Subfield-specific longitudinal changes of hippocampal volumes in patients with early-stage bipolar disorder.

BACKGROUND: The hippocampus is a heterogeneous structure composed of biologically and functionally distinct subfields. Hippocampal aberrations are proposed to play a fundamental role in the etiology of psychotic symptoms. Bipolar disorder (BPD) has substantial overlap in symptomatology and genetic liability with schizophrenia (SZ), and reduced hippocampal volumes, particularly at the chronic illness stages, are documented in both disorders. Studies of hippocampal subfields in the early stage of BPD are limited and cross-sectional findings to date report no reduction in hippocampal volumes. To our knowledge, there have been no longitudinal studies of BPD evaluating hippocampal volumes in the early phase of illness. We investigated the longitudinal changes in hippocampal regions and subfields in BPD mainly and in early stage of psychosis (ESP) patients more broadly and compared them to those in controls (HC). METHODS: Baseline clinical and structural MRI data were acquired from 88 BPD, from a total of 143 ESP patients, and 74 HCs. Of those, 66 participants (23 HC, 43 patients) completed a 12-month follow-up visit. The hippocampus regions and subfields were segmented using Freesurfer automated pipeline. RESULTS: We found general baseline deficits in hippocampal volumes among BPD and ESP cohorts. Both cohorts displayed significant increases in the anterior hippocampal region and dentate gyrus compared with controls. Additionally, antipsychotic medications were positively correlated with the posterior region at baseline. CONCLUSION: These findings highlight brain plasticity in BPD and in ESP patients providing evidence that deviations in hippocampal volumes are adaptive responses to atypical signaling rather than progressive degeneration.

Effect of intranasal oxytocin on the core social symptoms of autism spectrum disorder: a randomized clinical trial.

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.

Quantitative facial expression analysis revealed the efficacy and time course of oxytocin in autism.

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.

Neuroanatomical Correlates of Advanced Paternal and Maternal Age at Birth in Autism Spectrum Disorder.

Although advanced paternal and maternal age at birth (PA/MA) increases the risk of autism spectrum disorder (ASD), the underlying neurobiological mechanisms are not fully understood. To explore the neuroanatomical correlates of advanced PA/MA, the current study conducted brain morphometric analyses in 39 high-functioning adult males with ASD and 39 age-, intellectual level-, and parental socioeconomic background-matched, typically developed (TD) males. Whole-brain analysis revealed that the regional gray matter volume (GMV) in bilateral posterior cingulate cortex (PCC) and precuneus (PCU) were significantly smaller in the individuals with ASD than in TD subjects (false discovery rate-corrected P = 0.014). Additional analyses of the constituents of GMV reduction in these brain regions revealed that the cortical thickness of the right ventral PCC was significantly thinner (P = 0.014) and the surface area of bilateral PCU was significantly smaller (left: P = 0.001; right: P = 0.049) in the adults with ASD, compared with TD subjects. Although the analyses were exploratory, the thinner cortical thickness of right ventral PCC was significantly correlated with older PA in the ASD individuals (P = 0.028). The current findings shed new light on the neurobiological mechanisms underlying the link between advanced PA and ASD.

Paternal age contribution to brain white matter aberrations in autism spectrum disorder.

AIM: Although advanced parental age holds an increased risk for autism spectrum disorder (ASD), its role as a potential risk factor for an atypical white matter development underlying the pathophysiology of ASD has not yet been investigated. The current study was aimed to detect white matter disparities in ASD, and further investigate the relationship of paternal and maternal age at birth with such disparities. METHODS: Thirty-nine adult males with high-functioning ASD and 37 typically developing (TD) males were analyzed in the study. The FMRIB Software Library and tract-based spatial statistics were utilized to process and analyze the diffusion tensor imaging data. RESULTS: Subjects with ASD exhibited significantly higher mean diffusivity (MD) and radial diffusivity (RD) in white matter fibers, including the association (inferior fronto-occipital fasciculus, right inferior longitudinal fasciculus, superior longitudinal fasciculi, uncinate fasciculus, and cingulum), commissural (forceps minor), and projection tracts (anterior thalamic radiation and right corticospinal tract) compared to TD subjects (Padjusted < 0.05). No differences were seen in either fractional anisotropy or axial diffusivity. Linear regression analyses assessing the relationship between parental ages and the white matter aberrations revealed a positive correlation between paternal age (PA), but not maternal age, and both MD and RD in the affected fibers (Padjusted < 0.05). Multiple regression showed that only PA was a predictor of both MD and RD. CONCLUSION: Our findings suggest that PA contributes to the white matter disparities seen in individuals with ASD compared to TD subjects.

