Aberrant dynamics of cognitive control and motor circuits predict distinct restricted and repetitive behaviors in children with autism

Understanding the link between different types of maternal diabetes and the onset of autism spectrum disorders

Autism spectrum disorders (ASD) encompass a collection of neurodevelopmental disorders that exhibit impaired social interactions and repetitive stereotypic behaviors. Although the exact cause of these disorders remains unknown, it is widely accepted that both genetic and environmental factors contribute to their onset and progression. Recent studies have highlighted the potential negative impact of maternal diabetes on embryonic neurodevelopment, suggesting that intrauterine hyperglycemia could pose an additional risk to early brain development and contribute to the development of ASD. This paper presents a comprehensive analysis of the current research on the relationship between various forms of maternal diabetes, such as type 1 diabetes mellitus, type 2 diabetes mellitus, and gestational diabetes mellitus, and the likelihood of ASD in offspring. The study elucidates the potential mechanisms through which maternal hyperglycemia affects fetal development, involving metabolic hormones, immune dysregulation, heightened oxidative stress, and epigenetic alterations. The findings of this review offer valuable insights for potential preventive measures and evidence-based interventions targeting ASD.

Induction of autism-related behavior in male mice by early-life vitamin D deficiency: association with disruption of the gut microbial composition and homeostasis

Vitamin D deficiency (VDD) during early life emerges as a potential risk factor for autism spectrum disorder (ASD). Individuals with autism commonly exhibit lower vitamin D (VD) levels compared to the general population, and VD deficiency is prevalent during pregnancy and lactation. Moreover, gastrointestinal comorbidity, prevalent in ASD patients, correlates closely with disruptions in the gut microbiota and altered intestinal permeability. Therefore, it is fascinating and significant to explore the effects of maternal VD deficiency during pregnancy and lactation on the maturation of the gut microbiota of the offspring and its relevance to autism spectrum disorders. In this study, we established maternal pregnancy and lactation VD-deficient mouse models, employed shotgun macrogenomic sequencing to unveil alterations in the gut microbiome of offspring mice, and observed autism-related behaviours. Furthermore, fecal microbial transplantation (FMT) reversed repetitive and anxious behaviours and alleviated social deficits in offspring mice by modulating the gut microbiota and increasing short-chain fatty acid levels in the cecum, along with influencing the concentrations of claudin-1 and occludin in the colon. Our findings confirm that VDD during pregnancy and lactation is a risk factor for autism in the offspring, with disturbances in the structure and function of the offspring's gut microbiota contributing at least part of the effect. The study emphasises the importance of nutrition and gut health early in life. Simultaneously, this study further demonstrates the effect of VDD on ASD and provides potential ideas for early prevention and intervention of ASD.

Dorsal Striatal Functional Connectivity and Repetitive Behavior Dimensions in Children and Youths With Neurodevelopmental Disorders

BACKGROUND

Impairing repetitive behaviors are one of the core diagnostic symptoms in autism spectrum disorder and obsessive-compulsive disorder, but they also manifest in attention-deficit/hyperactivity disorder. Although the dorsal striatal circuit has been implicated in repetitive behaviors, extensive heterogeneity in and cross-diagnostic manifestations of these behaviors have suggested phenotypic and likely neurobiological heterogeneity across neurodevelopmental disorders (NDDs).

METHODS

Intrinsic dorsal striatal functional connectivity was examined in 3 NDDs (autism spectrum disorder, obsessive-compulsive disorder, and attention-deficit/hyperactivity disorder) and typically developing control participants in a large single-cohort sample (N = 412). To learn how diagnostic labels and overlapping behaviors manifest in dorsal striatal functional connectivity measured with functional magnetic resonance imaging, the main and interaction effects of diagnosis and behavior were examined in 8 models (2 seed functional connectivity [caudate and putamen] × 4 sub-behavioral domains [sameness/ritualistic, self-injury, stereotypy, and compulsions]).

RESULTS

The obsessive-compulsive disorder group demonstrated distinctive patterns in visual and visuomotor coordination regions compared with the other diagnostic groups. Lower-order repetitive behaviors (self-injury and stereotypy) manifesting across all participants were implicated in regions involved in motor and cognitive control, although the findings did not survive effects of multiple comparisons, suggesting heterogeneity in these behavioral domains. An interaction between self-injurious behavior and an attention-deficit/hyperactivity disorder diagnosis were observed on caudate-cerebellum functional connectivity.

CONCLUSIONS

These findings confirmed high heterogeneity and overlapping behavioral manifestations in NDDs and their complex underlying neural mechanisms. A call for diagnosis-free symptom measures that can capture not only observable symptoms and severity across NDDs but also the underlying functions and motivations of such behaviors across diagnoses is needed.

