Molecular Autism最新文献

Background: According to recent models of autism, autistic individuals may find learning probabilistic cue-outcome associations more challenging than deterministic learning, though empirical evidence for this is mixed. Here we examined the mechanism of probabilistic learning more closely by comparing autistic and non-autistic adults on inferring a target cue from multiple cues or integrating multiple target cues and learning from associations with various predictive strengths.

Methods: 52 autistic and 52 non-autistic participants completed three tasks: (i) single-cue probabilistic learning, in which they had to infer a single target cue from multiple cues to learn cue-outcome associations; (ii) multi-cue probabilistic learning, in which they had to learn associations of various predictive strengths via integration of multiple cues; and (iii) reinforcement learning, which required learning the contingencies of two stimuli with a probabilistic reinforcement schedule. Accuracy on the two probabilistic learning tasks was modelled separately using a binomial mixed effects model whereas computational modelling was performed on the reinforcement learning data to obtain a model parameter on prediction error integration (i.e., learning rate).

Results: No group differences were found in the single-cue probabilistic learning task. Group differences were evident for the multi-cue probabilistic learning task for associations that are weakly predictive (between 40 and 60%) but not when they are strongly predictive (10-20% or 80-90%). Computational modelling on the reinforcement learning task revealed that, as a group, autistic individuals had a higher learning rate than non-autistic individuals.

Limitations: Due to the online nature of the study, we could not confirm the diagnosis of our autistic sample. The autistic participants were likely to have typical intelligence, and so our findings may not be generalisable to the entire autistic population. The learning tasks are constrained by a relatively small number of trials, and so it is unclear whether group differences will still be seen when given more trials.

Conclusions: Autistic adults showed similar performance as non-autistic adults in learning associations by inferring a single cue or integrating multiple cues when the predictive strength was strong. However, non-autistic adults outperformed autistic adults when the predictive strength was weak, but only in the later phase. Autistic individuals were also more likely to incorporate prediction errors during decision making, which may explain their atypical performance on the weakly predictive associations. Our findings have implications for understanding differences in social cognition, which is often noisy and weakly predictive, among autistic individuals.

Background: Intellectual developmental disorder with autism and dysmorphic facies (IDDADF) is a rare syndromic intellectual disability (ID) caused by homozygous disruption of PDZD8 (PDZ domain-containing protein 8), an integral endoplasmic reticulum (ER) protein. All four previously identified IDDADF cases exhibit autistic behavior, with autism spectrum disorder (ASD) diagnosed in three cases. To determine whether autistic behavior is a common outcome of PDZD8 disruption, we studied a third family with biallelic mutation of PDZD8 (family C) and further characterized PDZD8-deficient (Pdzd8^tm1b) mice that exhibit stereotyped motor behavior relevant to ASD.

Methods: Homozygosity mapping, whole-exome sequencing, and cosegregation analysis were used to identify the PDZD8 variant responsible for IDDADF, including diagnoses of ASD, in consanguineous family C. To assess the in vivo effect of PDZD8 disruption on social responses and related phenotypes, behavioral, structural magnetic resonance imaging, and microscopy analyses were conducted on the Pdzd8^tm1b mouse line. Metabolic activity was profiled using sealed metabolic cages.

Results: The discovery of a third family with IDDADF caused by biallelic disruption of PDZD8 permitted identification of a core clinical phenotype consisting of developmental delay, ID, autism, and facial dysmorphism. In addition to impairments in social recognition and social odor discrimination, Pdzd8^tm1b mice exhibit increases in locomotor activity (dark phase only) and metabolic rate (both lights-on and dark phases), and decreased plasma triglyceride in males. In the brain, Pdzd8^tm1b mice exhibit increased levels of accessory olfactory bulb volume, primary olfactory cortex volume, dendritic spine density, and ER stress- and mitochondrial fusion-related transcripts, as well as decreased levels of cerebellar nuclei volume and adult neurogenesis.

Limitations: The total number of known cases of PDZD8-related IDDADF remains low. Some mouse experiments in the study did not use balanced numbers of males and females. The assessment of ER stress and mitochondrial fusion markers did not extend beyond mRNA levels.

