The Heritability of Autism Spectrum Disorder

Prenatal exposure to valproic acid reduces synaptic δ-catenin levels and disrupts ultrasonic vocalization in neonates

Valproic acid (VPA) is an effective and commonly prescribed drug for epilepsy and bipolar disorder. However, children born from mothers treated with VPA during pregnancy exhibit an increased incidence of autism spectrum disorder (ASD). Although VPA may impair brain development at the cellular level, the mechanism of VPA-induced ASD has not been completely addressed. A previous study has found that VPA treatment strongly reduces δ-catenin mRNA levels in cultured human neurons. δ-catenin is important for the control of glutamatergic synapses and is strongly associated with ASD. VPA inhibits dendritic morphogenesis in developing neurons, an effect that is also found in neurons lacking δ-catenin expression. We thus hypothesize that prenatal exposure to VPA significantly reduces δ-catenin levels in the brain, which impairs glutamatergic synapses to cause ASD. Here, we found that prenatal exposure to VPA markedly reduced δ-catenin levels in the brain of mouse pups. VPA treatment also impaired dendritic branching in developing mouse cortical neurons, which was partially reversed by elevating δ-catenin expression. Prenatal VPA exposure significantly reduced synaptic α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor levels and postsynaptic density 95 (PSD95) in the brain of mouse pups, indicating dysfunctions in glutamatergic synaptic transmission. VPA exposure also significantly altered ultrasonic vocalization (USV) in newly born pups when they were isolated from their nest. Moreover, VPA-exposed pups show impaired hypothalamic response to isolation, which is required to produce animals' USVs following isolation from the nest. Therefore, these results suggest that VPA-induced ASD pathology can be mediated by the loss of δ-catenin functions.

Amino acid transporters in neurological disorders and neuroprotective effects of cysteine derivatives

For most diseases and disorders occurring in the brain, the full causes behind them are yet unknown, but many show signs of dysfunction of amino acid transporters or abnormalities in amino acid metabolism. The blood-brain barrier (BBB) plays a key role in supporting the function of the central nervous system (CNS). Because of its unique structure, the BBB can maintain the optimal environment for CNS by controlling the passage of hydrophilic molecules from blood to the brain. Nutrients, such as amino acids, can cross the BBB via specific transporters. Many amino acids are essential for CNS function, and dysfunction of these amino acid transporters can lead to abnormalities in amino acid levels. This has been linked to causes behind certain genetic brain diseases, such as schizophrenia, autism spectrum disorder, and Huntington's disease (HD). One example of crucial amino acids is L-Cys, the rate-limiting factor in the biosynthesis of an important antioxidant, glutathione (GSH). Deficiency of L-Cys and GSH has been linked to oxidative stress and has been shown as a plausible cause behind certain CNS diseases, like schizophrenia and HD. This review presents the current status of potential L-Cys therapies and gives future directions that can be taken to improve amino acid transportation related to distinct CNS diseases.

Cntnap2 loss drives striatal neuron hyperexcitability and behavioral inflexibility

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by two major diagnostic criteria - persistent deficits in social communication and interaction, and the presence of restricted, repetitive patterns of behavior (RRBs). Evidence from both human and animal model studies of ASD suggest that alteration of striatal circuits, which mediate motor learning, action selection, and habit formation, may contribute to the manifestation of RRBs. CNTNAP2 is a syndromic ASD risk gene, and loss of function of Cntnap2 in mice is associated with RRBs. How loss of Cntnap2 impacts striatal neuron function is largely unknown. In this study, we utilized Cntnap2 -/- mice to test whether altered striatal neuron activity contributes to aberrant motor behaviors relevant to ASD. We find that Cntnap2 -/- mice exhibit increased cortical drive of striatal projection neurons (SPNs), with the most pronounced effects in direct pathway SPNs. This enhanced drive is likely due to increased intrinsic excitability of SPNs, which make them more responsive to cortical inputs. We also find that Cntnap2 -/- mice exhibit spontaneous repetitive behaviors, increased motor routine learning, and cognitive inflexibility. Increased corticostriatal drive, in particular of the direct pathway, may contribute to the acquisition of repetitive, inflexible behaviors in Cntnap2 mice.

Noncoding de novo mutations in SCN2A are associated with autism spectrum disorders

Coding de novo mutations (DNMs) contribute to the risk for autism spectrum disorders (ASD), but the contribution of noncoding DNMs remains relatively unexplored. Here we use whole genome sequencing (WGS) data of 12,411 individuals (including 3,508 probands and 2,218 unaffected siblings) from 3,357 families collected in Simons Foundation Powering Autism Research for Knowledge (SPARK) to detect DNMs associated with ASD, while examining Simons Simplex Collection (SSC) with 6383 individuals from 2274 families to replicate the results. For coding DNMs, SCN2A reached exome-wide significance (p=2.06×10 -11 ) in SPARK. The 618 known dominant ASD genes as a group are strongly enriched for coding DNMs in cases than sibling controls (fold change=1.51, p =1.13×10 -5 for SPARK; fold change=1.86, p =2.06×10 -9 for SSC). For noncoding DNMs, we used two methods to assess statistical significance: a point-based test that analyzes sites with a Combined Annotation Dependent Depletion (CADD) score ≥15, and a segment-based test that analyzes 1kb genomic segments with segment-specific background mutation rates (inferred from expected rare mutations in Gnocchi genome constraint scores). The point-based test identified SCN2A as marginally significant ( p =6.12×10 -4 ) in SPARK, yet segment-based test identified CSMD1 , RBFOX1 and CHD13 as exome-wide significant. We did not identify significant enrichment of noncoding DNMs (in all 1kb segments or those with Gnocchi>4) in the 618 known ASD genes as a group in cases than sibling controls. When combining evidence from both coding and noncoding DNMs, we found that SCN2A with 11 coding and 5 noncoding DNMs exhibited the strongest significance (p=4.15×10 -13 ). In summary, we identified both coding and noncoding DNMs in SCN2A associated with ASD, while nominating additional candidates for further examination in future studies.

Dimensional Neuroimaging Endophenotypes: Neurobiological Representations of Disease Heterogeneity Through Machine Learning

Machine learning has been increasingly used to obtain individualized neuroimaging signatures for disease diagnosis, prognosis, and response to treatment in neuropsychiatric and neurodegenerative disorders. Therefore, it has contributed to a better understanding of disease heterogeneity by identifying disease subtypes with different brain phenotypic measures. In this Review, we first present a systematic literature overview of studies using machine learning and multimodal MRI to unravel disease heterogeneity in various neuropsychiatric and neurodegenerative disorders, including Alzheimer's disease, schizophrenia, major depressive disorder, autism spectrum disorder, multiple sclerosis, as well as their potential in a transdiagnostic framework, where neuroanatomical and neurobiological commonalities were assessed across diagnostic boundaries. Subsequently, we summarize relevant machine learning methodologies and their clinical interpretability. We discuss the potential clinical implications of the current findings and envision future research avenues. Finally, we discuss an emerging paradigm called dimensional neuroimaging endophenotypes (DNE). DNE dissects the neurobiological heterogeneity of neuropsychiatric and neurodegenerative disorders into low-dimensional yet informative, quantitative brain phenotypic representations, serving as robust intermediate phenotypes (i.e., endophenotypes) presumably reflecting the interplay of underlying genetic, lifestyle, and environmental processes associated with the disease etiology.

Functional connectivity in autism spectrum disorder evaluated using rs-fMRI and DKI

We evaluated functional connectivity (FC) in patients with adult autism spectrum disorder (ASD) using resting-state functional MRI (rs-fMRI) and diffusion kurtosis imaging (DKI). We acquired rs-fMRI data from 33 individuals with ASD and 33 healthy controls (HC) and DKI data from 18 individuals with ASD and 17 HC. ASD showed attenuated FC between the right frontal pole (FP) and the bilateral temporal fusiform cortex (TFusC) and enhanced FC between the right thalamus and the bilateral inferior division of lateral occipital cortex, and between the cerebellar vermis and the right occipital fusiform gyrus (OFusG) and the right lingual gyrus, compared with HC. ASD demonstrated increased axial kurtosis (AK) and mean kurtosis (MK) in white matter (WM) tracts, including the right anterior corona radiata (ACR), forceps minor (FM), and right superior longitudinal fasciculus (SLF). In ASD, there was also a significant negative correlation between MK and FC between the cerebellar vermis and the right OFusG in the corpus callosum, FM, right SLF and right ACR. Increased DKI metrics might represent neuroinflammation, increased complexity, or disrupted WM tissue integrity that alters long-distance connectivity. Nonetheless, protective or compensating adaptations of inflammation might lead to more abundant glial cells and cytokine activation effectively alleviating the degeneration of neurons, resulting in increased complexity. FC abnormality in ASD observed in rs-fMRI may be attributed to microstructural alterations of the commissural and long-range association tracts in WM as indicated by DKI.

