New evidences on the altered gut microbiota in autism spectrum disorders

BACKGROUND

Autism spectrum disorders (ASDs) are neurodevelopmental conditions characterized by social and behavioural impairments. In addition to neurological symptoms, ASD subjects frequently suffer from gastrointestinal abnormalities, thus implying a role of the gut microbiota in ASD gastrointestinal pathophysiology.

RESULTS

Here, we characterized the bacterial and fungal gut microbiota in a cohort of autistic individuals demonstrating the presence of an altered microbial community structure. A fraction of 90% of the autistic subjects were classified as severe ASDs. We found a significant increase in the Firmicutes/Bacteroidetes ratio in autistic subjects due to a reduction of the Bacteroidetes relative abundance. At the genus level, we observed a decrease in the relative abundance of Alistipes, Bilophila, Dialister, Parabacteroides, and Veillonella in the ASD cohort, while Collinsella, Corynebacterium, Dorea, and Lactobacillus were significantly increased. Constipation has been then associated with different bacterial patterns in autistic and neurotypical subjects, with constipated autistic individuals characterized by high levels of bacterial taxa belonging to Escherichia/Shigella and Clostridium cluster XVIII. We also observed that the relative abundance of the fungal genus Candida was more than double in the autistic than neurotypical subjects, yet due to a larger dispersion of values, this difference was only partially significant.

CONCLUSIONS

The finding that, besides the bacterial gut microbiota, also the gut mycobiota contributes to the alteration of the intestinal microbial community structure in ASDs opens the possibility for new potential intervention strategies aimed at the relief of gastrointestinal symptoms in ASDs.

Heritability of autism spectrum disorders: a meta-analysis of twin studies

BACKGROUND

The etiology of Autism Spectrum Disorder (ASD) has been recently debated due to emerging findings on the importance of shared environmental influences. However, two recent twin studies do not support this and instead re-affirm strong genetic effects on the liability to ASD, a finding consistent with previous reports. This study conducts a systematic review and meta-analysis of all twin studies of ASD published to date and explores the etiology along the continuum of a quantitative measure of ASD.

METHODS

A PubMed Central, Science Direct, Google Scholar, Web of Knowledge structured search conducted online, to identify all twin studies on ASD published to date. Thirteen primary twin studies were identified, seven were included in the meta-analysis by meeting Systematic Recruitment criterion; correction for selection and ascertainment strategies, and applied prevalences were assessed for these studies. In addition, a quantile DF extremes analysis was carried out on Childhood Autism Spectrum Test scores measured in a population sample of 6,413 twin pairs including affected twins.

RESULTS

The meta-analysis correlations for monozygotic twins (MZ) were almost perfect at .98 (95% Confidence Interval, .96-.99). The dizygotic (DZ) correlation, however, was .53 (95% CI .44-.60) when ASD prevalence rate was set at 5% (in line with the Broad Phenotype of ASD) and increased to .67 (95% CI .61-.72) when applying a prevalence rate of 1%. The meta-analytic heritability estimates were substantial: 64-91%. Shared environmental effects became significant as the prevalence rate decreased from 5-1%: 07-35%. The DF analyses show that for the most part, there is no departure from linearity in heritability.

CONCLUSIONS

We demonstrate that: (a) ASD is due to strong genetic effects; (b) shared environmental effects become significant as a function of lower prevalence rate; (c) previously reported significant shared environmental influences are likely a statistical artefact of overinclusion of concordant DZ twins.

Environmental risk factors for autism: an evidence-based review of systematic reviews and meta-analyses

BACKGROUND

According to recent evidence, up to 40-50% of variance in autism spectrum disorder (ASD) liability might be determined by environmental factors. In the present paper, we conducted a review of systematic reviews and meta-analyses of environmental risk factors for ASD. We assessed each review for quality of evidence and provided a brief overview of putative mechanisms of environmental risk factors for ASD.

