Moral foundations in autistic people and people with systemizing minds.

BACKGROUND: Do autistic people share the same moral foundations as typical people? Here we built on two prominent theories in psychology, moral foundations theory and the empathizing-systemizing (E-S) theory, to observe the nature of morality in autistic people and systemizers. METHODS: In dataset 1, we measured five foundations of moral judgements (Care, Fairness, Loyalty, Authority, and Sanctity) measured by the Moral Foundations Questionnaire (MFQ) in autistic (n = 307) and typical people (n = 415) along with their scores on the Empathy Quotient (EQ) and Systemizing Quotient (SQ). In dataset 2, we measured these same five foundations along with E-S cognitive types (previously referred to as "brain types") in a large sample of typical people (N = 7595). RESULTS: Autistic people scored the same on Care (i.e., concern for others) as typical people (h1). Their affective empathy (but not their cognitive empathy) scores were positively correlated with Care. Autistic people were more likely to endorse Fairness (i.e., giving people what they are owed, and treating them with justice) over Care (h2). Their systemizing scores were positively correlated with Fairness. Autistic people or those with a systemizing cognitive profile had lower scores on binding foundations: Loyalty, Authority, and Sanctity (h3). Systemizing in typical people was positively correlated with Liberty (i.e., hypervigilance against oppression), which is a sixth moral foundation (h4). Although the majority of people in all five E-S cognitive types self-identified as liberal, with a skew towards empathizing (h5), the percentage of libertarians was highest in systemizing cognitive types (h6). E-S cognitive types accounted for 2 to 3 times more variance for Care than did sex. LIMITATIONS: Our study is limited by its reliance on self-report measures and a focus on moral judgements rather than behavior or decision-making. Further, only dataset 2 measured political identification, therefore we were unable to assess politics in autistic people. CONCLUSIONS: We conclude that some moral foundations in autistic people are similar to those in typical people (despite the difficulties in social interaction that are part of autism), and some are subtly different. These subtle differences vary depending on empathizing and systemizing cognitive types.

Eye-Tracking Biomarkers and Autism Diagnosis in Primary Care.

Importance: Finding effective and scalable solutions to address diagnostic delays and disparities in autism is a public health imperative. Approaches that integrate eye-tracking biomarkers into tiered community-based models of autism evaluation hold promise for addressing this problem. Objective: To determine whether a battery of eye-tracking biomarkers can reliably differentiate young children with and without autism in a community-referred sample collected during clinical evaluation in the primary care setting and to evaluate whether combining eye-tracking biomarkers with primary care practitioner (PCP) diagnosis and diagnostic certainty is associated with diagnostic outcome. Design, Setting, and Participants: Early Autism Evaluation (EAE) Hub system PCPs referred a consecutive sample of children to this prospective diagnostic study for blinded eye-tracking index test and follow-up expert evaluation from June 7, 2019, to September 23, 2022. Participants included 146 children (aged 14-48 months) consecutively referred by 7 EAE Hubs. Of 154 children enrolled, 146 provided usable data for at least 1 eye-tracking measure. Main Outcomes and Measures: The primary outcomes were sensitivity and specificity of a composite eye-tracking (ie, index) test, which was a consolidated measure based on significant eye-tracking indices, compared with reference standard expert clinical autism diagnosis. Secondary outcome measures were sensitivity and specificity of an integrated approach using an index test and PCP diagnosis and certainty. Results: Among 146 children (mean [SD] age, 2.6 [0.6] years; 104 [71%] male; 21 [14%] Hispanic or Latine and 96 [66%] non-Latine White; 102 [70%] with a reference standard autism diagnosis), 113 (77%) had concordant autism outcomes between the index (composite biomarker) and reference outcomes, with 77.5% sensitivity (95% CI, 68.4%-84.5%) and 77.3% specificity (95% CI, 63.0%-87.2%). When index diagnosis was based on the combination of a composite biomarker, PCP diagnosis, and diagnostic certainty, outcomes were concordant with reference standard for 114 of 127 cases (90%) with a sensitivity of 90.7% (95% CI, 83.3%-95.0%) and a specificity of 86.7% (95% CI, 70.3%-94.7%). Conclusions and Relevance: In this prospective diagnostic study, a composite eye-tracking biomarker was associated with a best-estimate clinical diagnosis of autism, and an integrated diagnostic model including PCP diagnosis and diagnostic certainty demonstrated improved sensitivity and specificity. These findings suggest that equipping PCPs with a multimethod diagnostic approach has the potential to substantially improve access to timely, accurate diagnosis in local communities.

