Autism spectrum heterogeneity: fact or artifact?

Large language models deconstruct the clinical intuition behind diagnosing autism

Efforts to use genome-wide assays or brain scans to diagnose autism have seen diminishing returns. Yet the clinical intuition of healthcare professionals, based on longstanding first-hand experience, remains the gold standard for diagnosis of autism. We leveraged deep learning to deconstruct and interrogate the logic of expert clinician intuition from clinical reports to inform our understanding of autism. After pre-training on hundreds of millions of general sentences, we finessed large language models (LLMs) on >4,000 free-form health records from healthcare professionals to distinguish confirmed versus suspected autism cases. By introducing an explainability strategy, our extended language model architecture could pin down the most salient single sentences in what drives clinical thinking toward correct diagnoses. Our framework flagged the most autism-critical DSM-5 criteria to be stereotyped repetitive behaviors, special interests, and perception-based behaviors, which challenges today's focus on deficits in social interplay, suggesting necessary revision of long-trusted diagnostic criteria in gold-standard instruments.

Autistic traits relate to reduced reward sensitivity in learning from point-light displays (PLDs)

A number of studies have linked autistic traits to difficulties in learning from social (versus non-social) stimuli. However, these stimuli are often difficult to match on low-level visual properties, which is especially important given the impact of autistic traits on sensory processing. Additionally, studies often fail to account for dissociable aspects of the learning process in the specification of model parameters (learning rates and reward sensitivity). Here, we investigate whether learning deficits in individuals with high autistic traits exhibit deficits when learning from facial point-light displays (PLDs) depicting emotional expressions. Social and non-social stimuli were created from random arrangements of the same number of point-lights and carefully matched on low-level visual properties. Neurotypical participants (N = 63) were assessed using the autism spectrum quotient (AQ) and completed a total of 96 trials in a reinforcement learning task. Although linear multi-level modelling did not indicate learning deficits, pre-registered computational modelling using a Rescorla-Wagner framework revealed that higher autistic traits were associated with reduced reward sensitivity in the win domain, demonstrating an attenuated response to received feedback during learning. These findings suggest that autistic traits can significantly impact learning from PLD feedback beyond a general deficit in learning rates.

Gangliosides and Cholesterol: Dual Regulators of Neuronal Membrane Framework in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with heterogeneous clinical presentation. Diagnosing ASD is complex, and the criteria for diagnosis, as well as the term ASD, have changed during the last decades. Diagnosis is made based on observation and accomplishment of specific diagnostic criteria, while a particular biomarker of ASD does not yet exist. However, studies universally report a disequilibrium in membrane lipid content, pointing to a unique neurolipid signature of ASD. This review sheds light on the possible role of cholesterol and gangliosides, complex membrane glycosphingolipids, in the development of ASD. In addition to maintaining membrane integrity, neuronal signaling, and synaptic plasticity, these lipids play a role in neurotransmitter release and calcium signaling. Evidence linking ASD to lipidome changes includes low cholesterol levels, unusual ganglioside levels, and unique metabolic profiles. ASD symptoms may be mitigated with therapeutic interventions targeting the lipid composition of membranes. However, restoring membrane equilibrium in the central nervous system remains a challenge. This review underscores the need for comprehensive research into lipid metabolism to uncover practical insights into ASD etiology and treatment as lipidomics emerges as a major area in ASD research.

Can memantine treat autism? Answers from preclinical and clinical studies

Autism Spectrum Disorder (ASD) represents a clinical challenge due to its diverse behavioral symptoms and complex neuro-pathophysiology. Finding effective treatments that target the fundamental mechanisms of ASD remains a top priority. This narrative review presents the potential of the NMDA-receptor blocker memantine in managing ASD symptoms. Preclinical studies indicate that memantine could abrogate excitotoxicity, GABA/glutamate imbalance, reduced levels of brain-derived neurotrophic factor (BDNF), blood-brain barrier (BBB) leakage, and neuroinflammation, offering hope for managing core deficits associated with ASD like impaired social interaction and repetitive behaviors. However, clinical trials yield conflicting results, with some showing slight improvements in symptom severity and cognitive function, while others demonstrate limited efficacy. Further exploration of memantine's neurobiological mechanisms and refinement of treatment approaches are crucial for comprehensively tackling ASD complexities. Drawing from both animal models and clinical data, this review examines memantine's impact on core ASD symptoms, cognitive function, and potential mechanisms of action. Lastly, it identifies research gaps and proposes avenues for future investigations to enhance our understanding and utilization of memantine in ASD management.

Gut microbial GABA imbalance emerges as a metabolic signature in mild autism spectrum disorder linked to overrepresented Escherichia

Gut microbiota (GM) alterations have been implicated in autism spectrum disorder (ASD), yet the specific functional architecture remains elusive. Here, employing multi-omics approaches, we investigate stool samples from two distinct cohorts comprising 203 children with mild ASD or typical development. In our screening cohort, regression-based analysis for metabolomic profiling identifies an elevated γ-aminobutyric acid (GABA) to glutamate (Glu) ratio as a metabolic signature of ASD, independent of age and gender. In the validating cohort, we affirm the GABA/Glu ratio as an ASD diagnostic indicator after adjusting for geography, age, gender, and specific food-consuming frequency. Integrated analysis of metabolomics, 16S rRNA sequencing, and metagenomics reveals a correlation between overrepresented Escherichia and disrupted GABA metabolism. Furthermore, we observe social behavioral impairments in weaning mice transplanted with E. coli, suggesting a potential link to ASD symptomatology. Collectively, these findings provide insights into potential diagnostic and therapeutic strategies aimed at evaluating and restoring gut microbial neurotransmitter homeostasis.

Understanding Autism as a Condition in Mental Health Clinical Practice: Clinical Perspectives from a Youth Early Psychosis Service

Autism is a rapidly growing phenomenon, with rates of diagnosed autism in the community rising every decade. Autism and traits of autism are also regularly part of presentation at youth mental health services, including early psychosis services. In early psychosis services young people's symptoms tend to be formulated through a psychosis lens, rather than a neurodevelopmental lens which can lead to unnecessary medicalised treatment, and treatment plans that do not consider the possible impact of neurodiversity. The following paper explores autism and traits of autism in relation to youth early psychosis, examining the complexity in accurate formulation, and the possible impacts for young people. Future directions for how services can address this issue and more effectively tailor treatment to young people are also discussed.

Is it still autism? The increasing broadening of the autism spectrum

Clinical significance of a broad autism phenotype (BAP) seems to be increasingly supported by growing reports of high prevalence of subthreshold autism spectrum disorder (sASD) or autistic traits (AT) in various demographic samples, particularly in individuals with psychiatric conditions. We question this increasing extension of the autism spectrum and its potential negative consequences for clinical services, research, cultural attitudes, and resource allocation, as well as alternative explanations of what is currently attributed to sASD and AT. In modern psychiatry the diagnostic threshold is paramount and associated with a significant impairment of functioning, implying that symptom specificity is more relevant than sensitivity. Within a syndrome, symptoms have to be present together, with the parts related to and interconnected with the whole. Single autism symptomatic dimensions have low syndromic specificity and can be observed in many different mental disorders. For instance, communication problems may present in communication disorders, social-cognitive difficulties can be found in schizophrenia, and rigid and/or repetitive behaviors can be found in obsessive compulsive disorder. One alternative interpretation of AT and/or sASD relates to personality traits. For example, within the Big 5 Model, low openness is associated with a dislike of change and a narrow range of interests, low extraversion with social withdrawal and coldness, and low agreeableness with disinterest in others and disregard for their feelings. These risks of overreliance on non-specific aspects of autism are particularly likely to occur with screening checklists, self-assessment, or assessment by a lay interviewer with only limited expertise in clinical assessment.

