Increased glutamate and glutamine levels and their relationship to astrocytes and dopaminergic transmissions in the brains of adults with autism.

Increased excitatory neuronal tones have been implicated in autism, but its mechanism remains elusive. The amplified glutamate signals may arise from enhanced glutamatergic circuits, which can be affected by astrocyte activation and suppressive signaling of dopamine neurotransmission. We tested this hypothesis using magnetic resonance spectroscopy and positron emission tomography scan with 11C-SCH23390 for dopamine D1 receptors in the anterior cingulate cortex (ACC). We enrolled 18 male adults with high-functioning autism and 20 typically developed (TD) male subjects. The autism group showed elevated glutamate, glutamine, and myo-inositol (mI) levels compared with the TD group (p = 0.045, p = 0.044, p = 0.030, respectively) and a positive correlation between glutamine and mI levels in the ACC (r = 0.54, p = 0.020). In autism and TD groups, ACC D1 receptor radioligand binding was negatively correlated with ACC glutamine levels (r = - 0.55, p = 0.022; r = - 0.58, p = 0.008, respectively). The enhanced glutamate-glutamine metabolism might be due to astroglial activation and the consequent reinforcement of glutamine synthesis in autistic brains. Glutamine synthesis could underly the physiological inhibitory control of dopaminergic D1 receptor signals. Our findings suggest a high neuron excitation-inhibition ratio with astrocytic activation in the etiology of autism.

Generalizable neuromarker for autism spectrum disorder across imaging sites and developmental stages: A multi-site study.

Autism spectrum disorder (ASD) is a lifelong condition, and its underlying biological mechanisms remain elusive. The complexity of various factors, including inter-site and development-related differences, makes it challenging to develop generalizable neuroimaging-based biomarkers for ASD. This study used a large-scale, multi-site dataset of 730 Japanese adults to develop a generalizable neuromarker for ASD across independent sites and different developmental stages. Our adult ASD neuromarker achieved successful generalization for the US and Belgium adults and Japanese adults. The neuromarker demonstrated significant generalization for children and adolescents. We identified 141 functional connections (FCs) important for discriminating individuals with ASD from TDCs. Finally, we mapped schizophrenia (SCZ) and major depressive disorder (MDD) onto the biological axis defined by the neuromarker and explored the biological continuity of ASD with SCZ and MDD. We observed that SCZ, but not MDD, was located proximate to ASD on the biological dimension defined by the ASD neuromarker. The successful generalization in multifarious datasets and the observed relations of ASD with SCZ on the biological dimensions provide new insights for a deeper understanding of ASD.

Pathological social withdrawal in autism spectrum disorder: A case control study of hikikomori in Japan.

Introduction: Hikikomori, a form of pathological social withdrawal, has been suggested to have comorbidity with autism spectrum disorder (ASD). This study aimed to clarify how characteristics of ASD are associated with hikikomori. Methods: Thirty-nine adult male patients with a diagnosis of ASD attending our outpatient clinic for neurodevelopmental disabilities were subjected to a structured interview regarding social withdrawal, various self-administered questionnaires, and blood tests. Through structured interviews, the subjects were divided into two groups: (Group 1) ASD with hikikomori condition and (Group 2) ASD without hikikomori condition. Sixteen subjects qualified as hikikomori and 23 subjects qualified as subjects without hikikomori. Age, sex, autism spectrum quotient (AQ), Autism Diagnostic Observation Schedule (ADOS), and FIQ were matched. Results: Compared to non-hikikomori controls, hikikomori cases were likely to have stronger sensory symptoms, lower uric acid (UA) (p = 0.038), and higher rates of atopic dermatitis (p = 0.01). Cases showed more severe depressive and social anxiety symptoms based on self-rated scales: Patient Heath Questionnaire 9 (PHQ-9) (p < 0.001) and Liebowitz Social Anxiety Scale Japanese Version (LSAS-J) (p = 0.04). Tarumi's Modern-Type Depression Trait Scale (TACS-22), which measure traits of Modern-Type Depression (MTD), were significantly higher in cases (p = 0.003). Conclusion: The present study has suggested that ASD patients with hikikomori were more likely to have higher sensory abnormalities, comorbid atopic dermatitis, lower UA, stronger depressive, and anxiety tendency. Evaluating and approaching these aspects are important for appropriate interventions in ASD with hikikomori. Further investigations should be conducted to validate our pilot findings.