Effect of Ketamine Treatment on Social Withdrawal in Autism and Autism-Like Conditions.

OBJECTIVE: Ketamine and esketamine have been used in the field of psychiatry to alleviate conditions such as major depressive disorder. Our objective was to evaluate the current literature on the use of ketamine for symptoms of social withdrawal in autism spectrum disorder (ASD) and autism-like conditions. METHODS: A comprehensive search of PubMed and Web of Science was conducted to identify literature involving the use of ketamine to treat symptoms of autism and social withdrawal. Patients with comorbid disorders were also included. RESULTS: Two original studies were found, showing mixed results on the use of ketamine for ASD. The use of esketamine found no statistically significant results, whereas the use of intravenous ketamine was shown to alleviate symptoms of social withdrawal especially in the short term. Neither study reported a significant amount of serious adverse events. Five case reports were also included, showing decreased depressive symptoms and evidence of increased social condition. CONCLUSIONS: Research on the use of ketamine for ASD and ASD-related conditions is limited. Evidence of improved social condition exists, but further studies should be conducted to increase sample power and test various doses and methods of administration.

A hybrid CNN-SVM model for enhanced autism diagnosis.

Autism is a representative disorder of pervasive developmental disorder. It exerts influence upon an individual's behavior and performance, potentially co-occurring with other mental illnesses. Consequently, an effective diagnostic approach proves to be invaluable in both therapeutic interventions and the timely provision of medical support. Currently, most scholars' research primarily relies on neuroimaging techniques for auxiliary diagnosis and does not take into account the distinctive features of autism's social impediments. In order to address this deficiency, this paper introduces a novel convolutional neural network-support vector machine model that integrates resting state functional magnetic resonance imaging data with the social responsiveness scale metrics for the diagnostic assessment of autism. We selected 821 subjects containing the social responsiveness scale measure from the publicly available Autism Brain Imaging Data Exchange dataset, including 379 subjects with autism spectrum disorder and 442 typical controls. After preprocessing of fMRI data, we compute the static and dynamic functional connectivity for each subject. Subsequently, convolutional neural networks and attention mechanisms are utilized to extracts their respective features. The extracted features, combined with the social responsiveness scale features, are then employed as novel inputs for the support vector machine to categorize autistic patients and typical controls. The proposed model identifies salient features within the static and dynamic functional connectivity, offering a possible biological foundation for clinical diagnosis. By incorporating the behavioral assessments, the model achieves a remarkable classification accuracy of 94.30%, providing a more reliable support for auxiliary diagnosis.

Exploring early life social and executive function development in infants and risk for autism: a prospective cohort study protocol of NICU graduates and infants at risk for cerebral palsy.

BACKGROUND: Delays in early social and executive function are predictive of later developmental delays and eventual neurodevelopmental diagnoses. There is limited research examining such markers in the first year of life. High-risk infant groups commonly present with a range of neurodevelopmental challenges, including social and executive function delays, and show higher rates of autism diagnoses later in life. For example, it has been estimated that up to 30% of infants diagnosed with cerebral palsy (CP) will go on to be diagnosed with autism later in life. METHODS: This article presents a protocol of a prospective longitudinal study. The primary aim of this study is to identify early life markers of delay in social and executive function in high-risk infants at the earliest point in time, and to explore how these markers may relate to the increased risk for social and executive delay, and risk of autism, later in life. High-risk infants will include Neonatal Intensive Care Unit (NICU) graduates, who are most commonly admitted for premature birth and/or cardiovascular problems. In addition, we will include infants with, or at risk for, CP. This prospective study will recruit 100 high-risk infants at the age of 3-12 months old and will track social and executive function across the first 2 years of their life, when infants are 3-7, 8-12, 18 and 24 months old. A multi-modal approach will be adopted by tracking the early development of social and executive function using behavioural, neurobiological, and caregiver-reported everyday functioning markers. Data will be analysed to assess the relationship between the early markers, measured from as early as 3-7 months of age, and the social and executive function as well as the autism outcomes measured at 24 months. DISCUSSION: This study has the potential to promote the earliest detection and intervention opportunities for social and executive function difficulties as well as risk for autism in NICU graduates and/or infants with, or at risk for, CP. The findings of this study will also expand our understanding of the early emergence of autism across a wider range of at-risk groups.

