There is a wealth of literature characterizing social difficulties in autism spectrum disorder (ASD). However, little work has replicated longitudinal findings from typical development that adolescent social competence predicts positive adult outcomes in ASD. The current study examined social competence trajectories from 2 to 26 and the utility of three social competence measures collected in adolescence in predicting work, residential status, friendship, and romantic outcomes in a longitudinal cohort (n = 253) of ASD. Using group-based trajectory modeling, we identified two patterns of social competence development: a low trajectory characterized by slow linear gains throughout childhood and plateauing in adulthood, and a high trajectory characterized by steeper linear gains in childhood followed by decline in adulthood. Regression models indicated one social competence measure, Vineland Social-AE scores, significantly predicted employment, residential status, and friendships in adulthood. One other social competence measure, SSQ total scores, also significantly predicted friendship in adulthood. Only nonverbal IQ at 9 predicted the likelihood of having ever had a romantic relationship. These findings highlight the role of social competence in both atypical and typical development and suggest the social impairments associated with ASD do not necessarily impact all realms of social functioning equally.

Given high rates of co-occurring conditions in youth and adults with autism spectrum disorder (ASD), it is critical to examine the developmental trajectories of these symptoms of psychopathology. Using data from a cohort of participants (n = 194), most of whom were first assessed for ASD in very early childhood, we investigated the trajectories of co-occurring depressive, anxiety, and attention-deficit hyperactivity disorder (ADHD) symptoms from late childhood to adulthood. Additionally, childhood predictors and adult outcomes associated with these symptom trajectories were examined. Using group-based trajectory modeling, we found two distinct classes of individuals exhibiting each of these co-occurring symptom patterns: one class exhibited fairly low symptoms across time, and one class with elevated symptoms with varied fluctuation across time (ADHD symptoms starting high but decreasing, anxiety symptoms high and stable, and depressive symptoms fluctuating but peaking at clinically significant levels in young adulthood). All high trajectory classes were associated with age 9 adaptive skills; verbal IQ predicted higher anxiety and depressive symptom classes. After accounting for verbal IQ, all high symptom trajectory classes were negative predictors of objective adult outcomes. These findings call for wide-ranging considerations of the needs of individuals across ability levels, autism symptoms, and behavioral and emotional challenges.

The goal of psychopharmacohgic research in autism is to provide guidance to clinicians and families on the risks and benefits of specific interventions. Careful subject selection and subject characterization in clinical trials are necessary for replication, to inform clinicians about the sample, and to elucidate the type of patients who might benefit from, the treatment. At minimum, subject characterization includes demographic information, diagnosis (autism, Åsperger's syndrome, or pervasive developmental disorder-not otherwise specified), intellectual functioning, adaptive functioning, symptom severity, general behavioral profile, health status, pertinent clinical laboratory measures, height, weight, current treatments, and educational placements. Subject selection, sample size, and choice of the primary outcome measure are closely interrelated and linked to the study hypothesis. The magnitude of expected improvement on the primary outcome measure, which can be expressed by effect size, has direct implications for sample size. Large sample sizes are required to detect small effect sizes. To facilitate interpretation of study results, research reports should provide descriptive characteristics of the sample as well as the mean change and standard deviation on the primary outcome measure data to permit calculation of the effect size.