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Meta-Analysis
. 2025 Apr 1;182(4):373-388.
doi: 10.1176/appi.ajp.20230806. Epub 2025 Feb 26.

Estimating Multimodal Structural Brain Variability in Schizophrenia Spectrum Disorders: A Worldwide ENIGMA Study

Wolfgang Omlor  1 Finn Rabe  1 Simon Fuchs  1 Werner Surbeck  1 Giacomo Cecere  1 Gao-Yang Huang  1 Stephanie Homan  1 Nils Kallen  1 Foivos Georgiadis  1 Tobias Spiller  1 Erich Seifritz  1 Thomas Weickert  1 Jason Bruggemann  1 Cynthia Weickert  1 Steven Potkin  1 Ryota Hashimoto  1 Kang Sim  1 Kelly Rootes-Murdy  1 Yann Quide  1 Josselin Houenou  1 Nerisa Banaj  1 Daniela Vecchio  1 Fabrizio Piras  1 Federica Piras  1 Gianfranco Spalletta  1 Raymond Salvador  1 Andriana Karuk  1 Edith Pomarol-Clotet  1 Amanda Rodrigue  1 Godfrey Pearlson  1 David Glahn  1 David Tomecek  1 Filip Spaniel  1 Antonin Skoch  1 Matthias Kirschner  1 Stefan Kaiser  1 Peter Kochunov  1 Feng-Mei Fan  1 Ole A Andreassen  1 Lars T Westlye  1 Pierre Berthet  1 Vince D Calhoun  1 Fleur Howells  1 Anne Uhlmann  1 Freda Scheffler  1 Dan Stein  1 Felice Iasevoli  1 Murray J Cairns  1 Vaughan J Carr  1 Stanley V Catts  1 Maria A Di Biase  1 Assen Jablensky  1 Melissa J Green  1 Frans A Henskens  1 Paul Klauser  1 Carmel Loughland  1 Patricia T Michie  1 Bryan Mowry  1 Christos Pantelis  1 Paul E Rasser  1 Ulrich Schall  1 Rodney Scott  1 Andrew Zalesky  1 Andrea de Bartolomeis  1 Annarita Barone  1 Mariateresa Ciccarelli  1 Arturo Brunetti  1 Sirio Cocozza  1 Giuseppe Pontillo  1 Mario Tranfa  1 Annabella Di Giorgio  1 Sophia I Thomopoulos  1 Neda Jahanshad  1 Paul M Thompson  1 Theo van Erp  1 Jessica Turner  1 Philipp Homan  1
Affiliations
Meta-Analysis

Estimating Multimodal Structural Brain Variability in Schizophrenia Spectrum Disorders: A Worldwide ENIGMA Study

Wolfgang Omlor et al. Am J Psychiatry. .

Abstract

Objective: The clinical diversity of schizophrenia is reflected by structural brain variability. It remains unclear how this variability manifests across different gray and white matter features. In this meta- and mega-analysis, the authors investigated how brain heterogeneity in schizophrenia is distributed across multimodal structural indicators.

Methods: The authors used the ENIGMA dataset of MRI-based brain measures from 22 international sites with up to 6,037 individuals for a given brain measure. Variability and mean values of cortical thickness, cortical surface area, cortical folding index, subcortical volume, and fractional anisotropy were examined in individuals with schizophrenia and healthy control subjects.

Results: Individuals with schizophrenia showed greater variability in cortical thickness, cortical surface area, subcortical volume, and fractional anisotropy within the frontotemporal and subcortical network. This increased structural variability was mainly associated with psychopathological symptom domains, and the schizophrenia group frequently displayed lower mean values in the respective structural measures. Unexpectedly, folding patterns were more uniform in individuals with schizophrenia, particularly in the right caudal anterior cingulate region. The mean folding values of the right caudal anterior cingulate region did not differ between the schizophrenia and healthy control groups, and folding patterns in this region were not associated with disease-related parameters.

Conclusions: In patients with schizophrenia, uniform folding patterns in the right caudal anterior cingulate region contrasted with the multimodal variability in the frontotemporal and subcortical network. While variability in the frontotemporal and subcortical network was associated with disease-related diversity, uniform folding may indicate a less flexible interplay between genetic and environmental factors during neurodevelopment.

Keywords: Neuroimaging; Neuroscience; Schizophrenia Spectrum and Other Psychotic Disorders.

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Conflict of interest statement

Dr. Andreassen has served as a consultant for Cortechs.ai and has received speakers honoraria from Janssen, Lundbeck, and Sunovion. Dr. Seifritz has served as an adviser and provided educational lectures for Angelini, Janssen, Lundbeck, Mepha Pharma, Otsuka, Recordati, Sunovion, and Schwabe. Dr. P. Homan has received grants and honoraria from Boehringer Ingelheim, Janssen, Lundbeck, Mepha, Neurolite, and Novartis. The other authors report no financial relationships with commercial interests.