Differences in mid-gestational and early postnatal neonatal cytokines and chemokines are associated with patterns of maternal autoantibodies in the context of autism.

Associations between maternal immune dysregulation (including autoimmunity and skewed cytokine/chemokine profiles) and offspring neurodevelopmental disorders such as autism have been reported. In maternal autoantibody-related autism, specific maternally derived autoantibodies can access the fetal compartment to target eight proteins critical for neurodevelopment. We examined the relationship between maternal autoantibodies to the eight maternal autoantibody-related autism proteins and cytokine/chemokine profiles in the second trimester of pregnancy in mothers of children later diagnosed with autism and their neonates' cytokine/chemokine profiles. Using banked maternal serum samples from 15 to 19 weeks of gestation from the Early Markers for Autism Study and corresponding banked newborn bloodspots, we identified three maternal/offspring groups based on maternal autoantibody status: (1) mothers with autoantibodies to one or more of the eight maternal autoantibody-related autismassociated proteins but not a maternal autoantibody-related autism-specific pattern, (2) mothers with a known maternal autoantibody-related autism pattern, and (3) mothers without autoantibodies to any of the eight maternal autoantibody-related autism proteins. Using a multiplex platform, we measured maternal second trimester and neonatal cytokine/chemokine levels. This combined analysis aimed to determine potential associations between maternal autoantibodies and the maternal and neonatal cytokine/chemokine profiles, each of which has been shown to have implications on offspring neurodevelopment independently.

Differential neural correlates underlying visuospatial versus semantic reasoning in autistic children.

While fronto-posterior underconnectivity has often been reported in autism, it was shown that different contexts may modulate between-group differences in functional connectivity. Here, we assessed how different task paradigms modulate functional connectivity differences in a young autistic sample relative to typically developing children. Twenty-three autistic and 23 typically developing children aged 6 to 15 years underwent functional magnetic resonance imaging (fMRI) scanning while completing a reasoning task with visuospatial versus semantic content. We observed distinct connectivity patterns in autistic versus typical children as a function of task type (visuospatial vs. semantic) and problem complexity (visual matching vs. reasoning), despite similar performance. For semantic reasoning problems, there was no significant between-group differences in connectivity. However, during visuospatial reasoning problems, we observed occipital-occipital, occipital-temporal, and occipital-frontal over-connectivity in autistic children relative to typical children. Also, increasing the complexity of visuospatial problems resulted in increased functional connectivity between occipital, posterior (temporal), and anterior (frontal) brain regions in autistic participants, more so than in typical children. Our results add to several studies now demonstrating that the connectivity alterations in autistic relative to neurotypical individuals are much more complex than previously thought and depend on both task type and task complexity and their respective underlying cognitive processes.

Increased number of excitatory synapsis and decreased number of inhibitory synapsis in the prefrontal cortex in autism.