The Prevalence of Persistent Toe Walking in Children With and Without Autism Spectrum Disorder and the Odds of Subsequent Surgery

Persistent toe walking is associated with autism spectrum disorder. The true prevalence of persistent toe walking and odds of progression to surgery in children with and without autism remains unclear. This retrospective descriptive study identified patients ages 3 to 17 years who were enrolled in our healthcare system over a 2-year period. Using international classification of disease codes, we identified all children with autism and persistent toe walking, and excluded children with conditions that may independently cause toe walking. Data on Achilles lengthening surgeries, sex, race and body mass index was gathered. The toe walking prevalence amongst children with and without autism was calculated. Multivariable logistic regression analysis controlling for sex, race and body mass index was used to determine independent risk factors for persistent toe walking and surgery. Of the children who met inclusion criteria (N = 284,925), 4622 (1.6%) had persistent toe walking. Prevalence of persistent toe walking was higher amongst children with autism (6.3% vs 1.5%, p < .01), as were odds of persistent toe walking (OR 4.13, 95% CI 3.74 to 4.56, p < .01). Males and White patients had higher odds of persistent toe walking compared to females and patients of any other race, respectively (p < .01 for all). Although children with autism and toe walking had higher rates of surgery than their counterparts without autism (4.3% vs 2.6%, p = .04), this difference was not significant after controlling for sex, race and BMI (OR 1.59, 95% CI 0.95 to 2.69, p > .05).

Autism spectrum disorder variation as a computational trade-off via dynamic range of neuronal population responses

Individuals diagnosed with autism spectrum disorder (ASD) show neural and behavioral characteristics differing from the neurotypical population. This may stem from a computational principle that relates inference and computational dynamics to the dynamic range of neuronal population responses, reflecting the signal levels for which the system is responsive. In the present study, we showed that an increased dynamic range (IDR), indicating a gradual response of a neuronal population to changes in input, accounts for neural and behavioral variations in individuals diagnosed with ASD across diverse tasks. We validated the model with data from finger-tapping synchronization, orientation reproduction and global motion coherence tasks. We suggested that increased heterogeneity in the half-activation point of individual neurons may be the biological mechanism underlying the IDR in ASD. Taken together, this model provides a proof of concept for a new computational principle that may account for ASD and generates new testable and distinct predictions regarding its behavioral, neural and biological foundations.

Correlation of biochemical markers and inflammatory cytokines in autism spectrum disorder (ASD)

INTRODUCTION

Autism Spectrum Disorder (ASD) is a disorder that severely affects neurodevelopment, and its underlying causes are not yet entirely understood. Research suggests that there may be a connection between the occurrence of ASD and changes in immune responses. This study aims to know if some biochemical and inflammatory cytokines are promising biomarkers for ASD and whether they are involved in the pathogenesis of ASD.

METHODS

The serum levels of CRP, TNF-α, TGF-β, IL-1β, IL-10, 1 L-8, and IL-6 were measured in all of the patients (n = 22) and in the healthy (n = 12) children using ELISA method.

RESULTS

The serum concentrations of IL-10 and IL-8 were significantly lower in the ASD patients compared to the control group (p < 0.05) and there were not significant differences between CRP, TNF-α, TGF-β, IL-6 and IL-1β levels in two groups. There were positive correlations between CRP and IL-10, also CRP and IL-8, in ASD group. In contrast to the ASD patients, the correlations of IL-8, IL-10, and CRP were not significant in the control group.

CONCLUSION

In conclusion, this study highlights the potential role of certain biochemical markers and inflammatory cytokines in ASD. Specifically, the lower levels of IL-10 and IL-8 in ASD patients, along with the significant correlations between CRP and these cytokines, suggest an altered immune response in individuals with ASD. These findings support the hypothesis that immune dysregulation may be involved in ASD pathogenesis. Further research is needed to explore these biomarkers and their mechanistic links to ASD, which could lead to improved diagnostics or therapeutic strategies.

Heterogeneity and convergence across seven neuroimaging modalities: a review of the autism spectrum disorder literature

Background

A growing body of literature classifies autism spectrum disorder (ASD) as a heterogeneous, complex neurodevelopmental disorder that often is identified prior to three years of age. We aim to provide a narrative review of key structural and functional properties that differentiate the neuroimaging profile of autistic youth from their typically developing (TD) peers across different neuroimaging modalities.

Methods

Relevant studies were identified by searching for key terms in PubMed, with the most recent search conducted on September 1, 2023. Original research papers were included if they applied at least one of seven neuroimaging modalities (structural MRI, functional MRI, DTI, MRS, fNIRS, MEG, EEG) to compare autistic children or those with a family history of ASD to TD youth or those without ASD family history; included only participants <18 years; and were published from 2013 to 2023.

Results

In total, 172 papers were considered for qualitative synthesis. When comparing ASD to TD groups, structural MRI-based papers (n = 26) indicated larger subcortical gray matter volume in ASD groups. DTI-based papers (n = 14) reported higher mean and radial diffusivity in ASD participants. Functional MRI-based papers (n = 41) reported a substantial number of between-network functional connectivity findings in both directions. MRS-based papers (n = 19) demonstrated higher metabolite markers of excitatory neurotransmission and lower inhibitory markers in ASD groups. fNIRS-based papers (n = 20) reported lower oxygenated hemoglobin signals in ASD. Converging findings in MEG- (n = 20) and EEG-based (n = 32) papers indicated lower event-related potential and field amplitudes in ASD groups. Findings in the anterior cingulate cortex, insula, prefrontal cortex, amygdala, thalamus, cerebellum, corpus callosum, and default mode network appeared numerous times across modalities and provided opportunities for multimodal qualitative analysis.

Conclusions

Comparing across neuroimaging modalities, we found significant differences between the ASD and TD neuroimaging profile in addition to substantial heterogeneity. Inconsistent results are frequently seen within imaging modalities, comparable study populations and research designs. Still, converging patterns across imaging modalities support various existing theories on ASD.

Finding Similarities in Differences Between Autistic Adults: Two Replicated Subgroups

Autism is heterogeneous, which complicates providing tailored support and future prospects. We aim to identify subgroups in autistic adults with average to high intelligence, to clarify if certain subgroups might need support. We included 14 questionnaire variables related to aging and/or autism (e.g., demographic, psychological, and lifestyle). Community detection analysis was used for subgroup identification in an original sample of 114 autistic adults with an adulthood diagnosis (autism) and 58 non-autistic adults as comparison group (COMP), and a replication sample (NAutism = 261; NCOMP = 287), both aged 30-89 years. Next, we identified subgroups and assessed external validity (for cognitive and psychological difficulties, and quality of life [QoL]) in the autism samples. To test specificity, we repeated the analysis after adding 123 adults with ADHD, aged 30-80 years. As expected, the autism and COMP groups formed distinct subgroups. Among autistic adults, we identified three subgroups of which two were replicated. One of these subgroups seemed most vulnerable on the cluster variables; this subgroup also reported the most cognitive and psychological difficulties, and lowest QoL. Adding the ADHD group did not alter results. Within autistic adults, one subgroup could especially benefit from support and specialized care, although this must be tested in future studies.

Association of genetic variants with autism spectrum disorder in Japanese children revealed by targeted sequencing

Introduction

Autism spectrum disorders (ASD) represent a heterogeneous group of neurodevelopmental disorders with strong genetic predispositions. Although an increasing number of genetic variants have been implicated in the pathogenesis of ASD, little is known about the relationship between ASD-associated genetic variants and individual ASD traits. Therefore, we aimed to investigate these relationships.

Methods

Here, we report a case-control association study of 32 Japanese children with ASD (mainly with high-functioning autism [HFA]) and 36 with typical development (TD). We explored previously established ASD-associated genes using a next-generation sequencing panel and determined the association between Social Responsiveness Scale (SRS) T-scores and intelligence quotient (IQ) scores.

Results

In the genotype-phenotype analyses, 40 variants of five genes (SCN1A, SHANK3, DYRK1A, CADPS, and SCN2A) were associated with ASD/TD phenotypes. In particular, 10 SCN1A variants passed permutation filtering (false discovery rate <0.05). In the quantitative association analyses, 49 variants of 12 genes (CHD8, SCN1A, SLC6A1, KMT5B, CNTNAP2, KCNQ3, SCN2A, ARID1B, SHANK3, DYRK1A, FOXP1, and GRIN2B) and 50 variants of 10 genes (DYRK1A, SCN2A, SLC6A1, ARID1B, CNTNAP2, SHANK3, FOXP1, PTEN, SCN1A, and CHD8) were associated with SRS T- and IQ-scores, respectively.