FINDINGS

Current evidence suggests that several environmental factors including vaccination, maternal smoking, thimerosal exposure, and most likely assisted reproductive technologies are unrelated to risk of ASD. On the contrary, advanced parental age is associated with higher risk of ASD. Birth complications that are associated with trauma or ischemia and hypoxia have also shown strong links to ASD, whereas other pregnancy-related factors such as maternal obesity, maternal diabetes, and caesarian section have shown a less strong (but significant) association with risk of ASD. The reviews on nutritional elements have been inconclusive about the detrimental effects of deficiency in folic acid and omega 3, but vitamin D seems to be deficient in patients with ASD. The studies on toxic elements have been largely limited by their design, but there is enough evidence for the association between some heavy metals (most important inorganic mercury and lead) and ASD that warrants further investigation. Mechanisms of the association between environmental factors and ASD are debated but might include non-causative association (including confounding), gene-related effect, oxidative stress, inflammation, hypoxia/ischemia, endocrine disruption, neurotransmitter alterations, and interference with signaling pathways.

CONCLUSIONS

Compared to genetic studies of ASD, studies of environmental risk factors are in their infancy and have significant methodological limitations. Future studies of ASD risk factors would benefit from a developmental psychopathology approach, prospective design, precise exposure measurement, reliable timing of exposure in relation to critical developmental periods and should take into account the dynamic interplay between gene and environment by using genetically informed designs.

Deriving reproducible biomarkers from multi-site resting-state data: An Autism-based example

Resting-state functional Magnetic Resonance Imaging (R-fMRI) holds the promise to reveal functional biomarkers of neuropsychiatric disorders. However, extracting such biomarkers is challenging for complex multi-faceted neuropathologies, such as autism spectrum disorders. Large multi-site datasets increase sample sizes to compensate for this complexity, at the cost of uncontrolled heterogeneity. This heterogeneity raises new challenges, akin to those face in realistic diagnostic applications. Here, we demonstrate the feasibility of inter-site classification of neuropsychiatric status, with an application to the Autism Brain Imaging Data Exchange (ABIDE) database, a large (N=871) multi-site autism dataset. For this purpose, we investigate pipelines that extract the most predictive biomarkers from the data. These R-fMRI pipelines build participant-specific connectomes from functionally-defined brain areas. Connectomes are then compared across participants to learn patterns of connectivity that differentiate typical controls from individuals with autism. We predict this neuropsychiatric status for participants from the same acquisition sites or different, unseen, ones. Good choices of methods for the various steps of the pipeline lead to 67% prediction accuracy on the full ABIDE data, which is significantly better than previously reported results. We perform extensive validation on multiple subsets of the data defined by different inclusion criteria. These enables detailed analysis of the factors contributing to successful connectome-based prediction. First, prediction accuracy improves as we include more subjects, up to the maximum amount of subjects available. Second, the definition of functional brain areas is of paramount importance for biomarker discovery: brain areas extracted from large R-fMRI datasets outperform reference atlases in the classification tasks.

Excitation/Inhibition Imbalance in Animal Models of Autism Spectrum Disorders

Imbalances between excitation and inhibition in synaptic transmission and neural circuits have been implicated in autism spectrum disorders. Excitation and inhibition imbalances are frequently observed in animal models of autism spectrum disorders, and their correction normalizes key autistic-like phenotypes in these animals. These results suggest that excitation and inhibition imbalances may contribute to the development and maintenance of autism spectrum disorders and represent an important therapeutic target.

Blood-brain barrier and intestinal epithelial barrier alterations in autism spectrum disorders

Background

Autism spectrum disorders (ASD) are complex conditions whose pathogenesis may be attributed to gene–environment interactions. There are no definitive mechanisms explaining how environmental triggers can lead to ASD although the involvement of inflammation and immunity has been suggested. Inappropriate antigen trafficking through an impaired intestinal barrier, followed by passage of these antigens or immune-activated complexes through a permissive blood–brain barrier (BBB), can be part of the chain of events leading to these disorders. Our goal was to investigate whether an altered BBB and gut permeability is part of the pathophysiology of ASD.

Methods

Postmortem cerebral cortex and cerebellum tissues from ASD, schizophrenia (SCZ), and healthy subjects (HC) and duodenal biopsies from ASD and HC were analyzed for gene and protein expression profiles. Tight junctions and other key molecules associated with the neurovascular unit integrity and function and neuroinflammation were investigated.

