Cross-Disorder Investigation of Environmental Associations with Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder

Poster Presentation
Thursday, May 2, 2019: 11:30 AM-1:30 PM
Room: 710 (Palais des congres de Montreal)
A. Kalkbrenner1, C. Zheng2, T. E. Jenson2, J. Yu2, C. Ladd-Acosta3, C. B. Pedersen4, S. Daalsgard5, P. Mortensen6 and D. Schendel4, (1)University of Wisconsin-Milwaukee, Milwaukee, WI, (2)Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI, (3)Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, (4)Aarhus University, Aarhus, Denmark, (5)National Centre for Register-based Research, Aarhus University, Aarhus, Denmark, (6)National Centre for Register-based Research, Aarhus University, Denmark, 8210 Aarhus V, Denmark
Background: Neurodevelopmental disorders like autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) are phenotypically heterogenous and potentially encompass etiologically distinct subgroups. The identification of modifiable risk factors for neurodevelopmental impairments may be enhanced by systematic, quantitative comparison of risk factor associations across phenotypic subgroups.

Objectives: As proof of principle, we made quantitative comparisons of the strength of associations between urbanicity at birth and maternal smoking during pregnancy with three neurodevelopmental phenotypic subgroups defined by diagnoses of ASD and ADHD.

Methods: From iPSYCH, a Danish population-based case cohort study (singleton births 1981- 2005, known mother, residing in Denmark at 1st birthday; random 2% sample as controls), we further restricted to births January 1991 - December 1999, with complete follow up and no emigration or death until the 13th birthday. Cases had an ICD-10 ASD (F84.0,1,5,8,9) and/or ADHD (F90.0) diagnosis reported to the Danish Psychiatric Central Research Registry prior to the 13th birthday and controls comprised iPSYCH controls with cases removed. We estimated adjusted odds ratios (adjOR) and 95% confidence intervals using logistic regression for: ASD/- ADHD (n=3,905), ADHD/-ASD (n=3,556), and ASD+ADHD (n= 891) comparing the most urban birth residence (capital region – Copenhagen, 13% of controls) to regions with 50% or less urban area (22% of controls) and also evaluated maternal smoking (28% of controls) versus no smoking. We adjusted for birth year, maternal smoking (urbanicity analyses only), inter-pregnancy interval, urbanicity (smoking analyses only), marital status, maternal and paternal immigrant status, education, employment, ages, and incomes. To compare the strength of association across the 3 subgroups while accounting for non-independence of these ORs, we used a Bayesian multiplier bootstrap method to estimate the variance-covariance matrix for log ORs. We computed Wald-type p value tests of the equivalency of pairs of adjORs, using a conservative alpha = 0.005 given multiple comparisons and preference for stringency in concluding different risk between phenotypic groups..

Results: Urbanicity was associated with subgroups including autism: ASD/-ADHD adjOR 1.7 (1.4, 1.9) and ASD+ADHD adjOR 2.3 (1.7, 3.1) and these associations were statistically of similar strength (p = 0.045). In contrast, urbanicity was not associated with ADHD alone: ADHD/-ASD adjOR 1.0 (0.8, 1.2), an association statistically distinct from the other subgroups (both p = 0.000). Maternal smoking in pregnancy was associated with ADHD alone: ADHD/- ASD: adjOR 1.5 (1.3, 1.6) but not autism alone: ASD/- ADHD adjOR 1.0 (0.9, 1.1), with a p contrasting these ORs = 0.000. The association of maternal smoking and ASD+ADHD: adjOR 1.2 (1.0, 1.5) was not statistically distinguishable from associations with the single diagnosis groups: ASD/-ADHD (p = 0.018) or ADHD/-ASD (p = 0.073).

Conclusions: Risk from urban residence at birth and maternal smoking in pregnancy differed significantly across ASD and ADHD neurodevelopmental phenotypic subgroups, thereby highlighting at-risk cross-diagnosis subgroups as potential targets for further analyses of pathogenic mechanisms associated with these modifiable risk factors. Our approach supports attempts to align phenotypic and etiologic heterogeneity to clarify the risk architecture underlying neurodevelopmental impairments.