Individualized cortical gradient and network topology reveal symptom-linked disruptions and neurobiological subtypes in schizophrenia

Schizophrenia is often conceptualized as a brain network disorder, yet the organizational principles and heterogeneity underlying widespread cortical abnormalities remain poorly understood. Leveraging multisite MRI data from 3,958 individuals diagnosed with schizophrenia and 5,489 neurotypical individuals, we studied the cortical organization and its subtyping by analyzing individualized cortical network similarity. We used eigenvector decompositions to study spatial patterning of the gradients and graph theory to study small-world topology. Individuals with schizophrenia showed widespread alterations of gradient loadings, which followed inferior-superior and frontal-temporal axes. Alterations in small-world topology were localized in key network hubs, including the insula and anterior cingulate cortex. Brain-symptom association analyses identified a latent dimension linking disorganization symptoms to topological alterations. Finally, clustering cortical alterations identified two robust subtypes, characterized by divergent anterior cingulate (S1) versus temporoparietal (S2) thickness differences aligned with the intrinsic gradient-topology patterns. Both subtypes were present early in the illness and stable across disease stages and age groups. These findings reveal systematic disruptions of cortical organization in schizophrenia, providing a network-level framework for macroscale brain organization and inter-individual heterogeneity.

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Journal
medRxiv
Published
2026-04-27
DOI
https://doi.org/10.64898/2026.04.25.26351736
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Individualized cortical gradient and network topology reveal symptom-linked disruptions and neurobiological subtypes in schizophrenia

Stefan Ehrlich, Erik G. Jönsson, Elysha Ringin, Will Woods et al.
medRxiv
Functional Brain Connectivity Studies
article

Individualized cortical gradient and network topology reveal symptom-linked disruptions and neurobiological subtypes in schizophrenia

Stefan Ehrlich, Erik G. Jönsson, Elysha Ringin, Will Woods, Paul E. Rasser, Ingrid Agartz, Carmel Loughland, Clara Moreau, Stanley V. Catts, Bin Wan, Caroline Demro, Emma Corley, Bryan J. Mowry, Stener Nerland, Kosha Ruparel, Frans Henskens, Patricia Segura, Giacomo Cecere, Soyolsaikhan Odkhuu, Sara Larivière, Derin Cobia, Kyle M. Jensen, Jakub Kopál, Christian Sorg, Ulrich Schall, Melissa Thalhammer, Rosanne Picotin, I‐Jou Chi, Freda Scheffler, Tamsyn E. Van Rheenen, Wolfgang Omlor, Nerisa Banaj, Maria Lee, Young Chul Chung, Daniela Vecchio, Lei Wang, C Lopez-Jaramillo, Melissa Green, Henk Temmingh, Amanda Rodrigue, Ole Andreassen, Nadine Parker, Nicolas Crossley, Erin Dickie, David Glahn, Lars T. Westlye, Christos Pantelis, Felice Iasevoli, Raquel Gur, Patricia Michie, Andriana Karuk, Vaughan Carr, Varun Warrier, Susan Rossell, Yuankai He, Yun-Shuang Fan, Sean Carruthers, Edith Pomarol-Clotet, Oliver Gruber, Dag Alnaes, Giuseppe Pontillo, Carl M Sellgren, Raymond Salvador, Aristotle Voineskos, Jaroslav Rokicki, Ali Saffet Gonul, Tilo Kircher, Benedicto Crespo Facorro, Rodney Scott, Vince D. Calhoun, Tim Hahn, Albert Yang, Udo Dannlowski, Philip James Sumner, Matthew Hughes, Mihai Avram, Lea Teutenberg, Stefan Borgwardt, Frederike Stein, Aslihan Uyar Demir, Ruben C. Gur, Peter Kochunov, Unn K.H. Haukvik, Kang Sim, Theodore D. Satterthwaite, Scott Sponheim, Dominik Grotegerd, Filip _paniel, Gary Donohoe, Tiana Borgers, Murray Cairns, Rafael Romero-Garcia, Yann Quide, Philipp Homan, Richard A.I. Bethlehem, Rebekka Lencer Lencer, Alfonso Gonzalez-Valderrama, David Tomecek
article en

