Pubertal maturation and timing effects on resting state electroencephalography in autistic and comparison youth.

Autistic and comparison individuals differ in resting-state electroencephalography (EEG), such that sex and age explain variability within and between groups. Pubertal maturation and timing may further explain variation, as previous work has suggested alterations in pubertal timing in autistic youth. In a sample from two studies of 181 autistic and 94 comparison youth (8 years to 17 years and 11 months), mixed-effects linear regressions were conducted to assess differences in EEG (midline power for theta, alpha, and beta frequency bands). Alpha power was analyzed as a mediator in the relation between pubertal maturation and timing with autistic traits in the autistic groups to understand the role of puberty in brain-based changes that contribute to functional outcomes. Individuals advanced in puberty exhibited decreased power in all bands. Those who experienced puberty relatively early showed decreased power in theta and beta bands, controlling for age, sex, and diagnosis. Autistic individuals further along in pubertal development exhibited lower social skills. Alpha mediated the relation between puberty and repetitive behaviors. Pubertal maturation and timing appear to play unique roles in the development of cognitive processes for autistic and comparison youth and should be considered in research on developmental variation in resting-state EEG.

Delineation of a novel neurodevelopmental syndrome associated with PAX5 haploinsufficiency.

PAX5 is a transcription factor associated with abnormal posterior midbrain and cerebellum development in mice. PAX5 is highly loss-of-function intolerant and missense constrained, and has been identified as a candidate gene for autism spectrum disorder (ASD). We describe 16 individuals from 12 families who carry deletions involving PAX5 and surrounding genes, de novo frameshift variants that are likely to trigger nonsense-mediated mRNA decay, a rare stop-gain variant, or missense variants that affect conserved amino acid residues. Four of these individuals were published previously but without detailed clinical descriptions. All these individuals have been diagnosed with one or more neurodevelopmental phenotypes including delayed developmental milestones (DD), intellectual disability (ID), and/or ASD. Seizures were documented in four individuals. No recurrent patterns of brain magnetic resonance imaging (MRI) findings, structural birth defects, or dysmorphic features were observed. Our findings suggest that PAX5 haploinsufficiency causes a neurodevelopmental disorder whose cardinal features include DD, variable ID, and/or ASD.

Discovering a new part of the phenotypic spectrum of Coffin-Siris syndrome in a fetal cohort.

PURPOSE: Genome-wide sequencing is increasingly being performed during pregnancy to identify the genetic cause of congenital anomalies. The interpretation of prenatally identified variants can be challenging and is hampered by our often limited knowledge of prenatal phenotypes. To better delineate the prenatal phenotype of Coffin-Siris syndrome (CSS), we collected clinical data from patients with a prenatal phenotype and a pathogenic variant in one of the CSS-associated genes. METHODS: Clinical data was collected through an extensive web-based survey. RESULTS: We included 44 patients with a variant in a CSS-associated gene and a prenatal phenotype; 9 of these patients have been reported before. Prenatal anomalies that were frequently observed in our cohort include hydrocephalus, agenesis of the corpus callosum, hypoplastic left heart syndrome, persistent left vena cava, diaphragmatic hernia, renal agenesis, and intrauterine growth restriction. Anal anomalies were frequently identified after birth in patients with ARID1A variants (6/14, 43%). Interestingly, pathogenic ARID1A variants were much more frequently identified in the current prenatal cohort (16/44, 36%) than in postnatal CSS cohorts (5%-9%). CONCLUSION: Our data shed new light on the prenatal phenotype of patients with pathogenic variants in CSS genes.

Infant social attention: an endophenotype of ASD-related traits?

