Elise B. Robinson

An atlas of genetic correlations across human diseases and traits

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-level 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 educational attainment and several diseases. These results highlight the power of genome-wide analyses, as there currently are no significantly associated SNPs for anorexia nervosa and only three for educational attainment.

A framework for the interpretation of de novo mutation in human disease

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.

Insights into Autism Spectrum Disorder Genomic Architecture and Biology from 71 Risk Loci

Analysis of de novo CNVs (dnCNVs) from the full Simons Simplex Collection (SSC) (N = 2,591 families) replicates prior findings of strong association with autism spectrum disorders (ASDs) and confirms six risk loci (1q21.1, 3q29, 7q11.23, 16p11.2, 15q11.2-13, and 22q11.2). The addition of published CNV data from the Autism Genome Project (AGP) and exome sequencing data from the SSC and the Autism Sequencing Consortium (ASC) shows that genes within small de novo deletions, but not within large dnCNVs, significantly overlap the high-effect risk genes identified by sequencing. Alternatively, large dnCNVs are found likely to contain multiple modest-effect risk genes. Overall, we find strong evidence that de novo mutations are associated with ASD apart from the risk for intellectual disability. Extending the transmission and de novo association test (TADA) to include small de novo deletions reveals 71 ASD risk loci, including 6 CNV regions (noted above) and 65 risk genes (FDR ≤ 0.1).

Examining and interpreting the female protective effect against autistic behavior

Male preponderance in autistic behavioral impairment has been explained in terms of a hypothetical protective effect of female sex, yet little research has tested this hypothesis empirically. If females are protected, they should require greater etiologic load to manifest the same degree of impairment as males. The objective of this analysis was to examine whether greater familial etiologic load was associated with quantitative autistic impairments in females compared with males. Subjects included 3,842 dizygotic twin pairs from the Twins Early Development Study (TEDS) and 6,040 dizygotic twin pairs from the Child and Adolescent Twin Study of Sweden (CATSS). In both samples, we compared sibling autistic traits between female and male probands, who were identified as children scoring in the top 90th and 95th percentiles of the population autistic trait distributions. In both TEDS and CATSS, siblings of female probands above the 90th percentile had significantly more autistic impairments than the siblings of male probands above the 90th percentile. The siblings of female probands above the 90th percentile also had greater categorical recurrence risk in both TEDS and CATSS. Results were similar in probands above the 95th percentile. This finding, replicated across two nationally-representative samples, suggests that female sex protects girls from autistic impairments and that girls may require greater familial etiologic load to manifest the phenotype. It provides empirical support for the hypothesis of a female protective effect against autistic behavior and can be used to inform and interpret future gene finding efforts in autism spectrum disorders.

Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population

Almost all genetic risk factors for autism spectrum disorders (ASDs) can be found in the general population, but the effects of this risk are unclear in people not ascertained for neuropsychiatric symptoms. Using several large ASD consortium and population-based resources (total n > 38,000), we find genome-wide 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 diagnosis with an ASD or other neuropsychiatric disorder. A continuum model should inform the design and interpretation of studies of neuropsychiatric disease biology.

Prenatal antidepressant exposure is associated with risk for attention-deficit hyperactivity disorder but not autism spectrum disorder in a large health system

Previous studies suggested that risk for Autism Spectrum Disorder (ASD) may be increased in children exposed to antidepressants during the prenatal period. The disease specificity of this risk has not been addressed and the possibility of confounding has not been excluded. Children with ASD or attention-deficit hyperactivity disorder (ADHD) delivered in a large New England health-care system were identified from electronic health records (EHR), and each diagnostic group was matched 1:3 with children without ASD or ADHD. All children were linked with maternal health data using birth certificates and EHRs to determine prenatal medication exposures. Multiple logistic regression was used to examine association between prenatal antidepressant exposures and ASD or ADHD risk. A total of 1377 children diagnosed with ASD and 2243 with ADHD were matched with healthy controls. In models adjusted for sociodemographic features, antidepressant exposure prior to and during pregnancy was associated with ASD risk, but risk associated with exposure during pregnancy was no longer significant after controlling for maternal major depression (odds ratio (OR) 1.10 (0.70–1.70)). Conversely, antidepressant exposure during but not prior to pregnancy was associated with ADHD risk, even after adjustment for maternal depression (OR 1.81 (1.22–2.70)). These results suggest that the risk of autism observed with prenatal antidepressant exposure is likely confounded by severity of maternal illness, but further indicate that such exposure may still be associated with ADHD risk. This risk, modest in absolute terms, may still be a result of residual confounding and must be balanced against the substantial consequences of untreated maternal depression.