Association between parental psychiatric disorders and risk of offspring autism spectrum disorder: a Swedish and Finnish population-based cohort study

Background

Roughly more than one in six adults worldwide suffer from psychiatric conditions. Sporadic studies have associated parental psychiatric disorders with autism spectrum disorder in offspring. Comprehensively examining the association between parental psychiatric disorders and offspring autism spectrum disorder is needed to guide health policies, and to inform etiologic studies.

Methods

We included all children born in Sweden and Finland 1997-2016. Diagnoses were clinically ascertained from National Registers through 2017. We calculated adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for autism spectrum disorder in offspring of fathers and mothers with psychiatric disorders, in both parents jointly and across co-occurring conditions.

Findings

Among 2,505,842 children, 33,612 were diagnosed with autism spectrum disorder, of which 20% had a parent with psychiatric disorders. The risk of autism spectrum disorder was increased across all psychiatric disorders in fathers (Sweden: aHR = 2.02, 95% CI = 1.92-2.12; Finland: aHR = 1.63, 95% CI = 1.50-1.77), mothers (Sweden: aHR = 2.34, 95% CI = 2.24-2.43; Finland aHR = 2.12, 95% CI = 1.92-2.28), or both parents (Sweden: aHR = 3.76, 95% CI = 3.48-4.07; Finland aHR = 3.61, 95% CI = 3.20-4.07), compared to neither parents. Co-occurrence of parental psychiatric disorders further increased risk (e.g., Sweden: for one, two or ≥three different diagnostic categories compared to no diagnosis, in fathers aHR = 1.81, 2.07, 2.52; in mothers aHR = 2.05, 2.63, 3.57).

Interpretation

Psychiatric disorders in both parents conveyed the highest risk of offspring autism spectrum disorder, followed by mothers and then fathers. The risk increased with number of co-occurring disorders. All parental psychiatric disorders were associated with increased the risk of autism spectrum disorder. To reliably assess the risk of autism spectrum disorder in children, a comprehensive history incorporating the full range of parental psychiatric disorders is needed beyond solely focusing on familial autism spectrum disorder.

Funding

Swedish-Research-Council-2021-0214.

Examining Sex Differences in Autism Heritability

Importance

Autism spectrum disorder (ASD) is a neurodevelopmental disorder more prevalent in males than in females. The cause of ASD is largely genetic, but the association of genetics with the skewed sex ratio is not yet understood. To our knowledge, no large population-based study has provided estimates of heritability by sex.

Objective

To estimate the sex-specific heritability of ASD.

Design, Setting, and Participants

This was a population-based, retrospective analysis using national health registers of nontwin siblings and cousins from Sweden born between January 1, 1985, and December 31, 1998, with follow-up to 19 years of age. Data analysis occurred from August 2022 to November 2023.

Main Outcomes and Measures

Models were fitted to estimate the relative variance in risk for ASD occurrence owing to sex-specific additive genetics, shared environmental effects, and a common residual term. The residual term conceptually captured other factors that promote individual behavioral variation (eg, maternal effects, de novo variants, rare genetic variants not additively inherited, or gene-environment interactions). Estimates were adjusted for differences in prevalence due to birth year and maternal and paternal age by sex.

Results

The sample included 1 047 649 individuals in 456 832 families (538 283 males [51.38%]; 509 366 females [48.62%]). Within the entire sample, 12 226 (1.17%) received a diagnosis of ASD, comprising 8128 (1.51%) males and 4098 (0.80%) females. ASD heritability was estimated at 87.0% (95% CI, 81.4%-92.6%) for males and 75.7% (95% CI, 68.4%-83.1%) for females with a difference in heritability estimated at 11.3% (95% CI, 1.0%-21.6%). There was no support for shared environmental contributions.

Conclusions and Relevance

These findings suggest that the degree of phenotypic variation attributable to genetic differences (heritability) differs between males and females, indicating that some of the underlying causes of the condition may differ between the 2 sexes. The skewed sex ratio in ASD may be partly explained by differences in genetic variance between the sexes.

Exploring genetic testing requests, genetic alterations and clinical associations in a cohort of children with autism spectrum disorder

Several studies show great heterogeneity in the type of genetic test requested and in the clinicopathological characteristics of patients with ASD. The following study aims, firstly, to explore the factors that might influence professionals' decisions about the appropriateness of requesting genetic testing for their patients with ASD and, secondly, to determine the prevalence of genetic alterations in a representative sample of children with a diagnosis of ASD. Methods: We studied the clinical factors associated with the request for genetic testing in a sample of 440 children with ASD and the clinical factors of present genetic alterations. Even though the main guidelines recommend genetic testing all children with an ASD diagnosis, only 56% of children with an ASD diagnosis were genetically tested. The prevalence of genetic alterations was 17.5%. These alterations were more often associated with intellectual disability and dysmorphic features. There are no objective data to explicitly justify the request for genetic testing, nor are there objective data to justify requesting one genetic study versus multiple studies. Remarkably, only 28% of males were genetically tested with the recommended tests (fragile X and CMA). Children with dysmorphic features and organic comorbidities were more likely to be genetic tested than those without. Previous diagnosis of ASD (family history of ASD) and attendance at specialist services were also associated with Genetically tested Autism Spectrum Disorder GTASD. Our findings emphasize the importance of establishing algorithms to facilitate targeted genetic consultation for individuals with ASD who are likely to benefit, considering clinical phenotypes, efficiency, ethics, and benefits.

Identification of moderate effect size genes in autism spectrum disorder through a novel gene pairing approach

Autism Spectrum Disorder (ASD) arises from complex genetic and environmental factors, with inherited genetic variation playing a substantial role. This study introduces a novel approach to uncover moderate effect size (MES) genes in ASD, which individually do not meet the ASD liability threshold but collectively contribute when paired with specific other MES genes. Analyzing 10,795 families from the SPARK dataset, we identified 97 MES genes forming 50 significant gene pairs, demonstrating a substantial association with ASD when considered in tandem, but not individually. Our method leverages familial inheritance patterns and statistical analyses, refined by comparisons against control cohorts, to elucidate these gene pairs' contribution to ASD liability. Furthermore, expression profile analyses of these genes in brain tissues underscore their relevance to ASD pathology. This study underscores the complexity of ASD's genetic landscape, suggesting that gene combinations, beyond high impact single-gene mutations, significantly contribute to the disorder's etiology and heterogeneity. Our findings pave the way for new avenues in understanding ASD's genetic underpinnings and developing targeted therapeutic strategies.

Roles of Epigenetics and Glial Cells in Drug-Induced Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by severe deficits in social communication and interaction, repetitive movements, abnormal focusing on objects, or activity that can significantly affect the quality of life of the afflicted. Neuronal and glial cells have been implicated. It has a genetic component but can also be triggered by environmental factors or drugs. For example, prenatal exposure to valproic acid or acetaminophen, or ingestion of propionic acid, can increase the risk of ASD. Recently, epigenetic influences on ASD have come to the forefront of investigations on the etiology, prevention, and treatment of this disorder. Epigenetics refers to DNA modifications that alter gene expression without making any changes to the DNA sequence. Although an increasing number of pharmaceuticals and environmental chemicals are being implicated in the etiology of ASD, here, we specifically focus on the molecular influences of the abovementioned chemicals on epigenetic alterations in neuronal and glial cells and their potential connection to ASD. We conclude that a better understanding of these phenomena can lead to more effective interventions in ASD.

Etiologic Evaluation of Children with Autism Spectrum Disorder

Autism spectrum disorder (ASD) is clinically and etiologically heterogeneous. A causal genetic variant can be identified in approximately 20% to 25% of affected individuals with current clinical genetic testing, and all patients with an ASD diagnosis should be offered genetic etiologic evaluation. We suggest that exome sequencing with copy number variant coverage should be the first-line etiologic evaluation for ASD. Neuroimaging, neurophysiologic, metabolic, and other biochemical evaluations can provide insight into the pathophysiology of ASD but should be recommended in the appropriate clinical circumstances.

Autophagy in neural stem cells and glia for brain health and diseases

Autophagy is a multifaceted cellular process that not only maintains the homeostatic and adaptive responses of the brain but is also dynamically involved in the regulation of neural cell generation, maturation, and survival. Autophagy facilities the utilization of energy and the microenvironment for developing neural stem cells. Autophagy arbitrates structural and functional remodeling during the cell differentiation process. Autophagy also plays an indispensable role in the maintenance of stemness and homeostasis in neural stem cells during essential brain physiology and also in the instigation and progression of diseases. Only recently, studies have begun to shed light on autophagy regulation in glia (microglia, astrocyte, and oligodendrocyte) in the brain. Glial cells have attained relatively less consideration despite their unquestioned influence on various aspects of neural development, synaptic function, brain metabolism, cellular debris clearing, and restoration of damaged or injured tissues. Thus, this review composes pertinent information regarding the involvement of autophagy in neural stem cells and glial regulation and the role of this connexion in normal brain functions, neurodevelopmental disorders, and neurodegenerative diseases. This review will provide insight into establishing a concrete strategic approach for investigating pathological mechanisms and developing therapies for brain diseases.