Facial emotion recognition in patients with focal and diffuse axonal injury.

OBJECTIVE: Facial emotion recognition impairment has been well documented in patients with traumatic brain injury. Studies exploring the neural substrates involved in such deficits have implicated specific grey matter structures (e.g. orbitofrontal regions), as well as diffuse white matter damage. Our study aims to clarify whether different types of injuries (i.e. focal vs. diffuse) will lead to different types of impairments on facial emotion recognition tasks, as no study has directly compared these patients. METHODS: The present study examined performance and response patterns on a facial emotion recognition task in 14 participants with diffuse axonal injury (DAI), 14 with focal injury (FI) and 22 healthy controls. RESULTS: We found that, overall, participants with FI and DAI performed more poorly than controls on the facial emotion recognition task. Further, we observed comparable emotion recognition performance in participants with FI and DAI, despite differences in the nature and distribution of their lesions. However, the rating response pattern between the patient groups was different. CONCLUSION: This is the first study to show that pure DAI, without gross focal lesions, can independently lead to facial emotion recognition deficits and that rating patterns differ depending on the type and location of trauma.

Corpus Callosum Pathology as a Potential Surrogate Marker of Cognitive Impairment in Diffuse Axonal Injury.

Diffuse axonal injury is a major form of traumatic brain injury. Neuropsychological assessments and high-resolution structural MRI were conducted using T1-weighted and diffusion tensor imaging. This study included 10 patients with diffuse axonal injury (all men, mean age 30.8±10.5 years) and 12 age- and sex-matched normal control participants. Patients with diffuse axonal injury had widespread volume reductions and lower fractional anisotropy in the corpus callosum (CC) compared with controls. Furthermore, cognitive processing speed was associated with reductions in white matter volume and fractional anisotropy in the CC. These findings suggest that CC pathology may be a potential surrogate marker of the cognitive deficits in these patients.

AUTISM IN REVIEW.

Autism spectrum disorders are a group of neurodevelopmental disorders characterized by impaired verbal and/or nonverbal communication in addition to repeti- tive stereotypical behaviors. We present a review article on this topic. Criteria for diagnosis are defined by the Diagnos- tic and Statistical Manual of Mental Disorders Fifth Edition (DSM 5). Abnormalities at the level of synapses, including newly described genetic perturbations, have been implicated in the pathogenesis of autism. Non-invasive modalities like Diffusion Tensor Magnetic Resonance Imaging have identi- fied white matter tract involvemeht in the brains of autistic in- dividuals. Early and intensive intervention impact prognosis. Risperidone and aripiprazole are FDA approved for irritability in autism although no known medication relieves core symp- toms of social and communication impairment. Fluoxetine is used to decrease anxiety in autistic patients.

Neuroimaging studies of social cognition in schizophrenia.

