BACKGROUND: The neurobiological underpinnings of Autism Spectrum Disorder (ASD) are diverse and likely multifactorial. One possible mechanism is increased oxidative stress leading to altered neurodevelopment and brain function. However, this hypothesis has mostly been tested in post-mortem studies. So far, available in vivo studies in autistic individuals have reported no differences in glutathione (GSH) levels in frontal, occipital, and subcortical regions. However, these studies were limited by the technically challenging quantification of GSH, the main brain antioxidant molecule. This study aimed to overcome previous studies\' limitations by using a GSH-tailored spectroscopy sequence and optimised quantification methodology to provide clarity on GSH levels in autistic adults.
METHODS: We used spectral editing proton-magnetic resonance spectroscopy (1H-MRS) combined with linear combination model fitting to quantify GSH in the dorsomedial prefrontal cortex (DMPFC) and medial occipital cortex (mOCC) of autistic and non-autistic adults (male and female). We compared GSH levels between groups. We also examined correlations between GSH and current autism symptoms, measured using the Autism Quotient (AQ).
RESULTS: Data were available from 31 adult autistic participants (24 males, 7 females) and 40 non-autistic participants (21 males, 16 females); the largest sample to date. The GSH levels did not differ between groups in either region. No correlations with AQ were observed.
CONCLUSIONS: GSH levels as measured using 1H-MRS are unaltered in the DMPFC and mOCC regions of autistic adults, suggesting that oxidative stress in these cortical regions is not a marked neurobiological signature of ASD.

OBJECTIVE: Care navigation support is designed to help connect families with health care resources. Given that children with autism have more unmet needs than their peers, such a service may be especially valuable to families who have recently received a diagnosis. This study sought to examine engagement in care navigation support after an autism telehealth evaluation. Specifically, we report on what demographic and diagnostic factors predicted engagement in care navigation support and satisfaction with this service.
METHODS: Care navigation was offered to 220 families receiving autism telehealth evaluations between April 2020 and April 2022. Survey data from initial evaluation appointments and 2 follow-up care navigation meetings (approximately 1-3 months and approximately 9-12 months after evaluation), along with data from medical records, were collected and analyzed to determine whether any traits predicted engagement in care navigation. Satisfaction with care navigation was also analyzed.
RESULTS: Of 220 families, 48.2% (n = 106) participated in a care navigation meeting within 1 to 3 months after an evaluation and 59.5% (n = 131) participated in at least 1 meeting across 2 time periods. The findings did not support the hypothesis that a diagnosis of autism would predict engagement. Analyses found that child sex (female compared with male) and child race and ethnicity (children of color compared with White children) predicted engagement. For those who engaged in care navigation, high satisfaction was reported.
CONCLUSIONS: Participants\' engagement rates and satisfaction levels suggest care navigation is a valuable service for families after a telehealth autism evaluation.

This study had two aims. First, we aimed to investigate the prevalence of ACB, PCB, and oral habits among a group of Albanian children with ASD compared with a group of children without ASD. Second, we aimed to identify the associations of ASD with ACB, PCB, and oral habits. The sample inlcuded 125 children with ASD (91 males, 34 females) from 2 special schools for children with disabilities and 2 daily residential centers in Tirana. The control group included 125 children without ASD. The relationships between categorical variables were evaluated via the chi-square test. To identify the potential risk factors for ASD, we performed binary logistic regression. No statistically significant differences were found for CB or oral habits between the primary and adolescent dentition stages. A comparison of children with ASD with CB and oral habits revealed a significant difference in the prevalence of PCB. Binary logistic regression revealed that ACB, PCB and oral habits were not associated with ASD. CB was more prevalent among children with ASD in the primary and mixed dentition stages. Oral habits were more prevalent in the mixed and adolescent dentition stages. However, ASD is not a risk factor for CB or other oral habits.

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Although mindreading is an important prerequisite for successful social interactions, the underlying mechanisms are still matter of debate. It is unclear, for example, if inferring others\' and own mental states are distinct processes or are based on a common mechanism. Using an affect-induction experimental set-up with an acoustic heart rate feedback that addresses affective mindreading in self and others, we investigated if non-autistic study participants relied on similar information for self- and other-directed mindreading. We assumed that due to altered mindreading capacities in autism, mainly individuals with low autistic traits would focus on additional sensory cues, such as heart rate, to infer their own and their gambling partner\'s affective states. Our analyses showed that the interpretation of a heart rate signal differed in self- and other-directed mindreading trials. This effect was modulated by autistic traits suggesting that individuals with higher autistic traits might not have interpreted the heart rate feedback for gambling partner ratings and differentiated less between self- and other-directed mindreading trials. We discuss these results in the context of a common mechanism underlying self- and other-directed mindreading and hypothesize that the weighting of internal and external sensory information might contribute to how we make sense of our and others\' mental states.

BACKGROUND: Having more \"autistic traits\" is associated with an increased risk of mental health conditions. However, few studies have examined autistic traits in nonclinical samples. This study aims to analyze the relationship between autistic traits and internalizing symptoms among early adolescents and to examine the moderating effect of self-efficacy.
METHODS: Survey data were collected from early adolescents ages 10-14 living in Darjeeling, India (n = 274) to assess autistic traits, self-efficacy, and internalizing symptoms.
RESULTS: Higher internalizing symptoms were significantly associated with a higher report of autistic traits. Academic, social, and emotional dimensions of self-efficacy moderated the relationship between autistic traits and internalizing symptoms.
CONCLUSIONS: The moderation effects between social and emotional self-efficacy among youth with high versus low autism trait scores suggest the need for social-emotional learning interventions designed for and with neurodivergent youth. Such interventions aim to reduce internalizing symptoms during early adolescence and improve future mental health trajectories.