Cerebellar phenotypes in germline PTEN mutation carriers

PTEN hamartoma tumour syndrome (PHTS) comprises different hereditary conditions caused by germline PTEN mutations, predisposing to the development of multiple hamartomas in many body tissues and also increasing the risk of some types of cancer. Cerebellar involvement in PHTS patients has been long known due to the development of a pathognomonic cerebellar hamartoma (known as dysplastic gangliocytoma of the cerebellum or Lhermitte-Duclos disease). Recently, a crucial role of the cerebellum has been highlighted in the pathogenesis of autism spectrum disorders, now recognised as a phenotype expressed in a variable percentage of PHTS children. In addition, rare PTEN variants are indeed identified in medulloblastoma as well, even if they are less frequent than other germline gene mutations. The importance of PTEN and its downstream signalling enzymatic pathways, PI3K/AKT/mTOR, has been studied at different levels in both human clinical settings and animal models, not only leading to a better understanding of the pathogenesis of different disorders but, most importantly, to identify potential targets for specific therapies. In particular, PTEN integrity makes an important contribution to the normal development of tissue architecture in the nervous system, including the cerebellum. Thus, in patients with PTEN germline mutations, the cerebellum is an affected organ that is increasingly recognised in different disorders, whereas, in animal models, cerebellar Pten loss causes a variety of functional and histological alterations. In this review, we summarise the range of cerebellar involvement observed in PHTS and its relationships with germline PTEN mutations, along with the phenotypes expressed by murine models with PTEN deficiency in cerebellar tissue.

Differential cognitive and behavioral development from 6 to 24 months in autism and fragile X syndrome

BACKGROUND

Specifying early developmental differences among neurodevelopmental disorders with distinct etiologies is critical to improving early identification and tailored intervention during the first years of life. Recent studies have uncovered important differences between infants with fragile X syndrome (FXS) and infants with familial history of autism spectrum disorder who go on to develop autism themselves (FH-ASD), including differences in brain development and behavior. Thus far, there have been no studies longitudinally investigating differential developmental skill profiles in FXS and FH-ASD infants.

METHODS

The current study contrasted longitudinal trajectories of verbal (expressive and receptive language) and nonverbal (gross and fine motor, visual reception) skills in FXS and FH-ASD infants, compared to FH infants who did not develop ASD (FH-nonASD) and typically developing controls.

RESULTS

Infants with FXS showed delays on a nonverbal composite compared to FH-ASD (as well as FH-nonASD and control) infants as early as 6 months of age. By 12 months an ordinal pattern of scores was established between groups on all domains tested, such that controls > FH-nonASD > FH-ASD > FXS. This pattern persisted through 24 months. Cognitive level differentially influenced developmental trajectories for FXS and FH-ASD.

CONCLUSIONS

Our results demonstrate detectable group differences by 6 months between FXS and FH-ASD as well as differential trajectories on each domain throughout infancy. This work further highlights an earlier onset of global cognitive delays in FXS and, conversely, a protracted period of more slowly emerging delays in FH-ASD. Divergent neural and cognitive development in infancy between FXS and FH-ASD contributes to our understanding of important distinctions in the development and behavioral phenotype of these two groups.

What do parents of nonverbal and minimally verbal autistic children think about genomic autism research?

LAY ABSTRACT

In Summer 2021, a genomic study of autism, Spectrum 10 K, was paused due to backlash from the autistic and autism communities. This raised important questions about how these communities perceive genomic research. The Personal Experiences of Autism and Perceptions of DNA-based research study was established to address this issue among a range of sub-groups within these communities. Twenty parents of nonverbal or minimally verbal autistic children took part in the current study. Data were provided in diverse formats including online interviews, telephone interviews, and writing. This approach was co-produced with autistic experts by experience and involved a parent of a minimally verbal autistic child. Data were analysed using reflexive Thematic Analysis. We found that participants were supportive of autism research, including some genomic research, as long as it is designed to support autistic people and is ethical and transparent. However, while some believed that polygenic scores, genomic predictors of the statistical probability of being autistic, would be helpful, others argued that this would only be true in an ideal world and that the world is too far from ideal. Participants felt excluded from the autistic and autism communities and that the dominant voices in those communities do not represent them or their children. We concluded that genomic researchers need to work with the autistic and autism communities to design future work, and that it is important to ensure a representative range of voices are heard.

White matter development and language abilities during infancy in autism spectrum disorder

White matter (WM) fiber tract differences are present in autism spectrum disorder (ASD) and could be important markers of behavior. One of the earliest phenotypic differences in ASD are language atypicalities. Although language has been linked to WM in typical development, no work has evaluated this association in early ASD. Participants came from the Infant Brain Imaging Study and included 321 infant siblings of children with ASD at high likelihood (HL) for developing ASD; 70 HL infants were later diagnosed with ASD (HL-ASD), and 251 HL infants were not diagnosed with ASD (HL-Neg). A control sample of 140 low likelihood infants not diagnosed with ASD (LL-Neg) were also included. Infants contributed expressive language, receptive language, and diffusion tensor imaging data at 6-, 12-, and 24 months. Mixed effects regression models were conducted to evaluate associations between WM and language trajectories. Trajectories of microstructural changes in the right arcuate fasciculus were associated with expressive language development. HL-ASD infants demonstrated a different developmental pattern compared to the HL-Neg and LL-Neg groups, wherein the HL-ASD group exhibited a positive association between WM fractional anisotropy and language whereas HL-Neg and LL-Neg groups showed weak or no association. No other fiber tracts demonstrated significant associations with language. In conclusion, results indicated arcuate fasciculus WM is linked to language in early toddlerhood for autistic toddlers, with the strongest associations emerging around 24 months. To our knowledge, this is the first study to evaluate associations between language and WM development during the pre-symptomatic period in ASD.

Topologically associating domains define the impact of de novo promoter variants on autism spectrum disorder risk

Whole-genome sequencing (WGS) studies of autism spectrum disorder (ASD) have demonstrated the roles of rare promoter de novo variants (DNVs). However, most promoter DNVs in ASD are not located immediately upstream of known ASD genes. In this study analyzing WGS data of 5,044 ASD probands, 4,095 unaffected siblings, and their parents, we show that promoter DNVs within topologically associating domains (TADs) containing ASD genes are significantly and specifically associated with ASD. An analysis considering TADs as functional units identified specific TADs enriched for promoter DNVs in ASD and indicated that common variants in these regions also confer ASD heritability. Experimental validation using human induced pluripotent stem cells (iPSCs) showed that likely deleterious promoter DNVs in ASD can influence multiple genes within the same TAD, resulting in overall dysregulation of ASD-associated genes. These results highlight the importance of TADs and gene-regulatory mechanisms in better understanding the genetic architecture of ASD.

Ultrafine particulate matter exposure during second year of life, but not before, associated with increased risk of autism spectrum disorder in BKMR mixtures model of multiple air pollutants

Prenatal and early postnatal air pollution exposures have been shown to be associated with autism spectrum disorder (ASD) risk but results regarding specific air pollutants and exposure timing are mixed and no study has investigated the effects of combined exposure to multiple air pollutants using a mixtures approach. We aimed to evaluate prenatal and early life multipollutant mixtures for the drivers of associations of air pollution with ASD. This study examined 484 typically developing (TD) and 660 ASD children from the CHARGE case-control study. Daily air concentrations for NO2, O3, ultrafine (PM0.1), fine (PM0.1-2.5), and coarse (PM2.5-10) particles were predicted from chemical transport models with statistical bias adjustment based on ground-based monitors. Daily averages were calculated for each exposure period (pre-pregnancy, each trimester of pregnancy, first and second year of life) between 2000 and 2016. Air pollution variables were natural log-transformed and then standardized. Individual and joint effects of pollutant exposure with ASD, and potential interactions, were evaluated for each period using hierarchical Bayesian Kernel Machine Regression (BKMR) models, with three groups: PM size fractions (PM0.1, PM0.1-2.5, PM2.5-10), NO2, and O3. In BKMR models, the PM group was associated with ASD in year 2 (group posterior inclusion probability (gPIP) = 0.75), and marginally associated in year 1 (gPIP = 0.497). PM2.5-10 appeared to drive the association (conditional PIP (cPIP) = 0.64) in year 1, while PM0.1 appeared to drive the association in year 2 (cPIP = 0.76), with both showing a moderately strong increased risk. Pre-pregnancy O3 showed a slight J-shaped risk of ASD (gPIP = 0.55). No associations were observed for exposures during pregnancy. Pre-pregnancy O3 and year 2 p.m.0.1 exposures appear to be associated with an increased risk of ASD. Future research should examine ultrafine particulate matter in relation to ASD.

