Functional brain network dysfunctions in subjects at high-risk for psychosis: A meta-analysis of resting-state functional connectivity. (September 2021)

• Record Type: Journal Article
• Authors: Del Fabro, Lorenzo; Schmidt, André; Fortea, Lydia; Delvecchio, Giuseppe; D'Agostino, Armando; Radua, Joaquim; Borgwardt, Stefan; Brambilla, Paolo
• Is Part Of: Neuroscience and biobehavioral reviews. Volume 128(2021)
• Page Start: 90
• Page End: 101
• Publication Date: 2021-09
• Subjects: fMRI -- Functional connectivity -- Large-scale networks -- Salience network -- Meta-analysis -- Psychosis -- Clinical high risk; Psychophysiology -- Periodicals; Human behavior -- Periodicals; Animal behavior -- Periodicals; Neurology -- Periodicals; Behavior -- Periodicals; Ethology -- Periodicals; Neurology -- Periodicals; Psychophysiologie -- Périodiques; Comportement humain -- Périodiques; Animaux -- Mœurs et comportement -- Périodiques; Neurologie -- Périodiques; Animal behavior; Human behavior; Neurology; Psychophysiology; Periodicals; Electronic journals; 573.8
• DOI: 10.1016/j.neubiorev.2021.06.020
• Languages: English
• ISSNs: 0149-7634

Abstract

Highlights: Emerging evidence suggests altered functional connectivity in high-risk for psychosis. This meta-analysis synthesizes results from 29 resting-state fMRI studies. Clinical high-risk is associated with hypo-connectivity within the salience network. Negative symptoms are correlated with functional connectivity changes in clinical high-risk. 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.