TY - JOUR
T1 - Genetic Heterogeneity Shapes Brain Connectivity in Psychiatry
AU - Moreau, Clara A
AU - Harvey, Annabelle
AU - Kumar, Kuldeep
AU - Huguet, Guillaume
AU - Urchs, Sebastian G W
AU - Douard, Elise A
AU - Schultz, Laura M
AU - Sharmarke, Hanad
AU - Jizi, Khadije
AU - Martin, Charles-Olivier
AU - Younis, Nadine
AU - Tamer, Petra
AU - Rolland, Thomas
AU - Martineau, Jean-Louis
AU - Orban, Pierre
AU - Silva, Ana Isabel
AU - Hall, Jeremy
AU - van den Bree, Marianne B M
AU - Owen, Michael J
AU - Linden, David E J
AU - Labbe, Aurelie
AU - Lippé, Sarah
AU - Bearden, Carrie E
AU - Almasy, Laura
AU - Glahn, David C
AU - Thompson, Paul M
AU - Bourgeron, Thomas
AU - Bellec, Pierre
AU - Jacquemont, Sebastien
N1 - Copyright © 2022 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - 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.
AB - 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.
U2 - 10.1016/j.biopsych.2022.08.024
DO - 10.1016/j.biopsych.2022.08.024
M3 - Article
C2 - 36372570
SN - 0006-3223
VL - 93
SP - 45
EP - 58
JO - Biological Psychiatry
JF - Biological Psychiatry
IS - 1
ER -