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[Preprint]. 2023 Nov 2:2023.09.22.559032.
doi: 10.1101/2023.09.22.559032.

Estimating multimodal brain variability in schizophrenia spectrum disorders: A worldwide ENIGMA study

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

Estimating multimodal brain variability in schizophrenia spectrum disorders: A worldwide ENIGMA study

Wolfgang Omlor et al. bioRxiv. .

Update in

  • Estimating Multimodal Structural Brain Variability in Schizophrenia Spectrum Disorders: A Worldwide ENIGMA Study.
    Omlor W, Rabe F, Fuchs S, Surbeck W, Cecere G, Huang GY, Homan S, 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. Am J Psychiatry. 2025 Apr 1;182(4):373-388. doi: 10.1176/appi.ajp.20230806. Epub 2025 Feb 26. Am J Psychiatry. 2025. PMID: 40007253

Abstract

Objective: Schizophrenia is a multifaceted disorder associated with structural brain heterogeneity. Despite its relevance for identifying illness subtypes and informative biomarkers, structural brain heterogeneity in schizophrenia remains incompletely understood. Therefore, the objective of this study was to provide a comprehensive insight into the structural brain heterogeneity associated with schizophrenia.

Methods: This meta- and mega-analysis investigated the variability of multimodal structural brain measures of white and gray matter in individuals with schizophrenia versus healthy controls. Using the ENIGMA dataset of MRI-based brain measures from 22 international sites with up to 6139 individuals for a given brain measure, we examined variability in cortical thickness, surface area, folding index, subcortical volume and fractional anisotropy.

Results: We found that individuals with schizophrenia are distinguished by higher heterogeneity in the frontotemporal network with regard to multimodal structural measures. Moreover, individuals with schizophrenia showed higher homogeneity of the folding index, especially in the left parahippocampal region.

Conclusions: Higher multimodal heterogeneity in frontotemporal regions potentially implies different subtypes of schizophrenia that converge on impaired frontotemporal interaction as a core feature of the disorder. Conversely, more homogeneous folding patterns in the left parahippocampal region might signify a consistent characteristic of schizophrenia shared across subtypes. These findings underscore the importance of structural brain variability in advancing our neurobiological understanding of schizophrenia, and aid in identifying illness subtypes as well as informative biomarkers.

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