Conclusion

Our data suggest that these identified variants are essential for the genetic architecture of HFA.

Database-assisted screening of autism spectrum disorder related gene set

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social and communication difficulties, along with repetitive behaviors. While genetic factors play a significant role in ASD, the precise genetic landscape remains complex and not fully understood, particularly in non-syndromic cases. The study performed an in silico comparison of three genetic databases. ClinVar, SFARI Gene, and AutDB were utilized to identify relevant gene subset and genetic variations associated with non-syndromic ASD. Gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) network analysis were conducted to elucidate the biological significance of the identified genes. The integrity of ASD-related gene subset and the distribution of their variations were statistically assessed. A subset of twenty overlapping genes potentially specific for non-syndromic ASD was identified. GSEA revealed enrichment of biological processes related to neuronal development and differentiation, synaptic function, and social skills, highlighting their importance in ASD pathogenesis. PPI network analysis demonstrated functional relationships among the identified genes. Analysis of genetic variations showed predominance of rare variants and database-specific distribution patterns. The results provide valuable insights into the genetic landscape of ASD and outline the genes and biological processes involved in the condition, while taking into account that the study relied exclusively on in silico analyses, which may be subject to biases inherent to database methodologies. Further research incorporating multi-omics data and experimental validation is warranted to enhance our understanding of non-syndromic ASD genetics and facilitate the development of targeted research, interventions and therapies.

The diagnosis of ASD with MRI: a systematic review and meta-analysis

While diagnosing autism spectrum disorder (ASD) based on an objective test is desired, the current diagnostic practice involves observation-based criteria. This study is a systematic review and meta-analysis of studies that aim to diagnose ASD using magnetic resonance imaging (MRI). The main objective is to describe the state of the art of diagnosing ASD using MRI in terms of performance metrics and interpretation. Furthermore, subgroups, including different MRI modalities and statistical heterogeneity, are analyzed. Studies that dichotomously diagnose individuals with ASD and healthy controls by analyses progressing from magnetic resonance imaging obtained in a resting state were systematically selected by two independent reviewers. Studies were sought on Web of Science and PubMed, which were last accessed on February 24, 2023. The included studies were assessed on quality and risk of bias using the revised Quality Assessment of Diagnostic Accuracy Studies tool. A bivariate random-effects model was used for syntheses. One hundred and thirty-four studies were included comprising 159 eligible experiments. Despite the overlap in the studied samples, an estimated 4982 unique participants consisting of 2439 individuals with ASD and 2543 healthy controls were included. The pooled summary estimates of diagnostic performance are 76.0% sensitivity (95% CI 74.1-77.8), 75.7% specificity (95% CI 74.0-77.4), and an area under curve of 0.823, but uncertainty in the study assessments limits confidence. The main limitations are heterogeneity and uncertainty about the generalization of diagnostic performance. Therefore, comparisons between subgroups were considered inappropriate. Despite the current limitations, methods progressing from MRI approach the diagnostic performance needed for clinical practice. The state of the art has obstacles but shows potential for future clinical application.

Exploring the physiological role of the G protein-coupled estrogen receptor (GPER) and its associations with human diseases

Estrogen is a group of hormones that collaborate with the nervous system to impact the overall well-being of all genders. It influences many processes, including those occurring in the central nervous system, affecting learning and memory, and playing roles in neurodegenerative diseases and mental disorders. The hormone's action is mediated by specific receptors. Significant roles of classical estrogen receptors, ERα and ERβ, in various diseases were known since many years, but after identifying a structurally and locationally distinct receptor, the G protein-coupled estrogen receptor (GPER), its role in human physiology and pathophysiology was investigated. This review compiles GPER-related information, highlighting its impact on homeostasis and diseases, while putting special attention on functions and dysfunctions of this receptor in neurobiology and biobehavioral processes. Understanding the receptor modulation possibilities is essential for therapy, as disruptions in receptors can lead to diseases or disorders, irrespective of correct estrogen levels. We conclude that studies on the GPER receptor have the potential to develop therapies that regulate estrogen and positively impact human health.

Reduced precision of motor and perceptual rhythmic timing in autistic adults

Recent results suggest that autistic individuals exhibit reduced accuracy compared to non-autistic peers in temporally coordinating their actions with predictable external cues, e.g., synchronizing finger taps to an auditory metronome. However, it is not yet clear whether these difficulties are driven primarily by motor differences or extend into perceptual rhythmic timing tasks. We recruited autistic and non-autistic participants for an online study testing both finger tapping synchronization and continuation as well as rhythmic time perception (anisochrony detection). We fractionated each participant's synchronization results into parameters representing error correction, motor noise, and internal time-keeper noise, and also investigated error-correcting responses to small metronome timing perturbations. Contrary to previous work, we did not find strong evidence for reduced synchronization error correction. However, we found compelling evidence for noisier internal rhythmic timekeeping in the synchronization, continuation, and perceptual components of the experiment. These results suggest that noisier internal rhythmic timing processes underlie some sensorimotor coordination challenges in autism.

Individual Deviation-Based Functional Hypergraph for Identifying Subtypes of Autism Spectrum Disorder

Heterogeneity has been one of the main barriers to understanding and treatment of autism spectrum disorder (ASD). Previous studies have identified several subtypes of ASD through unsupervised clustering analysis. However, most of them primarily depicted the pairwise similarity between individuals through second-order relationships, relying solely on patient data for their calculation. This leads to an underestimation of the complexity inherent in inter-individual relationships and the diagnostic information provided by typical development (TD). To address this, we utilized an elastic net model to construct an individual deviation-based hypergraph (ID-Hypergraph) based on functional MRI data. We then conducted a novel community detection clustering algorithm to the ID-Hypergraph, with the aim of identifying subtypes of ASD. By applying this framework to the Autism Brain Imaging Data Exchange repository data (discovery: 147/125, ASD/TD; replication: 134/132, ASD/TD), we identified four reproducible ASD subtypes with roughly similar patterns of ALFF between the discovery and replication datasets. Moreover, these subtypes significantly varied in communication domains. In addition, we achieved over 80% accuracy for the classification between these subtypes. Taken together, our study demonstrated the effectiveness of identifying subtypes of ASD through the ID-hypergraph, highlighting its potential in elucidating the heterogeneity of ASD and diagnosing ASD subtypes.

Biomimetic nanoparticles with enhanced rapamycin delivery for autism spectrum disorder treatment via autophagy activation and oxidative stress modulation

Rationale: Autism spectrum disorder (ASD) represents a complex neurodevelopmental condition lacking specific pharmacological interventions. Given the multifaced etiology of ASD, there exist no effective treatment for ASD. Rapamycin (RAPA) can activate autophagy by inhibiting the mTOR pathway and has exhibited promising effects in treating central nervous system disorders; however, its limited ability to cross the blood-brain barrier (BBB) has hindered its clinical efficacy, leading to substantial side effects. Methods: To address this challenge, we designed a drug delivery system utilizing red blood cell membrane (CM) vesicles modified with SS31 peptides to enhance the brain penetration of RAPA for the treatment of autism. Results: The fabricated SCM@RAPA nanoparticles, with an average diameter of 110 nm, exhibit rapid release of RAPA in a pathological environment characterized by oxidative stress. In vitro results demonstrate that SCM@RAPA effectively activate cellular autophagy, reduce intracellular ROS levels, improve mitochondrial function, thereby ameliorating neuronal damage. SS31 peptide modification significantly enhances the BBB penetration and rapid brain accumulation of SCM@RAPA. Notably, SCM@RAPA nanoparticles demonstrate the potential to ameliorate social deficits, improve cognitive function, and reverse neuronal impairments in valproic acid (VPA)-induced ASD models. Conclusions: The therapeutic potential of SCM@RAPA in managing ASD signifies a paradigm shift in autism drug treatment, holding promise for clinical interventions in diverse neurological conditions.