Previous studies in autism spectrum disorder demonstrated an increased number of excitatory pyramidal cells and a decreased number of inhibitory parvalbumin+ chandelier interneurons in the prefrontal cortex of postmortem brains. How these changes in cellular composition affect the overall abundance of excitatory and inhibitory synapses in the cortex is not known. Herein, we quantified the number of excitatory and inhibitory synapses in the prefrontal cortex of 10 postmortem autism spectrum disorder brains and 10 control cases. To identify excitatory synapses, we used VGlut1 as a marker of the presynaptic component and postsynaptic density protein-95 as marker of the postsynaptic component. To identify inhibitory synapses, we used the vesicular gamma-aminobutyric acid transporter as a marker of the presynaptic component and gephyrin as a marker of the postsynaptic component. We used Puncta Analyzer to quantify the number of co-localized pre- and postsynaptic synaptic components in each area of interest. We found an increase in the number of excitatory synapses in upper cortical layers and a decrease in inhibitory synapses in all cortical layers in autism spectrum disorder brains compared with control cases. The alteration in the number of excitatory and inhibitory synapses could lead to neuronal dysfunction and disturbed network connectivity in the prefrontal cortex in autism spectrum disorder.

Trajectory of depressive symptoms over adolescence in autistic and neurotypical youth.

BACKGROUND: Adolescence coincides with a dramatic rise in the onset of psychiatric conditions including depression. Depression symptoms may be particularly prevalent and impairing for youth with autism spectrum disorder (ASD). While prior research suggests adolescence is associated with worsening depression symptoms for typically developing (TD) and autistic youth, it is unclear if they follow a similar course. METHOD: The study examined the trajectory of depressive symptoms in autistic and neurotypical youth over a 4-year longitudinal study using linear and logistic mixed effects models. In youth with clinically relevant depressive scores (t-score > 65), moderating factors (i.e., diagnosis, age, puberty, sex) were explored. During Year 1, the sample included 244 youth 10-to-13 years: 140 in the ASD group (36 females) and 104 in the TD group (46 females). RESULTS: Autistic youth had elevated depression scores compared to TD peers (p < 0.001) and females were higher than males in both groups (p = 0.001). There was significant diagnosis by age (p < 0.001) and diagnosis by pubertal stage (p < 0.05) interactions. In the ASD group, elevated depressive scores presented in early adolescence and decreased during middle adolescence and puberty, whereas the TD group showed the opposite trend with an increase in depression symptoms with advancing development. LIMITATIONS: Limitations include an unequal sex distribution (fewer females), non-representative autistic sample (e.g., cognition and race/ethnicity), and potential confound of the COVID-19 pandemic. CONCLUSIONS: Autistic youth present with higher rates of depressive symptoms early in development; yet, approaching middle adolescence and puberty, the symptom trajectory in the autistic youth declines coinciding with an increase in the TD youth. While group trajectories are divergent, they lead to similar levels of depression in late adolescence with higher symptoms in females. Findings suggest a period of quiescence in depressive symptomology influenced by biopsychosocial factors impacting affective profiles.

Atypical functional connectivity between the amygdala and visual, salience regions in infants with genetic liability for autism.

The amygdala undergoes a period of overgrowth in the first year of life, resulting in enlarged volume by 12 months in infants later diagnosed with ASD. The overgrowth of the amygdala may have functional consequences during infancy. We investigated whether amygdala connectivity differs in 12-month-olds at high likelihood (HL) for ASD (defined by having an older sibling with autism), compared to those at low likelihood (LL). We examined seed-based connectivity of left and right amygdalae, hypothesizing that the HL and LL groups would differ in amygdala connectivity, especially with the visual cortex, based on our prior reports demonstrating that components of visual circuitry develop atypically and are linked to genetic liability for autism. We found that HL infants exhibited weaker connectivity between the right amygdala and the left visual cortex, as well as between the left amygdala and the right anterior cingulate, with evidence that these patterns occur in distinct subgroups of the HL sample. Amygdala connectivity strength with the visual cortex was related to motor and communication abilities among HL infants. Findings indicate that aberrant functional connectivity between the amygdala and visual regions is apparent in infants with genetic liability for ASD and may have implications for early differences in adaptive behaviors.

Quantitative proteomics of dorsolateral prefrontal cortex reveals an early pattern of synaptic dysmaturation in children with idiopathic autism.