Results

Claudin (CLDN)-5 and -12 were increased in the ASD cortex and cerebellum. CLDN-3, tricellulin, and MMP-9 were higher in the ASD cortex. IL-8, tPA, and IBA-1 were downregulated in SCZ cortex; IL-1b was increased in the SCZ cerebellum. Differences between SCZ and ASD were observed for most of the genes analyzed in both brain areas. CLDN-5 protein was increased in ASD cortex and cerebellum, while CLDN-12 appeared reduced in both ASD and SCZ cortexes. In the intestine, 75% of the ASD samples analyzed had reduced expression of barrier-forming TJ components (CLDN-1, OCLN, TRIC), whereas 66% had increased pore-forming CLDNs (CLDN-2, -10, -15) compared to controls.

Conclusions

In the ASD brain, there is an altered expression of genes associated with BBB integrity coupled with increased neuroinflammation and possibly impaired gut barrier integrity. While these findings seem to be specific for ASD, the possibility of more distinct SCZ subgroups should be explored with additional studies.

Altered gut microbiota and activity in a murine model of autism spectrum disorders

Autism spectrum disorder (ASD) is a heterogeneous group of complex neurodevelopmental disorders with evidence of genetic predisposition. Intestinal disturbances are reported in ASD patients and compositional changes in gut microbiota are described. However, the role of microbiota in brain disorders is poorly documented. Here, we used a murine model of ASD to investigate the relation between gut microbiota and autism-like behaviour. Using next generation sequencing technology, microbiota composition was investigated in mice in utero exposed to valproic acid (VPA). Moreover, levels of short chain fatty acids (SCFA) and lactic acid in caecal content were determined. Our data demonstrate a transgenerational impact of in utero VPA exposure on gut microbiota in the offspring. Prenatal VPA exposure affected operational taxonomic units (OTUs) assigned to genera within the main phyla of Bacteroidetes and Firmicutes and the order of Desulfovibrionales, corroborating human ASD studies. In addition, OTUs assigned to genera of Alistipes, Enterorhabdus, Mollicutes and Erysipelotrichalis were especially associated with male VPA-exposed offspring. The microbial differences of VPA in utero-exposed males deviated from those observed in females and was (i) positively associated with increased levels of caecal butyrate as well as ileal neutrophil infiltration and (ii) inversely associated with intestinal levels of serotonin and social behaviour scores. These findings show that autism-like behaviour and its intestinal phenotype is associated with altered microbial colonization and activity in a murine model for ASD, with preponderance in male offspring. These results open new avenues in the scientific trajectory of managing neurodevelopmental disorders by gut microbiome modulation.

Altered functional and structural brain network organization in autism

Structural and functional underconnectivity have been reported for multiple brain regions, functional systems, and white matter tracts in individuals with autism spectrum disorders (ASD). Although recent developments in complex network analysis have established that the brain is a modular network exhibiting small-world properties, network level organization has not been carefully examined in ASD. Here we used resting-state functional MRI (n = 42 ASD, n = 37 typically developing; TD) to show that children and adolescents with ASD display reduced short and long-range connectivity within functional systems (i.e., reduced functional integration) and stronger connectivity between functional systems (i.e., reduced functional segregation), particularly in default and higher-order visual regions. Using graph theoretical methods, we show that pairwise group differences in functional connectivity are reflected in network level reductions in modularity and clustering (local efficiency), but shorter characteristic path lengths (higher global efficiency). Structural networks, generated from diffusion tensor MRI derived fiber tracts (n = 51 ASD, n = 43 TD), displayed lower levels of white matter integrity yet higher numbers of fibers. TD and ASD individuals exhibited similar levels of correlation between raw measures of structural and functional connectivity (n = 35 ASD, n = 35 TD). However, a principal component analysis combining structural and functional network properties revealed that the balance of local and global efficiency between structural and functional networks was reduced in ASD, positively correlated with age, and inversely correlated with ASD symptom severity. Overall, our findings suggest that modeling the brain as a complex network will be highly informative in unraveling the biological basis of ASD and other neuropsychiatric disorders.

Default mode network in childhood autism: posteromedial cortex heterogeneity and relationship with social deficits

BACKGROUND

The default mode network (DMN), a brain system anchored in the posteromedial cortex, has been identified as underconnected in adults with autism spectrum disorder (ASD). However, to date there have been no attempts to characterize this network and its involvement in mediating social deficits in children with ASD. Furthermore, the functionally heterogeneous profile of the posteromedial cortex raises questions regarding how altered connectivity manifests in specific functional modules within this brain region in children with ASD.