Endophenotyping social cognition in the broader autism phenotype

Relatives of individuals with autism spectrum disorder (ASD) may display milder social traits of the broader autism phenotype (BAP) providing potential endophenotypic markers of genetic risk for ASD. We performed a case-control comparison to quantify social cognition and pragmatic language difficulties in the BAP (n = 25 cases; n = 33 controls) using the Faux Pas test (FPT) and the Goldman-Eisler Cartoon task. Using deep phenotyping we then examined patterns of inheritance of social cognition in two large multiplex families and the spectrum of performance in 32 additional families (159 members; n = 51 ASD, n = 87 BAP, n = 21 unaffected). BAP individuals showed significantly poorer FPT performance and reduced verbal fluency with the absence of a compression effect in social discourse compared to controls. In multiplex families, we observed reduced FPT performance in 89% of autistic family members, 63% of BAP relatives and 50% of unaffected relatives. Across all affected families, there was a graded spectrum of difficulties, with ASD individuals showing the most severe FPT difficulties, followed by the BAP and unaffected relatives compared to community controls. We conclude that relatives of probands show an inherited pattern of graded difficulties in social cognition with atypical faux pas detection in social discourse providing a novel candidate endophenotype for ASD.

[Advances in Mendelian randomization studies on autism spectrum disorder]

Autism spectrum disorder (ASD) is a pervasive neurodevelopmental disorder with onset in infancy or early childhood. Mendelian randomization (MR) is a statistical method used to infer causal relationships between exposures and outcomes. This article summarizes MR studies related to ASD. Existing research supports a causal relationship between maternal inflammatory bowel disease in children with ASD, parental education levels, screen time exposure, obesity, insomnia, serum transferrin, decreased blood selenium, abnormal signals in brain functional MRI, interleukin-6, phosphodiesterase 2A, mitogen-activated protein kinase kinase 3, mitochondrial ribosomal protein L33, serotonin, and ASD. However, it does not support a causal relationship between parental rheumatoid arthritis, systemic lupus erythematosus, neonatal jaundice in children with ASD, cytomegalovirus infection, asthma, oral ulcers, vitamin D levels, and ASD. This article reviews the etiological factors related to ASD and MR studies, aiming to explore and deepen the understanding of the pathophysiology of ASD. It provides strong statistical support for the prevention, diagnosis, and treatment of ASD, and offers new methods and strategies for the etiological analysis of complex traits.

Strategic social decision making undergoes significant changes in typically developing and autistic early adolescents

Information sampling about others' trustworthiness prior to cooperation allows humans to minimize the risk of exploitation. Here, we examined whether early adolescence or preadolescence, a stage defined as in between childhood and adolescence, is a significant developmental period for strategic social decisions. We also sought to characterize differences between autistic children and their typically developing (TD) peers. TD (N = 48) and autistic (N = 56) 8- to 12-year-olds played an online information sampling trust game. While both groups adapted their information sampling and cooperation to the various trustworthiness levels of the trustees, groups differed in how age and social skills modulated task behavior. In the TD group social skills were a stronger overall predictor of task behavior. In the autistic group, age was a stronger predictor and interacted with social skills. Computational modeling revealed that both groups used the same heuristic information sampling strategy-albeit older TD children were more efficient as reflected by decreasing decision noise with age. Autistic children had lower prior beliefs about the trustee's trustworthiness compared to TD children. These lower priors indicate that children believed the trustees to be less trustworthy. Lower priors scaled with lower social skills across groups. Notably, groups did not differ in prior uncertainty, meaning that the priors of TD and autistic children were equally strong. Taken together, we found significant development in information sampling and cooperation in early adolescence and nuanced differences between TD and autistic children. Our study highlights the importance of deep phenotyping of children including clinical measures, behavioral experiments and computational modeling. RESEARCH HIGHLIGHTS: We specified how early adolescents with and without an autism diagnosis sampled information about their interaction partners and made cooperation decisions in a strategic game. Early adolescence is a significant developmental period for strategic decision making, marked by significant changes in information sampling efficiency and adaptivity to the partner's behavior. Autistic and non-autistic groups differed in how age and social skills modulated task behavior; in non-autistic children behavior was more indicative of overall social skills. Computational modeling revealed differences between autistic and non-autistic groups in their initial beliefs about cooperation partners; autistic children expected their partners to be less trustworthy.

Central Executive and Default Mode Networks: An Appraisal of Executive Function and Social Skill Brain-Behavior Correlates in Youth with Autism Spectrum Disorder

Atypical connectivity patterns have been observed for individuals with autism spectrum disorders (ASD), particularly across the triple-network model. The current study investigated brain-behavior relationships in the context of social skills and executive function profiles for ASD youth. We calculated connectivity measures from diffusion tensor imaging using Bayesian estimation and probabilistic tractography. We replicated prior structural equation modeling of behavioral measures with total default mode network (DMN) connectivity to include comparisons with central executive network (CEN) connectivity and CEN-DMN connectivity. Increased within-CEN connectivity was related to metacognitive strengths. Our findings indicate behavior regulation difficulties in youth with ASD may be attributable to impaired connectivity between the CEN and DMN and social skill difficulties may be exacerbated by impaired within-DMN connectivity.

The effect of autistic traits on prosocial behavior: The chain mediating role of received social support and perceived social support

ABSTRACT

There is growing evidence that the defining characteristics of autism spectrum disorder are distributed across the general population; therefore, understanding the correlates of prosocial behavior in individuals with high levels of autistic traits could shed light on autism spectrum disorder and prosocial behavior. In this study, the mechanism underlying the influence of individuals’ autistic traits on their prosocial behavior was explored by conducting a questionnaire survey of 414 Chinese college students. The results showed that autistic traits can influence individuals’ prosocial behavior not only through the separate effects of received social support and perceived social support but also through the chain mediating effects of received social support and perceived social support; however, the direct effect of autistic traits on individuals’ prosocial behavior is not significant. This study is conducive to understanding the internal mechanism underlying the relationship between autistic traits and prosocial behavior. Future work is required to further investigate the clinical autism spectrum disorder samples and cross-cultural applicability of the model found in this study.

Autism spectrum disorder in ICD-11-a critical reflection of its possible impact on clinical practice and research

This perspective article compares and contrasts the conceptualization of Autism Spectrum Disorder (ASD) in ICD-11 and DSM-5. By guiding the user through the ICD-11 text, it is argued that, in contrast to DSM-5, ICD-11 allows a high variety in symptom combinations, which results in an operationalization of ASD that is in favor of an extreme diverse picture, yet possibly at the expense of precision, including unforeseeable effects on clinical practice, care, and research. The clinical utility is questionable as this conceptualization can hardly be differentiated from other mental disorders and autism-like traits. It moves away from an observable, behavioral, and neurodevelopmental disorder to a disorder of inner experience that can hardly be measured objectively. It contains many vague and subjective concepts that lead to non-falsifiable diagnoses. This bears a large danger of false positive diagnoses, of further increased prevalence rates, limitations of access to ASD-specific services and of increasing the non-specificity of treatments. For research, the hypothesis is that the specificity of ASD will be reduced and this will additional increase the already high heterogeneity with the effect that replication of studies will be hampered. This could limit our understanding of etiology and biological pathways of ASD and bears the risk that precision medicine, i.e., a targeted approach for individual treatment strategies based on precise diagnostic markers, is more far from becoming reality. Thus, a more precise, quantitative description and more objective measurement of symptoms are suggested that define the clinical ASD phenotype. Identification of core ASD subtypes/endophenotypes and a precise description of symptoms is the necessary next step to advance diagnostic classification systems. Therefore, employing a more finely grained, objective, clinical symptom characterization which is more relatable to neurobehavioral concepts is of central significance.

