Autism spectrum disorder (ASD) is highly heritable neurodevelopmental disorder. Genetic influences account for between 64-91% of the variance in childhood ASD. Yet, little is known about how specific genes (i.e. common SNPs) map onto neural substrates that have been theorized to underlie its development. Furthermore, ASD frequently co-occurs with other neurodevelopmental disorders, co-occurring with attention-deficit/hyperactivity disorder (ADHD) at a rate of 28-87%. And yet, the biological mechanisms that underlie their frequent comorbidity has also been unexplored. Our lack of knowledge regarding the mechanisms underlying this comorbidity is particularly problematic from a clinical perspective; when compared to individuals with either ADHD or ASD alone, youths with both ASD and ADHD are more likely to be prescribed psychotropic medications such as risperidone and aripiprazole, which are not intended to treat either of these disorders. There is an urgent need to correct this gap in knowledge because co-occurring ASD and ADHD may have distinct genetic and neurobiological underpinnings compared to ASD or ADHD alone. In line with NICHD priorities to understand the complexity of comorbid symptoms, our goal is to identify the neurobiological mechanisms of genetic risk for ASD alone, ADHD alone, and their comorbid presentation (i.e., ASD+ADHD). As a first step toward accomplishing this goal, our first main objective is to test and subsequently validate innovative polygenic score models that incorporate statistical and a bioinformatic information to precisely predict membership into one of these three clinical phenotypes. This will be demonstrated in large population datasets (Aim 1) and in a well-characterized clinically representative dataset (Aim 2). The second main objective is to investigate the neurobiological mechanism underlying these polygenic score associations with neurodevelopmental phenotypes by testing whether they are biologically mediated by a key and vastly understudied brain structure in the brainstem (Aim 3).
Brittany Travers, Ph.D. (Kinesiology)
Qiongshi Lu, Ph.D. (Biostatistics & Medical Informatics)