Impaired social cognition is considered a core contributor to unfavorable psychosocial functioning in schizophrenia. Rather than being a unitary process, social cognition is a collection of multifaceted processes that recruit multiple brain structures, thus structural and functional neuroimaging techniques are ideal methodologies for revealing the underlying pathophysiology of impaired social cognition. Many neuroimaging studies have suggested that in addition to white-matter deficits, schizophrenia is associated with decreased gray-matter volume in multiple brain areas, especially fronto-temporal and limbic regions. However, few schizophrenia studies have examined associations between brain abnormalities and social cognitive disabilities. During the last decade, we have investigated structural brain abnormalities in schizophrenia using high-resolution magnetic resonance imaging, and our findings have been confirmed by us and others. By assessing different types of social cognitive abilities, structural abnormalities in multiple brain regions have been found to be associated with disabilities in social cognition, such as recognition of facial emotion, theory of mind, and empathy. These structural deficits have also been associated with alexithymia and quality of life in ways that are closely related to the social cognitive disabilities found in schizophrenia. Here, we overview a series of neuroimaging studies from our laboratory that exemplify current research into this topic, and discuss how it can be further tackled using recent advances in neuroimaging technology.

Prefrontal-Limbic Circuitry Is Associated With Reward Sensitivity in Nonhuman Primates.

BACKGROUND: Abnormal reward sensitivity is a risk factor for psychiatric disorders, including eating disorders such as overeating and binge-eating disorder, but the brain structural mechanisms that underlie it are not completely understood. Here, we sought to investigate the relationship between multimodal whole-brain structural features and reward sensitivity in nonhuman primates. METHODS: Reward sensitivity was evaluated through behavioral economic analysis in which monkeys (adult rhesus macaques; 7 female, 5 male) responded for sweetened condensed milk (10%, 30%, 56%), Gatorade, or water using an operant procedure in which the response requirement increased incrementally across sessions (i.e., fixed ratio 1, 3, 10). Animals were divided into high (n = 6) or low (n = 6) reward sensitivity groups based on essential value for 30% milk. Multimodal magnetic resonance imaging was used to measure gray matter volume and white matter microstructure. Brain structural features were compared between groups, and their correlations with reward sensitivity for various stimuli was investigated. RESULTS: Animals in the high sensitivity group had greater dorsolateral prefrontal cortex, centromedial amygdaloid complex, and middle cingulate cortex volumes than animals in the low sensitivity group. Furthermore, compared with monkeys in the low sensitivity group, high sensitivity monkeys had lower fractional anisotropy in the left dorsal cingulate bundle connecting the centromedial amygdaloid complex and middle cingulate cortex to the dorsolateral prefrontal cortex, and in the left superior longitudinal fasciculus 1 connecting the middle cingulate cortex to the dorsolateral prefrontal cortex. CONCLUSIONS: These results suggest that neuroanatomical variation in prefrontal-limbic circuitry is associated with reward sensitivity. These brain structural features may serve as predictive biomarkers for vulnerability to food-based and other reward-related disorders.

Resting-State Networks of Awake Adolescent and Adult Squirrel Monkeys Using Ultra-High Field (9.4†T) Functional Magnetic Resonance Imaging.

Resting-state networks (RSNs) are increasingly forwarded as candidate biomarkers for neuropsychiatric disorders. Such biomarkers may provide objective measures for evaluating novel therapeutic interventions in nonhuman primates often used in translational neuroimaging research. This study aimed to characterize the RSNs of awake squirrel monkeys and compare the characteristics of those networks in adolescent and adult subjects. Twenty-seven squirrel monkeys [n = 12 adolescents (6 male/6 female) ∼2.5 years and n = 15 adults (7 male/8 female) ∼9.5 years] were gradually acclimated to awake scanning procedures; whole-brain fMRI images were acquired with a 9.4 T scanner. Group-level independent component analysis (ICA; 30 ICs) with dual regression was used to detect and compare RSNs. Twenty ICs corresponding to physiologically meaningful networks representing a range of neural functions, including motor, sensory, reward, and cognitive processes, were identified in both adolescent and adult monkeys. The reproducibility of these RSNs was evaluated across several ICA model orders. Adults showed a trend for greater connectivity compared with adolescent subjects in two of the networks of interest: (1) in the right occipital region with the OFC network and (2) in the left temporal cortex, bilateral occipital cortex, and cerebellum with the posterior cingulate network. However, when age was entered into the above model, this trend for significance was lost. These results demonstrate that squirrel monkey RSNs are stable and consistent with RSNs previously identified in humans, rodents, and other nonhuman primate species. These data also identify several networks in adolescence that are conserved and others that may change into adulthood.