Theoretical-Methodological Foundations for the Global Integration Method (Método de Integração Global-MIG) in the Treatment of Autism Spectrum Disorder

Currently, there is no intervention model for autism spectrum disorder (ASD) that addresses all levels and factors of the International Classification of Functioning, Disability and Health (ICF, WHO). The most researched programs focus on naturalistic, developmental and behavioral approaches to socio-communication. Less attention has been paid to motor and environmental reactivity aspects (behavior/interest restriction and sensory reactivity). The evidence rationale for the Global Integration Method (MIG, "Método de Integração Global"), a model addressing sensorimotor reactivity in addition to socio-communication, is presented. MIG is an integrative, interdisciplinary, family-oriented intervention and naturalistic program that addresses all levels and moderating factors of ASD's impact. MIG's theoretical rationale is based on the predictive coding impairment and embodied cognition hypotheses. MIG incorporates both bottom-up (flexible therapeutic suit, social-motor synchronization) and top-down (schematic social information processing, narratives, imagery) strategies to promote the building and use of accurate, flexible and context-sensitive internal predictive models. MIG is based on the premises that predictive coding improves both socio-communication and environmental reactivity, and that the postural stabilization provided by the flexible therapeutic suit frees information processing resources for socio-cognitive learning. MIG builds on interdisciplinary, professionally and parentally mediated work based on behavioral principles of intensive training in a situated environment.

Higher Sensory Sensitivity is Linked to Greater Expansion Amongst Functional Connectivity Gradients

Insofar as the autistic-like phenotype presents in the general population, it consists of partially dissociable traits, such as social and sensory issues. Here, we investigate individual differences in cortical organisation related to autistic-like traits. Connectome gradient decomposition based on resting state fMRI data reliably reveals a principal gradient spanning from unimodal to transmodal regions, reflecting the transition from perception to abstract cognition. In our non-clinical sample, this gradient's expansion, indicating less integration between visual and default mode networks, correlates with subjective sensory sensitivity (measured using the Glasgow Sensory Questionnaire, GSQ), but not other autistic-like traits (measured using the Autism Spectrum Quotient, AQ). This novel brain-based correlate of the GSQ demonstrates sensory issues can be disentangled from the wider autistic-like phenotype.

Modelling the overlap and divergence of autistic and schizotypal traits on hippocampal subfield volumes and regional cerebral blood flow

Psychiatric disorders show high co-morbidity, including co-morbid expressions of subclinical psychopathology across multiple disease spectra. Given the limitations of classical case-control designs in elucidating this overlap, new approaches are needed to identify biological underpinnings of spectra and their interaction. We assessed autistic-like traits (using the Autism Quotient, AQ) and schizotypy - as models of subclinical expressions of disease phenotypes and examined their association with volumes and regional cerebral blood flow (rCBF) of anterior, mid- and posterior hippocampus segments from  structural MRI scans in 318 and arterial spin labelling (ASL) in 346 nonclinical subjects, which overlapped with the structural imaging sample (N = 298). We demonstrate significant interactive effects of positive schizotypy and AQ social skills as well as of positive schizotypy and AQ imagination on hippocampal subfield volume variation. Moreover, we show that AQ attention switching modulated hippocampal head rCBF, while positive schizotypy by AQ attention to detail interactions modulated hippocampal tail rCBF. In addition, we show significant correlation of hippocampal volume and rCBF in both region-of-interest and voxel-wise analyses, which were robust after removal of variance related to schizotypy and autistic traits. These findings provide empirical evidence for both the modulation of hippocampal subfield structure and function through subclinical traits, and in particular how only the interaction of phenotype facets leads to significant reductions or variations in these parameters. This makes a case for considering the synergistic impact of different (subclinical) disease spectra on transdiagnostic biological parameters in psychiatry.

Investigating the borders of autism spectrum disorder: lessons from the former diagnosis of pervasive developmental disorder not otherwise specified

Introduction

Autism Spectrum Disorder (ASD) diagnosis is relatively consensual in typical forms. The margins of the spectrum and their degree of extension, however, are controversial. This has far-reaching implications, which extend beyond theoretical considerations: first, peripheral forms of autism are more prevalent than central forms; second, we do not know how relevant typical-targeted recommendations are for atypical forms. In DSM-IV-TR, these margins of autism were studied within the category of Pervasive Developmental Disorder - Not Otherwise Specified (PDD-NOS). In spite of its low reliability, this former diagnosis was of particular interest to shed light on the gray area of margins. The aim of this systematic is therefore to investigate the clinical characteristics of PDD-NOS in comparison with Autistic Disorder.

Method

A stepwise systematic PRISMA literature review was conducted by searching PubMed and Web Of Science databases to select corresponding studies.

Results

The systematic review included 81 studies comprising 6,644 children with PDD-NOS. Cross-sectional and longitudinal studies comparing PDD-NOS and AD showed that PDD-NOS corresponds to milder form of autism with less impact and less associated disorder, with the exception of schizophrenia and mood disorder.

Discussion

Our review challenges initial views of PDD-NOS, and shows the clinical relevance of this diagnosis when dealing with the margins of autism, and the de facto diversity included in the spectrum. However, in view of the many limitations of PDD-NOS (low reliability, instability through time, low acceptability), we suggest taxonomic changes in DSM-5: we introduce a new category based on three main dimensions related to socialization impairment, emotional lability and psychotic symptoms.

Conclusion

Our review argues for a distinction between AD and PDD-NOS on clinical characteristics and thus highlights the need to study the margins of autism. While the limitations of the PDD-NOS category made it irrelevant to investigate these margins from a research perspective, we believe that a multidimensional approach for mental health professionals taping socialization, emotion lability and psychotic symptoms would be interesting. Our review therefore encourage future studies to test relevant criteria for a new category and possibly identify developmental trajectories, specific interventions and treatments.

SNAP-25 Polymorphisms in Autism Spectrum Disorder: A Pilot Study towards a Possible Endophenotype

While there is substantial agreement on the diagnostic criteria for autism spectrum disorder, it is also acknowledged that it has a broad range of clinical presentations. This can complicate the diagnostic process and aggravate the choice of the most suitable rehabilitative strategy for each child. Attentional difficulties are among the most frequently reported comorbidities in autism spectrum disorder. We investigated the role of SNAP-25 polymorphisms. Synaptosome-associated protein 25 (SNAP25) is a presynaptic membrane-binding protein; it plays a crucial role in neurotransmission and has already been studied in numerous psychiatric disorders. It was also seen to be associated with hyperactivity in children with autism spectrum disorder. We collected clinical, behavioral and neuropsychological data on 41 children with a diagnosis of autism spectrum disorder, and then genotyped them for five single-nucleotide polymorphisms of SNAP-25. Participants were divided into two groups according to the Autism Diagnostic Observation Schedule (ADOS-2) Severity Score. In the group with the highest severity score, we found significant associations of clinical data with polymorphism rs363050 (A/G): children with the GG genotype had lower total IQ, more severe autistic functioning and more attentional difficulties. Our research could be the starting point for outlining a possible endophenotype among patients with autism spectrum disorder who are clinically characterized by severe autistic functioning and significant attentional difficulties.

Gut microbiota functional profiling in autism spectrum disorders: bacterial VOCs and related metabolic pathways acting as disease biomarkers and predictors

Background

Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental disorder. Major interplays between the gastrointestinal (GI) tract and the central nervous system (CNS) seem to be driven by gut microbiota (GM). Herein, we provide a GM functional characterization, based on GM metabolomics, mapping of bacterial biochemical pathways, and anamnestic, clinical, and nutritional patient metadata.

Methods

Fecal samples collected from children with ASD and neurotypical children were analyzed by gas-chromatography mass spectrometry coupled with solid phase microextraction (GC-MS/SPME) to determine volatile organic compounds (VOCs) associated with the metataxonomic approach by 16S rRNA gene sequencing. Multivariate and univariate statistical analyses assessed differential VOC profiles and relationships with ASD anamnestic and clinical features for biomarker discovery. Multiple web-based and machine learning (ML) models identified metabolic predictors of disease and network analyses correlated GM ecological and metabolic patterns.

