Recently, greater resolution in the measurement of grey matter has allowed a focus on cortical thickness, rather than grey matter volume, which represents the product of cortical thickness and surface area. Cortical thickness within neocortex primarily follows an inverted ‘U’ cubic pattern of development with an increase early in development followed by thinning in adolescence that is thought to reflect the sculpting forces of neuronal pruning (developmental trajectories for some phylogenetically older portions of cortex, however, are best explained by quadratic or linear functions; Shaw et al., 2008).

The inverted U developmental trajectory of typical grey matter maturation poses a challenge for comparisons across cross-sectional studies as a developmental delay (or acceleration) in a given group could make cortical thickness relatively larger at one age but relatively smaller at a different age. This age effect, along with high individual variability (Lange et al., 1997) and the difficulty of acquiring large sample sizes, has yielded a somewhat inconsistent picture in the few studies to date investigating cortical thickness in autism spectrum disorders. Among 8- to 12-year-old children, Hardan et al. (2006) found overall thicker cortex (particularly in the temporal lobe) for 17 relatively high-functioning males with autism spectrum disorders as compared with 14 typically developing males. However, it is important to note that the groups were not matched on intelligence quotient (IQ), with the autism spectrum disorders group scoring on average 20 points lower than the typically developing control group. In contrast, Chung et al. (2005) found mostly thinner cortex among 16 adolescent and young adult males (ages 12–25 years) with autism spectrum disorders versus 12 neurotypical control males. IQ levels were not reported in this study so it is unclear how well these groups were matched for intellectual ability, which may affect interpretation of these results as well. Hyde et al. (2009) documented a mixture of thicker (e.g. anterior and medial frontal regions, anterior cingulate, superior temporal sulcus, Heschl’s gyrus and inferior parietal lobule) and thinner (e.g. portions of the pre-, para- and post-central gyri) cortex in 15 adolescent and adult males with high-functioning autism versus 15 neurotypical controls matched on age (ages 14–34 years) and IQ. Even more striking, Hadjikhani et al. (2006) found only thinner cortex among 14 adult males (mean age=33years) with high-functioning autism spectrum disorders versus 14 age- and IQ-matched control males, particularly in temporal, parietal and inferior frontal regions. Similarly, Wallace, Happé and Giedd (2009) found thinner temporal, parietal and frontal cortices for an adult male savant with Asperger’s syndrome as compared to 14 male controls matched on age and verbal ability. Perhaps reconciling Hardan and colleagues’ (2006) finding of increased cortical thickness in children with these findings of decreased cortical thickness in adolescents and adults, Hardan et al. (2009) completed a longitudinal paediatric study by collecting second scans (on average 1.9 years later) from many of the male participants with autism spectrum disorders in their 2006 study. They found accelerated thinning in the temporal and occipital lobes among children with autism spectrum disorders relative to typically developing children, although group differences dissipated after IQ covariation.