Generalizable neuromarker for autism spectrum disorder across imaging sites and developmental stages: A multi-site study.

Autism spectrum disorder (ASD) is a lifelong condition, and its underlying biological mechanisms remain elusive. The complexity of various factors, including inter-site and development-related differences, makes it challenging to develop generalizable neuroimaging-based biomarkers for ASD. This study used a large-scale, multi-site dataset of 730 Japanese adults to develop a generalizable neuromarker for ASD across independent sites (U.S., Belgium, and Japan) and different developmental stages (children and adolescents). Our adult ASD neuromarker achieved successful generalization for the US and Belgium adults (area under the curve [AUC] = 0.70) and Japanese adults (AUC = 0.81). The neuromarker demonstrated significant generalization for children (AUC = 0.66) and adolescents (AUC = 0.71; all P<0.05, family-wise-error corrected). We identified 141 functional connections (FCs) important for discriminating individuals with ASD from TDCs. These FCs largely centered on social brain regions such as the amygdala, hippocampus, dorsomedial and ventromedial prefrontal cortices, and temporal cortices. Finally, we mapped schizophrenia (SCZ) and major depressive disorder (MDD) onto the biological axis defined by the neuromarker and explored the biological continuity of ASD with SCZ and MDD. We observed that SCZ, but not MDD, was located proximate to ASD on the biological dimension defined by the ASD neuromarker. The successful generalization in multifarious datasets and the observed relations of ASD with SCZ on the biological dimensions provide new insights for a deeper understanding of ASD.

Sensitivity to interaural level and time differences in individuals with autism spectrum disorder.

Individuals with autism spectrum disorders (ASD) are reported to exhibit degraded performance in sound localization. This study investigated whether the sensitivity to the interaural level differences (ILDs) and interaural time differences (ITDs), major cues for horizontal sound localization, are affected in ASD. Thresholds for discriminating the ILD and ITD were measured for adults with ASD and age- and IQ-matched controls in a lateralization experiment. Results show that the ASD group exhibited higher ILD and ITD thresholds than the control group. Moreover, there was a significant diversity of ITD sensitivity in the ASD group, and it contained a larger proportion of participants with poor ITD sensitivity than the control group. The current study suggests that deficits in relatively low-level processes in the auditory pathway are implicated in degraded performance of sound localization in individuals with ASD. The results are consistent with the structural abnormalities and great variability in the morphology in the brainstem reported by neuroanatomical studies of ASD.

Asymmetric Complexity in a Pupil Control Model With Laterally Imbalanced Neural Activity in the Locus Coeruleus: A Potential Biomarker for Attention-Deficit/Hyperactivity Disorder.

Locus coeruleus (LC) overactivity, especially in the right hemisphere, is a recognized pathophysiology of attention-deficit/hyperactivity disorder (ADHD) and may be related to inattention. LC activity synchronizes with the kinetics of the pupil diameter and reflects neural activity related to cognitive functions such as attention and arousal. Recent studies highlight the importance of the complexity of the temporal patterns of pupil diameter. Moreover, asymmetrical pupil diameter, which correlates with the severity of inattention, impulsivity, and hyperactivity in ADHD, might be attributed to a left-right imbalance in LC activity. We recently constructed a computational model of pupil diameter based on the newly discovered contralateral projection from the LC to the Edinger-Westphal nucleus (EWN), which demonstrated mechanisms for the complex temporal patterns of pupil kinetics; however, it remains unclear how LC overactivity and its asymmetry affect pupil diameter. We hypothesized that a neural model of pupil diameter control featuring left-right differences in LC activity and projections onto two opponent sides may clarify the role of pupil behavior in ADHD studies. Therefore, we developed a pupil diameter control model reflecting LC overactivity in the right hemisphere by incorporating a contralateral projection from the LC to EWN and evaluated the complexity of the temporal patterns of pupil diameter generated by the model. Upon comparisons with experimentally measured pupil diameters in adult patients with ADHD, the parameter region of interest of the neural model was estimated, which was a region in the two-dimensional plot of complexity versus left-side LC baseline activity and that of the right. A region resulting in relatively high right-side complexity, which corresponded to the pathophysiological indexes, was identified. We anticipate that the discovery of lateralization of complexity in pupil diameter fluctuations will facilitate the development of biomarkers for accurate diagnosis of ADHD.

