Heterogeneity of morphometric similarity networks in health and schizophrenia

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 assessed at each region. At the group-level, altered average morphometric similarity has been reported in psychotic disorders. At the individual level variability of morphometric similarity exists. We used normative modeling to address inter-individual heterogeneity of morphometric similarity in health and schizophrenia. Methods: Morphometric similarity for 68 cortical regions were obtained from baseline and follow-up T1-weighted scans of healthy individuals and patients with chronic schizophrenia. Using Bayesian Linear Regression and taking into account age, sex, image quality and scanner, normative models were trained and validated in healthy controls from multi-site data (n = 4310). Individual deviations from the norm (z-scores) were computed for each participant for each 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. Regions were classified into seven predefined brain networks that have been derived from resting state functional MRI in order to assess morphometric similarity of functional networks. Results: The percentage of patients with infra- or supra-normal values for any region at baseline and follow-up was low (<6%) and not different from healthy controls. There were no longitudinal group differences in change over time of the total number of infra- or supra-normal regions per participant. At baseline, patients had decreased morphometric similarity of the default mode network and increased morphometric similarity of the somatomotor network when compared to healthy controls. Conclusions: In a case-control setting, a decrease of morphometric similarity within the default mode network may be a robust finding implicated in schizophrenia. Nevertheless, significant reductions were evident only in a minority of patients indicating that caution is warranted when extrapolating group-average results to the individual.