Molecular Autism最新文献

Background: When working on jigsaw puzzles, we mentally "combine" two pieces to form a composite image even before physically fitting them together. This happens when the separate pieces could logically create a cohesive picture and not when they are mismatched or incoherent. The capacity of the brain to combine individual elements to form possible wholes serves as the basis of perceptual organisation. This drive for perceptual cohesion-the "Tetris effect"-can be seen in the famous game, where people automatically perceive logical combinations from separate pieces. However, it is unclear how this presents in populations known to have perceptual differences, such as autistic people. Theories on the inclination to process local over global details in autism and autistic strengths in pattern recognition lead to conflicting predictions regarding the drive for perceptual cohesion in autistic compared to non-autistic people.

Methods: In this large-scale (n = 470) pre-registered online behavioural study, we aimed to replicate previous research conducted on neurotypical participants and to extend this work to autistic participants. We used two tasks with Tetris-style stimuli to examine how autistic (n = 196) and non-autistic (n = 274) adults implicitly perceive possible wholes from individual parts. Data were analysed using logistic mixed-effects regression models and hierarchical Signal Detection Theory modelling.

Results: Overall, we replicated the results from the original study in finding participants are more likely to perceive parts as wholes when there is the potential to form a whole, compared to when there is not. However, we found no differences between autistic and non-autistic participants across both tasks.

Limitations: Although power calculations were carried out to assess sample sizes needed to detect a group difference, given the small effect size (Cohen's d = 0.37) in the original study, it may be that any existing group differences are still undetectable with the current sample size.

Conclusions: We conclude that the "Tetris effect" is ubiquitous and seen in both neurotypical and neurodiverse populations. Our findings challenge the deficit-focussed narrative often seen in the autism literature and highlight the similarities in task performance between autistic and non-autistic participants.

Background: Research has demonstrated a strong relationship between autism and gender dysphoria (GD) and that this relationship could be explained by obsessional interests which are characteristic of autism. However, these studies often measured obsessions using either single items which questions the reliability of the findings, or within autistic trait measures meaning the findings may simply index a more general relationship between autistic traits and GD. Therefore, the present study aimed to investigate the relationships between obsessional thoughts and traits of GD using a measure of obsessional thoughts alongside a measure of autistic traits, which was investigated in both non-clinical and clinical samples.

Methods: A total of 145 non-clinical participants took part in Study 1 and all completed the Autism-Spectrum Quotient (AQ) as a measure of autistic traits, the Obsessive-Compulsive Inventory-Revised (OCI-R) obsessional thoughts subscale as a measure of obsessional thoughts, and the Gender-Identity/Gender-Dysphoria Questionnaire (GIDYQ) to measure traits of GD. For Study 2, a total of 226 participants took part in Study 2 and all completed the same measures as in Study 1. They included participants diagnosed with GD (N = 49), autism (N = 65), OCD (N = 46) and controls with no diagnosis (N = 66).

Results: The hierarchical linear regression for Study 1 showed that both total AQ and OCI-R obsessional thoughts scores were uniquely associated with GIDYQ scores, with no interaction effect between the scores. The results for Study 2, from a hierarchical linear regression, once again found that obsessional thoughts and autistic traits were each uniquely associated with GIDYQ scores, but not their interaction. The GD and autistic groups both reported significantly greater traits of GD than the OCD and control groups, with the GD group reporting higher scores than the autistic group.

Limitations: Participants self-reported their diagnoses for Study 2, but diagnostic tests to verify these were not administered. Traits of GD were also measured at a single point in time, despite such traits being transient and continuous.

Conclusions: The results show both obsessional thoughts and autistic traits are uniquely associated with GD, and that autistic people experience greater traits of GD than other clinical groups.

Dysfunction in social interactions is a core symptom of autism spectrum disorder (ASD). Nevertheless, the neural mechanisms underlying social deficits in ASD are poorly understood. By integrating electrophysiological, in vivo fiber photometry, viral-mediated tracing, optogenetic and pharmacological stimulation, we show reduced intrinsic excitability and hypoactivity of SOM interneurons in medial prefrontal cortex (mPFC) in Magel2-deficient mice, an established ASD model, were required to social defects. Chemogenetic inhibition of mPFC SOM-containing interneurons resulted in reduced social interaction in wild-type Magel2 mice. These sociability deficits can be rescued by optogenetic activation by excitability of SOM in the mPFC and mPFC^SOM-LS inhibitory pathway in Magel 2 knockout mice. These results demonstrate the hypoactivity for SOM action in the mPFC in social impairments, and suggest targeting this mechanism that may prove therapeutically beneficial for mitigating social behavioral disturbances observed in ASD.

