Disrupted anatomic networks in the 22q11.2 deletion syndrome

Abstract

The 22q11.2 deletion syndrome (22q11DS) is an uncommon genetic disorder with an increased risk of psychosis. Although the neural substrates of psychosis and schizophrenia are not well understood, aberrations in cortical networks represent intriguing potential mechanisms. Investigations of anatomic networks within 22q11DS are sparse. We investigated group differences in anatomic network structure in 48 individuals with 22q11DS and 370 typically developing controls by analyzing covariance patterns in cortical thickness among 68 regions of interest using graph theoretical models. Subjects with 22q11DS had less robust geographic organization relative to the control group, particularly in the occipital and parietal lobes. Multiple global graph theoretical statistics were decreased in 22q11DS. These results are consistent with prior studies demonstrating decreased connectivity in 22q11DS using other neuroimaging methodologies.

Keywords: 22q11DS; MRI; cortical thickness; morphometry; network; schizophrenia.

Fig. 1

Summary of the statistical pipeline. Correlation matrices for corrected measures of cortical thickness (A) were constructed for TD and 22q11DS groups separately. Significant edges were then identified either via serial thresholding or using the PCIT algorithm (B). Finally, undirected networks for each group were generated in igraph (C). The same pipeline was used for subsequent bootstrap and permutation analyses.

Fig. 2

Results of hierarchical cluster analysis for cortical thickness for TD and 22q11DS groups. Positive correlations are shown in green, negative correlations in red. In the TD group, ROIs were strongly clustered by lobar anatomy: 1) frontal, 2) parieto-occipital, 3) insulo-temporal, and 4) limbic. Cross-trait correlations in 22q11DS were weaker, as was the degree of anatomic clustering.

Fig. 3

Group differences in global cortical thickness network properties as a function of correlational threshold. Network statistics are shown for typically developing (black circles) and 22q11DS (red triangles) separately with error bars representing standard deviations. Insets display results of AUC analysis for each network statistic; there were significant group differences (p < 0.0001) for all statistics.

Fig. 4

Group differences in global cortical thickness network properties as a function of network sparcicity. Network statistics are shown for typically developing (black circles) and 22q11DS (red triangles) separately with error bars representing standard deviations. Insets display results of AUC analysis for each network statistic; there were significant group differences (p < 0.0001) for all statistics.

Fig. 5

Disrupted connectivity and modularity in 22q11DS. Graph models of cortical thickness networks for TD and 22q11DS (top). Nodes represent 68 regions of interest color-coded by lobar anatomy. Node shape indicates laterality (square = right, circle = left). Global connectivity statistics (bottom). Black dots represent difference scores (TD - 22q11DS) for measures of network cohesion. The null distribution was estimated empirically via permutation, with mean (open dot) and 95% confidence intervals.