Autism Spectrum Disorder (ASD) is diagnosed three to four times more frequently in males than in females. Genetic studies of rare variants support a female protective effect (FPE) against ASD. However, sex differences in common inherited genetic risk for ASD are less studied, particularly within families. Leveraging the Danish iPSYCH resource, we found siblings of female ASD cases (n = 1,707) had higher rates of ASD than siblings of male ASD cases (n = 6,270; p < 1.0 × 10−10). In the Simons Simplex and SPARK collections, mothers of ASD cases (n = 7,436) carried more polygenic risk for ASD than fathers of ASD cases (n = 5,926; 0.08 polygenic risk score [PRS] SD; p = 7.0 × 10−7). Further, male unaffected siblings under-inherited polygenic risk (n = 1,519; p = 0.03). Using both epidemiologic and genetic approaches, our findings strongly support an FPE against ASD’s common inherited influences.
The female protective effect against autism spectrum disorder
Neural precursor cell (NPC) dysfunction has been consistently implicated in autism. Induced pluripotent stem cell (iPSC)-derived NPCs from two autism groups (three idiopathic [I-ASD] and two 16p11.2 deletion [16pDel]) were used to investigate if proliferation is commonly disrupted. All five individuals display defects, with all three macrocephalic individuals (two 16pDel, one I-ASD) exhibiting hyperproliferation and the other two I-ASD subjects displaying hypoproliferation. NPCs were challenged with bFGF, and all hyperproliferative NPCs displayed blunted responses, while responses were increased in hypoproliferative cells. mRNA expression studies suggest that different pathways can result in similar proliferation phenotypes. Since 16pDel deletes MAPK3, P-ERK was measured. P-ERK is decreased in hyperproliferative but increased in hypoproliferative NPCs. While these P-ERK changes are not responsible for the phenotypes, P-ERK and bFGF response are inversely correlated with the defects. Finally, we analyzed iPSCs and discovered that 16pDel displays hyperproliferation, while idiopathic iPSCs were normal. These data suggest that NPC proliferation defects are common in ASD.
Keywords: 16p11.2 deletion; autism spectrum disorders; basic FGF; copy number variant; human NPCs; human iPSCs; macrocephaly; phospho-ERK signaling; proliferation.
Copy-number variants and structural variants (CNVs/SVs) drive many neurodevelopmental-related disorders. While many neurodevelopmental-related CNVs/SVs give rise to complex phenotypes, the overlap in phenotypic presentation between independent CNVs can be extensive and provides a motivation for shared approaches. This confluence at the level of clinical phenotype implies convergence in at least some aspects of the underlying genomic mechanisms. With this perspective, our Commission on Novel Technologies for Neurodevelopmental CNVs asserts that the time has arrived to approach neurodevelopmental-related CNVs/SVs as a class of disorders that can be identified, investigated, and treated on the basis of shared mechanisms and/or pathways (e.g., molecular, neurological, or developmental). To identify common etiologic mechanisms among uncommon neurodevelopmental-related disorders and to potentially identify common therapies, it is paramount for teams of scientists, clinicians, and patients to unite their efforts. We bring forward novel, collaborative, and integrative strategies to translational CNV/SV research that engages diverse stakeholders to help expedite therapeutic outcomes. We articulate a clear vision for piloted roadmap strategies to reduce patient/caregiver burden and redundancies, increase efficiency, avoid siloed data, and accelerate translational discovery across CNV/SV-based syndromes.
Keywords: CNVs; biobank; community engagement; copy-number variants; genomic disorders; iPSCs; inclusion; infrastructure; long-read sequencing; neurodevelopment; neurological; patient centered; patient led; structural variants; systematic phenotyping; team science.
Objective: Collier/Olf/EBF (COE) transcription factors have distinct expression patterns in the developing and mature nervous system. To date, a neurological disease association has been conclusively established for only the Early B-cell Factor-3 (EBF3) COE family member through the identification of heterozygous loss-of-function variants in individuals with autism spectrum/neurodevelopmental disorders (NDD). Here, we identify a symptom severity risk association with missense variants primarily disrupting the zinc finger domain (ZNF) in EBF3-related NDD.
Methods: A phenotypic assessment of 41 individuals was combined with a literature meta-analysis for a total of 83 individuals diagnosed with EBF3-related NDD. Quantitative diagnostic phenotypic and symptom severity scales were developed to compare EBF3 variant type and location to identify genotype-phenotype correlations. To stratify the effects of EBF3 variants disrupting either the DNA-binding domain (DBD) or the ZNF, we used in vivo fruit fly UAS-GAL4 expression and in vitro luciferase assays.
