Sharing parental genomes by siblings concordant or discordant for autism.

Studying thousands of families, we find siblings concordant for autism share more of their parental genomes than expected by chance, and discordant siblings share less, consistent with a role of transmission in autism incidence. The excess sharing of the father is highly significant (p value of 0.0014), with less significance for the mother (p value of 0.31). To compare parental sharing, we adjust for differences in meiotic recombination to obtain a p value of 0.15 that they are shared equally. These observations are contrary to certain models in which the mother carries a greater load than the father. Nevertheless, we present models in which greater sharing of the father is observed even though the mother carries a greater load. More generally, our observations of sharing establish quantitative constraints that any complete genetic model of autism must satisfy, and our methods may be applicable to other complex disorders.

Rates of contributory de novo mutation in high and low-risk autism families.

Autism arises in high and low-risk families. De novo mutation contributes to autism incidence in low-risk families as there is a higher incidence in the affected of the simplex families than in their unaffected siblings. But the extent of contribution in low-risk families cannot be determined solely from simplex families as they are a mixture of low and high-risk. The rate of de novo mutation in nearly pure populations of high-risk families, the multiplex families, has not previously been rigorously determined. Moreover, rates of de novo mutation have been underestimated from studies based on low resolution microarrays and whole exome sequencing. Here we report on findings from whole genome sequence (WGS) of both simplex families from the Simons Simplex Collection (SSC) and multiplex families from the Autism Genetic Resource Exchange (AGRE). After removing the multiplex samples with excessive cell-line genetic drift, we find that the contribution of de novo mutation in multiplex is significantly smaller than the contribution in simplex. We use WGS to provide high resolution CNV profiles and to analyze more than coding regions, and revise upward the rate in simplex autism due to an excess of de novo events targeting introns. Based on this study, we now estimate that de novo events contribute to 52-67% of cases of autism arising from low risk families, and 30-39% of cases of all autism.

Damaging de novo mutations diminish motor skills in children on the autism spectrum.

In individuals with autism spectrum disorder (ASD), de novo mutations have previously been shown to be significantly correlated with lower IQ but not with the core characteristics of ASD: deficits in social communication and interaction and restricted interests and repetitive patterns of behavior. We extend these findings by demonstrating in the Simons Simplex Collection that damaging de novo mutations in ASD individuals are also significantly and convincingly correlated with measures of impaired motor skills. This correlation is not explained by a correlation between IQ and motor skills. We find that IQ and motor skills are distinctly associated with damaging mutations and, in particular, that motor skills are a more sensitive indicator of mutational severity than is IQ, as judged by mutational type and target gene. We use this finding to propose a combined classification of phenotypic severity: mild (little impairment of either), moderate (impairment mainly to motor skills), and severe (impairment of both IQ and motor skills).

Measuring shared variants in cohorts of discordant siblings with applications to autism.

We develop a method of analysis [affected to discordant sibling pairs (A2DS)] that tests if shared variants contribute to a disorder. Using a standard measure of genetic relation, test individuals are compared with a cohort of discordant sibling pairs (CDS) to derive a comparative similarity score. We ask if a test individual is more similar to an unrelated affected than to the unrelated unaffected sibling from the CDS and then, sum over such individuals and pairs. Statistical significance is judged by randomly permuting the affected status in the CDS. In the analysis of published genotype data from the Simons Simplex Collection (SSC) and the Autism Genetic Resource Exchange (AGRE) cohorts of children with autism spectrum disorder (ASD), we find strong statistical significance that the affected are more similar to the affected than to the unaffected of the CDS (P value ∼ 0.00001). Fathers in multiplex families have marginally greater similarity (P value = 0.02) to unrelated affected individuals. These results do not depend on ethnic matching or gender.

Exploring the relationship between anxiety and insistence on sameness in autism spectrum disorders.

Elevated anxiety symptoms are one of the most common forms of psychopathology to co-occur with autism spectrum disorders (ASDs). The purpose of this study was to explore the association between anxiety and ASD symptoms, particularly the degree to which the relationship is explained by insistence on sameness (IS) behaviors and/or cognitive ability. The sample included 1429 individuals aged 5:8-18:0 years who participated in the Simons Simplex Collection, a genetic consortium study of ASD. Child Behavior Checklist Anxiety Problems T-scores and Autism Diagnostic Interview-Revised "IS" item raw totals were treated as both categorical and continuous measures of anxiety and IS, respectively. Chronological age, verbal intelligence quotient (IQ), and a variety of ASD phenotype-related and other behavioral variables were assessed for potential association with anxiety and IS. Anxiety and IS continuous variables were minimally, although significantly, associated with each other and with chronological age and verbal IQ. Neither anxiety nor IS was associated with other core autism diagnostic scores. Anxiety was associated with a variety of other psychiatric and behavioral symptoms in ASD, including irritability, attention problems, and aggression, while IS was not. Anxiety and IS appear to function as distinct constructs, each with a wide range of expression in children with ASD across age and IQ levels. Thus, both variables could be of use in ASD behavioral research or in dimensional approaches to genetic exploration. Unlike IS, however, anxiety is related to non-ASD-specific behavioral symptoms.