Causal effects of gut microbiota on autism spectrum disorder: A two-sample mendelian randomization study

There is increasing evidence that alterations in gut microbiota (GM) composition are associated with autism spectrum disorder (ASD), but no reliable causal relationship has been established. Therefore, a 2-sample Mendelian randomization (MR) study was conducted to reveal a potential causal relationship between GM and ASD. Instrumental variables for 211 GM taxa were obtained from genome-wide association studies (GWAS) and Mendelian randomization studies to estimate their impact on ASD risk in the iPSYCH-PGC GWAS dataset (18,382 ASD cases and 27,969 controls). Inverse variance weighted (IVW) is the primary method for causality analysis, and several sensitivity analyses validate MR results. Among 211 GM taxa, IVW results confirmed that Tenericutes (P value = .0369), Mollicutes (P value = .0369), Negativicutes (P value = .0374), Bifidobacteriales (P value = .0389), Selenomonadales (P value = .0374), Bifidobacteriaceae (P value = .0389), Family XIII (P value = .0149), Prevotella7 (P value = .0215), Ruminococcaceae NK4A214 group (P value = .0205) were potential protective factors for ASD. Eisenbergiella (P value = .0159) was a possible risk factor for ASD. No evidence of heterogeneous, pleiotropic, or outlier single-nucleotide polymorphism was detected. Additionally, further sensitivity analysis verified the robustness of the above results. We confirm a potential causal relationship between certain gut microbes and ASD, providing new insights into how gut microbes mediate ASD. The association between them needs to be further explored and will provide new ideas for the prevention and treatment of ASD.

DiffModeler: Large Macromolecular Structure Modeling in Low-Resolution Cryo-EM Maps Using Diffusion Model

Cryogenic electron microscopy (cryo-EM) has now been widely used for determining multi-chain protein complexes. However, modeling a complex structure is challenging particularly when the map resolution is low, typically in the intermediate resolution range of 5 to 10 Å. Within this resolution range, even accurate structure fitting is difficult, let alone de novo modeling. To address this challenge, here we present DiffModeler, a fully automated method for modeling protein complex structures. DiffModeler employs a diffusion model for backbone tracing and integrates AlphaFold2-predicted single-chain structures for structure fitting. Extensive testing on cryo-EM maps at intermediate resolutions demonstrates the exceptional accuracy of DiffModeler in structure modeling, achieving an average TM-Score of 0.92, surpassing existing methodologies significantly. Notably, DiffModeler successfully modeled a protein complex composed of 47 chains and 13,462 residues, achieving a high TM-Score of 0.94. Further benchmarking at low resolutions (10-20 Å confirms its versatility, demonstrating plausible performance. Moreover, when coupled with CryoREAD, DiffModeler excels in constructing protein-DNA/RNA complex structures for near-atomic resolution maps (0-5 Å), showcasing state-of-the-art performance with average TM-Scores of 0.88 and 0.91 across two datasets.

Role of autonomic, nociceptive, and limbic brainstem nuclei in core autism features

Although multiple theories have speculated about the brainstem reticular formation's involvement in autistic behaviors, the in vivo imaging of brainstem nuclei needed to test these theories has proven technologically challenging. Using methods to improve brainstem imaging in children, this study set out to elucidate the role of the autonomic, nociceptive, and limbic brainstem nuclei in the autism features of 145 children (74 autistic children, 6.0-10.9 years). Participants completed an assessment of core autism features and diffusion- and T1-weighted imaging optimized to improve brainstem images. After data reduction via principal component analysis, correlational analyses examined associations among autism features and the microstructural properties of brainstem clusters. Independent replication was performed in 43 adolescents (24 autistic, 13.0-17.9 years). We found specific nuclei, most robustly the parvicellular reticular formation-alpha (PCRtA) and to a lesser degree the lateral parabrachial nucleus (LPB) and ventral tegmental parabrachial pigmented complex (VTA-PBP), to be associated with autism features. The PCRtA and some of the LPB associations were independently found in the replication sample, but the VTA-PBP associations were not. Consistent with theoretical perspectives, the findings suggest that individual differences in pontine reticular formation nuclei contribute to the prominence of autistic features. Specifically, the PCRtA, a nucleus involved in mastication, digestion, and cardio-respiration in animal models, was associated with social communication in children, while the LPB, a pain-network nucleus, was associated with repetitive behaviors. These findings highlight the contributions of key autonomic brainstem nuclei to the expression of core autism features.