Mother and child mental health over time in children with Autism and/or ADHD in the Longitudinal Study of Australian Children

This study utilised a longitudinal population-based study to explore mother and child mental health trajectories over time from child age 0 to 14 years, between children with ASD, ADHD, or ASD + ADHD. It explored whether a bidirectional relationship between mother psychological distress and child emotional and behavioural problems (EBPs) existed. The birth cohort from the Longitudinal Study of Australian Children was used. Child EBPs were assessed using the Strengths and Difficulties Questionnaire; and mother emotional distress using the Kessler K6. Generalised estimating equations and structured equation modelling was used to understand changes over time, differences between groups and bidirectional relationships. As expected, children with ASD, ADHD or ASD + ADHD had higher EBPs than children without, and their mothers had higher levels of psychological distress across most time points, but with differing trajectories. Mothers of children with ASD (with or without ADHD) showed increasing psychological distress over time, while mothers of children with ADHD had reducing distress. The bidirectional relationship between mother and child mental health found in children without diagnoses was only partially present in children with ASD/ADHD. Findings highlight support needs and discuss implications for transactional models of parent/child emotional problems in children with neurodevelopmental disorders.

Gating of Social Behavior by Inhibitory Inputs from Hippocampal CA1 to Retrosplenial Agranular Cortex

The retrosplenial cortex has been implicated in processing sensory information and spatial learning, with abnormal neural activity reported in association with psychedelics and in mouse and non-human primate models of autism spectrum disorders (ASDs). The direct role of the retrosplenial cortex in regulating social behaviors remains unclear. In this work, we reveal that neural activity in the retrosplenial agranular cortex (RSA), a subregion of the retrosplenial cortex, is initially activated, then quickly suppressed upon social contact. This up-down phase of RSA neurons is crucial for normal social behaviors. Parvalbumin-positive GABAergic neurons in the hippocampal CA1 region were found to send inhibitory projections to the RSA. Blocking these CA1-RSA inhibitory inputs significantly impaired social behavior. Notably, enhancing the CA1-RSA inhibitory input rescued the social behavior defects in an ASD mouse model. This work suggests a neural mechanism for the salience processing of social behavior and identifies a potential target for ASD intervention using neural modulation approaches.

Age effects on autism heritability and etiological stability of autistic traits

BACKGROUND

Autism and autistic traits onset in childhood but persist into adulthood. Little is known about how genetic and environmental factors influence autism and autistic traits into adulthood. We aimed to determine age effects on the heritability of clinically diagnosed autism and the etiological stability of autistic traits from childhood to adulthood using twin methods.

METHODS

From 23,849 twin pairs in the Swedish Twin Register born between 1959 and 2010, we identified 485 individuals (1.01%, 31.5% female) with a clinical autism diagnosis. We estimated and compared the relative contribution of genetic, shared, and nonshared environmental influences to autism in childhood and adulthood. We further used multivariate twin analysis with four measurement points among 1,348 twin pairs in the longitudinal Twin Study of Child and Adolescent Development to assess the phenotypic and etiological stability of autistic traits - measured with three scales from the Child Behavior Checklist - from childhood to adulthood.

RESULTS

Autism heritability was comparable from childhood, (96% [95% CI, 76-99%]) to adulthood (87% [67-96%]). Autistic traits were moderately stable (phenotypic correlation = 0.35-0.61) from childhood to adulthood, and their heritability varied between 52 and 71%. We observed stable as well as newly emerging genetic influences on autistic traits from ages 8-9 to 19-20, and unique nonshared environmental influences at each age.

CONCLUSIONS

Genetic factors are important for autism and autistic traits in adulthood and separate genetic studies in adults are warranted.

Dimensional Neuroimaging Endophenotypes: Neurobiological Representations of Disease Heterogeneity Through Machine Learning

Machine learning has been increasingly used to obtain individualized neuroimaging signatures for disease diagnosis, prognosis, and response to treatment in neuropsychiatric and neurodegenerative disorders. Therefore, it has contributed to a better understanding of disease heterogeneity by identifying disease subtypes that present significant differences in various brain phenotypic measures. In this review, we first present a systematic literature overview of studies using machine learning and multimodal MRI to unravel disease heterogeneity in various neuropsychiatric and neurodegenerative disorders, including Alzheimer's disease, schizophrenia, major depressive disorder, autism spectrum disorder, multiple sclerosis, as well as their potential in transdiagnostic settings. Subsequently, we summarize relevant machine learning methodologies and discuss an emerging paradigm which we call dimensional neuroimaging endophenotype (DNE). DNE dissects the neurobiological heterogeneity of neuropsychiatric and neurodegenerative disorders into a low-dimensional yet informative, quantitative brain phenotypic representation, serving as a robust intermediate phenotype (i.e., endophenotype) largely reflecting underlying genetics and etiology. Finally, we discuss the potential clinical implications of the current findings and envision future research avenues.

Neuronal knockdown of Cullin3 as a Drosophila model of autism spectrum disorder

Mutations in Cullin-3 (Cul3), a conserved gene encoding a ubiquitin ligase, are strongly associated with autism spectrum disorder (ASD). Here, we characterize ASD-related pathologies caused by neuron-specific Cul3 knockdown in Drosophila. We confirmed that neuronal Cul3 knockdown causes short sleep, paralleling sleep disturbances in ASD. Because sleep defects and ASD are linked to metabolic dysregulation, we tested the starvation response of neuronal Cul3 knockdown flies; they starved faster and had lower triacylglyceride levels than controls, suggesting defects in metabolic homeostasis. ASD is also characterized by increased biomarkers of oxidative stress; we found that neuronal Cul3 knockdown increased sensitivity to hyperoxia, an exogenous oxidative stress. Additional hallmarks of ASD are deficits in social interactions and learning. Using a courtship suppression assay that measures social interactions and memory of prior courtship, we found that neuronal Cul3 knockdown reduced courtship and learning compared to controls. Finally, we found that neuronal Cul3 depletion alters the anatomy of the mushroom body, a brain region required for memory and sleep. Taken together, the ASD-related phenotypes of neuronal Cul3 knockdown flies establish these flies as a genetic model to study molecular and cellular mechanisms underlying ASD pathology, including metabolic and oxidative stress dysregulation and neurodevelopment.

Dynamic fusion of genomics and functional network connectivity in UK biobank reveals static and time-varying SNP manifolds

Many psychiatric and neurological disorders show significant heritability, indicating strong genetic influence. In parallel, dynamic functional network connectivity (dFNC) measures functional temporal coupling between brain networks in a time-varying manner and has proven to identify disease-related changes in the brain. However, it remains largely unclear how genetic risk contributes to brain dysconnectivity that further manifests into clinical symptoms. The current work aimed to address this gap by proposing a novel joint ICA (jICA)-based "dynamic fusion" framework to identify dynamically tuned SNP manifolds by linking static SNPs to dynamic functional information of the brain. The sliding window approach was utilized to estimate four dFNC states and compute subject-level state-specific dFNC features. Each state of dFNC features were then combined with 12946 SZ risk SNPs for jICA decomposition, resulting in four parallel fusions in 32861 European ancestry individuals within the UK Biobank cohort. The identified joint SNP-dFNC components were further validated for SZ relevance in an aggregated SZ cohort, and compared for across-state similarity to indicate level of dynamism. The results supported that dynamic fusion yielded "static" and "dynamic" components (i.e., high and low across-state similarity, respectively) for SNP and dFNC modalities. As expected, the SNP components presented a mixture of static and dynamic manifolds, with the latter largely driven by fusion with dFNC. We also showed that some of the dynamic SNP manifolds uniquely elicited by fusion with state-specific dFNC features complemented each other in terms of biological interpretation. This dynamic fusion framework thus allows expanding the SNP modality to manifolds in the time dimension, which provides a unique lens to elicit unique SNP correlates of dFNC otherwise unseen, promising additional insights on how genetic risk links to disease-related dysconnectivity.

Association of verbal and non-verbal theory of mind abilities with non-coding variants of OXTR in youth with autism spectrum disorder and typically developing individuals: a case-control study

BACKGROUND

The ability to attribute mental states to others is called theory of mind (ToM) and is a substantial component of social cognition. This ability is abnormally developed in individuals with autism spectrum disorder (ASD). Several studies over the past decade have identified the oxytocin receptor gene (OXTR) and its variants as promising components for explaining the molecular mechanisms underlying Theory of Mind (ToM). The main aim of this study is to examine the association between rs2268498 and rs53576, two functional single nucleotide polymorphisms (SNPs), and verbal and non-verbal ToM in children and adolescents with ASD and a group of typically developing youth.

METHODS

The study involved 44 children and adolescents with high-functioning ASD aged 8 to 18 years old and 44 TD individuals who were matched on age and sex. In all participants, blood samples were collected and rs2268498 and rs53576 were genotyped. Happe's Strange Stories test and the moving shapes paradigm were used to measure verbal and non-verbal ToM in all participants.

