which could have diagnostic value in a network model differentiating the metabolome of autistic and unaffected siblings. Finally, it points toward the existence of a “metabolic autism spectrum” distributed as an endophenotype, with unaffected siblings possibly displaying a metabolic profile intermediate between their autistic siblings and unrelated typically-developing controls.

Antipsychotics (APDs) represent the main pharmacological strategy in the treatment of schizophrenia; however, their administration often may result in severe adverse effects, such as extrapyramidal symptoms. Typically, dystonic movements are considered the result of impaired function and/or abnormalities of dopaminergic neurotransmission/signaling in the basal ganglia. The catechol O-methyltransferase (COMT) gene is located within the 22q11.2 region, and its product is an enzyme involved in transferring a methyl group from S-adenosylmethionine to catecholamines, including dopamine. Studies showed that COMT Val158Met polymorphism modifies enzymatic activity and, consequently, synaptic dopamine concentration in specific brain areas. We identified a patient with 22q11.2 deletion syndrome presenting with cervical and trunk dystonia after paliperidone administration, which persisted even after drug discontinuation. Given the patient’s genetic condition, we hypothesized that the dopaminergic dysfunction had been aggravated by COMT involvement, thus causing dystonia. In line with this hypothesis, we carried out a study on psychiatric patients in chronic treatment with APD to evaluate the distribution of the COMT Val158Met polymorphism and its role in the onset of adverse extrapyramidal symptoms. The study included four patients with dystonia after administration of APDs compared to 17 patients who never presented adverse drug reactions. Our data suggest that the Val/Val and Met/Met polymorphisms of the COMT gene are associated with a protective effect for the development of collateral extrapyramidal symptoms in patients treated with APDs, while the Val/Met genotype could be considered a risk factor for the development of dystonia after APDs administration.

Background: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social interaction/communication, stereotypic behaviors, restricted interests, and abnormal sensory-processing. Several studies have reported significantly elevated urinary and foecal levels of p-cresol in ASD children, an aromatic compound either of environmental origin or produced by specific gut bacterial strains. Methods: Since p-cresol is a known uremic toxin, able to negatively affect multiple brain functions, the present study was undertaken to assess the effects of a single acute injection of low- or high-dose (1 or 10 mg/kg i.v. respectively) of p-cresol in behavioral and neurochemical phenotypes of BTBR mice, a reliable animal model of human ASD. Results: P-cresol significantly increased anxiety-like behaviors and hyperactivity in the open field, in addition to producing stereotypic behaviors and loss of social preference in BTBR mice. Tissue levels of monoaminergic neurotransmitters and their metabolites unveiled significantly activated dopamine turnover in amygdala as well as in dorsal and ventral striatum after p-cresol administration; no effect was recorded in medial-prefrontal cortex and hippocampus. Conclusion: Our study supports a gene x environment interaction model, whereby p-cresol, acting upon a susceptible genetic background, can acutely induce autism-like behaviors and produce abnormal dopamine metabolism in the reward circuitry.