Background: Exposure to ambient air pollution is widespread and may be detrimental to human brain development and a potential risk factor for Autism Spectrum Disorder (ASD). We conducted a systematic review of the human evidence on the relationship between ASD and exposure to all airborne pollutants, including particulate matter air pollutants and others (e.g. pesticides and metals).
Objective: To answer the question: “is developmental exposure to air pollution associated with ASD?”
Methods: We conducted a comprehensive search of the literature, identified relevant studies using inclusion/exclusion criteria pre-specified in our protocol (registered in PROSPERO, CRD # 42015017890), evaluated the potential risk of bias for each included study and identified an appropriate subset of studies to combine in a meta-analysis. We then rated the overall quality and strength of the evidence collectively across all air pollutants.
Results: Of 1,158 total references identified, 23 human studies met our inclusion criteria (17 case-control, 4 ecological, 2 cohort). Risk of bias was generally low across studies for most domains; study limitations were related to potential confounding and accuracy of exposure assessment methods. We rated the quality of the body of evidence across all air pollutants as “moderate.” From our meta-analysis, we found statistically significant summary odds ratios (ORs) of 1.07 (95% CI: 1.06, 1.08) per 10-μg/m3 increase in PM10 exposure (n = 6 studies) and 2.32 (95% CI: 2.15, 2.51) per 10-μg/m3 increase in PM2.5 exposure (n = 3 studies). For pollutants not included in a meta-analysis, we collectively evaluated evidence from each study in rating the strength and quality of overall evidence considering factors such as inconsistency, imprecision, and evidence of dose-response. All included studies generally showed increased risk of ASD with increasing exposure to air pollution, although not consistently across all chemical components.
Conclusion: After considering strengths and limitations of the body of research, we concluded that there is “limited evidence of toxicity” for the association between early life exposure to air pollution as a whole and diagnosis of ASD. The strongest evidence was between prenatal exposure to particulate matter and ASD. However, the small number of studies in the meta-analysis and unexplained statistical heterogeneity across the individual study estimates means that the effect could be larger or smaller (including not significant) than these studies estimate. Our research supports the need for health protective public policy to reduce exposures to harmful airborne contaminants among pregnant women and children and suggests opportunities for optimizing future research.
Genetic studies of autism spectrum disorder (ASD) have established that de novo duplications and deletions contribute to risk. However, ascertainment of structural variants (SVs) has been restricted by the coarse resolution of current approaches. By applying a custom pipeline for SV discovery, genotyping, and de novo assembly to genome sequencing of 235 subjects (71 affected individuals, 26 healthy siblings, and their parents), we compiled an atlas of 29,719 SV loci (5,213/genome), comprising 11 different classes. We found a high diversity of de novo mutations, the majority of which were undetectable by previous methods. In addition, we observed complex mutation clusters where combinations of de novo SVs, nucleotide substitutions, and indels occurred as a single event. We estimate a high rate of structural mutation in humans (20%) and propose that genetic risk for ASD is attributable to an elevated frequency of gene-disrupting de novo SVs, but not an elevated rate of genome rearrangement.
Summary: Children in America today are at an unacceptably high risk of developing neurodevelopmental disorders that affect the brain and nervous system including autism, attention deficit hyperactivity disorder, intellectual disabilities, and other learning and behavioral disabilities. These are complex disorders with multiple causes—genetic, social, and environmental. The contribution of toxic chemicals to these disorders can be prevented. Approach: Leading scientific and medical experts, along with children’s health advocates, came together in 2015 under the auspices of Project TENDR: Targeting Environmental Neuro-Developmental Risks to issue a call to action to reduce widespread exposures to chemicals that interfere with fetal and children’s brain development. Based on the available scientific evidence, the TENDR authors have identified prime examples of toxic chemicals and pollutants that increase children’s risks for neurodevelopmental disorders. These include chemicals that are used extensively in consumer products and that have become widespread in the environment. Some are chemicals to which children and pregnant women are regularly exposed, and they are detected in the bodies of virtually all Americans in national surveys conducted by the U.S. Centers for Disease Control and Prevention. The vast majority of chemicals in industrial and consumer products undergo almost no testing for developmental neurotoxicity or other health effects. Conclusion: Based on these findings, we assert that the current system in the United States for evaluating scientific evidence and making health-based decisions about environmental chemicals is fundamentally broken. To help reduce the unacceptably high prevalence of neurodevelopmental disorders in our children, we must eliminate or significantly reduce exposures to chemicals that contribute to these conditions. We must adopt a new framework for assessing chemicals that have the potential to disrupt brain development and prevent the use of those that may pose a risk. This consensus statement lays the foundation for developing recommendations to monitor, assess, and reduce exposures to neurotoxic chemicals. These measures are urgently needed if we are to protect healthy brain development so that current and future generations can reach their fullest potential.
