Autism spectrum disorder (ASD) is a behaviorally defined and heterogeneous disorder. Biomarkers for ASD offer the opportunity to improve prediction, diagnosis, stratification by severity and subtype, monitoring over time and in response to interventions, and overall understanding of the underlying biology of this disorder. A variety of potential biomarkers, from the level of genes and proteins to network-level interactions, is currently being examined. Many of these biomarkers relate to inhibition, which is of particular interest because in many cases ASD is thought to be a disorder of imbalance between excitation and inhibition. Abnormalities in inhibition at the cellular level lead to emergent properties in networks of neurons. These properties take into account a more complete genetic and cellular background than findings at the level of individual genes or cells, and are able to be measured in live humans, offering additional potential as diagnostic biomarkers and predictors of behaviors. In this review we provide examples of how altered inhibition may inform the search for ASD biomarkers at multiple levels, from genes to cells to networks.
Inhibition-Based Biomarkers for Autism Spectrum Disorder
We sought to determine the potential effects of pooling on power, false positive rate (FPR), and bias of the estimated associations between hypothetical environmental exposures and dichotomous autism spectrum disorders (ASD) status. Simulated birth cohorts in which ASD outcome was assumed to have been ascertained with uncertainty were created. We investigated the impact on the power of the analysis (using logistic regression) to detect true associations with exposure (X₁) and the FPR for a non-causal correlate of exposure (X₂, r = 0.7) for a dichotomized ASD measure when the pool size, sample size, degree of measurement error variance in exposure, strength of the true association, and shape of the exposure-response curve varied. We found that there was minimal change (bias) in the measures of association for the main effect (X₁). There is some loss of power but there is less chance of detecting a false positive result for pooled compared to individual level models. The number of pools had more effect on the power and FPR than the overall sample size. This study supports the use of pooling to reduce laboratory costs while maintaining statistical efficiency in scenarios similar to the simulated prospective risk-enriched ASD cohort.
Keywords: autism spectrum disorders; measurement error; pooling.
This study examined vocal coordination during mother-infant interactions in the infant siblings (high risk infants; HR) of children with autism spectrum disorder (ASD), a population at heightened risk for developing language delays. Vocal coordination between mothers and HR infants was compared to a group of low risk (LR; no first- or second-degree relative with ASD) dyads, and used to predict later language development. Nine-month-old infants were videotaped at home playing with their mothers, and interactions were coded for the frequency and timing of vocalizations. Percent infant simultaneous speech was predictive of later language delay (LD), and dyads with LD infants were less coordinated with one another in average latency to respond than dyads with non-delayed (ND) infants. The degree of coordination between mothers and infants on this variable predicted a continuous measure of language development in the third year. This research underscores the importance of understanding early development in the context of interaction.
Keywords: Parent-infant interaction; coordination; high risk siblings; language development.
Variation in the odds ratio (OR) resulting from selection of cutoffs for categorizing continuous variables is rarely discussed. We present results for the effect of varying cutoffs used to categorize a mismeasured exposure in a simulated population in the context of autism spectrum disorders research. Simulated cohorts were created with three distinct exposure-outcome curves and three measurement error variances for the exposure. ORs were calculated using logistic regression for 61 cutoffs (mean ± 3 standard deviations) used to dichotomize the observed exposure. ORs were calculated for five categories with a wide range for the cutoffs. For each scenario and cutoff, the OR, sensitivity, and specificity were calculated. The three exposure-outcome relationships had distinctly shaped OR (versus cutoff) curves, but increasing measurement error obscured the shape. At extreme cutoffs, there was non-monotonic oscillation in the ORs that cannot be attributed to “small numbers.” Exposure misclassification following categorization of the mismeasured exposure was differential, as predicted by theory. Sensitivity was higher among cases and specificity among controls. Cutoffs chosen for categorizing continuous variables can have profound effects on study results. When measurement error is not too great, the shape of the OR curve may provide insight into the true shape of the exposure-disease relationship.
Keywords: autism spectrum disorders; categorization; dichotomization; epidemiology methods; misclassification.
Usage of the term ‘theory of mind’ (ToM) has exploded across fields ranging from developmental psychology to social neuroscience and psychiatry research. However, its meaning is often vague and inconsistent, its biological bases are a subject of debate, and the methods used to study it are highly heterogeneous. Most crucially, its original definition does not permit easy downward translation to more basic processes such as those studied by behavioral neuroscience, leaving the interpretation of neuroimaging results opaque. We argue for a reformulation of ToM through a systematic two-stage approach, beginning with a deconstruction of the construct into a comprehensive set of basic component processes, followed by a complementary reconstruction from which a scientifically tractable concept of ToM can be recovered.
One of the most consistent findings in autism spectrum disorder (ASD) research is a higher rate of ASD diagnosis in males than females. Despite this, remarkably little research has focused on the reasons for this disparity. Better understanding of this sex difference could lead to major advancements in the prevention or treatment of ASD in both males and females. In October of 2014, Autism Speaks and the Autism Science Foundation co-organized a meeting that brought together almost 60 clinicians, researchers, parents, and self-identified autistic individuals. Discussion at the meeting is summarized here with recommendations on directions of future research endeavors.
Keywords: Autism; Diagnosis; Female; Protection; Research; Symposium.