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Are Autistic Traits in the General Population Related to Global and Regional Differences in Brain Structure?
There is accumulating evidence that autistic traits in the general population lie on a continuum, with clinical ASD representing the extreme end of this distribution. Individual differences in autism-spectrum quotient (AQ) have been shown to predict differences in performance on behavioral tasks that are impaired in ASD. Yet it remains unknown if individual differences in AQ also relate to brain anatomical measures. It could be argued that biological mechanisms associated with clinical ASD may also underpin variation in autistic-like traits within the general population. Here, we want to elucidate the possible effects of autistic traits on various indices of brain structure in the general population and compare the results with neuroanatomical differences reported in ASD.
Objectives:
To address whether AQ scores in the general population are related to structural variation in global or local gray matter volume, thickness and surface area.
Methods:
All healthy individuals completed the abbreviated version of the AQ questionnaire (28 items). High-resolution T1 anatomical MRI scans were acquired from 508 healthy individuals. We performed a quantitative cross-validation on structural brain indices by creating two independent stratified groups based on age, sex, and level of education: Group1: N=204 (105 Males, Mean age=22.85, SD=1.7, Mean AQ=55.6, SD=9, range=33-80); Group2: N=304 (155 Males, Mean age=22.82, SD=1.7, Mean AQ=57.1, SD=8.7, range=32-91).
To assess global differences in brain structure, FreeSurfer was used to derive cortical thickness and surface area measures. Regional volumes were assessed with VBM. To examine the relationship with behavior, correlations between structural brain indices and AQ were calculated taking age, sex and handedness into account.
Results:
Here we present preliminary results based on Group1, using a standard cross-sectional approach including correction for multiple comparisons.
No significant associations were found between AQ scores and cortical thickness or surface area in Group1 (FDR, p<.05, >100 vertices) or on regional brain volumes using permutation-based non-parametric testing.
Conclusions:
The first preliminary analyses do not indicate that ASD symptom severity is related to gray matter volume, thickness or surface area in healhty young adults. Hence, it could well be that the relationships observed in clinical populations are unique for those with an actual disorder instead of being of relevance for those with mild ASD symptoms in the general population. We are currently pursuing the actual cross-validation between groups and expect to present the results on May 2014.