Results

The GM core volatilome for all ASD patients was characterized by a high concentration of 1-pentanol, 1-butanol, phenyl ethyl alcohol; benzeneacetaldehyde, octadecanal, tetradecanal; methyl isobutyl ketone, 2-hexanone, acetone; acetic, propanoic, 3-methyl-butanoic and 2-methyl-propanoic acids; indole and skatole; and o-cymene. Patients were stratified based on age, GI symptoms, and ASD severity symptoms. Disease risk prediction allowed us to associate butanoic acid with subjects older than 5 years, indole with the absence of GI symptoms and low disease severity, propanoic acid with the ASD risk group, and p-cymene with ASD symptoms, all based on the predictive CBCL-EXT scale. The HistGradientBoostingClassifier model classified ASD patients vs. CTRLs by an accuracy of 89%, based on methyl isobutyl ketone, benzeneacetaldehyde, phenyl ethyl alcohol, ethanol, butanoic acid, octadecane, acetic acid, skatole, and tetradecanal features. LogisticRegression models corroborated methyl isobutyl ketone, benzeneacetaldehyde, phenyl ethyl alcohol, skatole, and acetic acid as ASD predictors.

Conclusion

Our results will aid the development of advanced clinical decision support systems (CDSSs), assisted by ML models, for advanced ASD-personalized medicine, based on omics data integrated into electronic health/medical records. Furthermore, new ASD screening strategies based on GM-related predictors could be used to improve ASD risk assessment by uncovering novel ASD onset and risk predictors.

A longitudinal study on language acquisition in monozygotic twins concordant for autism and hyperlexia

BACKGROUND

Hyperlexia, a strong orientation towards written materials, along with a discrepancy between the precocious acquisition of decoding skills and weaker comprehension abilities, characterizes up to 20% of autistic children. Sometimes perceived as an obstacle to oral language acquisition, hyperlexia may alternatively be the first step in a non-social pathway of language acquisition in autism.

METHOD

We describe two monozygotic twin brothers, both autistic and hyperlexic, from the ages of 4 to 8 years old. Following an in-depth diagnostic assessment, we investigated cross-sectionally and longitudinally their verbal and non-verbal cognitive abilities, language, reading and writing skills, interests, and strengths.

RESULTS

The twins' features, including their high non-verbal level of intelligence, their special interests, and their skills in various domains, were highly similar. Their language consisted exclusively of letters and numbers until their fourth year. After that, their vocabulary broadened until they developed full sentences, and their perception-related interests expanded and merged over time to serve the development of other skills.

CONCLUSION

Our results show that hyperlexic skills can be harnessed to favor oral language development. Given the strong concordance between the twins' cognitive and behavioral phenotypes, we discuss the environmental and genetic influence that could explain their abilities.

An internet-based behavioral intervention for adults with autism spectrum disorder - A randomized controlled trial and feasibility study

Background

The increased prevalence of Autism Spectrum Disorder (ASD) diagnoses in combination with psychiatric comorbidity, has led to an increased need for effective interventions. The evidence for internet-based interventions for several mental health problems is established but has not been evaluated for adults with ASD.

Objective

The aim of this randomized controlled trial is to evaluate the feasibility and effects of an internet-based intervention targeting quality of life and psychiatric symptoms (depression and anxiety) in adults with ASD.

Methods

84 participants were randomly allocated to intervention (n = 42) or control (n = 42). The 18-week internet-based intervention covered a range of themes related to difficulties common in ASD, and exercises based on cognitive behavioral strategies. Participants were provided with individual feedback following each module and were invited to regular chat sessions with peer participants. The primary outcomes were subjective quality of life and sense of coherence, and secondary outcomes were symptoms of depression and anxiety. All outcomes were measured at five occasions and analysed with linear mixed effect models. Participant satisfaction and adherence was also analysed.

Results

Participant satisfaction and adherence was satisfactory but no significant interaction between group and time was found for any outcome measure. Autistic traits were negatively related to quality of life and sense of coherence and positively related to anxiety and depressive symptoms.

Conclusions

This internet-based intervention showed feasibility regarding adherence and participant satisfaction. However, no significant effects on quality of life, sense of coherence or psychiatric symptoms were found, likely due to limitations in the design and methodology of this specific trial in combination to the heterogeneity of the group. Individuals with ASD may require interventions that are flexible and individually tailored in regard to both format, content and therapeutic support. The current trial provides useful information and suggestions for the future research on internet-based interventions for ASD.

Animacy Processing in Autism: Event-Related Potentials Reflect Social Functioning Skills

Though previous studies with autistic individuals have provided behavioral evidence of animacy perception difficulties, the spatio-temporal dynamics of animacy processing in autism remain underexplored. This study investigated how animacy is neurally encoded in autistic adults, and whether potential deficits in animacy processing have cascading deleterious effects on their social functioning skills. We employed a picture naming paradigm that recorded accuracy and response latencies to animate and inanimate pictures in young autistic adults and age- and IQ-matched healthy individuals, while also employing high-density EEG analysis to map the spatio-temporal dynamics of animacy processing. Participants' social skills were also assessed through a social comprehension task. The autistic adults exhibited lower accuracy than controls on the animate pictures of the task and also exhibited altered brain responses, including larger and smaller N100 amplitudes than controls on inanimate and animate stimuli, respectively. At late stages of processing, there were shorter slow negative wave latencies for the autistic group as compared to controls for the animate trials only. The autistic individuals' altered brain responses negatively correlated with their social difficulties. The results suggest deficits in brain responses to animacy in the autistic group, which were related to the individuals' social functioning skills.

Diversity and Classification of Genetic Variations in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition with symptoms that affect the whole personality and all aspects of life. Although there is a high degree of heterogeneity in both its etiology and its characteristic behavioral patterns, the disorder is well-captured along the autistic triad. Currently, ASD status can be confirmed following an assessment of behavioral features, but there is a growing emphasis on conceptualizing autism as a spectrum, which allows for establishing a diagnosis based on the level of support need, free of discrete categories. Since ASD has a high genetic predominance, the number of genetic variations identified in the background of the condition is increasing exponentially as genetic testing methods are rapidly evolving. However, due to the huge amount of data to be analyzed, grouping the different DNA variations is still challenging. Therefore, in the present review, a multidimensional classification scheme was developed to accommodate most of the currently known genetic variants associated with autism. Genetic variations have been grouped according to six criteria (extent, time of onset, information content, frequency, number of genes involved, inheritance pattern), which are themselves not discrete categories, but form a coherent continuum in line with the autism spectrum approach.

The Neurogenetics of Functional Connectivity Alterations in Autism: Insights From Subtyping in 657 Individuals

BACKGROUND

There is little consensus and controversial evidence on anatomical alterations in the brains of people with autism spectrum disorder (ASD), due in part to the large heterogeneity present in ASD, which in turn is a major drawback for developing therapies. One strategy to characterize this heterogeneity in ASD is to cluster large-scale functional brain connectivity profiles.

METHODS

A subtyping approach based on consensus clustering of functional brain connectivity patterns was applied to a population of 657 autistic individuals with quality-assured neuroimaging data. We then used high-resolution gene transcriptomic data to characterize the molecular mechanism behind each subtype by performing enrichment analysis of the set of genes showing a high spatial similarity with the profiles of functional connectivity alterations between each subtype and a group of typically developing control participants.

RESULTS

Two major stable subtypes were found: subtype 1 exhibited hypoconnectivity (less average connectivity than typically developing control participants) and subtype 2, hyperconnectivity. The 2 subtypes did not differ in structural imaging metrics in any of the analyzed regions (68 cortical and 14 subcortical) or in any of the behavioral scores (including IQ, Autism Diagnostic Interview, and Autism Diagnostic Observation Schedule). Finally, only subtype 2, comprising about 43% of ASD participants, led to significant enrichments after multiple testing corrections. Notably, the dominant enrichment corresponded to excitation/inhibition imbalance, a leading well-known primary mechanism in the pathophysiology of ASD.

CONCLUSIONS

Our results support a link between excitation/inhibition imbalance and functional connectivity alterations, but only in one ASD subtype, overall characterized by brain hyperconnectivity and major alterations in somatomotor and default mode networks.