Intergroup bias in punishing behaviors of adults with autism spectrum disorder.

Groups are essential elements of society, and humans, by nature, commonly manifest intergroup bias (i.e., behave more positively toward an ingroup member than toward an outgroup member). Despite the growing evidence of various types of altered decision-making in individuals with autism spectrum disorder (ASD), their behavior under the situation involving group membership remains largely unexplored. By modifying a third-party punishment paradigm, we investigated intergroup bias in individuals with ASD and typical development (TD). In our experiment, participants who were considered as the third party observed a dictator game wherein proposers could decide how to distribute a provided amount of money while receivers could only accept unconditionally. Participants were confronted with two different group situations: the proposer was an ingroup member and the recipient was an outgroup member (IN/OUT condition) or the proposer was an outgroup member and the recipient was an ingroup member (OUT/IN condition). Participants with TD punished proposers more severely when violating social norms in the OUT/IN condition than in IN/OUT condition, indicating that their decisions were influenced by the intergroup context. This intergroup bias was attenuated in individuals with ASD. Our findings deepen the understanding of altered decision-making and socioeconomic behaviors in individuals with ASD.

Decision flexibilities in autism spectrum disorder: an fMRI study of moral dilemmas.

People make flexible decisions across a wide range of contexts to resolve social or moral conflicts. Individuals with autism spectrum disorder (ASD) frequently report difficulties in such behaviors, which hinders the flexibility in changing strategies during daily activities or adjustment of perspective during communication. However, the underlying mechanisms of this issue are insufficiently understood. This study aimed to investigate decision flexibility in ASD using a functional magnetic resonance imaging task that involved recognizing and resolving two types of moral dilemmas: cost-benefit analysis (CBA) and mitigating inevitable misconducts (MIM). The CBA session assessed the participants' pitting of result-oriented outcomes against distressful harmful actions, whereas the MIM session assessed their pitting of the extenuation of a criminal sentence against a sympathetic situation of defendants suffering from violence or disease. The behavioral outcome in CBA-related flexibility was significantly lower in the ASD group compared to that of the typical development group. In the corresponding CBA contrast, activation in the left inferior frontal gyrus was lower in the ASD group. Meanwhile, in the MIM-related flexibility, there were no significant group differences in behavioral outcome or brain activity. Our findings add to our understanding of flexible decision-making in ASD.

A multi-site, multi-disorder resting-state magnetic resonance image database.

Machine learning classifiers for psychiatric disorders using resting-state functional magnetic resonance imaging (rs-fMRI) have recently attracted attention as a method for directly examining relationships between neural circuits and psychiatric disorders. To develop accurate and generalizable classifiers, we compiled a large-scale, multi-site, multi-disorder neuroimaging database. The database comprises resting-state fMRI and structural images of the brain from 993 patients and 1,421 healthy individuals, as well as demographic information such as age, sex, and clinical rating scales. To harmonize the multi-site data, nine healthy participants ("traveling subjects") visited the sites from which the above datasets were obtained and underwent neuroimaging with 12 scanners. All participants consented to having their data shared and analyzed at multiple medical and research institutions participating in the project, and 706 patients and 1,122 healthy individuals consented to having their data disclosed. Finally, we have published four datasets: 1) the SRPBS Multi-disorder Connectivity Dataset 2), the SRPBS Multi-disorder MRI Dataset (restricted), 3) the SRPBS Multi-disorder MRI Dataset (unrestricted), and 4) the SRPBS Traveling Subject MRI Dataset.

Common Brain Networks Between Major Depressive-Disorder Diagnosis and Symptoms of Depression That Are Validated for Independent Cohorts.