BACKGROUND: As a neurodevelopmental disorder, symptoms of ASD likely emerge from a complex interaction between preexisting genetic vulnerabilities and the child's environment. One way to understand causal paths to ASD is to identify dimensional ASD-related traits that vary in the general population and that predispose individuals with other risk factors toward ASD. Moving beyond behavioral traits to explore underlying neurocognitive processes may further constrain the underlying genetics. Endophenotypes are quantitative, heritable, trait-related differences that are generally assessed with laboratory-based methods, can be identified in the general population, and may be more closely tied to particular causal chains that have a more restricted set of genetic roots. The most fruitful endophenotypes may be those observed in infancy, prior to the emergence of behavioral symptoms that they are hypothesized to cause. Social motivation is an ASD-related trait that is highly heritable. In this study, we investigate whether infant endophenotypes of social attention relate to familial risk for lower social motivation in the general population. METHODS: We examined whether infant social attention (measured using habituation, EEG power, and event-related potential tasks previously used in infants/toddlers with ASD) varies quantitatively with parental social motivation in 117 six-month-old and 106 twelve-month-old typically developing infants assessed cross-sectionally. To assess heritable aspects of social motivation, primary caregiver biological parents completed two self-report measures of social avoidance and discomfort that have shown high heritability in previous work. RESULTS: Parents with higher social discomfort and avoidance had infants who showed shorter looks to faces but not objects; reduced theta power during naturalistic social attention; and smaller P400 responses to faces versus objects. CONCLUSIONS: Early reductions in social attention are continuously related to lower parental social motivation. Alterations in social attention may be infant endophenotypes of social motivation traits related to ASD.

Developmental changes in infant brain activity during naturalistic social experiences.

Between 6 and 12 months, typically developing infants undergo a socio-cognitive "revolution." The Interactive Specialization (IS) theory of brain development predicts that these behavioral changes will be underpinned by developmental increases in the power and topographic extent of socially selective cortical responses. To test this hypothesis, we used EEG to examine developmental changes in cortical selectivity for ecologically valid dynamic social versus non-social stimuli in a large cohort of 6- and 12-month-old infants. Consistent with the Interactive Specialization model, results showed that differences in EEG Θ activity between social and non-social stimuli became more pronounced and widespread with age. Differences in EEG activity were most clearly elicited by a live naturalistic interaction, suggesting that measuring brain activity in ecologically valid contexts is central to mapping social brain development in infancy.

Characterizing Sensory Phenotypes of Subgroups with a Known Genetic Etiology Pertaining to Diagnoses of Autism Spectrum Disorder and Intellectual Disability.

We aimed to identify unique constellations of sensory phenotypes for genetic etiologies associated with diagnoses of autism spectrum disorder (ASD) and intellectual disability (ID). Caregivers reported on sensory behaviors via the Sensory Profile for 290 participants (younger than 25 years of age) with ASD and/or ID diagnoses, of which ~ 70% have a known pathogenic genetic etiology. Caregivers endorsed poor registration (i.e., high sensory threshold, passive behaviors) for all genetic subgroups relative to an "idiopathic" comparison group with an ASD diagnosis and without a known genetic etiology. Genetic profiles indicated prominent sensory seeking in ADNP, CHD8, and DYRK1A, prominent sensory sensitivities in SCN2A, and fewer sensation avoidance behaviors in GRIN2B (relative to the idiopathic ASD comparison group).

Characterizing the autism spectrum phenotype in DYRK1A-related syndrome.

Likely gene-disrupting (LGD) variants in DYRK1A are causative of DYRK1A syndrome and associated with autism spectrum disorder (ASD) and intellectual disability (ID). While many individuals with DYRK1A syndrome are diagnosed with ASD, they may present with a unique profile of ASD traits. We present a comprehensive characterization of the ASD profile in children and young adults with LGDs in DYRK1A. Individuals with LGD variants in DYRK1A (n = 29) were compared to children who had ASD with no known genetic cause, either with low nonverbal IQ (n = 14) or average or above nonverbal IQ (n = 41). ASD was assessed using the ADOS-2, ADI-R, SRS-2, SCQ, and RBS-R. Quantitative score comparisons were conducted, as were qualitative analyses of clinicians' behavioral observations. Diagnosis of ASD was confirmed in 85% and ID was confirmed in 89% of participants with DYRK1A syndrome. Individuals with DYRK1A syndrome showed broadly similar social communication behaviors to children with idiopathic ASD and below-average nonverbal IQ, with specific challenges noted in social reciprocity and nonverbal communication. Children with DYRK1A syndrome also showed high rates of sensory-seeking behaviors. Phenotypic characterization of individuals with DYRK1A syndrome may provide additional information on mechanisms contributing to co-occurring ASD and ID and contribute to the identification of genetic predictors of specific ASD traits.

