Neuropsychiatric conditions such as autism and schizophrenia have long been attributed to genetic alterations, but identifying the genes responsible has proved challenging. Microarray experiments ...have now revealed abundant copy-number variation--a type of variation in which stretches of DNA are duplicated, deleted and sometimes rearranged--in the human population. Genes affected by copy-number variation are good candidates for research into disease susceptibility. The complexity of neuropsychiatric genetics, however, dictates that assessment of the biomedical relevance of copy-number variants and the genes that they affect needs to be considered in an integrated context.
Spontaneously arising (de novo) mutations have an important role in medical genetics. For diseases with extensive locus heterogeneity, such as autism spectrum disorders (ASDs), the signal from de ...novo mutations is distributed across many genes, making it difficult to distinguish disease-relevant mutations from background variation. Here we provide a statistical framework for the analysis of excesses in de novo mutation per gene and gene set by calibrating a model of de novo mutation. We applied this framework to de novo mutations collected from 1,078 ASD family trios, and, whereas we affirmed a significant role for loss-of-function mutations, we found no excess of de novo loss-of-function mutations in cases with IQ above 100, suggesting that the role of de novo mutations in ASDs might reside in fundamental neurodevelopmental processes. We also used our model to identify ∼1,000 genes that are significantly lacking in functional coding variation in non-ASD samples and are enriched for de novo loss-of-function mutations identified in ASD cases.
Because of the role played by miRNAs in post-transcriptional regulation of an array of genes, their impact in neuropsychiatric disease pathophysiology has increasingly been evident. In the present ...study, we assessed microRNA expression in prefrontal cortex (Brodmann area 10) of a well-characterized cohort of major depressed, bipolar, and schizophrenia subjects (obtained from Stanley Neuropathology Consortium; n = 15 in each group), using high throughput RT-PCR plates. Discrete miRNA alterations were observed in all disorders, as well as in suicide subjects (pooled across diagnostic categories) compared to all non-suicide subjects. The changes in the schizophrenia group were partially similar to those in the bipolar group, but distinct from changes in depression and suicide. Intriguingly, those miRNAs which were down-regulated in the schizophrenia group tended to be synaptically enriched, whereas up-regulated miRNAs tended not to be. To follow this up, we purified synaptosomes from pooled samples of the schizophrenia vs. control groups and subjected them to Illumina deep sequencing. There was a significant loss of small RNA expression in schizophrenia synaptosomes only for certain sequence lengths within the miRNA range. Moreover, 73 miRNAs were significantly down-regulated whereas only one was up-regulated. Strikingly, across all expressed miRNAs in synaptosomes, there was a significant inverse correlation between the fold-change of a given miRNA seen in schizophrenia and its synaptic enrichment ratio observed in controls. Thus, synaptic miRNAs tended to be down-regulated in schizophrenia, and the more highly synaptically enriched miRNAs tended to show greater down-regulation. These findings point to some deficit in miRNA biogenesis, transport, processing or turnover in schizophrenia that is selective for the synaptic compartment. A novel class of ncRNA-derived small RNAs, shown to be strongly induced during an early phase of learning in mouse, is also expressed in man, and at least one representative (SNORD85) was strongly down-regulated in schizophrenia synaptosomes.
Background: The Social Communication Questionnaire (SCQ), formerly the Autism Screening Questionnaire (ASQ), is based on a well‐validated parent interview, the Autism Diagnostic Interview (ADI). It ...has shown promise as a screening measure for autism spectrum disorders (ASDs) in a research‐referred older sample, though recent studies with younger children reported lower sensitivities when using the suggested cutoff of ≥15 to differentiate ASDs from children with nonspectrum disorders (NS).
Methods: Diagnostic discrimination of the SCQ was evaluated alone and in combination with the ADOS (Autism Diagnostic Observation Schedule) in a clinical and research‐referred sample of 590 children and adolescents (2 to 16 years), with best estimate consensus diagnoses of autism, pervasive developmental disorder, not otherwise specified (PDD‐NOS) and non‐ASD disorders. The SCQ was completed before the evaluation in most cases. Performance of the SCQ was also compared with the Autism Diagnostic Interview – Revised (ADI‐R).
Results: Absolute scores and sensitivity in the younger children and specificity for all groups were lower than reported in the original study. Using receiver operating curves (ROC) to examine the area under the curve (AUC), the SCQ was more similar to the ADI‐R total score in differentiating ASD from NS disorders in the older (8–10, >11) than younger age groups (<5, 5–7). Lowering the cutoff score in the 2 younger groups improved sensitivity, with specificity remaining relatively low in all groups. Using the SCQ in combination with the ADOS resulted in improved specificity. Diagnostic discrimination was best using the ADI‐R and ADOS in combination.