Large-scale neuroimaging data acquired and shared by multiple institutions are essential to advance neuroscientific understanding of pathophysiological mechanisms in psychiatric disorders, such as major depressive disorder (MDD). About 75% of studies that have applied machine learning technique to neuroimaging have been based on diagnoses by clinicians. However, an increasing number of studies have highlighted the difficulty in finding a clear association between existing clinical diagnostic categories and neurobiological abnormalities. Here, using resting-state functional magnetic resonance imaging, we determined and validated resting-state functional connectivity related to depression symptoms that were thought to be directly related to neurobiological abnormalities. We then compared the resting-state functional connectivity related to depression symptoms with that related to depression diagnosis that we recently identified. In particular, for the discovery dataset with 477 participants from 4 imaging sites, we removed site differences using our recently developed harmonization method and developed a brain network prediction model of depression symptoms (Beck Depression Inventory-II [BDI] score). The prediction model significantly predicted BDI score for an independent validation dataset with 439 participants from 4 different imaging sites. Finally, we found 3 common functional connections between those related to depression symptoms and those related to MDD diagnosis. These findings contribute to a deeper understanding of the neural circuitry of depressive symptoms in MDD, a hetero-symptomatic population, revealing the neural basis of MDD.

Identification of attention-deficit hyperactivity disorder based on the complexity and symmetricity of pupil diameter.

Adult attention-deficit/hyperactivity disorder (ADHD) frequently leads to psychological/social dysfunction if unaddressed. Identifying a reliable biomarker would assist the diagnosis of adult ADHD and ensure that adults with ADHD receive treatment. Pupil diameter can reflect inherent neural activity and deficits of attention or arousal characteristic of ADHD. Furthermore, distinct profiles of the complexity and symmetricity of neural activity are associated with some psychiatric disorders. We hypothesized that analysing the relationship between the size, complexity of temporal patterns, and asymmetricity of pupil diameters will help characterize the nervous systems of adults with ADHD and that an identification method combining these features would ease the diagnosis of adult ADHD. To validate this hypothesis, we evaluated the resting state hippus in adult participants with or without ADHD by examining the pupil diameter and its temporal complexity using sample entropy and the asymmetricity of the left and right pupils using transfer entropy. We found that large pupil diameters and low temporal complexity and symmetry were associated with ADHD. Moreover, the combination of these factors by the classifier enhanced the accuracy of ADHD identification. These findings may contribute to the development of tools to diagnose adult ADHD.

Pupillometric Complexity and Symmetricity Follow Inverted-U Curves Against Baseline Diameter Due to Crossed Locus Coeruleus Projections to the Edinger-Westphal Nucleus.

In addition to photic reflex function, the temporal behavior of the pupil diameter reflects levels of arousal and attention and thus internal cognitive neural activity. Recent studies have reported that these behaviors are characterized by baseline activity, temporal complexity, and symmetricity (i.e., degree of symmetry) between the right and left pupil diameters. We hypothesized that experimental analysis to reveal relationships among these characteristics and model-based analysis focusing on the newly discovered contralateral projection from the locus coeruleus (LC) to the Edinger-Westphal nucleus (EWN) within the neural system for controlling pupil diameter could contribute to another dimension of understanding of complex pupil dynamics. In this study, we aimed to validate our hypothesis by analyzing the pupillary hippus in the healthy resting state in terms of sample entropy (SampEn), to capture complexity, and transfer entropy (TranEn), to capture symmetricity. We also constructed a neural model embedded with the new findings on neural pathways. The following results were observed: first, according to surrogate data analysis, the complexity and symmetricity of pupil diameter changes reflect a non-linear deterministic process. Second, both the complexity and the symmetricity are unimodal, peaking at intermediate pupil diameters. Third, according to simulation results, the neural network that controls pupil diameter has an inverted U-shaped profile of complexity and symmetricity vs. baseline LC activity; this tendency is enhanced by the contralateral synaptic projections from the LCs to the EWNs. Thus, we characterized the typical relationships between the baseline activity and the complexity and symmetricity of the pupillometric data in terms of SampEn and TranEn. Our evaluation method and findings may facilitate the development of estimation and diagnostic tools for exploring states of the healthy brain and psychiatric disorders based on measurements of pupil diameter.

Brain activations while processing degraded speech in adults with autism spectrum disorder.