We and others have demonstrated the resting-state (RS) peak alpha frequency (PAF) as a potential clinical marker for young children with autism spectrum disorder (ASD), with previous studies observing a higher PAF in school-age children with ASD versus typically developing (TD) children, as well as an association between the RS PAF and measures of processing speed in TD but not ASD. The brain mechanisms associated with these findings are unknown. A few studies have found that in children more mature optic radiation white matter is associated with a higher PAF. Other studies have reported white matter and neural activity associations in TD but not ASD. The present study hypothesized that group differences in the RS PAF are due, in part, to group differences in optic radiation white matter and PAF associations. The maturation of the RS PAF (measured using magnetoencephalography(MEG)), optic radiation white matter (measured using diffusion tensor imaging(DTI)), and associations with processing speed were assessed in a longitudinal cohort of TD and ASD children. Time 1 MEG and DTI measures were obtained at 6-8 years old (59TD and 56ASD) with follow-up brain measures collected ~ 1.5 and ~ 3 years later. The parietal-occipital PAF increased with age in both groups by 0.13 Hz/year, with a main effect of group showing the expected higher PAF in ASD than TD (an average of 0.26 Hz across the 3 time points). Across age, the RS PAF predicted processing speed in TD but not ASD. Finally, more mature optic radiation white matter measures (FA, RD, MD, AD) were associated with a higher PAF in both groups. Present findings provide additional evidence supporting the use of the RS PAF as a brain marker in children with ASD 6-10 years old, and replicate findings of an association between the RS PAF and processing speed in TD but not ASD. The hypothesis that the RS PAF group differences (with ASD leading TD by about 2 years) would be explained by group differences in optic radiation white matter was not supported, with brain structure-function associations indicating that more mature optic radiation white matter is associated with a higher RS PAF in both groups.

Background: Fragile X syndrome is caused by the loss of the Fmr1 gene expression. Deletion of Fmr1 in various neuronal and non-neuronal subpopulations in the brain of mice leads to cell-type-specific effects. Microglia, immune cells critical for the refinement of neuronal circuits during brain development, have been implicated in various neurodevelopmental disorders, including fragile X syndrome. However, it is unknown whether reduced Fmr1 expression in microglia leads to molecular and behavioral phenotypes.

Methods: We downregulated Fmr1 in microglia during early and late postnatal development and studied the effect on microglial morphology and distinct behaviours.

Results: Female, but not male, adult mice with downregulation of Fmr1 in microglia during early development exhibited reactive microglia and behavioral phenotypes, including enhanced self-grooming and alterations in social interaction. Downregulation of Fmr1 in microglia during late development induced a milder phenotype, characterized by impaired preference for social novelty without affecting microglia morphology.

Conclusions: The downregulation of Fmr1 and its encoded protein FMRP in microglia contributes to behavioural phenotypes in a sex-specific manner.

Background: Autism spectrum disorder (ASD) is a lifelong condition that profoundly impacts health, independence, and quality of life. However, research on brain aging in autistic adults is limited, and microstructural variations in white and gray matter remain poorly understood. To address this critical gap, we assessed novel diffusion MRI (dMRI) biomarkers, free water, and free water corrected fractional anisotropy (fwcFA), and mean diffusivity (fwcMD) across 32 transcallosal tracts and their corresponding homotopic grey matter origin/endpoint regions of interest (ROIs) in middle and old aged autistic adults.

Methods: Forty-three autistic adults aged 30-73 and 43 age-, sex-, and IQ-matched neurotypical controls underwent dMRI scans. We examined free water, fwcFA, fwcMD differences between the two groups and age-related pattern of each dMRI metric across the whole brain for each group. The relationships between clinical measures of ASD and free water in regions that significantly differentiated autistic adults from neurotypical controls were also explored. In supplementary analyses, we also assessed free water uncorrected FA and MD using conventional single tensor modeling.

Results: Autistic adults exhibited significantly elevated free water in seven frontal transcallosal tracts compared to controls. In controls, age-related increases in free water and decreases in fwcFA were observed across most transcallosal tracts. However, these age-associated patterns were entirely absent in autistic adults. In gray matter, autistic adults showed elevated free water in the calcarine cortices and lower fwcMD in the dorsal premotor cortices compared to controls. Lastly, age-related increases in free water were found across all white matter and gray matter ROIs in neurotypical controls, whereas no age-related associations were detected in any dMRI metrics for autistic adults.

Limitations: We only recruited cognitively capable autistic adults, which limits the generalizability of our findings across the full autism spectrum. The cross-sectional design precludes inferences about microstructural changes over time in middle and old aged autistic adults.

Conclusions: Our findings revealed increased free water load in frontal white matter in autistic adults and identified distinct age-associated microstructural variations between the two groups. These findings highlight more heterogeneous brain aging profiles in autistic adults. Our study also demonstrated the importance of quantifying free water in dMRI studies of ASD.

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).