Abstract

Schizophrenia is often conceptualized as a brain network disorder, yet the organizational principles and heterogeneity underlying widespread cortical abnormalities remain poorly understood. Leveraging multisite MRI data from 3,958 individuals diagnosed with schizophrenia and 5,489 neurotypical individuals, we studied the cortical organization and its subtyping by analyzing individualized cortical network similarity. We used eigenvector decompositions to study spatial patterning of the gradients and graph theory to study small-world topology. Individuals with schizophrenia showed widespread alterations of gradient loadings, which followed inferior-superior and frontal-temporal axes. Alterations in small-world topology were localized in key network hubs, including the insula and anterior cingulate cortex. Brain-symptom association analyses identified a latent dimension linking disorganization symptoms to topological alterations. Finally, clustering cortical alterations identified two robust subtypes, characterized by divergent anterior cingulate (S1) versus temporoparietal (S2) thickness differences aligned with the intrinsic gradient-topology patterns. Both subtypes were present early in the illness and stable across disease stages and age groups. These findings reveal systematic disruptions of cortical organization in schizophrenia, providing a network-level framework for macroscale brain organization and inter-individual heterogeneity.

medRxiv
University of Geneva (CH), University of Maryland, Baltimore (US), Oslo University Hospital (NO), Boston Children's Hospital (US), University of Minnesota (US), Université de Sherbrooke (CA), National Yang Ming Chiao Tung University (TW), University of Electronic Science and Technology of China (CN), Kaohsiung Medical University (TW), University of Cape Town (ZA), Queensland University of Technology (AU), Philipps University of Marburg (DE), Pontificia Universidad Católica de Chile (CL), The University of Queensland (AU), The University of Melbourne (AU), Forschungszentrum Jülich (DE), University of Oslo (NO), University of Toronto (CA), Ollscoil na Gaillimhe – University of Galway (IE), University of Zurich (CH), Heidelberg University (DE), University of Münster (DE), University of Cambridge (GB), Instituto de Salud Carlos III (ES), German Center for Neurodegenerative Diseases (DE), Centre Hospitalier Universitaire Sainte-Justine (CA), Baycrest Hospital (CA), TUM Klinikum (DE), Taipei Veterans General Hospital (TW), Vilnius College of Technologies and Design (LT), Karolinska Institutet (SE), Kyungpook National University (KR), UNSW Sydney (AU), Universidad de Antioquia (CO), Ege University (TR), Hunter Medical Research Institute (AU), Centro de Investigación Biomédica en Red de Salud Mental (ES), Mental Health Research Canada (CA), Finis Terrae University (CL), Diakonhjemmet Hospital (NO), Fidmag Sisters Hospitallers (ES), Center for Behavioral Brain Sciences (DE), Social Neuroscience Lab (DE), Max Planck Institute for Human Cognitive and Brain Sciences (DE), Instituto de Biomedicina de Sevilla (ES), Center for Translational Research in Neuroimaging and Data Science (US), Stockholm Health Care Services (SE), Institute of Mental Health (SG), Fondazione Santa Lucia (IT), National Institute of Mental Health (CZ), Swinburne University of Technology (AU), University of Naples Federico II (IT), University of Pennsylvania (US), Jeonbuk National University (KR), Bethel University (US), University of Lübeck (DE)
National Science Foundation, U.S. Department of Energy, National Alliance for Research on Schizophrenia and Depression, National Imaging Facility, Macquarie University, Science Foundation Ireland, Deutsche Forschungsgemeinschaft, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Swinburne University of Technology, Ministerstvo Zdravotnictví Ceské Republiky, Centre of Excellence in Cognition and its Disorders, Australian Research Council, Karolinska Institutet, Knut och Alice Wallenbergs Stiftelse, Stockholms Läns Landsting, Vetenskapsrådet, Svenska Läkaresällskapet, National Institutes of Health, Medical Research Council, National Health and Medical Research Council, National Institute of Mental Health, National Center for Research Resources
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