Autism spectrum disorder (ASD) affects 1 in 59 children1, and is caused by both genetic and environmental factors. Nevertheless, the modifiable risk factors for this disorder remain unknown, creating a pressing public health need. As ASD likely arises early in prenatal development considerable efforts in identifying such modifiable risk factors have focused on maternal exposures in pregnancy. Some of those studies have shown higher rates of ASD among children of women with e.g. diabetes, depression or recurrent infections. However, (1) women experience many other conditions in pregnancy, most of which have not been studied in the context of offspring ASD risk; and (2) the mechanisms underlying the association between maternal diagnoses and ASD remain unknown. While placental permeability to multiple factors in maternal circulation renders direct effects of maternal health on fetus plausible, this explanation has not been rigorously evaluated against the possibility that both maternal diagnosis and child?s ASD are caused by overlapping genetic factors, transmitted from mother to the child. In response, the key objectives of our proposal are to (1) test the associations between maternal health and ASD systematically, across the full spectrum of maternal diagnoses, and accounting for their correlation, and (2) elucidate the genetic and/or non-genetic mechanisms underlying those associations. To achieve this, we propose independent, but synergistic, aims to increase the reliability and generalizability of our results.
Aim 1 : Systematically identify maternal diagnoses in pregnancy associated with ASD in offspring.
Aim 2 : Determine if the association between maternal diagnoses and ASD is due to transmitted genetic factors, using information on family relations available in Denmark.
Aim 3 : Test the association between maternal diagnoses in pregnancy and child?s genetic liability for ASD using molecular genetic data. We will use large, well-powered sample of >723k live births from Denmark with full demographic, medical and pedigree information, as well as genetic data for a subset of those individuals (N~26k). All significant associations will be replicated in an American dataset (Kaiser Permanente Northern California) with ~320k births, ensuring external validity of our results. The innovation of this project is three-fold: (1) it has a potential to identify novel risk factors (shown in our preliminary data), (2) it introduces a methodological shift in ASD epidemiology, with large-scale, exposure- wide and rigorous inference process, akin to that already applied in the field of genetics; and (3) for the first time, it integrates national data from Nordic registries with one of the largest US-based cohorts (Kaiser Permanente). This project will deliver a systematic list of high-confidence, maternal diagnoses around pregnancy associated with ASD risk in two, independent cohorts, and triangulated evidence regarding genetic and non-genetic mechanisms linking those diagnoses in pregnancy with risk of ASD in offspring. Collectively, these outputs will contribute new insights into ASD etiology, suggest potential preventive factors and aid the efforts towards early identification of high-risk families.
We will perform first systematic test of associations between maternal diagnoses around pregnancy and the risk of ASD in offspring. In order to understand whether the observed associations between maternal diagnoses and ASD arise due to genetic or non-genetic mechanisms, we will then analyze family and molecular genetic data available for this large cohort. Our goal is to identify potential novel risk factors for ASD, close important gaps in the knowledge about the etiology of ASD, and elucidate possible pathways to prevention.
