Predicting the diagnosis of autism in adults using the Autism-Spectrum Quotient (AQ) questionnaire.

BACKGROUND: Many adults with autism spectrum disorder (ASD) remain undiagnosed. Specialist assessment clinics enable the detection of these cases, but such services are often overstretched. It has been proposed that unnecessary referrals to these services could be reduced by prioritizing individuals who score highly on the Autism-Spectrum Quotient (AQ), a self-report questionnaire measure of autistic traits. However, the ability of the AQ to predict who will go on to receive a diagnosis of ASD in adults is unclear. METHOD: We studied 476 adults, seen consecutively at a national ASD diagnostic referral service for suspected ASD. We tested AQ scores as predictors of ASD diagnosis made by expert clinicians according to International Classification of Diseases (ICD)-10 criteria, informed by the Autism Diagnostic Observation Schedule-Generic (ADOS-G) and Autism Diagnostic Interview-Revised (ADI-R) assessments. RESULTS: Of the participants, 73% received a clinical diagnosis of ASD. Self-report AQ scores did not significantly predict receipt of a diagnosis. While AQ scores provided high sensitivity of 0.77 [95% confidence interval (CI) 0.72-0.82] and positive predictive value of 0.76 (95% CI 0.70-0.80), the specificity of 0.29 (95% CI 0.20-0.38) and negative predictive value of 0.36 (95% CI 0.22-0.40) were low. Thus, 64% of those who scored below the AQ cut-off were 'false negatives' who did in fact have ASD. Co-morbidity data revealed that generalized anxiety disorder may 'mimic' ASD and inflate AQ scores, leading to false positives. CONCLUSIONS: The AQ's utility for screening referrals was limited in this sample. Recommendations supporting the AQ's role in the assessment of adult ASD, e.g. UK NICE guidelines, may need to be reconsidered.

The effect of age, diagnosis, and their interaction on vertex-based measures of cortical thickness and surface area in autism spectrum disorder.

Autism spectrum disorder (ASD) is a lifelong neurodevelopmental condition that is accompanied by an atypical development of brain maturation. So far, brain development has mainly been studied during early childhood in ASD, and using measures of total or lobular brain volume. However, cortical volumetric measures are a product of two distinct biological neuroanatomical features, cortical thickness, and surface area, which most likely also have different neurodevelopmental trajectories in ASD. Here, we therefore examined age-related differences in cortical thickness and surface area in a cross-sectional sample of 77 male individuals with ASD ranging from 7 to 25 years of age, and 77 male neurotypical controls matched for age and FSIQ. Surface-based measures were analyzed using a general linear model (GLM) including linear, quadratic, and cubic age terms, as well as their interactions with the main effect of group. When controlling for the effects of age, individuals with ASD had spatially distributed reductions in cortical thickness relative to controls, particularly in fronto-temporal regions, and also showed significantly reduced surface area in the prefrontal cortex and the anterior temporal lobe. We also observed significant group × age interactions for both measures. However, while cortical thickness was best predicted by a quadratic age term, the neurodevelopmental trajectory for measures of surface area was mostly linear. Our findings suggest that ASD is accompanied by age-related and region-specific reductions in cortical thickness and surface area during childhood and early adulthood. Thus, differences in the neurodevelopmental trajectory of maturation for both measures need to be taken into account when interpreting between-group differences overall.