Characterizing the Relationship between Personality Dimensions and Psychosis-Specific Clinical Characteristics.

Background: Past studies associating personality with psychosis have been limited by small nonclinical samples and a focus on general symptom burden. This study uses a large clinical sample to examine personality's relationship with psychosis-specific features and compare personality dimensions across clinically and neurobiologically defined categories of psychoses. Methods: A total of 1352 participants with schizophrenia, schizoaffective disorder, and bipolar with psychosis, as well as 623 healthy controls (HC), drawn from the Bipolar-Schizophrenia Network for Intermediate Phenotypes (BSNIP-2) study, were included. Three biomarker-derived biotypes were used to separately categorize the probands. Mean personality factors (openness, conscientiousness, extraversion, agreeableness, and neuroticism) were compared between HC and proband subgroups using independent sample t-tests. A robust linear regression was utilized to determine personality differences across biotypes and diagnostic subgroups. Associations between personality factors and cognition were determined through Pearson's correlation. A canonical correlation was run between the personality factors and general functioning, positive symptoms, and negative symptoms to delineate the relationship between personality and clinical outcomes of psychosis. Results: There were significant personality differences between the proband and HC groups across all five personality factors. Overall, the probands had higher neuroticism and lower extraversion, agreeableness, conscientiousness, and openness. Openness showed the greatest difference across the diagnostic subgroups and biotypes, and greatest correlation with cognition. Openness, agreeableness, and extraversion had the strongest associations with symptom severity. Conclusions: Individuals with psychosis have different personality profiles compared to HC. In particular, openness may be relevant in distinguishing psychosis-specific phenotypes and experiences, and associated with biological underpinnings of psychosis, including cognition. Further studies should identify potential causal factors and mediators of this relationship.

Gyrification across psychotic disorders: A bipolar-schizophrenia network of intermediate phenotypes study.

BACKGROUND: The profiles of cortical gyrification across schizophrenia, bipolar I disorder, and schizoaffective disorder have been studied to a limited extent, report discordant findings, and are rarely compared in the same study. Here we assess gyrification in a large dataset of psychotic disorder probands, categorized according to the DSM-IV. Furthermore, we explore gyrification changes with age across healthy controls and probands. METHODS: Participants were recruited within the Bipolar-Schizophrenia Network of Intermediate Phenotypes study and received T1-MPRAGE and clinical assessment. Gyrification was measured using FreeSurfer 7.1.0. Pairwise t-tests were conducted in R, and age-related gyrification changes were analyzed in MATLAB. P values <0.05 after false discovery rate correction were considered significant. RESULTS: Significant hypogyria in schizophrenia, bipolar disorder, and schizoaffective disorder probands compared to controls was found, with a significant difference bilaterally in the frontal lobe between schizophrenia and bipolar disorder probands. Verbal memory was associated with gyrification in the right frontal and right cingulate cortex in schizophrenia. Age-fitted gyrification curves differed significantly among psychotic disorders and controls. CONCLUSIONS: Findings indicate hypogyria in DSM-IV psychotic disorders compared to controls and suggest differential patterns of gyrification across the different diagnoses. The study extends age related models of gyrification to psychotic disorder probands and supports that age-related differences in gyrification may differ across diagnoses. Fitted gyrification curves among probands categorized by DSM-IV significantly deviate from controls, with the model capturing early hypergyria and later hypogyria in schizophrenia compared to controls; this suggests unique disease and age-related changes in gyrification across psychotic disorders.

The schizophrenia syndrome, circa 2024: What we know and how that informs its nature.