Autism spectrum disorder (ASD) is a developmental disorder with a rising prevalence and unknown etiology presenting with deficits in cognition and abnormal behavior. We hypothesized that the investigation of the synaptic component of prefrontal cortex may provide proteomic signatures that may identify the biological underpinnings of cognitive deficits in childhood ASD. Subcellular fractions of synaptosomes from prefrontal cortices of age-, brain area-, and postmortem-interval-matched samples from children and adults with idiopathic ASD vs. controls were subjected to HPLC-tandem mass spectrometry. Analysis of data revealed the enrichment of ASD risk genes that participate in slow maturation of the postsynaptic density (PSD) structure and function during early brain development. Proteomic analysis revealed down regulation of PSD-related proteins including AMPA and NMDA receptors, GRM3, DLG4, olfactomedins, Shank1-3, Homer1, CaMK2α, NRXN1, NLGN2, Drebrin1, ARHGAP32, and Dock9 in children with autism (FDR-adjusted P < 0.05). In contrast, PSD-related alterations were less severe or unchanged in adult individuals with ASD. Network analyses revealed glutamate receptor abnormalities. Overall, the proteomic data support the concept that idiopathic autism is a synaptopathy involving PSD-related ASD risk genes. Interruption in evolutionarily conserved slow maturation of the PSD complex in prefrontal cortex may lead to the development of ASD in a susceptible individual.

Neuroanatomy of autism: what is the role of the cerebellum?

Autism (or autism spectrum disorder) was initially defined as a psychiatric disorder, with the likely cause maternal behavior (the very destructive "refrigerator mother" theory). It took several decades for research into brain mechanisms to become established. Both neuropathological and imaging studies found differences in the cerebellum in autism spectrum disorder, the most widely documented being a decreased density of Purkinje cells in the cerebellar cortex. The popular interpretation of these results is that cerebellar neuropathology is a critical cause of autism spectrum disorder. We challenge that view by arguing that if fewer Purkinje cells are critical for autism spectrum disorder, then any condition that causes the loss of Purkinje cells should also cause autism spectrum disorder. We will review data on damage to the cerebellum from cerebellar lesions, tumors, and several syndromes (Joubert syndrome, Fragile X, and tuberous sclerosis). Collectively, these studies raise the question of whether the cerebellum really has a role in autism spectrum disorder. Autism spectrum disorder is now recognized as a genetically caused developmental disorder. A better understanding of the genes that underlie the differences in brain development that result in autism spectrum disorder is likely to show that these genes affect the development of the cerebellum in parallel with the development of the structures that do underlie autism spectrum disorder.

A multimodal interface for speech perception: the role of the left superior temporal sulcus in social cognition and autism.

Multimodal integration is crucial for human interaction, in particular for social communication, which relies on integrating information from various sensory modalities. Recently a third visual pathway specialized in social perception was proposed, which includes the right superior temporal sulcus (STS) playing a key role in processing socially relevant cues and high-level social perception. Importantly, it has also recently been proposed that the left STS contributes to audiovisual integration of speech processing. In this article, we propose that brain areas along the right STS that support multimodal integration for social perception and cognition can be considered homologs to those in the left, language-dominant hemisphere, sustaining multimodal integration of speech and semantic concepts fundamental for social communication. Emphasizing the significance of the left STS in multimodal integration and associated processes such as multimodal attention to socially relevant stimuli, we underscore its potential relevance in comprehending neurodevelopmental conditions characterized by challenges in social communication such as autism spectrum disorder (ASD). Further research into this left lateral processing stream holds the promise of enhancing our understanding of social communication in both typical development and ASD, which may lead to more effective interventions that could improve the quality of life for individuals with atypical neurodevelopment.

Decision-making under conditions of explicit risk and uncertainty in autistic and typically developing adolescents and young adults.