RESULTS

The results of permutation tests and logistic regression suggested that in TD group, rs2268498 AA carriers showed significant higher scores in variables representing verbal ToM (ToM stories and appropriateness score) whereas, in ASD group, rs53576 AA carriers exhibited significant better performance in parameters related to non-verbal ToM (ToM general rule and intentionality score). The results of hierarchical clustering in both groups support the findings by distinguishing between language-related and language-independent aspects of ToM.

CONCLUSIONS

In the present study, we examined the association between rs2268498 and rs53576 and social functioning in individuals with ASD and TD group. We found preliminary evidence that rs2268498 and rs53576 are associated with ToM related abilities in healthy individuals as well as in autistic individuals. Accordingly, rs2268498 and rs53576 may play an important role in predicting ToM capabilities. It will be necessary to conduct further research to address the association of genetic variants with a deficit in ToM in individuals with ASD.

Genomic Machine Learning Meta-regression: Insights on Associations of Study Features With Reported Model Performance

Many studies have been conducted with the goal of correctly predicting diagnostic status of a disorder using the combination of genomic data and machine learning. It is often hard to judge which components of a study led to better results and whether better reported results represent a true improvement or an uncorrected bias inflating performance. We extracted information about the methods used and other differentiating features in genomic machine learning models. We used these features in linear regressions predicting model performance. We tested for univariate and multivariate associations as well as interactions between features. Of the models reviewed, 46% used feature selection methods that can lead to data leakage. Across our models, the number of hyperparameter optimizations reported, data leakage due to feature selection, model type, and modeling an autoimmune disorder were significantly associated with an increase in reported model performance. We found a significant, negative interaction between data leakage and training size. Our results suggest that methods susceptible to data leakage are prevalent among genomic machine learning research, resulting in inflated reported performance. Best practice guidelines that promote the avoidance and recognition of data leakage may help the field avoid biased results.

A sensory signature of unaffected biological parents predicts the risk of autism in their offspring

AIM

Despite the emphasis on sensory dysfunction phenotypes in the revised diagnostic criteria for autism spectrum disorder (ASD), there has been limited research, particularly in the field of neurobiology, investigating the concordance in sensory features between individuals with ASD and their genetic relatives. Therefore, our objective was to examine whether neurobehavioral sensory patterns could serve as endophenotypic markers for ASD.

METHODS

We combined questionnaire- and lab-based sensory evaluations with sensory fMRI measures to examine the patterns of sensory responsivity in 30 clinically diagnosed with ASD, 26 matched controls (CON), and 48 biological parents for both groups (27 parents of individuals with ASD [P-ASD] and 21 for individuals with CON [P-CON]).

RESULTS

The ASD and P-ASD groups had higher sensory responsivity and rated sensory stimuli as more unpleasant than the CON and P-CON groups, respectively. They also exhibited greater hemodynamic responses within the sensory cortices. Overlapping activations were observed within these sensory cortices in the ASD and P-ASD groups. Using a machine learning approach with robust prediction models across cohorts, we demonstrated that the sensory profile of biological parents accurately predicted the likelihood of their offspring having ASD, achieving a prediction accuracy of 71.4%.

CONCLUSIONS

These findings provide support for the hereditary basis of sensory alterations in ASD and suggest a potential avenue to improve ASD diagnosis by utilizing the sensory signature of biological parents, especially in families with a high risk of ASD. This approach holds promising prospects for early detection, even before the birth of the offspring.

A novel autism-associated UBLCP1 mutation impacts proteasome regulation/activity

The landscape of autism spectrum disorder (ASD) in Lebanon is unique because of high rates of consanguinity, shared ancestry, and increased remote consanguinity. ASD prevalence in Lebanon is 1 in 68 with a male-to-female ratio of 2:1. This study aims to investigate the impact of an inherited deletion in UBLCP1 (Ubiquitin-Like Domain-Containing CTD Phosphatase 1) on the ubiquitin-proteasome system (UPS) and proteolysis. Whole exome sequencing in a Lebanese family with ASD without pathogenic copy number variations (CNVs) uncovered a deletion in UBLCP1. Functional evaluation of the identified variant is described in fibroblasts from the affected. The deletion in UBLCP1 exon 10 (g.158,710,261CAAAG > C) generates a premature stop codon interrupting the phosphatase domain and is predicted as pathogenic. It is absent from databases of normal variation worldwide and in Lebanon. Wild-type UBLCP1 is widely expressed in mouse brains. The mutation results in decreased UBLCP1 protein expression in patient-derived fibroblasts from the autistic patient compared to controls. The truncated UBLCP1 protein results in increased proteasome activity decreased ubiquitinated protein levels, and downregulation in expression of other proteasome subunits in samples from the affected compared to controls. Inhibition of the proteasome by using MG132 in proband cells reverses alterations in gene expression due to the restoration of protein levels of the common transcription factor, NRF1. Finally, treatment with gentamicin, which promotes premature termination codon read-through, restores UBLCP1 expression and function. Discovery of an ASD-linked mutation in UBLCP1 leading to overactivation of cell proteolysis is reported. This, in turn, leads to dysregulation of proteasome subunit transcript levels as a compensatory response.

Prenatal exposure to valproic acid reduces synaptic δ-catenin levels and disrupts ultrasonic vocalization in neonates

Valproic acid (VPA) is an effective and commonly prescribed drug for epilepsy and bipolar disorder. However, children born from mothers treated with VPA during pregnancy exhibit an increased incidence of autism spectrum disorder (ASD). Although VPA may impair brain development at the cellular level, the mechanism of VPA-induced ASD has not been completely addressed. A previous study has found that VPA treatment strongly reduces δ-catenin mRNA levels in cultured human neurons. δ-catenin is important for the control of glutamatergic synapses and is strongly associated with ASD. VPA inhibits dendritic morphogenesis in developing neurons, an effect that is also found in neurons lacking δ-catenin expression. We thus hypothesize that prenatal exposure to VPA significantly reduces δ-catenin levels in the brain, which impairs glutamatergic synapses to cause ASD. Here, we found that prenatal exposure to VPA markedly reduced δ-catenin levels in the brain of mouse pups. VPA treatment also impaired dendritic branching in developing mouse cortical neurons, which was reversed by elevating δ-catenin expression. Prenatal VPA exposure significantly reduced synaptic AMPA receptor levels and postsynaptic density 95 (PSD95) in the brain of mouse pups, indicating dysfunctions in glutamatergic synaptic transmission. VPA exposure also significantly altered ultrasonic vocalization (USV) in newly born pups when they were isolated from their nest. Moreover, VPA-exposed pups show impaired hypothalamic response to isolation, which is required to produce animals' USVs following isolation from the nest. Therefore, these results suggest that VPA-induced ASD pathology can be mediated by the loss of δ-catenin functions.

Highlights

Prenatal exposure of valproic acid (VPA) in mice significantly reduces synaptic δ-catenin protein and AMPA receptor levels in the pups' brains.VPA treatment significantly impairs dendritic branching in cultured cortical neurons, which is reversed by increased δ-catenin expression.VPA exposed pups exhibit impaired communication such as ultrasonic vocalization.Neuronal activation linked to ultrasonic vocalization is absent in VPA-exposed pups.The loss of δ-catenin functions underlies VPA-induced autism spectrum disorder (ASD) in early childhood.

Pre-autism: What a paediatrician should know about early diagnosis of autism‎

Autism, also known as an autism spectrum disorder, is a complex neurodevelopmental disorder usually diagnosed in the first three years of a child's life. A range of symptoms characterizes it and can be diagnosed at any age, including adolescence and adulthood. However, early diagnosis is crucial for effective management, prognosis, and care. Unfortunately, there are no established fetal, prenatal, or newborn screening programs for autism, making early detection difficult. This review aims to shed light on the early detection of autism prenatally, natally, and early in life, during a stage we call as "pre-autism" when typical symptoms are not yet apparent. Some fetal, neonatal, and infant biomarkers may predict an increased risk of autism in the coming baby. By developing a biomarker array, we can create an objective diagnostic tool to diagnose and rank the severity of autism for each patient. These biomarkers could be genetic, immunological, hormonal, metabolic, amino acids, acute phase reactants, neonatal brainstem function biophysical activity, behavioral profile, body measurements, or radiological markers. However, every biomarker has its accuracy and limitations. Several factors can make early detection of autism a real challenge. To improve early detection, we need to overcome various challenges, such as raising community awareness of early signs of autism, improving access to diagnostic tools, reducing the stigma attached to the diagnosis of autism, and addressing various culturally sensitive concepts related to the disorder.

Investigating the Influence of Autism Spectrum Traits on Face Processing Mechanisms in Developmental Prosopagnosia

Autism traits are common exclusionary criteria in developmental prosopagnosia (DP) studies. We investigated whether autism traits produce qualitatively different face processing in 43 DPs with high vs. low autism quotient (AQ) scores. Compared to controls (n = 27), face memory and perception were similarly deficient in the high- and low-AQ DPs, with the high-AQ DP group additionally showing deficient face emotion recognition. Task-based fMRI revealed reduced occipito-temporal face selectivity in both groups, with high-AQ DPs additionally demonstrating decreased posterior superior temporal sulcus selectivity. Resting-state fMRI showed similar reduced face-selective network connectivity in both DP groups compared with controls. Together, this demonstrates that high- and low-AQ DP groups have very similar face processing deficits, with additional facial emotion deficits in high-AQ DPs.