METHODS

Resting-state functional magnetic resonance imaging and an anatomically informed approach were used to investigate the functional connectivity of the DMN in 20 children with ASD and 19 age-, gender-, and IQ-matched typically developing (TD) children. Multivariate regression analyses were used to test whether altered patterns of connectivity are predictive of social impairment severity.

RESULTS

Compared with TD children, children with ASD demonstrated hyperconnectivity of the posterior cingulate and retrosplenial cortices with predominately medial and anterolateral temporal cortex. In contrast, the precuneus in ASD children demonstrated hypoconnectivity with visual cortex, basal ganglia, and locally within the posteromedial cortex. Aberrant posterior cingulate cortex hyperconnectivity was linked with severity of social impairments in ASD, whereas precuneus hypoconnectivity was unrelated to social deficits. Consistent with previous work in healthy adults, a functionally heterogeneous profile of connectivity within the posteromedial cortex in both TD and ASD children was observed.

CONCLUSIONS

This work links hyperconnectivity of DMN-related circuits to the core social deficits in young children with ASD and highlights fundamental aspects of posteromedial cortex heterogeneity.

Efficacy of early interventions for infants and young children with, and at risk for, autism spectrum disorders

With advances in the field's ability to identify autism spectrum disorders (ASD) at younger ages, the need for information about the evidence-base for early intervention continues to rise. This review of the ASD early intervention (EI) literature focuses on efficacy studies published within the past 15 years. The neurodevelopmental context for early intervention, timing of initiating intervention, primary intervention approaches, and predictors of treatment outcomes are discussed. The evidence indicates that young children with ASD benefit from EI, and their parents learn to implement child-responsive engagement strategies when a parent-coaching intervention is provided. Evidence supports combining parent-mediated and direct clinician-implemented intervention to maximize child developmental gains. Clinical practice recommendations are presented, based on the literature reviewed.

Oxytocin and vasopressin neural networks: Implications for social behavioral diversity and translational neuroscience

Oxytocin- and vasopressin-related systems are present in invertebrate and vertebrate bilaterian animals, including humans, and exhibit conserved neuroanatomical and functional properties. In vertebrates, these systems innervate conserved neural networks that regulate social learning and behavior, including conspecific recognition, social attachment, and parental behavior. Individual and species-level variation in central organization of oxytocin and vasopressin systems has been linked to individual and species variation in social learning and behavior. In humans, genetic polymorphisms in the genes encoding oxytocin and vasopressin peptides and/or their respective target receptors have been associated with individual variation in social recognition, social attachment phenotypes, parental behavior, and psychiatric phenotypes such as autism. Here we describe both conserved and variable features of central oxytocin and vasopressin systems in the context of social behavioral diversity, with a particular focus on neural networks that modulate social learning, behavior, and salience of sociosensory stimuli during species-typical social contexts.

The Effects of Early Intervention on Social Communication Outcomes for Children with Autism Spectrum Disorder: A Meta-analysis

This meta-analysis examined the effects of early interventions on social communication outcomes for young children with autism spectrum disorder. A systematic review of the literature included 1442 children (mean age 3.55 years) across 29 studies. The overall effect size of intervention on social communication outcomes was significant (g = 0.36). The age of the participants was related to the treatment effect size on social communication outcomes, with maximum benefits occurring at age 3.81 years. Results did not differ significantly depending on the person implementing the intervention. However, significantly larger effect sizes were observed in studies with context-bound outcome measures. The findings of this meta-analysis highlight the need for further research examining specific components of interventions associated with greater and more generalized gains.

Probiotics and fructo-oligosaccharide intervention modulate the microbiota-gut brain axis to improve autism spectrum reducing also the hyper-serotonergic state and the dopamine metabolism disorder

