Charting Brain Structure in 22q11.2 Deletion Syndrome with Clinical Neuroimaging

Abstract

Background: 22q11.2 deletion syndrome (22q11DS) is a common microdeletion associated with widespread brain alterations and elevated risk for schizophrenia and other neuropsychiatric conditions. Prospective research studies often exclude individuals with severe cognitive impairment, medical comorbidities, or inability to tolerate research MRI without sedation, features common in 22q11DS. This limits both the generalizability of neuroimaging findings and our understanding of the full phenotypic spectrum. Moreover, while standard brain growth charts quantify deviation from typical development, they cannot identify patients who are disproportionately affected relative to their genetic peers, limiting clinical utility for risk stratification. Leveraging clinical MRI data offers a scalable approach to address these gaps.

Methods: We analyzed 92 patients with 22q11DS (age 0.5-21 years, 49% female) and 252 matched clinical controls. Using normative modeling derived from 1,995 reference clinical scans, we quantified individual-level brain deviations from population norms. We validated clinical findings against the independent ENIGMA-22q research consortium, characterized rates of extreme structural deviations to assess within-syndrome heterogeneity, correlated spatial patterns of brain alterations with gene expression from the Allen Human Brain Atlas, and generated syndrome-specific growth charts to test whether deviations from syndrome-specific norms predicted cognitive and language outcomes.

Results: Patients with 22q11DS showed widespread reductions in brain volumes (max Cohen's d=-1.31) and cortical surface area (d=-0.71) with increased cortical thickness (d=0.39). These findings were highly convergent with the ENIGMA-22q research cohort (r=0.61-0.87). Forty percent of patients showed at least one global brain measure below the 2.5th percentile. Spatial patterns of cortical volume and surface area correlated with the expression of genes within the 22q11.2 locus. Critically, syndrome-specific growth charts revealed that smaller cerebellar volume relative to 22q11DS peers predicted lower language scores across two independent assessment methods (p<0.03), demonstrating potential prognostic utility.

Conclusions: This study provides a critical proof of principle for using heterogeneous clinical imaging to robustly characterize brain structure in rare genetic disorders. Syndrome-specific growth charts provide a novel framework to quantify within-syndrome variability and demonstrate potential prognostic value by linking individual brain structure to cognitive outcomes.

Keywords: 22q11.2 deletion syndrome; copy number variation; electronic health records; normative modeling; schizophrenia; structural imaging.

Figure 1.. Effect sizes of 22q11.2 Deletion syndrome (22q11DS) on brain deviation scores.

(A) Boxplots show individual standardized deviation scores for global brain measures in patients with 22q11DS (n=92) and controls (n=252). (B and C) Brain maps display Cohen’s d effect sizes for regional deviations in (B) subcortical gray matter volume (GMV) and (C) cortical GMV, surface area (SA), and thickness (CT). Regions with negative deviation scores in 22q11DS (i.e., smaller values in 22q11DS) are shown in blue, and regions with positive scores are shown in red. Solid black outlines indicate regions with significant case-control differences. (D) Scatter plots show the correlation between Cohen’s d effect sizes from the primary CHOP cohort (x-axis) and the independent ENIGMA-22q cohort (y-axis). All deviation scores were derived from population growth charts predicting deviations based on age, sex, and scanner. P-values were corrected for multiple comparisons using the Benjamini-Hochberg false discovery rate (FDR) procedure. Asterisks indicate the level of statistical significance after correction. **** p < 0.0001, *** p < 0.001, ** p < 0.01 , * < 0.05. Abbreviations: CT, cortical thickness; GMV, gray matter volume; ICV, intracranial volume; n.s., not significant; SA, total SA; sGMV, subcortical GMV; WMV, white matter volume.

Figure 2.. Extreme atypicality of brain features is common in 22q11.2 Deletion syndrome (22q11DS).

Brain maps showing the percentage of patients with atypically low scores (A) and atypically high scores (B) for each brain feature. Atypically low scores were defined as falling below the 2.5^th percentile of the reference distribution, while atypically high scores were defined as above the 97.5^th percentile. The statistical significance of regional enrichment for extreme phenotypes (indicated by solid black outlines) was assessed using a permutation test of case-control diagnoses (1,000 permutations). P-values were corrected for multiple comparisons using the Benjamini-Hochberg false discovery rate (FDR) procedure. n.s. indicates not significant.

Figure 3.. Spatial correlation between brain deviations in 22q11.2 Deletion syndrome (22q11DS) and expression of genes in the 22q11.2 locus in postmortem brain tissue

(A) The spatial maps of median deviation scores for gray matter volume (GMV), surface area (SA), and cortical thickness (CT) were compared to the first principal component (PC1) of brain-wide gene expression from the Allen Human Brain Atlas. The scatter plots on the right show a significant negative correlation between the PC1 gradient and the deviation maps for both GMV (r = −0.50, p_perm < 0.001) and SA (r = −0.48, p_perm = 0.03) in 22q11DS. No significant correlation was observed for CT (r = −0.12, p_perm = 0.3). (B) Follow-up analyses show significant correlations between the GMV and SA deviation maps and the expression patterns of individual genes in the 22q11DS locus. Shown are the six 22q11DS genes that were significantly correlated with deviation maps after multiple comparisons correction. Significance was assessed by comparing the difference in correlation coefficients of cases and controls to a null distribution across 1,000 permutations. Abbreviations: CT, cortical thickness; GMV, gray matter volume; PC1, first principal component; SA, surface area.

Figure 4.. Syndrome-specific brain growth charts for 22q11.2 Deletion syndrome (22q11DS) and their association with cognitive outcomes.

(A) Global brain growth charts for intracranial volume (ICV), cortical gray matter volume (GMV), subcortical GMV (sGMV) and white matter volume (WMV). For each measure, the left panel (“Reference”) shows individual data points from the 22q11DS cohort plotted against the reference population’s growth curves. The middle panel (“22q Adjusted”) displays the same data points against the newly generated growth charts that are specific to 22q11DS. The right panel (“Overlap“) directly compares the median (solid lines) and 2.5th/97.5th centile (dashed lines) curves for both the reference (gray) and 22q11DS-specific models (black) averaged across sexes to visualize the shift in curves. (B) Exploratory analysis linking brain deviations to clinical outcomes. The points represent the estimated association (standardized beta coefficient) from linear models testing the relationship between an individual’s deviation from 22q11DS-specific growth charts and their scores on intelligence and language tests. Error bars indicate 95% confidence intervals. Cortical thickness measures were excluded from this analysis due to limited sample sizes. Abbreviations: CELF, Clinical Evaluation of Language Fundamentals; CT, cortical thickness; FSIQ, full-scale intelligence quotient; GMV, gray matter volume; ICV, intracranial volume; PIQ, performance intelligence quotient; PLS, Preschool Language Scales; SA, surface area; sGMV, subcortical GMV; VIQ, verbal intelligence quotient; WMV, white matter volume.