Taken together, the trend in findings from the autism spectrum disorders literature suggests that cortical thickness, like brain volumes, may follow a pattern in which early overgrowth is followed by prematurely arrested growth. However, the studies completed thus far have included <20 participants in each of the clinical and control groups, limiting statistical power. One recent exception to these patterns is a study of 76 individuals with autism spectrum disorders and 51 typically developing controls ranging in age from 10 to 60 years (Raznahan et al., 2010). In this study, while temporal cortex thinned with increasing age in the typically developing group, there was little change in temporal cortical thickness in the autism spectrum disorders group. However, this study had several limitations worth noting. The very large age range studied includes periods of complex developmental cortical changes, which are curvilinear in nature; nevertheless, linear methods of analysis were used to model age effects. Furthermore, there are issues of matching and clinical characterization. Participants with autism spectrum disorders were not matched to controls on IQ and just over 40% of the participants with autism spectrum disorders were not diagnosed using a gold-standard diagnostic tool. We therefore sought to improve upon this and other previous studies by concentrating on a more discrete period, adolescence and young adulthood, which is associated with a linear decline in cortical thickness, and by not only matching groups on IQ, but also acquiring detailed clinical characterization using gold-standard diagnostic instruments whenever possible. Although two studies (Chung et al., 2005; Hyde et al., 2009) evaluated cortical thickness in autism spectrum disorders during the adolescent and young adult age range, limited sample sizes (as in the Raznahan et al., study that included 16 typically developing controls and 19 individuals with autism spectrum disorders who fell in the adolescent and young adult age range studied here) prevented examination of age effects within their samples. As adolescence and adulthood may be the period during which accelerated cortical thinning emerges in autism spectrum disorders, filling this gap in the literature is particularly important. Finally, as previously mentioned, matching on IQ in particular has been inconsistent in prior studies, limiting comparability across studies and interpretation, especially given the established effect of IQ on cortical thickness (Shaw et al., 2006a; Narr et al., 2007). Given findings of autism spectrum disorders-related thicker cortex during childhood and thinner cortex during adulthood, examination of cortical thickness in well-matched samples during the full range of adolescence and young adulthood may help to pinpoint the divergence of growth trajectories between individuals with autism spectrum disorders versus neurotypical controls.

Vertex-by-vertex analyses conducted on the cortical surface yielded similar results to the gyral-level analyses. As illustrated in Fig. 1, thinner cortex was found in the autism spectrum disorders group, localized to temporal and parietal regions, most prominently in the left hemisphere. Adding full-scale IQ as a covariate did not alter these findings.

More specifically, the present results complement earlier findings of thinner cortex in adults with autism spectrum disorders (Chung et al., 2005; Hadjikhani et al., 2006; Wallace et al., 2009) and may therefore pinpoint adolescence as the time window during which the cortical growth trajectories diverge a second time (in addition to the overgrowth during early development). Taken from this perspective, these findings somewhat parallel those previously reported for amygdala volumes; the amygdala was found to be significantly larger among pre-adolescent children (ages 7.5–12.5 years) with autism spectrum disorders versus typically developing children in this age range, while similar amygdala volumes were reported for adolescents (ages 12.75–18.5 years) with autism spectrum disorders versus their same age typically developing peers (Schumann et al., 2006). Placed in the context of the wider literature, the current findings suggest that the presence of thinner cortex continues into young adulthood, although it is unclear whether the cortical developmental trajectory in autism spectrum disorders across childhood, adolescence and young adulthood is parallel to that found in typical development. Longitudinal studies are needed to validate this proposed accelerated cortical thinning during adolescence and young adulthood in autism spectrum disorders.

The regional specificity of the present findings was largely consistent with prior studies (that have documented both thinner and thicker cortex in autism spectrum disorders depending on the age group studied). As in the present study, thinner temporal and parietal cortices, particularly in the left hemisphere, were also documented by Hadjikhani et al. (2006) and Wallace et al. (2009) among high-functioning adult males on the autism spectrum. Hardan et al. (2006) measured cortical thickness over lobar regions, finding that thicker cortex in autism spectrum disorders was restricted to temporal and parietal cortices during childhood, just as thinner cortex was confined to those regions in our sample of adolescent and young adult males with autism spectrum disorders. Similarly, the more pronounced age-related cortical thinning in autism spectrum disorders documented in the current study was confined to the temporal cortex, corresponding to Hardan et al.’s (2009) longitudinal study finding accelerated thinning in the temporal cortex in the autism spectrum disorders group. In the context of a large cross-sectional study (autism spectrum disorders n=76), Raznahan et al. (2010) also found significant age×diagnosis interactions, primarily in the temporal cortex. However, the pattern of group differences was discrepant from those shown here. While we found more pronounced cortical thinning in individuals with autism spectrum disorders than in typically developing individuals, Raznahan et al. found relatively flat age-related changes in the temporal cortex in the autism spectrum disorders group, unlike the typically developing group, which displayed thinner temporal cortex with increasing age. The different age ranges studied and the modelling chosen in that study very likely contributed to inconsistent findings. While our study concentrated on adolescence and young adulthood (associated with a linear decline in cortical thickness), their study encompassed a much larger age band, with individuals ranging in age from 10 to 60 years (periods of both decline and levelling off of cortical thickness developmental curves, suggesting that their use of linear models may be problematic). Additionally, their findings do not fit the general pattern in the literature of increased cortical thinning in autism spectrum disorders at later ages. Finally, participants with autism spectrum disorders in their study, as in most other studies of cortical thickness in autism spectrum disorders, were not matched to the control group on IQ. Instead, any IQ effects were accounted for via covariation only.

