A window into autism's early development: features of behavioral data in a longitudinal multisystem evaluation in infants at high risk for autism
MetadataShow full item record
Autism spectrum disorders (ASDs) are a biologically-based and behaviorally-defined spectrum of conditions which impact development. These conditions affect and are diagnosed based on features in three psychological and behavioral domains: social interaction, communication, and repetitive behaviors. Developing better ways to identify early signs of autism, whether through behavioral or other types of measures, is important because it will allow children to gain access to interventions and treatments earlier, which has demonstrated positive outcomes. Over the past 10 years, the prevalence of reported autism cases has increased. As a result, much research has focused on the etiology and phenotype of autism. Investigations seeking early signs of autism have generally studied vulnerable populations, particularly infants with an older sibling diagnosed with autism. Aside from observable behavioral differences, biological abnormalities, often within the gastrointestinal and immune systems as well as endocrine, autonomic and other systems, have been observed in a significant number of children diagnosed with autism. These features raise the possibility that cellular and tissue change in body and brain may be altering brain function such that behaviors emerge later and downstream of these cellular and tissue problems. However, research on the pathophysiology underlying these medical features, and particularly regarding how they develop in infancy, has received almost no attention. Such investigation would require measuring pathophysiological and medical features alongside current standard measures of behavioral and phenotypical presentations of autism. This thesis describes a study, funded by the Department of Defense Autism Research Program and carried out at the Massachusetts General Hospital Lurie Center, that proposed to look for early markers of autism in the pathophysiological domains in high risk infants and place them into developmental context by correlating these observations (some of which might potentially become early markers) with well-established neurocognitive measures. The goal of the study is to find biomarkers of clinical importance that reflect the pathophysiologial development of autism which might substantially precede behavioral changes that are currently used as a standard of diagnosis, but are not developmentally apparent or reliably measurable until well into the second or third year of life. While the overall scope of the study encompassed a range of systemic and nervous system measures as well as neurocognitive assessments, the focus of this thesis is mainly on a subset of the behavioral and neurocognitive measures collected through the study, specifically the Autism Diagnostic Observation Scale (ADOS), Autism Observational Scale for Infants (AOSI), Mullen Scales of Early Learning (MSEL) and Vineland Adaptive Behavior Scales (VABS). Subject development was tracked and assessed through developmental quotients (DQs) and then correlated to measures designed to identify autistic-like features. Results demonstrate that verbal development was the most significant indicator for autism. Additionally, delay in communication preceded problems with socialization. The analysis and information used for this thesis will contribute to the infrastructure utilized by the investigators for assessing further behavioral data. In addition, this behavioral data and the metrics generated in these analyses will be analyzed in relation to physiological data (e.g. brain, autonomic, metabolic, immune, and microbiome data). Tracking early biomedical development, especially alongside the current standard of observing behavioral development, has the potential of offering more comprehensive understanding of the brain-behavior-body relationship in children diagnosed with ASD, which can hopefully contribute to a non-invasive, more accurate, and earlier method of diagnosis and to the development of more treatment options.