A meta-analytic approach to mapping co-occurrent grey matter volume increases and decreases in psychiatric disorders.


Journal

NeuroImage
ISSN: 1095-9572
Titre abrégé: Neuroimage
Pays: United States
ID NLM: 9215515

Informations de publication

Date de publication:
15 11 2020
Historique:
received: 02 06 2020
revised: 24 07 2020
accepted: 28 07 2020
pubmed: 11 8 2020
medline: 26 2 2021
entrez: 11 8 2020
Statut: ppublish

Résumé

Numerous studies have investigated grey matter (GM) volume changes in diverse patient groups. Reports of disorder-related GM reductions are common in such work, but many studies also report evidence for GM volume increases in patients. It is unclear whether these GM increases and decreases are independent or related in some way. Here, we address this question using a novel meta-analytic network mapping approach. We used a coordinate-based meta-analysis of 64 voxel-based morphometry studies of psychiatric disorders to calculate the probability of finding a GM increase or decrease in one region given an observed change in the opposite direction in another region. Estimating this co-occurrence probability for every pair of brain regions allowed us to build a network of concurrent GM changes of opposing polarity. Our analysis revealed that disorder-related GM increases and decreases are not independent; instead, a GM change in one area is often statistically related to a change of opposite polarity in other areas, highlighting distributed yet coordinated changes in GM volume as a function of brain pathology. Most regions showing GM changes linked to an opposite change in a distal area were located in salience, executive-control and default mode networks, as well as the thalamus and basal ganglia. Moreover, pairs of regions showing coupled changes of opposite polarity were more likely to belong to different canonical networks than to the same one. Our results suggest that regional GM alterations in psychiatric disorders are often accompanied by opposing changes in distal regions that belong to distinct functional networks.

Identifiants

pubmed: 32777357
pii: S1053-8119(20)30706-0
doi: 10.1016/j.neuroimage.2020.117220
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

117220

Informations de copyright

Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare no competing interest.

Auteurs

Lorenzo Mancuso (L)

FOCUS Lab, Department of Psychology, University of Turin, Turin, Italy; GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy.

Alex Fornito (A)

The Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University,Victoria, Australia; Monash Biomedical Imaging, Monash University,Victoria, Australia.

Tommaso Costa (T)

FOCUS Lab, Department of Psychology, University of Turin, Turin, Italy; GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy. Electronic address: tommaso.costa@unito.it.

Linda Ficco (L)

FOCUS Lab, Department of Psychology, University of Turin, Turin, Italy; GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy.

Donato Liloia (D)

FOCUS Lab, Department of Psychology, University of Turin, Turin, Italy; GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy.

Jordi Manuello (J)

FOCUS Lab, Department of Psychology, University of Turin, Turin, Italy; GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy.

Sergio Duca (S)

GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy.

Franco Cauda (F)

FOCUS Lab, Department of Psychology, University of Turin, Turin, Italy; GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy.

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