A comprehensive diversity analysis on the gut microbiomes of ASD patients: from alpha, beta to gamma diversities

Autism spectrum disorder (ASD) is estimated to influence as many as 1% children worldwide, but its etiology is still unclear. It has been suggested that gut microbiomes play an important role in regulating abnormal behaviors associated with ASD. A de facto standard analysis on the microbiome-associated diseases has been diversity analysis, and nevertheless, existing studies on ASD-microbiome relationship have not produced a consensus. Here, we perform a comprehensive analysis of the diversity changes associated with ASD involving alpha-, beta-, and gamma-diversity metrics, based on 8 published data sets consisting of 898 ASD samples and 467 healthy controls (HC) from 16S-rRNA sequencing. Our findings include: (i) In terms of alpha-diversity, in approximately 1/3 of the studies cases, ASD patients exhibited significantly higher alpha-diversity than the HC, which seems to be consistent with the "1/3 conjecture" of diversity-disease relationship (DDR). (ii) In terms of beta-diversity, the AKP (Anna Karenina principle) that predict all healthy microbiomes should be similar, and every diseased microbiome should be dissimilar in its own way seems to be true in approximately 1/2 to 3/4 studies cases. (iii) In terms of gamma-diversity, the DAR (diversity-area relationship) modeling suggests that ASD patients seem to have large diversity-area scaling parameter than the HC, which is consistent with the AKP results. However, the MAD (maximum accrual diversity) and RIP (ratio of individual to population diversity) parameters did not suggest significant differences between ASD patients and HC. Throughout the study, we adopted Hill numbers to measure diversity, which stratified the diversity measures in terms of the rarity-commonness-dominance spectrum. It appears that the differences between ASD patients and HC are more propounding on rare-species side than on dominant-species side. Finally, we discuss the apparent inconsistent diversity-ASD relationships among different case studies and postulate that the relationships are not monotonic.

Mapping Psychomotor Behavior in the Brain

This Viewpoint describes a new conception of brain regions that may be associated with abnormal psychomotor behaviors in psychotic and mood disorders.

Atypical cognitive training-induced learning and brain plasticity and their relation to insistence on sameness in children with autism

Children with autism spectrum disorders (ASDs) often display atypical learning styles; however, little is known regarding learning-related brain plasticity and its relation to clinical phenotypic features. Here, we investigate cognitive learning and neural plasticity using functional brain imaging and a novel numerical problem-solving training protocol. Children with ASD showed comparable learning relative to typically developing children but were less likely to shift from rule-based to memory-based strategy. While learning gains in typically developing children were associated with greater plasticity of neural representations in the medial temporal lobe and intraparietal sulcus, learning in children with ASD was associated with more stable neural representations. Crucially, the relation between learning and plasticity of neural representations was moderated by insistence on sameness, a core phenotypic feature of ASD. Our study uncovers atypical cognitive and neural mechanisms underlying learning in children with ASD, and informs pedagogical strategies for nurturing cognitive abilities in childhood autism.

Molecular and network-level mechanisms explaining individual differences in autism spectrum disorder

The mechanisms underlying phenotypic heterogeneity in autism spectrum disorder (ASD) are not well understood. Using a large neuroimaging dataset, we identified three latent dimensions of functional brain network connectivity that predicted individual differences in ASD behaviors and were stable in cross-validation. Clustering along these three dimensions revealed four reproducible ASD subgroups with distinct functional connectivity alterations in ASD-related networks and clinical symptom profiles that were reproducible in an independent sample. By integrating neuroimaging data with normative gene expression data from two independent transcriptomic atlases, we found that within each subgroup, ASD-related functional connectivity was explained by regional differences in the expression of distinct ASD-related gene sets. These gene sets were differentially associated with distinct molecular signaling pathways involving immune and synapse function, G-protein-coupled receptor signaling, protein synthesis and other processes. Collectively, our findings delineate atypical connectivity patterns underlying different forms of ASD that implicate distinct molecular signaling mechanisms.

Atypical cognitive training-induced learning and brain plasticity and their relation to insistence on sameness in children with autism

Children with autism spectrum disorders (ASD) often display atypical learning styles, however little is known regarding learning-related brain plasticity and its relation to clinical phenotypic features. Here, we investigate cognitive learning and neural plasticity using functional brain imaging and a novel numerical problem-solving training protocol. Children with ASD showed comparable learning relative to typically developing children but were less likely to shift from rule-based to memory-based strategy. Critically, while learning gains in typically developing children were associated with greater plasticity of neural representations in the medial temporal lobe and intraparietal sulcus, learning in children with ASD was associated with more stable neural representations. Crucially, the relation between learning and plasticity of neural representations was moderated by insistence on sameness, a core phenotypic feature of ASD. Our study uncovers atypical cognitive and neural mechanisms underlying learning in children with ASD, and informs pedagogical strategies for nurturing cognitive abilities in childhood autism.

