Person:

Robinson, Elise

Background: This twin study investigated whether autistic traits during childhood were associated with adolescent psychotic experiences. Methods: Data were collected from a community sample of approximately 5000 twin pairs, which included 32 individuals with diagnosed autism spectrum conditions (ASC). Parents rated autistic traits in the twins at four points between ages 8–16 years. Positive, negative, and cognitive psychotic experiences were assessed at age 16 years using self- and parent-report scales. Longitudinal twin analyses tested the associations between these measures. Results: Autistic traits correlated weakly or nonsignificantly with positive psychotic experiences (paranoia, hallucinations, and grandiosity), and modestly with cognitive psychotic experiences (cognitive disorganisation). Higher correlations were observed for parent-rated negative symptoms and self-reported anhedonia, although the proportion of variance in both accounted for by autistic traits was low (10 and 31 %, respectively). The majority of the genetic influences on negative symptoms and anhedonia were independent of autistic traits. Additionally, individuals with ASC displayed significantly more negative symptoms, anhedonia, and cognitive disorganisation than controls. Conclusions: Autistic traits do not appear to be strongly associated with psychotic experiences in adolescence; associations were also largely restricted to negative symptoms. Of note, the degree to which the genetic and environmental causes of autistic traits influenced psychotic experiences was limited. These findings thus support a phenotypic and etiological distinction between autistic traits and psychotic experiences. Electronic supplementary material The online version of this article (doi:10.1186/s13229-015-0037-9) contains supplementary material, which is available to authorized users.

People with epilepsy must adopt many self-management behaviors, especially regarding medication adherence, stress management, and sleep quality. In response to the need for theory-based self-management programs that people with epilepsy can easily access, the WebEase Web site was created and tested for feasibility, acceptability, and usability. This article discusses the theoretical background and developmental phases of WebEase and lessons learned throughout the development process. The WebEase research team developed content for the Web site on the basis of social cognitive theory, the transtheoretical model of behavior change, and motivational interviewing. Formative research and development of the WebEase program included a literature search, computer use survey, a focus group, and review by content experts and consumers. The program has 2 main components: 1) the modules, which provide a tailored opportunity for learning, reflection, and goal setting, and 2) MyLog, a place to enter daily information.

The objective of this analysis was to examine the genetic architecture of diverse cognitive abilities in children and adolescents, including the magnitude of common genetic effects and patterns of shared and unique genetic influences. Subjects included 3,689 members of the Philadelphia Neurodevelopmental Cohort, a general population sample of ages 8-21 years who completed an extensive battery of cognitive tests. We used genome-wide complex trait analysis (GCTA) to estimate the SNP-based heritability of each domain, as well as the genetic correlation between all domains that showed significant genetic influence. Several of the individual domains suggested strong influence of common genetic variants (e.g. reading ability, h2g=0.43, p=4e-06; emotion identification, h2g=0.36, p=1e-05; verbal memory, h2g=0.24, p=0.005). The genetic correlations highlighted trait domains that are candidates for joint interrogation in future genetic studies (e.g. language reasoning and spatial reasoning, r(g)=0.72, p=0.007). These results can be used to structure future genetic and neuropsychiatric investigations of diverse cognitive abilities.

Spontaneously arising (‘de novo’) mutations play an important role in medical genetics. For diseases with extensive locus heterogeneity – such as autism spectrum disorders (ASDs) – the signal from de novo mutations (DNMs) is distributed across many genes, making it difficult to distinguish disease-relevant mutations from background variation. We provide a statistical framework for the analysis of DNM excesses per gene and gene set by calibrating a model of de novo mutation. We applied this framework to DNMs collected from 1,078 ASD trios and – while affirming a significant role for loss-of-function (LoF) mutations – found no excess of de novo LoF mutations in cases with IQ above 100, suggesting that the role of DNMs in ASD may reside in fundamental neurodevelopmental processes. We also used our model to identify ~1,000 genes that are significantly lacking functional coding variation in non-ASD samples and are enriched for de novo LoF mutations identified in ASD cases.

