IN UTERO EXPOSURE TO MATERNAL IMMUNE ACTIVATION AND AUTISM SPECTRUM DISORDER

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social interaction and communication, and repetitive behavior and stereotypical interests. First we describe what is known about ASD risk factors, including genetic variants and environmental exposures, particularly during gestation (Chapter 1). Then we tested the hypothesis that prenatal exposure to maternal immune activation (MIA) increases the risk of ASD. In a prospective birth cohort (Boston Birth Cohort, BBC), we found that prenatal exposure to maternal fever, and not maternal genitourinary infections or influenza, is associated with an increased risk of ASD (Chapter 2). Electronic medical records (EMR) were used to identify children in the BBC with ASD or typical development. While reliance on EMR enables us to increase sample size compared to a traditional study that requires extensive research contact, it could lead to outcome misclassification. Here, we explored using Random Forests, a data mining and machine learning technique, and Latent Class Analysis, a probabilistic clustering method, to identify other EMR diagnosis codes that help predict a child’s ASD status (Chapter 3). These techniques were able to identify children with typical and atypical development in the BBC. Finally, to further explore the potential biological consequences of prenatal exposure to MIA, we analyzed DNA methylation in the whole blood of 2-5 year old children in the Study to Explore Early Development (Chapter 4). We found one site in an intergenic region that was differentially methylated in children whose mothers contracted an infection shortly before they were conceived, and two sites in the genome (IQSEC1, EPS8L3) that were differentially methylated in children whose mother had an infection during her third trimester. While the differences in percent methylation were small in magnitude (<1% mean or median absolute difference), they were statistically significant after accounting for technical and biological sources of variation, including ancestry and ASD case status. This dissertation contributes to our understanding of the role of MIA exposure during pregnancy in ASD risk, biological changes identified in early childhood associated with prenatal exposure to MIA, and suitable methods for conducting EMR-based epidemiological research of ASD

IN UTERO EXPOSURE TO MATERNAL IMMUNE ACTIVATION AND AUTISM SPECTRUM DISORDER

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social interaction and communication, and repetitive behavior and stereotypical interests. First we describe what is known about ASD risk factors, including genetic variants and environmental exposures, particularly during gestation (Chapter 1). Then we tested the hypothesis that prenatal exposure to maternal immune activation (MIA) increases the risk of ASD. In a prospective birth cohort (Boston Birth Cohort, BBC), we found that prenatal exposure to maternal fever, and not maternal genitourinary infections or influenza, is associated with an increased risk of ASD (Chapter 2). Electronic medical records (EMR) were used to identify children in the BBC with ASD or typical development. While reliance on EMR enables us to increase sample size compared to a traditional study that requires extensive research contact, it could lead to outcome misclassification. Here, we explored using Random Forests, a data mining and machine learning technique, and Latent Class Analysis, a probabilistic clustering method, to identify other EMR diagnosis codes that help predict a child’s ASD status (Chapter 3). These techniques were able to identify children with typical and atypical development in the BBC. Finally, to further explore the potential biological consequences of prenatal exposure to MIA, we analyzed DNA methylation in the whole blood of 2-5 year old children in the Study to Explore Early Development (Chapter 4). We found one site in an intergenic region that was differentially methylated in children whose mothers contracted an infection shortly before they were conceived, and two sites in the genome (IQSEC1, EPS8L3) that were differentially methylated in children whose mother had an infection during her third trimester. While the differences in percent methylation were small in magnitude (<1% mean or median absolute difference), they were statistically significant after accounting for technical and biological sources of variation, including ancestry and ASD case status. This dissertation contributes to our understanding of the role of MIA exposure during pregnancy in ASD risk, biological changes identified in early childhood associated with prenatal exposure to MIA, and suitable methods for conducting EMR-based epidemiological research of ASD