The prevalence of autism spectrum disorders (ASD) is increasing, but its etiology remains elusive and hence an effective treatment is not available. Previous research conducted on animal models suggests that microbiota-gut-brain axis may contribute to ASD pathology and more human research is needed. This study was divided into two stages,.At the discovery stage, we compared the differences in gut microbiota profiles (using 16S rRNA sequencing), fecal SCFAs (using GC-MS) and plasma neurotransmitters (using UHPLC-MS/MS) of 26 children with ASD and 24 normal children. All 26 children with ASD participated in the intervention stage, and we measured the gut microbiota profiles, SCFAs and neurotransmitters before and after probiotics + FOS (n = 16) or placebo supplementation (n = 10). We found that gut microbiota was in a state of dysbiosis and significantly lower levels of Bifidobacteriales and Bifidobacterium longum were observed at the discovery stage in children with ASD. An increase in beneficial bacteria (Bifidobacteriales and B. longum) and suppression of suspected pathogenic bacteria (Clostridium) emerged after probiotics + FOS intervention, with significant reduction in the severity of autism and gastrointestinal symptoms. Compared to children in the control group, significantly lower levels of acetic acid, propionic acid and butyric acid were found, and a hyperserotonergic state (increased serotonin) and dopamine metabolism disorder (decreased homovanillic acid) were observed in children with ASD. Interestingly, the above SCFAs in children with autism significantly elevated after probiotics + FOS intervention and approached those in the control group. In addition, our data demonstrated that decreased serotonin and increased homovanillic acid emerged after probiotics + FOS intervention. However, the above-mentioned changes did not appear in the placebo group for ASD children. Probiotics + FOS intervention can modulate gut microbiota, SCFAs and serotonin in association with improved ASD symptoms, including a hyper-serotonergic state and dopamine metabolism disorder.

Maternal high fat diet consumption during the perinatal period programs offspring behavior

The environment that a developing offspring experiences during the perinatal period is markedly influenced by maternal health and diet composition. Evidence from both epidemiological studies and animal models indicates that maternal diet and metabolic status play a critical role in programming the neural circuitry that regulates behavior, resulting in long-term consequences for offspring behavior. Maternal diet and metabolic state influence the behavior of offspring directly by impacting the intrauterine environment and indirectly by modulating maternal behavior. The mechanisms by which maternal diet and metabolic profile shape the perinatal environment remain largely unknown, but recent research has found that increases in inflammatory cytokines, nutrients (glucose and fatty acids), and hormones (insulin and leptin) affect the environment of the developing offspring. Offspring exposed to maternal obesity and high fat diet consumption during development are more susceptible to developing mental health and behavioral disorders such as anxiety, depression, attention deficit hyperactivity disorder, and autism spectrum disorders. Recent evidence suggests that this increased risk for behavioral disorders is driven by modifications in the development of neural pathways involved in behavioral regulation. In particular, research indicates that the development of the serotonergic system is impacted by exposure to maternal obesity and high fat diet consumption, and this disruption may underlie many of the behavioral disturbances observed in these offspring. Given the high rates of obesity and high fat diet consumption in pregnant women, it is vital to examine the influence that maternal nutrition and metabolic profile have on the developing offspring.

Genetic epidemiology and insights into interactive genetic and environmental effects in autism spectrum disorders

Understanding the pathogenesis of neurodevelopmental disorders has proven to be challenging. Using autism spectrum disorder (ASD) as a paradigmatic neurodevelopmental disorder, this article reviews the existing literature on the etiological substrates of ASD and explores how genetic epidemiology approaches including gene-environment interactions (G×E) can play a role in identifying factors associated with ASD etiology. New genetic and bioinformatics strategies have yielded important clues to ASD genetic substrates. The next steps for understanding ASD pathogenesis require significant effort to focus on how genes and environment interact with one another in typical development and its perturbations. Along with larger sample sizes, future study designs should include sample ascertainment that is epidemiologic and population-based to capture the entire ASD spectrum with both categorical and dimensional phenotypic characterization; environmental measurements with accuracy, validity, and biomarkers; statistical methods to address population stratification, multiple comparisons, and G×E of rare variants; animal models to test hypotheses; and new methods to broaden the capacity to search for G×E, including genome-wide and environment-wide association studies, precise estimation of heritability using dense genetic markers, and consideration of G×E both as the disease cause and a disease course modifier. Although examination of G×E appears to be a daunting task, tremendous recent progress in gene discovery has opened new horizons for advancing our understanding of the role of G×E in the pathogenesis of ASD and ultimately identifying the causes, treatments, and even preventive measures for ASD and other neurodevelopmental disorders.