Almost all genetic risk factors for autism spectrum disorders (ASDs) can be found in the general population, but the effects of that risk are unclear in people not ascertained for neuropsychiatric symptoms. Using several large ASD consortia and population based resources (total n>38,000), we find genomewide genetic links between ASDs and typical variation in social behavior and adaptive functioning. This finding is evidenced through both LD score correlation and de novo variant analysis, indicating that multiple types of genetic risk for ASDs influence a continuum of behavioral and developmental traits, the severe tail of which can result in an ASD or other neuropsychiatric disorder diagnosis. A continuum model should inform the design and interpretation of studies of neuropsychiatric disease biology.

Disruptive and damaging ultra-rare variants (URVs) in highly constrained (HC) genes are enriched in individuals with neurodevelopmental disorders. In the general population, this class of variants was associated with a decrease in years of education (YOE; −3.1 months; P-value=3.3×10−8). This effect was stronger among high brain-expressed genes and explained more YOE variance than pathogenic copy number variation, but less than common variants. Disruptive and damaging URVs in HC genes influence the determinants of YOE in the general population.

Language difficulties have historically been viewed as integral to autism spectrum conditions (ASC), leading molecular genetic studies to consider whether ASC and language difficulties have overlapping genetic bases. The extent of genetic, and also environmental, overlap between ASC and language is, however, unclear. We hence conducted a twin study of the concurrent association between autistic traits and receptive language abilities. Internet-based language tests were completed by ~3,000 pairs of twins, while autistic traits were assessed via parent ratings. Twin model fitting explored the association between these measures in the full sample, while DeFries-Fulker analysis tested these associations at the extremes of the sample. Phenotypic associations between language ability and autistic traits were modest and negative. The degree of genetic overlap was also negative, indicating that genetic influences on autistic traits lowered language scores in the full sample (mean genetic correlation = −0.13). Genetic overlap was also low at the extremes of the sample (mean genetic correlation = 0.14), indicating that genetic influences on quantitatively defined language difficulties were largely distinct from those on extreme autistic traits. Variation in language ability and autistic traits were also associated with largely different nonshared environmental influences. Language and autistic traits are influenced by largely distinct etiological factors. This has implications for molecular genetic studies of ASC and understanding the etiology of ASC. Additionally, these findings lend support to forthcoming DSM-5 changes to ASC diagnostic criteria that will see language difficulties separated from the core ASC communication symptoms, and instead listed as a clinical specifier.

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 ASD cases and 27,969 controls that identifies five genome-wide significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), seven additional loci shared with other traits are identified at equally strict significance levels. Dissecting the polygenic architecture we find both quantitative and qualitative polygenic heterogeneity across ASD subtypes, in contrast to what is typically seen in other complex disorders. These results highlight biological insights, particularly relating to neuronal function and corticogenesis and establish that GWAS performed at scale will be much more productive in the near term in ASD, just as it has been in a broad range of important psychiatric and diverse medical phenotypes.

Identifying genetic correlations between complex traits and diseases can provide useful etiological insights and help prioritize likely causal relationships. The major challenges preventing estimation of genetic correlation from genome-wide association study (GWAS) data with current methods are the lack of availability of individual genotype data and widespread sample overlap among meta-analyses. We circumvent these difficulties by introducing a technique – cross-trait LD Score regression – for estimating genetic correlation that requires only GWAS summary statistics and is not biased by sample overlap. We use this method to estimate 276 genetic correlations among 24 traits. The results include genetic correlations between anorexia nervosa and schizophrenia, anorexia and obesity and associations between educational attainment and several diseases. These results highlight the power of genome-wide analyses, since there currently are no significantly associated SNPs for anorexia nervosa and only three for educational attainment.

Autism spectrum disorder (ASD) risk is influenced by common polygenic and de novo variation. We aimed to clarify the influence of polygenic risk for ASDs and to identify subgroups of ASD cases, including those with strong acting de novo variants, in which polygenic risk is relevant. Using a novel approach called the polygenic transmission disequilibrium test, and data from 6,454 families with a child with ASD, we show that polygenic risk for ASDs, schizophrenia, and greater educational attainment is over transmitted to children with ASDs. These findings hold independent of proband IQ. We find that polygenic variation contributes additively to risk in ASD cases who carry a strong acting de novo variant. Lastly, we show that elements of polygenic risk are independent and differ in their relationship with phenotype. These results confirm that ASDs’ genetic influences are additive and suggest they create risk through at least partially distinct etiologic pathways.