Participant Demographics, Diagnostic Group, and Global Brain Measures
There were no significant between-group differences in participants’ age. However, groups differed significantly in gender distribution (c2(3)=2.26, p=0.016), with a lower percentage of females in the idiopathic ASD group relative to the other subgroups, and in full-scale IQ (F(3)=21.01, p<0.001), with TD controls scoring higher than all other groups, and individuals with 22q11.2DS having a lower IQ than individuals with idiopathic ASD. Further, we found a significant effect of group for total brain volume (F(3)=10.56, p<0.001) and total SA (F(3)=12.41, p<0.001), with both 22q11.2DS groups having a significantly lower total volume and area compared to both idiopathic ASD and TD controls (p<0.05 for all pair-wise comparisons). Last, there was a significant effect of group for mean CT (F(3)=3.74, p<0.05) across the cortex, with idiopathic ASD individuals having a trend towards reduced CT compared to 22q11.nonASD individuals (p=0.088), while no other pair-wise comparison was significant (see Table 1 and Supplementary Tables S1 for all pair-wise comparisons). We thus co-varied for gender, full-scale IQ, and respective total brain measure in all subsequent analyses.
Results of the categorical fixed-effects analyses
Main Effect of 22q11.2DS on CV, SA, and CT
Significant neuroanatomical differences between 22q11.2 deletion carriers (i.e. 22q11.2DS with and without ASD) and non-carriers (i.e. idiopathic ASD and TD controls) were observed in several large clusters distributed across the cortex. More specifically, CV was increased in 22q11.2DS in the bilateral superior frontal cortex, the lateral and medial orbitofrontal cortex, the pre- and postcentral gyrus, the insula, and the supramarginal gyrus, with increases being driven by a commensurate increase in SA. Increased CV in 22q11.2DS was also observed in the left middle temporal gyrus, while increased SA was further observed in the left superior temporal gyrus and the left posterior cingulate cortex (PCC). In contrast, CV was decreased in 22q11.2DS in a large cluster centered on the bilateral medial occipital and temporal lobes, as well as in the bilateral anterior cingulate cortex, and the pre- and postcentral gyrus, accompanied by commensurate decreases in SA. Further decreases in SA were observed in the bilateral dorsal anterior cingulate area and inferior temporal gyri. Last, we identified increased CT in 22q11.2DS in some scattered regions, including the bilateral lateral occipital cortex, the right postcentral gyrus, and the left supramarginal gyrus, whereas decreases in CT were observed in the bilateral superior temporal lobes, the parahippocampal gyri, and the posterior cingulate cortex (see Fig. 1, Supplementary Fig. S3, and Supplementary Table S3). Effect size images for the main effect of 22q11.2DS are shown in Supplementary Fig. S4. A similar pattern of effects was also obtained when comparing the 22q11.2DS individuals to TD controls only (see Supplementary Fig. S1), and when strictly matching for age and gender (see Supplementary Fig. S6).
Main Effect of ASD on CV, SA, and CT
For the main effect of ASD, we established that individuals with ASD symptomatology (i.e. individuals with idiopathic ASD and 22q11.ASD) were neuroanatomically distinct from those without (i.e. compared to TD controls and 22q11.nonASD), with significantly increased CV in the left insula and left superior temporal gyrus, accompanied by a more widespread increase in SA, also spanning the fusiform, parahippocampal, lingual, and supramarginal gyri. CV was further increased in the right inferior parietal cortex in ASD. In contrast, decreases in CV in ASD were observed in the left entorhinal cortex, accompanied by a commensurate decrease in SA, that was more pronounced and also implicated the left fusiform gyrus. For measures of CT, individuals with ASD showed significant increases in the right isthmus cingulate cortex and the right superior temporal gyrus (see Fig. 1, Supplementary Fig. S3, and Supplementary Table S4). Effect size images for the main effect of ASD are shown in Supplementary Fig. S4. A similar pattern of effects was also obtained when comparing the idiopathic ASD individuals to TD controls only (see Supplementary Fig. S2), and when strictly matching for age and gender (see Supplementary Fig. S6).
Significant Interactions between 22q11.2DS and ASD
In addition to the main effects, we observed significant interactions between 22q11.2DS and ASD for measures of CV and SA. These were located in the left dorsolateral prefrontal cortex (DLPFC) for both, CV and SA, as well as in the right precentral gyrus for CV only, and in the left PCC for SA only (see Fig. 1, Supplementary Fig. S3, and Supplementary Table S5). Effect size images for the 22q11.2DS-by-ASD interaction are shown in Supplementary Fig. S4. In significant clusters, ASD was associated with increased CV and/or SA in 22q11.2DS (i.e. 22q11.ASD > 22q11.nonASD), but reduced CV and/or SA in individuals without the microdeletion (i.e. idiopathic ASD < TD controls). In the DLPFC and PCC, individuals with 22q11.nonASD were the most affected on the neuroanatomical level (i.e. had the most reduced CV and/or SA relative to all other groups), while both ASD groups were comparable in terms of their mean CV and/or SA (22q11.nonASD 22q11.ASD = ASD TD controls). In the precentral cluster exclusively, 22q11.ASD individuals had the largest mean CV compared to all other groups, with the mean of 22q11.nonASD individuals being between idiopathic ASD and TD controls (for boxplots see Supplementary Fig. S9). As the 22q11.ASD and idiopathic ASD groups differed in symptom severity in the repetitive behavior domain of the ADI-R, we also performed the analysis covarying for the SRS Restricted Interests and Repetitive Behavior subscale. However, the patterns of significant 22q11.2DS-by-ASD interactions remained unchanged overall (see Supplementary Fig. S10). In regions with significant 22q11.2DS-by-ASD interactions, there were also no significant differences in variance between the idiopathic ASD individuals and the 22q11.ASD group (see Supplementary Fig. S5), and very little effect of age and gender (see Supplementary Fig. S6).