Conclusions: Those interested in using the SCQ should consider adjusting cutoff scores according to age and purpose, and using it in combination with another measure. Sensitivity or specificity may be prioritized for research or screening depending on goals.
Background: Standard case criteria are proposed for combined use of the Autism Diagnostic Interview-Revised and Autism Diagnostic Observation Schedule to diagnose autism and to define the broader ...category of autism spectrum disorders. Method: Single and combined Autism Diagnostic Interview-Revised and Autism Diagnostic Observation Schedule algorithms were compared to best estimate diagnoses in four samples: U.S. (n = 960) and Canadian (n = 232) participants 3 years and older, U.S. participants younger than 36 months (n = 270), and U.S. participants older than 36 months with profound mental retardation (n = 67). Results: Sensitivities and specificities of 80% and higher were obtained when strict criteria for an autism diagnosis using both instruments were applied in the U.S. samples, and 75% or greater in the Canadian sample. Single-instrument criteria resulted in significant loss of specificity. Specificity was poor in the sample with profound mental retardation. Lower sensitivity and specificity were also obtained when proposed criteria for broader spectrum disorders were applied. Conclusions: The Autism Diagnostic Interview-Revised and Autism Diagnostic Observation Schedule make independent, additive contributions to the judgment of clinicians that result in a more consistent and rigorous application of diagnostic criteria. (Contains 3 tables.)
Abstract Background Phenotypic heterogeneity in autism has long been conjectured to be a major hindrance to the discovery of genetic risk factors, leading to numerous attempts to stratify children ...based on phenotype to increase power of discovery studies. This approach, however, is based on the hypothesis that phenotypic heterogeneity closely maps to genetic variation, which has not been tested. Our study examines the impact of subphenotyping of a well-characterized autism spectrum disorder (ASD) sample on genetic homogeneity and the ability to discover common genetic variants conferring liability to ASD. Methods Genome-wide genotypic data of 2576 families from the Simons Simplex Collection were analyzed in the overall sample and phenotypic subgroups defined on the basis of diagnosis, IQ, and symptom profiles. We conducted a family-based association study, as well as estimating heritability and evaluating allele scores for each phenotypic subgroup. Results Association analyses revealed no genome-wide significant association signal. Subphenotyping did not increase power substantially. Moreover, allele scores built from the most associated single nucleotide polymorphisms, based on the odds ratio in the full sample, predicted case status in subsets of the sample equally well and heritability estimates were very similar for all subgroups. Conclusions In genome-wide association analysis of the Simons Simplex Collection sample, reducing phenotypic heterogeneity had at most a modest impact on genetic homogeneity. Our results are based on a relatively small sample, one with greater homogeneity than the entire population; if they apply more broadly, they imply that analysis of subphenotypes is not a productive path forward for discovering genetic risk variants in ASD.
Duplications of 15q11.2-q13.1 (Dup15q syndrome) are highly penetrant for autism spectrum disorder (ASD). A distinct electrophysiological (EEG) pattern characterized by excessive activity in the beta ...band has been noted in clinical reports. We asked whether EEG power in the beta band, as well as in other frequency bands, distinguished children with Dup15q syndrome from those with non-syndromic ASD and then examined the clinical correlates of this electrophysiological biomarker in Dup15q syndrome.
In the first study, we recorded spontaneous EEG from children with Dup15q syndrome (n = 11), age-and-IQ-matched children with ASD (n = 10) and age-matched typically developing (TD) children (n = 9) and computed relative power in 6 frequency bands for 9 regions of interest (ROIs). Group comparisons were made using a repeated measures analysis of variance. In the second study, we recorded spontaneous EEG from a larger cohort of individuals with Dup15q syndrome (n = 27) across two sites and examined age, epilepsy, and duplication type as predictors of beta power using simple linear regressions.
In the first study, spontaneous beta1 (12-20 Hz) and beta2 (20-30 Hz) power were significantly higher in Dup15q syndrome compared with both comparison groups, while delta (1-4 Hz) was significantly lower than both comparison groups. Effect sizes in all three frequency bands were large (|d| > 1). In the second study, we found that beta2 power was significantly related to epilepsy diagnosis in Dup15q syndrome.
Here, we have identified an electrophysiological biomarker of Dup15q syndrome that may facilitate clinical stratification, treatment monitoring, and measurement of target engagement for future clinical trials. Future work will investigate the genetic and neural underpinnings of this electrophysiological signature as well as the functional consequences of excessive beta oscillations in Dup15q syndrome.