With new data about different aspects of schizophrenia being continually generated, it becomes necessary to periodically revisit exactly what we know. Along with a need to review what we currently know about schizophrenia, there is an equal imperative to evaluate the construct itself. With these objectives, we undertook an iterative, multi-phase process involving fifty international experts in the field, with each step building on learnings from the prior one. This review assembles currently established findings about schizophrenia (construct, etiology, pathophysiology, clinical expression, treatment) and posits what they reveal about its nature. Schizophrenia is a heritable, complex, multi-dimensional syndrome with varying degrees of psychotic, negative, cognitive, mood, and motor manifestations. The illness exhibits a remitting and relapsing course, with varying degrees of recovery among affected individuals with most experiencing significant social and functional impairment. Genetic risk factors likely include thousands of common genetic variants that each have a small impact on an individual's risk and a plethora of rare gene variants that have a larger individual impact on risk. Their biological effects are concentrated in the brain and many of the same variants also increase the risk of other psychiatric disorders such as bipolar disorder, autism, and other neurodevelopmental conditions. Environmental risk factors include but are not limited to urban residence in childhood, migration, older paternal age at birth, cannabis use, childhood trauma, antenatal maternal infection, and perinatal hypoxia. Structural, functional, and neurochemical brain alterations implicate multiple regions and functional circuits. Dopamine D-2 receptor antagonists and partial agonists improve psychotic symptoms and reduce risk of relapse. Certain psychological and psychosocial interventions are beneficial. Early intervention can reduce treatment delay and improve outcomes. Schizophrenia is increasingly considered to be a heterogeneous syndrome and not a singular disease entity. There is no necessary or sufficient etiology, pathology, set of clinical features, or treatment that fully circumscribes this syndrome. A single, common pathophysiological pathway appears unlikely. The boundaries of schizophrenia remain fuzzy, suggesting the absence of a categorical fit and need to reconceptualize it as a broader, multi-dimensional and/or spectrum construct.

Resting state networks of awake adolescent and adult squirrel monkeys using ultra-high field (9.4T) functional magnetic resonance imaging.

Resting state networks (RSNs) are increasingly forwarded as candidate biomarkers for neuropsychiatric disorders. Such biomarkers may provide objective measures for evaluating novel therapeutic interventions in nonhuman primates often used in translational neuroimaging research. This study aimed to characterize the RSNs of awake squirrel monkeys and compare the characteristics of those networks in adolescent and adult subjects. Twenty-seven squirrel monkeys ( n =12 adolescents [6 male/6 female] ∼2.5 years and n =15 adults [7 male/8 female] ∼9.5 years) were gradually acclimated to awake scanning procedures; whole-brain fMRI images were acquired with a 9.4 Tesla scanner. Group level independent component (IC) analysis (30 ICs) with dual regression was used to detect and compare RSNs. Twenty ICs corresponding to physiologically meaningful networks representing a range of neural functions, including motor, sensory, reward (e.g., basal ganglia), and cognitive processes were identified in both adolescent and adult monkeys. Significant age-related differences between the adult and adolescent subjects (adult > adolescent) were found in two networks of interest: (1) the right upper occipital region with an OFC IC and (2) the left temporal cortex, bilateral visual areas, and cerebellum with the cingulate IC. These results demonstrate that squirrel monkey RSNs are stable and consistent with RSNs previously identified in humans, rodents, and other nonhuman primate species. These data also identify several networks in adolescence that are conserved and others that may change into adulthood. Significance Statement: Functional magnetic resonance imaging procedures have revealed important information about how the brain is modified by experimental manipulations, disease states, and aging throughout the lifespan. Preclinical neuroimaging, especially in nonhuman primates, has become a frequently used means to answer targeted questions related to brain resting-state functional connectivity. The present study characterized resting state networks (RSNs) in adult and adolescent squirrel monkeys; twenty RSNs corresponding to networks representing a range of neural functions were identified. The RSNs identified here can be utilized in future studies examining the effects of experimental manipulations on brain connectivity in squirrel monkeys. These data also may be useful for comparative analysis with other primate species to provide an evolutionary perspective for understanding brain function and organization.

Identification of diagnostic markers for ASD: a restrictive interest analysis based on EEG combined with eye tracking.