Adolescence has been characterized as a period of risky and possibly suboptimal decision-making, yet the development of decision-making in autistic adolescents is not well understood. To investigate decision-making in autism, we evaluated performance on 2 computerized tasks capturing decision-making under explicit risk and uncertainty in autistic and non-autistic adolescents/young adults ages 12-22 years. Participants completed the Game of Dice Task (32 IQ-matched participant pairs) to assess decision-making under explicit risk and the modified Iowa Gambling Task (35 IQ-matched pairs) to assess decision-making under uncertainty. Autistic participants overall made riskier decisions than non-autistic participants on the Game of Dice Task, and the odds of making riskier decisions varied by age and IQ. In contrast, the autistic group showed comparable levels of learning over trial blocks to the non-autistic group on the modified Iowa Gambling Task. For both tasks, younger autistic participants performed poorer than their non-autistic counterparts, while group differences diminished in older ages. This age-related pattern suggests positive development during adolescence on risk assessment and decision-making in autism but also implies differential developmental trajectories between groups. These findings also suggest differential performance by the risk type, with additional complex influences of IQ and fluid cognition, which warrants further investigations.

Enhanced neural synchronization during social communications between dyads with high autistic traits.

Autism is characterized by atypical social communication styles. To investigate whether individuals with high autistic traits could still have effective social communication among each other, we compared the behavioral patterns and communication quality within 64 dyads of college students paired with both high, both low, and mixed high-low (HL) autistic traits, with their gender matched. Results revealed that the high-high (HH) autistic dyads exhibited atypical behavioral patterns during conversations, including reduced mutual gaze, communicational turns, and emotional sharing compared with the low-low and/or HL autistic dyads. However, the HH autistic dyads displayed enhanced interpersonal neural synchronization during social communications measured by functional near-infrared spectroscopy, suggesting an effective communication style. Besides, they also provided more positive subjective evaluations of the conversations. These findings highlight the potential for alternative pathways to effectively communicate with the autistic community, contribute to a deeper understanding of how high autistic traits influence social communication dynamics among autistic individuals, and provide important insights for the clinical practices for supporting autistic people.

Noninvasive brain stimulation in autism: review and outlook for personalized interventions in adult patients.

Noninvasive brain stimulation (NIBS) has been increasingly investigated during the last decade as a treatment option for persons with autism spectrum disorder (ASD). Yet, previous studies did not reach a consensus on a superior treatment protocol or stimulation target. Persons with ASD often suffer from social isolation and high rates of unemployment, arising from difficulties in social interaction. ASD involves multiple neural systems involved in perception, language, and cognition, and the underlying brain networks of these functional domains have been well documented. Aiming to provide an overview of NIBS effects when targeting these neural systems in late adolescent and adult ASD, we conducted a systematic search of the literature starting at 631 non-duplicate publications, leading to six studies corresponding with inclusion and exclusion criteria. We discuss these studies regarding their treatment rationale and the accordingly chosen methodological setup. The results of these studies vary, while methodological advances may allow to explain some of the variability. Based on these insights, we discuss strategies for future clinical trials to personalize the selection of brain stimulation targets taking into account intersubject variability of brain anatomy as well as function.

Early autism diagnosis based on path signature and Siamese unsupervised feature compressor.

Autism spectrum disorder has been emerging as a growing public health threat. Early diagnosis of autism spectrum disorder is crucial for timely, effective intervention and treatment. However, conventional diagnosis methods based on communications and behavioral patterns are unreliable for children younger than 2 years of age. Given evidences of neurodevelopmental abnormalities in autism spectrum disorder infants, we resort to a novel deep learning-based method to extract key features from the inherently scarce, class-imbalanced, and heterogeneous structural MR images for early autism diagnosis. Specifically, we propose a Siamese verification framework to extend the scarce data, and an unsupervised compressor to alleviate data imbalance by extracting key features. We also proposed weight constraints to cope with sample heterogeneity by giving different samples different voting weights during validation, and used Path Signature to unravel meaningful developmental features from the two-time point data longitudinally. We further extracted machine learning focused brain regions for autism diagnosis. Extensive experiments have shown that our method performed well under practical scenarios, transcending existing machine learning methods and providing anatomical insights for autism early diagnosis.

Infants' reorienting efficiency depends on parental autistic traits and predicts future socio-communicative behaviors.