Autism is a childhood neurodevelopmental disorder with a strong genetic component, yet the identification of autism susceptibility loci remains elusive. We investigated 180 autism probands and 372 ...control subjects by array comparative genomic hybridization (aCGH) using a 19K whole-genome tiling path bacterial artificial chromosome microarray to identify submicroscopic chromosomal rearrangements specific to autism. We discovered a recurrent 16p11.2 microdeletion in two probands with autism and none in controls. The deletion spans ∼500-kb and is flanked by ∼147-kb segmental duplications (SDs) that are >99% identical, a common characteristic of genomic disorders. We assessed the frequency of this new autism genomic disorder by screening an additional 532 probands and 465 controls by quantitative PCR and identified two more patients but no controls with the microdeletion, indicating a combined frequency of 0.6% (4/712 autism versus 0/837 controls; Fisher exact test P = 0.044). We confirmed all 16p11.2 deletions using fluorescence in situ hybridization, microsatellite analyses and aCGH, and mapped the approximate deletion breakpoints to the edges of the flanking SDs using a custom-designed high-density oligonucleotide microarray. Bioinformatic analysis localized 12 of the 25 genes within the microdeletion to nodes in one interaction network. We performed phenotype analyses and found no striking features that distinguish patients with the 16p11.2 microdeletion as a distinct autism subtype. Our work reports the first frequency, breakpoint, bioinformatic and phenotypic analyses of a de novo 16p11.2 microdeletion that represents one of the most common recurrent genomic disorders associated with autism to date.
Sensorimotor abnormalities are common in autism spectrum disorder (ASD) and among the earliest manifestations of the disorder. They have been studied far less than the social-communication and ...cognitive deficits that define ASD, but a mechanistic understanding of sensorimotor abnormalities in ASD may provide key insights into the neural underpinnings of the disorder. In this human study, we examined rapid, precision grip force contractions to determine whether feedforward mechanisms supporting initial motor output before sensory feedback can be processed are disrupted in ASD. Sustained force contractions also were examined to determine whether reactive adjustments to ongoing motor behavior based on visual feedback are altered. Sustained force was studied across multiple force levels and visual gains to assess motor and visuomotor mechanisms, respectively. Primary force contractions of individuals with ASD showed greater peak rate of force increases and large transient overshoots. Individuals with ASD also showed increased sustained force variability that scaled with force level and was more severe when visual gain was highly amplified or highly degraded. When sustaining a constant force level, their reactive adjustments were more periodic than controls, and they showed increased reliance on slower feedback mechanisms. Feedforward and feedback mechanism alterations each were associated with more severe social-communication impairments in ASD. These findings implicate anterior cerebellar circuits involved in feedforward motor control and posterior cerebellar circuits involved in transforming visual feedback into precise motor adjustments in ASD.
Many factors affect the risks for neurodevelopmental maladies such as autism spectrum disorders (ASD) and intellectual disability (ID). To compare environmental, phenotypic, socioeconomic and ...state-policy factors in a unified geospatial framework, we analyzed the spatial incidence patterns of ASD and ID using an insurance claims dataset covering nearly one third of the US population. Following epidemiologic evidence, we used the rate of congenital malformations of the reproductive system as a surrogate for environmental exposure of parents to unmeasured developmental risk factors, including toxins. Adjusted for gender, ethnic, socioeconomic, and geopolitical factors, the ASD incidence rates were strongly linked to population-normalized rates of congenital malformations of the reproductive system in males (an increase in ASD incidence by 283% for every percent increase in incidence of malformations, 95% CI: 91%, 576%, p<6×10(-5)). Such congenital malformations were barely significant for ID (94% increase, 95% CI: 1%, 250%, p = 0.0384). Other congenital malformations in males (excluding those affecting the reproductive system) appeared to significantly affect both phenotypes: 31.8% ASD rate increase (CI: 12%, 52%, p<6×10(-5)), and 43% ID rate increase (CI: 23%, 67%, p<6×10(-5)). Furthermore, the state-mandated rigor of diagnosis of ASD by a pediatrician or clinician for consideration in the special education system was predictive of a considerable decrease in ASD and ID incidence rates (98.6%, CI: 28%, 99.99%, p = 0.02475 and 99% CI: 68%, 99.99%, p = 0.00637 respectively). Thus, the observed spatial variability of both ID and ASD rates is associated with environmental and state-level regulatory factors; the magnitude of influence of compound environmental predictors was approximately three times greater than that of state-level incentives. The estimated county-level random effects exhibited marked spatial clustering, strongly indicating existence of as yet unidentified localized factors driving apparent disease incidence. Finally, we found that the rates of ASD and ID at the county level were weakly but significantly correlated (Pearson product-moment correlation 0.0589, p = 0.00101), while for females the correlation was much stronger (0.197, p<2.26×10(-16)).
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