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T156. FUNCTIONAL CONNECTIVITY AND RISK OF PSYCHOSIS: AN ACTIVATION LIKELIHOOD ESTIMATION (ALE) META-ANALYSIS OF FUNCTIONAL MAGNETIC RESONANCE IMAGING STUDIES

BACKGROUND: Disrupted communication involving large-scale neural networks is hypothesized to underlie the pathophysiology of schizophrenia, as demonstrated by impaired resting-state functional connectivity (rsFC). Seed-based functional magnetic resonance imaging (fMRI) studies in subjects at increas...

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Detalles Bibliográficos
Autores principales: Del Fabro, Lorenzo, Schmidt, André, Delvecchio, Giuseppe, D’Agostino, Armando, Borgwardt, Stefan, Brambilla, Paolo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7234455/
http://dx.doi.org/10.1093/schbul/sbaa029.716
Descripción
Sumario:BACKGROUND: Disrupted communication involving large-scale neural networks is hypothesized to underlie the pathophysiology of schizophrenia, as demonstrated by impaired resting-state functional connectivity (rsFC). Seed-based functional magnetic resonance imaging (fMRI) studies in subjects at increased risk of developing psychosis have begun to identify abnormalities in rsFC, although reported findings remain mixed. The aim of this study was to conduct a meta-analysis of seed-based resting-state fMRI studies to test whether high-risk subjects show rsFC alterations relative to healthy controls within and between the default mode network (DMN), control executive network (CEN), and salience network (SN). METHODS: A literature search was performed to identify seed-based resting-state fMRI studies comparing subjects with genetic risk factors, psychotic-like experiences, and clinical high-risk for psychosis to healthy controls. Then, coordinates of seed regions were extracted and categorized into networks by their location within a priori templates. Activation likelihood estimate (ALE) analysis examined the reported coordinates for hypo-connectivity and hyper-connectivity with each a priori network. RESULTS: The meta-analysis included 15 studies (774 subjects at risk, 628 healthy controls) on clinical high-risk for psychosis, 6 studies (123 subjects at risk, 147 healthy controls) on psychotic-like experiences, and 5 studies (173 subjects at risk, 256 healthy controls) on genetic risk factors of developing psychosis. We found specific patterns of hypo- and hyper-connectivity within and between large-scale networks. Our results showed that subjects with high-risk for psychosis were characterized by hypo-connectivity within the SN and CEN and hyper-connectivity within the DMN and CEN. Network seeds in the DMN, CEN, and SN displayed hyper-connectivity with regions in other networks. The DMN seeds displayed hypo-connectivity with regions in the CEN, while CEN and SN seeds displayed hypo-connectivity with regions in the DMN. DISCUSSION: This meta-analysis provides evidence that subjects at risk for psychosis present distinctive abnormalities of hyper- and hypo-connectivity within and between the DMN, CEN and SN, particularly implicating network dys-connectivity as a core deficit underlying the psychopathology of psychosis in the preclinical phase. More studies are needed to investigate whether subjects at risk to develop psychosis present patterns of dysfunction between the rsFC of healthy subjects and that of patients with established psychosis.