Molecular Autism最新文献

Background: Elevated or reduced responses to sensory stimuli, known as sensory features, are common in autistic individuals and often impact quality of life. Little is known about the neurobiological basis of sensory features in autistic children. However, the brainstem may offer critical insights as it has been associated with both basic sensory processing and core features of autism.

Methods: Diffusion-weighted imaging (DWI) and parent-report of sensory features were acquired from 133 children (61 autistic children with and 72 non-autistic children, 6-11 years-old). Leveraging novel DWI processing techniques, we investigated the relationship between sensory features and white matter microstructure properties (free-water-elimination-corrected fractional anisotropy [FA] and mean diffusivity [MD]) in precisely delineated brainstem white matter tracts. Follow-up analyses assessed relationships between microstructure and sensory response patterns/modalities and analyzed whole brain white matter using voxel-based analysis.

Results: Results revealed distinct relationships between brainstem microstructure and sensory features in autistic children compared to non-autistic children. In autistic children, more prominent sensory features were generally associated with lower MD. Further, in autistic children, sensory hyporesponsiveness and tactile responsivity were strongly associated with white matter microstructure in nearly all brainstem tracts. Follow-up voxel-based analyses confirmed that these relationships were more prominent in the brainstem/cerebellum, with additional sensory-brain findings in the autistic group in the white matter of the primary motor and somatosensory cortices, the occipital lobe, the inferior parietal lobe, and the thalamic projections.

Limitations: All participants communicated via spoken language and acclimated to the sensory environment of an MRI session, which should be considered when assessing the generalizability of this work to the whole of the autism spectrum.

Conclusions: These findings suggest unique brainstem white matter contributions to sensory features in autistic children compared to non-autistic children. The brainstem correlates of sensory features underscore the potential reflex-like nature of behavioral responses to sensory stimuli in autism and have implications for how we conceptualize and address sensory features in autistic populations.

Background: Fragile X syndrome (FXS) is the leading inherited monogenic cause of intellectual disability and autism spectrum disorder. Executive function (EF), necessary for adaptive goal-oriented behavior and dependent on frontal lobe function, is impaired in individuals with FXS. Yet, little is known how alterations in frontal lobe neural activity is related to EF deficits in FXS.

Methods: Sixty-one participants with FXS (54% males) and 71 age- and sex-matched typically-developing controls (TDC; 58% males) completed a five-minute resting state electroencephalography (EEG) protocol and a computerized battery of tests of EF, the Test of Attentional Performance for Children (KiTAP). Following source localization (minimum-norm estimate), we computed debiased weighted phase lag index (dWPLI), a phase connectivity value, for pairings between 18 nodes in frontal regions for gamma (30-55 Hz) and alpha (10.5-12.5 Hz) bands. Linear models were generated with fixed factors of group, sex, frequency, and connection. Relationships between frontal connectivity and EF variables also were examined.

Results: Individuals with FXS demonstrated increased gamma band and reduced alpha band connectivity across all frontal regions and across hemispheres compared to TDC. After controlling for nonverbal IQ, increased error rates on EF tasks were associated with increased gamma band and reduced alpha band connectivity.

Limitations: Frontal connectivity findings are limited to intrinsic brain activity during rest and may not generalize to frontal connectivity during EF tasks or everyday function.

Conclusions: We report gamma hyper-connectivity and alpha hypo-connectivity within source-localized frontal brain regions in FXS compared to TDC during resting-state EEG. For the first time in FXS, we report significant associations between EF and altered frontal connectivity, with increased error rate relating to increased gamma band connectivity and reduced alpha band connectivity. These findings suggest increased phase connectivity within gamma band may impair EF performance, whereas greater alpha band connectivity may provide compensatory support for EF. Together, these findings provide important insight into neurophysiological mechanisms of EF deficits in FXS and provide novel targets for treatment development.

Background: Autism is proposed to be characterised by an atypical balance of cortical excitation and inhibition (E/I). However, most studies have examined E/I alterations in older autistic individuals, meaning that findings could in part reflect homeostatic compensation. To assess the directionality of effects, it is necessary to examine alterations in E/I balance early in the lifespan before symptom emergence. Recent explanatory frameworks have argued that it is also necessary to consider how early risk features interact with later developing modifier factors to predict autism outcomes.

Method: We indexed E/I balance in early infancy by extracting the aperiodic exponent of the slope of the electroencephalogram (EEG) power spectrum ('1/f'). To validate our index of E/I balance, we tested for differences in the aperiodic exponent in 10-month-old infants with (n = 22) and without (n = 27) neurofibromatosis type 1 (NF1), a condition thought to be characterised by alterations to cortical inhibition. We then tested for E/I alterations in a larger heterogeneous longitudinal cohort of infants with and without a family history of neurodevelopmental conditions (n = 150) who had been followed to early childhood. We tested the relevance of alterations in E/I balance and our proposed modifier, executive attention, by assessing whether associations between 10-month aperiodic slope and 36-month neurodevelopmental traits were moderated by 24-month executive attention. Analyses adjusted for age at EEG assessment, sex and number of EEG trials.