Conceptualization of the latent structure of autism: further evidence and discussion of dimensional and hybrid models

Autism spectrum disorder (ASD) might be conceptualized as an essentially dimensional, categorical, or hybrid model. Yet, current empirical studies are inconclusive and the latent structure of ASD has explicitly been examined only in a few studies. The aim of our study was to identify and discuss the latent model structure of behavioral symptoms related to ASD and to address the question of whether categories and/or dimensions best represent ASD symptoms. We included data of 2920 participants (1-72 years of age), evaluated with the Autism Diagnostic Observation Schedule (Modules 1-4). We applied latent class analysis, confirmatory factor analysis, and factor mixture modeling and evaluated the model fit by a combination of criteria. Based on the model selection criteria, the model fits, the interpretability as well as the clinical utility we conclude that the hybrid model serves best for conceptualization and assessment of ASD symptoms. It is both grounded in empirical evidence and in clinical usefulness, is in line with the current classification system (DSM-5) and has the potential of being more specific than the dimensional approach (decreasing false positive diagnoses).

Autism spectrum disorder prevalence in Italy: a nationwide study promoted by the Ministry of Health

BACKGROUND

This nationwide study aimed to estimate Autism Spectrum Disorder (ASD) prevalence in 7-9-year-old Italian children. Promoted by Italy's Ministry of Health and coordinated by the National Observatory for Autism at the National Institute of Health, it covered schools in northern (Lecco and Monza-Brianza), central (Rome and its province), and southern (Palermo and its province) regions from February 24, 2016, to February 23, 2018, using a multi-stage approach defined by the European Union's ASD network.

METHODS

Phase one identified ASD-diagnosed children in mainstream schools through local Ministry of Education (MoE) disability registries. Phase two had a subset of schools screen 7-9-year-olds using the Social Communication Questionnaire-Life version (SCQ-L). Those with SCQ-L scores of 15 + underwent clinical consultation for ASD symptoms, cognitive abilities, and life skills. To counter potential false negatives, 20% scoring 11-14 were randomly assessed via Autism Diagnostic Interview-Revised (ADI-R).

RESULTS

MoE data revealed 9.8 per 1000 certified ASD children in the north, 12.2 in the central, and 10.3 in the south. In phase two, 35,823 SCQ-L questionnaires were distributed across 198 schools (northern: 11,190 in 49 schools, central: 13,628 in 87 schools, southern: 11,005 in 62 schools). Of SCQ-L respondents, 2.4% (n = 390) scored above the 15 cutoff. Among these, 100 had ASD diagnoses, and 50 had other diagnoses. Among 115 families assessed, 16.5% (n = 19) received ASD diagnoses.

CONCLUSIONS

The estimated prevalence of ASD in Italy was 13.4 (11.3-16.0) per 1,000 children aged 7-9 years, with a male-to-female ratio of 4.4:1. It will guide national policies in enhancing services tailored to the specific needs of autistic children.

Impaired white matter integrity in infants and young children with autism spectrum disorder: What evidence does diffusion tensor imaging provide?

BACKGROUND

Abnormal functional connections are associated with impaired white matter tract integrity in the brain. Diffusion tensor imaging (DTI) is a promising method for evaluating white matter integrity in infants and young children. This work aims to shed light on the location and nature of the decrease in white matter integrity.

METHODS

Here, the results of 19 studies have been presented that investigated white matter integrity in infants and young children (6 months to 12 years) with autism using diffusion tensor imaging.

RESULTS

In most of the reviewed studies, an increase in Fractional Anisotropy (FA) and a decrease in Radial Diffusivity (RD) were reported in Corpus Callosum (CC), Uncinate Fasciculus (UF), Cingulum (Cg), Inferior Longitudinal Fasciculus (ILF), and Superior Longitudinal Fasciculus (SLF), and in the Inferior Fronto-Occipital Fasciculus (IFOF) tract, a decrease in FA and an increase in RD were reported.

CONCLUSION

In the reviewed articles, except for one study, the diffusion indices were different compared to the control group.

Differentiated, rather than shared, strategies for time-coordinated action in social and non-social domains in autistic individuals

Autism spectrum disorder (ASD) is a neurodevelopmental condition with a highly heterogeneous adult phenotype that includes social and non-social behavioral characteristics. The link between the characteristics assignable to the different domains remains unresolved. One possibility is that social and non-social behaviors in autism are modulated by a common underlying deficit. However, here we report evidence supporting an alternative concept that is individual-centered rather than deficit-centered. Individuals are assumed to have a distinctive style in the strategies they adopt to perform social and non-social tasks with these styles presumably being structured differently between autistic individuals and typically-developed (TD) individuals. We tested this hypothesis for the execution of time-coordinated (synchronized) actions. Participants performed (i) a social task that required synchronized gaze and pointing actions to interact with another person, and (ii) a non-social task that required finger-tapping actions synchronized to periodic stimuli at different time-scales and sensory modalities. In both tasks, synchronization behavior differed between ASD and TD groups. However, a principal component analysis of individual behaviors across tasks revealed associations between social and non-social features for the TD persons but such cross-domain associations were strikingly absent for autistic individuals. The highly differentiated strategies between domains in ASD are inconsistent with a general synchronization deficit and instead highlight the individualized developmental heterogeneity in the acquisition of domain-specific behaviors. We propose a cognitive model to help disentangle individual-centered from deficit-centered effects in other domains. Our findings reinforce the importance to identify individually differentiated phenotypes to personalize autism therapies.

Comorbidities Affecting Children with Autism Spectrum Disorder: A Retrospective Chart Review

Autism spectrum disorder (ASD) is a developmental disorder characterized by deficits in social interaction/communication, restricted interests, and repetitive behaviors. Recent discussions have emerged worldwide regarding the heterogeneity around presentation/etiology and comorbidities. This study aimed to determine the frequency and characteristics of comorbidities among children diagnosed with ASD in Manitoba and to evaluate differences in presentation between those with and without medical comorbidities. We conducted a retrospective chart review of >1900 electronic charts at the only publicly funded referral site for children ≤6 years requiring evaluation for ASD in Manitoba. All children aged 0-6 years diagnosed with ASD at this site between May 2016 and September 2021 were identified. χ2 and t-tests were used to compare groups. Of the total of 1858 children identified, 1452 (78.1%) were boys, 251 (13.5%) were prematurely born, and 539 (29.0%) had ≥1 medical comorbidity. Global developmental delay (GDD) was diagnosed in 428 (23.0%). The age of referral and diagnosis did not differ between groups. Comorbidities were more common among premature children (16.0% vs. 12.5%, p: 0.005) and children with comorbid GDD (34.9% vs. 18.2%, p < 0.001). Neurological comorbidities were most common (37.1%). No sex difference in the overall presence of comorbidities was found (boys = 77.1% vs. 78.5%, p: 0.518); however, girls had a higher incidence of neurological comorbidities, e.g., cerebral palsy, seizures, hypotonia (14.8% vs. 9.64%, p: 0.009), as well as genetic comorbidities (4.92% vs. 2.75%, p: 0.04). The high rates of associated neurological conditions, GDD, and prematurity add heterogeneity to this group leading to potential difficulties with prognosis and service allocation. Primary vs. secondary ASD can be a way of separating individuals based on relevant medical comorbidities.

Prioritizing genes associated with brain disorders by leveraging enhancer-promoter interactions in diverse neural cells and tissues

BACKGROUND

Prioritizing genes that underlie complex brain disorders poses a considerable challenge. Despite previous studies have found that they shared symptoms and heterogeneity, it remained difficult to systematically identify the risk genes associated with them.

METHODS

By using the CAGE (Cap Analysis of Gene Expression) read alignment files for 439 human cell and tissue types (including primary cells, tissues and cell lines) from FANTOM5 project, we predicted enhancer-promoter interactions (EPIs) of 439 cell and tissue types in human, and examined their reliability. Then we evaluated the genetic heritability of 17 diverse brain disorders and behavioral-cognitive phenotypes in each neural cell type, brain region, and developmental stage. Furthermore, we prioritized genes associated with brain disorders and phenotypes by leveraging the EPIs in each neural cell and tissue type, and analyzed their pleiotropy and functionality for different categories of disorders and phenotypes. Finally, we characterized the spatiotemporal expression dynamics of these associated genes in cells and tissues.