Genetic Ablation of GIGYF1, Associated With Autism, Causes Behavioral and Neurodevelopmental Defects in Zebrafish and Mice.

BACKGROUND: Autism spectrum disorder is characterized by deficits in social communication and restricted or repetitive behaviors. Due to the extremely high genetic and phenotypic heterogeneity, it is critical to pinpoint the genetic factors for understanding the pathology of these disorders. METHODS: We analyzed the exomes generated by the SPARK (Simons Powering Autism Research) project and performed a meta-analysis with previous data. We then generated 1 zebrafish knockout model and 3 mouse knockout models to examine the function of GIGYF1 in neurodevelopment and behavior. Finally, we performed whole tissue and single-nucleus transcriptome analysis to explore the molecular and cellular function of GIGYF1. RESULTS: GIGYF1 variants are significantly associated with various neurodevelopmental disorder phenotypes, including autism, global developmental delay, intellectual disability, and sleep disturbance. Loss of GIGYF1 causes similar behavioral effects in zebrafish and mice, including elevated levels of anxiety and reduced social engagement, which is reminiscent of the behavioral deficits in human patients carrying GIGYF1 variants. Moreover, excitatory neuron-specific Gigyf1 knockout mice recapitulate the increased repetitive behaviors and impaired social memory, suggesting a crucial role of Gigyf1 in excitatory neurons, which correlates with the observations in single-nucleus RNA sequencing. We also identified a series of downstream target genes of GIGYF1 that affect many aspects of the nervous system, especially synaptic transmission. CONCLUSIONS: De novo variants of GIGYF1 are associated with neurodevelopmental disorders, including autism spectrum disorder. GIGYF1 is involved in neurodevelopment and animal behavior, potentially through regulating hippocampal CA2 neuronal numbers and disturbing synaptic transmission.

GIGYF1 disruption associates with autism and impaired IGF-1R signaling.

Autism spectrum disorder (ASD) represents a group of neurodevelopmental phenotypes with a strong genetic component. An excess of likely gene-disruptive (LGD) mutations in GIGYF1 was implicated in ASD. Here, we report that GIGYF1 is the second-most mutated gene among known ASD high-confidence risk genes. We investigated the inheritance of 46 GIGYF1 LGD variants, including the highly recurrent mutation c.333del:p.L111Rfs*234. Inherited GIGYF1 heterozygous LGD variants were 1.8 times more common than de novo mutations. Among individuals with ASD, cognitive impairments were less likely in those with GIGYF1 LGD variants relative to those with other high-confidence gene mutations. Using a Gigyf1 conditional KO mouse model, we showed that haploinsufficiency in the developing brain led to social impairments without significant cognitive impairments. In contrast, homozygous mice showed more severe social disability as well as cognitive impairments. Gigyf1 deficiency in mice led to a reduction in the number of upper-layer cortical neurons, accompanied by a decrease in proliferation and increase in differentiation of neural progenitor cells. We showed that GIGYF1 regulated the recycling of IGF-1R to the cell surface. KO of GIGYF1 led to a decreased level of IGF-1R on the cell surface, disrupting the IGF-1R/ERK signaling pathway. In summary, our findings show that GIGYF1 is a regulator of IGF-1R recycling. Haploinsufficiency of GIGYF1 was associated with autistic behavior, likely through interference with IGF-1R/ERK signaling pathway.