Electroencephalography (EEG) functional connectivity (EFC) and eye tracking (ET) have been explored as objective screening methods for autism spectrum disorder (ASD), but no study has yet evaluated restricted and repetitive behavior (RRBs) simultaneously to infer early ASD diagnosis. Typically developing (TD) children (n = 27) and ASD (n = 32), age- and sex-matched, were evaluated with EFC and ET simultaneously, using the restricted interest stimulus paradigm. Network-based machine learning prediction (NBS-predict) was used to identify ASD. Correlations between EFC, ET, and Autism Diagnostic Observation Schedule-Second Edition (ADOS-2) were performed. The Area Under the Curve (AUC) of receiver-operating characteristics (ROC) was measured to evaluate the predictive performance. Under high restrictive interest stimuli (HRIS), ASD children have significantly higher α band connectivity and significantly more total fixation time (TFT)/pupil enlargement of ET relative to TD children (p = 0.04299). These biomarkers were not only significantly positively correlated with each other (R = 0.716, p = 8.26e-4), but also with ADOS total scores (R = 0.749, p = 34e-4) and RRBs sub-score (R = 0.770, p = 1.87e-4) for EFC (R = 0.641, p = 0.0148) for TFT. The accuracy of NBS-predict in identifying ASD was 63.4%. ROC curve demonstrated TFT with 91 and 90% sensitivity, and 78.7% and 77.4% specificity for ADOS total and RRB sub-scores, respectively. Simultaneous EFC and ET evaluation in ASD is highly correlated with RRB symptoms measured by ADOS-2. NBS-predict of EFC offered a direct prediction of ASD. The use of both EFC and ET improve early ASD diagnosis.

Characterization of childhood trauma, hippocampal mediation and Cannabis use in a large dataset of psychosis and non-psychosis individuals.

BACKGROUND: Cannabis use (CA) and childhood trauma (CT) independently increase the risk of earlier psychosis onset; but their interaction in relation to psychosis risk and association with endocannabinoid-receptor rich brain regions, i.e. the hippocampus (HP), remains unclear. The objective was to determine whether lower age of psychosis onset (AgePsyOnset) is associated with CA and CT through mediation by the HP volumes, and genetic risk, as measured by schizophrenia polygene scores (SZ-PGRS). METHODS: Cross-sectional, case-control, multicenter sample from 5 metropolitan US regions. Participants (n = 1185) included 397 controls not affected by psychosis (HC); 209 participants with bipolar disorder type-1; 279 with schizoaffective disorder; and 300 with schizophrenia (DSM IV-TR). CT was assessed using the Childhood Trauma Questionnaire (CTQ); CA was assessed by self-reports and trained clinical interviewers. Assessment included neuroimaging, symptomatology, cognition and calculation of the SZ polygenic risk score (SZ-PGRS). RESULTS: In survival analysis, CT and CA exposure interact to be associated with lower AgePsyOnset. At high CT or CA, CT or CA are individually sufficient to affect AgePsyOnset. CT relation with AgePsyOnset is mediated in part by the HP in CA users before AgePsyOnset. CA before AgePsyOnset is associated with higher SZ-PGRS and correlated with younger age at CA usage. DISCUSSION: CA and CT interact to increase risk when moderate; while severe CT and/or CA abuse/dependence are each sufficient to affect AgePsyOnset, indicating a ceiling effect. Probands with/out CA before AgePsyOnset differ on biological variables, suggesting divergent pathways to psychosis. FUNDING: MH077945; MH096942; MH096913; MH077862; MH103368; MH096900; MH122759.

Application of a Machine Learning Algorithm for Structural Brain Images in Chronic Schizophrenia to Earlier Clinical Stages of Psychosis and Autism Spectrum Disorder: A Multiprotocol Imaging Dataset Study.

