Background: In this study, we revised the comprehensive autistic trait inventory (CATI)-a self-report inventory of autistic traits, in collaboration with autistic people and provided preliminary evidence for its validity as a self-report measure of autistic traits in the general population. An established strength of the CATI is its ability to capture female autistic traits. Our project aimed to extend this further, to increase the inventory's accessibility, and to minimise stigma induced by deficit-based representations of autistic experience.
Methods: Together with 22 individuals from the autism and autistic communities, we created the Revised Comprehensive Autistic Trait Inventory (CATI-R). Revisions included rewording items to increase clarity or reduce stigma and expanding items to capture diverse autistic experiences. We also present a series of guidelines for developing self-report inventories of subclinical neurodivergent traits. We validated the CATI-R within a large sample (n = 1439), comprising people with a self-reported autism diagnosis (n = 331), people who self-identified as autistic (n = 44), and non-autistic participants (n = 1046).
Results: We successfully validated a revision of the CATI. A confirmatory factor analysis supported the six-subscale structure (two-factor bifactors model: Chi-squared = 2705.73, p < .001, RMSEA = .04, SRMR = .03, CFI = .95, TLI = .94). Spearman's rank correlations showed positive relationships between all subscales (all rs > .56, ps < .001). Convergent validity was demonstrated by significant correlations between the CATI-R and two contemporary inventories of autistic traits: the AQ (rho = .86, p < .01) and BAPQ (rho = .82, p < .01). Finally, a measurement invariance analysis indicated that total-scale scores can be compared across genders.
Limitations: Our study presents only initial evidence for the validity of the CATI-R that should be enriched with further analyses and types of data, including a larger number of participants who do not identify as male or female.
Conclusions: This project provides a revised trait inventory that resonates with actual autistic experience, along with guidelines for creating self-report measures that are sensitive, accessible, and non-stigmatising.
Background: Language difficulties are common in autism spectrum disorder (ASD), a neurodevelopmental condition characterized by impairments in social communication as well as restricted and repetitive behaviors. Amongst infant siblings of children with an ASD diagnosis - who are at higher likelihood for developing ASD - a high proportion also show difficulties and delays in language acquisition.
Methods: In this study, we used functional magnetic resonance imaging (fMRI) to examine differences in language processing in 9-month-old infants at high (HL) and typical (TL) familial likelihood for ASD. Infants were presented with native (English) and novel (Japanese) speech while sleeping naturally in the scanner. Whole-brain and a priori region-of-interest analyses were conducted to evaluate neural differences in language processing based on likelihood group and language condition.
Results: HL infants showed attenuated responses to speech in general, particularly in left temporal language areas, as well as a lack of neural discrimination between the native and novel languages compared to the TL group. Importantly, we also demonstrate that HL infants show distinctly atypical patterns of lateralization for speech processing, particularly during native speech processing, suggesting a failure to left-lateralize.
Limitations: The sample size, particularly for the TL group, is relatively modest because of the challenges inherent to collecting auditory stimulus-evoked data from sleeping participants, as well as retention and follow-up difficulties posed by the COVID-19 pandemic. The groups were not matched on some demographic variables, but the present findings held even after accounting for these differences.
Conclusions: To our knowledge, this is the first fMRI study to directly measure autism-associated atypicalities in native language uptake during infancy. These findings provide a better understanding of the neurodevelopmental underpinnings of language delay in ASD, which is a prerequisite step for developing earlier and more effective interventions for autistic children and HL siblings who experience language impairments.
Background: Significant progress has been made in elucidating the genetic underpinnings of Autism Spectrum Disorder (ASD). However, there are still significant gaps in our understanding of the link between genomics, neurobiology and clinical phenotype in scientific discovery. New models are therefore needed to address these gaps. Rhesus macaques (Macaca mulatta) have been extensively used for preclinical neurobiological research because of remarkable similarities to humans across biology and behaviour that cannot be captured by other experimental animals.
Methods: We used the macaque Genotype and Phenotype (mGAP) resource consisting of 2,054 macaque genomes to examine patterns of evolutionary constraint in known human neurodevelopmental genes. Residual variation intolerance scores (RVIS) were calculated for all annotated autosomal genes (N = 18,168) and Gene Set Enrichment Analysis (GSEA) was used to examine patterns of constraint across ASD genes and related neurodevelopmental genes.
