Network-based spreading of grey matter changes across different stages of psychosis

Abstract

AbstractImportancePsychotic illness is associated with anatomically distributed grey matter reductions that can worsen with illness progression, but the mechanisms underlying the specific spatial patterning of these changes is unknown.ObjectiveTo test the hypothesis that brain network architecture constrains cross-sectional and longitudinal grey matter alterations across different stages of psychotic illness and to identify whether certain brain regions act as putative epicentres from which volume loss spreads.Design, Settings, ParticipantsThis study included 534 individuals from 4 cohorts, spanning early and late stages of psychotic illness. Early-stage cohorts included patients with antipsychotic-naïve first episode psychosis (N=59) and a group of medicated patients within 3 years of psychosis onset (N=121). Late-stage cohorts comprised two independent samples of people with established schizophrenia (N=136 in total). Each patient group had a corresponding matched control group (N=218 in total). A further independent sample of healthy adults (N=346) was used to derive representative structural and functional brain networks for modelling of network-based spreading processes. We additionally examined longitudinal illness-related and antipsychotic-related grey matter changes over 3 and 12 months using a triple-blind randomised placebo-control MRI study of the antipsychotic-naïve patients. All data were collected between April 2008 and January 2020, and analyses were performed between March 2021 and January 2023.Main Outcomes and MeasuresWe used coordinated deformation models to predict the extent of grey matter volume change in each of 332 parcellated areas by the volume changes observed in areas to which they were structurally or functionally coupled. To identify putative epicentres of volume loss, we used a network diffusion model to simulate the spread of pathology from different seed regions. Correlations between predicted and empirical spatial patterns of grey matter volume alterations were used to quantify model performance.ResultsIn both early and late stages of illness, spatial patterns of cross-sectional volume differences between patients and controls were more accurately predicted by coordinated deformation models constrained by structural, rather than functional, network architecture (. 46 <r< .57; p < .001). The same model also robustly predicted longitudinal volume changes related to illness (r> 52;p< .001) and antipsychotic exposure (r> .50;p< .001). Diffusion modelling consistently identified, across all four datasets, the anterior hippocampus as a putative epicentre of pathological spread in psychosis (all p< .05). Epicentres of longitudinal grey matter loss were apparent posteriorly early in the illness and shifted anteriorly to prefrontal cortex with illness progression.Conclusion and RelevanceOur findings highlight a robust and central role for white matter fibres as conduits for the spread of pathology across different stages of psychotic illness, mirroring findings reported in neurodegenerative conditions. The structural connectome thus represents a fundamental constraint on brain changes in psychosis, regardless of whether these changes are caused by illness or medication. Moreover, the anterior hippocampus represents a putative epicentre of early brain pathology from which dysfunction may spread to affect connected areas.Key pointsQuestionAre grey matter changes across the psychosis continuum constrained by brain network architecture and are certain regions epicentres of volume loss?FindingsAcross four independent samples spanning different stages of psychotic illness, grey matter alterations are strongly constrained by the underlying architecture of the brain’s axonal pathways and the hippocampus is consistently identified as a putative source from which volume-loss may spread to connected regions.MeaningWhite matter fibres may act as conduits for the spread of pathology across all stages of psychotic illness and medial temporal regions play a critical role in the origins of grey matter reductions.