Background: Disruptive behavior in autism spectrum disorder (ASD) is an important clinical problem, but its neural basis remains poorly understood. The current research aims to better understand the neural underpinnings of disruptive behavior in ASD, while addressing whether the neural basis is shared with or separable from that of core ASD symptoms.
Methods: Participants consisted of 48 male children and adolescents: 31 ASD (7 had high disruptive behavior) and 17 typically developing (TD) controls, well-matched on sex, age, and IQ. For ASD participants, autism symptom severity, disruptive behavior, anxiety symptoms, and ADHD symptoms were measured. All participants were scanned while viewing biological motion (BIO) and scrambled motion (SCR). Two fMRI contrasts were analyzed: social perception (BIO > SCR) and Default Mode Network (DMN) deactivation (fixation > BIO). Age and IQ were included as covariates of no interest in all analyses.
Results: First, the between-group analyses on BIO > SCR showed that ASD is characterized by hypoactivation in the social perception circuitry, and ASD with high or low disruptive behavior exhibited similar patterns of hypoactivation. Second, the between-group analyses on fixation > BIO showed that ASD with high disruptive behavior exhibited more restricted and less DMN deactivation, when compared to ASD with low disruptive behavior or TD. Third, the within-ASD analyses showed that (a) autism symptom severity (but not disruptive behavior) was uniquely associated with less activation in the social perception regions including the posterior superior temporal sulcus and inferior frontal gyrus; (b) disruptive behavior (but not autism symptom severity) was uniquely associated with less DMN deactivation in the medial prefrontal cortex (MPFC) and lateral parietal cortex; and (c) anxiety symptoms mediated the link between disruptive behavior and less DMN deactivation in both anterior cingulate cortex (ACC) and MPFC, while ADHD symptoms mediated the link primarily in ACC.
Conclusions: In boys with ASD, disruptive behavior has a neural basis in reduced DMN deactivation, which is distinct and separable from that of core ASD symptoms, with the latter characterized by hypoactivation in the social perception circuitry. These differential neurobiological markers may potentially serve as neural targets or predictors for interventions when treating disruptive behavior vs. core symptoms in ASD.
Keywords: ADHD; Anxiety disorders; Autism spectrum disorder; Comorbidity; Default mode network; Disruptive behavior; Neuroimaging; Oppositional defiant disorder; Social perception.
An emerging hypothesis postulates that internal noise is a key factor influencing perceptual abilities in autism spectrum disorder (ASD). Given fundamental and inescapable effects of noise on nearly all aspects of neural processing, this could be a critical abnormality with broad implications for perception, behavior, and cognition. However, this proposal has been challenged by both theoretical and empirical studies. A crucial question is whether and how internal noise limits perception in ASD, independently from other sources of perceptual inefficiency, such as the ability to filter out external noise. Here, we separately estimated internal noise and external noise filtering in ASD. In children and adolescents with and without ASD, we computationally modeled individuals’ visual orientation discrimination in the presence of varying levels of external noise. The results revealed increased internal noise and worse external noise filtering in individuals with ASD. For both factors, we also observed high inter-individual variability in ASD, with only the internal noise estimates significantly correlating with severity of ASD symptoms. We provide evidence for reduced perceptual efficiency in ASD that is due to both increased internal noise and worse external noise filtering, while highlighting internal noise as a possible contributing factor to variability in ASD symptoms.