Conclusions: Our finding that the Pdzd8^tm1b mouse model and all six known cases of IDDADF exhibit autistic behavior, with ASD diagnosed in five cases, identifies this trait as a common outcome of biallelic disruption of PDZD8 in humans and mice. Other abnormalities exhibited by Pdzd8^tm1b mice suggest that the range of comorbidities associated with PDZD8 deficiency may be wider than presently recognized.

Background: Autism is a complex neurodevelopmental condition, the precise neurobiological underpinnings of which remain elusive. Here, we focus on group differences in resting state EEG (rsEEG). Although many previous reports have pointed to differences between autistic and neurotypical participants in rsEEG, results have failed to replicate, sample sizes have typically been small, and only a small number of variables are reported in each study.

Methods: Here, we combined five datasets to create a large sample of autistic and neurotypical individuals (n = 776) and extracted 726 variables from each participant's data. We computed effect sizes and split-half replication rate for group differences between autistic and neurotypical individuals for each EEG variable while accounting for age, sex and IQ. Bootstrapping analysis with different sample sizes was done to establish how effect size and replicability varied with sample size.

Results: Despite the broad and exploratory approach, very few EEG measures varied with autism diagnosis, and when larger effects were found, the majority were not replicable under split-half testing. In the bootstrap analysis, smaller sample sizes were associated with larger effect sizes but lower replication rates.

Limitations: Although we extracted a comprehensive set of EEG signal components from the data, there is the possibility that measures more sensitive to group differences may exist outside the set that we tested. The combination of data from different laboratories may have obscured group differences. However, our harmonisation process was sufficient to reveal several expected maturational changes in the EEG (e.g. delta power reduction with age), providing reassurance regarding both the integrity of the data and the validity of our data-handling and analysis approaches.

Conclusions: Taken together, these data do not produce compelling evidence for a clear neurobiological signature that can be identified in autism. Instead, our results are consistent with heterogeneity in autism, and caution against studies that use autism diagnosis alone as a method to categorise complex and varied neurobiological profiles.

Background: Previous eye-tracking research on autistic individuals has mostly examined the gaze behavior of one individual in response to social stimuli presented on a computer screen, suggesting that there is atypical gaze behavior. However, it is unknown how these findings translate to the interactive dynamics of gaze behavior during "face-to-face" encounters between two individuals. Only by analyzing the gaze behaviour of both interaction partners is it possible to determine the frequency of actual eye-contact and who initiates or breaks such periods of mutual eye gaze. The knowledge gained from this analysis could contribute to theorizing about the psychological mechanisms (e.g., gaze avoidance vs. gaze indifference) underlying autism.

Methods: The present study applied a novel dual eye-tracking setup that allows the assessment and analysis of the interactive dynamics of gaze behavior regarding (i) mutual eye gaze (i.e., eye contact), (ii) initiations, and (iii) break-ups of eye contact. Participants (37 autistic individuals, 37 age- and IQ-matched neurotypical individuals) performed a semi-standardized social interaction (i.e., Fast Friends Procedure) with a confederate (trained to interact in a standardized manner).

Results: Eye contact was reduced in interactions involving autistic individuals. Additional analyses revealed that this reduction was primarily due to the more frequent breaking of eye contact by these individuals. We also found considerable heterogeneity among autistic individuals, with atypical gaze behavior present in only about half of the sample.

Limitations: Further research is required to determine whether the interactive dynamics of gaze behavior observed in this dual eye-tracking setup can be generalized to real-world situations. Future studies could also include arousal-related physiological measures.

Conclusions: By tracking the gaze behavior of two interacting individuals, this study reveals specific atypicalities in the interactive dynamics of gaze behavior in a subset of autistic individuals, potentially informing diagnostic and therapeutic decisions. More broadly, our study highlights the added value of dual eye-tracking in elucidating the interactive nature of social encounters in both neurodiverse and neurotypical individuals.

Trial registration: The study was registered as a clinical trial before starting data collection ( https://drks.de/search/en/trial/DRKS00018957 ; Registration Date: 12/17/2019).

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.