Genes To Mental Health (G2MH): A Framework to Map the Combined Effects of Rare and Common Variants on Dimensions of Cognition and Psychopathology.

Rare genomic disorders (RGDs) confer elevated risk for neurodevelopmental psychiatric disorders. In this era of intense genomics discoveries, the landscape of RGDs is rapidly evolving. However, there has not been comparable progress to date in scalable, harmonized phenotyping methods. As a result, beyond associations with categorical diagnoses, the effects on dimensional traits remain unclear for many RGDs. The nature and specificity of RGD effects on cognitive and behavioral traits is an area of intense investigation: RGDs are frequently associated with more than one psychiatric condition, and those studied to date affect, to varying degrees, a broad range of developmental and cognitive functions. Although many RGDs have large effects, phenotypic expression is typically influenced by additional genomic and environmental factors. There is emerging evidence that using polygenic risk scores in individuals with RGDs offers opportunities to refine prediction, thus allowing for the identification of those at greatest risk of psychiatric illness. However, translation into the clinic is hindered by roadblocks, which include limited genetic testing in clinical psychiatry, and the lack of guidelines for following individuals with RGDs, who are at high risk of developing psychiatric symptoms. The Genes to Mental Health Network (G2MH) is a newly funded National Institute of Mental Health initiative that will collect, share, and analyze large-scale data sets combining genomics and dimensional measures of psychopathology spanning diverse populations and geography. The authors present here the most recent understanding of the effects of RGDs on dimensional behavioral traits and risk for psychiatric conditions and discuss strategies that will be pursued within the G2MH network, as well as how expected results can be translated into clinical practice to improve patient outcomes.

De novo variants in genes regulating stress granule assembly associate with neurodevelopmental disorders.

Stress granules (SGs) are cytoplasmic assemblies in response to a variety of stressors. We report a new neurodevelopmental disorder (NDD) with common features of language problems, intellectual disability, and behavioral issues caused by de novo likely gene-disruptive variants in UBAP2L, which encodes an essential regulator of SG assembly. Ubap2l haploinsufficiency in mouse led to social and cognitive impairments accompanied by disrupted neurogenesis and reduced SG formation during early brain development. On the basis of data from 40,853 individuals with NDDs, we report a nominally significant excess of de novo variants within 29 genes that are not implicated in NDDs, including 3 essential genes (G3BP1, G3BP2, and UBAP2L) in the core SG interaction network. We validated that NDD-related de novo variants in newly implicated and known NDD genes, such as CAPRIN1, disrupt the interaction of the core SG network and interfere with SG formation. Together, our findings suggest the common SG pathology in NDDs.

Sleep Problems in Children with ASD and Gene Disrupting Mutations.

Sleep difficulties are pervasive in autism spectrum disorder (ASD), yet how sleep problems relate to underlying biological mechanisms such as genetic etiology is unclear, despite recent reports of profound sleep problems in children with ASD-associated de novo likely gene disrupting (dnLGD) mutations, CHD8, DYRK1A, and ADNP. We aimed to inform etiological contributions to ASD and sleep by characterizing sleep problems in individuals with dnLGD mutations. Participants (N = 2886) were families who completed dichotomous questions about sleep problems within a medical history interview for their child with ASD (age 3-28 years). Confirmatory factor analyses compared between those with ASD and a dnLGD mutation and those with idiopathic ASD (i.e., no known genetic event, NON) highlighted four domains (sleep onset, breathing issues, nighttime awakenings, and daytime tiredness) with sleep onset as a strong factor for both groups. Overall, participant predictors indicated that internalizing behavioral problems and lower cognitive scores were related to increased sleep problems. Internalizing problems were also related to increase nighttime awakenings in the dnLGD group. As an exploratory aim, patterns of sleep issues are described for genetic subgroups with unique patterns including more overall sleep issues in ADNP (n = 19), problems falling asleep in CHD8 (n = 22), and increased daytime naps in DYRK1A (n = 23). Implications for considering genetically defined subgroups when approaching sleep problems in children with ASD are discussed.