Attentional reorienting is dysfunctional not only in children with autism spectrum disorder (ASD), but also in infants who will develop ASD, thus constituting a potential causal factor of future social interaction and communication abilities. Following the research domain criteria framework, we hypothesized that the presence of subclinical autistic traits in parents should lead to atypical infants' attentional reorienting, which in turn should impact on their future socio-communication behavior in toddlerhood. During an attentional cueing task, we measured the saccadic latencies in a large sample (total enrolled n = 89; final sample n = 71) of 8-month-old infants from the general population as a proxy for their stimulus-driven attention. Infants were grouped in a high parental traits (HPT; n = 23) or in a low parental traits (LPT; n = 48) group, according to the degree of autistic traits self-reported by their parents. Infants (n = 33) were then longitudinally followed to test their socio-communicative behaviors at 21 months. Results show a sluggish reorienting system, which was a longitudinal predictor of future socio-communicative skills at 21 months. Our combined transgenerational and longitudinal findings suggest that the early functionality of the stimulus-driven attentional network-redirecting attention from one event to another-could be directly connected to future social and communication development.

Synergistic effect of mesenchymal stem cell-derived extracellular vesicle and miR-137 alleviates autism-like behaviors by modulating the NF-κB pathway.

Autism spectrum disorder (ASD) is a multifaceted neurodevelopmental disorder predominant in childhood. Despite existing treatments, the benefits are still limited. This study explored the effectiveness of mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) loaded with miR-137 in enhancing autism-like behaviors and mitigating neuroinflammation. Utilizing BTBR mice as an autism model, the study demonstrated that intranasal administration of MSC-miR137-EVs ameliorates autism-like behaviors and inhibits pro-inflammatory factors via the TLR4/NF-κB pathway. In vitro evaluation of LPS-activated BV2 cells revealed that MSC-miR137-EVs target the TLR4/NF-κB pathway through miR-137 inhibits proinflammatory M1 microglia. Moreover, bioinformatics analysis identified that MSC-EVs are rich in miR-146a-5p, which targets the TRAF6/NF-κB signaling pathway. In summary, the findings suggest that the integration of MSC-EVs with miR-137 may be a promising therapeutic strategy for ASD, which is worthy of clinical adoption.

Reduced lateralization of multiple functional brain networks in autistic males.

BACKGROUND: Autism spectrum disorder has been linked to a variety of organizational and developmental deviations in the brain. One such organizational difference involves hemispheric lateralization, which may be localized to language-relevant regions of the brain or distributed more broadly. METHODS: In the present study, we estimated brain hemispheric lateralization in autism based on each participant's unique functional neuroanatomy rather than relying on group-averaged data. Additionally, we explored potential relationships between the lateralization of the language network and behavioral phenotypes including verbal ability, language delay, and autism symptom severity. We hypothesized that differences in hemispheric asymmetries in autism would be limited to the language network, with the alternative hypothesis of pervasive differences in lateralization. We tested this and other hypotheses by employing a cross-sectional dataset of 118 individuals (48 autistic, 70 neurotypical). Using resting-state fMRI, we generated individual network parcellations and estimated network asymmetries using a surface area-based approach. A series of multiple regressions were then used to compare network asymmetries for eight significantly lateralized networks between groups. RESULTS: We found significant group differences in lateralization for the left-lateralized Language (d = -0.89), right-lateralized Salience/Ventral Attention-A (d = 0.55), and right-lateralized Control-B (d = 0.51) networks, with the direction of these group differences indicating less asymmetry in autistic males. These differences were robust across different datasets from the same participants. Furthermore, we found that language delay stratified language lateralization, with the greatest group differences in language lateralization occurring between autistic males with language delay and neurotypical individuals. CONCLUSIONS: These findings evidence a complex pattern of functional lateralization differences in autism, extending beyond the Language network to the Salience/Ventral Attention-A and Control-B networks, yet not encompassing all networks, indicating a selective divergence rather than a pervasive one. Moreover, we observed an association between Language network lateralization and language delay in autistic males.