Results: Infants with NF1 were characterised by a higher aperiodic exponent, indicative of greater inhibition, supporting our infant measure of E/I. Longitudinal analyses showed a significant interaction between aperiodic slope and executive attention, such that higher aperiodic exponents predicted greater autistic traits in childhood, but only in infants who also had weaker executive functioning abilities.

Limitations: The current study relied on parent report of infant executive functioning-type abilities; future work is required to replicate effects with objective measures of cognition.

Conclusions: Results suggest alterations in E/I balance are on the developmental pathway to autism outcomes, and that higher executive functioning abilities may buffer the impact of early cortical atypicalities, consistent with proposals that stronger executive functioning abilities may modify the impact of a wide range of risk factors.

Background: Non-suicidal self-injury (NSSI) has been linked with a higher risk of suicide attempts in autistic and non-autistic people. In the general population, NSSI may confer acquired capability for suicide by eroding one's fear and avoidance of pain and death. The present study aimed to explore acquired capability as the mediator of increased suicide risk conferred by NSSI in autistic and non-autistic adults.

Methods: Autistic and non-autistic adults (n = 314, n = 312) completed an online survey exploring lifetime suicide attempts, experience with NSSI, and acquired capability for suicide. We explored relationships between lifetime incidence of NSSI and lifetime suicide attempts via three facets of acquired capability (pain tolerance, reduced fear of death, and mental rehearsal of suicide). In self-harming participants (224 autistic and 156 non-autistic), we explored whether particular types and features of NSSI might be especially associated with capability and through that with suicide: namely engagement in scratching, cutting, and self-hitting, and engaging in more numerous forms of NSSI.

Results: While a higher frequency of NSSI was associated with all three facets of acquired capability, only reduced fear of death and mental rehearsal of suicide mediated an indirect relationship with lifetime suicide attempts. NSSI also directly predicted more numerous suicide attempts. Autistic people tended towards reduced fear of death and mental rehearsal regardless of NSSI status. Among self-harming autistic and non-autistic participants, cutting and an increased number of NSSI behaviours were associated with lifetime suicide attempts directly and indirectly via acquired capability. In both groups, self-hitting was associated with lifetime suicide attempts only via acquired capability.

Limitations: Our cross-sectional methodology negates inferences of directionality. While we controlled for age, our samples were poorly matched, with the autistic group two times older on average. The autistic sample, predominantly late-diagnosed, female and highly qualified, were unrepresentative of the whole autistic community.

Conclusions: Our data suggest that acquired capability, as measured herein, is an incomplete explanation for the association between NSSI and suicide risk. A broader construct with stable and transient facets may offer greater explanatory power, but it is probable that other variables explain or provide additional means through which this association arises.

Background: There has been a growing interest in the association between maternal levels of vitamin D during pregnancy and offspring autism. However, whether any associations reflect causal effects is still inconclusive.

Methods: We used data from a UK-based pregnancy cohort study (Avon Longitudinal Study of Parents and Children) comprising 7689 births between 1991 and 1992 with maternal blood vitamin D levels recorded during pregnancy and at least one recorded outcome measure, including autism diagnosis and autism-associated traits. The association between each outcome with seasonal and gestational age-adjusted maternal serum 25-hydroxyvitamin D during pregnancy was estimated using confounder-adjusted regression models. Multiple imputation was used to account for missing data, and restricted cubic splines were used to investigate nonlinear associations. Mendelian randomization was used to strengthen causal inference.

Results: No strong evidence of an association between maternal serum 25-hydroxyvitamin D during pregnancy and any offspring autism-associated outcome was found using multivariable regression analysis (autism diagnosis: adjusted OR = 0.98, 95% CI = 0.90-1.06), including with multiple imputation (autism diagnosis: adjusted OR = 0.99, 95% CI = 0.93-1.06), and no evidence of a causal effect was suggested by Mendelian randomization (autism diagnosis: causal OR = 1.08, 95% CI = 0.46-2.55). Some evidence of increased odds of autism-associated traits at lower levels of maternal serum 25-hydroxyvitamin D was found using spline analysis.

Limitations: Our study was potentially limited by low power, particularly for diagnosed autism cases as an outcome. The cohort may not have captured the extreme lows of the distribution of serum 25-hydroxyvitamin D, and our analyses may have been biased by residual confounding and missing data.