Individuals with autism spectrum disorder (ASD) are found to have difficulties in understanding speech in adverse conditions. In this study, we used noise-vocoded speech (VS) to investigate neural processing of degraded speech in individuals with ASD. We ran fMRI experiments in the ASD group and a typically developed control (TDC) group while they listened to clear speech (CS), VS, and spectrally rotated VS (SRVS), and they were requested to pay attention to the heard sentence and answer whether it was intelligible or not. The VS used in this experiment was spectrally degraded but still intelligible, but the SRVS was unintelligible. We recruited 21 right-handed adult males with ASD and 24 age-matched and right-handed male TDC participants for this experiment. Compared with the TDC group, we observed reduced functional connectivity (FC) between the left dorsal premotor cortex and left temporoparietal junction in the ASD group for the effect of task difficulty in speech processing, computed as VS-(CS + SRVS)/2. Furthermore, the observed reduced FC was negatively correlated with their Autism-Spectrum Quotient scores. This observation supports our hypothesis that the disrupted dorsal stream for attentive process of degraded speech in individuals with ASD might be related to their difficulty in understanding speech in adverse conditions.

Neural correlates of shared sensory symptoms in autism and attention-deficit/hyperactivity disorder.

Symptoms of autism spectrum disorder and attention-deficit/hyperactivity disorder often co-occur. Among these, sensory impairment, which is a core diagnostic feature of autism spectrum disorder, is often observed in children with attention-deficit/hyperactivity disorder. However, the underlying mechanisms of symptoms that are shared across disorders remain unknown. To examine the neural correlates of sensory symptoms that are associated with autism spectrum disorder and attention-deficit/hyperactivity disorder, we analysed resting-state functional MRI data obtained from 113 people with either autism spectrum disorder or attention-deficit/hyperactivity disorder (n = 78 autism spectrum disorder, mean age = 29.5; n = 35 attention-deficit/hyperactivity disorder, mean age = 31.2) and 96 neurotypical controls (mean age = 30.6, range: 20-55 years) using a cross-sectional study design. First, we used a multi-dimensional approach to examine intrinsic brain functional connectivity related to sensory symptoms in four domains (i.e. low registration, sensation seeking, sensory sensitivity and sensation avoidance), after controlling for age, handedness and head motion. Then, we used a partial least squares correlation to examine the link between sensory symptoms related to intrinsic brain functional connectivity and neurodevelopmental symptoms measured using the Autism Spectrum Quotient and Conners' Adult Attention-Deficit/Hyperactivity Disorder Rating Scale, regardless of diagnosis. To test whether observed associations were specific to sensory symptoms related to intrinsic brain functional connectivity, we conducted a control analysis using a bootstrap framework. The results indicated that transdiagnostic yet distinct intrinsic brain functional connectivity neural bases varied according to the domain of the examined sensory symptom. Partial least squares correlation analysis revealed two latent components (latent component 1: q < 0.001 and latent component 2: q < 0.001). For latent component 1, a set of intrinsic brain functional connectivity was predominantly associated with neurodevelopmental symptom-related composite score (r = 0.64, P < 0.001), which was significantly correlated with Conners' Adult Attention-Deficit/Hyperactivity Disorder Rating Scale total T scores (r = -0.99, q < 0.001). For latent component 2, another set of intrinsic brain functional connectivity was positively associated with neurodevelopmental symptom-related composite score (r = 0.58, P < 0.001), which was eventually positively associated with Autism Spectrum Quotient total scores (r = 0.92, q < 0.001). The bootstrap analysis showed that the relationship between intrinsic brain functional connectivity and neurodevelopmental symptoms was relative to sensory symptom-related intrinsic brain functional connectivity (latent component 1: P = 0.003 and latent component 2: P < 0.001). The current results suggest that sensory symptoms in individuals with autism spectrum disorder and those with attention-deficit/hyperactivity disorder have shared neural correlates. The neural correlates of the sensory symptoms were associated with the severity of both autism spectrum disorder and attention-deficit/hyperactivity disorder symptoms, regardless of diagnosis.

Atypical alert state control in adult patients with ADHD: A pupillometry study.

Although behavioral studies have repeatedly demonstrated that individuals with attention-deficit/hyperactivity disorder (ADHD) have deficits in alertness, little is known about its underlying neural basis. It is hypothesized that pupil diameter reflects the firing of norepinephrine (NE) neurons in the locus coeruleus (LC), and that the LC-NE neuromodulatory system for regulating alertness may be dysfunctional in ADHD. To clinically and non-invasively examine this hypothesis, we monitored the kinetics of pupil diameter in response to stimuli and compared them between adults with ADHD (n = 17) and typically developing (TD) adults (n = 23) during an auditory continuous performance task. Individuals in the ADHD group exhibited a significantly larger tonic pupil diameter, and a suppressed stimulus-evoked phasic pupil dilation, compared to those in the TD group. These findings provide support for the idea that the aberrant regulatory control of pupil diameter in adults with ADHD may be consistent with a compromised state of alertness resulting from a hyperactivated LC-NE system.

