Abstract
INTRODUCTION: Morphometric similarity is a recently developed neuroimaging phenotype of inter-regional connectivity by quantifying the similarity of a region to other regions based on multiple MRI parameters. Altered average morphometric similarity has been reported in psychotic disorders at the group level, with considerable heterogeneity across individuals. We used normative modeling to address cross-sectional and longitudinal inter-individual heterogeneity of morphometric similarity in health and schizophrenia.
METHODS: Morphometric similarity for 62 cortical regions was obtained from baseline and follow-up T1-weighted scans of healthy individuals and patients with chronic schizophrenia. Cortical regions were classified into seven predefined brain functional networks. Using Bayesian Linear Regression and taking into account age, sex, image quality and scanner, we trained and validated normative models in healthy controls from eleven datasets (n = 4310). Individual deviations from the norm (z-scores) in morphometric similarity were computed for each participant for each network and region at both timepoints. A z-score ≧ than 1.96 was considered supra-normal and a z-score ≦ -1.96 infra-normal. As a longitudinal metric, we calculated the change over time of the total number of infra- or supra-normal regions per participant.
RESULTS: At baseline, patients with schizophrenia had decreased morphometric similarity of the default mode network and increased morphometric similarity of the somatomotor network when compared with healthy controls. The percentage of patients with infra- or supra-normal values for any region at baseline and follow-up was low (<6%) and did not differ from healthy controls. Mean intra-group changes over time in the total number of infra- or supra-normal regions were small in schizophrenia and healthy control groups (<1) and there were no significant between-group differences.
CONCLUSIONS: In a case-control setting, a decrease of morphometric similarity within the default mode network may be a robust finding implicated in schizophrenia. However, normative modeling suggests that significant reductions and changes over time of regional morphometric similarity are evident only in a minority of patients.
| Original language | English |
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| Publisher | bioRxiv |
| Number of pages | 46 |
| DOIs | |
| Publication status | Published - 18 Jun 2024 |
Publication series
| Name | bioRxiv |
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| Publisher | Cold Spring Harbor Laboratory |
| ISSN (Print) | 2692-8205 |
Funding
Supported by the Spanish Ministry of Science and Innovation, Instituto de Salud Carlos III (ISCIII), CIBER -Consorcio Centro de Investigación Biomédica en Red- (CB/07/09/0023), co-financed by the European Union, ERDF Funds from the European Commission, “A way of making Europe”, (PI16/02012, PI17/01249, PI17/00997, PI19/01024, PI20/00721, PI22/01824, PI22/01621, PI23/00625), financed by the European Union - NextGenerationEU (PMP21/00051), Madrid Regional Government (S2022/BMD-7216 AGES 3-CM), European Union Seventh Framework Program, European Union H2020 Program under the Innovative Medicines Initiative 2 Joint Undertaking: Project PRISM-2 (Grant agreement No.101034377), Project AIMS-2-TRIALS (Grant agreement No 777394), Project COllaborative Network for European Clinical Trials For Children “c4c” (Grant agreement No 777389) Horizon Europe, the National Institute of Mental Health of the National Institutes of Health under Award Number 1U01MH124639-01 (Project ProNET), Award Number 5P50MH115846-03 (Project FEP-CAUSAL) and AwardNumber 1R01MH128971-01A1 (Project SZ-aging), Fundación Familia Alonso, and Fundación Alicia Koplowitz. The authors thank Yasser Alemán-Goméz, Alberto Fernández Pena, Zimbo Boudewijns, and Joyce van Baaren for code and technical assistance.