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.

Endophenotype trait domains for advancing gene discovery in autism spectrum disorder

Autism spectrum disorder (ASD) is associated with a diverse range of etiological processes, including both genetic and non-genetic causes. For a plurality of individuals with ASD, it is likely that the primary causes involve multiple common inherited variants that individually account for only small levels of variation in phenotypic outcomes. This genetic landscape creates a major challenge for detecting small but important pathogenic effects associated with ASD. To address similar challenges, separate fields of medicine have identified endophenotypes, or discrete, quantitative traits that reflect genetic likelihood for a particular clinical condition and leveraged the study of these traits to map polygenic mechanisms and advance more personalized therapeutic strategies for complex diseases. Endophenotypes represent a distinct class of biomarkers useful for understanding genetic contributions to psychiatric and developmental disorders because they are embedded within the causal chain between genotype and clinical phenotype, and they are more proximal to the action of the gene(s) than behavioral traits. Despite their demonstrated power for guiding new understanding of complex genetic structures of clinical conditions, few endophenotypes associated with ASD have been identified and integrated into family genetic studies. In this review, we argue that advancing knowledge of the complex pathogenic processes that contribute to ASD can be accelerated by refocusing attention toward identifying endophenotypic traits reflective of inherited mechanisms. This pivot requires renewed emphasis on study designs with measurement of familial co-variation including infant sibling studies, family trio and quad designs, and analysis of monozygotic and dizygotic twin concordance for select trait dimensions. We also emphasize that clarification of endophenotypic traits necessarily will involve integration of transdiagnostic approaches as candidate traits likely reflect liability for multiple clinical conditions and often are agnostic to diagnostic boundaries. Multiple candidate endophenotypes associated with ASD likelihood are described, and we propose a new focus on the analysis of "endophenotype trait domains" (ETDs), or traits measured across multiple levels (e.g., molecular, cellular, neural system, neuropsychological) along the causal pathway from genes to behavior. To inform our central argument for research efforts toward ETD discovery, we first provide a brief review of the concept of endophenotypes and their application to psychiatry. Next, we highlight key criteria for determining the value of candidate endophenotypes, including unique considerations for the study of ASD. Descriptions of different study designs for assessing endophenotypes in ASD research then are offered, including analysis of how select patterns of results may help prioritize candidate traits in future research. We also present multiple candidate ETDs that collectively cover a breadth of clinical phenomena associated with ASD, including social, language/communication, cognitive control, and sensorimotor processes. These ETDs are described because they represent promising targets for gene discovery related to clinical autistic traits, and they serve as models for analysis of separate candidate domains that may inform understanding of inherited etiological processes associated with ASD as well as overlapping neurodevelopmental disorders.

Discovery and Validation of Novel Genes in a Large Chinese Autism Spectrum Disorder Cohort

BACKGROUND

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that causes impairments in social communication and stereotypical behaviors, often accompanied by developmental delay or intellectual disability. A growing body of evidence suggests that ASD is highly heritable, and genetic studies have defined numerous risk genes. However, most studies have been conducted with individuals of European and Hispanic ancestry, and there is a lack of genetic analyses of ASD in the East Asian population.

METHODS

We performed whole-exome sequencing on 772 Chinese ASD trios and combined the data with a previous study of 369 Chinese ASD trios, identifying de novo variants in 1141 ASD trios. We used single-cell RNA sequencing analysis to identify the cell types in which ASD-related genes were enriched. In addition, we validated the function of a candidate high-functioning autism gene in mouse models using genetic approaches.

RESULTS

Our findings showed that ASD without developmental delay or intellectual disability carried fewer disruptive de novo variants than ASD with developmental delay or intellectual disability. Moreover, we identified 9 novel ASD candidate genes that were not present in the current ASD gene database. We further validated one such novel ASD candidate gene, SLC35G1, by showing that mice harboring a heterozygous deletion of Slc35g1 exhibited defects in interactive social behaviors.

CONCLUSIONS

Our work nominates novel ASD candidate genes and emphasizes the importance of genome-wide genetic studies with ASD cohorts of different ancestries to reveal the comprehensive genetic architecture of ASD.

Altered motor learning and coordination in mouse models of autism spectrum disorder

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with increasing prevalence. Over 1,000 risk genes have now been implicated in ASD, suggesting diverse etiology. However, the diagnostic criteria for the disorder still comprise two major behavioral domains - deficits in social communication and interaction, and the presence of restricted and repetitive patterns of behavior (RRBs). The RRBs associated with ASD include both stereotyped repetitive movements and other motor manifestations including changes in gait, balance, coordination, and motor skill learning. In recent years, the striatum, the primary input center of the basal ganglia, has been implicated in these ASD-associated motor behaviors, due to the striatum's role in action selection, motor learning, and habit formation. Numerous mouse models with mutations in ASD risk genes have been developed and shown to have alterations in ASD-relevant behaviors. One commonly used assay, the accelerating rotarod, allows for assessment of both basic motor coordination and motor skill learning. In this corticostriatal-dependent task, mice walk on a rotating rod that gradually increases in speed. In the extended version of this task, mice engage striatal-dependent learning mechanisms to optimize their motor routine and stay on the rod for longer periods. This review summarizes the findings of studies examining rotarod performance across a range of ASD mouse models, and the resulting implications for the involvement of striatal circuits in ASD-related motor behaviors. While performance in this task is not uniform across mouse models, there is a cohort of models that show increased rotarod performance. A growing number of studies suggest that this increased propensity to learn a fixed motor routine may reflect a common enhancement of corticostriatal drive across a subset of mice with mutations in ASD-risk genes.

Identification of two novel autism genes, TRPC4 and SCFD2, in Qatar simplex families through exome sequencing

This study investigated the genetic underpinnings of autism spectrum disorder (ASD) in a Middle Eastern cohort in Qatar using exome sequencing. The study identified six candidate autism genes in independent simplex families, including both four known and two novel autosomal dominant and autosomal recessive genes associated with ASD. The variants consisted primarily of de novo and homozygous missense and splice variants. Multiple individuals displayed more than one candidate variant, suggesting the potential involvement of digenic or oligogenic models. These variants were absent in the Genome Aggregation Database (gnomAD) and exhibited extremely low frequencies in the local control population dataset. Two novel autism genes, TRPC4 and SCFD2, were discovered in two Qatari autism individuals. Furthermore, the D651A substitution in CLCN3 and the splice acceptor variant in DHX30 were identified as likely deleterious mutations. Protein modeling was utilized to evaluate the potential impact of three missense variants in DEAF1, CLCN3, and SCFD2 on their respective structures and functions, which strongly supported the pathogenic natures of these variants. The presence of multiple de novo mutations across trios underscored the significant contribution of de novo mutations to the genetic etiology of ASD. Functional assays and further investigations are necessary to confirm the pathogenicity of the identified genes and determine their significance in ASD. Overall, this study sheds light on the genetic factors underlying ASD in Qatar and highlights the importance of considering diverse populations in ASD research.

eQTL colocalization analysis highlights novel susceptibility genes in Autism Spectrum Disorders (ASD)

Autism Spectrum Disorders (ASD) are a group of neurodevelopmental disorders (NDDs) characterized by difficulties in social interaction and communication, repetitive behavior, and restricted interests. ASD has proven to have a strong genetic component. However, defining causal genes is still one of the main challenges in GWAS, since the vast majority (>90%) of detected signals lie within the non-coding genome. Expression quantitative trait locus (eQTL) colocalization analysis determines whether a specific variant is responsible for both a local eQTL and GWAS association and has helped leverage data and rendering gene discovery for a wide array of diseases. Here we further mine the largest ASD GWAS performed to date (18,381 cases and 27,969 controls) altogether with GWAS summary statistics from the main PGC studies (Schizophrenia, MD (Major Depression) and ADHD (Attention Deficit/Hyperactivity Disorder)), by using eQTpLot, a newly developed tool that illustrates the colocalization of GWAS and eQTL signals in a locus, and the enrichment of and correlation between the candidate gene eQTLs and trait-significant variants. This analysis points up 8 genes with a significant eQTL colocalization signal in ASD (CRHR1, KANSL1, MANBA, MAPT, MMP12, NKX2-2, PTPRE and WNT3) and one gene (SRPK2) with a marginally significant colocalization signal (r = 0.69, p < 1 × 10-6), and specifically highlights the potentially causal role of MAPT (r = 0.76, p < 1 × 10-6), NKX2-2 (r = 0.71, p-value = 2.26-02) and PTPRE (r = 0.97, p-value = 2.63-04) when restricting the analysis to brain tissue.