Brief Report: Associations Between Self-injurious Behaviors and Abdominal Pain Among Individuals with ASD-Associated Disruptive Mutations.

Self-injurious behaviors (SIB) are elevated in autism spectrum disorder (ASD) and related genetic disorders, but the genetic and biological mechanisms that contribute to SIB in ASD are poorly understood. This study examined rates and predictors of SIB in 112 individuals with disruptive mutations to ASD-risk genes. Current SIB were reported in 30% of participants and associated with poorer cognitive and adaptive skills. History of severe abdominal pain predicted higher rates of SIB and SIB severity after controlling for age and adaptive behavior; individuals with a history of severe abdominal pain were eight times more likely to exhibit SIB than those with no history. Future research is needed to examine associations between genetic risk, pain, and SIB in this population.

The CHD8/CHD7/Kismet family links blood-brain barrier glia and serotonin to ASD-associated sleep defects.

Sleep disturbances in autism and neurodevelopmental disorders are common and adversely affect patient's quality of life, yet the underlying mechanisms are understudied. We found that individuals with mutations in CHD8, among the highest-confidence autism risk genes, or CHD7 suffer from disturbed sleep maintenance. These defects are recapitulated in Drosophila mutants affecting kismet, the sole CHD8/CHD7 ortholog. We show that Kismet is required in glia for early developmental and adult sleep architecture. This role localizes to subperineurial glia constituting the blood-brain barrier. We demonstrate that Kismet-related sleep disturbances are caused by high serotonin during development, paralleling a well-established but genetically unsolved autism endophenotype. Despite their developmental origin, Kismet's sleep architecture defects can be reversed in adulthood by a behavioral regime resembling human sleep restriction therapy. Our findings provide fundamental insights into glial regulation of sleep and propose a causal mechanistic link between the CHD8/CHD7/Kismet family, developmental hyperserotonemia, and autism-associated sleep disturbances.

Recent ultra-rare inherited variants implicate new autism candidate risk genes.

Autism is a highly heritable complex disorder in which de novo mutation (DNM) variation contributes significantly to risk. Using whole-genome sequencing data from 3,474 families, we investigate another source of large-effect risk variation, ultra-rare variants. We report and replicate a transmission disequilibrium of private, likely gene-disruptive (LGD) variants in probands but find that 95% of this burden resides outside of known DNM-enriched genes. This variant class more strongly affects multiplex family probands and supports a multi-hit model for autism. Candidate genes with private LGD variants preferentially transmitted to probands converge on the E3 ubiquitin-protein ligase complex, intracellular transport and Erb signaling protein networks. We estimate that these variants are approximately 2.5 generations old and significantly younger than other variants of similar type and frequency in siblings. Overall, private LGD variants are under strong purifying selection and appear to act on a distinct set of genes not yet associated with autism.

Author Correction: Large-scale targeted sequencing identifies risk genes for neurodevelopmental disorders.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Large-scale targeted sequencing identifies risk genes for neurodevelopmental disorders.

Most genes associated with neurodevelopmental disorders (NDDs) were identified with an excess of de novo mutations (DNMs) but the significance in case-control mutation burden analysis is unestablished. Here, we sequence 63 genes in 16,294 NDD cases and an additional 62 genes in 6,211 NDD cases. By combining these with published data, we assess a total of 125 genes in over 16,000 NDD cases and compare the mutation burden to nonpsychiatric controls from ExAC. We identify 48 genes (25 newly reported) showing significant burden of ultra-rare (MAF < 0.01%) gene-disruptive mutations (FDR 5%), six of which reach family-wise error rate (FWER) significance (p < 1.25E-06). Among these 125 targeted genes, we also reevaluate DNM excess in 17,426 NDD trios with 6,499 new autism trios. We identify 90 genes enriched for DNMs (FDR 5%; e.g., GABRG2 and UIMC1); of which, 61 reach FWER significance (p < 3.64E-07; e.g., CASZ1). In addition to doubling the number of patients for many NDD risk genes, we present phenotype-genotype correlations for seven risk genes (CTCF, HNRNPU, KCNQ3, ZBTB18, TCF12, SPEN, and LEO1) based on this large-scale targeted sequencing effort.