Results: We demonstrated that patterns of constraint across autosomal genes are correlated in humans and macaques, and that ASD-associated genes exhibit significant constraint in macaques (p = 9.4 × 10- 27). Among macaques, many key ASD-implicated genes were observed to harbour predicted damaging mutations. A small number of key ASD-implicated genes that are highly intolerant to mutation in humans, however, showed no evidence of similar intolerance in macaques (CACNA1D, MBD5, AUTS2 and NRXN1). Constraint was also observed across genes associated with intellectual disability (p = 1.1 × 10- 46), epilepsy (p = 2.1 × 10- 33) and schizophrenia (p = 4.2 × 10- 45), and for an overlapping neurodevelopmental gene set (p = 4.0 × 10- 10).
Limitations: The lack of behavioural phenotypes among the macaques whose genotypes were studied means that we are unable to further investigate whether genetic variants have similar phenotypic consequences among nonhuman primates.
Conclusion: The presence of pathological mutations in ASD genes among macaques, along with evidence of similar genetic constraints to those in humans, provides a strong rationale for further investigation of genotype-phenotype relationships in macaques. This highlights the importance of developing primate models of ASD to elucidate the neurobiological underpinnings and advance approaches for precision medicine and therapeutic interventions.
Background: Risk preference changes nonlinearly across development. Although extensive developmental research on the neurotypical (NTP) population has shown that risk preference is highest during adolescence, developmental changes in risk preference in autistic (AUT) people, who tend to prefer predictable behaviors, have not been investigated. Here, we aimed to investigate these changes and underlying computational mechanisms.
Method: We ran a game-like risk-sensitive reinforcement learning task on 75 participants aged 6-30 years (AUT group, n = 31; NTP group, n = 44). Focusing on choices between alternatives with the same objective value but different risks, we calculated the risk preference and stay probability of a risky choice after a rewarding or non-rewarding outcome. Analyses using t-tests and multiple regression analyses were conducted. Using the choice-related data of each participant, we fit four reinforcement learning models and compared the fit of each model to the data. Furthermore, we validated the results of model fitting with multiple methods, model recovery, parameter recovery, and posterior predictive check.
Results: We found a significant difference in nonlinear developmental changes in risk preference between the AUT and NTP groups. The computational modeling approach with reinforcement learning models revealed that individual preferences for surprise modulated such preferences.
Conclusions: These findings indicate that for NTP people, adolescence is a developmental period involving risk preference, possibly due to lower surprise aversion. Conversely, for AUT people, who show opposite developmental change of risk preference, adolescence could be a developmental period involving risk avoidance because of low surprise preference.
Background: Alterations in sensory perception, a core phenotype of autism, are attributed to imbalanced integration of sensory information and prior knowledge during perceptual statistical (Bayesian) inference. This hypothesis has gained momentum in recent years, partly because it can be implemented both at the computational level, as in Bayesian perception, and at the level of canonical neural microcircuitry, as in predictive coding. However, empirical investigations have yielded conflicting results with evidence remaining limited. Critically, previous studies did not assess the independent contributions of priors and sensory uncertainty to the inference.
Method: We addressed this gap by quantitatively assessing both the independent and interdependent contributions of priors and sensory uncertainty to perceptual decision-making in autistic and non-autistic individuals (N = 126) during an orientation categorization task.
Results: Contrary to common views, autistic individuals integrated the two Bayesian components into their decision behavior, and did so indistinguishably from non-autistic individuals. Both groups adjusted their decision criteria in a suboptimal manner.
Limitations: This study focuses on explicit priors in a perceptual categorization task and high-functioning adults. Thus, although the findings provide strong evidence against a general and basic alteration in prior integration in autism, they cannot rule out more specific cases of reduced prior effect - such as due to implicit prior learning, particular level of decision making (e.g., social), and level of functioning of the autistic person.
Conclusions: These results reveal intact inference for autistic individuals during perceptual decision-making, challenging the notion that Bayesian computations are fundamentally altered in autism.
