The morphometric co‐atrophy networking of schizophrenia, autistic and obsessive spectrum disorders

Abstract

By means of a novel methodology that can statistically derive patterns of co-alterations distribution from voxel-based morphological data, this study analyzes the patterns of brain alterations of three important psychiatric spectra-that is, schizophrenia spectrum disorder (SCZD), autistic spectrum disorder (ASD), and obsessive-compulsive spectrum disorder (OCSD). Our analysis provides five important results. First, in SCZD, ASD, and OCSD brain alterations do not distribute randomly but, rather, follow network-like patterns of co-alteration. Second, the clusters of co-altered areas form a net of alterations that can be defined as morphometric co-alteration network or co-atrophy network (in the case of gray matter decreases). Third, within this network certain cerebral areas can be identified as pathoconnectivity hubs, the alteration of which is supposed to enhance the development of neuronal abnormalities. Fourth, within the morphometric co-atrophy network of SCZD, ASD, and OCSD, a subnetwork composed of eleven highly connected nodes can be distinguished. This subnetwork encompasses the anterior insulae, inferior frontal areas, left superior temporal areas, left parahippocampal regions, left thalamus and right precentral gyri. Fifth, the co-altered areas also exhibit a normal structural covariance pattern which overlaps, for some of these areas (like the insulae), the co-alteration pattern. These findings reveal that, similarly to neurodegenerative diseases, psychiatric disorders are characterized by anatomical alterations that distribute according to connectivity constraints so as to form identifiable morphometric co-atrophy patterns.

Hubs of long-distance co-alteration in brain pathology

“…4), areas with long-distance co-alterations of GM decreases have auditory and linguistic roles; a finding that is in accordance with the auditory hallucinations affecting a portion of these patients . Also the caudate and the MTL exhibit long-distance co-alterations, as well as the SN, which is in line with the involvement of this network in the disease White et al, 2010;, Cauda et al, 2018a. Long co-alterations of GM increases are found especially in the left putamen, which is coherent with a study that found an increased putamen characterized by leftward asymmetry in schizophrenic patients .…”

“…This mechanism has been put forward to explain the development of anatomical alterations observed in such diseases in terms of connectivity pathways, along which pathological proteins (proteinopathy) or other toxic agents can propagate . However, the network-like account of coalterations seems to provide insights also in clinical conditions that do not have a neurodegenerative origin, such as schizophrenia, autism, obsessive-compulsive disorder, depression, and chronic pain (Cauda et al, , 2018a. Furthermore, transdiagnostic meta-analyses merging data of studies about psychiatric and neurologic diseases support the following ideas: i) the most affected areas of the brain correspond to the hubs of the functional and structural connectomes , and ii) the distribution and development of co-alterations are mainly explained by functional and structural connectivity constraints (Cauda et al, 2018b).…”

“…In the present study we assessed the mean physical distance of co-alterations and its relationship with functional degree centrality (DC) in a meta-analytic, transdiagnostic way, so as to identify the cerebral areas that are more involved in long-range systems of pathological modifications. We obtained from the BrainMap database both voxel-based morphometry (VBM) and activation data to be used in a meta-analytic technique based on the Patel's κ , Cauda et al, 2018a. This transdiagnostic approach was motivated by the assumption that the mechanisms underlying the phenomenon of co-alteration seem to be related to normative brain connectivity Meyer-Lindenberg, 2012, Cauda et al, 2018b).…”

Addressing reverse inference in structural brain alterations

“…We run a simulation to understand the capacity of BF to highlight the earliest areas to be altered. As already showed (18,24,(62)(63)(64)(65)(66), neuropathological alterations are supposed to be distributed across the brain following structural and functional connectivity pathways. In order to simulate the alteration spread related to a certain pathology we used the anatomical connectivity matrix derived from Hagmann, Cammoun (67).…”

“…Finally, our simulations of alteration spreads related to different pathologies are based on the premise that alterations move diffusively along brain connectivity pathways. Although this underlying mechanism has been confirmed by recent research (18,24,62,63,65,66,71,109,110), it is not the only one that might play a role in the alteration spread. Moreover, the contributions of different mechanisms can vary with regard to the type of pathology affecting the brain, so that our simulations, even though they offer in our view the best approximation to real pathological spreads with the available data, do not pretend to grasp all the complexities of the actual phenomenon.…”