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Functional brain network dysfunctions in subjects at high-risk for psychosis: A meta-analysis of resting-state functional connectivity

Lorenzo Del Fabro, André Schmidt, Lydia Fortea, Giuseppe Delvecchio, Armando D'Agostino, Joaquim Radua, Stefan Borgwardt, Paolo Brambilla*

*Corresponding author for this work

Abstract

Although emerging evidence suggests that altered functional connectivity (FC) of large-scale neural networks is associated with disturbances in individuals at high-risk for psychosis, the findings are still far to be conclusive. We conducted a meta-analysis of seed-based resting-state functional magnetic resonance imaging studies that compared individuals at clinical high-risk for psychosis (CHR), first-degree relatives of patients with schizophrenia, or subjects who reported psychotic-like experiences with healthy controls. Twenty-nine studies met the inclusion criteria. The MetaNSUE method was used to analyze connectivity comparisons and symptom correlations. Our results showed a significant hypo-connectivity within the salience network (p = 0.012, uncorrected) in the sample of CHR individuals (n = 810). Additionally, we found a positive correlation between negative symptom severity and FC between the default mode network and both the salience network (p < 0.001, r = 0.298) and the central executive network (p = 0.003, r = 0.23) in the CHR group. This meta-analysis lends support for the hypothesis that large-scale network dysfunctions represent a core neural deficit underlying psychosis development.

Original languageEnglish
JournalNeuroscience and Biobehavioral Reviews
Volume128
Pages (from-to)90-101
Number of pages12
ISSN0149-7634
DOIs
Publication statusPublished - 09.2021

Funding

Dr. L.F. was supported by a grant from the PFIS ( FI20/00,047 ). Dr. J.R. was supported by the Spanish Ministry of Science, Innovation and Universities / Economy and Competitiveness / Institudo de Salud Carlos III ( CPII19/00009 , PI19/00394 ), co-financed by ERDF Funds from the European Commission (“A Way of Making Europe”). All the authors report no other biomedical financial interests or potential conflicts of interest related to this publication.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 10 - Reduced Inequalities
    SDG 10 Reduced Inequalities

Research Areas and Centers

  • Academic Focus: Center for Brain, Behavior and Metabolism (CBBM)

DFG Research Classification Scheme

  • 2.23-04 Cognitive, Systems and Behavioural Neurobiology
  • 2.23-10 Clinical Psychiatry, Psychotherapy, Child and Adolescent Psychiatry
  • 2.23-09 Biological Psychiatry

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