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Multiple Network Dysconnectivity in Adolescents with Psychotic Experiences: A Longitudinal Population-Based Study.

ABSTRACT: Abnormal functional connectivity (FC, the temporal synchronization of activation across distinct brain regions) of the default mode (DMN), salience (SN), central executive (CEN), and motor (MN) networks is well established in psychosis. However, little is known about FC in individuals, particularly adolescents, reporting subthreshold psychotic experiences (PE) and their trajectory over time. Thus, the aim of this study was to investigate the FC of these networks in adolescents with PE. In this population-based case-control study, 24 adolescents (mean age = 13.58) meeting the criteria for PE were drawn from a sample of 211 young people recruited and scanned for a neuroimaging study, with a follow-up scan 2 years later (n = 18, mean age = 15.78) and compared to matched controls drawn from the same sample. We compared FC of DMN, SN, CEN, and MN regions between PE and controls using whole-brain FC analyses. At both timepoints, the PE group displayed significant hypoconnectivity compared to controls. At baseline, FC in the PE group was decreased between MN and DMN regions. At follow-up, dysconnectivity in the PE group was more widespread. Over time, controls displayed greater FC changes than the PE group, with FC generally increasing between MN, DMN, and SN regions. Adolescents with PE exhibit hypoconnectivity across several functional networks also found to be hypoconnected in established psychosis. Our findings highlight the potential for studies of adolescents reporting PE to reveal early neural correlates of psychosis and support further investigation of the role of the MN in PE and psychotic disorders.

SUBMITTER: O'Neill A

PROVIDER: S-EPMC7846103 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Purpose: Psychotic experiences in childhood (such as hearing voices or being suspicious) represent an important phenotype for early intervention. However, these experiences can be defined in several ways: self-reported psychotic experiences (SRPE) rely exclusively on the child's report, clinically validated psychotic experiences (CRPE) are based on clinical assessment, and attenuated psychotic symptoms (APS) represents a categorization to do with clinical relevance in relation to severity. Very few studies have investigated how these distinctions impact clinical and other domains. The present study aims to compare SRPE, CRPE, and APS among children and adolescents. Methods: This study is part of the Brazilian High-Risk Cohort Study for Psychiatric Disorders, in which 2,241 individuals aged 6-14 years provided self-ratings of 20 psychotic experiences using the Community Assessment of Psychic Experiences (CAPE). A trained psychologist conducted an interview to validate or reject reported experiences and to rate the presence of APS and affective flattening. In parallel, parents provided information about child mental health to an independent interviewer. We tested the association of mutually exclusive categories of non-validated SRPE (nSRPE), clinically validated PE below the threshold for APS (nCRPE), and APS (nSRPE = 33%, nCRPE = 11%, APS = 6%), with parents' information about the child's positive attributes and levels of psychopathology and psychologist assessment of blunted affect. Results: Most associations were qualitatively similar, and there was a dose-response in the strength of associations across categories, such that APS > nCRPE > nSRPE. Experiences in all three categories were associated with female sex. nSRPE were associated with overall levels of psychopathology, but to a lesser degree than nCRPE and APS. APS and nCRPE were associated with less positive attributes, with APS more so than nCRPE. Only APS was associated with affective flattening. Conclusions: In children and adolescents, SRPE, CRPE, and APS all index liability for psychopathology, but as clinician rated relevance increases, associations get stronger and become evident across more domains.

Project description:BackgroundProgress in precision psychiatry is predicated on identifying reliable individual-level diagnostic biomarkers. For psychosis, measures of structural and functional connectivity could be promising biomarkers given consistent reports of dysconnectivity across psychotic disorders using magnetic resonance imaging.MethodsWe leveraged data from four independent cohorts of patients with psychosis and control subjects with observations from approximately 800 individuals. We used group-level analyses and two supervised machine learning algorithms (support vector machines and ridge regression) to test within-, between-, and across-sample classification performance of white matter and resting-state connectivity metrics.ResultsAlthough we replicated group-level differences in brain connectivity, individual-level classification was suboptimal. Classification performance within samples was variable across folds (highest area under the curve [AUC] range = 0.30) and across datasets (average support vector machine AUC range = 0.50; average ridge regression AUC range = 0.18). Classification performance between samples was similarly variable or resulted in AUC values of approximately 0.65, indicating a lack of model generalizability. Furthermore, collapsing across samples (resting-state functional magnetic resonance imaging, N = 888; diffusion tensor imaging, N = 860) did not improve model performance (maximal AUC = 0.67). Ridge regression models generally outperformed support vector machine models, although classification performance was still suboptimal in terms of clinical relevance. Adjusting for demographic covariates did not greatly affect results.ConclusionsConnectivity measures were not suitable as diagnostic biomarkers for psychosis as assessed in this study. Our results do not negate that other approaches may be more successful, although it is clear that a systematic approach to individual-level classification with large independent validation samples is necessary to properly vet neuroimaging features as diagnostic biomarkers.

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Multiple Network Dysconnectivity in Adolescents with Psychotic Experiences: A Longitudinal Population-Based Study.

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