Coupled with findings of early overgrowth, the increasingly thinner cortex during adolescence and young adulthood could reflect a leftward shift in autism spectrum disorders of the inverted U-shaped pattern of grey matter observed for both volumes and cortical thickness during typical development (Giedd et al., 1999; Shaw et al., 2008), perhaps reflecting synaptogenesis/neurogenesis gone awry. It could be that, in autism spectrum disorders, early cortical overgrowth is followed by either earlier synaptic pruning or over-pruning during adolescence, a period characterized by selective synaptic elimination and arborization of dendrites and axons (Huttenlocher and Dabholkar, 1997). We are reassured that findings reported in the present study do not simply reflect tissue compartmental shift (i.e. as grey matter decreases, white matter increases), given that white matter volume in our sample is either not different between groups or indeed smaller in the autism spectrum disorders group. Similarly, whether or not a participant with autism spectrum disorders was taking psychotropic medication or exhibited clinically elevated psychopathology did not change the pattern of results. This rules out medication usage and comorbid psychopathology as contributory factors to our findings of cortical thinning, and furthermore, suggests that the cortical thinning documented here is a result of autism spectrum disorders, not comorbid conditions. What genetic and/or environmental forces contribute to this abnormal cortical growth trajectory remain unknown, although it is well established that brain volumes (Wallace et al., 2006), and to a lesser extent cortical thickness (Lenroot et al., 2009), during childhood and adolescence are highly heritable. Recently, Wassink and colleagues (2007) linked cortical grey matter overgrowth in autism spectrum disorders with variation of the serotonin transporter gene, though Raznahan and colleagues (2009) could not replicate this result. Davis et al. (2008) also linked cortical enlargement in autism spectrum disorders with the ‘low activity’ allele of the Monoamine oxidase A (MAOA) gene. The cortical growth trajectory in autism spectrum disorders may also vary for individuals with optimal versus more typical outcomes, as has been shown in attention-deficit/hyperactivity disorder (Shaw et al., 2006b). Future research should continue to explore links between genetic/environmental factors and this atypical trajectory of brain growth, particularly focusing on cortical thinning, in autism spectrum disorders.

Although these results are promising, there are limitations to consider. First, the present study included only high-functioning males; therefore, this pattern of findings may not apply to either lower functioning individuals or females with autism spectrum disorders. This study focused on high-functioning individuals with autism spectrum disorders in order to better isolate autism spectrum disorders-specific effects on cortical thickness, above and beyond intellectual disability and because prior studies demonstrated significant associations between IQ and cortical thickness (Shaw et al., 2006a; Narr et al., 2007). Additionally, the sample was restricted to males, because previous work reveals sex differences in neuroanatomy, not only in typical development (Lenroot et al., 2007), but also in autism spectrum disorders (Bloss and Courchesne, 2007; Craig et al., 2007; Schumann et al., 2010). Finally, this investigation was cross-sectional in design, though larger than previously reported similar studies. Longitudinal designs, such as those conducted by Schumann et al. (2010) in early development and Hardan et al. (2009) in late childhood, are needed in later developmental windows to more definitively test postulations surrounding the cortical growth trajectory in autism spectrum disorders.