Conclusions: The present study found no strong evidence of a causal link between maternal vitamin D levels in pregnancy and offspring diagnosis or traits of autism.

Background: Difficulties in social communication are a defining clinical feature of autism. However, the underlying neurobiological heterogeneity has impeded targeted therapies and requires new approaches to identifying clinically relevant bio-behavioural subgroups. In the largest autism cohort to date, we comprehensively examined difficulties in facial expression recognition, a key process in social communication, as a bio-behavioural stratification biomarker, and validated them against clinical features and neurofunctional responses.

Methods: Between 255 and 488 participants aged 6-30 years with autism, typical development and/or mild intellectual disability completed the Karolinska Directed Emotional Faces task, the Reading the Mind in the Eyes Task and/or the Films Expression Task. We first examined mean-group differences on each test. Then, we used a novel intersection approach that compares two centroid and connectivity-based clustering methods to derive subgroups based on the combined performance across the three tasks. Measures and subgroups were then related to clinical features and neurofunctional differences measured using fMRI during a fearful face-matching task.

Results: We found significant mean-group differences on each expression recognition test. However, cluster analyses showed that these were driven by a low-performing autistic subgroup (~ 30% of autistic individuals who performed below 2SDs of the neurotypical mean on at least one test), while a larger subgroup (~ 70%) performed within 1SD on at least 2 tests. The low-performing subgroup also had on average significantly more social communication difficulties and lower activation in the amygdala and fusiform gyrus than the high-performing subgroup.

Limitations: Findings of autism expression recognition subgroups and their characteristics require independent replication. This is currently not possible, as there is no other existing dataset that includes all relevant measures. However, we demonstrated high internal robustness (91.6%) of findings between two clustering methods with fundamentally different assumptions, which is a critical pre-condition for independent replication.

Conclusions: We identified a subgroup of autistic individuals with expression recognition difficulties and showed that this related to clinical and neurobiological characteristics. If replicated, expression recognition may serve as bio-behavioural stratification biomarker and aid in the development of targeted interventions for a subgroup of autistic individuals.

Background: Deficits in establishing and maintaining eye-contact are early and persistent vulnerabilities of autism spectrum disorder (ASD), and the neural bases of these deficits remain elusive. A promising hypothesis is that social features of autism may reflect difficulties in making predictions about the social world under conditions of uncertainty. However, no research in ASD has examined how predictability impacts the neural processing of eye-contact in naturalistic interpersonal interactions.

Method: We used eye tracking to facilitate an interactive social simulation wherein onscreen faces would establish eye-contact when the participant looked at them. In Experiment One, receipt of eye-contact was unpredictable; in Experiment Two, receipt of eye-contact was predictable. Neural response to eye-contact was measured via the N170 and P300 event-related potentials (ERPs). Experiment One included 23 ASD and 46 typically developing (TD) adult participants. Experiment Two included 25 ASD and 43 TD adult participants.

Results: When receipt of eye-contact was unpredictable, individuals with ASD showed increased N170 and increased, but non-specific, P300 responses. The magnitude of the N170 responses correlated with measures of sensory and anxiety symptomology, such that increased response to eye-contact was associated with increased symptomology. However, when receipt of eye-contact was predictable, individuals with ASD, relative to controls, exhibited slower N170s and no differences in the amplitude of N170 or P300.

Limitations: Our ASD sample was composed of adults with IQ > 70 and included only four autistic women. Thus, further research is needed to evaluate how these results generalize across the spectrum of age, sex, and cognitive ability. Additionally, as analyses were exploratory, some findings failed to survive false-discovery rate adjustment.

Conclusions: Neural response to eye-contact in ASD ranged from attenuated to hypersensitive depending on the predictability of the social context. These findings suggest that the vulnerabilities in eye-contact during social interactions in ASD may arise from differences in anticipation and expectation of eye-contact in addition to the perception of gaze alone.

MAIN: In recent years, substantial advances in social neuroscience have been realized, including the generation of numerous rodent models of autism spectrum disorder. Still, it can be argued that those methods currently being used to analyze animal social behavior create a bottleneck that significantly slows down progress in this field. Indeed, the bulk of research still relies on a small number of simple behavioral paradigms, the results of which are assessed without considering behavioral dynamics. Moreover, only few variables are examined in each paradigm, thus overlooking a significant portion of the complexity that characterizes social interaction between two conspecifics, subsequently hindering our understanding of the neural mechanisms governing different aspects of social behavior. We further demonstrate these constraints by discussing the most commonly used paradigm for assessing rodent social behavior, the three-chamber test. We also point to the fact that although emotions greatly influence human social behavior, we lack reliable means for assessing the emotional state of animals during social tasks. As such, we also discuss current evidence supporting the existence of pro-social emotions and emotional cognition in animal models. We further suggest that adequate social behavior analysis requires a novel multimodal approach that employs automated and simultaneous measurements of multiple behavioral and physiological variables at high temporal resolution in socially interacting animals. We accordingly describe several computerized systems and computational tools for acquiring and analyzing such measurements. Finally, we address several behavioral and physiological variables that can be used to assess socio-emotional states in animal models and thus elucidate intricacies of social behavior so as to attain deeper insight into the brain mechanisms that mediate such behaviors. CONCLUSIONS: In summary, we suggest that combining automated multimodal measurements with machine-learning algorithms will help define socio-emotional states and determine their dynamics during various types of social tasks, thus enabling a more thorough understanding of the complexity of social behavior.

