Source-based morphometry reveals structural brain pattern abnormalities in 22q11.2 deletion syndrome

Ruiyang Ge, Christopher R. K. Ching, Anne S. Bassett, Leila Kushan, Kevin M. Antshel, Therese van Amelsvoort, Geor Bakker, Nancy J. Butcher, Linda E. Campbell, Eva W. C. Chow, Michael Craig, Nicolas A. Crossley, Adam Cunningham, Eileen Daly, Joanne L. Doherty, Courtney A. Durdle, Beverly S. Emanuel, Ania Fiksinski, Jennifer K. Forsyth, Wanda FremontNaomi J. Goodrich-Hunsaker, Maria Gudbrandsen, Raquel E. Gur, Maria Jalbrzikowski, Wendy R. Kates, Amy Lin, David E. J. Linden, Kathryn L. Mccabe, Donna McDonald-McGinn, Hayley Moss, Declan G. Murphy, Kieran C. Murphy, Michael J. Owen, Julio E. Villalon-Reina, Gabriela M. Repetto, David R. Roalf, Kosha Ruparel, J. Eric Schmitt, Sanne Schuite-Koops, Kathleen Angkustsiri, Daqiang Sun, Ariana Vajdi, Marianne van den Bree, Jacob Vorstman, Paul M. Thompson, Fidel Vila-Rodriguez*, Carrie E. Bearden*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

22q11.2 deletion syndrome (22q11DS) is the most frequently occurring microdeletion in humans. It is associated with a significant impact on brain structure, including prominent reductions in gray matter volume (GMV), and neuropsychiatric manifestations, including cognitive impairment and psychosis. It is unclear whether GMV alterations in 22q11DS occur according to distinct structural patterns. Then, 783 participants (470 with 22q11DS: 51% females, mean age [SD] 18.2 [9.2]; and 313 typically developing [TD] controls: 46% females, mean age 18.0 [8.6]) from 13 datasets were included in the present study. We segmented structural T1-weighted brain MRI scans and extracted GMV images, which were then utilized in a novel source-based morphometry (SBM) pipeline (SS-Detect) to generate structural brain patterns (SBPs) that capture co-varying GMV. We investigated the impact of the 22q11.2 deletion, deletion size, intelligence quotient, and psychosis on the SBPs. Seventeen GMV-SBPs were derived, which provided spatial patterns of GMV covariance associated with a quantitative metric (i.e., loading score) for analysis. Patterns of topographically widespread differences in GMV covariance, including the cerebellum, discriminated individuals with 22q11DS from healthy controls. The spatial extents of the SBPs that revealed disparities between individuals with 22q11DS and controls were consistent with the findings of the univariate voxel-based morphometry analysis. Larger deletion size was associated with significantly lower GMV in frontal and occipital SBPs; however, history of psychosis did not show a strong relationship with these covariance patterns. 22q11DS is associated with distinct structural abnormalities captured by topographical GMV covariance patterns that include the cerebellum. Findings indicate that structural anomalies in 22q11DS manifest in a nonrandom manner and in distinct covarying anatomical patterns, rather than a diffuse global process. These SBP abnormalities converge with previously reported cortical surface area abnormalities, suggesting disturbances of early neurodevelopment as the most likely underlying mechanism.Using a novel source-based morphometry method called SS-Detect, we identified 12 structural brain patterns (SBPs) that discriminated individuals with 22q11.2 deletion syndrome from healthy controls. We further demonstrated that deletion size was related to structural covariance patterns; however, history of psychosis did not show a strong relationship with these covariance patterns.image
Original languageEnglish
Article numbere26553
Number of pages15
JournalHuman Brain Mapping
Volume45
Issue number1
DOIs
Publication statusPublished - 1 Jan 2024

Keywords

  • 22q11 deletion syndrome
  • gray matter volume
  • magnetic resonnance imaging
  • source-based morphometry
  • LARGE-SCALE
  • CHILDREN
  • COVARIANCE
  • BEHAVIOR
  • ASSOCIATIONS
  • DISORDERS
  • NETWORKS

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