RESULTS

We found that identified EPIs showed activity specificity and network aggregation in cell and tissue types, and enriched TF binding in neural cells played key roles in synaptic plasticity and nerve cell development, i.e., EGR1 and SOX family. We also discovered that most neurological disorders exhibit heritability enrichment in neural stem cells and astrocytes, while psychiatric disorders and behavioral-cognitive phenotypes exhibit enrichment in neurons. Furthermore, our identified genes recapitulated well-known risk genes, which exhibited widespread pleiotropy between psychiatric disorders and behavioral-cognitive phenotypes (i.e., FOXP2), and indicated expression specificity in neural cell types, brain regions, and developmental stages associated with disorders and phenotypes. Importantly, we showed the potential associations of brain disorders with brain regions and developmental stages that have not been well studied.

CONCLUSIONS

Overall, our study characterized the gene-enhancer regulatory networks and genetic mechanisms in the human neural cells and tissues, and illustrated the value of reanalysis of publicly available genomic datasets.

The metabolic role of vitamin D in children's neurodevelopment: a network study

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with various proposed environmental risk factors and a rapidly increasing prevalence. Mounting evidence suggests a potential role of vitamin D deficiency in ASD pathogenesis, though the causal mechanisms remain largely unknown. Here we investigate the impact of vitamin D on child neurodevelopment through an integrative network approach that combines metabolomic profiles, clinical traits, and neurodevelopmental data from a pediatric cohort. Our results show that vitamin D deficiency is associated with changes in the metabolic networks of tryptophan, linoleic, and fatty acid metabolism. These changes correlate with distinct ASD-related phenotypes, including delayed communication skills and respiratory dysfunctions. Additionally, our analysis suggests the kynurenine and serotonin sub-pathways may mediate the effect of vitamin D on early childhood communication development. Altogether, our findings provide metabolome-wide insights into the potential of vitamin D as a therapeutic option for ASD and other communication disorders.

Are sleep disturbances a cause or consequence of autism spectrum disorder?

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by core symptoms such as atypical social communication, stereotyped behaviors, and restricted interests. One of the comorbid symptoms of individuals with ASD is sleep disturbance. There are two major hypotheses regarding the neural mechanism underlying ASD, i.e., the excitation/inhibition (E/I) imbalance and the altered neuroplasticity hypotheses. However, the pathology of ASD remains unclear due to inconsistent research results. This paper argues that sleep is a confounding factor, thus, must be considered when examining the pathology of ASD because sleep plays an important role in modulating the E/I balance and neuroplasticity in the human brain. Investigation of the E/I balance and neuroplasticity during sleep might enhance our understanding of the neural mechanisms of ASD. It may also lead to the development of neurobiologically informed interventions to supplement existing psychosocial therapies.

Carving joints into nature: reengineering scientific concepts in light of concept-laden evidence

A new wave of proposals suggests that scientists must reassess scientific concepts in light of accumulated evidence. However, reengineering scientific concepts in light of data is challenging because scientific concepts affect the evidence itself in multiple ways. Among other possible influences, concepts (i) prime scientists to overemphasize within-concept similarities and between-concept differences; (ii) lead scientists to measure conceptually relevant dimensions more accurately; (iii) serve as units of scientific experimentation, communication, and theory-building; and (iv) affect the phenomena themselves. When looking for improved ways to carve nature at its joints, scholars must take the concept-laden nature of evidence into account to avoid entering a vicious circle of concept-evidence mutual substantiation.

A systematic review of non-coding RNA genes with differential expression profiles associated with autism spectrum disorders

AIMS

To identify differential expression of shorter non-coding RNA (ncRNA) genes associated with autism spectrum disorders (ASD).

BACKGROUND

ncRNA are functional molecules that derive from non-translated DNA sequence. The HUGO Gene Nomenclature Committee (HGNC) have approved ncRNA gene classes with alignment to the reference human genome. One subset is microRNA (miRNA), which are highly conserved, short RNA molecules that regulate gene expression by direct post-transcriptional repression of messenger RNA. Several miRNA genes are implicated in the development and regulation of the nervous system. Expression of miRNA genes in ASD cohorts have been examined by multiple research groups. Other shorter classes of ncRNA have been examined less. A comprehensive systematic review examining expression of shorter ncRNA gene classes in ASD is timely to inform the direction of research.

METHODS

We extracted data from studies examining ncRNA gene expression in ASD compared with non-ASD controls. We included studies on miRNA, piwi-interacting RNA (piRNA), small NF90 (ILF3) associated RNA (snaR), small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), transfer RNA (tRNA), vault RNA (vtRNA) and Y RNA. The following electronic databases were searched: Cochrane Library, EMBASE, PubMed, Web of Science, PsycINFO, ERIC, AMED and CINAHL for papers published from January 2000 to May 2022. Studies were screened by two independent investigators with a third resolving discrepancies. Data was extracted from eligible papers.

RESULTS

Forty-eight eligible studies were included in our systematic review with the majority examining miRNA gene expression alone. Sixty-four miRNA genes had differential expression in ASD compared to controls as reported in two or more studies, but often in opposing directions. Four miRNA genes had differential expression in the same direction in the same tissue type in at least 3 separate studies. Increased expression was reported in miR-106b-5p, miR-155-5p and miR-146a-5p in blood, post-mortem brain, and across several tissue types, respectively. Decreased expression was reported in miR-328-3p in bloods samples. Seven studies examined differential expression from other classes of ncRNA, including piRNA, snRNA, snoRNA and Y RNA. No individual ncRNA genes were reported in more than one study. Six studies reported differentially expressed snoRNA genes in ASD. A meta-analysis was not possible because of inconsistent methodologies, disparate tissue types examined, and varying forms of data presented.

CONCLUSION

There is limited but promising evidence associating the expression of certain miRNA genes and ASD, although the studies are of variable methodological quality and the results are largely inconsistent. There is emerging evidence associating differential expression of snoRNA genes in ASD. It is not currently possible to say whether the reports of differential expression in ncRNA may relate to ASD aetiology, a response to shared environmental factors linked to ASD such as sleep and nutrition, other molecular functions, human diversity, or chance findings. To improve our understanding of any potential association, we recommend improved and standardised methodologies and reporting of raw data. Further high-quality research is required to shine a light on possible associations, which may yet yield important information.

Research status and prospects of acupuncture for autism spectrum disorders

Autism spectrum disorder (ASD) is a neurodevelopmental disorder and has a predilection for children. Its symptoms, such as lifelong social communication deficits and repetitive sensory-motor behaviors, put a huge burden on the patient's family and society. Currently, there is no cure for ASD, and some medications that can improve its symptoms are often accompanied by adverse effects. Among many complementary and alternative medicine (CAM) therapies, acupuncture has shown promising application potential, but after years of practice, it has not been recognized as the preferred CAM therapy for ASD. Therefore, we analyzed and discussed the clinical study reports of acupuncture in the treatment of ASD in the past 15 years from the aspects of study subjects, group setting, intervention modalities, acupoint selection, outcome evaluation, and safety. The data accumulated at present are not sufficient to support the clinical effectiveness of acupuncture in ASD and to justify its use in clinical practice. They provide, however, initial evidence of possible effectiveness and encourage further investigation in order to reach firm conclusions. Based on a comprehensive analysis, we believed that following the Standards for Reporting Interventions in Clinical Trials of Acupuncture (STRICTA) and Consolidated Standards of Reporting Trials (CONSORT), screening the optimal combination of acupoints applying a rigorous scientific study design, and performing the related functional experiments may be the effective way to convincingly test the hypothesis that acupuncture may be beneficial in ASD patients. The significance of this review is to provide a reference for researchers to carry out high-quality clinical trials of acupuncture in the treatment of ASD from the perspective of the combination of modern medicine and traditional Chinese medicine.