BACKGROUND: Autism spectrum conditions (ASC) and quantitative autistic traits (QATs) are associated with sensory symptoms, which may contribute to anxiety and adversely affect social and cognitive development. Although sensory symptoms can occur across all senses, the relative roles of specific sensory modalities as contributors to the autistic phenotype and to anxiety are not well understood. The objective of this study was to examine which sensory symptoms were most predictive of high anxiety.
METHODS: We recruited 257 female primary caregivers of children aged 6 to 11 years (49% girls) to a questionnaire study comprising parent-report measures for classical QATs (social, communicative, and rigid), autism-related sensorimotor symptoms (visual, auditory, tactile, olfactory, gustatory, vestibular, proprioceptive, and motor), and anxiety symptoms. First, Bayesian stochastic search variable selection (SSVS) was used to identify the most probable sensorimotor predictors of specific QATs as well as diagnosed ASC. Then, the selected predictors were used in another SSVS, using anxiety symptoms as a dependent variable, to identify which of the autism-relevant sensorimotor symptoms were most robustly predictive of anxiety. Finally, the effect sizes of anxiety-related sensory symptoms were estimated with linear regressions.
RESULTS: We found that auditory symptoms and motor difficulties were most predictive of ASC diagnosis. Developmental motor difficulties were also strongly related to all individual QATs, whereas auditory symptoms were more selectively predictive of rigid traits. Tactile symptoms robustly predicted social interaction QATs, and proprioceptive symptoms predicted communicative QATs. Anxiety outcomes were most strongly predicted by difficulties with auditory and olfactory processing.
CONCLUSIONS: The results support the clinical importance of being alert to complaints about sounds and hearing in neurodevelopmental populations, and that auditory processing difficulties may be evaluated as an early marker of poor mental health in children with and without diagnosed autism. Olfactory processing differences appeared to be an anxiety marker less strongly associated with ASC or QATs, while motor difficulties were highly autism-relevant but not equally strongly associated with anxiety outcomes. We suggest that future studies may focus on the mechanisms and consequences of neurodevelopmental central auditory processing dysfunction and its potential relationship to anxiety disorders.

The diagnosis of childhood schizophrenia was widely employed in the U.S. from the 1930s to the late 1970s. In this paper I will provide a history of the diagnosis. Some of the earliest publications on childhood schizophrenia outlined the notion that childhood schizophrenia had different types. I will outline the development of these types, outlining differing symptoms and causes associated with various types. I outline how different types of childhood schizophrenia were demarcated from one another primarily on age of onset and the type of psychosis which was believed to be present. I will outline how various child psychiatrists viewed the types of childhood schizophrenia posited by other child psychiatrists. I will outline the process of abandoning childhood schizophrenia. I use my history to challenge what I believe are misconceptions about childhood schizophrenia. Also, I will use my history to draw lessons for thinking about modern notions of autism. It shows potential problems around formulating psychiatric diagnoses around causes and how compromises might be needed to prevent those problems. Additionally, childhood schizophrenia shows that psychiatrists could formulate subtypes that are not based upon functioning levels and that we can conceive of subtypes as dynamic whereby someone can change which subtype they exhibit over time.

Domain-general prediction differences have been posited as underlying many aspects of the cognitive-behavioral profile in autism. An interesting potential implication of such differences is hyperplasticity of learning-the idea that autistic individuals may privilege more recent input over the accumulation of prior learning. Because real world language input is highly variable, hyperplasticity could have serious ramifications for language learning. To investigate potential hyperplasticity during a language processing task, we administered an experimental anticipatory eye movement (AEM) task to 2- to 3-year-old autistic children and neurotypical (NT) peers. Autistic children\'s change in anticipation from before to after a switch in contingencies did not significantly differ from NT counterparts, failing to support claims of hyperplasticity in the linguistic domain. Analysis of individual differences among autistic children revealed that cognitive ability was associated with prediction of the initial, stable contingencies, but neither age nor receptive language related to task performance. Results are discussed in terms of clinical implications and the broader context of research investigating prediction differences in autism.

One of the main drivers of autism spectrum disorder is risk alleles within hundreds of genes, which may interact within shared but unknown protein complexes. Here we develop a scalable genome-editing-mediated approach to target 14 high-confidence autism risk genes within the mouse brain for proximity-based endogenous proteomics, achieving the identification of high-specificity spatial proteomes. The resulting native proximity proteomes are enriched for human genes dysregulated in the brain of autistic individuals, and reveal proximity interactions between proteins from high-confidence risk genes with those of lower-confidence that may provide new avenues to prioritize genetic risk. Importantly, the datasets are enriched for shared cellular functions and genetic interactions that may underlie the condition. We test this notion by spatial proteomics and CRISPR-based regulation of expression in two autism models, demonstrating functional interactions that modulate mechanisms of their dysregulation. Together, these results reveal native proteome networks in vivo relevant to autism, providing new inroads for understanding and manipulating the cellular drivers underpinning its etiology.