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Convergent gray matter alterations across drugs of abuse and network-level implications: A meta-analysis of structural MRI studies.
Hill-Bowen, Lauren D; Riedel, Michael C; Salo, Taylor; Flannery, Jessica S; Poudel, Ranjita; Laird, Angela R; Sutherland, Matthew T.
Afiliação
  • Hill-Bowen LD; Department of Psychology, Florida International University, 11200 SW 8th Street, Miami, FL 33199, United States.
  • Riedel MC; Department of Physics, Florida International University, 11200 SW 8th Street, Miami, FL 33199, United States.
  • Salo T; Department of Psychology, Florida International University, 11200 SW 8th Street, Miami, FL 33199, United States.
  • Flannery JS; Department of Psychology and Neuroscience, University of North Carolina, Chapel Hill, NC, United States.
  • Poudel R; Department of Psychology, Florida International University, 11200 SW 8th Street, Miami, FL 33199, United States.
  • Laird AR; Department of Physics, Florida International University, 11200 SW 8th Street, Miami, FL 33199, United States.
  • Sutherland MT; Department of Psychology, Florida International University, 11200 SW 8th Street, Miami, FL 33199, United States. Electronic address: masuther@fiu.edu.
Drug Alcohol Depend ; 240: 109625, 2022 11 01.
Article em En | MEDLINE | ID: mdl-36115222
ABSTRACT

BACKGROUND:

Neuroimaging studies often consider brain alterations linked with substance abuse within the context of individual drugs (e.g., nicotine), while neurobiological theories of addiction emphasize common brain network-level alterations across drug classes. Using emergent meta-analytic techniques, we identified common structural brain alterations across drugs and characterized the functionally-connected networks with which such structurally altered regions interact.

METHODS:

We identified 82 articles characterizing gray matter (GM) volume differences for substance users vs. controls. Using the anatomical likelihood estimation algorithm, we identified convergent GM reductions across drug classes. Next, we performed resting-state and meta-analytic functional connectivity analyses using each structurally altered region as a seed and computed whole-brain functional connectivity profiles as the union of both maps. We characterized an "extended network" by identifying brain areas demonstrating the highest degree of functional coupling with structurally impacted regions. Finally, hierarchical clustering was performed leveraging extended network nodes' functional connectivity profiles to delineate subnetworks.

RESULTS:

Across drug classes, we identified medial frontal/ventromedial prefrontal, and multiple regions in anterior cingulate (ACC) and insula as regions displaying convergent GM reductions among users. Overlap of these regions' functional connectivity profiles identified ACC, inferior frontal, PCC, insula, superior temporal, and putamen as regions of an impacted extended network. Hierarchical clustering revealed 3 subnetworks closely corresponding to default mode (PCC, angular), salience (dACC, caudate), and executive control networks (dlPFC and parietal).

CONCLUSIONS:

These outcomes suggest that substance-related structural brain alterations likely have implications for the functioning of canonical large-scale networks and the perpetuation of substance use and neurocognitive alterations.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Substância Cinzenta / Nicotina Tipo de estudo: Systematic_reviews Limite: Humans Idioma: En Revista: Drug Alcohol Depend Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Substância Cinzenta / Nicotina Tipo de estudo: Systematic_reviews Limite: Humans Idioma: En Revista: Drug Alcohol Depend Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos