Molecular Autism最新文献

Background: Autistic adults experience differences in social interactions involving physical contact. Brain imaging studies suggest that these differences may be related to atypical brain responses to social-affective cues, affecting both the experience of receiving touch and observing it in others. However, it remains unclear whether these atypical responses are limited to specific brain regions or represent broader alterations in brain connectivity. The current study investigated how the functional network architecture is modulated during touch observation associated with autism and explored the extent to which changes in this architecture are associated with individual differences in social touch preferences and social responsiveness.

Methods: By integrating generalized psychophysiological interaction (gPPI) analysis with independent component analysis (ICA), the current study analyzed existing fMRI datasets, in which 21 autistic and 21 non-autistic male adults viewed videos of social and nonsocial touch while undergoing MRI scans.

Results: A gPPI analysis of regions of interest revealed that autistic adults exhibited increased connectivity between sensory and social brain regions. The strength of some of these connections was positively associated with a higher preference for social touch and greater social responsiveness, suggesting neural compensatory mechanisms that may help autistic adults better understand the meaning of touch. At the level of large-scale brain networks extracted using ICA, atypical connectivity was predominantly observed between the sensorimotor network and other networks involved in social-emotional processing. Increased connectivity was observed in the sensorimotor network during nonsocial touch, suggesting that embodied simulation, the process by which individuals internally simulate touch experience of others in this context, may be more engaged when observing human-object interactions than during human-to-human touch.

Limitations: This study focused on a specific subgroup of 21 autistic male adults with minimal support needs. Future research would benefit from including a more diverse autistic sample.

Conclusions: This study reveals atypical context-dependent modulation of functional brain architecture associated with autism during touch observation. Neural compensatory mechanisms in autistic individuals who enjoy social touch and show higher social responsiveness may function as adaptive social responses. However, these compensations may be limited to specific brain regions, rather than occurring at the level of large-scale brain networks.

Background: Developmental language disorder (DLD) refers to children who present with language difficulties that are not due to a known biomedical condition or associated with autism spectrum disorder (ASD) or intellectual disability (ID). The clinical heterogeneity of language disorders, the frequent presence of comorbidities, and the inconsistent terminology used over the years have impeded both research and clinical practice. Identifying sub-groups of children (i.e. DLD cases without childhood apraxia of speech (CAS)) with language difficulties is essential for elucidating the underlying genetic causes of this condition. DLD presents along a spectrum of severity, ranging from mild speech delays to profound disturbances in oral language structure in otherwise typically intelligent children. The prevalence of DLD is ~ 7-8% or 2% if severe forms are considered. This study aims to investigate a homogeneous cohort of DLD patients, excluding cases of ASD, ID or CAS, using multiple genomic approaches to better define the molecular basis of the disorder.

Methods: Fifteen families, including 27 children with severe DLD, were enrolled. The majority of cases (n = 24) were included in multiplex families while three cases were sporadic. This resulted in a cohort of 59 individuals for whom chromosomal microarray analysis and exome or genome sequencing were performed.

Results: We identified copy number variants (CNVs) predisposing to neurodevelopmental disorders with incomplete penetrance and variable expressivity in two families. These CNVs (i.e., 15q13.3 deletion and proximal 16p11.2 duplication) are interpreted as pathogenic. In one sporadic case, a de novo pathogenic variant in the ZNF292 gene, known to be associated with ID, was detected, broadening the spectrum of this syndrome.

Limitations: The strict diagnostic criteria applied by our multidisciplinary team, including speech-language physicians, neuropsychologists, and paediatric neurologists, resulted in a relatively small sample size, which limit the strength of our findings.

Conclusion: These findings highlight a common genetic architecture between DLD, ASD and ID, and underline the need for further investigation into overlapping neurodevelopmental pathways.

Trial registration: ClinicalTrials.gov Identifier: NCT06660108.

Background: The prevalence of depression is elevated in individuals with autism spectrum disorder (ASD) compared to the general population, yet the reasons for this disparity remain unclear. While social deficits central to ASD may contribute to depression, it is uncertain whether social interaction behavior themselves or individuals' introspection about their social behaviors are more impactful. Although the anterior cingulate cortex (ACC) is frequently implicated in ASD, depression, and social functioning, it is unknown if it explains differences between ASD adults with and without co-occurring depression.

Methods: The present study contrasted observed vs. subjective perception of autism symptoms and social interaction assessed with both standardized measures and a lab task, in 65 sex-balanced (52.24% male) autistic young adults. We also quantified ACC and amygdala volume with 7-Tesla structural neuroimaging to examine correlations with self-reported depression and social functioning.

Results: We found that ASD individuals with self-reported depression exhibited differences in subjective evaluations including heightened self-awareness of ASD symptoms, lower subjective satisfaction with social relations, and less perceived affiliation during the social interaction task, yet no differences in corresponding observed measures, compared to those without depression. Larger ACC volume was related to depression, greater self-awareness of ASD symptoms, and worse subjective satisfaction with social relations. In contrast, amygdala volume, despite its association with clinician-rated ASD symptoms, was not related to depression.

Limitations: Due to the cross-sectional nature of our study, we cannot determine the directionality of the observed relationships. Additionally, we included only individuals with an IQ over 60 to ensure participants could complete the social task. We also utilized self-reported depression indices instead of clinically diagnosed depression, which may limit the comprehensiveness of the findings.

Conclusions: Our approach highlights the unique role of subjective perception of autism symptoms and social interactions, beyond the observable manifestation of social impairment in ASD, in contributing to self-reported depression, with the ACC playing a crucial role. These findings imply possible heterogeneity of ASD concerning co-occurring depression. Using neuroimaging, we were able to demarcate depressive phenotypes co-occurring alongside autistic phenotypes.

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.