Figures

Figure 1:
Figure 1:. Variability ratio of cortical thickness.
Lower panel: Variability ratio (VR) effect sizes for schizophrenia patients (SZ) vs. healthy controls (HC) are shown for different cortical regions and on a linear scale, statistically controlling for age and gender. Upper panel: VR effect sizes are projected onto the brain surface and color-coded as z-values. In these cortical maps, areas with higher VRs in patients appear in gradients of red, and areas with higher VRs in controls appear in gradients of blue. CI: Confidence Interval. Independent of the applied variability measure (variability ratio vs. coefficient of variation ratio), higher heterogeneity in schizophrenia was observed for the following regions: Bilateral superior, middle and inferior temporal region, bilateral superior frontal region, left supramarginal and fusiform region as well as right pars orbitalis and precentral region.
Figure 2:
Figure 2:. Variability ratio for cortical surface area.
Same conventions as for Fig. 1. Higher heterogeneity in schizophrenia was observed for the following regions, irrespective of the deployed variability measure: Bilateral superiorfrontal and transverse temporal regions, cortical areas around the right superior temporal sulcus, right superiortemporal region, right supramarginal region, left postcentral region, right medialorbitofrontal region, left superiorparietal region, left precuneus, right middle temporal region and right lingual region.
Figure 3:
Figure 3:. Variability ratio for cortical folding index.
Same conventions as for Fig. 1. Irrespective of the applied variability measure, schizophrenia patients exhibited higher heterogeneity in the right inferiortemporal region, but lower heterogeneity in the left parahippocampal area.
Figure 4:
Figure 4:. Variability ratio for subcortical volume.
Same conventions as for Fig. 1. Lower panel: Variability ratio (VR) effect sizes are shown for subcortical volumes. Upper panel: VR effect sizes are projected onto respective subcortical structures and color-coded as z-values. In these subcortical maps, areas with higher VRs in patients appear in gradients of red, and areas with higher VRs in controls appear in gradients of blue. Independent of the applied variability measure, schizophrenia patients showed higher heterogeneity for lateral ventricles, left nucleus accumbens, left caudate and right hippocampus.
Figure 5:
Figure 5:. Variability ratio for fractional anisotropy.
Same conventions as for Fig. 1. Lower panel: Variability ratio (VR) effect sizes are shown for fractional anisotropy (FA) of white matter structures. Upper panel: VR effect sizes are projected onto respective white matter structures and color-coded as z-values. In these maps, areas with higher VRs in patients appear in gradients of red, and areas with higher VRs in controls appear in gradients of blue. Irrespective of the deployed variability measure, higher homogeneity in schizophrenia was observed for the superior fronto-occipital fasciculus in both hemispheres.
Figure 6:
Figure 6:. PBSI analysis.
PBSI for cortical thickness (CT), cortical surface area (SA), cortical folding Index (FI), subcortical volume (SV) and fractional anisotropy (FA).

Update of

  • Estimating multimodal brain variability in schizophrenia spectrum disorders: A worldwide ENIGMA study.
    Omlor W, Rabe F, Fuchs S, Cecere G, Homan S, Surbeck W, Kallen N, Georgiadis F, Spiller T, Seifritz E, Weickert T, Bruggemann J, Weickert C, Potkin S, Hashimoto R, Sim K, Rootes-Murdy K, Quide Y, Houenou J, Banaj N, Vecchio D, Piras F, Piras F, Spalletta G, Salvador R, Karuk A, Pomarol-Clotet E, Rodrigue A, Pearlson G, Glahn D, Tomecek D, Spaniel F, Skoch A, Kirschner M, Kaiser S, Kochunov P, Fan FM, Andreassen OA, Westlye LT, Berthet P, Calhoun VD, Howells F, Uhlmann A, Scheffler F, Stein D, Iasevoli F, Cairns MJ, Carr VJ, Catts SV, Di Biase MA, Jablensky A, Green MJ, Henskens FA, Klauser P, Loughland C, Michie PT, Mowry B, Pantelis C, Rasser PE, Schall U, Scott R, Zalesky A, de Bartolomeis A, Barone A, Ciccarelli M, Brunetti A, Cocozza S, Pontillo G, Tranfa M, Di Giorgio A, Thomopoulos SI, Jahanshad N, Thompson PM, van Erp T, Turner J, Homan P. Omlor W, et al. bioRxiv [Preprint]. 2023 Nov 2:2023.09.22.559032. doi: 10.1101/2023.09.22.559032. bioRxiv. 2023. Update in: Am J Psychiatry. 2025 Apr 01;182(4):373-388. doi: 10.1176/appi.ajp.20230806. PMID: 37961617 Free PMC article. Updated. Preprint.

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