Results of the CCA
Initially, CCA was performed across all individuals within our sample (i.e. carriers and non-carriers of the 22q11.2 microdeletion). Here, we observed a significant multivariate association between the 63 regional measures of brain anatomy highlighted to be of importance by the stepwise variable selection approach, and the five symptom domains of the SRS (RVcoef=0.082, p<0.001; see Supplementary Fig. S11 for distribution of SRS total and subdomain scores across groups). Based on the number of clinical predictors (q=5), the CCA yielded five canonical variate pairs with the canonical correlations of 0.822, 0.772, 0.764, 0.724, and 0.653 for each successive canonical variate pair, respectively (see Fig. 2A). Collectively, the full model including all canonical variates was statistically significant using Wilks’ l=0.015 (F(315,319)=1.35, p<0.01) and Pillai’s trace=2.81 (F(315,335)=1.36, p<0.01). As Wilks’ l indicates the variance unaccounted for by the model, the R-square type (r2) effect size of the model was 0.985 (i.e. 1-l), which means that the full model explained about 98.5% of the variance shared between measures of neuroanatomy and clinical symptom profile. Moreover, the total variance in SRS scores that could be explained by neuroanatomical variation was 57.47%, which only the first two neuroanatomical canonical variates contributed to significantly (20.82% and 21.59%, respectively; see Fig. 2A). Out of all canonical variates, the 1st (Bartlett’s c2(315)=402.24, p<0.001) and the 2nd (Bartlett’s c2(248)=294.58, p<0.05) were also statistically significant, with the 1st clinical canonical variate explaining a total of 30.80%, and the 2nd clinical canonical variate explaining a total of 36.19% of variability within the set of clinical variables on their own (clinical canonical variate adequacy, see Fig. 2B). Thus, given the r2 effects for each canonical variate pair, only the first two pairs were considered noteworthy in the context of the present study. Both clinical canonical variates, and the 2nd canonical variate in particular, also provided a good discrimination between individuals with and without ASD (see Figs. 2C & 2D). Figures 2E and 2F show the canonical loadings (lC) for each neuroanatomical predictor on the cortical surface, which highlights the set of brain regions maximally correlated with the 2nd (E) and 1st (F) neuroanatomical canonical variate. As expected, high positive loadings (i.e. >0.25) were observed in many regions of the social brain including the right medial orbitofrontal lobe (CT, lC2=0.28), the right rostral middle frontal gyrus (CT, lC2=0.30), the left insula (CV, lC2=0.34), and the left transverse temporal lobe (CV, lC2=0.28). High negative loadings were observed in the left precuneus (CT, lC1=-0.27), the bilateral superior parietal lobes (CT, right: lC2=-0.28; CV, left: lC2=-0.28), and the left temporal pole (SA, lC1=-0.30; CV, lC1=-0.38).
After fitting the CCA in the total sample, we utilized the resulting canonical variate scores to derive group-specific factor loadings (clinical and neuroanatomical) for carriers and non-carriers of the 22q11.2 microdeletion, which were subsequently compared between groups. Overall, there was a high degree of similarity in the clinical canonical variate structure observed carriers and non-carriers, with Tucker’s congruence coefficients for the 1st and 2nd clinical covariates exceeding a value of 0.99 (see Figs. 3A & 3B). However, when examining the neuroanatomical underpinnings of these clinical variates between groups, we found that there was a low degree of neuroanatomical similarity overall (mean Tucker’s congruence coefficient across canonical variates=0.336), and low levels of congruence for canonical variate 1 (Tucker’s congruence coefficient=0.393) and variate 2 (Tucker’s congruence coefficient=0.404). We also observed significant between-group differences in individual neuroanatomical loading pairs, which are displayed in Figs. 3C-F. More specifically, for canonical variate 2, which is the variate that explained the largest percentage of clinical variability (see Figs. 3C & 3D), we observed a significant difference in the loadings of the right rostral middle frontal cortex (CT; Fisher’s Z=1.68, p<0.05), the left precuneus (CT; Fisher’s Z=2.01, p<0.05), the left paracentral gyrus (SA; Fisher’s Z=2.48, p<0.01), the left medial orbitofrontal cortex (CT; Fisher’s Z=1.90, p<0.05), the left fusiform gyrus (CT; Fisher’s Z=2.80, p<0.01), and the right temporal pole (CT; Fisher’s Z=1.78, p<0.05). For canonical variate 1, the variate to explain the second most variability (Figs. 3E & 3F), individuals with 22q11.2DS had significantly higher neuroanatomical loadings in the left insula (CT; Fisher’s Z=1.99, p<0.05), the left cuneus (CT; Fisher’s Z=1.95, p<0.05), the right lateral orbitofrontal cortex (CT; Fisher’s Z=1.76, p<0.05), the left pars triangularis (SA; Fisher’s Z=1.94, p<0.05), and in the right rostral anterior cingulate cortex (SA; Fisher’s Z=2.84, p<0.01). Individuals with 22q11.2DS further had a more negative loading between the 1st canonical variate and the volume of the medial orbitofrontal cortex compared to non22q11.2DS individuals (CV; Fisher’s Z=1.74, p<0.05). Thus, despite the high degree of similarity in the clinical composition of autism symptoms across groups, we observed that inter-individual differences in clinical symptom profiles were underpinned by different neuroanatomical substrates in carriers and non-carriers of the 22q11.2 microdeletion.