Research studies using existing samples of individuals with autism spectrum disorders have identified differences in symptoms between males and females. Differences are typically reported in school age and adolescence, with similarities in symptom presentation at earlier ages. However, existing studies on sex differences are significantly limited, making it challenging to discern if, how, and at what point in development females with autism spectrum disorder actually exhibit a different behavioral presentation than males. The purpose of this study was to gather impressions from a large group of clinicians to isolate specific areas for future study of sex differences. Clinicians were surveyed about their opinions and perceptions of symptom severity in females, as compared to males, at different points during development. They were also asked to provide open-ended responses about female symptom presentation. Consistent with previous literature, clinicians noted more sex-related differences in restricted and repetitive behaviors and fewer differences for social communication features. Differences were most commonly observed in school age and adolescence, suggesting this time period as a critical and particularly vulnerable window for females with autism spectrum disorder. The results are discussed in the context of other male/female differences across development so that more targeted investigations of autism spectrum disorder sex differences across development.
Keywords: adolescents; autism spectrum disorders; diagnosis; preschool children; qualitative research; repetitive behaviors and interests; school-age children; social cognition and social behavior.
Recent theoretical accounts have proposed excitation and inhibition (E/I) imbalance as a possible mechanistic, network-level hypothesis underlying neural and behavioral dysfunction across neurodevelopmental disorders, particularly autism spectrum disorder (ASD) and schizophrenia (SCZ). These two disorders share some overlap in their clinical presentation as well as convergence in their underlying genes and neurobiology. However, there are also clear points of dissociation in terms of phenotypes and putatively affected neural circuitry. We highlight emerging work from the clinical neuroscience literature examining neural correlates of E/I imbalance across children and adults with ASD and adults with both chronic and early-course SCZ. We discuss findings from diverse neuroimaging studies across distinct modalities, conducted with electroencephalography, magnetoencephalography, proton magnetic resonance spectroscopy, and functional magnetic resonance imaging, including effects observed both during task and at rest. Throughout this review, we discuss points of convergence and divergence in the ASD and SCZ literature, with a focus on disruptions in neural E/I balance. We also consider these findings in relation to predictions generated by theoretical neuroscience, particularly computational models predicting E/I imbalance across disorders. Finally, we discuss how human noninvasive neuroimaging can benefit from pharmacological challenge studies to reveal mechanisms in ASD and SCZ. Collectively, we attempt to shed light on shared and divergent neuroimaging effects across disorders with the goal of informing future research examining the mechanisms underlying the E/I imbalance hypothesis across neurodevelopmental disorders. We posit that such translational efforts are vital to facilitate development of neurobiologically informed treatment strategies across neuropsychiatric conditions.
Keywords: Autism; Computational modeling; E/I balance; Mechanism; Neuroimaging; Review; Schizophrenia.
Background: Phelan-McDermid syndrome (PMS) occurs as a result of a chromosomal abnormality, most frequently
deletion, in the long arm of chromosome 22, involving the SHANK3 gene. Our goal was to prospectively assess the
neurological phenotype in this syndrome.
METHODS: Twenty-nine participants were recruited from ongoing studies in PMS at the Seaver Autism Center. They
had a structured, uniform neurological examination performed by a pediatric neurologist (Y.F.). Abnormal findings
were graded as mild, moderate or severe. In addition, reports of seizures, magnetic resonance imaging (MRI) and
electroencephalograms (EEG) were reviewed. We calculated the frequency and severity of neurological
abnormalities, as well as correlations between items on the neurological examination and items on the Mullen Scales
of Early Learning and on the Vineland Adaptive Behavioral Scales (VABS).
RESULTS: Hypotonia, abnormal gait, fine motor coordination deficits, and expressive and receptive language delays
were present in all participants. Attention deficits were present in 96% (severe in 62%), and abnormal visual tracking
was present in 86%. A history of seizures was obtained in 44.8% of participants but 46.1% of these were febrile only.
Of the 13 EEG reports available for review – 69.2% were abnormal- with epileptic features present in 53.8%.
Abnormalities were present in 62.5% of MRI reports. Correlations were found between neurological abnormalities
and scores on the Mullen and Vineland Scales.
CONCLUSIONS: Neurological abnormalities are very common in PMS and are correlated with measures of cognitive
and adaptive functioning. The neurological examination may be used for clinical diagnosis, identification of PMS
phenotypes, and, in the future, for evaluation of therapy.