Subcategories of restricted and repetitive behaviors in children with autism spectrum disorders.

Research suggests that restricted and repetitive behaviors (RRBs) can be subdivided into repetitive sensory motor (RSM) and insistence on sameness (IS) behaviors. However, because the majority of previous studies have used the autism diagnostic interview-revised (ADI-R), it is not clear whether these subcategories reflect the actual organization of RRBs in ASD. Using data from the Simons simplex collection (n = 1,825), we examined the association between scores on the ADI-R and the repetitive behavior scale-revised. Analyses supported the construct validity of RSM and IS subcategories. As in previous studies, IS behaviors showed no relationship with IQ. These findings support the continued use of RRB subcategories, particularly IS behaviors, as a means of creating more behaviorally homogeneous subgroups of children with ASD.

Covariance adjustments for the analysis of randomized field experiments.

BACKGROUND: It has become common practice to analyze randomized experiments using linear regression with covariates. Improved precision of treatment effect estimates is the usual motivation. In a series of important articles, David Freedman showed that this approach can be badly flawed. Recent work by Winston Lin offers partial remedies, but important problems remain. RESULTS: In this article, we address those problems through a reformulation of the Neyman causal model. We provide a practical estimator and valid standard errors for the average treatment effect. Proper generalizations to well-defined populations can follow. CONCLUSION: In most applications, the use of covariates to improve precision is not worth the trouble.

Dosage-dependent phenotypes in models of 16p11.2 lesions found in autism.

Recurrent copy number variations (CNVs) of human 16p11.2 have been associated with a variety of developmental/neurocognitive syndromes. In particular, deletion of 16p11.2 is found in patients with autism, developmental delay, and obesity. Patients with deletions or duplications have a wide range of clinical features, and siblings carrying the same deletion often have diverse symptoms. To study the consequence of 16p11.2 CNVs in a systematic manner, we used chromosome engineering to generate mice harboring deletion of the chromosomal region corresponding to 16p11.2, as well as mice harboring the reciprocal duplication. These 16p11.2 CNV models have dosage-dependent changes in gene expression, viability, brain architecture, and behavior. For each phenotype, the consequence of the deletion is more severe than that of the duplication. Of particular note is that half of the 16p11.2 deletion mice die postnatally; those that survive to adulthood are healthy and fertile, but have alterations in the hypothalamus and exhibit a "behavior trap" phenotype-a specific behavior characteristic of rodents with lateral hypothalamic and nigrostriatal lesions. These findings indicate that 16p11.2 CNVs cause brain and behavioral anomalies, providing insight into human neurodevelopmental disorders.

Rare de novo and transmitted copy-number variation in autistic spectrum disorders.

To explore the genetic contribution to autistic spectrum disorders (ASDs), we have studied genomic copy-number variation in a large cohort of families with a single affected child and at least one unaffected sibling. We confirm a major contribution from de novo deletions and duplications but also find evidence of a role for inherited "ultrarare" duplications. Our results show that, relative to males, females have greater resistance to autism from genetic causes, which raises the question of the fate of female carriers. By analysis of the proportion and number of recurrent loci, we set a lower bound for distinct target loci at several hundred. We find many new candidate regions, adding substantially to the list of potential gene targets, and confirm several loci previously observed. The functions of the genes in the regions of de novo variation point to a great diversity of genetic causes but also suggest functional convergence.

Graphical inference for Infovis.

How do we know if what we see is really there? When visualizing data, how do we avoid falling into the trap of apophenia where we see patterns in random noise? Traditionally, infovis has been concerned with discovering new relationships, and statistics with preventing spurious relationships from being reported. We pull these opposing poles closer with two new techniques for rigorous statistical inference of visual discoveries. The "Rorschach" helps the analyst calibrate their understanding of uncertainty and "line-up" provides a protocol for assessing the significance of visual discoveries, protecting against the discovery of spurious structure.

Statistical inference for exploratory data analysis and model diagnostics.

We propose to furnish visual statistical methods with an inferential framework and protocol, modelled on confirmatory statistical testing. In this framework, plots take on the role of test statistics, and human cognition the role of statistical tests. Statistical significance of 'discoveries' is measured by having the human viewer compare the plot of the real dataset with collections of plots of simulated datasets. A simple but rigorous protocol that provides inferential validity is modelled after the 'lineup' popular from criminal legal procedures. Another protocol modelled after the 'Rorschach' inkblot test, well known from (pop-)psychology, will help analysts acclimatize to random variability before being exposed to the plot of the real data. The proposed protocols will be useful for exploratory data analysis, with reference datasets simulated by using a null assumption that structure is absent. The framework is also useful for model diagnostics in which case reference datasets are simulated from the model in question. This latter point follows up on previous proposals. Adopting the protocols will mean an adjustment in working procedures for data analysts, adding more rigour, and teachers might find that incorporating these protocols into the curriculum improves their students' statistical thinking.