Stability of Autistic Traits in the General Population: Further Evidence for a Continuum of Impairment

OBJECTIVE This study investigated the developmental course of autistic traits in a nationally representative sample of subjects 7 to 13 years of age. METHOD The parents of 6,539 children in the Avon Longitudinal Study of Parents and Children completed the Social and Communication Disorders Checklist at ages 7, 10, and 13. The phenotypic progression of autistic traits was assessed in the full sample and in high-scoring individuals (e.g., top 10%, 5%). Gender, IQ, and overall behavior difficulties were examined as potentially relevant influences on autistic trait trajectories. RESULTS Autistic traits were highly stable in the general population overall and in the high-scoring groups. In the full sample, there was no change in mean Social and Communication Disorders Checklist scores for female subjects ages 7 to 13 (p = .43). Scores for male subjects decreased slightly, but significantly, on the order of 0.1 standard deviations (p < .001). There was no mean change in parent-rated autistic traits within any of the high-scoring groups. IQ was not related to phenotypic progression; high parent-rated behavior problems predicted slight improvement in Social and Communication Disorders Checklist scores over the course of the study period in high-scoring individuals (p < .01). CONCLUSIONS These findings suggest that autistic traits are highly stable in the general population, even in individuals with the highest concentrations of autism-like behaviors. Phenotypic stability is consistent with expectations for individuals with autism spectrum disorders, providing further support for a phenomenologic continuum across the clinical threshold. Moreover, the gap between female and male risk for autistic symptomology is consistent over time.

A multivariate twin study of autistic traits in 12-year-olds: testing the fractionable autism triad hypothesis

Autistic traits—social impairment, communication impairment, and restricted and repetitive behaviors and interests—are heritable in the general population. Previous analyses have consistently reported limited genetic and environmental overlap between autistic trait domains in samples assessed in middle childhood. Here we extend this research to parent-report data for 12-year-olds. Data from 5,944 pairs in the Twins Early Development Study were analyzed to explore the domain-specific heritability and degree of shared genetic and environmental influences across different autistic traits in the general population and among individuals scoring in the top 5% of each domain. Sex differences in the etiological estimates were also tested in these analyses. Autistic traits were moderately to highly heritable (0.58–0.88) at age 12. Bivariate genetic correlations in the full sample (0.18–0.40) and the extremes (0.24–0.67), as well as even lower unique environmental correlations, all suggested considerable fractionation of genetic and environmental influences across autistic trait domains, in line with previous findings.

Refining the role of de novo protein-truncating variants in neurodevelopmental disorders by using population reference samples

Recent research has uncovered an important role for de novo variation in neurodevelopmental disorders. Using aggregated data from 9,246 families with autism spectrum disorder, intellectual disability, or developmental delay, we found that ∼1/3 of de novo variants are independently present as standing variation in the Exome Aggregation Consortiums cohort of 60,706 adults, and these de novo variants do not contribute to neurodevelopmental risk. We further used a loss-of-function (LoF)-intolerance metric, pLI, to identify a subset of LoF-intolerant genes containing the observed signal of associated de novo protein-truncating variants (PTVs) in neurodevelopmental disorders. LoF-intolerant genes also carry a modest excess of inherited PTVs, although the strongest de novo–affected genes contribute little to this excess, thus suggesting that the excess of inherited risk resides in lower-penetrant genes. These findings illustrate the importance of population-based reference cohorts for the interpretation of candidate pathogenic variants, even for analyses of complex diseases and de novo variation.

Autism spectrum disorder severity reflects the average contribution of de novo and familial influences

Significance Autism spectrum disorder (ASD) research is complicated by heterogeneity. There are several types of genetic risk factors for ASDs, and that diversity may be reflected in case presentation. This study presents evidence for systematic variation in the genetic architecture of ASDs in which higher functioning cases, defined through cognitive and behavioral assessments, are more likely to manifest familial influences. This finding suggests that genetic and neurobiological research into ASDs and other neuropsychiatric disorders may be pursued more efficiently through greater phenotypic characterization. Autism spectrum disorders (ASDs) are a highly heterogeneous group of conditions—phenotypically and genetically—although the link between phenotypic variation and differences in genetic architecture is unclear. This study aimed to determine whether differences in cognitive impairment and symptom severity reflect variation in the degree to which ASD cases reflect de novo or familial influences. Using data from more than 2,000 simplex cases of ASD, we examined the relationship between intelligence quotient (IQ), behavior and language assessments, and rate of de novo loss of function (LOF) mutations and family history of broadly defined psychiatric disease (depressive disorders, bipolar disorder, and schizophrenia; history of psychiatric hospitalization). Proband IQ was negatively associated with de novo LOF rate (P = 0.03) and positively associated with family history of psychiatric disease (P = 0.003). Female cases had a higher frequency of sporadic genetic events across the severity distribution (P = 0.01). High rates of LOF mutation and low frequencies of family history of psychiatric illness were seen in individuals who were unable to complete a traditional IQ test, a group with the greatest degree of language and behavioral impairment. These analyses provide strong evidence that familial risk for neuropsychiatric disease becomes more relevant to ASD etiology as cases become higher functioning. The findings of this study reinforce that there are many routes to the diagnostic category of autism and could lead to genetic studies with more specific insights into individual cases.