Confirmation of chromosomal microarray as a first-tier clinical diagnostic test for individuals with developmental delay, intellectual disability, autism spectrum disorders and dysmorphic features

BACKGROUND AND OBJECTIVES

Submicroscopic chromosomal rearrangements are the most common identifiable causes of intellectual disability and autism spectrum disorders associated with dysmorphic features. Chromosomal microarray (CMA) can detect copy number variants <1 Mb and identifies size and presence of known genes. The aim of this study was to demonstrate the usefulness of CMA, as a first-tier tool in detecting the etiology of unexplained intellectual disability/autism spectrum disorders (ID/ASDs) associated with dysmorphic features in a large cohort of pediatric patients.

PATIENTS AND METHODS

We studied 349 individuals; 223 males, 126 females, aged 5 months-19 years. Blood samples were analyzed with CMA at a resolution ranging from 1 Mb to 40 Kb. The imbalance was confirmed by FISH or qPCR. We considered copy number variants (CNVs) causative if the variant was responsible for a known syndrome, encompassed gene/s of known function, occurred de novo or, if inherited, the parent was variably affected, and/or the involved gene/s had been reported in association with ID/ASDs in dedicated databases.

RESULTS

91 CNVs were detected in 77 (22.06%) patients: 5 (6.49%) of those presenting with borderline cognitive impairment, 54 (70.13%) with a variable degree of DD/ID, and 18/77 (23.38%) with ID of variable degree and ASDs. 16/77 (20.8%) patients had two different rearrangements. Deletions exceeded duplications (58 versus 33); 45.05% (41/91) of the detected CNVs were de novo, 45.05% (41/91) inherited, and 9.9% (9/91) unknown. The CNVs caused the phenotype in 57/77 (74%) patients; 12/57 (21.05%) had ASDs/ID, and 45/57 (78.95%) had DD/ID.

CONCLUSIONS

Our study provides further evidence of the high diagnostic yield of CMA for genetic testing in children with unexplained ID/ASDs who had dysmorphic features. We confirm the value of CMA as the first-tier tool in the assessment of those conditions in the pediatric setting.

Exome sequencing of 457 autism families recruited online provides evidence for autism risk genes

Autism spectrum disorder (ASD) is a genetically heterogeneous condition, caused by a combination of rare de novo and inherited variants as well as common variants in at least several hundred genes. However, significantly larger sample sizes are needed to identify the complete set of genetic risk factors. We conducted a pilot study for SPARK (SPARKForAutism.org) of 457 families with ASD, all consented online. Whole exome sequencing (WES) and genotyping data were generated for each family using DNA from saliva. We identified variants in genes and loci that are clinically recognized causes or significant contributors to ASD in 10.4% of families without previous genetic findings. In addition, we identified variants that are possibly associated with ASD in an additional 3.4% of families. A meta-analysis using the TADA framework at a false discovery rate (FDR) of 0.1 provides statistical support for 26 ASD risk genes. While most of these genes are already known ASD risk genes, BRSK2 has the strongest statistical support and reaches genome-wide significance as a risk gene for ASD (p-value = 2.3e-06). Future studies leveraging the thousands of individuals with ASD who have enrolled in SPARK are likely to further clarify the genetic risk factors associated with ASD as well as allow accelerate ASD research that incorporates genetic etiology.

Intellectual disability and autism spectrum disorders: causal genes and molecular mechanisms

Intellectual disability (ID) and autism spectrum disorder (ASD) are the most common developmental disorders present in humans. Combined, they affect between 3 and 5% of the population. Additionally, they can be found together in the same individual thereby complicating treatment. The causative factors (genes, epigenetic and environmental) are quite varied and likely interact so as to further complicate the assessment of an individual patient. Nonetheless, much valuable information has been gained by identifying candidate genes for ID or ASD. Understanding the etiology of either ID or ASD is of utmost importance for families. It allows a determination of the risk of recurrence, the possibility of other comorbidity medical problems, the molecular and cellular nature of the pathobiology and hopefully potential therapeutic approaches.

Cognitive and language skills in adults with autism: a 40-year follow-up

BACKGROUND

It is well established that very few individuals with autism spectrum disorders (ASD) and an IQ below 70 are able to live independently as adults. However, even amongst children with an IQ in the normal range, outcome is very variable. Childhood factors that predict later stability, improvement or decline in cognitive functioning remain uncertain and, in particular, very little is known about trajectories in later adulthood.