Results: We show that patient symptom severity correlates with EBF3 missense variants perturbing the ZNF, which is a key protein domain required for stabilizing the interaction between EBF3 and the target DNA sequence. We found that ZNF-associated variants failed to restore viability in the fruit fly and impaired transcriptional activation. However, the recurrent variant EBF3 p.Arg209Trp in the DBD is capable of partially rescuing viability in the fly and preserved transcriptional activation.
Interpretation: We describe a symptom severity risk association with ZNF perturbations and EBF3 loss-of-function in the largest reported cohort to date of EBF3-related NDD patients. This analysis should have potential predictive clinical value for newly identified patients with EBF3 gene variants.
Children with autism spectrum disorder (ASD) are at elevated risk of suicidal ideation, particularly those with comorbid anxiety disorders and/or obsessive-compulsive disorder (OCD). We investigated the risk factors associated with suicidal ideation in 166 children with ASD and comorbid anxiety disorders/OCD, and the unique contribution of externalizing behaviors. Suicidal ideation was reported in the child sample by 13% of parents. Controlling for child age, sex, and IQ, perceived loneliness positively predicted the likelihood of suicidal ideation. In addition, externalizing behaviors positively predicted suicidal ideation, controlling for all other factors. Reliance on parental report to detect suicidal ideation in youth with ASD is a limitation of this study. Nonetheless, these findings highlight the importance of assessing and addressing suicidal ideation in children with ASD and comorbid anxiety disorders/OCD, and more importantly in those with elevated externalizing behaviors and perceptions of loneliness.
Keywords: ASD; Anxiety; Externalizing behaviors; OCD; Suicidal thoughts.
Participation in research can provide direct and indirect benefit to individuals with autism spectrum disorder (ASD), their caregivers, families, and society at large. Unfortunately, individuals with high support needs, including those with intellectual disability, cognitive disability or minimal verbal ability, are often systematically excluded from research on ASD. This limits the ability to generalize discoveries to all people with ASD, and results in a disparity in who benefits from research. This piece outlines the importance and extent of the problem, which is part of a broader lack of inclusivity in ASD research. It also provides examples of studies that have directly addressed issues that arise when conducting inclusive research and makes recommendations for researchers to reduce disparities in research participation.
Keywords: Inclusion; Intellectual Disability; Participation; Research.
Autistic individuals who are also people of color or from lower socioeconomic strata are historically underrepresented in research. Lack of representation in autism research has contributed to health and healthcare disparities. Reducing these disparities will require culturally competent research that is relevant to under-resourced communities as well as collecting large nationally representative samples, or samples in which traditionally disenfranchised groups are over-represented. To achieve these goals, a diverse group of culturally competent researchers must partner with and gain the trust of communities to identify and eliminate barriers to participating in research. We suggest community-academic partnerships as one promising approach that results in high-quality research built on cultural competency, respect, and shared decision making.
Keywords: Autism; Engagement; Ethnicity; Participation; Race; Socioeconomic status
Awareness of autism has grown monumentally over the past 20 years. Yet, this increased awareness has not been accompanied by improvements in services to support autistic individuals and their families. Many fundamental questions remain about the care of people with autism—including which interventions are effective, for whom, when, and at what intensity. The Lancet Commission on the future of care and clinical research in autism aims to answer the question of what can be done in the next 5 years to address the current needs of autistic individuals and families worldwide
Background: Early identification of autism spectrum disorder (ASD) provides an opportunity for early intervention and improved developmental outcomes. The use of electroencephalography (EEG) in infancy has shown promise in predicting later ASD diagnoses and in identifying neural mechanisms underlying the disorder. Given the high co-morbidity with language impairment, we and others have speculated that infants who are later diagnosed with ASD have altered language learning, including phoneme discrimination. Phoneme learning occurs rapidly in infancy, so altered neural substrates during the first year of life may serve as early, accurate indicators of later autism diagnosis.
Methods: Using EEG data collected at two different ages during a passive phoneme task in infants with high familial risk for ASD, we compared the predictive accuracy of a combination of feature selection and machine learning models at 6 months (during native phoneme learning) and 12 months (after native phoneme learning), and we identified a single model with strong predictive accuracy (100%) for both ages. Samples at both ages were matched in size and diagnoses (n = 14 with later ASD; n = 40 without ASD). Features included a combination of power and nonlinear measures across the 10‑20 montage electrodes and 6 frequency bands. Predictive features at each age were compared both by feature characteristics and EEG scalp location. Additional prediction analyses were performed on all EEGs collected at 12 months; this larger sample included 67 HR infants (27 HR-ASD, 40 HR-noASD).
