Integrating clinical and research imaging to uncover neuroanatomic deviations in 22q11.2 deletions
Poster No:
697
Submission Type:
Abstract Submission
Authors:
Benjamin Jung1, J. Eric Schmitt2, Jenna Schabdach1, Jakob Seidlitz1, T. Blaine Crowley1, Shivaram Karandikar1, Ayan Mandal1, Dabriel Zimmerman1, Remo Williams1, Viveknarayanan Padmanabhan1, Daniel McGinn1, Elaine Zackai1, Beverly Emanuel1, Sarah Hopkins1, Madeline Chadehumbe1, ENIGMA 22q Working Group3, Chris Ching4, Carrie Bearden3, David Roalf2, Raquel Gur2, Donna McDonald-McGinn1, Aaron Alexander-Bloch2
Institutions:
1Children's Hospital of Philadelphia, Philadelphia, PA, 2University of Pennsylvania, Philadelphia, PA, 3University of California, Los Angeles, Los Angeles, CA, 4University of Southern California, California, CA
First Author:
Co-Author(s):
Introduction:
While the neuroanatomy of 22q11.2 deletion syndrome (22q11DS) has been characterized (Gur et al., 2021), ascertainment biases owed to study exclusion criteria and limited data in infants and toddlers provides an incomplete picture of 22q11DS endophenotypes. Clinically acquired brain MRIs are often assumed to have limited use for research due to a lack of demographically-matched controls and other methodological hurdles. However, growth charts of scans with limited imaging pathology in clinical MRI, comparable to those derived from large research cohorts, permit the assessment of neuroanatomical deviations in clinical scans (Schabdach et al., 2023). This study integrates research data from the ENIGMA 22q11.2 Working Group, the largest neuroimaging consortium on 22q11DS, with clinical MRI from the Children's Hospital of Philadelphia (CHOP), the largest center in the USA for 22q11DS diagnosis and treatment, to provide a comprehensive characterization of neuroanatomic effects in 22q11DS.
Methods:
We retrospectively curated a cross-sectional cohort of individuals with 22q11DS who received MRIs at CHOP (Figure 1). First, we performed a systematic clinical review of all available (N=167) CHOP brain MRI data by a board certified neuroradiologist with expertise in 22q11DS to advance our understanding of 22q11DS qualitative imaging abnormalities (Schmitt et al., 2014). Scans with limited imaging pathology were then matched to "clinical controls" as described previously (Schabdach et al, 2023) and processed using Synthseg or Infant FreeSurfer (Billot et al., 2023; Zollei et al., 2020). Growth curve models fit on clinical data with generalized additive models for location, scale, and shape (GAMLSS) were used to calculate grey matter volume centiles (Schabdach et al., 2023). Scans from the ENIGMA consortium were processed using Freesurfer v5.3 using growth curve models fitted to research data (Bethlehem et al., 2022). After quality control, sample sizes included 513 individuals with 22q11DS, including 73 patients from CHOP (age 0.9 to 37 years) and 440 individuals from ENIGMA = 44 (age 6 to 54 years) and 826 controls (CHOP = 522, ENIGMA = 344).
Results:
On neuroradiological review, individuals with 22q11DS were found to have generalized cerebral volume loss (41% mild, 17% moderate, 6% severe) and disproportionately high rates of cavum septum pellucidum (37%), polymicrogyria/pachygyria (5%), Chiari I malformations (4%), cerebellar hypoplasia (2%), and rhombencephalosynapsis (1%).
Quantitative analyses found robust neuroanatomical deviations in individuals with 22q11DS (Figure 2). Intracranial volume was lower in 22q11DS than controls (Cohen's d=-0.6). Cortical volume differences were most pronounced in the occipital (d=-1.2 to -0.8) and parietal (d=-1.1 to -0.2) cortices. In the subcortex, volume loss was found in the brainstem (d=-1.3), cerebellum (left/right Cohen's d = -1.3/-1.3), hippocampus (d=-1.0/-1.0), amygdala (d=-0.5/-0.5), putamen (d=-0.4/-0.5), and right pallidum (d=-0.2). Ventricles were significantly larger (d=0.9), as was the right caudate (d=0.2), and bilateral accumbens (d=0.2/0.4). Cortical volumes were strongly correlated between datasets (spin-test; r = 0.66, p < 0.001).
Quantitative analyses found robust neuroanatomical deviations in individuals with 22q11DS (Figure 2). Intracranial volume was lower in 22q11DS than controls (Cohen's d=-0.6). Cortical volume differences were most pronounced in the occipital (d=-1.2 to -0.8) and parietal (d=-1.1 to -0.2) cortices. In the subcortex, volume loss was found in the brainstem (d=-1.3), cerebellum (left/right Cohen's d = -1.3/-1.3), hippocampus (d=-1.0/-1.0), amygdala (d=-0.5/-0.5), putamen (d=-0.4/-0.5), and right pallidum (d=-0.2). Ventricles were significantly larger (d=0.9), as was the right caudate (d=0.2), and bilateral accumbens (d=0.2/0.4). Cortical volumes were strongly correlated between datasets (spin-test; r = 0.66, p < 0.001).
Conclusions:
This integration of large-scale research and clinical imaging highlights the robust neuroanatomic signature of 22q11DS. Findings broadly recapitulate those previously reported by ENIGMA (Ching et al., 2020; Sun et al., 2020). However, the present study is unique in combining qualitative neuroradiological review with quantitative image analysis, finding that cerebral volume loss was observable in over half of the clinical cohort. The clinical sample also incorporates youth who may not participate in prospective research studies, increasing the generalizability of findings. Collectively, these results advance our understanding of 22q11DS and its impact on brain development.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 2
Genetics:
Neurogenetic Syndromes 1
Lifespan Development:
Normal Brain Development: Fetus to Adolescence
Keywords:
Development
Phenotype-Genotype
Schizophrenia
STRUCTURAL MRI
Other - 22q11.2 Deletion Syndrome
1|2Indicates the priority used for review
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Provide references using APA citation style.
Billot, B., et al. (2023). SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining. Medical Image Analysis, 86, 102789.
Ching, C. R. K., et al. (2020). Mapping Subcortical Brain Alterations in 22q11.2 Deletion Syndrome: Effects of Deletion Size and Convergence With Idiopathic Neuropsychiatric Illness. American Journal of Psychiatry, 177(7), 589-600.
Gur, R. E., et al. (2021). Pathways to understanding psychosis through rare - 22q11.2DS - and common variants. Current Opinion in Genetics & Development, 68, 35-40.
Schabdach, J. M., et al. (2023). Brain Growth Charts for Quantitative Analysis of Pediatric Clinical Brain MRI Scans with Limited Imaging Pathology. Radiology, 309(1), e230096.
Schmitt, J. E., et al. (2014). Incidental radiologic findings in the 22q11.2 deletion syndrome. American Journal of Neuroradiology, 35(11), 2186-2191.
Sun, D., et al. (2020). Large-scale mapping of cortical alterations in 22q11.2 deletion syndrome: Convergence with idiopathic psychosis and effects of deletion size. Molecular Psychiatry, 25(8), 1822-1834.
Zollei, L., et al. (2020). Infant FreeSurfer: An automated segmentation and surface extraction pipeline for T1-weighted neuroimaging data of infants 0-2 years. Neuroimage, 218, 116946.