METHOD

Changes in cognitive and language ability from childhood to adulthood were assessed in 60 individuals with autism, all of whom had an IQ in the average range as children. Mean age in childhood = 6 years (range 2-13 years); mean age in adulthood = 44 years (range 29-64 years). Trajectories of change and factors related to current cognitive abilities were explored.

RESULTS

For the majority of participants (N = 45, 75%), who were testable both as children and adults, IQ remained very stable and language also improved over time. However, 15 individuals could not be assessed on standard tests as adults and their developmental level could be estimated only on the Vineland Adaptive Behavior Scales. Almost all these adults (apart from one who had suffered a major stroke) showed severe aggressive or self-injurious behaviours; none had ever developed language above a 3-year level, and seven had developed epilepsy.

CONCLUSIONS

For most individuals with autism who had an IQ in the average range (i.e. ≥ 70) as children, childhood IQ proved a reliable predictor of cognitive functioning well into mid- to- later adulthood. However, a significant minority was no longer testable on standard tests as adults. Their current very low levels of functional ability were generally associated with severe behavioural disturbance and persisting and severe language impairment; 50% of these individuals had also developed epilepsy, pointing to the role of organic brain dysfunction. Implications for early intervention are discussed.

CACNA1D de novo mutations in autism spectrum disorders activate Cav1.3 L-type calcium channels

BACKGROUND

Cav1.3 voltage-gated L-type calcium channels (LTCCs) are part of postsynaptic neuronal signaling networks. They play a key role in brain function, including fear memory and emotional and drug-taking behaviors. A whole-exome sequencing study identified a de novo mutation, p.A749G, in Cav1.3 α1-subunits (CACNA1D), the second main LTCC in the brain, as 1 of 62 high risk-conferring mutations in a cohort of patients with autism and intellectual disability. We screened all published genetic information available from whole-exome sequencing studies and identified a second de novo CACNA1D mutation, p.G407R. Both mutations are present only in the probands and not in their unaffected parents or siblings.

METHODS

We functionally expressed both mutations in tsA-201 cells to study their functional consequences using whole-cell patch-clamp.

RESULTS

The mutations p.A749G and p.G407R caused dramatic changes in channel gating by shifting (~15 mV) the voltage dependence for steady-state activation and inactivation to more negative voltages (p.A749G) or by pronounced slowing of current inactivation during depolarizing stimuli (p.G407R). In both cases, these changes are compatible with a gain-of-function phenotype.

CONCLUSIONS

Our data, together with the discovery that Cav1.3 gain-of-function causes primary aldosteronism with seizures, neurologic abnormalities, and intellectual disability, suggest that Cav1.3 gain-of-function mutations confer a major part of the risk for autism in the two probands and may even cause the disease. Our findings have immediate clinical relevance because blockers of LTCCs are available for therapeutic attempts in affected individuals. Patients should also be explored for other symptoms likely resulting from Cav1.3 hyperactivity, in particular, primary aldosteronism.

Annual Research Review: Looking back to look forward - changes in the concept of autism and implications for future research

The concept of autism is a significant contribution from child psychiatry that has entered wider culture and public consciousness, and has evolved significantly over the last four decades. Taking a rather personal retrospective, reflecting on our own time in autism research, this review explores changes in the concept of autism and the implications of these for future research. We focus on seven major changes in how autism is thought of, operationalised, and recognised: (1) from a narrow definition to wide diagnostic criteria; (2) from a rare to a relatively common condition, although probably still under-recognised in women; (3) from something affecting children, to a lifelong condition; (4) from something discreet and distinct, to a dimensional view; (5) from one thing to many 'autisms', and a compound or 'fractionable' condition; (6) from a focus on 'pure' autism, to recognition that complexity and comorbidity is the norm; and finally, (7) from conceptualising autism purely as a 'developmental disorder', to recognising a neurodiversity perspective, operationalised in participatory research models. We conclude with some challenges for the field and suggestions for areas currently neglected in autism research.

Prevalence and neonatal factors associated with autism spectrum disorders in preterm infants

OBJECTIVES

To determine the prevalence of autism spectrum disorders (ASD) across gestational age, examine the risk of ASD by gestational age controlling for other risk factors, and identify potential risk factors in the neonatal intensive care unit.

