Kuldeep Kumar, Claudia Modenato, Clara Moreau, Christopher R. K. Ching, Annabelle Harvey, Sandra Martin-Brevet, Guillaume Huguet, Martineau Jean-Louis, Elise Douard, Charles-Olivier Martin, Nadine Younis, Petra Tamer, Anne M. Maillard, Borja Rodriguez-Herreros, Aurélie Pain, Sonia Richetin, 16p11.2 European Consortium, Simons Searchlight Consortium, Leila Kushan, Dmitry Isaev, Kathryn Alpert, Anjani Ragothaman, Jessica A. Turner, Lei Wang, Tiffany C. Ho, Lianne Schmaal, Ana I. Silva, Marianne B.M. van den Bree, David E.J. Linden, Michael J. Owen, Jeremy Hall, Sarah Lippé, Guillaume Dumas, Bogdan Draganski, Boris A. Gutman, Ida E. Sønderby, Ole A. Andreassen, Laura Schultz, Laura Almasy, David C. Glahn, Carrie E. Bearden, Paul M. Thompson, Sébastien Jacquemont
Publication year: 2023


Objectives Copy number variants (CNVs) are well-known genetic pleiotropic risk factors for multiple neurodevelopmental and psychiatric disorders (NPDs) including autism (ASD) and schizophrenia (SZ). Overall, little is known about how different CNVs conferring risk for the same condition may affect subcortical brain structures and how these alterations relate to the level of disease risk conferred by CNVs. To fill this gap, we investigated gross volume, and vertex level thickness and surface maps of subcortical structures in 11 different CNVs and 6 different NPDs.

Methods Subcortical structures were characterized using harmonized ENIGMA protocols in 675 CNV carriers (at the following loci: 1q21.1, TAR, 13q12.12, 15q11.2, 16p11.2, 16p13.11, and 22q11.2) and 782 controls (Male/Female: 727/730; age-range: 6-80 years) as well as ENIGMA summary-statistics for ASD, SZ, ADHD, Obsessive-Compulsive-Disorder, Bipolar-Disorder, and Major-Depression.

Results Nine of the 11 CNVs affected volume of at least one subcortical structure. The hippocampus and amygdala were affected by five CNVs. Effect sizes of CNVs on subcortical volume, thickness and local surface area were correlated with their previously reported effect sizes on cognition and risk for ASD and SZ. Shape analyses were able to identify subregional alterations that were averaged out in volume analyses. We identified a common latent dimension – characterized by opposing effects on basal ganglia and limbic structures – across CNVs and across NPDs.

Conclusion Our findings demonstrate that subcortical alterations associated with CNVs show varying levels of similarities with those associated with neuropsychiatric conditions. We also observed distinct effects with some CNVs clustering with adult conditions while others clustered with ASD. This large cross-CNV and NPDs analysis provide insight into the long-standing questions of why CNVs at different genomic loci increase the risk for the same NPD, as well as why a single CNV increases the risk for a diverse set of NPDs.

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