Of Decrements and Disorders: Assessing Quantitative Traits Related to Autism Spectrum Disorders in Prospective Epidemiologic Studies of Environmental Toxicant Exposures

Background: Prenatal and early life neurodevelopment is exquisitely sensitive to environmental toxicant exposures. Identifying the effects of environmental toxicants on autism spectrum disorders (ASD) is particularly important from a public health perspective because many of these exposures are modifiable and may be targeted for intervention. Prospective cohort studies that measure quantitative, dimensional traits related to ASD using standardized psychometric tools may offer alternate approaches to investigating associations with environmental toxicants.  

Objectives: To identify the study validity and feasibility impacts resulting from the use of prospective cohort studies that measure quantitative, dimensional autism traits compared to studies of clinically diagnosed ASD in epidemiologic studies of environmental toxicant exposures. 

Methods: We considered the impact of this design approach on exposure measurement error, outcome misclassification, selection bias and statistical power. 

Results: We identified four main advantages to using prospective designs that measure quantitative, dimensional traits vs. clinically diagnosed ASD in epidemiologic studies of environmental toxicant exposures: 1) Prospective studies enhance exposure assessment by facilitating high quality quantitative measures, such as biomarkers or micro-environmental measurements, during developmentally relevant windows, such as the prenatal and early life periods, which are thought to be the most vulnerable for development of ASD. 2) Prospective cohort studies that measure continuous outcomes are not vulnerable to a control selection bias, which can be introduced when an outside control group is enrolled, because there is no defined case or control group; rather, all children enrolled are assessed and compared across levels of dimensional autism traits that fall along a continuum. 3) Analyzing continuously distributed traits enhances statistical power because traits are measured on all individuals in the cohort and compared across a range of severity in relation to an environmental toxicant exposure; power is therefore not limited by the number of cases in the cohort. 4) Analyzing quantitative, dimensional traits reduces ASD outcome misclassification because rather than lumping together individuals with very heterogeneous phenotypes into one category, which could mask associations, this approach focuses on a single trait underlying ASD, such as social cognition. The psychometric measurement of this single trait reduces outcome heterogeneity and may allow for identification of a more specific exposure-related biologic pathway. This approach is also immune to temporal changes in diagnostic criteria and can include mild or early manifestations of ASD among children that may not otherwise meet diagnostic criteria but share similar challenges. A disadvantage of this approach is that an underlying dimensional trait, such as social cognition, may be shared by other neurodevelopmental disorders, such as attention deficit hyperactivity disorder.

Conclusions: Investigating the determinants of ASD – particularly modifiable determinants such as environmental toxicant exposures – is of great public health importance, given their apparent substantial rise over the past few decades. The use of prospective designs measuring quantitative, dimensional traits of ASD offers a powerful opportunity to provide important clues to the etiology of these disorders and is likely to accelerate the discovery of the role of environmental toxicant exposures as risk factors for ASD.