STUDY DESIGN

A retrospective cohort of infants born at ≥ 24 weeks between January 1, 2000, and December 31, 2007 at 11 Kaiser Permanente Northern California hospitals (n = 195,021). ASD cases were defined by a diagnosis made at a Kaiser Permanente ASD evaluation center, by a clinical specialist, or by a pediatrician. Cox proportional hazards regression models were used to evaluate the association between gestational age and ASD as well as potential risk factors in the neonatal intensive care unit and ASD.

RESULTS

The prevalence of ASD in infants <37 weeks was 1.78% compared with 1.22% in infants born ≥ 37 weeks (P < .001). Compared with term infants, infants born at 24-26 weeks had an adjusted hazard ratio (HR) for a diagnosis of ASD of 2.7 (95% CI 1.5-5.0). Infants born at 27-33 weeks (adjusted HR 1.4, 95% CI 1.1-1.8) and 34-36 weeks (adjusted HR 1.3, 95% CI 1.1-1.4) were also at increased risk. High frequency ventilation and intracranial hemorrhage were associated with ASD in infants < 34 weeks.

CONCLUSIONS

ASD was ~ 3 times more prevalent in infants <27 weeks compared with term infants. Each week of shorter gestation was associated with an increased risk of ASD. High frequency ventilation and intracranial hemorrhage were associated with ASD among infants <34 weeks.

Paediatric population neuroimaging and the Generation R Study: the second wave

Paediatric population neuroimaging is an emerging field that falls at the intersection between developmental neuroscience and epidemiology. A key feature of population neuroimaging studies involves large-scale recruitment that is representative of the general population. One successful approach for population neuroimaging is to embed neuroimaging studies within large epidemiological cohorts. The Generation R Study is a large, prospective population-based birth-cohort in which nearly 10,000 pregnant mothers were recruited between 2002 and 2006 with repeated measurements in the children and their parents over time. Magnetic resonance imaging was included in 2009 with the scanning of 1070 6-to-9-year-old children. The second neuroimaging wave was initiated in April 2013 with a total of 4245 visiting the MRI suite and 4087 9-to-11-year-old children being scanned. The sequences included high-resolution structural MRI, 35-direction diffusion weighted imaging, and a 6 min and 2 s resting-state functional MRI scan. The goal of this paper is to provide an overview of the imaging protocol and the overlap between the neuroimaging data and metadata. We conclude by providing a brief overview of results from our first wave of neuroimaging, which highlights a diverse array of questions that can be addressed by merging the fields of developmental neuroscience and epidemiology.

Update of a Meta-analysis of Sensory Symptoms in ASD: A New Decade of Research

This meta-analysis updated evidence regarding sensory over-responsivity (SOR), under-responsivity (SUR) and seeking symptoms in individuals with autism spectrum disorders (ASDs) relative to typical controls and those with other conditions. Fifty-five questionnaire studies included 4606 individuals with ASD. Moderators tested were age, IQ, male ratio, matching group, and self-report. Compared to typical controls, effect size was large and significant for SOR, SUR, and Seeking but heterogeneous. For Seeking, age, IQ and self-report were significant moderators. Compared with developmental disorders (DDs) groups, effect size was significantly positive for SOR and Seeking; whereas compared with other clinical groups, only SOR was significant. These findings highlight the core nature of sensory symptoms in ASD and particularly SOR. Explanatory factors are yet to be revealed.

Genetics and epigenetics of autism spectrum disorder-current evidence in the field

Autism spectrum disorders (ASD) is a heterogenous group of neurodevelopmental disorders characterized by problems in social interaction and communication as well as the presence of repetitive and stereotyped behavior. It is estimated that the prevalence of ASD is 1–2% in the general population with the average male to female ratio 4–5:1. Although the causes of ASD remain largely unknown, the studies have shown that both genetic and environmental factors play an important role in the etiology of these disorders. Array comparative genomic hybridization and whole exome/genome sequencing studies identified common and rare copy number or single nucleotide variants in genes encoding proteins involved in brain development, which play an important role in neuron and synapse formation and function. The genetic etiology is recognized in ~ 25–35% of patients with ASD. In this article, we review the current state of knowledge about the genetic etiology of ASD and also propose a diagnostic algorithm for patients.