Heterozygous deletion of the autism-associated gene CHD8 impairs synaptic function through widespread changes in gene expression and chromatin compaction

Whole-exome sequencing of autism spectrum disorder (ASD) probands and unaffected family members has identified many genes harboring de novo variants suspected to play a causal role in the disorder. Of these, chromodomain helicase DNA-binding protein 8 (CHD8) is the most recurrently mutated. Despite the prevalence of CHD8 mutations, we have little insight into how CHD8 loss affects genome organization or the functional consequences of these molecular alterations in neurons. Here, we engineered two isogenic human embryonic stem cell lines with CHD8 loss-of-function mutations and characterized differences in differentiated human cortical neurons. We identified hundreds of genes with altered expression, including many involved in neural development and excitatory synaptic transmission. Field recordings and single-cell electrophysiology revealed a 3-fold decrease in firing rates and synaptic activity in CHD8+/- neurons, as well as a similar firing-rate deficit in primary cortical neurons from Chd8+/- mice. These alterations in neuron and synapse function can be reversed by CHD8 overexpression. Moreover, CHD8+/- neurons displayed a large increase in open chromatin across the genome, where the greatest change in compaction was near autism susceptibility candidate 2 (AUTS2), which encodes a transcriptional regulator implicated in ASD. Genes with changes in chromatin accessibility and expression in CHD8+/- neurons have significant overlap with genes mutated in probands for ASD, intellectual disability, and schizophrenia but not with genes mutated in healthy controls or other disease cohorts. Overall, this study characterizes key molecular alterations in genome structure and expression in CHD8+/- neurons and links these changes to impaired neuronal and synaptic function.

The neuroanatomical substrates of autism and ADHD and their link to putative genomic underpinnings

BACKGROUND

Autism spectrum disorders (ASD) are neurodevelopmental conditions accompanied by differences in brain development. Neuroanatomical differences in autism are variable across individuals and likely underpin distinct clinical phenotypes. To parse heterogeneity, it is essential to establish how the neurobiology of ASD is modulated by differences associated with co-occurring conditions, such as attention-deficit/hyperactivity disorder (ADHD). This study aimed to (1) investigate between-group differences in autistic individuals with and without co-occurring ADHD, and to (2) link these variances to putative genomic underpinnings.

METHODS

We examined differences in cortical thickness (CT) and surface area (SA) and their genomic associations in a sample of 533 individuals from the Longitudinal European Autism Project. Using a general linear model including main effects of autism and ADHD, and an ASD-by-ADHD interaction, we examined to which degree ADHD modulates the autism-related neuroanatomy. Further, leveraging the spatial gene expression data of the Allen Human Brain Atlas, we identified genes whose spatial expression patterns resemble our neuroimaging findings.

RESULTS

In addition to significant main effects for ASD and ADHD in fronto-temporal, limbic, and occipital regions, we observed a significant ASD-by-ADHD interaction in the left precentral gyrus and the right frontal gyrus for measures of CT and SA, respectively. Moreover, individuals with ASD + ADHD differed in CT to those without. Both main effects and the interaction were enriched for ASD-but not for ADHD-related genes.

LIMITATIONS

Although we employed a multicenter design to overcome single-site recruitment limitations, our sample size of N = 25 individuals in the ADHD only group is relatively small compared to the other subgroups, which limits the generalizability of the results. Also, we assigned subjects into ADHD positive groupings according to the DSM-5 rating scale. While this is sufficient for obtaining a research diagnosis of ADHD, our approach did not take into account for how long the symptoms have been present, which is typically considered when assessing ADHD in the clinical setting.

CONCLUSION

Thus, our findings suggest that the neuroanatomy of ASD is significantly modulated by ADHD, and that autistic individuals with co-occurring ADHD may have specific neuroanatomical underpinnings potentially mediated by atypical gene expression.

Use of big data and machine learning algorithms to extract possible treatment targets in neurodevelopmental disorders

Neurodevelopmental disorders (NDDs) impact multiple aspects of an individual's functioning, including social interactions, communication, and behaviors. The underlying biological mechanisms of NDDs are not yet fully understood, and pharmacological treatments have been limited in their effectiveness, in part due to the complex nature of these disorders and the heterogeneity of symptoms across individuals. Identifying genetic loci associated with NDDs can help in understanding biological mechanisms and potentially lead to the development of new treatments. However, the polygenic nature of these complex disorders has made identifying new treatment targets from genome-wide association studies (GWAS) challenging. Recent advances in the fields of big data and high-throughput tools have provided radically new insights into the underlying biological mechanism of NDDs. This paper reviews various big data approaches, including classical and more recent techniques like deep learning, which can identify potential treatment targets from GWAS and other omics data, with a particular emphasis on NDDs. We also emphasize the increasing importance of explainable and causal machine learning (ML) methods that can aid in identifying genes, molecular pathways, and more complex biological processes that may be future targets of intervention in these disorders. We conclude that these new developments in genetics and ML hold promise for advancing our understanding of NDDs and identifying novel treatment targets.

Dual-Hit: Glyphosate exposure at NOAEL level negatively impacts birth and glia-behavioural measures in heterozygous shank3 mutants

The omnipresence of environmental contaminants represents a health danger with ramifications for adverse neurological trajectories. Here, we tested the dual-hit hypothesis that continuous exposure to non-observable adverse effect level (NOAEL) glyphosate from pre-natal to adulthood represents a risk factor for neurological-associated adaptations when in the presence of the heterozygote or homozygote mutation of the Shank3 synaptic gene. Ultrasound analysis of pregnant dams revealed patterns of pre-natal mortality with effects dependent on wild-type, Shank3ΔC/+, or Shank3ΔC/ΔC genotypes exposed to NOAEL glyphosate (GLY) compared to unexposed conditions. The postnatal survival rate was negatively impacted, specifically in Shank3ΔC/+ exposed to GLY. Next, the resulting six groups of pups were tracked into adulthood and analyzed for signs of neuroinflammation and neurological adaptions. Sholl's analysis revealed cortical microgliosis across groups exposed to GLY, with Shank3ΔC/+ mice presenting the most significant modifications. Brain tissues were devoid of astrocytosis, except for the perivascular compartment in the cortex in response to GLY. Distinct behavioral adaptations accompanied these cellular modifications, as locomotion and social preference were decreased in Shank3ΔC/+ mice exposed to GLY. Notably, GLY exposure from weaning did not elicit glial or neurological adaptations across groups, indicating the importance of pre-natal contaminant exposure. These results unveil the intersection between continuous pre-natal to adulthood environmental input and a pre-existing synaptic mutation. In an animal model, NOAEL GLY predominantly impacted Shank3ΔC/+ mice, compounding an otherwise mild phenotype compared to Shank3ΔC/ΔC. The possible relevance of these findings to neurodevelopmental risk is critically discussed, along with avenues for future research.

A Pilot Feasibility Study Assessing the Combined Effects of Early Behavioral Intervention and Propranolol on Autism Spectrum Disorder (ASD)

Autism spectrum disorder (ASD), a neurodevelopmental disorder typified by differences in social communication as well as restricted and repetitive behaviors, is often responsive to early behavioral intervention. However, there is limited information on whether such intervention can be augmented with pharmacological approaches. We conducted a double-blinded, placebo-controlled feasibility trial to examine the effects of the β-adrenergic antagonist propranolol combined with early intensive behavioral intervention (EIBI) for children with ASD. Nine participants with ASD, ages three to ten, undergoing EIBI were enrolled and randomized to a 12-week course of propranolol or placebo. Blinded assessments were conducted at baseline, 6 weeks, and 12 weeks. The primary outcome measures focusing on social interaction were the General Social Outcome Measure-2 (GSOM-2) and Social Responsiveness Scale-Second Edition (SRS-2). Five participants completed the 12-week visit. The sample size was insufficient to evaluate the treatment efficacy. However, side effects were infrequent, and participants were largely able to fully participate in the procedures. Conducting a larger clinical trial to investigate propranolol's effects on core ASD features within the context of behavioral therapy will be beneficial, as this will advance and individualize combined therapeutic approaches to ASD intervention. This initial study helps to understand feasibility constraints on performing such a study.

Single cell analysis of dup15q syndrome reveals developmental and postnatal molecular changes in autism

Duplication 15q (dup15q) syndrome is the most common genetic cause of autism spectrum disorder (ASD). Due to a higher genetic and phenotypic homogeneity compared to idiopathic autism, dup15q syndrome provides a well-defined setting to investigate ASD mechanisms. Previous bulk gene expression studies identified shared molecular changes in ASD. However, how cell type specific changes compare across different autism subtypes and how they change during development is largely unknown. In this study, we used single cell and single nucleus mRNA sequencing of dup15q cortical organoids from patient iPSCs, as well as post-mortem patient brain samples. We find cell-type specific dysregulated programs that underlie dup15q pathogenesis, which we validate by spatial resolved transcriptomics using brain tissue samples. We find degraded identity and vulnerability of deep-layer neurons in fetal stage organoids and highlight increased molecular burden of postmortem upper-layer neurons implicated in synaptic signaling, a finding shared between idiopathic ASD and dup15q syndrome. Gene co-expression network analysis of organoid and postmortem excitatory neurons uncovers modules enriched with autism risk genes. Organoid developmental modules were involved in transcription regulation via chromatin remodeling, while postmortem modules were associated with synaptic transmission and plasticity. The findings reveal a shifting landscape of ASD cellular vulnerability during brain development.

