bioRxivNeurosciencePreprint
Estimating multimodal brain variability in schizophrenia spectrum disorders: A worldwide ENIGMA study
Wolfgang OmloriD, Finn RabeiD, Simon FuchsiD, Giacomo CecereiD, Stephanie HomaniD, Werner SurbeckiD, Nils Kallen, Foivos GeorgiadisiD, Tobias R. SpilleriD, Erich SeifritziD, Thomas Wesley WeickertiD, Jason M. BruggemanniD, Cynthia Shannon WeickertiD, Steven G. PotkiniD, Ryota HashimotoiD, Kang SimiD, Kelly Rootes-MurdyiD, Yann QuidéiD, Josselin HouenouiD, Nerisa BanajiD, Daniela VecchioiD, Fabrizio PirasiD, Federica PirasiD, Gianfranco SpallettaiD, Raymond M. SalvadoriD, , Philipp HomaniD
Abstract
ObjectiveSchizophrenia 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. MethodsThis 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. ResultsWe 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. ConclusionsHigher 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.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 2
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Topographic diversity of structural connectivity in schizophrenia
Hongtao Ruan, Qiang Luo, … Jianfeng Feng·Schizophrenia ResearchPeer-reviewed·Nov 6, 2019
- Individual deviations from normative models of brain structure in a large cross-sectional schizophrenia cohort
Jinglei Lv, Maria Angelique Di Biase, … Andrew Zalesky·Molecular PsychiatryPeer-reviewed·Sep 22, 2020
- The dark side of the mean: brain structural heterogeneity in schizophrenia and its polygenic risk.
Dag Alnæs, Tobias Kaufmann, … Lars Tjelta Westlye·bioRxiv·Sep 4, 2018
- Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study
Foivos Georgiadis, Sara Larivière, … Matthias Kirschner·Molecular PsychiatryPeer-reviewed·Feb 9, 2024
- Altered Temporal Variability of Local and Large-scale Resting-state Brain Functional Connectivity Patterns in Schizophrenia and Bipolar Disorder
Yicheng Long, Zhening Liu, … Weidan Pu·Frontiers in PsychiatryPeer-reviewed·May 12, 2020
- Heterogeneity in Functional Connectivity: Dimensional Predictors of Individual Variability during Rest and Task fMRI in Psychosis
Maria Teodora Secara, Lindsay D. Oliver, … Colin S. Hawco·Progress in Neuro-Psychopharmacology and Biological PsychiatryPeer-reviewed·Jun 1, 2024