Compelling evidence in Caucasian populations suggests a role for copy-number variations (CNVs) in autism spectrum disorder (ASD) and schizophrenia (SCZ). We analyzed 1,108 ASD cases, 2,458 SCZ cases, and 2,095 controls in a Japanese population and confirmed an increased burden of rare exonic CNVs in both disorders. Clinically significant (or pathogenic) CNVs, including those at 29 loci common to both disorders, were found in about 8% of ASD and SCZ cases, which was significantly higher than in controls. Phenotypic analysis revealed an association between clinically significant CNVs and intellectual disability. Gene set analysis showed significant overlap of biological pathways in both disorders including oxidative stress response, lipid metabolism/modification, and genomic integrity. Finally, based on bioinformatics analysis, we identified multiple disease-relevant genes in eight well-known ASD/SCZ-associated CNV loci (e.g., 22q11.2, 3q29). Our findings suggest an etiological overlap of ASD and SCZ and provide biological insights into these disorders.

Although small-scale studies have described the effects of oxytocin on social deficits in autism spectrum disorder (ASD), no large-scale study has been conducted. In this randomized, parallel-group, multicenter, placebo-controlled, double-blind trial in Japan, 106 ASD individuals (18-48 y.o.) were enrolled between Jan 2015 and March 2016. Participants were randomly assigned to a 6-week intranasal oxytocin (48IU/day, n = 53) or placebo (n = 53) group. One-hundred-three participants were analyzed. Since oxytocin reduced the primary endpoint, Autism Diagnostic Observation Schedule (ADOS) reciprocity, (from 8.5 to 7.7; P < .001) but placebo also reduced the score (8.3 to 7.2; P < .001), no between-group difference was found (effect size -0.08; 95% CI, -0.46 to 0.31; P = .69); however, plasma oxytocin was only elevated from baseline to endpoint in the oxytocin-group compared with the placebo-group (effect size -1.12; -1.53 to -0.70; P < .0001). Among the secondary endpoints, oxytocin reduced ADOS repetitive behavior (2.0 to 1.5; P < .0001) compared with placebo (2.0 to 1.8; P = .43) (effect size 0.44; 0.05 to 0.83; P = .026). In addition, the duration of gaze fixation on socially relevant regions, another secondary endpoint, was increased by oxytocin (41.2 to 52.3; P = .03) compared with placebo (45.7 to 40.4; P = .25) (effect size 0.55; 0.10 to 1.0; P = .018). No significant effects were observed for the other secondary endpoints. No significant difference in the prevalence of adverse events was observed between groups, although one participant experienced temporary gynecomastia during oxytocin administration. Based on the present findings, we cannot recommend continuous intranasal oxytocin treatment alone at the current dose and duration for treatment of the core social symptoms of high-functioning ASD in adult men, although this large-scale trial suggests oxytocin's possibility to treat ASD repetitive behavior.

Neuropsychiatric disorders are diagnosed based on behavioral criteria, which makes the diagnosis challenging. Objective biomarkers such as neuroimaging are needed, and when coupled with machine learning, can assist the diagnostic decision and increase its reliability. Sixty-four schizophrenia, 36 autism spectrum disorder (ASD), and 106 typically developing individuals were analyzed. FreeSurfer was used to obtain the data from the participant's brain scans. Six classifiers were utilized to classify the subjects. Subsequently, 26 ultra-high risk for psychosis (UHR) and 17 first-episode psychosis (FEP) subjects were run through the trained classifiers. Lastly, the classifiers' output of the patient groups was correlated with their clinical severity. All six classifiers performed relatively well to distinguish the subject groups, especially support vector machine (SVM) and Logistic regression (LR). Cortical thickness and subcortical volume feature groups were most useful for the classification. LR and SVM were highly consistent with clinical indices of ASD. When UHR and FEP groups were run with the trained classifiers, majority of the cases were classified as schizophrenia, none as ASD. Overall, SVM and LR were the best performing classifiers. Cortical thickness and subcortical volume were most useful for the classification, compared to surface area. LR, SVM, and DT's output were clinically informative. The trained classifiers were able to help predict the diagnostic category of both UHR and FEP Individuals.

