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Free keywords:
Substance use disorders; Cortical thickness; Subcortical volume; Brain connectome; Hub vulnerability
Abstract:
Background
Substance use disorders (SUD) are increasingly recognized as network disorders and associated with system-wide structural brain alterations. Though network mechanisms have been shown to guide the spatial patterning of structural alterations in neuropsychiatric conditions, their relevance in SUD remains unclear. Here, we tested whether large-scale structural alterations in SUD relate to normative connectome architecture.
Methods
We generated cortical and subcortical case-control differences in SUD from 2,847 individuals with different SUD (alcohol, methamphetamines, cocaine, opioids, cannabis, nicotine) and 1,951 non-affected individuals of the ENIGMA Addiction consortium. Using normative rs-fMRI and diffusion MRI connectivity data from the Human Connectome Project (n=207), we evaluated SUD-related structural alterations against two network susceptibility models: i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; ii) epicenter mapping, which identify regions whose typical connectivity profile most closely resembles the disease-related morphological alterations.
Results
We identified widespread cortical thickness and subcortical volume reductions in individuals with SUD compared to non-affect controls. SUD-related regional cortical alterations were associated with higher cortico-cortical and subcortical-cortical degree centrality (all r > 0.4, pspin < 0.05). Functional connectivity epicenters encompassed multiple parieto-temporal and frontal areas as well as subcortical regions. Structural connectivity epicenters were more circumscribed, and located in sensory and parietal cortical areas and striatum and thalamus.
Conclusions
In SUD, hub regions are more vulnerable to the SUD-related structural alterations and distinct subcortical and cortical connectivity profiles are linked to the spatial pattern of cortical alterations. Together, our study provides novel insights how network mechanisms may guide the spatial distribution of SUD-related structural alterations.