Clinical phenotype of ASD-associated DYRK1A haploinsufficiency.

BACKGROUND: DYRK1A is a gene recurrently disrupted in 0.1-0.5% of the ASD population. A growing number of case reports with DYRK1A haploinsufficiency exhibit common phenotypic features including microcephaly, intellectual disability, speech delay, and facial dysmorphisms. METHODS: Phenotypic information from previously published DYRK1A cases (n = 51) and participants in an ongoing study at the University of Washington (UW, n = 10) were compiled. Frequencies of recurrent phenotypic features in this population were compared to features observed in a large sample with idiopathic ASD from the Simons Simplex Collection (n = 1981). UW DYRK1A cases were further characterized quantitatively and compared to a randomly subsampled set of idiopathic ASD cases matched on age and gender (n = 10) and to cases with an ASD-associated disruptive mutation to CHD8 (n = 12). Contribution of familial genetic background to clinical heterogeneity was assessed by comparing head circumference, IQ, and ASD-related symptoms of UW DYRK1A cases to their unaffected parents. RESULTS: DYRK1A haploinsufficiency results in a common phenotypic profile including intellectual disability, speech and motor difficulties, microcephaly, feeding difficulties, and vision abnormalities. Eighty-nine percent of DYRK1A cases ascertained for ASD presented with a constellation of five or more of these symptoms. When compared quantitatively, DYRK1A cases presented with significantly lower IQ and adaptive functioning compared to idiopathic cases and significantly smaller head size compared to both idiopathic and CHD8 cases. Phenotypic variability in parental head circumference, IQ, and ASD-related symptoms corresponded to observed variability in affected child phenotype. CONCLUSIONS: Results confirm a core clinical phenotype for DYRK1A disruptions, with a combination of features that is distinct from idiopathic ASD. Cases with DYRK1A mutations are also distinguishable from disruptive mutations to CHD8 by head size. Measurable, quantitative characterization of DYRK1A haploinsufficiency illuminates clinical variability, which may be, in part, due to familial genetic background.

The promise of multi-omics and clinical data integration to identify and target personalized healthcare approaches in autism spectrum disorders.

Complex diseases are caused by a combination of genetic and environmental factors, creating a difficult challenge for diagnosis and defining subtypes. This review article describes how distinct disease subtypes can be identified through integration and analysis of clinical and multi-omics data. A broad shift toward molecular subtyping of disease using genetic and omics data has yielded successful results in cancer and other complex diseases. To determine molecular subtypes, patients are first classified by applying clustering methods to different types of omics data, then these results are integrated with clinical data to characterize distinct disease subtypes. An example of this molecular-data-first approach is in research on Autism Spectrum Disorder (ASD), a spectrum of social communication disorders marked by tremendous etiological and phenotypic heterogeneity. In the case of ASD, omics data such as exome sequences and gene and protein expression data are combined with clinical data such as psychometric testing and imaging to enable subtype identification. Novel ASD subtypes have been proposed, such as CHD8, using this molecular subtyping approach. Broader use of molecular subtyping in complex disease research is impeded by data heterogeneity, diversity of standards, and ineffective analysis tools. The future of molecular subtyping for ASD and other complex diseases calls for an integrated resource to identify disease mechanisms, classify new patients, and inform effective treatment options. This in turn will empower and accelerate precision medicine and personalized healthcare.