Autism spectrum disorder (ASD) is characterized by difficulties in social interaction, communication challenges, and repetitive behaviors. Despite extensive research, the molecular mechanisms underlying these neurodevelopmental abnormalities remain elusive. We integrated microscale brain gene expression data with macroscale MRI data from 1829 participants, including individuals with ASD and typically developing controls, from the autism brain imaging data exchange I and II. Using fractal dimension as an index for quantifying cortical complexity, we identified significant regional alterations in ASD, within the left temporoparietal, left peripheral visual, right central visual, left somatomotor (including the insula), and left ventral attention networks. Partial least squares regression analysis revealed gene sets associated with these cortical complexity changes, enriched for biological functions related to synaptic transmission, synaptic plasticity, mitochondrial dysfunction, and chromatin organization. Cell-specific analyses, protein-protein interaction network analysis and gene temporal expression profiling further elucidated the dynamic molecular landscape associated with these alterations. These findings indicate that ASD-related alterations in cortical complexity are closely linked to specific genetic pathways. The combined analysis of neuroimaging and transcriptomic data enhances our understanding of how genetic factors contribute to brain structural changes in ASD.
Background: Angelman syndrome (AS), a severe neurodevelopmental disorder resulting from the loss of the maternal UBE3A gene, is marked by changes in the brain's white matter (WM). The extent of WM abnormalities seems to correlate with the severity of clinical symptoms, but these deficits are still poorly characterized or understood. This study provides the first large-scale measurement of WM volume reduction in children with AS. Furthermore, we probed the possibility of underlying WM neuropathology by examining the progression of myelination in an AS mouse model.
Methods: We conducted magnetic resonance imaging (MRI) on children with AS (n = 32) and neurotypical controls (n = 99) aged 0.5-12 years. In parallel, we examined myelination in postnatal Ube3a maternal-null mice (Ube3am-/p+; AS model), Ube3a paternal-null mice (Ube3am+/p-), and wildtype controls (Ube3am+/p+) using MRI, immunohistochemistry, western blotting, and electron microscopy.
Results: Our data revealed that AS individuals exhibit significant reductions in brain volume by ~ 1 year of age, and by 6-12 years of age WM is reduced by 26% and gray matter by 21%-approximately twice the reductions observed in the adult AS mouse model. Our AS mouse model saw a global delay in the onset of myelination, which normalized within days (likely corresponding to months or years in human development). This myelination delay is caused by the loss of UBE3A in neurons rather than UBE3A haploinsufficiency in oligodendrocytes. Interestingly, ultrastructural analyses did not reveal abnormalities in myelinated or unmyelinated axons.
Limitations: It is difficult to extrapolate the timing and duration of the myelination delay observed in AS model mice to individuals with AS.
Conclusions: This study reveals WM deficits as a hallmark in children with AS, demonstrating for the first time that these deficits are already apparent at 1 year of age. Parallel studies in a mouse model of AS show these deficits occur alongside the delayed onset of myelination, which results from the loss of neuronal (but not glial) UBE3A, though the causal relationship between these phenotypes remains to be determined. These findings emphasize the potential of WM as both a therapeutic target for interventions and a valuable biomarker for tracking the progression of AS and the effectiveness of potential treatments.
Background: Difficulties with (non-verbal) social communication, including facial expression processing, constitute a hallmark of autism. Intranasal administration of oxytocin has been considered a potential therapeutic option for improving social difficulties in autism, either by enhancing the salience of social cues or by reducing the social stress and anxiety experienced in social encounters.
Methods: We recorded fMRI brain activity while presenting neutral, fearful and scrambled faces, to compare the neural face processing signature of autistic children (n = 58) with that of matched non-autistic controls (n = 38). Next, in the autistic children group, we implemented this fMRI face processing task in a double-blind, placebo-controlled, multiple-dose oxytocin clinical trial, to evaluate the impact of four-week repeated oxytocin administration (24 IU daily dose) on brain activity in face processing regions.
Results: No significant diagnostic-group differences were identified between autistic versus non-autistic children with regard to neural face processing. Furthermore, no significant treatment effects were found in the oxytocin clinical trial. However, exploratory analyses (uncorrected for multiple comparisons) demonstrated decreases in brain activity in the left superior temporal sulcus (STS) and inferior frontal region in the oxytocin compared to the placebo group, and change-from-baseline analyses in the oxytocin group revealed significantly reduced neural activity in the core face-processing network (STS, inferior occipital, and posterior fusiform), as well as in amygdala and inferior frontal region.
Conclusion: These findings suggest an attenuating effect of multiple-dose oxytocin administration on neural face processing, potentially supporting the anxiolytic account of oxytocin.
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