Genetic heterogeneity shapes brain connectivity in psychiatry

Moreau, Clara A., Harvey, Annabelle, Kumar, Kuldeep, Huguet, Guillaume, Urchs, Sebastian G.W., Douard, Elise A., Schultz, Laura M., Sharmarke, Hanad, Jizi, Khadije, Martin, Charles-Olivier, Younis, Nadine, Tamer, Petra, Rolland, Thomas, Martineau, Jean-Louis, Orban, Pierre, Silva, Ana Isabel ORCID: https://orcid.org/0000-0002-1184-4909, Hall, Jeremy, van den Bree, Marianne B.M. ORCID: https://orcid.org/0000-0002-4426-3254, Owen, Michael J. ORCID: https://orcid.org/0000-0003-4798-0862, Linden, David E.J. ORCID: https://orcid.org/0000-0002-5638-9292, Labbe, Aurelie, Lippé, Sarah, Bearden, Carrie E., Almasy, Laura, Glahn, David C., Thompson, Paul M., Bourgeron, Thomas, Bellec, Pierre and Jacquemont, Sebastien 2023. Genetic heterogeneity shapes brain connectivity in psychiatry. Biological Psychiatry 93 (1) , pp. 45-58. 10.1016/j.biopsych.2022.08.024

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Abstract

Background Polygenicity and genetic heterogeneity pose great challenges for studying psychiatric conditions. Genetically informed approaches have been implemented in neuroimaging studies to address this issue. However, the effects on functional connectivity of rare and common genetic risks for psychiatric disorders are largely unknown. Our objectives were to estimate and compare the effect sizes on brain connectivity of psychiatric genomic risk factors with various levels of complexity: oligogenic copy number variants (CNVs), multigenic CNVs, and polygenic risk scores (PRSs) as well as idiopathic psychiatric conditions and traits. Methods Resting-state functional magnetic resonance imaging data were processed using the same pipeline across 9 datasets. Twenty-nine connectome-wide association studies were performed to characterize the effects of 15 CNVs (1003 carriers), 7 PRSs, 4 idiopathic psychiatric conditions (1022 individuals with autism, schizophrenia, bipolar conditions, or attention-deficit/hyperactivity disorder), and 2 traits (31,424 unaffected control subjects). Results Effect sizes on connectivity were largest for psychiatric CNVs (estimates: 0.2–0.65 z score), followed by psychiatric conditions (0.15–0.42), neuroticism and fluid intelligence (0.02–0.03), and PRSs (0.01–0.02). Effect sizes of CNVs on connectivity were correlated to their effects on cognition and risk for disease (r = 0.9, p = 5.93 × 10−6). However, effect sizes of CNVs adjusted for the number of genes significantly decreased from small oligogenic to large multigenic CNVs (r = −0.88, p = 8.78 × 10−6). PRSs had disproportionately low effect sizes on connectivity compared with CNVs conferring similar risk for disease. Conclusions Heterogeneity and polygenicity affect our ability to detect brain connectivity alterations underlying psychiatric manifestations.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Advanced Research Computing @ Cardiff (ARCCA) Medicine Psychology
Additional Information:	License information from Publisher: LICENSE 1: URL: http://creativecommons.org/licenses/by-nc-nd/4.0/, Start Date: 2023-11-28
Publisher:	Elsevier
ISSN:	0006-3223
Date of Acceptance:	22 August 2022
Last Modified:	23 Jul 2024 15:56
URI:	https://orca.cardiff.ac.uk/id/eprint/154600

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