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 magnetic resonance imaging (MRI) without sedation, features common in 22q11DS and other rare genetic disorders. 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 In this retrospective, cross-sectional study, 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 patient 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 centile. Spatial patterns of cortical volume and surface area correlated with expression of genes within the 22q11.2 locus. In exploratory analyses, syndrome-specific growth chart deviations in cerebellar volumes relative to 22q11DS peers were nominally associated with lower language scores across two independent assessment methods ( p < 0.03), suggesting 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.

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Journal
Genome Medicine
Published
2026-10-17
DOI
https://doi.org/10.1186/s13073-026-01788-7
Primary Topic
Genomic variations and chromosomal abnormalities
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article
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article

Charting brain structure in 22q11.2 deletion syndrome with clinical neuroimaging

Jennifer K. Forsyth, Elaine H. Zackai, Ruth M. O'Hara, Naomi J. Goodrich‐Hunsaker et al.
Genome Medicine
Genomic variations and chromosomal abnormalities
article

Charting brain structure in 22q11.2 deletion syndrome with clinical neuroimaging

Jennifer K. Forsyth, Elaine H. Zackai, Ruth M. O'Hara, Naomi J. Goodrich‐Hunsaker, Carrie E. Bearden, Ayan S. Mandal, Kieran C. Murphy, Richard A. I. Bethlehem, Madeline A. Chadehumbe, Charles H. Schleifer, Raquel E. Gur, Marianna Frascarelli, Fabio Di Fabio, Aaron F. Alexander‐Bloch, Beverly S. Emanuel, Thérèse van Amelsvoort, Margaret Gardner, Wendy R. Kates, Michael John Owen, Samuel J. R. A. Chawner, James William Gaynor, Rune Bøen, J. Eric Schmitt, Russell Taki Shinohara, Kathleen Angkustsiri, David R. Roalf, Geor Bakker, Donna M. McDonald‐McGinn, Jacob A. S. Vorstman, Kosha Ruparel, David E.J. Linden, Ania Fiksinski, Hayley M. Moss, Allan L. Reiss, Sarah E. Hopkins, Sanne Koops, Kevin M. Antshel, Gabriela M. Repetto, Linda Campbell, Maria Gudbrandsen, Wanda P. Fremont, Jakob Seidlitz, Bogdan Paşaniuc, Elizabeth Levitis, Karen Jaqueline Low, Viveknarayanan Padmanabhan, Joachim Franz Hallmayer, Jenna Schabdach, Remo Williams, Smrithi Prem, Daniel E. McGinn, Julio E. Villalón‐Reina, Nancy J. Butcher, Lena Dorfschmidt, Benjamin Jung, Terrence Blaine Crowley, Katherine Cyr, Kathryn McCabe, Jerome H. Taylor, Anne S. Bassett, Hoki Fung, Maria Jalbrzikowski, Marianne B. M. van den Bree, Courtney Alexandra Durdle, Tim J. Cole, Paul M. Thompson, Declan G. Murphy, Stewart A. Anderson, Eva W.C. Chow, Tony J. Simon, Dabriel Zimmerman, Shivaram Karandikar, Joanne Doherty, Leila Kushan, Adam Cunningham, Michael C. Craig, Nicolas A. Crossley, Christopher R. K. Ching, the ENIGMA 22q11.2 Deletion Syndrome Working Group, Eileen Daly
article en

Abstract

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 magnetic resonance imaging (MRI) without sedation, features common in 22q11DS and other rare genetic disorders. 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 In this retrospective, cross-sectional study, 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 patient 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 centile. Spatial patterns of cortical volume and surface area correlated with expression of genes within the 22q11.2 locus. In exploratory analyses, syndrome-specific growth chart deviations in cerebellar volumes relative to 22q11DS peers were nominally associated with lower language scores across two independent assessment methods ( p < 0.03), suggesting 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.

Genome Medicine
University of Southern California (US), Children's Hospital of Philadelphia (US), Harvard University (US), University of California, Los Angeles (US), University of Cambridge (GB), University of Bristol (GB), Massachusetts General Hospital (US), NeuroDevelopment Center (US), University of Pennsylvania Health System (US), University Hospitals Bristol and Weston NHS Foundation Trust (GB), University College London (GB), Mass General Brigham (US), University of Pennsylvania (US)
Good health and well-being
Openalex Percentile: Top 15%
Genomic variations and chromosomal abnormalities
DOIOpen Access PDFOpenAlex
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