SOX7: Novel Autistic Gene Identified by Analysis of Multi-Omics Data

Background

Despite thousands of variants identified by genome-wide association studies (GWAS) to be associated with autism spectrum disorder (ASD), it is unclear which mutations are causal because most are noncoding. Consequently, reliable diagnostic biomarkers are lacking. RNA-seq analysis captures biomolecular complexity that GWAS cannot by considering transcriptomic patterns. Therefore, integrating DNA and RNA testing may reveal causal genes and useful biomarkers for ASD.

Methods

We performed gene-based association studies using an adaptive test method with GWAS summary statistics from two large Psychiatric Genomics Consortium (PGC) datasets (ASD2019: 18,382 cases and 27,969 controls; ASD2017: 6,197 cases and 7,377 controls). We also investigated differential expression for genes identified with the adaptive test using an RNA-seq dataset (GSE30573: 3 cases and 3 controls) and DESeq2.

Results

We identified 5 genes significantly associated with ASD in ASD2019 (KIZ-AS1, p = 8.67×10- 10; KIZ, p = 1.16×10- 9; XRN2, p = 7.73×10- 9; SOX7, p = 2.22×10- 7; LOC101929229 (also known as PINX1-DT), p = 2.14×10- 6). Two of the five genes were replicated in ASD2017: SOX7 (p = 0.00087) and LOC101929229 (p = 0.009), and KIZ was close to the replication boundary of replication (p = 0.06). We identified significant expression differences for SOX7 (p = 0.0017, adjusted p = 0.0085), LOC101929229 (p = 5.83×10- 7, adjusted p = 1.18×10- 5), and KIZ (p = 0.00099, adjusted p = 0.0055). SOX7 encodes a transcription factor that regulates developmental pathways, alterations in which may contribute to ASD.

Limitations

The limitation of the gene-based analysis is the reliance on a reference population for estimating linkage disequilibrium between variants. The similarity of this reference population to the population of study is crucial to the accuracy of many gene-based analyses, including those performed in this study. As a result, the extent of our findings is limited to European populations, as this was our reference of choice. Future work includes a tighter integration of DNA and RNA information as well as extensions to non-European populations that have been under-researched.

Conclusions

These findings suggest that SOX7 and its related SOX family genes encode transcription factors that are critical to the downregulation of the canonical Wnt/β-catenin signaling pathway, an important developmental signaling pathway, providing credence to the biologic plausibility of the association between gene SOX7 and autism spectrum disorder.

Bidirectional genetic overlap between autism spectrum disorder and cognitive traits

Autism spectrum disorder (ASD) is a highly heritable condition with a large variation in cognitive function. Here we investigated the shared genetic architecture between cognitive traits (intelligence (INT) and educational attainment (EDU)), and risk loci jointly associated with ASD and the cognitive traits. We analyzed data from genome-wide association studies (GWAS) of INT (n = 269,867), EDU (n = 766,345) and ASD (cases n = 18,381, controls n = 27,969). We used the bivariate causal mixture model (MiXeR) to estimate the total number of shared genetic variants, local analysis of co-variant annotation (LAVA) to estimate local genetic correlations, conditional false discovery rate (cond/conjFDR) to identify specific overlapping loci. The MiXeR analyses showed that 12.7k genetic variants are associated with ASD, of which 12.0k variants are shared with EDU, and 11.1k are shared with INT with both positive and negative relationships within overlapping variants. The majority (59-68%) of estimated shared loci have concordant effect directions, with a positive, albeit modest, genetic correlation between ASD and EDU (rg = 0.21, p = 2e-13) and INT (rg = 0.22, p = 4e-12). We discovered 43 loci jointly associated with ASD and cognitive traits (conjFDR<0.05), of which 27 were novel for ASD. Functional analysis revealed significant differential expression of candidate genes in the cerebellum and frontal cortex. To conclude, we quantified the genetic architecture shared between ASD and cognitive traits, demonstrated mixed effect directions, and identified the associated genetic loci and molecular pathways. The findings suggest that common genetic risk factors for ASD can underlie both better and worse cognitive functioning across the ASD spectrum, with different underlying biology.

Modeling idiopathic autism in forebrain organoids reveals an imbalance of excitatory cortical neuron subtypes during early neurogenesis

Idiopathic autism spectrum disorder (ASD) is highly heterogeneous, and it remains unclear how convergent biological processes in affected individuals may give rise to symptoms. Here, using cortical organoids and single-cell transcriptomics, we modeled alterations in the forebrain development between boys with idiopathic ASD and their unaffected fathers in 13 families. Transcriptomic changes suggest that ASD pathogenesis in macrocephalic and normocephalic probands involves an opposite disruption of the balance between excitatory neurons of the dorsal cortical plate and other lineages such as early-generated neurons from the putative preplate. The imbalance stemmed from divergent expression of transcription factors driving cell fate during early cortical development. While we did not find genomic variants in probands that explained the observed transcriptomic alterations, a significant overlap between altered transcripts and reported ASD risk genes affected by rare variants suggests a degree of gene convergence between rare forms of ASD and the developmental transcriptome in idiopathic ASD.

Heterogeneity of autism symptoms in community-referred infants and toddlers at elevated or low familial likelihood of autism

Evidence suggests autistic individuals at elevated familial likelihood of autism spectrum disorder (by virtue of having an autistic sibling) have stronger cognitive abilities on average than autistic individuals with no family history of the condition, who have a low familial likelihood of autism. Investigating phenotypic differences between community-referred infants and toddlers with autism symptoms at elevated or low familial likelihood of autism may provide important insight into heterogeneity in the emerging autism phenotype. This study compared behavioral, cognitive, and language abilities of community-referred infants and toddlers with confirmed autism symptoms at elevated (EL) or low familial likelihood of autism (LL). Participants were 121 children aged 12 to 36 months who participated in two larger randomized trials of parent-mediated interventions for children with autism symptoms. Behavioral phenotypes were compared across three groups: children with at least one autistic sibling (EL-Sibs, n = 30), those with at least one older, non-autistic sibling and no family history of autism (LL-Sibs, n = 40), and first-born children with no family history of autism (LL-FB, n = 51). EL-Sibs had less severe autism symptoms and stronger cognitive abilities than children in LL groups. While the rate of receptive language delay was similar across groups, the rate of expressive language delay was markedly lower among EL-Sibs. After controlling for age and nonverbal cognitive ability, EL-Sibs were significantly less likely to present with expressive language delay than LL-Sibs. Familial likelihood of autism may play an important role in shaping the emerging autism phenotype in infancy and toddlerhood.

Prevalence of Autism Spectrum Disorder in the Centro region of Portugal: a population based study of school age children within the ASDEU project

Introduction

Accurate prevalence estimates for Autism Spectrum Disorder (ASD) are fundamental to adequately program medical and educational resources for children. However, estimates vary globally and across Europe, and it is therefore wise to conduct epidemiological studies in defined geo-cultural contexts.

Methods

We used a population screening approach to estimate the prevalence of ASD in the Centro region of Portugal, using a harmonized protocol as part of the Autism Spectrum Disorders in the European Union (ASDEU) project.

Results

The overall prevalence was estimated at 0.5% (95% CI 0.3-0.7), higher in schools with Autism Units (3.3%, 95%CI 2.7-3.9) than in regular schools (0.3%, 95% CI 0.1-0.5) or schools with Multiple Disability Units (0.3%, 95% CI 0.04-0.6).

Discussion

The results indicate that the diagnosis of ASD is followed by the most effective educational policies in Centro Region. The variability in prevalence estimates across the different regions from the ASDEU project, and globally, is discussed.

Structural Variations Contribute to the Genetic Etiology of Autism Spectrum Disorder and Language Impairments

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by restrictive interests and/or repetitive behaviors and deficits in social interaction and communication. ASD is a multifactorial disease with a complex polygenic genetic architecture. Its genetic contributing factors are not yet fully understood, especially large structural variations (SVs). In this study, we aimed to assess the contribution of SVs, including copy number variants (CNVs), insertions, deletions, duplications, and mobile element insertions, to ASD and related language impairments in the New Jersey Language and Autism Genetics Study (NJLAGS) cohort. Within the cohort, ~77% of the families contain SVs that followed expected segregation or de novo patterns and passed our filtering criteria. These SVs affected 344 brain-expressed genes and can potentially contribute to the genetic etiology of the disorders. Gene Ontology and protein-protein interaction network analysis suggested several clusters of genes in different functional categories, such as neuronal development and histone modification machinery. Genes and biological processes identified in this study contribute to the understanding of ASD and related neurodevelopment disorders.