Generalizable brain network markers of major depressive disorder across multiple imaging sites.

Many studies have highlighted the difficulty inherent to the clinical application of fundamental neuroscience knowledge based on machine learning techniques. It is difficult to generalize machine learning brain markers to the data acquired from independent imaging sites, mainly due to large site differences in functional magnetic resonance imaging. We address the difficulty of finding a generalizable marker of major depressive disorder (MDD) that would distinguish patients from healthy controls based on resting-state functional connectivity patterns. For the discovery dataset with 713 participants from 4 imaging sites, we removed site differences using our recently developed harmonization method and developed a machine learning MDD classifier. The classifier achieved an approximately 70% generalization accuracy for an independent validation dataset with 521 participants from 5 different imaging sites. The successful generalization to a perfectly independent dataset acquired from multiple imaging sites is novel and ensures scientific reproducibility and clinical applicability.

White matter alterations in autism spectrum disorder and attention-deficit/hyperactivity disorder in relation to sensory profile.

BACKGROUND: Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) have high rates of co-occurrence and share atypical behavioral characteristics, including sensory symptoms. The present diffusion tensor imaging (DTI) study was conducted to examine whether and how white matter alterations are observed in adult populations with developmental disorders (DD) and to determine how brain-sensory relationships are either shared between or distinct to ASD and ADHD. METHODS: We collected DTI data from adult population with DD (a primary diagnosis of ASD: n = 105, ADHD: n = 55) as well as age- and sex-matched typically developing (TD) participants (n = 58). Voxel-wise fractional anisotropy (FA), mean diffusivity, axial diffusivity, and radial diffusivity (RD) were analyzed using tract-based spatial statistics. The severities of sensory symptoms were assessed using the Adolescent/Adult Sensory Profile (AASP). RESULTS: Categorical analyses identified voxel clusters showing significant effects of DD on FA and RD in the posterior portion of the corpus callosum and its extension in the right hemisphere. Furthermore, regression analyses using the AASP scores revealed that slopes in relationships of FA or RD with the degree of sensory symptoms were parallel between the two DDs in large parts of the affected corpus callosum regions. A small but significant cluster did exist showing difference in association between an AASP subscale score and RD across ASD and ADHD. LIMITATIONS: Wide age range of the participants may be oversimplified. CONCLUSIONS: These results indicate that white matter alteration and their relationships to sensory symptoms are largely shared between ASD and ADHD, with localized abnormalities showing significant between-diagnosis differences within DD.

Publisher Correction: Primary functional brain connections associated with melancholic major depressive disorder and modulation by antidepressants.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Binding of Dopamine D1 Receptor and Noradrenaline Transporter in Individuals with Autism Spectrum Disorder: A PET Study.

Although previous studies have suggested the involvement of dopamine (DA) and noradrenaline (NA) neurotransmissions in the autism spectrum disorder (ASD) pathophysiology, few studies have examined these neurotransmissions in individuals with ASD in vivo. Here, we investigated DA D1 receptor (D1R) and noradrenaline transporter (NAT) binding in adults with ASD (n = 18) and neurotypical controls (n = 20) by utilizing two different PET radioligands, [11C]SCH23390 and (S,S)-[18F]FMeNER-D2, respectively. We found no significant group differences in DA D1R (striatum, anterior cingulate cortex, and temporal cortex) or NAT (thalamus and pons) binding. However, in the ASD group, there were significant negative correlations between DA D1R binding (striatum, anterior cingulate cortex and temporal cortex) and the "attention to detail" subscale score of the Autism Spectrum Quotient. Further, there was a significant positive correlation between DA D1R binding (temporal cortex) and emotion perception ability assessed by the neurocognitive battery. Associations of NAT binding with empathic abilities and executive function were found in controls, but were absent in the ASD group. Although a lack of significant group differences in binding might be partly due to the heterogeneity of ASD, our results indicate that central DA and NA function might play certain roles in the clinical characteristics of ASD.