To develop novel interventions for autism spectrum disorder (ASD) core symptoms, valid, reliable, and sensitive longitudinal outcome measures are required for detecting symptom change over time. Here, we tested whether a computerized analysis of quantitative facial expression measures could act as a marker for core ASD social symptoms. Facial expression intensity values during a semi-structured socially interactive situation extracted from the Autism Diagnostic Observation Schedule (ADOS) were quantified by dedicated software in 18 high-functioning adult males with ASD. Controls were 17 age-, gender-, parental socioeconomic background-, and intellectual level-matched typically developing (TD) individuals. Statistical analyses determined whether values representing the strength and variability of each facial expression element differed significantly between the ASD and TD groups and whether they correlated with ADOS reciprocal social interaction scores. Compared with the TD controls, facial expressions in the ASD group appeared more "Neutral" (d = 1.02, P = 0.005, P FDR < 0.05) with less variation in Neutral expression (d = 1.08, P = 0.003, P FDR < 0.05). Their expressions were also less "Happy" (d = −0.78, P = 0.038, P FDR > 0.05) with lower variability in Happy expression (d = 1.10, P = 0.003, P FDR < 0.05). Moreover, the stronger Neutral facial expressions in the ASD participants were positively correlated with poorer ADOS reciprocal social interaction scores (ρ = 0.48, P = 0.042). These findings indicate that our method for quantitatively measuring reduced facial expressivity during social interactions can be a promising marker for core ASD social symptoms.

Discrepancies in efficacy between single-dose and repeated administration of oxytocin for autism spectrum disorder have led researchers to hypothesize that time-course changes in efficacy are induced by repeated administrations of the peptide hormone. However, repeatable, objective, and quantitative measurement of autism spectrum disorder’s core symptoms are lacking, making it difficult to examine potential time-course changes in efficacy. We tested this hypothesis using repeatable, objective, and quantitative measurement of the core symptoms of autism spectrum disorder. We examined videos recorded during semi-structured social interaction administered as the primary outcome in single-site exploratory (n = 18, crossover within-subjects design) and multisite confirmatory (n = 106, parallel-group design), double-blind, placebo-controlled 6-week trials of repeated intranasal administrations of oxytocin (48 IU/day) in adult males with autism spectrum disorder. The main outcomes were statistical representative values of objectively quantified facial expression intensity in a repeatable part of the Autism Diagnostic Observation Schedule: the maximum probability (i.e. mode) and the natural logarithm of mode on the probability density function of neutral facial expression and the natural logarithm of mode on the probability density function of happy expression. Our recent study revealed that increases in these indices characterize autistic facial expression, compared with neurotypical individuals. The current results revealed that oxytocin consistently and significantly decreased the increased natural logarithm of mode on the probability density function of neutral facial expression compared with placebo in exploratory (effect-size, −0.57; 95% CI, −1.27 to 0.13; P = 0.023) and confirmatory trials (−0.41; −0.62 to −0.20; P < 0.001). A significant interaction between time-course (at baseline, 2, 4, 6, and 8 weeks) and the efficacy of oxytocin on the natural logarithm of mode on the probability density function of neutral facial expression was found in confirmatory trial (P < 0.001). Post hoc analyses revealed maximum efficacy at 2 weeks (P < 0.001, Cohen’s d = −0.78; 95% CI, −1.21 to −0.35) and deterioration of efficacy at 4 weeks (P = 0.042, Cohen’s d = −0.46; 95% CI, −0.90 to −0.01) and 6 weeks (P = 0.10, Cohen’s d = −0.35; 95% CI, −0.77 to 0.08), while efficacy was preserved at 2 weeks post-treatment (i.e. 8 weeks) (P < 0.001, Cohen’s d = −1.24; 95% CI, −1.71 to −0.78). Quantitative facial expression analyses successfully verified the positive effects of repeated oxytocin on autistic individuals’ facial expressions and demonstrated a time-course change in efficacy. The current findings support further development of an optimized regimen of oxytocin treatment.