BACKGROUND AND HYPOTHESIS: Machine learning approaches using structural magnetic resonance imaging (MRI) can be informative for disease classification; however, their applicability to earlier clinical stages of psychosis and other disease spectra is unknown. We evaluated whether a model differentiating patients with chronic schizophrenia (ChSZ) from healthy controls (HCs) could be applied to earlier clinical stages such as first-episode psychosis (FEP), ultra-high risk for psychosis (UHR), and autism spectrum disorders (ASDs). STUDY DESIGN: Total 359 T1-weighted MRI scans, including 154 individuals with schizophrenia spectrum (UHR, n = 37; FEP, n = 24; and ChSZ, n = 93), 64 with ASD, and 141 HCs, were obtained using three acquisition protocols. Of these, data regarding ChSZ (n = 75) and HC (n = 101) from two protocols were used to build a classifier (training dataset). The remainder was used to evaluate the classifier (test, independent confirmatory, and independent group datasets). Scanner and protocol effects were diminished using ComBat. STUDY RESULTS: The accuracy of the classifier for the test and independent confirmatory datasets were 75% and 76%, respectively. The bilateral pallidum and inferior frontal gyrus pars triangularis strongly contributed to classifying ChSZ. Schizophrenia spectrum individuals were more likely to be classified as ChSZ compared to ASD (classification rate to ChSZ: UHR, 41%; FEP, 54%; ChSZ, 70%; ASD, 19%; HC, 21%). CONCLUSION: We built a classifier from multiple protocol structural brain images applicable to independent samples from different clinical stages and spectra. The predictive information of the classifier could be useful for applying neuroimaging techniques to clinical differential diagnosis and predicting disease onset earlier.

Oxytocin-induced increase in N,N-dimethylglycine and time course of changes in oxytocin efficacy for autism social core symptoms.

BACKGROUND: Oxytocin is expected as a novel therapeutic agent for autism spectrum disorder (ASD) core symptoms. However, previous results on the efficacy of repeated administrations of oxytocin are controversial. Recently, we reported time-course changes in the efficacy of the neuropeptide underlying the controversial effects of repeated administration; however, the underlying mechanisms remained unknown. METHODS: The current study explored metabolites representing the molecular mechanisms of oxytocin's efficacy using high-throughput metabolomics analysis on plasma collected before and after 6-week repeated intranasal administration of oxytocin (48 IU/day) or placebo in adult males with ASD (N = 106) who participated in a multi-center, parallel-group, double-blind, placebo-controlled, randomized controlled trial. RESULTS: Among the 35 metabolites measured, a significant increase in N,N-dimethylglycine was detected in the subjects administered oxytocin compared with those given placebo at a medium effect size (false discovery rate (FDR) corrected P = 0.043, d = 0.74, N = 83). Furthermore, subgroup analyses of the participants displaying a prominent time-course change in oxytocin efficacy revealed a significant effect of oxytocin on N,N-dimethylglycine levels with a large effect size (PFDR = 0.004, d = 1.13, N = 60). The increase in N,N-dimethylglycine was significantly correlated with oxytocin-induced clinical changes, assessed as changes in quantifiable characteristics of autistic facial expression, including both of improvements between baseline and 2 weeks (PFDR = 0.006, r = - 0.485, N = 43) and deteriorations between 2 and 4 weeks (PFDR = 0.032, r = 0.415, N = 37). LIMITATIONS: The metabolites changes caused by oxytocin administration were quantified using peripheral blood and therefore may not directly reflect central nervous system changes. CONCLUSION: Our findings demonstrate an association of N,N-dimethylglycine upregulation with the time-course change in the efficacy of oxytocin on autistic social deficits. Furthermore, the current findings support the involvement of the N-methyl-D-aspartate receptor and neural plasticity to the time-course change in oxytocin's efficacy. TRIAL REGISTRATION: A multi-center, parallel-group, placebo-controlled, double-blind, confirmatory trial of intranasal oxytocin in participants with autism spectrum disorders (the date registered: 30 October 2014; UMIN Clinical Trials Registry: https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000017703 ) (UMIN000015264).

Machine-learning classification using neuroimaging data in schizophrenia, autism, ultra-high risk and first-episode psychosis.

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.