Heterogeneity of morphometric similarity networks in health and schizophrenia

Reduced structural network connectivity is proposed as a biomarker for chronic schizophrenia. This study assessed regional morphometric similarity as an indicator of cortical inter-regional connectivity, employing longitudinal normative modeling to evaluate whether decreases are consistent across individuals with schizophrenia. Normative models were trained and validated using data from healthy controls (n = 4310). Individual deviations from these norms were measured at baseline and follow-up, and categorized as infra-normal, normal, or supra-normal. Additionally, we assessed the change over time in the total number of infra- or supra-normal regions for each individual. At baseline, patients exhibited reduced morphometric similarity within the default mode network compared to healthy controls. The proportion of patients with infra- or supra-normal values in any region at both baseline and follow-up was low (<6%) and similar to that of healthy controls. Mean intra-group changes in the number of infra- or supra-normal regions over time were minimal (<1) for both the schizophrenia and control groups, with no significant differences observed between them. Normative modeling with multiple timepoints enables the identification of patients with significant static decreases and dynamic changes of morphometric similarity over time and provides further insight into the pervasiveness of morphometric similarity abnormalities across individuals with chronic schizophrenia.

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Publication Details

Journal
Schizophrenia
Published
2025-04-24
DOI
https://doi.org/10.1038/s41537-025-00612-2
Citations
13
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
18.60

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article

Heterogeneity of morphometric similarity networks in health and schizophrenia

Hilleke E. Hulshoff Pol, Celso Arango, Javier González‐Peñas, Hugo Gerard Schnack et al.
13 citations
Schizophrenia
Functional Brain Connectivity Studies
18.60
article

Heterogeneity of morphometric similarity networks in health and schizophrenia

Hilleke E. Hulshoff Pol, Celso Arango, Javier González‐Peñas, Hugo Gerard Schnack, René S. Kahn, Covadonga M. Díaz‐Caneja, Niels Janssen, Pedro M. Gordaliza, Joost Janssen, Elizabeth E.L. Buimer, Neeltje E.M. van Haren, Noemi G. Lois, A. Gallego
article en
13 citations

Abstract

Reduced structural network connectivity is proposed as a biomarker for chronic schizophrenia. This study assessed regional morphometric similarity as an indicator of cortical inter-regional connectivity, employing longitudinal normative modeling to evaluate whether decreases are consistent across individuals with schizophrenia. Normative models were trained and validated using data from healthy controls (n = 4310). Individual deviations from these norms were measured at baseline and follow-up, and categorized as infra-normal, normal, or supra-normal. Additionally, we assessed the change over time in the total number of infra- or supra-normal regions for each individual. At baseline, patients exhibited reduced morphometric similarity within the default mode network compared to healthy controls. The proportion of patients with infra- or supra-normal values in any region at both baseline and follow-up was low (<6%) and similar to that of healthy controls. Mean intra-group changes in the number of infra- or supra-normal regions over time were minimal (<1) for both the schizophrenia and control groups, with no significant differences observed between them. Normative modeling with multiple timepoints enables the identification of patients with significant static decreases and dynamic changes of morphometric similarity over time and provides further insight into the pervasiveness of morphometric similarity abnormalities across individuals with chronic schizophrenia.

SchizophreniaVol. 11(1)
Universidad Complutense de Madrid (ES), Universidad de La Laguna (ES), University of Applied Sciences Utrecht (NL), Utrecht University (NL), Instituto de Salud Carlos III (ES), Hospital General Universitario Gregorio Marañón (ES), University Medical Center Utrecht (NL), Centro de Investigación Biomédica en Red de Salud Mental (ES), Centre d'Imagerie BioMedicale (CH), Erasmus MC - Sophia Children’s Hospital (NL), University of Lausanne (CH), Icahn School of Medicine at Mount Sinai (US)
Autism Speaks, Fundación Alicia Koplowitz, European Federation of Pharmaceutical Industries and Associations, Simons Foundation Autism Research Initiative, European Commission, Ministerio de Ciencia e Innovación, National Institutes of Health, Horizon 2020 Framework Programme, HORIZON EUROPE Framework Programme, Instituto de Salud Carlos III, European Regional Development Fund, National Institute of Mental Health
Openalex Percentile: Top 1%
Functional Brain Connectivity Studies
18.60
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