Results: Using a combination of Pearson correlation feature selection and support vector machine classifier, 100% predictive diagnostic accuracy was observed at both 6 and 12 months. Predictive features differed between the models trained on 6- versus 12-month data. At 6 months, predictive features were biased to measures from central electrodes, power measures, and frequencies in the alpha range. At 12 months, predictive features were more distributed between power and nonlinear measures, and biased toward frequencies in the beta range. However, diagnosis prediction accuracy substantially decreased in the larger, more behaviorally heterogeneous 12-month sample.
Conclusions: These results demonstrate that speech processing EEG measures can facilitate earlier identification of ASD but emphasize the need for age-specific predictive models with large sample sizes to develop clinically relevant classification algorithms.
Keywords: Autism; EEG; Infant; Language development; Machine learning; Sensitive period.
In this study we investigated the impact of parental language input on language development and associated neuroscillatory patterns in toddlers at risk of Autism Spectrum Disorder (ASD). Forty-six mother-toddler dyads at either high (n = 22) or low (n = 24) familial risk of ASD completed a longitudinal, prospective study including free-play, resting electroencephalography, and standardized language assessments. Input quantity/quality at 18 months positively predicted expressive language at 24 months, and relationships were stronger for high-risk toddlers. Moderated mediations revealed that input-language relationships were explained by 24-month frontal and temporal gamma power (30-50 Hz) for high-risk toddlers who would later develop ASD. Results suggest that high-risk toddlers may be cognitively and neurally more sensitive to their language environments, which has implications for early intervention.
Keywords: Autism; EEG; Early experience; Language development; Language input.
Infant vocalizations are early-emerging communicative markers shown to be atypical in autism spectrum disorder (ASD), but few longitudinal, prospective studies exist. In this study, 23,850 infant vocalizations from infants at low (LR)- and high (HR)-risk for ASD (HR-ASD = 23, female = 3; HR-Neg = 35, female = 13; LR = 32, female = 10; 80% White; collected from 2007 to 2017 near Philadelphia) were analyzed at 6, 12, and 24 months. At 12 months, HR-ASD infants produced fewer vocalizations than HR-Neg infants. From 6 to 24 months, HR-Neg infants demonstrated steeper vocalization growth compared to HR-ASD and LR infants. Finally, among HR infants, vocalizing at 12 months was associated with language, social phenotype, and diagnosis at age 2. Infant vocalizing is an objective behavioral marker that could facilitate earlier detection of ASD.
Background
Autism spectrum disorder (ASD) is a neurodevelopmental disorder diagnosed based on social impairment, restricted interests, and repetitive behaviors. Contemporary theories posit that cerebellar pathology contributes causally to ASD by disrupting error-based learning (EBL) during infancy. The present study represents the first test of this theory in a prospective infant sample, with potential implications for ASD detection.
Methods
Data from the Infant Brain Imaging Study (n=94, 68 male) were used to examine 6-month cerebellar functional connectivity (fcMRI) in relation to later (12/24-month) ASD-associated behaviors and outcomes. Hypothesis-driven univariate analyses and machine learning-based predictive tests examined cerebellar-frontoparietal (FPN; subserves error signaling in support of EBL) and cerebellar-default mode (DMN; broadly implicated in ASD) network connections. Cerebellar-FPN functional connectivity was used as a proxy for EBL, and cerebellar-DMN functional connectivity provided a comparative foil. Data-driven fcMRI enrichment examined brain-wide behavioral associations, with post-hoc tests of cerebellar connections.
Results
Cerebellar-FPN and cerebellar-DMN connections did not demonstrate associations with ASD. fcMRI enrichment identified 6-month correlates of later ASD-associated behaviors in networks of a priori interest (FPN, DMN), as well as in cingulo-opercular (also implicated in error signaling) and medial visual networks. Post-hoc tests did not suggest a role for cerebellar connections.
Conclusions
We failed to identify cerebellar functional connectivity-based contributions to ASD. However, we observed prospective correlates of ASD-associated behaviors in networks that support EBL. Future studies may replicate and extend network-level positive results, and tests of the cerebellum may investigate brain-behavior associations at different developmental stages and/or using different neuroimaging modalities.
Keywords
Autismfunctional connectivitycerebelluminfancyerror-based learningdevelopment