Background: A core symptom of autism spectrum disorder (ASD) is repetitive and restrictive patterns of behavior. Cognitive inflexibility has been proposed as a potential basis for these symptoms of ASD. More generally, behavioral inflexibility has been proposed to underlie repetitive and restrictive behavior in ASD. Here, we investigated whether and how behavioral flexibility is compromised in a widely used animal model of ASD.

Methods: We compared the behavioral performance of Shank2-knockout mice and wild-type littermates in reversal learning employing a probabilistic classical trace conditioning paradigm. A conditioned stimulus (odor) was paired with an unconditioned appetitive (water, 6 µl) or aversive (air puff) stimulus in a probabilistic manner. We also compared air puff-induced eye closure responses of Shank2-knockout and wild-type mice.

Results: Male, but not female, Shank2-knockout mice showed impaired reversal learning when the expected outcomes consisted of a water reward and a strong air puff. Moreover, male, but not female, Shank2-knockout mice showed stronger anticipatory eye closure responses to the air puff compared to wild-type littermates, raising the possibility that the impairment might reflect enhanced fear. In support of this contention, male Shank2-knockout mice showed intact reversal learning when the strong air puff was replaced with a mild air puff and when the expected outcomes consisted of only rewards.

Limitations: We examined behavioral flexibility in one behavioral task (reversal learning in a probabilistic classical trace conditioning paradigm) using one ASD mouse model (Shank2-knockout mice). Thus, future work is needed to clarify the extent to which our findings (that enhanced fear limits behavioral flexibility in ASD) can explain the behavioral inflexibility associated with ASD. Also, we examined only the relationship between fear and behavioral flexibility, leaving open the question of whether abnormalities in processes other than fear contribute to behavioral inflexibility in ASD. Finally, the neurobiological mechanisms linking Shank2-knockout and enhanced fear remain to be elucidated.

Conclusions: Our results indicate that enhanced fear suppresses reversal learning in the presence of an intact capability to learn cue-outcome contingency changes in Shank2-knockout mice. Our findings suggest that behavioral flexibility might be seriously limited by abnormal emotional responses in ASD.

Background: Across behavioral studies, autistic individuals show greater variability than typically developing individuals. However, it remains unknown to what extent this variability arises from heterogeneity across individuals, or from unreliability within individuals. Here, we focus on eye tracking, which provides rich dependent measures that have been used extensively in studies of autism. Autistic individuals have an atypical gaze onto both static visual images and dynamic videos that could be leveraged for diagnostic purposes if the above open question could be addressed.

Methods: We tested three competing hypotheses: (1) that gaze patterns of autistic individuals are less reliable or noisier than those of controls, (2) that atypical gaze patterns are individually reliable but heterogeneous across autistic individuals, or (3) that atypical gaze patterns are individually reliable and also homogeneous among autistic individuals. We collected desktop-based eye tracking data from two different full-length television sitcom episodes, at two independent sites (Caltech and Indiana University), in a total of over 150 adult participants (N = 48 autistic individuals with IQ in the normal range, 105 controls) and quantified gaze onto features of the videos using automated computer vision-based feature extraction.

Results: We found support for the second of these hypotheses. Autistic people and controls showed equivalently reliable gaze onto specific features of videos, such as faces, so much so that individuals could be identified significantly above chance using a fingerprinting approach from video epochs as short as 2 min. However, classification of participants into diagnostic groups based on their eye tracking data failed to produce clear group classifications, due to heterogeneity in the autistic group.

Limitations: Three limitations are the relatively small sample size, assessment across only two videos (from the same television series), and the absence of other dependent measures (e.g., neuroimaging or genetics) that might have revealed individual-level variability that was not evident with eye tracking. Future studies should expand to larger samples across longer longitudinal epochs, an aim that is now becoming feasible with Internet- and phone-based eye tracking.

Conclusions: These findings pave the way for the investigation of autism subtypes, and for elucidating the specific visual features that best discriminate gaze patterns-directions that will also combine with and inform neuroimaging and genetic studies of this complex disorder.