Blood RNA Sequencing Indicates Upregulated BATF2 and LY6E and Downregulated ISG15 and MT2A Expression in Children with Autism Spectrum Disorder

Mutations in over 100 genes are implicated in autism spectrum disorder (ASD). DNA SNPs, CNVs, and epigenomic modifications also contribute to ASD. Transcriptomics analysis of blood samples may offer clues for pathways dysregulated in ASD. To expand and validate published findings of RNA-sequencing (RNA-seq) studies, we performed RNA-seq of whole blood samples from an Israeli discovery cohort of eight children with ASD compared with nine age- and sex-matched neurotypical children. This revealed 10 genes with differential expression. Using quantitative real-time PCR, we compared RNAs from whole blood samples of 73 Israeli and American children with ASD and 26 matched neurotypical children for the 10 dysregulated genes detected by RNA-seq. This revealed higher expression levels of the pro-inflammatory transcripts BATF2 and LY6E and lower expression levels of the anti-inflammatory transcripts ISG15 and MT2A in the ASD compared to neurotypical children. BATF2 was recently reported as upregulated in blood samples of Japanese adults with ASD. Our findings support an involvement of these genes in ASD phenotypes, independent of age and ethnicity. Upregulation of BATF2 and downregulation of ISG15 and MT2A were reported to reduce cancer risk. Implications of the dysregulated genes for pro-inflammatory phenotypes, immunity, and cancer risk in ASD are discussed.

Alteration of Gut Microbiota: New Strategy for Treating Autism Spectrum Disorder

Autism spectrum disorder (ASD) is defined as a complex heterogeneous disorder and characterized by stereotyped behavior and deficits in communication and social interactions. The emerging microbial knowledge has pointed to a potential link between gut microbiota dysbiosis and ASD. Evidence from animal and human studies showed that shifts in composition and activity of the gut microbiota may causally contribute to the etiopathogenesis of core symptoms in the ASD individuals with gastrointestinal tract disturbances and act on microbiota-gut-brain. In this review, we summarized the characterized gut bacterial composition of ASD and the involvement of gut microbiota and their metabolites in the onset and progression of ASD; the possible underlying mechanisms are also highlighted. Given this correlation, we also provide an overview of the microbial-based therapeutic interventions such as probiotics, antibiotics, fecal microbiota transplantation therapy, and dietary interventions and address their potential benefits on behavioral symptoms of ASD. The precise contribution of altering gut microbiome to treating core symptoms in the ASD needs to be further clarified. It seemed to open up promising avenues to develop microbial-based therapies in ASD.

Repetitive Restricted Behaviors in Autism Spectrum Disorder: From Mechanism to Development of Therapeutics

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by deficits in social communication, social interaction, and repetitive restricted behaviors (RRBs). It is usually detected in early childhood. RRBs are behavioral patterns characterized by repetition, inflexibility, invariance, inappropriateness, and frequent lack of obvious function or specific purpose. To date, the classification of RRBs is contentious. Understanding the potential mechanisms of RRBs in children with ASD, such as neural connectivity disorders and abnormal immune functions, will contribute to finding new therapeutic targets. Although behavioral intervention remains the most effective and safe strategy for RRBs treatment, some promising drugs and new treatment options (e.g., supplementary and cell therapy) have shown positive effects on RRBs in recent studies. In this review, we summarize the latest advances of RRBs from mechanistic to therapeutic approaches and propose potential future directions in research on RRBs.

Deep learning identifies robust gender differences in functional brain organization and their dissociable links to clinical symptoms in autism

BACKGROUND

Autism spectrum disorder (ASD) is a highly heterogeneous disorder that affects nearly 1 in 189 females and 1 in 42 males. However, the neurobiological basis of gender differences in ASD is poorly understood, as most studies have neglected females and used methods ill-suited to capture such differences.

AIMS

To identify robust functional brain organisation markers that distinguish between females and males with ASD and predict symptom severity.

METHOD

We leveraged multiple neuroimaging cohorts (ASD n = 773) and developed a novel spatiotemporal deep neural network (stDNN), which uses spatiotemporal convolution on functional magnetic resonance imaging data to distinguish between groups.

RESULTS

stDNN achieved consistently high classification accuracy in distinguishing between females and males with ASD. Notably, stDNN trained to distinguish between females and males with ASD could not distinguish between neurotypical females and males, suggesting that there are gender differences in the functional brain organisation in ASD that differ from normative gender differences. Brain features associated with motor, language and visuospatial attentional systems reliably distinguished between females and males with ASD. Crucially, these results were observed in a large multisite cohort and replicated in a fully independent cohort. Furthermore, brain features associated with the motor network's primary motor cortex node predicted the severity of restricted/repetitive behaviours in females but not in males with ASD.

CONCLUSIONS

Our replicable findings reveal that the brains of females and males with ASD are functionally organised differently, contributing to their clinical symptoms in distinct ways. They inform the development of gender-specific diagnoses and treatment strategies for ASD, and ultimately advance precision psychiatry.